def _open(self):
self._closed = False
self._step = 0
self._frame = -1
if isinstance(self.filename, chemfiles.Trajectory):
self._file = self.filename
else:
self._file = chemfiles.Trajectory(self.filename, 'r', self._format)
def __init__(self, file, mode='r'):
super().__init__()
try:
import chemfiles
except:
raise ImportError(
'Currently mstools use chemfiles to parse XTC format. Cannot import chemfiles'
)
if mode not in ('r', 'w', 'a'):
raise Exception('Invalid mode')
self._xtc = chemfiles.Trajectory(file, mode)
def __init__(self,
filename,
n_atoms=0,
mode="w",
chemfiles_format="",
topology=None,
**kwargs):
"""
Parameters
----------
filename: str
filename of trajectory file.
n_atoms: int
number of atoms in the trajectory to write. This value is not
used and can vary during trajectory, if the underlying format
support it
mode : str (optional)
file opening mode: use 'a' to append to an existing file or 'w' to
create a new file
chemfiles_format : str (optional)
use the given format name instead of guessing from the extension.
The `list of supported formats <formats>`_ and the associated names
is available in chemfiles documentation.
topology : Universe or AtomGroup (optional)
use the topology from this :class:`~MDAnalysis.core.groups.AtomGroup`
or :class:`~MDAnalysis.core.universe.Universe` to write all the
timesteps to the file
**kwargs : dict
General writer arguments.
.. _formats: http://chemfiles.org/chemfiles/latest/formats.html
"""
if not check_chemfiles_version():
raise RuntimeError("Please install Chemfiles > {}"
"".format(MIN_CHEMFILES_VERSION))
self.filename = filename
self.n_atoms = n_atoms
if mode != "a" and mode != "w":
raise IOError("Expected 'a' or 'w' as mode in ChemfilesWriter")
self._file = chemfiles.Trajectory(self.filename, mode,
chemfiles_format)
self._closed = False
if topology is not None:
if isinstance(topology, string_types):
self._file.set_topology(topology)
else:
topology = self._topology_to_chemfiles(topology, n_atoms)
self._file.set_topology(topology)
def replace_pos(f_data, f_traj, mol_types, out_data, translate_z=0):
data = Data(f_data)
traj = chemfiles.Trajectory(f_traj)
frame = traj.read()
mol_atomid = []
for mol_type in mol_types:
mol_atomid.extend(get_atoms_id(mol_type, frame))
mol_atomid.sort() # array is 0-index
positions = frame.positions()
mol_pos = positions[mol_atomid]
for loop, item in enumerate(mol_atomid):
atom = data.Atoms[item].strip().split()
pos = mol_pos[loop]
pos[2] += translate_z
data.Atoms[item] = '%s %s %s %s %.4f %.4f %.4f %s %s' % (atom[0], atom[1], atom[2], atom[3], pos[0], pos[1], pos[2], atom[7], atom[8])
data.write(out_data)
import sys
import chemfiles
from rascaline import SoapPowerSpectrum
# read structures using chemfiles
with chemfiles.Trajectory(sys.argv[1]) as trajectory:
frames = [f for f in trajectory]
# define hyper parameters for the calculation
HYPER_PARAMETERS = {
"cutoff": 5.0,
"max_radial": 6,
"max_angular": 4,
"atomic_gaussian_width": 0.3,
"gradients": False,
"radial_basis": {
"Gto": {},
},
"cutoff_function": {
"ShiftedCosine": {
"width": 0.5
},
},
}
calculator = SoapPowerSpectrum(**HYPER_PARAMETERS)
# run the actual calculation
descriptor = calculator.compute(frames)
def bench_chemfiles(path):
file = chemfiles.Trajectory(path)
for step in range(file.nsteps):
file.read()
def count_eg_displaced(f_traj, eg_types=[7, 8, 9, 10], num_bins=5000, n_seg=5):
atoms_in_eg = 10.0
if type(f_traj) == type([]):
