def before_parsing(self):
self.geoopt = False # Is this a GeoOpt? Needed for SCF targets/values.
self.periodic_table = utils.PeriodicTable()
def symbol2int(symbol):
t = utils.PeriodicTable()
return t.number[symbol]
def __init__(self, source, loglevel=logging.INFO, logname="Log",
logstream=sys.stdout, datatype=ccData_optdone_bool, **kwds):
"""Initialise the Logfile object.
This should be called by a subclass in its own __init__ method.
Inputs:
source - a logfile, list of logfiles, or stream with at least a read method
loglevel - integer corresponding to a log level from the logging module
logname - name of the source logfile passed to this constructor
logstream - where to output the logging information
datatype - class to use for gathering data attributes
"""
# Set the filename to source if it is a string or a list of strings, which are
# assumed to be filenames. Otherwise, assume the source is a file-like object
# if it has a read method, and we will try to use it like a stream.
if isinstance(source, str):
self.filename = source
self.isstream = False
elif isinstance(source, list) and all([isinstance(s, str) for s in source]):
self.filename = source
self.isstream = False
elif hasattr(source, "read"):
self.filename = "stream %s" % str(type(source))
self.isstream = True
self.stream = source
else:
raise ValueError
# Set up the logger.
# Note that calling logging.getLogger() with one name always returns the same instance.
# Presently in cclib, all parser instances of the same class use the same logger,
# which means that care needs to be taken not to duplicate handlers.
self.loglevel = loglevel
self.logname = logname
self.logger = logging.getLogger('%s %s' % (self.logname, self.filename))
self.logger.setLevel(self.loglevel)
if len(self.logger.handlers) == 0:
handler = logging.StreamHandler(logstream)
handler.setFormatter(logging.Formatter("[%(name)s %(levelname)s] %(message)s"))
self.logger.addHandler(handler)
# Set up the metadata.
if not hasattr(self, "metadata"):
self.metadata = {}
self.metadata["package"] = self.logname
self.metadata["methods"] = []
# Periodic table of elements.
self.table = utils.PeriodicTable()
# This is the class that will be used in the data object returned by parse(), and should
# normally be ccData or a subclass of it.
self.datatype = datatype
# Change the class used if we want optdone to be a list or if the 'future' option
# is used, which might have more consequences in the future.
optdone_as_list = kwds.get("optdone_as_list", False) or kwds.get("future", False)
optdone_as_list = optdone_as_list if isinstance(optdone_as_list, bool) else False
if optdone_as_list:
self.datatype = ccData
def extract(self, inputfile, line):
"""Extract information from the file object inputfile."""
# Extract the version number and optionally the Git tag and hash.
if "version" in line:
match = re.search(r"\s{2,}version\s(\d*\.\d*)", line)
if match:
package_version = match.groups()[0]
self.metadata["package_version"] = package_version
# Don't add revision information to the main package version for now.
if "tag" in line:
tag = line.split()[-1]
if "build" in line:
match = re.search(r"\*\s*build\s(\S*)\s*\*", line)
if match:
revision = match.groups()[0]
## This section is present when executing &GATEWAY.
# ++ Molecular structure info:
# -------------------------
# ************************************************
# **** Cartesian Coordinates / Bohr, Angstrom ****
# ************************************************
# Center Label x y z x y z
# 1 C1 0.526628 -2.582937 0.000000 0.278679 -1.366832 0.000000
# 2 C2 2.500165 -0.834760 0.000000 1.323030 -0.441736 0.000000
if line[25:63] == 'Cartesian Coordinates / Bohr, Angstrom':
if not hasattr(self, 'atomnos'):
self.atomnos = []
if not hasattr(self, 'atomcoords'):
self.atomcoords = []
self.skip_lines(inputfile, ['stars', 'blank', 'header'])
line = next(inputfile)
atomelements = []
atomcoords = []
while not self.re_dashes_and_spaces.search(line):
sline = line.split()
atomelements.append(
self.re_atomelement.search(sline[1]).groups()[0])
atomcoords.append(list(map(float, sline[5:])))
line = next(inputfile)
self.atomcoords.append(atomcoords)
if self.atomnos == []:
self.atomnos = [
utils.PeriodicTable().number[atomelement]
for atomelement in atomelements
]
if not hasattr(self, 'natom'):
self.set_attribute('natom', len(self.atomnos))
## This section is present when executing &SCF.
# ++ Orbital specifications:
# -----------------------
# Symmetry species 1
# Frozen orbitals 0
# Occupied orbitals 3
# Secondary orbitals 77
# Deleted orbitals 0
# Total number of orbitals 80
# Number of basis functions 80
# --
if line[:29] == '++ Orbital specifications:':
self.skip_lines(inputfile, ['dashes', 'blank'])
line = next(inputfile)
while line[:2] != '--':
if line[6:30] == 'Total number of orbitals':
self.set_attribute('nmo', int(line.split()[-1]))
if line[6:31] == 'Number of basis functions':
self.set_attribute('nbasis', int(line.split()[-1]))
line = next(inputfile)
#Parsing the molecular charge
if line[6:23] == 'Molecular charge ':
self.set_attribute('charge', int(float(line.split()[-1])))
# ++ Molecular charges:
# ------------------
# Mulliken charges per centre and basis function type
# ---------------------------------------------------
# C1
# 1s 2.0005
# 2s 2.0207
# 2px 0.0253
# 2pz 0.1147
# 2py 1.8198
# *s -0.0215
# *px 0.0005
# *pz 0.0023
# *py 0.0368
# *d2+ 0.0002
# *d1+ 0.0000
# *d0 0.0000
# *d1- 0.0000
# *d2- 0.0000
# *f3+ 0.0000
# *f2+ 0.0001
# *f1+ 0.0000
# *f0 0.0001
# *f1- 0.0001
# *f2- 0.0000
# *f3- 0.0003
# *g4+ 0.0000
# *g3+ 0.0000
# *g2+ 0.0000
# *g1+ 0.0000
# *g0 0.0000
# *g1- 0.0000
# *g2- 0.0000
# *g3- 0.0000
# *g4- 0.0000
# Total 6.0000
# N-E 0.0000
# Total electronic charge= 6.000000
# Total charge= 0.000000
#--
if line[:24] == '++ Molecular charges:':
atomcharges = []
while line[6:29] != 'Total electronic charge':
line = next(inputfile)
if line[6:9] == 'N-E':
atomcharges.extend(map(float, line.split()[1:]))
# Molcas only performs Mulliken population analysis.
self.set_attribute('atomcharges', {'mulliken': atomcharges})
# Ensure the charge printed here is identical to the
# charge printed before entering the SCF.
self.skip_line(inputfile, 'blank')
line = next(inputfile)
assert line[6:30] == 'Total charge='
if hasattr(self, 'charge'):
assert int(float(line.split()[2])) == self.charge
# This section is present when executing &SCF
# This section parses the total SCF Energy.
# *****************************************************************************************************************************
# * *
# * SCF/KS-DFT Program, Final results *
# * *
# * *
# * *
# * Final Results *
# * *
# *****************************************************************************************************************************
# :: Total SCF energy -37.6045426484
if line[:
22] == ':: Total SCF energy' or line[:
25] == ':: Total KS-DFT energy':
if not hasattr(self, 'scfenergies'):
self.scfenergies = []
scfenergy = float(line.split()[-1])
self.scfenergies.append(utils.convertor(scfenergy, 'hartree',
'eV'))
## Parsing the scftargets in this section
# ++ Optimization specifications:
# ----------------------------
# SCF Algorithm: Conventional
# Minimized density differences are used
# Number of density matrices in core 9
# Maximum number of NDDO SCF iterations 400
# Maximum number of HF SCF iterations 400
# Threshold for SCF energy change 0.10E-08
# Threshold for density matrix 0.10E-03
# Threshold for Fock matrix 0.15E-03
# Threshold for linear dependence 0.10E-08
# Threshold at which DIIS is turned on 0.15E+00
# Threshold at which QNR/C2DIIS is turned on 0.75E-01
# Threshold for Norm(delta) (QNR/C2DIIS) 0.20E-04
if line[:34] == '++ Optimization specifications:':
self.skip_lines(inputfile, ['d', 'b'])
line = next(inputfile)
if line.strip().startswith('SCF'):
scftargets = []
self.skip_lines(inputfile,
['Minimized', 'Number', 'Maximum', 'Maximum'])
lines = [next(inputfile) for i in range(7)]
targets = [
'Threshold for SCF energy change',
'Threshold for density matrix',
'Threshold for Fock matrix',
'Threshold for Norm(delta)',
]
for y in targets:
scftargets.extend(
[float(x.split()[-1]) for x in lines if y in x])
self.append_attribute('scftargets', scftargets)
