API Reference¶
Auto-generated documentation from source code docstrings.
Automatic Generation
This documentation is automatically extracted from NumPy-style docstrings using mkdocstrings.
Modules¶
Core Pipeline¶
| Module | Description |
|---|---|
| anomaly_detection | Outlier detection methods (11 methods) |
| imputation | Signal reconstruction (8 methods) |
| featurization | Feature extraction |
| classification | Model training and evaluation |
| decomposition | PLR waveform decomposition (5 methods) |
Support Modules¶
| Module | Description |
|---|---|
| data_io | Data loading and preprocessing |
| ensemble | Ensemble methods |
| log_helpers | Logging and MLflow utilities |
| stats | Statistical analysis and metrics |
| metrics | Evaluation metrics |
| orchestration | Pipeline orchestration |
| preprocess | Data preprocessing |
| summarization | Results summarization |
Visualization¶
| Module | Description |
|---|---|
| viz | Python visualization (calibration, DCA, CD diagrams) |
Usage¶
Each module page shows:
- Functions: With parameters, return types, and examples
- Classes: With attributes and methods
- Source code: Links to the implementation
R Code Documentation¶
R code in src/r/ uses roxygen2 documentation conventions.
mkdocstrings does not have an R handler, so R function documentation is maintained
separately via roxygen2 comments (#') in .R files. See src/r/README.md for R API details.
Docstring Style¶
All Python docstrings follow NumPy style:
def example_function(param1: int, param2: str) -> dict:
"""
Short description of the function.
Longer description with more details about what the function does.
Parameters
----------
param1 : int
Description of first parameter.
param2 : str
Description of second parameter.
Returns
-------
dict
Description of return value.
Examples
--------
>>> example_function(1, "test")
{"result": "success"}
"""