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sax.nn.utils module

sax.nn.utils module#

Sax Neural Network Default Utilities

cartesian_product(*arrays)[source]#

calculate the n-dimensional cartesian product of an arbitrary number of arrays

Parameters:

arrays (ComplexArrayND) –

Return type:

ComplexArrayND

denormalize(x, mean=0.0, std=1.0)[source]#

denormalize an array with a given mean and standard deviation

Parameters:

  • x (ComplexArrayND) –

  • mean (float) –

  • std (float) –

Return type:

ComplexArrayND

class norm(mean, std)#

Bases: tuple

mean#

Alias for field number 0

std#

Alias for field number 1

get_normalization(x)[source]#

Get mean and standard deviation for a given array

Parameters:

x (ComplexArrayND) –

get_df_columns(df, *names)[source]#

Get certain columns from a pandas DataFrame as jax.numpy arrays

Parameters:

  • df (DataFrame) –

  • names (str) –

Return type:

Tuple[ComplexArrayND, …]

normalize(x, mean=0.0, std=1.0)[source]#

normalize an array with a given mean and standard deviation

Parameters:

  • x (ComplexArrayND) –

  • mean (float) –

  • std (float) –

Return type:

ComplexArrayND

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