def calculate_f(a, t, q):
# Fi(t) formulas: I + (A^q)/q!
# A is matrix
f = np.eye(3)
q = int(q)
val = a * t
for i in range(1, q + 1):
f += np.linalg.matrix_power(val, i) / m.fact(i)
return f
def product_exp(x):
ide = create_ide(x)
res = create_empty_matrix(x)
i = 0
for i in range(100):
temp = scalaire_product(ide, 1 / fact(i))
for k in range(len(res)):
for j in range(len(res[0])):
res[k][j] += temp[k][j]
ide = matrix_product(ide, x)
return res
def product_sin(x):
ide = create_ide(x)
res = create_empty_matrix(x)
k = 1
ide = matrix_product(ide, x)
for i in range(0, 100):
if (i != 0):
ide = matrix_product(ide, x)
ide = matrix_product(ide, x)
k = ((-1)**i) / fact(2 * i + 1)
temp = scalaire_product(ide, k)
for k in range(len(res)):
for j in range(len(res[0])):
res[k][j] += temp[k][j]
return res
def test_fact_1(self):
self.assertEqual(my_math.fact(1), 1)
def test_fact_0(self):
self.assertEqual(my_math.fact(0), 1)
def test_float_numbers(self):
with self.assertRaises(TypeError):
my_math.fact(1.66)
def test_negative_vals(self):
with self.assertRaises(ValueError):
my_math.fact(-1)