ndarray.prod(axis=None, dtype=None, out=None, keepdims=False) Return the product of the array elements over the given axis Refer to numpy.prod for full documentation. See also numpy.prod equivalent function

numpy.polynomial.laguerre.lagadd(c1, c2) [source] Add one Laguerre series to another. Returns the sum of two Laguerre series c1 + c2. The arguments are sequences of coefficients ordered from lowest order term to highest, i.e., [1,2,3] represents the series P_0 + 2*P_1 + 3*P_2. Parameters: c1, c2 : array_like 1-D arrays of Laguerre series coefficients ordered from low to high. Returns: out : ndarray Array representing the Laguerre series of their sum. See also lagsub, lagmul, lagdiv

numpy.core.defchararray.splitlines(a, keepends=None) [source] For each element in a, return a list of the lines in the element, breaking at line boundaries. Calls str.splitlines element-wise. Parameters: a : array_like of str or unicode keepends : bool, optional Line breaks are not included in the resulting list unless keepends is given and true. Returns: out : ndarray Array of list objects See also str.splitlines

numpy.ma.diag(v, k=0) [source] Extract a diagonal or construct a diagonal array. This function is the equivalent of numpy.diag that takes masked values into account, see numpy.diag for details. See also numpy.diag Equivalent function for ndarrays.

numpy.polynomial.laguerre.lagvander2d(x, y, deg) [source] Pseudo-Vandermonde matrix of given degrees. Returns the pseudo-Vandermonde matrix of degrees deg and sample points (x, y). The pseudo-Vandermonde matrix is defined by where 0 <= i <= deg[0] and 0 <= j <= deg[1]. The leading indices of V index the points (x, y) and the last index encodes the degrees of the Laguerre polynomials. If V = lagvander2d(x, y, [xdeg, ydeg]), then the columns of V correspond to the elements of a

flatiter.next x.next() -> the next value, or raise StopIteration

numpy.set_string_function(f, repr=True) [source] Set a Python function to be used when pretty printing arrays. Parameters: f : function or None Function to be used to pretty print arrays. The function should expect a single array argument and return a string of the representation of the array. If None, the function is reset to the default NumPy function to print arrays. repr : bool, optional If True (default), the function for pretty printing (__repr__) is set, if False the function tha

ndarray.sort(axis=-1, kind='quicksort', order=None) Sort an array, in-place. Parameters: axis : int, optional Axis along which to sort. Default is -1, which means sort along the last axis. kind : {?quicksort?, ?mergesort?, ?heapsort?}, optional Sorting algorithm. Default is ?quicksort?. order : str or list of str, optional When a is an array with fields defined, this argument specifies which fields to compare first, second, etc. A single field can be specified as a string, and not all

numpy.left_shift(x1, x2[, out]) = Shift the bits of an integer to the left. Bits are shifted to the left by appending x2 0s at the right of x1. Since the internal representation of numbers is in binary format, this operation is equivalent to multiplying x1 by 2**x2. Parameters: x1 : array_like of integer type Input values. x2 : array_like of integer type Number of zeros to append to x1. Has to be non-negative. Returns: out : array of integer type Return x1 with bits shifted x2 time

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