def grep_aimd(inputfile):
# Routine for the extraction of AIMD geometries, MOs and energies.
# The geometries are converted to the zmat format using babel.
a = qc.read(inputfile)
# Get geometries in zmat format
geo_list = []
for geo in a.aimd.geometries:
geo.write('dummy.xyz')
os.system('babel dummy.xyz dummy.gzmat')
infile = open('dummy.gzmat', 'r')
content = infile.readlines()
infile.close()
os.system('rm dummy.xyz; rm dummy.gzmat')
geometry = []
for line in content:
if '=' in line:
dummy = line.split('=')
geometry.append(float(dummy[1]))
geometry = np.asarray(geometry)
geo_list.append(geometry)
# Get Overlap Matrices
#overlap_list=grep_overlap(inputfile)
# Get Core Hamiltonians
core_list = grep_core(inputfile)
# Get Fock Matrices
fock_list = grep_fock(inputfile)
# Get MO-Energies
e_mos = grep_e_mo(inputfile)
# Get MOs
mos_list = grep_MOs(inputfile)
# Get energies
energies = a.aimd.energies
# Get nuclear repulsion energies
e_rep = grep_nuc_rep(inputfile)
# Get basis set information
(atom_indices, basis_types) = grep_basis_info(inputfile)
# Q-Chem does extra SCF before AIMD starts,
# so first entries of 'e_mos', 'mos', 'core', 'fock', 'overlap' and 'e_rep' have to be cut
del e_rep[0]
del e_mos[0]
del mos_list[0]
del fock_list[0]
del core_list[0]
#del overlap_list[0]
return (geo_list, e_rep, core_list, fock_list, e_mos, mos_list, energies,
atom_indices, basis_types)
def grep_sp(inputfile):
# Routine for the extraction of AIMD geometries, MOs and energies.
# The geometries are converted to the zmat format using babel.
a = qc.read(inputfile, silent=True)
# Get Overlap Matrices
overlap = grep_overlap(inputfile)
# Get Core Hamiltonians
core = grep_core(inputfile)
# Get Fock Matrices
fock = grep_fock(inputfile)
# Get MO-Energies
e_mos = grep_e_mo(inputfile)
# Get MOs
#mos = grep_MOs_sp(inputfile)
# Get Density Matrix
density = grep_density(inputfile)
# Get energies
energy = a.general.energy
# Get nuclear repulsion energies
e_rep = grep_nuc_rep(inputfile)
# Get basis set information
#(atom_indices,basis_types) = grep_basis_info(inputfile)
# Get Mulliken charges
mull = grep_mull(inputfile)
return (e_rep, overlap, core, fock, e_mos, density, energy, mull)
# pyQChem script for a AIMD follow-up with reduced basis set size
#
# AWH/RM 2015
import pyQChem as qc
# First, read all N geometries from aimd outputfile
a = qc.read('aimd_small.out')
aa = a.list_of_jobs[1]
# Second, create the template
myrem = qc.rem_array()
myrem.jobtype('sp')
myrem.exchange('hf')
myrem.basis('sto-3g')
myrem.scf_algorithm('rca_diis')
#myrem.max_rca_cycles('10')
#myrem.thresh_rca_switch('7')
myrem.scf_guess('sad')
myrem.scf_convergence('9')
myrem.thresh('14')
myrem.incfock('0')
myrem.incdft('0')
#myrem.max_scf_cycles('500')
#myrem.symmetry('false')
#myrem.sym_ignore('true')
myrem.mem_total('16000')
myrem.mem_static('4000')
# Add rem_array
myfile = qc.inputfile()
def __init__(self, infile,charge=0,mult=1,jobtype='opt',basis='6-31+g*',method='tpssh', \
geom_read=False, nametrunc=True, bond_cons = None, infodump=False):
self.jobdict = {'sp':self.jobSp, 'opt':self.jobOpt, 'fq':self.jobFreq, 'sopt':self.jobSopt, \
'cube':self.jobCube, 'constr':self.jobConstrainedOpt, 'fixbonds':self.jobFixedBondOpt, \
'cdft':self.jobCdft, \
}
# self.bond_cons = [[2,5,con_N_x],[3,4,con_N_x],[2,3,con_N_y],[4,5,con_N_y]]
self.bond_cons = bond_cons