# ++ Convergence information
# SCF iterations: Energy and convergence statistics
#
# Iter Tot. SCF One-electron Two-electron Energy Max Dij or Max Fij DNorm TNorm AccCon Time
# Energy Energy Energy Change Delta Norm in Sec.
# 1 -36.83817703 -50.43096166 13.59278464 0.00E+00 0.16E+00* 0.27E+01* 0.30E+01 0.33E+02 NoneDa 0.
# 2 -36.03405202 -45.74525152 9.71119950 0.80E+00* 0.14E+00* 0.93E-02* 0.26E+01 0.43E+01 Damp 0.
# 3 -37.08936118 -48.41536598 11.32600480 -0.11E+01* 0.12E+00* 0.91E-01* 0.97E+00 0.16E+01 Damp 0.
# 4 -37.31610460 -50.54103969 13.22493509 -0.23E+00* 0.11E+00* 0.96E-01* 0.72E+00 0.27E+01 Damp 0.
# 5 -37.33596239 -49.47021484 12.13425245 -0.20E-01* 0.59E-01* 0.59E-01* 0.37E+00 0.16E+01 Damp 0.
if line[46:91] == 'iterations: Energy and convergence statistics':
self.skip_line(inputfile, 'blank')
while line.split() != [
'Energy', 'Energy', 'Energy', 'Change', 'Delta', 'Norm',
'in', 'Sec.'
]:
line = next(inputfile)
scfvalues = []
line = next(inputfile)
while line.split()[0] != 'Convergence':
if line.split()[0].isdigit():
info = line.split()
energy = float(info[4].replace('*', ''))
density = float(info[5].replace('*', ''))
fock = float(info[6].replace('*', ''))
dnorm = float(info[7].replace('*', ''))
scfvalues.append([energy, density, fock, dnorm])
try:
line = next(inputfile)
if line.split() == []:
line = next(inputfile)
except StopIteration:
self.logger.warning(
'File terminated before end of last SCF!')
break
self.append_attribute('scfvalues', scfvalues)
# Harmonic frequencies in cm-1
#
# IR Intensities in km/mol
#
# 1 2 3 4 5 6
#
# Frequency: i60.14 i57.39 128.18 210.06 298.24 309.65
#
# Intensity: 3.177E-03 2.129E-06 4.767E-01 2.056E-01 6.983E-07 1.753E-07
# Red. mass: 2.42030 2.34024 2.68044 3.66414 2.61721 3.34904
#
# C1 x -0.00000 0.00000 0.00000 -0.05921 0.00000 -0.06807
# C1 y 0.00001 -0.00001 -0.00001 0.00889 0.00001 -0.02479
# C1 z -0.03190 0.04096 -0.03872 0.00001 -0.12398 -0.00002
# C2 x -0.00000 0.00001 0.00000 -0.06504 0.00000 -0.03487
# C2 y 0.00000 -0.00000 -0.00000 0.01045 0.00001 -0.05659
# C2 z -0.03703 -0.03449 -0.07269 0.00000 -0.07416 -0.00001
# C3 x -0.00000 0.00001 0.00000 -0.06409 -0.00001 0.05110
# C3 y -0.00000 0.00001 0.00000 0.00152 0.00000 -0.03263
# C3 z -0.03808 -0.08037 -0.07267 -0.00001 0.07305 0.00000
# ...
# H20 y 0.00245 -0.00394 0.03215 0.03444 -0.10424 -0.10517
# H20 z 0.00002 -0.00001 0.00000 -0.00000 -0.00000 0.00000
#
#
#
# ++ Thermochemistry
if line[1:29] == 'Harmonic frequencies in cm-1':
self.skip_line(inputfile, 'blank')
line = next(inputfile)
while 'Thermochemistry' not in line:
if 'Frequency:' in line:
if not hasattr(self, 'vibfreqs'):
self.vibfreqs = []
vibfreqs = [
float(i.replace('i', '-')) for i in line.split()[1:]
]
self.vibfreqs.extend(vibfreqs)
if 'Intensity:' in line:
if not hasattr(self, 'vibirs'):
self.vibirs = []
vibirs = map(float, line.split()[1:])
self.vibirs.extend(vibirs)
if 'Red.' in line:
self.skip_line(inputfile, 'blank')
line = next(inputfile)
if not hasattr(self, 'vibdisps'):
self.vibdisps = []
disps = []
for n in range(3 * self.natom):
numbers = [float(s) for s in line[17:].split()]
# The atomindex should start at 0 instead of 1.
atomindex = int(
re.search(r'\d+$',
line.split()[0]).group()) - 1
numbermodes = len(numbers)
if len(disps) == 0:
# Appends empty array of the following
# dimensions (numbermodes, natom, 0) to disps.
for mode in range(numbermodes):
disps.append([[]
for x in range(0, self.natom)])
for mode in range(numbermodes):
disps[mode][atomindex].append(numbers[mode])
line = next(inputfile)
self.vibdisps.extend(disps)
line = next(inputfile)
