diff options
Diffstat (limited to 'numpy/ma/core.py')
| -rw-r--r-- | numpy/ma/core.py | 248 |
1 files changed, 93 insertions, 155 deletions
diff --git a/numpy/ma/core.py b/numpy/ma/core.py index 33ac936d0..2baf547a4 100644 --- a/numpy/ma/core.py +++ b/numpy/ma/core.py @@ -59,14 +59,14 @@ __all__ = [ 'choose', 'clip', 'common_fill_value', 'compress', 'compressed', 'concatenate', 'conjugate', 'convolve', 'copy', 'correlate', 'cos', 'cosh', 'count', 'cumprod', 'cumsum', 'default_fill_value', 'diag', 'diagonal', - 'diff', 'divide', 'dump', 'dumps', 'empty', 'empty_like', 'equal', 'exp', + 'diff', 'divide', 'empty', 'empty_like', 'equal', 'exp', 'expand_dims', 'fabs', 'filled', 'fix_invalid', 'flatten_mask', 'flatten_structured_array', 'floor', 'floor_divide', 'fmod', 'frombuffer', 'fromflex', 'fromfunction', 'getdata', 'getmask', 'getmaskarray', 'greater', 'greater_equal', 'harden_mask', 'hypot', 'identity', 'ids', 'indices', 'inner', 'innerproduct', 'isMA', 'isMaskedArray', 'is_mask', 'is_masked', 'isarray', 'left_shift', - 'less', 'less_equal', 'load', 'loads', 'log', 'log10', 'log2', + 'less', 'less_equal', 'log', 'log10', 'log2', 'logical_and', 'logical_not', 'logical_or', 'logical_xor', 'make_mask', 'make_mask_descr', 'make_mask_none', 'mask_or', 'masked', 'masked_array', 'masked_equal', 'masked_greater', @@ -77,7 +77,7 @@ __all__ = [ 'maximum_fill_value', 'mean', 'min', 'minimum', 'minimum_fill_value', 'mod', 'multiply', 'mvoid', 'ndim', 'negative', 'nomask', 'nonzero', 'not_equal', 'ones', 'outer', 'outerproduct', 'power', 'prod', - 'product', 'ptp', 'put', 'putmask', 'rank', 'ravel', 'remainder', + 'product', 'ptp', 'put', 'putmask', 'ravel', 'remainder', 'repeat', 'reshape', 'resize', 'right_shift', 'round', 'round_', 'set_fill_value', 'shape', 'sin', 'sinh', 'size', 'soften_mask', 'sometrue', 'sort', 'sqrt', 'squeeze', 'std', 'subtract', 'sum', @@ -602,8 +602,10 @@ def filled(a, fill_value=None): ---------- a : MaskedArray or array_like An input object. - fill_value : scalar, optional - Filling value. Default is None. + fill_value : array_like, optional. + Can be scalar or non-scalar. If non-scalar, the + resulting filled array should be broadcastable + over input array. Default is None. Returns ------- @@ -623,10 +625,19 @@ def filled(a, fill_value=None): array([[999999, 1, 2], [999999, 4, 5], [ 6, 7, 8]]) + >>> x.filled(fill_value=333) + array([[333, 1, 2], + [333, 4, 5], + [ 6, 7, 8]]) + >>> x.filled(fill_value=np.arange(3)) + array([[0, 1, 2], + [0, 4, 5], + [6, 7, 8]]) """ if hasattr(a, 'filled'): return a.filled(fill_value) + elif isinstance(a, ndarray): # Should we check for contiguity ? and a.flags['CONTIGUOUS']: return a @@ -800,7 +811,7 @@ class _DomainCheckInterval(object): def __init__(self, a, b): "domain_check_interval(a,b)(x) = true where x < a or y > b" - if (a > b): + if a > b: (a, b) = (b, a) self.a = a self.b = b @@ -1060,7 +1071,7 @@ class _MaskedBinaryOperation(_MaskedUFunc): if t.shape == (): t = t.reshape(1) if m is not nomask: - m = make_mask(m, copy=1) + m = make_mask(m, copy=True) m.shape = (1,) if m is nomask: @@ -1165,7 +1176,7 @@ class _DomainedBinaryOperation(_MaskedUFunc): if domain is not None: m |= domain(da, db) # Take care of the scalar case first - if (not m.ndim): + if not m.ndim: if m: return masked else: @@ -1554,7 +1565,7 @@ def make_mask(m, copy=False, shrink=True, dtype=MaskType): Return `m` as a boolean mask, creating a copy if necessary or requested. The function can accept any sequence that is convertible to integers, or ``nomask``. Does not require that contents must