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ice_manager.py
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import matplotlib.pyplot as plt
from src import ice_build_geoms
from src import ice_build_geoms_v2
# from src import error_mexc_v9
from src import error_mexc_v11
from src import error_mexc_vib
from src import gather_energies
from src import vibrational_frequencies
from src import df_latexTable as df_latex
from src import discrete_to_art as dis_art
import time
import glob
import os
import sys
import pandas as pd
import subprocess
import numpy as np
import scipy.signal
import math
import matplotlib
matplotlib.use("Agg")
# print(sys.path)
# NEED TO CHECK IF Q SUBMITTED BEFORE RESUBMITTING
def jobResubmit(
min_delay,
number_delays,
method_opt,
basis_set_opt,
mem_com_opt,
mem_pbs_opt,
method_mexc,
basis_set_mexc,
mem_com_mexc,
mem_pbs_mexc,
nStates,
SCRF="",
):
min_delay = min_delay * 60
cluster_list = glob.glob("calc_zone/geom*")
print(cluster_list)
complete = []
resubmissions = []
for i in range(len(cluster_list)):
complete.append(0)
resubmissions.append(2)
calculations_complete = False
for i in range(number_delays):
for num, j in enumerate(cluster_list):
os.chdir(j)
print(j)
delay = i
if basis_set_mexc == "6-311G(d,p)":
basis_dir_name = ""
else:
basis_dir_name = "_" + basis_set_mexc
if nStates == "25":
pass
else:
basis_dir_name += "_n%s" % nStates
if SCRF != "":
basis_dir_name += "_SCRF_%s" % SCRF
if method_mexc == "B3LYP":
mexc_check = glob.glob("mexc" + basis_dir_name)
path_mexc = "mexc" + basis_dir_name
print(method_mexc.lower() + basis_dir_name)
else:
mexc_check = glob.glob(method_mexc.lower() + basis_dir_name)
path_mexc = method_mexc.lower() + basis_dir_name
print(method_mexc.lower() + basis_dir_name)
# print(mexc_check)
if len(mexc_check) > 0:
print("{0} entered mexc checkpoint 1".format(num + 1))
complete[num] = 1
# mexc_check_out = glob.glob("mexc/mexc.o*")
# mexc_check_out_complete = glob.glob("mexc_o/mexc.o*")
mexc_check_out = glob.glob("%s/mexc.o*" % path_mexc)
mexc_check_out_complete = glob.glob("%s/mexc_o.o*" % path_mexc)
# if complete[num] != 2 and len(mexc_check_out) > 1:
if (
complete[num] != 2
and len(mexc_check_out) > 0
and len(mexc_check_out_complete) > 0
):
print("{0} entered mexc checkpoint 2".format(num + 1))
complete[num] = 2
if complete[num] < 1:
action, resubmissions = error_mexc_v11.main(
num,
method_opt,
basis_set_opt,
mem_com_opt,
mem_pbs_opt,
method_mexc,
basis_set_mexc,
mem_com_mexc,
mem_pbs_mexc,
resubmissions,
delay,
nStates,
SCRF=SCRF,
)
# print(resubmissions)
mexc_check = []
os.chdir("../..")
stage = 0
for k in range(len(complete)):
stage += complete[k]
if stage == len(complete) * 2:
calculations_complete = True
if calculations_complete == True:
print(complete)
print("\nCalculations are complete.")
