@thewtex/vtk.js-esm
Version:
Visualization Toolkit for the Web
1,933 lines (1,601 loc) • 63.8 kB
JavaScript
import _slicedToArray from '@babel/runtime/helpers/slicedToArray';
import { s as seedrandom } from '../../../vendor/seedrandom/index.js';
import macro from '../../../macro.js';
var vtkErrorMacro = macro.vtkErrorMacro,
vtkWarningMacro = macro.vtkWarningMacro; // ----------------------------------------------------------------------------
/* eslint-disable camelcase */
/* eslint-disable no-cond-assign */
/* eslint-disable no-bitwise */
/* eslint-disable no-multi-assign */
// ----------------------------------------------------------------------------
var randomSeedValue = 0;
var VTK_MAX_ROTATIONS = 20;
var VTK_SMALL_NUMBER = 1.0e-12;
function notImplemented(method) {
return function () {
return vtkErrorMacro("vtkMath::".concat(method, " - NOT IMPLEMENTED"));
};
}
function vtkSwapVectors3(v1, v2) {
for (var i = 0; i < 3; i++) {
var tmp = v1[i];
v1[i] = v2[i];
v2[i] = tmp;
}
}
function createArray() {
var size = arguments.length > 0 && arguments[0] !== undefined ? arguments[0] : 3;
var array = [];
while (array.length < size) {
array.push(0);
}
return array;
} // ----------------------------------------------------------------------------
// Global methods
// ----------------------------------------------------------------------------
var Pi = function Pi() {
return Math.PI;
};
function radiansFromDegrees(deg) {
return deg / 180 * Math.PI;
}
function degreesFromRadians(rad) {
return rad * 180 / Math.PI;
}
var round = Math.round,
floor = Math.floor,
ceil = Math.ceil,
min = Math.min,
max = Math.max;
function arrayMin(arr) {
var offset = arguments.length > 1 && arguments[1] !== undefined ? arguments[1] : 0;
var stride = arguments.length > 2 && arguments[2] !== undefined ? arguments[2] : 1;
var minValue = Infinity;
for (var i = offset, len = arr.length; i < len; i += stride) {
if (arr[i] < minValue) {
minValue = arr[i];
}
}
return minValue;
}
function arrayMax(arr) {
var offset = arguments.length > 1 && arguments[1] !== undefined ? arguments[1] : 0;
var stride = arguments.length > 2 && arguments[2] !== undefined ? arguments[2] : 1;
var maxValue = -Infinity;
for (var i = offset, len = arr.length; i < len; i += stride) {
if (maxValue < arr[i]) {
maxValue = arr[i];
}
}
return maxValue;
}
function arrayRange(arr) {
var offset = arguments.length > 1 && arguments[1] !== undefined ? arguments[1] : 0;
var stride = arguments.length > 2 && arguments[2] !== undefined ? arguments[2] : 1;
var minValue = Infinity;
var maxValue = -Infinity;
for (var i = offset, len = arr.length; i < len; i += stride) {
if (arr[i] < minValue) {
minValue = arr[i];
}
if (maxValue < arr[i]) {
maxValue = arr[i];
}
}
return [minValue, maxValue];
}
var ceilLog2 = notImplemented('ceilLog2');
var factorial = notImplemented('factorial');
function nearestPowerOfTwo(xi) {
var v = 1;
while (v < xi) {
v *= 2;
}
return v;
}
function isPowerOfTwo(x) {
return x === nearestPowerOfTwo(x);
}
function binomial(m, n) {
var r = 1;
for (var i = 1; i <= n; ++i) {
r *= (m - i + 1) / i;
}
return Math.floor(r);
}
function beginCombination(m, n) {
if (m < n) {
return 0;
}
var r = createArray(n);
for (var i = 0; i < n; ++i) {
r[i] = i;
}
return r;
}
function nextCombination(m, n, r) {
var status = 0;
for (var i = n - 1; i >= 0; --i) {
if (r[i] < m - n + i) {
var j = r[i] + 1;
while (i < n) {
r[i++] = j++;
}
status = 1;
break;
}
}
return status;
}
function randomSeed(seed) {
seedrandom("".concat(seed), {
global: true
});
randomSeedValue = seed;
}
function getSeed() {
return randomSeedValue;
}
function random() {
var minValue = arguments.length > 0 && arguments[0] !== undefined ? arguments[0] : 0;
var maxValue = arguments.length > 1 && arguments[1] !== undefined ? arguments[1] : 1;
var delta = maxValue - minValue;
return minValue + delta * Math.random();
}
var gaussian = notImplemented('gaussian'); // Vect3 operations
function add(a, b, out) {
out[0] = a[0] + b[0];
out[1] = a[1] + b[1];
out[2] = a[2] + b[2];
return out;
}
function subtract(a, b, out) {
out[0] = a[0] - b[0];
out[1] = a[1] - b[1];
out[2] = a[2] - b[2];
return out;
}
function multiplyScalar(vec, scalar) {
vec[0] *= scalar;
vec[1] *= scalar;
vec[2] *= scalar;
return vec;
}
function multiplyScalar2D(vec, scalar) {
vec[0] *= scalar;
vec[1] *= scalar;
return vec;
}
function multiplyAccumulate(a, b, scalar, out) {
out[0] = a[0] + b[0] * scalar;
out[1] = a[1] + b[1] * scalar;
out[2] = a[2] + b[2] * scalar;
return out;
}
function multiplyAccumulate2D(a, b, scalar, out) {
out[0] = a[0] + b[0] * scalar;
out[1] = a[1] + b[1] * scalar;
return out;
}
function dot(x, y) {
return x[0] * y[0] + x[1] * y[1] + x[2] * y[2];
}
function outer(x, y, out_3x3) {
for (var i = 0; i < 3; i++) {
for (var j = 0; j < 3; j++) {
out_3x3[i][j] = x[i] * y[j];
}
}
}
function cross(x, y, out) {
var Zx = x[1] * y[2] - x[2] * y[1];
var Zy = x[2] * y[0] - x[0] * y[2];
var Zz = x[0] * y[1] - x[1] * y[0];
out[0] = Zx;
out[1] = Zy;
out[2] = Zz;
return out;
}
function norm(x) {
var n = arguments.length > 1 && arguments[1] !== undefined ? arguments[1] : 3;
switch (n) {
case 1:
return Math.abs(x);
case 2:
return Math.sqrt(x[0] * x[0] + x[1] * x[1]);