be 0s and 1s, values - of 0 are interepreted as False, everything else as True. + of 0 are interpreted as False, everything else as True. Parameters ---------- @@ -1743,7 +1754,7 @@ def mask_or(m1, m2, copy=False, shrink=True): if m1 is m2 and is_mask(m1): return m1 (dtype1, dtype2) = (getattr(m1, 'dtype', None), getattr(m2, 'dtype', None)) - if (dtype1 != dtype2): + if dtype1 != dtype2: raise ValueError("Incompatible dtypes '%s'<>'%s'" % (dtype1, dtype2)) if dtype1.names is not None: # Allocate an output mask array with the properly broadcast shape. @@ -2681,15 +2692,13 @@ class MaskedIterator(object): -------- >>> x = np.ma.array([3, 2], mask=[0, 1]) >>> fl = x.flat - >>> fl.next() + >>> next(fl) 3 - >>> fl.next() + >>> next(fl) masked - >>> fl.next() + >>> next(fl) Traceback (most recent call last): - File "<stdin>", line 1, in <module> - File "/home/ralf/python/numpy/numpy/ma/core.py", line 2243, in next - d = self.dataiter.next() + ... StopIteration """ @@ -3077,7 +3086,7 @@ class MaskedArray(ndarray): def view(self, dtype=None, type=None, fill_value=None): """ - Return a view of the MaskedArray data + Return a view of the MaskedArray data. Parameters ---------- @@ -3091,6 +3100,14 @@ class MaskedArray(ndarray): type : Python type, optional Type of the returned view, either ndarray or a subclass. The default None results in type preservation. + fill_value : scalar, optional + The value to use for invalid entries (None by default). + If None, then this argument is inferred from the passed `dtype`, or + in its absence the original array, as discussed in the notes below. + + See Also + -------- + numpy.ndarray.view : Equivalent method on ndarray object. Notes ----- @@ -3143,7 +3160,7 @@ class MaskedArray(ndarray): # also make the mask be a view (so attr changes to the view's # mask do no affect original object's mask) # (especially important to avoid affecting np.masked singleton) - if (getmask(output) is not nomask): + if getmask(output) is not nomask: output._mask = output._mask.view() # Make sure to reset the _fill_value if needed @@ -3156,7 +3173,6 @@ class MaskedArray(ndarray): else: output.fill_value = fill_value return output - view.__doc__ = ndarray.view.__doc__ def __getitem__(self, indx): """ @@ -3382,7 +3398,7 @@ class MaskedArray(ndarray): if mask is masked: mask = True - if (current_mask is nomask): + if current_mask is nomask: # Make sure the mask is set # Just don't do anything if there's nothing to do. if mask is nomask: @@ -3648,6 +3664,14 @@ class MaskedArray(ndarray): @fill_value.setter def fill_value(self, value=None): target = _check_fill_value(value, self.dtype) + if not target.ndim == 0: + # 2019-11-12, 1.18.0 + warnings.warn( + "Non-scalar arrays for the fill value are deprecated. Use " + "arrays with scalar values instead. The filled function " + "still supports any array as `fill_value`.", + DeprecationWarning, stacklevel=2) + _fill_value = self._fill_value if _fill_value is None: # Create the attribute if it was undefined @@ -3668,9 +3692,11 @@ class MaskedArray(ndarray): Parameters ---------- - fill_value : scalar, optional - The value to use for invalid entries (None by default). - If None, the `fill_value` attribute of the array is used instead. + fill_value : array_like, optional + The value to use for invalid entries. Can be scalar or non-scalar. + If non-scalar, the resulting ndarray must be broadcastable over + input array. Default is None, in which case, the `fill_value` + attribute of the array is used instead. Returns ------- @@ -3689,6 +3715,8 @@ class MaskedArray(ndarray): >>> x = np.ma.array([1,2,3,4,5], mask=[0,0,1,0,1], fill_value=-999) >>> x.filled() array([ 1, 2, -999, 4, -999]) + >>> x.filled(fill_value=1000) + array([ 1, 2, 1000, 4, 1000]) >>> type(x.filled()) <class 'numpy.ndarray'> @@ -4389,7 +4417,7 @@ class MaskedArray(ndarray): ---------- axis : None or int or tuple of ints, optional Axis or axes along which the count is performed. - The default (`axis` = `None`) performs the count over all + The default, None, performs the count over all the dimensions of the input array. `axis` may be negative, in which case it counts from the last to the first axis. @@ -4769,7 +4797,7 @@ class MaskedArray(ndarray): See Also -------- - ndarray.all : corresponding function for ndarrays + numpy.ndarray.all : corresponding function for ndarrays numpy.all : equivalent function Examples @@ -4807,7 +4835,7 @@ class MaskedArray(ndarray): See Also -------- - ndarray.any : corresponding function for ndarrays + numpy.ndarray.any : corresponding function for ndarrays numpy.any : equivalent function """ @@ -4861,7 +4889,7 @@ class MaskedArray(ndarray): flatnonzero : Return indices that are non-zero in the flattened version of the input array. - ndarray.nonzero : + numpy.ndarray.nonzero : Equivalent ndarray method. count_nonzero : Counts the number of non-zero elements in the input array. @@ -4989,7 +5017,7 @@ class MaskedArray(ndarray): See Also -------- - ndarray.sum : corresponding function for ndarrays + numpy.ndarray.sum : corresponding function for ndarrays numpy.sum : equivalent function Examples @@ -5036,7 +5064,7 @@ class MaskedArray(ndarray): result = self.filled(0).sum(axis, dtype=dtype, out=out, **kwargs) if isinstance(out, MaskedArray): outmask = getmask(out) - if (outmask is nomask): + if outmask is nomask: outmask = out._mask = make_mask_none(out.shape) outmask.flat = newmask return out @@ -5060,7 +5088,7 @@ class MaskedArray(ndarray): See Also -------- - ndarray.cumsum : corresponding function for ndarrays + numpy.ndarray.cumsum : corresponding function for ndarrays numpy.cumsum : equivalent function Examples @@ -5097,7 +5125,7 @@ class MaskedArray(ndarray): See Also -------- - ndarray.prod : corresponding function for ndarrays + numpy.ndarray.prod : corresponding function for ndarrays numpy.prod : equivalent function """ kwargs = {} if keepdims is np._NoValue else {'keepdims': keepdims} @@ -5118,7 +5146,7 @@ class MaskedArray(ndarray): result = self.filled(1).prod(axis, dtype=dtype, out=out, **kwargs) if isinstance(out, MaskedArray): outmask = getmask(out) - if (outmask is nomask): + if outmask is nomask: outmask = out._mask = make_mask_none(out.shape) outmask.flat = newmask return out @@ -5143,7 +5171,7 @@ class MaskedArray(ndarray): See Also -------- - ndarray.cumprod : corresponding function for ndarrays + numpy.ndarray.cumprod : corresponding function for ndarrays numpy.cumprod : equivalent function """ result = self.filled(1).cumprod(axis=axis, dtype=dtype, out=out) @@ -5166,7 +5194,7 @@ class MaskedArray(ndarray): See Also -------- - ndarray.mean : corresponding function for ndarrays + numpy.ndarray.mean : corresponding function for ndarrays numpy.mean : Equivalent function numpy.ma.average: Weighted average. @@ -5197,7 +5225,7 @@ class MaskedArray(ndarray): out.flat = result if isinstance(out, MaskedArray): outmask = getmask(out) - if (outmask is nomask): + if outmask is nomask: outmask = out._mask = make_mask_none(out.shape) outmask.flat = getmask(result) return out @@ -5239,9 +5267,9 @@ class MaskedArray(ndarray): return m if not axis: - return (self - m) + return self - m else: - return (self - expand_dims(m, axis)) + return self - expand_dims(m, axis) def var(self, axis=None, dtype=None, out=None, ddof=0, keepdims=np._NoValue): @@ -5255,7 +5283,7 @@ class MaskedArray(ndarray): See Also -------- - ndarray.var : corresponding function for ndarrays + numpy.ndarray.var : corresponding function for ndarrays numpy.var : Equivalent function """ kwargs = {} if keepdims is np._NoValue else {'keepdims': keepdims} @@ -5318,7 +5346,7 @@ class MaskedArray(ndarray): See Also -------- - ndarray.std : corresponding function for ndarrays + numpy.ndarray.std : corresponding function for ndarrays numpy.std : Equivalent function """ kwargs = {} if keepdims is np._NoValue else {'keepdims': keepdims} @@ -5339,7 +5367,7 @@ class MaskedArray(ndarray): See Also -------- - ndarray.around : corresponding function for ndarrays + numpy.ndarray.around : corresponding function for ndarrays numpy.around : equivalent function """ result = self._data.round(decimals=decimals, out=out).view(type(self)) @@ -5401,7 +5429,7 @@ class MaskedArray(ndarray): -------- MaskedArray.sort : Describes sorting algorithms used. lexsort : Indirect stable sort with multiple keys. - ndarray.sort : Inplace sort. + numpy.ndarray.sort : Inplace sort. Notes ----- @@ -5553,7 +5581,7 @@ class MaskedArray(ndarray): See Also -------- - ndarray.sort : Method to sort an array in-place. + numpy.ndarray.sort : Method to sort an array in-place. argsort : Indirect sort. lexsort : Indirect stable sort on multiple keys. searchsorted : Find elements in a sorted array. @@ -5616,6 +5644,10 @@ class MaskedArray(ndarray): fill_value : {var}, optional Value used to fill in the masked values. If None, use the output of `minimum_fill_value`. + keepdims : bool, optional + If this is set to True, the axes which are reduced are left + in the result as dimensions with size one. With this option, + the result will broadcast correctly against the array. Returns ------- @@ -5652,7 +5684,7 @@ class MaskedArray(ndarray): result = self.filled(fill_value).min(axis=axis, out=out, **kwargs) if isinstance(out, MaskedArray): outmask = getmask(out) - if (outmask is nomask): + if outmask is nomask: outmask = out._mask = make_mask_none(out.shape) outmask.flat = newmask else: @@ -5746,6 +5778,10 @@ class MaskedArray(ndarray): fill_value : {var}, optional Value used to fill in the masked values. If None, use the output of maximum_fill_value(). + keepdims : bool, optional + If this is set to True, the axes which are reduced are left + in the result as dimensions with size one. With this option, + the result will broadcast correctly against the array. Returns ------- @@ -5782,7 +5818,7 @@ class MaskedArray(ndarray): result = self.filled(fill_value).max(axis=axis, out=out, **kwargs) if isinstance(out, MaskedArray): outmask = getmask(out) - if (outmask is nomask): + if outmask is nomask: outmask = out._mask = make_mask_none(out.shape) outmask.flat = newmask else: @@ -5810,6 +5846,10 @@ class MaskedArray(ndarray): but the type will be cast if necessary. fill_value : {var}, optional Value used to fill in the masked values. + keepdims : bool, optional + If this is set to True, the axes which are reduced are left + in the result as dimensions with size one. With this option, + the result will broadcast correctly against the array. Returns ------- @@ -5961,7 +6001,7 @@ class MaskedArray(ndarray): See Also -------- - ndarray.tobytes + numpy.ndarray.tobytes tolist, tofile Notes @@ -6203,9 +6243,11 @@ class mvoid(MaskedArray): Parameters ---------- - fill_value : scalar, optional - The value to use for