westonpace commented on code in PR #14378:
URL: https://github.com/apache/arrow/pull/14378#discussion_r1172672469
##########
python/pyarrow/tests/test_sparse_tensor.py:
##########
@@ -434,6 +433,23 @@ def test_sparse_coo_tensor_scipy_roundtrip(dtype_str,
arrow_type):
assert sparse_tensor.has_canonical_format
assert out_scipy_matrix.has_canonical_format
+ scipy_matrix = coo_matrix([[0, 0], [0, 0]])
+ sparse_tensor = pa.SparseCOOTensor.from_scipy(scipy_matrix,
+ dim_names=dim_names)
+ out_scipy_matrix = sparse_tensor.to_scipy()
Review Comment:
Can we verify the shape of `sparse_tensor` here? It should be 2 x 2 correct?
##########
cpp/src/arrow/sparse_tensor.cc:
##########
@@ -134,6 +134,10 @@ inline Status CheckSparseCOOIndexValidity(const
std::shared_ptr<DataType>& type,
RETURN_NOT_OK(internal::CheckSparseIndexMaximumValue(type, shape));
+ // Indexes with no values are considered valid
Review Comment:
I don't understand what is happening here (I don't understand much about the
tensors so not surprising). Why is it ok if one of the shape elements is zero?
I would expect an empty sparse matrix to still have a shape:
```
>>> scipy.sparse.coo_matrix(numpy.zeros((2,4)), dtype=numpy.float32).shape
(2, 4)
```
##########
python/pyarrow/tests/test_sparse_tensor.py:
##########
@@ -434,6 +434,21 @@ def test_sparse_coo_tensor_scipy_roundtrip(dtype_str,
arrow_type):
assert sparse_tensor.has_canonical_format
assert out_scipy_matrix.has_canonical_format
+ scipy_matrix = coo_matrix([[0, 0], [0, 0]])
Review Comment:
I believe @rok has the correct test here but I could be wrong. The original
issue is about a sparse matrix with a valid non-zero shape but no elements:
```
>>> scipy.sparse.coo_matrix(numpy.zeros((2,4)), dtype=numpy.float32)
<2x4 sparse matrix of type '<class 'numpy.float32'>'
with 0 stored elements in COOrdinate format>
>>> numpy.zeros((2,4))
array([[0., 0., 0., 0.],
[0., 0., 0., 0.]])
>>> numpy.zeros((2,4)).shape
(2, 4)
```
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