RandomState.rand(d0, d1, ..., dn) Random values in a given shape. Create an array of the given shape and populate it with random samples from a uniform distribution over [0, 1). Parameters: d0, d1, ..., dn : int, optional The dimensions of the returned array, should all be positive. If no argument is given a single Python float is returned. Returns: out : ndarray, shape (d0, d1, ..., dn) Random values. See also random Notes This is a convenience function. If you want an interface

numpy.can_cast(from, totype, casting = 'safe') Returns True if cast between data types can occur according to the casting rule. If from is a scalar or array scalar, also returns True if the scalar value can be cast without overflow or truncation to an integer. Parameters: from : dtype, dtype specifier, scalar, or array Data type, scalar, or array to cast from. totype : dtype or dtype specifier Data type to cast to. casting : {?no?, ?equiv?, ?safe?, ?same_kind?, ?unsafe?}, optional Con

Laguerre.convert(domain=None, kind=None, window=None) [source] Convert series to a different kind and/or domain and/or window. Parameters: domain : array_like, optional The domain of the converted series. If the value is None, the default domain of kind is used. kind : class, optional The polynomial series type class to which the current instance should be converted. If kind is None, then the class of the current instance is used. window : array_like, optional The window of the conver

numpy.isposinf(x, y=None) [source] Test element-wise for positive infinity, return result as bool array. Parameters: x : array_like The input array. y : array_like, optional A boolean array with the same shape as x to store the result. Returns: y : ndarray A boolean array with the same dimensions as the input. If second argument is not supplied then a boolean array is returned with values True where the corresponding element of the input is positive infinity and values False where t

numpy.matlib.repmat(a, m, n) [source] Repeat a 0-D to 2-D array or matrix MxN times. Parameters: a : array_like The array or matrix to be repeated. m, n : int The number of times a is repeated along the first and second axes. Returns: out : ndarray The result of repeating a. Examples >>> import numpy.matlib >>> a0 = np.array(1) >>> np.matlib.repmat(a0, 2, 3) array([[1, 1, 1], [1, 1, 1]]) >>> a1 = np.arange(4) >>> np.matlib.repma

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

numpy.random.wald(mean, scale, size=None) Draw samples from a Wald, or inverse Gaussian, distribution. As the scale approaches infinity, the distribution becomes more like a Gaussian. Some references claim that the Wald is an inverse Gaussian with mean equal to 1, but this is by no means universal. The inverse Gaussian distribution was first studied in relationship to Brownian motion. In 1956 M.C.K. Tweedie used the name inverse Gaussian because there is an inverse relationship between the

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