10000 ENH: Make memmaps return arrays in ufuncs and fancy indexing by seberg · Pull Request #2932 · numpy/numpy · GitHub
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ENH: Make memmaps return arrays in ufuncs and fancy indexing #2932

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ENH: Make memmaps return arrays in ufuncs and fancy indexing #2932

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d86c8bd
ENH: Make memmaps return arrays in ufuncs and fancy indexing
seberg Jan 18, 2013
e33b664
BUG: Tweak memmap __array_*__ calls to avoid possible regressions
seberg Jan 22, 2013
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BUG: Tweak memmap __array_*__ calls to avoid possible regressions 
Need to call the underlying __array_*__ function to look exactly
the same to a class subclassing memmap. To make sure that multiply
inheritence would keep working exactly the same, need to do the
try/excepts. However __array_finalize__ does not really support
multiple inheritences well in any case.
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@seberg
seberg committed Jan 22, 2013
commit e33b66490a3dccb01c32d877a25860a97fd2d73c
30 changes: 18 additions & 12 deletions numpy/core/memmap.py
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Original file line number Diff line number Diff line change
Expand Up @@ -283,24 +283,30 @@ def __array_finalize__(self, obj):
self.mode = None

def __array_wrap__(self, arr, context=None):
# If the type is not memmap, then a user subclass may have some special
# functions that should be preserved to avoid a regression
if type(self) is not memmap:
return arr.view(type=type(self))
return arr
# If the type is not memmap, then a user subclass may do some more
# things that need to be preserved. Otherwise, return a base array
# since it should not p
if type(self) is memmap and not np.may_share_memory(self, arr):
return arr
try:
return super(memmap, self).__array_wrap__(arr, context=context)
except TypeError:
return super(memmap, self).__array_wrap__(arr)

def __array_prepare__(self, arr, context=None):
if type(self) is not memmap:
return arr.view(type=type(self))
# There is no use in making an array a memmap, since it does not own
# its memory.
return arr
# There is no need to make an array a memmap, but we still have to do
# it in case this is not of memmap type.
if type(self) is memmap and not np.may_share_memory(self, arr):
return arr
try:
return super(memmap, self).__array_prepare__(arr, context=context)
except TypeError:
return super(memmap, self).__array_prepare__(arr)

def __getitem__(self, index):
# return an array if the result does not point to self's memory
res = super(memmap, self).__getitem__(index)
if type(res) is memmap and res._mmap is None:
return res.view(ndarray)
return res.view(type=ndarray)
return res

def flush(self):
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7 changes: 6 additions & 1 deletion numpy/core/tests/test_memmap.py
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Expand Up @@ -116,7 +116,11 @@ def test_view(self):
assert(new_array.base is fp)

def test_to_array_conversions(self):
class MMSubclass(memmap):
class DummyInerhitance(np.ndarray):
def __array_wrap__(self, arr):
arr = super(DummyInerhitance, self).__array_wrap__(arr)
arr.info = 'set'
class MMSubclass(memmap, DummyInerhitance):
pass
m = memmap(self.tmpfp, dtype=self.dtype, shape=self.shape)
r = m + 1
Expand All @@ -128,6 +132,7 @@ class MMSubclass(memmap):
m = MMSubclass(self.tmpfp, dtype=self.dtype, shape=self.shape)
r = m + 1
assert_(isinstance(r, MMSubclass))
assert_(hasattr(r, 'info'))
assert_(isinstance(m[:,[0,1]], MMSubclass))

if __name__ == "__main__":
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