print("Took %.2f hours" % (i * min_delay / 60))
return complete
print("Completion List\n", complete, "\n")
print("delay %d" % (i))
time.sleep(min_delay)
return complete
def vibrational_resubmit(
min_delay,
number_delays,
method_opt,
basis_set_opt,
mem_com_opt,
mem_pbs_opt,
method_vib,
basis_set_vib,
mem_com_vib,
mem_pbs_vib,
SCRF="",
overall_name="vib",
):
min_delay = min_delay * 60
cluster_list = glob.glob("calc_zone/geom*")
print(cluster_list)
complete = []
resubmissions = []
for i in range(len(cluster_list)):
complete.append(0)
resubmissions.append(2)
calculations_complete = False
for i in range(number_delays):
for num, j in enumerate(cluster_list):
os.chdir(j)
print(j)
delay = i
basis_dir_name = "_vib"
if basis_set_vib == "6-311G(d,p)":
pass
else:
basis_dir_name = "_" + basis_set_vib
if SCRF != "":
basis_dir_name += "_SCRF_%s" % SCRF
if method_vib == "B3LYP":
mexc_check = glob.glob("mexc" + basis_dir_name)
path_mexc = "mexc" + basis_dir_name
print(method_vib.lower() + basis_dir_name)
else:
mexc_check = glob.glob(method_vib.lower() + basis_dir_name)
path_mexc = method_vib.lower() + basis_dir_name
print(method_vib.lower() + basis_dir_name)
# print(mexc_check)
if len(mexc_check) > 0:
print("{0} entered mexc checkpoint 1".format(num + 1))
complete[num] = 1
mexc_check_out = glob.glob("%s/mexc.o*" % path_mexc)
mexc_check_out_complete = glob.glob("%s/mexc_o.o*" % path_mexc)
if (
complete[num] != 2
and len(mexc_check_out) > 0
and len(mexc_check_out_complete) > 0
):
print("{0} entered mexc checkpoint 2".format(num + 1))
complete[num] = 2
if complete[num] < 1:
action, resubmissions = error_mexc_vib.main(
num,
method_opt,
basis_set_opt,
mem_com_opt,
mem_pbs_opt,
method_vib,
basis_set_vib,
mem_com_vib,
mem_pbs_vib,
resubmissions,
delay,
"25",
SCRF=SCRF,
spectroscopy_type="vib",
overall_name=overall_name,
)
mexc_check = []
os.chdir("../..")
stage = 0
for k in range(len(complete)):
stage += complete[k]
if stage == len(complete) * 2:
calculations_complete = True
if calculations_complete == True:
print(complete)
print("\nCalculations are complete.")
print("Took %.2f hours" % (i * min_delay / 60))
return complete
print("Completion List\n", complete, "\n")
print("delay %d" % (i))
time.sleep(min_delay)
return complete
def boltzmannAnalysisSetup(
complete,
method_mexc="B3LYP",
basis_set_mexc="6-311G(d,p)",
nStates="25",
acquiredStates="25",
SCRF="",
):
analysis_ready = []
if "results" not in glob.glob("results"):
os.mkdir("results")
os.chdir("results")
if "mexc_values" not in glob.glob("mexc_values"):
os.mkdir("mexc_values")
os.chdir("..")
else:
os.chdir("..")
if basis_set_mexc == "6-311G(d,p)":
basis_dir_name = ""
else:
basis_dir_name = "_" + basis_set_mexc
if nStates == "25":
pass
else:
basis_dir_name += "_n%s" % nStates
if SCRF != "":
basis_dir_name += "_SCRF_%s" % SCRF
if method_mexc == "PBE0":
path_mexc = method_mexc.lower() + basis_dir_name
method_mexc = "PBE1PBE"
elif method_mexc == "wB97XD":
new_dir = "wb97xd"
path_mexc = method_mexc.lower() + basis_dir_name
elif method_mexc == "B3LYP":
path_mexc = "mexc" + basis_dir_name
# print("B3LYP here")
elif method_mexc == "B3LYPD3":
new_dir = "b3lypd3"
path_mexc = method_mexc.lower() + basis_dir_name
method_mexc = "B3lYP empiricaldispersion=gd3 "
elif method_mexc == "CAM-B3LYP":
new_dir = "cam-b3lyp"
path_mexc = method_mexc.lower() + basis_dir_name
method_mexc = "CAM-B3LYP"
elif method_mexc == "B97D3":
new_dir = "b97d3"
path_mexc = method_mexc.lower() + basis_dir_name
method_mexc = "B97D3"
else:
print("This method is not supported for TD-DFT yet.")
