def gro_to_tracks(filename, destination, sub=slice(None), clear=True):
gro_reader = GroReader(filename, sub)
num_atoms = gro_reader.num_atoms
names = ["time"]
fields = [("time", numpy.float32)]
names.extend(sum((
["atom.pos.%07i.x" % index, "atom.pos.%07i.y" % index,
"atom.pos.%07i.z" % index]
for index in xrange(num_atoms)
), []))
fields.append(("pos", numpy.float32, (num_atoms,3)))
names.extend(sum((
["atom.vel.%07i.x" % index, "atom.vel.%07i.y" % index,
"atom.vel.%07i.z" % index]
for index in xrange(num_atoms)
), []))
fields.append(("vel", numpy.float32, (num_atoms,3)))
names.extend([
"cell.a.x", "cell.b.x", "cell.c.x",
"cell.a.y", "cell.b.y", "cell.c.y",
"cell.a.z", "cell.b.z", "cell.c.z",
])
fields.append(("cell", numpy.float32, (3,3)))
dtype = numpy.dtype(fields)
filenames = [os.path.join(destination, name) for name in names]
mtw = MultiTracksWriter(filenames, dtype, clear=clear)
for time, pos, vel, cell in gro_reader:
mtw.dump_row((time, pos, vel, cell))
mtw.finish()
def atrj_to_tracks(filename, destination, sub=slice(None), atom_indexes=None, clear=True):
atrj_reader = ATRJReader(filename, sub)
if atom_indexes is None:
atom_indexes = range(atrj_reader.num_atoms)
else:
atom_indexes = list(atom_indexes)
filenames = []
fields = []
for index in atom_indexes:
for cor in ["x", "y", "z"]:
filenames.append(os.path.join(destination, "atom.pos.%07i.%s" % (index, cor)))
fields.append( ("cor", float, (len(atom_indexes),3)) )
filenames.append(os.path.join(destination, "time"))
fields.append( ("time", float, 1) )
filenames.append(os.path.join(destination, "step"))
fields.append( ("step", int, 1) )
filenames.append(os.path.join(destination, "total_energy"))
fields.append( ("tote", float, 1) )
dtype = numpy.dtype(fields)
mtw = MultiTracksWriter(filenames, dtype, clear=clear)
for frame in atrj_reader:
mtw.dump_row((
frame.coordinates[atom_indexes],
frame.time, frame.step, frame.total_energy
))
mtw.finish()
def cpmd_traj_to_tracks(filename, num_atoms, destination, sub=slice(None), atom_indexes=None, clear=True):
"""Convert a cpmd trajectory file into separate tracks.
num_atoms must be the number of atoms in the system.
"""
if atom_indexes is None:
atom_indexes = range(num_atoms)
else:
atom_indexes = list(atom_indexes)
names = []
for index in atom_indexes:
names.append("atom.pos.%07i.x" % index)
names.append("atom.pos.%07i.y" % index)
names.append("atom.pos.%07i.z" % index)
for index in atom_indexes:
names.append("atom.vel.%07i.x" % index)
names.append("atom.vel.%07i.y" % index)
names.append("atom.vel.%07i.z" % index)
filenames = list(os.path.join(destination, name) for name in names)
shape = (len(atom_indexes), 3)
dtype = numpy.dtype([("pos", float, shape), ("vel", float, shape)])
mtw = MultiTracksWriter(filenames, dtype, clear=clear)
ctr = CPMDTrajectoryReader(filename, sub)
for pos, vel in ctr:
mtw.dump_row((pos,vel))
mtw.finish()
def cpmd_ener_to_tracks(filename, destination, sub=slice(None), clear=True):
"""Convert a cp2k energy file into separate tracks."""
