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| R2012a Documentation → Model-Based Calibration Toolbox | |
Learn more about Model-Based Calibration Toolbox |
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| R2012a Documentation → Model-Based Calibration Toolbox | |
Learn more about Model-Based Calibration Toolbox |
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| Contents | Index |
Y = gridEvaluate(optimstore, X) Y = gridEvaluate(optimstore, X, objconname) Y = gridEvaluate(optimstore, X, objconname, datasetname) Y = gridEvaluate(optimstore, X, objconname, datasetname, rowind)
A method of cgoptimstore.
Y = gridEvaluate(optimstore, X) evaluates all the objectives and constraints at the points X for the current run. This call produces identical results to the equivalent call to cgoptimstore/evaluate.
Y = gridEvaluate(optimstore, X, objconname) evaluates the objectives/constraints specified in the cell array objconname as described above.
Y = gridEvaluate(optimstore, X, objconname, datasetname) evaluates all the objectives and constraints at all combinations of the points in datasetname with X. The return matrix, Y, is of size SIZE(X,1)-by-(NOBJ+NCON)-by-NPTS, where NOBJ is the number of objectives, NCON is the number of constraints and NPTS is the number of rows in P. Further, Y(I, J, K) is the value of the J-th objective/constraint at X(I, :) and P(K, :). Y is scaled on [-1 1].
Objectives : O1, O2
Constraints : C1, C2
Primary data set:
| A | B |
|---|---|
4 | 5 |
1 | 3 |
Free variables:
| X1 | X2 | X3 |
|---|---|---|
2 | 4 | 8 |
1 | 9 | 3 |
6 | 2 | 7 |
X
In this case, the following command
Y = gridEvaluate(optimstore, X)
evaluates objectives and constraints at the following points:
| A | B | X1 | X2 | X3 |
|---|---|---|---|---|
4 | 5 | 2 | 4 | 8 |
4 | 5 | 1 | 9 | 3 |
4 | 5 | 6 | 2 | 7 |
1 | 3 | 2 | 4 | 8 |
1 | 3 | 1 | 9 | 3 |
1 | 3 | 6 | 2 | 7 |
Y is a 3-by-4-by-2 matrix where
Y(:, 1, 1) = Values of 01 at A = 4, B = 5
Y(:, 2, 1) = Values of 02 at A = 4, B = 5
Y(:, 3, 1) = Values of C1 at A = 4, B = 5
Y(:, 4, 1) = Values of C2 at A = 4, B = 5
Y(:, 1, 2) = Values of 01 at A = 1, B = 3
Y(:, 2, 2) = Values of 02 at A = 1, B = 3
Y(:, 3, 2) = Values of C1 at A = 1, B = 3
Y(:, 4, 2) = Values of C2 at A = 1, B = 3
Y = gridEvaluate(optimstore, X, objconname, datasetname, rowind)
evaluates the specified objectives/constraints at the points of datasetname given by rowind as described above. Y is a length(rowind) by length(objconname) by npts matrix.
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