#essential imports
from SNAP.DiffIm import make_diff_image
from ContextManager import cd
from ObjData import *
#number of processors to use
nproc = 7
#reference files
band = ['B', 'V', 'I']
refs = ['../ref/' + Brefname, '../ref/' + Vrefname, '../ref/' + Irefname]
#current working directory
wd = os.getcwd()
#make directory for diff images
with cd(wd + "/../"):
if not os.path.isdir("diff"): os.mkdir('diff')
if not os.path.isdir("conv"): os.mkdir('conv')
#initialize multiprocess
pool = Pool(nproc)
queue = []
#for each band
for i in range(len(band)):
#get all band files
files = sorted(glob('../raw/' + prefix + band[i] + '*.fits'))
for n, filename in enumerate(files):
#output filename
diffname = '.'.join(filename.split('.')[:-1]) + ".diff.fits"
diffname = '../diff/' + '/'.join(diffname.split('/')[2:])
convname = '.'.join(filename.split('.')[:-1]) + ".conv.fits"
# Allen electronegativity
weights = [0.912,1.916,1.88,1.85,1.994,1.47]
# Covalent radii
#weights = [1.28,1.11,1.24,1.32,1.2,1.54]
####################################################################################################
# Train
####################################################################################################
if is_train:
for seed in SEED:
# This use the context manager to operate in the data directory
with cd(Name+f'-{seed}'):
pickle.dump(sym_params, open("sym_params.sav", "wb"))
logfile = open('log.txt','w+')
resultfile = open('result.txt','w+')
if os.path.exists('test.sav'):
logfile.write('Did not calculate symfunctions.\n')
else:
data_dict = snn2sav(db, Name, elements, params_set,
element_energy=element_energy)
train_dict = train_test_split(data_dict,1-test_percent,seed=seed)
train_val_split(train_dict,1-val_percent,seed=seed)
logfile.flush()
train_dict = torch.load('final_train.sav')
#essential modules
import os
from glob import glob
import subprocess
#essential imports
from ContextManager import cd
from MakeReg import makeReg
from ObjData import *
#current working directory
wd = os.getcwd()
#make directories
with cd(wd+"/../"):
if not os.path.isdir("raw"): os.mkdir('raw')
if not os.path.isdir("ref"): os.mkdir('ref')
#make reg file
makeReg(name+".reg", ra, dec)
#synchronize reference files from remote
os.system("rsync -tv "+rawfiles+"REF_Images/*.fits ../ref/")
#synchronize raw files from remote
os.system("rsync -tv "+rawfiles+"*.fz ../raw/")
#unpack files
with cd(wd+"/../raw/"):
filenames = sorted(glob(prefix+'*.fits.fz'))