path_mexc = path_mexc.replace("(", "\(").replace(")", "\)")
print("\nPATH::: ", path_mexc, method_mexc)
for i in range(len(complete)):
if complete[i] == 2:
analysis_ready.append(i)
else:
# print('geom%d/mexc %d is not finished with TD-DFT' % (i+1, i+1))
print(
"geom%d/%s %d is not finished with TD-DFT" % (i + 1, path_mexc, i + 1)
)
os.chdir("calc_zone")
for i in analysis_ready:
# cmd = '''awk '/Excited State/ {print $7, $9}' geom%d/%s/mexc.out | sed 's/f=//g' > ../results/mexc_values/mexc_out%d.csv''' % (
# i+1, path_mexc, i+1)
cmd = (
"""awk '/Excited State/ {print $7, $9}' geom%d/%s/mexc.out | sed 's/f=//g' | tac | tail -n %s > ../results/mexc_values/mexc_out%d.csv"""
% (i + 1, path_mexc, acquiredStates, i + 1)
)
failure = subprocess.call(cmd, shell=True)
os.chdir("..")
print(cmd)
print("\nBoltzmann Analysis Setup Complete.\n")
return
def boltzmannAnalysis(
T, energy_levels="electronic", DeltaN="2", x_range=[50, 4100], overtones=False
):
if energy_levels == "electronic":
os.chdir("results/mexc_values")
csv_name = "mexc_out"
cmd = "perl ../../../src/specsim.pl"
elif energy_levels == "vibrational":
os.chdir("results/vibrational_values")
csv_name = "vib"
cmd = "perl ../../../src/specsim_xrange.pl 50 4100"
cmd = "perl ../../../src/specsim_args.pl %d %d %s" % (
x_range[0],
x_range[1],
DeltaN,
)
# print(os.getcwd())
mexc_out_names = glob.glob("*.csv")
# print(mexc_out_names)
mexc_dict = {}
# print(mexc_out_names)
for i in mexc_out_names:
val = i[:-4]
# print("val")
# print(val)
# print(np.genfromtxt(i, delimiter=" "))
mexc_dict["{0}".format(val)] = np.genfromtxt(i, delimiter=" ")
os.chdir("../energies")
energy_all = np.genfromtxt("energy_all.csv", delimiter=",")
energy_all = energy_all[np.argsort(energy_all[:, 0])]
lowest_energy = np.amin(energy_all[:, 1])
lowest_energy_ind = (np.where(energy_all[:, 1] == lowest_energy))[0][0]
print("LOWEST_ENERGY", lowest_energy)
lowest_energy = lowest_energy * 4.3597e-18 # convert hartrees to joules
print("lowest energy:", lowest_energy, lowest_energy_ind)
kb = 1.380649e-23
# combining_mexc = mexc_dict['mexc_out{0}'.format(lowest_energy_ind+1)]
combining_mexc = mexc_dict["{0}".format(csv_name + str(lowest_energy_ind + 1))]
# print(combining_mexc)
# print("energy_all:\n", energy_all)
for key, value in mexc_dict.items():
if key == "mexc_out{0}".format(lowest_energy_ind + 1):
continue
# print(key) # crashes if not all mexc_out*.csv accounted for
# remember energy_all array index starts at zero
if energy_levels == "electronic":
current_energy_ind = int(key[8:]) - 1
elif energy_levels == "vibrational":
current_energy_ind = int(key[3:]) - 1
# print(current_energy_ind)
# find current energy and convert hartrees to joules
current_energy = ((energy_all[current_energy_ind, :])[1]) * 4.3597e-18
# print(lowest_energy)
# print(current_energy)
ni_nj = math.exp((lowest_energy - current_energy) / (T * kb))
"""
print("n%d / n%d = %.10f" %
(lowest_energy_ind+1, current_energy_ind + 1, ni_nj))
"""
for i in range(len(value)):
value[i][1] = value[i][1] * ni_nj
# print(value[i][1])
# print(value[i])
# if want only certain number randomly, modify here
combining_mexc = np.concatenate((combining_mexc, value), axis=0)
# print(combining_mexc)
# os.chdir("../final/data")
os.chdir("..")
