我们从Python开源项目中，提取了以下21个代码示例，用于说明如何使用numpy.ma.make_mask_descr()。
def __array_finalize__(self, obj): # Make sure we have a _fieldmask by default _mask = getattr(obj, '_mask', None) if _mask is None: objmask = getattr(obj, '_mask', nomask) _dtype = ndarray.__getattribute__(self, 'dtype') if objmask is nomask: _mask = ma.make_mask_none(self.shape, dtype=_dtype) else: mdescr = ma.make_mask_descr(_dtype) _mask = narray([tuple([m] * len(mdescr)) for m in objmask], dtype=mdescr).view(recarray) # Update some of the attributes _dict = self.__dict__ _dict.update(_mask=_mask) self._update_from(obj) if _dict['_baseclass'] == ndarray: _dict['_baseclass'] = recarray return
def __new__(cls, shape, dtype=None, buf=None, offset=0, strides=None, formats=None, names=None, titles=None, byteorder=None, aligned=False, mask=nomask, hard_mask=False, fill_value=None, keep_mask=True, copy=False, **options): self = recarray.__new__(cls, shape, dtype=dtype, buf=buf, offset=offset, strides=strides, formats=formats, names=names, titles=titles, byteorder=byteorder, aligned=aligned,) mdtype = ma.make_mask_descr(self.dtype) if mask is nomask or not np.size(mask): if not keep_mask: self._mask = tuple([False] * len(mdtype)) else: mask = np.array(mask, copy=copy) if mask.shape != self.shape: (nd, nm) = (self.size, mask.size) if nm == 1: mask = np.resize(mask, self.shape) elif nm == nd: mask = np.reshape(mask, self.shape) else: msg = "Mask and data not compatible: data size is %i, " + \ "mask size is %i." raise MAError(msg % (nd, nm)) copy = True if not keep_mask: self.__setmask__(mask) self._sharedmask = True else: if mask.dtype == mdtype: _mask = mask else: _mask = np.array([tuple([m] * len(mdtype)) for m in mask], dtype=mdtype) self._mask = _mask return self
def view(self, dtype=None, type=None): """ Returns a view of the mrecarray. """ # OK, basic copy-paste from MaskedArray.view. if dtype is None: if type is None: output = ndarray.view(self) else: output = ndarray.view(self, type) # Here again. elif type is None: try: if issubclass(dtype, ndarray): output = ndarray.view(self, dtype) dtype = None else: output = ndarray.view(self, dtype) # OK, there's the change except TypeError: dtype = np.dtype(dtype) # we need to revert to MaskedArray, but keeping the possibility # of subclasses (eg, TimeSeriesRecords), so we'll force a type # set to the first parent if dtype.fields is None: basetype = self.__class__.__bases__[0] output = self.__array__().view(dtype, basetype) output._update_from(self) else: output = ndarray.view(self, dtype) output._fill_value = None else: output = ndarray.view(self, dtype, type) # Update the mask, just like in MaskedArray.view if (getattr(output, '_mask', nomask) is not nomask): mdtype = ma.make_mask_descr(output.dtype) output._mask = self._mask.view(mdtype, ndarray) output._mask.shape = output.shape return output
