def test_analyse_average_distribution_function():
from carmm.analyse.distribution_functions import average_distribution_function
#Build model
from data.model_gen import get_example_slab as slab
slab_1 = slab(adsorbate=True)
slab_2 = slab(adsorbate=True)
slab_2.positions *= 1.05
slab_trajectory = [slab_1, slab_2]
all_data, snapshots = average_distribution_function(
trajectory=slab_trajectory, samples=2)
assert (len(all_data) == 420)
assert (1e-5 > abs(sum(all_data) - 1754.778323))
# Example how to plot data
from carmm.analyse.distribution_functions import plot_distribution_function
from matplotlib import pyplot as plt
# Clean axes before new plot
plt.cla()
# Plot all snapshots
for i in range(len(snapshots)):
plot_distribution_function(snapshots[i], color='#808080', density=True)
# Plot mean (i.e. average bins over all data, rather than separate snapshots).
# This probably need double checking with something known e.g. H2O TODO
plot_distribution_function(
all_data,
title='Last ' + str(len(snapshots)) + ' Snapshots',
density=True,
# Additional graph plotting variables
label='Mean',
color="#000000")
plt.legend()
def test_build_cutout():
from carmm.build.cutout import cutout_sphere
#### Traditional ASE functionality #####
from data.model_gen import get_example_slab as slab
slab = slab(adsorbate=True)
#########
cutout = cutout_sphere(slab, 13)
assert (len(cutout) == 12)
def test_analyse_planes():
from carmm.analyse.planes import get_interplane_distances
#### Traditional ASE functionality #####
from data.model_gen import get_example_slab as slab
slab = slab(adsorbate=True)
#########
distances_sorted = sorted(get_interplane_distances(slab))
# As the adsorbate is 3 Angstrom above the surface, this should be the shortest distance
assert (1e-5 > abs(3.0 - distances_sorted[0]))
def test_run_k_grid():
from carmm.run.aims_calculator import get_k_grid
from ase.build import molecule
#### Traditional ASE functionality #####
from data.model_gen import get_example_slab as slab
slab = slab(adsorbate=True)
#########
sampling_density = 0.02 # example value of sampling density /Angstrom
k_grid = get_k_grid(slab, sampling_density, verbose=True)
assert k_grid == (6, 6, 1)
assert get_k_grid(molecule("CO2"), sampling_density) == None
def test_distance_between_centers_of_mass():
from carmm.analyse.molecules import calculate_molecules
from carmm.analyse.planes import distance_between_centers_of_mass
from data.model_gen import get_example_slab as slab
### Traditional ASE functionality #####
slab = slab(adsorbate=True)
molecules = calculate_molecules(slab)
A_mol = slab[molecules[0]]
B_mol = slab[molecules[1]]
distance_between_centers_of_mass(A_mol, B_mol)
#print(distances_between_centers_of_mass(A_mol, B_mol))
value = distance_between_centers_of_mass(A_mol, B_mol)
assert(1e-5 > value - 6.32082)
def test_neighbours():
'''
Test neighbour function
'''
from carmm.analyse.neighbours import neighbours
# Build model
from data.model_gen import get_example_slab as slab
slab = slab(adsorbate=True)
# Calculate neighbours
all_neighbour_atoms, shell_list = neighbours(slab, [13], 1, verbose=True)
# Verify results
assert (all_neighbour_atoms == [1, 2, 4, 10, 11, 12, 13, 14, 15, 16])
assert (shell_list == [[13], [1, 2, 4, 10, 11, 12, 14, 15, 16]])
def test_analyse_bonds():
from carmm.analyse.bonds import analyse_all_bonds
#### Traditional ASE functionality #####
from data.model_gen import get_example_slab as slab
slab = slab(adsorbate=True)
# Deform the z-coordinate for C so the Au-C bond length is too short, to test deformation
slab.positions[-3][2] -= 1.5
#########
abnormal_count, abnormal_bond_names = analyse_all_bonds(slab,
abnormal=True)
assert (len(abnormal_count) == 1)
def test_analyse_angles():
from carmm.analyse.angles import analyse_all_angles
#### Traditional ASE functionality #####
from data.model_gen import get_example_slab as slab
slab = slab(adsorbate=True)
#########
