#!/usr/bin/env python
# Wenchang Yang (wenchang@princeton.edu)
# Wed Sep 18 23:01:01 EDT 2019
#import os.path, sys, os
import matplotlib.pyplot as plt
import xarray as xr, numpy as np, pandas as pd

figname = 'fig_ts_tropMean.png'

plt.figure(figsize=(8,4))

# ctl
label = 'CTL'
ifile = 'data/CTL1860_newdiag_tigercpu_intelmpi_18_576PE.t_surf.tropMean.0001-1000.nc'
da = xr.open_dataarray(ifile)
da.groupby('time.year').mean('time').plot(color='k', label=label)

# m6
label = '$-$6% solar'
ifile = 'data/m6p0sol_CTL1860_tigercpu_intelmpi_18_576PE.t_surf.tropMean.0101-0597.nc'
da = xr.open_dataarray(ifile)
da.groupby('time.year').mean('time').plot(label=label)

# p6
label = '+6% solar'
ifile = 'data/p6p0sol_CTL1860_tigercpu_intelmpi_18_576PE.t_surf.tropMean.0101-0400.nc'
da = xr.open_dataarray(ifile)
da.groupby('time.year').mean('time').plot(label=label)

# m6 recover
label = '$-$6% recover'
ifile = 'data/m6p0sol_CTL1860_recover0501_tigercpu_intelmpi_18_576PE.t_surf.tropMean.0501-0900.nc'
da = xr.open_dataarray(ifile)
da.groupby('time.year').mean('time').plot(label=label)

plt.legend()
plt.ylabel('Tropical Mean Ts [K]')

plt.tight_layout()
plt.savefig(figname, dpi=128)