Processing pipeline

Overview

This page provides a conceptual overview of the transient nutation analysis workflow implemented in this package.

The pipeline transforms raw experimental data into frequency-domain spectra through a sequence of well-defined processing steps.

Pipeline structure

The overall workflow can be summarised as:

Step-by-step description

1. Data loading

Experimental data are loaded from .DTA / .DSC files.

• 1D datasets: directly loaded as time-domain signals

• 2D datasets: loaded as field-resolved data matrices

2. Data selection (2D only)

For two-dimensional datasets, a single field slice is selected to obtain a time-domain signal.

3. Pre-processing

A sequence of optional processing steps is applied to the time-domain signal.

These may include:

• baseline correction

• signal reconstruction

• mean subtraction

• window functions

The exact steps are controlled via the parameter configuration.

4. Fourier transformation

The processed time-domain signal is transformed into the frequency domain.

Optional features:

• zero-filling (resolution enhancement)

• reference frequency scaling

5. Result

The final result consists of:

• time-domain signal (processed)

• frequency-domain spectrum

For 2D workflows, this process is applied to each field slice individually, resulting in a 2D frequency-domain dataset.

Relation to implementation

The pipeline is implemented through the following functions:

• tna.functions.run_tna() for single datasets

• tna.functions.run_tna_2d() for full 2D processing

Processing steps are applied internally via a configurable pipeline defined by the parameter object.