pmsco-public/tests/test_cluster.py
matthias muntwiler bbd16d0f94 add files for public distribution
based on internal repository 0a462b6 2017-11-22 14:41:39 +0100
2017-11-22 14:55:20 +01:00

322 lines
12 KiB
Python

"""
@package tests.test_cluster
unit tests for pmsco.cluster
the purpose of these tests is to check whether the code runs as expected in a particular environment.
to run the tests, change to the directory which contains the tests directory, and execute =nosetests=.
@pre nose must be installed (python-nose package on Debian).
@author Matthias Muntwiler, matthias.muntwiler@psi.ch
@copyright (c) 2015-17 by Paul Scherrer Institut @n
Licensed under the Apache License, Version 2.0 (the "License"); @n
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
"""
import unittest
import math
import numpy as np
import pmsco.cluster as mc
class TestClusterFunctions(unittest.TestCase):
def setUp(self):
# before each test method
pass
def tearDown(self):
# after each test method
pass
@classmethod
def setup_class(cls):
# before any methods in this class
pass
@classmethod
def teardown_class(cls):
# teardown_class() after any methods in this class
pass
@staticmethod
def create_cube():
"""
create a cluster object with atoms on the corners, faces and body center of the unit cube.
the atom types are unique in an arbitrary sequence.
the emitter is at the origin, atom type 1.
@return: cluster.Cluster object.
"""
clu = mc.Cluster()
clu.add_atom(1, np.asarray([0, 0, 0]), 1)
clu.add_atom(2, np.asarray([1, 0, 0]), 0)
clu.add_atom(3, np.asarray([0, 1, 0]), 0)
clu.add_atom(4, np.asarray([0, 0, 1]), 0)
clu.add_atom(5, np.asarray([-1, 0, 0]), 0)
clu.add_atom(6, np.asarray([0, -1, 0]), 0)
clu.add_atom(7, np.asarray([0, 0, -1]), 0)
clu.add_atom(8, np.asarray([1, 1, 0]), 0)
clu.add_atom(9, np.asarray([0, 1, 1]), 0)
clu.add_atom(10, np.asarray([1, 0, 1]), 0)
clu.add_atom(11, np.asarray([-1, 1, 0]), 0)
clu.add_atom(12, np.asarray([0, -1, 1]), 0)
clu.add_atom(13, np.asarray([1, 0, -1]), 0)
clu.add_atom(14, np.asarray([-1, -1, 0]), 0)
clu.add_atom(15, np.asarray([0, -1, -1]), 0)
clu.add_atom(16, np.asarray([-1, 0, -1]), 0)
clu.add_atom(17, np.asarray([1, -1, 0]), 0)
clu.add_atom(18, np.asarray([0, 1, -1]), 0)
clu.add_atom(19, np.asarray([-1, 0, 1]), 0)
clu.add_atom(20, np.asarray([1, 1, 1]), 0)
clu.add_atom(21, np.asarray([-1, 1, 1]), 0)
clu.add_atom(22, np.asarray([1, -1, 1]), 0)
clu.add_atom(23, np.asarray([1, 1, -1]), 0)
clu.add_atom(24, np.asarray([-1, -1, -1]), 0)
clu.add_atom(25, np.asarray([1, -1, -1]), 0)
clu.add_atom(26, np.asarray([-1, 1, -1]), 0)
clu.add_atom(27, np.asarray([-1, -1, 1]), 0)
return clu
def test_numpy_extract(self):
"""
test array extraction code which should be compatible to numpy versions before and after 1.14.
numpy 1.14 introduces changes to multi-column indexing of structured arrays such as data[['x','y']].
first, it will return a view instead of a copy.
second, it will assign fields by position rather than by name.
the first change affects our cluster code in several places
where we extract XYZ coordinates from the cluster data array.
this test checks whether the new code works with a particular numpy version.
@return: None
"""
clu = self.create_cube()
xy2 = clu.data[['x', 'y']].copy()
xy3 = xy2.view((xy2.dtype[0], len(xy2.dtype.names)))
ctr = np.asarray((1.0, 0.0, 0.0))
dist = np.linalg.norm(xy3 - ctr[0:2], axis=1)
self.assertAlmostEqual(1.0, dist[0])
self.assertAlmostEqual(0.0, dist[1])
clu.clear()
xy2 = clu.data[['x', 'y']].copy()
xy3 = xy2.view((xy2.dtype[0], len(xy2.dtype.names)))
ctr = np.asarray((1.0, 0.0, 0.0))
dist = np.linalg.norm(xy3 - ctr[0:2], axis=1)
self.assertEqual(0, dist.shape[0])
def test_get_positions(self):
"""
check that we get an independent copy of the original data.