## Parsing thermochemistry attributes here
# ++ Thermochemistry
#
# *********************
# * *
# * THERMOCHEMISTRY *
# * *
# *********************
#
# Mass-centered Coordinates (Angstrom):
# ***********************************************************
# ...
# *****************************************************
# Temperature = 0.00 Kelvin, Pressure = 1.00 atm
# -----------------------------------------------------
# Molecular Partition Function and Molar Entropy:
# q/V (M**-3) S(kcal/mol*K)
# Electronic 0.100000D+01 0.000
# Translational 0.100000D+01 0.000
# Rotational 0.100000D+01 2.981
# Vibrational 0.100000D+01 0.000
# TOTAL 0.100000D+01 2.981
#
# Thermal contributions to INTERNAL ENERGY:
# Electronic 0.000 kcal/mol 0.000000 au.
# Translational 0.000 kcal/mol 0.000000 au.
# Rotational 0.000 kcal/mol 0.000000 au.
# Vibrational 111.885 kcal/mol 0.178300 au.
# TOTAL 111.885 kcal/mol 0.178300 au.
#
# Thermal contributions to
# ENTHALPY 111.885 kcal/mol 0.178300 au.
# GIBBS FREE ENERGY 111.885 kcal/mol 0.178300 au.
#
# Sum of energy and thermal contributions
# INTERNAL ENERGY -382.121931 au.
# ENTHALPY -382.121931 au.
# GIBBS FREE ENERGY -382.121931 au.
# -----------------------------------------------------
# ...
# ENTHALPY -382.102619 au.
# GIBBS FREE ENERGY -382.179819 au.
# -----------------------------------------------------
# --
#
# ++ Isotopic shifts:
if line[4:19] == 'THERMOCHEMISTRY':
temperature_values = []
pressure_values = []
entropy_values = []
internal_energy_values = []
enthalpy_values = []
free_energy_values = []
while 'Isotopic' not in line:
if line[1:12] == 'Temperature':
temperature_values.append(float(line.split()[2]))
pressure_values.append(float(line.split()[6]))
if line[1:
48] == 'Molecular Partition Function and Molar Entropy:':
while 'TOTAL' not in line:
line = next(inputfile)
entropy_values.append(
utils.convertor(float(line.split()[2]), 'kcal',
'hartree'))
if line[1:40] == 'Sum of energy and thermal contributions':
internal_energy_values.append(
float(next(inputfile).split()[2]))
enthalpy_values.append(float(next(inputfile).split()[1]))
free_energy_values.append(float(
next(inputfile).split()[3]))
line = next(inputfile)
# When calculations for more than one temperature value are
# performed, the values corresponding to room temperature (298.15 K)
# are returned and if no calculations are performed for 298.15 K, then
# the values corresponding last temperature value are returned.
index = -1
if 298.15 in temperature_values:
index = temperature_values.index(298.15)
self.set_attribute('temperature', temperature_values[index])
if len(temperature_values) > 1:
self.logger.warning('More than 1 values of temperature found')
self.set_attribute('pressure', pressure_values[index])
if len(pressure_values) > 1:
self.logger.warning('More than 1 values of pressure found')
self.set_attribute('entropy', entropy_values[index])
if len(entropy_values) > 1:
self.logger.warning('More than 1 values of entropy found')
self.set_attribute('enthalpy', enthalpy_values[index])
if len(enthalpy_values) > 1:
self.logger.warning('More than 1 values of enthalpy found')
self.set_attribute('freeenergy', free_energy_values[index])
if len(free_energy_values) > 1:
self.logger.warning('More than 1 values of freeenergy found')
## Parsing Geometrical Optimization attributes in this section.
# ++ Slapaf input parameters:
# ------------------------
#
# Max iterations: 2000
# Convergence test a la Schlegel.
# Convergence criterion on gradient/para.<=: 0.3E-03
# Convergence criterion on step/parameter<=: 0.3E-03
# Convergence criterion on energy change <=: 0.0E+00
# Max change of an internal coordinate: 0.30E+00
# ...
# ...
# **********************************************************************************************************************
# * Energy Statistics for Geometry Optimization *
# **********************************************************************************************************************
# Energy Grad Grad Step Estimated Geom Hessian
# Iter Energy Change Norm Max Element Max Element Final Energy Update Update Index
# 1 -382.30023222 0.00000000 0.107221 0.039531 nrc047 0.085726 nrc047 -382.30533799 RS-RFO None 0
# 2 -382.30702964 -0.00679742 0.043573 0.014908 nrc001 0.068195 nrc001 -382.30871333 RS-RFO BFGS 0
# 3 -382.30805348 -0.00102384 0.014883 0.005458 nrc010 -0.020973 nrc001 -382.30822089 RS-RFO BFGS 0
# ...
# ...
# 18 -382.30823419 -0.00000136 0.001032 0.000100 nrc053 0.012319 nrc053 -382.30823452 RS-RFO BFGS 0
# 19 -382.30823198 0.00000221 0.001051 -0.000092 nrc054 0.066565 nrc053 -382.30823822 RS-RFO BFGS 0
# 20 -382.30820252 0.00002946 0.001132 -0.000167 nrc021 -0.064003 nrc053 -382.30823244 RS-RFO BFGS 0
#
# +----------------------------------+----------------------------------+
# + Cartesian Displacements + Gradient in internals +
# + Value Threshold Converged? + Value Threshold Converged? +
# +-----+----------------------------------+----------------------------------+
# + RMS + 5.7330E-02 1.2000E-03 No + 1.6508E-04 3.0000E-04 Yes +
# +-----+----------------------------------+----------------------------------+
# + Max + 1.2039E-01 1.8000E-03 No + 1.6711E-04 4.5000E-04 Yes +
# +-----+----------------------------------+----------------------------------+
if 'Convergence criterion on energy change' in line:
self.energy_threshold = float(line.split()[6])
# If energy change threshold equals zero,
# then energy change is not a criteria for convergence.
if self.energy_threshold == 0:
self.energy_threshold = numpy.inf
if 'Energy Statistics for Geometry Optimization' in line:
if not hasattr(self, 'geovalues'):
self.geovalues = []
self.skip_lines(inputfile, ['stars', 'header'])
line = next(inputfile)
assert 'Iter Energy Change Norm' in line
# A variable keeping track of ongoing iteration.
iter_number = len(self.geovalues) + 1
# Iterate till blank line.
while line.split() != []:
for i in range(iter_number):
line = next(inputfile)
self.geovalues.append([float(line.split()[2])])
line = next(inputfile)
# Along with energy change, RMS and Max values of change in
# Cartesian Diaplacement and Gradients are used as optimization
# criteria.
self.skip_lines(inputfile,
['border', 'header', 'header', 'border'])
line = next(inputfile)
assert '+ RMS +' in line
line_rms = line.split()
line = next(inputfile)
line_max = next(inputfile).split()
if not hasattr(self, 'geotargets'):
# The attribute geotargets is an array consisting of the following
# values: [Energy threshold, Max Gradient threshold, RMS Gradient threshold, \
# Max Displacements threshold, RMS Displacements threshold].
max_gradient_threshold = float(line_max[8])
rms_gradient_threshold = float(line_rms[8])
max_displacement_threshold = float(line_max[4])
rms_displacement_threshold = float(line_rms[4])
self.geotargets = [
self.energy_threshold, max_gradient_threshold,
rms_gradient_threshold, max_displacement_threshold,
rms_displacement_threshold
]
max_gradient_change = float(line_max[7])
rms_gradient_change = float(line_rms[7])
max_displacement_change = float(line_max[3])
rms_displacement_change = float(line_rms[3])
self.geovalues[iter_number - 1].extend([
max_gradient_change, rms_gradient_change,
max_displacement_change, rms_displacement_change
])
# *********************************************************
# * Nuclear coordinates for the next iteration / Angstrom *
# *********************************************************
# ATOM X Y Z
# C1 0.235560 -1.415847 0.012012
# C2 1.313797 -0.488199 0.015149
# C3 1.087050 0.895510 0.014200
# ...
# ...
# H19 -0.021327 -4.934915 -0.029355
# H20 -1.432030 -3.721047 -0.039835
#
# --
if 'Nuclear coordinates for the next iteration / Angstrom' in line:
self.skip_lines(inputfile, ['s', 'header'])
line = next(inputfile)
atomcoords = []
while line.split() != []:
atomcoords.append([float(c) for c in line.split()[1:]])
line = next(inputfile)
self.atomcoords.append(atomcoords)
# **********************************************************************************************************************
# * Energy Statistics for Geometry Optimization *
# **********************************************************************************************************************
# Energy Grad Grad Step Estimated Geom Hessian
# Iter Energy Change Norm Max Element Max Element Final Energy Update Update Index
# 1 -382.30023222 0.00000000 0.107221 0.039531 nrc047 0.085726 nrc047 -382.30533799 RS-RFO None 0
# ...
# ...
# 23 -382.30823115 -0.00000089 0.001030 0.000088 nrc053 0.000955 nrc053 -382.30823118 RS-RFO BFGS 0
#
# +----------------------------------+----------------------------------+
# + Cartesian Displacements + Gradient in internals +
# + Value Threshold Converged? + Value Threshold Converged? +
# +-----+----------------------------------+----------------------------------+
# + RMS + 7.2395E-04 1.2000E-03 Yes + 2.7516E-04 3.0000E-04 Yes +
# +-----+----------------------------------+----------------------------------+
# + Max + 1.6918E-03 1.8000E-03 Yes + 8.7768E-05 4.5000E-04 Yes +
# +-----+----------------------------------+----------------------------------+
#
# Geometry is converged in 23 iterations to a Minimum Structure
if 'Geometry is converged' in line:
if not hasattr(self, 'optdone'):
self.optdone = []
self.optdone.append(len(self.atomcoords))
