src.array.sparse package

Submodules

src.array.sparse.csr module

class src.array.sparse.csr.CsrArray(values_like, index_like, /, *, shape, dtype=None, copy_values=False, copy_index=False)

Bases: Generic[Data], SparseArray[Data]

Parameters:

• values_like (Any)

• index_like (Sequence[Any])

• shape (Sequence[int])

• dtype (Optional[type])

• copy_values (bool)

• copy_index (bool)

static as_array(values_like, index_like, /, *, shape=None, dtype=None, copy_values=False, copy_index=False)

Parameters:

• values_like (Any)

• index_like (Sequence[Any])

• shape (Sequence[int] | None)

• dtype (type | None)

• copy_values (bool)

• copy_index (bool)

Return type:

CsrArray[Data]

as_csr(copy_values=True, copy_index=True)

Parameters:

• copy_values (bool)

• copy_index (bool)

Return type:

Self

as_nparray()

Return type:

ndarray

static broadcast_to(*, shape)

Parameters:

shape (int | Sequence[int])

Return type:

NoReturn

compress(*, keep, axis=0)

Parameters:

• keep (Any | Sequence[Any])

• axis (int | Sequence[int] | None)

Return type:

CsrArray[Data]

compress_axis(*, keep, axis=0)

Parameters:

• keep (Any)

• axis (int | None)

Return type:

CsrArray[Data]

static concat(arrs, /, *, axis=0)

Parameters:

• arrs (Sequence[CsrArray[Data]])

• axis (int)

Return type:

CsrArray[Data]

count_nonzero(*, axis=None, keepdims=False)

Parameters:

• axis (int | Sequence[int] | None)

• keepdims (bool)

Return type:

DenseArray[Data]

diagonal()

Return type:

BaseArray[Data]

static expand_dims(*, axis)

Parameters:

axis (int | Sequence[int])

Return type:

NoReturn

fill_diagonal(other)

Parameters:

other (Any)

Return type:

CsrArray[Data]

get_dense_index()

Return type:

tuple[Storage[Data], Storage[Data]]

property indices: Storage[Data]

property indptr: Storage[Data]

static mask_as_csr_index(mask_like)

Parameters:

mask_like (Any)

Return type:

tuple[Storage[Data], Storage[Data], tuple[int, int]]

max(*, axis=None, keepdims=False)

Parameters:

• axis (int | Sequence[int] | None)

• keepdims (bool)

Return type:

DenseArray[Data]

mean(*, axis=None, keepdims=False)

Parameters:

• axis (int | Sequence[int] | None)

• keepdims (bool)

Return type:

DenseArray[Data]

min(*, axis=None, keepdims=False)

Parameters:

• axis (int | Sequence[int] | None)

• keepdims (bool)

Return type:

DenseArray[Data]

property ncols: int

property nrows: int

static reshape(*, shape)

Parameters:

shape (int | Sequence[int])

Return type:

NoReturn

property shape: tuple[int, int]

static squeeze(*, axis)

Parameters:

axis (int | Sequence[int])

Return type:

NoReturn

static stack(arrs, /, *, axis=0)

Parameters:

• arrs (Sequence[CsrArray[Data]])

• axis (int)

Return type:

NoReturn

sum(*, axis=None, keepdims=False)

Parameters:

• axis (int | Sequence[int] | None)

• keepdims (bool)

Return type:

DenseArray[Data]

src.array.sparse.sparse module

class src.array.sparse.sparse.SparseArray(values_like, index_like, /, *, shape, dtype=None, copy_values=False, copy_index=False, **kwargs)

Bases: Generic[Data], BaseArray[Data]

Parameters:

• values_like (Any)

• index_like (Sequence[Any])

• shape (Sequence[int])

• dtype (Optional[type])

• copy_values (bool)

• copy_index (bool)

• kwargs (Any)

as_dense(fill_value)

Parameters:

fill_value (Any)

Return type:

DenseArray[Data]

as_type(*, dtype, copy_values=False, copy_index=False)

Parameters:

• dtype (type)

• copy_values (bool)

• copy_index (bool)

Return type:

Self

copy(copy_values=True, copy_index=True)

Parameters:

• copy_values (bool)

• copy_index (bool)

Return type:

Self

cos(copy_index=False)

Parameters:

• self (SparseArray[Data])

• copy_index (bool)

Return type:

SparseArray[Data]

exp(copy_index=False)

Parameters:

• self (SparseArray[Data])

• copy_index (bool)

Return type:

SparseArray[Data]

abstractmethod get_dense_index()

Return type:

tuple[Storage[Data], …]

icos()

Parameters:

self (SparseArray[Data])

Return type:

SparseArray[Data]

iexp()

Parameters:

self (SparseArray[Data])

Return type:

SparseArray[Data]

ilog()

Parameters:

self (SparseArray[Data])

Return type:

SparseArray[Data]

property index: tuple[Storage[Data], ...]

isin()

Parameters:

self (SparseArray[Data])

Return type:

SparseArray[Data]

isqrt()

Parameters:

self (SparseArray[Data])

Return type:

SparseArray[Data]

log(copy_index=False)

Parameters:

• self (SparseArray[Data])

• copy_index (bool)

Return type:

SparseArray[Data]

property shape: tuple[int, ...]

sin(copy_index=False)

Parameters:

• self (SparseArray[Data])

• copy_index (bool)

Return type:

SparseArray[Data]

property sparsity: float

sqrt(copy_index=False)

Parameters:

• self (SparseArray[Data])

