import numpy as np
from hypothesis import assume, given, settings
from hypothesis import strategies as st
from hypothesis.extra import numpy as hnp
from scipy.stats import rankdata


@given(
    hnp.arrays(
        hnp.floating_dtypes(),
        st.tuples(
            st.integers(min_value=1, max_value=1000),
            st.integers(min_value=1, max_value=1000),
        ),
    )
)
@settings(max_examples=500)
def test_rank_func(x):
    assume(not np.any(np.isinf(x)))
    y = x.copy()
    rank_result_y = rankdata(-y, method="min")
    rank_result_y[np.isnan(rank_result_y)] = len(rank_result_y)

    min_x = x.min() - 1
    np.nan_to_num(x, copy=False, nan=min_x)
    rank_result_x = rankdata(-x, method="min")

    np.testing.assert_allclose(rank_result_x, rank_result_y)