The following constraints apply to the sizes of breakpoint data sets and table data associated with lookup table blocks:
The memory limitations of your system constrain the overall size of a lookup table.
Lookup tables must use consistent dimensions so that the overall size of the table data reflects the size of each breakpoint data set.
To illustrate the second constraint, consider the following vectors of input and output values that create the relationship in the plot.
Vector of input values: [-3 -2 -1 0 1 2 3] Vector of output values: [-3 -1 0 -1 0 1 3]
In this example, the input and output data are the same size (1-by-7), making the data consistently dimensioned for a 1-D lookup table.
The following input and output values define the 2-D lookup table that is graphically shown.
Row index input values: [1 2 3] Column index input values: [1 2 3 4] Table data: [11 12 13 14; 21 22 23 24; 31 32 33 34]
In this example, the sizes of the vectors representing the row and column indices are 1-by-3 and 1-by-4, respectively. Consequently, the output table must be of size 3-by-4 for consistent dimensions.
The first stage of a table lookup operation involves relating inputs to the breakpoint data sets. The search algorithm requires that input breakpoint sets be strictly monotonically increasing, that is, each successive element is greater than its preceding element. For example, the vector
A = [0 0.5 1 1.9 2.1 3]
is a valid breakpoint data set as each element is larger than its predecessors.
Although a breakpoint data set is strictly monotonic in
double format, it might not be so after conversion to a
fixed-point data type.
You can represent evenly spaced breakpoints in a data set by using one of these methods.
|Formulation||Example||When to Use This Formulation|
|The lookup table does not use
|The lookup table uses |
Because floating-point data types cannot precisely represent some numbers, the
second formulation works better for
single. For example, use
1 + (0.02 *
[0:450]) instead of
[1:0.02:10]. For a list of
lookup table blocks that support evenly spaced breakpoints, see Summary of Lookup Table Block Features.
Among other advantages, evenly spaced breakpoints can make the generated code division-free and reduce memory usage. For more information, see:
in the Simulink® documentation
Effects of Spacing on Speed, Error, and Memory Usage (Fixed-Point Designer)
Identify questionable fixed-point operations (Embedded Coder)
Do not use the MATLAB®
linspace function to define evenly spaced breakpoints.
Simulink uses a tighter tolerance to check whether a breakpoint set has
even spacing. If you use
linspace to define breakpoints for
your lookup table, Simulink considers the breakpoints to be unevenly spaced.