8000 BUG: np.ma.array changes subdtype fill_value · Issue #9303 · numpy/numpy · GitHub
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BUG: np.ma.array changes subdtype fill_value #9303

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eric-wieser opened this issue Jun 26, 2017 · 1 comment
Open

BUG: np.ma.array changes subdtype fill_value #9303

eric-wieser opened this issue Jun 26, 2017 · 1 comment
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00 - Bug component: numpy.ma masked arrays

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@eric-wieser
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eric-wieser commented Jun 26, 2017 •
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Repro:

>>> dt = np.dtype([('value', int, 3)])
>>> m = np.ma.array(([1, 2, 3],), dtype=dt, fill_value=([10, 20, 30],))
masked_array(data = ([1, 2, 3],),
             mask = ([False, False, False],),
       fill_value = ([10, 10, 10],),           # wrong!
            dtype = [('value', '<i4', (3,))])

Or perhaps more alarmingly:

>>> m = np.ma.array(([1, 2, 3],), dtype=dt)
>>> m.fill_value['value'][1] = 20
masked_array(data = ([1, 2, 3],),
             mask = ([False, False, False],),
       fill_value = ([10, 20, 10],),           # OK!
            dtype = [('value', '<i4', (3,))])
>>> np.ma.array(m)
masked_array(data = ([1, 2, 3],),
             mask = ([False, False, False],),
       fill_value = (10,),                     # Wait, what?
            dtype = [('value', '<i4', (3,))])

Is any of this by design? Surely m.dtype == m.fill_value.dtype is an invariant?
@eric-wieser
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eric-wieser commented Jun 26, 2017 •
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e2df0c7 by @pierregm introduced this peculiar line that breaks this invariant, without any obvious rationale.

It's possible that this was trying to preempt #6723

@eric-wieser eric-wieser mentioned this issue Jun 27, 2017
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00 - Bug component: numpy.ma masked arrays
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