numpy.polynomial.laguerre.lagcompanion(c) [source] Return the companion matrix of c. The usual companion matrix of the Laguerre polynomials is already symmetric when c is a basis Laguerre polynomial, so no scaling is applied. Parameters: c : array_like 1-D array of Laguerre series coefficients ordered from low to high degree. Returns: mat : ndarray Companion matrix of dimensions (deg, deg). Notes

matrix.argmin(axis=None, out=None) [source] Indexes of the minimum values along an axis. Return the indexes of the first occurrences of the minimum values along the specified axis. If axis is None, the index is for the flattened matrix. Parameters: See `numpy.argmin` for complete descriptions. See also numpy.argmin Notes This is the same as ndarray.argmin, but returns a matrix object where ndarray.argmin would return an ndarray. Examples >>> x = -np.matrix(np.arange(12).reshape((

numpy.polynomial.laguerre.lagx = array([ 1, -1])

numpy.less(x1, x2[, out]) = Return the truth value of (x1 < x2) element-wise. Parameters: x1, x2 : array_like Input arrays. If x1.shape != x2.shape, they must be broadcastable to a common shape (which may be the shape of one or the other). Returns: out : bool or ndarray of bool Array of bools, or a single bool if x1 and x2 are scalars. See also greater, less_equal, greater_equal, equal, not_equal Examples >>> np.less([1, 2], [2, 2]) array([ True, False], dtype=bool)

classmethod Hermite.fromroots(roots, domain=[], window=None) [source] Return series instance that has the specified roots. Returns a series representing the product (x - r[0])*(x - r[1])*...*(x - r[n-1]), where r is a list of roots. Parameters: roots : array_like List of roots. domain : {[], None, array_like}, optional Domain for the resulting series. If None the domain is the interval from the smallest root to the largest. If [] the domain is the class domain. The default is []. windo

ndarray.put(indices, values, mode='raise') Set a.flat[n] = values[n] for all n in indices. Refer to numpy.put for full documentation. See also numpy.put equivalent function

recarray.dtype Data-type of the array?s elements. Parameters: None Returns: d : numpy dtype object See also numpy.dtype Examples >>> x array([[0, 1], [2, 3]]) >>> x.dtype dtype('int32') >>> type(x.dtype) <type 'numpy.dtype'>

classmethod HermiteE.cast(series, domain=None, window=None) [source] Convert series to series of this class. The series is expected to be an instance of some polynomial series of one of the types supported by by the numpy.polynomial module, but could be some other class that supports the convert method. New in version 1.7.0. Parameters: series : series The series instance to be converted. domain : {None, array_like}, optional If given, the array must be of the form [beg, end], where b

numpy.nanargmin(a, axis=None) [source] Return the indices of the minimum values in the specified axis ignoring NaNs. For all-NaN slices ValueError is raised. Warning: the results cannot be trusted if a slice contains only NaNs and Infs. Parameters: a : array_like Input data. axis : int, optional Axis along which to operate. By default flattened input is used. Returns: index_array : ndarray An array of indices or a single index value. See also argmin, nanargmax Examples >>&

numpy.polynomial.legendre.leg2poly(c) [source] Convert a Legendre series to a polynomial. Convert an array representing the coefficients of a Legendre series, ordered from lowest degree to highest, to an array of the coefficients of the equivalent polynomial (relative to the ?standard? basis) ordered from lowest to highest degree. Parameters: c : array_like 1-D array containing the Legendre series coefficients, ordered from lowest order term to highest. Returns: pol : ndarray 1-D arra