TACT Documentation

TACT (Turbulence Adjustment Computation Tool) is a Python package for processing, adjusting, and comparing LiDAR-based turbulence intensity measurements with traditional anemometer-based measurements.

🚀 Getting Started

New to TACT? Start here:

Installation Guide - Install TACT as a Python package
Getting Started Guide - Complete walkthrough from installation to first results
Data Import Guide - How to prepare and load your data
Quick Start - Basic usage examples

✨ Features

Standardized Data Processing: Consistent formatting and validation for LiDAR and anemometer data
Multiple Adjustment Methods:
- Baseline (no adjustment reference)
- Site-Specific Simple + Filter (SS-SF) - recommended
- Site-Specific Wind Speed (SSWS)
- Site-Specific Wind Speed + Std Dev (SSWSStd)
DNV RP-0661 Validation: Industry-standard validation with MRBE/RRMSE metrics
Professional Visualization: Publication-ready plots with DNV acceptance criteria
Method Comparison Framework: Automated benchmarking of all methods
Extensible Architecture: Easy to add custom adjustment methods
Statistical Analysis Tools: Comprehensive metrics and regression analysis

📖 User Guides

Core Workflows

Getting Started - Installation, first run, and basic usage
Data Import Guide - Preparing and loading your data
Adding Custom Models - Extending TACT with your own methods

Example Scripts

main.py - Complete pipeline with DNV validation and visualization
compare_all_methods.py - Compare all adjustment methods
Example Test Scripts - Method-specific examples

📚 API Documentation

Core Components

TACT Core - Main TACT class and factory
Base Classes - Abstract base classes for methods
Registry System - Method registration

Adjustment Methods

Baseline - No adjustment (reference comparison)
SS-SF - Site-Specific Simple + Filter (recommended)
SSWS - Site-Specific Wind Speed
SSWSStd - SS Wind Speed + Standard Deviation

Validation & Visualization

DNV RP-0661 Validation (tact/validation/dnv_rp0661.py) - Industry-standard validation
Visualization Suite (tact/visualization/dnv_plots.py) - Professional plotting

Utilities

Data Processing - Loading and processing data
Statistics - Statistical computations
Setup - Configuration and processors

📊 Method Comparison

See Method Comparison Results for detailed performance analysis of all implemented methods on example data. Quick Summary:

SS-SF: Best overall performance (MRBE: 37.8%, RRMSE: 111.1%)
SSWSStd: Second best (MRBE: 37.7%, RRMSE: 121.6%)
SSWS: Third (MRBE: 92.1%, RRMSE: 188.0%)
Baseline: Reference (MRBE: 90.4%, RRMSE: 183.0%)

🔧 Configuration

TACT uses JSON configuration files to map your data columns and set processing parameters:

{
    "input_data_column_mapping": {
        "reference": {
            "wind_speed": "ref_ws",
            "wind_speed_std": "ref_sd",
            "turbulence_intensity": "ref_ti"
        },
        "rsd": {
            "primary": {
                "wind_speed": "rsd_ws",
                "wind_speed_std": "rsd_sd",
                "turbulence_intensity": "rsd_ti"
            }
        }
    },
    "binning_config": {
        "bin_size": 1.0,
        "bin_min": 4.0,
        "bin_max": 20.0
    }
}

See Data Import Guide for details.

🎯 Quick Examples

Run Adjustment with Validation

from tact import TACT
from tact.utils.load_data import load_data
from tact.utils.setup_processors import setup_processors
from tact.validation import validate_dnv_rp0661

# Load and process data
data = load_data("data.csv")
bp, tp, sp = setup_processors("config.json")
data = bp.process(tp.process(data))

# Run adjustment
tact = TACT()
results = tact.adjust(data, "ss-sf", {"split": True, "config_path": "config.json"})

# Validate with DNV RP-0661
validation = validate_dnv_rp0661(
    adjusted_data=results["adjusted_data"],
    reference_col="ref_ti",
    adjusted_col="adjTI_RSD_TI",
    wind_speed_col="ref_ws",
    bin_col="bins",
    criteria_type="LV"
)

print(f"MRBE: {validation['overall']['MRBE_%'].iloc[0]:.2f}%")
print(f"RRMSE: {validation['overall']['RRMSE_%'].iloc[0]:.2f}%")

Compare All Methods

from compare_all_methods import compare_all_methods

# Runs baseline, ss-sf, ssws, sswsstd
comparison = compare_all_methods()
print(comparison)

Add Custom Method

from tact.core.base import AdjustmentMethod
from tact.core.registry import AdjustmentRegistry

@AdjustmentRegistry.register("my-method")
class MyMethod(AdjustmentMethod):
    def required_model_parameters(self):
        return {"config_path": str}

    def required_data_columns(self):
        return ["reference.wind_speed", ...]

    def adjust(self, data, parameters):
        # Your implementation
        return {"adjusted_data": adjusted_data}

See Adding Custom Models for complete tutorial.

📦 Project Structure

TACT/
├── tact/                      # Main package
│   ├── adjustments/          # Adjustment method implementations
│   ├── validation/           # DNV RP-0661 validation
│   ├── visualization/        # Plotting functions
│   ├── core/                 # Core infrastructure
│   ├── utils/                # Utility functions
│   ├── example/              # Example data and configs
│   └── tests/                # Test suite
├── docs/                     # Documentation (you are here!)
├── legacy/                   # Original monolithic implementation
├── main.py                   # Example pipeline script
├── compare_all_methods.py    # Method comparison script
└── requirements.txt          # Dependencies

🤝 Contributing

We welcome contributions! See the Contributing Guide for:

Code style and standards
Testing requirements
Pull request process
Development setup

📄 License

This project is licensed under the BSD 3-Clause License - see the LICENSE file for details.

📞 Support

Documentation: You’re reading it!
Issues: GitHub Issues
Email: aea@nrgsystems.com

📝 Additional Resources

Status Report - Current implementation status and comparison with legacy
Method Comparison Results - Detailed performance analysis
README - Project overview and quick start

Ready to get started? → Getting Started Guide

​TACT Documentation

​🚀 Getting Started

​✨ Features

​📖 User Guides

​Core Workflows

​Example Scripts

​📚 API Documentation

​Core Components

​Adjustment Methods

​Validation & Visualization

​Utilities

​📊 Method Comparison

​🔧 Configuration

​🎯 Quick Examples

​Run Adjustment with Validation

​Compare All Methods

​Add Custom Method

​📦 Project Structure

​🤝 Contributing

​📄 License

​📞 Support

​📝 Additional Resources