import math
import geopandas as gpd
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import matplotlib as mpl
from matplotlib.lines import Line2D
from svgpathtools import svg2paths
from svgpath2mpl import parse_path


color_dict = {2022: "#CC5A43", 2004: "#5375D4", }

xy_ticklabel_color,color_map, h_line ='#101628','#D3D3D3', '#939AA1'

data = {
    "year": [2004, 2022, 2004, 2022, 2004, 2022],
    "countries" : ["Sweden", "Sweden", "Denmark", "Denmark", "Norway", "Norway"],
    "sites": [13,15,4,10,5,8]
}

df= pd.DataFrame(data)
df['diff']=df.groupby('countries')['sites'].diff().fillna(df.sites).astype(int)

df['sub_total'] = df.groupby('countries')['diff'].transform('sum')
#custom sort
sort_order_dict = {"Denmark":2, "Sweden":3, "Norway":1, 2004:5, 2022:4}
df = df.sort_values(by=['countries','year',], key=lambda x: x.map(sort_order_dict))
df['color']= df.year.map(color_dict)
df

icon_path, attributes = svg2paths('../flags/Unesco_World_Heritage_logo_notext_transparent.svg')
#matplotlib path object of the icon
icon_marker  = parse_path(attributes[0]['d'])

icon_marker.vertices -= icon_marker.vertices.mean(axis=0)
icon_marker = icon_marker.transformed(mpl.transforms.Affine2D().rotate_deg(180))
icon_marker = icon_marker.transformed(mpl.transforms.Affine2D().scale(-1,1))

# Get the NUTS2 GeoJSON here: https://github.com/eurostat/Nuts2json
url = "https://raw.githubusercontent.com/eurostat/Nuts2json/master/pub/v2/2021/3035/20M/0.json"
map_df = gpd.read_file(url,  layer='nutsrg')
map_df = map_df[map_df.id.isin(['NO','SE', 'DK']) ]

map_df

c:\Users\Ruth Pozuelo\Documents\SynologyDrive\100-matplotlib\.venv\Lib\site-packages\pyogrio\geopandas.py:275: UserWarning: More than one layer found in '0.json': 'nutsrg' (default), 'nutsbn', 'cntrg', 'cntbn', 'gra'. Specify layer parameter to avoid this warning.
  result = read_func(

fig = plt.figure(figsize=(15,10))
ax_map = fig.add_axes([0, 0, 1, 1])
map_df.plot(color=color_map,ax=ax_map)
ax_map.set_axis_off()

lat = [0.32,0.22,0.68]
lon = [0.5,0.14,0.28]

xmin_line =[1,1,0]
xmax_line =[2,2.5,-1]
y_line = -0.4

max_sites = df.sub_total.max()
matrix_rows = 3
matrix_columns = math.ceil(max_sites/ matrix_rows)
#create the matrix
x = np.repeat(np.arange(1, matrix_columns + 1), matrix_rows)
y = np.tile(np.arange(1, matrix_rows + 1), matrix_columns)

for i, (country, group) in enumerate(df.groupby("countries", sort = False)):
    axes_height = 0.2
    axes_width = 0.1
    #add the axes at lat and lon
    ax_matrix = fig.add_axes([lat[i] ,lon[i] , axes_width, axes_height]) 

    ax_matrix.set(xlim = (0,4), ylim = (0,6))

    symbol_color = np.insert( np.repeat(group.color, group['diff']), 0,  ["#FFFFFF"] * (max_sites - group.sub_total.iloc[0]))

    ax_matrix.scatter(
        y,
        x, 
        marker=icon_marker, 
        s=800,
        color= symbol_color
        )
    #add the x labels
    ax_matrix.set_xlabel(
            f'{group.countries.iloc[0]} {group.sub_total.iloc[0]}', 
            color =xy_ticklabel_color, 
            size =14, 
            )

    #add horizontal line
    ax_matrix.axhline( 
        y= y_line, 
        xmin = xmin_line[i], 
        xmax = xmax_line[i],
        lw = 1, 
        clip_on = False, 
        color = h_line
        )

    
    # hlines uses axes coordinates, convert to data coordinates
    x0, x1 = ax_matrix.get_xlim()
    x_end = x0 + xmax_line[i] * (x1 - x0)

    # add a circle at the end using scatter
    ax_matrix.scatter(
        x_end,            
        y_line,           
        s=20,             
        color=h_line,  
        fc = color_map,   
        zorder=3,         
        clip_on=False     
    )

    #add styling
    ax_matrix.grid(False)
    ax_matrix.set_frame_on(False)
    ax_matrix.tick_params(
        axis='both', 
        which='both',
        length = 0, 
        labelleft = False, 
        labelbottom = False
        )
fig

#add legend
text_legends = ["Before", "After"]
colors = df.color.unique()

lines = [Line2D([0], [0], color=c,  marker=icon_marker,linestyle='', markersize=20,) for c in colors]
labels  = [f'{text_legend} 2004' for  text_legend in text_legends]

for year in df.year.unique():
    fig.legend( 
        lines,
        labels,   
        labelcolor=xy_ticklabel_color,
        bbox_to_anchor=(0.5, -0.05), 
        loc="lower center",
        ncols = 2,
        frameon=False, 
        fontsize= 12
        )

fig

	id	na	geometry	country
33	DK	Danmark	MULTIPOLYGON (((4649929.995 3564341.094, 46459...	DK
34	SE	Sverige	MULTIPOLYGON (((4968534.919 4802763.317, 49724...	SE
36	NO	Norge	MULTIPOLYGON (((5121937.289 5303632.941, 51295...	NO

Generate the data and import packages¶

Get the map¶

Plot the map¶

Plot the matrices on the map¶

Add legends¶

Find me here

	year	countries	sites	diff	sub_total	color
5	2022	Norway	8	3	8	#CC5A43
4	2004	Norway	5	5	8	#5375D4
3	2022	Denmark	10	6	10	#CC5A43
2	2004	Denmark	4	4	10	#5375D4
1	2022	Sweden	15	2	15	#CC5A43
0	2004	Sweden	13	13	15	#5375D4