X-Git-Url: http://gitweb.michael.orlitzky.com/?a=blobdiff_plain;f=mjo%2Finterpolation.py;h=8c3936edabaf5aff434f5f1728edffa899330f6d;hb=64c3510634164b0d8a43c2f034bdcc0c24b281cb;hp=e3e69338348ccdedb9fc581569f71422206cf787;hpb=d6c9163d4844d519559a1a35cd7094fc97572973;p=sage.d.git diff --git a/mjo/interpolation.py b/mjo/interpolation.py index e3e6933..8c3936e 100644 --- a/mjo/interpolation.py +++ b/mjo/interpolation.py @@ -1,5 +1,5 @@ from sage.all import * -load('~/.sage/init.sage') +from misc import product def lagrange_coefficient(k, x, xs): """ @@ -22,7 +22,7 @@ def lagrange_coefficient(k, x, xs): OUTPUT: - A symbolic function of one variable. + A symbolic expression of one variable. TESTS:: @@ -38,27 +38,28 @@ def lagrange_coefficient(k, x, xs): -def lagrange_polynomial(f, x, xs): +def lagrange_polynomial(x, xs, ys): """ Return the Lagrange form of the interpolation polynomial in `x` of - `f` at the points `xs`. + at the points (xs[k], ys[k]). INPUT: - - ``f`` - The function to interpolate. - - ``x`` - The independent variable of the resulting polynomial. - ``xs`` - The list of points at which we interpolate `f`. + - ``ys`` - The function values at `xs`. + OUTPUT: - A symbolic function (polynomial) interpolating `f` at `xs`. + A symbolic expression (polynomial) interpolating each (xs[k], ys[k]). TESTS:: sage: xs = [ -pi/2, -pi/6, 0, pi/6, pi/2 ] - sage: L = lagrange_polynomial(sin, x, xs) + sage: ys = map(sin, xs) + sage: L = lagrange_polynomial(x, xs, ys) sage: expected = 27/16*(pi - 6*x)*(pi - 2*x)*(pi + 2*x)*x/pi^4 sage: expected -= 1/8*(pi - 6*x)*(pi - 2*x)*(pi + 6*x)*x/pi^4 sage: expected -= 1/8*(pi - 6*x)*(pi + 2*x)*(pi + 6*x)*x/pi^4 @@ -67,7 +68,227 @@ def lagrange_polynomial(f, x, xs): True """ - ys = [ f(xs[k]) for k in range(0, len(xs)) ] ls = [ lagrange_coefficient(k, x, xs) for k in range(0, len(xs)) ] sigma = sum([ ys[k] * ls[k] for k in range(0, len(xs)) ]) return sigma + + + +def divided_difference_coefficients(xs): + """ + Assuming some function `f`, compute the coefficients of the + divided difference f[xs[0], ..., xs[n]]. + + TESTS: + + sage: divided_difference_coefficients([0]) + [1] + sage: divided_difference_coefficients([0, pi]) + [-1/pi, 1/pi] + sage: divided_difference_coefficients([0, pi, 2*pi]) + [1/2/pi^2, -1/pi^2, 1/2/pi^2] + + """ + coeffs = [ product([ (QQ(1) / (xj - xi)) for xi in xs if xi != xj ]) + for xj in xs ] + return coeffs + + +def divided_difference(xs, ys): + """ + Return the Newton divided difference of the points (xs[k], + ys[k]). Reference: + + http://en.wikipedia.org/wiki/Divided_differences + + INPUT: + + - ``xs`` -- The list of x-values. + + - ``ys`` -- The function values at `xs`. + + OUTPUT: + + The (possibly symbolic) divided difference function. + + TESTS:: + + sage: xs = [0] + sage: ys = map(sin, xs) + sage: divided_difference(xs, ys) + 0 + sage: xs = [0, pi] + sage: ys = map(sin, xs) + sage: divided_difference(xs, ys) + 0 + sage: xs = [0, pi, 2*pi] + sage: ys = map(sin, xs) + sage: divided_difference(xs, ys) + 0 + + We try something entirely symbolic:: + + sage: f = function('f', x) + sage: divided_difference([x], [f(x=x)]) + f(x) + sage: x1,x2 = var('x1,x2') + sage: divided_difference([x1,x2], [f(x=x1),f(x=x2)]) + f(x1)/(x1 - x2) - f(x2)/(x1 - x2) + + """ + coeffs = divided_difference_coefficients(xs) + v_cs = vector(coeffs) + v_ys = vector(ys) + return v_cs.dot_product(v_ys) + + +def newton_polynomial(x, xs, ys): + """ + Return the Newton form of the interpolating polynomial of the + points (xs[k], ys[k]) in the variable `x`. + + INPUT: + + - ``x`` -- The independent variable to use for the interpolating + polynomial. + + - ``xs`` -- The list of x-values. + + - ``ys`` -- The function values at `xs`. + + OUTPUT: + + A symbolic expression. + + TESTS: + + sage: xs = [ -pi/2, -pi/6, 0, pi/6, pi/2 ] + sage: ys = map(sin, xs) + sage: L = lagrange_polynomial(x, xs, ys) + sage: N = newton_polynomial(x, xs, ys) + sage: bool(N == L) + True + + """ + degree = len(xs) - 1 + + N = SR(0) + + for k in range(0, degree+1): + term = divided_difference(xs[:k+1], ys[:k+1]) + term *= product([ x - xk for xk in xs[:k]]) + N += term + + return N + + +def hermite_coefficient(k, x, xs): + """ + Return the Hermite coefficient h_{k}(x). See Atkinson, p. 160. + + INPUT: + + - ``k`` -- The index of the coefficient. + + - ``x`` -- The symbolic variable to use as the argument of h_{k}. + + - ``xs`` -- The list of points at which the function values are + known. + + OUTPUT: + + A symbolic expression. + + """ + lk = lagrange_coefficient(k, x, xs) + return (1 - 2*lk.diff(x)(x=xs[k])*(x - xs[k]))*(lk**2) + + +def hermite_deriv_coefficient(k, x, xs): + """ + Return the Hermite derivative coefficient, \tilde{h}_{k}(x). See + Atkinson, p. 160. + + INPUT: + + - ``k`` -- The index of the coefficient. + + - ``x`` -- The symbolic variable to use as the argument of h_{k}. + + - ``xs`` -- The list of points at which the function values are + known. + + OUTPUT: + + A symbolic expression. + + """ + lk = lagrange_coefficient(k, x, xs) + return (x - xs[k])*(lk**2) + + +def hermite_interpolant(x, xs, ys, y_primes): + """ + Return the Hermite interpolant `H(x)` such that H(xs[k]) = ys[k] + and H'(xs[k]) = y_primes[k] for each k. + + Reference: Atkinson, p. 160. + + INPUT: + + - ``x`` -- The symbolic variable to use as the argument of H(x). + + - ``xs`` -- The list of points at which the function values are + known. + + - ``ys`` -- The function values at the `xs`. + + - ``y_primes`` -- The derivatives at the `xs`. + + OUTPUT: + + A symbolic expression. + + TESTS: + + sage: xs = [ 0, pi/6, pi/2 ] + sage: ys = map(sin, xs) + sage: y_primes = map(cos, xs) + sage: H = hermite_interpolant(x, xs, ys, y_primes) + sage: expected = -27/4*(pi - 6*x)*(pi - 2*x)^2*sqrt(3)*x^2/pi^4 + sage: expected += (5*(pi - 2*x)/pi + 1)*(pi - 6*x)^2*x^2/pi^4 + sage: expected += 81/2*((pi - 6*x)/pi + 1)*(pi - 2*x)^2*x^2/pi^4 + sage: expected += (pi - 6*x)^2*(pi - 2*x)^2*x/pi^4 + sage: bool(H == expected) + True + + """ + s1 = sum([ ys[k] * hermite_coefficient(k, x, xs) + for k in range(0, len(xs)) ]) + + s2 = sum([ y_primes[k] * hermite_deriv_coefficient(k, x, xs) + for k in range(0, len(xs)) ]) + + return (s1 + s2) + + +def lagrange_psi(x, xs): + """ + The function, + + Psi(x) = (x - xs[0])*(x - xs[1])* ... *(x - xs[-1]) + + used in Lagrange and Hermite interpolation. + + INPUT: + + - ``x`` -- The independent variable of the resulting expression. + + - ``xs`` -- A list of points. + + OUTPUT: + + A symbolic expression in one variable, `x`. + """ + + return product([ (x - xj) for xj in xs ])