import xarray as xr

# 7 8 9 10 11 12 13 14 15 16
# 24 25 26

ds = xr.open_dataset('combined.nc')


#for i in [-99,4,10,11,12]:  # winds
#    for j in [-99,17,18,22,23,24,25]: # temp
for i in [-99] + list(range(4, 12)):
    for j in [-99] + list(range(17, 25)):
    #for j in range(0,1):
        if (i == -99) & (j == -99):
            continue
        print('WND: ', i, " tmax: ", j)
        dx = ds.where((ds.WND >= i) & (ds.tmx7 >= (j))).groupby('times.year').count(dim='times')
        dy = ds.where((ds.WND >= i) & (ds.tmx60 >= j)).groupby('times.year').count(dim='times')

        dfx = dx['WND'].to_dataframe().reset_index().drop(['x', 'y'], axis=1)
        dfy = dy['WND'].to_dataframe().reset_index().drop(['x', 'y'], axis=1)

        dfx = dfx[dfx.WND != 0]
        dfy = dfy[dfy.WND != 0]

        dfx.columns = ['year', 'lat', 'lon', 'value']
        dfy.columns = ['year', 'lat', 'lon', 'value']
        dfx['tmax_window'] = 7
        dfy['tmax_window'] = 60
        dfx['wind_thld'] = i
        dfy['wind_thld'] = i
        dfx['tmax_thld'] = j
        dfy['tmax_thld'] = j

        dfx.to_csv('data/wnd{}_t{}_{}.csv'.format(i, 7, j), index=False)
        dfy.to_csv('data/wnd{}_t{}_{}.csv'.format(i, 60, j), index=False)



#year lat lon rolling(7,60) tmax_threshold wind_threshold value