cupyx.scipy.sparse.spmatrix#
- class cupyx.scipy.sparse.spmatrix(maxprint=50)[source]#
Base class of all sparse matrixes.
Methods
- asformat(format)[source]#
Return this matrix in a given sparse format.
- Parameters
format (str or None) – Format you need.
- asfptype()[source]#
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
- astype(t)[source]#
Casts the array to given data type.
- Parameters
t – Type specifier.
- Returns
A copy of the array with the given type and the same format.
- Return type
- conj(copy=True)[source]#
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
- conjugate(copy=True)[source]#
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
- copy()[source]#
Returns a copy of this matrix.
No data/indices will be shared between the returned value and current matrix.
- diagonal(k=0)[source]#
Returns the k-th diagonal of the matrix.
- Parameters
k (int, optional) – Which diagonal to get, corresponding to elements
a[i – 0 (the main diagonal).
Default (i+k].) – 0 (the main diagonal).
- Returns
The k-th diagonal.
- Return type
- get(stream=None)[source]#
Return 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
An array on host memory.
- Return type
- mean(axis=None, dtype=None, out=None)[source]#
Compute the arithmetic mean along the specified axis.
Returns the average of the matrix elements. The average is taken over all elements in the matrix by default, otherwise over the specified axis. float64 intermediate and return values are used for integer inputs.
- Parameters
{-2 (axis) – optional Axis along which the mean is computed. The default is to compute the mean of all elements in the matrix (i.e., axis = None).
-1 – optional Axis along which the mean is computed. The default is to compute the mean of all elements in the matrix (i.e., axis = None).
0 – optional Axis along which the mean is computed. The default is to compute the mean of all elements in the matrix (i.e., axis = None).
1 – optional Axis along which the mean is computed. The default is to compute the mean of all elements in the matrix (i.e., axis = None).
None} – optional Axis along which the mean is computed. The default is to compute the mean of all elements in the matrix (i.e., axis = None).
dtype (dtype) – optional Type to use in computing the mean. For integer inputs, the default is float64; for floating point inputs, it is the same as the input dtype.
out (cupy.ndarray) – optional Alternative output matrix in which to place the result. It must have the same shape as the expected output, but the type of the output values will be cast if necessary.
- Returns
Output array of means
- Return type
m (cupy.ndarray)
See also
scipy.sparse.spmatrix.mean()
- reshape(*shape, order='C')[source]#
Gives a new shape to a sparse matrix without changing its data.
- Parameters
shape (tuple) – The new shape should be compatible with the original shape.
order – {‘C’, ‘F’} (optional) Read the elements using this index order. ‘C’ means to read and write the elements using C-like index order. ‘F’ means to read and write the elements using Fortran-like index order. Default: C.
- Returns
sparse matrix
- Return type
- setdiag(values, k=0)[source]#
Set diagonal or off-diagonal elements of the array.
- Parameters
values (cupy.ndarray) – New values of the diagonal elements. Values may have any length. If the diagonal is longer than values, then the remaining diagonal entries will not be set. If values is longer than the diagonal, then the remaining values are ignored. If a scalar value is given, all of the diagonal is set to it.
k (int, optional) – Which diagonal to set, corresponding to elements a[i, i+k]. Default: 0 (the main diagonal).
- sum(axis=None, dtype=None, out=None)[source]#
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
scipy.sparse.spmatrix.sum()
Attributes
- H#
- T#
- device#
CUDA device on which this array resides.
- ndim#
- nnz#
- shape#
- size#