elements, indices, angles = analyse_all_angles(slab, verbose=True)
index_au = elements.index(('Au', 'Au', 'Au'))
assert (len(elements) == 2)
assert (len(indices) == 2 and len(indices[index_au]) == 648)
assert (len(angles) == 2 and len(angles[index_au]) == 648)
def test_analyse_get_sorted_distances():
from carmm.analyse.bonds import get_sorted_distances
#Build a model
from data.model_gen import get_example_slab as slab
slab = slab(adsorbate=True)
distances = get_sorted_distances(slab)
# Check values are stil lthe same and ordering is correct
assert (len(distances) == 210)
assert (1e-5 > abs(distances[0] - 1.178657))
assert (1e-5 > abs(distances[-1] - 7.132005))
# Test plot
from carmm.analyse.distribution_functions import plot_distribution_function
plt = plot_distribution_function(distances,
title='Radial Distribution Function')
def test_analyse_radial_distribution_function():
from carmm.analyse.distribution_functions import radial_distribution_function
#Build model
from data.model_gen import get_example_slab as slab
slab = slab(adsorbate=True)
distances = radial_distribution_function(model=slab,
radius=10,
position=0,
verbose=True)
assert (len(distances) == 88)
assert (1e-5 > abs(distances[0] - 2.938999))
assert (1e-5 > abs(distances[87] - 9.936709))
from carmm.analyse.distribution_functions import plot_distribution_function
plt = plot_distribution_function(distances,
title='Radial Distribution Function')
def test_build_symmetry_mirror():
###### EXAMPLE OF USE - MIRROR AND TRANSLATION ########
#from ase.visualize import view
from data.model_gen import get_example_slab as slab
from carmm.build.neb.symmetry import mirror, translation, rotate_fcc
for surface_facet in ['111', '100', '110']:
# Toy model of CO2 on top of Au FCC(111)
model = slab(adsorbate=True, surface=surface_facet)
#view(model)
# Retrieve index of the C atom
index = [atom.index for atom in model if atom.symbol == "C"]
# Mirror model in the x plane with respect to C atom
# C atom remains in place, the rest of unit cell is shifted accordingly
model = mirror(model,
center_index=index[0],
plane='y',
surf=surface_facet)
#view(model)
# Translate one row of atoms at a time in x and y
# Move adsorbate to the middle of the unit cell
model = translation(model, axis=0, surface=surface_facet)
model = translation(model, axis=1, surface=surface_facet)
#view(model)
### ASSERTION ###
eps = 1e-8
# Check if Oxygen moves as expected
if surface_facet == "111":
assert (model[19].position - [4.01974776, 2.0844678, 15.39968345] <
[eps, eps, eps]).all()
elif surface_facet == "100":
assert (model[19].position - [3.50559559, 3.65087324, 15.07818683]
< [eps, eps, eps]).all()
elif surface_facet == "110":
assert (model[19].position - [5.33165608, 3.65087324, 14.4695] <
[eps, eps, eps]).all()
def test_build_alloy():
from carmm.build.alloy import binary_alloy
#### Traditional ASE functionality #####
from data.model_gen import get_example_slab as slab
slab = slab()
#########
alloy_slab = binary_alloy(slab, 'Pd', 8)
assert(alloy_slab.get_chemical_symbols().count('Pd') == 8)
assert(alloy_slab.get_chemical_symbols().count('Au') == 10)
#### Ternary_alloy test ####
from carmm.build.alloy import ternary_alloy
ternary_slab = ternary_alloy(slab, 'Pd', 'Zn', 4, 5)
# This currently fails.
# TODO: Improve ternary so it preserves the requested composition for 2nd element
# assert(ternary_slab.get_chemical_symbols().count('Pd') == 4)
assert(ternary_slab.get_chemical_symbols().count('Zn') == 5)
def test_molecules():
'''
Test function for number of molecules in model
'''
from ase.visualize import view
from carmm.analyse.molecules import calculate_molecules
# Build model
from data.model_gen import get_example_slab as slab
slab = slab(adsorbate=True)
# Calculate neighbours
molecules = calculate_molecules(slab)
# View seperate molecules and recombine
A_mol = slab[molecules[0]]
B_mol = slab[molecules[1]]
#view(A_mol)
#view(B_mol)
#view(slab)
# Verify results
assert (len(molecules) == 2)