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final.py
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from operator import add, sub
import numpy as np
import os
import itertools
import glob
import subprocess
import time
import sys
import subprocess
sys.path.insert(1, "./src") # this adds src to python path at runtime for modules
import error_mexc_dyes_v1
import error_mexc_dyes_v2
import ES_extraction
from absorpt import absorpt
from molecule_json import *
# requires obabel installed...
# brew install obabel
# conda install -c openbabel openbabel
def read_user():
with open("user", "r") as fp:
return fp.read().rstrip()
def collectLocalStructures(subdirectories, banned=[]):
localStructuresDict = {}
number_locals = 0
for num, i in enumerate(subdirectories):
os.chdir(i)
print("\n%s\n" % i)
localStructuresDict["local{0}".format(num + 1)] = []
localSmiles = glob.glob("*.smi")
for j in localSmiles:
# print(j[:-4])
if j[:-4] not in banned:
# print(j[:-4])
with open(j) as f:
smiles = f.read()
smiles = smiles.split("\n")
smiles[0] = smiles[0].rstrip()
localStructuresDict["local{0}".format(num + 1)].append(
(smiles[0], j[:-4], smiles[1])
)
# smiles[0]==smiles, j[:-4]==local_name, smiles[1]==name
else:
print(j[:-4], "skipped due to banned")
os.chdir("..")
number_locals += 1
print(localStructuresDict)
return localStructuresDict
def permutationDict(localStructuresDict):
pre_perm = []
for key, value in localStructuresDict.items():
pre_perm = pre_perm + [value]
post_perm = list(itertools.product(*pre_perm))
# print(len(post_perm))
return post_perm
def smilesRingCleanUp(f, s, t):
print()
smi1, na1, form1 = f
smi2, na2, form2 = s
smi3, na3, form3 = t
name = na1 + "_" + na2 + "_" + na3
formalName = form1 + "::" + form2 + "::" + form3
cmd = "../src/number_rings.pl '%s' '%s' '%s'" % (smi1, smi2, smi3)
line = subprocess.getoutput(cmd)
return line, name, formalName
def generateMolecules(
smiles_tuple_list, method_opt, basis_set_opt, mem_com_opt, mem_pbs_opt, cluster
):
monitor_jobs = []
if not os.path.exists("results"):
os.mkdir("results")
if not os.path.exists("results/smiles_input"):
os.mkdir("results/smiles_input")
os.chdir("results")
for num, i in enumerate(smiles_tuple_list):
first, second, third = i
line, name, formalName = smilesRingCleanUp(first, second, third)
mol_lst = MoleculeList()
if os.path.exists("../results.json"):
mol_lst.setData("../results.json")
else:
print("Creating results.json\n")
mol_lst.sendToFile("../results.json")
if mol_lst.checkMolecule(line):
print("\nMolecule already exists and the name smiles is... \n%s\n" % line)
continue
mol = Molecule()
mol.setSMILES(line)
file = open("smiles_input/{0}.smi".format(name), "w+")
file.write(line)
file.close()
cmd = "obabel -ismi smiles_input/{0}.smi -oxyz --gen3D".format(name)
carts = subprocess.check_output(cmd, shell=True)
carts = str(carts)
carts = carts.rstrip()
carts = carts.splitlines()
for n, i in enumerate(carts):
carts[n] = i.split("\\n")
carts_cleaned = []
invalid = True
for n, i in enumerate(carts[0]):
if n > 1:
carts_cleaned.append(i)
invalid = False
if invalid:
print("invalid line{0}".format(num), line)
invalid = True
continue
del carts_cleaned[-1]
# print(carts_cleaned)
os.mkdir(name)
err = subprocess.call("touch %s/info.json" % name, shell=True)
mol.setName(name)
mol.setParts(formalName)
mol.setLocalName(name)
mol.sendToFile("%s/info.json" % name)
data = ""
for line in carts_cleaned:
data += line + "\n"
error_mexc_dyes_v1.gaussianInputFiles(
0,
method_opt,
basis_set_opt,
mem_com_opt,
mem_pbs_opt,
cluster,
baseName="mex",
procedure="OPT",
data=data,
dir_name=name,
)
add_qsub_dir("./", name, "../qsub_queue")
# need to add qsub here for v2
mol_lst.addMolecule(mol)
mol_lst.sendToFile("../results.json")
monitor_jobs.append(name)
os.chdir("..")
