dolfinx.cpp.la

Linear algebra module

Classes

BlockMode(*values)
InsertMode(*values)
MatrixCSR_complex128(self, p[, block_mode])
MatrixCSR_complex64(self, p[, block_mode])
MatrixCSR_float32(self, p[, block_mode])
MatrixCSR_float64(self, p[, block_mode])
MatrixCSR_int32(self, p[, block_mode])
MatrixCSR_int64(self, p[, block_mode])
MatrixCSR_int8(self, p[, block_mode])
Norm(*values)
SparsityPattern()
SuperLUDistMatrix_complex128(self, A)
SuperLUDistMatrix_float32(self, A)
SuperLUDistMatrix_float64(self, A)
SuperLUDistSolver_complex128(self, A)
SuperLUDistSolver_float32(self, A)
SuperLUDistSolver_float64(self, A)
Vector_complex128()
Vector_complex64()
Vector_float32()
Vector_float64()
Vector_int32()
Vector_int64()
Vector_int8()

class dolfinx.cpp.la.BlockMode(*values)

Bases: Enum

compact = 0

expanded = 1

class dolfinx.cpp.la.InsertMode(*values)

Bases: Enum

add = 0

insert = 1

class dolfinx.cpp.la.MatrixCSR_complex128(self, p: dolfinx.cpp.la.SparsityPattern, block_mode: dolfinx.cpp.la.BlockMode = BlockMode.compact)

Bases: object

add(self, arg0: ndarray[dtype=complex128, shape=(*), order='C', writable=False], arg1: ndarray[dtype=int32, shape=(*), order='C', writable=False], arg2: ndarray[dtype=int32, shape=(*), order='C', writable=False], arg3: int, /) → None

property bs

(self) -> list[int]

property data

(self) -> numpy.ndarray[dtype=complex128]

property dtype

(self) -> str

index_map(self, arg: int, /) → dolfinx.cpp.common.IndexMap

property indices

(self) -> numpy.ndarray[dtype=int32, writable=False]

property indptr

(self) -> numpy.ndarray[dtype=int64, writable=False]

mult(self, arg0: dolfinx.cpp.la.Vector_complex128, arg1: dolfinx.cpp.la.Vector_complex128, /) → None

mult(self, arg: dolfinx.cpp.la.MatrixCSR_complex128, /) → dolfinx.cpp.la.MatrixCSR_complex128

multT(self, arg0: dolfinx.cpp.la.Vector_complex128, arg1: dolfinx.cpp.la.Vector_complex128, /) → None

scatter_rev_begin(self) → None

scatter_rev_end(self) → None

scatter_reverse(self) → None

set(self, arg0: ndarray[dtype=complex128, shape=(*), order='C', writable=False], arg1: ndarray[dtype=int32, shape=(*), order='C', writable=False], arg2: ndarray[dtype=int32, shape=(*), order='C', writable=False], arg3: int, /) → None

squared_norm(self) → float

to_dense(self) → numpy.ndarray[dtype=complex128]

transpose(self) → dolfinx.cpp.la.MatrixCSR_complex128

class dolfinx.cpp.la.MatrixCSR_complex64(self, p: dolfinx.cpp.la.SparsityPattern, block_mode: dolfinx.cpp.la.BlockMode = BlockMode.compact)

Bases: object

add(self, arg0: ndarray[dtype=complex64, shape=(*), order='C', writable=False], arg1: ndarray[dtype=int32, shape=(*), order='C', writable=False], arg2: ndarray[dtype=int32, shape=(*), order='C', writable=False], arg3: int, /) → None

property bs

(self) -> list[int]

property data

(self) -> numpy.ndarray[dtype=complex64]

property dtype

(self) -> str

index_map(self, arg: int, /) → dolfinx.cpp.common.IndexMap

property indices

(self) -> numpy.ndarray[dtype=int32, writable=False]

property indptr

(self) -> numpy.ndarray[dtype=int64, writable=False]

mult(self, arg0: dolfinx.cpp.la.Vector_complex64, arg1: dolfinx.cpp.la.Vector_complex64, /) → None

mult(self, arg: dolfinx.cpp.la.MatrixCSR_complex64, /) → dolfinx.cpp.la.MatrixCSR_complex64

