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# Module matrix_power

source code

Module for the calculation of the matrix power, for higher dimensional data.

 Functions

 create_index(data) Method to create the helper index matrix, to help figuring out the index to store in the data matrix. source code
numpy float array of rank [NE][NS][NM][NO][ND][X][X]
 matrix_power_strided_rank_NE_NS_NM_NO_ND_x_x(data, power) Calculate the exact matrix power by striding through higher dimensional data. source code

 stride_help_array_rank_NE_NS_NM_NO_ND_x(data) Method to stride through the data matrix, extracting the outer array with nr of elements as Column length. source code

 stride_help_element_rank_NE_NS_NM_NO_ND(data) Method to stride through the data matrix, extracting the outer element. source code

 stride_help_square_matrix_rank_NE_NS_NM_NO_ND_x_x(data) Helper function calculate the strides to go through the data matrix, extracting the outer Row X Col matrix. source code
 Variables
__package__ = `'lib.dispersion'`

Imports: as_strided, float64, int16, zeros, matrix_power

 Function Details

### matrix_power_strided_rank_NE_NS_NM_NO_ND_x_x(data, power)

source code

Calculate the exact matrix power by striding through higher dimensional data. This of dimension [NE][NS][NM][NO][ND][X][X].

Here X is the Row and Column length, of the outer square matrix.

Parameters:
• `data` (numpy float array of rank [NE][NS][NM][NO][ND][X][X]) - The square matrix to calculate the matrix exponential of.
• `power` (numpy int array of rank [NE][NS][NM][NO][ND]) - The matrix exponential power array, which hold the power integer to which to raise the outer matrix X,X to.
Returns: numpy float array of rank [NE][NS][NM][NO][ND][X][X]
The matrix pwer. This will have the same dimensionality as the data matrix.

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