names = ["step", "fict_kinectic_energy", "temperature", "potential_energy", "classical_energy", "hamiltonian_energy", "ms_displacement"]
filenames = list(os.path.join(destination, name) for name in names)
dtypes = [int, float, float, float, float, float, float]
dtype = numpy.dtype([ (name, t, 1) for name, t in zip(names, dtypes) ])
mtw = MultiTracksWriter(filenames, dtype, clear=clear)
f = file(filename)
for line in itertools.islice(f, sub.start, sub.stop, sub.step):
row = tuple(float(word) for word in line.split()[:7])
mtw.dump_row(row)
f.close()
mtw.finish()
def cp2k_ener_to_tracks(filename, destination, sub=slice(None), clear=True):
"""Convert a cp2k energy file into separate tracks."""
names = ["step", "time", "kinetic_energy", "temperature", "potential_energy", "conserved_quantity"]
filenames = list(os.path.join(destination, name) for name in names)
dtypes = [int, float, float, float, float, float]
dtype = numpy.dtype([ (name, t, 1) for name, t in zip(names, dtypes) ])
mtw = MultiTracksWriter(filenames, dtype, clear=clear)
f = file(filename)
for line in itertools.islice(iter_real_lines(f), sub.start, sub.stop, sub.step):
row = [float(word) for word in line.split()[:6]]
row[1] = row[1]*femtosecond
mtw.dump_row(tuple(row))
f.close()
mtw.finish()
def cp2k_stress_to_tracks(filename, destination, sub=slice(None), clear=True):
names = ["step", "time", "stress.xx", "stress.xy", "stress.xz", "stress.yx", "stress.yy", "stress.yz", "stress.zx", "stress.zy", "stress.zz", "pressure"]
filenames = list(os.path.join(destination, name) for name in names)
dtype = numpy.dtype([("step", int),("time", float),("stress", float, (3,3)),("pressure", float)])
mtw = MultiTracksWriter(filenames, dtype, clear=clear)
f = file(filename)
for line in itertools.islice(iter_real_lines(f), sub.start, sub.stop, sub.step):
values = [float(word) for word in line.split()[:11]]
row = [int(values[0]),values[1]*femtosecond]
cell = numpy.array(values[2:11]).reshape(3,3).transpose()*bar
row.append(cell)
row.append((cell[0,0]+cell[1,1]+cell[2,2])/3)
mtw.dump_row(tuple(row))
f.close()
mtw.finish()
def xyz_to_tracks(filename, middle_word, destination, sub=slice(None), file_unit=angstrom, atom_indexes=None, clear=True):
"""Convert an xyz file into separate tracks."""
xyz_reader = XYZReader(filename, sub, file_unit=file_unit)
filenames = []
if atom_indexes is None:
atom_indexes = range(len(xyz_reader.numbers))
else:
atom_indexes = list(atom_indexes)
for index in atom_indexes:
for cor in ["x", "y", "z"]:
filenames.append(os.path.join(destination, "atom.%s.%07i.%s" % (middle_word, index, cor)))
shape = (len(atom_indexes),3)
dtype = numpy.dtype([("cor", float, shape)])
mtw = MultiTracksWriter(filenames, dtype, clear=clear)
for title, coordinates in xyz_reader:
mtw.dump_row((coordinates[atom_indexes],))
mtw.finish()
def cp2k_cell_to_tracks(filename, destination, sub=slice(None), clear=True):
names = ["step", "time", "cell.a.x", "cell.a.y", "cell.a.z", "cell.b.x", "cell.b.y", "cell.b.z", "cell.c.x", "cell.c.y", "cell.c.z", "volume", "cell.a", "cell.b", "cell.c", "cell.alpha", "cell.beta", "cell.gamma"]
filenames = list(os.path.join(destination, name) for name in names)
dtype = numpy.dtype([("step", int),("time", float),("cell", float, (3,3)),("volume", float),("norms", float, 3),("angles", float, 3)])
mtw = MultiTracksWriter(filenames, dtype, clear=clear)
f = file(filename)
