Implement plotly-resampler

stats/id_viewer.py

@@ -7,7 +7,7 @@ from pathlib import Path
 import numpy as np
 import pandas as pd
 import plotly.graph_objects as go
-import lttbc
+from plotly_resampler import FigureResampler
 from stats.utils.extractor import load_data
 
 def _format_can_id_vec(s: pd.Series) -> pd.Series:
@@ -41,29 +41,21 @@ def prepare_data(df, target_id):
     return filtered, byte_cols
 
 def plot_bits(df, byte_cols, can_id, title):
-    fig = go.Figure()
+    fig = FigureResampler()
     colors = ['#e41a1c', '#377eb8', '#4daf4a', '#984ea3', '#ff7f00', '#ffff33', '#a65628', '#f781bf']
     n = len(byte_cols)
-    max_points = 2000
 
     x = df['Timestamp'].to_numpy() if not df.empty else np.array([])
     for i, col in enumerate(byte_cols):
         y = df[col].to_numpy(dtype=np.float32, copy=False) if not df.empty else np.array([])
 
-        if len(x) > max_points and len(x) == len(y):
-            x_plot, y_plot = lttbc.downsample(x, y, max_points)
-        else:
-            x_plot, y_plot = x, y
-
-        fig.add_trace(go.Scattergl(
-            x=x_plot,
-            y=y_plot,
+        fig.add_trace(go.Scatter(
             mode='lines',
             line=dict(shape='hv', width=2, color=colors[i % len(colors)]),
             name=col.upper(),
             legendgroup=col.upper(),
             hovertemplate=f"<b>{col.upper()}</b><br>Time: %{{x}}<br>Value: %{{y}}<extra></extra>",
-        ))
+        ), hf_x=x, hf_y=y)
 
     all_button = dict(label='ALL', method='restyle', args=[{'visible': [True] * n}])
     none_button = dict(label='NONE', method='restyle', args=[{'visible': ['legendonly'] * n}])