Coverage for tests/test_numerical.py: 0%

1from hypothesis import given, strategies as st 

2import numpy as np 

3 

4import swiift.lib.numerical as numerical 

5from tests.utils import float_kw 

6 

7 

8@st.composite 

9def make_use_an_sol_params( 

10 draw: st.DrawFn, 

11) -> tuple[bool | None, float, tuple[np.ndarray, float] | None, bool | None]: 

12 an_sol = draw(st.booleans() | st.none()) 

13 length = draw(st.floats(-100, 100, **float_kw)) 

14 _mean = draw( 

15 st.lists(st.floats(-100, 100, **float_kw), min_size=1, max_size=5) | st.none() 

16 ) 

17 if _mean is not None: 

18 growth_params = np.array(_mean), 1.0 # value of std does not matter 

19 else: 

20 growth_params = None 

21 linear_curvature = draw(st.booleans() | st.none()) 

22 return an_sol, length, growth_params, linear_curvature 

23 

24 

25@given(params=make_use_an_sol_params()) 

26def test_use_an_sol(params): 

27 an_sol, length, growth_params, linear_curvature = params 

28 use_an_sol = numerical._use_an_sol(*params) 

29 

30 if an_sol is not None: 

31 assert use_an_sol == an_sol 

32 else: 

33 if growth_params is None: 

34 if linear_curvature is None: 

35 assert use_an_sol is True 

36 else: 

37 assert use_an_sol == linear_curvature 

38 else: 

39 if np.any(growth_params[0] < length): 

40 assert use_an_sol is False 

41 else: 

42 if linear_curvature is None: 

43 assert use_an_sol is True 

44 else: 

45 assert use_an_sol is linear_curvature