TENSOR Functions

Compute the generalized tensor product of two arrays.

enabled.

Usage

c = TENSOR_ADD( a, b )

c = TENSOR_DIV( a, b )

c = TENSOR_EQ( a, b )

c = TENSOR_EXP( a, b )

c = TENSOR_GE( a, b )

c = TENSOR_GT( a, b )

c = TENSOR_LE( a, b )

c = TENSOR_LT( a, b )

c = TENSOR_MAX( a, b )

c = TENSOR_MIN( a, b )

c = TENSOR_MOD( a, b )

c = TENSOR_MUL( a, b )

c = TENSOR_NE( a, b )

c = TENSOR_SUB( a, b )

Input Parameters

a—An array.

b—An array.

Keywords

None.

Returned Value

c—The generalized tensor product of a and b. For logical operators (EQ, NE, etc.), a byte type result is returned. Otherwise, the result type depends on the type(s) of the input parameters.

If a is an m dimensional array of dimension lengths a₁, ..., a_m and if b is an n dimensional array of dimension lengths b₁, ..., b_n then c is a m+n dimensional array with dimension lengths a₁, ..., a_m, b₁, ..., b_n.

Each element of c is computed as:

c(i₁ , . . i_m, j₁ , . . j_n) = a(i₁ , . . i_m) % b( j₁ , . . j_n)

where % symbolizes the operator associated with the selected function. PV-WAVE Operators lists the available PV‑WAVE operators.

PV-WAVE Operators
Function	PV-WAVE Operator
TENSOR_ADD	+
TENSOR_DIV	/
TENSOR_EQ	EQ
TENSOR_EXP	^
TENSOR_GE	GE
TENSOR_GT	GT
TENSOR_LE	LE
TENSOR_LT	LT
TENSOR_MAX	>
TENSOR_MIN	<
TENSOR_MOD	MOD
TENSOR_MUL	*
TENSOR_NE	NE
TENSOR_SUB	–

Discussion

The TENSOR functions are useful when it is necessary to apply a binary operator to all combinations of elements of one array with elements of a second array.

The combined dimensions of the two input parameters cannot exceed eight (8). If it does, an error is printed. If input parameters are not of the same type, one will be converted according to the rules used by PV‑WAVE binary operators.

Example

Refer to the Standard Library routine WHEREIN, where TENSOR_EQ is used to perform intersections and other related set operations.

Unix: <RW_DIR>/wave/lib/std/wherein.pro

Windows: <RW_DIR>\wave\lib\std\wherein.pro