{"group":{"id":1,"name":"Community","lockable":false,"created_at":"2012-01-18T18:02:15.000Z","updated_at":"2026-04-16T00:12:35.000Z","description":"Problems submitted by members of the MATLAB Central community.","is_default":true,"created_by":161519,"badge_id":null,"featured":false,"trending":false,"solution_count_in_trending_period":0,"trending_last_calculated":"2026-04-16T00:00:00.000Z","image_id":null,"published":true,"community_created":false,"status_id":2,"is_default_group_for_player":false,"deleted_by":null,"deleted_at":null,"restored_by":null,"restored_at":null,"description_opc":null,"description_html":null,"published_at":null},"problems":[{"id":1995,"title":"Loading/Expanding a ZIP file from File Exchange","description":"This challenge is to load a ZIP file from Mathworks File Exchange and UNZIP the contents.\r\n\r\n*Input:* url_link of ZIP'd file\r\n\r\n*Output:* UNZIPPED MAT file\r\n\r\n*Verification:* filename and size will be confirmed \r\n\r\n*Commentary:* This challenge was inspired by some of my links going dead. Alfonso suggested utilizing File Exchange(FE). My first attempts to load a MAT was unsuccessful due to using the incorrect FE link. The nice matlab unzip function with a valid link led to an efficient method. ","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.4333px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 183px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 91.5px; transform-origin: 407px 91.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 281.217px 7.91667px; transform-origin: 281.217px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThis challenge is to load a ZIP file from Mathworks File Exchange and UNZIP the contents.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 19.4333px 7.91667px; transform-origin: 19.4333px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eInput:\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 60.85px 7.91667px; transform-origin: 60.85px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e url_link of ZIP'd file\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 25.2667px 7.91667px; transform-origin: 25.2667px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eOutput:\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 64.4333px 7.91667px; transform-origin: 64.4333px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e UNZIPPED MAT file\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 40.0667px 7.91667px; transform-origin: 40.0667px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eVerification:\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 110.483px 7.91667px; transform-origin: 110.483px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e filename and size will be confirmed\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 63px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 31.5px; text-align: left; transform-origin: 384px 31.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 45.1333px 7.91667px; transform-origin: 45.1333px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eCommentary:\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 338.433px 7.91667px; transform-origin: 338.433px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e This challenge was inspired by some of my links going dead. Alfonso suggested utilizing File Exchange(FE). My first attempts to load a MAT was unsuccessful due to using the incorrect FE link. The nice matlab unzip function with a valid link led to an efficient method.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function ans=load_file(url_link)\r\n% Link is to a binary zip file\r\n% Load it and unzip to create mat file\r\n dir;\r\nend","test_suite":"%%\r\n%url_link='http://www.mathworks.com/matlabcentral/fileexchange/44314-cody-knotssample-zip-file?download=true';\r\nurl_link='https://www.mathworks.com/matlabcentral/mlc-downloads/downloads/submissions/44314/versions/3/download/zip'\r\n\r\nload_file(url_link);\r\n\r\nz=dir;\r\n\r\nvalid=0;\r\nfor k=1:size(z,1)\r\n if strcmp(z(k).name,'Knots_sample.mat')\r\n  valid=1;\r\n  break;\r\n end\r\nend\r\n\r\nassert(valid==1);\r\nassert(z(k).bytes==58803)\r\n\r\n\r\n\r\n\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":1,"created_by":3097,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":17,"test_suite_updated_at":"2020-10-01T18:26:03.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2013-11-16T03:45:19.000Z","updated_at":"2026-03-16T12:47:34.000Z","published_at":"2013-11-16T04:05:42.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis challenge is to load a ZIP file from Mathworks File Exchange and UNZIP the contents.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eInput:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e url_link of ZIP'd file\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eOutput:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e UNZIPPED MAT file\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eVerification:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e filename and size will be confirmed\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eCommentary:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e This challenge was inspired by some of my links going dead. Alfonso suggested utilizing File Exchange(FE). My first attempts to load a MAT was unsuccessful due to using the incorrect FE link. The nice matlab unzip function with a valid link led to an efficient method.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":60536,"title":"Jigsaw 001: Intro 2x2 square. Pieces 128x128","description":"This challenge is to re-assemble camerman.tif in grayscale from four 128x128 pieces into a 256x256 image.\r\n\r\n\r\nThe pointer layout of the image is [1 3; 2 4].\r\nReturn a four value vector that remaps the scrambled image into an original form.\r\nThe displayed scramble is [2 4 1 3] making the solution [3 1 4 2].\r\nThe four pieces will be provided as matrices in a cell array, along with size of puzzle in pieces and piece size.\r\n\r\n\r\nThis series will explore various puzzle pieces, orientations, sizes,double sided, and ultimately DARPA shredder data.\r\nMultiple methods are provided in the template to achieve re-mapping. Which will work and which will fail?","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.4333px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 522.5px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 261.25px; transform-origin: 407px 261.25px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 338px 8px; transform-origin: 338px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThis challenge is to re-assemble camerman.tif in grayscale from four 128x128 pieces into a 256x256 image.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan 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\" 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\" data-image-state=\"image-loaded\" width=\"289\" height=\"217\"\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 137.5px 8px; transform-origin: 137.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThe pointer layout of the image is [1 3; 2 4].\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 256px 8px; transform-origin: 256px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eReturn a four value vector that remaps the scrambled image into an original form.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 203px 8px; transform-origin: 203px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThe displayed scramble is [2 4 1 3] making the solution [3 1 4 2].\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 340px 8px; transform-origin: 340px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThe four pieces will be provided as matrices in a cell array, along with size of puzzle in pieces and piece size.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 8px; transform-origin: 0px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 8px; transform-origin: 0px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 363.5px 8px; transform-origin: 363.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThis series will explore various puzzle pieces, orientations, sizes,double sided, and ultimately DARPA shredder data.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 326.5px 8px; transform-origin: 326.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eMultiple methods are provided in the template to achieve re-mapping. Which will work and which will fail?\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function v = jigsaw001(pc,nr,nc,pnr,pnc)\r\n% pc cell array of jigsaw pieces, all the same size and double\r\n% nr,nc  Jigsaw piece counts rows and columns\r\n% pnr,pnc Jigsaw piece size row pixels, col pixels\r\n\r\n %Four scoring methods created\r\n % 1 sum of abs delta       \r\n % 2 sum of (abs delta)^2   \r\n % 3 sum of (abs delta)^0.5 \r\n % 4 median of abs delta    \r\n %\r\n\r\n% Brute force\r\n %Try all piece permutations and score the piece edges\r\n  v=1:nr*nc; % Total pieces\r\n  vperms=perms(1:nr*nc);\r\n  [vnr,vnc]=size(vperms);\r\n  m=zeros(nr*pnr,nc*pnc); %matrix to hold created image\r\n  \r\n  best_score=inf;\r\n  for i=1:vnr % cycle thru all permutations\r\n   vidx=vperms(i,:);\r\n   m=[pc{vidx(1)} pc{vidx(3)};pc{vidx(2)} pc{vidx(4)}];\r\n   \r\n % Four scoring methods created\r\n   score=sum(abs(m(pnr,:)-m(pnr+1,:)))+sum(abs(m(:,pnc)-m(:,pnc+1))); % Method 1\r\n   %score=sum(abs(m(pnr,:)-m(pnr+1,:)).^2)+sum(abs(m(:,pnc)-m(:,pnc+1)).^2); % Method 2\r\n   %score=sum(abs(m(pnr,:)-m(pnr+1,:)).^.5)+sum(abs(m(:,pnc)-m(:,pnc+1)).^.5); % Method 3\r\n   \r\n   %sort_score=sort([abs(m(pnr,:)-m(pnr+1,:)) [abs(m(:,pnc)-m(:,pnc+1))]']); %Method 4\r\n   %score=sort_score(256);  %Median delta                                    %Method 4\r\n   \r\n   %fprintf('%i %i %i %i Score: %.2f\\n',vidx,score);\r\n   if score\u003cbest_score\r\n    v=vidx;\r\n    best_score=score;\r\n    %fprintf('New Best score\\n');\r\n   end\r\n   \r\n  end % i vperms vnr\r\n  \r\nend %jigsaw001","test_suite":"%%\r\n% all imdata 2019 are hosted for cody at https://drive.google.com/drive/folders/1TZkBMEEKHiFJExqVoJgj5VVeHbvOfTYB\r\n% a Text file of matlab urlwrite links will be added in the future\r\n%camerman.tif\r\n%https://drive.google.com/uc?export=download\u0026id=1WNWSIp29e_BM47RSiNwom9zMSUTUVKv7\r\n% future will show cody matlab imdata location and how to access\r\n\r\nurl='https://drive.google.com/uc?export=download\u0026id=1WNWSIp29e_BM47RSiNwom9zMSUTUVKv7'; \r\nfname='cameraman.tif';\r\n%tic\r\nurlwrite(url,fname);\r\n%toc\r\n%dir\r\n%figure;imshow('cameraman.tif') % valid\r\n\r\nm_cameraman=imread('cameraman.tif');\r\nm_cameraman=double(m_cameraman);\r\n\r\n%{\r\nd1=sum(abs(m_cameraman(:,128)-m_cameraman(:,129)));\r\nd2=sum(abs(m_cameraman(:,1)-m_cameraman(:,256)));\r\nfprintf('col delta scr: 128:129 %.2f  256:1 %.2f\\n',d1,d2);\r\n\r\nd1=sum((abs(m_cameraman(:,128)-m_cameraman(:,129))).^.5);\r\nd2=sum((abs(m_cameraman(:,1)-m_cameraman(:,256))).^.5);\r\nfprintf('col root scr: 128:129 %.2f  256:1 %.2f\\n',d1,d2);\r\n%}\r\n\r\n\r\nfprintf('Original image\\n');\r\nfigure;imagesc(m_cameraman);colormap gray %\r\n\r\n%{\r\nfigure;plot(1:256,abs(m_cameraman(:,128)-m_cameraman(:,129)));hold on\r\nplot(1:256,sort(abs(m_cameraman(:,128)-m_cameraman(:,129))));\r\n\r\nfigure;plot(1:256,abs(m_cameraman(:,1)-m_cameraman(:,256)));hold on\r\nplot(1:256,sort(abs(m_cameraman(:,1)-m_cameraman(:,256))));\r\n\r\nfigure;plot(1:256,(abs(m_cameraman(:,128)-m_cameraman(:,129))).^.5);hold on\r\nplot(1:256,sort((abs(m_cameraman(:,128)-m_cameraman(:,129))).^.5));\r\n\r\nfigure;plot(1:256,(abs(m_cameraman(:,1)-m_cameraman(:,256))).^.5);hold on\r\nplot(1:256,sort((abs(m_cameraman(:,1)-m_cameraman(:,256))).^.5));\r\n%}\r\n\r\n%size(m_cameraman) % 256 256\r\n\r\nnr=2;nc=2;\r\npnr=128;pnc=128;\r\nTotal_pieces=nr*nc;\r\npc{Total_pieces}=[];\r\n\r\nptr=0;\r\nfor c=1:nc\r\n for r=1:nr\r\n  p=m_cameraman(1+(r-1)*pnr:r*pnr,1+(c-1)*pnc:c*pnc);\r\n  ptr=ptr+1;\r\n  pc{ptr}=p;\r\n end\r\nend\r\n\r\nvperm=1:nr*nc;\r\nwhile nnz((vperm-[1:nr*nc])==0) % want each piece moved\r\n vperm=randperm(nr*nc);\r\nend\r\n\r\nfor i=1:Total_pieces % scramble puzzle pieces\r\n jpc{i}=pc{vperm(i)};\r\nend\r\n\r\n% scrambled image\r\njigsaws=[jpc{1} jpc{3};jpc{2} jpc{4}];\r\nfprintf('Scrambled image\\n')\r\nfigure;imagesc(jigsaws);colormap gray %\r\n\r\nv = jigsaw001(jpc,nr,nc,pnr,pnc);\r\n\r\njigsawf=[jpc{v(1)} jpc{v(3)};jpc{v(2)} jpc{v(4)}];\r\n\r\nfprintf('Final image\\n');\r\nfigure;imagesc(jigsawf);colormap gray %\r\n\r\nassert(isequal(jigsawf,m_cameraman))\r\n\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":3097,"edited_by":3097,"edited_at":"2024-06-14T22:50:25.000Z","deleted_by":null,"deleted_at":null,"solvers_count":5,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2024-06-14T16:43:17.000Z","updated_at":"2025-03-02T14:00:42.000Z","published_at":"2024-06-14T22:50:26.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis challenge is to re-assemble camerman.tif in grayscale from four 128x128 pieces into a 256x256 image.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:customXml w:element=\\\"image\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"height\\\" w:val=\\\"217\\\"/\u003e\u003cw:attr w:name=\\\"width\\\" w:val=\\\"289\\\"/\u003e\u003cw:attr w:name=\\\"verticalAlign\\\" w:val=\\\"baseline\\\"/\u003e\u003cw:attr w:name=\\\"altText\\\" w:val=\\\"\\\"/\u003e\u003cw:attr w:name=\\\"relationshipId\\\" w:val=\\\"rId1\\\"/\u003e\u003c/w:customXmlPr\u003e\u003c/w:customXml\u003e\u003cw:customXml w:element=\\\"image\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"height\\\" w:val=\\\"217\\\"/\u003e\u003cw:attr w:name=\\\"width\\\" w:val=\\\"289\\\"/\u003e\u003cw:attr w:name=\\\"verticalAlign\\\" w:val=\\\"baseline\\\"/\u003e\u003cw:attr w:name=\\\"altText\\\" w:val=\\\"\\\"/\u003e\u003cw:attr w:name=\\\"relationshipId\\\" w:val=\\\"rId2\\\"/\u003e\u003c/w:customXmlPr\u003e\u003c/w:customXml\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe pointer layout of the image is [1 3; 2 4].\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eReturn a four value vector that remaps the scrambled image into an original form.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe displayed scramble is [2 4 1 3] making the solution [3 1 4 2].\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe four pieces will be provided as matrices in a cell array, along with size of puzzle in pieces and piece size.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis series will explore various puzzle pieces, orientations, sizes,double sided, and ultimately DARPA shredder data.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eMultiple methods are provided in the template to achieve re-mapping. Which will work and which will 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\",\"relationship\":null},{\"partUri\":\"/media/image2.png\",\"contentType\":\"image/png\",\"content\":\"data:image/png;base64,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\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":58503,"title":"Google Drive file download","description":"This Challenge is to download a file from GoogleDrive given its \"copylink\" provided URL and a file name.\r\nGoogleDrive links fail for Matlab function like urlwrite, imread, imwrite, webread, and others. \r\nThe file 2.png is given by https://drive.google.com/file/d/1v3GsGgP3p905wzdvUqypL_-djYmxiyzK/view?usp=drive_link, which will bring up the file in a new window but this URL fails for matlab commands.\r\nThe GoogleDrive file must be \"Shared\" . The file must at least have share to those \"anyone with this link\".\r\nTo enable file download the Google URL string must be modified:\r\n 1) Delete the end '/view?usp=*'; Anything after and inlcuding \"/view\" must be deleted\r\n 2) Replace 'file/d/' with 'uc?export=download\u0026id='\r\n\r\nGiven a URL and filename download the URL contents into a file called filename in the local Cody directory.\r\nVerification will be done by file name and file size.\r\n\r\n","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.4333px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 372px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 186px; transform-origin: 407px 186px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 327px 8px; transform-origin: 327px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThis Challenge is to download a file from GoogleDrive given its \"copylink\" provided URL and a file name.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 288px 8px; transform-origin: 288px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eGoogleDrive links fail for Matlab function like urlwrite, imread, imwrite, webread, and others. \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 21px; text-align: left; transform-origin: 384px 21px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 81px 8px; transform-origin: 81px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThe file 2.png is given by \u003c/span\u003e\u003c/span\u003e\u003ca target='_blank' href = \"https://drive.google.com/file/d/1v3GsGgP3p905wzdvUqypL_-djYmxiyzK/view?usp=drive_link,\"\u003e\u003cspan style=\"\"\u003e\u003cspan style=\"\"\u003ehttps://drive.google.com/file/d/1v3GsGgP3p905wzdvUqypL_-djYmxiyzK/view?usp=drive_link,\u003c/span\u003e\u003c/span\u003e\u003c/a\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 2px 8px; transform-origin: 2px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e which will bring up the file in a new window but this URL fails for matlab commands.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 330.5px 8px; transform-origin: 330.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThe GoogleDrive file must be \"Shared\" . The file must at least have share to those \"anyone with this link\".\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 203.5px 8px; transform-origin: 203.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eTo enable file download the Google URL string must be modified:\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 266.5px 8px; transform-origin: 266.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e 1) Delete the end '/view?usp=*'; Anything after and inlcuding \"/view\" must be deleted\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 156.5px 8px; transform-origin: 156.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e 2) Replace 'file/d/' with 'uc?export=download\u0026amp;id='\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 8px; transform-origin: 0px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 336px 8px; transform-origin: 336px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eGiven a URL and filename download the URL contents into a file called filename in the local Cody directory.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 154.5px 8px; transform-origin: 154.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eVerification will be done by file name and file size.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 8px; transform-origin: 0px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 8px; transform-origin: 0px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function url=GoogleDrive_urlwrite(url,fname)\r\n% The GoogleDrive \"copy link\" does not play well with matlab urlwrite/imread/imwrite/webread/... \r\n% Expect 'https://drive.google.com/file/d/1WDYDJJZ3wJ8Fs0-8E2u6bYxlZbOapNJn/view?usp=drive_link'\r\n% 1) Delete the end '/view...'\r\n% 2) Replace 'file/d/' with 'uc?export=download\u0026id='\r\n \r\n %urlwrite(url,fname);\r\nend","test_suite":"%%\r\n%Google Drive Dowloads need to come from shared files\r\n% Tweak link: file/d/ to uc?export=download\u0026id=   while removing /view?usp=sharing\r\n% https://drive.google.com/file/d/1v3GsGgP3p905wzdvUqypL_-djYmxiyzK/view?usp=sharing\r\n% https://drive.google.com/uc?export=download\u0026id=1v3GsGgP3p905wzdvUqypL_-djYmxiyzK\r\n\r\n\r\n%2.png Robot\r\nurl='https://drive.google.com/file/d/1v3GsGgP3p905wzdvUqypL_-djYmxiyzK/view?usp=drive_link';\r\nfname='2.png'; \r\nfile_size=7025; % bytes \r\n\r\nfprintf('******Initial Test 1 Dir:\\n\\n')\r\ndir % Initial Dir\r\n\r\nGoogleDrive_urlwrite(url,fname); %expect  7025 bytes for 2.png\r\n\r\nfprintf('Dir after first call:\\n\\n')\r\ndir\r\ndir_struct=dir\r\nvalid=0;\r\nfor i=1:length(dir_struct)\r\n fprintf('%i %s %i\\n',i,dir_struct(i).name,dir_struct(i).bytes)\r\n if isequal(dir_struct(i).name,fname)  % contains(dir_struct(i).name,fname)\r\n  if dir_struct(i).bytes==file_size\r\n   valid=1;\r\n   break;\r\n  end\r\n end\r\nend\r\n\r\nassert(valid)\r\n%%\r\n%28.png Starry Night\r\nurl='https://drive.google.com/file/d/1WDYDJJZ3wJ8Fs0-8E2u6bYxlZbOapNJn/view?usp=drive_link';\r\nfname='28.png'; \r\nfile_size=58061; % bytes \r\n\r\nfprintf('\\n***** Test 2 start Dir:\\n\\n')\r\ndir % Test 2 Dir\r\n\r\nGoogleDrive_urlwrite(url,fname); %expect  58061 bytes for 28.png\r\n\r\nfprintf('Dir after second Call:\\n\\n')\r\ndir\r\ndir_struct=dir\r\nvalid=0;\r\nfor i=1:length(dir_struct)\r\n fprintf('%i %s %i\\n',i,dir_struct(i).name,dir_struct(i).bytes)\r\n if isequal(dir_struct(i).name,fname)  % contains(dir_struct(i).name,fname)\r\n  if dir_struct(i).bytes==file_size\r\n   valid=1;\r\n   break;\r\n  end\r\n end\r\nend\r\n\r\nassert(valid)\r\n%%\r\n%cube_small.gif Rubiks Cube\r\nurl='https://drive.google.com/file/d/1N3p9M6WKGXqD3lilYuv-sUKTkGGI66Xk/view?usp=drive_link';\r\nfname='cube_small.gif'; \r\nfile_size=3812; % bytes \r\n\r\nfprintf('\\n***** Test 3 Dir:\\n\\n\\n')\r\ndir % Initial Dir\r\n\r\nGoogleDrive_urlwrite(url,fname); %expect   bytes for cube_small.gif\r\n\r\nfprintf('Dir after third call:\\n\\n')\r\ndir\r\ndir_struct=dir\r\nvalid=0;\r\nfor i=1:length(dir_struct)\r\n fprintf('%i %s %i\\n',i,dir_struct(i).name,dir_struct(i).bytes)\r\n if isequal(dir_struct(i).name,fname)  % contains(dir_struct(i).name,fname)\r\n  if dir_struct(i).bytes==file_size\r\n   valid=1;\r\n   break;\r\n  end\r\n end\r\nend\r\n\r\nassert(valid)","published":true,"deleted":false,"likes_count":1,"comments_count":2,"created_by":3097,"edited_by":3097,"edited_at":"2023-07-13T17:33:19.000Z","deleted_by":null,"deleted_at":null,"solvers_count":7,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2023-07-13T14:26:50.000Z","updated_at":"2023-07-13T17:33:19.000Z","published_at":"2023-07-13T16:15:25.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis Challenge is to download a file from GoogleDrive given its \\\"copylink\\\" provided URL and a file name.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGoogleDrive links fail for Matlab function like urlwrite, imread, imwrite, webread, and others. \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe file 2.png is given by \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"https://drive.google.com/file/d/1v3GsGgP3p905wzdvUqypL_-djYmxiyzK/view?usp=drive_link,\\\"\u003e\u003cw:r\u003e\u003cw:t\u003ehttps://drive.google.com/file/d/1v3GsGgP3p905wzdvUqypL_-djYmxiyzK/view?usp=drive_link,\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e which will bring up the file in a new window but this URL fails for matlab commands.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe GoogleDrive file must be \\\"Shared\\\" . The file must at least have share to those \\\"anyone with this link\\\".\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eTo enable file download the Google URL string must be modified:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e 1) Delete the end '/view?usp=*'; Anything after and inlcuding \\\"/view\\\" must be deleted\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e 2) Replace 'file/d/' with 'uc?export=download\u0026amp;id='\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGiven a URL and filename download the URL contents into a file called filename in the local Cody directory.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eVerification will be done by file name and file size.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":58513,"title":"Google Drive:  MATLAB mat file download","description":"Matlab 'mat' files are notoriously hard to email and download as they are binary files.\r\nTo make a 'mat' file downloadable from Google Drive requires a trick.\r\nCopy the 'mat' file and change its extension to 'PDF'. Place this 'PDF' on the Google Drive.\r\nTo download this file into 'mat' form use urlwrite with a Google Drive url, which will need to be fixed, and a destination fname ending in '.mat'\r\n\r\nThis Challenge is to download a file given a GoogleDrive link  and a fname, ending in '.mat', to the local directory. \r\nThe file for this URL ends in 'PDF' on a GoogleDrive.\r\nVerification will be done by loading the fname and verifying the size. This file is the ICFP2023 Orchestra Problem set compressed 90% as a mat file.","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.4333px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 273px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 136.5px; transform-origin: 407px 136.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 265.5px 8px; transform-origin: 265.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eMatlab 'mat' files are notoriously hard to email and download as they are binary files.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 216px 8px; transform-origin: 216px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eTo make a 'mat' file downloadable from Google Drive requires a trick.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 284.5px 8px; transform-origin: 284.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eCopy the 'mat' file and change its extension to 'PDF'. Place this 'PDF' on the Google Drive.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 21px; text-align: left; transform-origin: 384px 21px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 366.5px 8px; transform-origin: 366.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eTo download this file into 'mat' form use urlwrite with a Google Drive url, which will need to be fixed, and a destination fname ending in '.mat'\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 8px; transform-origin: 0px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 357px 8px; transform-origin: 357px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThis Challenge is to download a file given a GoogleDrive link  and a fname, ending in '.mat', to the local directory. \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 166px 8px; transform-origin: 166px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThe file for this URL ends in 'PDF' on a GoogleDrive.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 21px; text-align: left; transform-origin: 384px 21px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 366px 8px; transform-origin: 366px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eVerification will be done by loading the fname and verifying the size. This file is the ICFP2023 Orchestra Problem set compressed 90% as a mat file.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function url=GoogleDrive_urlwrite(url,fname)\r\n% The GoogleDrive \"copy link\" does not play well with matlab urlwrite/imread/imwrite/webread/... \r\n% Expect 'https://drive.google.com/file/d/1WDYDJJZ3wJ8Fs0-8E2u6bYxlZbOapNJn/view?usp=drive_link'\r\n% 1) Delete the end '/view...'\r\n% 2) Replace 'file/d/' with 'uc?export=download\u0026id='\r\n\r\n%This Challenge gives a URL for a .mat file that was saved as a .PDF on the googledrive.\r\n \r\n %urlwrite(url,fname);\r\nend","test_suite":"%%\r\nurl='https://drive.google.com/file/d/1mgxzsmVQNXgqHEdd61QR2r0STm3N9lgG/view?usp=drive_link';\r\nfname='orc_d_mu_axy_am_pxyr.mat';\r\ntic\r\nGoogleDrive_urlwrite(url,fname);\r\nfprintf('Process/Download Time: %.1f sec\\n',toc);\r\n\r\nload(fname); % This loads the cell array orc\r\n\r\nz=dir;\r\nfprintf('Local Directory: Filenames      Sizes\\n');\r\nfor i=1:length(z)\r\n fprintf('%30s  %i\\n',z(i).name,z(i).bytes);\r\nend\r\nfprintf('\\n\\n');\r\n\r\nfprintf('Size orc: %i %i\\n',size(orc));\r\n\r\nfprintf('\\n\\n orc{end}\\n');\r\norc{end}\r\n\r\nvalid=isequal([1 90],size(orc));\r\nassert(valid)\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":1,"created_by":3097,"edited_by":3097,"edited_at":"2023-07-13T18:21:49.000Z","deleted_by":null,"deleted_at":null,"solvers_count":8,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2023-07-13T17:45:26.000Z","updated_at":"2023-07-13T18:21:49.000Z","published_at":"2023-07-13T18:21:49.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eMatlab 'mat' files are notoriously hard to email and download as they are binary files.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eTo make a 'mat' file downloadable from Google Drive requires a trick.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eCopy the 'mat' file and change its extension to 'PDF'. Place this 'PDF' on the Google Drive.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eTo download this file into 'mat' form use urlwrite with a Google Drive url, which will need to be fixed, and a destination fname ending in '.mat'\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis Challenge is to download a file given a GoogleDrive link  and a fname, ending in '.mat', to the local directory. \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe file for this URL ends in 'PDF' on a GoogleDrive.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eVerification will be done by loading the fname and verifying the size. This file is the ICFP2023 Orchestra Problem set compressed 90% as a mat file.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":699,"title":"Reading Web Binary Files (jpg,pdf,tiff,png)","description":"The Challenge is to access a Web binary file, a PDF in this case, and provide the value of a specific byte.\r\n\r\n.\r\n\r\nAccessing files on the web provide multiple challenges due to the data structures being text or binary.\r\n\r\nThe functions urlread and urlwrite both access web files but provide different results for binary files. (jpg, pdf, tiff, png, ppt)\r\n\r\n\r\n\r\nInput:\r\n\r\nfname 'http://some valid location/file.pdf'\r\n\r\nn      The byte for which the value is being requested.\r\n\r\nOutput: Value of the byte, an integer ranging from 0 to 255\r\n\r\n.\r\n\r\n\r\nA solution exists in the test suite to show the different data created by urlread and urlwrite for binary data.\r\n\r\nA urlreadbin can be readily created to directly push the file to an array.","description_html":"\u003cp\u003eThe Challenge is to access a Web binary file, a PDF in this case, and provide the value of a specific byte.\u003c/p\u003e\u003cp\u003e.\u003c/p\u003e\u003cp\u003eAccessing files on the web provide multiple challenges due to the data structures being text or binary.\u003c/p\u003e\u003cp\u003eThe functions urlread and urlwrite both access web files but provide different results for binary files. (jpg, pdf, tiff, png, ppt)\u003c/p\u003e\u003cp\u003eInput:\u003c/p\u003e\u003cp\u003efname 'http://some valid location/file.pdf'\u003c/p\u003e\u003cp\u003en      The byte for which the value is being requested.\u003c/p\u003e\u003cp\u003eOutput: Value of the byte, an integer ranging from 0 to 255\u003c/p\u003e\u003cp\u003e.\u003c/p\u003e\u003cp\u003eA solution exists in the test suite to show the different data created by urlread and urlwrite for binary data.\u003c/p\u003e\u003cp\u003eA urlreadbin can be readily created to directly push the file to an array.\u003c/p\u003e","function_template":"function y = access_web_pdf(fname,n)\r\n  y = 0;\r\nend","test_suite":"%%\r\n% Cody External accessibility\r\n\r\n% This file may need to change in the future\r\nin_f='http://www.pvplc.org/_volunteer/docs/PVPLC%20Trail%20Crew%20Training%20Jan-Jun%202012.pdf';\r\n\r\nout_f='PVPLC.pdf';\r\n\r\nurlwrite(in_f,out_f);\r\n\r\nfid=fopen(out_f);\r\nurlwrite_out=fread(fid,128,'*uint8'); \r\n% Display Correct Binary Data\r\nurlwrite_out(1:16)'\r\n\r\n\r\nblock=urlread(in_f);\r\n% Display invalid binary data\r\nurlread_out=block(1:16)-char(0)\r\n% unicode urlread conversion affects bytes 12 thru 15\r\n\r\nn=12\r\nbyte_val = access_web_pdf(in_f,n)\r\n\r\nbyte_correct=181;\r\n\r\nassert(isequal(byte_val,byte_correct))\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":1,"created_by":3097,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":11,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2012-05-18T04:26:21.000Z","updated_at":"2012-05-21T05:35:07.000Z","published_at":"2012-05-21T05:35:07.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe Challenge is to access a Web binary file, a PDF in this case, and provide the value of a specific byte.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eAccessing files on the web provide multiple challenges due to the data structures being text or binary.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe functions urlread and urlwrite both access web files but provide different results for binary files. (jpg, pdf, tiff, png, ppt)\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eInput:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003efname 'http://some valid location/file.pdf'\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003en The byte for which the value is being requested.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eOutput: Value of the byte, an integer ranging from 0 to 255\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eA solution exists in the test suite to show the different data created by urlread and urlwrite for binary data.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eA urlreadbin can be readily created to directly push the file to an array.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":1097,"title":"USC Fall 2012 ACM Question A : Read Input File","description":"This Challenge is to read the Question A input text file of the \u003chttp://contest.usc.edu/index.php/Fall12/Home USC ACM Fall 2012 Contest\u003e.\r\n\r\nThe text format is: Number of sets,RowsSet1 ColsSet1,Array1, Vector1, RowsSet2 ColsSet2, Array2, Vector2\r\n\r\neg:Two data sets of arrays 3x3 and 2x4\r\n\r\n  2\r\n  3 3\r\n  000\r\n  111\r\n  110\r\n  010\r\n  2 4\r\n  1010\r\n  1100\r\n  0001\r\n\r\n\r\nThe USC input file has 17 data sets.\r\n\r\nInput: [ url_filename, k],  k= array data set to return\r\n\r\nOutput: Selected data set Array\r\n\r\nExample: [ \u003chttp://contest.usc.edu/index.php/Fall12/Home?action=download\u0026upname=codes.in.txt\u003e, 1]\r\n\r\nOutput:\r\n[0 0 0; 1 1 1; 1 1 0]\r\n\r\nHow will the Pros read and process the text file?\r\n\r\nFollow up Challenge will be solving the actual ACM question.\r\n\r\n\r\n\r\n","description_html":"\u003cp\u003eThis Challenge is to read the Question A input text file of the \u003ca href=\"http://contest.usc.edu/index.php/Fall12/Home\"\u003eUSC ACM Fall 2012 Contest\u003c/a\u003e.\u003c/p\u003e\u003cp\u003eThe text format is: Number of sets,RowsSet1 ColsSet1,Array1, Vector1, RowsSet2 ColsSet2, Array2, Vector2\u003c/p\u003e\u003cp\u003eeg:Two data sets of arrays 3x3 and 2x4\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003e2\r\n3 3\r\n000\r\n111\r\n110\r\n010\r\n2 4\r\n1010\r\n1100\r\n0001\r\n\u003c/pre\u003e\u003cp\u003eThe USC input file has 17 data sets.\u003c/p\u003e\u003cp\u003eInput: [ url_filename, k],  k= array data set to return\u003c/p\u003e\u003cp\u003eOutput: Selected data set Array\u003c/p\u003e\u003cp\u003eExample: [ \u003ca href=\"http://contest.usc.edu/index.php/Fall12/Home?action=download\u0026amp;upname=codes.in.txt\"\u003ehttp://contest.usc.edu/index.php/Fall12/Home?action=download\u0026upname=codes.in.txt\u003c/a\u003e, 1]\u003c/p\u003e\u003cp\u003eOutput:\r\n[0 0 0; 1 1 1; 1 1 0]\u003c/p\u003e\u003cp\u003eHow will the Pros read and process the text file?\u003c/p\u003e\u003cp\u003eFollow up Challenge will be solving the actual ACM question.\u003c/p\u003e","function_template":"function A = USC_file(urlfn,ptr)\r\n% urlfn is 'http://contest.usc.edu/index.php/Fall12/Home?action=download\u0026upname=codes.in.txt';\r\n\r\n urlwrite(urlfn,'codesinput.txt');\r\n A=[];\r\n\r\nend","test_suite":"%%\r\ntic\r\nurlfn='http://contest.usc.edu/index.php/Fall12/Home?action=download\u0026upname=codes.in.txt';\r\nurlwrite(urlfn,'codesin_A.txt'); % Load file from USC\r\ntoc\r\n\r\nfor trial=1:3\r\n\r\n ptr=randi(17);\r\n\r\n A_USC = USC_file(urlfn,ptr);\r\n\r\n fid=fopen('codesin_A.txt','r');\r\n\r\n qty=fscanf(fid,'%i',1);\r\n for q=1:ptr\r\n  nr=fscanf(fid,'%i',1);\r\n  nc=fscanf(fid,'%i',1);\r\n \r\n  A=zeros(nr,nc);\r\n  for i=1:nr\r\n   strv=fscanf(fid,'%s',1); % Reads a line of text\r\n   A(i,:)=strv-'0'; % vectorize the string\r\n  end\r\n \r\n  strv=fscanf(fid,'%s',1);\r\n  Test=strv-'0';\r\n \r\n end\r\n fclose(fid);\r\n \r\n assert(isequal(A,A_USC))\r\n \r\nend % trial\r\n \r\n\r\ntoc\r\n\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":3097,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":9,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2012-12-06T00:57:32.000Z","updated_at":"2012-12-06T02:39:34.000Z","published_at":"2012-12-06T02:37:29.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis Challenge is to read the Question A input text file of the\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"http://contest.usc.edu/index.php/Fall12/Home\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eUSC ACM Fall 2012 Contest\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe text format is: Number of sets,RowsSet1 ColsSet1,Array1, Vector1, RowsSet2 ColsSet2, Array2, Vector2\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eeg:Two data sets of arrays 3x3 and 2x4\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[2\\n3 3\\n000\\n111\\n110\\n010\\n2 4\\n1010\\n1100\\n0001]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe USC input file has 17 data sets.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eInput: [ url_filename, k], k= array data set to return\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eOutput: Selected data set Array\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eExample: [\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"http://contest.usc.edu/index.php/Fall12/Home?action=download\u0026amp;upname=codes.in.txt\\\"\u003e\u003cw:r\u003e\u003cw:t\u003e\u0026lt;http://contest.usc.edu/index.php/Fall12/Home?action=download\u0026amp;upname=codes.in.txt\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e\u0026gt;, 1]\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eOutput: [0 0 0; 1 1 1; 1 1 0]\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eHow will the Pros read and process the text file?\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFollow up Challenge will be solving the actual ACM question.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":781,"title":"Access a web hosted copy of the Tiles Contest MAT file","description":"Access a web hosted copy of the Tiles Contest sample \"mat\" and verify success by returning for a board the number of tiles, number of rows, and number of columns of the board.\r\n\r\nDetails of the Tiles Contest can be found at \u003chttp://www.mathworks.com/matlabcentral/contest/contests/36 Tiles Contest\u003e.\r\n\r\nThe runcontest.m provides testsuite structure information.\r\n\r\n*Input:* (urlfname, board)\r\n\r\nfn='http://www.toobigforemail.com/cryptkeeper.toobig?nppmkc2=xyeffg\u00266cq_kc2=yae1d8\u00266cq_konmpb=y88ayxyx8xxy1xdyx'\r\n\r\n*Output:* (number of tiles, nrows, ncols)\r\n\r\nFor board 99\r\n\r\n[ 20 10 8 ]\r\n\r\n\r\n\r\nNote: The mat file is a very efficiently packed binary file.\r\n\r\nFollow-up questions will be creation of a mat file and a timed contest for a few of the perfectly solveable Tile boards","description_html":"\u003cp\u003eAccess a web hosted copy of the Tiles Contest sample \"mat\" and verify success by returning for a board the number of tiles, number of rows, and number of columns of the board.\u003c/p\u003e\u003cp\u003eDetails of the Tiles Contest can be found at \u003ca href=\"http://www.mathworks.com/matlabcentral/contest/contests/36\"\u003eTiles Contest\u003c/a\u003e.\u003c/p\u003e\u003cp\u003eThe runcontest.m provides testsuite structure information.\u003c/p\u003e\u003cp\u003e\u003cb\u003eInput:\u003c/b\u003e (urlfname, board)\u003c/p\u003e\u003cp\u003efn='http://www.toobigforemail.com/cryptkeeper.toobig?nppmkc2=xyeffg\u00266cq_kc2=yae1d8\u00266cq_konmpb=y88ayxyx8xxy1xdyx'\u003c/p\u003e\u003cp\u003e\u003cb\u003eOutput:\u003c/b\u003e (number of tiles, nrows, ncols)\u003c/p\u003e\u003cp\u003eFor board 99\u003c/p\u003e\u003cp\u003e[ 20 10 8 ]\u003c/p\u003e\u003cp\u003eNote: The mat file is a very efficiently packed binary file.\u003c/p\u003e\u003cp\u003eFollow-up questions will be creation of a mat file and a timed contest for a few of the perfectly solveable Tile boards\u003c/p\u003e","function_template":"function out = access_url_mat(urlfname,brd)\r\n \r\n %tiles=tests.testsuite(brd).tiles;\r\n\r\n ntiles=1;nrow=1;ncol=1;\r\n \r\n out=[ntiles nrow ncol];\r\n\r\nend","test_suite":"%%\r\n% Cody External accessibility\r\ny=clock;\r\nrand('state',floor(10000*y(6)))\r\nbrd=randi(100,1)\r\n\r\nfn='http://www.toobigforemail.com/cryptkeeper.toobig?nppmkc2=xyeffg\u00266cq_kc2=yae1d8\u00266cq_konmpb=y88ayxyx8xxy1xdyx';\r\n\r\nfn='http://tinyurl.com/matlab-tiles-mat';\r\ntestSuiteFile = 'raz_tiles.mat';\r\nurlwrite(fn,testSuiteFile);\r\n\r\ntests = load(testSuiteFile,'testsuite');\r\n\r\ntiles = tests.testsuite(brd).tiles;\r\nrows = tests.testsuite(brd).r;\r\ncols = tests.testsuite(brd).c;\r\n\r\nexpected=[size(tiles,1) rows cols]\r\n\r\nout=access_url_mat(fn,brd)\r\n\r\nassert(isequal(out,expected))\r\n%%\r\nbrd=randi(100,1)\r\n\r\nfn='http://www.toobigforemail.com/cryptkeeper.toobig?nppmkc2=xyeffg\u00266cq_kc2=yae1d8\u00266cq_konmpb=y88ayxyx8xxy1xdyx';\r\n\r\nfn='http://tinyurl.com/matlab-tiles-mat';\r\ntestSuiteFile = 'raz_tiles.mat';\r\nurlwrite(fn,testSuiteFile);\r\n\r\ntests = load(testSuiteFile,'testsuite');\r\n\r\ntiles = tests.testsuite(brd).tiles;\r\nrows = tests.testsuite(brd).r;\r\ncols = tests.testsuite(brd).c;\r\n\r\nexpected=[size(tiles,1) rows cols]\r\n\r\nout=access_url_mat(fn,brd)\r\n\r\nassert(isequal(out,expected))\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":2,"created_by":3097,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":7,"test_suite_updated_at":"2012-11-22T12:22:58.