24 lines
847 B
Python
24 lines
847 B
Python
import pytest
|
|
import numpy as np
|
|
from scipy.spatial import cKDTree
|
|
|
|
from damask import seeds
|
|
|
|
class TestSeeds:
|
|
|
|
@pytest.mark.parametrize('grid',[None,np.ones(3,dtype='i')*10])
|
|
def test_from_random(self,grid):
|
|
N_seeds = np.random.randint(30,300)
|
|
size = np.ones(3) + np.random.random(3)
|
|
coords = seeds.from_random(size,N_seeds,grid)
|
|
assert (0<=coords).all() and (coords<size).all()
|
|
|
|
def test_from_Poisson_disc(self):
|
|
N_seeds = np.random.randint(30,300)
|
|
N_candidates = N_seeds//15
|
|
distance = np.random.random()
|
|
size = np.ones(3)*distance*N_seeds
|
|
coords = seeds.from_Poisson_disc(size,N_seeds,N_candidates,distance)
|
|
min_dists, _ = cKDTree(coords).query(coords, 2)
|
|
assert (0<= coords).all() and (coords<size).all() and np.min(min_dists[:,1])>=distance
|