8000 Fix putmask by charris · Pull Request #106 · numpy/numpy · GitHub
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Fix putmask #106

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Merged
merged 2 commits into from
Jul 10, 2011
Merged

Fix putmask #106

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f35015c
STY: Put some spaces in.
charris Jul 9, 2011
b5cdaee
ENH: Fix some functions to use copyto instead of the deprecated putmask.
charris Jul 9, 2011
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ENH: Fix some functions to use copyto instead of the deprecated putmask.
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@charris
charris committed Jul 9, 2011
commit b5cdaee35bab2a06604f204ba18e00bf465879a7
14 changes: 7 additions & 7 deletions numpy/lib/function_base.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1146,9 +1146,9 @@ def unwrap(p, discont=pi, axis=-1):
slice1 = [slice(None, None)]*nd # full slices
slice1[axis] = slice(1, None)
ddmod = mod(dd+pi, 2*pi)-pi
_nx.putmask(ddmod, (ddmod==-pi) & (dd > 0), pi)
_nx.copyto(ddmod, pi, where=(ddmod==-pi) & (dd > 0))
ph_correct = ddmod - dd;
_nx.putmask(ph_correct, abs(dd)<discont, 0)
_nx.copyto(ph_correct, 0, where=abs(dd)<discont)
up = array(p, copy=True, dtype='d')
up[slice1] = p[slice1] + ph_correct.cumsum(axis)
return up
Expand Down Expand Up @@ -1273,7 +1273,7 @@ def extract(condition, arr):

See Also
--------
take, put, putmask, compress
take, put, copyto, compress

Examples
--------
Expand Down Expand Up @@ -1303,9 +1303,9 @@ def place(arr, mask, vals):
"""
Change elements of an array based on conditional and input values.

Similar to ``np.putmask(arr, mask, vals)``, the difference is that `place`
Similar to ``np.copyto(arr, vals, where=mask)``, the difference is that `place`
uses the first N elements of `vals`, where N is the number of True values
in `mask`, while `putmask` uses the elements where `mask` is True.
in `mask`, while `copyto` uses the elements where `mask` is True.

Note that `extract` does the exact opposite of `place`.

Expand All @@ -1322,7 +1322,7 @@ def place(arr, mask, vals):

See Also
--------
putmask, put, take, extract
copyto, put, take, extract

Examples
--------
Expand Down Expand Up @@ -1366,7 +1366,7 @@ def _nanop(op, fill, a, axis=None):
# y[mask] = fill
# We can't use fancy indexing here as it'll mess w/ MaskedArrays
# Instead, let's fill the array directly...
np.putmask(y, mask, fill)
np.copyto(y, fill, where=mask)
res = op(y, axis=axis)
mask_all_along_axis = mask.all(axis=axis)

Expand Down
46 changes: 23 additions & 23 deletions numpy/ma/core.py
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Expand Up @@ -860,7 +860,7 @@ def __call__ (self, a, *args, **kwargs):
if m is not nomask:
# In case result has a lower dtype than the inputs (as in equal)
try:
np.putmask(result, m, d)
np.copyto(result, d, where=m)
except TypeError:
pass
# Transform to
Expand Down Expand Up @@ -939,7 +939,7 @@ def __call__ (self, a, b, *args, **kwargs):
# Case 2. : array
# Revert result to da where masked
if m.any():
np.putmask(result, m, 0)
np.copyto(result, 0, casting='unsafe', where=m)
# This only makes sense if the operation preserved the dtype
if result.dtype == da.dtype:
result += m * da
Expand Down Expand Up @@ -1001,7 +1001,7 @@ def outer (self, a, b):
(da, db) = (getdata(a), getdata(b))
d = self.f.outer(da, db)
if m is not nomask:
np.putmask(d, m, da)
np.copyto(d, da, where=m)
if d.shape:
d = d.view(get_masked_subclass(a, b))
d._mask = m
Expand Down Expand Up @@ -1084,7 +1084,7 @@ def __call__(self, a, b, *args, **kwargs):
else:
return result
# When the mask is True, put back da
np.putmask(result, m, 0)
np.copyto(result, 0, casting='unsafe', where=m)
result += m * da
result = result.view(get_masked_subclass(a, b))
result._mask = m
Expand Down Expand Up @@ -2289,7 +2289,7 @@ def _recursive_printoption(result, mask, printopt):
if curdata.dtype.names:
_recursive_printoption(curdata, curmask, printopt)
else:
np.putmask(curdata, curmask, printopt)
np.copyto(curdata, printopt, where=curmask)
return

_print_templates = dict(long_std="""\
Expand Down Expand Up @@ -2334,7 +2334,7 @@ def _recursive_filled(a, mask, fill_value):
if current.dtype.names:
_recursive_filled(current, mask[name], fill_value[name])
else:
np.putmask(current, mask[name], fill_value[name])
np.copyto(current, fill_value[name], where=mask[name])



