dolfinx.cpp.la

Linear algebra module

Classes

`BlockMode`(value[, names, module, qualname, ...])
`InsertMode`(value[, names, module, qualname, ...])
`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`(value[, names, module, qualname, type, ...])
`SparsityPattern`()
`Vector_complex128`()
`Vector_complex64`()
`Vector_float32`()
`Vector_float64`()
`Vector_int32`()
`Vector_int64`()
`Vector_int8`()

class dolfinx.cpp.la.BlockMode(value, names=<not given>, *values, module=None, qualname=None, type=None, start=1, boundary=None)

Bases: Enum

compact = 0

expanded = 1

class dolfinx.cpp.la.InsertMode(value, names=<not given>, *values, module=None, qualname=None, type=None, start=1, boundary=None)

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

property bs: (self) -> list[int]

property data: (self) -> numpy.ndarray[dtype=complex128]

property dtype: (self) -> str

index_map

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

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

scatter_rev_begin

scatter_rev_end

scatter_reverse

set

set_value

squared_norm

to_dense

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

Bases: object

add

property bs: (self) -> list[int]

property data: (self) -> numpy.ndarray[dtype=complex64]

property dtype: (self) -> str

index_map

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

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

scatter_rev_begin

scatter_rev_end

scatter_reverse

set

set_value

squared_norm

to_dense

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

Bases: object

add

property bs: (self) -> list[int]

property data: (self) -> numpy.ndarray[dtype=float32]

property dtype: (self) -> str

index_map

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

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

scatter_rev_begin

scatter_rev_end

scatter_reverse

set

set_value

squared_norm

to_dense

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

Bases: object

add

property bs: (self) -> list[int]

property data: (self) -> numpy.ndarray[dtype=float64]

property dtype: (self) -> str

index_map

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

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

scatter_rev_begin

scatter_rev_end

scatter_reverse

set

set_value

squared_norm

to_dense

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

Bases: object

add

property bs: (self) -> list[int]

property data: (self) -> numpy.ndarray[dtype=int32]

property dtype: (self) -> str

index_map

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

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

scatter_rev_begin

scatter_rev_end

scatter_reverse

set

set_value

squared_norm

to_dense

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

Bases: object

add

property bs: (self) -> list[int]

property data: (self) -> numpy.ndarray[dtype=int64]

property dtype: (self) -> str

index_map

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

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

scatter_rev_begin

scatter_rev_end

scatter_reverse

set

set_value

squared_norm

to_dense

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

Bases: object

add

property bs: (self) -> list[int]

property data: (self) -> numpy.ndarray[dtype=int8]

property dtype: (self) -> str

index_map

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

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

scatter_rev_begin

scatter_rev_end

scatter_reverse

set

set_value

squared_norm

to_dense

class dolfinx.cpp.la.Norm(value, names=<not given>, *values, module=None, qualname=None, type=None, start=1, boundary=None)

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

column_index_map

finalize

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

index_map

insert

insert_diagonal

property num_nonzeros: (self) -> 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

scatter_reverse

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

scatter_reverse

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

scatter_reverse

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

scatter_reverse

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

scatter_reverse

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

scatter_reverse

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

scatter_reverse