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Handle np.array(DataIO) for numpy in py38 #248

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merged 5 commits into from
Jan 9, 2020
Merged

Handle np.array(DataIO) for numpy in py38 #248

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cd922b3
Handle np.array(DataIO) for numpy in py38
rly Jan 9, 2020
7e37201
Merge branch 'dev' into fix/numpy_py38
rly Jan 9, 2020
74c0a4a
Fix check for getattr of array_struct
rly Jan 9, 2020
7831820
Merge branch 'fix/numpy_py38' of https://github.com/hdmf-dev/hdmf int…
rly Jan 9, 2020
79302d8
Merge branch 'dev' into fix/numpy_py38
rly Jan 9, 2020
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2 changes: 2 additions & 0 deletions src/hdmf/data_utils.py
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Original file line number Diff line number Diff line change
Expand Up @@ -626,6 +626,8 @@ def __bool__(self):

def __getattr__(self, attr):
"""Delegate attribute lookup to data object"""
if attr == '__array_struct__': # np.array() checks __array__ or __array_struct__ attribute dep. on version
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Does this mean delegation of __array__ is allows but delegation of __array_struct__ is not? I.e., depending on the version of numpy we allow conversion of DataIO to a numpy array or not? Could you clarify what the problem with the __array_struct__ method is?

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My mistake. The error should only be thrown if the object is not self.valid. I have added that back.

raise InvalidDataIOError("Cannot convert data to array. Data is not valid.")
if not self.valid:
raise InvalidDataIOError("Cannot get attribute '%s' of data. Data is not valid." % attr)
return getattr(self.data, attr)
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