/usr/share/pyshared/cclib/parser/jaguarparser.py is in python-cclib 1.1-1.
This file is owned by root:root, with mode 0o644.
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# and interpreting the results of computational chemistry packages.
#
# Copyright (C) 2006, the cclib development team
#
# The library is free software, distributed under the terms of
# the GNU Lesser General Public version 2.1 or later. You should have
# received a copy of the license along with cclib. You can also access
# the full license online at http://www.gnu.org/copyleft/lgpl.html.
__revision__ = "$Revision: 1032 $"
import re
import numpy
import logfileparser
import utils
class Jaguar(logfileparser.Logfile):
"""A Jaguar output file"""
def __init__(self, *args, **kwargs):
# Call the __init__ method of the superclass
super(Jaguar, self).__init__(logname="Jaguar", *args, **kwargs)
def __str__(self):
"""Return a string representation of the object."""
return "Jaguar output file %s" % (self.filename)
def __repr__(self):
"""Return a representation of the object."""
return 'Jaguar("%s")' % (self.filename)
def normalisesym(self, label):
"""Normalise the symmetries used by Jaguar.
To normalise, three rules need to be applied:
(1) To handle orbitals of E symmetry, retain everything before the /
(2) Replace two p's by "
(2) Replace any remaining single p's by '
>>> t = Jaguar("dummyfile").normalisesym
>>> labels = ['A', 'A1', 'Ag', 'Ap', 'App', "A1p", "A1pp", "E1pp/Ap"]
>>> answers = map(t, labels)
>>> print answers
['A', 'A1', 'Ag', "A'", 'A"', "A1'", 'A1"', 'E1"']
"""
ans = label.split("/")[0].replace("pp", '"').replace("p", "'")
return ans
def before_parsing(self):
self.geoopt = False # Is this a GeoOpt? Needed for SCF targets/values.
def extract(self, inputfile, line):
"""Extract information from the file object inputfile."""
if line[0:4] == "etot":
# Get SCF convergence information
if not hasattr(self, "scfvalues"):
self.scfvalues = []
self.scftargets = [[5E-5, 5E-6]]
values = []
while line[0:4] == "etot":
# Jaguar 4.2
# etot 1 N N 0 N -382.08751886450 2.3E-03 1.4E-01
# etot 2 Y Y 0 N -382.27486023153 1.9E-01 1.4E-03 5.7E-02
# Jaguar 6.5
# etot 1 N N 0 N -382.08751881733 2.3E-03 1.4E-01
# etot 2 Y Y 0 N -382.27486018708 1.9E-01 1.4E-03 5.7E-02
temp = line.split()[7:]
if len(temp)==3:
denergy = float(temp[0])
else:
denergy = 0 # Should really be greater than target value
# or should we just ignore the values in this line
ddensity = float(temp[-2])
maxdiiserr = float(temp[-1])
if not self.geoopt:
values.append([denergy, ddensity])
else:
values.append([ddensity])
line = inputfile.next()
self.scfvalues.append(values)
# Hartree-Fock energy after SCF
if line[1:18] == "SCFE: SCF energy:":
if not hasattr(self, "scfenergies"):
self.scfenergies = []
temp = line.strip().split()
scfenergy = float(temp[temp.index("hartrees") - 1])
scfenergy = utils.convertor(scfenergy, "hartree", "eV")
self.scfenergies.append(scfenergy)
