Implement plotly-resampler
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+10
-2
@@ -7,6 +7,7 @@ from pathlib import Path
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import numpy as np
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import numpy as np
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import pandas as pd
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import pandas as pd
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import plotly.graph_objects as go
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import plotly.graph_objects as go
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import lttbc
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from stats.utils.extractor import load_data
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from stats.utils.extractor import load_data
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def _format_can_id_vec(s: pd.Series) -> pd.Series:
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def _format_can_id_vec(s: pd.Series) -> pd.Series:
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@@ -43,13 +44,20 @@ def plot_bits(df, byte_cols, can_id, title):
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fig = go.Figure()
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fig = go.Figure()
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colors = ['#e41a1c', '#377eb8', '#4daf4a', '#984ea3', '#ff7f00', '#ffff33', '#a65628', '#f781bf']
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colors = ['#e41a1c', '#377eb8', '#4daf4a', '#984ea3', '#ff7f00', '#ffff33', '#a65628', '#f781bf']
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n = len(byte_cols)
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n = len(byte_cols)
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max_points = 2000
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x = df['Timestamp'].to_numpy() if not df.empty else np.array([])
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x = df['Timestamp'].to_numpy() if not df.empty else np.array([])
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for i, col in enumerate(byte_cols):
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for i, col in enumerate(byte_cols):
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y = df[col].to_numpy(dtype=np.float32, copy=False) if not df.empty else np.array([])
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y = df[col].to_numpy(dtype=np.float32, copy=False) if not df.empty else np.array([])
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if len(x) > max_points and len(x) == len(y):
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x_plot, y_plot = lttbc.downsample(x, y, max_points)
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else:
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x_plot, y_plot = x, y
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fig.add_trace(go.Scattergl(
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fig.add_trace(go.Scattergl(
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x=x,
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x=x_plot,
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y=y,
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y=y_plot,
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mode='lines',
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mode='lines',
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line=dict(shape='hv', width=2, color=colors[i % len(colors)]),
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line=dict(shape='hv', width=2, color=colors[i % len(colors)]),
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name=col.upper(),
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name=col.upper(),
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