Adding non-negative value check for input data objects #73
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jrbourbeau
reviewed
May 29, 2018
pyunfold/unfold.py
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| @@ -121,6 +121,8 @@ def iterative_unfold(data=None, data_err=None, response=None, | |||
| for name in inputs: | |||
| if inputs[name] is None: | |||
| raise ValueError('The input for "{}" must not be None.'.format(name)) | |||
| if np.any(np.array(inputs[name]) < 0.): | |||
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Could you use np.asarray instead of np.array? That way, if the input data are already ndarrays, then they aren't copied.
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Just wondering, is there a reason to use 0. here instead of just 0?
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I used 0. to ensure floating point comparison. I used np.array() because it merely copies and the cast_to_array method is used just after, so I thought it would be redundant. Either way it should be fine of course :)
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Added quick value error check to ensure all input data objects have non-negative values. Initial issue #72 implements ValueError check, but need a unit test to check failure mode.