SaSNoPy - Semiautomatic Spectral Normalization code with Python
SaSNoPy is a Python tool designed for the semi-automatic normalization of astronomical spectra. It proves particularly useful for handling spectral data from various sources, automatically calculating the median of the highest defined points (top-level) in local spectral regions (splits). This tool facilitates the normalization process, making it convenient for further analysis, especially when dealing with long-wavelength range spectra and echelle orders.
- Interactive UI: Provides a graphical user interface (GUI) for easy interaction.
- Flexible Input Format: Spectra can be in any ASCII or FIT/FITS format. For now, the output is without a header.
- List Support: Can handle a list of spectra, strongly recommended for short wavelength range spectra, like echelle orders.
- Instantaneous Normalization: Can graph the normalized spectra and fit instantaneously.
- Automatic and Non-Automatic Modes: It can normalize automatically without supervision. The non-automatic way allows users to add and delete points, change the function, clear the points and reset.
- Keyboard Shortcuts: Convenient keyboard shortcuts for common actions.
- Spectral Division: Divide a given spectrum into smaller regions based on specified criteria (Currently is included but still is better to improve).
- Temporary Files: Save divided spectral regions as temporary files for individual processing.
- Output header: Add the option to save on fit/fits with header
- Automatize the top level: Currently, SaSNoPy employs a 'high-rejection' method with a fixed top-level parameter (top=50). The ongoing development aims to enhance this by implementing a sophisticated algorithm for automatic determination of the top level. This improvement will enable the tool to adapt dynamically to the characteristics of the spectral data, providing a more robust and user-friendly experience.
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Install the required libraries:
pip install -r docs/requirement.txt
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Run the program:
python sasnopy.py input_spec.asc/fit
or with a list:
python sasnopy.py -l input_spec.list
- Clear Selection - C: Clears the current selection.
- Reset - R: Resets the normalization to its initial state with the automatic points.
- Function: Select the type of function for normalization.
- Order: Sets the order for the selected function.
- Divide Spectrum: Initiates the process of dividing the spectrum.
- < , >: Navigate to the previous or next division on the same spectrum.
- Previous Spectrum - Left: Loads the previous spectrum in the list.
- Next Spectrum - Right: Loads the next spectrum in the list.
- Autosave Prefix, Yes or No: Enables or disables autosaving with a user-defined prefix.
- Save Normalized Spectrum - S: Saves the normalized spectrum.
- Quit - Q: Exits the program.
- - Space: Performs the actions of both save normalized spectrum and load the next spectrum.
- SASNoPy is designed for specific use cases and may not cover all scenarios.
- The division criteria are predefined and may not suit every dataset.
SASNoPy is versatile for normalizing spectra with specific criteria. However, additional tools may be required for more advanced or specialized normalization tasks.
- Mauricio Cabezas
This project is licensed under the .
Please consider citing if you use SASNoPy in a publication, thesis, or project. You can use the following BibTeX entry:
@software{cabezas2023sasnopy,
author = {Mauricio Cabezas},
title = {SASNoPy - Semi-Automatic Spectral Normalization in Python},
year = {2023},
url = {https://github.com/maurcabezas/SASNoPy}
}- Companion Simulations: The 'median' concept and ideas used in this code were inspired by the work carried out in the Companion Simulations project. While no specific names or sources were provided, the project served as a valuable reference for spectral normalizations.