numpy.polynomial.chebyshev.chebfromroots(roots) [source] Generate a Chebyshev series with given roots. The function returns the coefficients of the polynomial in Chebyshev 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

numpy.polynomial.chebyshev.chebvander(x, deg) [source] Pseudo-Vandermonde matrix of given degree. Returns the pseudo-Vandermonde matrix of degree deg and sample points x. The pseudo-Vandermonde matrix is defined by where 0 <= i <= deg. The leading indices of V index the elements of x and the last index is the degree of the Chebyshev polynomial. If c is a 1-D array of coefficients of length n + 1 and V is the matrix V = chebvander(x, n), then np.dot(V, c) and chebval(x, c) are the s

numpy.polynomial.chebyshev.poly2cheb(pol) [source] Convert a polynomial to a Chebyshev series. Convert an array representing the coefficients of a polynomial (relative to the ?standard? basis) ordered from lowest degree to highest, to an array of the coefficients of the equivalent Chebyshev series, ordered from lowest to highest degree. Parameters: pol : array_like 1-D array containing the polynomial coefficients Returns: c : ndarray 1-D array containing the coefficients of the equiva

See also Array creation Ones and zeros empty(shape[, dtype, order]) Return a new array of given shape and type, without initializing entries. empty_like(a[, dtype, order, subok]) Return a new array with the same shape and type as a given array. eye(N[, M, k, dtype]) Return a 2-D array with ones on the diagonal and zeros elsewhere. identity(n[, dtype]) Return the identity array. ones(shape[, dtype, order]) Return a new array of given shape and type, filled with ones. ones_like(a[, dtyp

numpy.isfinite(x[, out]) = Test element-wise for finiteness (not infinity or not Not a Number). The result is returned as a boolean array. Parameters: x : array_like Input values. out : ndarray, optional Array into which the output is placed. Its type is preserved and it must be of the right shape to hold the output. See doc.ufuncs. Returns: y : ndarray, bool For scalar input, the result is a new boolean with value True if the input is finite; otherwise the value is False (input is

numpy.polynomial.hermite.hermweight(x) [source] Weight function of the Hermite polynomials. The weight function is and the interval of integration is . the Hermite polynomials are orthogonal, but not normalized, with respect to this weight function. Parameters: x : array_like Values at which the weight function will be computed. Returns: w : ndarray The weight function at x. Notes

numpy.core.defchararray.count(a, sub, start=0, end=None) [source] Returns an array with the number of non-overlapping occurrences of substring sub in the range [start, end]. Calls str.count element-wise. Parameters: a : array_like of str or unicode sub : str or unicode The substring to search for. start, end : int, optional Optional arguments start and end are interpreted as slice notation to specify the range in which to count. Returns: out : ndarray Output array of ints. See al

numpy.bitwise_xor(x1, x2[, out]) = Compute the bit-wise XOR of two arrays element-wise. Computes the bit-wise XOR of the underlying binary representation of the integers in the input arrays. This ufunc implements the C/Python operator ^. Parameters: x1, x2 : array_like Only integer and boolean types are handled. Returns: out : array_like Result. See also logical_xor, bitwise_and, bitwise_or binary_repr Return the binary representation of the input number as a string. Examples

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

generic.ndim number of array dimensions