@return: None
"""
clu = self.create_cube()
pos = clu.get_positions()
self.assertEqual(clu.data.shape[0], pos.shape[0])
self.assertEqual(3, pos.shape[1])
self.assertEqual(np.float32, pos.dtype)
self.assertEqual(1.0, pos[1, 0])
self.assertEqual(0.0, pos[1, 1])
self.assertEqual(0.0, pos[1, 2])
pos[0, 0] = 15.0
self.assertEqual(0.0, clu.data['x'][0])
# empty cluster
clu.clear()
self.assertEqual(clu.data.shape[0], 0)
self.assertEqual(3, pos.shape[1])
self.assertEqual(np.float32, pos.dtype)
def test_set_positions(self):
clu = mc.Cluster()
clu.data = np.zeros(2, dtype=clu.dtype)
pos = np.array([[1., 2., 3.], [4., 5., 6.]])
clu.set_positions(pos)
self.assertEqual(1., clu.data['x'][0])
self.assertEqual(2., clu.data['y'][0])
self.assertEqual(3., clu.data['z'][0])
self.assertEqual(4., clu.data['x'][1])
self.assertEqual(5., clu.data['y'][1])
self.assertEqual(6., clu.data['z'][1])
def test_get_emitters(self):
clu = self.create_cube()
clu.set_emitter(idx=0)
clu.set_emitter(idx=9)
self.assertEqual(2, clu.get_emitter_count())
result = clu.get_emitters()
expect = [(0., 0., 0., 1), (1., 0., 1., 10)]
self.assertItemsEqual(expect, result)
def test_get_z_layers(self):
clu = mc.Cluster()
clu.add_atom(1, np.asarray([1, 0, 0.1]), 0)
clu.add_atom(2, np.asarray([0, 1, -0.3]), 0)
clu.add_atom(1, np.asarray([0, 1, -0.2]), 0)
clu.add_atom(1, np.asarray([1, 0, 0]), 1)
clu.add_atom(1, np.asarray([0, 1, -0.2001]), 0)
clu.add_atom(2, np.asarray([0, 1, -0.1]), 0)
clu.add_atom(1, np.asarray([0, 1, -0.1999]), 0)
layers = clu.get_z_layers(0.01)
np.testing.assert_allclose(layers, np.asarray([-0.3, -0.2, -0.1, 0.0, +0.1]), atol=0.001)
def test_relax(self):
clu = mc.Cluster()
clu.add_atom(1, np.asarray([1, 0, 1]), 0)
clu.add_atom(1, np.asarray([1, 0, 0]), 1)
clu.add_atom(2, np.asarray([0, 1, -1]), 0)
clu.add_atom(1, np.asarray([0, 1, -2]), 0)
clu.add_atom(2, np.asarray([0, 1, -3]), 0)
idx = clu.relax(-0.3, -0.1, 2)
np.testing.assert_almost_equal(idx, np.asarray([[2, 4]]))
np.testing.assert_allclose(clu.get_position(0), np.asarray([1, 0, 1]), atol=1e-6)
np.testing.assert_allclose(clu.get_position(1), np.asarray([1, 0, 0]), atol=1e-6)
np.testing.assert_allclose(clu.get_position(2), np.asarray([0, 1, -1.1]), atol=1e-6)
np.testing.assert_allclose(clu.get_position(3), np.asarray([0, 1, -2.0]), atol=1e-6)
np.testing.assert_allclose(clu.get_position(4), np.asarray([0, 1, -3.1]), atol=1e-6)
def test_rotate_x(self):
clu = mc.Cluster()
clu.add_atom(1, np.asarray([1, 0, 0]), 0)
clu.add_atom(1, np.asarray([0, 1, 0]), 0)
clu.add_atom(1, np.asarray([0, 0, 1]), 0)
clu.rotate_x(90)
np.testing.assert_allclose(clu.get_position(0), np.asarray([1, 0, 0]), atol=1e-6)
np.testing.assert_allclose(clu.get_position(1), np.asarray([0, 0, 1]), atol=1e-6)
np.testing.assert_allclose(clu.get_position(2), np.asarray([0, -1, 0]), atol=1e-6)
def test_rotate_y(self):
clu = mc.Cluster()
clu.add_atom(1, np.asarray([1, 0, 0]), 0)
clu.add_atom(1, np.asarray([0, 1, 0]), 0)
clu.add_atom(1, np.asarray([0, 0, 1]), 0)
clu.rotate_y(90)
np.testing.assert_allclose(clu.get_position(0), np.asarray([0, 0, -1]), atol=1e-6)
np.testing.assert_allclose(clu.get_position(1), np.asarray([0, 1, 0]), atol=1e-6)
np.testing.assert_allclose(clu.get_position(2), np.asarray([1, 0, 0]), atol=1e-6)
def test_rotate_z(self):
clu = mc.Cluster()
clu.add_atom(1, np.asarray([1, 0, 0]), 0)
clu.add_atom(1, np.asarray([0, 1, 0]), 0)
clu.add_atom(1, np.asarray([0, 0, 1]), 0)
