I understand ,sometimes, it is normal that number of equations are less or
more than number of unknowns that means non square matrix appearance. If so,
how would you compose Av(v) function, because I have only constant dimensional
values such as A matrix(MxN) and array b array (M)???
Среда,
In [2]: %debug
> (5)Av()
4 def Av(A,v):
> 5 return np.dot(A,v)
6
ipdb> !A.shape
(4, 8)
ipdb> !v.shape
(4,)
In your code it looks like you are essentially computing A.dot(v)
where A is a 4-by-8 matrix and v is vector of length 4. That's what
the error is telling you --- that
Hello,
I am trying to solve linear Ax=b problem, but some error occurs in the process
like:
--
Traceback (most recent call last):
File "C:\Python27\Conjugate_Gradient.py", line 66, in
x, iter_number = conjGrad(Av,A, x, b)
File "C:\Python27\Conjugate_
