numpy.swapaxes(a, axis1, axis2) [source] Interchange two axes of an array. Parameters: a : array_like Input array. axis1 : int First axis. axis2 : int Second axis. Returns: a_swapped : ndarray For Numpy >= 1.10, if a is an ndarray, then a view of a is returned; otherwise a new array is created. For earlier Numpy versions a view of a is returned only if the order of the axes is changed, otherwise the input array is returned. Examples >>> x = np.array([[1,2,3]]) >&g

numpy.ma.max(obj, axis=None, out=None, fill_value=None) [source] Return the maximum along a given axis. Parameters: axis : {None, int}, optional Axis along which to operate. By default, axis is None and the flattened input is used. out : array_like, optional Alternative output array in which to place the result. Must be of the same shape and buffer length as the expected output. fill_value : {var}, optional Value used to fill in the masked values. If None, use the output of maximum_fi

classmethod Legendre.identity(domain=None, window=None) [source] Identity function. If p is the returned series, then p(x) == x for all values of x. Parameters: domain : {None, array_like}, optional If given, the array must be of the form [beg, end], where beg and end are the endpoints of the domain. If None is given then the class domain is used. The default is None. window : {None, array_like}, optional If given, the resulting array must be if the form [beg, end], where beg and end ar

numpy.ma.min(obj, axis=None, out=None, fill_value=None) [source] Return the minimum along a given axis. Parameters: axis : {None, int}, optional Axis along which to operate. By default, axis is None and the flattened input is used. out : array_like, optional Alternative output array in which to place the result. Must be of the same shape and buffer length as the expected output. fill_value : {var}, optional Value used to fill in the masked values. If None, use the output of minimum_fi

MaskedArray.__setslice__(i, j, value) [source] x.__setslice__(i, j, value) <==> x[i:j]=value Set the slice (i,j) of a to value. If value is masked, mask those locations.

record.itemsize length of one element in bytes

numpy.polynomial.chebyshev.chebdiv(c1, c2) [source] Divide one Chebyshev series by another. Returns the quotient-with-remainder of two Chebyshev series c1 / c2. The arguments are sequences of coefficients from lowest order ?term? to highest, e.g., [1,2,3] represents the series T_0 + 2*T_1 + 3*T_2. Parameters: c1, c2 : array_like 1-D arrays of Chebyshev series coefficients ordered from low to high. Returns: [quo, rem] : ndarrays Of Chebyshev series coefficients representing the quotien

chararray.tofile(fid, sep="", format="%s") Write array to a file as text or binary (default). Data is always written in ?C? order, independent of the order of a. The data produced by this method can be recovered using the function fromfile(). Parameters: fid : file or str An open file object, or a string containing a filename. sep : str Separator between array items for text output. If ?? (empty), a binary file is written, equivalent to file.write(a.tobytes()). format : str Format str

MaskedArray.iscontiguous() [source] Return a boolean indicating whether the data is contiguous. Parameters: None Examples >>> x = np.ma.array([1, 2, 3]) >>> x.iscontiguous() True iscontiguous returns one of the flags of the masked array: >>> x.flags C_CONTIGUOUS : True F_CONTIGUOUS : True OWNDATA : False WRITEABLE : True ALIGNED : True UPDATEIFCOPY : False

MaskedArray.compress(condition, axis=None, out=None) [source] Return a where condition is True. If condition is a MaskedArray, missing values are considered as False. Parameters: condition : var Boolean 1-d array selecting which entries to return. If len(condition) is less than the size of a along the axis, then output is truncated to length of condition array. axis : {None, int}, optional Axis along which the operation must be performed. out : {None, ndarray}, optional Alternative ou