multT(self, arg0: dolfinx.cpp.la.Vector_complex64, arg1: dolfinx.cpp.la.Vector_complex64, /) → None

scatter_rev_begin(self) → None

scatter_rev_end(self) → None

scatter_reverse(self) → None

set(self, arg0: ndarray[dtype=complex64, shape=(*), order='C', writable=False], arg1: ndarray[dtype=int32, shape=(*), order='C', writable=False], arg2: ndarray[dtype=int32, shape=(*), order='C', writable=False], arg3: int, /) → None

squared_norm(self) → float

to_dense(self) → numpy.ndarray[dtype=complex64]

transpose(self) → dolfinx.cpp.la.MatrixCSR_complex64

class dolfinx.cpp.la.MatrixCSR_float32(self, p: dolfinx.cpp.la.SparsityPattern, block_mode: dolfinx.cpp.la.BlockMode = BlockMode.compact)

Bases: object

add(self, arg0: ndarray[dtype=float32, shape=(*), order='C', writable=False], arg1: ndarray[dtype=int32, shape=(*), order='C', writable=False], arg2: ndarray[dtype=int32, shape=(*), order='C', writable=False], arg3: int, /) → None

property bs

(self) -> list[int]

property data

(self) -> numpy.ndarray[dtype=float32]

property dtype

(self) -> str

index_map(self, arg: int, /) → dolfinx.cpp.common.IndexMap

property indices

(self) -> numpy.ndarray[dtype=int32, writable=False]

property indptr

(self) -> numpy.ndarray[dtype=int64, writable=False]

mult(self, arg0: dolfinx.cpp.la.Vector_float32, arg1: dolfinx.cpp.la.Vector_float32, /) → None

mult(self, arg: dolfinx.cpp.la.MatrixCSR_float32, /) → dolfinx.cpp.la.MatrixCSR_float32

multT(self, arg0: dolfinx.cpp.la.Vector_float32, arg1: dolfinx.cpp.la.Vector_float32, /) → None

scatter_rev_begin(self) → None

scatter_rev_end(self) → None

scatter_reverse(self) → None

set(self, arg0: ndarray[dtype=float32, shape=(*), order='C', writable=False], arg1: ndarray[dtype=int32, shape=(*), order='C', writable=False], arg2: ndarray[dtype=int32, shape=(*), order='C', writable=False], arg3: int, /) → None

squared_norm(self) → float

to_dense(self) → numpy.ndarray[dtype=float32]

transpose(self) → dolfinx.cpp.la.MatrixCSR_float32

class dolfinx.cpp.la.MatrixCSR_float64(self, p: dolfinx.cpp.la.SparsityPattern, block_mode: dolfinx.cpp.la.BlockMode = BlockMode.compact)

Bases: object

add(self, arg0: ndarray[dtype=float64, shape=(*), order='C', writable=False], arg1: ndarray[dtype=int32, shape=(*), order='C', writable=False], arg2: ndarray[dtype=int32, shape=(*), order='C', writable=False], arg3: int, /) → None

property bs

(self) -> list[int]

property data

(self) -> numpy.ndarray[dtype=float64]

property dtype

(self) -> str

index_map(self, arg: int, /) → dolfinx.cpp.common.IndexMap

property indices

(self) -> numpy.ndarray[dtype=int32, writable=False]

property indptr

(self) -> numpy.ndarray[dtype=int64, writable=False]

mult(self, arg0: dolfinx.cpp.la.Vector_float64, arg1: dolfinx.cpp.la.Vector_float64, /) → None

mult(self, arg: dolfinx.cpp.la.MatrixCSR_float64, /) → dolfinx.cpp.la.MatrixCSR_float64

multT(self, arg0: dolfinx.cpp.la.Vector_float64, arg1: dolfinx.cpp.la.Vector_float64, /) → None

scatter_rev_begin(self) → None

scatter_rev_end(self) → None

scatter_reverse(self) → None

set(self, arg0: ndarray[dtype=float64, shape=(*), order='C', writable=False], arg1: ndarray[dtype=int32, shape=(*), order='C', writable=False], arg2: ndarray[dtype=int32, shape=(*), order='C', writable=False], arg3: int, /) → None

squared_norm(self) → float

to_dense(self) → numpy.ndarray[dtype=float64]

transpose(self) → dolfinx.cpp.la.MatrixCSR_float64

class dolfinx.cpp.la.MatrixCSR_int32(self, p: dolfinx.cpp.la.SparsityPattern, block_mode: dolfinx.cpp.la.BlockMode = BlockMode.compact)

