Integrating weather events into TLO

pyproject.toml

@@ -60,6 +60,8 @@ dev = [
     "pyinstrument>=4.3",
     # Building requirements files
     "pip-tools",
+    "shapely", 
+    "geopandas"
 ]
 
 [project.scripts]

requirements/base.txt

@@ -62,6 +62,8 @@ et-xmlfile==1.1.0
     # via openpyxl
 fonttools==4.42.1
     # via matplotlib
+geopandas==1.0.1
+    # via tlo (pyproject.toml)
 gitdb==4.0.10
     # via gitpython
 gitpython==3.1.36
@@ -137,6 +139,10 @@ requests-oauthlib==1.3.1
     # via msrest
 scipy==1.10.1
     # via tlo (pyproject.toml)
+shapely==2.1.0
+    # via
+    #   geopandas
+    #   tlo (pyproject.toml)
 six==1.16.0
     # via
     #   azure-core

requirements/dev.txt

@@ -45,6 +45,8 @@ cachetools==5.3.1
 certifi==2023.7.22
     # via
     #   msrest
+    #   pyogrio
+    #   pyproj
     #   requests
 cffi==1.15.1
     # via cryptography
@@ -90,6 +92,8 @@ filelock==3.12.4
     #   virtualenv
 fonttools==4.42.1
     # via matplotlib
+geopandas==1.0.1
+    # via tlo (pyproject.toml)
 gitdb==4.0.10
     # via gitpython
 gitpython==3.1.36
@@ -128,9 +132,12 @@ msrestazure==0.6.4
 numpy==1.24.4
     # via
     #   contourpy
+    #   geopandas
     #   matplotlib
     #   pandas
+    #   pyogrio
     #   scipy
+    #   shapely
     #   tlo (pyproject.toml)
 oauthlib==3.2.2
     # via requests-oauthlib
@@ -139,12 +146,16 @@ openpyxl==3.1.0
 packaging==23.1
     # via
     #   build
+    #   geopandas
     #   matplotlib
+    #   pyogrio
     #   pyproject-api
     #   pytest
     #   tox
 pandas==2.0.3
-    # via tlo (pyproject.toml)
+    # via
+    #   geopandas
+    #   tlo (pyproject.toml)
 pillow==10.0.1
     # via matplotlib
 pip-tools==7.3.0
@@ -173,8 +184,12 @@ pyjwt[crypto]==2.8.0
     #   pyjwt
 pylint==3.0.1
     # via tlo (pyproject.toml)
+pyogrio==0.10.0
+    # via geopandas
 pyparsing==3.1.1
     # via matplotlib
+pyproj==3.7.1
+    # via geopandas
 pyproject-api==1.6.1
     # via tox
 pyproject-hooks==1.0.0
@@ -210,6 +225,10 @@ ruff==0.0.292
     # via tlo (pyproject.toml)
 scipy==1.10.1
     # via tlo (pyproject.toml)
+shapely==2.1.0
+    # via
+    #   geopandas
+    #   tlo (pyproject.toml)
 six==1.16.0
     # via
     #   azure-core

src/scripts/climate_disruptions/assigning_location_based_on_density.py

@@ -0,0 +1,43 @@
+import pandas as pd
+import geopandas as gpd
+from shapely.geometry import Point
+from pathlib import Path
+import os
+
+
+resourcefilepath = '/Users/rem76/PycharmProjects/TLOmodel/resources'
+
+
+worldpop_density_data = pd.read_csv(
+    Path(resourcefilepath) /'climate_change_impacts' / 'mwi_pd_2020_1km_ASCII_XYZ_worldpop.csv',
+)
+
+print(worldpop_density_data.head())
+
+worldpop_density_data['Z'] = pd.to_numeric(worldpop_density_data['X'], errors='coerce')
+worldpop_density_data['Y'] = pd.to_numeric(worldpop_density_data['Y'], errors='coerce')
+worldpop_density_data['Z'] = pd.to_numeric(worldpop_density_data['Z'], errors='coerce')
+
+geometry = [Point(xy) for xy in zip(worldpop_density_data['X'], worldpop_density_data['Y'])]
+worldpop_gdf = gpd.GeoDataFrame(worldpop_density_data, geometry=geometry, crs="EPSG:4326")
+
+malawi_admin2 = gpd.read_file(
+    Path(resourcefilepath) / 'mapping' / 'ResourceFile_mwi_admbnda_adm2_nso_20181016.shp')
+
+worldpop_gdf.set_crs("EPSG:4326", inplace=True)
+malawi_admin2.set_crs("EPSG:4326", inplace=True)
+
+print(worldpop_gdf.crs)
+print(malawi_admin2.crs)
+worldpop_gdf = worldpop_gdf.to_crs(malawi_admin2.crs)
+
+joined = gpd.sjoin(worldpop_gdf, malawi_admin2[['ADM2_EN', 'geometry']], how='left', predicate='within')
+
+joined['Z_prop'] = joined.groupby('ADM2_EN')['Z'].transform(lambda x: x / x.sum())
+
+print(joined)
+
+joined.to_file(
+    Path(resourcefilepath) / 'climate_change_impacts'/'worldpop_density_with_districts.shp',
+    driver='ESRI Shapefile'
+)