import pytest
from numpy.testing import assert_allclose

from logistic import f, iterate_f


def test_f_corner_cases():
    # Test cases are (x, r, expected)
    cases = [
        (0, 1.1, 0),
        (1, 3.7, 0),
    ]
    for x, r, expected in cases:
        result = f(x, r)
        assert_allclose(result, expected)

# Hands on 1
#Add a new test for these generic cases using the for-loop pattern:
# x=0.1, r=2.2 => f(x, r)=0.198
# x=0.2, r=3.4 => f(x, r)=0.544
# x=0.5, r=2   => f(x, r)=0.5


# Hands on 2:
# parametrize the above test using @pytest.mark.parametrize


@pytest.mark.parametrize(
    'x, r, expected',
    [
        (0.1, 2.2 ,0.198),
        (0.2, 3.4 ,0.544),
        (0.5, 2   ,0.5)
    ]
)
def test_f_generic_cases(x, r, expected):
    result = f(x, r)
    assert_allclose(result, expected)


@pytest.mark.parametrize(
    'x, r, n_iterations, expected',
    [
        (0.1, 2.2 , 1, [0.1, 0.198]),
        (0.2, 3.4 , 4, [0.2, 0.544, 0.843418, 0.449019, 0.841163]),
        (0.5, 2, 3, [0.5, 0.5, 0.5, 0.5])
    ]
)
def test_iterate_f_generic(x, r, n_iterations, expected):
    result = iterate_f(x, r, n_iterations)
    assert_allclose(result, expected, rtol=1e-6)
# Hands on 3
# Implement a function iterate_f that runs f for it iterations. Write tests for the following cases:
# x=0.1, r=2.2, it=1 => iterate_f(it, x, r)=[0.1, 0.198]
# x=0.2, r=3.4, it=4 => iterate_f(it, x, r)=[0.2, 0.544, 0.843418, 0.449019, 0.841163]
# x=0.5, r=2, it=3 => iterate_f(it, x, r)=[0.5, 0.5, 0.5]