Expand Down Expand Up @@ -2828,7 +2828,7 @@ def __array_wrap__(self, obj, context=None):
# Domain not recognized, use fill_value instead
fill_value = self.fill_value
result = result.copy()
np.putmask(result, d, fill_value)
np.copyto(result, fill_value, where=d)
# Update the mask
if m is nomask:
if d is not nomask:
Expand Down Expand Up @@ -3389,7 +3389,7 @@ def filled(self, fill_value=None):
else:
result = self._data.copy()
try:
np.putmask(result, m, fill_value)
np.copyto(result, fill_value, where=m)
except (TypeError, AttributeError):
fill_value = narray(fill_value, dtype=object)
d = result.astype(object)
Expand Down Expand Up @@ -3516,7 +3516,7 @@ def __str__(self):
m = m.view((bool, len(m.dtype)))
if m.any():
r = np.array(self._data.tolist(), dtype=object)
np.putmask(r, m, f)
np.copyto(r, f, where=m)
return str(tuple(r))
else:
return str(self._data)
Expand Down Expand Up @@ -3771,7 +3771,7 @@ def __ipow__(self, other):
self._mask |= invalid
else:
self._mask = invalid
np.putmask(self._data, invalid, self.fill_value)
np.copyto(self._data, self.fill_value, where=invalid)
new_mask = mask_or(other_mask, invalid)
self._mask = mask_or(self._mask, new_mask)
return self
Expand Down Expand Up @@ -5059,7 +5059,7 @@ def min(self, axis=None, out=None, fill_value=None):
result.__setmask__(newmask)
# Get rid of Infs
if newmask.ndim:
np.putmask(result, newmask, result.fill_value)
np.copyto(result, result.fill_value, where=newmask)
elif newmask:
result = masked
return result
Expand All @@ -5075,7 +5075,7 @@ def min(self, axis=None, out=None, fill_value=None):
errmsg = "Masked data information would be lost in one or more"\
" location."
raise MaskError(errmsg)
np.putmask(out, newmask, np.nan)
np.copyto(out, np.nan, where=newmask)
return out

def mini(self, axis=None):
Expand Down Expand Up @@ -5158,7 +5158,7 @@ def max(self, axis=None, out=None, fill_value=None):
result.__setmask__(newmask)
# Get rid of Infs
if newmask.ndim:
np.putmask(result, newmask, result.fill_value)
np.copyto(result, result.fill_value, where=newmask)
elif newmask:
result = masked
return result
Expand All @@ -5175,7 +5175,7 @@ def max(self, axis=None, out=None, fill_value=None):
errmsg = "Masked data information would be lost in one or more"\
" location."
raise MaskError(errmsg)
np.putmask(out, newmask, np.nan)
np.copyto(out, np.nan, where=newmask)
return out

def ptp(self, axis=None, out=None, fill_value=None):
Expand Down Expand Up @@ -6040,7 +6040,7 @@ def power(a, b, third=None):
# if m.all():
# fa.flat = 1
# else:
# np.putmask(fa,m,1)
# np.copyto(fa, 1, where=m)
# return masked_array(umath.power(fa, fb), m)

#..............................................................................
Expand Down Expand Up @@ -6333,17 +6333,17 @@ def putmask(a, mask, values): #, mode='raise'):
if valmask is not nomask:
a._sharedmask = True
a._mask = make_mask_none(a.shape, a.dtype)
np.putmask(a._mask, mask, valmask)
np.copyto(a._mask, valmask, where=mask)
elif a._hardmask:
if valmask is not nomask:
m = a._mask.copy()
np.putmask(m, mask, valmask)
np.copyto(m, valmask, where=mask)
a.mask |= m
else:
if valmask is nomask:
valmask = getmaskarray(values)
np.putmask(a._mask, mask, valmask)
np.putmask(a._data, mask, valdata)
np.copyto(a._mask, valmask, where=mask)
np.copyto(a._data, valdata, where=mask)
return

def transpose(a, axes=None):
Expand Down Expand Up @@ -6553,12 +6553,12 @@ def where (condition, x=None, y=None):
# Construct an empty array and fill it
d = np.empty(fc.shape, dtype=ndtype).view(MaskedArray)
_data = d._data
np.putmask(_data, fc, xv.astype(ndtype))
np.putmask(_data, notfc, yv.astype(ndtype))
np.copyto(_data, xv.astype(ndtype), where=fc)
np.copyto(_data, yv.astype(ndtype), where=notfc)
# Create an empty mask and fill it
_mask = d._mask = np.zeros(fc.shape, dtype=MaskType)
np.putmask(_mask, fc, getmask(x))
np.putmask(_mask, notfc, getmask(y))
np.copyto(_mask, getmask(x), where=fc)
np.copyto(_mask, getmask(y), where=notfc)
_mask |= getmaskarray(condition)
if not _mask.any():
d._mask = nomask
Expand Down
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