10000 Order-dependence setting nested arrays of different shapes · Issue #9684 · numpy/numpy · GitHub
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comatrion opened this issue Sep 13, 2017 · 4 comments
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Order-dependence setting nested arrays of different shapes #9684

comatrion opened this issue Sep 13, 2017 · 4 comments
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00 - Bug component: numpy._core
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1.16.0 release

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@comatrion
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comatrion commented Sep 13, 2017 •
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For example:

>>> a = np.array([np.array([1, 2]), np.array(1)])
>>> a
array([array([1, 2]), array(1)], dtype=object)

>>> b = np.array([np.array(1), np.array([1, 2])])
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
ValueError: setting an array element with a sequence.

Specifying dtype avoids the exception for b:

>>> b = np.array([np.array(1), np.array([1, 2])], dtype=object)
>>> b
array([array(1), array([1, 2])], dtype=object)

However dtype is optional. If an array can be instantiated successfully without dtype for a given input sequence, then re-ordering the sequence should not cause an exception.

python 3.4.5 numpy 1.13.1.
@jsclose
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jsclose commented Apr 2, 2018

Is this an actual issue? Should numpy automatically re order the array?

@eric-wieser
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We're definitely aware of this, and there's an issue somewhere suggesting that we change this behavior so that passing dtype=object is always required, and that otherwise both cases should error.

@jsclose
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jsclose commented Apr 2, 2018

#5353 it seems like issue and this experiment #10147. Was there any resolution to that?

@eric-wieser
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Fixed in #11601

@eric-wieser eric-wieser added this to the 1.16.0 release milestone Jul 23, 2018
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