if "final" not in glob.glob("final"):
os.mkdir("final")
os.chdir("final")
if "data" not in glob.glob("data"):
os.mkdir("data")
os.chdir("data")
np.savetxt("data", combining_mexc, fmt="%s")
print("\ndata file made for specsim.pl\n")
subprocess.call(cmd, shell=True)
if overtones:
x, y = collectSpecSimData(x_units="cm-1", path_to_data="./")
arr_y = np.array(y)
print("local maxima")
peaks_dat, _ = scipy.signal.find_peaks(arr_y, height=0)
with open("extra_bands", "w") as fp:
for j in peaks_dat:
# print(round(x[i],2), arr_y[i])
height = arr_y[j]
frequency = round(x[j], 4)
fp.write(str(height) + " " + str(frequency) + "\n")
a = vibrational_frequencies.overtones("extra_bands", T=T)
a = vibrational_frequencies.combine_modes_overtones("spec", a)
# time_data
np.savetxt("data", a, fmt="%s")
print("\ndata file made for specsim.pl after overtones\n")
subprocess.call(cmd, shell=True)
os.chdir("../../../")
return
def generateGraph(
spec_name, T, title, filename, x_range=[100, 300], x_units="nm", peaks=False
):
# print(os.getcwd())
fig, ax1 = plt.subplots()
data = np.genfromtxt("results/final/data/" + spec_name, delimiter=" ")
data = data.tolist()
# print(data)
x = []
y = []
highest_y = 0
for i in data:
# print(i)
x.append(i[0])
y.append(i[1])
if i[1] > highest_y:
highest_y = i[1]
for i in range(len(y)):
y[i] /= highest_y
if x_units == "eV" or x_units == "ev":
h = 6.626e-34
c = 3e17
ev_to_joules = 1.60218e-19
x = [h * c / (i * ev_to_joules) for i in x]
x.reverse()
y.reverse()
elif x_units == "cm-1":
x.reverse()
y.reverse()
# maxima = scipy.signal.argrelextrema(y, np.greater)
# print(x)
# print('\n', y)
ax1.plot(x, y, "k-", label="T = {0} K".format(T))
# ax1.set_xlim([x[0], x[-1]])
ax1.set_xlim(x_range)
ax1.set_ylim(0, 1.4)
plt.title(title)
if x_units == "ev" or x_units == "eV":
plt.xlabel("Electronvolts (eV)")
ax1.legend(shadow=True, fancybox=True)
if peaks:
arr_y = np.array(y)
print("local maxima")
peaks, _ = scipy.signal.find_peaks(arr_y, height=0)
for i in peaks:
print(round(x[i], 2), arr_y[i])
height = arr_y[i]
frequency = round(x[i], 2)
if height > 0.02:
plt.text(frequency - 0.08, arr_y[i] + 0.05, "%.2f" % frequency)
elif x_units == "cm-1":
plt.xlabel(r"Wavenumbers cm$^{-1}$")
if peaks:
arr_y = np.array(y)
print("local maxima")
peaks, _ = scipy.signal.find_peaks(arr_y, height=0)
for i in peaks:
print(round(x[i]), arr_y[i])
height = arr_y[i]
frequency = round(x[i])
if height > 0.02:
plt.text(frequency + 100, arr_y[i] + 0.1, "%d" % frequency)
else:
plt.xlabel("Wavelength (nm)")
ax1.legend(shadow=True, fancybox=True)
plt.ylabel("Oscillator Strength")
# plt.grid(b=None, which='major', axis='y', linewidth=1)
# plt.grid(b=None, which='major', axis='x', linewidth=1)
# os.chdir("results/final/graphs")
os.chdir("results/final")
if "graphs" not in glob.glob("graphs"):
os.mkdir("graphs")
if x_units == "cm-1":
ax1.yaxis_inverted()
os.chdir("graphs")
plt.savefig(filename)
os.chdir("../../..")
