siml.siml_variables.array_variables package

Submodules

siml.siml_variables.array_variables.interface_wrapper module

class siml.siml_variables.array_variables.interface_wrapper.ISimlArray(data: T)

Bases: object

abstract apply(function: Callable[[T], T], componentwise: bool, *, skip_nan: bool = False, use_diagonal: bool = False, **kwards) → T

Apply user defined function

Parameters:

• function (Callable[[T], T]) – function to apply

• componentwise (bool) – If True, fucnction is applied by component wise way

• skip_nan (bool, optional) –

  If True, np.nan value is ignored. This option is valid

  only when data is np.ndarray. By default False

• use_diagonal (bool, optional) –

  If True, only diagonal values are used. This option is valid

  only when data is sparse array. By default False

Returns:

T

Return type:

Same type of instance caraible

abstract reshape(componentwise: bool, *, skip_nan: bool = False, use_diagonal: bool = False, **kwrds) → T

abstract property shape: tuple[int]

siml.siml_variables.array_variables.ndarray_wrapper module

class siml.siml_variables.array_variables.ndarray_wrapper.NdArrayWrapper(data: ndarray)

Bases: ISimlArray

apply(function: Callable[[ndarray], ndarray], componentwise: bool, *, skip_nan: bool = False, **kwards) → ndarray

Apply user defined function

Parameters:

• function (Callable[[T], T]) – function to apply

• componentwise (bool) – If True, fucnction is applied by component wise way

• skip_nan (bool, optional) –

  If True, np.nan value is ignored. This option is valid

  only when data is np.ndarray. By default False

• use_diagonal (bool, optional) –

  If True, only diagonal values are used. This option is valid

  only when data is sparse array. By default False

Returns:

T

Return type:

Same type of instance caraible

reshape(componentwise: bool, *, skip_nan: bool = False, **kwards) → ndarray

property shape: tuple[int]

siml.siml_variables.array_variables.sparce_array_wrapper module

class siml.siml_variables.array_variables.sparce_array_wrapper.SparseArrayWrapper(data: coo_matrix | csr_matrix | csc_matrix)

Bases: ISimlArray

apply(apply_function: Callable[[coo_matrix | csr_matrix | csc_matrix], coo_matrix | csr_matrix | csc_matrix], componentwise: bool, *, use_diagonal: bool = False, **kwards) → coo_matrix | csr_matrix | csc_matrix

Apply user defined function

Parameters:

• function (Callable[[T], T]) – function to apply

• componentwise (bool) – If True, fucnction is applied by component wise way

• skip_nan (bool, optional) –

  If True, np.nan value is ignored. This option is valid

  only when data is np.ndarray. By default False

• use_diagonal (bool, optional) –

  If True, only diagonal values are used. This option is valid

  only when data is sparse array. By default False

Returns:

T

Return type:

Same type of instance caraible

reshape(componentwise: bool, *, use_diagonal: bool = False, **kwards) → coo_matrix | csr_matrix | csc_matrix

property shape: tuple[int]

Module contents

siml.siml_variables.array_variables.create_siml_arrray(data: ndarray | coo_matrix | csr_matrix | csc_matrix) → ISimlArray