import sys, datetime, copy, os
from dateutil.relativedelta import relativedelta
import numpy as np; np.set_printoptions(threshold=sys.maxsize)
import matplotlib; matplotlib.use('Agg')
import matplotlib.pyplot as plt
import matplotlib.colors as clr
from mpl_toolkits.basemap import Basemap

import seaborn as sns
from matplotlib.colors import ListedColormap
from netCDF4 import Dataset

#nc   = Dataset('Out/FD_Char_1961-2020_1yrs_Daily_Reg_New.nc','r') #../NC/FD_Char_1961-2020_1yrs_Daily_Reg.nc','r')
nc   = Dataset('Out/R_T2m_Tx_Tm_7Stn_1961-2020.nc','r')

year = nc.variables['year'][:]
reg  = nc.variables['reg'][:]
mon  = nc.variables['mon'][:]
fd   = nc.variables['t2m'][:] ; varnm = "T2m"
#fd   = nc.variables['pr'][:] ; varnm = "R"

#regs = ['R1','R2','R3','R4','R5','R6','R7']

var  = ["Jan","Feb","Mar","Apr","May","Jun","Jul","Aug","Sep","Oct","Nov","Dec"]
regs = ['B1','B2','B3','B4','N1','N2','N3']

Max_All = [35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35]
aa = fd[:,:,:]
aax = round(np.nanmax(aa)); aam = round(np.nanmin(aa))

for i in range(len(mon)):
    fig, ax = plt.subplots(7,figsize=(6,12))
    plt.subplots_adjust(hspace=0.5)

    a = fd[:,i,:]
    amax = round(np.nanmax(a)); amin = round(np.nanmin(a))
#    amax = Max_All[i]; amin = 15
#    amax = aax; amin = aam + 3
    print (amax, amin)
    atext = amax * 4/5
    yticks = np.linspace(amin,amax,3)

    for k in range(len(reg)):
        x = year[:]  # day[0:30]
        y = fd[:,i,k] # sw1[0:30,k]
        fit = np.polyfit(x, y, 1)

        ax[k].scatter(x, y, s=20,c="blue",marker ="^")
        ax[k].set_ylim(amin,amax)
        ax[k].set_xlim(0,60)
   

        ax[k].plot(x, fit[0]*x + fit[1], 'r-')
#        ax[k].text(5, atext, 'y='+str(round(fit[0],2))+'*x + '+str(round(fit[1],2)))
#        ax[k].text(3, atext, 'y='+str(round(fit[0],2))+'*x + '+str(round(fit[1],2)))

#        ax[k].text(20, atext, 'y='+str(round(fit[0],2))+'*x + '+str(round(fit[1],2)),horizontalalignment='right', verticalalignment='top')
#        ax[k].text('y='+str(round(fit[0],2))+'*x + '+str(round(fit[1],2)),horizontalalignment='right', verticalalignment='top')
#        ax[k].set_title(regs[k])
        equa=regs[k]+': y='+str(round(fit[0],3))+'*x + '+str(round(fit[1],2))
#        ax[k].set_title(regs[k],str(equa))
        ax[k].set_title(equa)
        ax[k].set_yticks(yticks)

#    fig.suptitle("ABCDF")
    fig.savefig("Out/Trend_"+varnm+"_"+var[i]+".pdf", bbox_inches="tight", pad_inches=.05, dpi=600)

    plt.cla()
    plt.clf()
    plt.close()