def _negate_column(self, matrix, dim, min_row, column_i, secondary_matrix=None, secondary_dim=(0, 0)):
for k in range(min_row, dim[0]):
matrix[k][column_i] *= -1
if secondary_matrix is not None:
for k in range(secondary_dim[1]):
secondary_matrix[column_i][k] *= -1
self._transform = mh.multiply_matrices(self._transform, [[self._negate_transform_value(i, j, column_i) for j in range(self._m1_base)] for i in range(self._m1_base)], (self._m1_base, self._m1_base), (self._m1_base, self._m1_base))
def _add_row(self, matrix, dim, min_column, row_i, row_j, coefficient, save_to_transform=False):
'''Add row_i to the row_j with coefficient c
If save_to_transform=True, then we should save transformation in transform matrix, because we make it fro M2 and change the basis of the M1
'''
for k in range(min_column, dim[1]):
matrix[row_j][k] += coefficient * matrix[row_i][k]
if save_to_transform:
self._transform = mh.multiply_matrices(self._transform, [[self._add_transform_value(i, j, row_j, row_i, -1*coefficient) for j in range(self._m1_base)] for i in range(self._m1_base)], (self._m1_base, self._m1_base), (self._m1_base, self._m1_base))
def _negate_row(self, matrix, dim, min_column, row_i, secondary_matrix=None, secondary_dim=(0, 0), save_to_transform=False):
for k in range(min_column, dim[1]):
matrix[row_i][k] *= -1
if secondary_matrix is not None:
for k in range(secondary_dim[0]):
secondary_matrix[k][row_i] *= -1
if save_to_transform:
self._transform = mh.multiply_matrices(self._transform, [[self._negate_transform_value(i, j, row_i) for j in range(self._m1_base)] for i in range(self._m1_base)], (self._m1_base, self._m1_base), (self._m1_base, self._m1_base))
def _add_column(self, matrix, dim, min_row, column_i, column_j, coefficient, secondary_matrix=None, secondary_dim=(0, 0)):
'''Add column_i to the column_j with coefficient c
For secondary matrix subtract from i-th row the j-th row with coefficient c
'''
for k in range(min_row, dim[0]):
matrix[k][column_j] += coefficient*matrix[k][column_i]
if secondary_matrix is not None:
for k in range(secondary_dim[1]):
secondary_matrix[column_i][k] -= coefficient*secondary_matrix[column_j][k]
self._transform = mh.multiply_matrices(self._transform, [[self._add_transform_value(i, j, column_i, column_j, coefficient) for j in range(self._m1_base)] for i in range(self._m1_base)], (self._m1_base, self._m1_base), (self._m1_base, self._m1_base))
def _switch_row(self, matrix, dim, min_column, row_i, row_j, second_matrix=None, second_dim=(0, 0), save_to_transform=False):
'''If second matrix is not None, switch columns of it
'''
for k in range(min_column, dim[1]):
c = matrix[row_i][k]
matrix[row_i][k] = matrix[row_j][k]
matrix[row_j][k] = c
if second_matrix is not None:
for k in range(second_dim[0]):
c = second_matrix[k][row_i]
second_matrix[k][row_i] = second_matrix[k][row_j]
second_matrix[k][row_j] = c
if second_matrix is not None or save_to_transform:
self._transform = mh.multiply_matrices(self._transform, [[self._switch_transfrom_value(i, j, row_i, row_j) for j in range(self._m1_base)] for i in range(self._m1_base)], (self._m1_base, self._m1_base), (self._m1_base, self._m1_base))
def _switch_columns(self, matrix, dim, min_row, column_i, column_j, second_matrix=None, second_dim=(0, 0)):
'''If second_matrix is not None, then switch row of it
'''
for k in range(min_row, dim[0]):
c = matrix[k][column_i]
matrix[k][column_i] = matrix[k][column_j]
matrix[k][column_j] = c
if second_matrix is not None:
for k in range(second_dim[1]):
c = second_matrix[column_i][k]
second_matrix[column_i][k] = second_matrix[column_j][k]
second_matrix[column_j][k] = c
# if second_matrix is not None, then we switch columns of the M1 matrix
self._transform = mh.multiply_matrices(self._transform, [[self._switch_transfrom_value(i, j, column_i, column_j) for j in range(self._m1_base)] for i in range(self._m1_base)], (self._m1_base, self._m1_base), (self._m1_base, self._m1_base))
def check_correct(self):
'''Is matrices, presented in processor, are boundary maps, i.e. M1 * M2 = 0
Return pair (bool, int), where bool is True for correct matrix pair, int is key for incorrect result
key = -1: correct result
key = 0: wrong dimensions
key = 1: M1 * M2 is not equal to zero matrix
'''
# check dimensions
m1_dim = mh.get_size(self._m1)
m2_dim = mh.get_size(self._m2)
if m1_dim[1] == m2_dim[0]:
# make multiplication
mult = mh.multiply_matrices(self._m1, self._m2, m1_dim, m2_dim)
# is all elements are zero
s = mh.get_size(mult)
for i in range(s[0]):
for j in range(s[1]):
if mult[i][j] != 0:
return (False, 1)
return (True, -1)
else:
return (False, 0)