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2012-06-21T04:54:17.000Z","updated_at":"2025-10-25T08:50:10.000Z","published_at":"2012-06-22T04:40:01.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eAccess a web hosted copy of the Tiles Contest sample \\\"mat\\\" and verify success by returning for a board the number of tiles, number of rows, and number of columns of the board.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eDetails of the Tiles Contest can be found at\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"http://www.mathworks.com/matlabcentral/contest/contests/36\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eTiles Contest\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe runcontest.m provides testsuite structure information.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eInput:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e (urlfname, board)\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003efn='http://www.toobigforemail.com/cryptkeeper.toobig?nppmkc2=xyeffg\u0026amp;6cq_kc2=yae1d8\u0026amp;6cq_konmpb=y88ayxyx8xxy1xdyx'\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eOutput:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e (number of tiles, nrows, ncols)\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFor board 99\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e[ 20 10 8 ]\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eNote: The mat file is a very efficiently packed binary file.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFollow-up questions will be creation of a mat file and a timed contest for a few of the perfectly solveable Tile boards\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":46686,"title":"Kaggle: Planetoid Game of Life - Solve 3000 of 50000 Puzzles","description":null,"description_html":"\u003cdiv style = \"text-align: start; line-height: 20.4333px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 419.167px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 209.583px; transform-origin: 407px 209.583px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 84px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 42px; text-align: left; transform-origin: 384px 42px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003ca target='_blank' href = \"https://www.kaggle.com/c/conways-reverse-game-of-life-2020\"\u003e\u003cspan style=\"\"\u003e\u003cspan style=\"\"\u003eKaggle's Conway's Reverse Game of Life 2020 \u003c/span\u003e\u003c/span\u003e\u003c/a\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 203.05px 7.91667px; transform-origin: 203.05px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003econtest inspires this Life challenge. The kaggle contest runs from Oct-01-2020 thru Nov-30-2020. References:\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 1.95px 7.91667px; transform-origin: 1.95px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e \u003c/span\u003e\u003c/span\u003e\u003ca target='_blank' href = \"http://mathworld.wolfram.com/GameofLife.html\"\u003e\u003cspan style=\"\"\u003e\u003cspan style=\"\"\u003eGame of Life at Wolfram\u003c/span\u003e\u003c/span\u003e\u003c/a\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 1.95px 7.91667px; transform-origin: 1.95px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e.\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 1.95px 7.91667px; transform-origin: 1.95px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e \u003c/span\u003e\u003c/span\u003e\u003ca target='_blank' href = \"http://en.wikipedia.org/wiki/Conway%27s_Game_of_Life\"\u003e\u003cspan style=\"\"\u003e\u003cspan style=\"\"\u003eWiki Life\u003c/span\u003e\u003c/span\u003e\u003c/a\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 138.467px 7.91667px; transform-origin: 138.467px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e. The Kaggle event is 50K cases to solve for a state 1 to 5 iterations prior to a given state. Imperfect solutions are allowed but penalized. Input file to Kaggle is a csv so Matlab solutions can be posted at the Kaggle site for this event.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 271.517px 7.91667px; transform-origin: 271.517px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThis Challenge is to Solve at least 3000 of the 50K puzzles per these revised Life Laws.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgb(247, 247, 247); block-size: 102.167px; border-bottom-left-radius: 4px; border-bottom-right-radius: 4px; border-end-end-radius: 4px; border-end-start-radius: 4px; border-start-end-radius: 4px; border-start-start-radius: 4px; border-top-left-radius: 4px; border-top-right-radius: 4px; margin-block-end: 10px; margin-block-start: 10px; margin-bottom: 10px; margin-inline-end: 3px; margin-inline-start: 3px; margin-left: 3px; margin-right: 3px; margin-top: 10px; perspective-origin: 404px 51.0833px; transform-origin: 404px 51.0833px; margin-left: 3px; margin-top: 10px; margin-bottom: 10px; margin-right: 3px; \"\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 0.833333px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.833333px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.833333px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.833333px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 350.35px 7.91667px; transform-origin: 350.35px 7.91667px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 26.95px 7.91667px; transform-origin: 26.95px 7.91667px; \"\u003e1. Any \u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(170, 4, 249); border-block-start-color: rgb(170, 4, 249); border-bottom-color: rgb(170, 4, 249); border-inline-end-color: rgb(170, 4, 249); border-inline-start-color: rgb(170, 4, 249); border-left-color: rgb(170, 4, 249); border-right-color: rgb(170, 4, 249); border-top-color: rgb(170, 4, 249); caret-color: rgb(170, 4, 249); color: rgb(170, 4, 249); column-rule-color: rgb(170, 4, 249); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(170, 4, 249); perspective-origin: 188.65px 7.91667px; text-decoration: none; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); transform-origin: 188.65px 7.91667px; \"\u003elive cell with fewer than two live neighbors dies\u003c/span\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 19.25px 7.91667px; transform-origin: 19.25px 7.91667px; \"\u003e, as \u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(170, 4, 249); border-block-start-color: rgb(170, 4, 249); border-bottom-color: rgb(170, 4, 249); border-inline-end-color: rgb(170, 4, 249); border-inline-start-color: rgb(170, 4, 249); border-left-color: rgb(170, 4, 249); border-right-color: rgb(170, 4, 249); border-top-color: rgb(170, 4, 249); caret-color: rgb(170, 4, 249); color: rgb(170, 4, 249); column-rule-color: rgb(170, 4, 249); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(170, 4, 249); perspective-origin: 115.5px 7.91667px; text-decoration: none; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); transform-origin: 115.5px 7.91667px; \"\u003eif caused by under-population.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 0.833333px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.833333px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.833333px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.833333px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 315.7px 7.91667px; transform-origin: 315.7px 7.91667px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 26.95px 7.91667px; transform-origin: 26.95px 7.91667px; \"\u003e2. Any \u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(170, 4, 249); border-block-start-color: rgb(170, 4, 249); border-bottom-color: rgb(170, 4, 249); border-inline-end-color: rgb(170, 4, 249); border-inline-start-color: rgb(170, 4, 249); border-left-color: rgb(170, 4, 249); border-right-color: rgb(170, 4, 249); border-top-color: rgb(170, 4, 249); caret-color: rgb(170, 4, 249); color: rgb(170, 4, 249); column-rule-color: rgb(170, 4, 249); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(170, 4, 249); perspective-origin: 288.75px 7.91667px; text-decoration: none; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); transform-origin: 288.75px 7.91667px; \"\u003elive cell with two or three live neighbors lives on to the next generation.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 0.833333px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.833333px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.833333px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.833333px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 311.85px 7.91667px; transform-origin: 311.85px 7.91667px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 26.95px 7.91667px; transform-origin: 26.95px 7.91667px; \"\u003e3. Any \u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(170, 4, 249); border-block-start-color: rgb(170, 4, 249); border-bottom-color: rgb(170, 4, 249); border-inline-end-color: rgb(170, 4, 249); border-inline-start-color: rgb(170, 4, 249); border-left-color: rgb(170, 4, 249); border-right-color: rgb(170, 4, 249); border-top-color: rgb(170, 4, 249); caret-color: rgb(170, 4, 249); color: rgb(170, 4, 249); column-rule-color: rgb(170, 4, 249); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(170, 4, 249); perspective-origin: 192.5px 7.91667px; text-decoration: none; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); transform-origin: 192.5px 7.91667px; \"\u003elive cell with more than three live neighbors dies\u003c/span\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 19.25px 7.91667px; transform-origin: 19.25px 7.91667px; \"\u003e, as \u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(170, 4, 249); border-block-start-color: rgb(170, 4, 249); border-bottom-color: rgb(170, 4, 249); border-inline-end-color: rgb(170, 4, 249); border-inline-start-color: rgb(170, 4, 249); border-left-color: rgb(170, 4, 249); border-right-color: rgb(170, 4, 249); border-top-color: rgb(170, 4, 249); caret-color: rgb(170, 4, 249); color: rgb(170, 4, 249); column-rule-color: rgb(170, 4, 249); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(170, 4, 249); perspective-origin: 73.15px 7.91667px; text-decoration: none; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); transform-origin: 73.15px 7.91667px; \"\u003eif by overcrowding.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 0.833333px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.833333px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.833333px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.833333px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 361.9px 7.91667px; transform-origin: 361.9px 7.91667px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 26.95px 7.91667px; transform-origin: 26.95px 7.91667px; \"\u003e4. Any \u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(170, 4, 249); border-block-start-color: rgb(170, 4, 249); border-bottom-color: rgb(170, 4, 249); border-inline-end-color: rgb(170, 4, 249); border-inline-start-color: rgb(170, 4, 249); border-left-color: rgb(170, 4, 249); border-right-color: rgb(170, 4, 249); border-top-color: rgb(170, 4, 249); caret-color: rgb(170, 4, 249); color: rgb(170, 4, 249); column-rule-color: rgb(170, 4, 249); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(170, 4, 249); perspective-origin: 242.55px 7.91667px; text-decoration: none; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); transform-origin: 242.55px 7.91667px; \"\u003edead cell with exactly three live neighbors becomes a live cell\u003c/span\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 19.25px 7.91667px; transform-origin: 19.25px 7.91667px; \"\u003e, as \u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(170, 4, 249); border-block-start-color: rgb(170, 4, 249); border-bottom-color: rgb(170, 4, 249); border-inline-end-color: rgb(170, 4, 249); border-inline-start-color: rgb(170, 4, 249); border-left-color: rgb(170, 4, 249); border-right-color: rgb(170, 4, 249); border-top-color: rgb(170, 4, 249); caret-color: rgb(170, 4, 249); color: rgb(170, 4, 249); column-rule-color: rgb(170, 4, 249); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(170, 4, 249); perspective-origin: 73.15px 7.91667px; text-decoration: none; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); transform-origin: 73.15px 7.91667px; \"\u003eif by reproduction.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 0.833333px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.833333px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.833333px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.833333px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 265.65px 7.91667px; transform-origin: 265.65px 7.91667px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 34.65px 7.91667px; transform-origin: 34.65px 7.91667px; \"\u003e5. Edges \u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(170, 4, 249); border-block-start-color: rgb(170, 4, 249); border-bottom-color: rgb(170, 4, 249); border-inline-end-color: rgb(170, 4, 249); border-inline-start-color: rgb(170, 4, 249); border-left-color: rgb(170, 4, 249); border-right-color: rgb(170, 4, 249); border-top-color: rgb(170, 4, 249); caret-color: rgb(170, 4, 249); color: rgb(170, 4, 249); column-rule-color: rgb(170, 4, 249); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(170, 4, 249); perspective-origin: 231px 7.91667px; text-decoration: none; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); transform-origin: 231px 7.91667px; \"\u003ewrap around. Eight Neighbors. (Change to normal planar life)\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 10px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 10px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 10px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 221.317px 7.91667px; transform-origin: 221.317px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eNote: The edges wrap so the matrix represents the surface of a sphere.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 21px; text-align: left; transform-origin: 384px 21px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 19.4333px 7.91667px; transform-origin: 19.4333px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eInput:\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 354.317px 7.91667px; transform-origin: 354.317px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e (mtest,numtosolve) the Finish state matrix of 50K rows of [casenumber, iterations, 625 values], number of case to solve (3000)\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 21px; text-align: left; transform-origin: 384px 21px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 25.2667px 7.91667px; transform-origin: 25.2667px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eOutput:\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 347.317px 7.91667px; transform-origin: 347.317px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e (mstart) the Starting state matrix of at least 3000 puzzles all with perfect zero error solutions, [casenumber, 625 values]\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 7.91667px; transform-origin: 0px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 15.95px 7.91667px; transform-origin: 15.95px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eHint:\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 250.483px 7.91667px; transform-origin: 250.483px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e There are 3726 trivial solutions where the  Finish state is the Start state solution.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function mstart = solveLife(mtest,numtosolve)\r\n  mstart=zeros(numtosolve,626)\r\nend","test_suite":"%%\r\n%'https://sites.google.com/site/razapor/matlab_cody/mtest.mat?attredirects=0\u0026d=1';\r\n%mtest format is [casenumer, iterations, start1:625,finish1:625] for 50K cases 0:49999\r\n%'https://sites.google.com/site/razapor/matlab_cody/mtrain.mat?attredirects=0\u0026d=1';\r\ntic\r\nfname='https://sites.google.com/site/razapor/matlab_cody/mtest.mat?attredirects=0\u0026d=1';\r\nurlwrite(fname,'mtest.mat') %1.22s\r\nload('mtest.mat'); %0.42s\r\ntoc\r\n\r\nnumtosolve=3000;\r\nmstart = solveLife(mtest,numtosolve);\r\ntoc\r\nmstart=unique(mstart,'rows'); % remove exact duplicate solutions\r\n\r\nvalid=0;\r\nfor i=1:size(mstart,1)  % \u003c0.5sec to process 3K cases\r\n icase=mstart(i,1); %50000:99999\r\n iter=mtest(icase-49999,2); %Test cases start at 50000\r\n \r\n A=reshape(mstart(i,2:end),25,25);\r\n for j=1:iter\r\n  C=0;\r\n  for r=-1:1 % -1 Up   Using circshift to perform wrap convolution\r\n   Ar=circshift(A,r,1);\r\n   for c=-1:1 % -1 Left\r\n     Arc=circshift(Ar,c,2);\r\n     C=C+Arc;\r\n   end\r\n  end\r\n  A = C==3 | A\u0026C==4;\r\n end %j\r\n\r\n if isequal(A(:)',mtest(icase-49999,3:end)) % mtest [case, iter, data1:625]\r\n  valid=valid+1;\r\n else\r\n  valid=0;\r\n  break;\r\n end\r\nend %main loop i\r\ntoc\r\n\r\nassert(valid\u003e=3000)\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":3097,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":3,"test_suite_updated_at":"2020-10-06T15:37:58.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2020-10-06T14:46:29.000Z","updated_at":"2020-10-06T15:37:58.000Z","published_at":"2020-10-06T15:37:58.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:hyperlink w:docLocation=\\\"https://www.kaggle.com/c/conways-reverse-game-of-life-2020\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eKaggle's Conway's Reverse Game of Life 2020 \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003econtest inspires this Life challenge. The kaggle contest runs from Oct-01-2020 thru Nov-30-2020. References:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"http://mathworld.wolfram.com/GameofLife.html\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eGame of Life at Wolfram\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e.\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"http://en.wikipedia.org/wiki/Conway%27s_Game_of_Life\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eWiki Life\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e. The Kaggle event is 50K cases to solve for a state 1 to 5 iterations prior to a given state. Imperfect solutions are allowed but penalized. Input file to Kaggle is a csv so Matlab solutions can be posted at the Kaggle site for this event.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis Challenge is to Solve at least 3000 of the 50K puzzles per these revised Life Laws.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[1. Any live cell with fewer than two live neighbors dies, as if caused by under-population.\\n2. Any live cell with two or three live neighbors lives on to the next generation.\\n3. Any live cell with more than three live neighbors dies, as if by overcrowding.\\n4. Any dead cell with exactly three live neighbors becomes a live cell, as if by reproduction.\\n5. Edges wrap around. Eight Neighbors. (Change to normal planar life)]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eNote: The edges wrap so the matrix represents the surface of a sphere.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eInput:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e (mtest,numtosolve) the Finish state matrix of 50K rows of [casenumber, iterations, 625 values], number of case to solve (3000)\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eOutput:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e (mstart) the Starting state matrix of at least 3000 puzzles all with perfect zero error solutions, [casenumber, 625 values]\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eHint:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e There are 3726 trivial solutions where the  Finish state is the Start state solution.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":46691,"title":"Kaggle: Planetoid Game of Life - Solve 40 non-trivial Puzzles","description":null,"description_html":"\u003cdiv style = \"text-align: start; line-height: 20.4333px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 482.167px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 241.083px; transform-origin: 407px 241.083px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 84px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 42px; text-align: left; transform-origin: 384px 42px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003ca target='_blank' href = \"https://www.kaggle.com/c/conways-reverse-game-of-life-2020\"\u003e\u003cspan style=\"\"\u003e\u003cspan style=\"\"\u003eKaggle's Conway's Reverse Game of Life 2020 \u003c/span\u003e\u003c/span\u003e\u003c/a\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 203.05px 7.91667px; transform-origin: 203.05px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003econtest inspires this Life challenge. The kaggle contest runs from Oct-01-2020 thru Nov-30-2020. References:\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 1.95px 7.91667px; transform-origin: 1.95px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e \u003c/span\u003e\u003c/span\u003e\u003ca target='_blank' href = \"http://mathworld.wolfram.com/GameofLife.html\"\u003e\u003cspan style=\"\"\u003e\u003cspan style=\"\"\u003eGame of Life at Wolfram\u003c/span\u003e\u003c/span\u003e\u003c/a\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 1.95px 7.91667px; transform-origin: 1.95px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e.\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 1.95px 7.91667px; transform-origin: 1.95px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e \u003c/span\u003e\u003c/span\u003e\u003ca target='_blank' href = \"http://en.wikipedia.org/wiki/Conway%27s_Game_of_Life\"\u003e\u003cspan style=\"\"\u003e\u003cspan style=\"\"\u003eWiki Life\u003c/span\u003e\u003c/span\u003e\u003c/a\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 138.467px 7.91667px; transform-origin: 138.467px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e. The Kaggle event is 50K cases to solve for a state 1 to 5 iterations prior to a given state. Imperfect solutions are allowed but penalized. Input file to Kaggle is a csv so Matlab solutions can be posted at the Kaggle site for this event.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 21px; text-align: left; transform-origin: 384px 21px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 384px 7.91667px; transform-origin: 384px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThis Challenge is to Solve at least 40, excluding trivials, of the 50K puzzles per these revised Life Laws. Trivial solutions are where the Final state may match the Start State.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgb(247, 247, 247); block-size: 102.167px; border-bottom-left-radius: 4px; border-bottom-right-radius: 4px; border-end-end-radius: 4px; border-end-start-radius: 4px; border-start-end-radius: 4px; border-start-start-radius: 4px; border-top-left-radius: 4px; border-top-right-radius: 4px; margin-block-end: 10px; margin-block-start: 10px; margin-bottom: 10px; margin-inline-end: 3px; margin-inline-start: 3px; margin-left: 3px; margin-right: 3px; margin-top: 10px; perspective-origin: 404px 51.0833px; transform-origin: 404px 51.0833px; margin-left: 3px; margin-top: 10px; margin-bottom: 10px; margin-right: 3px; \"\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 0.833333px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.833333px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.833333px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.833333px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 350.35px 7.91667px; transform-origin: 350.35px 7.91667px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 26.95px 7.91667px; transform-origin: 26.95px 7.91667px; \"\u003e1. Any \u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(170, 4, 249); border-block-start-color: rgb(170, 4, 249); border-bottom-color: rgb(170, 4, 249); border-inline-end-color: rgb(170, 4, 249); border-inline-start-color: rgb(170, 4, 249); border-left-color: rgb(170, 4, 249); border-right-color: rgb(170, 4, 249); border-top-color: rgb(170, 4, 249); caret-color: rgb(170, 4, 249); color: rgb(170, 4, 249); column-rule-color: rgb(170, 4, 249); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(170, 4, 249); perspective-origin: 188.65px 7.91667px; text-decoration: none; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); transform-origin: 188.65px 7.91667px; \"\u003elive cell with fewer than two live neighbors dies\u003c/span\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 19.25px 7.91667px; transform-origin: 19.25px 7.91667px; \"\u003e, as \u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(170, 4, 249); border-block-start-color: rgb(170, 4, 249); border-bottom-color: rgb(170, 4, 249); border-inline-end-color: rgb(170, 4, 249); border-inline-start-color: rgb(170, 4, 249); border-left-color: rgb(170, 4, 249); border-right-color: rgb(170, 4, 249); border-top-color: rgb(170, 4, 249); caret-color: rgb(170, 4, 249); color: rgb(170, 4, 249); column-rule-color: rgb(170, 4, 249); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(170, 4, 249); perspective-origin: 115.5px 7.91667px; text-decoration: none; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); transform-origin: 115.5px 7.91667px; \"\u003eif caused by under-population.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 0.833333px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.833333px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.833333px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.833333px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 315.7px 7.91667px; transform-origin: 315.7px 7.91667px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 26.95px 7.91667px; transform-origin: 26.95px 7.91667px; \"\u003e2. Any \u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(170, 4, 249); border-block-start-color: rgb(170, 4, 249); border-bottom-color: rgb(170, 4, 249); border-inline-end-color: rgb(170, 4, 249); border-inline-start-color: rgb(170, 4, 249); border-left-color: rgb(170, 4, 249); border-right-color: rgb(170, 4, 249); border-top-color: rgb(170, 4, 249); caret-color: rgb(170, 4, 249); color: rgb(170, 4, 249); column-rule-color: rgb(170, 4, 249); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(170, 4, 249); perspective-origin: 288.75px 7.91667px; text-decoration: none; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); transform-origin: 288.75px 7.91667px; \"\u003elive cell with two or three live neighbors lives on to the next generation.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 0.833333px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.833333px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.833333px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.833333px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 311.85px 7.91667px; transform-origin: 311.85px 7.91667px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 26.95px 7.91667px; transform-origin: 26.95px 7.91667px; \"\u003e3. Any \u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(170, 4, 249); border-block-start-color: rgb(170, 4, 249); border-bottom-color: rgb(170, 4, 249); border-inline-end-color: rgb(170, 4, 249); border-inline-start-color: rgb(170, 4, 249); border-left-color: rgb(170, 4, 249); border-right-color: rgb(170, 4, 249); border-top-color: rgb(170, 4, 249); caret-color: rgb(170, 4, 249); color: rgb(170, 4, 249); column-rule-color: rgb(170, 4, 249); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(170, 4, 249); perspective-origin: 192.5px 7.91667px; text-decoration: none; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); transform-origin: 192.5px 7.91667px; \"\u003elive cell with more than three live neighbors dies\u003c/span\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 19.25px 7.91667px; transform-origin: 19.25px 7.91667px; \"\u003e, as \u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(170, 4, 249); border-block-start-color: rgb(170, 4, 249); border-bottom-color: rgb(170, 4, 249); border-inline-end-color: rgb(170, 4, 249); border-inline-start-color: rgb(170, 4, 249); border-left-color: rgb(170, 4, 249); border-right-color: rgb(170, 4, 249); border-top-color: rgb(170, 4, 249); caret-color: rgb(170, 4, 249); color: rgb(170, 4, 249); column-rule-color: rgb(170, 4, 249); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(170, 4, 249); perspective-origin: 73.15px 7.91667px; text-decoration: none; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); transform-origin: 73.15px 7.91667px; \"\u003eif by overcrowding.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 0.833333px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.833333px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.833333px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.833333px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 361.9px 7.91667px; transform-origin: 361.9px 7.91667px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 26.95px 7.91667px; transform-origin: 26.95px 7.91667px; \"\u003e4. Any \u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(170, 4, 249); border-block-start-color: rgb(170, 4, 249); border-bottom-color: rgb(170, 4, 249); border-inline-end-color: rgb(170, 4, 249); border-inline-start-color: rgb(170, 4, 249); border-left-color: rgb(170, 4, 249); border-right-color: rgb(170, 4, 249); border-top-color: rgb(170, 4, 249); caret-color: rgb(170, 4, 249); color: rgb(170, 4, 249); column-rule-color: rgb(170, 4, 249); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(170, 4, 249); perspective-origin: 242.55px 7.91667px; text-decoration: none; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); transform-origin: 242.55px 7.91667px; \"\u003edead cell with exactly three live neighbors becomes a live cell\u003c/span\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 19.25px 7.91667px; transform-origin: 19.25px 7.91667px; \"\u003e, as \u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(170, 4, 249); border-block-start-color: rgb(170, 4, 249); border-bottom-color: rgb(170, 4, 249); border-inline-end-color: rgb(170, 4, 249); border-inline-start-color: rgb(170, 4, 249); border-left-color: rgb(170, 4, 249); border-right-color: rgb(170, 4, 249); border-top-color: rgb(170, 4, 249); caret-color: rgb(170, 4, 249); color: rgb(170, 4, 249); column-rule-color: rgb(170, 4, 249); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(170, 4, 249); perspective-origin: 73.15px 7.91667px; text-decoration: none; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); transform-origin: 73.15px 7.91667px; \"\u003eif by reproduction.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 0.833333px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.833333px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.833333px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.833333px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 265.65px 7.91667px; transform-origin: 265.65px 7.91667px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 34.65px 7.91667px; transform-origin: 34.65px 7.91667px; \"\u003e5. Edges \u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(170, 4, 249); border-block-start-color: rgb(170, 4, 249); border-bottom-color: rgb(170, 4, 249); border-inline-end-color: rgb(170, 4, 249); border-inline-start-color: rgb(170, 4, 249); border-left-color: rgb(170, 4, 249); border-right-color: rgb(170, 4, 249); border-top-color: rgb(170, 4, 249); caret-color: rgb(170, 4, 249); color: rgb(170, 4, 249); column-rule-color: rgb(170, 4, 249); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(170, 4, 249); perspective-origin: 231px 7.91667px; text-decoration: none; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); transform-origin: 231px 7.91667px; \"\u003ewrap around. Eight Neighbors. (Change to normal planar life)\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 10px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 10px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 10px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 221.317px 7.91667px; transform-origin: 221.317px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eNote: The edges wrap so the matrix represents the surface of a sphere.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 21px; text-align: left; transform-origin: 384px 21px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 19.4333px 7.91667px; transform-origin: 19.4333px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eInput:\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 354.317px 7.91667px; transform-origin: 354.317px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e (mtest,numtosolve) the Finish state matrix of 50K rows of [casenumber, iterations, 625 values], number of case to solve (40)\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 21px; text-align: left; transform-origin: 384px 21px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 25.2667px 7.91667px; transform-origin: 25.2667px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eOutput:\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 339.533px 7.91667px; transform-origin: 339.533px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e (mstart) the Starting state matrix of at least 40 puzzles all with perfect zero error solutions, [casenumber, 625 values]\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 7.91667px; transform-origin: 0px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 63px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 31.5px; text-align: left; transform-origin: 384px 31.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 15.95px 7.91667px; transform-origin: 15.95px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eHint:\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 364.467px 7.91667px; transform-origin: 364.467px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e There are 40 non-trivial solutions for iterations 1 and 2 where a solving Start state has a single bit flip that is adjacent to a set bit or is a set bit. Cases where there are more than 40 set bits in the final state may consume significant time for no solutions. \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function mstart = solveLife(mtest,numtosolve)\r\n  mstart=zeros(numtosolve,626)\r\nend","test_suite":"%%\r\n%'https://sites.google.com/site/razapor/matlab_cody/mtest.mat?attredirects=0\u0026d=1';\r\n%mtest format is [casenumer, iterations, start1:625,finish1:625] for 50K cases 0:49999\r\n%'https://sites.google.com/site/razapor/matlab_cody/mtrain.mat?attredirects=0\u0026d=1';\r\ntic\r\nfname='https://sites.google.com/site/razapor/matlab_cody/mtest.mat?attredirects=0\u0026d=1';\r\nurlwrite(fname,'mtest.mat') %1.22s\r\nload('mtest.mat'); %0.42s\r\ntoc\r\n\r\nnumtosolve=40;\r\nmstart = solveLife(mtest,numtosolve);\r\ntoc\r\nmstart=unique(mstart,'rows'); % remove exact duplicate solutions\r\n\r\n%Check for Trivial solutions; Life(mtest(case))==mtest(case)\r\nvalid=1;\r\nfor i=1:size(mstart,1)  % \r\n icase=mstart(i,1); %50000:99999\r\n iter=mtest(icase-49999,2); %Test cases start at 50000\r\n \r\n A=reshape(mtest(icase-49999,3:end),25,25);\r\n Abase=A;\r\n for j=1:iter\r\n  C=0;\r\n  for r=-1:1 % -1 Up   Using circshift to perform wrap convolution\r\n   Ar=circshift(A,r,1);\r\n   for c=-1:1 % -1 Left\r\n     Arc=circshift(Ar,c,2);\r\n     C=C+Arc;\r\n   end\r\n  end\r\n  A = C==3 | A\u0026C==4;\r\n end %j\r\n\r\n if isequal(Abase,A) % mtest [case, iter, data1:625]\r\n  valid=0; %Trivial solution entered\r\n  break;\r\n end\r\nend %main loop i\r\ntoc  % Trivial check timer\r\n\r\nLprocess=size(mstart,1)*valid;\r\nvalid=0; % Reset valid as counter for solutions\r\nfor i=1:Lprocess  % skip if any were trivial\r\n icase=mstart(i,1); %50000:99999\r\n iter=mtest(icase-49999,2); %Test cases start at 50000\r\n \r\n A=reshape(mstart(i,2:end),25,25);\r\n for j=1:iter\r\n  C=0;\r\n  for r=-1:1 % -1 Up   Using circshift to perform wrap convolution\r\n   Ar=circshift(A,r,1);\r\n   for c=-1:1 % -1 Left\r\n     Arc=circshift(Ar,c,2);\r\n     C=C+Arc;\r\n   end\r\n  end\r\n  A = C==3 | A\u0026C==4;\r\n end %j\r\n\r\n if ~isequal(A(:)',mtest(icase-49999,3:end)) % mtest [case, iter, data1:625]\r\n  valid=0; %Evolved does not match goal\r\n  break;\r\n else\r\n  valid=valid+1;\r\n end\r\nend %main loop i\r\ntoc\r\n\r\nassert(valid\u003e=40)\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":3097,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":2,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2020-10-06T18:14:45.000Z","updated_at":"2020-10-06T18:41:35.000Z","published_at":"2020-10-06T18:41:35.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:hyperlink w:docLocation=\\\"https://www.kaggle.com/c/conways-reverse-game-of-life-2020\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eKaggle's Conway's Reverse Game of Life 2020 \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003econtest inspires this Life challenge. The kaggle contest runs from Oct-01-2020 thru Nov-30-2020. References:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"http://mathworld.wolfram.com/GameofLife.html\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eGame of Life at Wolfram\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e.\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"http://en.wikipedia.org/wiki/Conway%27s_Game_of_Life\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eWiki Life\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e. The Kaggle event is 50K cases to solve for a state 1 to 5 iterations prior to a given state. Imperfect solutions are allowed but penalized. Input file to Kaggle is a csv so Matlab solutions can be posted at the Kaggle site for this event.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis Challenge is to Solve at least 40, excluding trivials, of the 50K puzzles per these revised Life Laws. Trivial solutions are where the Final state may match the Start State.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[1. Any live cell with fewer than two live neighbors dies, as if caused by under-population.\\n2. Any live cell with two or three live neighbors lives on to the next generation.\\n3. Any live cell with more than three live neighbors dies, as if by overcrowding.\\n4. Any dead cell with exactly three live neighbors becomes a live cell, as if by reproduction.\\n5. Edges wrap around. Eight Neighbors. (Change to normal planar life)]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eNote: The edges wrap so the matrix represents the surface of a sphere.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eInput:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e (mtest,numtosolve) the Finish state matrix of 50K rows of [casenumber, iterations, 625 values], number of case to solve (40)\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eOutput:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e (mstart) the Starting state matrix of at least 40 puzzles all with perfect zero error solutions, [casenumber, 625 values]\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eHint:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e There are 40 non-trivial solutions for iterations 1 and 2 where a solving Start state has a single bit flip that is adjacent to a set bit or is a set bit. Cases where there are more than 40 set bits in the final state may consume significant time for no solutions. \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":46618,"title":"Kaggle 2020 Drone Delivery Contest","description":null,"description_html":"\u003cdiv style = \"text-align: start; line-height: 20.4333px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 941.917px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 470.967px; transform-origin: 407px 470.967px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 84px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 42px; text-align: left; transform-origin: 384px 42px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 31.5167px 7.91667px; transform-origin: 31.5167px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThe 2020 \u003c/span\u003e\u003c/span\u003e\u003ca target='_blank' href = \"https://www.kaggle.com/c/hashcode-drone-delivery\"\u003e\u003cspan style=\"\"\u003e\u003cspan style=\"\"\u003eKaggle Drone\u003c/span\u003e\u003c/span\u003e\u003c/a\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 309.217px 7.91667px; transform-origin: 309.217px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e contest is an optimization task to maximize net customer satisfaction by using 30 drones across 10 warehouses to fulfill 1250 customer multi-item, 400 distinct items(products), orders. Satisfaction is (1-delivery_time/max_time)*100 and 0 if delivery not completed by max_time. The max time of 112993 is easily beaten with typical worse time of 40K. \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 331.8px 7.91667px; transform-origin: 331.8px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThis contest subset has disabled moving items from warehouse to warehouse thus wait times are not used.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 373.283px 7.91667px; transform-origin: 373.283px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThe maximum score is 125000. To succeed as a DroneManager requires a score of 110K, 5th at Kaggle contest 9/26/20.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 63px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 31.5px; text-align: left; transform-origin: 384px 31.