203 lines
6.2 KiB
JavaScript
203 lines
6.2 KiB
JavaScript
// Copyright 2012 The Closure Library Authors. All Rights Reserved.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS-IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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/**
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* @fileoverview A one dimensional cubic spline interpolator with not-a-knot
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* boundary conditions.
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*
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* See http://en.wikipedia.org/wiki/Spline_interpolation.
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*
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*/
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goog.provide('goog.math.interpolator.Spline1');
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goog.require('goog.array');
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goog.require('goog.math');
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goog.require('goog.math.interpolator.Interpolator1');
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goog.require('goog.math.tdma');
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/**
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* A one dimensional cubic spline interpolator with natural boundary conditions.
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* @implements {goog.math.interpolator.Interpolator1}
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* @constructor
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*/
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goog.math.interpolator.Spline1 = function() {
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/**
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* The abscissa of the data points.
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* @type {!Array.<number>}
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* @private
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*/
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this.x_ = [];
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/**
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* The spline interval coefficients.
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* Note that, in general, the length of coeffs and x is not the same.
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* @type {!Array.<!Array.<number>>}
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* @private
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*/
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this.coeffs_ = [[0, 0, 0, Number.NaN]];
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};
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/** @override */
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goog.math.interpolator.Spline1.prototype.setData = function(x, y) {
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goog.asserts.assert(x.length == y.length,
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'input arrays to setData should have the same length');
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if (x.length > 0) {
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this.coeffs_ = this.computeSplineCoeffs_(x, y);
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this.x_ = x.slice();
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} else {
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this.coeffs_ = [[0, 0, 0, Number.NaN]];
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this.x_ = [];
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}
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};
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/** @override */
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goog.math.interpolator.Spline1.prototype.interpolate = function(x) {
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var pos = goog.array.binarySearch(this.x_, x);
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if (pos < 0) {
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pos = -pos - 2;
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}
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pos = goog.math.clamp(pos, 0, this.coeffs_.length - 1);
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var d = x - this.x_[pos];
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var d2 = d * d;
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var d3 = d2 * d;
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var coeffs = this.coeffs_[pos];
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return coeffs[0] * d3 + coeffs[1] * d2 + coeffs[2] * d + coeffs[3];
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};
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/**
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* Solve for the spline coefficients such that the spline precisely interpolates
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* the data points.
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* @param {Array.<number>} x The abscissa of the spline data points.
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* @param {Array.<number>} y The ordinate of the spline data points.
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* @return {!Array.<!Array.<number>>} The spline interval coefficients.
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* @private
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*/
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goog.math.interpolator.Spline1.prototype.computeSplineCoeffs_ = function(x, y) {
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var nIntervals = x.length - 1;
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var dx = new Array(nIntervals);
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var delta = new Array(nIntervals);
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for (var i = 0; i < nIntervals; ++i) {
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dx[i] = x[i + 1] - x[i];
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delta[i] = (y[i + 1] - y[i]) / dx[i];
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}
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// Compute the spline coefficients from the 1st order derivatives.
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var coeffs = [];
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if (nIntervals == 0) {
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// Nearest neighbor interpolation.
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coeffs[0] = [0, 0, 0, y[0]];
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} else if (nIntervals == 1) {
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// Straight line interpolation.
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coeffs[0] = [0, 0, delta[0], y[0]];
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} else if (nIntervals == 2) {
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// Parabola interpolation.
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var c3 = 0;
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var c2 = (delta[1] - delta[0]) / (dx[0] + dx[1]);
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var c1 = delta[0] - c2 * dx[0];
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var c0 = y[0];
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coeffs[0] = [c3, c2, c1, c0];
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} else {
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// General Spline interpolation. Compute the 1st order derivatives from
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// the Spline equations.
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var deriv = this.computeDerivatives(dx, delta);
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for (var i = 0; i < nIntervals; ++i) {
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var c3 = (deriv[i] - 2 * delta[i] + deriv[i + 1]) / (dx[i] * dx[i]);
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var c2 = (3 * delta[i] - 2 * deriv[i] - deriv[i + 1]) / dx[i];
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var c1 = deriv[i];
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var c0 = y[i];
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coeffs[i] = [c3, c2, c1, c0];
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}
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}
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return coeffs;
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};
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/**
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* Computes the derivative at each point of the spline such that
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* the curve is C2. It uses not-a-knot boundary conditions.
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* @param {Array.<number>} dx The spacing between consecutive data points.
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* @param {Array.<number>} slope The slopes between consecutive data points.
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* @return {Array.<number>} The Spline derivative at each data point.
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* @protected
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*/
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goog.math.interpolator.Spline1.prototype.computeDerivatives = function(
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dx, slope) {
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var nIntervals = dx.length;
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// Compute the main diagonal of the system of equations.
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var mainDiag = new Array(nIntervals + 1);
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mainDiag[0] = dx[1];
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for (var i = 1; i < nIntervals; ++i) {
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mainDiag[i] = 2 * (dx[i] + dx[i - 1]);
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}
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mainDiag[nIntervals] = dx[nIntervals - 2];
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// Compute the sub diagonal of the system of equations.
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var subDiag = new Array(nIntervals);
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for (var i = 0; i < nIntervals; ++i) {
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subDiag[i] = dx[i + 1];
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}
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subDiag[nIntervals - 1] = dx[nIntervals - 2] + dx[nIntervals - 1];
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// Compute the super diagonal of the system of equations.
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var supDiag = new Array(nIntervals);
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supDiag[0] = dx[0] + dx[1];
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for (var i = 1; i < nIntervals; ++i) {
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supDiag[i] = dx[i - 1];
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}
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// Compute the right vector of the system of equations.
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var vecRight = new Array(nIntervals + 1);
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vecRight[0] = ((dx[0] + 2 * supDiag[0]) * dx[1] * slope[0] +
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dx[0] * dx[0] * slope[1]) / supDiag[0];
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for (var i = 1; i < nIntervals; ++i) {
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vecRight[i] = 3 * (dx[i] * slope[i - 1] + dx[i - 1] * slope[i]);
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}
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vecRight[nIntervals] = (dx[nIntervals - 1] * dx[nIntervals - 1] *
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slope[nIntervals - 2] + (2 * subDiag[nIntervals - 1] +
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dx[nIntervals - 1]) * dx[nIntervals - 2] * slope[nIntervals - 1]) /
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subDiag[nIntervals - 1];
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// Solve the system of equations.
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var deriv = goog.math.tdma.solve(
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subDiag, mainDiag, supDiag, vecRight);
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return deriv;
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};
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/**
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* Note that the inverse of a cubic spline is not a cubic spline in general.
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* As a result the inverse implementation is only approximate. In
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* particular, it only guarantees the exact inverse at the original input data
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* points passed to setData.
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* @override
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*/
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goog.math.interpolator.Spline1.prototype.getInverse = function() {
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var interpolator = new goog.math.interpolator.Spline1();
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var y = [];
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for (var i = 0; i < this.x_.length; i++) {
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y[i] = this.interpolate(this.x_[i]);
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}
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interpolator.setData(y, this.x_);
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return interpolator;
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};
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