# Energy after LMP2 correction
if line[1:18] == "Total LMP2 Energy":
if not hasattr(self, "mpenergies"):
self.mpenergies = [[]]
lmp2energy = float(line.split()[-1])
lmp2energy = utils.convertor(lmp2energy, "hartree", "eV")
self.mpenergies[-1].append(lmp2energy)
if line[2:14] == "new geometry" or line[1:21] == "Symmetrized geometry" or line.find("Input geometry") > 0:
# Get the atom coordinates
if not hasattr(self, "atomcoords") or line[1:21] == "Symmetrized geometry":
# Wipe the "Input geometry" if "Symmetrized geometry" present
self.atomcoords = []
p = re.compile("(\D+)\d+") # One/more letters followed by a number
atomcoords = []
atomnos = []
angstrom = inputfile.next()
title = inputfile.next()
line = inputfile.next()
while line.strip():
temp = line.split()
element = p.findall(temp[0])[0]
atomnos.append(self.table.number[element])
atomcoords.append(map(float, temp[1:]))
line = inputfile.next()
self.atomcoords.append(atomcoords)
self.atomnos = numpy.array(atomnos, "i")
self.natom = len(atomcoords)
# Extract charge and multiplicity
if line[2:22] == "net molecular charge":
self.charge = int(line.split()[-1])
self.mult = int(inputfile.next().split()[-1])
if line[2:24] == "start of program geopt":
if not self.geoopt:
# Need to keep only the RMS density change info
# if this is a geoopt
self.scftargets = [[self.scftargets[0][0]]]
if hasattr(self, "scfvalues"):
self.scfvalues[0] = [[x[0]] for x in self.scfvalues[0]]
self.geoopt = True
else:
self.scftargets.append([5E-5])
if line[2:28] == "geometry optimization step":
# Get Geometry Opt convergence information
if not hasattr(self, "geovalues"):
self.geovalues = []
self.geotargets = numpy.zeros(5, "d")
gopt_step = int(line.split()[-1])
energy = inputfile.next()
# quick hack for messages of the sort:
# ** restarting optimization from step 2 **
# as found in regression file ptnh3_2_H2O_2_2plus.out
if inputfile.next().strip():
blank = inputfile.next()
line = inputfile.next()
values = []
target_index = 0
if gopt_step == 1:
# The first optimization step does not produce an energy change
values.append(0.0)
target_index = 1
while line.strip():
if len(line) > 40 and line[41] == "(":
# A new geo convergence value
values.append(float(line[26:37]))
self.geotargets[target_index] = float(line[43:54])
target_index += 1
line = inputfile.next()
self.geovalues.append(values)
if line.find("number of occupied orbitals") > 0:
# Get number of MOs
occs = int(line.split()[-1])
line = inputfile.next()
virts = int(line.split()[-1])
self.nmo = occs + virts
self.homos = numpy.array([occs-1], "i")
self.unrestrictedflag = False
if line.find("number of alpha occupied orb") > 0:
# Get number of MOs for an unrestricted calc
aoccs = int(line.split()[-1])
line = inputfile.next()
avirts = int(line.split()[-1])
line = inputfile.next()
boccs = int(line.split()[-1])
line = inputfile.next()
bvirt = int(line.split()[-1])
self.nmo = aoccs + avirts
self.homos = numpy.array([aoccs-1, boccs-1], "i")
