cupyx.scipy.sparse.csr_matrix¶
-
class
cupyx.scipy.sparse.
csr_matrix
(arg1, shape=None, dtype=None, copy=False)¶ Compressed Sparse Row matrix.
Now it has only part of initializer formats:
csr_matrix(D)
D
is a rank-2cupy.ndarray
.csr_matrix(S)
S
is another sparse matrix. It is equivalent toS.tocsr()
.csr_matrix((M, N), [dtype])
- It constructs an empty matrix whose shape is
(M, N)
. Default dtype is float64. csr_matrix((data, indices, indptr))
- All
data
,indices
andindptr
are one-dimenaionalcupy.ndarray
.
Parameters: - arg1 – Arguments for the initializer.
- shape (tuple) – Shape of a matrix. Its length must be two.
- dtype – Data type. It must be an argument of
numpy.dtype
. - copy (bool) – If
True
, copies of given arrays are always used.
See also
Methods
-
__getitem__
(slices)¶
-
__len__
()¶
-
__iter__
()¶
-
arcsin
()¶ Elementwise arcsin.
-
arcsinh
()¶ Elementwise arcsinh.
-
arctan
()¶ Elementwise arctan.
-
arctanh
()¶ Elementwise arctanh.
-
asformat
(format)¶ Return this matrix in a given sparse format.
Parameters: format (str or None) – Format you need.
-
asfptype
()¶ Upcasts matrix to a floating point format.
When the matrix has floating point type, the method returns itself. Otherwise it makes a copy with floating point type and the same format.
Returns: A matrix with float type. Return type: cupyx.scipy.sparse.spmatrix
-
astype
(t)¶ Casts the array to given data type.
Parameters: dtype – Type specifier. Returns: A copy of the array with a given type.
-
ceil
()¶ Elementwise ceil.
-
conj
(copy=True)¶ Element-wise complex conjugation.
If the matrix is of non-complex data type and copy is False, this method does nothing and the data is not copied.
Parameters: copy (bool) – If True, the result is guaranteed to not share data with self. Returns: The element-wise complex conjugate. Return type: cupyx.scipy.sparse.spmatrix
-
conjugate
(copy=True)¶ Element-wise complex conjugation.
If the matrix is of non-complex data type and copy is False, this method does nothing and the data is not copied.
Parameters: copy (bool) – If True, the result is guaranteed to not share data with self. Returns: The element-wise complex conjugate. Return type: cupyx.scipy.sparse.spmatrix
-
copy
()¶ Returns a copy of this matrix.
No data/indices will be shared between the returned value and current matrix.
-
count_nonzero
()¶ Returns number of non-zero entries.
Note
This method counts the actual number of non-zero entories, which does not include explicit zero entries. Instead
nnz
returns the number of entries including explicit zeros.Returns: Number of non-zero entries.
-
deg2rad
()¶ Elementwise deg2rad.
-
diagonal
()¶ Returns the main diagonal of the matrix
-
dot
(other)¶ Ordinary dot product
-
eliminate_zeros
()¶ Removes zero entories in place.
-
expm1
()¶ Elementwise expm1.
-
floor
()¶ Elementwise floor.
-
get
(stream=None)¶ Returns a copy of the array on host memory.
Parameters: stream (cupy.cuda.Stream) – CUDA stream object. If it is given, the copy runs asynchronously. Otherwise, the copy is synchronous. Returns: Copy of the array on host memory. Return type: scipy.sparse.csr_matrix
-
getH
()¶
-
getformat
()¶
-
getmaxprint
()¶
-
getnnz
(axis=None)¶ Returns the number of stored values, including explicit zeros.
Parameters: axis – Not supported yet. Returns: The number of stored values. Return type: int
-
log1p
()¶ Elementwise log1p.
-
maximum
(other)¶
-
minimum
(other)¶
-
multiply
(other)¶ Point-wise multiplication by another matrix
-
power
(n, dtype=None)¶ Elementwise power function.
Parameters: - n – Exponent.
- dtype – Type specifier.
-
rad2deg
()¶ Elementwise rad2deg.
-
reshape
(shape, order='C')¶ Gives a new shape to a sparse matrix without changing its data.
-
rint
()¶ Elementwise rint.
-
set_shape
(shape)¶
-
sign
()¶ Elementwise sign.
-
sin
()¶ Elementwise sin.
-
sinh
()¶ Elementwise sinh.
-
sort_indices
()¶ Sorts the indices of the matrix in place.
-
sqrt
()¶ Elementwise sqrt.
-
sum
(axis=None, dtype=None, out=None)¶ Sums the matrix elements over a given axis.
Parameters: - axis (int or
None
) – Axis along which the sum is comuted. If it isNone
, it computes the sum of all the elements. Select from{None, 0, 1, -2, -1}
. - dtype – The type of returned matrix. If it is not specified, type of the array is used.
- out (cupy.ndarray) – Output matrix.
Returns: Summed array.
Return type: See also
- axis (int or
-
sum_duplicates
()¶
-
tan
()¶ Elementwise tan.
-
tanh
()¶ Elementwise tanh.
-
toarray
(order=None, out=None)¶ Returns a dense matrix representing the same value.
Parameters: - order ({'C', 'F', None}) – Whether to store data in C (row-major) order or F (column-major) order. Default is C-order.
- out – Not supported.
Returns: Dense array representing the same matrix.
Return type: See also
-
tobsr
(blocksize=None, copy=False)¶ Convert this matrix to Block Sparse Row format.
-
tocoo
(copy=False)¶ Converts the matrix to COOdinate format.
Parameters: copy (bool) – If False
, it shares data arrays as much as possible.Returns: Converted matrix. Return type: cupyx.scipy.sparse.coo_matrix
-
tocsc
(copy=False)¶ Converts the matrix to Compressed Sparse Column format.
Parameters: copy (bool) – If False
, it shares data arrays as much as possible. Actually this option is ignored because all arrays in a matrix cannot be shared in csr to csc conversion.Returns: Converted matrix. Return type: cupyx.scipy.sparse.csc_matrix
-
tocsr
(copy=False)¶ Converts the matrix to Compressed Sparse Row format.
Parameters: copy (bool) – If False
, the method returns itself. Otherwise it makes a copy of the matrix.Returns: Converted matrix. Return type: cupyx.scipy.sparse.csr_matrix
-
todense
(order=None, out=None)¶ Return a dense matrix representation of this matrix.
-
todia
(copy=False)¶ Convert this matrix to sparse DIAgonal format.
-
todok
(copy=False)¶ Convert this matrix to Dictionary Of Keys format.
-
tolil
(copy=False)¶ Convert this matrix to LInked List format.
-
transpose
(axes=None, copy=False)¶ Returns a transpose matrix.
Parameters: - axes – This option is not supported.
- copy (bool) – If
True
, a returned matrix shares no data. Otherwise, it shared data arrays as much as possible.
Returns: Transpose matrix.
Return type:
-
trunc
()¶ Elementwise trunc.
-
__eq__
(other)¶ Return self==value.
-
__ne__
(other)¶ Return self!=value.
-
__lt__
(other)¶ Return self<value.
-
__le__
(other)¶ Return self<=value.
-
__gt__
(other)¶ Return self>value.
-
__ge__
(other)¶ Return self>=value.
-
__nonzero__
()¶
-
__bool__
()¶
Attributes
-
H
¶
-
T
¶
-
device
¶ CUDA device on which this array resides.
-
dtype
¶ Data type of the matrix.
-
format
= 'csr'¶
-
has_canonical_format
¶
-
ndim
¶
-
nnz
¶
-
shape
¶
-
size
¶