traj = chemfiles.Trajectory(f_traj[0])
elif type(f_traj) == type(''):
traj = chemfiles.Trajectory(f_traj)
n_frame = traj.nsteps()
frame = traj.read()
eg_atoms = chemfiles.Selection(
"atoms: name {0:d} or name {1:d} or name {2:d} or name {3:d}".format(
*eg_types)).evaluate(frame)
box_x, box_y, box_z = frame.cell().lengths()
box_area = box_x * box_y
eg_z = []
positions = frame.positions()
eg_z.append(list(positions[eg_atoms, 2]))
atoms_per_frame = len(eg_z[0])
for i in range(traj.nsteps() - 1):
frame = traj.read()
positions = frame.positions()
eg_z.append(list(positions[eg_atoms, 2]))
if type(f_traj) == type([]) and len(f_traj) > 1:
for ft in f_traj[1:]:
traj = chemfiles.Trajectory(ft)
n_frame += traj.nsteps()
for i in range(traj.nsteps() - 1):
frame = traj.read()
positions = frame.positions()
eg_z.append(list(positions[eg_atoms, 2]))
eg_z = [pbc_wrap(x, box_z) for li in eg_z for x in li]
seg_egz = np.array_split(eg_z, n_seg)
seg_len = np.mean(list(map(len, seg_egz)))
displaced_array = []
with open('displaced_eg.txt', 'a') as f:
f.write(time.strftime("%c"))
f.write('\nNumber of segments: %d\n' % n_seg)
for i in range(n_seg):
count, binEdges = np.histogram(seg_egz[i], num_bins, density=False)
dist_bin = binEdges[1] - binEdges[0] # Unit = A
bincenters = 0.5 * (binEdges[1:] + binEdges[:-1])
n_frame_seg = len(seg_egz[i]) / atoms_per_frame
density = count / (box_area * dist_bin * n_frame_seg * atoms_in_eg
) # Convert to density [=] EG / A^3
for index, val in enumerate(density):
print('{0:d} {1:.5f}'.format(index, val))
fig = plt.figure()
plt.plot(bincenters, density, 'r-')
plt.xlabel('z (nm)')
plt.ylabel(r'$\rho_{EG}$ ($EG/A^3$)')
fig.savefig('eg_density_%d.png' % (i + 1), dpi=fig.dpi)
plt.show()
plt.close()
print('Bin with density=0.0002 contribution: %.3f' %
(dist_bin * box_area * 0.0002))
bin_to_cover = 4.5 / dist_bin
print('Number of bin to cover 4.5 A: %.1f' % bin_to_cover)
bottom_2 = int(input('Enter index of bottom peak end (> 0.00020): '))
print('Recommended bottom peak start: %.0d' %
(bottom_2 - round(bin_to_cover)))
# bottom_1 = int(input('Enter index of bottom peak start: '))
bottom_1 = int(bottom_2 - round(bin_to_cover))
top_1 = int(input('Enter index of top peak start (> 0.00020): '))
print('Recommended top peak end: %.0d' % (top_1 + round(bin_to_cover)))
# top_2 = int(input('Enter index of top peak end: '))
top_2 = int(top_1 + round(bin_to_cover))
displaced_array.append(
get_displaced(density, box_area, dist_bin, f_traj, bottom_1,
bottom_2, top_1, top_2, i, n_frame_seg))
d = {}
d['displaced_array'] = displaced_array
d['displaced_mean'] = np.mean(displaced_array)
d['displaced_sem'] = sem(displaced_array)
print('Displaced array:')
print('%.2f ' * len(d['displaced_array']) % tuple(d['displaced_array']))
print('Displaced: %.2f +/- %.2f' %
(d['displaced_mean'], d['displaced_sem']))
with open('displaced_eg.txt', 'a') as f:
f.write('\nSummary\n')
f.write('Displaced array: ')
f.write('%.2f ' * len(d['displaced_array']) %
tuple(d['displaced_array']))
f.write('\n')
f.write('Displaced: %.2f +/- %.2f\n\n' %
(d['displaced_mean'], d['displaced_sem']))
# d['density'] = density
# d['box_area'] = box_area
# d['dist_bin'] = dist_bin
# d['f_traj'] = f_traj
# d['bottom_1'] = bottom_1
# d['bottom_2'] = bottom_2
# d['top_1'] = top_1
# d['top_2'] = top_2
return d
def get_density(F_TRAJ,
ATOM_TYPE,
SURF_ATOMS,
NUMBINS=100,
ATOM_NAME='pvp',
ON_TOP=False):
if type(F_TRAJ) == type([]):
traj = chemfiles.Trajectory(F_TRAJ[0])
