Gaussian Peak Fitting

Table of contents

1. Introduction
2. How to use
3. Behavior
4. Method
5. References

---

Introduction

Gaussian Peak Fitting estimates Gaussian components for selected spectral peaks. It helps users inspect approximate peak centers, widths, amplitudes, and fitted peak shapes.

How to use

1. Upload data and finish preprocessing if needed.
2. Open Analytics Page.
3. In Select Analytics Plot, choose Gaussian Peak Fitting.
4. Select or identify peaks using the available peak fitting controls.
5. Review the fitted curves and fitting parameters.

Behavior

SpectraGuru fits Gaussian-shaped components to selected peak regions and displays the fitted result over the spectrum. The output helps compare measured peak structure with the fitted Gaussian approximation.

Method

The fitted signal is a sum of Gaussian components:

\[\hat{I}(x)=\sum_{k=1}^{K} A_k\exp\left(-\frac{(x-\mu_k)^2}{2\sigma_k^2}\right)\]

Parameter	Tunable or fixed	Implementation
Selected peaks	Tunable	Peaks chosen through the peak fitting workflow
Component shape	Fixed	Gaussian components
Fitting routine	Fixed	SciPy nonlinear curve fitting

References

1. Virtanen, P., Gommers, R., Oliphant, T. E., Haberland, M., Reddy, T., Cournapeau, D., … SciPy 1.0 Contributors. (2020). SciPy 1.0: Fundamental Algorithms for Scientific Computing in Python. Nature Methods, 17, 261-272. https://doi.org/10.1038/s41592-019-0686-2
2. SciPy Developers. scipy.optimize.curve_fit. https://docs.scipy.org/doc/scipy/reference/generated/scipy.optimize.curve_fit.html