numpy.polynomial.chebyshev.chebval(x, c, tensor=True) [source] Evaluate a Chebyshev series at points x. If c is of length n + 1, this function returns the value: The parameter x is converted to an array only if it is a tuple or a list, otherwise it is treated as a scalar. In either case, either x or its elements must support multiplication and addition both with themselves and with the elements of c. If c is a 1-D array, then p(x) will have the same shape as x. If c is multidimensional,

ndarray.__array_wrap__(obj) ? Object of same type as ndarray object a.

nditer.remove_axis(i) Removes axis i from the iterator. Requires that the flag ?multi_index? be enabled.

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.linalg.cholesky(a) [source] Cholesky decomposition. Return the Cholesky decomposition, L * L.H, of the square matrix a, where L is lower-triangular and .H is the conjugate transpose operator (which is the ordinary transpose if a is real-valued). a must be Hermitian (symmetric if real-valued) and positive-definite. Only L is actually returned. Parameters: a : (..., M, M) array_like Hermitian (symmetric if all elements are real), positive-definite input matrix. Returns: L : (..., M

numpy.core.defchararray.center(a, width, fillchar=' ') [source] Return a copy of a with its elements centered in a string of length width. Calls str.center element-wise. Parameters: a : array_like of str or unicode width : int The length of the resulting strings fillchar : str or unicode, optional The padding character to use (default is space). Returns: out : ndarray Output array of str or unicode, depending on input types See also str.center

ndarray.argmin(axis=None, out=None) Return indices of the minimum values along the given axis of a. Refer to numpy.argmin for detailed documentation. See also numpy.argmin equivalent function

The iterator object nditer, introduced in NumPy 1.6, provides many flexible ways to visit all the elements of one or more arrays in a systematic fashion. This page introduces some basic ways to use the object for computations on arrays in Python, then concludes with how one can accelerate the inner loop in Cython. Since the Python exposure of nditer is a relatively straightforward mapping of the C array iterator API, these ideas will also provide help working with array iteration from C or C++

numpy.polynomial.hermite.hermline(off, scl) [source] Hermite series whose graph is a straight line. Parameters: off, scl : scalars The specified line is given by off + scl*x. Returns: y : ndarray This module?s representation of the Hermite series for off + scl*x. See also polyline, chebline Examples >>> from numpy.polynomial.hermite import hermline, hermval >>> hermval(0,hermline(3, 2)) 3.0 >>> hermval(1,hermline(3, 2)) 5.0

matrix.all(axis=None, out=None) [source] Test whether all matrix elements along a given axis evaluate to True. Parameters: See `numpy.all` for complete descriptions See also numpy.all Notes This is the same as ndarray.all, but it returns a matrix object. Examples >>> x = np.matrix(np.arange(12).reshape((3,4))); x matrix([[ 0, 1, 2, 3], [ 4, 5, 6, 7], [ 8, 9, 10, 11]]) >>> y = x[0]; y matrix([[0, 1, 2, 3]]) >>> (x == y) matrix([[ True, Tru