diff options
Diffstat (limited to 'numpy/ma/core.py')
| -rw-r--r-- | numpy/ma/core.py | 26 |
1 files changed, 5 insertions, 21 deletions
diff --git a/numpy/ma/core.py b/numpy/ma/core.py index b2e6ad91b..ccf62bdcf 100644 --- a/numpy/ma/core.py +++ b/numpy/ma/core.py @@ -838,13 +838,9 @@ class _MaskedUnaryOperation: d = getdata(a) # Case 1.1. : Domained function if self.domain is not None: - # Save the error status - err_status_ini = np.geterr() - try: + with np.errstate(): np.seterr(divide='ignore', invalid='ignore') result = self.f(d, *args, **kwargs) - finally: - np.seterr(**err_status_ini) # Make a mask m = ~umath.isfinite(result) m |= self.domain(d) @@ -931,12 +927,9 @@ class _MaskedBinaryOperation: else: m = umath.logical_or(ma, mb) # Get the result - err_status_ini = np.geterr() - try: + with np.errstate(): np.seterr(divide='ignore', invalid='ignore') result = self.f(da, db, *args, **kwargs) - finally: - np.seterr(**err_status_ini) # Case 1. : scalar if not result.ndim: if m: @@ -1069,12 +1062,9 @@ class _DomainedBinaryOperation: (da, db) = (getdata(a, subok=False), getdata(b, subok=False)) (ma, mb) = (getmask(a), getmask(b)) # Get the result - err_status_ini = np.geterr() - try: + with np.errstate(): np.seterr(divide='ignore', invalid='ignore') result = self.f(da, db, *args, **kwargs) - finally: - np.seterr(**err_status_ini) # Get the mask as a combination of ma, mb and invalid m = ~umath.isfinite(result) m |= ma @@ -3815,12 +3805,9 @@ class MaskedArray(ndarray): "Raise self to the power other, in place." other_data = getdata(other) other_mask = getmask(other) - err_status = np.geterr() - try: + with np.errstate(): np.seterr(divide='ignore', invalid='ignore') ndarray.__ipow__(self._data, np.where(self._mask, 1, other_data)) - finally: - np.seterr(**err_status) invalid = np.logical_not(np.isfinite(self._data)) if invalid.any(): if self._mask is not nomask: @@ -6083,12 +6070,9 @@ def power(a, b, third=None): else: basetype = MaskedArray # Get the result and view it as a (subclass of) MaskedArray - err_status = np.geterr() - try: + with np.errstate(): np.seterr(divide='ignore', invalid='ignore') result = np.where(m, fa, umath.power(fa, fb)).view(basetype) - finally: - np.seterr(**err_status) result._update_from(a) # Find where we're in trouble w/ NaNs and Infs invalid = np.logical_not(np.isfinite(result.view(ndarray))) |