print(monitor_jobs)
return monitor_jobs
def submitOpt(monitor_jobs):
os.chdir("results")
for i in monitor_jobs:
os.chdir(i)
cmd = "qsub mex.pbs"
subprocess.call(cmd, shell=True)
os.chdir("..")
os.chdir("..")
def add_excitation_data(
dir_name,
baseName,
method_mexc,
basis_set_mexc,
):
occVal, virtVal = ES_extraction.ES_extraction("%s/%s.out" % (dir_name, baseName))
if occVal == virtVal and occVal == 0:
print("failed to add")
return 0, 0
mol = Molecule()
mol.setData("info.json")
mol.setHOMO(occVal)
mol.setLUMO(virtVal)
mol.appendExcitations(absorpt("mexc/mexc.out", method_mexc, basis_set_mexc))
mol.toJSON()
mol.sendToFile("info.json")
mol_lst = MoleculeList()
mol_lst.setData("../../results.json")
mol_lst.updateMolecule(mol)
mol_lst.sendToFile("../../results.json")
def jobResubmit(
monitor_jobs,
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,
cluster,
route="results",
add_methods={"methods": [], "basis_set": [], "mem_com": [], "mem_pbs": []},
):
"""
Modified from ice_analog_spectra_generator repo
"""
add_methods_length = len(add_methods["methods"])
if (
add_methods_length != len(add_methods["basis_set"])
and add_methods_length != len(add_methods["mem_com"])
and add_methods_length != len(add_methods["mem_pbs"])
):
print(
"add_methods must have values that have lists of the same length.\nTerminating jobResubmit before start"
)
return []
resubmission_max = add_methods_length
mol_lst = MoleculeList()
if os.path.exists("results.json"):
mol_lst.setData("results.json")
else:
mol_lst.sendToFile("results.json")
min_delay = min_delay * 60
# cluster_list = glob.glob("%s/*" % route)
complete = []
resubmissions = []
for i in range(len(monitor_jobs)):
complete.append(0)
resubmissions.append(2)
# resubmissions.append(resubmission_max)
calculations_complete = False
# comment change directory below in production
os.chdir(route)
for i in range(number_delays):
# time.sleep(min_delay)
for num, j in enumerate(monitor_jobs):
os.chdir(j)
delay = i
mexc_check = glob.glob("mexc")
if len(mexc_check) > 0:
complete[num] = 1
mexc_check_out = glob.glob("mexc/mexc.o*")
mexc_check_out_complete = glob.glob("mexc/*_o*")
# if complete[num] != 2 and len(mexc_check_out) > 0 and len(mexc_check_out_complete) > 0:
if (
complete[num] < 2
and len(mexc_check_out) > 0
and len(mexc_check_out_complete) > 0
):
occVal, virtVal = ES_extraction.ES_extraction("mexc/mexc.out")
if occVal == virtVal and occVal == 0:
print(j)
mol = Molecule()
mol.setData("info.json")
mol.setHOMO(occVal)
mol.setLUMO(virtVal)
# Testing below
mol.setExictations(
absorpt("mexc/mexc.out", method_mexc, basis_set_mexc)
)
mol.toJSON()
mol.sendToFile("info.json")
# mol_lst.addMolecule(mol)
mol_lst = MoleculeList()
mol_lst.setData("../../results.json")
mol_lst.updateMolecule(mol)
mol_lst.sendToFile("../../results.json")
complete[num] = 2
# if complete[num] >= 2
if complete[num] < 1:
print("directory for", j)
action, resubmissions = error_mexc_dyes_v1.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,
cluster,
j,
xyzSmiles=True,
)
elif complete[num] == 2:
pos = complete[num] - 2
action, resubmissions = error_mexc_dyes_v1.main(
num,
method_opt,
basis_set_opt,
mem_com_opt,
mem_pbs_opt,
add_methods["methods"][pos],
add_methods["basis_set"][pos],
add_methods["mem_com"][pos],
add_methods["mem_pbs"][pos],
resubmissions,
delay,
cluster,
j,
xyzSmiles=False,
)
pos = complete[num] - 2
if pos >= 0:
dir_name = add_methods["methods"][pos].lower()
mexc_check_out = glob.glob("%s/mexc.o*" % dir_name)
mexc_check_out_complete = glob.glob("%s/*_o*" % dir_name)
if (
complete[num] < 3
and len(mexc_check_out) > 0
and len(mexc_check_out_complete) > 0
):
add_excitation_data(
dir_name,
"mexc",
add_methods["methods"][pos],
add_methods["basis_set"][pos],
)
mexc_check = []
if complete[num] < 2:
print(complete[num], i)
print(j)
os.chdir("..")