elif type(F_TRAJ) == type(''):
traj = chemfiles.Trajectory(F_TRAJ)
n_frame = traj.nsteps()
frame = traj.read()
ATOMS = chemfiles.Selection(
"atoms: name {0:d}".format(ATOM_TYPE)).evaluate(frame)
ADJ_SURF_ATOMS = [x - 1 for x in SURF_ATOMS]
BOX_X, BOX_Y, BOX_Z = frame.cell().lengths()
BOX_AREA = BOX_X * BOX_Y
atom_z = []
surf_z = []
positions = frame.positions()
atom_z.append(list(positions[ATOMS, 2]))
surf_z.append(list(positions[ADJ_SURF_ATOMS, 2]))
ATOMS_PER_FRAME = len(atom_z[0])
for i in range(traj.nsteps() - 1):
frame = traj.read()
positions = frame.positions()
atom_z.append(list(positions[ATOMS, 2]))
surf_z.append(list(positions[ADJ_SURF_ATOMS, 2]))
if type(F_TRAJ) == type([]) and len(F_TRAJ) > 1:
for ft in F_TRAJ[1:]:
traj = chemfiles.Trajectory(ft)
n_frame += traj.nsteps()
for i in range(traj.nsteps() - 1):
frame = traj.read()
positions = frame.positions()
atom_z.append(list(positions[ATOMS, 2]))
surf_z.append(list(positions[ADJ_SURF_ATOMS, 2]))
atom_z = [[pbc_wrap(x, BOX_Z) for x in frame] for frame in atom_z]
surf_z = [[pbc_wrap(x, BOX_Z) for x in frame] for frame in surf_z]
avg_surf_z = [np.mean(frame) for frame in surf_z]
fig = plt.figure()
plt.hist([val for frame in surf_z for val in frame], 100)
plt.xlabel('z of surface atoms (A)')
plt.ylabel('counts')
plt.title(ATOM_NAME)
fig.savefig('ag_%s.png' % ATOM_NAME.replace(' ', '_'), dpi=fig.dpi)
plt.show()
plt.close()
adj_atom_z = []
for atom_frame, avg_surf in zip(atom_z, avg_surf_z):
if ON_TOP:
adj_atom_z.extend([atom - avg_surf for atom in atom_frame])
else:
adj_atom_z.extend([avg_surf - atom for atom in atom_frame])
count, binEdges = np.histogram(adj_atom_z, NUMBINS, density=False)
dist_bin = binEdges[1] - binEdges[0] # Unit = A
bincenters = 0.5 * (binEdges[1:] + binEdges[:-1])
density = count / (BOX_AREA * dist_bin * n_frame
) # Convert to density [=] atom / A^3
data = {}
data['name'] = ATOM_NAME
data['density'] = density
data['bincenters'] = bincenters
return data
def avg_eg_peak_width(f_traj, eg_types=[7, 8, 9, 10], num_bins=5000):
atoms_in_eg = 10.0
if type(f_traj) == type([]):
traj = chemfiles.Trajectory(f_traj[0])
elif type(f_traj) == type(''):
traj = chemfiles.Trajectory(f_traj)
n_frame = traj.nsteps()
frame = traj.read()
eg_atoms = chemfiles.Selection(
"atoms: name {0:d} or name {1:d} or name {2:d} or name {3:d}".format(
*eg_types)).evaluate(frame)
box_x, box_y, box_z = frame.cell().lengths()
box_area = box_x * box_y
eg_z = []
positions = frame.positions()
eg_z.append(list(positions[eg_atoms, 2]))
atoms_per_frame = len(eg_z[0])
for i in range(traj.nsteps() - 1):
frame = traj.read()
positions = frame.positions()
eg_z.append(list(positions[eg_atoms, 2]))
if type(f_traj) == type([]) and len(f_traj) > 1:
for ft in f_traj[1:]:
traj = chemfiles.Trajectory(ft)
n_frame += traj.nsteps()
for i in range(traj.nsteps() - 1):
frame = traj.read()
positions = frame.positions()
eg_z.append(list(positions[eg_atoms, 2]))
eg_z = [pbc_wrap(x, box_z) for li in eg_z for x in li]
count, binEdges = np.histogram(eg_z, num_bins, density=False)
dist_bin = binEdges[1] - binEdges[0] # Unit = A
bincenters = 0.5 * (binEdges[1:] + binEdges[:-1])
density = count / (box_area * dist_bin * n_frame * atoms_in_eg
) # Convert to density [=] EG / A^3
for index, val in enumerate(density):
print('{0:d} {1:.5f}'.format(index, val))
fig = plt.figure()
plt.plot(bincenters, density, 'r-')
plt.xlabel('z (nm)')
plt.ylabel(r'$\rho_{EG}$ ($EG/A^3$)')