self.info_dump = infodump
# self.free_atom = ['Fe','O']
self.free_atom = ['O']
self.job_arr_list = []
self.charge = charge
self.mult = mult
self.jobtype = jobtype
self.pcm_arr = None
self.sol_arr = None
self.plot_arr = None
#if nametrunc == True: self.name = (infile.split('.')[0]).split('_')[0]
#else: self.name = infile.split('.')[0]
splinfile = infile.split('/')
if len(splinfile) == 1:
self.path = ''
else:
self.path = '/'.join(splinfile[:-1]) + '/'
if nametrunc == True:
self.name = (splinfile[-1].split('.')[0]).split('_')[0]
else:
self.name = (splinfile[-1].split('.'))[0]
print(splinfile)
print(splinfile[-1])
print(self.name)
print(self.charge)
print(self.mult)
self.out = qc.read(infile)
self.rem = qc.rem_array()
self.rem.basis(basis)
self.rem.method(method)
self.rem.thresh("14")
self.rem.add('mem_total', '4096')
self.rem.add('mem_static', '256')
self.rem.add('max_scf_cycles', '500')
# self.rem.add('scf_convergence','7')
# self.rem.add('scf_algorithm','diis_gdm')
##For these metal-centered systems
self.rem.add('unrestricted', 'true')
# if self.mult == '1': ## I didn't find that this worked at all for any of the metal-macrocycle systems
# self.rem.add("scf_guess_mix", "1")
# self.rem.add("scf_guess", "gwh")
if geom_read:
self.mol = qc.mol_array()
self.mol.geometry("read")
self.rem.add('scf_guess', 'read')
else:
if infile.split('.')[-1] == 'out':
# self.mol=qc.mol_array(self.out.opt.geometries[-1])
self.mol = qc.mol_array(self.out.general.final_geometry)
# self.mol = qc.mol_array(self.out.general.initial_geometry)
else:
xyz = qc.cartesian(atom_list=self.out.list_of_atoms)
self.mol = qc.mol_array(xyz)
self.mol.charge(charge)
self.mol.multiplicity(mult)
rem = qc.rem_array()
rem.basis("sto-3g")
rem.jobtype("opt")
xyz = qc.cartesian()
xyz.add_atom()
xyz.add_atom("H", "0", "0", ".74")
molec = qc.mol_array(xyz)
job = qc.inputfile()
job.add(rem)
job.add(molec)
#run job with name "h2" making h2.in h2.sh, and h2.out
job.run(name="h2")
#read in output
out = qc.read("h2.out")
out.opt.info()
#let's approximate how much this has changed
#grab first geometry
start = out.opt.geometries[0]
#grab last geometry
end = out.opt.geometries[-1]
#Print statistics for geometric distortions
print "\n\nApproximate change between starting and ending geometries by two metrics:\n"
print qc.utilities.rmsd(start.xyzs, end.xyzs), " or ", qc.utilities.kabsch(
start.xyzs, end.xyzs), "\n"
#
# This sample file generates center-of-mass displaced water molecules from the standard water dimer
# and loops through different multiplicative displacements
#
# MBG (02/2014)
#
import pyQChem as qc
import os
from pylab import *
#load some sample inputs - here the first and second monomers of the water dimer
a = qc.read("../../databases/s22/Water-dimer_mono1.xyz")
a.name = "water-dimer_mono1"
b = qc.read("../../databases/s22/Water-dimer_mono2.xyz")
b.name = "water-dimer_mono2"
#Save direction and magnitude
d = b.com - a.com
#Translate both to origin
a.move(-a.com)
b.move(-b.com)
#loop over a multiplicative factor for center of mass distance and generate jobs
for i in arange(.9, 2.01, .1):
#translate to new coordinates
a.move(-i * d / 2)
b.move(i * d / 2)
#form new dimer
import pyQChem as qc
import os
#make a generic rem array
rem = qc.rem_array()
rem.basis("sto-3g")
rem.exchange("hf")
#make a list of jobs
job_list = []
