numpy.isfortran(a) [source] Returns True if the array is Fortran contiguous but not C contiguous. This function is obsolete and, because of changes due to relaxed stride checking, its return value for the same array may differ for versions of Numpy >= 1.10 and previous versions. If you only want to check if an array is Fortran contiguous use a.flags.f_contiguous instead. Parameters: a : ndarray Input array. Examples np.array allows to specify whether the array is written in C-contigu

ndarray.clip(min=None, max=None, out=None) Return an array whose values are limited to [min, max]. One of max or min must be given. Refer to numpy.clip for full documentation. See also numpy.clip equivalent function

numpy.reshape(a, newshape, order='C') [source] Gives a new shape to an array without changing its data. Parameters: a : array_like Array to be reshaped. newshape : int or tuple of ints The new shape should be compatible with the original shape. If an integer, then the result will be a 1-D array of that length. One shape dimension can be -1. In this case, the value is inferred from the length of the array and remaining dimensions. order : {?C?, ?F?, ?A?}, optional Read the elements of

recarray.take(indices, axis=None, out=None, mode='raise') Return an array formed from the elements of a at the given indices. Refer to numpy.take for full documentation. See also numpy.take equivalent function

recarray.conjugate() Return the complex conjugate, element-wise. Refer to numpy.conjugate for full documentation. See also numpy.conjugate equivalent function

ndarray.conj() Complex-conjugate all elements. Refer to numpy.conjugate for full documentation. See also numpy.conjugate equivalent function

numpy.polynomial.hermite.hermvander2d(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 Hermite polynomials. If V = hermvander2d(x, y, [xdeg, ydeg]), then the columns of V correspond to the elements of a

matrix.choose(choices, out=None, mode='raise') Use an index array to construct a new array from a set of choices. Refer to numpy.choose for full documentation. See also numpy.choose equivalent function

numpy.polynomial.legendre.legfromroots(roots) [source] Generate a Legendre series with given roots. The function returns the coefficients of the polynomial in Legendre form, where the r_n are the roots specified in roots. If a zero has multiplicity n, then it must appear in roots n times. For instance, if 2 is a root of multiplicity three and 3 is a root of multiplicity 2, then roots looks something like [2, 2, 2, 3, 3]. The roots can appear in any order. If the returned coefficients are

numpy.polynomial.chebyshev.chebmulx(c) [source] Multiply a Chebyshev series by x. Multiply the polynomial c by x, where x is the independent variable. Parameters: c : array_like 1-D array of Chebyshev series coefficients ordered from low to high. Returns: out : ndarray Array representing the result of the multiplication. Notes New in version 1.5.0.