Galactic and gravitational dynamics in Python

Overview

logo

Gala is a Python package for Galactic and gravitational dynamics.

Affiliated package Coverage Status Build status

Documentation

Documentation Status

The documentation for Gala is hosted on Read the docs.

Installation and Dependencies

conda PyPI

The easiest way to get Gala is to install with pip or conda.

The recommended install method is to use pip:

pip install gala

If you are on Linux or Mac, you can also install gala with conda using the conda-forge channel:

conda install gala --channel conda-forge

See the installation instructions in the documentation for more information.

Attribution

JOSS DOI

If you make use of this code, please cite the JOSS paper:

@article{gala,
  doi = {10.21105/joss.00388},
  url = {https://doi.org/10.21105%2Fjoss.00388},
  year = 2017,
  month = {oct},
  publisher = {The Open Journal},
  volume = {2},
  number = {18},
  author = {Adrian M. Price-Whelan},
  title = {Gala: A Python package for galactic dynamics},
  journal = {The Journal of Open Source Software}
}

Please also cite the Zenodo DOI DOI as a software citation - see the documentation for up to date citation information.

License

License

Copyright 2013-2021 Adrian Price-Whelan and contributors.

Gala is free software made available under the MIT License. For details see the LICENSE file.

Contributors

See the AUTHORS.rst file for a complete list of contributors to the project.

Comments
  • Incorporating Mass Evolution into Gala

    Incorporating Mass Evolution into Gala

    I was wondering whether there's a way to incorporate mass evolution or mass accretion over time of a halo into the orbital calculations of gala. I know it only takes a single halo mass numerical value and spits out an orbit, but is it possible to instead include a function for mass rather than a numerical value?

    question feature-request 
    opened by juliaespositon 11
  • [WIP] Simplify PhaseSpacePosition and Orbit classes

    [WIP] Simplify PhaseSpacePosition and Orbit classes

    This makes use of the representation differential classes in astropy/astropy#5871 to clean up a lot of the code. A natural byproduct of this is that CartesianPhaseSpacePosition and CartesianOrbit are no longer needed, since there is now a unified interface to any representations and their respective differentials.

    TODO:

    • [x] support <3D positions so nonlinear integrations work
    • [x] remove the velocity_coord_transforms.py and use the Differential classes instead
    • [x] figure out how to handle velocity frame transforms with the Differential classes
    • [x] update documentation and docstrings
    • [x] clean up all documentation that mentions Orbit or PhaseSpacePosition, check repr's (especially the orbits-in-detail.rst file
    • [x] make sure all mention of Cartesian* is gone
    • [x] make sure all code and doc tests run and don't use the old Cartesian* classes

    API-breaking changes:

    • Velocity frame transforms now return Differential classes
    • Velocity coord transforms are gone
    • CartesianPhaseSpacePosition and CartesianOrbit are deprecated
    opened by adrn 11
  • Add better interaction with and export to sympy, and uses sympy to implement more Hessian functions

    Add better interaction with and export to sympy, and uses sympy to implement more Hessian functions

    Describe your changes

    This adds a .to_sympy() classmethod to the potential classes. I've also then used this method with sympy to compute all of the Hessians, and implemented these using C code generated by sympy.

    Checklist

    • [x] Did you add tests?
    • [x] Did you add documentation for your changes?
    • [x] Did you add a changelog entry? (see CHANGES.rst)
    • [x] Are the CI tests passing?
    • [x] Is the milestone set?

    Amazingly, this closes #159, closes #56, closes #5, and closes #85 !!

    opened by adrn 7
  • plot_contours() requiring optional 'time' argument

    plot_contours() requiring optional 'time' argument

    running plot_contours() on an agama GalaPotential object requires a time object that is supposed to be optional, and forcing the variable to be a single value does not resolve the issue.wasn't encountering this issue until I updated agama and gala to their most recent versions. error stack below:

    grid = np.linspace(-15,15,64)
    fig,ax = plt.subplots(1, 1, figsize=(5,5))
    fig = galapot.plot_contours(grid=(grid,grid,0), cmap='Greys', ax=ax,time=1)
    
