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

numpy.polynomial.laguerre.poly2lag(pol) [source] Convert a polynomial to a Laguerre 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 Laguerre 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 equivalent

New in version 1.4.0. Using the Convenience ClassesBasics Calculus Other Polynomial Constructors Fitting Polynomial Module (numpy.polynomial.polynomial)Polynomial Class Basics Fitting Calculus Algebra Miscellaneous Chebyshev Module (numpy.polynomial.chebyshev)Chebyshev Class Basics Fitting Calculus Algebra Quadrature Miscellaneous Legendre Module (numpy.polynomial.legendre)Legendre Class Basics Fitting Calculus Algebra Quadrature Miscellaneous Laguerre Module (numpy.polynomial.lagu

MaskedArray.product(axis=None, dtype=None, out=None) [source] Return the product of the array elements over the given axis. Masked elements are set to 1 internally for computation. Parameters: axis : {None, int}, optional Axis over which the product is taken. If None is used, then the product is over all the array elements. dtype : {None, dtype}, optional Determines the type of the returned array and of the accumulator where the elements are multiplied. If dtype has the value None and t

Simple random data rand(d0, d1, ..., dn) Random values in a given shape. randn(d0, d1, ..., dn) Return a sample (or samples) from the ?standard normal? distribution. randint(low[, high, size, dtype]) Return random integers from low (inclusive) to high (exclusive). random_integers(low[, high, size]) Random integers of type np.int between low and high, inclusive. random_sample([size]) Return random floats in the half-open interval [0.0, 1.0). random([size]) Return random floats in the hal

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.polynomial.polynomial.polycompanion(c) [source] Return the companion matrix of c. The companion matrix for power series cannot be made symmetric by scaling the basis, so this function differs from those for the orthogonal polynomials. Parameters: c : array_like 1-D array of polynomial coefficients ordered from low to high degree. Returns: mat : ndarray Companion matrix of dimensions (deg, deg). Notes New in version 1.7.0.

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

ndarray.byteswap(inplace) Swap the bytes of the array elements Toggle between low-endian and big-endian data representation by returning a byteswapped array, optionally swapped in-place. Parameters: inplace : bool, optional If True, swap bytes in-place, default is False. Returns: out : ndarray The byteswapped array. If inplace is True, this is a view to self. Examples >>> A = np.array([1, 256, 8755], dtype=np.int16) >>> map(hex, A) ['0x1', '0x100', '0x2233'] >&g

recarray.all(axis=None, out=None, keepdims=False) Returns True if all elements evaluate to True. Refer to numpy.all for full documentation. See also numpy.all equivalent function