#!/usr/bin/env python
# Wenchang Yang (wenchang@princeton.edu)
# Thu Jun  4 11:50:59 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
import xaddon
"""
from amipHadISST.fig_scatter_ntc_vs_all import get_scatter_data as get_scatter_data_hiram, scatterplot
from ERA5.fig_scatter_ntc_vs_all import get_scatter_data as get_scatter_data_era5
from IBTrACS.data_ntc_cycle import get_cycle as cycle_ntc
"""
from ERA5.fig_scatter_ntc_vs_all_mbasins import ds as ds_obs #ntc is from IBTrACS in ds_obs
from amipHadISST.fig_scatter_ntc_vs_all_mbasins import ds as ds_hiram
from AM2p5.fig_scatter_ntc_vs_all_mbasins import ds as ds_floram
from AM2p5C360.fig_scatter_ntc_vs_all_mbasins import ds as ds_floramplus
#
if __name__ == '__main__':
    tt.check('end import')
#
#start from here
"""
basin = 'NA'
years = slice('1980', '2018')
ds_obs = get_scatter_data_era5(basin=basin, years=years)
ds_obs['ntc_era5'] = ds_obs['ntc']
ds_obs['ntc'] = cycle_ntc(basin=basin, years=years)['mclim']
ds_hiram = get_scatter_data_hiram(basin=basin, years=years)
"""
def scatterplot(x=None, y=None, data=None, ax=None, 
    xlabel=None, ylabel=None, title=None, alpha=0.5, 
    tag=None, scatter_on=True, rg_on=True, **kws):
    if ax is None:
        ax = plt.gca()
    if tag is None:
        tag = ''
    if scatter_on:
        ax.scatter(x=x, y=y, data=data, alpha=0.5, s=20, **kws)
    ax.set_xlim(0, None)
    ax.set_ylim(0, None)
    if xlabel is not None:
        ax.set_xlabel(xlabel)
    if ylabel is not None:
        ax.set_ylabel(ylabel)
    if title is not None:
        ax.set_title(title, loc='left')

    # linear regression
    if rg_on:
        xx, yy = data[x], data[y]
        rg = yy.linregress.on(xx)
        ax.plot(xx, rg.predicted, color='k', alpha=.5)
        # text
        if rg.intercept.item()>=0:
            s = f'{tag}\ny={rg.slope.item():.1f}x $+$ {rg.intercept.item():.2f}\nr$^2$={rg.r.item()**2:.2f}'
        else:
            s = f'{tag}\ny={rg.slope.item():.1f}x $-$ {-rg.intercept.item():.2f}\nr$^2$={rg.r.item()**2:.2f}'
        ax.text(0.02, 1-0.02, s, ha='left', va='top', transform=ax.transAxes)
        #print(rg)

basins = ['NA', 'EP', 'WP', 'NI', 'SI'] 
 
if __name__ == '__main__':
    from wyconfig import * #my plot settings
    fig, axes = plt.subplots(4, 3, sharey=True, sharex='col', figsize=(7.5,6.5))
    suptitle = None #'Obs. (IBTrACS TC)'
    #figname = __file__.replace('.py', f'_{tt.today()}.png')

    #obs
    ds = ds_obs.stack(s=['basin', 'month'])

    ax = axes[0, 0]
    #scatterplot(ax=ax, xlabel='ERA5 p($\Lambda$)', ylabel='IBTrACS N_TC', x='p', y='ntc', data=ds)
    scatterplot(ax=ax, xlabel=None, ylabel='N_TC', x='p', y='ntc', data=ds, title=None, tag='(a)', color='.99', label=None)
    for basin in basins:
        scatterplot(ax=ax, x='p', y='ntc', data=ds.sel(basin=basin), rg_on=False, label=basin)

    ax = axes[0, 1]
    #scatterplot(ax=ax, xlabel='N_SEED', x='nseed', y='ntc', data=ds)
    scatterplot(ax=ax, xlabel=None, x='nseed', y='ntc', data=ds, tag='(b)', color='.99', label=None)
    for basin in basins:
        scatterplot(ax=ax, x='nseed', y='ntc', data=ds.sel(basin=basin), rg_on=False, label=basin)

    ax = axes[0, 2]
    #scatterplot(ax=ax, xlabel='N_SEED$\\times$p($\Lambda$)', x='nseedxp', y='ntc', data=ds)
    scatterplot(ax=ax, xlabel=None, x='nseedxp', y='ntc', data=ds, tag='(c)', color='.99', label=None)
    for basin in basins:
        scatterplot(ax=ax, x='nseedxp', y='ntc', data=ds.sel(basin=basin), rg_on=False, label=basin)
    ax.text(0.99, 0.01, 'Obs.', transform=ax.transAxes, ha='right', va='bottom')

