Coverage for src/abcd_graph/graph/core/utils.py: 100%

20 statements  

« prev     ^ index     » next       coverage.py v7.5.3, created at 2024-11-17 23:31 +0100

1# Copyright (c) 2024 Jordan Barrett & Aleksander Wojnarowicz 

2# 

3# Permission is hereby granted, free of charge, to any person obtaining a copy 

4# of this software and associated documentation files (the "Software"), to deal 

5# in the Software without restriction, including without limitation the rights 

6# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell 

7# copies of the Software, and to permit persons to whom the Software is 

8# furnished to do so, subject to the following conditions: 

9# 

10# The above copyright notice and this permission notice shall be included in all 

11# copies or substantial portions of the Software. 

12# 

13# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR 

14# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, 

15# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE 

16# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER 

17# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, 

18# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE 

19# SOFTWARE. 

20 

21__all__ = ["rand_round", "powerlaw_distribution", "get_community_color_map"] 

22 

23import math 

24import random 

25from typing import TYPE_CHECKING 

26 

27import numpy as np 

28from numpy.typing import NDArray 

29 

30if TYPE_CHECKING: # pragma: no cover 

31 from abcd_graph.graph.core.abcd_objects import Community 

32 

33 

34def rand_round(x: float) -> int: 

35 p = x - math.floor(x) 

36 return int(math.floor(x) + 1) if random.uniform(0, 1) <= p else int(math.floor(x)) 

37 

38 

39def powerlaw_distribution(choices: NDArray[np.int64], intensity: float) -> NDArray[np.float64]: 

40 dist: NDArray[np.float64] = (choices ** (-intensity)) / np.sum(choices ** (-intensity)) 

41 return dist 

42 

43 

44def get_community_color_map(communities: list["Community"]) -> list[str]: 

45 import matplotlib.colors as colors # type: ignore[import] 

46 

47 colors_list = list(colors.BASE_COLORS.values())[: len(communities)] 

48 

49 color_map = [] 

50 

51 for i, community in enumerate(communities): 

52 color = colors_list[i] 

53 color_map.extend([color] * len(community.vertices)) 

54 

55 return color_map