for line in itertools.islice(iter_real_lines(f), sub.start, sub.stop, sub.step):
values = [float(word) for word in line.split()[:12]]
row = [int(values[0]),values[1]*femtosecond]
cell = numpy.array(values[2:11]).reshape(3,3).transpose()*angstrom
row.append(cell)
row.append(values[11] * angstrom**3)
norms = numpy.sqrt((cell**2).sum(axis=0))
row.append(norms)
alpha = numpy.arccos(numpy.clip(numpy.dot(cell[:,1],cell[:,2])/norms[1]/norms[2], -1,1))
beta = numpy.arccos(numpy.clip(numpy.dot(cell[:,2],cell[:,0])/norms[2]/norms[0], -1,1))
gamma = numpy.arccos(numpy.clip(numpy.dot(cell[:,0],cell[:,1])/norms[0]/norms[1], -1,1))
row.append(numpy.array([alpha,beta,gamma]))
mtw.dump_row(tuple(row))
f.close()
mtw.finish()
def lammps_dump_to_tracks(filename, destination, meta, sub=slice(None), clear=True):
units = []
for unit, name, isvector in meta:
if isvector:
units.extend([unit, unit, unit])
else:
units.append(unit)
dump_reader = LAMMPSDumpReader(filename, units, sub)
num_atoms = dump_reader.num_atoms
filenames = [os.path.join(destination, "step")]
fields = [("step", int)]
for unit, name, isvector in meta:
if isvector:
for i in xrange(num_atoms):
filenames.append(os.path.join(destination, "atom.%s.%07i.x" % (name, i)))
fields.append(("atom.%s.x" % name, float, num_atoms))
for i in xrange(num_atoms):
filenames.append(os.path.join(destination, "atom.%s.%07i.y" % (name, i)))
fields.append(("atom.%s.y" % name, float, num_atoms))
for i in xrange(num_atoms):
filenames.append(os.path.join(destination, "atom.%s.%07i.z" % (name, i)))
fields.append(("atom.%s.z" % name, float, num_atoms))
else:
for i in xrange(num_atoms):
filenames.append(os.path.join(destination, "atom.%s.%07i" % (name, i)))
fields.append(("atom.%s" % name, float, num_atoms))
dtype = numpy.dtype(fields)
mtw = MultiTracksWriter(filenames, dtype, clear=clear)
for frame in dump_reader:
mtw.dump_row(tuple(frame))
mtw.finish()
def dlpoly_output_to_tracks(
filename, destination, sub=slice(None), clear=True, skip_equi_period=True,
pos_unit=angstrom, time_unit=picosecond, angle_unit=deg, e_unit=amu/(angstrom/picosecond)**2
):
output_reader = DLPolyOutputReader(filename, sub, skip_equi_period, pos_unit, time_unit, angle_unit, e_unit)
filenames = [
"step", "conserved_quantity", "temperature", "potential_energy",
"vanderwaals_energy", "coulomb_energy", "bond_energy", "bending_energy",
"torsion_energy", "tethering_energy", "time", "enthalpy",
"rotational_temperature", "virial", "vanderwaals_virial",
"coulomb_virial", "bond_viral", "bending_virial", "constraint_virial",
"tethering_virial", "cputime", "volume", "shell_temperature",
"shell_energy", "shell_virial", "cell.alpha", "cell.beta", "cell.gamma",
"pmf_virial", "pressure",
]
filenames = [os.path.join(destination, filename) for filename in filenames]
fields = [("step", int)] + [("foo%i" % i, float) for i in xrange(29)]
dtype = numpy.dtype(fields)
mtw = MultiTracksWriter(filenames, dtype, clear=clear)
for row in output_reader:
mtw.dump_row(tuple(row))
mtw.finish()
def init_proj(self, output_prefix=None):
"""Setup the projection of the trajectory on the pca eigenmodes.
When output prefix is given, the principal components are written
to tracks with the following filenames: ${output_prefix}.${index}.
After init_proj, call data_proj one or more times with the relevant
data segments from the trajectory. Finally, call finish_proj.
