kuhyx/WUT_Computer_Science
1
0
Fork 0
mirror of https://github.com/kuhyx/WUT_Computer_Science.git synced 2026-07-06 20:03:10 +02:00
Code Issues Actions Packages Projects Releases Wiki Activity

fix: removed adding "size" to self values

Browse Source
This commit is contained in:
Krzysztof Rudnicki 2024-10-20 18:32:12 +02:00
parent ea98dc9712
commit 838d5ed563
2 changed files with 11 additions and 5 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

1
code/matrix_generator.py
View File

@ -4,7 +4,6 @@ class MatrixGenerator:
@staticmethod @staticmethod
def generate_random_matrix_and_vector(size): def generate_random_matrix_and_vector(size):
A = np.random.uniform(-1, 1, (size, size)) A = np.random.uniform(-1, 1, (size, size))
A = np.dot(A.T, A) + np.eye(size) * size # dodanie `size` do przekątnej zwiększa wartości własne -> obejście problemu z overflow
b = np.random.uniform(-1, 1, size) b = np.random.uniform(-1, 1, size)
return A, b return A, b

15
code/tests.py
View File

@ -15,22 +15,29 @@ def test_richardson_vs_cg(n):
solution_cg, info = cg(A, b) solution_cg, info = cg(A, b)
if info == 0: # SciPy CG converged if info == 0: # SciPy CG converged
assert_scipy_converged(solution_richardson, solution_cg, tolerance) assert_scipy_converged(solution_richardson, solution_cg, tolerance, A, b)
else: # SciPy CG did not converge else: # SciPy CG did not converge
assert_scipy_not_converged(solution_richardson) assert_scipy_not_converged(solution_richardson, A, b)
def assert_scipy_converged(solution_richardson, solution_cg, tolerance): def assert_scipy_converged(solution_richardson, solution_cg, tolerance, A, b):
if solution_richardson == "Richardson method for those values will NOT converge": if solution_richardson == "Richardson method for those values will NOT converge":
print("Richardson did not converge, while SciPy did") print("Richardson did not converge, while SciPy did")
print("Matrix A:\n", A)
print("Vector b:\n", b)
assert False, "Richardson did not converge, while SciPy did" assert False, "Richardson did not converge, while SciPy did"
else: else:
difference = np.linalg.norm(solution_richardson - solution_cg) difference = np.linalg.norm(solution_richardson - solution_cg)
print(f"Difference between Richardson and CG solutions: {difference:.8f}") print(f"Difference between Richardson and CG solutions: {difference:.8f}")
if difference >= tolerance:
print("Matrix A:\n", A)
print("Vector b:\n", b)
assert difference < tolerance, f"The solutions are different! Difference: {difference:.8f}" assert difference < tolerance, f"The solutions are different! Difference: {difference:.8f}"
def assert_scipy_not_converged(solution_richardson): def assert_scipy_not_converged(solution_richardson, A, b):
if solution_richardson == "Richardson method for those values will NOT converge": if solution_richardson == "Richardson method for those values will NOT converge":
print("Richardson and SciPy did not converge") print("Richardson and SciPy did not converge")
else: else:
print("Richardson converged while SciPy did not:", solution_richardson) print("Richardson converged while SciPy did not:", solution_richardson)
print("Matrix A:\n", A)
print("Vector b:\n", b)
assert False, "Richardson converged while SciPy did not" assert False, "Richardson converged while SciPy did not"