def dump(path, logfilename=sys.stdout, do_clyde_sort=False):
print("outputfiles:", path)
if do_clyde_sort:
xyzfiles = clyde_sort(get_outputfiles_from_path(path, ext=".xyz"))
else:
xyzfiles = get_outputfiles_from_path(path, ext=".xyz")
with open(logfilename, "w") as fh:
fh.write("{}\n".format(path))
for xyzfilename in xyzfiles:
coords_CO2 = get_coords_CO2(xyzfilename)
d1, d2 = calc_bond_lengths(coords_CO2)
theta = calc_theta(coords_CO2)
fh.write("{} {} {}\n".format(theta, d1, d2))
return
# 5. n_mm
BASEDIR = "/home/eric/Chemistry/calc.sgr/droplets/snapshot_method_dependence_4fs"
if args.file_operation == "save":
print("Trying to find output files...")
outputfiles = dict()
for CO2_type in CO2_types:
outputfiles[CO2_type] = dict()
for method in methods:
outputfiles[CO2_type][method] = dict()
for basis_set in basis_sets:
outputfiles[CO2_type][method][basis_set] = dict()
# hacky hack hack
for n_qm in (0, ):
outputfiles[CO2_type][method][basis_set][n_qm] = get_outputfiles_from_path(os.path.join(BASEDIR, "inputs_freq_{CO2_type}_0qm_{method}_{basis_set}".format(**locals())))
outputfiles[CO2_type][method][basis_set][n_qm] = filter_n_mm_into_dict(outputfiles[CO2_type][method][basis_set][n_qm])
with open('outputfiles.pypickle', 'wb') as picklefile:
pickle.dump(outputfiles, picklefile)
elif args.file_operation == "read":
print("Reading list of output files from: {}".format(os.path.abspath("outputfiles.pypickle")))
with open("outputfiles.pypickle", "rb") as picklefile:
outputfiles = pickle.load(picklefile)
elif args.file_operation == "none":
pass
else:
raise Exception
if args.parse_operation == "save":
# 1. method
# 2. basis set
# 3. n_qm
# 4. n_mm
if args.file_operation == "save":
print("Trying to find output files...")
basedir = "/home/eric/Chemistry/calc.sgr/droplets/snapshot_method_dependence"
outputfiles = dict()
for method in methods:
outputfiles[method] = dict()
for basis_set in basis_sets:
outputfiles[method][basis_set] = dict()
# hacky hack hack
for n_qm in (0, ):
outputfiles[method][basis_set][n_qm] = get_outputfiles_from_path(os.path.join(basedir, "inputs_freq_0qm_{method}_{basis_set}".format(method=method, basis_set=basis_set)))
outputfiles[method][basis_set][n_qm] = filter_n_mm_into_dict(outputfiles[method][basis_set][n_qm])
with open('outputfiles.pypickle', 'wb') as picklefile:
pickle.dump(outputfiles, picklefile)
elif args.file_operation == "read":
print("Reading list of output files from: {}".format(os.path.abspath("outputfiles.pypickle")))
with open("outputfiles.pypickle", "rb") as picklefile:
outputfiles = pickle.load(picklefile)
elif args.file_operation == "none":
pass
else:
raise Exception
if args.parse_operation == "save":
# pairs treated quantum mechanically (as opposed to using point
# charges).
outputs_freq_0qm = []
outputs_freq_1qm = []
outputs_freq_2qm = []
outputs_freq_3qm = []
outputs_freq_noCT_1qm = []
outputs_freq_noCT_2qm = []
outputs_freq_noCT_3qm = []
outputs_eda_covp_1qm = []
outputs_eda_covp_2qm = []
outputs_eda_covp_3qm = []
if args.file_operation == "save":
print("Trying to find output files...")
outputfiles = get_outputfiles_from_path(args.dir_to_search)
with open(args.logfilename, 'w') as logfile:
for outputfilename in outputfiles:
logfile.write("{}\n".format(outputfilename))
elif args.file_operation == "read":
print("Reading list of output files from: {}".format(os.path.abspath(args.logfilename)))
with open(args.logfilename) as logfile:
content = logfile.read()
outputfiles = content.splitlines()
elif args.file_operation == "none":
pass
else:
raise Exception
if args.debug:
print("len(outputfiles)")
from __future__ import print_function
import os
import numpy as np
import scipy.stats as sps
from analysis_utils import filter_outputfiles
from analysis_utils import get_CO2_frequencies
from analysis_utils import get_outputfiles_from_path
if __name__ == "__main__":
outputfiles = get_outputfiles_from_path(os.getcwd())
outputfiles_0mm = filter_outputfiles(outputfiles)
# B3LYP/6-31G**
weights_map = {
1: 0.06060606,
2: 0.24747475,
3: 0.4010101,
4: 0.22626263,
5: 0.06464646,
}
print('sum of weights: {}'.format(sum(weights_map.values())))
bins_outputfiles = dict()
bins_f = dict()
bins_i = dict()
