#!/usr/bin/env python
# coding: utf-8

# In[ ]:


import sys, datetime, copy, os
from dateutil.relativedelta import relativedelta
import numpy as np; np.set_printoptions(threshold=sys.maxsize)

import pandas as pd
import matplotlib.pyplot as plt
import matplotlib.colors as clr

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

nc     = Dataset('/work/users/hmo/remoclic/Phuong/PHD/BC_2023/Tan/NC1/All_Cha_landpoints.nc','r') 
Chars  = nc.variables['cha'][:]
Model  = nc.variables['mem'][:]
Npoint = nc.variables['point'][:]
aph    = nc.variables['aph'][:]
org    = nc.variables['org'][:]
qm     = nc.variables['qm'][:]

xlabels = ["CNRM","CSIRO","ECEA","GFDL","HadG","MPI","ENS","ENS_1"]
title = ["DF","DD","DS","DI"]
#Amax = [ 7, 150, 4000, 85, 35, 35 ]
Amax = [ 20, 80, 100, 10 ]

Xlab=[]
Del1=[]
Del2=[]
Del3=[]
for i in range(0,len(xlabels)):
    del1=0 + i*2
    del2=2 + i*2
    del3=4 + i*2
    xlab=i+1
    Del1.append(del1)
    Del2.append(del2)
    Del3.append(del3)
    Xlab.append(xlab)

nbox = len(Chars)

fig, ax = plt.subplots(nbox,figsize=(10,8),sharey=False)
plt.subplots_adjust(hspace=0.4)
plt.subplots_adjust(top=0.8)

MDF = []
for k in range(len(Chars)):
    data1 = pd.DataFrame(aph[:,:,k]).assign(Trial='aph')
    data2 = pd.DataFrame(org[:,:,k]).assign(Trial='org')
    data3 = pd.DataFrame(qm[:,:,k]).assign(Trial='qm')
    
    data1[data1 == -99.0] = np.nan
    data2[data2 == -99.0] = np.nan
    data3[data3 == -99.0] = np.nan
    
    cdf = pd.concat([data1, data2, data3]) 
    mdf = pd.melt(cdf, id_vars=['Trial'], var_name=['Number'])
    MDF.append(mdf)
    
#    sns.boxplot(flierprops={"marker": "+"})
#    sns.boxplot(ax = ax[k], data = MDF[k], x = 'Number', y = 'value', hue = 'Trial', width = 0.5)
    sns.boxplot(ax = ax[k], data = MDF[k], x = 'Number', y = 'value', hue = 'Trial', flierprops={"marker": "+"}, width = 0.5)
    h,l = ax[0].get_legend_handles_labels()
    ax[k].get_legend().remove()
    
fig.legend(h,l, loc = "center right", fontsize = 10)
fig.savefig('Box_plot_Chars_test.pdf', bbox_inches="tight", pad_inches=.01, dpi=300)

############
#sns.boxplot(ax = ax[k], data = MDF[k], x = 'Number', y = 'value', hue = 'Trial', flierprops={"marker": "+"})
#    h,l = ax[0].get_legend_handles_labels()
#    ax[k].get_legend().remove()
    
#fig.legend(h,l, loc = "center right", fontsize = 20)