return
def collectSpecSimData(
x_units="eV", spec_name="spec", normalize=True, path_to_data="results/final/data/"
):
data = np.genfromtxt(path_to_data + spec_name, delimiter=" ")
data = data.tolist()
# print(data)
x = []
y = []
highest_y = 0
for i in data:
# print(i)
x.append(i[0])
y.append(i[1])
if i[1] > highest_y:
highest_y = i[1]
print(highest_y, "HIGHEST")
cam_b3lyp_n125_y = 4.98005616
# cam_b3lyp_n125_y = 1.9835017
# cam_b3lyp_n125_y = 10.17985964
# print("CAM-B3LYP:", highest_y)
for i in range(len(y)):
y[i] /= highest_y
# y[i] /= cam_b3lyp_n125_y
if x_units == "eV" or x_units == "ev":
h = 6.626e-34
c = 3e17
ev_to_joules = 1.60218e-19
x = [h * c / (i * ev_to_joules) for i in x]
x.reverse()
y.reverse()
elif x_units == "cm-1":
x.reverse()
y.reverse()
# maxima = scipy.signal.argrelextrema(y, np.greater)
return x, y
def latexTable_addLine(path, line):
if os.path.exists(path):
with open(path, "r") as fp:
lines = fp.readlines()
lines.insert(-4, "\t" + line)
with open(path, "w") as fp:
for i in lines:
fp.write(i)
else:
with open(path, "w") as fp:
fp.write("\\begin{center}\n\\begin{tabular}{ |c|c|c|c| }\n\t\\hline\n")
fp.write("\tMethod & Basis Set & Excitation (eV) &")
fp.write(
"\\vtop{\\hbox{\\strut Oscillator Strength}\\hbox{\\strut (Normalized)}}\\\\\n\t\\hline\n"
)
fp.write("\t" + line)
fp.write("\t\\hline\n\\end{tabular}\n\\end{center}")
def electronicMultiPlot(
methods_lst,
T,
title,
filename,
x_range=[2, 16],
x_units="eV",
peaks=False,
spec_name="spec",
complete=[],
basis_set_mexc="6-31G(d,p)",
nStates="25",
):
location = os.getcwd().split("/")[-1]
if location == "src" or location == "calc_zone":
os.chdir("..")
# only pass blank complete if all TD-DFT calculations are complete since it is assumed
if complete == []:
num_geom = glob.glob("calc_zone/geom*")
for i in range(len(num_geom)):
complete.append(2)
fig, ax1 = plt.subplots()
if peaks:
print(os.path.exists("latex_df_6-311++G(2d,2p)"))
if os.path.exists("latex_df_6-311++G(2d,2p).tex"):
headers = [
"Method",
"Basis Set",
"Excitation (eV)",
"\\vtop{\\hbox{\\strut Oscillator Strength}\\hbox{\\strut (Normalized)}}",
]
df = df_latex.latexTable_df("latex_df_6-311++G(2d,2p).tex", headers)
elif os.path.exists("latex_df_6-311G(d,p).tex"):
headers = [
"Method",
"Basis Set",
"Excitation (eV)",
"\\vtop{\\hbox{\\strut Oscillator Strength}\\hbox{\\strut (Normalized)}}",
]
df = df_latex.latexTable_df("latex_df_6-311G(d,p).tex", headers)
else:
df = {
"Method": [],
"Basis Set": [],
"Excitation (eV)": [],
"\\vtop{\\hbox{\\strut Oscillator Strength}\\hbox{\\strut (Normalized)}}": [],
} # 4 col
df = pd.DataFrame(df)
for i in methods_lst:
gather_energies.main()
boltzmannAnalysisSetup(complete, i, basis_set_mexc, nStates, nStates)
boltzmannAnalysis(T, energy_levels="electronic")
x, y = collectSpecSimData(x_units=x_units)
"""
if i == 'B3LYP':
print(x, y)