# *********************************************************
# * Nuclear coordinates of the final structure / Angstrom *
# *********************************************************
# ATOM X Y Z
# C1 0.235547 -1.415838 0.012193
# C2 1.313784 -0.488201 0.015297
# C3 1.087036 0.895508 0.014333
# ...
# ...
# H19 -0.021315 -4.934913 -0.029666
# H20 -1.431994 -3.721026 -0.041078
if 'Nuclear coordinates of the final structure / Angstrom' in line:
self.skip_lines(inputfile, ['s', 'header'])
line = next(inputfile)
atomcoords = []
while line.split() != []:
atomcoords.append([float(c) for c in line.split()[1:]])
line = next(inputfile)
self.atomcoords.append(atomcoords)
# All orbitals with orbital energies smaller than E(LUMO)+0.5 are printed
#
# ++ Molecular orbitals:
# -------------------
#
# Title: RKS-DFT orbitals
#
# Molecular orbitals for symmetry species 1: a
#
# Orbital 1 2 3 4 5 6 7 8 9 10
# Energy -10.0179 -10.0179 -10.0075 -10.0075 -10.0066 -10.0066 -10.0056 -10.0055 -9.9919 -9.9919
# Occ. No. 2.0000 2.0000 2.0000 2.0000 2.0000 2.0000 2.0000 2.0000 2.0000 2.0000
#
# 1 C1 1s -0.6990 0.6989 0.0342 0.0346 0.0264 -0.0145 -0.0124 -0.0275 -0.0004 -0.0004
# 2 C1 2s -0.0319 0.0317 -0.0034 -0.0033 -0.0078 0.0034 0.0041 0.0073 -0.0002 -0.0002
# ...
# ...
# 58 H18 1s 0.2678
# 59 H19 1s -0.2473
# 60 H20 1s 0.1835
# --
if '++ Molecular orbitals:' in line:
self.skip_lines(inputfile, ['d', 'b'])
line = next(inputfile)
if 'Natural orbitals' not in line:
self.skip_lines(inputfile, ['b', 'symm'])
line = next(inputfile)
moenergies = []
homos = 0
mocoeffs = []
while line[:2] != '--':
line = next(inputfile)
if line.strip().startswith('Orbital'):
orbital_index = line.split()[1:]
for i in orbital_index:
mocoeffs.append([])
if 'Energy' in line:
energies = [
utils.convertor(float(x), 'hartree', 'eV')
for x in line.split()[1:]
]
moenergies.extend(energies)
if 'Occ. No.' in line:
for i in line.split()[2:]:
if float(i) != 0:
homos += 1
aonames = []
tokens = line.split()
if tokens and tokens[0] == '1':
while tokens and tokens[0] != '--':
aonames.append("{atom}_{orbital}".format(
atom=tokens[1], orbital=tokens[2]))
info = tokens[3:]
j = 0
for i in orbital_index:
mocoeffs[int(i) - 1].append(float(info[j]))
j += 1
line = next(inputfile)
tokens = line.split()
self.set_attribute('aonames', aonames)
if len(moenergies) != self.nmo:
moenergies.extend(
[numpy.nan for x in range(self.nmo - len(moenergies))])
self.append_attribute('moenergies', moenergies)
if not hasattr(self, 'homos'):
self.homos = []
self.homos.extend([homos - 1])
while len(mocoeffs) < self.nmo:
nan_array = [numpy.nan for i in range(self.nbasis)]
mocoeffs.append(nan_array)
self.append_attribute('mocoeffs', mocoeffs)
## Parsing MP energy from the &MBPT2 module.
# Conventional algorithm used...
#
# SCF energy = -74.9644564043 a.u.
# Second-order correlation energy = -0.0364237923 a.u.
#
# Total energy = -75.0008801966 a.u.
# Reference weight ( Cref**2 ) = 0.98652
#
# :: Total MBPT2 energy -75.0008801966
#
#
# Zeroth-order energy (E0) = -36.8202538520 a.u.
#
# Shanks-type energy S1(E) = -75.0009150108 a.u.
if 'Total MBPT2 energy' in line:
mpenergies = []
mpenergies.append(
utils.convertor(self.float(line.split()[4]), 'hartree', 'eV'))
if not hasattr(self, 'mpenergies'):
self.mpenergies = []
self.mpenergies.append(mpenergies)
# Parsing data ccenergies from &CCSDT module.
# --- Start Module: ccsdt at Thu Jul 26 14:03:23 2018 ---
#
# ()()()()()()()()()()()()()()()()()()()()()()()()()()()()()()()()()()()()()()()()()()()()()()()()()()
#
# &CCSDT
# ...
# ...
# 14 -75.01515915 -0.05070274 -0.00000029
# 15 -75.01515929 -0.05070289 -0.00000014
# 16 -75.01515936 -0.05070296 -0.00000007
# Convergence after 17 Iterations
#
#
# Total energy (diff) : -75.01515936 -0.00000007
# Correlation energy : -0.0507029554992
if 'Start Module: ccsdt' in line:
self.skip_lines(inputfile, ['b', '()', 'b'])
line = next(inputfile)
if '&CCSDT' in line:
while not line.strip().startswith('Total energy (diff)'):
line = next(inputfile)
ccenergies = utils.convertor(self.float(line.split()[4]),
'hartree', 'eV')
if not hasattr(self, 'ccenergies'):
self.ccenergies = []
self.ccenergies.append(ccenergies)
# ++ Primitive basis info:
# ---------------------
#
#
# *****************************************************
# ******** Primitive Basis Functions (Valence) ********
# *****************************************************
#
#
# Basis set:C.AUG-CC-PVQZ.........
#
# Type
# s
# No. Exponent Contraction Coefficients
# 1 0.339800000D+05 0.000091 -0.000019 0.000000 0.000000 0.000000 0.000000
# 2 0.508900000D+04 0.000704 -0.000151 0.000000 0.000000 0.000000 0.000000
# ...
# ...
# 29 0.424000000D+00 0.000000 1.000000
#
# Number of primitives 93
# Number of basis functions 80
#
# --
if line.startswith('++ Primitive basis info:'):
self.skip_lines(inputfile,
['d', 'b', 'b', 's', 'header', 's', 'b'])
line = next(inputfile)
gbasis_array = []
while '--' not in line and '****' not in line:
if 'Basis set:' in line:
basis_element_patterns = re.findall(
'Basis set:([A-Za-z]{1,2})\.', line)
assert len(basis_element_patterns) == 1
basis_element = basis_element_patterns[0].title()
gbasis_array.append((basis_element, []))
if 'Type' in line:
line = next(inputfile)
shell_type = line.split()[0].upper()
self.skip_line(inputfile, 'headers')
line = next(inputfile)
exponents = []
coefficients = []
func_array = []
while line.split():
exponents.append(self.float(line.split()[1]))
coefficients.append(
[self.float(i) for i in line.split()[2:]])
line = next(inputfile)
for i in range(len(coefficients[0])):
func_tuple = (shell_type, [])
for iexp, exp in enumerate(exponents):
coeff = coefficients[iexp][i]
if coeff != 0:
func_tuple[1].append((exp, coeff))
gbasis_array[-1][1].append(func_tuple)
line = next(inputfile)
atomsymbols = [
self.table.element[atomno] for atomno in self.atomnos
]
self.gbasis = [[] for i in range(self.natom)]
for element, gbasis in gbasis_array:
mask = [
element == possible_element
for possible_element in atomsymbols
]
indices = [i for (i, x) in enumerate(mask) if x]
for index in indices:
self.gbasis[index] = gbasis
def extract(self, inputfile, line):
"""Extract information from the file object inputfile."""