self.unrestrictedflag = True
# MO energies and symmetries.
# Jaguar 7.0: provides energies and symmetries for both
# restricted and unrestricted calculations, like this:
# Alpha Orbital energies/symmetry label:
# -10.25358 Bu -10.25353 Ag -10.21931 Bu -10.21927 Ag
# -10.21792 Bu -10.21782 Ag -10.21773 Bu -10.21772 Ag
# ...
# Jaguar 6.5: prints both only for restricted calculations,
# so for unrestricted calculations the output it looks like this:
# Alpha Orbital energies:
# -10.25358 -10.25353 -10.21931 -10.21927 -10.21792 -10.21782
# -10.21773 -10.21772 -10.21537 -10.21537 -1.02078 -0.96193
# ...
# Presence of 'Orbital energies' is enough to catch all versions.
if "Orbital energies" in line:
# Parsing results is identical for restricted/unrestricted
# calculations, just assert later that alpha/beta order is OK.
spin = int(line[2:6] == "Beta")
# Check if symmetries are printed also.
issyms = "symmetry label" in line
if not hasattr(self, "moenergies"):
self.moenergies = []
if issyms and not hasattr(self, "mosyms"):
self.mosyms = []
# Grow moeneriges/mosyms and make sure they are empty when
# parsed multiple times - currently cclib returns only
# the final output (ex. in a geomtry optimization).
if len(self.moenergies) < spin+1:
self.moenergies.append([])
self.moenergies[spin] = []
if issyms:
if len(self.mosyms) < spin+1:
self.mosyms.append([])
self.mosyms[spin] = []
line = inputfile.next().split()
while len(line) > 0:
if issyms:
energies = [float(line[2*i]) for i in range(len(line)/2)]
syms = [line[2*i+1] for i in range(len(line)/2)]
else:
energies = [float(e) for e in line]
energies = [utils.convertor(e, "hartree", "eV") for e in energies]
self.moenergies[spin].extend(energies)
if issyms:
syms = [self.normalisesym(s) for s in syms]
self.mosyms[spin].extend(syms)
line = inputfile.next().split()
# There should always be an extra blank line after all this.
line = inputfile.next()
if line.find("Occupied + virtual Orbitals- final wvfn") > 0:
blank = inputfile.next()
stars = inputfile.next()
blank = inputfile.next()
blank = inputfile.next()
if not hasattr(self,"mocoeffs"):
if self.unrestrictedflag:
spin = 2
else:
spin = 1
self.mocoeffs = []
aonames = []
lastatom = "X"
readatombasis = False
if not hasattr(self, "atombasis"):
self.atombasis = []
for i in range(self.natom):
self.atombasis.append([])
readatombasis = True
offset = 0
for s in range(spin):
mocoeffs = numpy.zeros((len(self.moenergies[s]), self.nbasis), "d")
if s == 1: #beta case
stars = inputfile.next()
blank = inputfile.next()
title = inputfile.next()
blank = inputfile.next()
stars = inputfile.next()
blank = inputfile.next()
blank = inputfile.next()
for k in range(0, len(self.moenergies[s]), 5):
if self.progress:
self.updateprogress(inputfile, "Coefficients")
numbers = inputfile.next()
eigens = inputfile.next()
line = inputfile.next()
for i in range(self.nbasis):
info = line.split()
# Fill atombasis only first time around.
if readatombasis and k == 0:
orbno = int(info[0])
atom = info[1]
if atom[1].isalpha():
atomno = int(atom[2:])
else:
atomno = int(atom[1:])
self.atombasis[atomno-1].append(orbno-1)
if not hasattr(self,"aonames"):
if lastatom != info[1]:
scount = 1
pcount = 3
dcount = 6 #six d orbitals in Jaguar
if info[2] == 'S':
aonames.append("%s_%i%s"%(info[1], scount, info[2]))
scount += 1
if info[2] == 'X' or info[2] == 'Y' or info[2] == 'Z':
aonames.append("%s_%iP%s"%(info[1], pcount / 3, info[2]))
pcount += 1
if info[2] == 'XX' or info[2] == 'YY' or info[2] == 'ZZ' or \
info[2] == 'XY' or info[2] == 'XZ' or info[2] == 'YZ':
aonames.append("%s_%iD%s"%(info[1], dcount / 6, info[2]))
dcount += 1
lastatom = info[1]
for j in range(len(info[3:])):
mocoeffs[j+k, i] = float(info[3+j])
line = inputfile.next()
if not hasattr(self,"aonames"):
self.aonames = aonames
offset += 5
self.mocoeffs.append(mocoeffs)
if line[2:6] == "olap":
if line[6] == "-":
