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('../NC/FD_Char_1961-2020_1yrs_Daily_Reg_New.nc','r') #FD_Char_1961-2020_1yrs_Daily_Reg.nc','r')
cha  = nc.variables['cha'][:]
year = nc.variables['year'][:]
reg  = nc.variables['reg'][:]
fd   = nc.variables['fd'][:]

#xlabels = ['R1','R2','R3','R4','R5','R6','R7']
#title = ["Num of FD event","Mean Duration (day)","Mean Severity (%)","Onset Mean Decline Speed (%/pentad)","Rate of Depletion (%)","Intensity (%/day)"]

xlabels = ['B1','B2','B3','B4','N1','N2','N3']
title = ["So dot han","Do dai trung binh (ngay)","Do khac nghiet trung binh (%)","Toc do sut giam trung binh giai doan khoi phat (%/pentad)","Toc do suy kiet trung binh (%)","Cuong do (%/ngay)"]
Amax = [ 7, 150, 4000, 85, 35, 35 ]

nbox = len(cha)
#fig, ax = plt.subplots(nbox,figsize=(6,10),sharey=False)
fig, ax = plt.subplots(nbox,figsize=(8,10),sharey=False)
plt.subplots_adjust(hspace=0.4)
plt.subplots_adjust(top=1)
#plt.subplots_adjust(left=0.01)
#plt.subplots_adjust(right=0.02)

for k in range(len(cha)):
    data = (fd[:,k,:])
#    ymax = round(np.nanmax(data)); ymin = round(np.nanmin(data))
    ymax = Amax[k]; ymin = 0 
    yticks = np.linspace(ymin,ymax,5)
    ax[k].boxplot(data, sym='k+')
#    ax[k].set_title('var'+str(k+1))
    ax[k].set_title(title[k])
    ax[k].set_xticklabels(xlabels)

    ax[k].set_yticks(yticks)

#plt.show()
fig.savefig('box_reg_new.pdf', bbox_inches="tight", pad_inches=.05, dpi=600)