"""
N = len(self.evals)
if output_prefix is not None:
paths_out = [
"%s.pc.%07i" % (output_prefix, index)
for index in xrange(N)
]
dtype = numpy.dtype([("data", float, N)])
self.proj_mtw = MultiTracksWriter(paths_out, dtype)
else:
self.proj_mtw = None
self.sqnorms_data = numpy.zeros(N, float)
self.sqnorms_cos = numpy.zeros(N, float)
self.dot_data_cos = numpy.zeros(N, float)
self.proj_counter = 0
class CovarianceMatrix(object):
"""A container for all information related to a covariance matrix."""
def __init__(self, length, matrix, sum, weights=None, correlation=False, reference=None):
"""Initialize a covariance matrix object
The arguments to initialize a CovarianceMatrix instance are built up
by processing a trajectory. Look at CovarianceBlocks for an example.
They are all stored as attributes. Also some direved properties are
computed during the initialization. In a second stage, one can
reprocess that data with init_proj, data_proj and finish_proj to
compute the principal components and the cosine content.
Arguments:
length -- the length of (a part of) the trajectory used to
construct the matrix
matrix -- the matrix built up by adding
numpy.data(data.transpose(),data) for multiple data
arrays belonging to one block
sum -- the sum of the data over time
Optional arguments:
weights -- When given, the principal components are computed in
weighted coordinates.
correlation -- When True, the analysis is performed on the matrix
with correlation coefficients. This might be usefull
to compare the eigenvalue spectrum with the Wishart
distribution.
reference -- When given, the reference is assumed to be the vector
with the averages of the inputs. Otherwise, the averages
are derived from the input.
Derive attributes:
cov -- The actual covariance/correlation matrix
mean -- The average of the inputs over time
evals -- The eigenvalues of the covariance matrix
evecs -- The corresponding eigenvectors
sigmas -- The square roots of the eigenvalues.
Attributes available after projection:
sqnorms_data -- squared norms of the principal components
sqnorms_cos -- squared norms of the cosines
dot_data_cos -- inner product between principal component and
cosine
ccs -- the cosine contents of each principal component
"""
# the raw data
self.length = length
self.matrix = matrix
self.sum = sum
self.weights = weights
self.correlation = correlation
self.reference = reference
# the derived properties
self.cov = self.matrix / self.length # the actual covariance matrix
if self.reference is None:
self.mean = self.sum / self.length
else:
self.mean = self.reference
self.cov -= numpy.outer(self.mean, self.mean)
if self.correlation:
diag_sqrt = numpy.sqrt(numpy.diag(self.cov))
self.cov /= numpy.outer(diag_sqrt, diag_sqrt)
elif self.weights is not None:
scale = numpy.sqrt(self.weights)
self.cov *= numpy.outer(scale, scale)
# the eigen decomposition
self.evals, self.evecs = numpy.linalg.eigh(self.cov)
# largest eigenvalues first
self.evals = self.evals[::-1]
self.evecs = self.evecs[:,::-1]
self.sigmas = numpy.sqrt(abs(self.evals))
def init_proj(self, output_prefix=None):
"""Setup the projection of the trajectory on the pca eigenmodes.
When output prefix is given, the principal components are written
to tracks with the following filenames: ${output_prefix}.${index}.
After init_proj, call data_proj one or more times with the relevant
data segments from the trajectory. Finally, call finish_proj.
"""
N = len(self.evals)
if output_prefix is not None:
paths_out = [
"%s.pc.%07i" % (output_prefix, index)
for index in xrange(N)
]
dtype = numpy.dtype([("data", float, N)])
self.proj_mtw = MultiTracksWriter(paths_out, dtype)
else:
self.proj_mtw = None
self.sqnorms_data = numpy.zeros(N, float)
self.sqnorms_cos = numpy.zeros(N, float)
self.dot_data_cos = numpy.zeros(N, float)
self.proj_counter = 0
def data_proj(self, data):
"""Process data to compute the principal components and the cosine content
First call init_proj, then call this routine multiple times. Finally
call finish_proj.