## This section is present when executing &GATEWAY.
# ++ Molecular structure info:
# -------------------------
# ************************************************
# **** Cartesian Coordinates / Bohr, Angstrom ****
# ************************************************
# Center Label x y z x y z
# 1 C1 0.526628 -2.582937 0.000000 0.278679 -1.366832 0.000000
# 2 C2 2.500165 -0.834760 0.000000 1.323030 -0.441736 0.000000
if line[25:63] == 'Cartesian Coordinates / Bohr, Angstrom':
if not hasattr(self, 'atomnos'):
self.atomnos = []
if not hasattr(self, 'atomcoords'):
self.atomcoords = []
self.skip_lines(inputfile, ['stars', 'blank', 'header'])
line = next(inputfile)
atomelements = []
atomcoords = []
while not self.re_dashes_and_spaces.search(line):
sline = line.split()
atomelements.append(
self.re_atomelement.search(sline[1]).groups()[0])
atomcoords.append(list(map(float, sline[5:])))
line = next(inputfile)
self.atomcoords.append(atomcoords)
if self.atomnos == []:
self.atomnos = [
utils.PeriodicTable().number[atomelement]
for atomelement in atomelements
]
if not hasattr(self, 'natom'):
self.set_attribute('natom', len(self.atomnos))
## This section is present when executing &SCF.
# ++ Orbital specifications:
# -----------------------
# Symmetry species 1
# Frozen orbitals 0
# Occupied orbitals 3
# Secondary orbitals 77
# Deleted orbitals 0
# Total number of orbitals 80
# Number of basis functions 80
# --
if line[:29] == '++ Orbital specifications:':
self.skip_lines(inputfile, ['dashes', 'blank'])
line = next(inputfile)
while line[:2] != '--':
if line[6:30] == 'Total number of orbitals':
self.set_attribute('nmo', int(line.split()[-1]))
if line[6:31] == 'Number of basis functions':
self.set_attribute('nbasis', int(line.split()[-1]))
line = next(inputfile)
#Parsing the molecular charge
if line[6:23] == 'Molecular charge ':
self.set_attribute('charge', int(float(line.split()[-1])))
# ++ Molecular charges:
# ------------------
# Mulliken charges per centre and basis function type
# ---------------------------------------------------
# C1
# 1s 2.0005
# 2s 2.0207
# 2px 0.0253
# 2pz 0.1147
# 2py 1.8198
# *s -0.0215
# *px 0.0005
# *pz 0.0023
# *py 0.0368
# *d2+ 0.0002
# *d1+ 0.0000
# *d0 0.0000
# *d1- 0.0000
# *d2- 0.0000
# *f3+ 0.0000
# *f2+ 0.0001
# *f1+ 0.0000
# *f0 0.0001
# *f1- 0.0001
# *f2- 0.0000
# *f3- 0.0003
# *g4+ 0.0000
# *g3+ 0.0000
# *g2+ 0.0000
# *g1+ 0.0000
# *g0 0.0000
# *g1- 0.0000
# *g2- 0.0000
# *g3- 0.0000
# *g4- 0.0000
# Total 6.0000
# N-E 0.0000
# Total electronic charge= 6.000000
# Total charge= 0.000000
#--
if line[:24] == '++ Molecular charges:':
atomcharges = []
while line[6:29] != 'Total electronic charge':
line = next(inputfile)
if line[6:9] == 'N-E':
atomcharges.extend(map(float, line.split()[1:]))
# Molcas only performs Mulliken population analysis.
self.set_attribute('atomcharges', {'mulliken': atomcharges})
# Ensure the charge printed here is identical to the
# charge printed before entering the SCF.
self.skip_line(inputfile, 'blank')
line = next(inputfile)
assert line[6:30] == 'Total charge='
if hasattr(self, 'charge'):
assert int(float(line.split()[2])) == self.charge
# This section is present when executing &SCF
# This section parses the total SCF Energy.
# *****************************************************************************************************************************
# * *
# * SCF/KS-DFT Program, Final results *
# * *
# * *
# * *
# * Final Results *
# * *
# *****************************************************************************************************************************
# :: Total SCF energy -37.6045426484
if line[:
22] == ':: Total SCF energy' or line[:
25] == ':: Total KS-DFT energy':
if not hasattr(self, 'scfenergies'):
self.scfenergies = []
scfenergy = float(line.split()[-1])
self.scfenergies.append(utils.convertor(scfenergy, 'hartree',
'eV'))
## Parsing the scftargets in this section
# ++ Optimization specifications:
# ----------------------------
# SCF Algorithm: Conventional
# Minimized density differences are used
# Number of density matrices in core 9
# Maximum number of NDDO SCF iterations 400
# Maximum number of HF SCF iterations 400
# Threshold for SCF energy change 0.10E-08
# Threshold for density matrix 0.10E-03
# Threshold for Fock matrix 0.15E-03
# Threshold for linear dependence 0.10E-08
# Threshold at which DIIS is turned on 0.15E+00
# Threshold at which QNR/C2DIIS is turned on 0.75E-01
# Threshold for Norm(delta) (QNR/C2DIIS) 0.20E-04
if line[:34] == '++ Optimization specifications:':
scftargets = []
while not line[6:37] == 'Threshold for SCF energy change':
line = next(inputfile)
if line[6:37] == 'Threshold for SCF energy change':
target = float(line.split()[-1])
scftargets.append(target)
line = next(inputfile)
if line[6:34] == 'Threshold for density matrix':
target = float(line.split()[-1])
scftargets.append(target)
line = next(inputfile)
if line[6:31] == 'Threshold for Fock matrix':
target = float(line.split()[-1])
scftargets.append(target)
self.skip_lines(inputfile,['Threshold for linear dependence', 'Threshold at which DIIS is turned on', \
'Threshold at which QNR/C2DIIS is turned on'])
line = next(inputfile)
if line[6:31] == 'Threshold for Norm(delta)':
target = float(line.split()[-1])
scftargets.append(target)
if not hasattr(self, 'scftargets'):
self.scftargets = []
self.scftargets.append(scftargets)
# ++ Convergence information
# SCF iterations: Energy and convergence statistics
# Iter Tot. SCF One-electron Two-electron Energy Max Dij or Max Fij DNorm TNorm AccCon Time
# Energy Energy Energy Change Delta Norm in Sec.
# 1 -36.83817703 -50.43096166 13.59278464 0.00E+00 0.16E+00* 0.27E+01* 0.30E+01 0.33E+02 NoneDa 0.
# 2 -36.03405202 -45.74525152 9.71119950 0.80E+00* 0.14E+00* 0.93E-02* 0.26E+01 0.43E+01 Damp 0.
# 3 -37.08936118 -48.41536598 11.32600480 -0.11E+01* 0.12E+00* 0.91E-01* 0.97E+00 0.16E+01 Damp 0.
# 4 -37.31610460 -50.54103969 13.22493509 -0.23E+00* 0.11E+00* 0.96E-01* 0.72E+00 0.27E+01 Damp 0.
# 5 -37.33596239 -49.47021484 12.13425245 -0.20E-01* 0.59E-01* 0.59E-01* 0.37E+00 0.16E+01 Damp 0.
if line[46:91] == 'iterations: Energy and convergence statistics':
self.skip_line(inputfile, 'blank')
while line.split() != [
'Energy', 'Energy', 'Energy', 'Change', 'Delta', 'Norm',
'in', 'Sec.'
]:
line = next(inputfile)
scfvalues = []
line = next(inputfile)
while line.split()[0] != 'Convergence':
if line.split()[0].isdigit():
energy = float(line.split()[4].replace('*', ''))
density = float(line.split()[5].replace('*', ''))
fock = float(line.split()[6].replace('*', ''))
dnorm = float(line.split()[7].replace('*', ''))
scfvalues.append([energy, density, fock, dnorm])
try:
line = next(inputfile)
if line.split() == []:
line = next(inputfile)
except StopIteration:
self.logger.warning(
'File terminated before end of last SCF!')