Bases: object

add(self, arg0: ndarray[dtype=int32, shape=(*), order='C', writable=False], arg1: ndarray[dtype=int32, shape=(*), order='C', writable=False], arg2: ndarray[dtype=int32, shape=(*), order='C', writable=False], arg3: int, /) → None

property bs

(self) -> list[int]

property data

(self) -> numpy.ndarray[dtype=int32]

property dtype

(self) -> str

index_map(self, arg: int, /) → dolfinx.cpp.common.IndexMap

property indices

(self) -> numpy.ndarray[dtype=int32, writable=False]

property indptr

(self) -> numpy.ndarray[dtype=int64, writable=False]

mult(self, arg0: dolfinx.cpp.la.Vector_int32, arg1: dolfinx.cpp.la.Vector_int32, /) → None

mult(self, arg: dolfinx.cpp.la.MatrixCSR_int32, /) → dolfinx.cpp.la.MatrixCSR_int32

multT(self, arg0: dolfinx.cpp.la.Vector_int32, arg1: dolfinx.cpp.la.Vector_int32, /) → None

scatter_rev_begin(self) → None

scatter_rev_end(self) → None

scatter_reverse(self) → None

set(self, arg0: ndarray[dtype=int32, shape=(*), order='C', writable=False], arg1: ndarray[dtype=int32, shape=(*), order='C', writable=False], arg2: ndarray[dtype=int32, shape=(*), order='C', writable=False], arg3: int, /) → None

squared_norm(self) → float

to_dense(self) → numpy.ndarray[dtype=int32]

transpose(self) → dolfinx.cpp.la.MatrixCSR_int32

class dolfinx.cpp.la.MatrixCSR_int64(self, p: dolfinx.cpp.la.SparsityPattern, block_mode: dolfinx.cpp.la.BlockMode = BlockMode.compact)

Bases: object

add(self, arg0: ndarray[dtype=int64, shape=(*), order='C', writable=False], arg1: ndarray[dtype=int32, shape=(*), order='C', writable=False], arg2: ndarray[dtype=int32, shape=(*), order='C', writable=False], arg3: int, /) → None

property bs

(self) -> list[int]

property data

(self) -> numpy.ndarray[dtype=int64]

property dtype

(self) -> str

index_map(self, arg: int, /) → dolfinx.cpp.common.IndexMap

property indices

(self) -> numpy.ndarray[dtype=int32, writable=False]

property indptr

(self) -> numpy.ndarray[dtype=int64, writable=False]

mult(self, arg0: dolfinx.cpp.la.Vector_int64, arg1: dolfinx.cpp.la.Vector_int64, /) → None

mult(self, arg: dolfinx.cpp.la.MatrixCSR_int64, /) → dolfinx.cpp.la.MatrixCSR_int64

multT(self, arg0: dolfinx.cpp.la.Vector_int64, arg1: dolfinx.cpp.la.Vector_int64, /) → None

scatter_rev_begin(self) → None

scatter_rev_end(self) → None

scatter_reverse(self) → None

set(self, arg0: ndarray[dtype=int64, shape=(*), order='C', writable=False], arg1: ndarray[dtype=int32, shape=(*), order='C', writable=False], arg2: ndarray[dtype=int32, shape=(*), order='C', writable=False], arg3: int, /) → None

squared_norm(self) → float

to_dense(self) → numpy.ndarray[dtype=int64]

transpose(self) → dolfinx.cpp.la.MatrixCSR_int64

class dolfinx.cpp.la.MatrixCSR_int8(self, p: dolfinx.cpp.la.SparsityPattern, block_mode: dolfinx.cpp.la.BlockMode = BlockMode.compact)

