import pandas as pd
import sys
import os
import numpy as np

args = sys.argv
ifile = args[1]
fn = os.path.basename(ifile)
#fpath = "/home/disk/rocinante/DATA/temp/kcp3/data/prismWRFhr/"
fpath = "/home/disk/rocinante/DATA/temp/kcp3/data/prismWRFnm/"
opath = "/home/disk/rocinante/DATA/temp/WRF/scripts/regrid_c2c/longwave/output/prismWRFcorr/"
#npath = "/home/disk/rocinante/DATA/temp/WRF/scripts/regrid_c2c/longwave/data/filter_elev.csv"

#s = fn.split('_')
#lat = "{:.5f}".format(round(float(s[1]),4))
#lon = "{:.5f}".format(round(float(s[2]),4))
#cfile = "{}/data_{}_{}".format(fpath, lat, lon)
#print(ifile)
#print(cfile)
cfile = "{}/{}".format(fpath, fn)

lapse = np.array([5.5, 5.5, 5.5, 5.0, 4.5, 4.0, 4.0, 4.0, 4.0, 4.5, 5.5, 5.5 ])
lapse /= -1000

df1 = pd.read_csv(ifile, header=None, sep=' ')
df2 = pd.read_csv(cfile, header=None, sep=' ')
dates = pd.to_datetime(df1[0], format='%m/%d/%Y-%H:%M:%S')
lr = [ lapse[x-1] for x in dates.dt.month]
df1[4] = df2[4]
df1[0] = df2[0]
df1['lp'] = lr

#nf = pd.read_csv(npath)
#nf[nf.jason_filename == ]

opath = "{}/{}".format(opath, fn)
df1.to_csv(opath, header=False, index=False, sep=' ')