case 3:
return Math.sqrt(x[0] * x[0] + x[1] * x[1] + x[2] * x[2]);
default:
{
var sum = 0;
for (var i = 0; i < n; i++) {
sum += x[i] * x[i];
}
return Math.sqrt(sum);
}
}
}
function normalize(x) {
var den = norm(x);
if (den !== 0.0) {
x[0] /= den;
x[1] /= den;
x[2] /= den;
}
return den;
}
function perpendiculars(x, y, z, theta) {
var x2 = x[0] * x[0];
var y2 = x[1] * x[1];
var z2 = x[2] * x[2];
var r = Math.sqrt(x2 + y2 + z2);
var dx;
var dy;
var dz; // transpose the vector to avoid divide-by-zero error
if (x2 > y2 && x2 > z2) {
dx = 0;
dy = 1;
dz = 2;
} else if (y2 > z2) {
dx = 1;
dy = 2;
dz = 0;
} else {
dx = 2;
dy = 0;
dz = 1;
}
var a = x[dx] / r;
var b = x[dy] / r;
var c = x[dz] / r;
var tmp = Math.sqrt(a * a + c * c);
if (theta !== 0) {
var sintheta = Math.sin(theta);
var costheta = Math.cos(theta);
if (y) {
y[dx] = (c * costheta - a * b * sintheta) / tmp;
y[dy] = sintheta * tmp;
y[dz] = (-(a * costheta) - b * c * sintheta) / tmp;
}
if (z) {
z[dx] = (-(c * sintheta) - a * b * costheta) / tmp;
z[dy] = costheta * tmp;
z[dz] = (a * sintheta - b * c * costheta) / tmp;
}
} else {
if (y) {
y[dx] = c / tmp;
y[dy] = 0;
y[dz] = -a / tmp;
}
if (z) {
z[dx] = -a * b / tmp;
z[dy] = tmp;
z[dz] = -b * c / tmp;
}
}
}
function projectVector(a, b, projection) {
var bSquared = dot(b, b);
if (bSquared === 0) {
projection[0] = 0;
projection[1] = 0;
projection[2] = 0;
return false;
}
var scale = dot(a, b) / bSquared;
for (var i = 0; i < 3; i++) {
projection[i] = b[i];
}
multiplyScalar(projection, scale);
return true;
}
function dot2D(x, y) {
return x[0] * y[0] + x[1] * y[1];
}
function projectVector2D(a, b, projection) {
var bSquared = dot2D(b, b);
if (bSquared === 0) {
projection[0] = 0;
projection[1] = 0;
return false;
}
var scale = dot2D(a, b) / bSquared;
for (var i = 0; i < 2; i++) {
projection[i] = b[i];
}
multiplyScalar2D(projection, scale);
return true;
}
function distance2BetweenPoints(x, y) {
return (x[0] - y[0]) * (x[0] - y[0]) + (x[1] - y[1]) * (x[1] - y[1]) + (x[2] - y[2]) * (x[2] - y[2]);
}
function angleBetweenVectors(v1, v2) {
var crossVect = [0, 0, 0];
cross(v1, v2, crossVect);
return Math.atan2(norm(crossVect), dot(v1, v2));
}
function signedAngleBetweenVectors(v1, v2, vN) {
var crossVect = [0, 0, 0];
cross(v1, v2, crossVect);
var angle = Math.atan2(norm(crossVect), dot(v1, v2));
return dot(crossVect, vN) >= 0 ? angle : -angle;
}
function gaussianAmplitude(mean, variance, position) {
var distanceFromMean = Math.abs(mean - position);
return 1 / Math.sqrt(2 * Math.PI * variance) * Math.exp(-Math.pow(distanceFromMean, 2) / (2 * variance));
}
function gaussianWeight(mean, variance, position) {
var distanceFromMean = Math.abs(mean - position);
return Math.exp(-Math.pow(distanceFromMean, 2) / (2 * variance));
}
function outer2D(x, y, out_2x2) {
for (var i = 0; i < 2; i++) {
for (var j = 0; j < 2; j++) {
out_2x2[i][j] = x[i] * y[j];
}
}
}
function norm2D(x2D) {
return Math.sqrt(x2D[0] * x2D[0] + x2D[1] * x2D[1]);
}
function normalize2D(x) {
var den = norm2D(x);
if (den !== 0.0) {
x[0] /= den;
x[1] /= den;
}
return den;
}
function determinant2x2() {
for (var _len = arguments.length, args = new Array(_len), _key = 0; _key < _len; _key++) {
args[_key] = arguments[_key];
}
if (args.length === 2) {
return args[0][0] * args[1][1] - args[1][0] * args[0][1];
}
if (args.length === 4) {
return args[0] * args[3] - args[1] * args[2];
}
return Number.NaN;
}
function LUFactor3x3(mat_3x3, index_3) {
var maxI;
var tmp;
var largest;
var scale = [0, 0, 0]; // Loop over rows to get implicit scaling information
for (var i = 0; i < 3; i++) {
largest = Math.abs(mat_3x3[i][0]);
if ((tmp = Math.abs(mat_3x3[i][1])) > largest) {
largest = tmp;
}
if ((tmp = Math.abs(mat_3x3[i][2])) > largest) {
largest = tmp;
}
scale[i] = 1 / largest;
} // Loop over all columns using Crout's method
// first column
largest = scale[0] * Math.abs(mat_3x3[0][0]);
maxI = 0;
if ((tmp = scale[1] * Math.abs(mat_3x3[1][0])) >= largest) {
largest = tmp;
maxI = 1;
}
if ((tmp = scale[2] * Math.abs(mat_3x3[2][0])) >= largest) {
maxI = 2;
}
if (maxI !== 0) {
vtkSwapVectors3(mat_3x3[maxI], mat_3x3[0]);
scale[maxI] = scale[0];
}
index_3[0] = maxI;
mat_3x3[1][0] /= mat_3x3[0][0];
mat_3x3[2][0] /= mat_3x3[0][0]; // second column
mat_3x3[1][1] -= mat_3x3[1][0] * mat_3x3[0][1];
mat_3x3[2][1] -= mat_3x3[2][0] * mat_3x3[0][1];
largest = scale[1] * Math.abs(mat_3x3[1][1]);
maxI = 1;
if ((tmp = scale[2] * Math.abs(mat_3x3[2][1])) >= largest) {
maxI = 2;
vtkSwapVectors3(mat_3x3[2], mat_3x3[1]);
scale[2] = scale[1];
}
index_3[1] = maxI;
mat_3x3[2][1] /= mat_3x3[1][1]; // third column
mat_3x3[1][2] -= mat_3x3[1][0] * mat_3x3[0][2];
mat_3x3[2][2] -= mat_3x3[2][0] * mat_3x3[0][2] + mat_3x3[2][1] * mat_3x3[1][2];
index_3[2] = 2;
}
function LUSolve3x3(mat_3x3, index_3, x_3) {
// forward substitution
var sum = x_3[index_3[0]];
x_3[index_3[0]] = x_3[0];
x_3[0] = sum;
sum = x_3[index_3[1]];
x_3[index_3[1]] = x_3[1];
x_3[1] = sum - mat_3x3[1][0] * x_3[0];
sum = x_3[index_3[2]];
x_3[index_3[2]] = x_3[2];
x_3[2] = sum - mat_3x3[2][0] * x_3[0] - mat_3x3[2][1] * x_3[1]; // back substitution
x_3[2] /= mat_3x3[2][2];
x_3[1] = (x_3[1] - mat_3x3[1][2] * x_3[2]) / mat_3x3[1][1];