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 19.4333px 7.91667px; transform-origin: 19.4333px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eInput:\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 1.95px 7.91667px; transform-origin: 1.95px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e [rows,cols,numdrones,maxturns,maxDronewt,numproducts,numOrders,delivery_xy_qty,delivery_list,distance_delivery\u0026amp;warehouse_to_delivery\u0026amp;warehouse, distance_warehouse_to_delivery,permutation_cell_array_for1to9]\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 25.2667px 7.91667px; transform-origin: 25.2667px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eOutput:\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 304.15px 7.91667px; transform-origin: 304.15px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e Commands matrix [number of commands,5]  The number of commands is likely to be 18K to 20K.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 380.167px 7.91667px; transform-origin: 380.167px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eLoading from a warehouse: [drone# 1 warehouse# item# quantity]. Drone1:30, Warehouse1:10, Item1:400. The 1 is LOAD.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 341.9px 7.91667px; transform-origin: 341.9px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eOnly one item type can be loaded on to drone at a time. Each Load/Deliver command consumes 1 unit of time.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 352.417px 7.91667px; transform-origin: 352.417px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eDelivery for an order:  [drone# 3 delivery# item# quantity]. Drone1:30, Delivery1:1250, Item1:400. The 3 is Deliver.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 286.283px 7.91667px; transform-origin: 286.283px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThe final delivery time for an order is the latest drone time inclusive of final delivery time unit.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 21px; text-align: left; transform-origin: 384px 21px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 117.867px 7.91667px; transform-origin: 117.867px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eAdditional approach comments are at \u003c/span\u003e\u003c/span\u003e\u003ca target='_blank' href = \"https://www.kaggle.com/c/hashcode-drone-delivery/discussion/186050\"\u003e\u003cspan style=\"\"\u003e\u003cspan style=\"\"\u003eKaggle Drone 111401\u003c/span\u003e\u003c/span\u003e\u003c/a\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 181.283px 7.91667px; transform-origin: 181.283px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e and in the template along with using a provided routine to create a Kaggle python submission file.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 84.5333px 7.91667px; transform-origin: 84.5333px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eDelivery/Warehouse Map.\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 275.333px 7.91667px; transform-origin: 275.333px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e Warehouses red*, Single item delivery redO, Two item delivery blackO, \u0026gt;2 items greenO\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 7.91667px; transform-origin: 0px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 425.917px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 212.967px; text-align: left; transform-origin: 384px 212.967px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cimg class=\"imageNode\" style=\"vertical-align: baseline;width: 560px;height: 420px\" 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\" data-image-state=\"image-loaded\" width=\"560\" height=\"420\"\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 7.91667px; transform-origin: 0px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function cmds=drone(nr,nc,ndr,nturns,max_wt,nprod,vpwt,nw,wxy,wprodq,norders,dxyq,dlist,dw2dw,w2d,pmapc)\r\n% Discussion of an approach can be read at \r\n%https://www.kaggle.com/c/hashcode-drone-delivery/discussion/186050\r\n%\r\n%Short approach description is: \r\n% 1) Create baskets for every order by unique warehouse and wt\r\n% 2)Fix warehouse usage for over-use of items\r\n% 3)Create matrix of baskets that will be reduced for each delivery, add an idx at far right and\r\n% also create a master reference copy for creation of cmds\r\n% 4) Select warehouse that is normalized closest to drone.  dist/f(number signle order baskets, tot baskets)\r\n% 5) Augment drone basket set by baskets along line segment. Function distP2S_tim provided, Point to Segment\r\n% 6) Optimize Loading/Delivery steps\r\n% 7) Optimal path of multi-baskets easily done by brute force as \u003c10 baskets in any drone flt,pmapc\r\n%\r\ncmds=zeros(20000,5); %early est number of commands, max=nd*nturns\r\ncptr=0; %cmd ptr\r\n% Initialize drones/delivery_timer\r\n%All drones start at first warehouse, drIdx(:)=1251\r\ndrIdx=ones(ndr,1)*(norders+1); % drone location index, quantized, range  [1:norders norders+wh]\r\ndrT=zeros(ndr,1); % Drone Time, includes loads and flight legs\r\ndt=zeros(norders,1); %delivery time of last item deposited\r\ndidb=zeros(norders,1); % Remaining baskets to complete a delivery id\r\n\r\n%[packc]=pack_init(nw,norders,nprod,dlist,dxyq,w2d,vpwt,wprodq,max_wt);\r\n% packc cell {wh,norders} vector of items from each wh for each order, \r\n%  baskets are item sequences wt sum to \u003c=200\r\n%  packc has single and multiple baskets\r\n\r\n% Create mb array \r\n%[mb,Rmb,didb]=create_baskets(nw,norders,packc,vpwt,max_wt,w2d,didb);\r\n%mb [whid,did,dist,totwt,itemlist,mbidx]\r\n%\r\n%Initial 4684 baskets\r\n\r\n%Start of Main Processing Loop Creating Packs from baskets\r\nzflt=0; % flt counting variable for debug\r\nwhile min(drT)\u003cnturns %112993   3357 cycles if no dist limit, 4684 baskets\r\n zflt=zflt+1;\r\n% if max(didb)==0\r\n%  break;\r\n% end % all package baskets delivered\r\n \r\n \r\n %drptr=find(drT==min(drT),1,'first');  %Next drone should be the one that reaches its preferred warehouse the soonest, not lowest time used\r\n \r\n %dr_wh=pick_wh(drIdx,drptr,norders,didb,mb,w2d,nw); \r\n %Critical is selecting warehouse for drone to reach based on single baskets remaining, qty baskets\r\n \r\nend % min(drT)  Drones alive to make orders\r\n\r\n\r\n% [drone_id,Action,WH/DE id,Item_id,Q]\r\n% Wait0 [drid 0 Nturns 0 0]\r\n% Load1 [drid 1 whid itid q]\r\n% UnLoad2 [drid 2 whid itid q]\r\n% Deliv3 [drid 3 Did itid q]\r\n \r\n %calc/print score\r\n %dt is tracked as max of drone delivery time\r\n %dt(???)=nturns; % Delivery not fulfilled set to nturns\r\n %scr= sum( ceil(100*(nturns-dt(:))/nturns) );\r\n %fprintf('scr: %i\\n',scr)\r\n \r\n %create python file to create submission.txt file from cmds array\r\n %writefile(cmds,cptr); %0.55s\r\nend % cmds=drone()\r\n\r\nfunction ans=distP2S_tim(x0,y0,x1,y1,x2,y2)\r\n% Distance from a Point to a segment\r\nz=complex(x0-x1,y0-y1);\r\ncomplex(x2-x1,y2-y1);\r\nabs(z-ans*min(1,max(0,real(z/ans))));\r\nend\r\n\r\nfunction writefile(cmds,cptr)\r\n% To create python.txt file for entry into a kaggle notebook\r\n%\r\n% [drone_id,Action,WH/DE id,Item_id,Q]\r\n% Wait0 [drid 0 Nturns 0 0]\r\n% Load1 [drid 1 whid itid q]\r\n% UnLoad2 [drid 2 whid itid q]\r\n% Deliv3 [drid 3 Did itid q]\r\n% sub = '8\\n'\r\n% sub+= '0 L 0 163 1\\n'\r\n% sub+= '0 D 1 163 1\\n'\r\n% \r\n%cmds [drone action wh/deliv Item q \r\n%cmds(cptr+1,:)=[drid 1 1 item 1];\r\n%cmds(cptr+2,:)=[drid 3 didx item 1];\r\n fname=['drone' datestr(now,'ddmmyyyy_hhMM') '.txt'];\r\n fid =fopen(fname,'w');\r\n \r\n %fprintf(fid,'sub = ''%i\\n''',cptr)\r\n fprintf(fid,'sub = ''%i\\\\n''\\n',cptr); % specials\r\n for i=1:cptr\r\n  if cmds(i,2)==0 % Wait\r\n   fprintf(fid,'sub+= ''%i W %i\\\\n''\\n',cmds(i,[1 3])-1); % specials\r\n  elseif cmds(i,2)==1 %Load\r\n   fprintf(fid,'sub+= ''%i L %i %i %i\\\\n''\\n',cmds(i,[1 3 4])-1,cmds(i,5)); % specials\r\n  elseif cmds(i,2)==2 %Unload\r\n   fprintf(fid,'sub+= ''%i U %i %i %i\\\\n''\\n',cmds(i,[1 3 4])-1,cmds(i,5)); % specials\r\n  elseif cmds(i,2)==3 %Delivery\r\n   fprintf(fid,'sub+= ''%i D %i %i %i\\\\n''\\n',cmds(i,[1 3 4])-1,cmds(i,5)); % specials\r\n  else % error in cmds action value\r\n   fprintf('Error Occurred: Invalid command: Line %i\\n',i);\r\n  end\r\n end\r\n \r\n %final section of code to write the python file that writes submission.csv\r\n fprintf(fid,'text_file = open(\"submission.csv\", \"w\")\\n');\r\n fprintf(fid,'text_file.write(sub)\\n');\r\n fprintf(fid,'text_file.close()\\n');\r\n \r\n fclose(fid);\r\n %https://www.mathworks.com/help/matlab/matlab_prog/formatting-strings.html\r\n % ' use ''\r\n % \\ use \\\\\r\nend\r\n","test_suite":"%%\r\ntic\r\nfname='https://sites.google.com/site/razapor/matlab_cody/busy_day.in?attredirects=0\u0026d=1';\r\nout_fn='busy_day_cody.in';\r\nurlwrite(fname,out_fn); %Load url file to local space 0.74s\r\nm=dlmread(out_fn); % 3775, 400  1.1s  Read in complete Kaggle Drone Test file\r\nnr=m(1,1);nc=m(1,2);ndr=m(1,3);nturns=m(1,4);max_wt=m(1,5);\r\n%nr400, nc600, ndr30 drones, nturns112993, max_wt200\r\n%All drones start at first warehouse  drones(1:30), warehouses(1:10)\r\nnprod=m(2,1); %400\r\nvpwt=m(3,1:nprod); %\r\nnw=m(4,1); %10 warehouses\r\nwxy=zeros(nw,2); % warehouses x,y\r\nwprodq=zeros(nw,nprod); % Quantity of each product in each warehouse\r\nLptr=5;\r\nfor i=1:nw\r\n wxy(i,:)=m(Lptr,1:2)+1; %locations moved off (0,0) to (1,1)\r\n wprodq(i,1:nprod)=m(Lptr+1,1:nprod); %qty of items(1:400) at each warehouse\r\n Lptr=Lptr+2;\r\nend\r\nnorders=m(Lptr,1); %1250 orders [1:1250]\r\n% Delivery dxyq locx,locy,qty_items\r\n% Delivery_list dlisth (repeat items possible)[dataset starts at 0, add 1) hist\r\ndxyq=zeros(norders,3);\r\ndlist=zeros(norders,nprod); % do not know current max of items in an order\r\n\r\nLptr=Lptr+1;\r\nfor i=1:norders %deliveries(1:1250)\r\n dxyq(i,1:2)=m(Lptr,1:2)+1; %locations moved off (0,0) to (1,1)\r\n dxyq(i,3)=m(Lptr+1,1); %qty of items for a delivery\r\n dlist(i,1:dxyq(i,3))=sort(m(Lptr+2,1:dxyq(i,3))+1); % items 0:399 become 1:400\r\n Lptr=Lptr+3;\r\nend\r\ndlist=dlist(:,1:max(dxyq(:,3))); %dlist width reduces from 400 to 19\r\n%read complete\r\n%Create three useful arrays required for scoring\r\n% delivery to delivery location and warehouse to delivery location\r\n dw2dw=zeros(norders+nw);\r\n vx=[dxyq(:,1);wxy(:,1)];\r\n vy=[dxyq(:,2);wxy(:,2)];\r\n for j=1:norders+nw\r\n  dw2dw(:,j)=ceil(((vx-vx(j)).^2+(vy-vy(j)).^2).^.5);\r\n end\r\n %warehouse to delivery distance [nw,norders]\r\n w2d=dw2dw(norders+1:end,1:norders);\r\n \r\n %Initialize permutation maps for Brute Force path calculation\r\n for i=9:-1:1\r\n  pmapc{i}=perms(1:i);\r\n end\r\n %1.3s Cody setup\r\n\r\ntoc\r\nfprintf('%i ',nr,nc,ndr,nturns,max_wt,nprod);fprintf('\\n')\r\n\r\ncmds=drone(nr,nc,ndr,nturns,max_wt,nprod,vpwt,nw,wxy,wprodq,norders,dxyq,dlist,dw2dw,w2d,pmapc);\r\ntoc\r\n\r\n%Evaluate cmds provided for accuracy and drone time to deliver packages\r\n drIdx=ones(ndr,1)*(norders+1); % drone location index, quantized, range  [1:norders norders+wh]\r\n drT=zeros(ndr,1); % Drone Time, includes loads and flight legs\r\n drW=zeros(ndr,1); % Drone Weight\r\n drL=zeros(ndr,nprod); %Histogram of drone loads\r\n dt=zeros(norders,1); %delivery time of last item deposited\r\n \r\n %Reduce cmds for illegal content and give warning \r\n csize=size(cmds,1);\r\n cmds=abs(cmds); %remove any negatives\r\n cmds(prod(cmds,2)==0,:)=[]; % No zeros allowed\r\n cmds(cmds(:,2)==1 \u0026 cmds(:,3)\u003enw,:)=[]; %For Load cmds(3)\u003c=1nw\r\n cmds(cmds(:,3)\u003enorders,:)=[];\r\n cmds(cmds(:,4)\u003enprod,:)=[];\r\n cmds(cmds(:,1)\u003c1,:)=[];\r\n cmds(cmds(:,1)\u003endr,:)=[];\r\n cmds(cmds(:,2)\u003c1,:)=[]; % invalid cmd type only 1/3 allowed\r\n cmds(cmds(:,2)==2,:)=[]; % invalid cmd type only 1/3 allowed\r\n cmds(cmds(:,2)\u003e3,:)=[]; % invalid cmd type only 1/3 allowed\r\n if size(cmds,1)\u003ccsize\r\n  fprintf('Warning: Invalid cmds purged\\n')\r\n end\r\n \r\n flag=0; % No issues 0\r\n for i=1:size(cmds,1)\r\n  vcmd=cmds(i,:); %[drone 1/3 warehouse/delivery item qty]\r\n  if vcmd(2)==1 %Load  vcmd(3) warehouse  (allow warehouse to warehouse,deliv to wh)\r\n   wptr=vcmd(3);\r\n   drT(vcmd(1))=drT(vcmd(1))+dw2dw(drIdx(vcmd(1)),norders+wptr)+1; %dist+load\r\n   drIdx(vcmd(1))=norders+wptr;\r\n   wprodq(wptr,vcmd(4))=wprodq(wptr,vcmd(4))-vcmd(5);\r\n   drL(vcmd(1),vcmd(4))=drL(vcmd(1),vcmd(4))+vcmd(5);\r\n   drW(vcmd(1))=drW(vcmd(1))+vcmd(5)*vpwt(vcmd(4)); %Add item(s) wt\r\n   if wprodq(wptr,vcmd(4))\u003c0 % Check for excess usage at warehouse\r\n    flag=1;\r\n    fprintf('Not enough of item %i at warehouse %i at cmds %i\\n',vcmd([4 3]),i);\r\n    break;\r\n   end\r\n   if drW(vcmd(1))\u003emax_wt % check for excess wt loaded\r\n    flag=1;\r\n    fprintf('Max wt exceeded: %i  drone %i at cmds %i\\n',drW(vcmd(1)),vcmd(1),i);\r\n    break;\r\n   end\r\n  else %Deliver:  vcmd(3) delivery location (wh2deliv, deliv2deliv)\r\n   % [drone 3 did item q]\r\n   dptr=vcmd(3);\r\n   drT(vcmd(1))=drT(vcmd(1))+dw2dw(drIdx(vcmd(1)),dptr)+1; % dist+drop\r\n   drIdx(vcmd(1))=dptr;\r\n   for j=1:vcmd(5)\r\n    iptr=find(dlist(dptr,:)==vcmd(4),1,'first');\r\n    if ~isempty(iptr)\r\n     dlist(dptr,iptr)=0;\r\n    else %Excess item being delivered\r\n     flag=1;\r\n     fprintf('Excess delivery of item %i at cmds %i\\n',vcmd(4),i)\r\n     break\r\n    end\r\n   end\r\n   if flag==1,break;end %Excess delivery break\r\n   drL(vcmd(1),vcmd(4))=drL(vcmd(1),vcmd(4))-vcmd(5);\r\n   drW(vcmd(1))=drW(vcmd(1))-vcmd(5)*vpwt(vcmd(4)); % Unload item(s) wt delivered\r\n   if drL(vcmd(1),vcmd(4))\u003c0\r\n    flag=1;\r\n    fprintf('Non-existent itme delivery attempt. Item %i cmds %i\\n',vcmd(4),i)\r\n    break;\r\n   end\r\n   dt(dptr)=max(dt(dptr),drT(vcmd(1)));\r\n  end % Load/Delivery \r\n end % cmds\r\n \r\n if flag\r\n  scr=0;\r\n else\r\n  dt(sum(dlist,2)\u003e0)=nturns; %Non-completed delivery scores Zero\r\n  dt(dt\u003enturns)=nturns; %Completed beyond time limit scores 0\r\n  scr= sum( ceil(100*(nturns-dt(:))/nturns) ); \r\n end\r\n fprintf('scr: %i\\n',scr)\r\n \r\n\r\nassert(scr\u003e110000)\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":1,"created_by":3097,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":1,"test_suite_updated_at":"2020-09-27T22:00:47.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2020-09-26T18:26:41.000Z","updated_at":"2025-12-08T15:43:28.000Z","published_at":"2020-09-27T00:08:03.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe 2020 \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"https://www.kaggle.com/c/hashcode-drone-delivery\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eKaggle Drone\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e contest is an optimization task to maximize net customer satisfaction by using 30 drones across 10 warehouses to fulfill 1250 customer multi-item, 400 distinct items(products), orders. Satisfaction is (1-delivery_time/max_time)*100 and 0 if delivery not completed by max_time. The max time of 112993 is easily beaten with typical worse time of 40K. \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis contest subset has disabled moving items from warehouse to warehouse thus wait times are not used.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe maximum score is 125000. To succeed as a DroneManager requires a score of 110K, 5th at Kaggle contest 9/26/20.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eInput:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e [rows,cols,numdrones,maxturns,maxDronewt,numproducts,numOrders,delivery_xy_qty,delivery_list,distance_delivery\u0026amp;warehouse_to_delivery\u0026amp;warehouse, distance_warehouse_to_delivery,permutation_cell_array_for1to9]\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eOutput:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e Commands matrix [number of commands,5]  The number of commands is likely to be 18K to 20K.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eLoading from a warehouse: [drone# 1 warehouse# item# quantity]. Drone1:30, Warehouse1:10, Item1:400. The 1 is LOAD.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eOnly one item type can be loaded on to drone at a time. Each Load/Deliver command consumes 1 unit of time.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eDelivery for an order:  [drone# 3 delivery# item# quantity]. Drone1:30, Delivery1:1250, Item1:400. The 3 is Deliver.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe final delivery time for an order is the latest drone time inclusive of final delivery time unit.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eAdditional approach comments are at \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"https://www.kaggle.com/c/hashcode-drone-delivery/discussion/186050\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eKaggle Drone 111401\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e and in the template along with using a provided routine to create a Kaggle python submission 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Planetoid Game of Life - Total Score 0.10","description":null,"description_html":"\u003cdiv style = \"text-align: start; line-height: 20.4333px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 482.167px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 241.083px; transform-origin: 407px 241.083px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 84px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 42px; text-align: left; transform-origin: 384px 42px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003ca target='_blank' href = \"https://www.kaggle.com/c/conways-reverse-game-of-life-2020\"\u003e\u003cspan style=\"\"\u003e\u003cspan style=\"\"\u003eKaggle's Conway's Reverse Game of Life 2020 \u003c/span\u003e\u003c/span\u003e\u003c/a\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 203.05px 7.91667px; transform-origin: 203.05px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003econtest inspires this Life challenge. The kaggle contest runs from Oct-01-2020 thru Nov-30-2020. References:\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 1.95px 7.91667px; transform-origin: 1.95px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e \u003c/span\u003e\u003c/span\u003e\u003ca target='_blank' href = \"http://mathworld.wolfram.com/GameofLife.html\"\u003e\u003cspan style=\"\"\u003e\u003cspan style=\"\"\u003eGame of Life at Wolfram\u003c/span\u003e\u003c/span\u003e\u003c/a\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 1.95px 7.91667px; transform-origin: 1.95px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e.\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 1.95px 7.91667px; transform-origin: 1.95px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e \u003c/span\u003e\u003c/span\u003e\u003ca target='_blank' href = \"http://en.wikipedia.org/wiki/Conway%27s_Game_of_Life\"\u003e\u003cspan style=\"\"\u003e\u003cspan style=\"\"\u003eWiki Life\u003c/span\u003e\u003c/span\u003e\u003c/a\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 138.467px 7.91667px; transform-origin: 138.467px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e. The Kaggle event is 50K cases to solve for a state 1 to 5 iterations prior to a given state. Imperfect solutions are allowed but penalized. Input file to Kaggle is a csv so Matlab solutions can be posted at the Kaggle site for this event.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 21px; text-align: left; transform-origin: 384px 21px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 379.783px 7.91667px; transform-origin: 379.783px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThis Challenge is to Solve the 50K puzzles with a Score \u0026lt;= 0.10, Kaggle Top 25 result, per these revised Life Laws. Trivial solutions are where the Final state may match the Start State.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgb(247, 247, 247); block-size: 102.167px; border-bottom-left-radius: 4px; border-bottom-right-radius: 4px; border-end-end-radius: 4px; border-end-start-radius: 4px; border-start-end-radius: 4px; border-start-start-radius: 4px; border-top-left-radius: 4px; border-top-right-radius: 4px; margin-block-end: 10px; margin-block-start: 10px; margin-bottom: 10px; margin-inline-end: 3px; margin-inline-start: 3px; margin-left: 3px; margin-right: 3px; margin-top: 10px; perspective-origin: 404px 51.0833px; transform-origin: 404px 51.0833px; margin-left: 3px; margin-top: 10px; margin-bottom: 10px; margin-right: 3px; \"\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 0.833333px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.833333px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.833333px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.833333px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 350.35px 7.91667px; transform-origin: 350.35px 7.91667px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 26.95px 7.91667px; transform-origin: 26.95px 7.91667px; \"\u003e1. Any \u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(170, 4, 249); border-block-start-color: rgb(170, 4, 249); border-bottom-color: rgb(170, 4, 249); border-inline-end-color: rgb(170, 4, 249); border-inline-start-color: rgb(170, 4, 249); border-left-color: rgb(170, 4, 249); border-right-color: rgb(170, 4, 249); border-top-color: rgb(170, 4, 249); caret-color: rgb(170, 4, 249); color: rgb(170, 4, 249); column-rule-color: rgb(170, 4, 249); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(170, 4, 249); perspective-origin: 188.65px 7.91667px; text-decoration: none; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); transform-origin: 188.65px 7.91667px; \"\u003elive cell with fewer than two live neighbors dies\u003c/span\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 19.25px 7.91667px; transform-origin: 19.25px 7.91667px; \"\u003e, as \u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(170, 4, 249); border-block-start-color: rgb(170, 4, 249); border-bottom-color: rgb(170, 4, 249); border-inline-end-color: rgb(170, 4, 249); border-inline-start-color: rgb(170, 4, 249); border-left-color: rgb(170, 4, 249); border-right-color: rgb(170, 4, 249); border-top-color: rgb(170, 4, 249); caret-color: rgb(170, 4, 249); color: rgb(170, 4, 249); column-rule-color: rgb(170, 4, 249); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(170, 4, 249); perspective-origin: 115.5px 7.91667px; text-decoration: none; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); transform-origin: 115.5px 7.91667px; \"\u003eif caused by under-population.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 0.833333px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.833333px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.833333px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.833333px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 315.7px 7.91667px; transform-origin: 315.7px 7.91667px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 26.95px 7.91667px; transform-origin: 26.95px 7.91667px; \"\u003e2. Any \u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(170, 4, 249); border-block-start-color: rgb(170, 4, 249); border-bottom-color: rgb(170, 4, 249); border-inline-end-color: rgb(170, 4, 249); border-inline-start-color: rgb(170, 4, 249); border-left-color: rgb(170, 4, 249); border-right-color: rgb(170, 4, 249); border-top-color: rgb(170, 4, 249); caret-color: rgb(170, 4, 249); color: rgb(170, 4, 249); column-rule-color: rgb(170, 4, 249); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(170, 4, 249); perspective-origin: 288.75px 7.91667px; text-decoration: none; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); transform-origin: 288.75px 7.91667px; \"\u003elive cell with two or three live neighbors lives on to the next generation.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 0.833333px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.833333px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.833333px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.833333px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 311.85px 7.91667px; transform-origin: 311.85px 7.91667px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 26.95px 7.91667px; transform-origin: 26.95px 7.91667px; \"\u003e3. Any \u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(170, 4, 249); border-block-start-color: rgb(170, 4, 249); border-bottom-color: rgb(170, 4, 249); border-inline-end-color: rgb(170, 4, 249); border-inline-start-color: rgb(170, 4, 249); border-left-color: rgb(170, 4, 249); border-right-color: rgb(170, 4, 249); border-top-color: rgb(170, 4, 249); caret-color: rgb(170, 4, 249); color: rgb(170, 4, 249); column-rule-color: rgb(170, 4, 249); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(170, 4, 249); perspective-origin: 192.5px 7.91667px; text-decoration: none; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); transform-origin: 192.5px 7.91667px; \"\u003elive cell with more than three live neighbors dies\u003c/span\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 19.25px 7.91667px; transform-origin: 19.25px 7.91667px; \"\u003e, as \u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(170, 4, 249); border-block-start-color: rgb(170, 4, 249); border-bottom-color: rgb(170, 4, 249); border-inline-end-color: rgb(170, 4, 249); border-inline-start-color: rgb(170, 4, 249); border-left-color: rgb(170, 4, 249); border-right-color: rgb(170, 4, 249); border-top-color: rgb(170, 4, 249); caret-color: rgb(170, 4, 249); color: rgb(170, 4, 249); column-rule-color: rgb(170, 4, 249); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(170, 4, 249); perspective-origin: 73.15px 7.91667px; text-decoration: none; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); transform-origin: 73.15px 7.91667px; \"\u003eif by overcrowding.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 0.833333px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.833333px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.833333px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.833333px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 361.9px 7.91667px; transform-origin: 361.9px 7.91667px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 26.95px 7.91667px; transform-origin: 26.95px 7.91667px; \"\u003e4. Any \u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(170, 4, 249); border-block-start-color: rgb(170, 4, 249); border-bottom-color: rgb(170, 4, 249); border-inline-end-color: rgb(170, 4, 249); border-inline-start-color: rgb(170, 4, 249); border-left-color: rgb(170, 4, 249); border-right-color: rgb(170, 4, 249); border-top-color: rgb(170, 4, 249); caret-color: rgb(170, 4, 249); color: rgb(170, 4, 249); column-rule-color: rgb(170, 4, 249); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(170, 4, 249); perspective-origin: 242.55px 7.91667px; text-decoration: none; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); transform-origin: 242.55px 7.91667px; \"\u003edead cell with exactly three live neighbors becomes a live cell\u003c/span\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 19.25px 7.91667px; transform-origin: 19.25px 7.91667px; \"\u003e, as \u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(170, 4, 249); border-block-start-color: rgb(170, 4, 249); border-bottom-color: rgb(170, 4, 249); border-inline-end-color: rgb(170, 4, 249); border-inline-start-color: rgb(170, 4, 249); border-left-color: rgb(170, 4, 249); border-right-color: rgb(170, 4, 249); border-top-color: rgb(170, 4, 249); caret-color: rgb(170, 4, 249); color: rgb(170, 4, 249); column-rule-color: rgb(170, 4, 249); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(170, 4, 249); perspective-origin: 73.15px 7.91667px; text-decoration: none; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); transform-origin: 73.15px 7.91667px; \"\u003eif by reproduction.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 0.833333px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.833333px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.833333px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.833333px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 265.65px 7.91667px; transform-origin: 265.65px 7.91667px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 34.65px 7.91667px; transform-origin: 34.65px 7.91667px; \"\u003e5. Edges \u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(170, 4, 249); border-block-start-color: rgb(170, 4, 249); border-bottom-color: rgb(170, 4, 249); border-inline-end-color: rgb(170, 4, 249); border-inline-start-color: rgb(170, 4, 249); border-left-color: rgb(170, 4, 249); border-right-color: rgb(170, 4, 249); border-top-color: rgb(170, 4, 249); caret-color: rgb(170, 4, 249); color: rgb(170, 4, 249); column-rule-color: rgb(170, 4, 249); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(170, 4, 249); perspective-origin: 231px 7.91667px; text-decoration: none; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); transform-origin: 231px 7.91667px; \"\u003ewrap around. Eight Neighbors. (Change to normal planar life)\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 10px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 10px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 10px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 221.317px 7.91667px; transform-origin: 221.317px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eNote: The edges wrap so the matrix represents the surface of a sphere.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 19.4333px 7.91667px; transform-origin: 19.4333px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eInput:\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 254.75px 7.91667px; transform-origin: 254.75px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e (mtest) the Finish state matrix of 50K rows of [casenumber, iterations, 625 values]\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 25.2667px 7.91667px; transform-origin: 25.2667px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eOutput:\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 233.35px 7.91667px; transform-origin: 233.35px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e (mstart) the Starting state matrix of 50K puzzles, [casenumber, 625 values]\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 39.9333px 7.91667px; transform-origin: 39.9333px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eTop Scores:\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 96.8667px 7.91667px; transform-origin: 96.8667px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e Zapor: 0.0818, 2556293 errors\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 105px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 52.5px; text-align: left; transform-origin: 384px 52.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 15.95px 7.91667px; transform-origin: 15.95px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eHint:\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 356.9px 7.91667px; transform-origin: 356.9px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e A Greedy Complete Single Adjacent bit flip can score \u0026lt;.0.09. Non-optimized processing time for Greedy Complete was 25Ksec. Candidate bits to flip are all wrap-convolve of Goal matrix with kernel ones(3). First test for trivial solution. Process all  bit flips on current optimal solution starting with Goal matrix. Make first best scoring solution the new optimal solution. Iterate on optimal solutions until no improvement on any single candidate bit flip. Greedy Complete for iterations=1 creates 176 solves not counting the 532 Trivial iteration 1 cases.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function mstart = solveLife(mtest)\r\n  %mstart=zeros(50000,626);  column 1 values should range from 50000:99999, other columns 0/1\r\n  urlname='';\r\n  urlwrite(urlname,'mstart.mat')\r\n  load('mstart.mat'); \r\n  \r\n  %Processing to \u003c0.10 Score is unlikely in Cody's 60 seconds\r\n  %Process offline mtest.mat file below.\r\n  %Create an mstart.mat file   using save('mstart.mat','mstart')  about 5.6MB\r\n  %Post the mstart.mat file in the cloud to download\r\n  %Copy the link location into urlname=''; above\r\n  \r\n  %Source data arrray to process mtest\r\n  %fname='https://sites.google.com/site/razapor/matlab_cody/mtest.mat?attredirects=0\u0026d=1';\r\n  %urlwrite(fname,'mtest.mat') %1.22s\r\n  %load('mtest.mat'); %0.42s\r\nend","test_suite":"%%\r\n%'https://sites.google.com/site/razapor/matlab_cody/mtest.mat?attredirects=0\u0026d=1';\r\n%mtest format is [casenumer, iterations, start1:625,finish1:625] for 50K cases 0:49999\r\n%'https://sites.google.com/site/razapor/matlab_cody/mtrain.mat?attredirects=0\u0026d=1';\r\nfname='https://sites.google.com/site/razapor/matlab_cody/mtest.mat?attredirects=0\u0026d=1';\r\nurlwrite(fname,'mtest.mat') %1.22s\r\nload('mtest.mat'); %0.42s\r\n\r\ncerr=zeros(50000,1);\r\nfor i=1:50000\r\n cerr(i)=nnz(mtest(i,3:end));\r\nend\r\n\r\ntic\r\nmstart = solveLife(mtest);\r\ntoc\r\nmstart=unique(mstart,'rows'); % remove exact duplicate solutions\r\n\r\n%Calc errors for each case submitted, otherwise use 0 input errors\r\ntic\r\nfor i=1:size(mstart,1)  % \r\n icase=mstart(i,1); %50000:99999\r\n Abase=reshape(mtest(icase-49999,3:end),25,25);;\r\n iter=mtest(icase-49999,2); %Test cases start at 50000\r\n \r\n A=reshape(mstart(i,2:end),25,25);\r\n \r\n for j=1:iter\r\n  C=0;\r\n  for r=-1:1 % -1 Up   Using circshift to perform wrap convolution\r\n   Ar=circshift(A,r,1);\r\n   for c=-1:1 % -1 Left\r\n     Arc=circshift(Ar,c,2);\r\n     C=C+Arc;\r\n   end\r\n  end\r\n  A = C==3 | A\u0026C==4;\r\n end %j\r\n cerr(icase-49999)=nnz(Abase-A);\r\n \r\nend %main loop i\r\ntoc  % 4.5s\r\n\r\nScore=sum(cerr)/50000/625;\r\nfprintf('Score %.4f  Total Errors: %i\\n',Score,sum(cerr));\r\n\r\nassert(Score\u003c=0.10)\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":3097,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":1,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2020-10-07T15:47:15.000Z","updated_at":"2020-10-07T16:39:36.000Z","published_at":"2020-10-07T16:39:36.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:hyperlink w:docLocation=\\\"https://www.kaggle.com/c/conways-reverse-game-of-life-2020\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eKaggle's Conway's Reverse Game of Life 2020 \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003econtest inspires this Life challenge. The kaggle contest runs from Oct-01-2020 thru Nov-30-2020. References:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"http://mathworld.wolfram.com/GameofLife.html\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eGame of Life at Wolfram\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e.\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"http://en.wikipedia.org/wiki/Conway%27s_Game_of_Life\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eWiki Life\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e. The Kaggle event is 50K cases to solve for a state 1 to 5 iterations prior to a given state. Imperfect solutions are allowed but penalized. Input file to Kaggle is a csv so Matlab solutions can be posted at the Kaggle site for this event.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis Challenge is to Solve the 50K puzzles with a Score \u0026lt;= 0.10, Kaggle Top 25 result, per these revised Life Laws. Trivial solutions are where the Final state may match the Start State.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[1. Any live cell with fewer than two live neighbors dies, as if caused by under-population.\\n2. Any live cell with two or three live neighbors lives on to the next generation.\\n3. Any live cell with more than three live neighbors dies, as if by overcrowding.\\n4. Any dead cell with exactly three live neighbors becomes a live cell, as if by reproduction.\\n5. Edges wrap around. Eight Neighbors. (Change to normal planar life)]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eNote: The edges wrap so the matrix represents the surface of a sphere.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eInput:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e (mtest) the Finish state matrix of 50K rows of [casenumber, iterations, 625 values]\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eOutput:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e (mstart) the Starting state matrix of 50K puzzles, [casenumber, 625 values]\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eTop Scores:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e Zapor: 0.0818, 2556293 errors\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eHint:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e A Greedy Complete Single Adjacent bit flip can score \u0026lt;.0.09. Non-optimized processing time for Greedy Complete was 25Ksec. Candidate bits to flip are all wrap-convolve of Goal matrix with kernel ones(3). First test for trivial solution. Process all  bit flips on current optimal solution starting with Goal matrix. Make first best scoring solution the new optimal solution. Iterate on optimal solutions until no improvement on any single candidate bit flip. Greedy Complete for iterations=1 creates 176 solves not counting the 532 Trivial iteration 1 cases.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":788,"title":"Tiles Contest: Perfect Solutions for Large Unique Tile  Boards","description":"*Tiles Contest:* The Large Unique Boards/Tiles that perfectly solve (50x50)\r\n\r\nReturn Perfect solutions for both boards. Scoring will be based upon size and time.\r\n\r\nSample \"Board 59\" and Actual(Contest) \"Board 6\" have perfect solutions with unique tiles. The tiles are unique with any number,except zero, occurring exactly twice.\r\n\r\nThe complete description of \u003chttp://www.mathworks.com/matlabcentral/contest/contests/36/rules Tiles\u003e explains what is a tile, orientation, and board output.\r\n\r\n*Input:* (boardsize, tiles)\r\n\r\n*Output:* (board, orientation)\r\n\r\n*Passing:* Two Perfect Boards.\r\n\r\n*Scoring:* Based upon Size/10 and Average Time(msec) of solutions.\r\n\r\n\r\nThe Test Suite demonstrates urlwrite usage with a customized tinyurl from an http site for acessing web mat files.\r\n\r\n\r\n\r\nThis is the first in a series of Tiles Contest challenges where the boards have interesting characteristics.  There are multiple perfect solution boards which were not solved during the contest.\r\n","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.4333px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 333px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 166.5px; transform-origin: 407px 166.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 46.15px 7.91667px; transform-origin: 46.15px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eTiles Contest:\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 184.517px 7.91667px; transform-origin: 184.517px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e The Large Unique Boards/Tiles that perfectly solve (50x50)\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 256.35px 7.91667px; transform-origin: 256.35px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eReturn Perfect solutions for both boards. Scoring will be based upon size and time.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 21px; text-align: left; transform-origin: 384px 21px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 370.917px 7.91667px; transform-origin: 370.917px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eSample \"Board 59\" and Actual(Contest) \"Board 6\" have perfect solutions with unique tiles. The tiles are unique with any number,except zero, occurring exactly twice.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 87.9167px 7.91667px; transform-origin: 87.9167px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThe complete description of \u003c/span\u003e\u003c/span\u003e\u003ca target='_blank' href = \"https://web.archive.org/web/20150224170744/http://www.mathworks.com/matlabcentral/contest/contests/36/rules\"\u003e\u003cspan style=\"\"\u003e\u003cspan style=\"\"\u003eTiles_wayback\u003c/span\u003e\u003c/span\u003e\u003c/a\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 1.95px 7.91667px; transform-origin: 1.95px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e \u003c/span\u003e\u003c/span\u003e\u003ca target='_blank' href = \"http://www.mathworks.com/matlabcentral/contest/contests/36/rules\"\u003e\u003cspan style=\"\"\u003e\u003cspan style=\"\"\u003eTiles\u003c/span\u003e\u003c/span\u003e\u003c/a\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 163.383px 7.91667px; transform-origin: 163.383px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e explains what is a tile, orientation, and board output.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 19.4333px 7.91667px; transform-origin: 19.4333px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eInput:\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 53.3px 7.91667px; transform-origin: 53.3px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e (boardsize, tiles)\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 25.2667px 7.91667px; transform-origin: 25.2667px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eOutput:\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 61.0833px 7.91667px; transform-origin: 61.0833px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e (board, orientation)\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 29.1667px 7.91667px; transform-origin: 29.1667px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003ePassing:\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 64.95px 7.91667px; transform-origin: 64.95px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e Two Perfect Boards.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 28.3833px 7.91667px; transform-origin: 28.3833px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eScoring:\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 184px 7.91667px; transform-origin: 184px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e Based upon Size/10 and Average Time(msec) of solutions.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 349.283px 7.91667px; transform-origin: 349.283px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThe Test Suite demonstrates urlwrite usage with a customized tinyurl from an http site for acessing web mat files.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 21px; text-align: left; transform-origin: 384px 21px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 380.933px 7.91667px; transform-origin: 380.933px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThis is the first in a series of Tiles Contest challenges where the boards have interesting characteristics. There are multiple perfect solution boards which were not solved during the contest.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function [board,orientation]=board_perfect(boardSize,tiles);\r\n  board=zeros(boardSize);\r\n  numtiles=size(tiles,1);\r\n  orientation=ones(numtiles,1);\r\n\r\n%Hint to help solve the board - This was a major contest innovation\r\n % te  Tiles expanded format 4*tiles, 4\r\n te = [t; t(:,[2:4,1]); t(:,[3:4,1:2]); t(:,[4,1:3])]; % 4*numtiles x 4\r\n \r\nend","test_suite":"%%\r\nfeval(@assignin,'caller','score',2000);\r\n%%\r\nformat short\r\nformat compact\r\n\r\nglobal net_time\r\n\r\n%fn='http://tinyurl.com/zapor-Tiles-sample-mat'; \r\n%fn='http://tinyurl.com/matlab-tiles-mat';\r\n%testsuite_sample.mat\r\nfn='https://sites.google.com/site/razapor/matlab_cody/testsuite_Tiles_sample.mat?attredirects=0\u0026d=1';\r\n\r\n\r\ntestSuiteFile = 'raz_tiles.mat';\r\nurlwrite(fn,testSuiteFile);\r\n\r\nbrd=59;\r\ntests = load(testSuiteFile,'testsuite');\r\ntiles = tests.testsuite(brd).tiles;\r\nrows = tests.testsuite(brd).r;\r\ncols = tests.testsuite(brd).c;\r\nboardSize = [rows, cols];\r\n\r\n[board,orientation]=board_perfect(boardSize,tiles); % run twice for timing\r\nt0=clock;\r\n[board,orientation]=board_perfect(boardSize,tiles);\r\ndt=etime(clock,t0)*1e3;\r\n\r\n% verify score\r\n t=tiles;\r\n ntiles=size(tiles,1);\r\n te = [t; t(:,[2:4,1]); t(:,[3:4,1:2]); t(:,[4,1:3])];\r\n \r\n % build check arrays UD, LR\r\n LR=zeros(rows,2*cols);\r\n UD=zeros(2*rows,cols);\r\n for r=1:rows\r\n  for c=1:cols\r\n   tptr=board(r,c);\r\n   tor=orientation(tptr);\r\n   UD(2*r-1,c)=te(tptr+ntiles*(tor-1),1);\r\n   UD(2*r,c)=te(tptr+ntiles*(tor-1),3);\r\n   LR(r,2*c-1)=te(tptr+ntiles*(tor-1),4);\r\n   LR(r,2*c)=te(tptr+ntiles*(tor-1),2);\r\n  end\r\n end\r\n checksum=sum([LR(:,1)' LR(:,end)' UD(1,:) UD(end,:)]);\r\n for idx=2:2:2*rows-2 % LR Square array assumed here\r\n  checksum=checksum+sum(LR(:,idx)-LR(:,idx+1))+sum(UD(idx,:)-UD(idx+1,:));\r\n end\r\n\r\n\r\nassert(checksum==0,sprintf('Checksum = %s\\n',num2str(checksum)));\r\nnet_time=dt\r\n%%\r\nglobal net_time\r\ntemp=net_time; % anti-cheat\r\n\r\n%fn='http://tinyurl.com/zapor-Tiles-contest-mat';\r\n%fn='http://tinyurl.com/matlab-tilesC-mat';\r\n%testsuite_actual.mat\r\nfn='https://sites.google.com/site/razapor/matlab_cody/testsuite_Tiles_contest.mat?attredirects=0\u0026d=1';\r\n\r\n\r\ntestSuiteFile = 'raz_tiles.mat';\r\nurlwrite(fn,testSuiteFile);\r\n\r\nbrd=6;\r\ntests = load(testSuiteFile,'testsuite');\r\ntiles = tests.testsuite(brd).tiles;\r\nrows = tests.testsuite(brd).r;\r\ncols = tests.testsuite(brd).c;\r\nboardSize = [rows, cols];\r\n\r\n[board,orientation]=board_perfect(boardSize,tiles); % run twice for timing\r\nt0=clock;\r\n[board,orientation]=board_perfect(boardSize,tiles);\r\ndt=etime(clock,t0)*1e3\r\n\r\n% verify score\r\n t=tiles;\r\n ntiles=size(tiles,1);\r\n te = [t; t(:,[2:4,1]); t(:,[3:4,1:2]); t(:,[4,1:3])];\r\n \r\n % build check arrays UD, LR\r\n LR=zeros(rows,2*cols);\r\n UD=zeros(2*rows,cols);\r\n for r=1:rows\r\n  for c=1:cols\r\n   tptr=board(r,c);\r\n   tor=orientation(tptr);\r\n   UD(2*r-1,c)=te(tptr+ntiles*(tor-1),1);\r\n   UD(2*r,c)=te(tptr+ntiles*(tor-1),3);\r\n   LR(r,2*c-1)=te(tptr+ntiles*(tor-1),4);\r\n   LR(r,2*c)=te(tptr+ntiles*(tor-1),2);\r\n  end\r\n end\r\n checksum=sum([LR(:,1)' LR(:,end)' UD(1,:) UD(end,:)]);\r\n for idx=2:2:2*rows-2 % LR Square array assumed here\r\n  checksum=checksum+sum(LR(:,idx)-LR(:,idx+1))+sum(UD(idx,:)-UD(idx+1,:));\r\n end\r\n\r\n\r\nassert(checksum==0,sprintf('Checksum = %s\\n',num2str(checksum)));\r\nnet_time=(dt+temp)/2\r\n%%\r\nglobal net_time\r\n\r\n% Limit Score to 2000 for graph quality\r\nt=mtree('board_perfect.m','-file');\r\nscr=floor(length(t.nodesize)/10+net_time);\r\nscr=min(scr,2000)\r\n\r\nfeval(@assignin,'caller','score',floor(scr));\r\n\r\n\r\n%fh=fopen('board_perfect.m','wt');\r\n%fprintf(fh,'%s\\n',repmat('1;',[1,round(scr/2)]));\r\n%fclose(fh);\r\n\r\n\r\n\r\n\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":2,"created_by":3097,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":1,"test_suite_updated_at":"2020-10-08T17:49:19.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2012-06-25T01:21:51.000Z","updated_at":"2025-05-05T20:22:13.000Z","published_at":"2012-06-26T18:09:51.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eTiles Contest:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e The Large Unique Boards/Tiles that perfectly solve (50x50)\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eReturn Perfect solutions for both boards. Scoring will be based upon size and time.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eSample \\\"Board 59\\\" and Actual(Contest) \\\"Board 6\\\" have perfect solutions with unique tiles. The tiles are unique with any number,except zero, occurring exactly twice.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe complete description of \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"https://web.archive.org/web/20150224170744/http://www.mathworks.com/matlabcentral/contest/contests/36/rules\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eTiles_wayback\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"http://www.mathworks.com/matlabcentral/contest/contests/36/rules\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eTiles\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e explains what is a tile, orientation, and board output.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eInput:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e (boardsize, tiles)\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eOutput:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e (board, orientation)\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ePassing:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e Two Perfect Boards.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eScoring:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e Based upon Size/10 and Average Time(msec) of solutions.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe Test Suite demonstrates urlwrite usage with a customized tinyurl from an http site for acessing web mat files.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis is the first in a series of Tiles Contest challenges where the boards have interesting characteristics. There are multiple perfect solution boards which were not solved during the contest.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":937,"title":"Rubik's Mini Cube: Solve Randomized Cube in 11 Moves or Less; Score is by Time (msec)","description":"The Challenge is to Near or Optimally Solve a thoroughly scrambled Mini-Rubik's Cube(2x2x2).\r\n\r\nAny Mini-Cube can be solved in 11 or fewer Face Moves. There are only 3,674,160 unique cube positions, with only 2344 requiring the fulll 11 moves. Cube moves do not count.\r\n\r\nThe Performance metric is cumulative Time to Solve 500 cubes (msec).\r\n\r\nA standard Mini-Rubik's Cube is shown in 3-D and also unfolded to identify the specific Tile-face/Vector numbering.\r\n\r\nThe faces are White-Up / Red-Left / Blue-Front / Orange-Right / Yellow-Down / Green-Back (ULFRDB)\r\n\r\nMoves are denoted as F for clockwise rotation of the Front face. F'(or FP) is CCW and F2 is F twice.  The provided function r_new=rubick_rot_mini(mov,r) implements moves 1-18: UFDLBRU'F'D'L'B'R'U2F2D2L2B2R2.\r\n\r\n\r\n\r\n\r\n\u003c\u003chttps://sites.google.com/site/razapor/matlab_cody/minicube2.png\u003e\u003e\r\n\r\n\u003c\u003chttps://sites.google.com/site/razapor/matlab_cody/miniCube_Map24_200.png\u003e\u003e\r\n\r\n\u003c\u003chttp://mathworks.com/matlabcentral/images/surf.gif\u003e\u003e\r\n\r\n\r\n  \r\n  \r\n  Input: (rubik)\r\n  \r\n  rubik: row vector of size 24\r\n  (The cube started [L=0,U=1,F=2,D=3,B=4,R=5] and then receives forty face moves.\r\n\r\n  Output: move_vec (Numeric of moves to solve)\r\n   move_vec:values 1:27 for UFDLBR U'F'D'L'B'R' U2F2D2L2B2R2 XYZX'Y'Z'X2Y2Z2\r\n\r\n* Example:\r\n* If the cube was randomized by [1 9] UD', one solution is [3 7]  which are the complements in reverse order. \r\n* Scoring is Time in msec to solve 500 cubes\r\n* Cube Moves X, Y, and Z do not constitute a move but are needed in the vector \r\n* A string to numeric value function is provided in the template\r\n* Verifications will be by executing your move vector against the provided Rubik and counting number of face moves.\r\n\r\nThe function rubik_rot_mini(mov,r) is provided in the template. Other functions are provided to re-orient the cube in Cody Challenge 931, Rubik's Mini-Cube.\r\n\r\n\r\nThe Challenge \u003chttp://www.mathworks.com/matlabcentral/cody/problems/931-rubik-s-mini-cube-solve-randomized-mini-cube-score-moves.html Challenge 931 Rubik's Mini-Cube\u003e contains a 3D Mini-Cube Viewer for program development.\r\n\r\n\r\n* \r\n* \u003chttp://kociemba.org/cube.htm Cube Theory: 20-moves Any Cube\u003e \r\n* \u003chttp://peter.stillhq.com/jasmine/rubikscubesolution.html General Cube Info and Middle Layer\u003e\r\n* \u003chttp://www.speedcubing.com/final_layer_print.html SpeedCube Bottom Sequences\u003e\r\n* The site \u003chttp://www.speedcubing.com/CubeSolver/MiniCubeSolver.html MiniCube Solver\u003e claims an outstanding 10 minutes to solve a randomized Mini-Cube. Matlab can achieve any Mini-Cube solution in \u003c 497 usec, independent of moves on an i5/16GB machine.\r\n\r\n\r\n(Note: Mini-Cube can use the full cube moves and ignore edge effects)\r\n\r\nComing Soon: Matlab Tetris\r\n","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.4333px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 1316.98px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 658.5px; transform-origin: 407px 658.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 294.65px 7.91667px; transform-origin: 294.65px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThe Challenge is to Near or Optimally Solve a thoroughly scrambled Mini-Rubik's Cube(2x2x2).\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 21px; text-align: left; transform-origin: 384px 21px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 377.2px 7.91667px; transform-origin: 377.2px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eAny Mini-Cube can be solved in 11 or fewer Face Moves. There are only 3,674,160 unique cube positions, with only 2344 requiring the fulll 11 moves. Cube moves do not count.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 221.45px 7.91667px; transform-origin: 221.45px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThe Performance metric is cumulative Time to Solve 500 cubes (msec).\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 355.467px 7.91667px; transform-origin: 355.467px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eA standard Mini-Rubik's Cube is shown in 3-D and also unfolded to identify the specific Tile-face/Vector numbering.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 316.733px 7.91667px; transform-origin: 316.733px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThe faces are White-Up / Red-Left / Blue-Front / Orange-Right / Yellow-Down / Green-Back (ULFRDB)\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 21px; text-align: left; transform-origin: 384px 21px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 380.533px 7.91667px; transform-origin: 380.533px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eMoves are denoted as F for clockwise rotation of the Front face. F'(or FP) is CCW and F2 is F twice. The provided function r_new=rubick_rot_mini(mov,r) implements moves 1-18: UFDLBRU'F'D'L'B'R'U2F2D2L2B2R2.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 138.917px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 69.4667px; text-align: center; transform-origin: 384px 69.4667px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cimg class=\"imageNode\" style=\"vertical-align: baseline\" 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\" 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border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.833333px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.833333px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.833333px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 0px 7.91667px; transform-origin: 0px 7.91667px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 0.833333px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.833333px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.833333px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.833333px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 107.8px 7.91667px; transform-origin: 107.8px 7.91667px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 69.3px 7.91667px; transform-origin: 69.3px 7.91667px; \"\u003erubik: row vector \u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(170, 4, 249); border-block-start-color: rgb(170, 4, 249); border-bottom-color: rgb(170, 4, 249); border-inline-end-color: rgb(170, 4, 249); border-inline-start-color: rgb(170, 4, 249); border-left-color: rgb(170, 4, 249); border-right-color: rgb(170, 4, 249); border-top-color: rgb(170, 4, 249); caret-color: rgb(170, 4, 249); color: rgb(170, 4, 249); column-rule-color: rgb(170, 4, 249); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(170, 4, 249); perspective-origin: 38.5px 7.91667px; text-decoration: none; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); transform-origin: 38.5px 7.91667px; \"\u003eof size 24\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 0.833333px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.833333px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.833333px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.833333px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 304.15px 7.91667px; transform-origin: 304.15px 7.91667px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e(The cube started [L=0,U=1,F=2,D=3,B=4,R=5] and then receives forty face moves.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 0.833333px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.833333px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.833333px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.833333px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 0px 7.91667px; transform-origin: 0px 7.91667px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 0.833333px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.833333px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.833333px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.833333px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 169.4px 7.91667px; transform-origin: 169.4px 7.91667px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003eOutput: move_vec (Numeric of moves to solve)\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 0.833333px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.833333px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.833333px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.833333px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 284.9px 7.91667px; transform-origin: 284.9px 7.91667px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 84.7px 7.91667px; transform-origin: 84.7px 7.91667px; \"\u003e move_vec:values 1:27 \u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(14, 0, 255); border-block-start-color: rgb(14, 0, 255); border-bottom-color: rgb(14, 0, 255); border-inline-end-color: rgb(14, 0, 255); border-inline-start-color: rgb(14, 0, 255); border-left-color: rgb(14, 0, 255); border-right-color: rgb(14, 0, 255); border-top-color: rgb(14, 0, 255); caret-color: rgb(14, 0, 255); color: rgb(14, 0, 255); column-rule-color: rgb(14, 0, 255); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(14, 0, 255); perspective-origin: 15.4px 7.91667px; text-decoration: none; text-decoration-color: rgb(14, 0, 255); text-emphasis-color: rgb(14, 0, 255); transform-origin: 15.4px 7.91667px; \"\u003efor \u003c/span\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 127.05px 7.91667px; transform-origin: 127.05px 7.91667px; \"\u003eUFDLBR U'F'D'L'B'R' U2F2D2L2B2R2 \u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(196, 0, 0); border-block-start-color: rgb(196, 0, 0); border-bottom-color: rgb(196, 0, 0); border-inline-end-color: rgb(196, 0, 0); border-inline-start-color: rgb(196, 0, 0); border-left-color: rgb(196, 0, 0); border-right-color: rgb(196, 0, 0); border-top-color: rgb(196, 0, 0); caret-color: rgb(196, 0, 0); color: rgb(196, 0, 0); column-rule-color: rgb(196, 0, 0); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(196, 0, 0); perspective-origin: 57.75px 7.91667px; text-decoration: none; text-decoration-color: rgb(196, 0, 0); text-emphasis-color: rgb(196, 0, 0); transform-origin: 57.75px 7.91667px; \"\u003eXYZX'Y'Z'X2Y2Z2\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003cul style=\"block-size: 122.6px; counter-reset: list-item 0; font-family: Helvetica, Arial, sans-serif; list-style-type: square; margin-block-end: 20px; margin-block-start: 10px; margin-bottom: 20px; margin-top: 10px; perspective-origin: 391px 61.3px; transform-origin: 391px 61.3px; margin-top: 10px; margin-bottom: 20px; \"\u003e\u003cli style=\"block-size: 20.4333px; counter-reset: none; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 363px 10.2167px; text-align: left; transform-origin: 363px 10.2167px; white-space: pre-wrap; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 29.1833px 7.91667px; transform-origin: 29.1833px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eExample:\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 20.4333px; counter-reset: none; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 363px 10.2167px; text-align: left; transform-origin: 363px 10.2167px; white-space: pre-wrap; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 327.667px 7.91667px; transform-origin: 327.667px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eIf the cube was randomized by [1 9] UD', one solution is [3 7] which are the complements in reverse order.\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 20.4333px; counter-reset: none; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 363px 10.2167px; text-align: left; transform-origin: 363px 10.2167px; white-space: pre-wrap; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 134.333px 7.91667px; transform-origin: 134.333px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eScoring is Time in msec to solve 500 cubes\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 20.4333px; counter-reset: none; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 363px 10.2167px; text-align: left; transform-origin: 363px 10.2167px; white-space: pre-wrap; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 242.583px 7.91667px; transform-origin: 242.583px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eCube Moves X, Y, and Z do not constitute a move but are needed in the vector\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 20.4333px; counter-reset: none; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 363px 10.2167px; text-align: left; transform-origin: 363px 10.2167px; white-space: pre-wrap; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 187.1px 7.91667px; transform-origin: 187.1px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eA string to numeric value function is provided in the template\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 20.4333px; counter-reset: none; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 363px 10.2167px; text-align: left; transform-origin: 363px 10.2167px; white-space: pre-wrap; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 355.933px 7.91667px; transform-origin: 355.933px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eVerifications will be by executing your move vector against the provided Rubik and counting number of face moves.\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ul\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 21px; text-align: left; transform-origin: 384px 21px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 374.067px 7.91667px; transform-origin: 374.067px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThe function rubik_rot_mini(mov,r) is provided in the template. Other functions are provided to re-orient the cube in Cody Challenge 931, Rubik's Mini-Cube.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 45.5333px 7.91667px; transform-origin: 45.5333px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThe Challenge\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 1.95px 7.91667px; transform-origin: 1.95px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e \u003c/span\u003e\u003c/span\u003e\u003ca target='_blank' href = \"http://www.mathworks.com/matlabcentral/cody/problems/931-rubik-s-mini-cube-solve-randomized-mini-cube-score-moves.html\"\u003e\u003cspan style=\"\"\u003e\u003cspan style=\"\"\u003eChallenge 931 Rubik's Mini-Cube\u003c/span\u003e\u003c/span\u003e\u003c/a\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 183.883px 7.91667px; transform-origin: 183.883px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e contains a 3D Mini-Cube Viewer for program development.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cul style=\"block-size: 122.6px; counter-reset: list-item 0; font-family: Helvetica, Arial, sans-serif; list-style-type: square; margin-block-end: 20px; margin-block-start: 10px; margin-bottom: 20px; margin-top: 10px; perspective-origin: 391px 61.3px; transform-origin: 391px 61.3px; margin-top: 10px; margin-bottom: 20px; \"\u003e\u003cli style=\"block-size: 20.4333px; counter-reset: none; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 363px 10.2167px; text-align: left; transform-origin: 363px 10.2167px; white-space: pre-wrap; margin-left: 56px; \"\u003e\u003c/li\u003e\u003cli style=\"block-size: 20.4333px; counter-reset: none; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 363px 10.2167px; text-align: left; transform-origin: 363px 10.2167px; white-space: pre-wrap; margin-left: 56px; \"\u003e\u003ca target='_blank' href = \"http://kociemba.org/cube.htm\"\u003e\u003cspan style=\"\"\u003e\u003cspan style=\"\"\u003eCube Theory: 20-moves Any Cube\u003c/span\u003e\u003c/span\u003e\u003c/a\u003e\u003c/li\u003e\u003cli style=\"block-size: 20.4333px; counter-reset: none; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 363px 10.2167px; text-align: left; transform-origin: 363px 10.2167px; white-space: pre-wrap; margin-left: 56px; \"\u003e\u003ca target='_blank' href = \"http://peter.stillhq.com/jasmine/rubikscubesolution.html\"\u003e\u003cspan style=\"\"\u003e\u003cspan style=\"\"\u003eGeneral Cube Info and Middle Layer\u003c/span\u003e\u003c/span\u003e\u003c/a\u003e\u003c/li\u003e\u003cli style=\"block-size: 20.4333px; counter-reset: none; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 363px 10.2167px; text-align: left; transform-origin: 363px 10.2167px; white-space: pre-wrap; margin-left: 56px; \"\u003e\u003ca target='_blank' href = \"http://www.speedcubing.com/final_layer_print.html\"\u003e\u003cspan style=\"\"\u003e\u003cspan style=\"\"\u003eSpeedCube Bottom Sequences\u003c/span\u003e\u003c/span\u003e\u003c/a\u003e\u003c/li\u003e\u003cli style=\"block-size: 40.8667px; counter-reset: none; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 363px 20.4333px; text-align: left; transform-origin: 363px 20.4333px; white-space: pre-wrap; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 24.9px 7.91667px; transform-origin: 24.9px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThe site\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 1.95px 7.91667px; transform-origin: 1.95px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e \u003c/span\u003e\u003c/span\u003e\u003ca target='_blank' href = \"http://www.speedcubing.com/CubeSolver/MiniCubeSolver.html\"\u003e\u003cspan style=\"\"\u003e\u003cspan style=\"\"\u003eMiniCube Solver\u003c/span\u003e\u003c/span\u003e\u003c/a\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 276.2px 7.91667px; transform-origin: 276.2px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e claims an outstanding 10 minutes to solve a randomized Mini-Cube. Matlab can achieve any Mini-Cube solution in \u0026lt; 497 usec, independent of moves on an i5/16GB machine.\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ul\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 218.883px 7.91667px; transform-origin: 218.883px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e(Note: Mini-Cube can use the full cube moves and ignore edge effects)\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 85.9667px 7.91667px; transform-origin: 85.9667px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eComing Soon: Matlab Tetris\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function solve_vec = rubik_solve_mini(r)\r\n% Expect Numeric representation of moves (1:27):\r\n% 1:27 are ufdlbr upfpdplpbprp u2f2d2l2b2r2 xyzxpypzpx2y2z2\r\n solve_vec=[]; \r\n\r\n% One path is to use Challenge 931's, Rubik's Mini Cube, initial Cube re-orientation provided in the template, followed by a solving algorithm that needs only RDB type moves\r\n% Loading an external data file is one method. First solve is not timed.\r\nend\r\n\r\nfunction r=rubik_rot_mini(mov,r)\r\n%mov is 1:27;  1-6 UFDLBR 7-12 U'F;D'L'B'R' 13-18 U2F2D2L2B2R2 \r\n%             19-27 XYZ X'Y'Z' X2Y2Z2  \r\n% X cube-R, Y cube-U,  Z cube-F\r\n%\r\n% r is a 24 element row vector\r\n% r output is a single row vector \r\n%\r\n% vector mov\r\n% r output is array of length(mov) x 24\r\n%\r\n% Perform Rubik Cube face rotations and cube rotations\r\n% L 1:4 U 5:8 F 9:12 D 13:16 B 17:20 R 21:24 \r\n% \r\npersistent vf\r\nif isempty(vf) %\r\nvf=[9 2 11 4 6 8 5 7 21 10 23 12 13 14 15 16 17 3 19 1 20 22 18 24 ; \r\n    1 2 13 15 5 4 7 3 10 12 9 11 22 14 21 16 17 18 19 20 6 8 23 24 ;\r\n    1 19 3 17 5 6 7 8 9 2 11 4 14 16 13 15 24 18 22 20 21 10 23 12 ;\r\n    2 4 1 3 17 18 7 8 5 6 11 12 9 10 15 16 13 14 19 20 21 22 23 24 ;\r\n    7 5 3 4 23 6 24 8 9 10 11 12 13 1 15 2 18 20 17 19 21 22 16 14 ;\r\n    1 2 3 4 5 6 11 12 9 10 15 16 13 14 19 20 17 18 7 8 22 24 21 23 ;\r\n    20 2 18 4 7 5 8 6 1 10 3 12 13 14 15 16 17 23 19 21 9 22 11 24 ;\r\n    1 2 8 6 5 21 7 22 11 9 12 10 3 14 4 16 17 18 19 20 15 13 23 24 ;\r\n    1 10 3 12 5 6 7 8 9 22 11 24 15 13 16 14 4 18 2 20 21 19 23 17 ;\r\n    3 1 4 2 9 10 7 8 13 14 11 12 17 18 15 16 5 6 19 20 21 22 23 24 ;\r\n    14 16 3 4 2 6 1 8 9 10 11 12 13 24 15 23 19 17 20 18 21 22 5 7 ;\r\n    1 2 3 4 5 6 19 20 9 10 7 8 13 14 11 12 17 18 15 16 23 21 24 22 ;\r\n    21 2 23 4 8 7 6 5 20 10 18 12 13 14 15 16 17 11 19 9 1 22 3 24 ;\r\n    1 2 22 21 5 15 7 13 12 11 10 9 8 14 6 16 17 18 19 20 4 3 23 24 ;\r\n    1 22 3 24 5 6 7 8 9 19 11 17 16 15 14 13 12 18 10 20 21 2 23 4 ;\r\n    4 3 2 1 13 14 7 8 17 18 11 12 5 6 15 16 9 10 19 20 21 22 23 24 ;\r\n    24 23 3 4 16 6 14 8 9 10 11 12 13 7 15 5 20 19 18 17 21 22 2 1 ;\r\n    1 2 3 4 5 6 15 16 9 10 19 20 13 14 7 8 17 18 11 12 24 23 22 21 ;\r\n    3 1 4 2 9 10 11 12 13 14 15 16 17 18 19 20 5 6 7 8 22 24 21 23 ;\r\n    9 10 11 12 6 8 5 7 21 22 23 24 15 13 16 14 4 3 2 1 20 19 18 17 ;\r\n    14 16 13 15 2 4 1 3 10 12 9 11 22 24 21 23 19 17 20 18 6 8 5 7 ;\r\n    2 4 1 3 17 18 19 20 5 6 7 8 9 10 11 12 13 14 15 16 23 21 24 22 ;\r\n    20 19 18 17 7 5 8 6 1 2 3 4 14 16 13 15 24 23 22 21 9 10 11 12 ;\r\n    7 5 8 6 23 21 24 22 11 9 12 10 3 1 4 2 18 20 17 19 15 13 16 14 ;\r\n    4 3 2 1 13 14 15 16 17 18 19 20 5 6 7 8 9 10 11 12 24 23 22 21 ;\r\n    21 22 23 24 8 7 6 5 20 19 18 17 16 15 14 13 12 11 10 9 1 2 3 4 ; \r\n    24 23 22 21 16 15 14 13 12 11 10 9 8 7 6 5 20 19 18 17 4 3 2 1 ];\r\nend\r\n\r\nr=r(vf(mov,:));\r\nend\r\n\r\n\r\nfunction move_vec=decode27_movestr_rev001(movestr)\r\n% Active character Inputs: UFDLBRXYZ, GQ are pre-processed\r\n% 1-6 UFDLBR 7-12 U'F;D'L'B'R' 13-18 U2F2D2L2B2R2 19-27 XYZX'Y'Z'X2Y2Z2\r\nmovestr=upper(movestr);\r\nmovestr=strrep(movestr,'''','P'); % simplify further searches\r\n\r\nmovestr=strrep(movestr,'UP',' 7 ');\r\nmovestr=strrep(movestr,'FP',' 8 ');\r\nmovestr=strrep(movestr,'DP',' 9 ');\r\nmovestr=strrep(movestr,'LP',' 10 ');\r\nmovestr=strrep(movestr,'BP',' 11 ');\r\nmovestr=strrep(movestr,'RP',' 12 ');\r\nmovestr=strrep(movestr,'U2',' 13 ');\r\nmovestr=strrep(movestr,'F2',' 14 ');\r\nmovestr=strrep(movestr,'D2',' 15 ');\r\nmovestr=strrep(movestr,'L2',' 16 ');\r\nmovestr=strrep(movestr,'B2',' 17 ');\r\nmovestr=strrep(movestr,'R2',' 18 ');\r\nmovestr=strrep(movestr,'U',' 1 ');\r\nmovestr=strrep(movestr,'F',' 2 ');\r\nmovestr=strrep(movestr,'D',' 3 ');\r\nmovestr=strrep(movestr,'L',' 4 ');\r\nmovestr=strrep(movestr,'B',' 5 ');\r\nmovestr=strrep(movestr,'R',' 6 ');\r\nmovestr=strrep(movestr,'XP',' 22 ');\r\nmovestr=strrep(movestr,'YP',' 23 ');\r\nmovestr=strrep(movestr,'ZP',' 24 ');\r\nmovestr=strrep(movestr,'X2',' 25 ');\r\nmovestr=strrep(movestr,'Y2',' 26 ');\r\nmovestr=strrep(movestr,'Z2',' 27 ');\r\nmovestr=strrep(movestr,'X',' 19 ');\r\nmovestr=strrep(movestr,'Y',' 20 ');\r\nmovestr=strrep(movestr,'Z',' 21 ');\r\n\r\nmove_vec=str2num(movestr);\r\n\r\nend % move_vec","test_suite":"%%\r\nfeval(@assignin,'caller','score',0);\r\n%%\r\nvf=[9 2 11 4 6 8 5 7 21 10 23 12 13 14 15 16 17 3 19 1 20 22 18 24 ; \r\n    1 2 13 15 5 4 7 3 10 12 9 11 22 14 21 16 17 18 19 20 6 8 23 24 ;\r\n    1 19 3 17 5 6 7 8 9 2 11 4 14 16 13 15 24 18 22 20 21 10 23 12 ;\r\n    2 4 1 3 17 18 7 8 5 6 11 12 9 10 15 16 13 14 19 20 21 22 23 24 ;\r\n    7 5 3 4 23 6 24 8 9 10 11 12 13 1 15 2 18 20 17 19 21 22 16 14 ;\r\n    1 2 3 4 5 6 11 12 9 10 15 16 13 14 19 20 17 18 7 8 22 24 21 23 ;\r\n    20 2 18 4 7 5 8 6 1 10 3 12 13 14 15 16 17 23 19 21 9 22 11 24 ;\r\n    1 2 8 6 5 21 7 22 11 9 12 10 3 14 4 16 17 18 19 20 15 13 23 24 ;\r\n    1 10 3 12 5 6 7 8 9 22 11 24 15 13 16 14 4 18 2 20 21 19 23 17 ;\r\n    3 1 4 2 9 10 7 8 13 14 11 12 17 18 15 16 5 6 19 20 21 22 23 24 ;\r\n    14 16 3 4 2 6 1 8 9 10 11 12 13 24 15 23 19 17 20 18 21 22 5 7 ;\r\n    1 2 3 4 5 6 19 20 9 10 7 8 13 14 11 12 17 18 15 16 23 21 24 22 ;\r\n    21 2 23 4 8 7 6 5 20 10 18 12 13 14 15 16 17 11 19 9 1 22 3 24 ;\r\n    1 2 22 21 5 15 7 13 12 11 10 9 8 14 6 16 17 18 19 20 4 3 23 24 ;\r\n    1 22 3 24 5 6 7 8 9 19 11 17 16 15 14 13 12 18 10 20 21 2 23 4 ;\r\n    4 3 2 1 13 14 7 8 17 18 11 12 5 6 15 16 9 10 19 20 21 22 23 24 ;\r\n    24 23 3 4 16 6 14 8 9 10 11 12 13 7 15 5 20 19 18 17 21 22 2 1 ;\r\n    1 2 3 4 5 6 15 16 9 10 19 20 13 14 7 8 17 18 11 12 24 23 22 21 ;\r\n    3 1 4 2 9 10 11 12 13 14 15 16 17 18 19 20 5 6 7 8 22 24 21 23 ;\r\n    9 10 11 12 6 8 5 7 21 22 23 24 15 13 16 14 4 3 2 1 20 19 18 17 ;\r\n    14 16 13 15 2 4 1 3 10 12 9 11 22 24 21 23 19 17 20 18 6 8 5 7 ;\r\n    2 4 1 3 17 18 19 20 5 6 7 8 9 10 11 12 13 14 15 16 23 21 24 22 ;\r\n    20 19 18 17 7 5 8 6 1 2 3 4 14 16 13 15 24 23 22 21 9 10 11 12 ;\r\n    7 5 8 6 23 21 24 22 11 9 12 10 3 1 4 2 18 20 17 19 15 13 16 14 ;\r\n    4 3 2 1 13 14 15 16 17 18 19 20 5 6 7 8 9 10 11 12 24 23 22 21 ;\r\n    21 22 23 24 8 7 6 5 20 19 18 17 16 15 14 13 12 11 10 9 1 2 3 4 ; \r\n    24 23 22 21 16 15 14 13 12 11 10 9 8 7 6 5 20 19 18 17 4 3 2 1 ];\r\n\r\n%r=r(vf(mov,:));  % Standard move, r=rubik_rot_min(mov,r);\r\n\r\nPass=1;\r\nr_fail=0;\r\n% Execute 500 cubes and verify completeness and count moves\r\n % initialize cube\r\n r(1:4)=0;     %Left   0 R\r\n r(5:8)=1;     %Up     1 W\r\n r(9:12)=2;    %Front  2 B\r\n r(13:16)=3;   %Down   3 Y\r\n r(17:20)=4;   %Back   4 G\r\n r(21:24)=5;   %Right  5 O\r\n rnorm=r;\r\n\r\nzcnt=500;\r\nsum_solve=0;\r\nmin_solve=1000;\r\nmax_solve=0;\r\nasolve=199;\r\nmix=40;\r\n\r\ntic\r\n\r\nfor cube_check=1:zcnt %zcnt\u003c100 %500\r\n %zcnt=zcnt+1;\r\n  r=rnorm;\r\n % Initial mix\r\n mov=randi(18,[mix,1]);\r\n for i=1:length(mov)  % Ignoring Move Undos since mix=40\r\n   r=r(vf(mov(i),:));\r\n end\r\n\r\n r_reset=r; % Used in assert\r\n\r\n solve_vec=rubik_solve_mini(r);\r\n\r\n for i=1:length(solve_vec) \r\n  r=r(vf(solve_vec(i),:));\r\n end\r\n\r\n  if all(r(1:4)==r(4)) \u0026\u0026 all(r(5:8)==r(8))  \u0026\u0026 all(r(9:12)==r(9)) \u0026\u0026 ...\r\n     all(r(13:16)==r(13))  \u0026\u0026 all(r(17:20)==r(17)) \u0026\u0026 all(r(21:24)==r(21))\r\n   solve_vec(solve_vec\u003e18)=[]; %   \r\n   lsolve=length(solve_vec);\r\n   if lsolve\u003e11, Pass=0;end % Length Rqmt\r\n   sum_solve=sum_solve+lsolve;\r\n   min_solve=min(min_solve,lsolve);\r\n   max_solve=max(max_solve,lsolve);\r\n   asolve=floor(sum_solve/zcnt);\r\n %  fprintf('Cube Solved Moves=%i  Avg Moves=%i min=%i  max=%i\\n',lsolve,asolve,min_solve,max_solve)\r\n  else % Deug info\r\n   Pass=0;\r\n   r_fail=r_reset;\r\n  % fprintf('\\n\\nCube NOT Solved???\\n\\n') \r\n  % fprintf('%i ',r); % Current ending data\r\n  % fprintf('\\n')\r\n  % fprintf('%i ',r_reset); % Starting Cube\r\n  end\r\n\r\nend % while of cubes\r\ntoc\r\n\r\nassert(isequal(Pass,1),sprintf('Max Len=%i \\n',max_solve)); % Length Exception\r\nassert(isequal(Pass,1),sprintf('%i ',r_fail)); % Output Non-Solved Cube Start\r\n\r\n%if Pass\r\n% feval(@assignin,'caller','score',min(100,floor(asolve)));\r\n%end\r\n\r\nfprintf('Moves: Avg %i   Min %i   Max %i\\n',asolve,min_solve,max_solve)\r\n\r\n%%\r\nvf=[9 2 11 4 6 8 5 7 21 10 23 12 13 14 15 16 17 3 19 1 20 22 18 24 ; \r\n    1 2 13 15 5 4 7 3 10 12 9 11 22 14 21 16 17 18 19 20 6 8 23 24 ;\r\n    1 19 3 17 5 6 7 8 9 2 11 4 14 16 13 15 24 18 22 20 21 10 23 12 ;\r\n    2 4 1 3 17 18 7 8 5 6 11 12 9 10 15 16 13 14 19 20 21 22 23 24 ;\r\n    7 5 3 4 23 6 24 8 9 10 11 12 13 1 15 2 18 20 17 19 21 22 16 14 ;\r\n    1 2 3 4 5 6 11 12 9 10 15 16 13 14 19 20 17 18 7 8 22 24 21 23 ;\r\n    20 2 18 4 7 5 8 6 1 10 3 12 13 14 15 16 17 23 19 21 9 22 11 24 ;\r\n    1 2 8 6 5 21 7 22 11 9 12 10 3 14 4 16 17 18 19 20 15 13 23 24 ;\r\n    1 10 3 12 5 6 7 8 9 22 11 24 15 13 16 14 4 18 2 20 21 19 23 17 ;\r\n    3 1 4 2 9 10 7 8 13 14 11 12 17 18 15 16 5 6 19 20 21 22 23 24 ;\r\n    14 16 3 4 2 6 1 8 9 10 11 12 13 24 15 23 19 17 20 18 21 22 5 7 ;\r\n    1 2 3 4 5 6 19 20 9 10 7 8 13 14 11 12 17 18 15 16 23 21 24 22 ;\r\n    21 2 23 4 8 7 6 5 20 10 18 12 13 14 15 16 17 11 19 9 1 22 3 24 ;\r\n    1 2 22 21 5 15 7 13 12 11 10 9 8 14 6 16 17 18 19 20 4 3 23 24 ;\r\n    1 22 3 24 5 6 7 8 9 19 11 17 16 15 14 13 12 18 10 20 21 2 23 4 ;\r\n    4 3 2 1 13 14 7 8 17 18 11 12 5 6 15 16 9 10 19 20 21 22 23 24 ;\r\n    24 23 3 4 16 6 14 8 9 10 11 12 13 7 15 5 20 19 18 17 21 22 2 1 ;\r\n    1 2 3 4 5 6 15 16 9 10 19 20 13 14 7 8 17 18 11 12 24 23 22 21 ;\r\n    3 1 4 2 9 10 11 12 13 14 15 16 17 18 19 20 5 6 7 8 22 24 21 23 ;\r\n    9 10 11 12 6 8 5 7 21 22 23 24 15 13 16 14 4 3 2 1 20 19 18 17 ;\r\n    14 16 13 15 2 4 1 3 10 12 9 11 22 24 21 23 19 17 20 18 6 8 5 7 ;\r\n    2 4 1 3 17 18 19 20 5 6 7 8 9 10 11 12 13 14 15 16 23 21 24 22 ;\r\n    20 19 18 17 7 5 8 6 1 2 3 4 14 16 13 15 24 23 22 21 9 10 11 12 ;\r\n    7 5 8 6 23 21 24 22 11 9 12 10 3 1 4 2 18 20 17 19 15 13 16 14 ;\r\n    4 3 2 1 13 14 15 16 17 18 19 20 5 6 7 8 9 10 11 12 24 23 22 21 ;\r\n    21 22 23 24 8 7 6 5 20 19 18 17 16 15 14 13 12 11 10 9 1 2 3 4 ; \r\n    24 23 22 21 16 15 14 13 12 11 10 9 8 7 6 5 20 19 18 17 4 3 2 1 ];\r\n\r\n%r=r(vf(mov,:));  % Standard move, r=rubik_rot_min(mov,r);\r\n\r\nPass=1;\r\nr_fail=0;\r\n% Execute 500 cubes and verify completeness and count moves\r\n % initialize cube\r\n r(1:4)=0;     %Left   0 R\r\n r(5:8)=1;     %Up     1 W\r\n r(9:12)=2;    %Front  2 B\r\n r(13:16)=3;   %Down   3 Y\r\n r(17:20)=4;   %Back   4 G\r\n r(21:24)=5;   %Right  5 O\r\n rnorm=r;\r\n\r\n for jrand=1:40  % Ignoring Move Undos since mix=40\r\n   r=r(vf(randi(18),:));\r\n end\r\n\r\n q=500;\r\n ra=zeros(q,24);\r\n for i=1:q\r\n  for jrand=1:10  % Ignoring Move Undos since base mix=40\r\n    r=r(vf(randi(18),:));\r\n  end\r\n % add 10 new moves to prior vector\r\n  ra(i,:)=r;\r\n end\r\n\r\n% The Time Trail section does not check accuracy, that is done above\r\nt0=clock;\r\nfor i=1:q\r\n solve_vec=rubik_solve_mini(ra(q,:));\r\nend\r\ndt=etime(clock,t0)*1000;\r\n\r\n%assert(isequal(find_fast(a,val(1)),find(a==val(1),1,'first')))\r\nfprintf('Your Time = %i msec\\n',floor(dt))\r\nfeval(@assignin,'caller','score',min(2000,floor(dt)));\r\n%   Performance Score","published":true,"deleted":false,"likes_count":5,"comments_count":0,"created_by":3097,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":1,"test_suite_updated_at":"2012-09-09T17:48:25.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2012-09-09T06:26:08.000Z","updated_at":"2025-11-17T16:25:58.000Z","published_at":"2012-09-09T16:33:58.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe Challenge is to Near or Optimally Solve a thoroughly scrambled Mini-Rubik's Cube(2x2x2).\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eAny Mini-Cube can be solved in 11 or fewer Face Moves. There are only 3,674,160 unique cube positions, with only 2344 requiring the fulll 11 moves. Cube moves do not count.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe Performance metric is cumulative Time to Solve 500 cubes (msec).\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eA standard Mini-Rubik's Cube is shown in 3-D and also unfolded to identify the specific Tile-face/Vector numbering.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe faces are White-Up / Red-Left / Blue-Front / Orange-Right / Yellow-Down / Green-Back (ULFRDB)\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eMoves are denoted as F for clockwise rotation of the Front face. F'(or FP) is CCW and F2 is F twice. The provided function r_new=rubick_rot_mini(mov,r) implements moves 1-18: UFDLBRU'F'D'L'B'R'U2F2D2L2B2R2.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"center\\\"/\u003e\u003c/w:pPr\u003e\u003cw:customXml w:element=\\\"image\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"height\\\" w:val=\\\"-1\\\"/\u003e\u003cw:attr w:name=\\\"width\\\" w:val=\\\"-1\\\"/\u003e\u003cw:attr w:name=\\\"verticalAlign\\\" w:val=\\\"baseline\\\"/\u003e\u003cw:attr w:name=\\\"altText\\\" w:val=\\\"\\\"/\u003e\u003cw:attr w:name=\\\"relationshipId\\\" w:val=\\\"rId1\\\"/\u003e\u003c/w:customXmlPr\u003e\u003c/w:customXml\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"center\\\"/\u003e\u003c/w:pPr\u003e\u003cw:customXml w:element=\\\"image\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"height\\\" w:val=\\\"-1\\\"/\u003e\u003cw:attr w:name=\\\"width\\\" w:val=\\\"-1\\\"/\u003e\u003cw:attr w:name=\\\"verticalAlign\\\" w:val=\\\"baseline\\\"/\u003e\u003cw:attr w:name=\\\"altText\\\" w:val=\\\"\\\"/\u003e\u003cw:attr w:name=\\\"relationshipId\\\" w:val=\\\"rId2\\\"/\u003e\u003c/w:customXmlPr\u003e\u003c/w:customXml\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"center\\\"/\u003e\u003c/w:pPr\u003e\u003cw:customXml w:element=\\\"image\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"height\\\" w:val=\\\"-1\\\"/\u003e\u003cw:attr w:name=\\\"width\\\" w:val=\\\"-1\\\"/\u003e\u003cw:attr w:name=\\\"verticalAlign\\\" w:val=\\\"baseline\\\"/\u003e\u003cw:attr w:name=\\\"altText\\\" w:val=\\\"\\\"/\u003e\u003cw:attr w:name=\\\"relationshipId\\\" w:val=\\\"rId3\\\"/\u003e\u003c/w:customXmlPr\u003e\u003c/w:customXml\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[Input: (rubik)\\n\\nrubik: row vector of size 24\\n(The cube started [L=0,U=1,F=2,D=3,B=4,R=5] and then receives forty face moves.\\n\\nOutput: move_vec (Numeric of moves to solve)\\n move_vec:values 1:27 for UFDLBR U'F'D'L'B'R' U2F2D2L2B2R2 XYZX'Y'Z'X2Y2Z2]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eExample:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eIf the cube was randomized by [1 9] UD', one solution is [3 7] which are the complements in reverse order.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eScoring is Time in msec to solve 500 cubes\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eCube Moves X, Y, and Z do not constitute a move but are needed in the vector\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eA string to numeric value function is provided in the template\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eVerifications will be by executing your move vector against the provided Rubik and counting number of face moves.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe function rubik_rot_mini(mov,r) is provided in the template. Other functions are provided to re-orient the cube in Cody Challenge 931, Rubik's Mini-Cube.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe Challenge\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"http://www.mathworks.com/matlabcentral/cody/problems/931-rubik-s-mini-cube-solve-randomized-mini-cube-score-moves.html\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eChallenge 931 Rubik's Mini-Cube\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e contains a 3D Mini-Cube Viewer for program development.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:hyperlink w:docLocation=\\\"http://kociemba.org/cube.htm\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eCube Theory: 20-moves Any Cube\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:hyperlink w:docLocation=\\\"http://peter.stillhq.com/jasmine/rubikscubesolution.html\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eGeneral Cube Info and Middle Layer\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:hyperlink w:docLocation=\\\"http://www.speedcubing.com/final_layer_print.html\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eSpeedCube Bottom Sequences\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe site\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"http://www.speedcubing.com/CubeSolver/MiniCubeSolver.html\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eMiniCube Solver\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e claims an outstanding 10 minutes to solve a randomized Mini-Cube. Matlab can achieve any Mini-Cube solution in \u0026lt; 497 usec, independent of moves on an i5/16GB machine.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e(Note: Mini-Cube can use the full cube moves and ignore edge effects)\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eComing Soon: Matlab 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\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"}],"problem_search":{"errors":[],"problems":[{"id":1995,"title":"Loading/Expanding a ZIP file from File Exchange","description":"This challenge is to load a ZIP file from Mathworks File Exchange and UNZIP the contents.\r\n\r\n*Input:* url_link of ZIP'd file\r\n\r\n*Output:* UNZIPPED MAT file\r\n\r\n*Verification:* filename and size will be confirmed \r\n\r\n*Commentary:* This challenge was inspired by some of my links going dead. Alfonso suggested utilizing File Exchange(FE). My first attempts to load a MAT was unsuccessful due to using the incorrect FE link. The nice matlab unzip function with a valid link led to an efficient method. ","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.4333px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 183px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 91.5px; transform-origin: 407px 91.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 281.217px 7.91667px; transform-origin: 281.217px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThis challenge is to load a ZIP file from Mathworks File Exchange and UNZIP the contents.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 19.4333px 7.91667px; transform-origin: 19.4333px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eInput:\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 60.85px 7.91667px; transform-origin: 60.85px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e url_link of ZIP'd file\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 25.2667px 7.91667px; transform-origin: 25.2667px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eOutput:\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 64.4333px 7.91667px; transform-origin: 64.4333px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e UNZIPPED MAT file\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 40.0667px 7.91667px; transform-origin: 40.0667px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eVerification:\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 110.483px 7.91667px; transform-origin: 110.483px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e filename and size will be confirmed\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 63px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 31.5px; text-align: left; transform-origin: 384px 31.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 45.1333px 7.91667px; transform-origin: 45.1333px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eCommentary:\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 338.433px 7.91667px; transform-origin: 338.433px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e This challenge was inspired by some of my links going dead. Alfonso suggested utilizing File Exchange(FE). My first attempts to load a MAT was unsuccessful due to using the incorrect FE link. The nice matlab unzip function with a valid link led to an efficient method.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function ans=load_file(url_link)\r\n% Link is to a binary zip file\r\n% Load it and unzip to create mat file\r\n dir;\r\nend","test_suite":"%%\r\n%url_link='http://www.mathworks.com/matlabcentral/fileexchange/44314-cody-knotssample-zip-file?download=true';\r\nurl_link='https://www.mathworks.com/matlabcentral/mlc-downloads/downloads/submissions/44314/versions/3/download/zip'\r\n\r\nload_file(url_link);\r\n\r\nz=dir;\r\n\r\nvalid=0;\r\nfor k=1:size(z,1)\r\n if strcmp(z(k).name,'Knots_sample.mat')\r\n  valid=1;\r\n  break;\r\n end\r\nend\r\n\r\nassert(valid==1);\r\nassert(z(k).bytes==58803)\r\n\r\n\r\n\r\n\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":1,"created_by":3097,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":17,"test_suite_updated_at":"2020-10-01T18:26:03.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2013-11-16T03:45:19.000Z","updated_at":"2026-03-16T12:47:34.000Z","published_at":"2013-11-16T04:05:42.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis challenge is to load a ZIP file from Mathworks File Exchange and UNZIP the contents.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eInput:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e url_link of ZIP'd file\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eOutput:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e UNZIPPED MAT file\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eVerification:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e filename and size will be confirmed\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eCommentary:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e This challenge was inspired by some of my links going dead. Alfonso suggested utilizing File Exchange(FE). My first attempts to load a MAT was unsuccessful due to using the incorrect FE link. The nice matlab unzip function with a valid link led to an efficient method.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":60536,"title":"Jigsaw 001: Intro 2x2 square. Pieces 128x128","description":"This challenge is to re-assemble camerman.tif in grayscale from four 128x128 pieces into a 256x256 image.\r\n\r\n\r\nThe pointer layout of the image is [1 3; 2 4].\r\nReturn a four value vector that remaps the scrambled image into an original form.\r\nThe displayed scramble is [2 4 1 3] making the solution [3 1 4 2].\r\nThe four pieces will be provided as matrices in a cell array, along with size of puzzle in pieces and piece size.\r\n\r\n\r\nThis series will explore various puzzle pieces, orientations, sizes,double sided, and ultimately DARPA shredder data.\r\nMultiple methods are provided in the template to achieve re-mapping. Which will work and which will fail?","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.4333px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 522.5px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 261.25px; transform-origin: 407px 261.25px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 338px 8px; transform-origin: 338px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThis challenge is to re-assemble camerman.tif in grayscale from four 128x128 pieces into a 256x256 image.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan 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\" 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\" data-image-state=\"image-loaded\" width=\"289\" height=\"217\"\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 137.5px 8px; transform-origin: 137.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThe pointer layout of the image is [1 3; 2 4].\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 256px 8px; transform-origin: 256px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eReturn a four value vector that remaps the scrambled image into an original form.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 203px 8px; transform-origin: 203px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThe displayed scramble is [2 4 1 3] making the solution [3 1 4 2].\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 340px 8px; transform-origin: 340px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThe four pieces will be provided as matrices in a cell array, along with size of puzzle in pieces and piece size.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 8px; transform-origin: 0px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 8px; transform-origin: 0px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 363.5px 8px; transform-origin: 363.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThis series will explore various puzzle pieces, orientations, sizes,double sided, and ultimately DARPA shredder data.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 326.5px 8px; transform-origin: 326.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eMultiple methods are provided in the template to achieve re-mapping. Which will work and which will fail?\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function v = jigsaw001(pc,nr,nc,pnr,pnc)\r\n% pc cell array of jigsaw pieces, all the same size and double\r\n% nr,nc  Jigsaw piece counts rows and columns\r\n% pnr,pnc Jigsaw piece size row pixels, col pixels\r\n\r\n %Four scoring methods created\r\n % 1 sum of abs delta       \r\n % 2 sum of (abs delta)^2   \r\n % 3 sum of (abs delta)^0.5 \r\n % 4 median of abs delta    \r\n %\r\n\r\n% Brute force\r\n %Try all piece permutations and score the piece edges\r\n  v=1:nr*nc; % Total pieces\r\n  vperms=perms(1:nr*nc);\r\n  [vnr,vnc]=size(vperms);\r\n  m=zeros(nr*pnr,nc*pnc); %matrix to hold created image\r\n  \r\n  best_score=inf;\r\n  for i=1:vnr % cycle thru all permutations\r\n   vidx=vperms(i,:);\r\n   m=[pc{vidx(1)} pc{vidx(3)};pc{vidx(2)} pc{vidx(4)}];\r\n   \r\n % Four scoring methods created\r\n   score=sum(abs(m(pnr,:)-m(pnr+1,:)))+sum(abs(m(:,pnc)-m(:,pnc+1))); % Method 1\r\n   %score=sum(abs(m(pnr,:)-m(pnr+1,:)).^2)+sum(abs(m(:,pnc)-m(:,pnc+1)).^2); % Method 2\r\n   %score=sum(abs(m(pnr,:)-m(pnr+1,:)).^.5)+sum(abs(m(:,pnc)-m(:,pnc+1)).^.5); % Method 3\r\n   \r\n   %sort_score=sort([abs(m(pnr,:)-m(pnr+1,:)) [abs(m(:,pnc)-m(:,pnc+1))]']); %Method 4\r\n   %score=sort_score(256);  %Median delta                                    %Method 4\r\n   \r\n   %fprintf('%i %i %i %i Score: %.2f\\n',vidx,score);\r\n   if score\u003cbest_score\r\n    v=vidx;\r\n    best_score=score;\r\n    %fprintf('New Best score\\n');\r\n   end\r\n   \r\n  end % i vperms vnr\r\n  \r\nend %jigsaw001","test_suite":"%%\r\n% all imdata 2019 are hosted for cody at https://drive.google.com/drive/folders/1TZkBMEEKHiFJExqVoJgj5VVeHbvOfTYB\r\n% a Text file of matlab urlwrite links will be added in the future\r\n%camerman.tif\r\n%https://drive.google.com/uc?export=download\u0026id=1WNWSIp29e_BM47RSiNwom9zMSUTUVKv7\r\n% future will show cody matlab imdata location and how to access\r\n\r\nurl='https://drive.google.com/uc?export=download\u0026id=1WNWSIp29e_BM47RSiNwom9zMSUTUVKv7'; \r\nfname='cameraman.tif';\r\n%tic\r\nurlwrite(url,fname);\r\n%toc\r\n%dir\r\n%figure;imshow('cameraman.tif') % valid\r\n\r\nm_cameraman=imread('cameraman.tif');\r\nm_cameraman=double(m_cameraman);\r\n\r\n%{\r\nd1=sum(abs(m_cameraman(:,128)-m_cameraman(:,129)));\r\nd2=sum(abs(m_cameraman(:,1)-m_cameraman(:,256)));\r\nfprintf('col delta scr: 128:129 %.2f  256:1 %.2f\\n',d1,d2);\r\n\r\nd1=sum((abs(m_cameraman(:,128)-m_cameraman(:,129))).^.5);\r\nd2=sum((abs(m_cameraman(:,1)-m_cameraman(:,256))).^.5);\r\nfprintf('col root scr: 128:129 %.2f  256:1 %.2f\\n',d1,d2);\r\n%}\r\n\r\n\r\nfprintf('Original image\\n');\r\nfigure;imagesc(m_cameraman);colormap gray %\r\n\r\n%{\r\nfigure;plot(1:256,abs(m_cameraman(:,128)-m_cameraman(:,129)));hold on\r\nplot(1:256,sort(abs(m_cameraman(:,128)-m_cameraman(:,129))));\r\n\r\nfigure;plot(1:256,abs(m_cameraman(:,1)-m_cameraman(:,256)));hold on\r\nplot(1:256,sort(abs(m_cameraman(:,1)-m_cameraman(:,256))));\r\n\r\nfigure;plot(1:256,(abs(m_cameraman(:,128)-m_cameraman(:,129))).^.5);hold on\r\nplot(1:256,sort((abs(m_cameraman(:,128)-m_cameraman(:,129))).^.5));\r\n\r\nfigure;plot(1:256,(abs(m_cameraman(:,1)-m_cameraman(:,256))).^.5);hold on\r\nplot(1:256,sort((abs(m_cameraman(:,1)-m_cameraman(:,256))).^.5));\r\n%}\r\n\r\n%size(m_cameraman) % 256 256\r\n\r\nnr=2;nc=2;\r\npnr=128;pnc=128;\r\nTotal_pieces=nr*nc;\r\npc{Total_pieces}=[];\r\n\r\nptr=0;\r\nfor c=1:nc\r\n for r=1:nr\r\n  p=m_cameraman(1+(r-1)*pnr:r*pnr,1+(c-1)*pnc:c*pnc);\r\n  ptr=ptr+1;\r\n  pc{ptr}=p;\r\n end\r\nend\r\n\r\nvperm=1:nr*nc;\r\nwhile nnz((vperm-[1:nr*nc])==0) % want each piece moved\r\n vperm=randperm(nr*nc);\r\nend\r\n\r\nfor i=1:Total_pieces % scramble puzzle pieces\r\n jpc{i}=pc{vperm(i)};\r\nend\r\n\r\n% scrambled image\r\njigsaws=[jpc{1} jpc{3};jpc{2} jpc{4}];\r\nfprintf('Scrambled image\\n')\r\nfigure;imagesc(jigsaws);colormap gray %\r\n\r\nv = jigsaw001(jpc,nr,nc,pnr,pnc);\r\n\r\njigsawf=[jpc{v(1)} jpc{v(3)};jpc{v(2)} jpc{v(4)}];\r\n\r\nfprintf('Final image\\n');\r\nfigure;imagesc(jigsawf);colormap gray %\r\n\r\nassert(isequal(jigsawf,m_cameraman))\r\n\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":3097,"edited_by":3097,"edited_at":"2024-06-14T22:50:25.000Z","deleted_by":null,"deleted_at":null,"solvers_count":5,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2024-06-14T16:43:17.000Z","updated_at":"2025-03-02T14:00:42.000Z","published_at":"2024-06-14T22:50:26.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis challenge is to re-assemble camerman.tif in grayscale from four 128x128 pieces into a 256x256 image.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:customXml w:element=\\\"image\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"height\\\" w:val=\\\"217\\\"/\u003e\u003cw:attr w:name=\\\"width\\\" w:val=\\\"289\\\"/\u003e\u003cw:attr w:name=\\\"verticalAlign\\\" w:val=\\\"baseline\\\"/\u003e\u003cw:attr w:name=\\\"altText\\\" w:val=\\\"\\\"/\u003e\u003cw:attr w:name=\\\"relationshipId\\\" w:val=\\\"rId1\\\"/\u003e\u003c/w:customXmlPr\u003e\u003c/w:customXml\u003e\u003cw:customXml w:element=\\\"image\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"height\\\" w:val=\\\"217\\\"/\u003e\u003cw:attr w:name=\\\"width\\\" w:val=\\\"289\\\"/\u003e\u003cw:attr w:name=\\\"verticalAlign\\\" w:val=\\\"baseline\\\"/\u003e\u003cw:attr w:name=\\\"altText\\\" w:val=\\\"\\\"/\u003e\u003cw:attr w:name=\\\"relationshipId\\\" w:val=\\\"rId2\\\"/\u003e\u003c/w:customXmlPr\u003e\u003c/w:customXml\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe pointer layout of the image is [1 3; 2 4].\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eReturn a four value vector that remaps the scrambled image into an original form.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe displayed scramble is [2 4 1 3] making the solution [3 1 4 2].\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe four pieces will be provided as matrices in a cell array, along with size of puzzle in pieces and piece size.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis series will explore various puzzle pieces, orientations, sizes,double sided, and ultimately DARPA shredder data.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eMultiple methods are provided in the template to achieve re-mapping. Which will work and which will 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\",\"relationship\":null},{\"partUri\":\"/media/image2.png\",\"contentType\":\"image/png\",\"content\":\"data:image/png;base64,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\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":58503,"title":"Google Drive file download","description":"This Challenge is to download a file from GoogleDrive given its \"copylink\" provided URL and a file name.\r\nGoogleDrive links fail for Matlab function like urlwrite, imread, imwrite, webread, and others. \r\nThe file 2.png is given by https://drive.google.com/file/d/1v3GsGgP3p905wzdvUqypL_-djYmxiyzK/view?usp=drive_link, which will bring up the file in a new window but this URL fails for matlab commands.\r\nThe GoogleDrive file must be \"Shared\" . The file must at least have share to those \"anyone with this link\".\r\nTo enable file download the Google URL string must be modified:\r\n 1) Delete the end '/view?usp=*'; Anything after and inlcuding \"/view\" must be deleted\r\n 2) Replace 'file/d/' with 'uc?export=download\u0026id='\r\n\r\nGiven a URL and filename download the URL contents into a file called filename in the local Cody directory.\r\nVerification will be done by file name and file size.\r\n\r\n","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.4333px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 372px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 186px; transform-origin: 407px 186px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 327px 8px; transform-origin: 327px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThis Challenge is to download a file from GoogleDrive given its \"copylink\" provided URL and a file name.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 288px 8px; transform-origin: 288px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eGoogleDrive links fail for Matlab function like urlwrite, imread, imwrite, webread, and others. \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 21px; text-align: left; transform-origin: 384px 21px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 81px 8px; transform-origin: 81px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThe file 2.png is given by \u003c/span\u003e\u003c/span\u003e\u003ca target='_blank' href = \"https://drive.google.com/file/d/1v3GsGgP3p905wzdvUqypL_-djYmxiyzK/view?usp=drive_link,\"\u003e\u003cspan style=\"\"\u003e\u003cspan style=\"\"\u003ehttps://drive.google.com/file/d/1v3GsGgP3p905wzdvUqypL_-djYmxiyzK/view?usp=drive_link,\u003c/span\u003e\u003c/span\u003e\u003c/a\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 2px 8px; transform-origin: 2px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e which will bring up the file in a new window but this URL fails for matlab commands.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 330.5px 8px; transform-origin: 330.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThe GoogleDrive file must be \"Shared\" . The file must at least have share to those \"anyone with this link\".\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 203.5px 8px; transform-origin: 203.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eTo enable file download the Google URL string must be modified:\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 266.5px 8px; transform-origin: 266.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e 1) Delete the end '/view?usp=*'; Anything after and inlcuding \"/view\" must be deleted\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 156.5px 8px; transform-origin: 156.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e 2) Replace 'file/d/' with 'uc?export=download\u0026amp;id='\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 8px; transform-origin: 0px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 336px 8px; transform-origin: 336px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eGiven a URL and filename download the URL contents into a file called filename in the local Cody directory.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 154.5px 8px; transform-origin: 154.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eVerification will be done by file name and file size.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 8px; transform-origin: 0px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 8px; transform-origin: 0px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function url=GoogleDrive_urlwrite(url,fname)\r\n% The GoogleDrive \"copy link\" does not play well with matlab urlwrite/imread/imwrite/webread/... \r\n% Expect 'https://drive.google.com/file/d/1WDYDJJZ3wJ8Fs0-8E2u6bYxlZbOapNJn/view?usp=drive_link'\r\n% 1) Delete the end '/view...'\r\n% 2) Replace 'file/d/' with 'uc?export=download\u0026id='\r\n \r\n %urlwrite(url,fname);\r\nend","test_suite":"%%\r\n%Google Drive Dowloads need to come from shared files\r\n% Tweak link: file/d/ to uc?export=download\u0026id=   while removing /view?usp=sharing\r\n% https://drive.google.com/file/d/1v3GsGgP3p905wzdvUqypL_-djYmxiyzK/view?usp=sharing\r\n% https://drive.google.com/uc?export=download\u0026id=1v3GsGgP3p905wzdvUqypL_-djYmxiyzK\r\n\r\n\r\n%2.png Robot\r\nurl='https://drive.google.com/file/d/1v3GsGgP3p905wzdvUqypL_-djYmxiyzK/view?usp=drive_link';\r\nfname='2.png'; \r\nfile_size=7025; % bytes \r\n\r\nfprintf('******Initial Test 1 Dir:\\n\\n')\r\ndir % Initial Dir\r\n\r\nGoogleDrive_urlwrite(url,fname); %expect  7025 bytes for 2.png\r\n\r\nfprintf('Dir after first call:\\n\\n')\r\ndir\r\ndir_struct=dir\r\nvalid=0;\r\nfor i=1:length(dir_struct)\r\n fprintf('%i %s %i\\n',i,dir_struct(i).name,dir_struct(i).bytes)\r\n if isequal(dir_struct(i).name,fname)  % contains(dir_struct(i).name,fname)\r\n  if dir_struct(i).bytes==file_size\r\n   valid=1;\r\n   break;\r\n  end\r\n end\r\nend\r\n\r\nassert(valid)\r\n%%\r\n%28.png Starry Night\r\nurl='https://drive.google.com/file/d/1WDYDJJZ3wJ8Fs0-8E2u6bYxlZbOapNJn/view?usp=drive_link';\r\nfname='28.png'; \r\nfile_size=58061; % bytes \r\n\r\nfprintf('\\n***** Test 2 start Dir:\\n\\n')\r\ndir % Test 2 Dir\r\n\r\nGoogleDrive_urlwrite(url,fname); %expect  58061 bytes for 28.png\r\n\r\nfprintf('Dir after second Call:\\n\\n')\r\ndir\r\ndir_struct=dir\r\nvalid=0;\r\nfor i=1:length(dir_struct)\r\n fprintf('%i %s %i\\n',i,dir_struct(i).name,dir_struct(i).bytes)\r\n if isequal(dir_struct(i).name,fname)  % contains(dir_struct(i).name,fname)\r\n  if dir_struct(i).bytes==file_size\r\n   valid=1;\r\n   break;\r\n  end\r\n end\r\nend\r\n\r\nassert(valid)\r\n%%\r\n%cube_small.gif Rubiks Cube\r\nurl='https://drive.google.com/file/d/1N3p9M6WKGXqD3lilYuv-sUKTkGGI66Xk/view?usp=drive_link';\r\nfname='cube_small.gif'; \r\nfile_size=3812; % bytes \r\n\r\nfprintf('\\n***** Test 3 Dir:\\n\\n\\n')\r\ndir % Initial Dir\r\n\r\nGoogleDrive_urlwrite(url,fname); %expect   bytes for cube_small.gif\r\n\r\nfprintf('Dir after third call:\\n\\n')\r\ndir\r\ndir_struct=dir\r\nvalid=0;\r\nfor i=1:length(dir_struct)\r\n fprintf('%i %s %i\\n',i,dir_struct(i).name,dir_struct(i).bytes)\r\n if isequal(dir_struct(i).name,fname)  % contains(dir_struct(i).name,fname)\r\n  if dir_struct(i).bytes==file_size\r\n   valid=1;\r\n   break;\r\n  end\r\n end\r\nend\r\n\r\nassert(valid)","published":true,"deleted":false,"likes_count":1,"comments_count":2,"created_by":3097,"edited_by":3097,"edited_at":"2023-07-13T17:33:19.000Z","deleted_by":null,"deleted_at":null,"solvers_count":7,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2023-07-13T14:26:50.000Z","updated_at":"2023-07-13T17:33:19.000Z","published_at":"2023-07-13T16:15:25.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis Challenge is to download a file from GoogleDrive given its \\\"copylink\\\" provided URL and a file name.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGoogleDrive links fail for Matlab function like urlwrite, imread, imwrite, webread, and others. \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe file 2.png is given by \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"https://drive.google.com/file/d/1v3GsGgP3p905wzdvUqypL_-djYmxiyzK/view?usp=drive_link,\\\"\u003e\u003cw:r\u003e\u003cw:t\u003ehttps://drive.google.com/file/d/1v3GsGgP3p905wzdvUqypL_-djYmxiyzK/view?usp=drive_link,\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e which will bring up the file in a new window but this URL fails for matlab commands.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe GoogleDrive file must be \\\"Shared\\\" . The file must at least have share to those \\\"anyone with this link\\\".\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eTo enable file download the Google URL string must be modified:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e 1) Delete the end '/view?usp=*'; Anything after and inlcuding \\\"/view\\\" must be deleted\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e 2) Replace 'file/d/' with 'uc?export=download\u0026amp;id='\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGiven a URL and filename download the URL contents into a file called filename in the local Cody directory.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eVerification will be done by file name and file size.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":58513,"title":"Google Drive:  MATLAB mat file download","description":"Matlab 'mat' files are notoriously hard to email and download as they are binary files.\r\nTo make a 'mat' file downloadable from Google Drive requires a trick.\r\nCopy the 'mat' file and change its extension to 'PDF'. Place this 'PDF' on the Google Drive.\r\nTo download this file into 'mat' form use urlwrite with a Google Drive url, which will need to be fixed, and a destination fname ending in '.mat'\r\n\r\nThis Challenge is to download a file given a GoogleDrive link  and a fname, ending in '.mat', to the local directory. \r\nThe file for this URL ends in 'PDF' on a GoogleDrive.\r\nVerification will be done by loading the fname and verifying the size. This file is the ICFP2023 Orchestra Problem set compressed 90% as a mat file.","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.4333px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 273px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 136.5px; transform-origin: 407px 136.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 265.5px 8px; transform-origin: 265.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eMatlab 'mat' files are notoriously hard to email and download as they are binary files.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 216px 8px; transform-origin: 216px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eTo make a 'mat' file downloadable from Google Drive requires a trick.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 284.5px 8px; transform-origin: 284.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eCopy the 'mat' file and change its extension to 'PDF'. Place this 'PDF' on the Google Drive.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 21px; text-align: left; transform-origin: 384px 21px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 366.5px 8px; transform-origin: 366.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eTo download this file into 'mat' form use urlwrite with a Google Drive url, which will need to be fixed, and a destination fname ending in '.mat'\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 8px; transform-origin: 0px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 357px 8px; transform-origin: 357px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThis Challenge is to download a file given a GoogleDrive link  and a fname, ending in '.mat', to the local directory. \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 166px 8px; transform-origin: 166px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThe file for this URL ends in 'PDF' on a GoogleDrive.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 21px; text-align: left; transform-origin: 384px 21px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 366px 8px; transform-origin: 366px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eVerification will be done by loading the fname and verifying the size. This file is the ICFP2023 Orchestra Problem set compressed 90% as a mat file.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function url=GoogleDrive_urlwrite(url,fname)\r\n% The GoogleDrive \"copy link\" does not play well with matlab urlwrite/imread/imwrite/webread/... \r\n% Expect 'https://drive.google.com/file/d/1WDYDJJZ3wJ8Fs0-8E2u6bYxlZbOapNJn/view?usp=drive_link'\r\n% 1) Delete the end '/view...'\r\n% 2) Replace 'file/d/' with 'uc?export=download\u0026id='\r\n\r\n%This Challenge gives a URL for a .mat file that was saved as a .PDF on the googledrive.\r\n \r\n %urlwrite(url,fname);\r\nend","test_suite":"%%\r\nurl='https://drive.google.com/file/d/1mgxzsmVQNXgqHEdd61QR2r0STm3N9lgG/view?usp=drive_link';\r\nfname='orc_d_mu_axy_am_pxyr.mat';\r\ntic\r\nGoogleDrive_urlwrite(url,fname);\r\nfprintf('Process/Download Time: %.1f sec\\n',toc);\r\n\r\nload(fname); % This loads the cell array orc\r\n\r\nz=dir;\r\nfprintf('Local Directory: Filenames      Sizes\\n');\r\nfor i=1:length(z)\r\n fprintf('%30s  %i\\n',z(i).name,z(i).bytes);\r\nend\r\nfprintf('\\n\\n');\r\n\r\nfprintf('Size orc: %i %i\\n',size(orc));\r\n\r\nfprintf('\\n\\n orc{end}\\n');\r\norc{end}\r\n\r\nvalid=isequal([1 90],size(orc));\r\nassert(valid)\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":1,"created_by":3097,"edited_by":3097,"edited_at":"2023-07-13T18:21:49.000Z","deleted_by":null,"deleted_at":null,"solvers_count":8,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2023-07-13T17:45:26.000Z","updated_at":"2023-07-13T18:21:49.000Z","published_at":"2023-07-13T18:21:49.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eMatlab 'mat' files are notoriously hard to email and download as they are binary files.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eTo make a 'mat' file downloadable from Google Drive requires a trick.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eCopy the 'mat' file and change its extension to 'PDF'. Place this 'PDF' on the Google Drive.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eTo download this file into 'mat' form use urlwrite with a Google Drive url, which will need to be fixed, and a destination fname ending in '.mat'\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis Challenge is to download a file given a GoogleDrive link  and a fname, ending in '.mat', to the local directory. \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe file for this URL ends in 'PDF' on a GoogleDrive.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eVerification will be done by loading the fname and verifying the size. This file is the ICFP2023 Orchestra Problem set compressed 90% as a mat file.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":699,"title":"Reading Web Binary Files (jpg,pdf,tiff,png)","description":"The Challenge is to access a Web binary file, a PDF in this case, and provide the value of a specific byte.\r\n\r\n.\r\n\r\nAccessing files on the web provide multiple challenges due to the data structures being text or binary.\r\n\r\nThe functions urlread and urlwrite both access web files but provide different results for binary files. (jpg, pdf, tiff, png, ppt)\r\n\r\n\r\n\r\nInput:\r\n\r\nfname 'http://some valid location/file.pdf'\r\n\r\nn      The byte for which the value is being requested.\r\n\r\nOutput: Value of the byte, an integer ranging from 0 to 255\r\n\r\n.\r\n\r\n\r\nA solution exists in the test suite to show the different data created by urlread and urlwrite for binary data.\r\n\r\nA urlreadbin can be readily created to directly push the file to an array.","description_html":"\u003cp\u003eThe Challenge is to access a Web binary file, a PDF in this case, and provide the value of a specific byte.\u003c/p\u003e\u003cp\u003e.\u003c/p\u003e\u003cp\u003eAccessing files on the web provide multiple challenges due to the data structures being text or binary.\u003c/p\u003e\u003cp\u003eThe functions urlread and urlwrite both access web files but provide different results for binary files. (jpg, pdf, tiff, png, ppt)\u003c/p\u003e\u003cp\u003eInput:\u003c/p\u003e\u003cp\u003efname 'http://some valid location/file.pdf'\u003c/p\u003e\u003cp\u003en      The byte for which the value is being requested.\u003c/p\u003e\u003cp\u003eOutput: Value of the byte, an integer ranging from 0 to 255\u003c/p\u003e\u003cp\u003e.\u003c/p\u003e\u003cp\u003eA solution exists in the test suite to show the different data created by urlread and urlwrite for binary data.\u003c/p\u003e\u003cp\u003eA urlreadbin can be readily created to directly push the file to an array.\u003c/p\u003e","function_template":"function y = access_web_pdf(fname,n)\r\n  y = 0;\r\nend","test_suite":"%%\r\n% Cody External accessibility\r\n\r\n% This file may need to change in the future\r\nin_f='http://www.pvplc.org/_volunteer/docs/PVPLC%20Trail%20Crew%20Training%20Jan-Jun%202012.pdf';\r\n\r\nout_f='PVPLC.pdf';\r\n\r\nurlwrite(in_f,out_f);\r\n\r\nfid=fopen(out_f);\r\nurlwrite_out=fread(fid,128,'*uint8'); \r\n% Display Correct Binary Data\r\nurlwrite_out(1:16)'\r\n\r\n\r\nblock=urlread(in_f);\r\n% Display invalid binary data\r\nurlread_out=block(1:16)-char(0)\r\n% unicode urlread conversion affects bytes 12 thru 15\r\n\r\nn=12\r\nbyte_val = access_web_pdf(in_f,n)\r\n\r\nbyte_correct=181;\r\n\r\nassert(isequal(byte_val,byte_correct))\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":1,"created_by":3097,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":11,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2012-05-18T04:26:21.000Z","updated_at":"2012-05-21T05:35:07.000Z","published_at":"2012-05-21T05:35:07.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe Challenge is to access a Web binary file, a PDF in this case, and provide the value of a specific byte.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eAccessing files on the web provide multiple challenges due to the data structures being text or binary.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe functions urlread and urlwrite both access web files but provide different results for binary files. (jpg, pdf, tiff, png, ppt)\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eInput:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003efname 'http://some valid location/file.pdf'\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003en The byte for which the value is being requested.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eOutput: Value of the byte, an integer ranging from 0 to 255\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eA solution exists in the test suite to show the different data created by urlread and urlwrite for binary data.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eA urlreadbin can be readily created to directly push the file to an array.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":1097,"title":"USC Fall 2012 ACM Question A : Read Input File","description":"This Challenge is to read the Question A input text file of the \u003chttp://contest.usc.edu/index.php/Fall12/Home USC ACM Fall 2012 Contest\u003e.\r\n\r\nThe text format is: Number of sets,RowsSet1 ColsSet1,Array1, Vector1, RowsSet2 ColsSet2, Array2, Vector2\r\n\r\neg:Two data sets of arrays 3x3 and 2x4\r\n\r\n  2\r\n  3 3\r\n  000\r\n  111\r\n  110\r\n  010\r\n  2 4\r\n  1010\r\n  1100\r\n  0001\r\n\r\n\r\nThe USC input file has 17 data sets.\r\n\r\nInput: [ url_filename, k],  k= array data set to return\r\n\r\nOutput: Selected data set Array\r\n\r\nExample: [ \u003chttp://contest.usc.edu/index.php/Fall12/Home?action=download\u0026upname=codes.in.txt\u003e, 1]\r\n\r\nOutput:\r\n[0 0 0; 1 1 1; 1 1 0]\r\n\r\nHow will the Pros read and process the text file?\r\n\r\nFollow up Challenge will be solving the actual ACM question.\r\n\r\n\r\n\r\n","description_html":"\u003cp\u003eThis Challenge is to read the Question A input text file of the \u003ca href=\"http://contest.usc.edu/index.php/Fall12/Home\"\u003eUSC ACM Fall 2012 Contest\u003c/a\u003e.\u003c/p\u003e\u003cp\u003eThe text format is: Number of sets,RowsSet1 ColsSet1,Array1, Vector1, RowsSet2 ColsSet2, Array2, Vector2\u003c/p\u003e\u003cp\u003eeg:Two data sets of arrays 3x3 and 2x4\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003e2\r\n3 3\r\n000\r\n111\r\n110\r\n010\r\n2 4\r\n1010\r\n1100\r\n0001\r\n\u003c/pre\u003e\u003cp\u003eThe USC input file has 17 data sets.\u003c/p\u003e\u003cp\u003eInput: [ url_filename, k],  k= array data set to return\u003c/p\u003e\u003cp\u003eOutput: Selected data set Array\u003c/p\u003e\u003cp\u003eExample: [ \u003ca href=\"http://contest.usc.edu/index.php/Fall12/Home?action=download\u0026amp;upname=codes.in.txt\"\u003ehttp://contest.usc.edu/index.php/Fall12/Home?action=download\u0026upname=codes.in.txt\u003c/a\u003e, 1]\u003c/p\u003e\u003cp\u003eOutput:\r\n[0 0 0; 1 1 1; 1 1 0]\u003c/p\u003e\u003cp\u003eHow will the Pros read and process the text file?\u003c/p\u003e\u003cp\u003eFollow up Challenge will be solving the actual ACM question.\u003c/p\u003e","function_template":"function A = USC_file(urlfn,ptr)\r\n% urlfn is 'http://contest.usc.edu/index.php/Fall12/Home?action=download\u0026upname=codes.in.txt';\r\n\r\n urlwrite(urlfn,'codesinput.txt');\r\n A=[];\r\n\r\nend","test_suite":"%%\r\ntic\r\nurlfn='http://contest.usc.edu/index.php/Fall12/Home?action=download\u0026upname=codes.in.txt';\r\nurlwrite(urlfn,'codesin_A.txt'); % Load file from USC\r\ntoc\r\n\r\nfor trial=1:3\r\n\r\n ptr=randi(17);\r\n\r\n A_USC = USC_file(urlfn,ptr);\r\n\r\n fid=fopen('codesin_A.txt','r');\r\n\r\n qty=fscanf(fid,'%i',1);\r\n for q=1:ptr\r\n  nr=fscanf(fid,'%i',1);\r\n  nc=fscanf(fid,'%i',1);\r\n \r\n  A=zeros(nr,nc);\r\n  for i=1:nr\r\n   strv=fscanf(fid,'%s',1); % Reads a line of text\r\n   A(i,:)=strv-'0'; % vectorize the string\r\n  end\r\n \r\n  strv=fscanf(fid,'%s',1);\r\n  Test=strv-'0';\r\n \r\n end\r\n fclose(fid);\r\n \r\n assert(isequal(A,A_USC))\r\n \r\nend % trial\r\n \r\n\r\ntoc\r\n\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":3097,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":9,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2012-12-06T00:57:32.000Z","updated_at":"2012-12-06T02:39:34.000Z","published_at":"2012-12-06T02:37:29.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis Challenge is to read the Question A input text file of the\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"http://contest.usc.edu/index.php/Fall12/Home\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eUSC ACM Fall 2012 Contest\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe text format is: Number of sets,RowsSet1 ColsSet1,Array1, Vector1, RowsSet2 ColsSet2, Array2, Vector2\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eeg:Two data sets of arrays 3x3 and 2x4\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[2\\n3 3\\n000\\n111\\n110\\n010\\n2 4\\n1010\\n1100\\n0001]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe USC input file has 17 data sets.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eInput: [ url_filename, k], k= array data set to return\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eOutput: Selected data set Array\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eExample: [\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"http://contest.usc.edu/index.php/Fall12/Home?action=download\u0026amp;upname=codes.in.txt\\\"\u003e\u003cw:r\u003e\u003cw:t\u003e\u0026lt;http://contest.usc.edu/index.php/Fall12/Home?action=download\u0026amp;upname=codes.in.txt\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e\u0026gt;, 1]\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eOutput: [0 0 0; 1 1 1; 1 1 0]\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eHow will the Pros read and process the text file?\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFollow up Challenge will be solving the actual ACM question.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":781,"title":"Access a web hosted copy of the Tiles Contest MAT file","description":"Access a web hosted copy of the Tiles Contest sample \"mat\" and verify success by returning for a board the number of tiles, number of rows, and number of columns of the board.\r\n\r\nDetails of the Tiles Contest can be found at \u003chttp://www.mathworks.com/matlabcentral/contest/contests/36 Tiles Contest\u003e.\r\n\r\nThe runcontest.m provides testsuite structure information.\r\n\r\n*Input:* (urlfname, board)\r\n\r\nfn='http://www.toobigforemail.com/cryptkeeper.toobig?nppmkc2=xyeffg\u00266cq_kc2=yae1d8\u00266cq_konmpb=y88ayxyx8xxy1xdyx'\r\n\r\n*Output:* (number of tiles, nrows, ncols)\r\n\r\nFor board 99\r\n\r\n[ 20 10 8 ]\r\n\r\n\r\n\r\nNote: The mat file is a very efficiently packed binary file.\r\n\r\nFollow-up questions will be creation of a mat file and a timed contest for a few of the perfectly solveable Tile boards","description_html":"\u003cp\u003eAccess a web hosted copy of the Tiles Contest sample \"mat\" and verify success by returning for a board the number of tiles, number of rows, and number of columns of the board.\u003c/p\u003e\u003cp\u003eDetails of the Tiles Contest can be found at \u003ca href=\"http://www.mathworks.com/matlabcentral/contest/contests/36\"\u003eTiles Contest\u003c/a\u003e.\u003c/p\u003e\u003cp\u003eThe runcontest.m provides testsuite structure information.\u003c/p\u003e\u003cp\u003e\u003cb\u003eInput:\u003c/b\u003e (urlfname, board)\u003c/p\u003e\u003cp\u003efn='http://www.toobigforemail.com/cryptkeeper.toobig?nppmkc2=xyeffg\u00266cq_kc2=yae1d8\u00266cq_konmpb=y88ayxyx8xxy1xdyx'\u003c/p\u003e\u003cp\u003e\u003cb\u003eOutput:\u003c/b\u003e (number of tiles, nrows, ncols)\u003c/p\u003e\u003cp\u003eFor board 99\u003c/p\u003e\u003cp\u003e[ 20 10 8 ]\u003c/p\u003e\u003cp\u003eNote: The mat file is a very efficiently packed binary file.\u003c/p\u003e\u003cp\u003eFollow-up questions will be creation of a mat file and a timed contest for a few of the perfectly solveable Tile boards\u003c/p\u003e","function_template":"function out = access_url_mat(urlfname,brd)\r\n \r\n %tiles=tests.testsuite(brd).tiles;\r\n\r\n ntiles=1;nrow=1;ncol=1;\r\n \r\n out=[ntiles nrow ncol];\r\n\r\nend","test_suite":"%%\r\n% Cody External accessibility\r\ny=clock;\r\nrand('state',floor(10000*y(6)))\r\nbrd=randi(100,1)\r\n\r\nfn='http://www.toobigforemail.com/cryptkeeper.toobig?nppmkc2=xyeffg\u00266cq_kc2=yae1d8\u00266cq_konmpb=y88ayxyx8xxy1xdyx';\r\n\r\nfn='http://tinyurl.com/matlab-tiles-mat';\r\ntestSuiteFile = 'raz_tiles.mat';\r\nurlwrite(fn,testSuiteFile);\r\n\r\ntests = load(testSuiteFile,'testsuite');\r\n\r\ntiles = tests.testsuite(brd).tiles;\r\nrows = tests.testsuite(brd).r;\r\ncols = tests.testsuite(brd).c;\r\n\r\nexpected=[size(tiles,1) rows cols]\r\n\r\nout=access_url_mat(fn,brd)\r\n\r\nassert(isequal(out,expected))\r\n%%\r\nbrd=randi(100,1)\r\n\r\nfn='http://www.toobigforemail.com/cryptkeeper.toobig?nppmkc2=xyeffg\u00266cq_kc2=yae1d8\u00266cq_konmpb=y88ayxyx8xxy1xdyx';\r\n\r\nfn='http://tinyurl.com/matlab-tiles-mat';\r\ntestSuiteFile = 'raz_tiles.mat';\r\nurlwrite(fn,testSuiteFile);\r\n\r\ntests = load(testSuiteFile,'testsuite');\r\n\r\ntiles = tests.testsuite(brd).tiles;\r\nrows = tests.testsuite(brd).r;\r\ncols = tests.testsuite(brd).c;\r\n\r\nexpected=[size(tiles,1) rows cols]\r\n\r\nout=access_url_mat(fn,brd)\r\n\r\nassert(isequal(out,expected))\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":2,"created_by":3097,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":7,"test_suite_updated_at":"2012-11-22T12:22:58.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2012-06-21T04:54:17.000Z","updated_at":"2025-10-25T08:50:10.000Z","published_at":"2012-06-22T04:40:01.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eAccess a web hosted copy of the Tiles Contest sample \\\"mat\\\" and verify success by returning for a board the number of tiles, number of rows, and number of columns of the board.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eDetails of the Tiles Contest can be found at\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"http://www.mathworks.com/matlabcentral/contest/contests/36\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eTiles Contest\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe runcontest.m provides testsuite structure information.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eInput:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e (urlfname, board)\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003efn='http://www.toobigforemail.com/cryptkeeper.toobig?nppmkc2=xyeffg\u0026amp;6cq_kc2=yae1d8\u0026amp;6cq_konmpb=y88ayxyx8xxy1xdyx'\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eOutput:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e (number of tiles, nrows, ncols)\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFor board 99\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e[ 20 10 8 ]\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eNote: The mat file is a very efficiently packed binary file.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFollow-up questions will be creation of a mat file and a timed contest for a few of the perfectly solveable Tile boards\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":46686,"title":"Kaggle: Planetoid Game of Life - Solve 3000 of 50000 Puzzles","description":null,"description_html":"\u003cdiv style = \"text-align: start; line-height: 20.4333px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 419.167px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 209.583px; transform-origin: 407px 209.583px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 84px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 42px; text-align: left; transform-origin: 384px 42px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003ca target='_blank' href = \"https://www.kaggle.com/c/conways-reverse-game-of-life-2020\"\u003e\u003cspan style=\"\"\u003e\u003cspan style=\"\"\u003eKaggle's Conway's Reverse Game of Life 2020 \u003c/span\u003e\u003c/span\u003e\u003c/a\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 203.05px 7.91667px; transform-origin: 203.05px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003econtest inspires this Life challenge. The kaggle contest runs from Oct-01-2020 thru Nov-30-2020. References:\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 1.95px 7.91667px; transform-origin: 1.95px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e \u003c/span\u003e\u003c/span\u003e\u003ca target='_blank' href = \"http://mathworld.wolfram.com/GameofLife.html\"\u003e\u003cspan style=\"\"\u003e\u003cspan style=\"\"\u003eGame of Life at Wolfram\u003c/span\u003e\u003c/span\u003e\u003c/a\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 1.95px 7.91667px; transform-origin: 1.95px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e.\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 1.95px 7.91667px; transform-origin: 1.95px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e \u003c/span\u003e\u003c/span\u003e\u003ca target='_blank' href = \"http://en.wikipedia.org/wiki/Conway%27s_Game_of_Life\"\u003e\u003cspan style=\"\"\u003e\u003cspan style=\"\"\u003eWiki Life\u003c/span\u003e\u003c/span\u003e\u003c/a\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 138.467px 7.91667px; transform-origin: 138.467px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e. The Kaggle event is 50K cases to solve for a state 1 to 5 iterations prior to a given state. Imperfect solutions are allowed but penalized. Input file to Kaggle is a csv so Matlab solutions can be posted at the Kaggle site for this event.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 271.517px 7.91667px; transform-origin: 271.517px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThis Challenge is to Solve at least 3000 of the 50K puzzles per these revised Life Laws.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgb(247, 247, 247); block-size: 102.167px; border-bottom-left-radius: 4px; border-bottom-right-radius: 4px; border-end-end-radius: 4px; border-end-start-radius: 4px; border-start-end-radius: 4px; border-start-start-radius: 4px; border-top-left-radius: 4px; border-top-right-radius: 4px; margin-block-end: 10px; margin-block-start: 10px; margin-bottom: 10px; margin-inline-end: 3px; margin-inline-start: 3px; margin-left: 3px; margin-right: 3px; margin-top: 10px; perspective-origin: 404px 51.0833px; transform-origin: 404px 51.0833px; margin-left: 3px; margin-top: 10px; margin-bottom: 10px; margin-right: 3px; \"\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 0.833333px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.833333px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.833333px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.833333px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 350.35px 7.91667px; transform-origin: 350.35px 7.91667px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 26.95px 7.91667px; transform-origin: 26.95px 7.91667px; \"\u003e1. Any \u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(170, 4, 249); border-block-start-color: rgb(170, 4, 249); border-bottom-color: rgb(170, 4, 249); border-inline-end-color: rgb(170, 4, 249); border-inline-start-color: rgb(170, 4, 249); border-left-color: rgb(170, 4, 249); border-right-color: rgb(170, 4, 249); border-top-color: rgb(170, 4, 249); caret-color: rgb(170, 4, 249); color: rgb(170, 4, 249); column-rule-color: rgb(170, 4, 249); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(170, 4, 249); perspective-origin: 188.65px 7.91667px; text-decoration: none; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); transform-origin: 188.65px 7.91667px; \"\u003elive cell with fewer than two live neighbors dies\u003c/span\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 19.25px 7.91667px; transform-origin: 19.25px 7.91667px; \"\u003e, as \u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(170, 4, 249); border-block-start-color: rgb(170, 4, 249); border-bottom-color: rgb(170, 4, 249); border-inline-end-color: rgb(170, 4, 249); border-inline-start-color: rgb(170, 4, 249); border-left-color: rgb(170, 4, 249); border-right-color: rgb(170, 4, 249); border-top-color: rgb(170, 4, 249); caret-color: rgb(170, 4, 249); color: rgb(170, 4, 249); column-rule-color: rgb(170, 4, 249); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(170, 4, 249); perspective-origin: 115.5px 7.91667px; text-decoration: none; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); transform-origin: 115.5px 7.91667px; \"\u003eif caused by under-population.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 0.833333px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.833333px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.833333px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.833333px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 315.7px 7.91667px; transform-origin: 315.7px 7.91667px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 26.95px 7.91667px; transform-origin: 26.95px 7.91667px; \"\u003e2. Any \u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(170, 4, 249); border-block-start-color: rgb(170, 4, 249); border-bottom-color: rgb(170, 4, 249); border-inline-end-color: rgb(170, 4, 249); border-inline-start-color: rgb(170, 4, 249); border-left-color: rgb(170, 4, 249); border-right-color: rgb(170, 4, 249); border-top-color: rgb(170, 4, 249); caret-color: rgb(170, 4, 249); color: rgb(170, 4, 249); column-rule-color: rgb(170, 4, 249); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(170, 4, 249); perspective-origin: 288.75px 7.91667px; text-decoration: none; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); transform-origin: 288.75px 7.91667px; \"\u003elive cell with two or three live neighbors lives on to the next generation.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 0.833333px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.833333px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.833333px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.833333px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 311.85px 7.91667px; transform-origin: 311.85px 7.91667px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 26.95px 7.91667px; transform-origin: 26.95px 7.91667px; \"\u003e3. Any \u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(170, 4, 249); border-block-start-color: rgb(170, 4, 249); border-bottom-color: rgb(170, 4, 249); border-inline-end-color: rgb(170, 4, 249); border-inline-start-color: rgb(170, 4, 249); border-left-color: rgb(170, 4, 249); border-right-color: rgb(170, 4, 249); border-top-color: rgb(170, 4, 249); caret-color: rgb(170, 4, 249); color: rgb(170, 4, 249); column-rule-color: rgb(170, 4, 249); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(170, 4, 249); perspective-origin: 192.5px 7.91667px; text-decoration: none; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); transform-origin: 192.5px 7.91667px; \"\u003elive cell with more than three live neighbors dies\u003c/span\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 19.25px 7.91667px; transform-origin: 19.25px 7.91667px; \"\u003e, as \u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(170, 4, 249); border-block-start-color: rgb(170, 4, 249); border-bottom-color: rgb(170, 4, 249); border-inline-end-color: rgb(170, 4, 249); border-inline-start-color: rgb(170, 4, 249); border-left-color: rgb(170, 4, 249); border-right-color: rgb(170, 4, 249); border-top-color: rgb(170, 4, 249); caret-color: rgb(170, 4, 249); color: rgb(170, 4, 249); column-rule-color: rgb(170, 4, 249); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(170, 4, 249); perspective-origin: 73.15px 7.91667px; text-decoration: none; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); transform-origin: 73.15px 7.91667px; \"\u003eif by overcrowding.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 0.833333px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.833333px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.833333px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.833333px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 361.9px 7.91667px; transform-origin: 361.9px 7.91667px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 26.95px 7.91667px; transform-origin: 26.95px 7.91667px; \"\u003e4. Any \u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(170, 4, 249); border-block-start-color: rgb(170, 4, 249); border-bottom-color: rgb(170, 4, 249); border-inline-end-color: rgb(170, 4, 249); border-inline-start-color: rgb(170, 4, 249); border-left-color: rgb(170, 4, 249); border-right-color: rgb(170, 4, 249); border-top-color: rgb(170, 4, 249); caret-color: rgb(170, 4, 249); color: rgb(170, 4, 249); column-rule-color: rgb(170, 4, 249); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(170, 4, 249); perspective-origin: 242.55px 7.91667px; text-decoration: none; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); transform-origin: 242.55px 7.91667px; \"\u003edead cell with exactly three live neighbors becomes a live cell\u003c/span\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 19.25px 7.91667px; transform-origin: 19.25px 7.91667px; \"\u003e, as \u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(170, 4, 249); border-block-start-color: rgb(170, 4, 249); border-bottom-color: rgb(170, 4, 249); border-inline-end-color: rgb(170, 4, 249); border-inline-start-color: rgb(170, 4, 249); border-left-color: rgb(170, 4, 249); border-right-color: rgb(170, 4, 249); border-top-color: rgb(170, 4, 249); caret-color: rgb(170, 4, 249); color: rgb(170, 4, 249); column-rule-color: rgb(170, 4, 249); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(170, 4, 249); perspective-origin: 73.15px 7.91667px; text-decoration: none; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); transform-origin: 73.15px 7.91667px; \"\u003eif by reproduction.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 0.833333px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.833333px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.833333px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.833333px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 265.65px 7.91667px; transform-origin: 265.65px 7.91667px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 34.65px 7.91667px; transform-origin: 34.65px 7.91667px; \"\u003e5. Edges \u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(170, 4, 249); border-block-start-color: rgb(170, 4, 249); border-bottom-color: rgb(170, 4, 249); border-inline-end-color: rgb(170, 4, 249); border-inline-start-color: rgb(170, 4, 249); border-left-color: rgb(170, 4, 249); border-right-color: rgb(170, 4, 249); border-top-color: rgb(170, 4, 249); caret-color: rgb(170, 4, 249); color: rgb(170, 4, 249); column-rule-color: rgb(170, 4, 249); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(170, 4, 249); perspective-origin: 231px 7.91667px; text-decoration: none; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); transform-origin: 231px 7.91667px; \"\u003ewrap around. Eight Neighbors. (Change to normal planar life)\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 10px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 10px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 10px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 221.317px 7.91667px; transform-origin: 221.317px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eNote: The edges wrap so the matrix represents the surface of a sphere.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 21px; text-align: left; transform-origin: 384px 21px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 19.4333px 7.91667px; transform-origin: 19.4333px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eInput:\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 354.317px 7.91667px; transform-origin: 354.317px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e (mtest,numtosolve) the Finish state matrix of 50K rows of [casenumber, iterations, 625 values], number of case to solve (3000)\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 21px; text-align: left; transform-origin: 384px 21px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 25.2667px 7.91667px; transform-origin: 25.2667px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eOutput:\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 347.317px 7.91667px; transform-origin: 347.317px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e (mstart) the Starting state matrix of at least 3000 puzzles all with perfect zero error solutions, [casenumber, 625 values]\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 7.91667px; transform-origin: 0px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 15.95px 7.91667px; transform-origin: 15.95px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eHint:\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 250.483px 7.91667px; transform-origin: 250.483px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e There are 3726 trivial solutions where the  Finish state is the Start state solution.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function mstart = solveLife(mtest,numtosolve)\r\n  mstart=zeros(numtosolve,626)\r\nend","test_suite":"%%\r\n%'https://sites.google.com/site/razapor/matlab_cody/mtest.mat?attredirects=0\u0026d=1';\r\n%mtest format is [casenumer, iterations, start1:625,finish1:625] for 50K cases 0:49999\r\n%'https://sites.google.com/site/razapor/matlab_cody/mtrain.mat?attredirects=0\u0026d=1';\r\ntic\r\nfname='https://sites.google.com/site/razapor/matlab_cody/mtest.mat?attredirects=0\u0026d=1';\r\nurlwrite(fname,'mtest.mat') %1.22s\r\nload('mtest.mat'); %0.42s\r\ntoc\r\n\r\nnumtosolve=3000;\r\nmstart = solveLife(mtest,numtosolve);\r\ntoc\r\nmstart=unique(mstart,'rows'); % remove exact duplicate solutions\r\n\r\nvalid=0;\r\nfor i=1:size(mstart,1)  % \u003c0.5sec to process 3K cases\r\n icase=mstart(i,1); %50000:99999\r\n iter=mtest(icase-49999,2); %Test cases start at 50000\r\n \r\n A=reshape(mstart(i,2:end),25,25);\r\n for j=1:iter\r\n  C=0;\r\n  for r=-1:1 % -1 Up   Using circshift to perform wrap convolution\r\n   Ar=circshift(A,r,1);\r\n   for c=-1:1 % -1 Left\r\n     Arc=circshift(Ar,c,2);\r\n     C=C+Arc;\r\n   end\r\n  end\r\n  A = C==3 | A\u0026C==4;\r\n end %j\r\n\r\n if isequal(A(:)',mtest(icase-49999,3:end)) % mtest [case, iter, data1:625]\r\n  valid=valid+1;\r\n else\r\n  valid=0;\r\n  break;\r\n end\r\nend %main loop i\r\ntoc\r\n\r\nassert(valid\u003e=3000)\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":3097,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":3,"test_suite_updated_at":"2020-10-06T15:37:58.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2020-10-06T14:46:29.000Z","updated_at":"2020-10-06T15:37:58.000Z","published_at":"2020-10-06T15:37:58.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:hyperlink w:docLocation=\\\"https://www.kaggle.com/c/conways-reverse-game-of-life-2020\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eKaggle's Conway's Reverse Game of Life 2020 \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003econtest inspires this Life challenge. The kaggle contest runs from Oct-01-2020 thru Nov-30-2020. References:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"http://mathworld.wolfram.com/GameofLife.html\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eGame of Life at Wolfram\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e.\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"http://en.wikipedia.org/wiki/Conway%27s_Game_of_Life\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eWiki Life\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e. The Kaggle event is 50K cases to solve for a state 1 to 5 iterations prior to a given state. Imperfect solutions are allowed but penalized. Input file to Kaggle is a csv so Matlab solutions can be posted at the Kaggle site for this event.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis Challenge is to Solve at least 3000 of the 50K puzzles per these revised Life Laws.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[1. Any live cell with fewer than two live neighbors dies, as if caused by under-population.\\n2. Any live cell with two or three live neighbors lives on to the next generation.\\n3. Any live cell with more than three live neighbors dies, as if by overcrowding.\\n4. Any dead cell with exactly three live neighbors becomes a live cell, as if by reproduction.\\n5. Edges wrap around. Eight Neighbors. (Change to normal planar life)]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eNote: The edges wrap so the matrix represents the surface of a sphere.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eInput:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e (mtest,numtosolve) the Finish state matrix of 50K rows of [casenumber, iterations, 625 values], number of case to solve (3000)\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eOutput:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e (mstart) the Starting state matrix of at least 3000 puzzles all with perfect zero error solutions, [casenumber, 625 values]\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eHint:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e There are 3726 trivial solutions where the  Finish state is the Start state solution.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":46691,"title":"Kaggle: Planetoid Game of Life - Solve 40 non-trivial Puzzles","description":null,"description_html":"\u003cdiv style = \"text-align: start; line-height: 20.4333px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 482.167px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 241.083px; transform-origin: 407px 241.083px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 84px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 42px; text-align: left; transform-origin: 384px 42px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003ca target='_blank' href = \"https://www.kaggle.com/c/conways-reverse-game-of-life-2020\"\u003e\u003cspan style=\"\"\u003e\u003cspan style=\"\"\u003eKaggle's Conway's Reverse Game of Life 2020 \u003c/span\u003e\u003c/span\u003e\u003c/a\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 203.05px 7.91667px; transform-origin: 203.05px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003econtest inspires this Life challenge. The kaggle contest runs from Oct-01-2020 thru Nov-30-2020. References:\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 1.95px 7.91667px; transform-origin: 1.95px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e \u003c/span\u003e\u003c/span\u003e\u003ca target='_blank' href = \"http://mathworld.wolfram.com/GameofLife.html\"\u003e\u003cspan style=\"\"\u003e\u003cspan style=\"\"\u003eGame of Life at Wolfram\u003c/span\u003e\u003c/span\u003e\u003c/a\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 1.95px 7.91667px; transform-origin: 1.95px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e.\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 1.95px 7.91667px; transform-origin: 1.95px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e \u003c/span\u003e\u003c/span\u003e\u003ca target='_blank' href = \"http://en.wikipedia.org/wiki/Conway%27s_Game_of_Life\"\u003e\u003cspan style=\"\"\u003e\u003cspan style=\"\"\u003eWiki Life\u003c/span\u003e\u003c/span\u003e\u003c/a\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 138.467px 7.91667px; transform-origin: 138.467px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e. The Kaggle event is 50K cases to solve for a state 1 to 5 iterations prior to a given state. Imperfect solutions are allowed but penalized. Input file to Kaggle is a csv so Matlab solutions can be posted at the Kaggle site for this event.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 21px; text-align: left; transform-origin: 384px 21px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 384px 7.91667px; transform-origin: 384px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThis Challenge is to Solve at least 40, excluding trivials, of the 50K puzzles per these revised Life Laws. Trivial solutions are where the Final state may match the Start State.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgb(247, 247, 247); block-size: 102.167px; border-bottom-left-radius: 4px; border-bottom-right-radius: 4px; border-end-end-radius: 4px; border-end-start-radius: 4px; border-start-end-radius: 4px; border-start-start-radius: 4px; border-top-left-radius: 4px; border-top-right-radius: 4px; margin-block-end: 10px; margin-block-start: 10px; margin-bottom: 10px; margin-inline-end: 3px; margin-inline-start: 3px; margin-left: 3px; margin-right: 3px; margin-top: 10px; perspective-origin: 404px 51.0833px; transform-origin: 404px 51.0833px; margin-left: 3px; margin-top: 10px; margin-bottom: 10px; margin-right: 3px; \"\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 0.833333px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.833333px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.833333px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.833333px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 350.35px 7.91667px; transform-origin: 350.35px 7.91667px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 26.95px 7.91667px; transform-origin: 26.95px 7.91667px; \"\u003e1. Any \u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(170, 4, 249); border-block-start-color: rgb(170, 4, 249); border-bottom-color: rgb(170, 4, 249); border-inline-end-color: rgb(170, 4, 249); border-inline-start-color: rgb(170, 4, 249); border-left-color: rgb(170, 4, 249); border-right-color: rgb(170, 4, 249); border-top-color: rgb(170, 4, 249); caret-color: rgb(170, 4, 249); color: rgb(170, 4, 249); column-rule-color: rgb(170, 4, 249); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(170, 4, 249); perspective-origin: 188.65px 7.91667px; text-decoration: none; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); transform-origin: 188.65px 7.91667px; \"\u003elive cell with fewer than two live neighbors dies\u003c/span\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 19.25px 7.91667px; transform-origin: 19.25px 7.91667px; \"\u003e, as \u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(170, 4, 249); border-block-start-color: rgb(170, 4, 249); border-bottom-color: rgb(170, 4, 249); border-inline-end-color: rgb(170, 4, 249); border-inline-start-color: rgb(170, 4, 249); border-left-color: rgb(170, 4, 249); border-right-color: rgb(170, 4, 249); border-top-color: rgb(170, 4, 249); caret-color: rgb(170, 4, 249); color: rgb(170, 4, 249); column-rule-color: rgb(170, 4, 249); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(170, 4, 249); perspective-origin: 115.5px 7.91667px; text-decoration: none; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); transform-origin: 115.5px 7.91667px; \"\u003eif caused by under-population.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 0.833333px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.833333px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.833333px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.833333px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 315.7px 7.91667px; transform-origin: 315.7px 7.91667px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 26.95px 7.91667px; transform-origin: 26.95px 7.91667px; \"\u003e2. Any \u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(170, 4, 249); border-block-start-color: rgb(170, 4, 249); border-bottom-color: rgb(170, 4, 249); border-inline-end-color: rgb(170, 4, 249); border-inline-start-color: rgb(170, 4, 249); border-left-color: rgb(170, 4, 249); border-right-color: rgb(170, 4, 249); border-top-color: rgb(170, 4, 249); caret-color: rgb(170, 4, 249); color: rgb(170, 4, 249); column-rule-color: rgb(170, 4, 249); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(170, 4, 249); perspective-origin: 288.75px 7.91667px; text-decoration: none; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); transform-origin: 288.75px 7.91667px; \"\u003elive cell with two or three live neighbors lives on to the next generation.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 0.833333px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.833333px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.833333px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.833333px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 311.85px 7.91667px; transform-origin: 311.85px 7.91667px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 26.95px 7.91667px; transform-origin: 26.95px 7.91667px; \"\u003e3. Any \u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(170, 4, 249); border-block-start-color: rgb(170, 4, 249); border-bottom-color: rgb(170, 4, 249); border-inline-end-color: rgb(170, 4, 249); border-inline-start-color: rgb(170, 4, 249); border-left-color: rgb(170, 4, 249); border-right-color: rgb(170, 4, 249); border-top-color: rgb(170, 4, 249); caret-color: rgb(170, 4, 249); color: rgb(170, 4, 249); column-rule-color: rgb(170, 4, 249); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(170, 4, 249); perspective-origin: 192.5px 7.91667px; text-decoration: none; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); transform-origin: 192.5px 7.91667px; \"\u003elive cell with more than three live neighbors dies\u003c/span\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 19.25px 7.91667px; transform-origin: 19.25px 7.91667px; \"\u003e, as \u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(170, 4, 249); border-block-start-color: rgb(170, 4, 249); border-bottom-color: rgb(170, 4, 249); border-inline-end-color: rgb(170, 4, 249); border-inline-start-color: rgb(170, 4, 249); border-left-color: rgb(170, 4, 249); border-right-color: rgb(170, 4, 249); border-top-color: rgb(170, 4, 249); caret-color: rgb(170, 4, 249); color: rgb(170, 4, 249); column-rule-color: rgb(170, 4, 249); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(170, 4, 249); perspective-origin: 73.15px 7.91667px; text-decoration: none; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); transform-origin: 73.15px 7.91667px; \"\u003eif by overcrowding.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 0.833333px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.833333px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.833333px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.833333px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 361.9px 7.91667px; transform-origin: 361.9px 7.91667px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 26.95px 7.91667px; transform-origin: 26.95px 7.91667px; \"\u003e4. Any \u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(170, 4, 249); border-block-start-color: rgb(170, 4, 249); border-bottom-color: rgb(170, 4, 249); border-inline-end-color: rgb(170, 4, 249); border-inline-start-color: rgb(170, 4, 249); border-left-color: rgb(170, 4, 249); border-right-color: rgb(170, 4, 249); border-top-color: rgb(170, 4, 249); caret-color: rgb(170, 4, 249); color: rgb(170, 4, 249); column-rule-color: rgb(170, 4, 249); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(170, 4, 249); perspective-origin: 242.55px 7.91667px; text-decoration: none; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); transform-origin: 242.55px 7.91667px; \"\u003edead cell with exactly three live neighbors becomes a live cell\u003c/span\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 19.25px 7.91667px; transform-origin: 19.25px 7.91667px; \"\u003e, as \u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(170, 4, 249); border-block-start-color: rgb(170, 4, 249); border-bottom-color: rgb(170, 4, 249); border-inline-end-color: rgb(170, 4, 249); border-inline-start-color: rgb(170, 4, 249); border-left-color: rgb(170, 4, 249); border-right-color: rgb(170, 4, 249); border-top-color: rgb(170, 4, 249); caret-color: rgb(170, 4, 249); color: rgb(170, 4, 249); column-rule-color: rgb(170, 4, 249); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(170, 4, 249); perspective-origin: 73.15px 7.91667px; text-decoration: none; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); transform-origin: 73.15px 7.91667px; \"\u003eif by reproduction.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 0.833333px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.833333px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.833333px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.833333px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 265.65px 7.91667px; transform-origin: 265.65px 7.91667px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 34.65px 7.91667px; transform-origin: 34.65px 7.91667px; \"\u003e5. Edges \u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(170, 4, 249); border-block-start-color: rgb(170, 4, 249); border-bottom-color: rgb(170, 4, 249); border-inline-end-color: rgb(170, 4, 249); border-inline-start-color: rgb(170, 4, 249); border-left-color: rgb(170, 4, 249); border-right-color: rgb(170, 4, 249); border-top-color: rgb(170, 4, 249); caret-color: rgb(170, 4, 249); color: rgb(170, 4, 249); column-rule-color: rgb(170, 4, 249); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(170, 4, 249); perspective-origin: 231px 7.91667px; text-decoration: none; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); transform-origin: 231px 7.91667px; \"\u003ewrap around. Eight Neighbors. (Change to normal planar life)\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 10px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 10px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 10px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 221.317px 7.91667px; transform-origin: 221.317px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eNote: The edges wrap so the matrix represents the surface of a sphere.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 21px; text-align: left; transform-origin: 384px 21px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 19.4333px 7.91667px; transform-origin: 19.4333px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eInput:\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 354.317px 7.91667px; transform-origin: 354.317px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e (mtest,numtosolve) the Finish state matrix of 50K rows of [casenumber, iterations, 625 values], number of case to solve (40)\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 21px; text-align: left; transform-origin: 384px 21px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 25.2667px 7.91667px; transform-origin: 25.2667px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eOutput:\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 339.533px 7.91667px; transform-origin: 339.533px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e (mstart) the Starting state matrix of at least 40 puzzles all with perfect zero error solutions, [casenumber, 625 values]\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 7.91667px; transform-origin: 0px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 63px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 31.5px; text-align: left; transform-origin: 384px 31.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 15.95px 7.91667px; transform-origin: 15.95px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eHint:\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 364.467px 7.91667px; transform-origin: 364.467px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e There are 40 non-trivial solutions for iterations 1 and 2 where a solving Start state has a single bit flip that is adjacent to a set bit or is a set bit. Cases where there are more than 40 set bits in the final state may consume significant time for no solutions. \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function mstart = solveLife(mtest,numtosolve)\r\n  mstart=zeros(numtosolve,626)\r\nend","test_suite":"%%\r\n%'https://sites.google.com/site/razapor/matlab_cody/mtest.mat?attredirects=0\u0026d=1';\r\n%mtest format is [casenumer, iterations, start1:625,finish1:625] for 50K cases 0:49999\r\n%'https://sites.google.com/site/razapor/matlab_cody/mtrain.mat?attredirects=0\u0026d=1';\r\ntic\r\nfname='https://sites.google.com/site/razapor/matlab_cody/mtest.mat?attredirects=0\u0026d=1';\r\nurlwrite(fname,'mtest.mat') %1.22s\r\nload('mtest.mat'); %0.42s\r\ntoc\r\n\r\nnumtosolve=40;\r\nmstart = solveLife(mtest,numtosolve);\r\ntoc\r\nmstart=unique(mstart,'rows'); % remove exact duplicate solutions\r\n\r\n%Check for Trivial solutions; Life(mtest(case))==mtest(case)\r\nvalid=1;\r\nfor i=1:size(mstart,1)  % \r\n icase=mstart(i,1); %50000:99999\r\n iter=mtest(icase-49999,2); %Test cases start at 50000\r\n \r\n A=reshape(mtest(icase-49999,3:end),25,25);\r\n Abase=A;\r\n for j=1:iter\r\n  C=0;\r\n  for r=-1:1 % -1 Up   Using circshift to perform wrap convolution\r\n   Ar=circshift(A,r,1);\r\n   for c=-1:1 % -1 Left\r\n     Arc=circshift(Ar,c,2);\r\n     C=C+Arc;\r\n   end\r\n  end\r\n  A = C==3 | A\u0026C==4;\r\n end %j\r\n\r\n if isequal(Abase,A) % mtest [case, iter, data1:625]\r\n  valid=0; %Trivial solution entered\r\n  break;\r\n end\r\nend %main loop i\r\ntoc  % Trivial check timer\r\n\r\nLprocess=size(mstart,1)*valid;\r\nvalid=0; % Reset valid as counter for solutions\r\nfor i=1:Lprocess  % skip if any were trivial\r\n icase=mstart(i,1); %50000:99999\r\n iter=mtest(icase-49999,2); %Test cases start at 50000\r\n \r\n A=reshape(mstart(i,2:end),25,25);\r\n for j=1:iter\r\n  C=0;\r\n  for r=-1:1 % -1 Up   Using circshift to perform wrap convolution\r\n   Ar=circshift(A,r,1);\r\n   for c=-1:1 % -1 Left\r\n     Arc=circshift(Ar,c,2);\r\n     C=C+Arc;\r\n   end\r\n  end\r\n  A = C==3 | A\u0026C==4;\r\n end %j\r\n\r\n if ~isequal(A(:)',mtest(icase-49999,3:end)) % mtest [case, iter, data1:625]\r\n  valid=0; %Evolved does not match goal\r\n  break;\r\n else\r\n  valid=valid+1;\r\n end\r\nend %main loop i\r\ntoc\r\n\r\nassert(valid\u003e=40)\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":3097,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":2,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2020-10-06T18:14:45.000Z","updated_at":"2020-10-06T18:41:35.000Z","published_at":"2020-10-06T18:41:35.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:hyperlink w:docLocation=\\\"https://www.kaggle.com/c/conways-reverse-game-of-life-2020\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eKaggle's Conway's Reverse Game of Life 2020 \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003econtest inspires this Life challenge. The kaggle contest runs from Oct-01-2020 thru Nov-30-2020. References:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"http://mathworld.wolfram.com/GameofLife.html\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eGame of Life at Wolfram\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e.\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"http://en.wikipedia.org/wiki/Conway%27s_Game_of_Life\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eWiki Life\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e. The Kaggle event is 50K cases to solve for a state 1 to 5 iterations prior to a given state. Imperfect solutions are allowed but penalized. Input file to Kaggle is a csv so Matlab solutions can be posted at the Kaggle site for this event.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis Challenge is to Solve at least 40, excluding trivials, of the 50K puzzles per these revised Life Laws. Trivial solutions are where the Final state may match the Start State.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[1. Any live cell with fewer than two live neighbors dies, as if caused by under-population.\\n2. Any live cell with two or three live neighbors lives on to the next generation.\\n3. Any live cell with more than three live neighbors dies, as if by overcrowding.\\n4. Any dead cell with exactly three live neighbors becomes a live cell, as if by reproduction.\\n5. Edges wrap around. Eight Neighbors. (Change to normal planar life)]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eNote: The edges wrap so the matrix represents the surface of a sphere.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eInput:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e (mtest,numtosolve) the Finish state matrix of 50K rows of [casenumber, iterations, 625 values], number of case to solve (40)\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eOutput:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e (mstart) the Starting state matrix of at least 40 puzzles all with perfect zero error solutions, [casenumber, 625 values]\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eHint:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e There are 40 non-trivial solutions for iterations 1 and 2 where a solving Start state has a single bit flip that is adjacent to a set bit or is a set bit. Cases where there are more than 40 set bits in the final state may consume significant time for no solutions. \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":46618,"title":"Kaggle 2020 Drone Delivery Contest","description":null,"description_html":"\u003cdiv style = \"text-align: start; line-height: 20.4333px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 941.917px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 470.967px; transform-origin: 407px 470.967px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 84px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 42px; text-align: left; transform-origin: 384px 42px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 31.5167px 7.91667px; transform-origin: 31.5167px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThe 2020 \u003c/span\u003e\u003c/span\u003e\u003ca target='_blank' href = \"https://www.kaggle.com/c/hashcode-drone-delivery\"\u003e\u003cspan style=\"\"\u003e\u003cspan style=\"\"\u003eKaggle Drone\u003c/span\u003e\u003c/span\u003e\u003c/a\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 309.217px 7.91667px; transform-origin: 309.217px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e contest is an optimization task to maximize net customer satisfaction by using 30 drones across 10 warehouses to fulfill 1250 customer multi-item, 400 distinct items(products), orders. Satisfaction is (1-delivery_time/max_time)*100 and 0 if delivery not completed by max_time. The max time of 112993 is easily beaten with typical worse time of 40K. \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 331.8px 7.91667px; transform-origin: 331.8px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThis contest subset has disabled moving items from warehouse to warehouse thus wait times are not used.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 373.283px 7.91667px; transform-origin: 373.283px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThe maximum score is 125000. To succeed as a DroneManager requires a score of 110K, 5th at Kaggle contest 9/26/20.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 63px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 31.5px; text-align: left; transform-origin: 384px 31.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 19.4333px 7.91667px; transform-origin: 19.4333px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eInput:\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 1.95px 7.91667px; transform-origin: 1.95px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e [rows,cols,numdrones,maxturns,maxDronewt,numproducts,numOrders,delivery_xy_qty,delivery_list,distance_delivery\u0026amp;warehouse_to_delivery\u0026amp;warehouse, distance_warehouse_to_delivery,permutation_cell_array_for1to9]\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 25.2667px 7.91667px; transform-origin: 25.2667px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eOutput:\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 304.15px 7.91667px; transform-origin: 304.15px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e Commands matrix [number of commands,5]  The number of commands is likely to be 18K to 20K.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 380.167px 7.91667px; transform-origin: 380.167px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eLoading from a warehouse: [drone# 1 warehouse# item# quantity]. Drone1:30, Warehouse1:10, Item1:400. The 1 is LOAD.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 341.9px 7.91667px; transform-origin: 341.9px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eOnly one item type can be loaded on to drone at a time. Each Load/Deliver command consumes 1 unit of time.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 352.417px 7.91667px; transform-origin: 352.417px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eDelivery for an order:  [drone# 3 delivery# item# quantity]. Drone1:30, Delivery1:1250, Item1:400. The 3 is Deliver.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 286.283px 7.91667px; transform-origin: 286.283px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThe final delivery time for an order is the latest drone time inclusive of final delivery time unit.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 21px; text-align: left; transform-origin: 384px 21px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 117.867px 7.91667px; transform-origin: 117.867px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eAdditional approach comments are at \u003c/span\u003e\u003c/span\u003e\u003ca target='_blank' href = \"https://www.kaggle.com/c/hashcode-drone-delivery/discussion/186050\"\u003e\u003cspan style=\"\"\u003e\u003cspan style=\"\"\u003eKaggle Drone 111401\u003c/span\u003e\u003c/span\u003e\u003c/a\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 181.283px 7.91667px; transform-origin: 181.283px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e and in the template along with using a provided routine to create a Kaggle python submission file.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 84.5333px 7.91667px; transform-origin: 84.5333px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eDelivery/Warehouse Map.\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 275.333px 7.91667px; transform-origin: 275.333px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e Warehouses red*, Single item delivery redO, Two item delivery blackO, \u0026gt;2 items greenO\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 7.91667px; transform-origin: 0px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 425.917px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 212.967px; text-align: left; transform-origin: 384px 212.967px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cimg class=\"imageNode\" style=\"vertical-align: baseline;width: 560px;height: 420px\" 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\" data-image-state=\"image-loaded\" width=\"560\" height=\"420\"\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 7.91667px; transform-origin: 0px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function cmds=drone(nr,nc,ndr,nturns,max_wt,nprod,vpwt,nw,wxy,wprodq,norders,dxyq,dlist,dw2dw,w2d,pmapc)\r\n% Discussion of an approach can be read at \r\n%https://www.kaggle.com/c/hashcode-drone-delivery/discussion/186050\r\n%\r\n%Short approach description is: \r\n% 1) Create baskets for every order by unique warehouse and wt\r\n% 2)Fix warehouse usage for over-use of items\r\n% 3)Create matrix of baskets that will be reduced for each delivery, add an idx at far right and\r\n% also create a master reference copy for creation of cmds\r\n% 4) Select warehouse that is normalized closest to drone.  dist/f(number signle order baskets, tot baskets)\r\n% 5) Augment drone basket set by baskets along line segment. Function distP2S_tim provided, Point to Segment\r\n% 6) Optimize Loading/Delivery steps\r\n% 7) Optimal path of multi-baskets easily done by brute force as \u003c10 baskets in any drone flt,pmapc\r\n%\r\ncmds=zeros(20000,5); %early est number of commands, max=nd*nturns\r\ncptr=0; %cmd ptr\r\n% Initialize drones/delivery_timer\r\n%All drones start at first warehouse, drIdx(:)=1251\r\ndrIdx=ones(ndr,1)*(norders+1); % drone location index, quantized, range  [1:norders norders+wh]\r\ndrT=zeros(ndr,1); % Drone Time, includes loads and flight legs\r\ndt=zeros(norders,1); %delivery time of last item deposited\r\ndidb=zeros(norders,1); % Remaining baskets to complete a delivery id\r\n\r\n%[packc]=pack_init(nw,norders,nprod,dlist,dxyq,w2d,vpwt,wprodq,max_wt);\r\n% packc cell {wh,norders} vector of items from each wh for each order, \r\n%  baskets are item sequences wt sum to \u003c=200\r\n%  packc has single and multiple baskets\r\n\r\n% Create mb array \r\n%[mb,Rmb,didb]=create_baskets(nw,norders,packc,vpwt,max_wt,w2d,didb);\r\n%mb [whid,did,dist,totwt,itemlist,mbidx]\r\n%\r\n%Initial 4684 baskets\r\n\r\n%Start of Main Processing Loop Creating Packs from baskets\r\nzflt=0; % flt counting variable for debug\r\nwhile min(drT)\u003cnturns %112993   3357 cycles if no dist limit, 4684 baskets\r\n zflt=zflt+1;\r\n% if max(didb)==0\r\n%  break;\r\n% end % all package baskets delivered\r\n \r\n \r\n %drptr=find(drT==min(drT),1,'first');  %Next drone should be the one that reaches its preferred warehouse the soonest, not lowest time used\r\n \r\n %dr_wh=pick_wh(drIdx,drptr,norders,didb,mb,w2d,nw); \r\n %Critical is selecting warehouse for drone to reach based on single baskets remaining, qty baskets\r\n \r\nend % min(drT)  Drones alive to make orders\r\n\r\n\r\n% [drone_id,Action,WH/DE id,Item_id,Q]\r\n% Wait0 [drid 0 Nturns 0 0]\r\n% Load1 [drid 1 whid itid q]\r\n% UnLoad2 [drid 2 whid itid q]\r\n% Deliv3 [drid 3 Did itid q]\r\n \r\n %calc/print score\r\n %dt is tracked as max of drone delivery time\r\n %dt(???)=nturns; % Delivery not fulfilled set to nturns\r\n %scr= sum( ceil(100*(nturns-dt(:))/nturns) );\r\n %fprintf('scr: %i\\n',scr)\r\n \r\n %create python file to create submission.txt file from cmds array\r\n %writefile(cmds,cptr); %0.55s\r\nend % cmds=drone()\r\n\r\nfunction ans=distP2S_tim(x0,y0,x1,y1,x2,y2)\r\n% Distance from a Point to a segment\r\nz=complex(x0-x1,y0-y1);\r\ncomplex(x2-x1,y2-y1);\r\nabs(z-ans*min(1,max(0,real(z/ans))));\r\nend\r\n\r\nfunction writefile(cmds,cptr)\r\n% To create python.txt file for entry into a kaggle notebook\r\n%\r\n% [drone_id,Action,WH/DE id,Item_id,Q]\r\n% Wait0 [drid 0 Nturns 0 0]\r\n% Load1 [drid 1 whid itid q]\r\n% UnLoad2 [drid 2 whid itid q]\r\n% Deliv3 [drid 3 Did itid q]\r\n% sub = '8\\n'\r\n% sub+= '0 L 0 163 1\\n'\r\n% sub+= '0 D 1 163 1\\n'\r\n% \r\n%cmds [drone action wh/deliv Item q \r\n%cmds(cptr+1,:)=[drid 1 1 item 1];\r\n%cmds(cptr+2,:)=[drid 3 didx item 1];\r\n fname=['drone' datestr(now,'ddmmyyyy_hhMM') '.txt'];\r\n fid =fopen(fname,'w');\r\n \r\n %fprintf(fid,'sub = ''%i\\n''',cptr)\r\n fprintf(fid,'sub = ''%i\\\\n''\\n',cptr); % specials\r\n for i=1:cptr\r\n  if cmds(i,2)==0 % Wait\r\n   fprintf(fid,'sub+= ''%i W %i\\\\n''\\n',cmds(i,[1 3])-1); % specials\r\n  elseif cmds(i,2)==1 %Load\r\n   fprintf(fid,'sub+= ''%i L %i %i %i\\\\n''\\n',cmds(i,[1 3 4])-1,cmds(i,5)); % specials\r\n  elseif cmds(i,2)==2 %Unload\r\n   fprintf(fid,'sub+= ''%i U %i %i %i\\\\n''\\n',cmds(i,[1 3 4])-1,cmds(i,5)); % specials\r\n  elseif cmds(i,2)==3 %Delivery\r\n   fprintf(fid,'sub+= ''%i D %i %i %i\\\\n''\\n',cmds(i,[1 3 4])-1,cmds(i,5)); % specials\r\n  else % error in cmds action value\r\n   fprintf('Error Occurred: Invalid command: Line %i\\n',i);\r\n  end\r\n end\r\n \r\n %final section of code to write the python file that writes submission.csv\r\n fprintf(fid,'text_file = open(\"submission.csv\", \"w\")\\n');\r\n fprintf(fid,'text_file.write(sub)\\n');\r\n fprintf(fid,'text_file.close()\\n');\r\n \r\n fclose(fid);\r\n %https://www.mathworks.com/help/matlab/matlab_prog/formatting-strings.html\r\n % ' use ''\r\n % \\ use \\\\\r\nend\r\n","test_suite":"%%\r\ntic\r\nfname='https://sites.google.com/site/razapor/matlab_cody/busy_day.in?attredirects=0\u0026d=1';\r\nout_fn='busy_day_cody.in';\r\nurlwrite(fname,out_fn); %Load url file to local space 0.74s\r\nm=dlmread(out_fn); % 3775, 400  1.1s  Read in complete Kaggle Drone Test file\r\nnr=m(1,1);nc=m(1,2);ndr=m(1,3);nturns=m(1,4);max_wt=m(1,5);\r\n%nr400, nc600, ndr30 drones, nturns112993, max_wt200\r\n%All drones start at first warehouse  drones(1:30), warehouses(1:10)\r\nnprod=m(2,1); %400\r\nvpwt=m(3,1:nprod); %\r\nnw=m(4,1); %10 warehouses\r\nwxy=zeros(nw,2); % warehouses x,y\r\nwprodq=zeros(nw,nprod); % Quantity of each product in each warehouse\r\nLptr=5;\r\nfor i=1:nw\r\n wxy(i,:)=m(Lptr,1:2)+1; %locations moved off (0,0) to (1,1)\r\n wprodq(i,1:nprod)=m(Lptr+1,1:nprod); %qty of items(1:400) at each warehouse\r\n Lptr=Lptr+2;\r\nend\r\nnorders=m(Lptr,1); %1250 orders [1:1250]\r\n% Delivery dxyq locx,locy,qty_items\r\n% Delivery_list dlisth (repeat items possible)[dataset starts at 0, add 1) hist\r\ndxyq=zeros(norders,3);\r\ndlist=zeros(norders,nprod); % do not know current max of items in an order\r\n\r\nLptr=Lptr+1;\r\nfor i=1:norders %deliveries(1:1250)\r\n dxyq(i,1:2)=m(Lptr,1:2)+1; %locations moved off (0,0) to (1,1)\r\n dxyq(i,3)=m(Lptr+1,1); %qty of items for a delivery\r\n dlist(i,1:dxyq(i,3))=sort(m(Lptr+2,1:dxyq(i,3))+1); % items 0:399 become 1:400\r\n Lptr=Lptr+3;\r\nend\r\ndlist=dlist(:,1:max(dxyq(:,3))); %dlist width reduces from 400 to 19\r\n%read complete\r\n%Create three useful arrays required for scoring\r\n% delivery to delivery location and warehouse to delivery location\r\n dw2dw=zeros(norders+nw);\r\n vx=[dxyq(:,1);wxy(:,1)];\r\n vy=[dxyq(:,2);wxy(:,2)];\r\n for j=1:norders+nw\r\n  dw2dw(:,j)=ceil(((vx-vx(j)).^2+(vy-vy(j)).^2).^.5);\r\n end\r\n %warehouse to delivery distance [nw,norders]\r\n w2d=dw2dw(norders+1:end,1:norders);\r\n \r\n %Initialize permutation maps for Brute Force path calculation\r\n for i=9:-1:1\r\n  pmapc{i}=perms(1:i);\r\n end\r\n %1.3s Cody setup\r\n\r\ntoc\r\nfprintf('%i ',nr,nc,ndr,nturns,max_wt,nprod);fprintf('\\n')\r\n\r\ncmds=drone(nr,nc,ndr,nturns,max_wt,nprod,vpwt,nw,wxy,wprodq,norders,dxyq,dlist,dw2dw,w2d,pmapc);\r\ntoc\r\n\r\n%Evaluate cmds provided for accuracy and drone time to deliver packages\r\n drIdx=ones(ndr,1)*(norders+1); % drone location index, quantized, range  [1:norders norders+wh]\r\n drT=zeros(ndr,1); % Drone Time, includes loads and flight legs\r\n drW=zeros(ndr,1); % Drone Weight\r\n drL=zeros(ndr,nprod); %Histogram of drone loads\r\n dt=zeros(norders,1); %delivery time of last item deposited\r\n \r\n %Reduce cmds for illegal content and give warning \r\n csize=size(cmds,1);\r\n cmds=abs(cmds); %remove any negatives\r\n cmds(prod(cmds,2)==0,:)=[]; % No zeros allowed\r\n cmds(cmds(:,2)==1 \u0026 cmds(:,3)\u003enw,:)=[]; %For Load cmds(3)\u003c=1nw\r\n cmds(cmds(:,3)\u003enorders,:)=[];\r\n cmds(cmds(:,4)\u003enprod,:)=[];\r\n cmds(cmds(:,1)\u003c1,:)=[];\r\n cmds(cmds(:,1)\u003endr,:)=[];\r\n cmds(cmds(:,2)\u003c1,:)=[]; % invalid cmd type only 1/3 allowed\r\n cmds(cmds(:,2)==2,:)=[]; % invalid cmd type only 1/3 allowed\r\n cmds(cmds(:,2)\u003e3,:)=[]; % invalid cmd type only 1/3 allowed\r\n if size(cmds,1)\u003ccsize\r\n  fprintf('Warning: Invalid cmds purged\\n')\r\n end\r\n \r\n flag=0; % No issues 0\r\n for i=1:size(cmds,1)\r\n  vcmd=cmds(i,:); %[drone 1/3 warehouse/delivery item qty]\r\n  if vcmd(2)==1 %Load  vcmd(3) warehouse  (allow warehouse to warehouse,deliv to wh)\r\n   wptr=vcmd(3);\r\n   drT(vcmd(1))=drT(vcmd(1))+dw2dw(drIdx(vcmd(1)),norders+wptr)+1; %dist+load\r\n   drIdx(vcmd(1))=norders+wptr;\r\n   wprodq(wptr,vcmd(4))=wprodq(wptr,vcmd(4))-vcmd(5);\r\n   drL(vcmd(1),vcmd(4))=drL(vcmd(1),vcmd(4))+vcmd(5);\r\n   drW(vcmd(1))=drW(vcmd(1))+vcmd(5)*vpwt(vcmd(4)); %Add item(s) wt\r\n   if wprodq(wptr,vcmd(4))\u003c0 % Check for excess usage at warehouse\r\n    flag=1;\r\n    fprintf('Not enough of item %i at warehouse %i at cmds %i\\n',vcmd([4 3]),i);\r\n    break;\r\n   end\r\n   if drW(vcmd(1))\u003emax_wt % check for excess wt loaded\r\n    flag=1;\r\n    fprintf('Max wt exceeded: %i  drone %i at cmds %i\\n',drW(vcmd(1)),vcmd(1),i);\r\n    break;\r\n   end\r\n  else %Deliver:  vcmd(3) delivery location (wh2deliv, deliv2deliv)\r\n   % [drone 3 did item q]\r\n   dptr=vcmd(3);\r\n   drT(vcmd(1))=drT(vcmd(1))+dw2dw(drIdx(vcmd(1)),dptr)+1; % dist+drop\r\n   drIdx(vcmd(1))=dptr;\r\n   for j=1:vcmd(5)\r\n    iptr=find(dlist(dptr,:)==vcmd(4),1,'first');\r\n    if ~isempty(iptr)\r\n     dlist(dptr,iptr)=0;\r\n    else %Excess item being delivered\r\n     flag=1;\r\n     fprintf('Excess delivery of item %i at cmds %i\\n',vcmd(4),i)\r\n     break\r\n    end\r\n   end\r\n   if flag==1,break;end %Excess delivery break\r\n   drL(vcmd(1),vcmd(4))=drL(vcmd(1),vcmd(4))-vcmd(5);\r\n   drW(vcmd(1))=drW(vcmd(1))-vcmd(5)*vpwt(vcmd(4)); % Unload item(s) wt delivered\r\n   if drL(vcmd(1),vcmd(4))\u003c0\r\n    flag=1;\r\n    fprintf('Non-existent itme delivery attempt. Item %i cmds %i\\n',vcmd(4),i)\r\n    break;\r\n   end\r\n   dt(dptr)=max(dt(dptr),drT(vcmd(1)));\r\n  end % Load/Delivery \r\n end % cmds\r\n \r\n if flag\r\n  scr=0;\r\n else\r\n  dt(sum(dlist,2)\u003e0)=nturns; %Non-completed delivery scores Zero\r\n  dt(dt\u003enturns)=nturns; %Completed beyond time limit scores 0\r\n  scr= sum( ceil(100*(nturns-dt(:))/nturns) ); \r\n end\r\n fprintf('scr: %i\\n',scr)\r\n \r\n\r\nassert(scr\u003e110000)\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":1,"created_by":3097,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":1,"test_suite_updated_at":"2020-09-27T22:00:47.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2020-09-26T18:26:41.000Z","updated_at":"2025-12-08T15:43:28.000Z","published_at":"2020-09-27T00:08:03.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe 2020 \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"https://www.kaggle.com/c/hashcode-drone-delivery\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eKaggle Drone\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e contest is an optimization task to maximize net customer satisfaction by using 30 drones across 10 warehouses to fulfill 1250 customer multi-item, 400 distinct items(products), orders. Satisfaction is (1-delivery_time/max_time)*100 and 0 if delivery not completed by max_time. The max time of 112993 is easily beaten with typical worse time of 40K. \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis contest subset has disabled moving items from warehouse to warehouse thus wait times are not used.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe maximum score is 125000. To succeed as a DroneManager requires a score of 110K, 5th at Kaggle contest 9/26/20.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eInput:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e [rows,cols,numdrones,maxturns,maxDronewt,numproducts,numOrders,delivery_xy_qty,delivery_list,distance_delivery\u0026amp;warehouse_to_delivery\u0026amp;warehouse, distance_warehouse_to_delivery,permutation_cell_array_for1to9]\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eOutput:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e Commands matrix [number of commands,5]  The number of commands is likely to be 18K to 20K.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eLoading from a warehouse: [drone# 1 warehouse# item# quantity]. Drone1:30, Warehouse1:10, Item1:400. The 1 is LOAD.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eOnly one item type can be loaded on to drone at a time. Each Load/Deliver command consumes 1 unit of time.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eDelivery for an order:  [drone# 3 delivery# item# quantity]. Drone1:30, Delivery1:1250, Item1:400. The 3 is Deliver.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe final delivery time for an order is the latest drone time inclusive of final delivery time unit.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eAdditional approach comments are at \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"https://www.kaggle.com/c/hashcode-drone-delivery/discussion/186050\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eKaggle Drone 111401\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e and in the template along with using a provided routine to create a Kaggle python submission 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Planetoid Game of Life - Total Score 0.10","description":null,"description_html":"\u003cdiv style = \"text-align: start; line-height: 20.4333px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 482.167px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 241.083px; transform-origin: 407px 241.083px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 84px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 42px; text-align: left; transform-origin: 384px 42px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003ca target='_blank' href = \"https://www.kaggle.com/c/conways-reverse-game-of-life-2020\"\u003e\u003cspan style=\"\"\u003e\u003cspan style=\"\"\u003eKaggle's Conway's Reverse Game of Life 2020 \u003c/span\u003e\u003c/span\u003e\u003c/a\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 203.05px 7.91667px; transform-origin: 203.05px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003econtest inspires this Life challenge. The kaggle contest runs from Oct-01-2020 thru Nov-30-2020. References:\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 1.95px 7.91667px; transform-origin: 1.95px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e \u003c/span\u003e\u003c/span\u003e\u003ca target='_blank' href = \"http://mathworld.wolfram.com/GameofLife.html\"\u003e\u003cspan style=\"\"\u003e\u003cspan style=\"\"\u003eGame of Life at Wolfram\u003c/span\u003e\u003c/span\u003e\u003c/a\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 1.95px 7.91667px; transform-origin: 1.95px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e.\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 1.95px 7.91667px; transform-origin: 1.95px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e \u003c/span\u003e\u003c/span\u003e\u003ca target='_blank' href = \"http://en.wikipedia.org/wiki/Conway%27s_Game_of_Life\"\u003e\u003cspan style=\"\"\u003e\u003cspan style=\"\"\u003eWiki Life\u003c/span\u003e\u003c/span\u003e\u003c/a\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 138.467px 7.91667px; transform-origin: 138.467px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e. The Kaggle event is 50K cases to solve for a state 1 to 5 iterations prior to a given state. Imperfect solutions are allowed but penalized. Input file to Kaggle is a csv so Matlab solutions can be posted at the Kaggle site for this event.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 21px; text-align: left; transform-origin: 384px 21px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 379.783px 7.91667px; transform-origin: 379.783px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThis Challenge is to Solve the 50K puzzles with a Score \u0026lt;= 0.10, Kaggle Top 25 result, per these revised Life Laws. Trivial solutions are where the Final state may match the Start State.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgb(247, 247, 247); block-size: 102.167px; border-bottom-left-radius: 4px; border-bottom-right-radius: 4px; border-end-end-radius: 4px; border-end-start-radius: 4px; border-start-end-radius: 4px; border-start-start-radius: 4px; border-top-left-radius: 4px; border-top-right-radius: 4px; margin-block-end: 10px; margin-block-start: 10px; margin-bottom: 10px; margin-inline-end: 3px; margin-inline-start: 3px; margin-left: 3px; margin-right: 3px; margin-top: 10px; perspective-origin: 404px 51.0833px; transform-origin: 404px 51.0833px; margin-left: 3px; margin-top: 10px; margin-bottom: 10px; margin-right: 3px; \"\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 0.833333px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.833333px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.833333px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.833333px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 350.35px 7.91667px; transform-origin: 350.35px 7.91667px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 26.95px 7.91667px; transform-origin: 26.95px 7.91667px; \"\u003e1. Any \u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(170, 4, 249); border-block-start-color: rgb(170, 4, 249); border-bottom-color: rgb(170, 4, 249); border-inline-end-color: rgb(170, 4, 249); border-inline-start-color: rgb(170, 4, 249); border-left-color: rgb(170, 4, 249); border-right-color: rgb(170, 4, 249); border-top-color: rgb(170, 4, 249); caret-color: rgb(170, 4, 249); color: rgb(170, 4, 249); column-rule-color: rgb(170, 4, 249); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(170, 4, 249); perspective-origin: 188.65px 7.91667px; text-decoration: none; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); transform-origin: 188.65px 7.91667px; \"\u003elive cell with fewer than two live neighbors dies\u003c/span\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 19.25px 7.91667px; transform-origin: 19.25px 7.91667px; \"\u003e, as \u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(170, 4, 249); border-block-start-color: rgb(170, 4, 249); border-bottom-color: rgb(170, 4, 249); border-inline-end-color: rgb(170, 4, 249); border-inline-start-color: rgb(170, 4, 249); border-left-color: rgb(170, 4, 249); border-right-color: rgb(170, 4, 249); border-top-color: rgb(170, 4, 249); caret-color: rgb(170, 4, 249); color: rgb(170, 4, 249); column-rule-color: rgb(170, 4, 249); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(170, 4, 249); perspective-origin: 115.5px 7.91667px; text-decoration: none; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); transform-origin: 115.5px 7.91667px; \"\u003eif caused by under-population.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 0.833333px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.833333px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.833333px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.833333px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 315.7px 7.91667px; transform-origin: 315.7px 7.91667px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 26.95px 7.91667px; transform-origin: 26.95px 7.91667px; \"\u003e2. Any \u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(170, 4, 249); border-block-start-color: rgb(170, 4, 249); border-bottom-color: rgb(170, 4, 249); border-inline-end-color: rgb(170, 4, 249); border-inline-start-color: rgb(170, 4, 249); border-left-color: rgb(170, 4, 249); border-right-color: rgb(170, 4, 249); border-top-color: rgb(170, 4, 249); caret-color: rgb(170, 4, 249); color: rgb(170, 4, 249); column-rule-color: rgb(170, 4, 249); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(170, 4, 249); perspective-origin: 288.75px 7.91667px; text-decoration: none; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); transform-origin: 288.75px 7.91667px; \"\u003elive cell with two or three live neighbors lives on to the next generation.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 0.833333px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.833333px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.833333px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.833333px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 311.85px 7.91667px; transform-origin: 311.85px 7.91667px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 26.95px 7.91667px; transform-origin: 26.95px 7.91667px; \"\u003e3. Any \u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(170, 4, 249); border-block-start-color: rgb(170, 4, 249); border-bottom-color: rgb(170, 4, 249); border-inline-end-color: rgb(170, 4, 249); border-inline-start-color: rgb(170, 4, 249); border-left-color: rgb(170, 4, 249); border-right-color: rgb(170, 4, 249); border-top-color: rgb(170, 4, 249); caret-color: rgb(170, 4, 249); color: rgb(170, 4, 249); column-rule-color: rgb(170, 4, 249); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(170, 4, 249); perspective-origin: 192.5px 7.91667px; text-decoration: none; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); transform-origin: 192.5px 7.91667px; \"\u003elive cell with more than three live neighbors dies\u003c/span\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 19.25px 7.91667px; transform-origin: 19.25px 7.91667px; \"\u003e, as \u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(170, 4, 249); border-block-start-color: rgb(170, 4, 249); border-bottom-color: rgb(170, 4, 249); border-inline-end-color: rgb(170, 4, 249); border-inline-start-color: rgb(170, 4, 249); border-left-color: rgb(170, 4, 249); border-right-color: rgb(170, 4, 249); border-top-color: rgb(170, 4, 249); caret-color: rgb(170, 4, 249); color: rgb(170, 4, 249); column-rule-color: rgb(170, 4, 249); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(170, 4, 249); perspective-origin: 73.15px 7.91667px; text-decoration: none; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); transform-origin: 73.15px 7.91667px; \"\u003eif by overcrowding.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 0.833333px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.833333px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.833333px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.833333px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 361.9px 7.91667px; transform-origin: 361.9px 7.91667px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 26.95px 7.91667px; transform-origin: 26.95px 7.91667px; \"\u003e4. Any \u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(170, 4, 249); border-block-start-color: rgb(170, 4, 249); border-bottom-color: rgb(170, 4, 249); border-inline-end-color: rgb(170, 4, 249); border-inline-start-color: rgb(170, 4, 249); border-left-color: rgb(170, 4, 249); border-right-color: rgb(170, 4, 249); border-top-color: rgb(170, 4, 249); caret-color: rgb(170, 4, 249); color: rgb(170, 4, 249); column-rule-color: rgb(170, 4, 249); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(170, 4, 249); perspective-origin: 242.55px 7.91667px; text-decoration: none; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); transform-origin: 242.55px 7.91667px; \"\u003edead cell with exactly three live neighbors becomes a live cell\u003c/span\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 19.25px 7.91667px; transform-origin: 19.25px 7.91667px; \"\u003e, as \u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(170, 4, 249); border-block-start-color: rgb(170, 4, 249); border-bottom-color: rgb(170, 4, 249); border-inline-end-color: rgb(170, 4, 249); border-inline-start-color: rgb(170, 4, 249); border-left-color: rgb(170, 4, 249); border-right-color: rgb(170, 4, 249); border-top-color: rgb(170, 4, 249); caret-color: rgb(170, 4, 249); color: rgb(170, 4, 249); column-rule-color: rgb(170, 4, 249); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(170, 4, 249); perspective-origin: 73.15px 7.91667px; text-decoration: none; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); transform-origin: 73.15px 7.91667px; \"\u003eif by reproduction.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 0.833333px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.833333px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.833333px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.833333px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 265.65px 7.91667px; transform-origin: 265.65px 7.91667px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 34.65px 7.91667px; transform-origin: 34.65px 7.91667px; \"\u003e5. Edges \u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(170, 4, 249); border-block-start-color: rgb(170, 4, 249); border-bottom-color: rgb(170, 4, 249); border-inline-end-color: rgb(170, 4, 249); border-inline-start-color: rgb(170, 4, 249); border-left-color: rgb(170, 4, 249); border-right-color: rgb(170, 4, 249); border-top-color: rgb(170, 4, 249); caret-color: rgb(170, 4, 249); color: rgb(170, 4, 249); column-rule-color: rgb(170, 4, 249); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(170, 4, 249); perspective-origin: 231px 7.91667px; text-decoration: none; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); transform-origin: 231px 7.91667px; \"\u003ewrap around. Eight Neighbors. (Change to normal planar life)\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 10px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 10px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 10px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 221.317px 7.91667px; transform-origin: 221.317px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eNote: The edges wrap so the matrix represents the surface of a sphere.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 19.4333px 7.91667px; transform-origin: 19.4333px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eInput:\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 254.75px 7.91667px; transform-origin: 254.75px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e (mtest) the Finish state matrix of 50K rows of [casenumber, iterations, 625 values]\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 25.2667px 7.91667px; transform-origin: 25.2667px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eOutput:\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 233.35px 7.91667px; transform-origin: 233.35px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e (mstart) the Starting state matrix of 50K puzzles, [casenumber, 625 values]\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 39.9333px 7.91667px; transform-origin: 39.9333px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eTop Scores:\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 96.8667px 7.91667px; transform-origin: 96.8667px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e Zapor: 0.0818, 2556293 errors\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 105px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 52.5px; text-align: left; transform-origin: 384px 52.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 15.95px 7.91667px; transform-origin: 15.95px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eHint:\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 356.9px 7.91667px; transform-origin: 356.9px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e A Greedy Complete Single Adjacent bit flip can score \u0026lt;.0.09. Non-optimized processing time for Greedy Complete was 25Ksec. Candidate bits to flip are all wrap-convolve of Goal matrix with kernel ones(3). First test for trivial solution. Process all  bit flips on current optimal solution starting with Goal matrix. Make first best scoring solution the new optimal solution. Iterate on optimal solutions until no improvement on any single candidate bit flip. Greedy Complete for iterations=1 creates 176 solves not counting the 532 Trivial iteration 1 cases.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function mstart = solveLife(mtest)\r\n  %mstart=zeros(50000,626);  column 1 values should range from 50000:99999, other columns 0/1\r\n  urlname='';\r\n  urlwrite(urlname,'mstart.mat')\r\n  load('mstart.mat'); \r\n  \r\n  %Processing to \u003c0.10 Score is unlikely in Cody's 60 seconds\r\n  %Process offline mtest.mat file below.\r\n  %Create an mstart.mat file   using save('mstart.mat','mstart')  about 5.6MB\r\n  %Post the mstart.mat file in the cloud to download\r\n  %Copy the link location into urlname=''; above\r\n  \r\n  %Source data arrray to process mtest\r\n  %fname='https://sites.google.com/site/razapor/matlab_cody/mtest.mat?attredirects=0\u0026d=1';\r\n  %urlwrite(fname,'mtest.mat') %1.22s\r\n  %load('mtest.mat'); %0.42s\r\nend","test_suite":"%%\r\n%'https://sites.google.com/site/razapor/matlab_cody/mtest.mat?attredirects=0\u0026d=1';\r\n%mtest format is [casenumer, iterations, start1:625,finish1:625] for 50K cases 0:49999\r\n%'https://sites.google.com/site/razapor/matlab_cody/mtrain.mat?attredirects=0\u0026d=1';\r\nfname='https://sites.google.com/site/razapor/matlab_cody/mtest.mat?attredirects=0\u0026d=1';\r\nurlwrite(fname,'mtest.mat') %1.22s\r\nload('mtest.mat'); %0.42s\r\n\r\ncerr=zeros(50000,1);\r\nfor i=1:50000\r\n cerr(i)=nnz(mtest(i,3:end));\r\nend\r\n\r\ntic\r\nmstart = solveLife(mtest);\r\ntoc\r\nmstart=unique(mstart,'rows'); % remove exact duplicate solutions\r\n\r\n%Calc errors for each case submitted, otherwise use 0 input errors\r\ntic\r\nfor i=1:size(mstart,1)  % \r\n icase=mstart(i,1); %50000:99999\r\n Abase=reshape(mtest(icase-49999,3:end),25,25);;\r\n iter=mtest(icase-49999,2); %Test cases start at 50000\r\n \r\n A=reshape(mstart(i,2:end),25,25);\r\n \r\n for j=1:iter\r\n  C=0;\r\n  for r=-1:1 % -1 Up   Using circshift to perform wrap convolution\r\n   Ar=circshift(A,r,1);\r\n   for c=-1:1 % -1 Left\r\n     Arc=circshift(Ar,c,2);\r\n     C=C+Arc;\r\n   end\r\n  end\r\n  A = C==3 | A\u0026C==4;\r\n end %j\r\n cerr(icase-49999)=nnz(Abase-A);\r\n \r\nend %main loop i\r\ntoc  % 4.5s\r\n\r\nScore=sum(cerr)/50000/625;\r\nfprintf('Score %.4f  Total Errors: %i\\n',Score,sum(cerr));\r\n\r\nassert(Score\u003c=0.10)\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":3097,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":1,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2020-10-07T15:47:15.000Z","updated_at":"2020-10-07T16:39:36.000Z","published_at":"2020-10-07T16:39:36.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:hyperlink w:docLocation=\\\"https://www.kaggle.com/c/conways-reverse-game-of-life-2020\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eKaggle's Conway's Reverse Game of Life 2020 \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003econtest inspires this Life challenge. The kaggle contest runs from Oct-01-2020 thru Nov-30-2020. References:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"http://mathworld.wolfram.com/GameofLife.html\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eGame of Life at Wolfram\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e.\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"http://en.wikipedia.org/wiki/Conway%27s_Game_of_Life\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eWiki Life\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e. The Kaggle event is 50K cases to solve for a state 1 to 5 iterations prior to a given state. Imperfect solutions are allowed but penalized. Input file to Kaggle is a csv so Matlab solutions can be posted at the Kaggle site for this event.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis Challenge is to Solve the 50K puzzles with a Score \u0026lt;= 0.10, Kaggle Top 25 result, per these revised Life Laws. Trivial solutions are where the Final state may match the Start State.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[1. Any live cell with fewer than two live neighbors dies, as if caused by under-population.\\n2. Any live cell with two or three live neighbors lives on to the next generation.\\n3. Any live cell with more than three live neighbors dies, as if by overcrowding.\\n4. Any dead cell with exactly three live neighbors becomes a live cell, as if by reproduction.\\n5. Edges wrap around. Eight Neighbors. (Change to normal planar life)]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eNote: The edges wrap so the matrix represents the surface of a sphere.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eInput:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e (mtest) the Finish state matrix of 50K rows of [casenumber, iterations, 625 values]\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eOutput:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e (mstart) the Starting state matrix of 50K puzzles, [casenumber, 625 values]\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eTop Scores:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e Zapor: 0.0818, 2556293 errors\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eHint:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e A Greedy Complete Single Adjacent bit flip can score \u0026lt;.0.09. Non-optimized processing time for Greedy Complete was 25Ksec. Candidate bits to flip are all wrap-convolve of Goal matrix with kernel ones(3). First test for trivial solution. Process all  bit flips on current optimal solution starting with Goal matrix. Make first best scoring solution the new optimal solution. Iterate on optimal solutions until no improvement on any single candidate bit flip. Greedy Complete for iterations=1 creates 176 solves not counting the 532 Trivial iteration 1 cases.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":788,"title":"Tiles Contest: Perfect Solutions for Large Unique Tile  Boards","description":"*Tiles Contest:* The Large Unique Boards/Tiles that perfectly solve (50x50)\r\n\r\nReturn Perfect solutions for both boards. Scoring will be based upon size and time.\r\n\r\nSample \"Board 59\" and Actual(Contest) \"Board 6\" have perfect solutions with unique tiles. The tiles are unique with any number,except zero, occurring exactly twice.\r\n\r\nThe complete description of \u003chttp://www.mathworks.com/matlabcentral/contest/contests/36/rules Tiles\u003e explains what is a tile, orientation, and board output.\r\n\r\n*Input:* (boardsize, tiles)\r\n\r\n*Output:* (board, orientation)\r\n\r\n*Passing:* Two Perfect Boards.\r\n\r\n*Scoring:* Based upon Size/10 and Average Time(msec) of solutions.\r\n\r\n\r\nThe Test Suite demonstrates urlwrite usage with a customized tinyurl from an http site for acessing web mat files.\r\n\r\n\r\n\r\nThis is the first in a series of Tiles Contest challenges where the boards have interesting characteristics.  There are multiple perfect solution boards which were not solved during the contest.\r\n","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.4333px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 333px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 166.5px; transform-origin: 407px 166.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 46.15px 7.91667px; transform-origin: 46.15px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eTiles Contest:\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 184.517px 7.91667px; transform-origin: 184.517px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e The Large Unique Boards/Tiles that perfectly solve (50x50)\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 256.35px 7.91667px; transform-origin: 256.35px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eReturn Perfect solutions for both boards. Scoring will be based upon size and time.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 21px; text-align: left; transform-origin: 384px 21px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 370.917px 7.91667px; transform-origin: 370.917px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eSample \"Board 59\" and Actual(Contest) \"Board 6\" have perfect solutions with unique tiles. The tiles are unique with any number,except zero, occurring exactly twice.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 87.9167px 7.91667px; transform-origin: 87.9167px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThe complete description of \u003c/span\u003e\u003c/span\u003e\u003ca target='_blank' href = \"https://web.archive.org/web/20150224170744/http://www.mathworks.com/matlabcentral/contest/contests/36/rules\"\u003e\u003cspan style=\"\"\u003e\u003cspan style=\"\"\u003eTiles_wayback\u003c/span\u003e\u003c/span\u003e\u003c/a\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 1.95px 7.91667px; transform-origin: 1.95px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e \u003c/span\u003e\u003c/span\u003e\u003ca target='_blank' href = \"http://www.mathworks.com/matlabcentral/contest/contests/36/rules\"\u003e\u003cspan style=\"\"\u003e\u003cspan style=\"\"\u003eTiles\u003c/span\u003e\u003c/span\u003e\u003c/a\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 163.383px 7.91667px; transform-origin: 163.383px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e explains what is a tile, orientation, and board output.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 19.4333px 7.91667px; transform-origin: 19.4333px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eInput:\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 53.3px 7.91667px; transform-origin: 53.3px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e (boardsize, tiles)\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 25.2667px 7.91667px; transform-origin: 25.2667px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eOutput:\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 61.0833px 7.91667px; transform-origin: 61.0833px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e (board, orientation)\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 29.1667px 7.91667px; transform-origin: 29.1667px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003ePassing:\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 64.95px 7.91667px; transform-origin: 64.95px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e Two Perfect Boards.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 28.3833px 7.91667px; transform-origin: 28.3833px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eScoring:\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 184px 7.91667px; transform-origin: 184px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e Based upon Size/10 and Average Time(msec) of solutions.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 349.283px 7.91667px; transform-origin: 349.283px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThe Test Suite demonstrates urlwrite usage with a customized tinyurl from an http site for acessing web mat files.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 21px; text-align: left; transform-origin: 384px 21px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 380.933px 7.91667px; transform-origin: 380.933px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThis is the first in a series of Tiles Contest challenges where the boards have interesting characteristics. There are multiple perfect solution boards which were not solved during the contest.