Returned solution of A*x=b via A.LUsolve(b) cannot be worked with

[hpaantee]

I have a system of equations Ax=b. A has a shape of 576x576.
Here, A is a sparse matrix where some entries might contain a symbol.
I can use x = A.LUsolve(b) just fine (~30) to solve for a symbolic solution of x.

However, I can't do anything with the result. Lambdify gives the following RuntimeError:

f = symengine.Lambdify([v], x)
File "symengine_wrapper.pyx", line 5276, in symengine.lib.symengine_wrapper.Lambdify
File "symengine_wrapper.pyx", line 4856, in symengine.lib.symengine_wrapper._Lambdify.__init__
File "symengine_wrapper.pyx", line 5091, in symengine.lib.symengine_wrapper.LLVMDouble._init
RuntimeError: -1.14183378644392e+50 + 8.20975478115991e+48*I

Substituting x and converting to numpy or printing the first element does never return.
Here is my code, matrix A is loaded from a file via sympy:

import sympy
from sympy.parsing.sympy_parser import parse_expr
import symengine

with open('matrix_A.txt', 'r') as f:
    A = parse_expr(f.read())
b = sympy.zeros(576, 1)
b[0,0] = 1
A = symengine.Matrix(A)
b = symengine.Matrix(b)
x = A.LUsolve(b)
print('solved!')
v = symengine.var('w01 Efield_01')
f = symengine.Lambdify([v], x)

Am I doing something wrong or am I just hitting some limitation?
Here is the attached file:
matrix_A.txt

[isuruf]

Note that the expressions are huge. For eg:

In [7]: symengine.count_ops(x)
Out[7]: 3823017280

Try doing

f = symengine.Lambdify([v], x, real=False, cse=True)

[hpaantee]

Thanks a lot, which those parameters in Lambdify I could successfully use the returned function!

[hpaantee]

Sorry to reopen this, but the problem somewhat persists. I generated a slightly different A for what Lambdify again does never return. Interestingly enough though,

In [2]: symengine.count_ops(x)
Out[2]: 10704814

gives a much smaller number than previously. Again I attached a minimal working example to reproduce the issue:

import sympy
import symengine
import pickle
with open('matrix_Ab.txt', 'rb') as f:
    A, b = pickle.load(f)
A = symengine.Matrix(A)
b = symengine.Matrix(b)
print('solve...')
x = A.LUsolve(b)
print('solved!')
print(f'Symbolic operations: {symengine.count_ops(x)}')
v = symengine.var('w_01 Efield_01')
f = symengine.Lambdify([v], x, real=False, cse=True)

matrix_Ab.txt

[hpaantee]

Can be closed, with a slightly different matrix A it works