DirIn = '../table/'
path_distrib_country = DirIn+'distribution_NLNRT_2020.tsv'
df_distrib = pd.read_csv(path_distrib_country, delimiter='\t', index_col=0)
df_distrib.reset_index(inplace=True)

path_data = '../table/'
df = pd.read_csv(path_data + 'table_aggregation_for_Raph_NLNRT.tsv', sep='\t')

dict_hist = {}
for HCAT2_name, list_cropcode in tqdm(zip(df.HCAT2_name.values, df.HCAT2_code_list.map(lambda x: [int(k) for k in x.split(';')]).values)):
    dict_hist[HCAT2_name] = df_distrib[df_distrib.HCAT2_code.isin(list_cropcode)].distrib.sum()
    
dfh = pd.DataFrame.from_dict(dict_hist, orient='index').sort_values(0, ascending=False)#.reset_index()

colors = np.array([mcolors.TABLEAU_COLORS['tab:blue']]*len(dfh))

dict_COI = {
'NLNRT' : ['green_silo_maize', 'potatoes','winter_common_soft_wheat', 'sugar_beet', 'spring_barley', 'grain_maize_corn_popcorn', 'spring_common_soft_wheat', 'winter_barley'],
'FRNRT' : ['winter_common_soft_wheat', 'grain_maize_corn_popcorn', 'green_silo_maize', 'winter_barley', 'winter_rapeseed_rape', 'sunflower', 'spring_barley', 'winter_triticale', 'beetroot_beets', 'millet_sorghum', 'winter_durum_hard_wheat', 'potatoes']
}
mask_COI = dfh.index.isin(dict_COI['NLNRT'])
colors[mask_COI] = mcolors.TABLEAU_COLORS['tab:green']

mask_COI = dfh.index.isin(['pasture_meadow_grassland', 'temporary_grass'])
colors[mask_COI] = mcolors.TABLEAU_COLORS['tab:red']

dfplot = dfh.reset_index().pivot(columns='index', values=0)[dfh.index]
dfplot.index = dfh.index

dfplot.plot.bar(color=colors, stacked=True, legend=None, log=True, figsize=(20,4), ylim=(1,6e5))

plt.xticks(rotation=60)
plt.ylabel('Samples')
plt.rc('xtick', labelsize=14) 
plt.xticks(horizontalalignment='right') 
plt.savefig('CropDeepTrans_Fig4_Distrib_NL.py', bbox_inches='tight')