Rogelio J. Baucells a80d135b56 multiply() - poc
2015-04-28 00:22:23 -04:00

472 lines
12 KiB
JavaScript

'use strict';
var clone = require('../../util/object').clone;
var DimensionError = require('../../error/DimensionError');
function factory (type, config, load, typed) {
var unaryMinus = load(require('./unaryMinus'));
var matrix = load(require('../construction/matrix'));
var equal = load(require('../relational/equal'));
var sparseScatter = load(require('./sparseScatter'));
var addScalar = load(require('./addScalar'));
var multiplyScalar = load(require('./multiplyScalar'));
var collection = load(require('../../type/collection'));
var DenseMatrix = type.DenseMatrix,
SparseMatrix = type.SparseMatrix;
/**
* Subtract two values, `x - y`.
* For matrices, the function is evaluated element wise.
*
* Syntax:
*
* math.subtract(x, y)
*
* Examples:
*
* math.subtract(5.3, 2); // returns Number 3.3
*
* var a = math.complex(2, 3);
* var b = math.complex(4, 1);
* math.subtract(a, b); // returns Complex -2 + 2i
*
* math.subtract([5, 7, 4], 4); // returns Array [1, 3, 0]
*
* var c = math.unit('2.1 km');
* var d = math.unit('500m');
* math.subtract(c, d); // returns Unit 1.6 km
*
* See also:
*
* add
*
* @param {Number | BigNumber | Boolean | Complex | Unit | Array | Matrix | null} x
* Initial value
* @param {Number | BigNumber | Boolean | Complex | Unit | Array | Matrix | null} y
* Value to subtract from `x`
* @return {Number | BigNumber | Complex | Unit | Array | Matrix}
* Subtraction of `x` and `y`
*/
var subtract = typed('subtract', {
'number, number': function (x, y) {
return x - y;
},
'Complex, Complex': function (x, y) {
return new type.Complex (
x.re - y.re,
x.im - y.im
);
},
'BigNumber, BigNumber': function (x, y) {
return x.minus(y);
},
'Unit, Unit': function (x, y) {
if (x.value == null) {
throw new Error('Parameter x contains a unit with undefined value');
}
if (y.value == null) {
throw new Error('Parameter y contains a unit with undefined value');
}
if (!x.equalBase(y)) {
throw new Error('Units do not match');
}
var res = x.clone();
res.value -= y.value;
res.fixPrefix = false;
return res;
},
'Matrix, Matrix': function (x, y) {
// matrix sizes
var xsize = x.size();
var ysize = y.size();
// check dimensions
if (xsize.length !== ysize.length)
throw new DimensionError(xsize.length, ysize.length);
// result
var c;
// process matrix storage
switch (x.storage()) {
case 'sparse':
switch (y.storage()) {
case 'sparse':
// sparse - sparse
c = _subtractSparseMatrixSparseMatrix(x, y, xsize, ysize);
break;
default:
c = _subtractSparseMatrixMatrix(x, y.valueOf(), xsize, ysize);
break;
}
break;
default:
switch (y.storage()) {
case 'sparse':
// sparse - sparse
c = _subtractMatrixSparseMatrix(x.valueOf(), y, xsize, ysize);
break;
default:
c = _subtractMatrixMatrix(x.valueOf(), y.valueOf(), x.storage());
break;
}
break;
}
return c;
},
'Array, Array': function (x, y) {
// use matrix implementation
return subtract(matrix(x), matrix(y)).valueOf();
},
'Array, Matrix': function (x, y) {
// use matrix implementation
return subtract(matrix(x), y);
},
'Matrix, Array': function (x, y) {
// use matrix implementation
return subtract(x, matrix(y));
},
'Matrix, any': function (x, y) {
// result
var c;
// check storage format
switch (x.storage()) {
case 'sparse':
c = _subtractSparseMatrixScalar(x, y, x.size());