stage = 0
for k in range(len(complete)):
stage += complete[k]
# if stage == len(complete)*2:
if stage == len(complete) * add_methods_length:
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))
"""
qsub_funct
"""
time.sleep(min_delay)
for i in range(len(resubmissions)):
if resubmissions[i] < 2:
print("Not finished %d: %s" % (resubmissions[i], monitor_jobs[i]))
os.chdir("..")
return complete
def check_add_methods(add_methods, funct_name):
ln = len(add_methods["methods"])
if (
ln == len(add_methods["basis_set"])
and ln == len(add_methods["mem_com"])
and ln == len(add_methods["mem_pbs"])
):
return True
else:
print(
"\nadd_methods must have values that have lists of the same length.\nTerminating %s before start\n"
% funct_name
)
return False
def qsub(path="."):
print("qsub dir", path)
resetDirNum = len(path.split("/"))
if path != ".":
os.chdir(path)
pbs_file = glob.glob("*.pbs")[0]
cmd = "qsub %s" % pbs_file
print(os.getcwd(), "cmd", cmd)
failure = subprocess.call(cmd, shell=True)
if path != ".":
for i in range(resetDirNum):
os.chdir("..")
def add_qsub_dir(qsub_dir, geom_dir, path_qsub_queue="../../qsub_queue"):
if qsub_dir == "None":
return 0
elif qsub_dir == "./":
qsub_path = geom_dir + "\n"
else:
qsub_path = "%s/%s\n" % (geom_dir, qsub_dir)
print(os.getcwd(), qsub_path, "../../qsub_queue")
with open(path_qsub_queue, "a") as fp:
fp.write(qsub_path)
return 1
def qsub_to_max(max_queue=100, user=""):
with open("../qsub_queue", "r") as fp:
qsubs = fp.readlines()
# cmd = 'qstat -u %s > ../qsub_len' % user
# subprocess.call(cmd, shell=True)
# print("qsub_to_max", os.getcwd(), '../qsub_len', '../qsub_queue')
# with open('../qsub_len', 'r') as fp:
# current_queue = len(fp.readlines())-5
# os.remove('../qsub_len')
cmd = "qstat -u %s | wc -l > ../qsub_len" % user
subprocess.call(cmd, shell=True)
print("qsub_to_max", os.getcwd(), "../qsub_len", "../qsub_queue")
with open("../qsub_len", "r") as fp:
current_queue = int(fp.read()) - 5
os.remove("../qsub_len")
dif = max_queue - current_queue
print("dif is", dif)
if dif > 0:
cnt = 0
while cnt < dif and len(qsubs) > 0:
qsub_path = qsubs.pop(0)
qsub_path = qsub_path.rstrip().replace("\n", "")
print("\n", qsub_path, os.getcwd(), "\n")
qsub(qsub_path)
cnt += 1
with open("../qsub_queue", "w") as fp:
for i in qsubs:
fp.write(i)
return 1
def r_qsub_dir(method_mexc, solvent):
if method_mexc == "CAM-B3LYP":
qsub_dir = "mexc"
else:
qsub_dir = method_mexc.lower()
if solvent != "":
qsub_dir += "_%s" % solvent
return qsub_dir
def jobResubmit_v2(
monitor_jobs,
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,
cluster,
route="results",
add_methods={
"methods": [],
"basis_set": [],
"solvent": [],
"mem_com": [],
"mem_pbs": [],
},
max_queue=200,
results_json="results.json",
user=read_user(),
identify_zeros=False,
create_smiles=True,
):
"""
Modified from jobResubmit above
"""
if identify_zeros:
zeros_lst = []
if not os.path.exists("qsub_queue"):
subprocess.call("touch qsub_queue", shell=True)
if not check_add_methods(add_methods, "jobResubmit_v2"):
return []
add_methods_length = len(add_methods["methods"])
mol_lst = MoleculeList()
if os.path.exists("results.json"):
mol_lst.setData("results.json")
else:
mol_lst.sendToFile("results.json")
min_delay = min_delay * 60
# cluster_list = glob.glob("%s/*" % route)
complete = []
resubmissions = []
