numpymax Method (BaseArraycomplex, OutArrayInt64, Int32, Boolean)

public static RetArray<complex> max(
	BaseArray<complex> A,
	OutArray<long> I = null,
	int dim = -1,
	bool keepdim = true
)

Public Shared Function max ( 
	A As BaseArray(Of complex),
	Optional I As OutArray(Of Long) = Nothing,
	Optional dim As Integer = -1,
	Optional keepdim As Boolean = true
) As RetArray(Of complex)

Dim A As BaseArray(Of complex)
Dim I As OutArray(Of Long)
Dim dim As Integer
Dim keepdim As Boolean
Dim returnValue As RetArray(Of complex)

returnValue = numpy.max(A, I, dim, keepdim)

Parameters

A

Type: ILNumericsBaseArraycomplex
Input array.

I (Optional)

Type: ILNumericsOutArrayInt64
[Optional] Output: 0-based index values of the found elements along the working dimension. Default: (null) don't return the indices.

dim (Optional)

Type: SystemInt32
The index of the dimension to be reduced.

keepdim (Optional)

Type: SystemBoolean
[Optional] True: reduced singleton dimension is not removed from the output (default). False: the new singleton dimension is removed.

Return Value

Empty arrays are handled in the same way as other shapes: the dimension specified by dim is reduced to 1. If A.S[dim] == 0 the dims dimension length in the array returned will also be 0.

Scalar arrays: numpy scalars give a numpy scalar (0 dim) as output.

Special floating point values (for floating point element types): positive and negative infinity are handled in the regular way. NaN ('not a number') values are ignored. If all elements in a working dimension are NaN, NaN is returned as result in the corresponding output element.

If the optional output parameter I is not null on entry the function computes and returns the indices in A of the values returned. Thus, I has the same shape as the return array. If the storage of I on entry is sufficient (i.e.: large enough and not shared with other arrays) it will be directly used for storing the indices and I is reshaped as required. Otherwise, a new array is created and returned. In order to safe the index computation null can be provided as I which is the default.

If I is requested and multiple elements along the working dimension in A have the same maximum value it is undefined which element is 'picked' for the output. Hence, in this case the corresponding value in I is undefined and may point to the first or any other occurrence of the value returned from the working dimension.

[ILNumerics numpy Module]

Reference