72 lines
3.3 KiB
Python
72 lines
3.3 KiB
Python
import pytest
|
|
import numpy as np
|
|
from scipy.spatial import cKDTree
|
|
|
|
from damask import seeds
|
|
from damask import grid_filters
|
|
from damask import GeomGrid
|
|
|
|
class TestSeeds:
|
|
|
|
@pytest.mark.parametrize('cells',[None,np.ones(3,dtype='i')*10])
|
|
def test_from_random(self,cells):
|
|
N_seeds = np.random.randint(30,300)
|
|
size = np.ones(3) + np.random.random(3)
|
|
coords = seeds.from_random(size,N_seeds,cells)
|
|
assert (0<=coords).all() and (coords<size).all()
|
|
|
|
@pytest.mark.parametrize('periodic',[True,False])
|
|
def test_from_Poisson_disc(self,periodic):
|
|
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,periodic=periodic)
|
|
min_dists, _ = cKDTree(coords,boxsize=size).query(coords, 2) if periodic else \
|
|
cKDTree(coords).query(coords, 2)
|
|
assert (0<= coords).all() and (coords<size).all() and np.min(min_dists[:,1])>=distance
|
|
|
|
@pytest.mark.parametrize('periodic',[True,False])
|
|
def test_from_Poisson_disc_invalid(self,periodic):
|
|
N_seeds = np.random.randint(30,300)
|
|
N_candidates = N_seeds//15
|
|
distance = np.random.random()
|
|
size = np.ones(3)*distance
|
|
with pytest.raises(ValueError):
|
|
seeds.from_Poisson_disc(size,N_seeds,N_candidates,distance,periodic=periodic)
|
|
|
|
def test_from_grid_reconstruct(self):
|
|
cells = np.random.randint(10,20,3)
|
|
N_seeds = np.random.randint(30,300)
|
|
size = np.ones(3) + np.random.random(3)
|
|
coords = seeds.from_random(size,N_seeds,cells)
|
|
grid_1 = GeomGrid.from_Voronoi_tessellation(cells,size,coords)
|
|
coords,material = seeds.from_grid(grid_1)
|
|
grid_2 = GeomGrid.from_Voronoi_tessellation(cells,size,coords,material)
|
|
assert (grid_2.material==grid_1.material).all()
|
|
|
|
@pytest.mark.parametrize('periodic',[True,False])
|
|
@pytest.mark.parametrize('average',[True,False])
|
|
def test_from_grid_grid(self,periodic,average):
|
|
cells = np.random.randint(10,20,3)
|
|
size = np.ones(3) + np.random.random(3)
|
|
coords = grid_filters.coordinates0_point(cells,size).reshape(-1,3)
|
|
np.random.shuffle(coords)
|
|
grid_1 = GeomGrid.from_Voronoi_tessellation(cells,size,coords)
|
|
coords,material = seeds.from_grid(grid_1,average=average,periodic=periodic)
|
|
grid_2 = GeomGrid.from_Voronoi_tessellation(cells,size,coords,material)
|
|
assert (grid_2.material==grid_1.material).all()
|
|
|
|
@pytest.mark.parametrize('periodic',[True,False])
|
|
@pytest.mark.parametrize('average',[True,False])
|
|
@pytest.mark.parametrize('invert',[True,False])
|
|
def test_from_grid_selection(self,periodic,average,invert):
|
|
cells = np.random.randint(10,20,3)
|
|
N_seeds = np.random.randint(30,300)
|
|
size = np.ones(3) + np.random.random(3)
|
|
coords = seeds.from_random(size,N_seeds,cells)
|
|
grid = GeomGrid.from_Voronoi_tessellation(cells,size,coords)
|
|
selection=np.random.randint(N_seeds)+1
|
|
coords,material = seeds.from_grid(grid,average=average,periodic=periodic,invert_selection=invert,selection=[selection])
|
|
assert selection not in material if invert else (selection==material).all()
|