#!/usr/bin/env python
# -*- Mode: Python; coding: utf-8; indent-tabs-mode: nil; tab-width: 4 -*-

# Post-diagnostic of STATION_ASF /  L. Brodeau, 2019

import sys
#from os import path as path
#from string import replace
import math
import numpy as nmp
#import scipy.signal as signal
from netCDF4 import Dataset
import matplotlib as mpl
mpl.use('Agg')
import matplotlib.pyplot as plt
import matplotlib.dates as mdates
#from string import find
#import warnings
#warnings.filterwarnings("ignore")
#import time

#import barakuda_plot as bp
#import barakuda_tool as bt

reload(sys)
sys.setdefaultencoding('utf8')

cy1     = '2016' ; # First year 
cy2     = '2018' ; # Last year

dir_figs='.'
size_fig=(13,7)
fig_ext='png'

clr_red = '#AD0000'
clr_sat = '#ffed00'
clr_mod = '#008ab8'

rDPI=200.

L_ALGOS = [ 'COARE3p6' , 'ECMWF'   , 'NCAR' ]
l_color = [  '#ffed00' , '#008ab8' , '0.4'  ] ; # colors to differentiate algos on the plot
l_width = [     3      ,    2      ,  1     ] ; # line-width to differentiate algos on the plot
l_style = [    '-'     ,   '-'     , '--'   ] ; # line-style

L_VNEM  = [ 'qla'  , 'qsb'   , 'qt'   , 'qlw' , 'taum'  , 'dt_skin'  ]
L_VARO  = [  'Qlat'    ,   'Qsen'    ,  'Qnet'    ,  'Qlw'    , 'Tau'   , 'dT_skin'  ] ; # name of variable on figure
L_VARL  = [r'$Q_{lat}$',r'$Q_{sens}$',r'$Q_{net}$',r'$Q_{lw}$',r'$|\tau|$',r'$\Delta T_{skin}$' ] ; # name of variable in latex mode
L_VUNT  = [  r'$W/m^2$'   ,  r'$W/m^2$'    ,  r'$W/m^2$'   ,  r'$W/m^2$'  , r'$N/m^2$' ,   'K'     ]
L_VMAX  = [    75.     ,    75.      ,   800.     ,    25.    ,   1.2   ,   -0.7     ]
L_VMIN  = [  -250.     ,  -125.      ,  -400.     ,  -150.    ,   0.    ,    0.7     ]
L_ANOM  = [  True      ,   True      ,   True     ,   True    ,  True   ,  False     ]

nb_algos = len(L_ALGOS) ; print(nb_algos)

# Getting arguments:
narg = len(sys.argv)
if narg != 3:
    print 'Usage: '+sys.argv[0]+' <DIR_OUT_SASF> <year>'; sys.exit(0)
cdir_data = sys.argv[1]
cyyyy     = sys.argv[2]



# Files to be read:
cf_in = []
for ja in range(nb_algos): cf_in.append(cdir_data+'/output/'+'STATION_ASF-'+L_ALGOS[ja]+'_1h_'+cy1+'0101_'+cy2+'1231_gridT.nc')
print('Files we are goin to use:')
for ja in range(nb_algos): print(cf_in[ja])


# Getting time array from the first file:
id_in = Dataset(cf_in[0])
vt = id_in.variables['time_counter'][:]
cunit_t = id_in.variables['time_counter'].units ; print(' "time_counter" is in "'+cunit_t+'"')
id_in.close()
nbr = len(vt)




vtime = nmp.zeros(nbr)

vt = vt + 1036800. # BUG!??? don't get why false in epoch to date conversion, and yet ncview gets it right!
for jt in range(nbr): vtime[jt] = mdates.epoch2num(vt[jt])

ii=nbr/300
ib=max(ii-ii%10,1)
xticks_d=int(30*ib)

font_inf = { 'fontname':'Open Sans', 'fontweight':'normal', 'fontsize':14 }

nb_var = len(L_VNEM)

xF  = nmp.zeros((nbr,nb_algos))
xFa = nmp.zeros((nbr,nb_algos))





for jv in range(nb_var):
    print('\n *** Treating variable: '+L_VARO[jv]+' !')

