tamag 1.0.0

"Magnetogram Transformations: A Python Toolkit for Transforming and Enhancing Magnetogram fits"

TaMag: Magnetogram Transformation Module

TaMag is a Python module designed for transforming magnetogram maps using various techniques that reduce information loss. This module is particularly useful for augmenting magnetograms, addressing data imbalance for predictive modeling.

Installation

TaMag requires Python (>= 3.9) and the following dependencies:

• numpy (>=1.17.0)
• scipy (>=1.3.0)
• astropy (>=5.0.6,!=5.1.0)

Install TaMag using pip:

pip install tamag

or using conda:

conda install -c conda-forge tamag

Usage Example

from tamag.transforms import Flip
from tamag.datasets import load_fits_data
import warnings
warnings.filterwarnings("ignore")
import matplotlib.pyplot as plt

# Create an instance of the transformer
transformer = Flip(direction='vertical')

# Load a sample magnetogram
magnetogram, magnetogram_header, bitmap  = load_fits_data()

# Transform the magnetogram
transformed_magnetogram = transformer.transform(magnetogram,scale=255,rgb=True)

# Display the results
plt.figure(figsize=(15, 5))
plt.subplot(1, 2, 1)
plt.imshow(magnetogram, cmap='gray')
plt.title('Original Image')

plt.subplot(1, 2, 2)
plt.imshow(transformed_magnetogram, cmap='gray')
plt.title('Flipped Image')

Documentation

For detailed documentation and examples, visit the TaMag Documentation.

Changelog

See the Changelog for information about notable changes.

License

TaMag is distributed under the GNU License. See GNU General Public License, Version 3 for details.

Citation

If you use TaMag in a scientific publication, please consider citing our work. Refer to the Citation Guide for details.

Acknowledgment

This work was supported by NSF Grant Award 2104004.

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This software is distributed using the GNU General Public License, Version 3

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© 2024 Temitope Adeyeha, Chetraj Pandey, Berkay Aydin

Data Mining Lab

Georgia State University