generate_feature_comparison_report
Create interactive HTML reports with violin plots to compare 17 time-domain features across signal groups, identifying 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).
**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 list of signal files.
Example: {"Healthy": ["baseline_1.csv", "baseline_2.csv"],
"Faulty": ["InnerRaceFault_1.csv", "OuterRaceFault_1.csv"]}
sampling_rate: Sampling rate (auto-detect from metadata if None)
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
Example:
>>> generate_feature_comparison_report(
... signal_groups={
... "Healthy": ["real_train/baseline_1.csv", "real_train/baseline_2.csv"],
... "Inner Fault": ["real_train/InnerRaceFault_vload_1.csv"],
... "Outer Fault": ["real_train/OuterRaceFault_1.csv"]
... }
... )
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| signal_groups | Yes | ||
| sampling_rate | No | ||
| segment_duration | No | ||
| overlap_ratio | No | ||
| features_to_plot | No |
Output Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||