def test_brenth_solve_from_tuples(self):
taw = TupleArrayWrapperFactory.create_taw_1()
k = NumericalSolver.solve(taw.taw, brenth, taw.taw.get_min_x(), taw.taw.get_max_x(), 1e-100, 1e-100)
assert_ans(self, k, taw.root)
taw = TupleArrayWrapperFactory.create_taw_2()
k = NumericalSolver.solve(taw.taw, brenth, taw.taw.get_min_x(), taw.taw.get_max_x(), 1e-100, 1e-100)
assert_ans(self, k, taw.root)
def test_data_clear_statistics(self):
taw = TupleArrayWrapperFactory.create_taw_1()
k = NumericalSolver.solve_with_methods(taw.taw, taw.taw.get_min_x(), taw.taw.get_max_x(), methods, 1e-100,
1e-100)
summ = 0
i = 0
for ans in k.values():
summ += ans.statistics.callsNumbers
i += 1
for ans in k.values():
self.assertNotEqual(summ / i, ans.statistics.callsNumbers)
def test_wrong_bracket(self):
assert NumericalSolver.solve(LambdaWrapper(lambda x: x), "", 2, 1, 0.1, 0.1).is_ok is False
def test_solve_from_tuples_2(self):
taw = TupleArrayWrapperFactory.create_taw_2()
k = NumericalSolver.solve_with_methods(taw.taw, taw.taw.get_min_x(), taw.taw.get_max_x(), methods, 1e-100,
1e-100)
self.assert_answer(k, taw)
def test_newton_small_eps(self):
eps_x = 1e-6
self.assertAlmostEqual(
NumericalSolver.solve(LambdaWrapper(lambda x: x * x + 2 * x - 3), "newton", -5, 0, eps_x, eps_x).root, -3,
10)
def test_newton(self):
self.assertAlmostEqual(
NumericalSolver.solve(LambdaWrapper(lambda x: x * x + 2 * x - 3), "newton", -5, 0, 0.1, 0.1).root, -3, 1)
def test_bisections(self):
eps_x = 1e-6
ans = NumericalSolver.solve(LambdaWrapper(lambda x: math.sin(x)), "bisections", -1.1, 1, eps_x, eps_x)
assert_ans(self, ans, 0)
def test_chords(self):
assert NumericalSolver.solve(LambdaWrapper(lambda x: x), "bisections", -1, 1, 0.1, 0.1).root == 0
def test_no_roots(self):
assert NumericalSolver.solve(LambdaWrapper(lambda x: x), "", 2, 3, 0.1, 0.1).is_ok is False
def process_file(file, args, inputp):
all_results_by_method = dict()
call_number_by_method = dict()
iters_by_method = dict()
fails_by_method = dict()
for method in args.methods:
all_results_by_method[method] = list()
call_number_by_method[method] = list()
iters_by_method[method] = list()
fails_by_method[method] = list()
res = NumericalSolver.solve_from_file_data(os.path.join(inputp, file),
args.epsilon_x, args.epsilon_y,
args.methods)
for i in res:
for j in i.values():
all_results_by_method[j.method].append(j)
total_eqs = len(all_results_by_method[args.methods[0]])
methods_output = list()
methods_output.append(f"Processed {total_eqs} equations.")
for method in args.methods:
good = 0
bad = 0
calls_number = 0
iters = 0
for eqs in all_results_by_method[method]:
if eqs.is_ok is not True:
bad += 1
continue
else:
good += 1
calls_number += eqs.statistics.callsNumbers
iters += eqs.statistics.iterations
methods_output.append(
f"METHOD {method}. Failed: {bad / total_eqs * 100}% | Avg func calls: {calls_number / good} | Avg iters: {iters / good}"
)
with open(os.path.join(inputp, f"{file}_REPORT.txt"), "w") as f:
f.write('\n'.join(methods_output))
for method in all_results_by_method.values():
for m in method:
if m.is_ok is True:
call_number_by_method[m.method].append(
m.statistics.callsNumbers)
iters_by_method[m.method].append(m.statistics.iterations)
fig, axes = plt.subplots(len(args.methods), 2)
fig.set_size_inches(18.5, 10.5)
i = 0
max_calls = max(call_number_by_method["bisections"])
max_iteration = max(iters_by_method["bisections"])
for method in args.methods:
axes[i, 1].hist(call_number_by_method[method],
density=True,
bins=np.arange(0, max_calls, max_calls / 50),
color="black")
axes[i, 1].set(xlabel='Function calls', ylabel="Probability")
axes[i, 1].set_title(method)
i += 1
i = 0
for method in args.methods:
axes[i, 0].hist(iters_by_method[method],
density=True,
bins=np.arange(0, max_iteration, max_iteration / 50),
color="black")
axes[i, 0].set(xlabel='Iterations', ylabel="Probability")
axes[i, 0].set_title(method)
i += 1
plt.tight_layout()
fig.savefig(os.path.join(inputp, f'{file}_GRAPH.png'), dpi=fig.dpi)