Modularize - split app.py

app.py

@@ -2,113 +2,19 @@ import gradio as gr
 import geopandas as gpd
 import pandas as pd
 import os
-import matplotlib.pyplot as plt
-from arcgis.features import FeatureLayer
-from arcgis.geometry import Geometry
-from shapely.geometry import shape
+#import matplotlib.pyplot as plt
+#from arcgis.features import FeatureLayer
+#from arcgis.geometry import Geometry
+#from shapely.geometry import shape
 from shapely.ops import unary_union
 #from datasets import load_dataset
 
 #ds = load_dataset('psalama/NYC_sensitive_sites', data_files=data_files)
 
+# Import functions from modules in data.py and plot.py
+from data import get_gdf_from_feature_layer, process_buildings, get_max_extent
+from plot import create_plot
 
-def get_gdf_from_feature_layer(url):
-    # Access the ArcGIS feature layer
-    feature_layer = FeatureLayer(url)
-
-    # Use the query() method to get all features where 'Borough' is 'MN'
-    sdf = feature_layer.query(where="Borough='MN'", out_sr=4326, as_df=True)
-    
-    # Convert the 'SHAPE' column from ArcGIS's JSON-based format into a Shapely geometry
-    sdf['geometry'] = sdf['SHAPE'].apply(lambda x: Geometry(x).as_shapely)
-    
-    # Convert the SpatialDataFrame to a GeoDataFrame
-    gdf = gpd.GeoDataFrame(sdf, geometry='geometry')
-    
-    return gdf
-
-
-def process_buildings(input_gdf, sensitive_sites_gdf, default_building_height_m, multiplier_factor):
-    # List to store all intersected sensitive sites
-    intersected_sites = []
-    
-    # List to store all buffers
-    buffers = []
-
-    intersection_desc = ""
-    
-    # Iterate over each building in the input file
-    for idx, building in input_gdf.iterrows():
-        building_name = building.get('building_name', 'Unnamed building')
-        
-        # If the 'building_height' field exists and its value is not null or zero for this building,
-        # use it as the building height. Otherwise, use the default building height provided by the user.
-        if 'building_height' in building and pd.notnull(building['building_height']) and building['building_height'] != 0:
-            building_height_m = building['building_height'] * 0.3048
-        else:
-            building_height_m = default_building_height_m
-
-        buffer_distance_m = building_height_m * multiplier_factor
-
-        # Convert building's geometry to EPSG:3857 for accurate meter-based distance measurement
-        building_geometry = gpd.GeoSeries([building['geometry']], crs="EPSG:4326")
-        building_geometry_m = building_geometry.to_crs("EPSG:3857")
-
-        # Create a buffer around the building and convert it to a GeoDataFrame
-        building_buffer = building_geometry_m.buffer(buffer_distance_m)
-        building_buffer_gdf = gpd.GeoDataFrame(geometry=building_buffer, crs="EPSG:3857")
-        building_buffer_gdf = building_buffer_gdf.to_crs("EPSG:4326")
-
-        # Convert back to feet for storing and printing, rounding to the nearest foot
-        building_height_ft = round(building_height_m / 0.3048)
-        buffer_distance_ft = round(buffer_distance_m / 0.3048)
-
-        # Assign additional attributes
-        building_buffer_gdf['building_name'] = building_name
-        building_buffer_gdf['building_height'] = building_height_ft
-        building_buffer_gdf['buffer_distance'] = buffer_distance_ft
-
-        buffers.append(building_buffer_gdf)
-
-        # Check if the buffer intersects with any sensitive sites
-        intersects = gpd.overlay(building_buffer_gdf, sensitive_sites_gdf, how='intersection')
-        
-        if not intersects.empty:
-            building_intersect_desc = f"Building {idx} ({building_name}), height: {building_height_ft}, buffer distance: {buffer_distance_ft} is in the vicinity of a sensitive site."
-            intersected_sites.append(intersects)
-        else:
-            building_intersect_desc = f"Building {idx} ({building_name}), height: {building_height_ft}, buffer distance: {buffer_distance_ft} is not in the vicinity of any sensitive sites."
-
-        if intersection_desc == "":
-            intersection_desc = building_intersect_desc
-        else:
-            intersection_desc += "\n" + building_intersect_desc
-    
-    return buffers, intersected_sites, intersection_desc
-
-def get_max_extent(*gdfs): # takes in unlimited number of gdfs and calculates max/min xy extents
-    minx = min(gdf.total_bounds[0] for gdf in gdfs)
-    miny = min(gdf.total_bounds[1] for gdf in gdfs)
-    maxx = max(gdf.total_bounds[2] for gdf in gdfs)
-    maxy = max(gdf.total_bounds[3] for gdf in gdfs)
-    
-    return minx, miny, maxx, maxy
-
-def create_plot(filename, extent, *gdfs): # takes in unlimited number of gdfs
-    fig, ax = plt.subplots(figsize=(10, 8)) #Sets image size by width & height (in inches)
-    
-    colors = ['tan', 'mediumseagreen', 'thistle', 'lightcoral', 'sienna', 'yellow'] # Extend/improve this list as needed
-
-    for idx, gdf in enumerate(gdfs):
-        gdf.plot(ax=ax, color=colors[idx % len(colors)]) # Cycle through colors
-
-    ax.set_xlim(extent[0], extent[2])
-    ax.set_ylim(extent[1], extent[3])
-
-    # Hide axes
-    ax.axis('off')
-
-    plt.savefig(filename, bbox_inches='tight', pad_inches=0) # remove padding
 
 def ss_intersect(geojson1, ss_geoselect, multiplier_factor, default_building_height): 
     # Read the GeoJSON files