break
if not hasattr(self, "scfvalues"):
self.scfvalues = []
self.scfvalues.append(scfvalues)
# Harmonic frequencies in cm-1
#
# IR Intensities in km/mol
#
# 1 2 3 4 5 6
#
# Frequency: i60.14 i57.39 128.18 210.06 298.24 309.65
#
# Intensity: 3.177E-03 2.129E-06 4.767E-01 2.056E-01 6.983E-07 1.753E-07
# Red. mass: 2.42030 2.34024 2.68044 3.66414 2.61721 3.34904
#
# C1 x -0.00000 0.00000 0.00000 -0.05921 0.00000 -0.06807
# C1 y 0.00001 -0.00001 -0.00001 0.00889 0.00001 -0.02479
# C1 z -0.03190 0.04096 -0.03872 0.00001 -0.12398 -0.00002
# C2 x -0.00000 0.00001 0.00000 -0.06504 0.00000 -0.03487
# C2 y 0.00000 -0.00000 -0.00000 0.01045 0.00001 -0.05659
# C2 z -0.03703 -0.03449 -0.07269 0.00000 -0.07416 -0.00001
# C3 x -0.00000 0.00001 0.00000 -0.06409 -0.00001 0.05110
# C3 y -0.00000 0.00001 0.00000 0.00152 0.00000 -0.03263
# C3 z -0.03808 -0.08037 -0.07267 -0.00001 0.07305 0.00000
# ...
# H20 y 0.00245 -0.00394 0.03215 0.03444 -0.10424 -0.10517
# H20 z 0.00002 -0.00001 0.00000 -0.00000 -0.00000 0.00000
#
#
#
# ++ Thermochemistry
if line[1:29] == 'Harmonic frequencies in cm-1':
self.skip_line(inputfile, 'blank')
line = next(inputfile)
while 'Thermochemistry' not in line:
if 'Frequency:' in line:
if not hasattr(self, 'vibfreqs'):
self.vibfreqs = []
vibfreqs = [
float(i.replace('i', '-')) for i in line.split()[1:]
]
self.vibfreqs.extend(vibfreqs)
if 'Intensity:' in line:
if not hasattr(self, 'vibirs'):
self.vibirs = []
vibirs = map(float, line.split()[1:])
self.vibirs.extend(vibirs)
if 'Red.' in line:
self.skip_line(inputfile, 'blank')
line = next(inputfile)
if not hasattr(self, 'vibdisps'):
self.vibdisps = []
disps = []
for n in range(3 * self.natom):
numbers = [float(s) for s in line[17:].split()]
# The atomindex should start at 0 instead of 1.
atomindex = int(
re.search(r'\d+$',
line.split()[0]).group()) - 1
numbermodes = len(numbers)
if len(disps) == 0:
# Appends empty array of the following
# dimensions (numbermodes, natom, 0) to disps.
for mode in range(numbermodes):
disps.append([[]
for x in range(0, self.natom)])
for mode in range(numbermodes):
disps[mode][atomindex].append(numbers[mode])
line = next(inputfile)
self.vibdisps.extend(disps)
line = next(inputfile)
## Parsing thermochemistry attributes here
# ++ Thermochemistry
#
# *********************
# * *
# * THERMOCHEMISTRY *
# * *
# *********************
#
# Mass-centered Coordinates (Angstrom):
# ***********************************************************
# ...
# *****************************************************
# Temperature = 0.00 Kelvin, Pressure = 1.00 atm
# -----------------------------------------------------
# Molecular Partition Function and Molar Entropy:
# q/V (M**-3) S(kcal/mol*K)
# Electronic 0.100000D+01 0.000
# Translational 0.100000D+01 0.000
# Rotational 0.100000D+01 2.981
# Vibrational 0.100000D+01 0.000
# TOTAL 0.100000D+01 2.981
#
# Thermal contributions to INTERNAL ENERGY:
# Electronic 0.000 kcal/mol 0.000000 au.
# Translational 0.000 kcal/mol 0.000000 au.
# Rotational 0.000 kcal/mol 0.000000 au.
# Vibrational 111.885 kcal/mol 0.178300 au.
# TOTAL 111.885 kcal/mol 0.178300 au.
#
# Thermal contributions to
# ENTHALPY 111.885 kcal/mol 0.178300 au.
# GIBBS FREE ENERGY 111.885 kcal/mol 0.178300 au.
#
# Sum of energy and thermal contributions
# INTERNAL ENERGY -382.121931 au.
# ENTHALPY -382.121931 au.
# GIBBS FREE ENERGY -382.121931 au.
# -----------------------------------------------------
# ...
# ENTHALPY -382.102619 au.
# GIBBS FREE ENERGY -382.179819 au.
# -----------------------------------------------------
# --
#
# ++ Isotopic shifts:
if line[4:19] == 'THERMOCHEMISTRY':
temperature_values = []
pressure_values = []
entropy_values = []
internal_energy_values = []
enthalpy_values = []
free_energy_values = []
while 'Isotopic' not in line:
if line[1:12] == 'Temperature':
temperature_values.append(float(line.split()[2]))
pressure_values.append(float(line.split()[6]))
if line[1:
48] == 'Molecular Partition Function and Molar Entropy:':
while 'TOTAL' not in line:
line = next(inputfile)
entropy_values.append(
utils.convertor(float(line.split()[2]), 'kcal',
'hartree'))
if line[1:40] == 'Sum of energy and thermal contributions':
internal_energy_values.append(
float(next(inputfile).split()[2]))
enthalpy_values.append(float(next(inputfile).split()[1]))
free_energy_values.append(float(
next(inputfile).split()[3]))
line = next(inputfile)
# When calculations for more than one temperature value are
# performed, the values corresponding to room temperature (298.15 K)
# are returned and if no calculations are performed for 298.15 K, then
# the values corresponding last temperature value are returned.
index = -1
if 298.15 in temperature_values:
index = temperature_values.index(298.15)
self.set_attribute('temperature', temperature_values[index])
if len(temperature_values) > 1:
self.logger.warning('More than 1 values of temperature found')
self.set_attribute('pressure', pressure_values[index])
if len(pressure_values) > 1:
self.logger.warning('More than 1 values of pressure found')
self.set_attribute('entropy', entropy_values[index])
if len(entropy_values) > 1:
self.logger.warning('More than 1 values of entropy found')
self.set_attribute('enthalpy', enthalpy_values[index])
if len(enthalpy_values) > 1:
self.logger.warning('More than 1 values of enthalpy found')
self.set_attribute('freeenergy', free_energy_values[index])
if len(free_energy_values) > 1:
self.logger.warning('More than 1 values of freeenergy found')
