#!/usr/bin/env python
# Wenchang Yang (wenchang@princeton.edu)
# Mon Mar 24 11:50:41 AM EDT 2025
if __name__ == '__main__':
    import sys,os
    try:
        from misc.timer import Timer
        tt = Timer(f'[{os.getcwd()}] start ' + ' '.join(sys.argv))
    except:
        pass
import sys, os.path, os, glob, datetime
import xarray as xr, numpy as np, pandas as pd, matplotlib.pyplot as plt
#more imports
wython = '/tigress/wenchang/wython'
if wython not in sys.path: sys.path.append(wython); print('added to python path:', wython)
#from misc import get_kws_from_argv
import xfilter
#
if __name__ == '__main__':
    try:
        tt.check('end import')
    except:
        pass
#
#start from here
basin = """
global
WP
NA
""".split()[-1]
timeslice_ref = slice('1900', '1999')
yearslice_ref = slice(1900, 1999)
#timeslice_ref = slice('1351', '1550')
#yearslice_ref = slice(1351, 1550)
norm = lambda da: da/da.sel(year=yearslice_ref).mean('year')*100 - 100
norm_bound = lambda da: da/da_lizzie.sel(year=yearslice_ref).mean('year')*100 - 100
units = f'% of {timeslice_ref.start}-{timeslice_ref.stop} mean'
func_units = lambda da: da.assign_attrs(units=units, long_name='HU')
pct_diff = lambda da: da.sel(year=slice(1451, 1550)).mean('year') - da.sel(year=slice(1351,1450)).mean('year')
#lowpass
n_window = 40 #40 years
lowpass = lambda da: da.filter.lowpass(1/n_window, dim='year', padtype='even')

#seeds
ifile = '/projects/w/wenchang/analysis/TC/HIRAM/amipLMR2019SST0850ic_tigercpu_intelmpi_18_540PE/netcdf/tc_counts.seeds.ens01.0850-1999.minohour12.nc'
ds_sd = xr.open_dataset(ifile)

#spi
ifile = 'spi_HIRAM_amipLMR2019SST0850ic_tigercpu_intelmpi_18_540PE_ens01_0850-1999_NAmean.nc'
da = xr.open_dataarray(ifile)#.groupby('time.year').mean('time')
da = da.assign_coords(time=ds_sd.time)
da_spi = da #adjust for HU from TC
 
#pvi
ifile = 'pvi_HIRAM_amipLMR2019SST0850ic_tigercpu_intelmpi_18_540PE_ens01_0850-1999_NAmean.nc'
da = xr.open_dataarray(ifile)#.groupby('time.year').mean('time')
da = da.assign_coords(time=ds_sd.time)
da_pvi = da ** 2 #adjust for HU from TC
 
if __name__ == '__main__':
    from wyconfig import * #my plot settings
    fig,ax = plt.subplots()
   
    #seeds
    label = 'seeds'
    da = ds_sd[basin].groupby('time.month') * da_pvi.sel(time=timeslice_ref).groupby('time.month').mean('time')
    da = da.groupby('time.year').sum('time')
    da.pipe(norm).pipe(lowpass).pipe(func_units).plot(label=label, ax=ax)
 
	#spi
    label = 'SPI'
    da = da_spi.groupby('time.month') * da_pvi.sel(time=timeslice_ref).groupby('time.month').mean('time')
    da = da.groupby('time.year').sum('time')
    da.pipe(norm).pipe(lowpass).pipe(func_units).plot(label=label, ax=ax)

    ax.axhline(0, color='gray', ls='--')
    ax.legend() 
    ax.set_title(f'HiRAM seeds vs. SPI over the last millennium')
    ax.set_ylabel(units)
 
    #savefig
    if 'savefig' in sys.argv or 's' in sys.argv:
        figname = __file__.replace('.py', f'.png')
        if 'overwritefig' in sys.argv or 'o' in sys.argv:
            wysavefig(figname, overwritefig=True)
        else:
            wysavefig(figname)
 
    try:
        tt.check(f'**Done**')
    except:
        pass
    print()
    if 'notshowfig' in sys.argv or 'n' in sys.argv:
        pass
    else:
        if 'plt' in globals(): plt.show()