Python 实现简单的矩阵

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    #!/usr/bin/python   
    # -*- coding: utf-8 -*-  
      
    ''''' 
    Created on 2015-1-7 
    @author: beyondzhou 
    @name: myarray.py 
    '''  
      
    # Implementation of the Matrix ADT using a 2D array  
    from myarray import Array2D  
      
    class 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,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,print 'r'    
              
        print 'nThe primary value of fmatrix'  
        for i in range(fMatrix.numRows()):  
            for j in range(fMatrix.numCols()):  
                print '%s ' % fMatrix[i,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,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,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,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,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,print 'r'     
              
                   
          
           
    if __name__ == "__main__":  
        test_matrix()  

    The primary value of amatrix  
    0.886197406941  0.304295996721  0.293469382347    
    0.154702139448  0.511075267985  0.387057640727    
      
    The primary value of bmatrix  
    0.574674206609  0.364815615899  0.493367650314    
    0.438101377839  0.801271107474  0.0891226289712    
      
    The primary value of fmatrix  
    0.00716087704081  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 amatrix  
    2.65859222082  0.912887990162  0.88040814704    
    0.464106418343  1.53322580395  1.16117292218    
      
    The transpose value of amatrix  
    2.65859222082  0.464106418343    
    0.912887990162  1.53322580395    
    0.88040814704  1.16117292218    

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