clu.rotate_z(90)
np.testing.assert_allclose(clu.get_position(0), np.asarray([0, 1, 0]), atol=1e-6)
np.testing.assert_allclose(clu.get_position(1), np.asarray([-1, 0, 0]), atol=1e-6)
np.testing.assert_allclose(clu.get_position(2), np.asarray([0, 0, 1]), atol=1e-6)
def test_add_layer(self):
clu = mc.Cluster()
# from hbncu project
b_surf = 2.50
clu.set_rmax(4.0)
b1 = np.array((b_surf, 0.0, 0.0))
b2 = np.array((b_surf / 2.0, b_surf * math.sqrt(3.0) / 2.0, 0.0))
a1 = -10.0 * b1 - 10.0 * b2
emitter = np.array((0.0, 0.0, 0.0))
clu.add_layer(7, a1, b1, b2)
pos = clu.find_positions(pos=emitter)
self.assertEqual(len(pos), 1)
def test_add_cluster(self):
clu1 = mc.Cluster()
clu1.add_atom(1, np.asarray([0, 0, 0]), 1)
clu1.add_atom(2, np.asarray([1, 0, 0]), 0)
clu1.add_atom(3, np.asarray([0, 1, 0]), 0)
clu1.add_atom(4, np.asarray([0, 0, -1]), 0)
clu1.add_atom(5, np.asarray([0, 0, -2]), 0)
clu2 = mc.Cluster()
clu2.add_atom(3, np.asarray([-0.2, 0, 0]), 0)
clu2.add_atom(4, np.asarray([0, -0.2, 0]), 0)
clu2.add_atom(5, np.asarray([0, 0.05, -1]), 0)
clu2.add_atom(5, np.asarray([0, 0, -1.01]), 0)
clu2.add_atom(6, np.asarray([0, 0, -1.99]), 0)
clu1.set_rmax(1.5)
clu1.add_cluster(clu2, check_rmax=True, check_unique=True, tol=0.1)
self.assertEqual(clu1.get_atom_count(), 5+2)
def test_find_positions(self):
clu = mc.Cluster()
# from hbncu project
b_surf = 2.50
clu.set_rmax(b_surf * 10.0)
b1 = np.array((b_surf, 0.0, 0.0))
b2 = np.array((b_surf / 2.0, b_surf * math.sqrt(3.0) / 2.0, 0.0))
a_N = np.array((0.0, 0.0, 0.0))
a_B = np.array(((b1[0] + b2[0]) / 3.0, (b1[1] + b2[1]) / 3.0, 0.0))
emitter = a_N + b1 * 1 + b2 * 2
clu.add_layer(7, a_N, b1, b2)
clu.add_layer(5, a_B, b1, b2)
pos = clu.find_positions(pos=emitter)
self.assertEqual(len(pos), 1)
self.assertEqual(pos[0], 206)
def test_find_index_cylinder(self):
clu = self.create_cube()
pos = np.array((0.8, 0.8, 0.8))
rxy = 0.5
rz = 1.0
idx = clu.find_index_cylinder(pos, rxy, rz, None)
self.assertEqual(len(idx), 2)
self.assertEqual(clu.get_atomtype(idx[0]), 8)
self.assertEqual(clu.get_atomtype(idx[1]), 20)
idx = clu.find_index_cylinder(pos, rxy, rz, 8)
self.assertEqual(len(idx), 1)
def test_trim_cylinder(self):
clu = mc.Cluster()
clu.set_rmax(10.0)
v_pos = np.asarray([0, 0, 0])
v_lat1 = np.asarray([1, 0, 0])
v_lat2 = np.asarray([0, 1, 0])
v_lat3 = np.asarray([0, 0, 1])
clu.add_bulk(7, v_pos, v_lat1, v_lat2, v_lat3)
clu.set_emitter(pos=v_pos)
clu.trim_cylinder(2.3, 4.2)
self.assertEqual(clu.data.dtype, clu.dtype)
self.assertEqual(clu.data.shape[0], 21 * 5)
self.assertEqual(clu.data[1]['i'], 2)
self.assertEqual(clu.data[1]['s'], 'N')
self.assertEqual(clu.data[1]['t'], 7)
self.assertEqual(clu.get_emitter_count(), 1)
def test_trim_sphere(self):
clu = mc.Cluster()
clu.set_rmax(10.0)
v_pos = np.asarray([0, 0, 0])
v_lat1 = np.asarray([1, 0, 0])
v_lat2 = np.asarray([0, 1, 0])
v_lat3 = np.asarray([0, 0, 1])
clu.add_bulk(7, v_pos, v_lat1, v_lat2, v_lat3)
clu.set_emitter(pos=v_pos)
clu.trim_sphere(2.3)
self.assertEqual(clu.data.dtype, clu.dtype)
self.assertEqual(clu.data.shape[0], 39)
self.assertEqual(clu.data[1]['i'], 2)
self.assertEqual(clu.data[1]['s'], 'N')
self.assertEqual(clu.data[1]['t'], 7)
self.assertEqual(clu.get_emitter_count(), 1)
def test_trim_slab(self):
clu = self.create_cube()
clu.trim_slab('x', 0.5, 1.1)
self.assertEqual(clu.data.dtype, clu.dtype)
self.assertEqual(clu.data.shape[0], 9 * 2)
self.assertEqual(clu.get_emitter_count(), 1)