PyAutoGalaxy | PyAutoGalaxy : Open-Source Multiwavelength Galaxy Structure
kandi X-RAY | PyAutoGalaxy Summary
kandi X-RAY | PyAutoGalaxy Summary
PyAutoGalaxy is a Python library. PyAutoGalaxy has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can install using 'pip install PyAutoGalaxy' or download it from GitHub, PyPI.
PyAutoGalaxy: Open-Source Multiwavelength Galaxy Structure & Morphology
PyAutoGalaxy: Open-Source Multiwavelength Galaxy Structure & Morphology
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PyAutoGalaxy has a low active ecosystem.
It has 19 star(s) with 10 fork(s). There are 4 watchers for this library.
It had no major release in the last 12 months.
There are 13 open issues and 25 have been closed. On average issues are closed in 86 days. There are no pull requests.
It has a neutral sentiment in the developer community.
The latest version of PyAutoGalaxy is 2023.3.27.1
Quality
PyAutoGalaxy has no bugs reported.
Security
PyAutoGalaxy has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
License
PyAutoGalaxy is licensed under the MIT License. This license is Permissive.
Permissive licenses have the least restrictions, and you can use them in most projects.
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PyAutoGalaxy releases are available to install and integrate.
Deployable package is available in PyPI.
Build file is available. You can build the component from source.
Top functions reviewed by kandi - BETA
kandi has reviewed PyAutoGalaxy and discovered the below as its top functions. This is intended to give you an instant insight into PyAutoGalaxy implemented functionality, and help decide if they suit your requirements.
- Fit a hyperparameter model
- Fit hyperfit with no noise
- Remove all hyper models from the model
- Generate a model from a result set
- Generate 1d plot of 1D image
- Creates a visual representation of mass objects from a list of mass objects
- Create a visual object based on a list of light profile objects
- Visualize the image
- Return a Plane instance from a model instance
- Calculate the log - likelihood function
- Plot the convergence grid of the grid
- Decomposes the convergence using cse
- Computes the deflections of the deflections in a 2D grid
- Compute the deflections for a 2D grid
- Log - likelihood function
- Calculate the kappa for a ludlow
- Decomposes the convergence using the cse
- Calculate the angular scaling factor between redshift and redshift
- Return 1D plot of the light profile
- Compute the potential grid from a 2D grid
- Create a stochastic model from a result object
- Calculate the deflections of deflections of a 2D grid
- Generate figure for 1D plot
- Plots the 1D plot of the image
- Visualize the hyperferometer
- Create a VisualS2D from a given plane
Get all kandi verified functions for this library.
PyAutoGalaxy Key Features
No Key Features are available at this moment for PyAutoGalaxy.
PyAutoGalaxy Examples and Code Snippets
No Code Snippets are available at this moment for PyAutoGalaxy.
Community Discussions
No Community Discussions are available at this moment for PyAutoGalaxy.Refer to stack overflow page for discussions.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install PyAutoGalaxy
You can install using 'pip install PyAutoGalaxy' or download it from GitHub, PyPI.
You can use PyAutoGalaxy like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
You can use PyAutoGalaxy like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
Support
For any new features, suggestions and bugs create an issue on GitHub.
If you have any questions check and ask questions on community page Stack Overflow .
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