def check_nrg(value):
"""
Check for PDF energy against known value
:param value:
:return:
"""
# setup
atoms1, atoms2 = value[0]
exp_dict = value[1]
p, thresh = value[2]
proc1, alg1 = value[3]
scat = ElasticScatter(verbose=True)
scat.update_experiment(exp_dict)
scat.set_processor(proc1, alg1)
if value[4] == 'FQ':
exp_func = scat.get_fq
exp_grad = scat.get_grad_fq
elif value[4] == 'PDF':
exp_func = scat.get_pdf
exp_grad = scat.get_grad_pdf
else:
exp_func = None
exp_grad = None
target_data = exp_func(atoms1)
calc = Calc1D(target_data=target_data,
exp_function=exp_func,
exp_grad_function=exp_grad,
potential=p)
atoms2.set_calculator(calc)
ans = atoms2.get_potential_energy()
assert ans >= thresh
del atoms1, atoms2, proc1, alg1, p, thresh, scat, target_data, calc, ans
def check_nrg(value):
"""
Check for PDF energy against known value
:param value:
:return:
"""
# setup
atoms1, atoms2 = value[0]
exp_dict = value[1]
p, thresh = value[2]
proc1, alg1 = value[3]
scat = ElasticScatter(verbose=True)
scat.update_experiment(exp_dict)
scat.set_processor(proc1, alg1)
if value[4] == 'FQ':
exp_func = scat.get_fq
exp_grad = scat.get_grad_fq
elif value[4] == 'PDF':
exp_func = scat.get_pdf
exp_grad = scat.get_grad_pdf
else:
exp_func = None
exp_grad = None
target_data = exp_func(atoms1)
calc = Calc1D(target_data=target_data,
exp_function=exp_func, exp_grad_function=exp_grad,
potential=p)
atoms2.set_calculator(calc)
ans = atoms2.get_potential_energy()
assert ans >= thresh
del atoms1, atoms2, proc1, alg1, p, thresh, scat, target_data, calc, ans
def check_nrg(value):
"""
Check two processor, algorithm pairs against each other for PDF energy
Parameters
----------
value: list or tuple
The values to use in the tests
"""
rtol = 4e-6
atol = 9e-6
# setup
atoms1, atoms2 = value[0]
exp_dict = value[1]
p, thresh = value[2]
proc1, alg1 = value[3][0]
proc2, alg2 = value[3][1]
scat = ElasticScatter(verbose=True)
scat.update_experiment(exp_dict)
scat.set_processor(proc1, alg1)
if value[4] == 'FQ':
exp_func = scat.get_fq
exp_grad = scat.get_grad_fq
elif value[4] == 'PDF':
exp_func = scat.get_pdf
exp_grad = scat.get_grad_pdf
else:
exp_func = None
exp_grad = None
target_data = exp_func(atoms1)
calc = Calc1D(target_data=target_data,
exp_function=exp_func,
exp_grad_function=exp_grad,
potential=p)
atoms2.set_calculator(calc)
ans1 = atoms2.get_potential_energy()
scat.set_processor(proc2, alg2)
calc = Calc1D(target_data=target_data,
exp_function=exp_func,
exp_grad_function=exp_grad,
potential=p)
atoms2.set_calculator(calc)
ans2 = atoms2.get_potential_energy()
stats_check(ans2, ans1, rtol, atol)
def check_forces(value):
"""
Check two processor, algorithm pairs against each other for PDF forces
:param value:
:return:
"""
# setup
rtol = 1e-4
atol = 6e-5
atoms1, atoms2 = value[0]
exp_dict = value[1]
p, thresh = value[2]
proc1, alg1 = value[3][0]
proc2, alg2 = value[3][1]
scat = ElasticScatter(verbose=True)
scat.update_experiment(exp_dict)
scat.set_processor(proc1, alg1)
if value[4] == 'FQ':
exp_func = scat.get_fq
exp_grad = scat.get_grad_fq
elif value[4] == 'PDF':
exp_func = scat.get_pdf
exp_grad = scat.get_grad_pdf
else:
exp_func = None
exp_grad = None
target_data = exp_func(atoms1)
calc = Calc1D(target_data=target_data,
exp_function=exp_func,
exp_grad_function=exp_grad,
potential=p)
atoms2.set_calculator(calc)
ans1 = atoms2.get_forces()
scat.set_processor(proc2, alg2)
calc = Calc1D(target_data=target_data,
exp_function=exp_func,
exp_grad_function=exp_grad,
potential=p)
atoms2.set_calculator(calc)
ans2 = atoms2.get_forces()
stats_check(ans2, ans1, rtol=rtol, atol=atol)