"""
ax1.plot(x, y, "-", label="%s" % i)
if peaks:
arr_y = np.array(y)
print("local maxima")
peaks_dat, _ = scipy.signal.find_peaks(arr_y, height=0)
for j in peaks_dat:
# print(round(x[i],2), arr_y[i])
height = arr_y[j]
frequency = round(x[j], 2)
print("x, y = %.2f, %.2f" % (frequency, height))
line = "%s & %s & %.2f & %.2f \\\\\n" % (
i,
basis_set_mexc,
frequency,
height,
)
latexTable_addLine("latexTable.tex", line)
df.loc[len(df.index)] = [i, basis_set_mexc, frequency, height]
"""
with open('latexTabel.tex', 'a') as fp:
fp.write("%s/%s,%.2f,%.2f\n" % (i, basis_set_mexc, frequency, height))
print(os.getcwd())
"""
"""
if height > 0.02:
plt.text(frequency - 0.08, arr_y[i]+0.05, '%.2f' % frequency )
"""
df_latex.df_latexTable("latex_df_%s.tex" % basis_set_mexc, df)
# ax1.set_xlim([x[0], x[-1]])
ax1.set_xlim(x_range)
ax1.set_ylim(0, 1.4)
plt.title(title)
if x_units == "ev" or x_units == "eV":
# print(x)
plt.xlabel("Electronvolts (eV)")
ax1.legend(shadow=True, fancybox=True, loc="upper right")
elif x_units == "cm-1":
plt.xlabel(r"Wavenumbers cm$^{-1}$")
else:
plt.xlabel("Wavelength (nm)")
ax1.legend(shadow=True, fancybox=True)
plt.ylabel("Oscillator Strength")
plt.grid(b=None, which="major", axis="y", linewidth=1)
plt.grid(b=None, which="major", axis="x", linewidth=1)
# os.chdir("results/final/graphs")
os.chdir("results/final")
if "graphs" not in glob.glob("graphs"):
os.mkdir("graphs")
os.chdir("graphs")
plt.savefig(filename)
os.chdir("../../..")
def electronicMultiPlot_Experiment(
methods_lst,
T,
title,
filename,
x_range=[2, 16],
x_units="eV",
peaks=False,
spec_name="spec",
complete=[],
basis_set_mexc="6-31G(d,p)",
nStates="25",
acquiredStates="25",
exp_data=[],
colors=[],
sec_y_axis=False,
rounding=1,
extra_data=np.array([[-1, -1]]),
SCRF="",
):
location = os.getcwd().split("/")[-1]
if location == "src" or location == "calc_zone":
os.chdir("..")
# only pass blank complete if all TD-DFT calculations are complete since it is assumed
if complete == []:
num_geom = glob.glob("calc_zone/geom*")
for i in range(len(num_geom)):
complete.append(2)
fig, ax1 = plt.subplots(dpi=400)
if peaks:
if os.path.exists("latex_df_6-311++G(2d,2p).tex"):
headers = [
"Method",
"Basis Set",
"Excitation (eV)",
"\\vtop{\\hbox{\\strut Oscillator Strength}\\hbox{\\strut (Normalized)}}",
]
df = df_latex.latexTable_df("latex_df_6-311++G(2d,2p).tex", headers)
elif os.path.exists("latex_df_6-311G(d,p).tex"):
headers = [
"Method",
"Basis Set",
"Excitation (eV)",
"\\vtop{\\hbox{\\strut Oscillator Strength}\\hbox{\\strut (Normalized)}}",
]
df = df_latex.latexTable_df("latex_df_6-311G(d,p).tex", headers)
else:
df = {
"Method": [],
"Basis Set": [],
"Excitation (eV)": [],
"\\vtop{\\hbox{\\strut Oscillator Strength}\\hbox{\\strut (Normalized)}}": [],
} # 4 col
df = pd.DataFrame(df)
for n, i in enumerate(methods_lst):
