diff options
| -rw-r--r-- | numpy/lib/function_base.py | 14 | ||||
| -rw-r--r-- | numpy/ma/core.py | 46 |
2 files changed, 30 insertions, 30 deletions
diff --git a/numpy/lib/function_base.py b/numpy/lib/function_base.py index 87052592c..3372f8aea 100644 --- a/numpy/lib/function_base.py +++ b/numpy/lib/function_base.py @@ -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 @@ -1273,7 +1273,7 @@ def extract(condition, arr): See Also -------- - take, put, putmask, compress + take, put, copyto, compress Examples -------- @@ -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`. @@ -1322,7 +1322,7 @@ def place(arr, mask, vals): See Also -------- - putmask, put, take, extract + copyto, put, take, extract Examples -------- @@ -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) diff --git a/numpy/ma/core.py b/numpy/ma/core.py index 50c60cd9d..4c40a7c30 100644 --- a/numpy/ma/core.py +++ b/numpy/ma/core.py @@ -860,7 +860,7 @@ class _MaskedUnaryOperation: 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 @@ -939,7 +939,7 @@ class _MaskedBinaryOperation: # 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 @@ -1001,7 +1001,7 @@ class _MaskedBinaryOperation: (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 @@ -1084,7 +1084,7 @@ class _DomainedBinaryOperation: 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 @@ -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="""\ @@ -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]) @@ -2828,7 +2828,7 @@ class MaskedArray(ndarray): # 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: @@ -3389,7 +3389,7 @@ class MaskedArray(ndarray): 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) @@ -3516,7 +3516,7 @@ class MaskedArray(ndarray): 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) @@ -3771,7 +3771,7 @@ class MaskedArray(ndarray): 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 @@ -5059,7 +5059,7 @@ class MaskedArray(ndarray): 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 @@ -5075,7 +5075,7 @@ class MaskedArray(ndarray): 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): @@ -5158,7 +5158,7 @@ class MaskedArray(ndarray): 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 @@ -5175,7 +5175,7 @@ class MaskedArray(ndarray): 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): @@ -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) #.............................................................................. @@ -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): @@ -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 |