N2 Fitting and Resolving Power Evaluation

Overview

This repository provides a Python-based tool for analyzing and fitting nitrogen spectra data, estimating the resolving power (RP), and calculating the third-peak to first-valley (3P1V) ratio. The package uses the Skewed Voigt model for fitting and is built on top of the lmfit library.

Features

• Automatic fitting of nitrogen spectra.
• Resolving power (RP) estimation based on Gaussian contributions.
• Calculation of the 3P1V ratio.
• Customizable initial parameters for fitting.
• Supports fixed or free fit parameters.
• Interactive visualization of spectral data and fits.

Installation

To use the package, clone the repository and install the necessary dependencies:

# Clone the repository
git clone https://github.com/simonevadi/n2_fit.git
cd n2_fit

# Install dependencies
pip install -r requirements.txt

Requirements

• Python 3.9+
• numpy
• pandas
• matplotlib
• lmfit
• tqdm

Usage

Basic Fit Example

The fit_n2 method accepts spectral data and fits it using the Skewed Voigt model:

from fit import N2_fit

# Example usage
n2fit = N2_fit()
energy = [list_of_energy_values]
intensity = [list_of_intensity_values]

n2fit.fit_n2(energy, intensity, title="MySpectrum", print_fit_results=True)

Options for fit_n2

• energy: List or array of energy values.
• intensity: List or array of intensity values.
• title (str): Title for the plot.
• print_fit_results (bool): Prints the lmfit fit report.
• n_peaks (int): Number of peaks to fit (default: 5).
• save_results (bool/str): Saves results to a file if a path is provided.
• show_results (bool): Displays the fit plot interactively.
• fwhm_l (float): Lorentzian FWHM value (default: 114).

Resolving Power Calculation

The RP is computed using the average Gaussian FWHM of the first three peaks:

$$RP = \frac{\mu_2}{FWHM_g}$$

Where the Gaussian FWHM is:

$$FWHM_g = 2 \sqrt{2 \ln(2)} \sigma_2$$

3rd-Peak to 1st-Valley Ratio

The 3P1V ratio is calculated and returned alongside the fit results, providing insight into spectral properties.The resolving power is also looked up in table, and this vaue is more reliable that the one from the fit.

Visualizations

The package includes tools for plotting:

• Initial fit guesses: Visualize the initial parameters used for fitting.
• Fitting results: Displays the data, fitted curve, and individual components.

Example:

n2fit.fit_n2(energy, intensity, plot_initial_guess=True)

Table Generation

Use the CreateTable class to generate tables of RP and 3P1V ratios across a range of Gaussian and Lorentzian FWHM values:

from create_table import CreateTable

# Generate and save the table
table_generator = CreateTable()
df_results = table_generator.create_table(savepath="results_table.csv")

Plot Table Results

table_generator.plot_table(table_to_plot="results_table.csv", show_plot=True)

Directory Structure

N2_Fit/
├── fit.py               # Main fitting class
├── models.py            # Skewed Voigt and background models
├── create_table.py      # Resolving power table generation
├── helper_functions.py  # Utility functions
├── n2_peaks_parameters.py # Default theoretical values for peaks
├── tables/              # Default tables (e.g., skewedVoigt.csv)
├── examples/            # Example scripts and usage
└── requirements.txt     # Dependencies

Contributing

Contributions are welcome! If you'd like to improve the package, submit a pull request or open an issue.

1. Fork the repository.
2. Create a new branch:

   git checkout -b feature/your-feature-name

3. Commit your changes:

   git commit -m "Add your description here"

4. Push the changes and open a pull request.

License

This project is licensed under the MIT License. See LICENSE for details.