Transient Nutation Analysis (TNA)

A Python package for the analysis of transient nutation data, including pre-processing, signal reconstruction, and Fourier transformation.

The package provides both a scripting interface and a graphical user interface for interactive data analysis.

Features

• Processing of 1D and 2D transient nutation datasets
• Configurable preprocessing pipeline:
  • baseline correction
  • autoregressive signal reconstruction
  • window functions (Hamming, Kaiser, Dolph–Chebyshev, Sine-bell, Lorentz–Gauss)
  • mean subtraction
• Fourier transformation with zero-filling and frequency scaling
• GUI for interactive data exploration
• Script-based workflow for reproducible analysis

Installation

Requirements

• Python 3.9 or higher
• pip

Setup

pip install transient-nutation-analysis

or via download from GitHub

git clone https://github.com/TheresiaQuintes/tna_transient_nutation_analysis
cd tna_transient_nutation_analysis
pip install .

For a more detailed setup (including virtual environments), see the documentation.

Quick start

import tna.classes as cl
import tna.functions as fun
from pathlib import Path
import matplotlib.pyplot as plt

params = cl.Parameters(
    two_d=True,
    path=Path("your_dataset.DSC"),
    reconstruction=True,
    mean_subtraction=True,
    wdw_hamming=True,
    zero_filling=True,
    reference_freq=True
)

data = fun.run_tna_2d(params.path, params)

plt.plot(data.freq, data.freq_signal[0])
plt.show()

GUI

Start the graphical interface with:

tna-gui

Documentation

Full documentation is available at:

https://theresiaquintes.github.io/tna_transient_nutation_analysis/