gather_energies.main()
boltzmannAnalysisSetup(
complete, i, basis_set_mexc, nStates, acquiredStates, SCRF
)
boltzmannAnalysis(T, energy_levels="electronic")
x, y = collectSpecSimData(x_units=x_units)
"""
if i == 'B3LYP':
print(x, y)
"""
# ax1.plot(x, y, "-", label="%s" % i, zorder=2)
# if i == 'wB97XD':
# i = r'$\omega$B97XD'
# ax1.plot(x, y, "-", c="%s" % (colors[n]), label="%s (Amorphous)" % i, zorder=2)
if i == "wB97XD":
i = r"$\omega$B97XD"
ax1.plot(x, y, "-", c="%s" % (colors[n]), label="%s" % i, zorder=2)
if peaks:
arr_y = np.array(y)
print("local maxima")
peaks_dat, _ = scipy.signal.find_peaks(arr_y, height=0)
for j in peaks_dat:
# print(round(x[i],2), arr_y[i])
height = arr_y[j]
frequency = round(x[j], 4)
if rounding == 1:
print("x, y = %.1f, %.1f" % (frequency, height))
line = "%s & %s & %.1f & %.1f \\\\\n" % (
i,
basis_set_mexc,
frequency,
height,
)
elif rounding == 2:
print("x, y = %.2f, %.2f" % (frequency, height))
line = "%s & %s & %.2f & %.2f \\\\\n" % (
i,
basis_set_mexc,
frequency,
height,
)
else:
print("x, y = %.4f, %.4f" % (frequency, height))
line = "%s & %s & %.4f & %.4f \\\\\n" % (
i,
basis_set_mexc,
frequency,
height,
)
# latexTable_addLine('latexTable.tex', line)
df.loc[len(df.index)] = [i, basis_set_mexc, frequency, height]
"""
with open('latexTabel.tex', 'a') as fp:
fp.write("%s/%s,%.2f,%.2f\n" % (i, basis_set_mexc, frequency, height))
print(os.getcwd())
"""
"""
if height > 0.02:
plt.text(frequency - 0.08, arr_y[i]+0.05, '%.2f' % frequency )
"""
df_latex.df_latexTable("latex_df_%s.tex" % basis_set_mexc, df, rounding)
# exp_names = [ "Exp. Solid", "Exp. Gas"]
exp_names = ["Exp. Solid A", "Exp. Solid B"]
# exp_names = [ "Exp. Solid B"]
# exp_names = [ "Exp. Solid", "Exp. Gas"]
# exp_names = [ "Exp. Solid A", "Exp. Solid B"]
exp_colors = ["k", "tab:grey"]
# exp_colors = [ "tab:grey"]
ax2 = ax1.twinx()
if len(exp_data) > 0:
for n, i in enumerate(exp_data):
print(i)
ymax = np.amax(i[:, 1], axis=0)
i[:, 1] /= ymax
# print(i)
ax2.plot(
i[:, 0],
i[:, 1],
"--",
c="%s" % exp_colors[n],
label="%s" % exp_names[n],
zorder=2,
)
if peaks:
arr_y = i[:, 1]
print("local maxima")
peaks_dat, _ = scipy.signal.find_peaks(arr_y, height=0)
for j in peaks_dat:
# print(round(x[i],2), arr_y[i])
height = arr_y[j]
frequency = round(i[j, 0], 2)
print("x, y = %.2f, %.2f" % (frequency, height))
line = "%s & %s & %.2f & %.2f \\\\\n" % (
exp_names[n],
basis_set_mexc,
frequency,
height,
)
# latexTable_addLine('latexTable.tex', line)
df.loc[len(df.index)] = [
exp_names[n],
basis_set_mexc,
frequency,
height,
]
df_latex.df_latexTable("latex_df_%s.tex" % basis_set_mexc, df, rounding)
# ax1.set_xlim([x[0], x[-1]])
if extra_data[0, 0] != -1 and extra_data[0, 1] != -1:
print("\n extra data\n")
ymax = np.amax(extra_data[:, 1], axis=0)
for i in range(len(extra_data[:, 1])):
extra_data[i, 1] /= ymax
ax1.plot(