break;
default:
c = collection.deepMap2(x, y, subtract);
break;
}
return c;
},
'any, Matrix': function (x, y) {
// result
var c;
// check storage format
switch (y.storage()) {
case 'sparse':
c = _subtractScalarSparseMatrix(x, y, y.size());
break;
default:
c = collection.deepMap2(x, y, subtract);
break;
}
return c;
},
'Array, any': function (x, y) {
return collection.deepMap2(x, y, subtract);
},
'any, Array': function (x, y) {
return collection.deepMap2(x, y, subtract);
}
});
/**
* C = A - B
*
* @param {Matrix} a SparseMatrix (MxN)
* @param {Scalar} b Scalar value
*
* @return {Matrix} SparseMatrix (MxN)
*/
var _subtractSparseMatrixScalar = function (a, b, asize) {
// rows and columns
var m = asize[0];
var n = asize[1];
// a arrays
var avalues = a._values;
var aindex = a._index;
var aptr = a._ptr;
// check b is zero
if (!equal(b, 0)) {
// c arrays
var cvalues = [];
var cindex = [];
var cptr = new Array(n);
// c matrix
var c = new SparseMatrix({
values: cvalues,
index: cindex,
ptr: cptr,
size: [m, n]
});
// loop columns
for (var j = 0; j < n; j++) {
// ptr for column j
cptr[j] = cindex.length;
// loop values for column j
for (var k0 = aptr[j], k1 = aptr[j + 1], k = k0; k < k1; k++) {
// subtract values
var v = subtract(avalues[k], b);
// compare with zero
if (!equal(v, 0)) {
// push to c
cindex.push(aindex[k]);
cvalues.push(v);
}
}
}
// update ptr
cptr[n] = cindex.length;
// return matrix
return c;
}
// return clone
return a.clone();
};
/**
* C = A - B
*
* @param {Scalar} a Scalar value
* @param {Matrix} b SparseMatrix (MxN)
*
* @return {Matrix} SparseMatrix (MxN)
*/
var _subtractScalarSparseMatrix = function (a, b, asize) {
// rows and columns
var m = asize[0];
var n = asize[1];
// b arrays
var bvalues = b._values;
var bindex = b._index;
var bptr = b._ptr;
// check a is zero
if (!equal(a, 0)) {
// c arrays
var cvalues = [];
var cindex = [];
var cptr = new Array(n);
// c matrix
var c = new SparseMatrix({
values: cvalues,
index: cindex,
ptr: cptr,
size: [m, n]
});
// loop columns
for (var j = 0; j < n; j++) {
// ptr for column j
cptr[j] = cindex.length;
// loop values for column j
for (var k0 = bptr[j], k1 = bptr[j + 1], k = k0; k < k1; k++) {
// subtract values
var v = subtract(a, bvalues[k]);
// compare with zero
if (!equal(v, 0)) {
// push to c
cindex.push(bindex[k]);
cvalues.push(v);
}
}
}
// update ptr
cptr[n] = cindex.length;
// return matrix
return c;
}
// return clone
return b.clone();
};
/**
* C = A - B
*
* @param {Matrix} a SparseMatrix (MxN)
* @param {Matrix} b SparseMatrix (MxN)
*
* @return {Matrix} SparseMatrix (MxN)
*/
var _subtractSparseMatrixSparseMatrix = function (a, b, asize, bsize) {
// check dimensions
if (asize[0] !== bsize[0] || asize[1] !== bsize[1])
throw new RangeError('Dimension mismatch in add. Matrix A (' + asize + ') must match Matrix B (' + bsize + ')');
// rows and columns
var m = asize[0];
var n = asize[1];
// a arrays
var avalues = a._values;
// b arrays
var bvalues = b._values;
// flag indicating both matrices (a & b) contain data
var values = avalues && bvalues;
// c arrays
var cvalues = values ? [] : undefined;
var cindex = [];
var cptr = new Array(n);
// c matrix
var c = new SparseMatrix({
values: cvalues,
index: cindex,
ptr: cptr,
size: [m, n]
});
// column vector (store matrix values)
var x = values ? new Array(m) : undefined;
