pitrou commented on code in PR #37533:
URL: https://github.com/apache/arrow/pull/37533#discussion_r1482681845
##########
python/pyarrow/array.pxi:
##########
@@ -3570,27 +3570,57 @@ class FixedShapeTensorArray(ExtensionArray):
def to_numpy_ndarray(self):
"""
- Convert fixed shape tensor extension array to a numpy array (with
dim+1).
+ Convert fixed shape tensor extension array to a multi-dimensional
numpy.ndarray.
- Note: ``permutation`` should be trivial (``None`` or ``[0, 1, ...,
len(shape)-1]``).
+ The resulting ndarray will have (ndim + 1) dimensions.
+ The size of the first dimension will be the length of the fixed shape
tensor array
+ and the rest of the dimensions will match the permuted shape of the
fixed
+ shape tensor.
+
+ The conversion is zero-copy.
+
Review Comment:
Nit: remove extraneous empty line.
```suggestion
```
##########
python/pyarrow/array.pxi:
##########
@@ -3573,17 +3602,19 @@ class FixedShapeTensorArray(ExtensionArray):
]
]
"""
- if not obj.flags["C_CONTIGUOUS"]:
- raise ValueError('The data in the numpy array need to be in a
single, '
- 'C-style contiguous segment.')
+
+ permutation = (-np.array(obj.strides)).argsort(kind='stable')
+ if permutation[0] != 0:
+ raise ValueError('First stride needs to be largest to ensure that '
+ 'individual tensor data is contiguous in memory.')
arrow_type = from_numpy_dtype(obj.dtype)
- shape = obj.shape[1:]
- size = obj.size / obj.shape[0]
+ shape = np.take(obj.shape, permutation)
+ values = np.ravel(obj, order="K")
Review Comment:
`as_strided` can be a later PR if desired. The docstring addition is good
for now!
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