for i in range(len(monitor_jobs)):
complete.append(0)
resubmissions.append(2)
# resubmissions.append(resubmission_max)
calculations_complete = False
# comment change directory below in production
print(os.getcwd())
os.chdir(route)
for i in range(number_delays):
# time.sleep(min_delay)
for num, j in enumerate(monitor_jobs):
os.chdir(j)
delay = i
mexc_check = glob.glob("mexc")
if len(mexc_check) > 0:
complete[num] = 1
mexc_check_out = glob.glob("mexc/mexc.o*")
mexc_check_out_complete = glob.glob("mexc/*_o*")
if (
complete[num] < 2
and len(mexc_check_out) > 0
and len(mexc_check_out_complete) > 0
):
"""
#occVal, virtVal = ES_extraction.ES_extraction('mexc/mexc.out')
#if occVal == virtVal and occVal == 0:
# print(j)
mol = Molecule()
mol.setData('info.json')
#mol.setHOMO(occVal)
#mol.setLUMO(virtVal)
# Testing below
#mol.setExictations(absorpt('mexc/mexc.out', method_mexc, basis_set_mexc))
mol.toJSON()
mol.sendToFile('info.json')
#mol_lst.addMolecule(mol)
mol_lst = MoleculeList()
print(os.getcwd())
#mol_lst.setData("../../results.json")
mol_lst.setData("../../%s" % results_json)
mol_lst.updateMolecule(mol)
#mol_lst.sendToFile('../../results.json')
mol_lst.sendToFile('../../%s' % results_json)
"""
complete[num] = 2
# if complete[num] >= 2
if complete[num] < 1:
if identify_zeros:
zeros_lst.append(j)
print("directory for", j)
action, resubmissions, qsub_dir = error_mexc_dyes_v2.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,
cluster,
j,
xyzSmiles=create_smiles,
)
if qsub_dir != "None":
add_qsub_dir(qsub_dir.lower(), j)
if complete[num] <= 2:
for pos in range(add_methods_length):
test_dir = r_qsub_dir(
add_methods["methods"][pos], add_methods["solvent"][pos]
)
if not os.path.exists(test_dir):
print("add method", add_methods)
action, resubmissions, qsub_dir = error_mexc_dyes_v2.main(
num,
method_opt,
basis_set_opt,
mem_com_opt,
mem_pbs_opt,
add_methods["methods"][pos],
add_methods["basis_set"][pos],
add_methods["mem_com"][pos],
add_methods["mem_pbs"][pos],
resubmissions,
delay,
cluster,
j,
xyzSmiles=False,
solvent=add_methods["solvent"][pos],
)
# print(pos, os.getcwd())
if qsub_dir != "None":
add_qsub_dir(qsub_dir.lower(), j)
else:
complete[num] += 1
mexc_check = []
os.chdir("..")
stage = 0
for k in range(len(complete)):
stage += complete[k]
# if stage == len(complete)*2:
if stage == len(complete) * (add_methods_length + 2):
calculations_complete = True
qsub_to_max(max_queue, user)
# qsub_to_max(max_queue, 'r2652')
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))
"""
qsub_funct
"""
if identify_zeros:
print("identified zeros:", zeros_lst)
time.sleep(min_delay)
for i in range(len(resubmissions)):
if resubmissions[i] < 2:
print("Not finished %d: %s" % (resubmissions[i], monitor_jobs[i]))
os.chdir("..")
return complete
def gather_general_smiles(monitor_jobs, path_results="./results"):
os.chdir(path_results)
for i in monitor_jobs:
os.chdir(i)
out_files = glob.glob("*.out*")
if len(out_files) == 0:
print("NO OUT FILE")
return
last_out = out_files[0]
highest = 1
for i in range(len(out_files)):
t = out_files[i][-1]
if t == "t":
t = 1
else:
t = int(t)
if t > highest:
t = highest
last_out = out_files[i]
with open(last_out, "r") as fp:
lines = fp.readlines()
error_mexc_dyes_v1.find_geom(
lines, error=False, filename=last_out, imaginary=False, geomDirName=i
)
os.chdir("..")