return
# This was continue (in loop) before parser refactoring.
# continue # avoid "olap-dev"
self.aooverlaps = numpy.zeros((self.nbasis, self.nbasis), "d")
for i in range(0, self.nbasis, 5):
if self.progress:
self.updateprogress(inputfile, "Overlap")
blank = inputfile.next()
header = inputfile.next()
for j in range(i, self.nbasis):
temp = map(float, inputfile.next().split()[1:])
self.aooverlaps[j, i:(i+len(temp))] = temp
self.aooverlaps[i:(i+len(temp)), j] = temp
if line[1:28] == "number of occupied orbitals":
self.homos = numpy.array([float(line.strip().split()[-1])-1], "i")
if line[2:27] == "number of basis functions":
self.nbasis = int(line.strip().split()[-1])
# IR output looks like this:
# frequencies 72.45 113.25 176.88 183.76 267.60 312.06
# symmetries Au Bg Au Bu Ag Bg
# intensities 0.07 0.00 0.28 0.52 0.00 0.00
# reduc. mass 1.90 0.74 1.06 1.42 1.19 0.85
# force const 0.01 0.01 0.02 0.03 0.05 0.05
# C1 X 0.00000 0.00000 0.00000 -0.05707 -0.06716 0.00000
# C1 Y 0.00000 0.00000 0.00000 0.00909 -0.02529 0.00000
# C1 Z 0.04792 -0.06032 -0.01192 0.00000 0.00000 0.11613
# C2 X 0.00000 0.00000 0.00000 -0.06094 -0.04635 0.00000
# ... etc. ...
# This is a complete ouput, some files will not have intensities,
# and older Jaguar versions sometimes skip the symmetries.
if line[2:23] == "start of program freq":
self.vibfreqs = []
self.vibdisps = []
forceconstants = False
intensities = False
blank = inputfile.next()
line = inputfile.next()
while line.strip():
if "force const" in line:
forceconstants = True
if "intensities" in line:
intensities = True
line = inputfile.next()
freqs = inputfile.next()
# The last block has an extra blank line after it - catch it.
while freqs.strip():
# Number of modes (columns printed in this block).
nmodes = len(freqs.split())-1
# Append the frequencies.
self.vibfreqs.extend(map(float, freqs.split()[1:]))
line = inputfile.next().split()
# May skip symmetries (older Jaguar versions).
if line[0] == "symmetries":
if not hasattr(self, "vibsyms"):
self.vibsyms = []
self.vibsyms.extend(map(self.normalisesym, line[1:]))
line = inputfile.next().split()
if intensities:
if not hasattr(self, "vibirs"):
self.vibirs = []
self.vibirs.extend(map(float, line[1:]))
line = inputfile.next().split()
if forceconstants:
line = inputfile.next()
# Start parsing the displacements.
# Variable 'q' holds up to 7 lists of triplets.
q = [ [] for i in range(7) ]
for n in range(self.natom):
# Variable 'p' holds up to 7 triplets.
p = [ [] for i in range(7) ]
for i in range(3):
line = inputfile.next()
disps = [float(disp) for disp in line.split()[2:]]
for j in range(nmodes):
p[j].append(disps[j])
for i in range(nmodes):
q[i].append(p[i])
self.vibdisps.extend(q[:nmodes])
blank = inputfile.next()
freqs = inputfile.next()
# Convert new data to arrays.
self.vibfreqs = numpy.array(self.vibfreqs, "d")
self.vibdisps = numpy.array(self.vibdisps, "d")
if hasattr(self, "vibirs"):
self.vibirs = numpy.array(self.vibirs, "d")
# Parse excited state output (for CIS calculations).
# Jaguar calculates only singlet states.
if line[2:15] == "Excited State":
if not hasattr(self, "etenergies"):
self.etenergies = []
if not hasattr(self, "etoscs"):
self.etoscs = []
if not hasattr(self, "etsecs"):
self.etsecs = []
self.etsyms = []
etenergy = float(line.split()[3])
etenergy = utils.convertor(etenergy, "eV", "cm-1")
self.etenergies.append(etenergy)
# Skip 4 lines
for i in range(5):
line = inputfile.next()
self.etsecs.append([])
# Jaguar calculates only singlet states.
self.etsyms.append('Singlet-A')
while line.strip() != "":
fromMO = int(line.split()[0])-1
toMO = int(line.split()[2])-1
coeff = float(line.split()[-1])
self.etsecs[-1].append([(fromMO, 0), (toMO, 0), coeff])
line = inputfile.next()
# Skip 3 lines
for i in range(4):
line = inputfile.next()
strength = float(line.split()[-1])
self.etoscs.append(strength)
if __name__ == "__main__":
import doctest, jaguarparser
doctest.testmod(jaguarparser, verbose=False)
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