Testpush

Geovisualization

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+import os
+import pandas as pd
+import bibtexparser
+import folium
+from concurrent.futures import ThreadPoolExecutor
+from tqdm import tqdm
+
+# Clear the terminal
+os.system('cls' if os.name == 'nt' else 'clear')
+
+# Pfade zu den Dateien
+geonames_file_path = 'allCountries.txt'
+bib_file_path = 'Research/Charité - Universitätsmedizin Berlin/Systematische Literaturrecherche/Literaturverzeichnis.bib'
+cleaned_bib_file_path = 'Research/Charité - Universitätsmedizin Berlin/Systematische Literaturrecherche/cleaned_Literaturverzeichnis.bib'
+
+# Spaltennamen laut Geonames README
+columns = [
+    'geonameid', 'name', 'asciiname', 'alternatenames', 'latitude', 'longitude',
+    'feature class', 'feature code', 'country code', 'cc2', 'admin1 code',
+    'admin2 code', 'admin3 code', 'admin4 code', 'population', 'elevation', 'dem',
+    'timezone', 'modification date'
+]
+
+# GeoNames-Daten laden
+print("Lade GeoNames-Daten...")
+geo_df = pd.read_csv(geonames_file_path, sep='\t', header=None, names=columns, usecols=['name', 'asciiname', 'latitude', 'longitude'])
+geo_df.dropna(subset=['latitude', 'longitude'], inplace=True)
+print("GeoNames-Daten geladen.")
+
+# BibTeX-Datei laden
+print("Lade BibTeX-Datei...")
+with open(bib_file_path, encoding='utf-8') as bibtex_file:
+    bib_database = bibtexparser.load(bibtex_file)
+print("BibTeX-Datei geladen.")
+
+# Ortsnamen extrahieren und bereinigen
+print("Extrahiere und bereinige Ortsnamen...")
+locations = set()
+for entry in bib_database.entries:
+    if 'address' in entry:
+        for loc in entry['address'].split(';'):
+            locations.update(loc.split(','))
+
+cleaned_locations = {loc.strip() for loc in locations}
+print("Ortsnamen extrahiert und bereinigt.")
+
+# Geo-Koordinaten zuordnen
+def find_coordinates(location):
+    match = geo_df[(geo_df['name'].str.lower() == location.lower()) | (geo_df['asciiname'].str.lower() == location.lower())]
+    if not match.empty:
+        return match.iloc[0]['latitude'], match.iloc[0]['longitude']
+    return None, None
+
+print("Suche Geo-Koordinaten...")
+location_coords = {}
+
+for location in tqdm(cleaned_locations, desc="Bearbeitung der Ortsnamen"):
+    latitude, longitude = find_coordinates(location)
+    if latitude is not None and longitude is not None:
+        location_coords[location] = (latitude, longitude)
+
+print("Geo-Koordinaten gefunden.")
+
+# Erstelle die Karte
+print("Erstelle Karte...")
+map_center = [geo_df['latitude'].mean(), geo_df['longitude'].mean()]
+map = folium.Map(location=map_center, zoom_start=2)
+
+for location, coords in location_coords.items():
+    folium.Marker(location=coords, popup=location).add_to(map)
+
+map_file_path = 'Research/Charité - Universitätsmedizin Berlin/Systematische Literaturrecherche/literature_map.html'
+map.save(map_file_path)
+print(f"Karte gespeichert unter {map_file_path}")
+
+# Bereinigen und Speichern der BibTeX-Datei
+print("Speichere bereinigte BibTeX-Datei...")
+with open(cleaned_bib_file_path, 'w', encoding='utf-8') as bibtex_file:
+    bibtexparser.dump(bib_database, bibtex_file)
+print(f"Bereinigte BibTeX-Datei gespeichert unter {cleaned_bib_file_path}")

Geovisualization copy.py

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+import os
+import bibtexparser
+import pandas as pd
+from tqdm import tqdm
+import folium
+from folium.plugins import Fullscreen
+
+# Terminal bereinigen
+os.system('cls' if os.name == 'nt' else 'clear')
+
+# Dateipfade
+geonames_file = 'allCountries.txt'
+bib_file = 'Research/Charité - Universitätsmedizin Berlin/Systematische Literaturrecherche/Literaturverzeichnis.bib'
+
+# Laden der GeoNames-Daten
+print("Laden der GeoNames-Daten...")
+geonames_columns = [
+    'geonameid', 'name', 'asciiname', 'alternatenames', 'latitude',
+    'longitude', 'feature class', 'feature code', 'country code', 'cc2',
+    'admin1 code', 'admin2 code', 'admin3 code', 'admin4 code', 'population',
+    'elevation', 'dem', 'timezone', 'modification date'
+]
+
+chunksize = 10**6
+geonames_data = pd.DataFrame()
+for chunk in tqdm(pd.read_csv(geonames_file, sep='\t', header=None, names=geonames_columns, chunksize=chunksize, dtype=str, encoding='utf-8')):
+    geonames_data = pd.concat([geonames_data, chunk], ignore_index=True)
+
+# Laden der BibTeX-Daten
+print("Laden der BibTeX-Daten...")
+with open(bib_file, encoding='utf-8') as bibtex_file:
+    bib_database = bibtexparser.load(bibtex_file)
+
+# Ortsnamen extrahieren und bereinigen
+print("Extrahieren und Bereinigen der Ortsnamen...")
+locations = set()
+for entry in bib_database.entries:
+    if 'address' in entry:
+        locations.update(entry['address'].replace(';', ',').replace('&', 'and').split(','))
+
+locations = {loc.strip() for loc in locations}
+print(f"Bereinigte Ortsnamen: {locations}")
+
+# Geo-Koordinaten zuordnen
+print("Zuordnen der Geo-Koordinaten...")
+geo_data = []
+for location in tqdm(locations):
+    matching_rows = geonames_data[geonames_data['name'].str.contains(location, case=False, na=False)]
+    if not matching_rows.empty:
+        best_match = matching_rows.iloc[0]
+        geo_data.append({
+            'name': location,
+            'latitude': best_match['latitude'],
+            'longitude': best_match['longitude']
+        })
+
+if not geo_data:
+    print("Keine gültigen Koordinaten gefunden.")
+else:
+    df = pd.DataFrame(geo_data)
+
+    # Karte erstellen
+    print("Erstellen der Karte...")
+    m = folium.Map(location=[0, 0], zoom_start=2)
+
+    for _, row in df.iterrows():
+        folium.Marker(
+            location=[row['latitude'], row['longitude']],
+            popup=row['name']
+        ).add_to(m)
+
+    # Vollbildmodus und LayerControl hinzufügen
+    Fullscreen(position='topright').add_to(m)
+    folium.LayerControl().add_to(m)
+
+    # Karte speichern
+    m.save('literature_map_with_zoom.html')
+    print("Karte wurde gespeichert als 'literature_map_with_zoom.html'.")