def gather_excitation_data(
path_results,
monitor_jobs,
add_methods,
method_mexc,
basis_set_mexc,
baseName="mexc",
results_json="results.json",
exc_json=False,
):
if not check_add_methods(add_methods, "gather_excitation_data"):
return
pops = ""
for i in path_results:
if i == "/":
pops += "../"
mol_lst = MoleculeList_exc()
mol_lst.setData("%s" % results_json)
os.chdir(path_results)
# print(mol_lst)
failed = []
for i in monitor_jobs:
os.chdir(i)
if not os.path.exists("mexc/mexc.out"):
print(i, "does not have mexc/mexc.out")
os.chdir("..")
continue
if exc_json:
mol = Molecule_exc()
mol.setData("info.json")
else:
mol = Molecule()
mol.setData("info.json")
occVal, virtVal = ES_extraction.ES_extraction("mexc/mexc.out")
if occVal == 0 and occVal == 0:
print(i, "no data found in mexc/mexc.out\n")
failed.append(i)
os.chdir("..")
continue
mol.setHOMO(occVal)
mol.setLUMO(virtVal)
excitations = absorpt(
"mexc/mexc.out", method_mexc, basis_set_mexc, exc_json=True
)
if i == "5ed_16b_8ea":
print(i, excitations)
if excitations == []:
if i not in failed:
failed.append(i)
print(i, "\n")
os.chdir("..")
continue
mol.setExictations(excitations)
methods_len = len(add_methods["methods"])
for j in range(methods_len):
method = add_methods["methods"][j]
basis_set = add_methods["basis_set"][j]
lPath = "%s/%s.out" % (method.lower(), baseName)
if os.path.exists(lPath):
mol.appendExcitations(
absorpt(lPath, method, basis_set, exc_json=exc_json)
)
else:
if i not in failed:
failed.append(i)
# for j in range(methods_len):
# try:
# method = add_methods['methods'][j]
# basis_set = add_methods['basis_set'][j]
# mol.appendExcitations(absorpt('%s/%s.out' % (method.lower(), baseName), method, basis_set, exc_json=exc_json))
# except:
# if i not in failed:
# failed.append(i)
mol_lst.updateMolecule(mol, exc_json=exc_json)
os.chdir("..")
mol_lst.sendToFile("%s%s" % (pops, results_json))
print("FAILED:", failed)
return True
def clean_dir_name(dir_name):
return dir_name.replace("-", "").replace(",", "")
def main():
# print("\n\tstart\n")
three_types = [
"eDonors",
"backbones",
"eAcceptors",
] # Name of subdirectories holding the local structures
banned = [
"10b",
"11b",
"12b",
"13b",
"14b",
"15b",
"2b",
"3b",
"4b",
"5b",
"7b",
"8b",
"9b",
"TPA2",
]
banned = [
"10b",
"11b",
"12b",
"13b",
"14b",
"15b",
"2b",
"3b",
"4b",
"5b",
"7b",
"8b",
"9b",
"TPA2",
"26b",
"27b",
"28b",
"1ed",
"2ed",
"3ed",