x_3[0] = (x_3[0] - mat_3x3[0][1] * x_3[1] - mat_3x3[0][2] * x_3[2]) / mat_3x3[0][0];
}
function linearSolve3x3(mat_3x3, x_3, y_3) {
var a1 = mat_3x3[0][0];
var b1 = mat_3x3[0][1];
var c1 = mat_3x3[0][2];
var a2 = mat_3x3[1][0];
var b2 = mat_3x3[1][1];
var c2 = mat_3x3[1][2];
var a3 = mat_3x3[2][0];
var b3 = mat_3x3[2][1];
var c3 = mat_3x3[2][2]; // Compute the adjoint
var d1 = +determinant2x2(b2, b3, c2, c3);
var d2 = -determinant2x2(a2, a3, c2, c3);
var d3 = +determinant2x2(a2, a3, b2, b3);
var e1 = -determinant2x2(b1, b3, c1, c3);
var e2 = +determinant2x2(a1, a3, c1, c3);
var e3 = -determinant2x2(a1, a3, b1, b3);
var f1 = +determinant2x2(b1, b2, c1, c2);
var f2 = -determinant2x2(a1, a2, c1, c2);
var f3 = +determinant2x2(a1, a2, b1, b2); // Compute the determinant
var det = a1 * d1 + b1 * d2 + c1 * d3; // Multiply by the adjoint
var v1 = d1 * x_3[0] + e1 * x_3[1] + f1 * x_3[2];
var v2 = d2 * x_3[0] + e2 * x_3[1] + f2 * x_3[2];
var v3 = d3 * x_3[0] + e3 * x_3[1] + f3 * x_3[2]; // Divide by the determinant
y_3[0] = v1 / det;
y_3[1] = v2 / det;
y_3[2] = v3 / det;
}
function multiply3x3_vect3(mat_3x3, in_3, out_3) {
var x = mat_3x3[0][0] * in_3[0] + mat_3x3[0][1] * in_3[1] + mat_3x3[0][2] * in_3[2];
var y = mat_3x3[1][0] * in_3[0] + mat_3x3[1][1] * in_3[1] + mat_3x3[1][2] * in_3[2];
var z = mat_3x3[2][0] * in_3[0] + mat_3x3[2][1] * in_3[1] + mat_3x3[2][2] * in_3[2];
out_3[0] = x;
out_3[1] = y;
out_3[2] = z;
}
function multiply3x3_mat3(a_3x3, b_3x3, out_3x3) {
var tmp = [[0, 0, 0], [0, 0, 0], [0, 0, 0]];
for (var i = 0; i < 3; i++) {
tmp[0][i] = a_3x3[0][0] * b_3x3[0][i] + a_3x3[0][1] * b_3x3[1][i] + a_3x3[0][2] * b_3x3[2][i];
tmp[1][i] = a_3x3[1][0] * b_3x3[0][i] + a_3x3[1][1] * b_3x3[1][i] + a_3x3[1][2] * b_3x3[2][i];
tmp[2][i] = a_3x3[2][0] * b_3x3[0][i] + a_3x3[2][1] * b_3x3[1][i] + a_3x3[2][2] * b_3x3[2][i];
}
for (var j = 0; j < 3; j++) {
out_3x3[j][0] = tmp[j][0];
out_3x3[j][1] = tmp[j][1];
out_3x3[j][2] = tmp[j][2];
}
}
function multiplyMatrix(a, b, rowA, colA, rowB, colB, out_rowXcol) {
// we need colA == rowB
if (colA !== rowB) {
vtkErrorMacro('Number of columns of A must match number of rows of B.');
} // output matrix is rowA*colB
// output row
for (var i = 0; i < rowA; i++) {
// output col
for (var j = 0; j < colB; j++) {
out_rowXcol[i][j] = 0; // sum for this point
for (var k = 0; k < colA; k++) {
out_rowXcol[i][j] += a[i][k] * b[k][j];
}
}
}
}
function transpose3x3(in_3x3, outT_3x3) {
var tmp;
tmp = in_3x3[1][0];
outT_3x3[1][0] = in_3x3[0][1];
outT_3x3[0][1] = tmp;
tmp = in_3x3[2][0];
outT_3x3[2][0] = in_3x3[0][2];
outT_3x3[0][2] = tmp;
tmp = in_3x3[2][1];
outT_3x3[2][1] = in_3x3[1][2];
outT_3x3[1][2] = tmp;
outT_3x3[0][0] = in_3x3[0][0];
outT_3x3[1][1] = in_3x3[1][1];
outT_3x3[2][2] = in_3x3[2][2];
}
function invert3x3(in_3x3, outI_3x3) {
var a1 = in_3x3[0][0];
var b1 = in_3x3[0][1];
var c1 = in_3x3[0][2];
var a2 = in_3x3[1][0];
var b2 = in_3x3[1][1];
var c2 = in_3x3[1][2];
var a3 = in_3x3[2][0];
var b3 = in_3x3[2][1];
var c3 = in_3x3[2][2]; // Compute the adjoint
var d1 = +determinant2x2(b2, b3, c2, c3);
var d2 = -determinant2x2(a2, a3, c2, c3);
var d3 = +determinant2x2(a2, a3, b2, b3);
var e1 = -determinant2x2(b1, b3, c1, c3);
var e2 = +determinant2x2(a1, a3, c1, c3);
var e3 = -determinant2x2(a1, a3, b1, b3);
var f1 = +determinant2x2(b1, b2, c1, c2);
var f2 = -determinant2x2(a1, a2, c1, c2);
var f3 = +determinant2x2(a1, a2, b1, b2); // Divide by the determinant
var det = a1 * d1 + b1 * d2 + c1 * d3;
outI_3x3[0][0] = d1 / det;
outI_3x3[1][0] = d2 / det;
outI_3x3[2][0] = d3 / det;
outI_3x3[0][1] = e1 / det;
outI_3x3[1][1] = e2 / det;
outI_3x3[2][1] = e3 / det;
outI_3x3[0][2] = f1 / det;
outI_3x3[1][2] = f2 / det;
outI_3x3[2][2] = f3 / det;
}
function identity3x3(mat_3x3) {
for (var i = 0; i < 3; i++) {
mat_3x3[i][0] = mat_3x3[i][1] = mat_3x3[i][2] = 0;
mat_3x3[i][i] = 1;
}
}
function determinant3x3(mat_3x3) {
return mat_3x3[0][0] * mat_3x3[1][1] * mat_3x3[2][2] + mat_3x3[1][0] * mat_3x3[2][1] * mat_3x3[0][2] + mat_3x3[2][0] * mat_3x3[0][1] * mat_3x3[1][2] - mat_3x3[0][0] * mat_3x3[2][1] * mat_3x3[1][2] - mat_3x3[1][0] * mat_3x3[0][1] * mat_3x3[2][2] - mat_3x3[2][0] * mat_3x3[1][1] * mat_3x3[0][2];
}
function quaternionToMatrix3x3(quat_4, mat_3x3) {
var ww = quat_4[0] * quat_4[0];
var wx = quat_4[0] * quat_4[1];
var wy = quat_4[0] * quat_4[2];
var wz = quat_4[0] * quat_4[3];
var xx = quat_4[1] * quat_4[1];
var yy = quat_4[2] * quat_4[2];
var zz = quat_4[3] * quat_4[3];
var xy = quat_4[1] * quat_4[2];
var xz = quat_4[1] * quat_4[3];
var yz = quat_4[2] * quat_4[3];
var rr = xx + yy + zz; // normalization factor, just in case quaternion was not normalized
var f = 1 / (ww + rr);
var s = (ww - rr) * f;
f *= 2;
mat_3x3[0][0] = xx * f + s;
mat_3x3[1][0] = (xy + wz) * f;
mat_3x3[2][0] = (xz - wy) * f;
mat_3x3[0][1] = (xy - wz) * f;
mat_3x3[1][1] = yy * f + s;
mat_3x3[2][1] = (yz + wx) * f;
mat_3x3[0][2] = (xz + wy) * f;
mat_3x3[1][2] = (yz - wx) * f;
mat_3x3[2][2] = zz * f + s;
}
/**
* Returns true if elements of both arrays are equals.
* @param {Array} a an array of numbers (vector, point, matrix...)
* @param {Array} b an array of numbers (vector, point, matrix...)
