added plot colors and the gap size issue

app.py

@@ -19,12 +19,10 @@ with gr.Blocks(title='Cabasus') as cabasus_sensor:
             repeat_process = gr.Button('Restart process')  
         with gr.Row():
             leg_dropdown = gr.Dropdown(choices=['GZ1', 'GZ2', 'GZ3', 'GZ4'], label='select leg', value='GZ1')
+            slice_slider = gr.Slider(minimum=1, maximum=300, label='Current slice', step=1)
         with gr.Row():
             plot_box_leg = gr.Plot(label="Filtered Signal Plot")
             plot_box_overlay = gr.Plot(label="Overlay Signal Plot")
-
-        with gr.Row():
-            slice_slider = gr.Slider(minimum=1, maximum=300, label='Current slice', step=1)
         
         with gr.Row():
             plot_slice_leg = gr.Plot(label="Sliced Signal Plot")

funcs/plot_func.py

@@ -39,7 +39,7 @@ def plot_sensor_data_from_json(json_file, sensor, slice_select=1):
 
     # Plot the sensor data
     fig, ax = plt.subplots(figsize=(12, 6))
-    ax = plt.plot(data['time'].to_list(), data[sensor].to_list())
+    ax = plt.plot(data['time'].to_list(), data[sensor].to_list(), '-b')
 
     df_temp = data[data['slice selection'] == int(slice_select)].reset_index()
     y = [np.NaN]*((int(slice_select)-1)*len(df_temp[sensor].to_list())) + df_temp[sensor].to_list() + [np.NaN]*((len(slices) - int(slice_select))*len(df_temp[sensor].to_list()))
@@ -152,8 +152,10 @@ def plot_other_sensor_with_same_timestamp(json_file, sensor, slice_select):
     # Create a DataFrame with the sensor data
     data = pd.DataFrame({'data': sensor_data, 'sensor': slice_item, 'time': timestamps})
 
+    sensor_unique = sorted(list(data.sensor.unique()), reverse=True)
+
     fig, ax = plt.subplots(figsize=(12, 6))
-    ax = sns.lineplot(data, x='time', y='data', hue='sensor')
+    ax = sns.lineplot(data, x='time', y='data', hue='sensor', hue_order=sensor_unique)
     
     plt.xlabel("Timestamp")
     plt.ylabel(sensor)

funcs/processor.py

@@ -69,7 +69,7 @@ def process_data(input_file, slice_size=64, min_slice_size=16, sample_rate=20, w
     if not no_significant_change_index.empty:
         # Save the data up to the point where no significant change appears in all channels
         data = data.loc[:no_significant_change_index[0]]
-        return None, None, f'Warning: gap of {gap_size} ms found at line {gap_start_index}', None, None, None, None, None
+        return None, None, f'Warning: Significantly shortened > check the recordings', None, None, None, None, None
 
     # Save the resulting DataFrame to a new file
     data.to_csv('output.csv', sep=";", na_rep="NaN", float_format="%.0f")
@@ -80,8 +80,4 @@ def process_data(input_file, slice_size=64, min_slice_size=16, sample_rate=20, w
     sensor_fig, slice_fig, get_all_slice = plot_sensor_data_from_json(file, "GZ1")
     overlay_fig = plot_overlay_data_from_json(file, ["GZ1", "GZ2", "GZ3", "GZ4"], use_precise_timestamp=True)
 
-    # plot all the curves from the timestep
-
-
-
     return 'output.csv', file, f'{len_}', sensor_fig, overlay_fig, gr.Slider.update(interactive=True, maximum=len_, minimum=1, value=1), slice_fig, get_all_slice