numpy.polynomial.laguerre.lagline(off, scl) [source] Laguerre 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 Laguerre series for off + scl*x. See also polyline, chebline Examples >>> from numpy.polynomial.laguerre import lagline, lagval >>> lagval(0,lagline(3, 2)) 3.0 >>> lagval(1,lagline(3, 2)) 5.0

numpy.core.defchararray.startswith(a, prefix, start=0, end=None) [source] Returns a boolean array which is True where the string element in a starts with prefix, otherwise False. Calls str.startswith element-wise. Parameters: a : array_like of str or unicode prefix : str start, end : int, optional With optional start, test beginning at that position. With optional end, stop comparing at that position. Returns: out : ndarray Array of booleans See also str.startswith

numpy.matlib.ones(shape, dtype=None, order='C') [source] Matrix of ones. Return a matrix of given shape and type, filled with ones. Parameters: shape : {sequence of ints, int} Shape of the matrix dtype : data-type, optional The desired data-type for the matrix, default is np.float64. order : {?C?, ?F?}, optional Whether to store matrix in C- or Fortran-contiguous order, default is ?C?. Returns: out : matrix Matrix of ones of given shape, dtype, and order. See also ones Array

Legendre.has_samecoef(other) [source] Check if coefficients match. New in version 1.6.0. Parameters: other : class instance The other class must have the coef attribute. Returns: bool : boolean True if the coefficients are the same, False otherwise.

Legendre.has_sametype(other) [source] Check if types match. New in version 1.7.0. Parameters: other : object Class instance. Returns: bool : boolean True if other is same class as self

Legendre.has_samewindow(other) [source] Check if windows match. New in version 1.6.0. Parameters: other : class instance The other class must have the window attribute. Returns: bool : boolean True if the windows are the same, False otherwise.

HermiteE.deriv(m=1) [source] Differentiate. Return a series instance of that is the derivative of the current series. Parameters: m : non-negative int Find the derivative of order m. Returns: new_series : series A new series representing the derivative. The domain is the same as the domain of the differentiated series.

classmethod Hermite.identity(domain=None, window=None) [source] Identity function. If p is the returned series, then p(x) == x for all values of x. Parameters: domain : {None, array_like}, optional If given, the array must be of the form [beg, end], where beg and end are the endpoints of the domain. If None is given then the class domain is used. The default is None. window : {None, array_like}, optional If given, the resulting array must be if the form [beg, end], where beg and end are

numpy.bitwise_or(x1, x2[, out]) = Compute the bit-wise OR of two arrays element-wise. Computes the bit-wise OR 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. 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: out : array_

numpy.matlib.zeros(shape, dtype=None, order='C') [source] Return a matrix of given shape and type, filled with zeros. Parameters: shape : int or sequence of ints Shape of the matrix dtype : data-type, optional The desired data-type for the matrix, default is float. order : {?C?, ?F?}, optional Whether to store the result in C- or Fortran-contiguous order, default is ?C?. Returns: out : matrix Zero matrix of given shape, dtype, and order. See also numpy.zeros Equivalent array