extra_data[:, 0],
extra_data[:, 1],
"-",
label="CAM-B3LYP (Ribbon Octamer)",
color="blue",
)
if peaks:
arr_y = extra_data[:, 1]
arr_x = extra_data[:, 0]
print(arr_y)
peaks_dat, _ = scipy.signal.find_peaks(arr_y, height=0)
print(peaks_dat)
for j in peaks_dat:
# print(round(x[i],2), arr_y[i])
height = arr_y[j]
frequency = round(arr_x[j], 4)
print("x, y = %.1f, %.1f\n" % (frequency, height))
df.loc[len(df.index)] = ["8 Ribbon", basis_set_mexc, frequency, height]
if sec_y_axis:
# ax2.set_ylabel(r"Cross Section / cm$^2$ (Normalized)")
ax2.set_ylim(0, 1.5)
ax1.set_xlim(x_range)
ax1.set_ylim(0, 1.5)
plt.title(title)
ax1.legend(shadow=True, fancybox=True, loc="upper left")
ax2.legend(shadow=True, fancybox=True, loc="upper right")
if x_units == "ev" or x_units == "eV":
# print(x)
plt.xlabel("Electronvolts (eV)")
ax1.set_xlabel("Electronvolts (eV)")
# ax1.legend(shadow=True, fancybox=True)
elif x_units == "cm-1":
plt.xlabel(r"Wavenumbers cm$^{-1}$")
else:
plt.xlabel("Wavelength (nm)")
# ax1.legend(shadow=True, fancybox=True)
ax1.set_ylabel("Oscillator Strength")
# plt.grid(zorder=0, b=None, which='major', axis='y', linewidth=1)
# plt.grid(zorder=0, b=None, which='major', axis='x', linewidth=1)
# os.chdir("results/final/graphs")
os.chdir("results/final")
if "graphs" not in glob.glob("graphs"):
os.mkdir("graphs")
os.chdir("graphs")
plt.savefig(filename)
os.chdir("../../..")
def method_update_selection(methods_lst, basis_set_mexc, nStates, SCRF=""):
if basis_set_mexc == "6-311G(d,p)":
basis_dir_name = ""
else:
basis_dir_name = "_" + basis_set_mexc
if nStates == "25":
pass
else:
basis_dir_name += "_n%s" % nStates
if SCRF != "":
basis_dir_name += "_SCRF_%s" % SCRF
for n, i in enumerate(methods_lst):
if i == "B3LYP":
i = "mexc" + basis_dir_name
print(i.lower() + basis_dir_name)
else:
i = i.lower() + basis_dir_name
print(i.lower() + basis_dir_name)
methods_lst[n] = i
return methods_lst
def sort_data(data):
return data[data[:, 0].argsort()]
def nmLst_evLst(nmData):
h = 6.62607004e-34
c = 299792458
c = 3e17
Joules_to_eV = 1.602e-19
for i in range(len(nmData[:, 0])):
nmData[i, 0] = h * c / (nmData[i, 0] * Joules_to_eV)
nmData = nmData[nmData[:, 0].argsort()]
return nmData
def main():
mol_xyz1 = "mon_nh3.xyz"
mol_xyz1 = "mon_h2o.xyz"
mol_xyz1 = "mon_h2co3.xyz"
mol_xyz1 = "mon_h2co3_ct.xyz"
mol_xyz2 = "mon_h2co3_tt.xyz"
mol_xyz1 = "mon_co.xyz"
mol_xyz2 = "mon_co.xyz"
# mol_xyz2 = "mon_methanol.xyz"
number_clusters = 1
# enter the number of molecules of each geometry in the respective index
molecules_in_cluster = [16, 0]
box_length = 9 # in angstroms
minium_distance_between_molecules = 2.5
resubmit_delay_min = 60 * 12
resubmit_max_attempts = 40
# geometry optimization options
method_opt = "wB97XD"
basis_set_opt = "6-31G(d)"
mem_com_opt = "1600" # mb
mem_pbs_opt = "15" # gb
# TD-DFT methods
# method_mexc = "B3LYP"