* @param {Number} eps tolerance
*/
function areEquals(a, b) {
var eps = arguments.length > 2 && arguments[2] !== undefined ? arguments[2] : 1e-6;
if (a.length !== b.length) {
return false;
}
function isEqual(element, index) {
return Math.abs(element - b[index]) <= eps;
}
return a.every(isEqual);
}
var areMatricesEqual = areEquals;
function roundNumber(num) {
var digits = arguments.length > 1 && arguments[1] !== undefined ? arguments[1] : 0;
if (!"".concat(num).includes('e')) {
return +"".concat(Math.round("".concat(num, "e+").concat(digits)), "e-").concat(digits);
}
var arr = "".concat(num).split('e');
var sig = '';
if (+arr[1] + digits > 0) {
sig = '+';
}
return +"".concat(Math.round("".concat(+arr[0], "e").concat(sig).concat(+arr[1] + digits)), "e-").concat(digits);
}
function roundVector(vector) {
var out = arguments.length > 1 && arguments[1] !== undefined ? arguments[1] : [];
var digits = arguments.length > 2 && arguments[2] !== undefined ? arguments[2] : 0;
out[0] = roundNumber(vector[0], digits);
out[1] = roundNumber(vector[1], digits);
out[2] = roundNumber(vector[2], digits);
return out;
}
function jacobiN(a, n, w, v) {
var i;
var j;
var k;
var iq;
var ip;
var numPos;
var tresh;
var theta;
var t;
var tau;
var sm;
var s;
var h;
var g;
var c;
var tmp;
var b = createArray(n);
var z = createArray(n);
var vtkROTATE = function vtkROTATE(aa, ii, jj, kk, ll) {
g = aa[ii][jj];
h = aa[kk][ll];
aa[ii][jj] = g - s * (h + g * tau);
aa[kk][ll] = h + s * (g - h * tau);
}; // initialize
for (ip = 0; ip < n; ip++) {
for (iq = 0; iq < n; iq++) {
v[ip][iq] = 0.0;
}
v[ip][ip] = 1.0;
}
for (ip = 0; ip < n; ip++) {
b[ip] = w[ip] = a[ip][ip];
z[ip] = 0.0;
} // begin rotation sequence
for (i = 0; i < VTK_MAX_ROTATIONS; i++) {
sm = 0.0;
for (ip = 0; ip < n - 1; ip++) {
for (iq = ip + 1; iq < n; iq++) {
sm += Math.abs(a[ip][iq]);
}
}
if (sm === 0.0) {
break;
} // first 3 sweeps
if (i < 3) {
tresh = 0.2 * sm / (n * n);
} else {
tresh = 0.0;
}
for (ip = 0; ip < n - 1; ip++) {
for (iq = ip + 1; iq < n; iq++) {
g = 100.0 * Math.abs(a[ip][iq]); // after 4 sweeps
if (i > 3 && Math.abs(w[ip]) + g === Math.abs(w[ip]) && Math.abs(w[iq]) + g === Math.abs(w[iq])) {
a[ip][iq] = 0.0;
} else if (Math.abs(a[ip][iq]) > tresh) {
h = w[iq] - w[ip];
if (Math.abs(h) + g === Math.abs(h)) {
t = a[ip][iq] / h;
} else {
theta = 0.5 * h / a[ip][iq];
t = 1.0 / (Math.abs(theta) + Math.sqrt(1.0 + theta * theta));
if (theta < 0.0) {
t = -t;
}
}
c = 1.0 / Math.sqrt(1 + t * t);
s = t * c;
tau = s / (1.0 + c);
h = t * a[ip][iq];
z[ip] -= h;
z[iq] += h;
w[ip] -= h;
w[iq] += h;
a[ip][iq] = 0.0; // ip already shifted left by 1 unit
for (j = 0; j <= ip - 1; j++) {
vtkROTATE(a, j, ip, j, iq);
} // ip and iq already shifted left by 1 unit
for (j = ip + 1; j <= iq - 1; j++) {
vtkROTATE(a, ip, j, j, iq);
} // iq already shifted left by 1 unit
for (j = iq + 1; j < n; j++) {
vtkROTATE(a, ip, j, iq, j);
}
for (j = 0; j < n; j++) {
vtkROTATE(v, j, ip, j, iq);
}
}
}
}
for (ip = 0; ip < n; ip++) {
b[ip] += z[ip];
w[ip] = b[ip];
z[ip] = 0.0;
}
} // this is NEVER called
if (i >= VTK_MAX_ROTATIONS) {
vtkWarningMacro('vtkMath::Jacobi: Error extracting eigenfunctions');
return 0;
} // sort eigenfunctions: these changes do not affect accuracy
for (j = 0; j < n - 1; j++) {
// boundary incorrect
k = j;
tmp = w[k];
for (i = j + 1; i < n; i++) {
// boundary incorrect, shifted already
if (w[i] >= tmp) {
// why exchange if same?
k = i;
tmp = w[k];
}
}
if (k !== j) {
w[k] = w[j];
w[j] = tmp;
for (i = 0; i < n; i++) {
tmp = v[i][j];
v[i][j] = v[i][k];
v[i][k] = tmp;
}
}
} // ensure eigenvector consistency (i.e., Jacobi can compute vectors that
// are negative of one another (.707,.707,0) and (-.707,-.707,0). This can
// reek havoc in hyperstreamline/other stuff. We will select the most
// positive eigenvector.
var ceil_half_n = (n >> 1) + (n & 1);
for (j = 0; j < n; j++) {
for (numPos = 0, i = 0; i < n; i++) {
if (v[i][j] >= 0.0) {
numPos++;
}
} // if ( numPos < ceil(double(n)/double(2.0)) )
if (numPos < ceil_half_n) {
for (i = 0; i < n; i++) {
v[i][j] *= -1.0;
}
}
}
return 1;
}
function matrix3x3ToQuaternion(mat_3x3, quat_4) {
var tmp = [[0, 0, 0, 0], [0, 0, 0, 0], [0, 0, 0, 0], [0, 0, 0, 0]]; // on-diagonal elements
tmp[0][0] = mat_3x3[0][0] + mat_3x3[1][1] + mat_3x3[2][2];
tmp[1][1] = mat_3x3[0][0] - mat_3x3[1][1] - mat_3x3[2][2];
tmp[2][2] = -mat_3x3[0][0] + mat_3x3[1][1] - mat_3x3[2][2];
tmp[3][3] = -mat_3x3[0][0] - mat_3x3[1][1] + mat_3x3[2][2]; // off-diagonal elements
tmp[0][1] = tmp[1][0] = mat_3x3[2][1] - mat_3x3[1][2];
tmp[0][2] = tmp[2][0] = mat_3x3[0][2] - mat_3x3[2][0];
tmp[0][3] = tmp[3][0] = mat_3x3[1][0] - mat_3x3[0][1];
tmp[1][2] = tmp[2][1] = mat_3x3[1][0] + mat_3x3[0][1];
tmp[1][3] = tmp[3][1] = mat_3x3[0][2] + mat_3x3[2][0];
tmp[2][3] = tmp[3][2] = mat_3x3[2][1] + mat_3x3[1][2];
var eigenvectors = [[0, 0, 0, 0], [0, 0, 0, 0], [0, 0, 0, 0], [0, 0, 0, 0]];
var eigenvalues = [0, 0, 0, 0]; // convert into format that JacobiN can use,
// then use Jacobi to find eigenvalues and eigenvectors
var NTemp = [0, 0, 0, 0];
var eigenvectorsTemp = [0, 0, 0, 0];
for (var i = 0; i < 4; i++) {
NTemp[i] = tmp[i];
eigenvectorsTemp[i] = eigenvectors[i];
}
jacobiN(NTemp, 4, eigenvalues, eigenvectorsTemp); // the first eigenvector is the one we want
quat_4[0] = eigenvectors[0][0];
quat_4[1] = eigenvectors[1][0];
quat_4[2] = eigenvectors[2][0];
quat_4[3] = eigenvectors[3][0];
}
function multiplyQuaternion(quat_1, quat_2, quat_out) {
var ww = quat_1[0] * quat_2[0];
var wx = quat_1[0] * quat_2[1];
var wy = quat_1[0] * quat_2[2];
var wz = quat_1[0] * quat_2[3];
var xw = quat_1[1] * quat_2[0];
var xx = quat_1[1] * quat_2[1];
var xy = quat_1[1] * quat_2[2];
var xz = quat_1[1] * quat_2[3];
var yw = quat_1[2] * quat_2[0];
var yx = quat_1[2] * quat_2[1];
var yy = quat_1[2] * quat_2[2];
var yz = quat_1[2] * quat_2[3];
var zw = quat_1[3] * quat_2[0];
var zx = quat_1[3] * quat_2[1];
var zy = quat_1[3] * quat_2[2];
var zz = quat_1[3] * quat_2[3];
quat_out[0] = ww - xx - yy - zz;
quat_out[1] = wx + xw + yz - zy;
quat_out[2] = wy - xz + yw + zx;
quat_out[3] = wz + xy - yx + zw;
}
function orthogonalize3x3(a_3x3, out_3x3) {
// copy the matrix
for (var i = 0; i < 3; i++) {
out_3x3[0][i] = a_3x3[0][i];
out_3x3[1][i] = a_3x3[1][i];
out_3x3[2][i] = a_3x3[2][i];
} // Pivot the matrix to improve accuracy
var scale = createArray(3);
var index = createArray(3);
var largest; // Loop over rows to get implicit scaling information
for (var _i = 0; _i < 3; _i++) {
var _x = Math.abs(out_3x3[_i][0]);
var _x2 = Math.abs(out_3x3[_i][1]);
var _x3 = Math.abs(out_3x3[_i][2]);
largest = _x2 > _x ? _x2 : _x;
largest = _x3 > largest ? _x3 : largest;
scale[_i] = 1;
if (largest !== 0) {
scale[_i] /= largest;
}
} // first column
var x1 = Math.abs(out_3x3[0][0]) * scale[0];
var x2 = Math.abs(out_3x3[1][0]) * scale[1];
var x3 = Math.abs(out_3x3[2][0]) * scale[2];
index[0] = 0;
largest = x1;
if (x2 >= largest) {
largest = x2;
index[0] = 1;
}
if (x3 >= largest) {
index[0] = 2;
}
if (index[0] !== 0) {
vtkSwapVectors3(out_3x3[index[0]], out_3x3[0]);
scale[index[0]] = scale[0];
} // second column
var y2 = Math.abs(out_3x3[1][1]) * scale[1];
var y3 = Math.abs(out_3x3[2][1]) * scale[2];
index[1] = 1;
largest = y2;
if (y3 >= largest) {
index[1] = 2;
vtkSwapVectors3(out_3x3[2], out_3x3[1]);
} // third column
index[2] = 2; // A quaternion can only describe a pure rotation, not
// a rotation with a flip, therefore the flip must be
// removed before the matrix is converted to a quaternion.
