Update app.py

app.py

@@ -170,6 +170,108 @@ def interpolation_geojson(json_file, chem_symbol, lat_min, lat_max, long_min, lo
     except Exception as e:
         return {"message": f"An error occurred: {str(e)}"}
 
+
+def plot_high_value_points(geojson_file, chem_symbol, lat_min, lat_max, long_min, long_max, threshold):
+    """
+    Plots points on a map for geochemical data that have values higher than a specified threshold.
+    Also calculates and includes statistics (mean, mode, median, std deviation, variance) of the chemical values.
+
+    Parameters:
+    - geojson_file (str): The file path to the GeoJSON file containing geochemical data.
+    - chem_symbol (str): The chemical symbol to visualize.
+    - lat_min (float): The minimum latitude value.
+    - lat_max (float): The maximum latitude value.
+    - long_min (float): The minimum longitude value.
+    - long_max (float): The maximum longitude value.
+    - threshold (float): The threshold value for chemical concentration in ppm.
+
+    Returns:
+    - dict: A dictionary containing the message and HTML content of the generated map.
+            {
+                "message": str,
+                "html": str (optional)
+            }
+    """
+    # Define lat/long limits
+    lat_limits = (lat_min, lat_max)
+    long_limits = (long_min, long_max)
+
+    try:
+        # Load GeoJSON data
+        gdf = gpd.read_file(geojson_file)
+        
+        # Check if the chemical symbol exists in the data
+        if chem_symbol not in gdf.columns:
+            return {"message": f"Error: Chemical symbol '{chem_symbol}' not found in the data."}
+        
+        # Filter data for the specified lat/long limits
+        gdf = gdf[(gdf.geometry.y >= lat_limits[0]) & (gdf.geometry.y <= lat_limits[1]) & 
+                  (gdf.geometry.x >= long_limits[0]) & (gdf.geometry.x <= long_limits[1])]
+        
+        if gdf.empty:
+            return {"message": "Error: No data available within the specified lat/long limits."}
+        
+        # Calculate statistics of the chemical values
+        chem_values = gdf[chem_symbol].values
+        mean_value = np.mean(chem_values)
+        mode_value = stats.mode(chem_values)  # Properly access the mode value
+        median_value = np.median(chem_values)
+        std_deviation = np.std(chem_values)
+        variance = np.var(chem_values)
+        
+        # Filter points with values higher than the threshold
+        high_value_points = gdf[gdf[chem_symbol] > threshold]
+        
+        # Base map centered on the midpoint of the given lat/long limits
+        lat_center = (lat_limits[0] + lat_limits[1]) / 2
+        long_center = (long_limits[0] + long_limits[1]) / 2
+        m = folium.Map(location=[lat_center, long_center], zoom_start=10)
+        
+        # Add markers for high value points with tooltips
+        for idx, row in high_value_points.iterrows():
+            folium.Marker(
+                location=[row.geometry.y, row.geometry.x],
+                tooltip=f'{chem_symbol}: {row[chem_symbol]:.2f} ppm'
+            ).add_to(m)
+        
+        # Add layer control to toggle markers
+        folium.LayerControl().add_to(m)
+        m.add_child(MeasureControl())
+
+        north_arrow_svg = """
+        <div style="position: fixed; 
+                    bottom: 30px; left: 10px; width: 40px; height: 40px; 
+                    z-index: 1000; pointer-events: none;">
+                    <div>North</div>
+            <svg version="1.1" id="icons" xmlns="http://www.w3.org/2000/svg" x="0" y="0" viewBox="0 0 128 128" style="enable-background:new 0 0 128 128" xml:space="preserve">
+                <style>.st0,.st1{display:none;fill:#191919}.st1,.st3{fill-rule:evenodd;clip-rule:evenodd}.st3,.st4{display:inline;fill:#191919}</style>
+                <g id="row1">
+                    <path id="nav:2_3_" d="M64 1 17.9 127 64 99.8l46.1 27.2L64 1zm0 20.4 32.6 89.2L64 91.3V21.4z" style="fill:#191919"/>
+                </g>
+            </svg>
+        </div>
+        """
+        m.get_root().html.add_child(folium.Element(north_arrow_svg))
+        # Generate the HTML content
+        html_content = m.get_root().render()
+        
+        # Construct the message with statistics
+        message = f"Plotted points with '{chem_symbol}' values higher than {threshold:.2f} ppm\n"
+        message += f"Mean: {mean_value:.2f} ppm\n"
+        message += f"Mode: {mode_value} ppm\n"
+        message += f"Median: {median_value:.2f} ppm\n"
+        message += f"Standard Deviation: {std_deviation:.2f} ppm\n"
+        message += f"Variance: {variance:.2f} ppm"
+        
+        return {
+            "message": message,
+            "html": html_content
+        }
+    
+    except Exception as e:
+        return {"message": f"An error occurred: {str(e)}"}
+
+
 def create_heatmap(geojson_file, chem_symbol, lat_min, lat_max, long_min, long_max):
     """
     Generates a heatmap from geochemical data within specified latitudinal and longitudinal limits.
@@ -400,7 +502,8 @@ def create_geochem_avg_histogram(geojson_file, chem_symbols, lat_min, lat_max, l
             plt.close()
             
             # Create the HTML content
-            html_content = f'<img src="data:image/png;base64,{img_base64}" />'
+            html_content = f'<img src="data:image/png;base64,{img_base64}" style="width: 400px; height: 500px;" />'
+
         else:
             html_content = '<p>No data available for the specified chemicals and area.</p>'
         
@@ -930,8 +1033,8 @@ def Manager_agent(query, lat_min, lat_max, long_min, long_max):
                             - If it's related to elevation,Empty the list and add 'elevation_' to the list.
                             - Do not print anything else.
 
-                            - Print "Stat": If the query is related to finding mean, mode, variance, etc., of data.
-                            In the next line, print a Python list with one element: the chemical formula(not name) in lowercase mentioned in the query.
+                            - Print "Threshold": If the query is related to finding all the points higher than a threshold.
+                            In the next line, print a Python list with 2 elements: first: the chemical formula(not name) in lowercase mentioned in the query and second: the threshold value.
 
                             - Print "Contour": If the query is related to creating contour maps.
                             In the next line, print a Python list with one element: the chemical formula(not name) in lowercase mentioned in the query.
@@ -1083,11 +1186,13 @@ def Manager_agent(query, lat_min, lat_max, long_min, long_max):
         else:
             retval= interpolation_geojson(stream_sed_file, column, lat_min, lat_max, long_min, long_max, 4)
     
-    
-    elif task == "Stat":
+    elif task == "Threshold":
         par_list = eval(lines[1])
+        #print(par_list)
         column = par_list[0]
-        retval= plot_high_value_points(stream_sed_file, column, lat_min, lat_max, long_min, long_max)
+        threshold = float(par_list[1])
+        retval= plot_high_value_points(stream_sed_file, column, lat_min, lat_max, long_min, long_max, threshold)
+    
     
     elif task == "Exploration":
         retval=plot_excavation_sites(exploration_file, lat_min, lat_max, long_min, long_max)