Bases: object

add(self, arg0: ndarray[dtype=int8, shape=(*), order='C', writable=False], arg1: ndarray[dtype=int32, shape=(*), order='C', writable=False], arg2: ndarray[dtype=int32, shape=(*), order='C', writable=False], arg3: int, /) → None

property bs

(self) -> list[int]

property data

(self) -> numpy.ndarray[dtype=int8]

property dtype

(self) -> str

index_map(self, arg: int, /) → dolfinx.cpp.common.IndexMap

property indices

(self) -> numpy.ndarray[dtype=int32, writable=False]

property indptr

(self) -> numpy.ndarray[dtype=int64, writable=False]

mult(self, arg0: dolfinx.cpp.la.Vector_int8, arg1: dolfinx.cpp.la.Vector_int8, /) → None

mult(self, arg: dolfinx.cpp.la.MatrixCSR_int8, /) → dolfinx.cpp.la.MatrixCSR_int8

multT(self, arg0: dolfinx.cpp.la.Vector_int8, arg1: dolfinx.cpp.la.Vector_int8, /) → None

scatter_rev_begin(self) → None

scatter_rev_end(self) → None

scatter_reverse(self) → None

set(self, arg0: ndarray[dtype=int8, shape=(*), order='C', writable=False], arg1: ndarray[dtype=int32, shape=(*), order='C', writable=False], arg2: ndarray[dtype=int32, shape=(*), order='C', writable=False], arg3: int, /) → None

squared_norm(self) → float

to_dense(self) → numpy.ndarray[dtype=int8]

transpose(self) → dolfinx.cpp.la.MatrixCSR_int8

class dolfinx.cpp.la.Norm(*values)

Bases: Enum

frobenius = 3

l1 = 0

l2 = 1

linf = 2

class dolfinx.cpp.la.SparsityPattern(self, comm: MPICommWrapper, maps: collections.abc.Sequence[dolfinx.cpp.common.IndexMap], bs: collections.abc.Sequence[int])

class dolfinx.cpp.la.SparsityPattern(self, comm: MPICommWrapper, patterns: collections.abc.Sequence[collections.abc.Sequence[dolfinx.cpp.la.SparsityPattern]], maps: collections.abc.Sequence[collections.abc.Sequence[tuple[std::reference_wrapper<dolfinx::common::IndexMap const>, int]]], bs: collections.abc.Sequence[collections.abc.Sequence[int]])

Bases: object

finalize(self) → None

property graph

(self) -> tuple[numpy.ndarray[dtype=int32, writable=False], numpy.ndarray[dtype=int64, writable=False]]

index_map(self, dim: int) → dolfinx.cpp.common.IndexMap

insert(self, rows: ndarray[dtype=int32, shape=(*), order='C', writable=False], cols: ndarray[dtype=int32, shape=(*), order='C', writable=False]) → None

insert(self, row: int, col: int) → None

insert_diagonal(self, rows: ndarray[dtype=int32, shape=(*), order='C', writable=False]) → None

property num_nonzeros

(self) -> int

class dolfinx.cpp.la.SuperLUDistMatrix_complex128(self, A: dolfinx.cpp.la.MatrixCSR_complex128)

Bases: object

property dtype

(self) -> str

class dolfinx.cpp.la.SuperLUDistMatrix_float32(self, A: dolfinx.cpp.la.MatrixCSR_float32)

Bases: object

property dtype

(self) -> str

class dolfinx.cpp.la.SuperLUDistMatrix_float64(self, A: dolfinx.cpp.la.MatrixCSR_float64)

Bases: object

property dtype

(self) -> str

class dolfinx.cpp.la.SuperLUDistSolver_complex128(self, A: dolfinx.cpp.la.SuperLUDistMatrix_complex128)

Bases: object

set_A(self, arg: dolfinx.cpp.la.SuperLUDistMatrix_complex128, /) → None

set_option(self, arg0: str, arg1: str, /) → None

solve(self, arg0: dolfinx.cpp.la.Vector_complex128, arg1: dolfinx.cpp.la.Vector_complex128, /) → int

class dolfinx.cpp.la.SuperLUDistSolver_float32(self, A: dolfinx.cpp.la.SuperLUDistMatrix_float32)

Bases: object

set_A(self, arg: dolfinx.cpp.la.SuperLUDistMatrix_float32, /) → None

set_option(self, arg0: str, arg1: str, /) → None

solve(self, arg0: dolfinx.cpp.la.Vector_float32, arg1: dolfinx.cpp.la.Vector_float32, /) → int

class dolfinx.cpp.la.SuperLUDistSolver_float64(self, A: dolfinx.cpp.la.SuperLUDistMatrix_float64)

