Tensor¶

class libadcc.Tensor¶

Bases: pybind11_builtins.pybind11_object

Class representing the Tensor objects used for computations in adcc

Attributes Summary

`mutable`
`ndim`
`shape`
`size`

Methods Summary

`add_linear_combination`(self, arg0, arg1)	Add a linear combination of tensors to this tensor
`antisymmetrise_to`(self, arg0, arg1)
`copy`(self)	Returns a deep copy of the tensor.
`copy_to`(self, arg0)	Writes a deep copy of the tensor to another tensor
`describe_symmetry`(self)	Return a string providing a hopefully discriptive rerpesentation of the symmetry information stored inside the tensor.
`dot`(args, *kwargs)	Overloaded function.
`empty_like`(self)
`is_allowed`(self, arg0)	Is a particular index allowed by symmetry
`nosym_like`(self)
`ones_like`(self)
`select_n_absmax`(self, arg0)	Select the n absolute maximal elements.
`select_n_absmin`(self, arg0)	Select the n absolute minimal elements.
`select_n_max`(self, arg0)	Select the n maximal elements.
`select_n_min`(self, arg0)	Select the n minimal elements.
`set_from_ndarray`(args, *kwargs)	Overloaded function.
`set_immutable`(self)	Set the tensor as immutable, allowing some optimisations to be performed.
`set_mask`(self, arg0, arg1)	Set all elements corresponding to an index mask, which is given by a string eg.
`set_random`(self)	Set all tensor elements to random data, adhering to the internal symmetry.
`symmetrise_to`(self, arg0, arg1)
`to_ndarray`(self)	Export the tensor data to a standard np::ndarray by making a copy.
`transpose`(args, *kwargs)	Overloaded function.
`zeros_like`(self)

Attributes Documentation

mutable¶

ndim¶

shape¶

size¶

Methods Documentation

add_linear_combination(self: libadcc.Tensor, arg0: numpy.ndarray[float64], arg1: list) → libadcc.Tensor¶: Add a linear combination of tensors to this tensor

antisymmetrise_to(self: libadcc.Tensor, arg0: libadcc.Tensor, arg1: list) → None¶

copy(self: libadcc.Tensor) → libadcc.Tensor¶: Returns a deep copy of the tensor.

copy_to(self: libadcc.Tensor, arg0: libadcc.Tensor) → None¶: Writes a deep copy of the tensor to another tensor

describe_symmetry(self: libadcc.Tensor) → str¶: Return a string providing a hopefully discriptive rerpesentation of the symmetry information stored inside the tensor.

dot(*args, **kwargs)¶

Overloaded function.

dot(self: libadcc.Tensor, arg0: libadcc.Tensor) -> float
dot(self: libadcc.Tensor, arg0: list) -> numpy.ndarray[float64]

empty_like(self: libadcc.Tensor) → libadcc.Tensor¶

is_allowed(self: libadcc.Tensor, arg0: tuple) → bool¶: Is a particular index allowed by symmetry

nosym_like(self: libadcc.Tensor) → libadcc.Tensor¶

ones_like(self: libadcc.Tensor) → libadcc.Tensor¶

select_n_absmax(self: libadcc.Tensor, arg0: int) → list¶: Select the n absolute maximal elements.

select_n_absmin(self: libadcc.Tensor, arg0: int) → list¶: Select the n absolute minimal elements.

select_n_max(self: libadcc.Tensor, arg0: int) → list¶: Select the n maximal elements.

select_n_min(self: libadcc.Tensor, arg0: int) → list¶: Select the n minimal elements.

set_from_ndarray(*args, **kwargs)¶

Overloaded function.

set_from_ndarray(self: libadcc.Tensor, arg0: array) -> None

Set all tensor elements from a standard np::ndarray by making a copy. Provide an optional tolerance argument to increase the tolerance for the check for symmetry consistency.

set_from_ndarray(self: libadcc.Tensor, arg0: numpy.ndarray[float64], arg1: float) -> None

Set all tensor elements from a standard np::ndarray by making a copy. Provide an optional tolerance argument to increase the tolerance for the check for symmetry consistency.

set_immutable(self: libadcc.Tensor) → None¶: Set the tensor as immutable, allowing some optimisations to be performed.

set_mask(self: libadcc.Tensor, arg0: str, arg1: float) → None¶: Set all elements corresponding to an index mask, which is given by a string eg. ‘iijkli’ sets elements T_{iijkli}

set_random(self: libadcc.Tensor) → None¶: Set all tensor elements to random data, adhering to the internal symmetry.

symmetrise_to(self: libadcc.Tensor, arg0: libadcc.Tensor, arg1: list) → None¶

to_ndarray(self: libadcc.Tensor) → numpy.ndarray[float64]¶: Export the tensor data to a standard np::ndarray by making a copy.

transpose(*args, **kwargs)¶

Overloaded function.

transpose(self: libadcc.Tensor) -> libadcc.Tensor
transpose(self: libadcc.Tensor, arg0: tuple) -> libadcc.Tensor

zeros_like(self: libadcc.Tensor) → libadcc.Tensor¶