numpy.ma.asanyarray(a, dtype=None) [source] Convert the input to a masked array, conserving subclasses. If a is a subclass of MaskedArray, its class is conserved. No copy is performed if the input is already an ndarray. Parameters: a : array_like Input data, in any form that can be converted to an array. dtype : dtype, optional By default, the data-type is inferred from the input data. order : {?C?, ?F?}, optional Whether to use row-major (?C?) or column-major (?FORTRAN?) memory repre

numpy.ma.array(data, dtype=None, copy=False, order=None, mask=False, fill_value=None, keep_mask=True, hard_mask=False, shrink=True, subok=True, ndmin=0) [source] An array class with possibly masked values. Masked values of True exclude the corresponding element from any computation. Construction: x = MaskedArray(data, mask=nomask, dtype=None, copy=False, subok=True, ndmin=0, fill_value=None, keep_mask=True, hard_mask=None, shrink=True, order=None) Parameters

numpy.ma.around = Round an array to the given number of decimals. Refer to around for full documentation. See also around equivalent function

numpy.ma.argsort(a, axis=None, kind='quicksort', order=None, fill_value=None) [source] Return an ndarray of indices that sort the array along the specified axis. Masked values are filled beforehand to fill_value. Parameters: axis : int, optional Axis along which to sort. The default is -1 (last axis). If None, the flattened array is used. fill_value : var, optional Value used to fill the array before sorting. The default is the fill_value attribute of the input array. kind : {?quicksor

numpy.ma.argmin(a, axis=None, fill_value=None) [source] Return array of indices to the minimum values along the given axis. Parameters: axis : {None, integer} If None, the index is into the flattened array, otherwise along the specified axis fill_value : {var}, optional Value used to fill in the masked values. If None, the output of minimum_fill_value(self._data) is used instead. out : {None, array}, optional Array into which the result can be placed. Its type is preserved and it must

numpy.ma.argmax(a, axis=None, fill_value=None) [source] Returns array of indices of the maximum values along the given axis. Masked values are treated as if they had the value fill_value. Parameters: axis : {None, integer} If None, the index is into the flattened array, otherwise along the specified axis fill_value : {var}, optional Value used to fill in the masked values. If None, the output of maximum_fill_value(self._data) is used instead. out : {None, array}, optional Array into w

numpy.ma.arange([start, ]stop, [step, ]dtype=None) = Return evenly spaced values within a given interval. Values are generated within the half-open interval [start, stop) (in other words, the interval including start but excluding stop). For integer arguments the function is equivalent to the Python built-in range function, but returns an ndarray rather than a list. When using a non-integer step, such as 0.1, the results will often not be consistent. It is better to use linspace for these

numpy.ma.apply_along_axis(func1d, axis, arr, *args, **kwargs) [source] Apply a function to 1-D slices along the given axis. Execute func1d(a, *args) where func1d operates on 1-D arrays and a is a 1-D slice of arr along axis. Parameters: func1d : function This function should accept 1-D arrays. It is applied to 1-D slices of arr along the specified axis. axis : integer Axis along which arr is sliced. arr : ndarray Input array. args : any Additional arguments to func1d. kwargs: any

numpy.ma.append(a, b, axis=None) [source] Append values to the end of an array. New in version 1.9.0. Parameters: a : array_like Values are appended to a copy of this array. b : array_like These values are appended to a copy of a. It must be of the correct shape (the same shape as a, excluding axis). If axis is not specified, b can be any shape and will be flattened before use. axis : int, optional The axis along which v are appended. If axis is not given, both a and b are flattened

numpy.ma.any(self, axis=None, out=None) = Check if any of the elements of a are true. Performs a logical_or over the given axis and returns the result. Masked values are considered as False during computation. Parameters: axis : {None, integer} Axis to perform the operation over. If None, perform over flattened array and return a scalar. out : {None, array}, optional Array into which the result can be placed. Its type is preserved and it must be of the right shape to hold the output.