"17b",
"19b",
"20b",
"21b",
"22b",
"7ed",
"8ed",
]
banned = [
"10b",
"11b",
"12b",
"13b",
"14b",
"15b",
"2b",
"3b",
"4b",
"5b",
"7b",
"8b",
"9b",
"TPA2",
]
# localStructuresDict = collectLocalStructures(three_types, banned) # p
# localStructuresDict = {'local1': [ ('N((BBD))(C1=CC=CC=C1)C2=CC=CC=C2', '2ed', 'N-methyl-N-phenylaniline'), ], 'local2': [ ('CC(C=C1)=CC=C1C(C2=C3SC4=C2SC5=C4C( C6=CC=C(C)C=C6)(C7=CC=C(C)C=C7)C8=C9C5=C(C=CC=C%10)C%10=C((BBA))C9=CC=C8)(C%11=CC=C(C)C=C%11)C%12=CC=CC%13=C((BBD))C%14=C(C=CC=C%14)C3=C%1 3%12', '26b', "9,9,19,19-tetra-p-tolyl-9,19-dihydrobenzo[10',1']phenanthro[3',4':4,5]thieno[3,2-b]benzo[10,1]phenanthro[3,4-d]thiophene"), ], 'local3': [('OC(C1=C(O)C=C(C#C(BBA))C=C1)=O', '11ea', '4-ethynyl-2-hydroxybenzoic acid'), ]}
# localStructuresDict = {'local1': [ ('C(BBD)(C=C1)=CC=C1N(C2=CC=CC=C2)C3=CC=CC=C3', '1ed', 'N-methyl-N-phenylaniline'), ], 'local2': [ ('C(BBA)1=C2C(N=CC=N2)=C((BBD))S1', '1b', "test"), ], 'local3': [('C(BBD)(C=C1)=CC=C1N(C2=CC=CC=C2)C3=CC=CC=C3', '1ea', 'acid'), ]}
# smiles_tuple_list = permutationDict(localStructuresDict)
# print("smiles_tuple_list", smiles_tuple_list)
"""
"""
resubmit_delay_min = 0.001
resubmit_max_attempts = 2
resubmit_delay_min = 60 * 6 # 60 * 12
resubmit_max_attempts = 120
# geometry optimization options
method_opt = "B3LYP"
# method_opt = "HF"
basis_set_opt = "6-311G(d,p)"
# basis_set_opt = "6-31G"
mem_com_opt = "1600" # mb
mem_pbs_opt = "10" # gb
# TD-DFT options
method_mexc = "CAM-B3LYP"
basis_set_mexc = "6-311G(d,p)"
mem_com_mexc = "1600" # mb
mem_pbs_mexc = "10" # gb"
# cluster='map'
cluster = "seq"
# comment for testing
# monitor_jobs = generateMolecules(smiles_tuple_list, method_opt, basis_set_opt,
# mem_com_opt, mem_pbs_opt, cluster)
"""
ds1 = ['3ed_11b_3ea', 'TPA2_4b_2ea', '7ed_6b_3ea',
'6ed_6b_3ea', '7ed_14b_3ea', '5ed_7b_1ea', '5ed_14b_1ea',
'2ed_13b_1ea', 'TPA2_14b_3ea', '1ed_3b_2ea',
'6ed_16b_1ea', '1ed_11b_1ea', '3ed_13b_2ea',
'TPA2_6b_3ea', '7ed_4b_2ea', '7ed_16b_2ea', '6ed_4b_2ea',
'1ed_1b_3ea', '1ed_9b_1ea', '3ed_8b_3ea', '2ed_8b_3ea',
'TPA2_16b_2ea', '3ed_15b_1ea', '7ed_2b_1ea', '6ed_2b_1ea',
'7ed_10b_1ea', '5ed_3b_3ea', 'TPA2_8b_2ea', '5ed_10b_3ea',
'1ed_15b_3ea', '2ed_6b_2ea', '3ed_6b_2ea', 'TPA2_10b_1ea',
'6ed_12b_3ea', '5ed_1b_2ea', '6ed_8b_2ea', '7ed_8b_2ea',
'TPA2_2b_1ea', '2ed_15b_2ea', '5ed_12b_2ea',
'6ed_10b_2ea', '1ed_5b_1ea', '2ed_4b_3ea', '3ed_4b_3ea',
