Matrix Update (General » Rank-1) (G Dataflow)

M-element vector.

This input accepts the following data types:

• 1D array of double-precision, floating-point numbers
• 1D array of complex double-precision, floating-point numbers

N-element vector.

This input accepts the following data types:

• 1D array of double-precision, floating-point numbers
• 1D array of complex double-precision, floating-point numbers

General matrix.

A must have dimensions greater than or equal to M × N. If A is an empty matrix, this node initializes A to be an M x N matrix with all elements set to 0.

This input accepts the following data types:

• 2D array of double-precision, floating-point numbers
• 2D array of complex double-precision, floating-point numbers

Error conditions that occur before this node runs.

The node responds to this input according to standard error behavior.

Standard Error Behavior

Many nodes provide an error in input and an error out output so that the node can respond to and communicate errors that occur while code is running. The value of error in specifies whether an error occurred before the node runs. Most nodes respond to values of error in in a standard, predictable way.

error in does not contain an error	error in contains an error
If no error occurred before the node runs, the node begins execution normally. If no error occurs while the node runs, it returns no error. If an error does occur while the node runs, it returns that error information as error out.	If an error occurred before the node runs, the node does not execute. Instead, it returns the error in value as error out.

Default: No error

Scalar that scales x * y ^T, where y^T represents y transposed.

This input accepts the following data types:

• Double-precision, floating-point numbers
• Complex double-precision, floating-point numbers

Default: The default value is 1 if alpha is a double-precision, floating-point number. The default value is 1+0i if alpha is a complex double-precision, floating-point number.

Matrix of the same dimensions as A.

For elements in the first M rows and N columns, dger returns the results of alpha * x * y^T + A, where y^T represents y transposed. For any remaining elements, dger returns the value of the element in A with the same index.

This output is available when you wire a 1D array of double-precision, floating-point numbers to x or y, or a 2D array of double-precision, floating-point numbers to A.

Matrix of the same dimensions as A.

For elements in the first M rows and N columns, zgeru returns the results of alpha * x * y^T + A, where y^T represents y transposed. For any remaining elements, zgeru returns the value of the element in A with the same index.

This output is available when you wire a 1D array of complex double-precision, floating-point numbers to x or y, or a 2D array of complex double-precision, floating-point numbers to A.

Error information.

The node produces this output according to standard error behavior.

Standard Error Behavior

Many nodes provide an error in input and an error out output so that the node can respond to and communicate errors that occur while code is running. The value of error in specifies whether an error occurred before the node runs. Most nodes respond to values of error in in a standard, predictable way.

error in does not contain an error	error in contains an error
If no error occurred before the node runs, the node begins execution normally. If no error occurs while the node runs, it returns no error. If an error does occur while the node runs, it returns that error information as error out.	If an error occurred before the node runs, the node does not execute. Instead, it returns the error in value as error out.