ILNumerics Ultimate VS

ILMathminall Method (ConcreteArrayUInt16, ArrayUInt16, InArrayUInt16, OutArrayUInt16, RetArrayUInt16, StorageUInt16, OutArrayInt64, StorageOrders, Boolean)

ILNumerics Ultimate VS Documentation
ILNumerics - Technical Application Development
Computes the (flattened, row-major) sequential index and value of the element with the minimum value in A.

[ILNumerics Computing Engine]

Namespace:  ILNumerics
Assembly:  ILNumerics.Computing (in ILNumerics.Computing.dll) Version: (5.5.7503.3146)

public static RetArray<ushort> minall(
	ConcreteArray<ushort, Array<ushort>, InArray<ushort>, OutArray<ushort>, RetArray<ushort>, Storage<ushort>> A,
	OutArray<long> index = null,
	StorageOrders order = StorageOrders.ColumnMajor,
	bool ignoreNaN = true


Type: ILNumerics.Core.ArraysConcreteArrayUInt16, ArrayUInt16, InArrayUInt16, OutArrayUInt16, RetArrayUInt16, StorageUInt16
Array to compute the minimum for. This is not altered.
index (Optional)
Type: ILNumericsOutArrayInt64
[Optional] index of the minimum value. Default: (null) the index is not returned.
order (Optional)
Type: ILNumericsStorageOrders
[Optional] iteration order for the flattened sequential indices. Default: ColumnMajor.
ignoreNaN (Optional)
Type: SystemBoolean
[Optional] determins how NaN values are handled for floating point element types. Ignored for integer elements. Defaul: (true) ignores NaNs.

Return Value

Type: RetArrayUInt16
Scalar array with the minimum value in A.

See min(BaseArrayUInt16, OutArrayInt64, Int32, Boolean) for getting the minimum values along a specific dimension.

The functions 'min','min','minall','minall' give all similar results between the framework APIs (ILNumericsV4/Matlab(R) / numpy) but show individual behavior regarding the handling of floating point NaN values and iteration order. The value of 'true' for ignoreNaN corresponds to the behavior of ILNumerics version 4/ Matlab(R). Only if all elements in A are NaN the value of the result will also be NaN. This is the default.

The value of 'false' for ignoreNaN gives the numpy behavior: NaN values take precedence over non-NaN values. If one element in the set of values is NaN the result will also be NaN. This is the default behavior for such functions defined as [numpy API] extension methods on the array classes.

[ILNumerics Computing Engine]

See Also


MathInternal.min(BaseArrayUInt16, OutArrayInt64, Int32, Boolean)