'6ed_11b_2ea', '1ed_4b_1ea', '2ed_5b_3ea', '3ed_5b_3ea',
'1ed_16b_2ea', '5ed_13b_2ea', '2ed_14b_2ea',
'TPA2_3b_1ea', '6ed_9b_2ea', '7ed_9b_2ea', '2ed_7b_2ea',
'3ed_7b_2ea', 'TPA2_11b_1ea', '6ed_13b_3ea',
'1ed_14b_3ea', '5ed_11b_3ea', '2ed_16b_3ea',
'TPA2_9b_2ea', '7ed_3b_1ea', '6ed_3b_1ea', '7ed_11b_1ea',
'5ed_2b_3ea', '3ed_14b_1ea', '1ed_8b_1ea', '3ed_9b_3ea',
'2ed_1b_1ea', '3ed_1b_1ea', '2ed_9b_3ea', '7ed_5b_2ea',
'6ed_5b_2ea', 'TPA2_7b_3ea', '3ed_12b_2ea', '1ed_10b_1ea',
'TPA2_15b_3ea', '1ed_2b_2ea', '2ed_12b_1ea',
'5ed_15b_1ea', '7ed_7b_3ea', '6ed_7b_3ea', '7ed_15b_3ea',
'5ed_6b_1ea', 'TPA2_5b_2ea', '3ed_10b_3ea', '3ed_13b_1ea',
'6ed_4b_1ea', '7ed_16b_1ea', '7ed_4b_1ea', '5ed_5b_3ea',
'2ed_11b_3ea', '5ed_16b_3ea', '1ed_13b_3ea',
'TPA2_16b_1ea', '1ed_9b_2ea', '6ed_14b_3ea', '5ed_7b_2ea',
'TPA2_4b_1ea', '2ed_13b_2ea', '5ed_14b_2ea',
'1ed_11b_2ea', '6ed_16b_2ea', '1ed_3b_1ea', '3ed_2b_3ea',
'2ed_2b_3ea', 'TPA2_2b_2ea', '7ed_12b_3ea', '7ed_8b_1ea',
'6ed_8b_1ea', '5ed_1b_1ea', '5ed_9b_3ea', '5ed_12b_1ea',
'2ed_15b_1ea', 'TPA2_12b_3ea', '1ed_5b_2ea',
'6ed_10b_1ea', '3ed_15b_2ea', 'TPA2_8b_1ea',
'7ed_10b_2ea', '6ed_2b_2ea', '7ed_2b_2ea', '1ed_7b_3ea',
'TPA2_10b_2ea', '3ed_6b_1ea', '2ed_6b_1ea', '1ed_6b_3ea',
'TPA2_11b_2ea', '3ed_7b_1ea', '2ed_7b_1ea', '7ed_11b_2ea',
'6ed_3b_2ea', '7ed_3b_2ea', 'TPA2_9b_1ea', 'TPA2_1b_3ea',
'3ed_14b_2ea', '1ed_16b_1ea', 'TPA2_13b_3ea',
'1ed_4b_2ea', '6ed_11b_1ea', '2ed_14b_1ea', '5ed_13b_1ea',
'6ed_1b_3ea', '7ed_13b_3ea', '7ed_9b_1ea', '6ed_9b_1ea',
'7ed_1b_3ea', '5ed_8b_3ea', 'TPA2_3b_2ea', '3ed_16b_3ea',
'1ed_2b_1ea', '3ed_3b_3ea', '2ed_3b_3ea', '1ed_10b_2ea',
'5ed_15b_2ea', '2ed_12b_2ea', 'TPA2_5b_1ea', '5ed_6b_2ea',
'3ed_1b_2ea', '2ed_1b_2ea', '1ed_8b_2ea', '6ed_15b_3ea',
'1ed_12b_3ea', '2ed_10b_3ea', '6ed_5b_1ea', '7ed_5b_1ea',
'5ed_4b_3ea', '3ed_12b_1ea', '3ed_8b_1ea', '2ed_8b_1ea',
'6ed_14b_2ea', '1ed_1b_1ea', '1ed_9b_3ea', '1ed_13b_2ea',
'5ed_16b_2ea', '2ed_11b_2ea', 'TPA2_6b_1ea', '5ed_5b_2ea',
'6ed_16b_3ea', '2ed_2b_2ea', 'TPA2_14b_1ea', '3ed_2b_2ea',
'1ed_11b_3ea', '5ed_14b_3ea', '2ed_13b_3ea', '5ed_7b_3ea',
'7ed_6b_1ea', '7ed_14b_1ea', '6ed_6b_1ea', '3ed_11b_1ea',
'2ed_4b_1ea', 'TPA2_12b_2ea', '3ed_4b_1ea', '1ed_5b_3ea',
'7ed_12b_2ea', '5ed_9b_2ea', 'TPA2_2b_3ea', '1ed_15b_1ea',
'1ed_7b_2ea', '6ed_12b_1ea', 'TPA2_10b_3ea',
'5ed_10b_1ea', '5ed_3b_1ea', '7ed_2b_3ea', '7ed_10b_3ea',
