Find All Minima nD (Not in Base Package)

Determines the minima of an n-dimension function in a given n-dimension interval.

accuracy controls the accuracy of the minima. The default is 1E - 8.
When algorithm is 0 it represents the Conjugate Gradient method. When algorithm is 1, it represents the Downhill Simplex method. The default is 0.
gradient method A value of 0 represents the Fletcher Reeves method, a value of 1 represents the Polak Ribiere method. The default is 0.
line minimum A value of 0 represents the line optimization without derivatives. A line minimum value of 1 represents the line optimization with derivatives. The default is 0.
number of trials is the number of the randomly chosen start points of the optimization process. These points belong to the interval (start,end). The default is 5.
Start is the start point in n D.
End is the end point in n-dimension.
X is an array of strings describing the n variables.
F(X) is a string describing the n-dimension function of X.
X Values is a matrix describing all determined local minima.
F Values is the function values at the points X Values.
ticks is the time in milliseconds for the whole calculation.
error returns any error or warning condition from the VI.