#for all xyzs in a database, create and append the job to the list
for i in os.popen("ls ../../databases/a24/*.xyz").read().splitlines():
#make the jobs
job = qc.inputfile()
#give job a name
job.runinfo.name = i.split('/')[-1].replace(".xyz", "")
#read the xyz
xyz = qc.read(i)
#append the molecule and rem array
job.add(qc.mol_array(xyz))
job.add(rem)
job_list.append(job)
# run all jobs in list using 12 workers
qc.queue(job_list, num_workers=12)
import pyQChem as qc
import os
#make a generic rem array
rem=qc.rem_array()
rem.basis("sto-3g")
rem.exchange("hf")
#make a list of jobs
job_list=[]
#for all xyzs in a database, create and append the job to the list
for i in os.popen("ls ../../databases/a24/*.xyz").read().splitlines():
#make the jobs
job=qc.inputfile()
#give job a name
job.runinfo.name=i.split('/')[-1].replace(".xyz","")
#read the xyz
xyz=qc.read(i)
#append the molecule and rem array
job.add(qc.mol_array(xyz))
job.add(rem)
job_list.append(job)
# run all jobs in list using 12 workers
qc.queue(job_list,num_workers=12)
rem1=pq.rem_array()
rem1.basis("6-31++G**")
rem1.exchange("hf")
rem1.thresh("14")
rem1.scf_convergence("10")
from copy import deepcopy
rem2=deepcopy(rem1)
rem2.scf_guess("fragmo")
#make a rem_frgm array
rem_frgm=pq.rem_frgm_array()
rem_frgm.thresh("7")
rem_frgm.scf_convergence("3")
#make objects for holding the molecular geometries
xyz=pq.read("4water.xyz")
frag=pq.fragment(atom_list=xyz.list_of_atoms)
#make molecule array from cartesian object
mol1=pq.mol_array(xyz)
mol2=pq.mol_array(frag)
#make input object and write to disk
job1=pq.inputfile()
job1.add(rem1)
job1.add(mol1)
job2=pq.inputfile()
job2.add(rem2)
job2.rem.scf_guess("fragmo")
job2.add(rem_frgm)
#generate rem array, cartesian object, mol array, and job via standard procedure (see input demos)
rem=qc.rem_array()
rem.basis("6-31g")
rem.jobtype("sp")
rem.method("adc(2)")
rem.ee_singlets("[2,0,0,0,0,2,0,0]")
xyz=qc.cartesian()
xyz.add_atom()
xyz.add_atom("H","0","0",".74")
molec=qc.mol_array(xyz)
job=qc.inputfile()
job.add(rem)
job.add(molec)
#run job with name "h2" making h2.in h2.sh, and h2.out
job.run(name="h2")
#read in output
out=qc.read("h2.out")
out.adc.info()
#let's compute the excitation energies between the excited states
print "\nExcitation energies between excited states:"
for i in range(0,len(out.adc.list_of_excited_states)-1):
es1 = out.adc.list_of_excited_states[i]
for j in range(i + 1,len(out.adc.list_of_excited_states)):
es2 = out.adc.list_of_excited_states[j]
print("{0:10s} -> {1:10s}: {2:12.6f}".format(es1.term_symbol, es2.term_symbol,es2.energy - es1.energy))
#
# This sample file generates center-of-mass displaced water molecules from the standard water dimer
# and loops through different multiplicative displacements
#
# MBG (02/2014)
#
import pyQChem as qc
import os
from pylab import *
#load some sample inputs - here the first and second monomers of the water dimer
a=qc.read("../../databases/s22/Water-dimer_mono1.xyz")
a.name="water-dimer_mono1"
b=qc.read("../../databases/s22/Water-dimer_mono2.xyz")
b.name="water-dimer_mono2"
#Save direction and magnitude
d=b.com-a.com
#Translate both to origin
a.move(-a.com)
b.move(-b.com)
#loop over a multiplicative factor for center of mass distance and generate jobs
for i in arange(.9,2.01,.1):
#translate to new coordinates
a.move(-i*d/2)
b.move(i*d/2)
#form new dimer