This repository is a hub of resources related to astrophysics and space science. It contains a variety of files and information for enthusiasts, students, and professionals looking to explore the mysteries of the universe and enhance their knowledge of astrophysics. Below is a more detailed description of the main components of this repository:
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scraping_data.py This file contains a powerful Python script designed to collect data from various sources related to astrophysics. It includes the ability to retrieve information from websites such as NASA and the European Southern Observatory. With the ability to collect data from different sources, this script is useful for researchers and enthusiasts who want access to up-to-date information about astronomy, planets, stars, and galaxies.
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cnn_space_earth.py This Python script is dedicated to processing and classifying images related to space and Earth. It utilizes Convolutional Neural Networks (CNNs) to learn to distinguish different features in space images. This has applications in areas such as galaxy classification, satellite image analysis, and more. Additionally, the script demonstrates how to use the TensorFlow library and Kerastuner for hyperparameter optimization in deep learning tasks.
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index.html The homepage of the AstroML application is an informative portal that provides an overview of key areas in astrophysics and space science. This page also serves as a starting point for exploring other parts of the project.
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htmls/about.html The "About AstroML" page provides detailed information about the project, its purpose, and its development team. It's a valuable source of information for those looking to understand the context behind this repository.
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htmls/astroml.html This page delves even further into topics related to astrophysics, providing detailed information about notable concepts and discoveries in the field. It serves as an excellent reference for those wishing to deepen their knowledge of astrophysics.
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htmls/calculus.html The "Calculus in Astrophysics" page explores fundamental mathematical topics used in astrophysics. It provides information and practical examples of how mathematics plays a critical role in understanding the cosmos.
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htmls/landpage.html This is an entry page that invites visitors to explore the world of astrophysics. It serves as a friendly starting point for beginners who want to embark on their learning journey about space.
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app/app.py This Flask web application provides a simple interface for searching for galaxy information based on their names. Users can send a POST request with the name of a galaxy and receive information about it, including a photo and related data. It's a demonstration of how astrophysics can be accessible through a web API.
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app/cnn_basis.py This script includes the training of a Convolutional Neural Network (CNN) to classify space-related images. It serves as an introduction to machine learning applied to astronomical image analysis and can be a foundation for more advanced computer vision projects in astrophysics.
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app/planets_3d.py This program uses the Pygame and OpenGL libraries to create a three-dimensional simulation of planets. It offers an interactive experience for visualizing the motion and orbits of planets in our solar system. This simulation is an engaging way to explore planetary dynamics.
This repository and its resources have several potential applications:
Learning and Education: The Python scripts and HTML pages provide valuable educational resources for students and enthusiasts of astrophysics looking to learn and deepen their knowledge in the field.
Scientific Research: The data collection and image processing scripts can be useful for researchers working on astrophysics projects, providing access to relevant information and tools.
Software Development: The web applications and code examples can serve as a solid foundation for developing astrophysics-related software, such as astronomical data analysis tools or custom simulations.
This project makes use of several technologies, including:
Python: The primary programming language for the scripts and applications.
Flask: A Python web framework used to create the web-based galaxy search application.
TensorFlow and Keras: Machine learning libraries used for training convolutional neural networks.
Pygame and OpenGL: Graphics libraries used to create the 3D planet simulation.
HTML and CSS: Languages used to develop the informative web pages.
Before running any of the scripts or applications, make sure you have all the necessary libraries and dependencies installed. You can install the dependencies using the following command: ''' bash Copy code pip install -r requirements.txt '''
Contributions to this project are welcome. If you'd like to contribute improvements, bug fixes, or new features, feel free to create a pull request.
This project is licensed under the MIT License - see the LICENSE file for details.
Enjoy your time exploring the resources of this repository related to astrophysics and space science! If you have any questions or suggestions, don't hesitate to contact us.
AstroML Project Team