Bases: object

set_A(self, arg: dolfinx.cpp.la.SuperLUDistMatrix_float64, /) → None

set_option(self, arg0: str, arg1: str, /) → None

solve(self, arg0: dolfinx.cpp.la.Vector_float64, arg1: dolfinx.cpp.la.Vector_float64, /) → int

class dolfinx.cpp.la.Vector_complex128(self, map: dolfinx.cpp.common.IndexMap, bs: int)

class dolfinx.cpp.la.Vector_complex128(self, vec: dolfinx.cpp.la.Vector_complex128)

Bases: object

property array

(self) -> numpy.ndarray[dtype=complex128]

property bs

(self) -> int

property dtype

(self) -> str

property index_map

(self) -> dolfinx.cpp.common.IndexMap

scatter_forward(self) → None

scatter_reverse(self, mode: dolfinx.cpp.la.InsertMode) → None

class dolfinx.cpp.la.Vector_complex64(self, map: dolfinx.cpp.common.IndexMap, bs: int)

class dolfinx.cpp.la.Vector_complex64(self, vec: dolfinx.cpp.la.Vector_complex64)

Bases: object

property array

(self) -> numpy.ndarray[dtype=complex64]

property bs

(self) -> int

property dtype

(self) -> str

property index_map

(self) -> dolfinx.cpp.common.IndexMap

scatter_forward(self) → None

scatter_reverse(self, mode: dolfinx.cpp.la.InsertMode) → None

class dolfinx.cpp.la.Vector_float32(self, map: dolfinx.cpp.common.IndexMap, bs: int)

class dolfinx.cpp.la.Vector_float32(self, vec: dolfinx.cpp.la.Vector_float32)

Bases: object

property array

(self) -> numpy.ndarray[dtype=float32]

property bs

(self) -> int

property dtype

(self) -> str

property index_map

(self) -> dolfinx.cpp.common.IndexMap

scatter_forward(self) → None

scatter_reverse(self, mode: dolfinx.cpp.la.InsertMode) → None

class dolfinx.cpp.la.Vector_float64(self, map: dolfinx.cpp.common.IndexMap, bs: int)

class dolfinx.cpp.la.Vector_float64(self, vec: dolfinx.cpp.la.Vector_float64)

Bases: object

property array

(self) -> numpy.ndarray[dtype=float64]

property bs

(self) -> int

property dtype

(self) -> str

property index_map

(self) -> dolfinx.cpp.common.IndexMap

scatter_forward(self) → None

scatter_reverse(self, mode: dolfinx.cpp.la.InsertMode) → None

class dolfinx.cpp.la.Vector_int32(self, map: dolfinx.cpp.common.IndexMap, bs: int)

class dolfinx.cpp.la.Vector_int32(self, vec: dolfinx.cpp.la.Vector_int32)

Bases: object

property array

(self) -> numpy.ndarray[dtype=int32]

property bs

(self) -> int

property dtype

(self) -> str

property index_map

(self) -> dolfinx.cpp.common.IndexMap

scatter_forward(self) → None

scatter_reverse(self, mode: dolfinx.cpp.la.InsertMode) → None

class dolfinx.cpp.la.Vector_int64(self, map: dolfinx.cpp.common.IndexMap, bs: int)

class dolfinx.cpp.la.Vector_int64(self, vec: dolfinx.cpp.la.Vector_int64)

Bases: object

property array

(self) -> numpy.ndarray[dtype=int64]

property bs

(self) -> int

property dtype

(self) -> str

property index_map

(self) -> dolfinx.cpp.common.IndexMap

scatter_forward(self) → None

scatter_reverse(self, mode: dolfinx.cpp.la.InsertMode) → None

class dolfinx.cpp.la.Vector_int8(self, map: dolfinx.cpp.common.IndexMap, bs: int)

class dolfinx.cpp.la.Vector_int8(self, vec: dolfinx.cpp.la.Vector_int8)

Bases: object

property array

(self) -> numpy.ndarray[dtype=int8]

property bs

(self) -> int

property dtype

(self) -> str

property index_map

(self) -> dolfinx.cpp.common.IndexMap

scatter_forward(self) → None

scatter_reverse(self, mode: dolfinx.cpp.la.InsertMode) → None