var flip = 0;
if (determinant3x3(out_3x3) < 0) {
flip = 1;
for (var _i2 = 0; _i2 < 3; _i2++) {
out_3x3[0][_i2] = -out_3x3[0][_i2];
out_3x3[1][_i2] = -out_3x3[1][_i2];
out_3x3[2][_i2] = -out_3x3[2][_i2];
}
} // Do orthogonalization using a quaternion intermediate
// (this, essentially, does the orthogonalization via
// diagonalization of an appropriately constructed symmetric
// 4x4 matrix rather than by doing SVD of the 3x3 matrix)
var quat = createArray(4);
matrix3x3ToQuaternion(out_3x3, quat);
quaternionToMatrix3x3(quat, out_3x3); // Put the flip back into the orthogonalized matrix.
if (flip) {
for (var _i3 = 0; _i3 < 3; _i3++) {
out_3x3[0][_i3] = -out_3x3[0][_i3];
out_3x3[1][_i3] = -out_3x3[1][_i3];
out_3x3[2][_i3] = -out_3x3[2][_i3];
}
} // Undo the pivoting
if (index[1] !== 1) {
vtkSwapVectors3(out_3x3[index[1]], out_3x3[1]);
}
if (index[0] !== 0) {
vtkSwapVectors3(out_3x3[index[0]], out_3x3[0]);
}
}
function diagonalize3x3(a_3x3, w_3, v_3x3) {
var i;
var j;
var k;
var maxI;
var tmp;
var maxVal; // do the matrix[3][3] to **matrix conversion for Jacobi
var C = [createArray(3), createArray(3), createArray(3)];
var ATemp = createArray(3);
var VTemp = createArray(3);
for (i = 0; i < 3; i++) {
C[i][0] = a_3x3[i][0];
C[i][1] = a_3x3[i][1];
C[i][2] = a_3x3[i][2];
ATemp[i] = C[i];
VTemp[i] = v_3x3[i];
} // diagonalize using Jacobi
jacobiN(ATemp, 3, w_3, VTemp); // if all the eigenvalues are the same, return identity matrix
if (w_3[0] === w_3[1] && w_3[0] === w_3[2]) {
identity3x3(v_3x3);
return;
} // transpose temporarily, it makes it easier to sort the eigenvectors
transpose3x3(v_3x3, v_3x3); // if two eigenvalues are the same, re-orthogonalize to optimally line
// up the eigenvectors with the x, y, and z axes
for (i = 0; i < 3; i++) {
// two eigenvalues are the same
if (w_3[(i + 1) % 3] === w_3[(i + 2) % 3]) {
// find maximum element of the independent eigenvector
maxVal = Math.abs(v_3x3[i][0]);
maxI = 0;
for (j = 1; j < 3; j++) {
if (maxVal < (tmp = Math.abs(v_3x3[i][j]))) {
maxVal = tmp;
maxI = j;
}
} // swap the eigenvector into its proper position
if (maxI !== i) {
tmp = w_3[maxI];
w_3[maxI] = w_3[i];
w_3[i] = tmp;
vtkSwapVectors3(v_3x3[i], v_3x3[maxI]);
} // maximum element of eigenvector should be positive
if (v_3x3[maxI][maxI] < 0) {
v_3x3[maxI][0] = -v_3x3[maxI][0];
v_3x3[maxI][1] = -v_3x3[maxI][1];
v_3x3[maxI][2] = -v_3x3[maxI][2];
} // re-orthogonalize the other two eigenvectors
j = (maxI + 1) % 3;
k = (maxI + 2) % 3;
v_3x3[j][0] = 0.0;
v_3x3[j][1] = 0.0;
v_3x3[j][2] = 0.0;
v_3x3[j][j] = 1.0;
cross(v_3x3[maxI], v_3x3[j], v_3x3[k]);
normalize(v_3x3[k]);
cross(v_3x3[k], v_3x3[maxI], v_3x3[j]); // transpose vectors back to columns
transpose3x3(v_3x3, v_3x3);
return;
}
} // the three eigenvalues are different, just sort the eigenvectors
// to align them with the x, y, and z axes
// find the vector with the largest x element, make that vector
// the first vector
maxVal = Math.abs(v_3x3[0][0]);
maxI = 0;
for (i = 1; i < 3; i++) {
if (maxVal < (tmp = Math.abs(v_3x3[i][0]))) {
maxVal = tmp;
maxI = i;
}
} // swap eigenvalue and eigenvector
if (maxI !== 0) {
tmp = w_3[maxI];
w_3[maxI] = w_3[0];
w_3[0] = tmp;
vtkSwapVectors3(v_3x3[maxI], v_3x3[0]);
} // do the same for the y element
if (Math.abs(v_3x3[1][1]) < Math.abs(v_3x3[2][1])) {
tmp = w_3[2];
w_3[2] = w_3[1];
w_3[1] = tmp;
vtkSwapVectors3(v_3x3[2], v_3x3[1]);
} // ensure that the sign of the eigenvectors is correct
for (i = 0; i < 2; i++) {
if (v_3x3[i][i] < 0) {
v_3x3[i][0] = -v_3x3[i][0];
v_3x3[i][1] = -v_3x3[i][1];
v_3x3[i][2] = -v_3x3[i][2];
}
} // set sign of final eigenvector to ensure that determinant is positive
if (determinant3x3(v_3x3) < 0) {
v_3x3[2][0] = -v_3x3[2][0];
v_3x3[2][1] = -v_3x3[2][1];
v_3x3[2][2] = -v_3x3[2][2];
} // transpose the eigenvectors back again
transpose3x3(v_3x3, v_3x3);
}
function singularValueDecomposition3x3(a_3x3, u_3x3, w_3, vT_3x3) {
var i;
var B = [createArray(3), createArray(3), createArray(3)]; // copy so that A can be used for U or VT without risk
for (i = 0; i < 3; i++) {
B[0][i] = a_3x3[0][i];
B[1][i] = a_3x3[1][i];
B[2][i] = a_3x3[2][i];
} // temporarily flip if determinant is negative
var d = determinant3x3(B);
if (d < 0) {
for (i = 0; i < 3; i++) {
B[0][i] = -B[0][i];
B[1][i] = -B[1][i];
B[2][i] = -B[2][i];
}
} // orthogonalize, diagonalize, etc.