def check_forces(value):
"""
Check for PDF forces against known value
:param value:
:return:
"""
# setup
atoms1, atoms2 = value[0]
exp_dict = value[1]
p, thresh = value[2]
proc1, alg1 = value[3]
scat = ElasticScatter(verbose=True)
scat.update_experiment(exp_dict)
scat.set_processor(proc1, alg1)
if value[4] == 'FQ':
exp_func = scat.get_fq
exp_grad = scat.get_grad_fq
elif value[4] == 'PDF':
exp_func = scat.get_pdf
exp_grad = scat.get_grad_pdf
else:
exp_func = None
exp_grad = None
target_data = exp_func(atoms1)
calc = Calc1D(target_data=target_data,
exp_function=exp_func,
exp_grad_function=exp_grad,
potential=p)
atoms2.set_calculator(calc)
# print atoms2.get_potential_energy()
forces = atoms2.get_forces()
print(forces)
com = atoms2.get_center_of_mass()
for i in range(len(atoms2)):
dist = atoms2[i].position - com
stats_check(np.cross(dist, forces[i]), np.zeros(3), atol=1e-7)
del dist
del atoms1, atoms2, proc1, alg1, p, thresh, scat, target_data, calc, \
forces, com
def check_forces(value):
"""
Check for PDF forces against known value
:param value:
:return:
"""
# setup
atoms1, atoms2 = value[0]
exp_dict = value[1]
p, thresh = value[2]
proc1, alg1 = value[3]
scat = ElasticScatter(verbose=True)
scat.update_experiment(exp_dict)
scat.set_processor(proc1, alg1)
if value[4] == 'FQ':
exp_func = scat.get_fq
exp_grad = scat.get_grad_fq
elif value[4] == 'PDF':
exp_func = scat.get_pdf
exp_grad = scat.get_grad_pdf
else:
exp_func = None
exp_grad = None
target_data = exp_func(atoms1)
calc = Calc1D(target_data=target_data,
exp_function=exp_func, exp_grad_function=exp_grad,
potential=p)
atoms2.set_calculator(calc)
# print atoms2.get_potential_energy()
forces = atoms2.get_forces()
print(forces)
com = atoms2.get_center_of_mass()
for i in range(len(atoms2)):
dist = atoms2[i].position - com
stats_check(np.cross(dist, forces[i]), np.zeros(3), atol=1e-7)
del dist
del atoms1, atoms2, proc1, alg1, p, thresh, scat, target_data, calc, \
forces, com
import numpy as np
from ase.atoms import Atoms
from pyiid.experiments.elasticscatter import ElasticScatter
import matplotlib.pyplot as plt
from matplotlib.colors import LogNorm
import ase.io
__author__ = 'christopher'
# atoms = Atoms('Au4', [[0, 0, 0], [3, 0, 0], [0, 3, 0], [3, 3, 0]])
atoms = ase.io.read('/mnt/work-data/dev/IID_data/db_test/PDF_LAMMPS_587.traj')
scat = ElasticScatter()
scat.update_experiment({'qmax': 8, 'qmin': .5})
s = scat.get_scatter_vector()
k = 100
i_max, j_max = k, k
pixel_array = np.zeros((i_max, j_max))
for i in range(i_max):
for j in range(j_max):
pixel_array[i, j] = np.sqrt(i**2 + j**2)
pixel_array /= np.max(pixel_array)
pixel_array *= np.max(s)
img = scat.get_2d_scatter(atoms, pixel_array)
print img.shape
# plt.imshow(pixel_array)
print np.max(img), np.min(img)
plt.imshow(img, aspect='auto')
import numpy as np
from ase.atoms import Atoms
from pyiid.experiments.elasticscatter import ElasticScatter
import matplotlib.pyplot as plt
from matplotlib.colors import LogNorm
import ase.io
__author__ = 'christopher'
# atoms = Atoms('Au4', [[0, 0, 0], [3, 0, 0], [0, 3, 0], [3, 3, 0]])
atoms = ase.io.read('/mnt/work-data/dev/IID_data/db_test/PDF_LAMMPS_587.traj')
scat = ElasticScatter()
scat.update_experiment({'qmax': 8, 'qmin': .5})
s = scat.get_scatter_vector()
k = 100
i_max, j_max = k, k
pixel_array = np.zeros((i_max, j_max))
for i in range(i_max):
for j in range(j_max):
pixel_array[i, j] = np.sqrt(i ** 2 + j ** 2)
pixel_array /= np.max(pixel_array)
pixel_array *= np.max(s)
img = scat.get_2d_scatter(atoms, pixel_array)
print img.shape
# plt.imshow(pixel_array)
print np.max(img), np.min(img)
