Python implements a simple matrix

Python implements a simple matrix

#!/usr/bin/python # -*- coding: utf-8 -*-'''Created on 2015-1-7@author: beyondzhou@name: myarray.py'''# Implementation of the Matrix ADT using a 2D arrayfrom myarray import Array2Dclass Matrix:    # Creates a matrix of size numRows * numCols initialized to 0    def __init__(self, numRows, numCols):        self._theGrid = Array2D(numRows, numCols)        self._theGrid.clear(0)    # Returns the number of rows in the matrix    def numRows(self):        return self._theGrid.numRows()    # Returns the number of columns in the matrix    def numCols(self):        return self._theGrid.numCols()    # Returns the value of element (i, j): x[i, j]    def __getitem__(self, ndxTuple):        return self._theGrid[ndxTuple[0], ndxTuple[1]]    # Sets the value of element (i,j) to the value s: x[i, j] = s    def __setitem__(self, ndxTuple, scalar):        self._theGrid[ndxTuple[0], ndxTuple[1]] = scalar    # Scales the matrix by the given scalar    def scaleBy(self, scalar):        for r in range(self.numRows()):            for c in range(self.numCols()):                self[r,c] *= scalar    # Creates and returns a new matrix that is the transpose of this matrix    def transpose(self):        # Create the new matrix        newMatrix = Matrix(self.numCols(), self.numRows())        # Add the corresponding elements in the two matrices        for r in range(self.numRows()):            for c in range(self.numCols()):                newMatrix[c,r] = self[r,c]         return newMatrix    # Creates and returns a new matrix that results from matrix addition    def __add__(self, rhsMatrix):        assert rhsMatrix.numRows() == self.numRows() and \                rhsMatrix.numCols() == self.numCols(), \                  "Matrix sizes not compatible for the add operation."        # Create the new matrix        newMatrix = Matrix(self.numRows(), self.numCols())        # Add the corresponding elements in the two matrices        for r in range(self.numRows()):            for c in range(self.numCols()):                newMatrix[r,c] = self[r,c] + rhsMatrix[r,c]        return newMatrix    # Creates and returns a new matrix that results from matrix sub    def __sub__(self, rhsMatrix):        assert rhsMatrix.numRows() == self.numRows() and \                rhsMatrix.numCols() == self.numCols(), \                  "Matrix sizes not compatible for the add operation."        # Create the new matrix        newMatrix = Matrix(self.numRows(), self.numCols())        # Add the corresponding elements in the two matrices        for r in range(self.numRows()):            for c in range(self.numCols()):                newMatrix[r,c] = self[r,c] - rhsMatrix[r,c]        return newMatrix    # Creates and returns a new matrix resulting from matrix multiplcation    def __mul__(self, rhsMatrix):        assert rhsMatrix.numRows() == self.numCols(), \                  "Matrix sizes not compatible for the multi operation."        # Create the new matrix        newMatrix = Matrix(self.numRows(), rhsMatrix.numCols())                # Mul the corresponding elements in the two matrices        for r in range(self.numRows()):            for c in range(rhsMatrix.numCols()):                mysum = 0.0                for k in range(self.numCols()):                    mysum += self[r,k] * rhsMatrix[k,r]                newMatrix[r,c] = mysum        return newMatrix

#!/usr/bin/python # -*- coding: utf-8 -*-'''Created on 2015-1-7@author: beyondzhou@name: test_matrix.py'''def test_matrix():       # Import    from mymatrix import Matrix    import random    # set default value for matrix    aMatrix = Matrix(2,3)    bMatrix = Matrix(2,3)    fMatrix = Matrix(3,2)    for i in range(aMatrix.numRows()):        for j in range(aMatrix.numCols()):            aMatrix[i,j] = random.random()            bMatrix[i,j] = random.random()    for i in range(fMatrix.numRows()):        for j in range(fMatrix.numCols()):            fMatrix[i,j] = random.random()                         print 'The primary value of amatrix'    for i in range(aMatrix.numRows()):        for j in range(aMatrix.numCols()):            print '%s ' % aMatrix[i,j],         print '\r'       print '\nThe primary value of bmatrix'    for i in range(bMatrix.numRows()):        for j in range(bMatrix.numCols()):            print '%s ' % bMatrix[i,j],         print '\r'              print '\nThe primary value of fmatrix'    for i in range(fMatrix.numRows()):        for j in range(fMatrix.numCols()):            print '%s ' % fMatrix[i,j],         print '\r'        # add amatrix and bmatrix to cmatrix    cMatrix = aMatrix + bMatrix        print '\nThe value of cMatrix (aMatrix + bMatrix)'    for i in range(cMatrix.numRows()):        for j in range(cMatrix.numCols()):            print '%s ' % cMatrix[i,j],         print '\r'       # sub amatrix and bmatrix to dmatrix    dMatrix = aMatrix - bMatrix        print '\nThe value of dMatrix (aMatrix - bMatrix)'    for i in range(dMatrix.numRows()):        for j in range(dMatrix.numCols()):            print '%s ' % dMatrix[i,j],         print '\r'          # Mul amatrix and fMatrix to ematrix    eMatrix = aMatrix * fMatrix        print '\nThe value of eMatrix (aMatrix * fMatrix)'    for i in range(eMatrix.numRows()):        for j in range(eMatrix.numCols()):            print '%s ' % eMatrix[i,j],         print '\r'                                # Scale the amatrix by 3    aMatrix.scaleBy(3)        print '\nThe scale value of amatrix'    for i in range(aMatrix.numRows()):        for j in range(aMatrix.numCols()):            print '%s ' % aMatrix[i,j],         print '\r'               # Transpose the amatrix     dMatrix = aMatrix.transpose()        print '\nThe transpose value of amatrix'    for i in range(dMatrix.numRows()):        for j in range(dMatrix.numCols()):            print '%s ' % dMatrix[i,j],         print '\r'                                 if __name__ == "__main__":    test_matrix()

Result:

The primary value of amatrix0.886197406941  0.304295996721  0.293469382347  0.154702139448  0.511075267985  0.387057640727  The primary value of bmatrix0.574674206609  0.364815615899  0.493367650314  0.438101377839  0.801271107474  0.0891226289712  The primary value of fmatrix0.00716087704081  0.537519043084  0.451888654276  0.234306298527  0.572987747957  0.479059183861  The value of cMatrix (aMatrix + bMatrix)1.46087161355  0.66911161262  0.78683703266  0.592803517287  1.31234637546  0.476180269699  The value of dMatrix (aMatrix - bMatrix)0.311523200332  -0.0605196191784  -0.199898267967  -0.283399238391  -0.290195839489  0.297935011756  The value of eMatrix (aMatrix * fMatrix)0.31200821961  0.31200821961  0.388327017743  0.388327017743  The scale value of amatrix2.65859222082  0.912887990162  0.88040814704  0.464106418343  1.53322580395  1.16117292218  The transpose value of amatrix2.65859222082  0.464106418343  0.912887990162  1.53322580395  0.88040814704  1.16117292218