ILNumerics Ultimate VS

MutableT1, LocalT, InT, OutT, RetT, StorageTItem Property (Int64, Int64, Int64, Int64, Int64, Int64)

ILNumerics Ultimate VS Documentation
ILNumerics - Technical Application Development
Retrieves the value(s) of the element(s) at the position specified by d0 ... d5 or sets them.

[ILNumerics Core Module]

Namespace:  ILNumerics.Core.Arrays
Assembly:  ILNumerics.Core (in ILNumerics.Core.dll) Version: (5.5.7503.3146)

public RetT this[
	long d0,
	long d1,
	long d2,
	long d3,
	long d4,
	long d5
] { get; set; }


Type: SystemInt64
Index into the first dimension.
Type: SystemInt64
Index into the second dimension.
Type: SystemInt64
Index into the third dimension.
Type: SystemInt64
Index into the fourth dimension.
Type: SystemInt64
Index into the fifths dimension.
Type: SystemInt64
Index into the sixths dimension or sequential index into remaining dimensions of the array.

Property Value

Type: RetT
Right side array with value(s) to be assigned to the element(s) addressed.

Return Value

Type: RetT
Element value(s) wrapped into a new array.

IndexOutOfRangeExceptionif the value of a given index exceeds the valid range.

This functions retrieves/ modifies an individual element or a subarray corresponding to d0 ... d5.

If this array has more dimensions than indices specified the size of the subarray returned / of the subarray addressed depends on the setting of ArrayStyle. For ILNumericsV4d5 is considered a sequential index into its own and into subsequent, merged dimensions. The array returned will be a scalar. This mode allows to expand / to remove parts of this array when using the set accessor.

For numpy all indices must fit into their dimensions. Any unspecified trailing dimensions are substituted with full and the array returned contains multiple elements from those dimensions. numpy does not allow to change the size of existing arrays.

This indexer is readonly on immutable types. It is optimized for efficient single element access by providing a distinct index parameter for each dimension of this array. Providing a number of indices matching the number of dimensions in this array is recommended for speed and for compatibility of the index access with both ArrayStyles.

In order to access elements based on their element type T1 directly (i.e.: without wrapping it into a new array) and as a faster alternative for scalar or mostly-scalar algorithms use one of the extension methods or similar overloads for concrete arrays.

This overload allows indexing into huge arrays and negative indices, addressing elements from the end of their respective dimension / merged dimensions.

[ILNumerics Core Module]

See Also


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