MaskedArray.resize(newshape, refcheck=True, order=False) [source] Warning This method does nothing, except raise a ValueError exception. A masked array does not own its data and therefore cannot safely be resized in place. Use the numpy.ma.resize function instead. This method is difficult to implement safely and may be deprecated in future releases of NumPy.

MaskedArray.reshape(*s, **kwargs) [source] Give a new shape to the array without changing its data. Returns a masked array containing the same data, but with a new shape. The result is a view on the original array; if this is not possible, a ValueError is raised. Parameters: shape : int or tuple of ints The new shape should be compatible with the original shape. If an integer is supplied, then the result will be a 1-D array of that length. order : {?C?, ?F?}, optional Determines whether

MaskedArray.repeat(repeats, axis=None) [source] Repeat elements of an array. Refer to numpy.repeat for full documentation. See also numpy.repeat equivalent function

MaskedArray.recordmask Return the mask of the records. A record is masked when all the fields are masked.

MaskedArray.real Real part

MaskedArray.ravel(order='C') [source] Returns a 1D version of self, as a view. Parameters: order : {?C?, ?F?, ?A?, ?K?}, optional The elements of a are read using this index order. ?C? means to index the elements in C-like order, with the last axis index changing fastest, back to the first axis index changing slowest. ?F? means to index the elements in Fortran-like index order, with the first index changing fastest, and the last index changing slowest. Note that the ?C? and ?F? options ta

MaskedArray.put(indices, values, mode='raise') [source] Set storage-indexed locations to corresponding values. Sets self._data.flat[n] = values[n] for each n in indices. If values is shorter than indices then it will repeat. If values has some masked values, the initial mask is updated in consequence, else the corresponding values are unmasked. Parameters: indices : 1-D array_like Target indices, interpreted as integers. values : array_like Values to place in self._data copy at target i

MaskedArray.ptp(axis=None, out=None, fill_value=None) [source] Return (maximum - minimum) along the the given dimension (i.e. peak-to-peak value). Parameters: axis : {None, int}, optional Axis along which to find the peaks. If None (default) the flattened array is used. out : {None, array_like}, optional Alternative output array in which to place the result. It must have the same shape and buffer length as the expected output but the type will be cast if necessary. fill_value : {var},

MaskedArray.product(axis=None, dtype=None, out=None) [source] Return the product of the array elements over the given axis. Masked elements are set to 1 internally for computation. Parameters: axis : {None, int}, optional Axis over which the product is taken. If None is used, then the product is over all the array elements. dtype : {None, dtype}, optional Determines the type of the returned array and of the accumulator where the elements are multiplied. If dtype has the value None and t

MaskedArray.prod(axis=None, dtype=None, out=None) [source] Return the product of the array elements over the given axis. Masked elements are set to 1 internally for computation. Parameters: axis : {None, int}, optional Axis over which the product is taken. If None is used, then the product is over all the array elements. dtype : {None, dtype}, optional Determines the type of the returned array and of the accumulator where the elements are multiplied. If dtype has the value None and the