    for ja in range(nb_algos):
        id_in = Dataset(cf_in[ja])
        xF[:,ja] = id_in.variables[L_VNEM[jv]][:,1,1] # only the center point of the 3x3 spatial domain!
        if ja == 0: cvar_lnm = id_in.variables[L_VNEM[jv]].long_name
        id_in.close()    
        #print('    => '+L_ALGOS[ja]+'  => ok!')


    fig = plt.figure(num = jv, figsize=size_fig, facecolor='w', edgecolor='k')

    ax1 = plt.axes([0.07, 0.22, 0.9, 0.75])

    ax1.set_xticks(vtime[::xticks_d])
    ax1.xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m-%d %H:%M:%S'))
    plt.xticks(rotation='60')

    for ja in range(nb_algos):
        plt.plot(vtime, xF[:,ja], '-', color=l_color[ja], linestyle=l_style[ja], linewidth=l_width[ja], label=L_ALGOS[ja], zorder=10+ja)

    ax1.set_ylim(L_VMIN[jv], L_VMAX[jv]) ; ax1.set_xlim(vtime[0],vtime[nbr-1])
    plt.ylabel(L_VARL[jv]+' ['+L_VUNT[jv]+']')
    
    ax1.grid(color='k', linestyle='-', linewidth=0.3)
    plt.legend(bbox_to_anchor=(0.45, 0.2), ncol=1, shadow=True, fancybox=True)
    ax1.annotate(cvar_lnm, xy=(0.3, 0.97), xycoords='axes fraction',  bbox={'facecolor':'w', 'alpha':1., 'pad':10}, zorder=50, **font_inf)
    plt.savefig(L_VARO[jv]+'.'+fig_ext, dpi=int(rDPI), transparent=False)
    plt.close(jv)



    if L_ANOM[jv]:

        for ja in range(nb_algos): xFa[:,ja] = xF[:,ja] - nmp.mean(xF,axis=1)

        # Want a symetric y-range that makes sense for the anomaly we're looking at:
        rmax = nmp.max(xFa) ; rmin = nmp.min(xFa)
        rmax = max( abs(rmax) , abs(rmin) )
        romagn = math.floor(math.log(rmax, 10)) ; # order of magnitude of the anomaly  we're dealing with
        rmlt = 10.**(int(romagn)) / 2.
        yrng = math.copysign( math.ceil(abs(rmax)/rmlt)*rmlt , rmax)
        #print 'yrng = ', yrng ;  #sys.exit(0)
        
        fig = plt.figure(num = 10+jv, figsize=size_fig, facecolor='w', edgecolor='k')
        ax1 = plt.axes([0.07, 0.22, 0.9, 0.75])
        
        ax1.set_xticks(vtime[::xticks_d])
        ax1.xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m-%d %H:%M:%S'))
        plt.xticks(rotation='60')
        
        for ja in range(nb_algos):
            plt.plot(vtime, xFa[:,ja], '-', color=l_color[ja], linewidth=l_width[ja], label=L_ALGOS[ja], zorder=10+ja)

        ax1.set_ylim(-yrng,yrng) ; ax1.set_xlim(vtime[0],vtime[nbr-1])
        plt.ylabel(L_VARL[jv]+' ['+L_VUNT[jv]+']')
        ax1.grid(color='k', linestyle='-', linewidth=0.3)
        plt.legend(bbox_to_anchor=(0.45, 0.2), ncol=1, shadow=True, fancybox=True)
        ax1.annotate('Anomaly of '+cvar_lnm, xy=(0.3, 0.97), xycoords='axes fraction',  bbox={'facecolor':'w', 'alpha':1., 'pad':10}, zorder=50, **font_inf)
        plt.savefig(L_VARO[jv]+'_anomaly.'+fig_ext, dpi=int(rDPI), transparent=False)
        plt.close(10+jv)