    /srv/conda/envs/notebook/lib/python3.8/site-packages/gala/potential/potential/core.py in plot_contours(self, grid, filled, ax, labels, subplots_kw, **kwargs)
        530                 r[ii] = slc
        531 
    --> 532             Z = self.energy(r*self.units['length']).value
        533 
        534             # make default colormap not suck
    
    /srv/conda/envs/notebook/lib/python3.8/site-packages/gala/potential/potential/core.py in energy(self, q, t)
        228         ret_unit = self.units['energy'] / self.units['mass']
        229 
    --> 230         return self._energy(q, t=t).T.reshape(orig_shape[1:]) * ret_unit
        231 
        232     def gradient(self, q, t=0.):
    
    /srv/conda/envs/notebook/lib/python3.8/site-packages/agama/py/pygama.py in <lambda>(q, t)
        898             except TypeError: PotentialBase.__init__(self, dict(), units=units)
        899             _agama.Potential.__init__(self, *args, **kwargs)
    --> 900             self._energy  = lambda q,t=0.: self.potential(q, t=t)
        901             self._density = lambda q,t=0.: _agama.Potential.density(self, q, t=t)
        902             self._gradient= lambda q,t=0.: -self.force(q, t=t)
    
    RuntimeError: Argument 'time', if provided, must be a single number or an array of the same length as points
    
    
    bug 
    opened by liljo0731 6
  • LeapfrogIntegrator will reverse the sign of velocity which may lead to incorrect result

    LeapfrogIntegrator will reverse the sign of velocity which may lead to incorrect result

    Hi, thank you for the great package. I realized the below code in the LeapfrogIntegrator may change the sign of the velocity when _dt is negative, which may change the result of the force function because it could depend on the velocity. In my case I add a dynamical friction term in my force function and LeapfrogIntegrator will give me incorrect results.

    https://github.com/adrn/gala/blob/782a8b1a19c8546d553b7c2122505e6ee82a93db/gala/integrate/pyintegrators/leapfrog.py#L146-L150

    opened by azz147 6
  • Make it so `autolim=True` doesn't set axis limits too small

    Make it so `autolim=True` doesn't set axis limits too small

    Describe your changes

    Added a check of the current axis limits when plotting Orbits with autolim=True to prevent Gala from making the axis limits too small to see everything already plotted.

    Checklist for contributor:

    • [x] Did you add tests?
    • [x] Did you add documentation for your changes?
    • [x] Did you reference any relevant issues?
    • [x] Did you add a changelog entry? (see CHANGES.rst)

    Checklist for maintainers:

    • [x] Are the CI tests passing?
    • [x] Is the milestone set?
    opened by TomWagg 6
  • Installation Issues

    Installation Issues

    Dear Community I´m having some when installing issues. When running the recommended way to install gala, !python -m pip install gala, I get various errors and warnings.

    imagen

    I suspect thsis is the reason why I get errors when running imports such as

    imagen imagen

    Thanks in advance

    opened by jortiz12 6
  • adding STcovar

    adding STcovar

    Describe your changes

    Checklist

    • [ ] Did you add tests?
    • [ ] Did you add documentation for your changes?
    • [ ] Did you reference any relevant issues?
    • [ ] Did you add a changelog entry? (see CHANGES.rst)
    • [ ] Are the CI tests passing?
    • [ ] Is the milestone set?
    opened by jngaravitoc 6
  • allow from_frame to be instance

    allow from_frame to be instance

    so that transformation works on skyoffset frames.

