#!/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
import geoxarray

figname = 'fig.map.flor1990-1860.png'
figsize = None#(8,4)
savefig = [False, True][1]
ylabel = None#'mm/day'
title = 'Mozambique mean annual precip max diff: FLOR1990-1860 [mm/day]'

plt.figure(figsize=figsize)

# 1860 
scale = 24*3600
ifile = 'data/FLOR.CTL1860_newdiag_tigercpu_intelmpi_18_576PE.precip.Mozambique.masked.nc'
da = xr.open_dataarray(ifile).sel(time=slice('0101', '1000'))
da1860 = da.groupby('time.year').max('time').mean('year').pipe(lambda x: x*scale)
#1990
ifile = 'data/FLOR.CTL1990_newdiag_tigercpu_intelmpi_18_576PE.precip.Mozambique.masked.nc'
da = xr.open_dataarray(ifile).sel(time=slice('0101', '1000'))
da1990 = da.groupby('time.year').max('time').mean('year').pipe(lambda x: x*scale)

daa = da1990 - da1860
daa.plot(cmap='Spectral')

if title is not None:
    plt.title(title)
if ylabel is not None:
    plt.ylabel(ylabel)

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