    ds = ds_hiram.stack(s=['basin', 'month'])
    ax = axes[1, 0]
    #scatterplot(ax=ax, xlabel='p($\Lambda$)', ylabel='HiRAM N_TC', x='p', y='ntc', data=ds)
    scatterplot(ax=ax, xlabel=None, ylabel='N_TC', x='p', y='ntc', data=ds, title=None, tag='(d)', color='.99', label=None)
    for basin in basins:
        scatterplot(ax=ax, x='p', y='ntc', data=ds.sel(basin=basin), rg_on=False, label=basin)

    ax = axes[1, 1]
    scatterplot(ax=ax, xlabel=None, x='nseed', y='ntc', data=ds, tag='(e)', color='.99', label=None)
    for basin in basins:
        scatterplot(ax=ax, x='nseed', y='ntc', data=ds.sel(basin=basin), rg_on=False, label=basin)

    ax = axes[1, 2]
    scatterplot(ax=ax, xlabel=None, x='nseedxp', y='ntc', data=ds, tag='(f)', color='.99', label=None)
    for basin in basins:
        scatterplot(ax=ax, x='nseedxp', y='ntc', data=ds.sel(basin=basin), rg_on=False, label=basin)
    ax.text(0.99, 0.01, 'HiRAM', transform=ax.transAxes, ha='right', va='bottom')

    ds = ds_floram.stack(s=['basin', 'month'])
    ax = axes[2, 0]
    #scatterplot(ax=ax, xlabel='p($\Lambda$)', ylabel='HiRAM N_TC', x='p', y='ntc', data=ds)
    scatterplot(ax=ax, xlabel=None, ylabel='N_TC', x='p', y='ntc', data=ds, title=None, tag='(g)', color='.99', label=None)
    for basin in basins:
        scatterplot(ax=ax, x='p', y='ntc', data=ds.sel(basin=basin), rg_on=False, label=basin)

    ax = axes[2, 1]
    scatterplot(ax=ax, xlabel=None, x='nseed', y='ntc', data=ds, tag='(h)', color='.99', label=None)
    for basin in basins:
        scatterplot(ax=ax, x='nseed', y='ntc', data=ds.sel(basin=basin), rg_on=False, label=basin)

    ax = axes[2, 2]
    scatterplot(ax=ax, xlabel=None, x='nseedxp', y='ntc', data=ds, tag='(i)', color='.99', label=None)
    for basin in basins:
        scatterplot(ax=ax, x='nseedxp', y='ntc', data=ds.sel(basin=basin), rg_on=False, label=basin)
    ax.text(0.99, 0.01, 'AM2.5', transform=ax.transAxes, ha='right', va='bottom')

    ds = ds_floramplus.stack(s=['basin', 'month'])
    ax = axes[3, 0]
    #scatterplot(ax=ax, xlabel='p($\Lambda$)', ylabel='HiRAM N_TC', x='p', y='ntc', data=ds)
    scatterplot(ax=ax, xlabel='p($\Lambda$)', ylabel='N_TC', x='p', y='ntc', data=ds, title=None, tag='(j)', color='.99', label=None)
    for basin in basins:
        scatterplot(ax=ax, x='p', y='ntc', data=ds.sel(basin=basin), rg_on=False, label=basin)
    ax.set_xlim(0, 0.21)

    ax = axes[3, 1]
    scatterplot(ax=ax, xlabel='N_SEED', x='nseed', y='ntc', data=ds, tag='(k)', color='.99', label=None)
    for basin in basins:
        scatterplot(ax=ax, x='nseed', y='ntc', data=ds.sel(basin=basin), rg_on=False, label=basin)
    ax.set_xlim(0, 29)

    ax = axes[3, 2]
    scatterplot(ax=ax, xlabel='N_SEED$\\times$p($\Lambda$)', x='nseedxp', y='ntc', data=ds, tag='(l)', color='.99', label=None)
    for basin in basins:
        scatterplot(ax=ax, x='nseedxp', y='ntc', data=ds.sel(basin=basin), rg_on=False, label=basin)
    ax.set_xlim(0, 3)
    ax.set_ylim(0,7.6)
    ax.text(0.99, 0.01, 'AM2.5C360', transform=ax.transAxes, ha='right', va='bottom')

    if suptitle is not None:
        fig.suptitle(suptitle)
    axes[0, 2].legend(bbox_to_anchor=(1.02, 1.03), loc='upper right', frameon=True, borderpad=0.1)

    if len(sys.argv)>1 and sys.argv[1]=='savefig':
        figname = __file__.replace('.py', '.png')
        wysavefig(figname)

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