fig.savefig('eg_density.png', dpi=fig.dpi)
plt.show()
plt.close()
print('Bin with density=0.0001 contribution: %.3f' %
(dist_bin * box_area * 0.0001))
bin_to_cover = 4.5 / dist_bin
print('Number of bin to cover 4.5 A: %.1f' % bin_to_cover)
bottom_2 = int(input('Enter index of bottom peak end (> 0.00010): '))
print('Recommended bottom peak start: %.0d' %
(bottom_2 - round(bin_to_cover)))
bottom_1 = int(input('Enter index of bottom peak start: '))
top_1 = int(input('Enter index of top peak start (> 0.00010): '))
print('Recommended top peak end: %.0d' % (top_1 + round(bin_to_cover)))
top_2 = int(input('Enter index of top peak end: '))
width_bottom = (bottom_2 - bottom_1) * dist_bin
width_top = (top_2 - top_1) * dist_bin
print('Width of bottom peak = %.2f A' % width_bottom)
print('Width of top peak = %.2f A' % width_top)
with open('eg_peak_width.txt', 'a') as f:
f.write(time.strftime("%c"))
f.write('\n')
f.write('Width of bottom peak = %.2f A\n' % width_bottom)
f.write('Width of top peak = %.2f A\n' % width_top)
def _sample_helper(self, frame_list, shift, is_pbc):
"""Helper function for sampling run.
Parameters
----------
frame_list :
List of frame ids to process
shift : list
Distances for translating all positions in nano meter
is_pbc : bool, optional
True to apply periodic boundary conditions
Returns : dictionary
Dictionary conatining all sampled data
"""
# Initialize
box = self._pore_props["box"] if self._pore else self._box
res = self._pore_props["res"] if self._pore else 0
com_list = []
idx_list = []
idx_list_mc = []
# Load trajectory
traj = cf.Trajectory(self._traj)
frame_form = "%"+str(len(str(self._num_frame)))+"i"
# Create local data structures
output = {}
if self._is_density:
output["density"] = self._density_data()
if self._is_gyration:
output["gyration"] = self._gyration_data()
if self._is_diffusion_bin:
output["diffusion_bin"] = self._diffusion_bin_data()
if self._is_diffusion_mc:
output["diffusion_mc"] = self._diffusion_mc_data()
# Run through frames
for frame_id in frame_list:
# Read frame
frame = traj.read_step(frame_id)
positions = frame.positions
# Add new dictionaries and remove unneeded references
if self._is_diffusion_bin:
len_fill = self._diff_bin_inp["len_window"]*self._diff_bin_inp["len_step"]
if len(com_list) >= len_fill:
com_list.pop(0)
idx_list.pop(0)
com_list.append({})
idx_list.append({})
# Add new dictionaries and remove unneeded references
if self._is_diffusion_mc:
if len(idx_list_mc) >= (max(self._diff_mc_inp["len_step"])+1):
idx_list_mc.pop(0)
idx_list_mc.append({})
# Run through residues
for res_id in self._res_list:
# Get position vectors
pos = [[positions[self._res_list[res_id][atom_id]][i]/10+shift[i] for i in range(3)] for atom_id in range(len(self._atoms))]
# Calculate centre of mass
com_no_pbc = [sum([pos[atom_id][i]*self._masses[atom_id] for atom_id in range(len(self._atoms))])/self._sum_masses for i in range(3)]
# Remove broken molecules
if self._is_diffusion_bin or self._is_density:
is_broken = False
for i in range(3):
is_broken = abs(com_no_pbc[i]-pos[0][i])>box[i]/3
if is_broken:
break
# Apply periodic boundary conditions
if is_pbc:
com = [com_no_pbc[i]-math.floor(com_no_pbc[i]/box[i])*box[i] for i in range(3)]
else:
com = com_no_pbc
# Sample if molecule not broken near boundary
if self._is_diffusion_bin or self._is_density:
if not is_broken:
# Calculate distance towards center axis
if isinstance(self._pore, pms.PoreCylinder):
