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Upgrade dependency for travis to h5py 2.9.0 and update code to avoid … #86

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Upgrade dependency for travis to h5py 2.9.0 and update code to avoid … #86

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5c495a4
Upgrade dependency for travis to h5py 2.9.0 and update code to avoid …
Apr 1, 2019
ea4fa43
Switch travis file to install h5py from pip instead of conda
Apr 1, 2019
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2 changes: 1 addition & 1 deletion .travis.yml
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Original file line number Diff line number Diff line change
Expand Up @@ -15,7 +15,7 @@ before_install:
- source activate myenv
- pip install --upgrade pip
install:
- conda install --yes numpy h5py==2.7.0
- pip install numpy h5py==2.9.0
- pip install --upgrade quantities future requests
- pip install pytest pytest-cov coveralls
- pip install --upgrade docopt
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6 changes: 3 additions & 3 deletions h5py_wrapper/wrapper.py
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Expand Up @@ -278,10 +278,10 @@ def _load_dataset(f, lazy=False):
'custom_shape' in f.attrs):
return _load_custom_shape(f)
elif '_unit' in f.attrs:
return _cast_value_type(f.value, value_type,
return _cast_value_type(f[()], value_type,
unit=f.attrs['_unit'])
else:
return _cast_value_type(f.value, value_type)
return _cast_value_type(f[()], value_type)


def _evaluate_key(f):
Expand All @@ -303,7 +303,7 @@ def _load_custom_shape(f):
Reshape array with unequal dimensions into original shape.
"""
data_reshaped = []
value = f.value
value = f[()]
custom_value_types = f.attrs['custom_value_types'].astype(np.unicode_)
for (j, i), value_type in zip(lib.accumulate(f.attrs['oldshape']),
custom_value_types):
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