## Parsing Geometrical Optimization attributes in this section.
# ++ Slapaf input parameters:
# ------------------------
#
# Max iterations: 2000
# Convergence test a la Schlegel.
# Convergence criterion on gradient/para.<=: 0.3E-03
# Convergence criterion on step/parameter<=: 0.3E-03
# Convergence criterion on energy change <=: 0.0E+00
# Max change of an internal coordinate: 0.30E+00
# ...
# ...
# **********************************************************************************************************************
# * Energy Statistics for Geometry Optimization *
# **********************************************************************************************************************
# Energy Grad Grad Step Estimated Geom Hessian
# Iter Energy Change Norm Max Element Max Element Final Energy Update Update Index
# 1 -382.30023222 0.00000000 0.107221 0.039531 nrc047 0.085726 nrc047 -382.30533799 RS-RFO None 0
# 2 -382.30702964 -0.00679742 0.043573 0.014908 nrc001 0.068195 nrc001 -382.30871333 RS-RFO BFGS 0
# 3 -382.30805348 -0.00102384 0.014883 0.005458 nrc010 -0.020973 nrc001 -382.30822089 RS-RFO BFGS 0
# ...
# ...
# 18 -382.30823419 -0.00000136 0.001032 0.000100 nrc053 0.012319 nrc053 -382.30823452 RS-RFO BFGS 0
# 19 -382.30823198 0.00000221 0.001051 -0.000092 nrc054 0.066565 nrc053 -382.30823822 RS-RFO BFGS 0
# 20 -382.30820252 0.00002946 0.001132 -0.000167 nrc021 -0.064003 nrc053 -382.30823244 RS-RFO BFGS 0
#
# +----------------------------------+----------------------------------+
# + Cartesian Displacements + Gradient in internals +
# + Value Threshold Converged? + Value Threshold Converged? +
# +-----+----------------------------------+----------------------------------+
# + RMS + 5.7330E-02 1.2000E-03 No + 1.6508E-04 3.0000E-04 Yes +
# +-----+----------------------------------+----------------------------------+
# + Max + 1.2039E-01 1.8000E-03 No + 1.6711E-04 4.5000E-04 Yes +
# +-----+----------------------------------+----------------------------------+
if 'Convergence criterion on energy change' in line:
self.energy_threshold = float(line.split()[6])
# If energy change threshold equals zero,
# then energy change is not a criteria for convergence.
if self.energy_threshold == 0:
self.energy_threshold = numpy.inf
if 'Energy Statistics for Geometry Optimization' in line:
if not hasattr(self, 'geovalues'):
self.geovalues = []
self.skip_lines(inputfile, ['stars', 'header'])
line = next(inputfile)
assert 'Iter Energy Change Norm' in line
# A variable keeping track of ongoing iteration.
iter_number = len(self.geovalues) + 1
# Iterate till blank line.
while line.split() != []:
for i in range(iter_number):
line = next(inputfile)
self.geovalues.append([float(line.split()[2])])
line = next(inputfile)
# Along with energy change, RMS and Max values of change in
# Cartesian Diaplacement and Gradients are used as optimization
# criteria.
self.skip_lines(inputfile,
['border', 'header', 'header', 'border'])
line = next(inputfile)
assert '+ RMS +' in line
line_rms = line.split()
line = next(inputfile)
line_max = next(inputfile).split()
if not hasattr(self, 'geotargets'):
# The attribute geotargets is an array consisting of the following
# values: [Energy threshold, Max Gradient threshold, RMS Gradient threshold, \
# Max Displacements threshold, RMS Displacements threshold].
max_gradient_threshold = float(line_max[8])
rms_gradient_threshold = float(line_rms[8])
max_displacement_threshold = float(line_max[4])
rms_displacement_threshold = float(line_rms[4])
self.geotargets = [
self.energy_threshold, max_gradient_threshold,
rms_gradient_threshold, max_displacement_threshold,
rms_displacement_threshold
]
max_gradient_change = float(line_max[7])
rms_gradient_change = float(line_rms[7])
max_displacement_change = float(line_max[3])
rms_displacement_change = float(line_rms[3])
self.geovalues[iter_number - 1].extend([
max_gradient_change, rms_gradient_change,
max_displacement_change, rms_displacement_change
])
# *********************************************************
# * Nuclear coordinates for the next iteration / Angstrom *
# *********************************************************
# ATOM X Y Z
# C1 0.235560 -1.415847 0.012012
# C2 1.313797 -0.488199 0.015149
# C3 1.087050 0.895510 0.014200
# ...
# ...
# H19 -0.021327 -4.934915 -0.029355
# H20 -1.432030 -3.721047 -0.039835
#
# --
if 'Nuclear coordinates for the next iteration / Angstrom' in line:
self.skip_lines(inputfile, ['s', 'header'])
line = next(inputfile)
atomcoords = []
while line.split() != []:
atomcoords.append([float(c) for c in line.split()[1:]])
line = next(inputfile)
self.atomcoords.append(atomcoords)
# **********************************************************************************************************************
# * Energy Statistics for Geometry Optimization *
# **********************************************************************************************************************
# Energy Grad Grad Step Estimated Geom Hessian
# Iter Energy Change Norm Max Element Max Element Final Energy Update Update Index
# 1 -382.30023222 0.00000000 0.107221 0.039531 nrc047 0.085726 nrc047 -382.30533799 RS-RFO None 0
# ...
# ...
# 23 -382.30823115 -0.00000089 0.001030 0.000088 nrc053 0.000955 nrc053 -382.30823118 RS-RFO BFGS 0
#
# +----------------------------------+----------------------------------+
# + Cartesian Displacements + Gradient in internals +
# + Value Threshold Converged? + Value Threshold Converged? +
# +-----+----------------------------------+----------------------------------+
# + RMS + 7.2395E-04 1.2000E-03 Yes + 2.7516E-04 3.0000E-04 Yes +
# +-----+----------------------------------+----------------------------------+
# + Max + 1.6918E-03 1.8000E-03 Yes + 8.7768E-05 4.5000E-04 Yes +
# +-----+----------------------------------+----------------------------------+
#
# Geometry is converged in 23 iterations to a Minimum Structure
if 'Geometry is converged' in line:
if not hasattr(self, 'optdone'):
self.optdone = []
self.optdone.append(len(self.atomcoords))
# *********************************************************
# * Nuclear coordinates of the final structure / Angstrom *
# *********************************************************
# ATOM X Y Z
# C1 0.235547 -1.415838 0.012193
# C2 1.313784 -0.488201 0.015297
# C3 1.087036 0.895508 0.014333
# ...
# ...
# H19 -0.021315 -4.934913 -0.029666
# H20 -1.431994 -3.721026 -0.041078
if 'Nuclear coordinates of the final structure / Angstrom' in line:
self.skip_lines(inputfile, ['s', 'header'])
line = next(inputfile)
atomcoords = []
while line.split() != []:
atomcoords.append([float(c) for c in line.split()[1:]])
line = next(inputfile)
self.atomcoords.append(atomcoords)
def setUp(self):
self.t = utils.PeriodicTable()
def extract(self, inputfile, line):
"""Extract information from the file object inputfile."""
## This section is present when executing &GATEWAY.
# ++ Molecular structure info:
# -------------------------
# ************************************************
# **** Cartesian Coordinates / Bohr, Angstrom ****
# ************************************************
# Center Label x y z x y z
# 1 C1 0.526628 -2.582937 0.000000 0.278679 -1.366832 0.000000
# 2 C2 2.500165 -0.834760 0.000000 1.323030 -0.441736 0.000000
if line[25:63] == 'Cartesian Coordinates / Bohr, Angstrom':
if not hasattr(self, 'atomnos'):
self.atomnos = []
if not hasattr(self, 'atomcoords'):
self.atomcoords = []
self.skip_lines(inputfile, ['stars', 'blank', 'header'])
line = next(inputfile)
atomelements = []
atomcoords = []
while not self.re_dashes_and_spaces.search(line):
sline = line.split()
atomelements.append(self.re_atomelement.search(sline[1]).groups()[0])
atomcoords.append(list(map(float, sline[5:])))
line = next(inputfile)
self.atomcoords.append(atomcoords)
if self.atomnos == []:
self.atomnos = [utils.PeriodicTable().number[atomelement] for atomelement in atomelements]
if not hasattr(self, 'natom'):
self.set_attribute('natom', len(self.atomnos))
## This section is present when executing &SCF.
# ++ Orbital specifications:
# -----------------------
# Symmetry species 1
# Frozen orbitals 0
# Occupied orbitals 3
# Secondary orbitals 77
# Deleted orbitals 0
# Total number of orbitals 80
# Number of basis functions 80
# --
if line[:29] == '++ Orbital specifications:':
self.skip_lines(inputfile, ['dashes', 'blank'])
line = next(inputfile)
while line[:2] != '--':
if line[6:30] == 'Total number of orbitals':
self.set_attribute('nmo', int(line.split()[-1]))
if line[6:31] == 'Number of basis functions':
self.set_attribute('nbasis', int(line.split()[-1]))
line = next(inputfile)
#Parsing the molecular charge
if line[6:23] == 'Molecular charge ':
self.set_attribute('charge', int(float(line.split()[-1])))
# ++ Molecular charges:
# ------------------
# Mulliken charges per centre and basis function type
# ---------------------------------------------------
# C1
# 1s 2.0005
# 2s 2.0207
# 2px 0.0253
# 2pz 0.1147
# 2py 1.8198
# *s -0.0215
# *px 0.0005
# *pz 0.0023
# *py 0.0368
# *d2+ 0.0002
# *d1+ 0.0000
# *d0 0.0000
# *d1- 0.0000
# *d2- 0.0000
# *f3+ 0.0000
# *f2+ 0.0001
# *f1+ 0.0000
# *f0 0.0001
# *f1- 0.0001
# *f2- 0.0000
# *f3- 0.0003
# *g4+ 0.0000
# *g3+ 0.0000
# *g2+ 0.0000
# *g1+ 0.0000
# *g0 0.0000
# *g1- 0.0000
# *g2- 0.0000
# *g3- 0.0000
# *g4- 0.0000
# Total 6.0000
# N-E 0.0000
# Total electronic charge= 6.000000
# Total charge= 0.000000
#--
if line[:24] == '++ Molecular charges:':
atomcharges = []
while line[6:29] != 'Total electronic charge':
line = next(inputfile)
if line[6:9] == 'N-E':
atomcharges.extend(map(float, line.split()[1:]))
# Molcas only performs Mulliken population analysis.
self.set_attribute('atomcharges', {'mulliken': atomcharges})
# Ensure the charge printed here is identical to the
# charge printed before entering the SCF.
self.skip_line(inputfile, 'blank')
line = next(inputfile)
assert line[6:30] == 'Total charge='
if hasattr(self, 'charge'):