'6ed_2b_3ea', '3ed_15b_3ea', '3ed_14b_3ea', 'TPA2_1b_2ea',
'5ed_2b_1ea', '7ed_3b_3ea', '7ed_11b_3ea', '6ed_3b_3ea',
'5ed_11b_1ea', '2ed_16b_1ea', '1ed_6b_2ea', '6ed_13b_1ea',
'TPA2_11b_3ea', '1ed_14b_1ea', '3ed_16b_2ea',
'TPA2_3b_3ea', '7ed_1b_2ea', '6ed_1b_2ea', '7ed_13b_2ea',
'5ed_8b_2ea', '2ed_5b_1ea', 'TPA2_13b_2ea', '3ed_5b_1ea',
'1ed_4b_3ea', '3ed_10b_1ea', '5ed_6b_3ea', '7ed_7b_1ea',
'7ed_15b_1ea', '6ed_7b_1ea', '2ed_12b_3ea', '5ed_15b_3ea',
'1ed_10b_3ea', '2ed_3b_2ea', 'TPA2_15b_1ea', '3ed_3b_2ea',
'5ed_4b_2ea', 'TPA2_7b_1ea', '2ed_10b_2ea', '1ed_12b_2ea',
'3ed_9b_1ea', '2ed_1b_3ea', '3ed_1b_3ea', '2ed_9b_1ea',
'6ed_15b_2ea', '1ed_8b_3ea', '3ed_2b_1ea', 'TPA2_14b_2ea',
'2ed_2b_1ea', '1ed_3b_3ea', '6ed_6b_2ea', '7ed_14b_2ea',
'7ed_6b_2ea', 'TPA2_4b_3ea', '3ed_11b_2ea', '1ed_13b_1ea',
'1ed_1b_2ea', '6ed_14b_1ea', '2ed_8b_2ea', 'TPA2_16b_3ea',
'3ed_8b_2ea', '2ed_11b_1ea', '5ed_16b_1ea', '5ed_5b_1ea',
'7ed_16b_3ea', '6ed_4b_3ea', '7ed_4b_3ea', 'TPA2_6b_2ea',
'3ed_13b_3ea', '3ed_6b_3ea', '2ed_6b_3ea', '6ed_12b_2ea',
'1ed_7b_1ea', '1ed_15b_2ea', '5ed_10b_2ea', 'TPA2_8b_3ea',
'5ed_3b_2ea', '6ed_10b_3ea', '3ed_4b_2ea', 'TPA2_12b_1ea',
'2ed_4b_2ea', '5ed_12b_3ea', '2ed_15b_3ea', '5ed_1b_3ea',
'5ed_9b_1ea', '7ed_12b_1ea', '7ed_8b_3ea', '6ed_8b_3ea',
'3ed_16b_1ea', '5ed_8b_1ea', '7ed_13b_1ea', '6ed_1b_1ea',
'7ed_9b_3ea', '6ed_9b_3ea', '7ed_1b_1ea', '2ed_14b_3ea',
'5ed_13b_3ea', '1ed_16b_3ea', '6ed_11b_3ea', '3ed_5b_2ea',
'TPA2_13b_1ea', '2ed_5b_2ea', '5ed_2b_2ea', 'TPA2_9b_3ea',
'TPA2_1b_1ea', '2ed_16b_2ea', '5ed_11b_2ea',
'1ed_14b_2ea', '3ed_7b_3ea', '2ed_7b_3ea', '6ed_13b_2ea',
'1ed_6b_1ea', '3ed_12b_3ea', 'TPA2_7b_2ea', '5ed_4b_1ea',
'6ed_5b_3ea', '7ed_5b_3ea', '2ed_10b_1ea', '6ed_15b_1ea',
'2ed_9b_2ea', '3ed_9b_2ea', '1ed_12b_1ea', '3ed_10b_2ea',
'TPA2_5b_3ea', '6ed_7b_2ea', '7ed_15b_2ea', '7ed_7b_2ea',
'3ed_3b_1ea', 'TPA2_15b_2ea', '2ed_3b_1ea', '1ed_2b_3ea']
"""
ds2 = [
"7ed_21b_6ea",
"7ed_21b_3ea",
"7ed_21b_8ea",
"7ed_21b_11ea",
"7ed_21b_5ea",
"7ed_21b_2ea",
"7ed_21b_7ea",
"7ed_21b_4ea",
"7ed_21b_10ea",
"7ed_21b_9ea",
"7ed_21b_1ea",
"7ed_20b_6ea",
"7ed_20b_3ea",
"7ed_20b_8ea",
"7ed_20b_11ea",
"7ed_20b_5ea",
"7ed_20b_2ea",
"7ed_20b_7ea",
"7ed_20b_4ea",
"7ed_20b_10ea",
"7ed_20b_9ea",
"7ed_20b_1ea",
"7ed_6b_6ea",
"7ed_6b_3ea",
"7ed_6b_8ea",
"7ed_6b_11ea",
"7ed_6b_5ea",
"7ed_6b_2ea",
"7ed_6b_7ea",
"7ed_6b_4ea",
"7ed_6b_10ea",
"7ed_6b_9ea",
"7ed_6b_1ea",
"7ed_26b_6ea",