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52 lines
2.2 KiB
Python
52 lines
2.2 KiB
Python
import pytest
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import numpy as np
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from scipy.sparse.linalg import cg
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from matrix_generator import MatrixGenerator
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from richardson_method import RichardsonMethod
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@pytest.mark.parametrize("n", [2, 3, 4, 5, 10, 20, 50, 100])
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def test_richardson_vs_cg(n: int):
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tolerance = 1e-5
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A, b = MatrixGenerator.generate_random_matrix_and_vector(n)
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richardson_solver = RichardsonMethod(A, b, size=n, max_iterations=1000, tol=1e-7)
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solution_richardson = richardson_solver.solve()
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solution_cg, info = cg(A, b)
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if info == 0: # SciPy CG converged
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assert_scipy_converged(solution_richardson, solution_cg, tolerance, A, b)
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else: # SciPy CG did not converge
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assert_scipy_not_converged(solution_richardson, A, b)
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def assert_scipy_converged(solution_richardson, solution_cg, tolerance, A, b):
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if solution_richardson == "Richardson method for those values will NOT converge":
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print("Richardson did not converge, while SciPy did")
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print("Matrix A:\n", A)
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print("Vector b:\n", b)
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assert False, "Richardson did not converge, while SciPy did"
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else:
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difference = np.linalg.norm(solution_richardson - solution_cg)
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print(f"Difference between Richardson and CG solutions: {difference:.8f}")
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if difference < tolerance:
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print("Both Richardson and CG converged and calculated correct values.")
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print("Solution CG:\n", solution_cg)
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print("Solution Richardson:\n", solution_richardson)
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else:
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print("Matrix A:\n", A)
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print("Vector b:\n", b)
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assert difference < tolerance, f"The solutions are different! Difference: {difference:.8f}"
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def assert_scipy_not_converged(solution_richardson, A, b):
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if solution_richardson == "Richardson method for those values will NOT converge":
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print("Richardson and SciPy did not converge")
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else:
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print("Richardson converged while SciPy did not:", solution_richardson)
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print("Matrix A:\n", A)
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print("Vector b:\n", b)
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assert False, "Richardson converged while SciPy did not"
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if __name__ == "__main__":
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# Run pytest and exit with the appropriate status code
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for n in [2, 3, 4, 5, 10, 20, 50, 100]:
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test_richardson_vs_cg(n) |