generate_feature_comparison_report
Creates interactive HTML report with violin plots comparing time-domain features across signal groups to identify discriminative features for fault detection.
Instructions
Generate feature comparison report with violin plots comparing time-domain features.
Creates interactive HTML report with violin plots showing distribution of 17
time-domain features across different signal groups (e.g., Healthy vs Faulty).
Requires every signal loaded via load_signal() first; each signal's
sampling rate comes from its stored metadata.
**Strategy**: Same HTML report approach as other reports. Useful for understanding
which features are most discriminative for fault detection.
Args:
signal_groups: Dictionary mapping group names to lists of stored
signal IDs.
Example: {"Healthy": ["real_train_baseline_1"],
"Faulty": ["real_train_OuterRaceFault_1"]}
segment_duration: Segment duration in seconds (default: 0.1s for ML)
overlap_ratio: Overlap ratio 0-1 (default: 0.5)
features_to_plot: List of feature names to plot (default: all 17 features)
ctx: MCP context
Returns:
Dictionary with file path, metadata, and summary
Raises:
ValueError: If a signal_id is not loaded or has no sampling rate.
Example:
>>> generate_feature_comparison_report(
... signal_groups={
... "Healthy": ["real_train_baseline_1", "real_train_baseline_2"],
... "Inner Fault": ["real_train_InnerRaceFault_vload_1"],
... "Outer Fault": ["real_train_OuterRaceFault_1"]
... }
... )
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| overlap_ratio | No | ||
| signal_groups | Yes | ||
| features_to_plot | No | ||
| segment_duration | No |
Output Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||