mathjs/src/function/algebra/solver/utils/solveValidation.js

Math.js is an extensive math library for JavaScript and Node.js. It features a flexible expression parser with support for symbolic computation, comes with a large set of built-in functions and constants, and offers an integrated solution to work with dif

import { isArray, isDenseMatrix, isMatrix } from '../../../../utils/is'
import { arraySize } from '../../../../utils/array'
import { format } from '../../../../utils/string'

export function createSolveValidation ({ DenseMatrix }) {
  /**
   * Validates matrix and column vector b for backward/forward substitution algorithms.
   *
   * @param {Matrix} m            An N x N matrix
   * @param {Array | Matrix} b    A column vector
   * @param {Boolean} copy        Return a copy of vector b
   *
   * @return {DenseMatrix}        Dense column vector b
   */
  return function solveValidation (m, b, copy) {
    // matrix size
    const size = m.size()
    // validate matrix dimensions
    if (size.length !== 2) { throw new RangeError('Matrix must be two dimensional (size: ' + format(size) + ')') }
    // rows & columns
    const rows = size[0]
    const columns = size[1]
    // validate rows & columns
    if (rows !== columns) { throw new RangeError('Matrix must be square (size: ' + format(size) + ')') }
    // vars
    let data, i, bdata
    // check b is matrix
    if (isMatrix(b)) {
      // matrix size
      const msize = b.size()
      // vector
      if (msize.length === 1) {
        // check vector length
        if (msize[0] !== rows) { throw new RangeError('Dimension mismatch. Matrix columns must match vector length.') }
        // create data array
        data = []
        // matrix data (DenseMatrix)
        bdata = b._data
        // loop b data
        for (i = 0; i < rows; i++) {
          // row array
          data[i] = [bdata[i]]
        }
        // return Dense Matrix
        return new DenseMatrix({
          data: data,
          size: [rows, 1],
          datatype: b._datatype
        })
      }
      // two dimensions
      if (msize.length === 2) {
        // array must be a column vector
        if (msize[0] !== rows || msize[1] !== 1) { throw new RangeError('Dimension mismatch. Matrix columns must match vector length.') }
        // check matrix type
        if (isDenseMatrix(b)) {
          // check a copy is needed
          if (copy) {
            // create data array
            data = []
            // matrix data (DenseMatrix)
            bdata = b._data
            // loop b data
            for (i = 0; i < rows; i++) {
              // row array
              data[i] = [bdata[i][0]]
            }
            // return Dense Matrix
            return new DenseMatrix({
              data: data,
              size: [rows, 1],
              datatype: b._datatype
            })
          }
          // b is already a column vector
          return b
        }
        // create data array
        data = []
        for (i = 0; i < rows; i++) { data[i] = [0] }
        // sparse matrix arrays
        const values = b._values
        const index = b._index
        const ptr = b._ptr
        // loop values in column 0
        for (let k1 = ptr[1], k = ptr[0]; k < k1; k++) {
          // row
          i = index[k]
          // add to data
          data[i][0] = values[k]
        }
        // return Dense Matrix
        return new DenseMatrix({
          data: data,
          size: [rows, 1],
          datatype: b._datatype
        })
      }
      // throw error
      throw new RangeError('Dimension mismatch. Matrix columns must match vector length.')
    }
    // check b is array
    if (isArray(b)) {
      // size
      const asize = arraySize(b)
      // check matrix dimensions, vector
      if (asize.length === 1) {
        // check vector length
        if (asize[0] !== rows) { throw new RangeError('Dimension mismatch. Matrix columns must match vector length.') }
        // create data array
        data = []
        // loop b
        for (i = 0; i < rows; i++) {
          // row array
          data[i] = [b[i]]
        }
        // return Dense Matrix
        return new DenseMatrix({
          data: data,
          size: [rows, 1]
        })
      }
      if (asize.length === 2) {
        // array must be a column vector
        if (asize[0] !== rows || asize[1] !== 1) { throw new RangeError('Dimension mismatch. Matrix columns must match vector length.') }
        // create data array
        data = []
        // loop b data
        for (i = 0; i < rows; i++) {
          // row array
          data[i] = [b[i][0]]
        }
        // return Dense Matrix
        return new DenseMatrix({
          data: data,
          size: [rows, 1]
        })
      }
      // throw error
      throw new RangeError('Dimension mismatch. Matrix columns must match vector length.')
    }
  }
}