// column vector to signal row values in column j
var w = new Array(m);
// loop columns
for (var j = 0; j < n; j++) {
// init ptr for j
cptr[j] = cindex.length;
// process column j of a and write it to x
sparseScatter(a, j, 1, w, x, j + 1, c, multiplyScalar, addScalar);
// process column j of b and write it to x (multiply value by negative one)
sparseScatter(b, j, -1, w, x, j + 1, c, multiplyScalar, addScalar);
// check matrix contains values (pattern matrix)
if (values) {
// loop column values in C
for (var p0 = cptr[j], p1 = cindex.length, p = p0; p < p1; p++) {
// copy x[i] to c[i, j]
cvalues.push(x[cindex[p]]);
}
}
}
// finish cptr
cptr[n] = cindex.length;
// return matrix
return c;
};
/**
* C = A - B
*
* @param {Matrix} a SparseMatrix (MxN)
* @param {Matrix} b DenseMatrix (MxN)
*
* @return {Matrix} SparseMatrix (MxN)
*/
var _subtractSparseMatrixMatrix = function (a, b, asize, bsize) {
// check dimensions
if (asize[0] !== bsize[0] || asize[1] !== bsize[1])
throw new RangeError('Dimension mismatch in add. Matrix A (' + asize + ') must match Matrix B (' + bsize + ')');
// rows and columns
var m = asize[0];
var n = asize[1];
// b array
var data = b;
// c arrays
var cvalues = [];
var cindex = [];
var cptr = new Array(n);
// c matrix
var c = new SparseMatrix({
values: cvalues,
index: cindex,
ptr: cptr,
size: [m, n]
});
// column vector (store matrix values)
var x = new Array(m);
// column vector to signal row values in column j
var w = new Array(m);
// loop columns
for (var j = 0; j < n; j++) {
// init ptr for j
cptr[j] = cindex.length;
// copy matrix b column to x
for (var i = 0; i < m; i++) {
// -value
var v = unaryMinus(data[i][j]);
// check for zero
if (!equal(v, 0)) {
x[i] = v;
w[i] = j + 1;
cindex.push(i);
}
}
// process column j of a and write it to x
sparseScatter(a, j, 1, w, x, j + 1, c, multiplyScalar, addScalar);
// loop column values in C
for (var p0 = cptr[j], p1 = cindex.length, p = p0; p < p1; p++) {
// copy x[i] to c[i, j]
cvalues.push(x[cindex[p]]);
}
}
// finish cptr
cptr[n] = cindex.length;
// return matrix
return c;
};
/**
* C = A - B
*
* @param {Matrix} a DenseMatrix (MxN)
* @param {Matrix} b SparseMatrix (MxN)
*
* @return {Matrix} DenseMatrix (MxN)
*/
var _subtractMatrixSparseMatrix = function (a, b, asize, bsize) {
// check dimensions
if (asize[0] !== bsize[0] || asize[1] !== bsize[1])
throw new RangeError('Dimension mismatch in add. Matrix A (' + asize + ') must match Matrix B (' + bsize + ')');
// rows and columns
var m = asize[0];
var n = asize[1];
// a array
var data = a;
// b arrays
var bvalues = b._values;
var bindex = b._index;
var bptr = b._ptr;
// c arrays
var cdata = clone(data);
// c matrix
var c = new DenseMatrix({
data: cdata,
size: [m, n]
});
// loop columns
for (var j = 0; j < n; j++) {
// loop values for column j
for (var k0 = bptr[j], k1 = bptr[j + 1], k = k0; k < k1; k++) {
// row
var i = bindex[k];
// subtract value
cdata[i][j] = subtract(cdata[i][j], bvalues[k]);
}
}
// return matrix
return c;
};
/**
* C = A - B
*
* @param {Matrix} a DenseMatrix (MxN)
* @param {Matrix} b DenseMatrix (MxN)
*
* @return {Matrix} DenseMatrix (MxN)
*/
var _subtractMatrixMatrix = function (a, b, format) {
// TODO: find a better implementation
return matrix(collection.deepMap2(a, b, subtract), format);
};
return subtract;
}
exports.name = 'subtract';
exports.factory = factory;