def test_consistent_groups():
""" Shuffling gives consistent groups """
# Note we dont actually need to check for renumbering between hfof and
# itself because even if you shuffle the points they end up in the same
# cells, which are treated in order, so the group numbers (at each
# position) are guaranteed to be the same. Only if you check against
# another FOF do you need to check the numbering.
pos = example_data.get_pos()
N = pos.shape[0]
rs = RandomState(seed=123)
idx = np.arange(N)
rs.shuffle(idx)
rcut = 0.01
# Non=periodic
doms1 = fof(pos, rcut)
doms2 = fof(pos[idx], rcut)
assert (np.all(np.equal(doms1[idx], doms2)))
# Periodic
doms1 = fof(pos, rcut, boxsize=0.8)
doms2 = fof(pos[idx], rcut, boxsize=0.8)
assert (np.all(np.equal(doms1[idx], doms2)))
def test_cosmo_isol():
""" Cosmological (non-periodic) """
pos = example_data.get_pos()
for rcut, n in ndom_isol.items():
domains = fof(pos, rcut)
n_doms = len(np.unique(domains))
assert (n == n_doms)
print(rcut, n_doms, n)
def test_cosmo_periodic():
""" Cosmological (periodic) """
pos = example_data.get_pos()
for rcut, n in ndom_prd.items():
domains = fof(pos, rcut, boxsize=1.0)
n_doms = len(np.unique(domains))
assert (n == n_doms)
print(rcut, n_doms, n)
def test_shift_scale():
""" Cube scaled and shifted """
shift, scale = (8.82334, 4.234, -15.234), 4.8271
pos = example_data.get_pos() * scale + shift
# scaled the box => scale the linking length
# Isolated
for rcut, n in ndom_isol.items():
domains = fof(pos, rcut * scale)
n_doms = len(np.unique(domains))
assert (n == n_doms)
print(rcut, n_doms, n)
#Periodic (scale boxsize too)
for rcut, n in ndom_prd.items():
domains = fof(pos, rcut * scale, boxsize=scale)
n_doms = len(np.unique(domains))
assert (n == n_doms)
print(rcut, n_doms, n)
def test_fof():
""" Test friends-of-friends """
pos = example_data.get_pos() # (32768,3) positions in [0,1]
pos[:, 2] *= 0.0 # project (squash) z-dimension
r_cut = 0.004 # linking length
fof_labels = fof(pos, r_cut, boxsize=1.0) # integer labels from 0...
print 'Number of labels', len(np.unique(fof_labels)), 'minimum', min(
fof_labels), 'maximum', max(fof_labels)
# color by number of particles in group
clrs = np.bincount(fof_labels)[fof_labels]
import pylab as pl
pl.scatter(pos[:, 0],
pos[:, 1],
c=np.power(clrs, 0.3),
s=1.0,
edgecolors='none')
# pl.xlim(0,1)
# pl.ylim(0,1)
# pl.axis('off')
# pl.savefig('figs/fof.png', dpi=50, bbox_inches='tight')
pl.show()