numpy.polynomial.polynomial.polydiv()

numpy.polynomial.polynomial.polydiv(c1, c2) [source] Divide one polynomial by another. Returns the quotient-with-remainder of two polynomials c1 / c2. The arguments are sequences of coefficients, from lowest order term to highest, e.g., [1,2,3] represents 1 + 2*x + 3*x**2. Parameters: c1, c2 : array_like 1-D arrays of polynomial coefficients ordered from low to high. Returns: [quo, rem] : ndarrays Of coefficient series representing the quotient and remainder. See also polyadd, poly

numpy.polynomial.polynomial.polyvander()

numpy.polynomial.polynomial.polyvander(x, deg) [source] Vandermonde matrix of given degree. Returns the Vandermonde matrix of degree deg and sample points x. The Vandermonde matrix is defined by where 0 <= i <= deg. The leading indices of V index the elements of x and the last index is the power of x. If c is a 1-D array of coefficients of length n + 1 and V is the matrix V = polyvander(x, n), then np.dot(V, c) and polyval(x, c) are the same up to roundoff. This equivalence is usef

numpy.arccosh()

numpy.arccosh(x[, out]) = Inverse hyperbolic cosine, element-wise. Parameters: x : array_like Input array. out : ndarray, optional Array of the same shape as x, to store results in. See doc.ufuncs (Section ?Output arguments?) for details. Returns: arccosh : ndarray Array of the same shape as x. See also cosh, arcsinh, sinh, arctanh, tanh Notes arccosh is a multivalued function: for each x there are infinitely many numbers z such that cosh(z) = x. The convention is to return the

numpy.ones_like()

numpy.ones_like(a, dtype=None, order='K', subok=True) [source] Return an array of ones with the same shape and type as a given array. Parameters: a : array_like The shape and data-type of a define these same attributes of the returned array. dtype : data-type, optional Overrides the data type of the result. New in version 1.6.0. order : {?C?, ?F?, ?A?, or ?K?}, optional Overrides the memory layout of the result. ?C? means C-order, ?F? means F-order, ?A? means ?F? if a is Fortran con

recarray.sort()

recarray.sort(axis=-1, kind='quicksort', order=None) Sort an array, in-place. Parameters: axis : int, optional Axis along which to sort. Default is -1, which means sort along the last axis. kind : {?quicksort?, ?mergesort?, ?heapsort?}, optional Sorting algorithm. Default is ?quicksort?. order : str or list of str, optional When a is an array with fields defined, this argument specifies which fields to compare first, second, etc. A single field can be specified as a string, and not al

HermiteE.basis()

classmethod HermiteE.basis(deg, domain=None, window=None) [source] Series basis polynomial of degree deg. Returns the series representing the basis polynomial of degree deg. New in version 1.7.0. Parameters: deg : int Degree of the basis polynomial for the series. Must be >= 0. 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 Non

Hermite.integ()

Hermite.integ(m=1, k=[], lbnd=None) [source] Integrate. Return a series instance that is the definite integral of the current series. Parameters: m : non-negative int The number of integrations to perform. k : array_like Integration constants. The first constant is applied to the first integration, the second to the second, and so on. The list of values must less than or equal to m in length and any missing values are set to zero. lbnd : Scalar The lower bound of the definite integral

HermiteE.trim()

HermiteE.trim(tol=0) [source] Remove trailing coefficients Remove trailing coefficients until a coefficient is reached whose absolute value greater than tol or the beginning of the series is reached. If all the coefficients would be removed the series is set to [0]. A new series instance is returned with the new coefficients. The current instance remains unchanged. Parameters: tol : non-negative number. All trailing coefficients less than tol will be removed. Returns: new_series : seri

numpy.minimum()

numpy.minimum(x1, x2[, out]) = Element-wise minimum of array elements. Compare two arrays and returns a new array containing the element-wise minima. If one of the elements being compared is a NaN, then that element is returned. If both elements are NaNs then the first is returned. The latter distinction is important for complex NaNs, which are defined as at least one of the real or imaginary parts being a NaN. The net effect is that NaNs are propagated. Parameters: x1, x2 : array_like T

Hermite.deriv()

Hermite.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.