Update app.py

app.py

@@ -3,6 +3,8 @@ import pandas as pd
 import matplotlib.pyplot as plt
 import numpy as np
 from io import BytesIO
+from scipy.signal import savgol_filter
+from scipy.ndimage import gaussian_filter1d
 
 # Function to save and download images with specified DPI
 def download_button(fig, file_name, file_format, dpi):
@@ -16,6 +18,22 @@ def download_button(fig, file_name, file_format, dpi):
         mime=f"image/{file_format.lower()}",
     )
 
+# Function to apply smoothing
+def apply_smoothing(data, method, **params):
+    if method == "None":
+        return data
+    elif method == "Moving Average":
+        window = params.get('window_size', 5)
+        return pd.Series(data).rolling(window=window, center=True).mean()
+    elif method == "Gaussian":
+        sigma = params.get('sigma', 2)
+        return gaussian_filter1d(data, sigma=sigma)
+    elif method == "Savitzky-Golay":
+        window = params.get('window_size', 5)
+        poly_order = params.get('poly_order', 2)
+        return savgol_filter(data, window_length=window, polyorder=poly_order)
+    return data
+
 # Title of the app
 st.set_page_config(layout="wide")  # Use wide layout
 st.title("Advanced CSV Data Visualization App")
@@ -86,6 +104,35 @@ if uploaded_file is not None:
             grid_color = st.color_picker("Grid Line Color:", "#DDDDDD")
             grid_line_width = st.slider("Grid Line Width:", 0.5, 2.5, 1.0)
 
+            # Smoothing Settings
+            st.subheader("Smoothing Settings")
+            smoothing_method = st.selectbox(
+                "Smoothing Method:",
+                ["None", "Moving Average", "Gaussian", "Savitzky-Golay"]
+            )
+            
+            # Smoothing parameters based on selected method
+            smoothing_params = {}
+            if smoothing_method == "Moving Average":
+                smoothing_params['window_size'] = st.slider(
+                    "Window Size:",
+                    3, 51, 5, step=2
+                )
+            elif smoothing_method == "Gaussian":
+                smoothing_params['sigma'] = st.slider(
+                    "Sigma (Blur Amount):",
+                    0.1, 5.0, 2.0, step=0.1
+                )
+            elif method == "Savitzky-Golay":
+                smoothing_params['window_size'] = st.slider(
+                    "Window Size:",
+                    3, 51, 5, step=2
+                )
+                smoothing_params['poly_order'] = st.slider(
+                    "Polynomial Order:",
+                    1, 5, 2
+                )
+
             # Vertical Marker Settings
             st.subheader("Vertical Marker Settings")
             marker_x_values = st.text_input("Enter X-axis Values for Markers (comma-separated):", value="")
@@ -173,18 +220,21 @@ if uploaded_file is not None:
             # Apply scaling for X-axis
             df, x_unit = apply_scaling(df, x_column, scale_option, x_unit)
 
-            # Apply scaling for Y-axis (same scaling options)
+            # Apply scaling for Y-axis
             for col in y_columns:
                 df, y_unit = apply_scaling(df, col, y_scale_option, y_unit)
 
-            # Plot data
+            # Plot data with smoothing
             for col in y_columns:
-                ax.plot(df[x_column], df[col], 
-                        label=col,
-                        linestyle=style_settings[col]["line_style"],
-                        marker=style_settings[col]["marker_style"],
-                        color=style_settings[col]["color"],
-                        linewidth=style_settings[col]["line_width"])
+                # Apply smoothing to the y-values
+                y_values = apply_smoothing(df[col].values, smoothing_method, **smoothing_params)
+                
+                ax.plot(df[x_column], y_values,
+                       label=col,
+                       linestyle=style_settings[col]["line_style"],
+                       marker=style_settings[col]["marker_style"],
+                       color=style_settings[col]["color"],
+                       linewidth=style_settings[col]["line_width"])
 
             # Axis limits and step size
             if x_min and x_max:
@@ -225,5 +275,4 @@ if uploaded_file is not None:
             # Download button
             download_button(fig, "graph", "PNG", dpi)
 
-    except Exception as e:
-        st.error(f"Error: {str(e)}")
+    except Exception as e: