{"group":{"id":1,"name":"Community","lockable":false,"created_at":"2012-01-18T18:02:15.000Z","updated_at":"2025-12-14T01:33:56.000Z","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":"2025-12-14T00:00:00.000Z","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":1019,"title":"Vector LCM","description":"Find Least Common Multiple of a given vector.\r\nNeed general solution as the test suite will be expanded.\r\nFunction Template:\r\nfunction ans = vectorLCM(v)\r\n   % v=[45 15 200 300];\r\n   1800;\r\nend","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: 163.033px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 81.5167px; transform-origin: 407px 81.5167px; vertical-align: baseline; \"\u003e\u003cul style=\"block-size: 61.3px; 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 30.65px; transform-origin: 391px 30.65px; 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: 145.5px 8px; transform-origin: 145.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eFind Least Common Multiple of a given 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: 177px 8px; transform-origin: 177px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eNeed general solution as the test suite will be expanded.\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: 60px 8px; transform-origin: 60px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eFunction Template:\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ul\u003e\u003cdiv style=\"background-color: rgb(247, 247, 247); block-size: 81.7333px; 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 40.8667px; transform-origin: 404px 40.8667px; 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: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; 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: 108px 8.5px; tab-size: 4; transform-origin: 108px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\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: 36px 8.5px; text-decoration-color: rgb(14, 0, 255); text-emphasis-color: rgb(14, 0, 255); transform-origin: 36px 8.5px; \"\u003efunction \u003c/span\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 72px 8.5px; transform-origin: 72px 8.5px; \"\u003eans = vectorLCM(v)\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: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; 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: 92px 8.5px; tab-size: 4; transform-origin: 92px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 12px 8.5px; transform-origin: 12px 8.5px; \"\u003e   \u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(2, 128, 9); border-block-start-color: rgb(2, 128, 9); border-bottom-color: rgb(2, 128, 9); border-inline-end-color: rgb(2, 128, 9); border-inline-start-color: rgb(2, 128, 9); border-left-color: rgb(2, 128, 9); border-right-color: rgb(2, 128, 9); border-top-color: rgb(2, 128, 9); caret-color: rgb(2, 128, 9); color: rgb(2, 128, 9); column-rule-color: rgb(2, 128, 9); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(2, 128, 9); perspective-origin: 80px 8.5px; text-decoration-color: rgb(2, 128, 9); text-emphasis-color: rgb(2, 128, 9); transform-origin: 80px 8.5px; \"\u003e% v=[45 15 200 300];\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: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; 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: 32px 8.5px; tab-size: 4; transform-origin: 32px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e   1800;\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: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; 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: 12px 8.5px; tab-size: 4; transform-origin: 12px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\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); text-decoration-color: rgb(14, 0, 255); text-emphasis-color: rgb(14, 0, 255); \"\u003eend\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function ans = vectorLCM(v)\r\n   % v=[45 15 200 300];\r\n   1800;\r\nend\r\n","test_suite":"%%\r\nv=[45 15 200 300];\r\nassert(isequal(vectorLCM(v),1800))\r\n%%\r\nv=ones(1,9);\r\nassert(isequal(vectorLCM(v),1))\r\n%%\r\nv=5:5:50;\r\nassert(isequal(vectorLCM(v),12600))\r\n%%\r\nv=primes(10);\r\nassert(isequal(vectorLCM(v),prod(v)))","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":166,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":93,"test_suite_updated_at":"2022-03-04T05:37:41.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2012-11-01T02:12:53.000Z","updated_at":"2026-02-19T14:27:03.000Z","published_at":"2012-11-01T02:15:48.000Z","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=\\\"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\u003eFind Least Common Multiple of a given 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\u003eNeed general solution as the test suite will be expanded.\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\u003eFunction Template:\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[function ans = vectorLCM(v)\\n   % v=[45 15 200 300];\\n   1800;\\nend]]\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":60997,"title":"Multiply real numbers to get the smallest integers","description":"Write a function that takes a vector of real numbers and multiplies them by a factor to produce the integers with the smallest absolute value. For example, if the input vector is [3/4 5/6 7/10], the output should be [45 50 42]; that is, the input vector should be multiplied by 60.","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; 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: none solid rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 63px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 408px 31.5px; transform-origin: 408px 31.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"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: 385px 31.5px; text-align: left; transform-origin: 385px 31.5px; white-space-collapse: preserve; 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 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eWrite a function that takes a vector of real numbers and multiplies them by a factor to produce the integers with the smallest absolute value. For example, if the input vector is [3/4 5/6 7/10], the output should be [45 50 42]; that is, the input vector should be multiplied by 60.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = integerize(x)\r\n  y = ceil(x);\r\nend","test_suite":"%%\r\nx = [3/4 5/6 7/10];\r\ny = integerize(x);\r\ny_correct = [45 50 42];\r\nassert(isequal(y,y_correct))\r\n\r\n%%\r\nx = [1.5 8.9 6.35 7.125];\r\ny = integerize(x);\r\ny_correct = [60 356 254 285];\r\nassert(isequal(y,y_correct))\r\n\r\n%%\r\nx = randi(80,[1 14])-40;\r\ny = integerize(x);\r\ny_correct = x;\r\nassert(isequal(y,y_correct))\r\n\r\n%%\r\nx = [4/5 -8/7 15/12 -13/49 83/56];\r\ny = integerize(x);\r\ny_correct = [1568 -2240 2450 -520 2905];\r\nassert(isequal(y,y_correct))\r\n\r\n%%\r\nm = randi(6);\r\np = primes(100);\r\nk = randperm(length(p),2*m);\r\nn = p(k(1:m));\r\nd = p(k(m+1:end));\r\nf = prod(d);\r\nx = n./d;\r\ny = integerize(x);\r\ny_correct = x*f;\r\nassert(isequal(y,y_correct))","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":46909,"edited_by":46909,"edited_at":"2025-09-08T01:51:47.000Z","deleted_by":null,"deleted_at":null,"solvers_count":10,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2025-09-08T01:51:22.000Z","updated_at":"2026-03-03T15:30:27.000Z","published_at":"2025-09-08T01:51:47.000Z","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\u003eWrite a function that takes a vector of real numbers and multiplies them by a factor to produce the integers with the smallest absolute value. For example, if the input vector is [3/4 5/6 7/10], the output should be [45 50 42]; that is, the input vector should be multiplied by 60.\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":46096,"title":"LCM","description":null,"description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; 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: none solid rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 49.96px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 406.5px 24.98px; transform-origin: 406.5px 24.98px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 20.48px; 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: 383.5px 10.24px; text-align: left; transform-origin: 383.5px 10.24px; 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 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003egiven two numbers, calculate the lcm.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 20.48px; 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: 383.5px 10.24px; text-align: left; transform-origin: 383.5px 10.24px; 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 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003enb. built-in functions are disabled\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = lc_cal(a,b)\r\n  y = x;\r\nend","test_suite":"%%\r\nassert(isequal(lc_cal(5,6),30))\r\n%%\r\nassert(isequal(lc_cal(65,24843),124215))\r\n%%\r\nassert(isequal(lc_cal(28851538,1183019),1933053046))\r\n%%\r\nassert(isequal(lc_cal(3,9),9))\r\n%%\r\nassert(isequal(lc_cal(1,1),1))\r\n%%\r\nassert(isequal(lc_cal(6236412, 24228),12591315828))\r\n%%\r\nfiletext = fileread('lc_cal.m');\r\nassert(isempty(strfind(filetext, 'gcd')),'gcd() forbidden')\r\nassert(isempty(strfind(filetext, 'lcm')),'lcm() forbidden')\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":363598,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":24,"test_suite_updated_at":"2020-08-03T02:00:39.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2020-08-03T01:54:30.000Z","updated_at":"2026-01-03T16:57:05.000Z","published_at":"2020-08-03T02:00:39.000Z","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\u003egiven two numbers, calculate the lcm.\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\u003enb. built-in functions are disabled\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":1975,"title":"Kaggle: Reverse Game of Life - Zoo of Stills and Oscillators","description":"\u003chttp://www.kaggle.com/c/conway-s-reverse-game-of-life Kaggle's Conway's Reverse Game of Life\u003e contest inspires this Reverse Life Zoo challenge. The kaggle contest runs from Oct-14-2013 thru Mar-02-2014. References: \u003chttp://mathworld.wolfram.com/GameofLife.html Game of Life at Wolfram\u003e. \u003chttp://en.wikipedia.org/wiki/Conway%27s_Game_of_Life Wiki Life\u003e.\r\n\r\n\r\n  1. Any live cell with fewer than two live neighbors dies, as if caused by under-population.\r\n  2. Any live cell with two or three live neighbors lives on to the next generation.\r\n  3. Any live cell with more than three live neighbors dies, as if by overcrowding.\r\n  4. Any dead cell with exactly three live neighbors becomes a live cell, as if by reproduction.\r\n5. No wrap around. Beyond edge is zero. Eight Neighbors.\r\n\r\n\r\n\r\nDetermine the Zoo of life at its previous Snapshot. The output must evolve to the given Zoo Snapshot.  It is a Zoo since all animals are in their private enclosures and do not interact with any other animals. Animals are stable or cyclic oscillators.\r\n\r\n*Input:* Zoo , an [m,n] array\r\n\r\n*Output:* ZooPre, image of the Zoo at its prior iteration\r\n\r\n\r\n*Example:*\r\n\r\n  Zoo        ZooPre\r\n  0000000000  000000000  \r\n  0110000100  011000000  \r\n  0110000100  011001110  \r\n  0000000100  000000000  \r\n  0000000000  000000000\r\n\r\n*Additional References:*\r\n\u003chttp://www.conwaylife.com/wiki/Oscillator Oscillators\u003e, \u003chttp://www.conwaylife.com/wiki/Still_life Still Life\u003e\r\n\r\n*Next:* Small Island - Prior Snapshot Prediction","description_html":"\u003cp\u003e\u003ca href = \"http://www.kaggle.com/c/conway-s-reverse-game-of-life\"\u003eKaggle's Conway's Reverse Game of Life\u003c/a\u003e contest inspires this Reverse Life Zoo challenge. The kaggle contest runs from Oct-14-2013 thru Mar-02-2014. References: \u003ca href = \"http://mathworld.wolfram.com/GameofLife.html\"\u003eGame of Life at Wolfram\u003c/a\u003e. \u003ca href = \"http://en.wikipedia.org/wiki/Conway%27s_Game_of_Life\"\u003eWiki Life\u003c/a\u003e.\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003e1. Any live cell with fewer than two live neighbors dies, as if caused by under-population.\r\n2. Any live cell with two or three live neighbors lives on to the next generation.\r\n3. Any live cell with more than three live neighbors dies, as if by overcrowding.\r\n4. Any dead cell with exactly three live neighbors becomes a live cell, as if by reproduction.\r\n5. No wrap around. Beyond edge is zero. Eight Neighbors.\r\n\u003c/pre\u003e\u003cp\u003eDetermine the Zoo of life at its previous Snapshot. The output must evolve to the given Zoo Snapshot.  It is a Zoo since all animals are in their private enclosures and do not interact with any other animals. Animals are stable or cyclic oscillators.\u003c/p\u003e\u003cp\u003e\u003cb\u003eInput:\u003c/b\u003e Zoo , an [m,n] array\u003c/p\u003e\u003cp\u003e\u003cb\u003eOutput:\u003c/b\u003e ZooPre, image of the Zoo at its prior iteration\u003c/p\u003e\u003cp\u003e\u003cb\u003eExample:\u003c/b\u003e\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003eZoo        ZooPre\r\n0000000000  000000000  \r\n0110000100  011000000  \r\n0110000100  011001110  \r\n0000000100  000000000  \r\n0000000000  000000000\r\n\u003c/pre\u003e\u003cp\u003e\u003cb\u003eAdditional References:\u003c/b\u003e \u003ca href = \"http://www.conwaylife.com/wiki/Oscillator\"\u003eOscillators\u003c/a\u003e, \u003ca href = \"http://www.conwaylife.com/wiki/Still_life\"\u003eStill Life\u003c/a\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eNext:\u003c/b\u003e Small Island - Prior Snapshot Prediction\u003c/p\u003e","function_template":"function ZooPre=Zoo_prior(Zoo)\r\n ZooPre=Zoo;\r\nend","test_suite":"%%\r\n block=[0 0 0 0;0 1 1 0;0 1 1 0;0 0 0 0];\r\n Zoo=repmat(block,3,1);\r\n\r\n ZooPre=Zoo_prior(Zoo);\r\n mc=conv2(single(ZooPre),[1 1 1;1 0 1;1 1 1],'same');\r\n ZooChk=~(mc\u003c2 | mc\u003e3) \u0026 ((ZooPre \u0026 mc==2) | (ZooPre \u0026 mc==3) | (~ZooPre \u0026 mc==3)); \r\n\r\n \r\n   assert(all(all(ZooChk==Zoo))) \r\n%  figure(1);imagesc(ZooPre)\r\n%  figure(2);imagesc(Zoo)\r\n\r\n%%\r\ncaterer1=[0 0 0 0 0 0 0 0 0 0;0 0 0 1 0 0 0 0 0 0;0 1 0 0 0 1 1 1 1 0;0 1 0 0 0 1 0 0 0 0;0 1 0 0 0 0 0 0 0 0;0 0 0 0 1 0 0 0 0 0;0 0 1 1 0 0 0 0 0 0;0 0 0 0 0 0 0 0 0 0];\r\n\r\ncaterer2=[0     0     0     0     0     0     0     0     0     0;\r\n     0     0     0     0     0     0     1     1     0     0;\r\n     0     0     1     0     1     1     1     1     0     0;\r\n     1     1     1     0     0     1     0     1     0     0;\r\n     0     0     0     0     0     0     0     0     0     0;\r\n     0     0     1     1     0     0     0     0     0     0;\r\n     0     0     0     1     0     0     0     0     0     0;\r\n     0     0     0     0     0     0     0     0     0     0];\r\n\r\ncaterer3=[0     0     0     0     0     0     0     0     0     0;\r\n     0     0     0     0     0     0     0     1     0     0;\r\n     0     0     1     1     1     0     0     0     1     0;\r\n     0     1     1     1     1     1     0     1     0     0;\r\n     0     0     0     1     0     0     0     0     0     0;\r\n     0     0     1     1     0     0     0     0     0     0;\r\n     0     0     1     1     0     0     0     0     0     0;\r\n     0     0     0     0     0     0     0     0     0     0];\r\n\r\n Zoo=[caterer1 zeros(8,1) caterer2 zeros(8,1) caterer3] ;\r\n\r\n ZooPre=Zoo_prior(Zoo);\r\n mc=conv2(single(ZooPre),[1 1 1;1 0 1;1 1 1],'same');\r\n ZooChk=~(mc\u003c2 | mc\u003e3) \u0026 ((ZooPre \u0026 mc==2) | (ZooPre \u0026 mc==3) | (~ZooPre \u0026 mc==3)); \r\n\r\n \r\n   assert(all(all(ZooChk==Zoo))) \r\n%  figure(1);imagesc(ZooPre)\r\n%  figure(2);imagesc(Zoo)\r\n\r\n%%\r\ncaterer1=[0 0 0 0 0 0 0 0 0 0;0 0 0 1 0 0 0 0 0 0;0 1 0 0 0 1 1 1 1 0;0 1 0 0 0 1 0 0 0 0;0 1 0 0 0 0 0 0 0 0;0 0 0 0 1 0 0 0 0 0;0 0 1 1 0 0 0 0 0 0;0 0 0 0 0 0 0 0 0 0]; % 8x10\r\nLoaf=[0 0 0 0 0 0;0 0 1 1 0 0;0 1 0 0 1 0;0 0 1 0 1 0;0 0 0 1 0 0;0 0 0 0 0 0]; % 6x6\r\nblinker=[0 0 0 0 0;0 0 0 0 0;0 1 1 1 0;0 0 0 0 0;0 0 0 0 0]; % 5x5\r\n\r\n\r\n\r\nZoo=[[Loaf;Loaf'] zeros(12,1) [caterer1;zeros(4,10)] [blinker;blinker';zeros(2,5)] ] ;\r\n\r\n ZooPre=Zoo_prior(Zoo);\r\n mc=conv2(single(ZooPre),[1 1 1;1 0 1;1 1 1],'same');\r\n ZooChk=~(mc\u003c2 | mc\u003e3) \u0026 ((ZooPre \u0026 mc==2) | (ZooPre \u0026 mc==3) | (~ZooPre \u0026 mc==3)); \r\n\r\n \r\n   assert(all(all(ZooChk==Zoo))) \r\n%  figure(1);imagesc(ZooPre)\r\n%  figure(2);imagesc(Zoo)\r\n\r\n","published":true,"deleted":false,"likes_count":3,"comments_count":1,"created_by":3097,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":19,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2013-11-09T04:53:18.000Z","updated_at":"2026-02-13T15:21:36.000Z","published_at":"2013-11-09T05:22:10.000Z","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:hyperlink w:docLocation=\\\"http://www.kaggle.com/c/conway-s-reverse-game-of-life\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eKaggle's Conway's Reverse Game of Life\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e contest inspires this Reverse Life Zoo challenge. The kaggle contest runs from Oct-14-2013 thru Mar-02-2014. 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.\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. No wrap around. Beyond edge is zero. Eight Neighbors.]]\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\u003eDetermine the Zoo of life at its previous Snapshot. The output must evolve to the given Zoo Snapshot. It is a Zoo since all animals are in their private enclosures and do not interact with any other animals. Animals are stable or cyclic oscillators.\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 Zoo , an [m,n] 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: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 ZooPre, image of the Zoo at its prior iteration\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\u003eExample:\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[Zoo        ZooPre\\n0000000000  000000000  \\n0110000100  011000000  \\n0110000100  011001110  \\n0000000100  000000000  \\n0000000000  000000000]]\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:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eAdditional 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://www.conwaylife.com/wiki/Oscillator\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eOscillators\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://www.conwaylife.com/wiki/Still_life\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eStill Life\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=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eNext:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e Small Island - Prior Snapshot Prediction\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":45402,"title":"Find an overlap in the cleaning schedule of two tank reactors","description":"In a certain pharmaceutical production company, there are two tank reactors operating simultaneously and independent of each other. Each reactor operates by cycling through 4 phases:\r\n\r\n# Filling phase - The empty reactor is filled with raw materials.\r\n# Reacting phase - The filled reactor is heated to start the chemical reaction.\r\n# Emptying phase - The reaction ends and the tank is emptied of all contents.\r\n# Cleaning phase - The emptied reactor must be cleaned to prepare for the next batch.\r\n\r\nAt the end of each cycle, a fresh new batch of drugs are being produced. The two reactors produce different drugs, and so the length of time to finish each phase for the two reactors may be different.\r\n\r\nHowever, the company manager wishes to avoid a scenario when the two reactors are both in the cleaning phase at the same time. This is because it takes manpower to clean a tank, and there is not enough manpower to clean two tanks at a time. If we start the filling phase of both reactors at this moment and continue producing batches one after the other without fail, can you determine the earliest time when both tanks require cleaning? \r\n\r\nWrite a function that takes 4 values, R1, C1, R2, C2, which respectively denotes the amount of time in hours for reacting and cleaning in reactor 1 followed by the amount of time in hours for reacting and cleaning in reactor 2. Since both tanks are of the same size, the filling and emptying phase each takes 1 hour for both of them. You are ensured that all inputs are integers and 1 \u003c= R1, C1, R2, C2 \u003c= 10. Output the earliest hour when the reactors are both undergoing a cleaning phase. You are also ensured that a positive integer answer exists for each test case.\r\n\r\nThe first two sample test cases below are illustrated in this figure: \u003chttps://drive.google.com/open?id=1BWnAMQgaiz5OZQe466DiFQ8yTWlm8JRI\u003e\r\n\r\nSample test cases:\r\n\r\n  \u003e\u003e two_reactors(3,2,2,1)\r\n  ans =\r\n      20\r\n  \u003e\u003e two_reactors(4,1,2,2)\r\n  ans =\r\n      35\r\n\u003e\u003e two_reactors(1,2,2,2)\r\n  ans =\r\n      5","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; 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: none solid rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 1028.2px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 514.1px; transform-origin: 407px 514.1px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 41.6px; 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 20.8px; text-align: left; transform-origin: 384px 20.8px; 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 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eIn a certain pharmaceutical production company, there are two tank reactors operating simultaneously and independent of each other. Each reactor operates by cycling through 4 phases:\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003col style=\"block-size: 80px; font-family: Helvetica, Arial, sans-serif; list-style-type: decimal; margin-block-end: 20px; margin-block-start: 10px; margin-bottom: 20px; margin-top: 10px; perspective-origin: 391px 40px; transform-origin: 391px 40px; margin-top: 10px; margin-bottom: 20px; \"\u003e\u003cli style=\"block-size: 20px; 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 10px; text-align: left; transform-origin: 363px 10px; white-space: pre-wrap; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eFilling phase - The empty reactor is filled with raw materials.\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 20px; 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 10px; text-align: left; transform-origin: 363px 10px; white-space: pre-wrap; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eReacting phase - The filled reactor is heated to start the chemical reaction.\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 20px; 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 10px; text-align: left; transform-origin: 363px 10px; white-space: pre-wrap; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eEmptying phase - The reaction ends and the tank is emptied of all contents.\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 20px; 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 10px; text-align: left; transform-origin: 363px 10px; white-space: pre-wrap; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eCleaning phase - The emptied reactor must be cleaned to prepare for the next batch.\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e\u003cdiv style=\"block-size: 41.6px; 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 20.8px; text-align: left; transform-origin: 384px 20.8px; 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 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eAt the end of each cycle, a fresh new batch of drugs are being produced. The two reactors produce different drugs, and so the length of time to finish each phase for the two reactors may be different.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 83.2px; 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 41.6px; text-align: left; transform-origin: 384px 41.6px; 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 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eHowever, the company manager wishes to avoid a scenario when the two reactors are both in the cleaning phase at the same time. This is because it takes manpower to clean a tank, and there is not enough manpower to clean two tanks at a time. If we start the filling phase of both reactors at this moment and continue producing batches one after the other without fail, can you determine the earliest time when both tanks require cleaning?\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 104px; 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 52px; text-align: left; transform-origin: 384px 52px; 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 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eWrite a function that takes 4 values, R1, C1, R2, C2, which respectively denotes the amount of time in hours for reacting and cleaning in reactor 1 followed by the amount of time in hours for reacting and cleaning in reactor 2. Since both tanks are of the same size, the filling and emptying phase each takes 1 hour for both of them. You are ensured that all inputs are integers and 1 \u0026lt;= R1, C1, R2, C2 \u0026lt;= 10. Output the earliest hour when the reactors are both undergoing a cleaning phase. You are also ensured that a positive integer answer exists for each test case.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 20.8px; 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 10.4px; text-align: left; transform-origin: 384px 10.4px; 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 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eThe first two sample test cases below are illustrated in the following figure.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 20.8px; 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 10.4px; text-align: left; transform-origin: 384px 10.4px; 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 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 311.6px; 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 155.8px; text-align: left; transform-origin: 384px 155.8px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cimg class=\"imageNode\" width=\"573\" height=\"306\" style=\"vertical-align: baseline;width: 573px;height: 306px\" 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data-image-state=\"image-loaded\"\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 20.8px; 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 10.4px; text-align: left; transform-origin: 384px 10.4px; 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 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 20.8px; 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 10.4px; text-align: left; transform-origin: 384px 10.4px; 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 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eSample test cases:\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgb(247, 247, 247); block-size: 180px; border-bottom-left-radius: 4px; border-bottom-right-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 90px; transform-origin: 404px 90px; margin-left: 3px; margin-top: 10px; margin-bottom: 10px; margin-right: 3px; \"\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; 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 10px; transform-origin: 404px 10px; 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 0px; tab-size: 4; transform-origin: 0px 0px; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e\u0026gt;\u0026gt; two_reactors(3,2,2,1)\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; 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 10px; transform-origin: 404px 10px; 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 0px; tab-size: 4; transform-origin: 0px 0px; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003eans =\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; 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 10px; transform-origin: 404px 10px; 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 0px; tab-size: 4; transform-origin: 0px 0px; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e    20\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; 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 10px; transform-origin: 404px 10px; 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 0px; tab-size: 4; transform-origin: 0px 0px; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e\u0026gt;\u0026gt; two_reactors(4,1,2,2)\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; 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 10px; transform-origin: 404px 10px; 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 0px; tab-size: 4; transform-origin: 0px 0px; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003eans =\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; 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 10px; transform-origin: 404px 10px; 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 0px; tab-size: 4; transform-origin: 0px 0px; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e    35\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; 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 10px; transform-origin: 404px 10px; 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 0px; tab-size: 4; transform-origin: 0px 0px; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e\u0026gt;\u0026gt; two_reactors(1,2,2,2)\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; 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 10px; transform-origin: 404px 10px; 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 0px; tab-size: 4; transform-origin: 0px 0px; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003eans =\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; 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 10px; transform-origin: 404px 10px; 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 0px; tab-size: 4; transform-origin: 0px 0px; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e    5\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = two_reactors(R1,C1,R2,C2)\r\n  y = R1;\r\nend","test_suite":"%%\r\nassert(isequal(two_reactors(5,1,6,5),24))\r\n%%\r\nassert(isequal(two_reactors(1,2,2,2),5))\r\n%%\r\nassert(isequal(two_reactors(7,7,7,1),10))\r\n%%\r\nassert(isequal(two_reactors(1,4,6,7),11))\r\n%%\r\nassert(isequal(two_reactors(5,9,8,10),11))\r\n%%\r\nassert(isequal(two_reactors(6,4,2,7),9))\r\n%%\r\nassert(isequal(two_reactors(8,5,1,3),11))\r\n%%\r\nassert(isequal(two_reactors(2,3,5,6),12))\r\n%%\r\nassert(isequal(two_reactors(5,9,6,10),9))\r\n%%\r\nassert(isequal(two_reactors(7,10,3,7),10))\r\n%%\r\nassert(isequal(two_reactors(3,7,7,1),10))\r\n%%\r\nassert(isequal(two_reactors(3,3,7,9),14))\r\n%%\r\nassert(isequal(two_reactors(4,8,7,1),10))\r\n%%\r\nassert(isequal(two_reactors(7,4,10,1),13))\r\n%%\r\nassert(isequal(two_reactors(5,5,5,8),8))\r\n%%\r\nassert(isequal(two_reactors(4,8,5,1),8))\r\n%%\r\nassert(isequal(two_reactors(2,8,5,2),8))\r\n%%\r\nassert(isequal(two_reactors(4,7,2,8),7))\r\n%%\r\nassert(isequal(two_reactors(3,10,3,8),6))\r\n%%\r\nassert(isequal(two_reactors(2,3,1,6),5))\r\n%%\r\nassert(isequal(two_reactors(7,6,5,7),10))\r\n%%\r\nassert(isequal(two_reactors(7,7,7,10),10))\r\n%%\r\nassert(isequal(two_reactors(3,8,3,2),6))\r\n%%\r\nassert(isequal(two_reactors(7,5,5,7),10))\r\n%%\r\nassert(isequal(two_reactors(8,4,7,5),11))\r\n%%\r\nassert(isequal(two_reactors(9,9,3,7),12))\r\n%%\r\nassert(isequal(two_reactors(6,6,9,3),12))\r\n%%\r\nassert(isequal(two_reactors(4,2,10,7),15))\r\n%%\r\nassert(isequal(two_reactors(10,1,9,1),156))\r\n%%\r\nassert(isequal(two_reactors(5,7,6,7),9))\r\n%%\r\nassert(isequal(two_reactors(6,8,6,10),9))\r\n%%\r\nassert(isequal(two_reactors(3,2,2,1),20))\r\n%%\r\nassert(isequal(two_reactors(5,5,4,8),8))\r\n%%\r\nassert(isequal(two_reactors(7,8,10,10),13))\r\n%%\r\nassert(isequal(two_reactors(2,2,7,1),30))\r\n%%\r\nassert(isequal(two_reactors(6,6,9,5),12))\r\n%%\r\nassert(isequal(two_reactors(4,7,8,6),11))\r\n%%\r\nassert(isequal(two_reactors(4,2,6,3),31))\r\n%%\r\nassert(isequal(two_reactors(1,8,3,5),6))\r\n%%\r\nassert(isequal(two_reactors(7,4,8,4),11))\r\n%%\r\nassert(isequal(two_reactors(7,8,5,1),16))\r\n%%\r\nassert(isequal(two_reactors(4,5,3,2),7))\r\n%%\r\nassert(isequal(two_reactors(9,5,9,4),12))\r\n%%\r\nassert(isequal(two_reactors(8,4,9,8),12))\r\n%%\r\nassert(isequal(two_reactors(4,3,8,10),16))\r\n%%\r\nassert(isequal(two_reactors(4,7,5,9),8))\r\n%%\r\nassert(isequal(two_reactors(8,2,9,10),12))\r\n%%\r\nassert(isequal(two_reactors(6,9,6,2),9))\r\n%%\r\nassert(isequal(two_reactors(2,5,8,9),14))\r\n%%\r\nassert(isequal(two_reactors(8,4,6,1),27))\r\n%%\r\nassert(isequal(two_reactors(2,2,7,5),11))\r\n%%\r\nassert(isequal(two_reactors(2,5,2,1),5))\r\n%%\r\nassert(isequal(two_reactors(9,6,10,7),13))\r\n%%\r\nassert(isequal(two_reactors(6,9,9,10),12))\r\n%%\r\nassert(isequal(two_reactors(1,9,7,10),10))\r\n%%\r\nassert(isequal(two_reactors(6,5,9,3),12))\r\n%%\r\nassert(isequal(two_reactors(5,10,6,9),9))\r\n%%\r\nassert(isequal(two_reactors(8,6,3,7),11))\r\n%%\r\nassert(isequal(two_reactors(1,7,7,8),10))\r\n%%\r\nassert(isequal(two_reactors(9,10,8,6),12))\r\n%%\r\nassert(isequal(two_reactors(10,6,1,2),14))\r\n%%\r\nassert(isequal(two_reactors(9,5,9,3),12))\r\n%%\r\nassert(isequal(two_reactors(6,7,1,7),9))\r\n%%\r\nassert(isequal(two_reactors(4,1,5,2),35))\r\n%%\r\nassert(isequal(two_reactors(2,3,2,2),5))\r\n%%\r\nassert(isequal(two_reactors(1,7,3,6),6))\r\n%%\r\nassert(isequal(two_reactors(7,5,6,5),10))\r\n%%\r\nassert(isequal(two_reactors(2,5,9,9),14))\r\n%%\r\nassert(isequal(two_reactors(3,3,6,7),14))\r\n%%\r\nassert(isequal(two_reactors(5,3,10,1),39))\r\n%%\r\nassert(isequal(two_reactors(2,2,2,7),5))\r\n%%\r\nassert(isequal(two_reactors(6,1,10,8),18))\r\n%%\r\nassert(isequal(two_reactors(8,1,9,10),33))\r\n%%\r\nassert(isequal(two_reactors(10,9,8,6),13))\r\n%%\r\nassert(isequal(two_reactors(2,4,2,1),5))\r\n%%\r\nassert(isequal(two_reactors(10,4,3,4),15))\r\n%%\r\nassert(isequal(two_reactors(5,7,1,9),8))\r\n%%\r\nassert(isequal(two_reactors(6,9,4,5),9))\r\n%%\r\nassert(isequal(two_reactors(1,2,7,4),10))\r\n%%\r\nassert(isequal(two_reactors(9,2,10,6),13))\r\n%%\r\nassert(isequal(two_reactors(8,10,3,5),16))\r\n%%\r\nassert(isequal(two_reactors(5,8,9,2),12))\r\n%%\r\nassert(isequal(two_reactors(2,4,1,6),5))\r\n%%\r\nassert(isequal(two_reactors(4,2,3,10),7))\r\n%%\r\nassert(isequal(two_reactors(7,5,10,2),13))\r\n%%\r\nassert(isequal(two_reactors(8,8,6,2),29))\r\n%%\r\nassert(isequal(two_reactors(6,3,2,3),20))\r\n%%\r\nassert(isequal(two_reactors(9,1,3,1),12))\r\n%%\r\nassert(isequal(two_reactors(5,1,9,2),64))\r\n%%\r\nassert(isequal(two_reactors(1,4,5,2),18))\r\n%%\r\nassert(isequal(two_reactors(10,4,3,1),30))\r\n%%\r\nassert(isequal(two_reactors(3,1,6,8),12))\r\n%%\r\nassert(isequal(two_reactors(7,1,1,8),10))\r\n%%\r\nassert(isequal(two_reactors(10,6,2,9),13))\r\n%%\r\nassert(isequal(two_reactors(4,3,8,1),44))\r\n%%\r\nassert(isequal(two_reactors(1,7,7,6),10))\r\n%%\r\nassert(isequal(two_reactors(8,8,8,3),11))\r\n%%\r\nassert(isequal(two_reactors(1,1,1,1),4))\r\n%%\r\nassert(isequal(two_reactors(7,6,4,1),14))\r\n%%\r\nassert(isequal(two_reactors(8,4,7,8),11))\r\n%%\r\nassert(isequal(two_reactors(2,2,6,5),11))\r\n%%\r\nassert(isequal(two_reactors(9,8,8,1),33))\r\n%%\r\nassert(isequal(two_reactors(1,1,8,10),12))\r\n%%\r\nassert(isequal(two_reactors(7,2,8,2),11))\r\n%%\r\nassert(isequal(two_reactors(2,7,4,7),7))\r\n%%\r\nassert(isequal(two_reactors(8,6,8,3),11))\r\n%%\r\nassert(isequal(two_reactors(8,10,9,1),12))\r\n%%\r\nassert(isequal(two_reactors(4,4,7,6),10))\r\n%%\r\nassert(isequal(two_reactors(8,4,3,1),12))\r\n%%\r\nassert(isequal(two_reactors(8,3,4,6),11))\r\n%%\r\nassert(isequal(two_reactors(3,7,5,2),8))\r\n%%\r\nassert(isequal(two_reactors(8,2,3,3),23))\r\n%%\r\nassert(isequal(two_reactors(6,1,5,2),9))\r\n%%\r\nassert(isequal(two_reactors(2,8,3,7),6))\r\n%%\r\nassert(isequal(two_reactors(10,5,7,8),13))\r\n%%\r\nassert(isequal(two_reactors(5,7,2,10),8))\r\n%%\r\nassert(isequal(two_reactors(2,3,8,5),12))\r\n%%\r\nassert(isequal(two_reactors(8,4,3,1),12))\r\n%%\r\nassert(isequal(two_reactors(7,5,5,7),10))\r\n%%\r\nassert(isequal(two_reactors(1,4,8,7),11))\r\n%%\r\nassert(isequal(two_reactors(2,2,1,1),12))\r\n%%\r\nassert(isequal(two_reactors(5,7,8,6),11))\r\n%%\r\nassert(isequal(two_reactors(2,7,2,2),5))\r\n%%\r\nassert(isequal(two_reactors(1,2,2,2),5))\r\n%%\r\nassert(isequal(two_reactors(4,4,3,3),7))\r\n%%\r\nassert(isequal(two_reactors(9,8,6,2),19))\r\n%%\r\nassert(isequal(two_reactors(3,1,10,8),18))\r\n%%\r\nassert(isequal(two_reactors(6,4,2,7),9))\r\n%%\r\nassert(isequal(two_reactors(10,2,3,4),27))\r\n%%\r\nassert(isequal(two_reactors(1,7,5,10),8))\r\n%%\r\nassert(isequal(two_reactors(5,7,2,4),8))\r\n%%\r\nassert(isequal(two_reactors(2,8,9,4),12))\r\n%%\r\nassert(isequal(two_reactors(7,3,6,9),10))\r\n%%\r\nassert(isequal(two_reactors(6,4,3,5),9))\r\n%%\r\nassert(isequal(two_reactors(5,4,6,8),9))\r\n%%\r\nassert(isequal(two_reactors(5,5,2,1),10))\r\n%%\r\nassert(isequal(two_reactors(3,4,7,10),15))\r\n%%\r\nassert(isequal(two_reactors(10,5,3,8),13))\r\n%%\r\nassert(isequal(two_reactors(8,8,8,2),11))\r\n%%\r\nassert(isequal(two_reactors(7,5,3,1),12))\r\n%%\r\nassert(isequal(two_reactors(9,2,2,7),38))\r\n%%\r\nassert(isequal(two_reactors(9,6,8,2),12))\r\n%%\r\nassert(isequal(two_reactors(10,6,7,1),50))\r\n%%\r\nassert(isequal(two_reactors(9,8,2,6),15))\r\n%%\r\nassert(isequal(two_reactors(4,6,4,5),7))\r\n%%\r\nassert(isequal(two_reactors(2,3,1,10),5))\r\n%%\r\nassert(isequal(two_reactors(7,10,2,10),10))\r\n%%\r\nassert(isequal(two_reactors(8,6,5,3),28))\r\n%%\r\nassert(isequal(two_reactors(8,3,1,8),11))\r\n%%\r\nassert(isequal(two_reactors(7,8,7,5),10))\r\n%%\r\nassert(isequal(two_reactors(4,9,4,9),7))\r\n%%\r\nassert(isequal(two_reactors(8,9,6,7),11))\r\n%%\r\nassert(isequal(two_reactors(10,5,1,9),16))\r\n","published":true,"deleted":false,"likes_count":3,"comments_count":0,"created_by":255320,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":55,"test_suite_updated_at":"2020-03-31T12:17:41.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2020-03-30T13:46:07.000Z","updated_at":"2026-03-31T14:28:25.000Z","published_at":"2020-03-30T14:06:30.000Z","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\u003eIn a certain pharmaceutical production company, there are two tank reactors operating simultaneously and independent of each other. Each reactor operates by cycling through 4 phases:\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=\\\"2\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFilling phase - The empty reactor is filled with raw materials.\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=\\\"2\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eReacting phase - The filled reactor is heated to start the chemical reaction.\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=\\\"2\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eEmptying phase - The reaction ends and the tank is emptied of all contents.\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=\\\"2\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eCleaning phase - The emptied reactor must be cleaned to prepare for the next batch.\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\u003eAt the end of each cycle, a fresh new batch of drugs are being produced. The two reactors produce different drugs, and so the length of time to finish each phase for the two reactors may be different.\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\u003eHowever, the company manager wishes to avoid a scenario when the two reactors are both in the cleaning phase at the same time. This is because it takes manpower to clean a tank, and there is not enough manpower to clean two tanks at a time. If we start the filling phase of both reactors at this moment and continue producing batches one after the other without fail, can you determine the earliest time when both tanks require cleaning?\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\u003eWrite a function that takes 4 values, R1, C1, R2, C2, which respectively denotes the amount of time in hours for reacting and cleaning in reactor 1 followed by the amount of time in hours for reacting and cleaning in reactor 2. Since both tanks are of the same size, the filling and emptying phase each takes 1 hour for both of them. You are ensured that all inputs are integers and 1 \u0026lt;= R1, C1, R2, C2 \u0026lt;= 10. Output the earliest hour when the reactors are both undergoing a cleaning phase. You are also ensured that a positive integer answer exists for each test case.\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 first two sample test cases below are illustrated in the following figure.\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=\\\"306\\\"/\u003e\u003cw:attr w:name=\\\"width\\\" w:val=\\\"573\\\"/\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=\\\"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\u003eSample test cases:\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[\u003e\u003e two_reactors(3,2,2,1)\\nans =\\n    20\\n\u003e\u003e two_reactors(4,1,2,2)\\nans =\\n    35\\n\u003e\u003e two_reactors(1,2,2,2)\\nans =\\n    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Sequences 95: LCM Sums ","description":"For a given , write the function lcmSum(n), defined as follows:\r\n                    \r\nFor example for :\r\n  \u003e\u003e lcmSum = @(n) sum(lcm(n,1:n));\r\n  \u003e\u003e lcmSum(20)\r\n  ans =\r\n        2320\r\nSince the sum grows very fast, please present your answer as a character string array and please limit the cody program size of the function to 150. ","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.440001px; 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: none; white-space: normal; \"\u003e\u003cdiv style=\"block-size: 248px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 124px; transform-origin: 407px 124px; 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: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eFor a given \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"font-family: STIXGeneral, STIXGeneral-webfont, serif; font-style: italic; font-weight: 400; color: rgb(0, 0, 0);\"\u003en\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: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003e, write the function \u003c/span\u003e\u003c/span\u003e\u003ca target='_blank' href = \"https://www.mathworks.com/help/matlab/ref/lcm.html\"\u003e\u003cspan style=\"\"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; font-weight: 700; text-decoration-line: underline; \"\u003elcm\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: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; font-weight: 700; \"\u003eSum(n)\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: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003e, defined as follows:\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 46px; 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 23px; text-align: left; transform-origin: 384px 23px; 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 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e                    \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"vertical-align:-17px\"\u003e\u003cimg src=\"data:image/png;base64,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\" width=\"173.5\" height=\"46\" style=\"width: 173.5px; height: 46px;\"\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 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eFor example for \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"vertical-align:-5px\"\u003e\u003cimg src=\"data:image/png;base64,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\" width=\"44\" height=\"18\" style=\"width: 44px; height: 18px;\"\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: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e:\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgb(247, 247, 247); block-size: 80px; 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 40px; transform-origin: 404px 40px; margin-left: 3px; margin-top: 10px; margin-bottom: 10px; margin-right: 3px; \"\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20px; 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: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; 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 10px; transform-origin: 404px 10px; 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 0px; tab-size: 4; transform-origin: 0px 0px; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e  \u0026gt;\u0026gt; lcmSum = @(n) sum(lcm(n,1:n));\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20px; 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: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; 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 10px; transform-origin: 404px 10px; 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 0px; tab-size: 4; transform-origin: 0px 0px; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e  \u0026gt;\u0026gt; lcmSum(20)\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20px; 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: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; 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 10px; transform-origin: 404px 10px; 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 0px; tab-size: 4; transform-origin: 0px 0px; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e  ans =\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20px; 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: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; 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 10px; transform-origin: 404px 10px; 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 0px; tab-size: 4; transform-origin: 0px 0px; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e        2320\u003c/span\u003e\u003c/span\u003e\u003c/div\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: 10px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 10px; perspective-origin: 384px 21px; text-align: left; transform-origin: 384px 21px; 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: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eSince the sum grows very fast, please present your answer as a character string array and please limit the \u003c/span\u003e\u003c/span\u003e\u003ca target='_blank' href = \"https://www.mathworks.com/matlabcentral/content/cody/about.html\"\u003e\u003cspan style=\"\"\u003e\u003cspan style=\"font-weight: 700; text-decoration-line: underline; \"\u003ecody program size\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: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e of the function to \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: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"font-weight: 700; text-decoration-line: underline; \"\u003e150\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: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e. \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function s = lcmSum(n)\r\n    s = num2str(sum(lcm(n,1:n)));\r\nend","test_suite":"%%\r\nn = 1:20;\r\ns = arrayfun(@(i) str2num(lcmSum(i)),n)\r\ns_correct = [1 4 12 24 55 66 154 176 279 320 616 468 1027 910 1110 1376 2329 1656 3268 2320];\r\nassert(isequal(s,s_correct))\r\n%%\r\nn = [50 500 5000];\r\ns = arrayfun(@(i) str2num(lcmSum(i)),n);\r\ns_correct = [39100 35808000 34993510000];\r\nassert(isequal(s,s_correct))\r\n%%\r\nn = [123 12345 123456 1234567 12345678 123456789];\r\ns = arrayfun(@(i) lcmSum(i),n,'uni',0);\r\ns_correct = {'706512' '613833706425' '487134624293760' '933390306503591194' '520297769997641090106' '708149874610092995986509'};\r\nassert(isequal(s,s_correct))\r\n%%\r\nn = 10.^(0:10);\r\ns = cellfun(@(x) [length(find(x-'0')) length(x) sum(x)],arrayfun(@(i) lcmSum(i),n,'uni',0),'uni',0);\r\ns_correct = {[1 1 49] [2 3 149] [4 6 310] [6 9 466] [7 12 608] [10 15 763] [12 18 922] [14 21 1085] [13 24 1234] [16 27 1387] [19 30 1535]};\r\nassert(isequal(s,s_correct))\r\n%%\r\nn = 100000001:100010000;\r\ns = sum(cellfun(@(s) sum(s),arrayfun(@(i) lcmSum(i),n,'uni',0)))\r\ns_correct = 12575131;\r\nassert(isequal(s,s_correct))\r\n%%\r\nfiletext = fileread('lcmSum.m');\r\nnot_allowed = contains(filetext, 'persistent') || contains(filetext, 'global') || contains(filetext, 'regexp') || contains(filetext, 'eval') || contains(filetext, 'assignin') || contains(filetext, 'java');\r\nassert(~not_allowed)\r\nassert(mtree(filetext).count\u003c=150)","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":255988,"edited_by":255988,"edited_at":"2023-02-27T19:21:17.000Z","deleted_by":null,"deleted_at":null,"solvers_count":2,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2023-02-11T06:55:56.000Z","updated_at":"2026-03-18T21:45:08.000Z","published_at":"2023-02-11T18:37:12.000Z","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:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eFor a given \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"false\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003en\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e, write the function \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"https://www.mathworks.com/help/matlab/ref/lcm.html\\\"\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003cw:u/\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003elcm\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eSum(n)\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e, defined as follows:\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\u003cw:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"true\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003e\\\\text{lcmSum}(n) = \\\\sum_{k=1}^{n}\\\\text{lcm}(n,k).\u003c/w:t\u003e\u003c/w:r\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\u003eFor example for \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"false\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003en=20\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\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=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[  \u003e\u003e lcmSum = @(n) sum(lcm(n,1:n));\\n  \u003e\u003e lcmSum(20)\\n  ans =\\n        2320]]\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\u003eSince the sum grows very fast, please present your answer as a character string array and please limit the \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"https://www.mathworks.com/matlabcentral/content/cody/about.html\\\"\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003cw:u/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ecody program size\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e of the function to \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003cw:u/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e150\u003c/w:t\u003e\u003c/w:r\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\"}]}"}],"problem_search":{"errors":[],"problems":[{"id":1019,"title":"Vector LCM","description":"Find Least Common Multiple of a given vector.\r\nNeed general solution as the test suite will be expanded.\r\nFunction Template:\r\nfunction ans = vectorLCM(v)\r\n   % v=[45 15 200 300];\r\n   1800;\r\nend","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: 163.033px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 81.5167px; transform-origin: 407px 81.5167px; vertical-align: baseline; \"\u003e\u003cul style=\"block-size: 61.3px; 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 30.65px; transform-origin: 391px 30.65px; 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: 145.5px 8px; transform-origin: 145.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eFind Least Common Multiple of a given 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: 177px 8px; transform-origin: 177px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eNeed general solution as the test suite will be expanded.\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: 60px 8px; transform-origin: 60px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eFunction Template:\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ul\u003e\u003cdiv style=\"background-color: rgb(247, 247, 247); block-size: 81.7333px; 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 40.8667px; transform-origin: 404px 40.8667px; 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: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; 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: 108px 8.5px; tab-size: 4; transform-origin: 108px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\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: 36px 8.5px; text-decoration-color: rgb(14, 0, 255); text-emphasis-color: rgb(14, 0, 255); transform-origin: 36px 8.5px; \"\u003efunction \u003c/span\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 72px 8.5px; transform-origin: 72px 8.5px; \"\u003eans = vectorLCM(v)\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: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; 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: 92px 8.5px; tab-size: 4; transform-origin: 92px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 12px 8.5px; transform-origin: 12px 8.5px; \"\u003e   \u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(2, 128, 9); border-block-start-color: rgb(2, 128, 9); border-bottom-color: rgb(2, 128, 9); border-inline-end-color: rgb(2, 128, 9); border-inline-start-color: rgb(2, 128, 9); border-left-color: rgb(2, 128, 9); border-right-color: rgb(2, 128, 9); border-top-color: rgb(2, 128, 9); caret-color: rgb(2, 128, 9); color: rgb(2, 128, 9); column-rule-color: rgb(2, 128, 9); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(2, 128, 9); perspective-origin: 80px 8.5px; text-decoration-color: rgb(2, 128, 9); text-emphasis-color: rgb(2, 128, 9); transform-origin: 80px 8.5px; \"\u003e% v=[45 15 200 300];\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: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; 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: 32px 8.5px; tab-size: 4; transform-origin: 32px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e   1800;\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: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; 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: 12px 8.5px; tab-size: 4; transform-origin: 12px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\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); text-decoration-color: rgb(14, 0, 255); text-emphasis-color: rgb(14, 0, 255); \"\u003eend\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function ans = vectorLCM(v)\r\n   % v=[45 15 200 300];\r\n   1800;\r\nend\r\n","test_suite":"%%\r\nv=[45 15 200 300];\r\nassert(isequal(vectorLCM(v),1800))\r\n%%\r\nv=ones(1,9);\r\nassert(isequal(vectorLCM(v),1))\r\n%%\r\nv=5:5:50;\r\nassert(isequal(vectorLCM(v),12600))\r\n%%\r\nv=primes(10);\r\nassert(isequal(vectorLCM(v),prod(v)))","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":166,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":93,"test_suite_updated_at":"2022-03-04T05:37:41.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2012-11-01T02:12:53.000Z","updated_at":"2026-02-19T14:27:03.000Z","published_at":"2012-11-01T02:15:48.000Z","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=\\\"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\u003eFind Least Common Multiple of a given 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\u003eNeed general solution as the test suite will be expanded.\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\u003eFunction Template:\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[function ans = vectorLCM(v)\\n   % v=[45 15 200 300];\\n   1800;\\nend]]\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":60997,"title":"Multiply real numbers to get the smallest integers","description":"Write a function that takes a vector of real numbers and multiplies them by a factor to produce the integers with the smallest absolute value. For example, if the input vector is [3/4 5/6 7/10], the output should be [45 50 42]; that is, the input vector should be multiplied by 60.","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; 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: none solid rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 63px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 408px 31.5px; transform-origin: 408px 31.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"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: 385px 31.5px; text-align: left; transform-origin: 385px 31.5px; white-space-collapse: preserve; 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 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eWrite a function that takes a vector of real numbers and multiplies them by a factor to produce the integers with the smallest absolute value. For example, if the input vector is [3/4 5/6 7/10], the output should be [45 50 42]; that is, the input vector should be multiplied by 60.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = integerize(x)\r\n  y = ceil(x);\r\nend","test_suite":"%%\r\nx = [3/4 5/6 7/10];\r\ny = integerize(x);\r\ny_correct = [45 50 42];\r\nassert(isequal(y,y_correct))\r\n\r\n%%\r\nx = [1.5 8.9 6.35 7.125];\r\ny = integerize(x);\r\ny_correct = [60 356 254 285];\r\nassert(isequal(y,y_correct))\r\n\r\n%%\r\nx = randi(80,[1 14])-40;\r\ny = integerize(x);\r\ny_correct = x;\r\nassert(isequal(y,y_correct))\r\n\r\n%%\r\nx = [4/5 -8/7 15/12 -13/49 83/56];\r\ny = integerize(x);\r\ny_correct = [1568 -2240 2450 -520 2905];\r\nassert(isequal(y,y_correct))\r\n\r\n%%\r\nm = randi(6);\r\np = primes(100);\r\nk = randperm(length(p),2*m);\r\nn = p(k(1:m));\r\nd = p(k(m+1:end));\r\nf = prod(d);\r\nx = n./d;\r\ny = integerize(x);\r\ny_correct = x*f;\r\nassert(isequal(y,y_correct))","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":46909,"edited_by":46909,"edited_at":"2025-09-08T01:51:47.000Z","deleted_by":null,"deleted_at":null,"solvers_count":10,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2025-09-08T01:51:22.000Z","updated_at":"2026-03-03T15:30:27.000Z","published_at":"2025-09-08T01:51:47.000Z","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\u003eWrite a function that takes a vector of real numbers and multiplies them by a factor to produce the integers with the smallest absolute value. For example, if the input vector is [3/4 5/6 7/10], the output should be [45 50 42]; that is, the input vector should be multiplied by 60.\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":46096,"title":"LCM","description":null,"description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; 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: none solid rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 49.96px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 406.5px 24.98px; transform-origin: 406.5px 24.98px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 20.48px; 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: 383.5px 10.24px; text-align: left; transform-origin: 383.5px 10.24px; 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 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003egiven two numbers, calculate the lcm.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 20.48px; 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: 383.5px 10.24px; text-align: left; transform-origin: 383.5px 10.24px; 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 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003enb. built-in functions are disabled\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = lc_cal(a,b)\r\n  y = x;\r\nend","test_suite":"%%\r\nassert(isequal(lc_cal(5,6),30))\r\n%%\r\nassert(isequal(lc_cal(65,24843),124215))\r\n%%\r\nassert(isequal(lc_cal(28851538,1183019),1933053046))\r\n%%\r\nassert(isequal(lc_cal(3,9),9))\r\n%%\r\nassert(isequal(lc_cal(1,1),1))\r\n%%\r\nassert(isequal(lc_cal(6236412, 24228),12591315828))\r\n%%\r\nfiletext = fileread('lc_cal.m');\r\nassert(isempty(strfind(filetext, 'gcd')),'gcd() forbidden')\r\nassert(isempty(strfind(filetext, 'lcm')),'lcm() forbidden')\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":363598,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":24,"test_suite_updated_at":"2020-08-03T02:00:39.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2020-08-03T01:54:30.000Z","updated_at":"2026-01-03T16:57:05.000Z","published_at":"2020-08-03T02:00:39.000Z","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\u003egiven two numbers, calculate the lcm.\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\u003enb. built-in functions are disabled\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":1975,"title":"Kaggle: Reverse Game of Life - Zoo of Stills and Oscillators","description":"\u003chttp://www.kaggle.com/c/conway-s-reverse-game-of-life Kaggle's Conway's Reverse Game of Life\u003e contest inspires this Reverse Life Zoo challenge. The kaggle contest runs from Oct-14-2013 thru Mar-02-2014. References: \u003chttp://mathworld.wolfram.com/GameofLife.html Game of Life at Wolfram\u003e. \u003chttp://en.wikipedia.org/wiki/Conway%27s_Game_of_Life Wiki Life\u003e.\r\n\r\n\r\n  1. Any live cell with fewer than two live neighbors dies, as if caused by under-population.\r\n  2. Any live cell with two or three live neighbors lives on to the next generation.\r\n  3. Any live cell with more than three live neighbors dies, as if by overcrowding.\r\n  4. Any dead cell with exactly three live neighbors becomes a live cell, as if by reproduction.\r\n5. No wrap around. Beyond edge is zero. Eight Neighbors.\r\n\r\n\r\n\r\nDetermine the Zoo of life at its previous Snapshot. The output must evolve to the given Zoo Snapshot.  It is a Zoo since all animals are in their private enclosures and do not interact with any other animals. Animals are stable or cyclic oscillators.\r\n\r\n*Input:* Zoo , an [m,n] array\r\n\r\n*Output:* ZooPre, image of the Zoo at its prior iteration\r\n\r\n\r\n*Example:*\r\n\r\n  Zoo        ZooPre\r\n  0000000000  000000000  \r\n  0110000100  011000000  \r\n  0110000100  011001110  \r\n  0000000100  000000000  \r\n  0000000000  000000000\r\n\r\n*Additional References:*\r\n\u003chttp://www.conwaylife.com/wiki/Oscillator Oscillators\u003e, \u003chttp://www.conwaylife.com/wiki/Still_life Still Life\u003e\r\n\r\n*Next:* Small Island - Prior Snapshot Prediction","description_html":"\u003cp\u003e\u003ca href = \"http://www.kaggle.com/c/conway-s-reverse-game-of-life\"\u003eKaggle's Conway's Reverse Game of Life\u003c/a\u003e contest inspires this Reverse Life Zoo challenge. The kaggle contest runs from Oct-14-2013 thru Mar-02-2014. References: \u003ca href = \"http://mathworld.wolfram.com/GameofLife.html\"\u003eGame of Life at Wolfram\u003c/a\u003e. \u003ca href = \"http://en.wikipedia.org/wiki/Conway%27s_Game_of_Life\"\u003eWiki Life\u003c/a\u003e.\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003e1. Any live cell with fewer than two live neighbors dies, as if caused by under-population.\r\n2. Any live cell with two or three live neighbors lives on to the next generation.\r\n3. Any live cell with more than three live neighbors dies, as if by overcrowding.\r\n4. Any dead cell with exactly three live neighbors becomes a live cell, as if by reproduction.\r\n5. No wrap around. Beyond edge is zero. Eight Neighbors.\r\n\u003c/pre\u003e\u003cp\u003eDetermine the Zoo of life at its previous Snapshot. The output must evolve to the given Zoo Snapshot.  It is a Zoo since all animals are in their private enclosures and do not interact with any other animals. Animals are stable or cyclic oscillators.\u003c/p\u003e\u003cp\u003e\u003cb\u003eInput:\u003c/b\u003e Zoo , an [m,n] array\u003c/p\u003e\u003cp\u003e\u003cb\u003eOutput:\u003c/b\u003e ZooPre, image of the Zoo at its prior iteration\u003c/p\u003e\u003cp\u003e\u003cb\u003eExample:\u003c/b\u003e\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003eZoo        ZooPre\r\n0000000000  000000000  \r\n0110000100  011000000  \r\n0110000100  011001110  \r\n0000000100  000000000  \r\n0000000000  000000000\r\n\u003c/pre\u003e\u003cp\u003e\u003cb\u003eAdditional References:\u003c/b\u003e \u003ca href = \"http://www.conwaylife.com/wiki/Oscillator\"\u003eOscillators\u003c/a\u003e, \u003ca href = \"http://www.conwaylife.com/wiki/Still_life\"\u003eStill Life\u003c/a\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eNext:\u003c/b\u003e Small Island - Prior Snapshot Prediction\u003c/p\u003e","function_template":"function ZooPre=Zoo_prior(Zoo)\r\n ZooPre=Zoo;\r\nend","test_suite":"%%\r\n block=[0 0 0 0;0 1 1 0;0 1 1 0;0 0 0 0];\r\n Zoo=repmat(block,3,1);\r\n\r\n ZooPre=Zoo_prior(Zoo);\r\n mc=conv2(single(ZooPre),[1 1 1;1 0 1;1 1 1],'same');\r\n ZooChk=~(mc\u003c2 | mc\u003e3) \u0026 ((ZooPre \u0026 mc==2) | (ZooPre \u0026 mc==3) | (~ZooPre \u0026 mc==3)); \r\n\r\n \r\n   assert(all(all(ZooChk==Zoo))) \r\n%  figure(1);imagesc(ZooPre)\r\n%  figure(2);imagesc(Zoo)\r\n\r\n%%\r\ncaterer1=[0 0 0 0 0 0 0 0 0 0;0 0 0 1 0 0 0 0 0 0;0 1 0 0 0 1 1 1 1 0;0 1 0 0 0 1 0 0 0 0;0 1 0 0 0 0 0 0 0 0;0 0 0 0 1 0 0 0 0 0;0 0 1 1 0 0 0 0 0 0;0 0 0 0 0 0 0 0 0 0];\r\n\r\ncaterer2=[0     0     0     0     0     0     0     0     0     0;\r\n     0     0     0     0     0     0     1     1     0     0;\r\n     0     0     1     0     1     1     1     1     0     0;\r\n     1     1     1     0     0     1     0     1     0     0;\r\n     0     0     0     0     0     0     0     0     0     0;\r\n     0     0     1     1     0     0     0     0     0     0;\r\n     0     0     0     1     0     0     0     0     0     0;\r\n     0     0     0     0     0     0     0     0     0     0];\r\n\r\ncaterer3=[0     0     0     0     0     0     0     0     0     0;\r\n     0     0     0     0     0     0     0     1     0     0;\r\n     0     0     1     1     1     0     0     0     1     0;\r\n     0     1     1     1     1     1     0     1     0     0;\r\n     0     0     0     1     0     0     0     0     0     0;\r\n     0     0     1     1     0     0     0     0     0     0;\r\n     0     0     1     1     0     0     0     0     0     0;\r\n     0     0     0     0     0     0     0     0     0     0];\r\n\r\n Zoo=[caterer1 zeros(8,1) caterer2 zeros(8,1) caterer3] ;\r\n\r\n ZooPre=Zoo_prior(Zoo);\r\n mc=conv2(single(ZooPre),[1 1 1;1 0 1;1 1 1],'same');\r\n ZooChk=~(mc\u003c2 | mc\u003e3) \u0026 ((ZooPre \u0026 mc==2) | (ZooPre \u0026 mc==3) | (~ZooPre \u0026 mc==3)); \r\n\r\n \r\n   assert(all(all(ZooChk==Zoo))) \r\n%  figure(1);imagesc(ZooPre)\r\n%  figure(2);imagesc(Zoo)\r\n\r\n%%\r\ncaterer1=[0 0 0 0 0 0 0 0 0 0;0 0 0 1 0 0 0 0 0 0;0 1 0 0 0 1 1 1 1 0;0 1 0 0 0 1 0 0 0 0;0 1 0 0 0 0 0 0 0 0;0 0 0 0 1 0 0 0 0 0;0 0 1 1 0 0 0 0 0 0;0 0 0 0 0 0 0 0 0 0]; % 8x10\r\nLoaf=[0 0 0 0 0 0;0 0 1 1 0 0;0 1 0 0 1 0;0 0 1 0 1 0;0 0 0 1 0 0;0 0 0 0 0 0]; % 6x6\r\nblinker=[0 0 0 0 0;0 0 0 0 0;0 1 1 1 0;0 0 0 0 0;0 0 0 0 0]; % 5x5\r\n\r\n\r\n\r\nZoo=[[Loaf;Loaf'] zeros(12,1) [caterer1;zeros(4,10)] [blinker;blinker';zeros(2,5)] ] ;\r\n\r\n ZooPre=Zoo_prior(Zoo);\r\n mc=conv2(single(ZooPre),[1 1 1;1 0 1;1 1 1],'same');\r\n ZooChk=~(mc\u003c2 | mc\u003e3) \u0026 ((ZooPre \u0026 mc==2) | (ZooPre \u0026 mc==3) | (~ZooPre \u0026 mc==3)); \r\n\r\n \r\n   assert(all(all(ZooChk==Zoo))) \r\n%  figure(1);imagesc(ZooPre)\r\n%  figure(2);imagesc(Zoo)\r\n\r\n","published":true,"deleted":false,"likes_count":3,"comments_count":1,"created_by":3097,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":19,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2013-11-09T04:53:18.000Z","updated_at":"2026-02-13T15:21:36.000Z","published_at":"2013-11-09T05:22:10.000Z","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:hyperlink w:docLocation=\\\"http://www.kaggle.com/c/conway-s-reverse-game-of-life\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eKaggle's Conway's Reverse Game of Life\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e contest inspires this Reverse Life Zoo challenge. The kaggle contest runs from Oct-14-2013 thru Mar-02-2014. 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.\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. No wrap around. Beyond edge is zero. Eight Neighbors.]]\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\u003eDetermine the Zoo of life at its previous Snapshot. The output must evolve to the given Zoo Snapshot. It is a Zoo since all animals are in their private enclosures and do not interact with any other animals. Animals are stable or cyclic oscillators.\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 Zoo , an [m,n] 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: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 ZooPre, image of the Zoo at its prior iteration\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\u003eExample:\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[Zoo        ZooPre\\n0000000000  000000000  \\n0110000100  011000000  \\n0110000100  011001110  \\n0000000100  000000000  \\n0000000000  000000000]]\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:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eAdditional 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://www.conwaylife.com/wiki/Oscillator\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eOscillators\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://www.conwaylife.com/wiki/Still_life\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eStill Life\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=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eNext:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e Small Island - Prior Snapshot Prediction\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":45402,"title":"Find an overlap in the cleaning schedule of two tank reactors","description":"In a certain pharmaceutical production company, there are two tank reactors operating simultaneously and independent of each other. Each reactor operates by cycling through 4 phases:\r\n\r\n# Filling phase - The empty reactor is filled with raw materials.\r\n# Reacting phase - The filled reactor is heated to start the chemical reaction.\r\n# Emptying phase - The reaction ends and the tank is emptied of all contents.\r\n# Cleaning phase - The emptied reactor must be cleaned to prepare for the next batch.\r\n\r\nAt the end of each cycle, a fresh new batch of drugs are being produced. The two reactors produce different drugs, and so the length of time to finish each phase for the two reactors may be different.\r\n\r\nHowever, the company manager wishes to avoid a scenario when the two reactors are both in the cleaning phase at the same time. This is because it takes manpower to clean a tank, and there is not enough manpower to clean two tanks at a time. If we start the filling phase of both reactors at this moment and continue producing batches one after the other without fail, can you determine the earliest time when both tanks require cleaning? \r\n\r\nWrite a function that takes 4 values, R1, C1, R2, C2, which respectively denotes the amount of time in hours for reacting and cleaning in reactor 1 followed by the amount of time in hours for reacting and cleaning in reactor 2. Since both tanks are of the same size, the filling and emptying phase each takes 1 hour for both of them. You are ensured that all inputs are integers and 1 \u003c= R1, C1, R2, C2 \u003c= 10. Output the earliest hour when the reactors are both undergoing a cleaning phase. You are also ensured that a positive integer answer exists for each test case.\r\n\r\nThe first two sample test cases below are illustrated in this figure: \u003chttps://drive.google.com/open?id=1BWnAMQgaiz5OZQe466DiFQ8yTWlm8JRI\u003e\r\n\r\nSample test cases:\r\n\r\n  \u003e\u003e two_reactors(3,2,2,1)\r\n  ans =\r\n      20\r\n  \u003e\u003e two_reactors(4,1,2,2)\r\n  ans =\r\n      35\r\n\u003e\u003e two_reactors(1,2,2,2)\r\n  ans =\r\n      5","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; 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: none solid rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 1028.2px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 514.1px; transform-origin: 407px 514.1px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 41.6px; 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 20.8px; text-align: left; transform-origin: 384px 20.8px; 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 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eIn a certain pharmaceutical production company, there are two tank reactors operating simultaneously and independent of each other. Each reactor operates by cycling through 4 phases:\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003col style=\"block-size: 80px; font-family: Helvetica, Arial, sans-serif; list-style-type: decimal; margin-block-end: 20px; margin-block-start: 10px; margin-bottom: 20px; margin-top: 10px; perspective-origin: 391px 40px; transform-origin: 391px 40px; margin-top: 10px; margin-bottom: 20px; \"\u003e\u003cli style=\"block-size: 20px; 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 10px; text-align: left; transform-origin: 363px 10px; white-space: pre-wrap; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eFilling phase - The empty reactor is filled with raw materials.\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 20px; 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 10px; text-align: left; transform-origin: 363px 10px; white-space: pre-wrap; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eReacting phase - The filled reactor is heated to start the chemical reaction.\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 20px; 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 10px; text-align: left; transform-origin: 363px 10px; white-space: pre-wrap; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eEmptying phase - The reaction ends and the tank is emptied of all contents.\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 20px; 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 10px; text-align: left; transform-origin: 363px 10px; white-space: pre-wrap; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eCleaning phase - The emptied reactor must be cleaned to prepare for the next batch.\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e\u003cdiv style=\"block-size: 41.6px; 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 20.8px; text-align: left; transform-origin: 384px 20.8px; 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 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eAt the end of each cycle, a fresh new batch of drugs are being produced. The two reactors produce different drugs, and so the length of time to finish each phase for the two reactors may be different.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 83.2px; 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 41.6px; text-align: left; transform-origin: 384px 41.6px; 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 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eHowever, the company manager wishes to avoid a scenario when the two reactors are both in the cleaning phase at the same time. This is because it takes manpower to clean a tank, and there is not enough manpower to clean two tanks at a time. If we start the filling phase of both reactors at this moment and continue producing batches one after the other without fail, can you determine the earliest time when both tanks require cleaning?\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 104px; 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 52px; text-align: left; transform-origin: 384px 52px; 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 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eWrite a function that takes 4 values, R1, C1, R2, C2, which respectively denotes the amount of time in hours for reacting and cleaning in reactor 1 followed by the amount of time in hours for reacting and cleaning in reactor 2. Since both tanks are of the same size, the filling and emptying phase each takes 1 hour for both of them. You are ensured that all inputs are integers and 1 \u0026lt;= R1, C1, R2, C2 \u0026lt;= 10. Output the earliest hour when the reactors are both undergoing a cleaning phase. You are also ensured that a positive integer answer exists for each test case.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 20.8px; 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 10.4px; text-align: left; transform-origin: 384px 10.4px; 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 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eThe first two sample test cases below are illustrated in the following figure.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 20.8px; 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 10.4px; text-align: left; transform-origin: 384px 10.4px; 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 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 311.6px; 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 155.8px; text-align: left; transform-origin: 384px 155.8px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cimg class=\"imageNode\" width=\"573\" height=\"306\" style=\"vertical-align: baseline;width: 573px;height: 306px\" 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data-image-state=\"image-loaded\"\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 20.8px; 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 10.4px; text-align: left; transform-origin: 384px 10.4px; 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 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 20.8px; 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 10.4px; text-align: left; transform-origin: 384px 10.4px; 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 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eSample test cases:\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgb(247, 247, 247); block-size: 180px; border-bottom-left-radius: 4px; border-bottom-right-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 90px; transform-origin: 404px 90px; margin-left: 3px; margin-top: 10px; margin-bottom: 10px; margin-right: 3px; \"\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; 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 10px; transform-origin: 404px 10px; 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 0px; tab-size: 4; transform-origin: 0px 0px; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e\u0026gt;\u0026gt; two_reactors(3,2,2,1)\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; 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 10px; transform-origin: 404px 10px; 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 0px; tab-size: 4; transform-origin: 0px 0px; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003eans =\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; 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 10px; transform-origin: 404px 10px; 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 0px; tab-size: 4; transform-origin: 0px 0px; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e    20\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; 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 10px; transform-origin: 404px 10px; 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 0px; tab-size: 4; transform-origin: 0px 0px; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e\u0026gt;\u0026gt; two_reactors(4,1,2,2)\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; 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 10px; transform-origin: 404px 10px; 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 0px; tab-size: 4; transform-origin: 0px 0px; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003eans =\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; 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 10px; transform-origin: 404px 10px; 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 0px; tab-size: 4; transform-origin: 0px 0px; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e    35\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; 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 10px; transform-origin: 404px 10px; 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 0px; tab-size: 4; transform-origin: 0px 0px; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e\u0026gt;\u0026gt; two_reactors(1,2,2,2)\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; 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 10px; transform-origin: 404px 10px; 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 0px; tab-size: 4; transform-origin: 0px 0px; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003eans =\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; 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 10px; transform-origin: 404px 10px; 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 0px; tab-size: 4; transform-origin: 0px 0px; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e    5\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = two_reactors(R1,C1,R2,C2)\r\n  y = R1;\r\nend","test_suite":"%%\r\nassert(isequal(two_reactors(5,1,6,5),24))\r\n%%\r\nassert(isequal(two_reactors(1,2,2,2),5))\r\n%%\r\nassert(isequal(two_reactors(7,7,7,1),10))\r\n%%\r\nassert(isequal(two_reactors(1,4,6,7),11))\r\n%%\r\nassert(isequal(two_reactors(5,9,8,10),11))\r\n%%\r\nassert(isequal(two_reactors(6,4,2,7),9))\r\n%%\r\nassert(isequal(two_reactors(8,5,1,3),11))\r\n%%\r\nassert(isequal(two_reactors(2,3,5,6),12))\r\n%%\r\nassert(isequal(two_reactors(5,9,6,10),9))\r\n%%\r\nassert(isequal(two_reactors(7,10,3,7),10))\r\n%%\r\nassert(isequal(two_reactors(3,7,7,1),10))\r\n%%\r\nassert(isequal(two_reactors(3,3,7,9),14))\r\n%%\r\nassert(isequal(two_reactors(4,8,7,1),10))\r\n%%\r\nassert(isequal(two_reactors(7,4,10,1),13))\r\n%%\r\nassert(isequal(two_reactors(5,5,5,8),8))\r\n%%\r\nassert(isequal(two_reactors(4,8,5,1),8))\r\n%%\r\nassert(isequal(two_reactors(2,8,5,2),8))\r\n%%\r\nassert(isequal(two_reactors(4,7,2,8),7))\r\n%%\r\nassert(isequal(two_reactors(3,10,3,8),6))\r\n%%\r\nassert(isequal(two_reactors(2,3,1,6),5))\r\n%%\r\nassert(isequal(two_reactors(7,6,5,7),10))\r\n%%\r\nassert(isequal(two_reactors(7,7,7,10),10))\r\n%%\r\nassert(isequal(two_reactors(3,8,3,2),6))\r\n%%\r\nassert(isequal(two_reactors(7,5,5,7),10))\r\n%%\r\nassert(isequal(two_reactors(8,4,7,5),11))\r\n%%\r\nassert(isequal(two_reactors(9,9,3,7),12))\r\n%%\r\nassert(isequal(two_reactors(6,6,9,3),12))\r\n%%\r\nassert(isequal(two_reactors(4,2,10,7),15))\r\n%%\r\nassert(isequal(two_reactors(10,1,9,1),156))\r\n%%\r\nassert(isequal(two_reactors(5,7,6,7),9))\r\n%%\r\nassert(isequal(two_reactors(6,8,6,10),9))\r\n%%\r\nassert(isequal(two_reactors(3,2,2,1),20))\r\n%%\r\nassert(isequal(two_reactors(5,5,4,8),8))\r\n%%\r\nassert(isequal(two_reactors(7,8,10,10),13))\r\n%%\r\nassert(isequal(two_reactors(2,2,7,1),30))\r\n%%\r\nassert(isequal(two_reactors(6,6,9,5),12))\r\n%%\r\nassert(isequal(two_reactors(4,7,8,6),11))\r\n%%\r\nassert(isequal(two_reactors(4,2,6,3),31))\r\n%%\r\nassert(isequal(two_reactors(1,8,3,5),6))\r\n%%\r\nassert(isequal(two_reactors(7,4,8,4),11))\r\n%%\r\nassert(isequal(two_reactors(7,8,5,1),16))\r\n%%\r\nassert(isequal(two_reactors(4,5,3,2),7))\r\n%%\r\nassert(isequal(two_reactors(9,5,9,4),12))\r\n%%\r\nassert(isequal(two_reactors(8,4,9,8),12))\r\n%%\r\nassert(isequal(two_reactors(4,3,8,10),16))\r\n%%\r\nassert(isequal(two_reactors(4,7,5,9),8))\r\n%%\r\nassert(isequal(two_reactors(8,2,9,10),12))\r\n%%\r\nassert(isequal(two_reactors(6,9,6,2),9))\r\n%%\r\nassert(isequal(two_reactors(2,5,8,9),14))\r\n%%\r\nassert(isequal(two_reactors(8,4,6,1),27))\r\n%%\r\nassert(isequal(two_reactors(2,2,7,5),11))\r\n%%\r\nassert(isequal(two_reactors(2,5,2,1),5))\r\n%%\r\nassert(isequal(two_reactors(9,6,10,7),13))\r\n%%\r\nassert(isequal(two_reactors(6,9,9,10),12))\r\n%%\r\nassert(isequal(two_reactors(1,9,7,10),10))\r\n%%\r\nassert(isequal(two_reactors(6,5,9,3),12))\r\n%%\r\nassert(isequal(two_reactors(5,10,6,9),9))\r\n%%\r\nassert(isequal(two_reactors(8,6,3,7),11))\r\n%%\r\nassert(isequal(two_reactors(1,7,7,8),10))\r\n%%\r\nassert(isequal(two_reactors(9,10,8,6),12))\r\n%%\r\nassert(isequal(two_reactors(10,6,1,2),14))\r\n%%\r\nassert(isequal(two_reactors(9,5,9,3),12))\r\n%%\r\nassert(isequal(two_reactors(6,7,1,7),9))\r\n%%\r\nassert(isequal(two_reactors(4,1,5,2),35))\r\n%%\r\nassert(isequal(two_reactors(2,3,2,2),5))\r\n%%\r\nassert(isequal(two_reactors(1,7,3,6),6))\r\n%%\r\nassert(isequal(two_reactors(7,5,6,5),10))\r\n%%\r\nassert(isequal(two_reactors(2,5,9,9),14))\r\n%%\r\nassert(isequal(two_reactors(3,3,6,7),14))\r\n%%\r\nassert(isequal(two_reactors(5,3,10,1),39))\r\n%%\r\nassert(isequal(two_reactors(2,2,2,7),5))\r\n%%\r\nassert(isequal(two_reactors(6,1,10,8),18))\r\n%%\r\nassert(isequal(two_reactors(8,1,9,10),33))\r\n%%\r\nassert(isequal(two_reactors(10,9,8,6),13))\r\n%%\r\nassert(isequal(two_reactors(2,4,2,1),5))\r\n%%\r\nassert(isequal(two_reactors(10,4,3,4),15))\r\n%%\r\nassert(isequal(two_reactors(5,7,1,9),8))\r\n%%\r\nassert(isequal(two_reactors(6,9,4,5),9))\r\n%%\r\nassert(isequal(two_reactors(1,2,7,4),10))\r\n%%\r\nassert(isequal(two_reactors(9,2,10,6),13))\r\n%%\r\nassert(isequal(two_reactors(8,10,3,5),16))\r\n%%\r\nassert(isequal(two_reactors(5,8,9,2),12))\r\n%%\r\nassert(isequal(two_reactors(2,4,1,6),5))\r\n%%\r\nassert(isequal(two_reactors(4,2,3,10),7))\r\n%%\r\nassert(isequal(two_reactors(7,5,10,2),13))\r\n%%\r\nassert(isequal(two_reactors(8,8,6,2),29))\r\n%%\r\nassert(isequal(two_reactors(6,3,2,3),20))\r\n%%\r\nassert(isequal(two_reactors(9,1,3,1),12))\r\n%%\r\nassert(isequal(two_reactors(5,1,9,2),64))\r\n%%\r\nassert(isequal(two_reactors(1,4,5,2),18))\r\n%%\r\nassert(isequal(two_reactors(10,4,3,1),30))\r\n%%\r\nassert(isequal(two_reactors(3,1,6,8),12))\r\n%%\r\nassert(isequal(two_reactors(7,1,1,8),10))\r\n%%\r\nassert(isequal(two_reactors(10,6,2,9),13))\r\n%%\r\nassert(isequal(two_reactors(4,3,8,1),44))\r\n%%\r\nassert(isequal(two_reactors(1,7,7,6),10))\r\n%%\r\nassert(isequal(two_reactors(8,8,8,3),11))\r\n%%\r\nassert(isequal(two_reactors(1,1,1,1),4))\r\n%%\r\nassert(isequal(two_reactors(7,6,4,1),14))\r\n%%\r\nassert(isequal(two_reactors(8,4,7,8),11))\r\n%%\r\nassert(isequal(two_reactors(2,2,6,5),11))\r\n%%\r\nassert(isequal(two_reactors(9,8,8,1),33))\r\n%%\r\nassert(isequal(two_reactors(1,1,8,10),12))\r\n%%\r\nassert(isequal(two_reactors(7,2,8,2),11))\r\n%%\r\nassert(isequal(two_reactors(2,7,4,7),7))\r\n%%\r\nassert(isequal(two_reactors(8,6,8,3),11))\r\n%%\r\nassert(isequal(two_reactors(8,10,9,1),12))\r\n%%\r\nassert(isequal(two_reactors(4,4,7,6),10))\r\n%%\r\nassert(isequal(two_reactors(8,4,3,1),12))\r\n%%\r\nassert(isequal(two_reactors(8,3,4,6),11))\r\n%%\r\nassert(isequal(two_reactors(3,7,5,2),8))\r\n%%\r\nassert(isequal(two_reactors(8,2,3,3),23))\r\n%%\r\nassert(isequal(two_reactors(6,1,5,2),9))\r\n%%\r\nassert(isequal(two_reactors(2,8,3,7),6))\r\n%%\r\nassert(isequal(two_reactors(10,5,7,8),13))\r\n%%\r\nassert(isequal(two_reactors(5,7,2,10),8))\r\n%%\r\nassert(isequal(two_reactors(2,3,8,5),12))\r\n%%\r\nassert(isequal(two_reactors(8,4,3,1),12))\r\n%%\r\nassert(isequal(two_reactors(7,5,5,7),10))\r\n%%\r\nassert(isequal(two_reactors(1,4,8,7),11))\r\n%%\r\nassert(isequal(two_reactors(2,2,1,1),12))\r\n%%\r\nassert(isequal(two_reactors(5,7,8,6),11))\r\n%%\r\nassert(isequal(two_reactors(2,7,2,2),5))\r\n%%\r\nassert(isequal(two_reactors(1,2,2,2),5))\r\n%%\r\nassert(isequal(two_reactors(4,4,3,3),7))\r\n%%\r\nassert(isequal(two_reactors(9,8,6,2),19))\r\n%%\r\nassert(isequal(two_reactors(3,1,10,8),18))\r\n%%\r\nassert(isequal(two_reactors(6,4,2,7),9))\r\n%%\r\nassert(isequal(two_reactors(10,2,3,4),27))\r\n%%\r\nassert(isequal(two_reactors(1,7,5,10),8))\r\n%%\r\nassert(isequal(two_reactors(5,7,2,4),8))\r\n%%\r\nassert(isequal(two_reactors(2,8,9,4),12))\r\n%%\r\nassert(isequal(two_reactors(7,3,6,9),10))\r\n%%\r\nassert(isequal(two_reactors(6,4,3,5),9))\r\n%%\r\nassert(isequal(two_reactors(5,4,6,8),9))\r\n%%\r\nassert(isequal(two_reactors(5,5,2,1),10))\r\n%%\r\nassert(isequal(two_reactors(3,4,7,10),15))\r\n%%\r\nassert(isequal(two_reactors(10,5,3,8),13))\r\n%%\r\nassert(isequal(two_reactors(8,8,8,2),11))\r\n%%\r\nassert(isequal(two_reactors(7,5,3,1),12))\r\n%%\r\nassert(isequal(two_reactors(9,2,2,7),38))\r\n%%\r\nassert(isequal(two_reactors(9,6,8,2),12))\r\n%%\r\nassert(isequal(two_reactors(10,6,7,1),50))\r\n%%\r\nassert(isequal(two_reactors(9,8,2,6),15))\r\n%%\r\nassert(isequal(two_reactors(4,6,4,5),7))\r\n%%\r\nassert(isequal(two_reactors(2,3,1,10),5))\r\n%%\r\nassert(isequal(two_reactors(7,10,2,10),10))\r\n%%\r\nassert(isequal(two_reactors(8,6,5,3),28))\r\n%%\r\nassert(isequal(two_reactors(8,3,1,8),11))\r\n%%\r\nassert(isequal(two_reactors(7,8,7,5),10))\r\n%%\r\nassert(isequal(two_reactors(4,9,4,9),7))\r\n%%\r\nassert(isequal(two_reactors(8,9,6,7),11))\r\n%%\r\nassert(isequal(two_reactors(10,5,1,9),16))\r\n","published":true,"deleted":false,"likes_count":3,"comments_count":0,"created_by":255320,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":55,"test_suite_updated_at":"2020-03-31T12:17:41.