Documentation |
Return value based on interpolating set of data points
tablelookup(x1d, x2d, yd, x1, x2, interpolation =
linear|cubic|spline, extrapolation = linear|nearest)
Use the tablelookup function in the equations section to compute an output value by interpolating the input value against a set of data points. This functionality is similar to that of the Simulink^{®} and Simscape™ Lookup Table blocks. It allows you to incorporate table-driven modeling directly in your custom block, without the need of connecting an external Lookup Table block to your model.
The tablelookup function supports one-dimensional and two-dimensional lookup tables. The full syntax is:
tablelookup(x1d, x2d, yd, x1, x2, interpolation = linear|cubic|spline, extrapolation = linear|nearest)
x1d | Data set of input values along the first direction, specified as a one-dimensional array. The values must be strictly monotonic, either increasing or decreasing. This is a required argument. |
x2d | Data set of input values along the second direction, specified as a one-dimensional array. The values must be strictly monotonic, either increasing or decreasing. This argument is used only for the two-dimensional table lookup. |
yd | Data set of output values for the table lookup. This is a required
argument. For one-dimensional table lookup, yd must be a one-dimensional array of the same size as x1d. For two-dimensional table lookup, yd must be a matrix, with the size matching the dimensions defined by the input data sets. For example, if x1d is a 1-by-m array, and x2d is a 1-by-n array, then yd must be an m-by-n matrix. |
x1 | The input value along the first direction. Its units must be commensurate with the units of x1d. This is a required argument. |
x2 | The input value along the second direction. Its units must be commensurate with the units of x2d. This argument is used only for the two-dimensional table lookup. |
interpolation = linear|cubic|spline | Optional argument that specifies the approximation method for calculating the output value when the input value is inside the range specified in the lookup table. The default is interpolation = linear. |
extrapolation = linear|nearest | Optional argument that specifies the approximation method for calculating the output value when the input value is outside the range specified in the lookup table. The default is extrapolation = linear. |
The interpolation argument values are:
linear — For one-dimensional table lookup, uses a linear function. For two-dimensional table lookup, uses a bilinear interpolation algorithm, which is an extension of linear interpolation for functions in two variables. The method performs linear interpolation first in x-direction and then in y-direction.
cubic — For one-dimensional table lookup, uses the Piecewise Cubic Hermite Interpolation Polinomial (PCHIP). For more information, see the pchip MATLAB^{®} function. For two-dimensional table lookup, uses the bicubic interpolation algorithm described in [1].
spline — For one-dimensional table lookup, uses the cubic spline interpolation algorithm described in [1]. For two-dimensional table lookup, uses the bicubic spline interpolation algorithm described in [1].
The extrapolation argument values are:
linear— Extrapolates using the linear method, based on the last two output values at the appropriate end of the range. That is, the function uses the first and second specified output values if the input value is below the specified range, and the two last specified output values if the input value is above the specified range.
nearest — Uses the last specified output value at the appropriate end of the range. That is, the function uses the last specified output value for all input values greater than the last specified input argument, and the first specified output value for all input values less than the first specified input argument.
The function returns an output value, in the units specified for yd, by looking up or estimating table values based on the input values:
When inputs x1 and x2... | The tablelookup function... |
---|---|
Match the values of indices in the input data sets, x1d and x2d | Outputs the corresponding table value, yd |
Do not match the values of indices in the input data sets, but are within range | Interpolates appropriate table values, using the method specified as the interpolation argument value |
Do not match the values of indices in the input data sets, and are out of range | Extrapolates the output value, using the method specified as the extrapolation argument value |
The following rules apply to data sets x1d, x2d, and yd:
For one-dimensional table lookup, x1d and yd must be one-dimensional arrays of the same size.
For two-dimensional table lookup, x1d and x2d must be one-dimensional arrays, and yd must be a matrix, with the size matching the dimensions defined by the input data sets. For example, if x1d is a 1-by-m array, and x2d is a 1-by-n array, then yd must be an m-by-n matrix.
The x1d and x2d values must be strictly monotonic, either increasing or decreasing.
For cubic or spline interpolation, each data set must contain at least three values. For linear interpolation, two values are sufficient.
If these rules are violated by... | You get an error... |
---|---|
The block author, in the component Simscape file | At build time, when running ssc_build to convert the component to a custom block |
The block user, when entering values in the block dialog box | At simulation time, when attempting to simulate the model containing the custom block |
This example implements a one-dimensional lookup table with linear interpolation and extrapolation.
component tlu_1d_linear inputs u = 0; end outputs y = 0; end parameters (Size=variable) xd = [1 2 3 4]; yd = [1 2 3 4]; end equations y == tablelookup(xd, yd, u); end end
xd and yd are declared as variable-size parameters. This enables the block users to provide their own data sets when the component is converted to a custom block. For more information, see Using Lookup Tables in Equations.
The xd values must be strictly monotonic, either increasing or decreasing. yd must have the same size as xd.
This example implements a two-dimensional lookup table with specific interpolation and extrapolation methods.
component tlu_2d inputs u1 = 0; u2 = 0; end outputs y = 0; end parameters (Size=variable) x1d = [1 2 3 4]; x2d = [1 2 3]; yd = [1 2 3; 3 4 5; 5 6 7; 7 8 9]; end equations y == tablelookup(x1d, x2d, yd, u1, u2, interpolation=spline, extrapolation=nearest); end end
x1d, x2d, and yd are declared as variable-size parameters. The x1d and x2d vector values must be strictly monotonic, either increasing or decreasing. For spline interpolation, each vector must have at least three values. The size of the yd matrix must match the dimensions of the x1d and x2d vectors.
The interpolation uses the bicubic spline algorithm. The extrapolation uses the nearest value of yd for out-of-range u1 and u2 values.
This example implements a one-dimensional lookup table with units, to map temperature to pressure, with linear interpolation and extrapolation.
component TtoP inputs u = {0, 'K'}; % temperature end outputs y = {0, 'Pa'}; % pressure end parameters (Size=variable) xd = {[100 200 300 400] 'K'}; yd = {[1e5 2e5 3e5 4e5] 'Pa'}; end equations y == tablelookup(xd, yd, u); end end
xd and yd are declared as variable-size parameters with units. This enables the block users to provide their own data sets when the component is converted to a custom block, and also to select commensurate units from the drop-downs in the custom block dialog box. For more information, see Using Lookup Tables in Equations.
The xd values must be strictly monotonic, either increasing or decreasing. yd must have the same size as xd.