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function [board,orientation]=board_perfect(boardSize,tiles);\r\n  board=zeros(boardSize);\r\n  numtiles=size(tiles,1);\r\n  orientation=ones(numtiles,1);\r\n\r\n%Hint to help solve the board - This was a major contest innovation\r\n % te  Tiles expanded format 4*tiles, 4\r\n te = [t; t(:,[2:4,1]); t(:,[3:4,1:2]); t(:,[4,1:3])]; % 4*numtiles x 4\r\n \r\nend","test_suite":"%%\r\nfeval(@assignin,'caller','score',2000);\r\n%%\r\nformat short\r\nformat compact\r\n\r\nglobal net_time\r\n\r\n%fn='http://tinyurl.com/zapor-Tiles-sample-mat'; \r\n%fn='http://tinyurl.com/matlab-tiles-mat';\r\n%testsuite_sample.mat\r\nfn='https://sites.google.com/site/razapor/matlab_cody/testsuite_Tiles_sample.mat?attredirects=0\u0026d=1';\r\n\r\n\r\ntestSuiteFile = 'raz_tiles.mat';\r\nurlwrite(fn,testSuiteFile);\r\n\r\nbrd=59;\r\ntests = load(testSuiteFile,'testsuite');\r\ntiles = tests.testsuite(brd).tiles;\r\nrows = tests.testsuite(brd).r;\r\ncols = tests.testsuite(brd).c;\r\nboardSize = [rows, cols];\r\n\r\n[board,orientation]=board_perfect(boardSize,tiles); % run twice for timing\r\nt0=clock;\r\n[board,orientation]=board_perfect(boardSize,tiles);\r\ndt=etime(clock,t0)*1e3;\r\n\r\n% verify score\r\n t=tiles;\r\n ntiles=size(tiles,1);\r\n te = [t; t(:,[2:4,1]); t(:,[3:4,1:2]); t(:,[4,1:3])];\r\n \r\n % build check arrays UD, LR\r\n LR=zeros(rows,2*cols);\r\n UD=zeros(2*rows,cols);\r\n for r=1:rows\r\n  for c=1:cols\r\n   tptr=board(r,c);\r\n   tor=orientation(tptr);\r\n   UD(2*r-1,c)=te(tptr+ntiles*(tor-1),1);\r\n   UD(2*r,c)=te(tptr+ntiles*(tor-1),3);\r\n   LR(r,2*c-1)=te(tptr+ntiles*(tor-1),4);\r\n   LR(r,2*c)=te(tptr+ntiles*(tor-1),2);\r\n  end\r\n end\r\n checksum=sum([LR(:,1)' LR(:,end)' UD(1,:) UD(end,:)]);\r\n for idx=2:2:2*rows-2 % LR Square array assumed here\r\n  checksum=checksum+sum(LR(:,idx)-LR(:,idx+1))+sum(UD(idx,:)-UD(idx+1,:));\r\n end\r\n\r\n\r\nassert(checksum==0,sprintf('Checksum = %s\\n',num2str(checksum)));\r\nnet_time=dt\r\n%%\r\nglobal net_time\r\ntemp=net_time; % anti-cheat\r\n\r\n%fn='http://tinyurl.com/zapor-Tiles-contest-mat';\r\n%fn='http://tinyurl.com/matlab-tilesC-mat';\r\n%testsuite_actual.mat\r\nfn='https://sites.google.com/site/razapor/matlab_cody/testsuite_Tiles_contest.mat?attredirects=0\u0026d=1';\r\n\r\n\r\ntestSuiteFile = 'raz_tiles.mat';\r\nurlwrite(fn,testSuiteFile);\r\n\r\nbrd=6;\r\ntests = load(testSuiteFile,'testsuite');\r\ntiles = tests.testsuite(brd).tiles;\r\nrows = tests.testsuite(brd).r;\r\ncols = tests.testsuite(brd).c;\r\nboardSize = [rows, cols];\r\n\r\n[board,orientation]=board_perfect(boardSize,tiles); % run twice for timing\r\nt0=clock;\r\n[board,orientation]=board_perfect(boardSize,tiles);\r\ndt=etime(clock,t0)*1e3\r\n\r\n% verify score\r\n t=tiles;\r\n ntiles=size(tiles,1);\r\n te = [t; t(:,[2:4,1]); t(:,[3:4,1:2]); t(:,[4,1:3])];\r\n \r\n % build check arrays UD, LR\r\n LR=zeros(rows,2*cols);\r\n UD=zeros(2*rows,cols);\r\n for r=1:rows\r\n  for c=1:cols\r\n   tptr=board(r,c);\r\n   tor=orientation(tptr);\r\n   UD(2*r-1,c)=te(tptr+ntiles*(tor-1),1);\r\n   UD(2*r,c)=te(tptr+ntiles*(tor-1),3);\r\n   LR(r,2*c-1)=te(tptr+ntiles*(tor-1),4);\r\n   LR(r,2*c)=te(tptr+ntiles*(tor-1),2);\r\n  end\r\n end\r\n checksum=sum([LR(:,1)' LR(:,end)' UD(1,:) UD(end,:)]);\r\n for idx=2:2:2*rows-2 % LR Square array assumed here\r\n  checksum=checksum+sum(LR(:,idx)-LR(:,idx+1))+sum(UD(idx,:)-UD(idx+1,:));\r\n end\r\n\r\n\r\nassert(checksum==0,sprintf('Checksum = %s\\n',num2str(checksum)));\r\nnet_time=(dt+temp)/2\r\n%%\r\nglobal net_time\r\n\r\n% Limit Score to 2000 for graph quality\r\nt=mtree('board_perfect.m','-file');\r\nscr=floor(length(t.nodesize)/10+net_time);\r\nscr=min(scr,2000)\r\n\r\nfeval(@assignin,'caller','score',floor(scr));\r\n\r\n\r\n%fh=fopen('board_perfect.m','wt');\r\n%fprintf(fh,'%s\\n',repmat('1;',[1,round(scr/2)]));\r\n%fclose(fh);\r\n\r\n\r\n\r\n\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":2,"created_by":3097,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":1,"test_suite_updated_at":"2020-10-08T17:49:19.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2012-06-25T01:21:51.000Z","updated_at":"2025-05-05T20:22:13.000Z","published_at":"2012-06-26T18:09:51.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eTiles Contest:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e The Large Unique Boards/Tiles that perfectly solve (50x50)\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eReturn Perfect solutions for both boards. Scoring will be based upon size and time.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eSample \\\"Board 59\\\" and Actual(Contest) \\\"Board 6\\\" have perfect solutions with unique tiles. The tiles are unique with any number,except zero, occurring exactly twice.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe complete description of \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"https://web.archive.org/web/20150224170744/http://www.mathworks.com/matlabcentral/contest/contests/36/rules\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eTiles_wayback\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"http://www.mathworks.com/matlabcentral/contest/contests/36/rules\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eTiles\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e explains what is a tile, orientation, and board output.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eInput:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e (boardsize, tiles)\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eOutput:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e (board, orientation)\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ePassing:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e Two Perfect Boards.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eScoring:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e Based upon Size/10 and Average Time(msec) of solutions.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe Test Suite demonstrates urlwrite usage with a customized tinyurl from an http site for acessing web mat files.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis is the first in a series of Tiles Contest challenges where the boards have interesting characteristics. There are multiple perfect solution boards which were not solved during the contest.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":937,"title":"Rubik's Mini Cube: Solve Randomized Cube in 11 Moves or Less; Score is by Time (msec)","description":"The Challenge is to Near or Optimally Solve a thoroughly scrambled Mini-Rubik's Cube(2x2x2).\r\n\r\nAny Mini-Cube can be solved in 11 or fewer Face Moves. There are only 3,674,160 unique cube positions, with only 2344 requiring the fulll 11 moves. Cube moves do not count.\r\n\r\nThe Performance metric is cumulative Time to Solve 500 cubes (msec).\r\n\r\nA standard Mini-Rubik's Cube is shown in 3-D and also unfolded to identify the specific Tile-face/Vector numbering.\r\n\r\nThe faces are White-Up / Red-Left / Blue-Front / Orange-Right / Yellow-Down / Green-Back (ULFRDB)\r\n\r\nMoves are denoted as F for clockwise rotation of the Front face. F'(or FP) is CCW and F2 is F twice.  The provided function r_new=rubick_rot_mini(mov,r) implements moves 1-18: UFDLBRU'F'D'L'B'R'U2F2D2L2B2R2.\r\n\r\n\r\n\r\n\r\n\u003c\u003chttps://sites.google.com/site/razapor/matlab_cody/minicube2.png\u003e\u003e\r\n\r\n\u003c\u003chttps://sites.google.com/site/razapor/matlab_cody/miniCube_Map24_200.png\u003e\u003e\r\n\r\n\u003c\u003chttp://mathworks.com/matlabcentral/images/surf.gif\u003e\u003e\r\n\r\n\r\n  \r\n  \r\n  Input: (rubik)\r\n  \r\n  rubik: row vector of size 24\r\n  (The cube started [L=0,U=1,F=2,D=3,B=4,R=5] and then receives forty face moves.\r\n\r\n  Output: move_vec (Numeric of moves to solve)\r\n   move_vec:values 1:27 for UFDLBR U'F'D'L'B'R' U2F2D2L2B2R2 XYZX'Y'Z'X2Y2Z2\r\n\r\n* Example:\r\n* If the cube was randomized by [1 9] UD', one solution is [3 7]  which are the complements in reverse order. \r\n* Scoring is Time in msec to solve 500 cubes\r\n* Cube Moves X, Y, and Z do not constitute a move but are needed in the vector \r\n* A string to numeric value function is provided in the template\r\n* Verifications will be by executing your move vector against the provided Rubik and counting number of face moves.\r\n\r\nThe function rubik_rot_mini(mov,r) is provided in the template. Other functions are provided to re-orient the cube in Cody Challenge 931, Rubik's Mini-Cube.\r\n\r\n\r\nThe Challenge \u003chttp://www.mathworks.com/matlabcentral/cody/problems/931-rubik-s-mini-cube-solve-randomized-mini-cube-score-moves.html Challenge 931 Rubik's Mini-Cube\u003e contains a 3D Mini-Cube Viewer for program development.\r\n\r\n\r\n* \r\n* \u003chttp://kociemba.org/cube.htm Cube Theory: 20-moves Any Cube\u003e \r\n* \u003chttp://peter.stillhq.com/jasmine/rubikscubesolution.html General Cube Info and Middle Layer\u003e\r\n* \u003chttp://www.speedcubing.com/final_layer_print.html SpeedCube Bottom Sequences\u003e\r\n* The site \u003chttp://www.speedcubing.com/CubeSolver/MiniCubeSolver.html MiniCube Solver\u003e claims an outstanding 10 minutes to solve a randomized Mini-Cube. Matlab can achieve any Mini-Cube solution in \u003c 497 usec, independent of moves on an i5/16GB machine.\r\n\r\n\r\n(Note: Mini-Cube can use the full cube moves and ignore edge effects)\r\n\r\nComing Soon: Matlab Tetris\r\n","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.4333px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 1316.98px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 658.5px; transform-origin: 407px 658.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 294.65px 7.91667px; transform-origin: 294.65px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThe Challenge is to Near or Optimally Solve a thoroughly scrambled Mini-Rubik's Cube(2x2x2).\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 21px; text-align: left; transform-origin: 384px 21px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 377.2px 7.91667px; transform-origin: 377.2px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eAny Mini-Cube can be solved in 11 or fewer Face Moves. There are only 3,674,160 unique cube positions, with only 2344 requiring the fulll 11 moves. Cube moves do not count.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 221.45px 7.91667px; transform-origin: 221.45px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThe Performance metric is cumulative Time to Solve 500 cubes (msec).\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 355.467px 7.91667px; transform-origin: 355.467px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eA standard Mini-Rubik's Cube is shown in 3-D and also unfolded to identify the specific Tile-face/Vector numbering.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 316.733px 7.91667px; transform-origin: 316.733px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThe faces are White-Up / Red-Left / Blue-Front / Orange-Right / Yellow-Down / Green-Back (ULFRDB)\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 21px; text-align: left; transform-origin: 384px 21px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 380.533px 7.91667px; transform-origin: 380.533px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eMoves are denoted as F for clockwise rotation of the Front face. F'(or FP) is CCW and F2 is F twice. The provided function r_new=rubick_rot_mini(mov,r) implements moves 1-18: UFDLBRU'F'D'L'B'R'U2F2D2L2B2R2.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 138.917px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 69.4667px; text-align: center; transform-origin: 384px 69.4667px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cimg class=\"imageNode\" style=\"vertical-align: baseline\" 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\" 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border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.833333px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.833333px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.833333px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 0px 7.91667px; transform-origin: 0px 7.91667px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 0.833333px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.833333px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.833333px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.833333px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 107.8px 7.91667px; transform-origin: 107.8px 7.91667px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 69.3px 7.91667px; transform-origin: 69.3px 7.91667px; \"\u003erubik: row vector \u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(170, 4, 249); border-block-start-color: rgb(170, 4, 249); border-bottom-color: rgb(170, 4, 249); border-inline-end-color: rgb(170, 4, 249); border-inline-start-color: rgb(170, 4, 249); border-left-color: rgb(170, 4, 249); border-right-color: rgb(170, 4, 249); border-top-color: rgb(170, 4, 249); caret-color: rgb(170, 4, 249); color: rgb(170, 4, 249); column-rule-color: rgb(170, 4, 249); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(170, 4, 249); perspective-origin: 38.5px 7.91667px; text-decoration: none; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); transform-origin: 38.5px 7.91667px; \"\u003eof size 24\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 0.833333px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.833333px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.833333px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.833333px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 304.15px 7.91667px; transform-origin: 304.15px 7.91667px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e(The cube started [L=0,U=1,F=2,D=3,B=4,R=5] and then receives forty face moves.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 0.833333px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.833333px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.833333px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.833333px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 0px 7.91667px; transform-origin: 0px 7.91667px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 0.833333px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.833333px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.833333px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.833333px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 169.4px 7.91667px; transform-origin: 169.4px 7.91667px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003eOutput: move_vec (Numeric of moves to solve)\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 0.833333px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.833333px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.833333px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.833333px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 284.9px 7.91667px; transform-origin: 284.9px 7.91667px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 84.7px 7.91667px; transform-origin: 84.7px 7.91667px; \"\u003e move_vec:values 1:27 \u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(14, 0, 255); border-block-start-color: rgb(14, 0, 255); border-bottom-color: rgb(14, 0, 255); border-inline-end-color: rgb(14, 0, 255); border-inline-start-color: rgb(14, 0, 255); border-left-color: rgb(14, 0, 255); border-right-color: rgb(14, 0, 255); border-top-color: rgb(14, 0, 255); caret-color: rgb(14, 0, 255); color: rgb(14, 0, 255); column-rule-color: rgb(14, 0, 255); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(14, 0, 255); perspective-origin: 15.4px 7.91667px; text-decoration: none; text-decoration-color: rgb(14, 0, 255); text-emphasis-color: rgb(14, 0, 255); transform-origin: 15.4px 7.91667px; \"\u003efor \u003c/span\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 127.05px 7.91667px; transform-origin: 127.05px 7.91667px; \"\u003eUFDLBR U'F'D'L'B'R' U2F2D2L2B2R2 \u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(196, 0, 0); border-block-start-color: rgb(196, 0, 0); border-bottom-color: rgb(196, 0, 0); border-inline-end-color: rgb(196, 0, 0); border-inline-start-color: rgb(196, 0, 0); border-left-color: rgb(196, 0, 0); border-right-color: rgb(196, 0, 0); border-top-color: rgb(196, 0, 0); caret-color: rgb(196, 0, 0); color: rgb(196, 0, 0); column-rule-color: rgb(196, 0, 0); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(196, 0, 0); perspective-origin: 57.75px 7.91667px; text-decoration: none; text-decoration-color: rgb(196, 0, 0); text-emphasis-color: rgb(196, 0, 0); transform-origin: 57.75px 7.91667px; \"\u003eXYZX'Y'Z'X2Y2Z2\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003cul style=\"block-size: 122.6px; counter-reset: list-item 0; font-family: Helvetica, Arial, sans-serif; list-style-type: square; margin-block-end: 20px; margin-block-start: 10px; margin-bottom: 20px; margin-top: 10px; perspective-origin: 391px 61.3px; transform-origin: 391px 61.3px; margin-top: 10px; margin-bottom: 20px; \"\u003e\u003cli style=\"block-size: 20.4333px; counter-reset: none; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 363px 10.2167px; text-align: left; transform-origin: 363px 10.2167px; white-space: pre-wrap; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 29.1833px 7.91667px; transform-origin: 29.1833px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eExample:\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 20.4333px; counter-reset: none; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 363px 10.2167px; text-align: left; transform-origin: 363px 10.2167px; white-space: pre-wrap; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 327.667px 7.91667px; transform-origin: 327.667px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eIf the cube was randomized by [1 9] UD', one solution is [3 7] which are the complements in reverse order.\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 20.4333px; counter-reset: none; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 363px 10.2167px; text-align: left; transform-origin: 363px 10.2167px; white-space: pre-wrap; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 134.333px 7.91667px; transform-origin: 134.333px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eScoring is Time in msec to solve 500 cubes\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 20.4333px; counter-reset: none; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 363px 10.2167px; text-align: left; transform-origin: 363px 10.2167px; white-space: pre-wrap; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 242.583px 7.91667px; transform-origin: 242.583px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eCube Moves X, Y, and Z do not constitute a move but are needed in the vector\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 20.4333px; counter-reset: none; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 363px 10.2167px; text-align: left; transform-origin: 363px 10.2167px; white-space: pre-wrap; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 187.1px 7.91667px; transform-origin: 187.1px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eA string to numeric value function is provided in the template\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 20.4333px; counter-reset: none; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 363px 10.2167px; text-align: left; transform-origin: 363px 10.2167px; white-space: pre-wrap; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 355.933px 7.91667px; transform-origin: 355.933px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eVerifications will be by executing your move vector against the provided Rubik and counting number of face moves.\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ul\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 21px; text-align: left; transform-origin: 384px 21px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 374.067px 7.91667px; transform-origin: 374.067px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThe function rubik_rot_mini(mov,r) is provided in the template. Other functions are provided to re-orient the cube in Cody Challenge 931, Rubik's Mini-Cube.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 45.5333px 7.91667px; transform-origin: 45.5333px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThe Challenge\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 1.95px 7.91667px; transform-origin: 1.95px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e \u003c/span\u003e\u003c/span\u003e\u003ca target='_blank' href = \"http://www.mathworks.com/matlabcentral/cody/problems/931-rubik-s-mini-cube-solve-randomized-mini-cube-score-moves.html\"\u003e\u003cspan style=\"\"\u003e\u003cspan style=\"\"\u003eChallenge 931 Rubik's Mini-Cube\u003c/span\u003e\u003c/span\u003e\u003c/a\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 183.883px 7.91667px; transform-origin: 183.883px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e contains a 3D Mini-Cube Viewer for program development.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cul style=\"block-size: 122.6px; counter-reset: list-item 0; font-family: Helvetica, Arial, sans-serif; list-style-type: square; margin-block-end: 20px; margin-block-start: 10px; margin-bottom: 20px; margin-top: 10px; perspective-origin: 391px 61.3px; transform-origin: 391px 61.3px; margin-top: 10px; margin-bottom: 20px; \"\u003e\u003cli style=\"block-size: 20.4333px; counter-reset: none; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 363px 10.2167px; text-align: left; transform-origin: 363px 10.2167px; white-space: pre-wrap; margin-left: 56px; \"\u003e\u003c/li\u003e\u003cli style=\"block-size: 20.4333px; counter-reset: none; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 363px 10.2167px; text-align: left; transform-origin: 363px 10.2167px; white-space: pre-wrap; margin-left: 56px; \"\u003e\u003ca target='_blank' href = \"http://kociemba.org/cube.htm\"\u003e\u003cspan style=\"\"\u003e\u003cspan style=\"\"\u003eCube Theory: 20-moves Any Cube\u003c/span\u003e\u003c/span\u003e\u003c/a\u003e\u003c/li\u003e\u003cli style=\"block-size: 20.4333px; counter-reset: none; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 363px 10.2167px; text-align: left; transform-origin: 363px 10.2167px; white-space: pre-wrap; margin-left: 56px; \"\u003e\u003ca target='_blank' href = \"http://peter.stillhq.com/jasmine/rubikscubesolution.html\"\u003e\u003cspan style=\"\"\u003e\u003cspan style=\"\"\u003eGeneral Cube Info and Middle Layer\u003c/span\u003e\u003c/span\u003e\u003c/a\u003e\u003c/li\u003e\u003cli style=\"block-size: 20.4333px; counter-reset: none; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 363px 10.2167px; text-align: left; transform-origin: 363px 10.2167px; white-space: pre-wrap; margin-left: 56px; \"\u003e\u003ca target='_blank' href = \"http://www.speedcubing.com/final_layer_print.html\"\u003e\u003cspan style=\"\"\u003e\u003cspan style=\"\"\u003eSpeedCube Bottom Sequences\u003c/span\u003e\u003c/span\u003e\u003c/a\u003e\u003c/li\u003e\u003cli style=\"block-size: 40.8667px; counter-reset: none; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 363px 20.4333px; text-align: left; transform-origin: 363px 20.4333px; white-space: pre-wrap; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 24.9px 7.91667px; transform-origin: 24.9px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThe site\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 1.95px 7.91667px; transform-origin: 1.95px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e \u003c/span\u003e\u003c/span\u003e\u003ca target='_blank' href = \"http://www.speedcubing.com/CubeSolver/MiniCubeSolver.html\"\u003e\u003cspan style=\"\"\u003e\u003cspan style=\"\"\u003eMiniCube Solver\u003c/span\u003e\u003c/span\u003e\u003c/a\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 276.2px 7.91667px; transform-origin: 276.2px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e claims an outstanding 10 minutes to solve a randomized Mini-Cube. Matlab can achieve any Mini-Cube solution in \u0026lt; 497 usec, independent of moves on an i5/16GB machine.\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ul\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 218.883px 7.91667px; transform-origin: 218.883px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e(Note: Mini-Cube can use the full cube moves and ignore edge effects)\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 85.9667px 7.91667px; transform-origin: 85.9667px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eComing Soon: Matlab Tetris\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function solve_vec = rubik_solve_mini(r)\r\n% Expect Numeric representation of moves (1:27):\r\n% 1:27 are ufdlbr upfpdplpbprp u2f2d2l2b2r2 xyzxpypzpx2y2z2\r\n solve_vec=[]; \r\n\r\n% One path is to use Challenge 931's, Rubik's Mini Cube, initial Cube re-orientation provided in the template, followed by a solving algorithm that needs only RDB type moves\r\n% Loading an external data file is one method. First solve is not timed.\r\nend\r\n\r\nfunction r=rubik_rot_mini(mov,r)\r\n%mov is 1:27;  1-6 UFDLBR 7-12 U'F;D'L'B'R' 13-18 U2F2D2L2B2R2 \r\n%             19-27 XYZ X'Y'Z' X2Y2Z2  \r\n% X cube-R, Y cube-U,  Z cube-F\r\n%\r\n% r is a 24 element row vector\r\n% r output is a single row vector \r\n%\r\n% vector mov\r\n% r output is array of length(mov) x 24\r\n%\r\n% Perform Rubik Cube face rotations and cube rotations\r\n% L 1:4 U 5:8 F 9:12 D 13:16 B 17:20 R 21:24 \r\n% \r\npersistent vf\r\nif isempty(vf) %\r\nvf=[9 2 11 4 6 8 5 7 21 10 23 12 13 14 15 16 17 3 19 1 20 22 18 24 ; \r\n    1 2 13 15 5 4 7 3 10 12 9 11 22 14 21 16 17 18 19 20 6 8 23 24 ;\r\n    1 19 3 17 5 6 7 8 9 2 11 4 14 16 13 15 24 18 22 20 21 10 23 12 ;\r\n    2 4 1 3 17 18 7 8 5 6 11 12 9 10 15 16 13 14 19 20 21 22 23 24 ;\r\n    7 5 3 4 23 6 24 8 9 10 11 12 13 1 15 2 18 20 17 19 21 22 16 14 ;\r\n    1 2 3 4 5 6 11 12 9 10 15 16 13 14 19 20 17 18 7 8 22 24 21 23 ;\r\n    20 2 18 4 7 5 8 6 1 10 3 12 13 14 15 16 17 23 19 21 9 22 11 24 ;\r\n    1 2 8 6 5 21 7 22 11 9 12 10 3 14 4 16 17 18 19 20 15 13 23 24 ;\r\n    1 10 3 12 5 6 7 8 9 22 11 24 15 13 16 14 4 18 2 20 21 19 23 17 ;\r\n    3 1 4 2 9 10 7 8 13 14 11 12 17 18 15 16 5 6 19 20 21 22 23 24 ;\r\n    14 16 3 4 2 6 1 8 9 10 11 12 13 24 15 23 19 17 20 18 21 22 5 7 ;\r\n    1 2 3 4 5 6 19 20 9 10 7 8 13 14 11 12 17 18 15 16 23 21 24 22 ;\r\n    21 2 23 4 8 7 6 5 20 10 18 12 13 14 15 16 17 11 19 9 1 22 3 24 ;\r\n    1 2 22 21 5 15 7 13 12 11 10 9 8 14 6 16 17 18 19 20 4 3 23 24 ;\r\n    1 22 3 24 5 6 7 8 9 19 11 17 16 15 14 13 12 18 10 20 21 2 23 4 ;\r\n    4 3 2 1 13 14 7 8 17 18 11 12 5 6 15 16 9 10 19 20 21 22 23 24 ;\r\n    24 23 3 4 16 6 14 8 9 10 11 12 13 7 15 5 20 19 18 17 21 22 2 1 ;\r\n    1 2 3 4 5 6 15 16 9 10 19 20 13 14 7 8 17 18 11 12 24 23 22 21 ;\r\n    3 1 4 2 9 10 11 12 13 14 15 16 17 18 19 20 5 6 7 8 22 24 21 23 ;\r\n    9 10 11 12 6 8 5 7 21 22 23 24 15 13 16 14 4 3 2 1 20 19 18 17 ;\r\n    14 16 13 15 2 4 1 3 10 12 9 11 22 24 21 23 19 17 20 18 6 8 5 7 ;\r\n    2 4 1 3 17 18 19 20 5 6 7 8 9 10 11 12 13 14 15 16 23 21 24 22 ;\r\n    20 19 18 17 7 5 8 6 1 2 3 4 14 16 13 15 24 23 22 21 9 10 11 12 ;\r\n    7 5 8 6 23 21 24 22 11 9 12 10 3 1 4 2 18 20 17 19 15 13 16 14 ;\r\n    4 3 2 1 13 14 15 16 17 18 19 20 5 6 7 8 9 10 11 12 24 23 22 21 ;\r\n    21 22 23 24 8 7 6 5 20 19 18 17 16 15 14 13 12 11 10 9 1 2 3 4 ; \r\n    24 23 22 21 16 15 14 13 12 11 10 9 8 7 6 5 20 19 18 17 4 3 2 1 ];\r\nend\r\n\r\nr=r(vf(mov,:));\r\nend\r\n\r\n\r\nfunction move_vec=decode27_movestr_rev001(movestr)\r\n% Active character Inputs: UFDLBRXYZ, GQ are pre-processed\r\n% 1-6 UFDLBR 7-12 U'F;D'L'B'R' 13-18 U2F2D2L2B2R2 19-27 XYZX'Y'Z'X2Y2Z2\r\nmovestr=upper(movestr);\r\nmovestr=strrep(movestr,'''','P'); % simplify further searches\r\n\r\nmovestr=strrep(movestr,'UP',' 7 ');\r\nmovestr=strrep(movestr,'FP',' 8 ');\r\nmovestr=strrep(movestr,'DP',' 9 ');\r\nmovestr=strrep(movestr,'LP',' 10 ');\r\nmovestr=strrep(movestr,'BP',' 11 ');\r\nmovestr=strrep(movestr,'RP',' 12 ');\r\nmovestr=strrep(movestr,'U2',' 13 ');\r\nmovestr=strrep(movestr,'F2',' 14 ');\r\nmovestr=strrep(movestr,'D2',' 15 ');\r\nmovestr=strrep(movestr,'L2',' 16 ');\r\nmovestr=strrep(movestr,'B2',' 17 ');\r\nmovestr=strrep(movestr,'R2',' 18 ');\r\nmovestr=strrep(movestr,'U',' 1 ');\r\nmovestr=strrep(movestr,'F',' 2 ');\r\nmovestr=strrep(movestr,'D',' 3 ');\r\nmovestr=strrep(movestr,'L',' 4 ');\r\nmovestr=strrep(movestr,'B',' 5 ');\r\nmovestr=strrep(movestr,'R',' 6 ');\r\nmovestr=strrep(movestr,'XP',' 22 ');\r\nmovestr=strrep(movestr,'YP',' 23 ');\r\nmovestr=strrep(movestr,'ZP',' 24 ');\r\nmovestr=strrep(movestr,'X2',' 25 ');\r\nmovestr=strrep(movestr,'Y2',' 26 ');\r\nmovestr=strrep(movestr,'Z2',' 27 ');\r\nmovestr=strrep(movestr,'X',' 19 ');\r\nmovestr=strrep(movestr,'Y',' 20 ');\r\nmovestr=strrep(movestr,'Z',' 21 ');\r\n\r\nmove_vec=str2num(movestr);\r\n\r\nend % move_vec","test_suite":"%%\r\nfeval(@assignin,'caller','score',0);\r\n%%\r\nvf=[9 2 11 4 6 8 5 7 21 10 23 12 13 14 15 16 17 3 19 1 20 22 18 24 ; \r\n    1 2 13 15 5 4 7 3 10 12 9 11 22 14 21 16 17 18 19 20 6 8 23 24 ;\r\n    1 19 3 17 5 6 7 8 9 2 11 4 14 16 13 15 24 18 22 20 21 10 23 12 ;\r\n    2 4 1 3 17 18 7 8 5 6 11 12 9 10 15 16 13 14 19 20 21 22 23 24 ;\r\n    7 5 3 4 23 6 24 8 9 10 11 12 13 1 15 2 18 20 17 19 21 22 16 14 ;\r\n    1 2 3 4 5 6 11 12 9 10 15 16 13 14 19 20 17 18 7 8 22 24 21 23 ;\r\n    20 2 18 4 7 5 8 6 1 10 3 12 13 14 15 16 17 23 19 21 9 22 11 24 ;\r\n    1 2 8 6 5 21 7 22 11 9 12 10 3 14 4 16 17 18 19 20 15 13 23 24 ;\r\n    1 10 3 12 5 6 7 8 9 22 11 24 15 13 16 14 4 18 2 20 21 19 23 17 ;\r\n    3 1 4 2 9 10 7 8 13 14 11 12 17 18 15 16 5 6 19 20 21 22 23 24 ;\r\n    14 16 3 4 2 6 1 8 9 10 11 12 13 24 15 23 19 17 20 18 21 22 5 7 ;\r\n    1 2 3 4 5 6 19 20 9 10 7 8 13 14 11 12 17 18 15 16 23 21 24 22 ;\r\n    21 2 23 4 8 7 6 5 20 10 18 12 13 14 15 16 17 11 19 9 1 22 3 24 ;\r\n    1 2 22 21 5 15 7 13 12 11 10 9 8 14 6 16 17 18 19 20 4 3 23 24 ;\r\n    1 22 3 24 5 6 7 8 9 19 11 17 16 15 14 13 12 18 10 20 21 2 23 4 ;\r\n    4 3 2 1 13 14 7 8 17 18 11 12 5 6 15 16 9 10 19 20 21 22 23 24 ;\r\n    24 23 3 4 16 6 14 8 9 10 11 12 13 7 15 5 20 19 18 17 21 22 2 1 ;\r\n    1 2 3 4 5 6 15 16 9 10 19 20 13 14 7 8 17 18 11 12 24 23 22 21 ;\r\n    3 1 4 2 9 10 11 12 13 14 15 16 17 18 19 20 5 6 7 8 22 24 21 23 ;\r\n    9 10 11 12 6 8 5 7 21 22 23 24 15 13 16 14 4 3 2 1 20 19 18 17 ;\r\n    14 16 13 15 2 4 1 3 10 12 9 11 22 24 21 23 19 17 20 18 6 8 5 7 ;\r\n    2 4 1 3 17 18 19 20 5 6 7 8 9 10 11 12 13 14 15 16 23 21 24 22 ;\r\n    20 19 18 17 7 5 8 6 1 2 3 4 14 16 13 15 24 23 22 21 9 10 11 12 ;\r\n    7 5 8 6 23 21 24 22 11 9 12 10 3 1 4 2 18 20 17 19 15 13 16 14 ;\r\n    4 3 2 1 13 14 15 16 17 18 19 20 5 6 7 8 9 10 11 12 24 23 22 21 ;\r\n    21 22 23 24 8 7 6 5 20 19 18 17 16 15 14 13 12 11 10 9 1 2 3 4 ; \r\n    24 23 22 21 16 15 14 13 12 11 10 9 8 7 6 5 20 19 18 17 4 3 2 1 ];\r\n\r\n%r=r(vf(mov,:));  % Standard move, r=rubik_rot_min(mov,r);\r\n\r\nPass=1;\r\nr_fail=0;\r\n% Execute 500 cubes and verify completeness and count moves\r\n % initialize cube\r\n r(1:4)=0;     %Left   0 R\r\n r(5:8)=1;     %Up     1 W\r\n r(9:12)=2;    %Front  2 B\r\n r(13:16)=3;   %Down   3 Y\r\n r(17:20)=4;   %Back   4 G\r\n r(21:24)=5;   %Right  5 O\r\n rnorm=r;\r\n\r\nzcnt=500;\r\nsum_solve=0;\r\nmin_solve=1000;\r\nmax_solve=0;\r\nasolve=199;\r\nmix=40;\r\n\r\ntic\r\n\r\nfor cube_check=1:zcnt %zcnt\u003c100 %500\r\n %zcnt=zcnt+1;\r\n  r=rnorm;\r\n % Initial mix\r\n mov=randi(18,[mix,1]);\r\n for i=1:length(mov)  % Ignoring Move Undos since mix=40\r\n   r=r(vf(mov(i),:));\r\n end\r\n\r\n r_reset=r; % Used in assert\r\n\r\n solve_vec=rubik_solve_mini(r);\r\n\r\n for i=1:length(solve_vec) \r\n  r=r(vf(solve_vec(i),:));\r\n end\r\n\r\n  if all(r(1:4)==r(4)) \u0026\u0026 all(r(5:8)==r(8))  \u0026\u0026 all(r(9:12)==r(9)) \u0026\u0026 ...\r\n     all(r(13:16)==r(13))  \u0026\u0026 all(r(17:20)==r(17)) \u0026\u0026 all(r(21:24)==r(21))\r\n   solve_vec(solve_vec\u003e18)=[]; %   \r\n   lsolve=length(solve_vec);\r\n   if lsolve\u003e11, Pass=0;end % Length Rqmt\r\n   sum_solve=sum_solve+lsolve;\r\n   min_solve=min(min_solve,lsolve);\r\n   max_solve=max(max_solve,lsolve);\r\n   asolve=floor(sum_solve/zcnt);\r\n %  fprintf('Cube Solved Moves=%i  Avg Moves=%i min=%i  max=%i\\n',lsolve,asolve,min_solve,max_solve)\r\n  else % Deug info\r\n   Pass=0;\r\n   r_fail=r_reset;\r\n  % fprintf('\\n\\nCube NOT Solved???\\n\\n') \r\n  % fprintf('%i ',r); % Current ending data\r\n  % fprintf('\\n')\r\n  % fprintf('%i ',r_reset); % Starting Cube\r\n  end\r\n\r\nend % while of cubes\r\ntoc\r\n\r\nassert(isequal(Pass,1),sprintf('Max Len=%i \\n',max_solve)); % Length Exception\r\nassert(isequal(Pass,1),sprintf('%i ',r_fail)); % Output Non-Solved Cube Start\r\n\r\n%if Pass\r\n% feval(@assignin,'caller','score',min(100,floor(asolve)));\r\n%end\r\n\r\nfprintf('Moves: Avg %i   Min %i   Max %i\\n',asolve,min_solve,max_solve)\r\n\r\n%%\r\nvf=[9 2 11 4 6 8 5 7 21 10 23 12 13 14 15 16 17 3 19 1 20 22 18 24 ; \r\n    1 2 13 15 5 4 7 3 10 12 9 11 22 14 21 16 17 18 19 20 6 8 23 24 ;\r\n    1 19 3 17 5 6 7 8 9 2 11 4 14 16 13 15 24 18 22 20 21 10 23 12 ;\r\n    2 4 1 3 17 18 7 8 5 6 11 12 9 10 15 16 13 14 19 20 21 22 23 24 ;\r\n    7 5 3 4 23 6 24 8 9 10 11 12 13 1 15 2 18 20 17 19 21 22 16 14 ;\r\n    1 2 3 4 5 6 11 12 9 10 15 16 13 14 19 20 17 18 7 8 22 24 21 23 ;\r\n    20 2 18 4 7 5 8 6 1 10 3 12 13 14 15 16 17 23 19 21 9 22 11 24 ;\r\n    1 2 8 6 5 21 7 22 11 9 12 10 3 14 4 16 17 18 19 20 15 13 23 24 ;\r\n    1 10 3 12 5 6 7 8 9 22 11 24 15 13 16 14 4 18 2 20 21 19 23 17 ;\r\n    3 1 4 2 9 10 7 8 13 14 11 12 17 18 15 16 5 6 19 20 21 22 23 24 ;\r\n    14 16 3 4 2 6 1 8 9 10 11 12 13 24 15 23 19 17 20 18 21 22 5 7 ;\r\n    1 2 3 4 5 6 19 20 9 10 7 8 13 14 11 12 17 18 15 16 23 21 24 22 ;\r\n    21 2 23 4 8 7 6 5 20 10 18 12 13 14 15 16 17 11 19 9 1 22 3 24 ;\r\n    1 2 22 21 5 15 7 13 12 11 10 9 8 14 6 16 17 18 19 20 4 3 23 24 ;\r\n    1 22 3 24 5 6 7 8 9 19 11 17 16 15 14 13 12 18 10 20 21 2 23 4 ;\r\n    4 3 2 1 13 14 7 8 17 18 11 12 5 6 15 16 9 10 19 20 21 22 23 24 ;\r\n    24 23 3 4 16 6 14 8 9 10 11 12 13 7 15 5 20 19 18 17 21 22 2 1 ;\r\n    1 2 3 4 5 6 15 16 9 10 19 20 13 14 7 8 17 18 11 12 24 23 22 21 ;\r\n    3 1 4 2 9 10 11 12 13 14 15 16 17 18 19 20 5 6 7 8 22 24 21 23 ;\r\n    9 10 11 12 6 8 5 7 21 22 23 24 15 13 16 14 4 3 2 1 20 19 18 17 ;\r\n    14 16 13 15 2 4 1 3 10 12 9 11 22 24 21 23 19 17 20 18 6 8 5 7 ;\r\n    2 4 1 3 17 18 19 20 5 6 7 8 9 10 11 12 13 14 15 16 23 21 24 22 ;\r\n    20 19 18 17 7 5 8 6 1 2 3 4 14 16 13 15 24 23 22 21 9 10 11 12 ;\r\n    7 5 8 6 23 21 24 22 11 9 12 10 3 1 4 2 18 20 17 19 15 13 16 14 ;\r\n    4 3 2 1 13 14 15 16 17 18 19 20 5 6 7 8 9 10 11 12 24 23 22 21 ;\r\n    21 22 23 24 8 7 6 5 20 19 18 17 16 15 14 13 12 11 10 9 1 2 3 4 ; \r\n    24 23 22 21 16 15 14 13 12 11 10 9 8 7 6 5 20 19 18 17 4 3 2 1 ];\r\n\r\n%r=r(vf(mov,:));  % Standard move, r=rubik_rot_min(mov,r);\r\n\r\nPass=1;\r\nr_fail=0;\r\n% Execute 500 cubes and verify completeness and count moves\r\n % initialize cube\r\n r(1:4)=0;     %Left   0 R\r\n r(5:8)=1;     %Up     1 W\r\n r(9:12)=2;    %Front  2 B\r\n r(13:16)=3;   %Down   3 Y\r\n r(17:20)=4;   %Back   4 G\r\n r(21:24)=5;   %Right  5 O\r\n rnorm=r;\r\n\r\n for jrand=1:40  % Ignoring Move Undos since mix=40\r\n   r=r(vf(randi(18),:));\r\n end\r\n\r\n q=500;\r\n ra=zeros(q,24);\r\n for i=1:q\r\n  for jrand=1:10  % Ignoring Move Undos since base mix=40\r\n    r=r(vf(randi(18),:));\r\n  end\r\n % add 10 new moves to prior vector\r\n  ra(i,:)=r;\r\n end\r\n\r\n% The Time Trail section does not check accuracy, that is done above\r\nt0=clock;\r\nfor i=1:q\r\n solve_vec=rubik_solve_mini(ra(q,:));\r\nend\r\ndt=etime(clock,t0)*1000;\r\n\r\n%assert(isequal(find_fast(a,val(1)),find(a==val(1),1,'first')))\r\nfprintf('Your Time = %i msec\\n',floor(dt))\r\nfeval(@assignin,'caller','score',min(2000,floor(dt)));\r\n%   Performance Score","published":true,"deleted":false,"likes_count":5,"comments_count":0,"created_by":3097,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":1,"test_suite_updated_at":"2012-09-09T17:48:25.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2012-09-09T06:26:08.000Z","updated_at":"2025-11-17T16:25:58.000Z","published_at":"2012-09-09T16:33:58.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe Challenge is to Near or Optimally Solve a thoroughly scrambled Mini-Rubik's Cube(2x2x2).\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eAny Mini-Cube can be solved in 11 or fewer Face Moves. There are only 3,674,160 unique cube positions, with only 2344 requiring the fulll 11 moves. Cube moves do not count.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe Performance metric is cumulative Time to Solve 500 cubes (msec).\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eA standard Mini-Rubik's Cube is shown in 3-D and also unfolded to identify the specific Tile-face/Vector numbering.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe faces are White-Up / Red-Left / Blue-Front / Orange-Right / Yellow-Down / Green-Back (ULFRDB)\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eMoves are denoted as F for clockwise rotation of the Front face. F'(or FP) is CCW and F2 is F twice. The provided function r_new=rubick_rot_mini(mov,r) implements moves 1-18: UFDLBRU'F'D'L'B'R'U2F2D2L2B2R2.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"center\\\"/\u003e\u003c/w:pPr\u003e\u003cw:customXml w:element=\\\"image\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"height\\\" w:val=\\\"-1\\\"/\u003e\u003cw:attr w:name=\\\"width\\\" w:val=\\\"-1\\\"/\u003e\u003cw:attr w:name=\\\"verticalAlign\\\" w:val=\\\"baseline\\\"/\u003e\u003cw:attr w:name=\\\"altText\\\" w:val=\\\"\\\"/\u003e\u003cw:attr w:name=\\\"relationshipId\\\" w:val=\\\"rId1\\\"/\u003e\u003c/w:customXmlPr\u003e\u003c/w:customXml\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"center\\\"/\u003e\u003c/w:pPr\u003e\u003cw:customXml w:element=\\\"image\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"height\\\" w:val=\\\"-1\\\"/\u003e\u003cw:attr w:name=\\\"width\\\" w:val=\\\"-1\\\"/\u003e\u003cw:attr w:name=\\\"verticalAlign\\\" w:val=\\\"baseline\\\"/\u003e\u003cw:attr w:name=\\\"altText\\\" w:val=\\\"\\\"/\u003e\u003cw:attr w:name=\\\"relationshipId\\\" w:val=\\\"rId2\\\"/\u003e\u003c/w:customXmlPr\u003e\u003c/w:customXml\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"center\\\"/\u003e\u003c/w:pPr\u003e\u003cw:customXml w:element=\\\"image\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"height\\\" w:val=\\\"-1\\\"/\u003e\u003cw:attr w:name=\\\"width\\\" w:val=\\\"-1\\\"/\u003e\u003cw:attr w:name=\\\"verticalAlign\\\" w:val=\\\"baseline\\\"/\u003e\u003cw:attr w:name=\\\"altText\\\" w:val=\\\"\\\"/\u003e\u003cw:attr w:name=\\\"relationshipId\\\" w:val=\\\"rId3\\\"/\u003e\u003c/w:customXmlPr\u003e\u003c/w:customXml\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[Input: (rubik)\\n\\nrubik: row vector of size 24\\n(The cube started [L=0,U=1,F=2,D=3,B=4,R=5] and then receives forty face moves.\\n\\nOutput: move_vec (Numeric of moves to solve)\\n move_vec:values 1:27 for UFDLBR U'F'D'L'B'R' U2F2D2L2B2R2 XYZX'Y'Z'X2Y2Z2]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eExample:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eIf the cube was randomized by [1 9] UD', one solution is [3 7] which are the complements in reverse order.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eScoring is Time in msec to solve 500 cubes\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eCube Moves X, Y, and Z do not constitute a move but are needed in the vector\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eA string to numeric value function is provided in the template\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eVerifications will be by executing your move vector against the provided Rubik and counting number of face moves.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe function rubik_rot_mini(mov,r) is provided in the template. Other functions are provided to re-orient the cube in Cody Challenge 931, Rubik's Mini-Cube.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe Challenge\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"http://www.mathworks.com/matlabcentral/cody/problems/931-rubik-s-mini-cube-solve-randomized-mini-cube-score-moves.html\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eChallenge 931 Rubik's Mini-Cube\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e contains a 3D Mini-Cube Viewer for program development.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:hyperlink w:docLocation=\\\"http://kociemba.org/cube.htm\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eCube Theory: 20-moves Any Cube\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:hyperlink w:docLocation=\\\"http://peter.stillhq.com/jasmine/rubikscubesolution.html\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eGeneral Cube Info and Middle Layer\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:hyperlink w:docLocation=\\\"http://www.speedcubing.com/final_layer_print.html\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eSpeedCube Bottom Sequences\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe site\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"http://www.speedcubing.com/CubeSolver/MiniCubeSolver.html\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eMiniCube Solver\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e claims an outstanding 10 minutes to solve a randomized Mini-Cube. Matlab can achieve any Mini-Cube solution in \u0026lt; 497 usec, independent of moves on an i5/16GB machine.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e(Note: Mini-Cube can use the full cube moves and ignore edge effects)\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eComing Soon: Matlab 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