assert int(float(line.split()[2])) == self.charge
# This section is present when executing &SCF
# This section parses the total SCF Energy.
# *****************************************************************************************************************************
# * *
# * SCF/KS-DFT Program, Final results *
# * *
# * *
# * *
# * Final Results *
# * *
# *****************************************************************************************************************************
# :: Total SCF energy -37.6045426484
if line[:22] == ':: Total SCF energy' or line[:25] == ':: Total KS-DFT energy':
if not hasattr(self, 'scfenergies'):
self.scfenergies = []
scfenergy = float(line.split()[-1])
self.scfenergies.append(utils.convertor(scfenergy, 'hartree', 'eV'))
## Parsing the scftargets in this section
# ++ Optimization specifications:
# ----------------------------
# SCF Algorithm: Conventional
# Minimized density differences are used
# Number of density matrices in core 9
# Maximum number of NDDO SCF iterations 400
# Maximum number of HF SCF iterations 400
# Threshold for SCF energy change 0.10E-08
# Threshold for density matrix 0.10E-03
# Threshold for Fock matrix 0.15E-03
if line[:34] == '++ Optimization specifications:':
while not line[6:37] == 'Threshold for SCF energy change':
line = next(inputfile)
if line[6:37] == 'Threshold for SCF energy change':
if not hasattr(self, 'scftargets'):
self.scftargets = [[]]
target = float(line.split()[-1])
self.scftargets[0].append(target)
line = next(inputfile)
if line[6:34] == 'Threshold for density matrix':
if not hasattr(self, 'scftargets'):
self.scftargets = [[]]
target = float(line.split()[-1])
self.scftargets[0].append(target)
line = next(inputfile)
if line[6:31] == 'Threshold for Fock matrix':
if not hasattr(self, 'scftargets'):
self.scftargets = [[]]
target = float(line.split()[-1])
self.scftargets[0].append(target)
# ++ Convergence information
# SCF iterations: Energy and convergence statistics
# Iter Tot. SCF One-electron Two-electron Energy Max Dij or Max Fij DNorm TNorm AccCon Time
# Energy Energy Energy Change Delta Norm in Sec.
# 1 -36.83817703 -50.43096166 13.59278464 0.00E+00 0.16E+00* 0.27E+01* 0.30E+01 0.33E+02 NoneDa 0.
# 2 -36.03405202 -45.74525152 9.71119950 0.80E+00* 0.14E+00* 0.93E-02* 0.26E+01 0.43E+01 Damp 0.
# 3 -37.08936118 -48.41536598 11.32600480 -0.11E+01* 0.12E+00* 0.91E-01* 0.97E+00 0.16E+01 Damp 0.
# 4 -37.31610460 -50.54103969 13.22493509 -0.23E+00* 0.11E+00* 0.96E-01* 0.72E+00 0.27E+01 Damp 0.
# 5 -37.33596239 -49.47021484 12.13425245 -0.20E-01* 0.59E-01* 0.59E-01* 0.37E+00 0.16E+01 Damp 0.
if line[46:91] == 'iterations: Energy and convergence statistics':
self.skip_line(inputfile,'blank')
while line.split() != ['Energy', 'Energy', 'Energy', 'Change', 'Delta', 'Norm', 'in', 'Sec.']:
line = next(inputfile)
if not hasattr(self, "scfvalues"):
self.scfvalues = [[]]
line = next(inputfile)
while line.split()[0] != 'Convergence':
if line.split()[0].isdigit():
energy = float(line.split()[4].replace('*',''))
density = float(line.split()[5].replace('*',''))
fock = float(line.split()[6].replace('*',''))
self.scfvalues[0].append([energy, density, fock])
try:
line = next(inputfile)
if line.split() == []:
line = next(inputfile)
except StopIteration:
self.logger.warning('File terminated before end of last SCF!')
break
# Harmonic frequencies in cm-1
#
# IR Intensities in km/mol
#
# 1 2 3 4 5 6
#
# Frequency: i60.14 i57.39 128.18 210.06 298.24 309.65
#
# Intensity: 3.177E-03 2.129E-06 4.767E-01 2.056E-01 6.983E-07 1.753E-07
# Red. mass: 2.42030 2.34024 2.68044 3.66414 2.61721 3.34904
#
# C1 x -0.00000 0.00000 0.00000 -0.05921 0.00000 -0.06807
# C1 y 0.00001 -0.00001 -0.00001 0.00889 0.00001 -0.02479
# C1 z -0.03190 0.04096 -0.03872 0.00001 -0.12398 -0.00002
# C2 x -0.00000 0.00001 0.00000 -0.06504 0.00000 -0.03487
# C2 y 0.00000 -0.00000 -0.00000 0.01045 0.00001 -0.05659
# C2 z -0.03703 -0.03449 -0.07269 0.00000 -0.07416 -0.00001
# C3 x -0.00000 0.00001 0.00000 -0.06409 -0.00001 0.05110
# C3 y -0.00000 0.00001 0.00000 0.00152 0.00000 -0.03263
# C3 z -0.03808 -0.08037 -0.07267 -0.00001 0.07305 0.00000
if line[1:29] == 'Harmonic frequencies in cm-1':
self.skip_line(inputfile,'blank')
line = next(inputfile)
if 'IR' in line.split():
freqmode = 'IR'
while 'Thermochemistry' not in line.split():
if 'Frequency:' in line.split():
if not hasattr(self, 'vibfreqs'):
self.vibfreqs = []
vibfreqs = [float(i.replace('i','-')) for i in line.split()[1:]]
self.vibfreqs.extend(vibfreqs)
if 'Intensity:' in line.split():
if freqmode == 'IR':
if not hasattr(self, 'vibirs'):
self.vibirs = []
vibirs = map(float, line.split()[1:])
self.vibirs.extend(vibirs)
if 'x' in line.split():
if not hasattr(self, 'vibdisps'):
self.vibdisps = []
disps = []
for n in range(3*self.natom):
numbers = [float(s) for s in line[17:].split()]
atomindex = int(re.search(r'\d+$',line.split()[0]).group()) - 1 # atom index, starting at zero
numbermodes = len(numbers)
if not disps:
for mode in range(numbermodes):
# For each mode, make list of list [atom][coord_index]
disps.append([[] for x in range(0, self.natom)])
for mode in range(numbermodes):
disps[mode][atomindex].append(numbers[mode])
line = next(inputfile)
self.vibdisps.extend(disps)
line = next(inputfile)
from cclib.io import ccread
import numpy as np
import glob
from cclib.parser import utils
import mdtraj
from matplotlib import pyplot as plt
import pandas as pd
symbols = utils.PeriodicTable().element[1:] # drop first item which is None
def load_log_files(fnames):
fname_list = glob.glob(fnames)
print('Filenames are : ')
[print(fname) for fname in fname_list]
return [ccread(log) for log in fname_list]
def get_scf_energies(data_list, unit1='eV', unit2='kcal'):
return [utils.convertor(d.scfenergies[0], unit1, unit2) for d in data_list]
def boltzmann_distribution(energy_dict, R=1.9872036e-3, T=300):
return [np.exp(-(x[1] / (R * T))) for x in energy_dict.values()]
def plot_conformer_population(energies_list,
R=1.9872036e-3,
T=300,
title=None):
'''
