def cal_plot(name, args, ints, conc, slope, intercept, r):
plt.figure()
plt.plot(conc, slope*conc + intercept, 'k-')
plt.plot(conc, ints, 'o', ms=8)
text_string = 'Slope: {:.2f}\nIntercept: {:.2f}\nR^2: {:.5f}'
plt.text(0.5, ints.max()*0.8, text_string.format(slope, intercept, r**2))
plt.savefig(os.path.join(args.cal_folder, name+'_cal_curve'), dpi=200)
plt.close()
if __name__ == '__main__':
h5f, table = cal_h5_build(args)
refs, ref_files = cal_file('calibration.csv')
gcms.clear_png(args.cal_folder)
if args.nproc == 1:
aias = [aia_build(i) for i in ref_files]
else:
p = Pool(args.nproc)
aias = p.map(aia_build, ref_files)
aias = dict( zip(ref_files, aias) )
for name in refs:
int_extract(name, refs[name], aias, args)
h5f.flush()
h5f.close()
files = os.listdir(args.data_folder)
files = [f for f in files if f[-3:] == 'CDF']
if args.cal_type == 'internal':
std_cons = {}
f = open('data.csv')
next(f)
for line in f:
if line[0] == '#': continue
elif line.isspace(): continue
sp = line.split(',')
std_cons[sp[0]] = float(sp[1])
f.close()
gcms.clear_png(args.data_folder)
if args.nproc > 1:
pool = Pool(args.nproc)
for fs in chunker(files, args.nproc):
if args.nproc > 1:
aias = pool.map(aia_proc, fs)
else:
aias = [ aia_proc(fs[0]), ]
for aia in aias:
f = os.path.split(aia.filename)[-1]
name = f[:-4]