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2020-03-30T13:46:07.000Z","updated_at":"2026-03-31T14:28:25.000Z","published_at":"2020-03-30T14:06:30.000Z","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\u003eIn a certain pharmaceutical production company, there are two tank reactors operating simultaneously and independent of each other. Each reactor operates by cycling through 4 phases:\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=\\\"2\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFilling phase - The empty reactor is filled with raw materials.\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=\\\"2\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eReacting phase - The filled reactor is heated to start the chemical reaction.\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=\\\"2\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eEmptying phase - The reaction ends and the tank is emptied of all contents.\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=\\\"2\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eCleaning phase - The emptied reactor must be cleaned to prepare for the next batch.\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\u003eAt the end of each cycle, a fresh new batch of drugs are being produced. The two reactors produce different drugs, and so the length of time to finish each phase for the two reactors may be different.\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\u003eHowever, the company manager wishes to avoid a scenario when the two reactors are both in the cleaning phase at the same time. This is because it takes manpower to clean a tank, and there is not enough manpower to clean two tanks at a time. If we start the filling phase of both reactors at this moment and continue producing batches one after the other without fail, can you determine the earliest time when both tanks require cleaning?\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\u003eWrite a function that takes 4 values, R1, C1, R2, C2, which respectively denotes the amount of time in hours for reacting and cleaning in reactor 1 followed by the amount of time in hours for reacting and cleaning in reactor 2. Since both tanks are of the same size, the filling and emptying phase each takes 1 hour for both of them. You are ensured that all inputs are integers and 1 \u0026lt;= R1, C1, R2, C2 \u0026lt;= 10. Output the earliest hour when the reactors are both undergoing a cleaning phase. You are also ensured that a positive integer answer exists for each test case.\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 first two sample test cases below are illustrated in the following figure.\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=\\\"306\\\"/\u003e\u003cw:attr w:name=\\\"width\\\" w:val=\\\"573\\\"/\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=\\\"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\u003eSample test cases:\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[\u003e\u003e two_reactors(3,2,2,1)\\nans =\\n    20\\n\u003e\u003e two_reactors(4,1,2,2)\\nans =\\n    35\\n\u003e\u003e two_reactors(1,2,2,2)\\nans =\\n    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Sequences 95: LCM Sums ","description":"For a given , write the function lcmSum(n), defined as follows:\r\n                    \r\nFor example for :\r\n  \u003e\u003e lcmSum = @(n) sum(lcm(n,1:n));\r\n  \u003e\u003e lcmSum(20)\r\n  ans =\r\n        2320\r\nSince the sum grows very fast, please present your answer as a character string array and please limit the cody program size of the function to 150. ","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.440001px; 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: none; white-space: normal; \"\u003e\u003cdiv style=\"block-size: 248px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 124px; transform-origin: 407px 124px; 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: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eFor a given \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"font-family: STIXGeneral, STIXGeneral-webfont, serif; font-style: italic; font-weight: 400; color: rgb(0, 0, 0);\"\u003en\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: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003e, write the function \u003c/span\u003e\u003c/span\u003e\u003ca target='_blank' href = \"https://www.mathworks.com/help/matlab/ref/lcm.html\"\u003e\u003cspan style=\"\"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; font-weight: 700; text-decoration-line: underline; \"\u003elcm\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: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; font-weight: 700; \"\u003eSum(n)\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: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003e, defined as follows:\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 46px; 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 23px; text-align: left; transform-origin: 384px 23px; 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 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e                    \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"vertical-align:-17px\"\u003e\u003cimg src=\"data:image/png;base64,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\" width=\"173.5\" height=\"46\" style=\"width: 173.5px; height: 46px;\"\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 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eFor example for \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"vertical-align:-5px\"\u003e\u003cimg src=\"data:image/png;base64,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\" width=\"44\" height=\"18\" style=\"width: 44px; height: 18px;\"\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: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e:\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgb(247, 247, 247); block-size: 80px; 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 40px; transform-origin: 404px 40px; margin-left: 3px; margin-top: 10px; margin-bottom: 10px; margin-right: 3px; \"\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20px; 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: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; 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 10px; transform-origin: 404px 10px; 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 0px; tab-size: 4; transform-origin: 0px 0px; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e  \u0026gt;\u0026gt; lcmSum = @(n) sum(lcm(n,1:n));\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20px; 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: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; 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 10px; transform-origin: 404px 10px; 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 0px; tab-size: 4; transform-origin: 0px 0px; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e  \u0026gt;\u0026gt; lcmSum(20)\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20px; 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: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; 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 10px; transform-origin: 404px 10px; 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 0px; tab-size: 4; transform-origin: 0px 0px; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e  ans =\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20px; 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: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; 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 10px; transform-origin: 404px 10px; 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 0px; tab-size: 4; transform-origin: 0px 0px; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e        2320\u003c/span\u003e\u003c/span\u003e\u003c/div\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: 10px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 10px; perspective-origin: 384px 21px; text-align: left; transform-origin: 384px 21px; 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: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eSince the sum grows very fast, please present your answer as a character string array and please limit the \u003c/span\u003e\u003c/span\u003e\u003ca target='_blank' href = \"https://www.mathworks.com/matlabcentral/content/cody/about.html\"\u003e\u003cspan style=\"\"\u003e\u003cspan style=\"font-weight: 700; text-decoration-line: underline; \"\u003ecody program size\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: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e of the function to \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: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"font-weight: 700; text-decoration-line: underline; \"\u003e150\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: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e. \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function s = lcmSum(n)\r\n    s = num2str(sum(lcm(n,1:n)));\r\nend","test_suite":"%%\r\nn = 1:20;\r\ns = arrayfun(@(i) str2num(lcmSum(i)),n)\r\ns_correct = [1 4 12 24 55 66 154 176 279 320 616 468 1027 910 1110 1376 2329 1656 3268 2320];\r\nassert(isequal(s,s_correct))\r\n%%\r\nn = [50 500 5000];\r\ns = arrayfun(@(i) str2num(lcmSum(i)),n);\r\ns_correct = [39100 35808000 34993510000];\r\nassert(isequal(s,s_correct))\r\n%%\r\nn = [123 12345 123456 1234567 12345678 123456789];\r\ns = arrayfun(@(i) lcmSum(i),n,'uni',0);\r\ns_correct = {'706512' '613833706425' '487134624293760' '933390306503591194' '520297769997641090106' '708149874610092995986509'};\r\nassert(isequal(s,s_correct))\r\n%%\r\nn = 10.^(0:10);\r\ns = cellfun(@(x) [length(find(x-'0')) length(x) sum(x)],arrayfun(@(i) lcmSum(i),n,'uni',0),'uni',0);\r\ns_correct = {[1 1 49] [2 3 149] [4 6 310] [6 9 466] [7 12 608] [10 15 763] [12 18 922] [14 21 1085] [13 24 1234] [16 27 1387] [19 30 1535]};\r\nassert(isequal(s,s_correct))\r\n%%\r\nn = 100000001:100010000;\r\ns = sum(cellfun(@(s) sum(s),arrayfun(@(i) lcmSum(i),n,'uni',0)))\r\ns_correct = 12575131;\r\nassert(isequal(s,s_correct))\r\n%%\r\nfiletext = fileread('lcmSum.m');\r\nnot_allowed = contains(filetext, 'persistent') || contains(filetext, 'global') || contains(filetext, 'regexp') || contains(filetext, 'eval') || contains(filetext, 'assignin') || contains(filetext, 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w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eFor a given \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"false\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003en\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e, write the function \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"https://www.mathworks.com/help/matlab/ref/lcm.html\\\"\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003cw:u/\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003elcm\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eSum(n)\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e, defined as follows:\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\u003cw:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"true\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003e\\\\text{lcmSum}(n) = \\\\sum_{k=1}^{n}\\\\text{lcm}(n,k).\u003c/w:t\u003e\u003c/w:r\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\u003eFor example for \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"false\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003en=20\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\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=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[  \u003e\u003e lcmSum = @(n) sum(lcm(n,1:n));\\n  \u003e\u003e lcmSum(20)\\n  ans =\\n        2320]]\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\u003eSince the sum grows very fast, please present your answer as a character string array and please limit the \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink 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