Update app.py

app.py

@@ -1,11 +1,84 @@
 import pickle
-with open("earthquake_model.pkl", 'rb') as file:
-    loaded_model = pickle.load(file)
 import gradio as gr
+import geopandas as gpd
+from shapely.geometry import Point
+import matplotlib.pyplot as plt
+import numpy as np
+with open("earthquake_model.pkl", 'rb') as file:
+    model = pickle.load(file)
+def time2num(x):
+    try:
+        (h, m, s) = str(x).split(':')
+        result = int(h) * 3600 + int(m) * 60 + int(s)
+        return result
+    except:
+        return 0
+
+def date2num(x):
+    try:
+        (m, d, y) = str(x).split("/")
+        result = int(y) * 365 + int(m) * 30 + int(d)
+        return result
+    except:
+        return 0
+
+def datetime2num(date_str, time_str):
+    date_value = date2num(date_str)
+    time_value = time2num(time_str)
+    return date_value ,time_value
+def test(model, date_str, time_str,all_points):
+    data_list = []
+    for lat, lon in all_points:
+        date, time = datetime2num(date_str, time_str)
+        data_list.append([date, time, lat, lon])
+    np_array = np.array(data_list)
+    res = model.predict_proba(np_array)
+    return res
+def create_geodf(all_points, model, date_str, time_str):
+    res = test(model, date_str, time_str,all_points)
+
+    data_list = []
+    for lat, lon in all_points:
+        date, time = datetime2num(date_str, time_str)
+        data_list.append([date, time, lat, lon])
+    np_array = np.array(data_list)
+
+    df = pd.DataFrame(np_array, columns=['Date', 'Time', 'Latitude', 'Longitude'])
+    df['Probability_2'] = [i[1] for i in res]
+    df['geometry'] = [Point(lon, lat) for lat, lon in zip(df['Latitude'], df['Longitude'])]
+
+    crs = "EPSG:4326"
+    gdf = gpd.GeoDataFrame(df, crs=crs, geometry='geometry')
+
+    return gdf
+
+def plot_func(date_str, time_str):
+    min_latitude = -90
+    max_latitude = 90
+    latitude_step = 1
+    min_longitude = -180
+    max_longitude = 180
+    longitude_step = 1
+    latitudes = np.arange(min_latitude, max_latitude + latitude_step, latitude_step)
+    longitudes = np.arange(min_longitude, max_longitude + longitude_step, longitude_step)
+    all_points = np.array(np.meshgrid(latitudes, longitudes)).T.reshape(-1, 2)
+    gdf = create_geodf(all_points, model, date_str, time_str)
+
+    top = gdf.nlargest(100, 'Probability_2')
+    world = gpd.read_file(gpd.datasets.get_path('naturalearth_lowres'))
+    fig, ax = plt.subplots(figsize=(12, 12))
+    ax.imshow(np.ones((180, 360)), cmap='gray', extent=[-180, 180, -90, 90])
+    world.plot(ax=ax, color='lightgray', edgecolor='black')
+    top.plot(ax=ax, markersize=50, color='red', legend=True, alpha=0.5)
+
+    plt.xlabel('Longitude')
+    plt.ylabel('Latitude')
+    plt.title('Possible Earthquake Map')
+    plt.grid(True)
+
+    return plt.gcf()
+
+inputs = [gr.inputs.Textbox(label="Date: (MM/DD/YYYY)"), gr.inputs.Textbox(label="Time: (HH:MM:SS) GMT-4")]
 
-def greet(name):
-    return "Hello " + name + "!"
 
-demo = gr.Interface(fn=greet, inputs="text", outputs="text")
-    
-demo.launch()
+gr.Interface(fn=plot_func, inputs=inputs, outputs="plot",debugging=True).launch()