def generate_random_data(number_of_files: int) -> list:
data_files = []
for i in range(0, number_of_files):
theta = generate_random_theta()
data = []
points = random.randint(2, 100)
power = random.randint(1, 5)
for _ in range(2, points):
error = ft_abs(
int(linear(ft_pow(random.randint(1, 10), power), theta)))
x = generate_random_int(power)
y = linear(x, theta) + random.randint(-error, error)
data.append([x, int(y)])
filename = 'test_' + str(i)
write_file(data, filename)
write_answer_file(theta, filename)
# il faut normalizer theta
data_files.append({'file': filename, 'result': theta})
return data_files
def compute_price(distance: int):
thetas = get_thetas()
price = ft_math.linear(distance, thetas)
print(
'This car should cost {} euros.\
\n\tHis kilometrage (distance) is {}\
\n\tfunction used: price(distance) = {} + {} * distance'
.format(
int(price),
distance,
thetas[0],
thetas[1]
)
)
def denormalize(x: float, theta_normalized: list, data_range: list,
average: list) -> float:
x_normalized = normalize(x, data_range[0], average[0])
result = linear(x_normalized, theta_normalized)
return result * data_range[1] + average[1]
def partial_derivative_theta0(theta: list, data: list) -> float:
return linear(data[0], theta) - data[1]
def cost_function(data: list, theta: list, count: int):
return 1 / (2 * count) * sum(
[ft_pow(linear(item[0], theta) - item[1], 2) for item in data])
def test():
linear_test = [
[[1, 0], 2, 1],
[[1, 0], 1, 1],
[[1, 0], 0, 1],
[[1, 0], -1, 1],
[[-2, 0], -1, -2],
[[0, 1], 2, 2],
[[0, 1], 1, 1],
[[0, 1], 0, 0],
[[0, 1], -1, -1],
[[0, -2], 2, -4],
[[1, 1], 1, 2],
[[-1, -1], 1, -2],
[[-1, 1], 1, 0],
[[-2, 3], 1, 1],
]
for item in linear_test:
result = linear(item[1], item[0])
if (result != item[2]):
print(item, result)
break
partial_derivative_theta_test = [
# theta = 0
[[0, 0], [1, 1], -1, -1],
[[0, 0], [2, 0], 0, 0],
[[0, 0], [0, 2], -2, 0],
# theta1 = 0
[[1, 0], [1, 1], 0, 0],
[[1, 0], [0, 2], -1, 0],
[[1, 0], [2, 0], 1, 2],
# theta0 = 0
[[0, 1], [2, 2], 0, 0],
[[0, 1], [2, 0], 2, 4],
[[0, 1], [0, 2], -2, 0],
# theta != 0
[[2, 2], [1, 1], 3, 3],
[[2, 2], [0, 2], 0, 0],
[[2, 2], [2, 0], 6, 12],
# with neg numbers
[[-2, 2], [2, 0], 2, 4],
[[-2, 2], [2, 1], 1, 2],
[[-2, 2], [2, -3], 5, 10],
[[-2, 2], [-2, 1], -7, 14],
]
for item in partial_derivative_theta_test:
result0 = partial_derivative_theta0(item[0], item[1])
result1 = partial_derivative_theta1(item[0], item[1])
if (result0 != item[2] or result1 != item[3]):
print(item, result0, result1)
break
gradient_descent_test = [
[[0, 0], [[0, 0], [1, 1]], [1, 1]],
[[1, 1], [[0, 0], [1, 1]], [-1, 0]],
[[0, -1], [[0, 0], [1, 1]], [2, 1]],
[[-1, -1], [[0, 0], [1, 1]], [3, 2]],
[[0, 1], [[0, 0], [1, 1]], [0, 1]],
]
ratio = 2
for item in gradient_descent_test:
result = gradient_descent(item[0], item[1], ratio / len(item[1]))
if (result != item[2]):
print(item, result)
break
gradient_descent_test = [
[[0, 0], [[0, 0], [1, 1]], [0.5, 0.5]],
[[1, 1], [[0, 0], [1, 1]], [0, 0.5]],
[[0, -1], [[0, 0], [1, 1]], [1, 0]],
[[-1, -1], [[0, 0], [1, 1]], [1, 0.5]],
[[0, 1], [[0, 0], [1, 1]], [0, 1]],
]
ratio = 1
for item in gradient_descent_test:
result = gradient_descent(item[0], item[1], ratio / len(item[1]))
if (result != item[2]):
print(item, result)
break
pow_test = [
[1, 2, 1],
[0, 2, 0],
[0, 0, 1],
[42, 0, 1],
[42, -1, 1 / 42],
[10, 2, 100],
[10, 3, 1000],
[2, 2, 4],
[2, 10, 1024],
[0.5, 2, 0.25],
]
for item in pow_test:
result = ft_pow(item[0], item[1])
if (result != item[2]):
print(item, result)
break
abs_test = [
[1, 1],
[0, 0],
[-1, -1],
[-0.5, -0.5],
]
for item in abs_test:
result = ft_abs(item[0])
if (result != item[1]):
print(item, result)
break