def test_occmap(): from numpy import cos, sin, pi, abs, all from pylada.crystal import binary from pylada.ce import Cluster lattice = binary.zinc_blende() for atom in lattice: atom.type = ['Si', 'Ge'] a = Cluster(lattice) mapping = a.occupation_mapping() assert len(mapping) == len(lattice) assert len(mapping[0]) == 2 assert len(mapping[1]) == 2 assert abs(mapping[0]['Si'] - cos(2e0*pi*0e0/2.0)) < 1e-8 assert abs(mapping[0]['Ge'] - cos(2e0*pi*1e0/2.0)) < 1e-8 assert abs(mapping[1]['Si'] - cos(2e0*pi*0e0/2.0)) < 1e-8 assert abs(mapping[1]['Ge'] - cos(2e0*pi*1e0/2.0)) < 1e-8 lattice = binary.zinc_blende() lattice[1].type = ['Si', 'Ge', 'C'] a = Cluster(lattice) mapping = a.occupation_mapping() assert len(mapping) == len(lattice) assert mapping[0] is None assert len(mapping[1]) == len(lattice[1].type) assert all(abs(mapping[1]['C'] - [cos(2e0*pi*0e0/3.0), sin(2e0*pi*2e0/3.0)])) assert all(abs(mapping[1]['Si'] - [cos(2e0*pi*1e0/3.0), sin(2e0*pi*1e0/3.0)])) assert all(abs(mapping[1]['Ge'] - [cos(2e0*pi*2e0/3.0), sin(2e0*pi*2e0/3.0)]))
def test_onsite():
""" Tests J0 PI calculation.
This uses the same algorithmic pathway as more complex figures, but can
be easily computed as the sum of particular specie-dependent terms on
each site.
"""
from numpy import dot, abs, all
from random import choice
from pylada.crystal import binary, supercell
from pylada.ce import Cluster
lattice = binary.zinc_blende()
for atom in lattice: atom.type = ['Si', 'Ge', 'C']
structure = binary.zinc_blende()
for atom in structure: atom.type = 'Si'
a = Cluster(lattice)
# Empty cluster first
assert abs(a(structure) - len(structure)) < 1e-8
for i in xrange(10):
superstructure = supercell(lattice, dot(lattice.cell, get_cell()))
for atom in superstructure: atom.type = choice(atom.type)
assert abs(a(superstructure) - len(superstructure)) < 1e-8
# Try on-site cluster.
# loop over random supercells.
# PI should be number of proportional to number of each atomic type on each
# site, or thereabouts
mapping = a.occupation_mapping()
for i in xrange(10):
# create random superstructure
superstructure = supercell(lattice, dot(lattice.cell, get_cell()))
for atom in superstructure: atom.type = choice(atom.type)
# now first and second site clusters
for i, site in enumerate(lattice):
# loop over flavors.
types = [u.type for u in superstructure]
a.spins = None
a.add_spin(site.pos)
s = mapping[i].itervalues().next().copy()
s[:] = 0e0
for t in site.type:
s += float(types.count(t)) * mapping[i][t]
assert all(abs(a(superstructure) - s) < 1e-8)
