numpy.polynomial.polynomial.polyint
- 
numpy.polynomial.polynomial.polyint(c, m=1, k=[], lbnd=0, scl=1, axis=0)[source]
- 
Integrate a polynomial. Returns the polynomial coefficients cintegratedmtimes fromlbndalongaxis. At each iteration the resulting series is multiplied byscland an integration constant,k, is added. The scaling factor is for use in a linear change of variable. (“Buyer beware”: note that, depending on what one is doing, one may wantsclto be the reciprocal of what one might expect; for more information, see the Notes section below.) The argumentcis an array of coefficients, from low to high degree along each axis, e.g., [1,2,3] represents the polynomial1 + 2*x + 3*x**2while [[1,2],[1,2]] represents1 + 1*x + 2*y + 2*x*yif axis=0 isxand axis=1 isy.Parameters: c : array_like 1-D array of polynomial coefficients, ordered from low to high. m : int, optional Order of integration, must be positive. (Default: 1) k : {[], list, scalar}, optional Integration constant(s). The value of the first integral at zero is the first value in the list, the value of the second integral at zero is the second value, etc. If k == [](the default), all constants are set to zero. Ifm == 1, a single scalar can be given instead of a list.lbnd : scalar, optional The lower bound of the integral. (Default: 0) scl : scalar, optional Following each integration the result is multiplied by sclbefore the integration constant is added. (Default: 1)axis : int, optional Axis over which the integral is taken. (Default: 0). New in version 1.7.0. Returns: S : ndarray Coefficient array of the integral. Raises: ValueError If m < 1,len(k) > m.See also NotesNote that the result of each integration is multiplied by scl. Why is this important to note? Say one is making a linear change of variable in an integral relative to in an integral relative tox. Then .. math::dx = du/a, so one will need to setsclequal to - perhaps not what one would have first thought. - perhaps not what one would have first thought.Examples>>> from numpy.polynomial import polynomial as P >>> c = (1,2,3) >>> P.polyint(c) # should return array([0, 1, 1, 1]) array([ 0., 1., 1., 1.]) >>> P.polyint(c,3) # should return array([0, 0, 0, 1/6, 1/12, 1/20]) array([ 0. , 0. , 0. , 0.16666667, 0.08333333, 0.05 ]) >>> P.polyint(c,k=3) # should return array([3, 1, 1, 1]) array([ 3., 1., 1., 1.]) >>> P.polyint(c,lbnd=-2) # should return array([6, 1, 1, 1]) array([ 6., 1., 1., 1.]) >>> P.polyint(c,scl=-2) # should return array([0, -2, -2, -2]) array([ 0., -2., -2., -2.])
    © 2008–2016 NumPy Developers
Licensed under the NumPy License.
    https://docs.scipy.org/doc/numpy-1.11.0/reference/generated/numpy.polynomial.polynomial.polyint.html