def test_neighbors(self):
for ha in [
hexgrid.HexArray(shape=(3, 3)),
hexgrid.HexArray(np.empty((3, 3), dtype=np.float64))
]:
for n in range(9):
if n == 4:
self.assertSequenceEqual(list(ha.neighbors(n)),
[0, 1, 5, 7, 6, 3])
else:
self.assertEqual(len(ha.neighbors(n)), 0)
def test_pos(self):
a = _get_test_array()
ha = hexgrid.HexArray(a)
self.assertSequenceEqual(ha.pos(0), (0.25, 0.0))
self.assertSequenceEqual(ha.pos(1), (1.25, 0.0))
self.assertSequenceEqual(ha.pos(3), (-0.25, 1.0))
self.assertSequenceEqual(ha.pos(4), (0.75, 1.0))
def test_critical_points(self):
a = _get_test_array()
ha = hexgrid.HexArray(a)
c = ha.classify_critical_points()
self.assertSequenceEqual(a.shape, c.shape)
# c should actually come out the same as a
np.testing.assert_array_equal(a.astype('i4'), c)
def test_convex(self):
ha = hexgrid.HexArray(shape=(10, 10))
pos = np.array([ha.pos(n) for n in range(ha.N)])
x, y = pos.T
r = np.sqrt((x - x.mean())**2 + (y - y.mean())**2)
mask = r <= 3
hr = hexgrid.HexArrayRegion(ha)
for n in np.nonzero(mask.ravel())[0]:
hr.add_point(n)
self.assertTrue(hr.is_convex())
mask += (abs(x) <= 1)
for n in np.nonzero(mask.ravel())[0]:
hr.add_point(n)
self.assertFalse(hr.is_convex())
def test_interior_exterior_boundary(self):
a = np.array([[0, 0, 0, 0, 0], [0, 0, 2, 2, 0], [0, 2, 1, 2, 0],
[0, 0, 2, 2, 0], [0, 0, 0, 0, 0]])
ha = hexgrid.HexArray(shape=a.shape)
hr = hexgrid.HexArrayRegion(ha)
a = a.ravel()
cpt = np.nonzero(a == 1)[0][0]
hr.add_point(cpt)
bd = set(np.nonzero(a == 2)[0])
eb = hr.exterior_boundary()
self.assertSetEqual(eb, bd)
for pt in bd:
hr.add_point(pt)
ib = hr.interior_boundary()
print(hr.members)
self.assertSetEqual(ib, bd)
def test_find_convex_regions(self):
# set up kelvin's cat's eyes flow on hexgrid
nx = 100
ha = hexgrid.HexArray(shape=(nx, nx))
pos = np.array([ha.pos(n) for n in range(ha.N)])
x, y = pos.T
x = (x - 5) * 2 * np.pi / 80
y = (y - nx / 2) * 2 * np.pi / 100
# Kelvin's cats eyes flow
a = 0.8
psi = np.log(np.cosh(y) + a * np.cos(x)) - np.log(1 + a)
cr = hexgrid.find_convex_regions(-psi.reshape(nx, nx))
self.assertEqual(len(cr), 1)
hr = cr[0]
self.assertTrue(np.all(psi[list(hr.members)] < 0))
# how do we know that the region was correctly identified?
psimask = (psi <= 0) & (x > 0.05) & (x <= (2 * np.pi + 0.05))
psiset = set(np.nonzero(psimask)[0])
# now remove a point we know is problematic
psiset.remove(5085)
self.assertSetEqual(psiset, hr.members)
# test minsize kwarg
cr = hexgrid.find_convex_regions(-psi.reshape(nx, nx), minsize=1e6)
self.assertEqual(len(cr), 0)
def setUp(self):
self.ha = hexgrid.HexArray(_get_test_array())
def test_maxima(self):
a = _get_test_array()
ha = hexgrid.HexArray(a)
maxima = ha.maxima()
self.assertEqual(len(maxima), 1)
self.assertEqual(maxima[0], 4)
from matplotlib import pyplot as plt
from floater import hexgrid
import numpy as np
from scipy.spatial import qhull
ha = hexgrid.HexArray(shape=(10, 10))
pos = np.array([ha.pos(n) for n in range(ha.N)])
x, y = pos.T
nmid = ha.N / 2 + ha.Nx / 2
r = -np.sqrt((x - x[nmid])**2 + (y - y[nmid])**2)
mask = r <= 3
plt.scatter(*pos.T, c=mask, cmap='Greys')
hr = hexgrid.HexArrayRegion(ha)
bpos = np.array([ha.pos(n) for n in hr.interior_boundary()])
ebpos = np.array([ha.pos(n) for n in hr.exterior_boundary()])
plt.scatter(*bpos.T, c='m')
plt.scatter(*ebpos.T, c='c')
hull = qhull.ConvexHull(bpos)
hv = np.hstack([hull.vertices, hull.vertices[0]])
plt.plot(*hull.points[hv].T, color='k')
def pnpoly(vertx, verty, testx, testy):
nvert = len(vertx)
i = 0
j = nvert - 1
c = False
while (i < nvert):
#for (i = 0, j = nvert-1; i < nvert; j = i++) {