AlenkaF commented on code in PR #45160:
URL: https://github.com/apache/arrow/pull/45160#discussion_r1903963210
##########
python/pyarrow/tensor.pxi:
##########
@@ -595,7 +595,25 @@ shape: {0.shape}""".format(self)
cdef class SparseCSRMatrix(_Weakrefable):
"""
- A sparse CSR matrix.
+ SparseCSRMatrix represents a sparse matrix in Compressed Sparse Row (CSR)
format.
+
+ Attributes:
+ indptr : array
+ Index pointer array.
+ indices : array
+ Column indices of the corresponding non-zero values.
+ shape : tuple
+ Shape of the matrix.
+ dim_names : list, optional
+ Names of the dimensions.
+
+ Example:
+ >>> import pyarrow as pa
+ >>> indptr = pa.array([0, 2, 3])
+ >>> indices = pa.array([0, 2, 1])
+ >>> shape = (2, 3)
+ >>> tensor = pa.SparseCSRMatrix(indptr, indices, shape)
+ >>> print(tensor)
Review Comment:
Did you meant to use one of the `from_*` methods here?
We do not use `SparseCSRMatrix`'s constructor directly, see:
https://github.com/apache/arrow/blob/ada8750917cd2ec2ae8a605d2673d78ef04c82e4/python/pyarrow/tensor.pxi#L617-L619
Could you change the example to use one of `pyarrow.SparseCSRMatrix.from_*`
functions and also add examples in separate `pyarrow.SparseCSRMatrix.from_*`
functions?
Attributes part should also be removed here (note we use NumPy style
docstrings).
Could we also then add similar examples (with outputs) to other tensor
formats/classes?
##########
docs/source/python/api/tensors.rst:
##########
@@ -0,0 +1,114 @@
+.. Licensed to the Apache Software Foundation (ASF) under one
+.. or more contributor license agreements. See the NOTICE file
+.. distributed with this work for additional information
+.. regarding copyright ownership. The ASF licenses this file
+.. to you under the Apache License, Version 2.0 (the
+.. "License"); you may not use this file except in compliance
+.. with the License. You may obtain a copy of the License at
+
+.. http://www.apache.org/licenses/LICENSE-2.0
+
+.. Unless required by applicable law or agreed to in writing,
+.. software distributed under the License is distributed on an
+.. "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+.. KIND, either express or implied. See the License for the
+.. specific language governing permissions and limitations
+.. under the License.
+
+.. currentmodule:: pyarrow
+
+.. _api.tensor:
+
+Tensors
+=======
+
+PyArrow supports both dense and sparse tensors. Dense tensors store all data
values explicitly, while sparse tensors represent only the non-zero elements
and their locations, making them efficient for storage and computation.
+
+Dense Tensors
+^^^^^^^^^^^^^
+
+.. autosummary::
+ :toctree: ../generated/
+
+ Tensor
+
+Sparse Tensors
+^^^^^^^^^^^^^
+
+PyArrow supports the following sparse tensor formats:
+
+.. autosummary::
+ :toctree: ../generated/
+
+ SparseCOOTensor
+ SparseCSRMatrix
+ SparseCSCMatrix
+ SparseCSFTensor
+
+"""SparseCOOTensor"""
+
+The ``SparseCOOTensor`` represents a sparse tensor in Coordinate (COO) format,
where non-zero elements are stored as tuples of row and column indices.
+
+Example:
+.. code-block:: python
+
+ import pyarrow as pa
+
+ indices = pa.array([[0, 0], [1, 2]])
+ data = pa.array([1, 2])
+ shape = (2, 3)
+
+ tensor = pa.SparseCOOTensor(indices, data, shape)
Review Comment:
We should use one of the `pyarrow.SparseCOOTensor.from_*` functions here and
add the output from the print statement.
##########
docs/source/python/api/tensors.rst:
##########
@@ -0,0 +1,114 @@
+.. Licensed to the Apache Software Foundation (ASF) under one
+.. or more contributor license agreements. See the NOTICE file
+.. distributed with this work for additional information
+.. regarding copyright ownership. The ASF licenses this file
+.. to you under the Apache License, Version 2.0 (the
+.. "License"); you may not use this file except in compliance
+.. with the License. You may obtain a copy of the License at
+
+.. http://www.apache.org/licenses/LICENSE-2.0
+
+.. Unless required by applicable law or agreed to in writing,
+.. software distributed under the License is distributed on an
+.. "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+.. KIND, either express or implied. See the License for the
+.. specific language governing permissions and limitations
+.. under the License.
+
+.. currentmodule:: pyarrow
+
+.. _api.tensor:
+
+Tensors
+=======
+
+PyArrow supports both dense and sparse tensors. Dense tensors store all data
values explicitly, while sparse tensors represent only the non-zero elements
and their locations, making them efficient for storage and computation.
+
+Dense Tensors
+^^^^^^^^^^^^^
+
+.. autosummary::
+ :toctree: ../generated/
+
+ Tensor
+
+Sparse Tensors
+^^^^^^^^^^^^^
+
+PyArrow supports the following sparse tensor formats:
+
+.. autosummary::
+ :toctree: ../generated/
+
+ SparseCOOTensor
+ SparseCSRMatrix
+ SparseCSCMatrix
+ SparseCSFTensor
+
+"""SparseCOOTensor"""
+
+The ``SparseCOOTensor`` represents a sparse tensor in Coordinate (COO) format,
where non-zero elements are stored as tuples of row and column indices.
Review Comment:
I would add code examples to `docs/source/python/data.rst` and keep the
reference docs cleaner.
We do not have a unified way of writing code blocks,
[unfortunately](https://github.com/apache/arrow/issues/28859). But we do use
prompt characters and add output, see example
https://raw.githubusercontent.com/apache/arrow/refs/heads/main/docs/source/python/numpy.rst.
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