def test_power_method_01(self):
b_verbose = False
if b_verbose:
print ("Power method 01")
for n in range(3, 10):
self.mat_a_half = matrix.get_random_mat(n, n)
self.mat_a_half_transpose = matrix.transpose_mat(self.mat_a_half)
self.mat_a = matrix.mul_mat(self.mat_a_half_transpose, self.mat_a_half)
lam, vec_x0 = evp.power_method(self.mat_a, espilon=1e-12)
if b_verbose:
print ('%s %s' % (lam, vec_x0))
vec_x1 = matrix.mul_mat_vec(self.mat_a, vec_x0)
vec_x0l = [lam * x0k for x0k in vec_x0]
self.assertEqual(len(vec_x0), n)
message = '''
x0 =
%s
mat_a x0 =
%s
''' % (vec_x0, vec_x0l)
self.assertSequenceAlmostEqual(vec_x0l, vec_x1, msg=me)
def test_gauss_jordan_00(self):
for n in range(3, 10):
mat_a = m.get_random_mat(n, n)
mat_a_inv = gj.gauss_jordan(mat_a)
mat_b = m.mul_mat(mat_a, mat_a_inv)
for i in range(n):
vec_exp = [0.0] * n
vec_exp[i] = 1.0
vec_res = mat_b[i]
self.assertSequenceAlmostEqual(vec_exp, vec_res)
del vec_exp
del mat_b[:]
del mat_b
del mat_a_inv[:]
del mat_a_inv
del mat_a[:]
del mat_a
def test_gauss_elimination_00(self):
n = 2
mat_a = m.get_random_mat(n, n)
vec_x = m.get_random_vector(n)
vec_b = m.mul_mat_vec(mat_a, vec_x)
vec_x_sol = ge.gauss_elimination(mat_a, vec_x_sol)
del vec_x_sol
del vec_x
del vec_b
del mat_a[:]
del mat_a
def test_gauss_elimination_01(self):
for n in range(3, 10):
mat_a = m.get_random_mat(n, n)
vec_x = m.get_random_vector(n)
vec_b = m.mul_mat_vec(mat_a, vec_x)
vec_x_sol = ge.gauss_elimination(mat_a, vec_b)
del mat_a[:]
del mat_a
del vec_x_sol
del vec_x
del vec_b
def test_gauss_elimination_01(self):
for n in range(3, 10):
mat_a = m.get_random_mat(n, n)
vec_x = m.get_random_vector(n)
vec_b = m.mul_mat_vec(mat_a, vec_x)
vec_x_sol = ge.gauss_elimination(mat_a, vec_b)
self.assertSequenceAlmostEqual(vec_x, vec_x_sol)
del mat_a[:]
del mat_a
del vec_x_sol
del vec_x
del vec_b
def run_mat_inv():
n = 10
mat_a = matrix.get_random_mat(n, n)
mat_a_adj = matrix.adjugate_matrix(mat_a)
mat_a_gj = gj.gauss_jordan(mat_a)
