#!/usr/bin/env python
# Wenchang Yang (wenchang@princeton.edu)
# Wed Jul  1 21:41:03 EDT 2020
if __name__ == '__main__':
    from misc.timer import Timer
    tt = Timer(f'start {__file__}')
import sys, os.path, os, glob
import xarray as xr, numpy as np, pandas as pd
#import matplotlib.pyplot as plt
#more imports
#
if __name__ == '__main__':
    tt.check('end import')
#
#start from here
thisdir = os.path.dirname(__file__)
#ifile = os.path.join(thisdir, 'ts.historical_ssp585.1850-2100.ens26.ocean.tc.nc')
ifile = os.path.join(thisdir, 'ts.past1000.0850-1849.ens02.ocean.tc.nc')
 
 
if __name__ == '__main__':
    from wyconfig import * #my plot settings
    with xr.open_dataset(ifile) as ds:
        HU = ds.HU
        PDI = ds.PDI
    years_base = slice(1800,1849) # slice(1981, 2000)
    years_warm = slice(850, 1849) # slice(2081, 2100)

    #HU
    fig, ax = plt.subplots()
    da = HU
    data_name = 'HU'
    da_mean = da.sel(year=years_base).mean('year')
    da_pct = (da/da_mean - 1)*100
    for model in HU.model:
        da.sel(model=model).plot(color='C0', alpha=0.1, lw=1)
    da.mean('model').plot(color='C0', lw=2)
    figname = __file__.replace('.py', f'.line.{data_name}.{tt.today()}.png')
    plt.savefig(figname)
    print('**saved**:', figname)

    """
    fig, ax = plt.subplots(figsize=(6, 5))
    da_base = da.sel(year=years_base).mean('year') 
    da_warm = da.sel(year=years_warm).mean('year')
    da_diff = (da_warm - da_base)/da_base*100 #pct
    da_diff.sortby(da_diff).to_pandas().plot.barh(ax=ax)
    ax.invert_yaxis()
    ax.axvline(0, color='gray')
    ax.set_ylabel('')
    ax.set_xlabel(f'{data_name} change from {years_base.start}-{years_base.stop} to {years_warm.start}-{years_warm.stop} [%]')
    figname = __file__.replace('.py', f'.bar.{data_name}.{tt.today()}.png')
    plt.savefig(figname)
    print('**saved**:', figname)
    """

    #PDI
    fig, ax = plt.subplots()
    da = PDI
    data_name = 'PDI'
    da_mean = da.sel(year=years_base).mean('year')
    da_pct = (da/da_mean - 1)*100
    for model in HU.model:
        da.sel(model=model).plot(color='C0', alpha=0.1, lw=1)
    da.mean('model').plot(color='C0', lw=2)
    figname = __file__.replace('.py', f'.line.{data_name}.{tt.today()}.png')
    plt.savefig(figname)
    print('**saved**:', figname)

    """
    fig, ax = plt.subplots(figsize=(6, 5))
    da_base = da.sel(year=years_base).mean('year') 
    da_warm = da.sel(year=years_warm).mean('year')
    da_diff = (da_warm - da_base)/da_base*100 #pct
    da_diff.sortby(da_diff).to_pandas().plot.barh(ax=ax)
    ax.invert_yaxis()
    ax.axvline(0, color='gray')
    ax.set_ylabel('')
    ax.set_xlabel(f'{data_name} change from {years_base.start}-{years_base.stop} to {years_warm.start}-{years_warm.stop} [%]')
    figname = __file__.replace('.py', f'.bar.{data_name}.{tt.today()}.png')
    plt.savefig(figname)
    print('**saved**:', figname)
    """

    tt.check(f'**Done**')
    plt.show()