Python 实现简单的矩阵，python实现矩阵, #!/usr/b

Python 实现简单的矩阵，python实现矩阵, #!/usr/b

    #!/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, 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 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