• copy_index (bool)

Return type:

SparseArray[Data]

Module contents

class src.array.sparse.CsrArray(values_like, index_like, /, *, shape, dtype=None, copy_values=False, copy_index=False)

Bases: Generic[Data], SparseArray[Data]

Parameters:

• values_like (Any)

• index_like (Sequence[Any])

• shape (Sequence[int])

• dtype (Optional[type])

• copy_values (bool)

• copy_index (bool)

static as_array(values_like, index_like, /, *, shape=None, dtype=None, copy_values=False, copy_index=False)

Parameters:

• values_like (Any)

• index_like (Sequence[Any])

• shape (Sequence[int] | None)

• dtype (type | None)

• copy_values (bool)

• copy_index (bool)

Return type:

CsrArray[Data]

as_csr(copy_values=True, copy_index=True)

Parameters:

• copy_values (bool)

• copy_index (bool)

Return type:

Self

as_nparray()

Return type:

ndarray

static broadcast_to(*, shape)

Parameters:

shape (int | Sequence[int])

Return type:

NoReturn

compress(*, keep, axis=0)

Parameters:

• keep (Any | Sequence[Any])

• axis (int | Sequence[int] | None)

Return type:

CsrArray[Data]

compress_axis(*, keep, axis=0)

Parameters:

• keep (Any)

• axis (int | None)

Return type:

CsrArray[Data]

static concat(arrs, /, *, axis=0)

Parameters:

• arrs (Sequence[CsrArray[Data]])

• axis (int)

Return type:

CsrArray[Data]

count_nonzero(*, axis=None, keepdims=False)

Parameters:

• axis (int | Sequence[int] | None)

• keepdims (bool)

Return type:

DenseArray[Data]

diagonal()

Return type:

BaseArray[Data]

static expand_dims(*, axis)

Parameters:

axis (int | Sequence[int])

Return type:

NoReturn

fill_diagonal(other)

Parameters:

other (Any)

Return type:

CsrArray[Data]

get_dense_index()

Return type:

tuple[Storage[Data], Storage[Data]]

property indices: Storage[Data]

property indptr: Storage[Data]

static mask_as_csr_index(mask_like)

Parameters:

mask_like (Any)

Return type:

tuple[Storage[Data], Storage[Data], tuple[int, int]]

max(*, axis=None, keepdims=False)

Parameters:

• axis (int | Sequence[int] | None)

• keepdims (bool)

Return type:

DenseArray[Data]

mean(*, axis=None, keepdims=False)

Parameters:

• axis (int | Sequence[int] | None)

• keepdims (bool)

Return type:

DenseArray[Data]

min(*, axis=None, keepdims=False)

Parameters:

• axis (int | Sequence[int] | None)

• keepdims (bool)

Return type:

DenseArray[Data]

property ncols: int

property nrows: int

static reshape(*, shape)

Parameters:

shape (int | Sequence[int])

Return type:

NoReturn

property shape: tuple[int, int]

static squeeze(*, axis)

Parameters:

axis (int | Sequence[int])

Return type:

NoReturn

static stack(arrs, /, *, axis=0)

Parameters:

• arrs (Sequence[CsrArray[Data]])

• axis (int)

Return type:

NoReturn

sum(*, axis=None, keepdims=False)

Parameters:

• axis (int | Sequence[int] | None)

• keepdims (bool)

Return type:

DenseArray[Data]

class src.array.sparse.SparseArray(values_like, index_like, /, *, shape, dtype=None, copy_values=False, copy_index=False, **kwargs)

Bases: Generic[Data], BaseArray[Data]

Parameters:

• values_like (Any)

• index_like (Sequence[Any])

• shape (Sequence[int])

• dtype (Optional[type])

• copy_values (bool)

• copy_index (bool)

• kwargs (Any)

as_dense(fill_value)

Parameters:

fill_value (Any)

Return type:

DenseArray[Data]

as_type(*, dtype, copy_values=False, copy_index=False)

Parameters:

• dtype (type)

• copy_values (bool)

• copy_index (bool)

Return type:

Self

copy(copy_values=True, copy_index=True)

Parameters:

• copy_values (bool)

• copy_index (bool)

Return type:

Self

cos(copy_index=False)

Parameters:

• self (SparseArray[Data])

• copy_index (bool)

Return type:

SparseArray[Data]

exp(copy_index=False)

Parameters:

• self (SparseArray[Data])

• copy_index (bool)

Return type:

SparseArray[Data]

abstractmethod get_dense_index()

Return type:

tuple[Storage[Data], …]

icos()

Parameters:

self (SparseArray[Data])

Return type:

SparseArray[Data]

iexp()

Parameters:

self (SparseArray[Data])

Return type:

SparseArray[Data]

ilog()

Parameters:

self (SparseArray[Data])

Return type:

SparseArray[Data]

property index: tuple[Storage[Data], ...]

isin()

Parameters:

self (SparseArray[Data])

Return type:

SparseArray[Data]

isqrt()

Parameters:

self (SparseArray[Data])

Return type:

SparseArray[Data]

log(copy_index=False)

Parameters:

• self (SparseArray[Data])

• copy_index (bool)

Return type:

SparseArray[Data]

property shape: tuple[int, ...]

sin(copy_index=False)

Parameters:

• self (SparseArray[Data])

• copy_index (bool)

Return type:

SparseArray[Data]

property sparsity: float

sqrt(copy_index=False)

Parameters:

• self (SparseArray[Data])

• copy_index (bool)

Return type:

SparseArray[Data]