orthogonalize3x3(B, u_3x3);
transpose3x3(B, B);
multiply3x3_mat3(B, u_3x3, vT_3x3);
diagonalize3x3(vT_3x3, w_3, vT_3x3);
multiply3x3_mat3(u_3x3, vT_3x3, u_3x3);
transpose3x3(vT_3x3, vT_3x3); // re-create the flip
if (d < 0) {
w_3[0] = -w_3[0];
w_3[1] = -w_3[1];
w_3[2] = -w_3[2];
}
}
function luFactorLinearSystem(A, index, size) {
var i;
var j;
var k;
var largest;
var maxI = 0;
var sum;
var temp1;
var temp2;
var scale = createArray(size); //
// Loop over rows to get implicit scaling information
//
for (i = 0; i < size; i++) {
for (largest = 0.0, j = 0; j < size; j++) {
if ((temp2 = Math.abs(A[i][j])) > largest) {
largest = temp2;
}
}
if (largest === 0.0) {
vtkWarningMacro('Unable to factor linear system');
return 0;
}
scale[i] = 1.0 / largest;
} //
// Loop over all columns using Crout's method
//
for (j = 0; j < size; j++) {
for (i = 0; i < j; i++) {
sum = A[i][j];
for (k = 0; k < i; k++) {
sum -= A[i][k] * A[k][j];
}
A[i][j] = sum;
} //
// Begin search for largest pivot element
//
for (largest = 0.0, i = j; i < size; i++) {
sum = A[i][j];
for (k = 0; k < j; k++) {
sum -= A[i][k] * A[k][j];
}
A[i][j] = sum;
if ((temp1 = scale[i] * Math.abs(sum)) >= largest) {
largest = temp1;
maxI = i;
}
} //
// Check for row interchange
//
if (j !== maxI) {
for (k = 0; k < size; k++) {
temp1 = A[maxI][k];
A[maxI][k] = A[j][k];
A[j][k] = temp1;
}
scale[maxI] = scale[j];
} //
// Divide by pivot element and perform elimination
//
index[j] = maxI;
if (Math.abs(A[j][j]) <= VTK_SMALL_NUMBER) {
vtkWarningMacro('Unable to factor linear system');
return 0;
}
if (j !== size - 1) {
temp1 = 1.0 / A[j][j];
for (i = j + 1; i < size; i++) {
A[i][j] *= temp1;
}
}
}
return 1;
}
function luSolveLinearSystem(A, index, x, size) {
var i;
var j;
var ii;
var idx;
var sum; //
// Proceed with forward and backsubstitution for L and U
// matrices. First, forward substitution.
//
for (ii = -1, i = 0; i < size; i++) {
idx = index[i];
sum = x[idx];
x[idx] = x[i];
if (ii >= 0) {
for (j = ii; j <= i - 1; j++) {
sum -= A[i][j] * x[j];
}
} else if (sum !== 0.0) {
ii = i;
}
x[i] = sum;
} //
// Now, back substitution
//
for (i = size - 1; i >= 0; i--) {
sum = x[i];
for (j = i + 1; j < size; j++) {
sum -= A[i][j] * x[j];
}
x[i] = sum / A[i][i];
}
}
function solveLinearSystem(A, x, size) {
// if we solving something simple, just solve it
if (size === 2) {
var y = createArray(2);
var det = determinant2x2(A[0][0], A[0][1], A[1][0], A[1][1]);
if (det === 0.0) {
// Unable to solve linear system
return 0;
}
y[0] = (A[1][1] * x[0] - A[0][1] * x[1]) / det;
y[1] = (-(A[1][0] * x[0]) + A[0][0] * x[1]) / det;
x[0] = y[0];
x[1] = y[1];
return 1;
}
if (size === 1) {
if (A[0][0] === 0.0) {
// Unable to solve linear system
return 0;
}
x[0] /= A[0][0];
return 1;
} //
// System of equations is not trivial, use Crout's method
//
// Check on allocation of working vectors
var index = createArray(size); // Factor and solve matrix
if (luFactorLinearSystem(A, index, size) === 0) {
return 0;
}
luSolveLinearSystem(A, index, x, size);
return 1;
}
function invertMatrix(A, AI, size) {
var index = arguments.length > 3 && arguments[3] !== undefined ? arguments[3] : null;
var column = arguments.length > 4 && arguments[4] !== undefined ? arguments[4] : null;
var tmp1Size = index || createArray(size);
var tmp2Size = column || createArray(size); // Factor matrix; then begin solving for inverse one column at a time.
// Note: tmp1Size returned value is used later, tmp2Size is just working
// memory whose values are not used in LUSolveLinearSystem
if (luFactorLinearSystem(A, tmp1Size, size) === 0) {
return 0;
}
for (var j = 0; j < size; j++) {
for (var i = 0; i < size; i++) {
tmp2Size[i] = 0.0;
}
tmp2Size[j] = 1.0;
luSolveLinearSystem(A, tmp1Size, tmp2Size, size);
for (var _i4 = 0; _i4 < size; _i4++) {
AI[_i4][j] = tmp2Size[_i4];
}
}
return 1;
}
function estimateMatrixCondition(A, size) {
var minValue = +Number.MAX_VALUE;
var maxValue = -Number.MAX_VALUE; // find the maximum value
for (var i = 0; i < size; i++) {
for (var j = i; j < size; j++) {
if (Math.abs(A[i][j]) > max) {
maxValue = Math.abs(A[i][j]);
}
}
} // find the minimum diagonal value
for (var _i5 = 0; _i5 < size; _i5++) {
if (Math.abs(A[_i5][_i5]) < min) {
minValue = Math.abs(A[_i5][_i5]);
}
}
if (minValue === 0.0) {
return Number.MAX_VALUE;
}
return maxValue / minValue;
}
function jacobi(a_3x3, w, v) {
return jacobiN(a_3x3, 3, w, v);
}
function solveHomogeneousLeastSquares(numberOfSamples, xt, xOrder, mt) {
// check dimensional consistency
if (numberOfSamples < xOrder) {
vtkWarningMacro('Insufficient number of samples. Underdetermined.');
return 0;
}
var i;
var j;
var k; // set up intermediate variables
// Allocate matrix to hold X times transpose of X
var XXt = createArray(xOrder); // size x by x
// Allocate the array of eigenvalues and eigenvectors
var eigenvals = createArray(xOrder);
var eigenvecs = createArray(xOrder); // Clear the upper triangular region (and btw, allocate the eigenvecs as well)
for (i = 0; i < xOrder; i++) {
eigenvecs[i] = createArray(xOrder);
XXt[i] = createArray(xOrder);
for (j = 0; j < xOrder; j++) {
XXt[i][j] = 0.0;
}
} // Calculate XXt upper half only, due to symmetry
for (k = 0; k < numberOfSamples; k++) {
for (i = 0; i < xOrder; i++) {
for (j = i; j < xOrder; j++) {
XXt[i][j] += xt[k][i] * xt[k][j];
}
}
} // now fill in the lower half of the XXt matrix
for (i = 0; i < xOrder; i++) {
for (j = 0; j < i; j++) {
XXt[i][j] = XXt[j][i];
}
} // Compute the eigenvectors and eigenvalues
jacobiN(XXt, xOrder, eigenvals, eigenvecs); // Smallest eigenval is at the end of the list (xOrder-1), and solution is
// corresponding eigenvec.
for (i = 0; i < xOrder; i++) {
mt[i][0] = eigenvecs[i][xOrder - 1];
}
return 1;
}
function solveLeastSquares(numberOfSamples, xt, xOrder, yt, yOrder, mt) {
var checkHomogeneous = arguments.length > 6 && arguments[6] !== undefined ? arguments[6] : true;
// check dimensional consistency
if (numberOfSamples < xOrder || numberOfSamples < yOrder) {
vtkWarningMacro('Insufficient number of samples. Underdetermined.');
return 0;
}
var homogenFlags = createArray(yOrder);
var allHomogeneous = 1;
var hmt;
var homogRC = 0;
var i;
var j;
var k;
var someHomogeneous = 0; // Ok, first init some flags check and see if all the systems are homogeneous
if (checkHomogeneous) {
// If Y' is zero, it's a homogeneous system and can't be solved via
// the pseudoinverse method. Detect this case, warn the user, and
// invoke SolveHomogeneousLeastSquares instead. Note that it doesn't
// really make much sense for yOrder to be greater than one in this case,
// since that's just yOrder occurrences of a 0 vector on the RHS, but
// we allow it anyway. N
// Initialize homogeneous flags on a per-right-hand-side basis
for (j = 0; j < yOrder; j++) {
homogenFlags[j] = 1;
}
for (i = 0; i < numberOfSamples; i++) {
for (j = 0; j < yOrder; j++) {
if (Math.abs(yt[i][j]) > VTK_SMALL_NUMBER) {
allHomogeneous = 0;
homogenFlags[j] = 0;
}
}
} // If we've got one system, and it's homogeneous, do it and bail out quickly.
if (allHomogeneous && yOrder === 1) {
vtkWarningMacro('Detected homogeneous system (Y=0), calling SolveHomogeneousLeastSquares()');
return solveHomogeneousLeastSquares(numberOfSamples, xt, xOrder, mt);
} // Ok, we've got more than one system of equations.
// Figure out if we need to calculate the homogeneous equation solution for
// any of them.
if (allHomogeneous) {
someHomogeneous = 1;
} else {
for (j = 0; j < yOrder; j++) {
if (homogenFlags[j]) {
someHomogeneous = 1;
}
}
}
} // If necessary, solve the homogeneous problem
if (someHomogeneous) {
// hmt is the homogeneous equation version of mt, the general solution.
hmt = createArray(xOrder);
for (j = 0; j < xOrder; j++) {
// Only allocate 1 here, not yOrder, because here we're going to solve
// just the one homogeneous equation subset of the entire problem
hmt[j] = [0];
} // Ok, solve the homogeneous problem
homogRC = solveHomogeneousLeastSquares(numberOfSamples, xt, xOrder, hmt);
} // set up intermediate variables
var XXt = createArray(xOrder); // size x by x
var XXtI = createArray(xOrder); // size x by x
var XYt = createArray(xOrder); // size x by y
for (i = 0; i < xOrder; i++) {
XXt[i] = createArray(xOrder);
XXtI[i] = createArray(xOrder);
for (j = 0; j < xOrder; j++) {
XXt[i][j] = 0.0;
XXtI[i][j] = 0.0;
}
XYt[i] = createArray(yOrder);
for (j = 0; j < yOrder; j++) {
XYt[i][j] = 0.0;
}
} // first find the pseudoinverse matrix
for (k = 0; k < numberOfSamples; k++) {
for (i = 0; i < xOrder; i++) {
// first calculate the XXt matrix, only do the upper half (symmetrical)
for (j = i; j < xOrder; j++) {
XXt[i][j] += xt[k][i] * xt[k][j];
} // now calculate the XYt matrix
for (j = 0; j < yOrder; j++) {
XYt[i][j] += xt[k][i] * yt[k][j];
}
}
} // now fill in the lower half of the XXt matrix
for (i = 0; i < xOrder; i++) {
for (j = 0; j < i; j++) {
XXt[i][j] = XXt[j][i];
}
}
var successFlag = invertMatrix(XXt, XXtI, xOrder); // next get the inverse of XXt
if (successFlag) {
for (i = 0; i < xOrder; i++) {
for (j = 0; j < yOrder; j++) {
mt[i][j] = 0.0;
for (k = 0; k < xOrder; k++) {
mt[i][j] += XXtI[i][k] * XYt[k][j];
}
}
}
} // Fix up any of the solutions that correspond to the homogeneous equation
// problem.
if (someHomogeneous) {
for (j = 0; j < yOrder; j++) {
if (homogenFlags[j]) {
// Fix this one
for (i = 0; i < xOrder; i++) {
mt[i][j] = hmt[i][0];
}
}
}
}
if (someHomogeneous) {
return homogRC && successFlag;
}
return successFlag;
}
function hex2float(hexStr) {
var outFloatArray = arguments.length > 1 && arguments[1] !== undefined ? arguments[1] : [0, 0.5, 1];
switch (hexStr.length) {
case 3:
// abc => #aabbcc
outFloatArray[0] = parseInt(hexStr[0], 16) * 17 / 255;
outFloatArray[1] = parseInt(hexStr[1], 16) * 17 / 255;
outFloatArray[2] = parseInt(hexStr[2], 16) * 17 / 255;
return outFloatArray;
case 4:
// #abc => #aabbcc
outFloatArray[0] = parseInt(hexStr[1], 16) * 17 / 255;
outFloatArray[1] = parseInt(hexStr[2], 16) * 17 / 255;
outFloatArray[2] = parseInt(hexStr[3], 16) * 17 / 255;
return outFloatArray;
case 6:
// ab01df => #ab01df
outFloatArray[0] = parseInt(hexStr.substr(0, 2), 16) / 255;
outFloatArray[1] = parseInt(hexStr.substr(2, 2), 16) / 255;
outFloatArray[2] = parseInt(hexStr.substr(4, 2), 16) / 255;
return outFloatArray;
case 7:
// #ab01df
outFloatArray[0] = parseInt(hexStr.substr(1, 2), 16) / 255;
outFloatArray[1] = parseInt(hexStr.substr(3, 2), 16) / 255;
outFloatArray[2] = parseInt(hexStr.substr(5, 2), 16) / 255;
return outFloatArray;
case 9:
// #ab01df00
outFloatArray[0] = parseInt(hexStr.substr(1, 2), 16) / 255;
outFloatArray[1] = parseInt(hexStr.substr(3, 2), 16) / 255;
outFloatArray[2] = parseInt(hexStr.substr(5, 2), 16) / 255;
outFloatArray[3] = parseInt(hexStr.substr(7, 2), 16) / 255;
return outFloatArray;
default:
return outFloatArray;
}
}
function rgb2hsv(rgb, hsv) {
var h;
var s;
var _rgb = _slicedToArray(rgb, 3),
r = _rgb[0],
g = _rgb[1],
b = _rgb[2];
var onethird = 1.0 / 3.0;
var onesixth = 1.0 / 6.0;
var twothird = 2.0 / 3.0;
var cmax = r;
var cmin = r;
if (g > cmax) {
cmax = g;
} else if (g < cmin) {
cmin = g;
}
if (b > cmax) {
cmax = b;
} else if (b < cmin) {
cmin = b;
}
var v = cmax;
if (v > 0.0) {
s = (cmax - cmin) / cmax;
} else {
s = 0.0;
}
if (s > 0) {
if (r === cmax) {
h = onesixth * (g - b) / (cmax - cmin);
} else if (g === cmax) {
h = onethird + onesixth * (b - r) / (cmax - cmin);
} else {
h = twothird + onesixth * (r - g) / (cmax - cmin);
}
if (h < 0.0) {
h += 1.0;
}
} else {
h = 0.0;
} // Set the values back to the array
hsv[0] = h;
hsv[1] = s;
hsv[2] = v;
}
function hsv2rgb(hsv, rgb) {
var _hsv = _slicedToArray(hsv, 3),
h = _hsv[0],
s = _hsv[1],
v = _hsv[2];
var onethird = 1.0 / 3.0;
var onesixth = 1.0 / 6.0;
var twothird = 2.0 / 3.0;
var fivesixth = 5.0 / 6.0;
var r;
var g;
var b; // compute RGB from HSV
if (h > onesixth && h <= onethird) {
// green/red
g = 1.0;
r = (onethird - h) / onesixth;
b = 0.0;
} else if (h > onethird && h <= 0.5) {
// green/blue
g = 1.0;
b = (h - onethird) / onesixth;
r = 0.0;
} else if (h > 0.5 && h <= twothird) {
// blue/green
b = 1.0;
g = (twothird - h) / onesixth;
r = 0.0;
} else if (h > twothird && h <= fivesixth) {
// blue/red
b = 1.0;
r = (h - twothird) / onesixth;
g = 0.0;
} else if (h > fivesixth && h <= 1.0) {
// red/blue
r = 1.0;
b = (1.0 - h) / onesixth;
g = 0.0;
} else {
// red/green
r = 1.0;
g = h / onesixth;
b = 0.0;
} // add Saturation to the equation.
