MiraPy: Python Package for Deep Learning in Astronomy

MiraPy is a Python package for Deep Learning in Astronomy. It is built using Keras for developing ML models to run on CPU and GPU seamlessly. The aim is to make applying machine learning techniques on astronomical data easy for astronomers, researchers and students.

Applications

MiraPy can be used for problem solving using ML techniques and will continue to grow to tackle new problems in Astronomy. Following are some of the experiments that you can perform right now:

• Classification of X-Ray Binaries using neural network
• Astronomical Image Reconstruction using Autoencoder
• Classification of the first catalog of variable stars by ATLAS
• HTRU1 Pulsar Dataset Image Classification using Convolutional Neural Network
• Curve Fitting using Autograd (incomplete implementation)

There are more projects that we will add soon and some of them are as following:

• Feature Engineering (Selection, Reduction and Visualization)
• Classification of different states of GRS1905+105 X-Ray Binaries using Recurrent Neural Network (RNN)
• Feature extraction from Images using Autoencoders and its applications in Astronomy

You can find the applications MiraPy in our tutorial repository.

In future, MiraPy will be able to do more and in better ways and we need your suggestions! Tell us what you would like to see as a part of this package on Slack.

Contributing

MiraPy is far from perfect and we would love to see your contributions to open source community! MiraPy is open source, built on open source, and we'd love to have you hang out in our community.

About Us

MiraPy is developed by Swapnil Sharma and Akhil Singhal as their final year 'Major Technical Project' under the guidance of Dr. Arnav Bhavsar at Indian Institute of Technology, Mandi.

License

This project is Copyright (c) Swapnil Sharma, Akhil Singhal and licensed under the terms of the MIT license.