dist = geometry.length(geometry.vector([self._pore_props["focal"][0], self._pore_props["focal"][1], com[2]], com))
elif isinstance(self._pore, pms.PoreSlit):
dist = abs(self._pore_props["focal"][1]-com[1])
else:
dist = 0
# Set region - in-inside, ex-outside
region = ""
if self._pore and com[2] > res+self._entry and com[2] < box[2]-res-self._entry:
region = "in"
elif not self._pore or com[2] <= res or com[2] > box[2]-res:
region = "ex"
# Remove window filling instances except from first processor
if self._is_diffusion_bin:
is_sample = len(com_list)==len_fill or frame_id<=len_fill
else:
is_sample = True
# Sampling routines
if is_sample:
if self._is_density:
self._density(output["density"], region, dist, com)
if self._is_gyration:
self._gyration(output["gyration"], region, dist, com_no_pbc, pos)
if self._is_diffusion_bin:
self._diffusion_bin(output["diffusion_bin"], region, dist, com_list, idx_list, res_id, com)
if self._is_diffusion_mc:
self._diffusion_mc(output["diffusion_mc"], idx_list_mc, res_id, com, frame_list, frame_id)
# Progress
if (frame_id+1)%10==0 or frame_id==0 or frame_id==self._num_frame-1:
sys.stdout.write("Finished frame "+frame_form%(frame_id+1)+"/"+frame_form%self._num_frame+"...\r")
sys.stdout.flush()
print()
return output
def __init__(self, system, link_traj, mol, atoms=[], masses=[], entry=0.5):
# Initialize
self._pore = utils.load(system) if isinstance(system, str) else None
self._box = system if isinstance(system, list) else []
self._traj = link_traj
self._mol = mol
self._atoms = atoms
self._masses = masses
self._entry = entry
# Set analysis routines
self._is_density = False
self._is_gyration = False
self._is_diffusion_bin = False
self._is_diffusion_mc = False
# Get molecule ids
self._atoms = [atom.get_name() for atom in mol.get_atom_list()] if not self._atoms else self._atoms
self._atoms = [atom_id for atom_id in range(mol.get_num()) if mol.get_atom_list()[atom_id].get_name() in self._atoms]
# Check masses
if not self._masses:
if len(self._atoms)==mol.get_num():
self._masses = mol.get_masses()
elif len(self._atoms) == 1:
self._masses = [1]
self._sum_masses = sum(self._masses)
# Check atom mass consistency
if self._atoms and not len(self._masses) == len(self._atoms):
print("Length of variables *atoms* and *masses* do not match!")
return
# Get number of frames
traj = cf.Trajectory(self._traj)
self._num_frame = traj.nsteps
# Get numer of residues
frame = traj.read()
num_res = len(frame.topology.atoms)/mol.get_num()
# Check number of residues
if abs(int(num_res)-num_res) >= 1e-5:
print("Number of atoms is inconsistent with number of residues.")
return
# Create residue list with all relevant atom ids
self._res_list = {}
for res_id in range(int(num_res)):
self._res_list[res_id] = [res_id*mol.get_num()+atom for atom in range(mol.get_num()) if atom in self._atoms]
# Get pore properties
self._pore_props = {}
if self._pore:
if isinstance(self._pore, pms.PoreCylinder):
self._pore_props["type"] = "CYLINDER"
elif isinstance(self._pore, pms.PoreSlit):
self._pore_props["type"] = "SLIT"
self._pore_props["res"] = self._pore.reservoir()
self._pore_props["focal"] = self._pore.centroid()
self._pore_props["box"] = self._pore.box()
self._pore_props["box"][2] += 2*self._pore_props["res"]
# Get pore diameter
if isinstance(self._pore, pms.PoreCylinder):
self._pore_props["diam"] = self._pore.diameter()
elif isinstance(self._pore, pms.PoreSlit):
self._pore_props["diam"] = self._pore.height()
