data_visualization.py

from email.mime import base
from bokeh.plotting import figure, save
from bokeh.models import ColumnDataSource, GeoJSONDataSource

import pandas as pd
import geopandas as gpd

def generate(shp_filename,nombre_destino):
    base_map = r"./datos/datasets/INEGI_2010/estatal.shp"
    population_dots = shp_filename

    points_gdf = gpd.read_file(population_dots)
    print(points_gdf.head)

    base_map_gdf = gpd.read_file(base_map)
    base_map_gdf.set_crs(epsg=6362, inplace=True)
    print(base_map_gdf.crs)

    base_map_gdf_correction = base_map_gdf.to_crs('epsg:4326')
    print(base_map_gdf_correction)


    points_to_plot_source = points_gdf[['LONGITUD','LATITUD']]
    print(points_to_plot_source)

    base_map_source = GeoJSONDataSource(geojson=base_map_gdf_correction.to_json())


    p = figure(title="Mapa de cobertura",plot_height = 700 ,
            plot_width = 1000,output_backend="webgl")
    print(p)


    p.multi_line('xs', 'ys', source=base_map_source, color='gray',
                    line_color = 'gray', 
                    line_width = 2)

    psource = ColumnDataSource(points_to_plot_source)
    # Initialize our plot figure
    # Add the points to the map from our 'psource' ColumnDataSource -object
    p.circle('LONGITUD', 'LATITUD', source=psource, color='red', size=3)

    outmap_route = "./maps/"+nombre_destino+".html"
    
    save(obj=p, filename=outmap_route, title='Localidades dentro de Cobertura')