invalid entries (None by default). - If None, the `fill_value` attribute is used instead. + fill_value : array_like, optional + The value to use for invalid entries. Can be scalar or + non-scalar. If latter is the case, the filled array should + be broadcastable over input array. Default is None, in + which case the `fill_value` attribute is used instead. Returns ------- @@ -6720,7 +6762,7 @@ def power(a, b, third=None): invalid = np.logical_not(np.isfinite(result.view(ndarray))) # Add the initial mask if m is not nomask: - if not (result.ndim): + if not result.ndim: return masked result._mask = np.logical_or(m, invalid) # Fix the invalid parts @@ -7081,23 +7123,6 @@ def resize(x, new_shape): return result -def rank(obj): - """ - maskedarray version of the numpy function. - - .. note:: - Deprecated since 1.10.0 - - """ - # 2015-04-12, 1.10.0 - warnings.warn( - "`rank` is deprecated; use the `ndim` function instead. ", - np.VisibleDeprecationWarning, stacklevel=2) - return np.ndim(getdata(obj)) - -rank.__doc__ = np.rank.__doc__ - - def ndim(obj): """ maskedarray version of the numpy function. @@ -7280,7 +7305,7 @@ def choose(indices, choices, out=None, mode='raise'): # Construct the mask outputmask = np.choose(c, masks, mode=mode) outputmask = make_mask(mask_or(outputmask, getmask(indices)), - copy=0, shrink=True) + copy=False, shrink=True) # Get the choices. d = np.choose(c, data, mode=mode, out=out).view(MaskedArray) if out is not None: @@ -7532,7 +7557,7 @@ def outer(a, b): return masked_array(d) ma = getmaskarray(a) mb = getmaskarray(b) - m = make_mask(1 - np.outer(1 - ma, 1 - mb), copy=0) + m = make_mask(1 - np.outer(1 - ma, 1 - mb), copy=False) return masked_array(d, mask=m) outer.__doc__ = doc_note(np.outer.__doc__, "Masked values are replaced by 0.") @@ -7886,93 +7911,6 @@ def _pickle_warn(method): stacklevel=3) -def dump(a, F): - """ - Pickle a masked array to a file. - - This is a wrapper around ``cPickle.dump``. - - Parameters - ---------- - a : MaskedArray - The array to be pickled. - F : str or file-like object - The file to pickle `a` to. If a string, the full path to the file. - - """ - _pickle_warn('dump') - if not hasattr(F, 'readline'): - with open(F, 'w') as F: - pickle.dump(a, F) - else: - pickle.dump(a, F) - - -def dumps(a): - """ - Return a string corresponding to the pickling of a masked array. - - This is a wrapper around ``cPickle.dumps``. - - Parameters - ---------- - a : MaskedArray - The array for which the string representation of the pickle is - returned. - - """ - _pickle_warn('dumps') - return pickle.dumps(a) - - -def load(F): - """ - Wrapper around ``cPickle.load`` which accepts either a file-like object - or a filename. - - Parameters - ---------- - F : str or file - The file or file name to load. - - See Also - -------- - dump : Pickle an array - - Notes - ----- - This is different from `numpy.load`, which does not use cPickle but loads - the NumPy binary .npy format. - - """ - _pickle_warn('load') - if not hasattr(F, 'readline'): - with open(F, 'r') as F: - return pickle.load(F) - else: - return pickle.load(F) - - -def loads(strg): - """ - Load a pickle from the current string. - - The result of ``cPickle.loads(strg)`` is returned. - - Parameters - ---------- - strg : str - The string to load. - - See Also - -------- - dumps : Return a string corresponding to the pickling of a masked array. - - """ - _pickle_warn('loads') - return pickle.loads(strg) - - def fromfile(file, dtype=float, count=-1, sep=''): raise NotImplementedError( "fromfile() not yet implemented for a MaskedArray.") |