Update app.py

app.py

@@ -1,76 +1,122 @@
 import gradio as gr
 import pandas as pd
-from vega_datasets import data
+import plotly.express as px
+from sklearn.datasets import make_blobs
 
-def update_dropdowns(csv_file):
+def create_dataset():
+    # Örnek veri oluştur
+    data, _ = make_blobs(n_samples=300, centers=3, n_features=2, random_state=42)
+    df = pd.DataFrame(data, columns=['X', 'Y'])
+    df['Category'] = ['A', 'B', 'C'] * 100
+    return df
+
+def update_columns(csv_file):
     if csv_file is None:
-        return gr.Dropdown(choices=[]), gr.Dropdown(choices=[])
+        return [gr.Dropdown(choices=[])] * 2
     df = pd.read_csv(csv_file.name)
     numeric_cols = df.select_dtypes(include=['number']).columns.tolist()
     return gr.Dropdown(choices=numeric_cols), gr.Dropdown(choices=numeric_cols)
 
-def plot_selection(selection, df):
-    if selection is None or df is None:
-        return pd.DataFrame()
-    return df.iloc[[i["index"] for i in selection]]
-
-def create_scatter_plot(csv_file, x_col, y_col):
+def create_plot(csv_file, x_col, y_col):
     if csv_file is None or x_col is None or y_col is None:
-        return None, None
+        df = create_dataset()
+        x_col, y_col = 'X', 'Y'
+    else:
+        df = pd.read_csv(csv_file.name)
     
-    df = pd.read_csv(csv_file.name)
-    plot = gr.ScatterPlot(
-        value=df,
-        x=x_col,
+    fig = px.scatter(
+        df, 
+        x=x_col, 
         y=y_col,
-        title="Custom CSV Scatter Plot",
-        x_title=x_col,
-        y_title=y_col,
-        tooltip=df.columns.tolist(),
-        color_legend_title="Values",
-        interactive=True,
-        brush_radius=5  # Lasso/polygon seçim için
+        color='Category' if 'Category' in df.columns else None,
+        title="Interactive Scatter Plot with Polygon Selection",
+        hover_data=df.columns.tolist()
+    )
+    
+    fig.update_layout(
+        dragmode='drawclosedpath',  # Polygon çizim modu
+        newshape=dict(line_color='cyan'),  # Çizim rengi
+        margin=dict(l=20, r=20, b=20, t=40)
     )
-    return plot, df
+    
+    config = {
+        'modeBarButtonsToAdd': [
+            'drawclosedpath',
+            'eraseshape'
+        ]
+    }
+    return fig, df
+
+def get_selected_points(plot_data, df):
+    if plot_data is None or 'range' in plot_data:
+        return pd.DataFrame()
+    
+    selected_points = []
+    for shape in plot_data.get('shapes', []):
+        if shape['type'] == 'path':
+            x_path = shape['path'].split('L')
+            polygon_points = [tuple(map(float, point.split(','))) for point in x_path]
+            
+            # Polygon içinde kalan noktaları bul
+            for idx, row in df.iterrows():
+                if is_point_in_polygon((row['X'], row['Y']), polygon_points):
+                    selected_points.append(idx)
+    
+    return df.iloc[selected_points] if selected_points else pd.DataFrame()
+
+def is_point_in_polygon(point, polygon):
+    # Ray casting algoritması ile nokta-polygon çakışma kontrolü
+    x, y = point
+    inside = False
+    n = len(polygon)
+    
+    for i in range(n):
+        j = (i + 1) % n
+        xi, yi = polygon[i]
+        xj, yj = polygon[j]
+        
+        intersect = ((yi > y) != (yj > y)) and (x < (xj - xi) * (y - yi) / (yj - yi) + xi)
+        if intersect:
+            inside = not inside
+            
+    return inside
 
 with gr.Blocks() as app:
-    gr.Markdown("## 📊 Custom CSV Scatter Plot with Selection")
+    gr.Markdown("## 🔷 Polygon ile Veri Seçimi")
     
     with gr.Row():
-        csv_upload = gr.UploadButton(label="Upload CSV", file_types=[".csv"])
-        x_axis = gr.Dropdown(label="X Axis Column")
-        y_axis = gr.Dropdown(label="Y Axis Column")
+        csv_upload = gr.UploadButton(label="CSV Yükle", file_types=[".csv"])
+        x_dropdown = gr.Dropdown(label="X Ekseni")
+        y_dropdown = gr.Dropdown(label="Y Ekseni")
     
     with gr.Row():
-        plot = gr.ScatterPlot(interactive=True, brush_radius=5)
-        selected_data = gr.DataFrame(label="Selected Points")
+        plot = gr.Plot(label="Scatter Plot")
+        selected_table = gr.DataFrame(label="Seçilen Veriler")
+    
+    df_state = gr.State()
     
-    df_store = gr.State()
-
-    # CSV yüklendiğinde dropdown'ları güncelle
     csv_upload.upload(
-        fn=update_dropdowns,
+        fn=update_columns,
         inputs=csv_upload,
-        outputs=[x_axis, y_axis]
+        outputs=[x_dropdown, y_dropdown]
     )
-
-    # Eksenler seçildiğinde grafiği oluştur
-    x_axis.change(
-        fn=create_scatter_plot,
-        inputs=[csv_upload, x_axis, y_axis],
-        outputs=[plot, df_store]
+    
+    x_dropdown.change(
+        fn=create_plot,
+        inputs=[csv_upload, x_dropdown, y_dropdown],
+        outputs=[plot, df_state]
     )
-    y_axis.change(
-        fn=create_scatter_plot,
-        inputs=[csv_upload, x_axis, y_axis],
-        outputs=[plot, df_store]
+    
+    y_dropdown.change(
+        fn=create_plot,
+        inputs=[csv_upload, x_dropdown, y_dropdown],
+        outputs=[plot, df_state]
     )
-
-    # Seçim yapıldığında verileri güncelle
+    
     plot.select(
-        fn=plot_selection,
-        inputs=df_store,
-        outputs=selected_data
+        fn=get_selected_points,
+        inputs=df_state,
+        outputs=selected_table
     )
 
 if __name__ == "__main__":