added plotly alternative to candlestick

app.py

@@ -6,6 +6,7 @@ import torch
 import numpy as np
 import pandas as pd
 import gradio as gr
+import plotly.graph_objects as go
 
 from phate import PHATEAE
 from pytvlwcharts import *
@@ -204,9 +205,13 @@ def get_som_mp4_v2(csv_file_box, slice_size_slider, sample_rate, window_size_sli
 
     scores      = cluster_som.score(embedding10d, threshold_radius=8.5)
     scores_df   = scores_to_dataframe(scores)
-    DailyChart  = Chart(data=scores_df, width = 1360, height = 500,
-                        time_scale=TimeScaleOptions(seconds_visible=True, 
-                                                    time_visible=True)).mark_candlestick()
+    
+    fig = go.Figure(data=[go.Candlestick(x=scores_df['time'],
+                    open=scores_df['open'],
+                    high=scores_df['high'],
+                    low=scores_df['low'],
+                    close=scores_df['close'])])
+
 
     # Write the processed data to a CSV file
     header = ['Gait', 'TS', 'State', 'Condition', 
@@ -224,7 +229,7 @@ def get_som_mp4_v2(csv_file_box, slice_size_slider, sample_rate, window_size_sli
     som_video = cluster.plot_activation(embedding10d)
     som_video.write_videofile('som_sequence.mp4')
         
-    return processed_file_box, json_file_box, slices_per_leg, plot_box_leg, plot_box_overlay, slice_slider, plot_slice_leg, get_all_slice, slice_json_box, 'som_sequence.mp4', 'animation.mp4', DailyChart
+    return processed_file_box, json_file_box, slices_per_leg, plot_box_leg, plot_box_overlay, slice_slider, plot_slice_leg, get_all_slice, slice_json_box, 'som_sequence.mp4', 'animation.mp4', fig
     return processed_file_box, json_file_box, slices_per_leg, plot_box_leg, plot_box_overlay, slice_slider, plot_slice_leg, get_all_slice, slice_json_box, 'som_sequence.mp4', None
 
 # ml inference