r = s * r + (1.0 - s);
g = s * g + (1.0 - s);
b = s * b + (1.0 - s);
r *= v;
g *= v;
b *= v; // Assign back to the array
rgb[0] = r;
rgb[1] = g;
rgb[2] = b;
}
function lab2xyz(lab, xyz) {
// LAB to XYZ
var _lab = _slicedToArray(lab, 3),
L = _lab[0],
a = _lab[1],
b = _lab[2];
var var_Y = (L + 16) / 116;
var var_X = a / 500 + var_Y;
var var_Z = var_Y - b / 200;
if (Math.pow(var_Y, 3) > 0.008856) {
var_Y = Math.pow(var_Y, 3);
} else {
var_Y = (var_Y - 16.0 / 116.0) / 7.787;
}
if (Math.pow(var_X, 3) > 0.008856) {
var_X = Math.pow(var_X, 3);
} else {
var_X = (var_X - 16.0 / 116.0) / 7.787;
}
if (Math.pow(var_Z, 3) > 0.008856) {
var_Z = Math.pow(var_Z, 3);
} else {
var_Z = (var_Z - 16.0 / 116.0) / 7.787;
}
var ref_X = 0.9505;
var ref_Y = 1.0;
var ref_Z = 1.089;
xyz[0] = ref_X * var_X; // ref_X = 0.9505 Observer= 2 deg Illuminant= D65
xyz[1] = ref_Y * var_Y; // ref_Y = 1.000
xyz[2] = ref_Z * var_Z; // ref_Z = 1.089
}
function xyz2lab(xyz, lab) {
var _xyz = _slicedToArray(xyz, 3),
x = _xyz[0],
y = _xyz[1],
z = _xyz[2];
var ref_X = 0.9505;
var ref_Y = 1.0;
var ref_Z = 1.089;
var var_X = x / ref_X; // ref_X = 0.9505 Observer= 2 deg, Illuminant= D65
var var_Y = y / ref_Y; // ref_Y = 1.000
var var_Z = z / ref_Z; // ref_Z = 1.089
if (var_X > 0.008856) var_X = Math.pow(var_X, 1.0 / 3.0);else var_X = 7.787 * var_X + 16.0 / 116.0;
if (var_Y > 0.008856) var_Y = Math.pow(var_Y, 1.0 / 3.0);else var_Y = 7.787 * var_Y + 16.0 / 116.0;
if (var_Z > 0.008856) var_Z = Math.pow(var_Z, 1.0 / 3.0);else var_Z = 7.787 * var_Z + 16.0 / 116.0;
lab[0] = 116 * var_Y - 16;
lab[1] = 500 * (var_X - var_Y);
lab[2] = 200 * (var_Y - var_Z);
}
function xyz2rgb(xyz, rgb) {
var _xyz2 = _slicedToArray(xyz, 3),
x = _xyz2[0],
y = _xyz2[1],
z = _xyz2[2];
var r = x * 3.2406 + y * -1.5372 + z * -0.4986;
var g = x * -0.9689 + y * 1.8758 + z * 0.0415;
var b = x * 0.0557 + y * -0.204 + z * 1.057; // The following performs a "gamma correction" specified by the sRGB color
// space. sRGB is defined by a canonical definition of a display monitor and
// has been standardized by the International Electrotechnical Commission (IEC
// 61966-2-1). The nonlinearity of the correction is designed to make the
// colors more perceptually uniform. This color space has been adopted by
// several applications including Adobe Photoshop and Microsoft Windows color
// management. OpenGL is agnostic on its RGB color space, but it is reasonable
// to assume it is close to this one.
if (r > 0.0031308) r = 1.055 * Math.pow(r, 1 / 2.4) - 0.055;else r *= 12.92;
if (g > 0.0031308) g = 1.055 * Math.pow(g, 1 / 2.4) - 0.055;else g *= 12.92;
if (b > 0.0031308) b = 1.055 * Math.pow(b, 1 / 2.4) - 0.055;else b *= 12.92; // Clip colors. ideally we would do something that is perceptually closest
// (since we can see colors outside of the display gamut), but this seems to
// work well enough.
var maxVal = r;
if (maxVal < g) maxVal = g;
if (maxVal < b) maxVal = b;
if (maxVal > 1.0) {
r /= maxVal;
g /= maxVal;
b /= maxVal;
}
if (r < 0) r = 0;
if (g < 0) g = 0;
if (b < 0) b = 0; // Push values back to array
rgb[0] = r;
rgb[1] = g;
rgb[2] = b;
}
function rgb2xyz(rgb, xyz) {
var _rgb2 = _slicedToArray(rgb, 3),
r = _rgb2[0],
g = _rgb2[1],
b = _rgb2[2]; // The following performs a "gamma correction" specified by the sRGB color
// space. sRGB is defined by a canonical definition of a display monitor and
// has been standardized by the International Electrotechnical Commission (IEC
// 61966-2-1). The nonlinearity of the correction is designed to make the
// colors more perceptually uniform. This color space has been adopted by
// several applications including Adobe Photoshop and Microsoft Windows color
// management. OpenGL is agnostic on its RGB color space, but it is reasonable
// to assume it is close to this one.
if (r > 0.04045) r = Math.pow((r + 0.055) / 1.055, 2.4);else r /= 12.92;
if (g > 0.04045) g = Math.pow((g + 0.055) / 1.055, 2.4);else g /= 12.92;
if (b > 0.04045) b = Math.pow((b + 0.055) / 1.055, 2.4);else b /= 12.92; // Observer. = 2 deg, Illuminant = D65
xyz[0] = r * 0.4124 + g * 0.3576 + b * 0.1805;
xyz[1] = r * 0.2126 + g * 0.7152 + b * 0.0722;
xyz[2] = r * 0.0193 + g * 0.1192 + b * 0.9505;
}
function rgb2lab(rgb, lab) {
var xyz = [0, 0, 0];
rgb2xyz(rgb, xyz);
xyz2lab(xyz, lab);
}
function lab2rgb(lab, rgb) {
var xyz = [0, 0, 0];
lab2xyz(lab, xyz);
xyz2rgb(xyz, rgb);
}
function uninitializeBounds(bounds) {
bounds[0] = 1.0;
bounds[1] = -1.0;
bounds[2] = 1.0;
bounds[3] = -1.0;
bounds[4] = 1.0;
bounds[5] = -1.0;
}
function areBoundsInitialized(bounds) {
return !(bounds[1] - bounds[0] < 0.0);
}
function computeBoundsFromPoints(point1, point2, bounds) {
bounds[0] = Math.min(point1[0], point2[0]);
bounds[1] = Math.max(point1[0], point2[0]);
bounds[2] = Math.min(point1[1], point2[1]);
bou