mathjs/lib/function/algebra/solver/forwardSubstitution.js
2015-04-12 23:55:17 -04:00

246 lines
6.6 KiB
JavaScript

'use strict';
function factory (type, config, load, typed) {
var matrix = load(require('../../construction/matrix'));
var divideScalar = load(require('../../arithmetic/divideScalar'));
var multiply = load(require('../../arithmetic/multiply'));
var subtract = load(require('../../arithmetic/subtract'));
var equal = load(require('../../relational/equal'));
var substitutionValidation = load(require('./substitutionValidation'));
var CcsMatrix = type.CcsMatrix;
var CrsMatrix = type.CrsMatrix;
var DenseMatrix = type.DenseMatrix;
/**
* Solves the linear equation system by forwards substitution. Matrix must be a lower triangular matrix.
*
* M * x = b
*
* @param {Matrix, Array} A N x N matrix or array
* @param {Matrix, Array} A column vector with the b values
*
* @return {Matrix} A column vector with the linear system solution
*/
var forwardSubstitution = typed('forwardSubstitution', {
'Matrix, Array | Matrix': function (m, b) {
// process matrix storage format
switch (m.storage()) {
case 'dense':
return _denseForwardSubstitution(m, b);
case 'ccs':
return _ccsForwardSubstitution(m, b);
case 'crs':
return _crsForwardSubstitution(m, b);
}
},
'Array, Array | Matrix': function (a, b) {
// create dense matrix from array
var m = matrix(a);
// use matrix implementation
var r = forwardSubstitution(m, b);
// result
return r.valueOf();
}
});
var _denseForwardSubstitution = function (m, b) {
// validate matrix and vector, return copy of column vector b
b = substitutionValidation(m, b);
// rows & columns
var rows = m._size[0];
var columns = m._size[1];
// result
var x = new Array(rows);
// data
var data = m._data;
// forward solve m * x = b, loop columns
for (var j = 0; j < columns; j++) {
// b[j]
var bj = b[j] || 0;
// x[j]
var xj;
// forward substitution (outer product) avoids inner looping when bj == 0
if (!equal(bj, 0)) {
// value @ [j, j]
var vjj = data[j][j];
// check vjj
if (equal(vjj, 0)) {
// system cannot be solved
throw new Error('Linear system cannot be solved since matrix is singular');
}
// calculate xj
xj = divideScalar(bj, vjj);
// loop rows
for (var i = j + 1; i < rows; i++) {
// update copy of b
b[i] = subtract(b[i] || 0, multiply(xj, data[i][j]));
}
}
else {
// zero @ j
xj = 0;
}
// update x
x[j] = [xj];
}
// return vector
return new DenseMatrix({
data: x,
size: [rows, 1]
});
};
var _ccsForwardSubstitution = function (m, b) {
// validate matrix and vector, return copy of column vector b
b = substitutionValidation(m, b);
// rows & columns
var rows = m._size[0];
var columns = m._size[1];
// matrix arrays
var values = m._values;
var index = m._index;
var ptr = m._ptr;
// result arrays
var xvalues = [];
var xindex = [];
var xptr = [];
// vars
var i, k;
// init ptr
xptr.push(0);
// forward solve m * x = b, loop columns
for (var j = 0; j < columns; j++) {
// b[j]
var bj = b[j] || 0;
// forward substitution (outer product) avoids inner looping when bj == 0
if (!equal(bj, 0)) {
// value @ [j, j]
var vjj = 0;
// last index in column
var l = ptr[j + 1];
// values in column, find value @ [j, j]
for (k = ptr[j]; k < l; k++) {
// row
i = index[k];
// check row
if (i === j) {
// update vjj
vjj = values[k];
}
else if (i > j) {
// exit loop
break;
}
}
// at this point we must have a value @ [j, j]
if (equal(vjj, 0)) {
// system cannot be solved, there is no value @ [j, j]
throw new Error('Linear system cannot be solved since matrix is singular');
}
// calculate xj
var xj = divideScalar(bj, vjj);
// values in column, continue from last loop
for (; k < l; k++) {
// row
i = index[k];
// update copy of b
b[i] = subtract(b[i] || 0, multiply(xj, values[k]));
}
// check for non zero
if (!equal(xj, 0)) {
// value @ row i
xvalues.push(xj);
// row
xindex.push(j);
}
}
}
// update ptr
xptr.push(xvalues.length);
// return column vector
return new CcsMatrix({
values: xvalues,
index: xindex,
ptr: xptr,
size: [rows, 1]
});
};
var _crsForwardSubstitution = function (m, b) {
// validate matrix and vector, initialize x as copy of column vector b
var x = substitutionValidation(m, b);
// rows & columns
var rows = m._size[0];
// matrix arrays
var values = m._values;
var index = m._index;
var ptr = m._ptr;
// result arrays
var xvalues = [];
var xindex = [];
var xptr = [];
// forward solve m * x = b
for (var i = 0; i < rows; i++) {
// update ptr
xptr.push(xvalues.length);
// initialize x
var xi = x[i] || 0;
// value @ [i, i]
var vii = 0;
// values in row
for (var k = ptr[i], l = ptr[i + 1]; k < l; k++) {
// column
var j = index[k];
// check column
if (j < i) {
// update x
xi = subtract(xi, multiply(values[k], x[j]));
}
else if (j === i) {
// set vii value
vii = values[k];
// exit loop
break;
}
else {
// exit loop, singular matrix
break;
}
}
// check we have a value @ [i, i]
if (equal(vii, 0)) {
// system cannot be solved, there is no value @ [i, i]
throw new Error('Linear system cannot be solved since matrix is singular');
}
// update xi
xi = divideScalar(xi, vii);
// check for zero
if (!equal(xi, 0)) {
// push to values
xvalues.push(xi);
// column vector
xindex.push(0);
}
// update dense vector
x[i] = xi;
}
// update ptr
xptr.push(xvalues.length);
// return column vector
return new CrsMatrix({
values: xvalues,
index: xindex,
ptr: xptr,
size: [rows, 1]
});
};
return forwardSubstitution;
}
exports.name = 'forwardSubstitution';
exports.factory = factory;