import flame
import laff as laff

def Mvmult_n_unb_var2(A, x, y):

    AL, AR = flame.part_1x2(A, \
                            0, 'LEFT')

    xT, \
    xB  = flame.part_2x1(x, \
                         0, 'TOP')

    while AL.shape[1] < A.shape[1]:

        A0, a1, A2 = flame.repart_1x2_to_1x3(AL, AR, \
                                             1, 'RIGHT')

        x0,   \
        chi1, \
        x2    = flame.repart_2x1_to_3x1(xT, \
                                        xB, \
                                        1, 'BOTTOM')

        #------------------------------------------------------------#

        laff.axpy( chi1, a1, y )

        #------------------------------------------------------------#

        AL, AR = flame.cont_with_1x3_to_1x2(A0, a1, A2, \
                                            'LEFT')

        xT, \
        xB  = flame.cont_with_3x1_to_2x1(x0,   \
                                         chi1, \
                                         x2,   \
                                         'TOP')






from numpy import random
from numpy import matrix

A = matrix( random.rand( 4,3 ) )
x = matrix( random.rand( 3,1 ) )
y = matrix( random.rand( 4,1 ) )
yold = matrix( random.rand( 4,1 ) )

print( 'y before =' )
print( y )

print( 'x before =' )
print( x )

print( 'y before =' )
print( y )

laff.copy( y, yold )   # save the original vector y

Mvmult_n_unb_var2( A, x, y )

print( 'y after =' )
print( y )

print( 'y - ( A * x + yold ) = ' )
print( y - ( A * x + yold ) )