def rdump_m(filename):
steps = []
with open(filename, 'r') as file:
while True:
line = file.readline()
if not line:
break
line = file.readline()
count_step = int(line.split()[0])
for i in range(2):
line = file.readline()
natoms = int(line.split()[0])
file.readline()
box = []
for i in range(3):
line = file.readline()
box.append([float(word) for word in line.split()])
line = file.readline()
kws = line.split()[2:]
atoms = {}
for i in range(natoms):
line = file.readline()
words = line.split()
properties = words
atom = Atom_m(properties)
atoms[atom.get_property('id',kws)] = atom
step = mt.Step(atoms, count_step, box)
steps.append(step)
return steps,kws
def convert_to_dump(pkas):
import numpy as np
atoms = {}
for pka in pkas:
atom = mt.Atom({
'id': pka[0],
'x': pka[2] * 1e10,
'y': pka[3] * 1e10,
'z': pka[4] * 1e10,
'E': pka[5],
'time': pka[1] * 1e6
})
atoms[atom.id] = atom
step = mt.Step(atoms, 0, np.array(box) * 1e10)
steps = [step]
mt.wdump(steps, 'pkas.dump', ['id', 'x', 'y', 'z', 'E', 'time'])
def sia_va(refdump, cascadedump, siavadump):
steps = mt.rdump(refdump)
refatoms = steps[0].atoms
with open(cascadedump, 'r') as file:
cascade_lines = file.readlines()
with open(siavadump, 'w') as file:
nline = 0
nstep = 0
while nline < len(cascade_lines):
for i in range(4):
line = cascade_lines[nline]
file.write(line)
nline += 1
ndefects = int(line.split()[0])
for i in range(4):
line = cascade_lines[nline]
file.write(line)
nline += 1
for i in range(1):
line = "ITEM: ATOMS id type x y z c_2[1]\n"
file.write(line)
nline += 1
for i in range(ndefects):
line = cascade_lines[nline]
words = line.split()
id = int(words[0])
r = refatoms[id].r
words = words[:2] + [str(xs) for xs in r] + words[2:]
words[2:5] = [str(xs) for xs in r]
line = "{0} {1} {2} {3} {4} {5}\n".format(
words[0], words[1], words[2], words[3], words[4], words[5])
file.write(line)
nline += 1
nstep += 1
if (nstep % 100 == 0):
print(nstep)
def rdump(filename):
steps = []
with open(filename, 'r') as file:
while True:
line = file.readline()
if not line:
break
line = file.readline()
count_step = int(line.split()[0])
for i in range(2):
line = file.readline()
natoms = int(line.split()[0])
file.readline()
box = []
for i in range(3):
line = file.readline()
box.append([float(word) for word in line.split()])
line = file.readline()
kws = line.split()[3:]
dir = {}
for kw in kws:
dir[kw] = []
index = []
for i in range(natoms):
line = file.readline()
words = [float(word) for word in line.split()]
for word, kw in zip(words[1:], kws):
dir[kw].append(word)
index.append(int(words[0]))
if i % 100000 == 0:
print('Loading atoms:', i)
atoms = pd.DataFrame(dir, index)
dir = {}
step = mt.Step(atoms, count_step, box)
steps.append(step)
return steps
import MDtools as mt
import math
import numpy as np
print('processing... don\'t touch me\n')
atoms_cell = mt.rdump('cell.dump')[-1].atoms
atoms_sia = mt.rdump('sia_lammps.dump')[-1].atoms
print('reading completed.')
print('start computing...')
