Coverage for src/foapy/core/_intervals_distribution.py: 100%

1import numpy as np 

2from numpy import ndarray 

3 

4 

5def intervals_distribution(tuple_result) -> ndarray: 

6 """ 

7 Compute the frequency distribution of interval values. 

8 

9 Given the output of :func:`intervals_tuple` (or any 1-D array of strictly 

10 positive integers), counts how many times each interval value occurs. 

11 The result is a 1-D array of length ``max(tuple_result)`` where 

12 ``result[i]`` is the count of interval value ``i + 1``. 

13 

14 Parameters 

15 ---------- 

16 tuple_result : array_like 

17 1-D array of strictly positive integers, typically produced by 

18 :func:`intervals_tuple`. 

19 

20 Returns 

21 ------- 

22 ndarray 

23 1-D integer array of length ``max(tuple_result)`` (or empty for 

24 empty input). ``result[i]`` equals the number of elements in 

25 *tuple_result* with value ``i + 1``. 

26 

27 Examples 

28 -------- 

29 

30 ``` py linenums="1" 

31 import numpy as np 

32 from foapy.core import intervals_distribution 

33 

34 print(intervals_distribution(np.array([1, 2, 2, 4, 2]))) 

35 # [1 3 0 1] 

36 

37 print(intervals_distribution(np.array([]))) 

38 # [] 

39 ``` 

40 """ 

41 ar = np.asanyarray(tuple_result, dtype=np.intp) 

42 

43 if ar.size == 0: 

44 return np.array([], dtype=np.intp) 

45 

46 return np.bincount(ar - 1).astype(np.intp)