"""
data = data - self.mean
if self.correlation:
data /= numpy.sqrt(numpy.diag(self.cov))
elif self.weights is not None:
data *= self.weights
pcs = numpy.dot(data, self.evecs)
if self.proj_mtw is not None:
self.proj_mtw.dump_buffer({"data": pcs})
t = numpy.arange(self.proj_counter, self.proj_counter+len(data))*(numpy.pi/self.length)
for i in xrange(data.shape[1]): # iterate ove the columns
c = numpy.cos((1+i)*t)
self.sqnorms_data[i] += numpy.dot(pcs[:,i], pcs[:,i])
self.sqnorms_cos[i] += numpy.dot(c, c)
self.dot_data_cos[i] += numpy.dot(pcs[:,i], c)
self.proj_counter += len(data)
def finish_proj(self):
"""Compute the actual cosine contents.
Call finish_proj after the last call to data_proj.
"""
self.ccs = self.dot_data_cos**2/(self.sqnorms_data*self.sqnorms_cos+1e-10)
if self.proj_mtw is not None:
self.proj_mtw.finish()
del self.proj_mtw
del self.proj_counter
def dlpoly_history_to_tracks(
filename, destination, sub=slice(None), atom_indexes=None, clear=True,
pos_unit=angstrom, vel_unit=angstrom/picosecond, frc_unit=amu*angstrom/picosecond**2, time_unit=picosecond,
mass_unit=amu
):
hist_reader = DLPolyHistoryReader(filename, sub, pos_unit, vel_unit, frc_unit, time_unit, mass_unit)
if atom_indexes is None:
atom_indexes = range(hist_reader.num_atoms)
else:
atom_indexes = list(atom_indexes)
filenames = []
fields = []
filenames.append(os.path.join(destination, "step"))
fields.append( ("step", int, 1) )
filenames.append(os.path.join(destination, "time"))
fields.append( ("time", float, 1) )
for vec in "abc":
for cor in "xyz":
filenames.append(os.path.join(destination, "cell.%s.%s" % (vec, cor)))
fields.append( ("cell", float, (3,3)) )
for vec in "abc":
filenames.append(os.path.join(destination, "cell.%s" % (vec)))
fields.append( ("norms", float, 3) )
for angle in "alpha", "beta", "gamma":
filenames.append(os.path.join(destination, "cell.%s" % (angle)))
fields.append( ("angles", float, 3) )
for index in atom_indexes:
for cor in "xyz":
filenames.append(os.path.join(destination, "atom.pos.%07i.%s" % (index, cor)))
fields.append( ("pos", float, (len(atom_indexes),3)) )
if hist_reader.keytrj > 0:
for index in atom_indexes:
for cor in "xyz":
filenames.append(os.path.join(destination, "atom.vel.%07i.%s" % (index, cor)))
fields.append( ("vel", float, (len(atom_indexes),3)) )
if hist_reader.keytrj > 1:
for index in atom_indexes:
for cor in "xyz":
filenames.append(os.path.join(destination, "atom.frc.%07i.%s" % (index, cor)))
fields.append( ("frc", float, (len(atom_indexes),3)) )
dtype = numpy.dtype(fields)
mtw = MultiTracksWriter(filenames, dtype, clear=clear)
for frame in hist_reader:
cell = frame["cell"]
norms = numpy.sqrt((cell**2).sum(axis=0))
frame["norms"] = norms
alpha = numpy.arccos(numpy.clip(numpy.dot(cell[:,1],cell[:,2])/norms[1]/norms[2], -1,1))
beta = numpy.arccos(numpy.clip(numpy.dot(cell[:,2],cell[:,0])/norms[2]/norms[0], -1,1))
gamma = numpy.arccos(numpy.clip(numpy.dot(cell[:,0],cell[:,1])/norms[0]/norms[1], -1,1))
frame["angles"] = [alpha, beta, gamma]
frame["pos"] = frame["pos"][atom_indexes]
if hist_reader.keytrj > 0:
frame["vel"] = frame["vel"][atom_indexes]
if hist_reader.keytrj > 0:
frame["frc"] = frame["frc"][atom_indexes]
mtw.dump_row(tuple(frame[name] for name, type, shape in fields))
mtw.finish()