def c_distance(r1, r2):
return math.sqrt(np.dot(r1 - r2, r1 - r2))
def find_neibour(self, atoms):
atoms_sorted = sorted(
atoms.items(), key=lambda item: c_distance(item[1].r, self.r))
self.neibours = [atoms_sorted[0][1], atoms_sorted[1][1]]
def sia_dirction(self):
dr = self.neibours[1].r - self.neibours[0].r
maxr = max(abs(dr))
for i in range(3):
if abs(dr[i]) / maxr < 0.3:
dr[i] = 0
self.dirction = [int(i / abs(i)) if i != 0 else 0 for i in dr]
self.properties['c_2[1]'] = int(self.properties['c_2[1]'])
if self.properties['c_2[1]'] == 0:
ave_msd[key] += value
for key, value in ave_msd.items():
ave_msd[key] /= len(ids)
return ave_msd
def compute_diff_coe(msddata):
'''
unit: unit: Angstrom^2/ps
'''
from scipy import stats
times = []
x2s = []
for time, x2 in msddata.items():
times.append(time)
x2s.append(x2)
linregress = stats.linregress(times, x2s)
diff_coe = linregress[0]
r2 = linregress[2]
return diff_coe, r2
if __name__ == '__main__':
import MDtools as mt
steps = mt.rdump('H1.dump')
msd = compute_msd(steps, [2001], istep=1000, ave_level=100, nplot=5)
coe = compute_diff_coe(msd)
print(coe)
for k, v in msd.items():
print(k, v)
addids.append(id)
break
elif (np.array([atom.properties['d1'], atom.properties['d2'], atom.properties['d3']]) == -1 * self.direction).all():
addids.append(id)
break
for id in addids:
self.add_member(atoms[id])
if len(addids) == 0:
self.fulled = 1
def divide_atoms(atoms, cut):
groups = []
for id, atom in atoms.items():
atom.fresh()
for id, atom in atoms.items():
if not hasattr(atom, 'swallowed'):
group = Group({atom.id: atom})
group.swallow(atoms, cut)
groups.append(group)
return groups
if __name__ == '__main__':
steps = mt.rdump('loop.dump')
atoms = steps[0].atoms
groups = divide_atoms(atoms, 10)
print(len(groups))
print(len(groups[0].members))
print(groups[1].size)
import MDtools as mt
import numpy as np
import math
import matplotlib.pyplot as plt
import os
def distance(r1, r2):
return math.sqrt((r2[0] - r1[0])**2 + (r2[1] - r1[1])**2 +
(r2[2] - r1[2])**2)
steps = mt.rdump('cell_direction.dump')
atoms = steps[0].atoms
s_center = np.array([0., 0., 0.])
s_n = 0
v_center = np.array([0., 0., 0.])
v_n = 0
for id_, atom in atoms.items():
if atom.properties['c_2[1]'] >= 2:
s_center += atom.r
s_n += 1
else:
v_center += atom.r
v_n += 1
s_center /= s_n
v_center /= v_n
import numpy as np
from numpy import linalg as LA
def compute_pressure(steps, c_stress='c_2'):
# unit: bar*A^3
for step in steps:
for id_, atom in step.atoms.items():
sts = [
atom.properties[c_stress + '[{0}]'.format(i)]
for i in range(1, 7)
]
stress_mat = np.mat([[sts[0], sts[3], sts[5]],
[sts[3], sts[1], sts[4]],
[sts[5], sts[4], sts[2]]])
eig_mat = LA.eig(stress_mat)[1]
diag_mat = eig_mat.I * stress_mat * eig_mat
pressure_v = np.array(diag_mat)[0][0] + np.array(
diag_mat)[1][1] + np.array(diag_mat)[2][2]
atom.properties['ps_v'] = pressure_v
if __name__ == '__main__':
import MDtools as mt
filename = input('File name: ')
steps = mt.rdump(filename)
compute_pressure(steps)
mt.wdump(steps, 'ps_v.' + filename)
import MDtools as mt
steps = mt.rdump('cell.dump')
displacements = []
for step in steps:
displacement = 0
for k,atom in step.atoms.items():
if atom.properties['c_2[1]'] == 0:
displacement += 1
displacements.append(displacement)
steps = []
times = []
with open('log.lammps','r') as log:
flag = 0
while True: # 这有点难 ( ╯□╰ ) 谔谔
line = log.readline()
if line == "Step Time Dt Temp \n":
flag += 1
elif line[:8] == "Fix halt":
break
elif flag == 2:
words = [float(word) for word in line.split()]
time = words[1] - 1.0
times.append(time)
with open('results/process.data','w') as file:
for time,displacement in zip(times,displacements):
file.write('{0} {1}\n'.format(time, displacement))