    Signed-off-by: Nathaniel Starkman [email protected]

    Describe your changes

    Checklist

    • [x] Did you add tests? There currently are no tests for get_transform_matrix
    • [x] Did you add documentation for your changes? yes
    • [x] Did you reference any relevant issues? yes
    • [ ] Did you add a changelog entry? (see CHANGES.rst)
    • [x] Are the CI tests passing? yes
    • [x] Is the milestone set?
    opened by nstarman 5
  • Segfault and core dump on manipulating hessians

    Segfault and core dump on manipulating hessians

    python 3.7 gala, numpy versions: 1.0, 1.16.4

    I get core dump / seg fault from doing the follwing:

    import astropy.units as u
    from gala.potential import BovyMWPotential2014
    
    BovyMWPotential2014().hessian([[0, 8, 0]]*u.kpc)
    

    Tracebacks: https://gist.github.com/smoh/0e803684b14d87bba4a97e5bb3e33bb0 1.out: beginning of errors from Red Hat 2.out: full traceback from Mac OSX 10.14.4

    In both I did fresh install with conda

    conda create -n gala-test
    conda install -c conda-forge astro-gala
    

    Any ideas?

    bug 
    opened by smoh 5
  • Add

    Add "fast" option to pericenter/apocenter and support multiple orbits

    Right now, .pericenter() and .apocenter() are slow because they do interpolation to figure out a precise value. There should be a fast=True option that skips the interpolation.

    We also need to support these methods for multiple orbits in the same object.

    bug enhancement priority:medium 
    opened by adrn 5
  • Fixed the oph19_to_icrs function

    Fixed the oph19_to_icrs function

    Describe your changes

    Fixed the bug described in this issue where the OrphanKoposov19 coordinate transformation called the wrong function.

    Checklist

    • [ ] Did you add tests?
    • [ ] Did you add documentation for your changes?
    • [x] Did you reference any relevant issues?
    • [x] Did you add a changelog entry? (see CHANGES.rst)
    • [x] Are the CI tests passing?
    • [x] Is the milestone set?
    opened by sophialilleengen 0
  • OrphanKoposov19 stream-to-ICRS transformation uses wrong fct

    OrphanKoposov19 stream-to-ICRS transformation uses wrong fct

    The OprhanKoposov19 oph19_to_icrs() fct returns OrphanNewberg10 matrix instead of Koposov19 matrix. In this line, galactic_to_orp() should be replaced by icrs_to_orp19().

    opened by sophialilleengen 2
  • CylSpline not C-enabled

    CylSpline not C-enabled

    Bug report from @abonaca: Not able to use the CylSpline potential with MockStream functionality because:

    ValueError: Input potential must be C-enabled: one or more components in the input external potential are Python-only.
    
    bug 
    opened by adrn 0
  • Improve speed of CylSplinePotential

    Improve speed of CylSplinePotential

    Right now it is very slow because it must construct a spline object with the input grids each time the energy/gradient/density functions are called. It might be possible to store this object on the Wrapper class and pass a pointer in to C. To do this, we need to add functionality to the potential classes (actually the struct types) to support having an array of pointers that get passed around.

    enhancement feature-request 
    opened by adrn 0
Releases(v1.6.1)
  • v1.6.1(Nov 7, 2022)

    Changelog included below:

    New Features

    • Added a .replicate() method to Potential classes to enable copying potential objects but modifying some parameter values.

    • Added a new potential class MN3ExponentialDiskPotential based on Smith et al. (2015): an approximation of the potential generated by a double exponential disk using a sum of three Miyamoto-Nagai disks.

    • The Orbit.estimate_period() method now returns period estimates in all phase-space components instead of just the radial period.

    • Added a store_all flag to the integrators to control whether to save phase-space information for all timesteps or only the final timestep.

    • Added a plot_rotation_curve() method to all potential objects to make a 1D plot of the circular velocity curve.

    • Added a new potential for representing multipole expansions MultipolePotential.

    • Added a new potential CylSplinePotential for flexible representation of axisymmetric potentials by allowing passing in grids of potential values evaluated grids of R, z values (like the CylSpline potential in Agama).

    • Added a show_time flag to Orbit.animate() to control whether to show the current timestep.

    • Changed Orbit.animate() to allow for different marker_style and segment_style options for individual orbits by passing a list of dicts instead of just a dict.

    • Added an experimental new class SCFInterpolatedPotential that accepts a time series of coefficients and interpolates the coefficient values to any evaluation time.

    Bug fixes

    • Fixed a bug where the NFWPotential energy was nan when evaluating at the origin, and added tests for all potentials to check for a finite value of the potential at the origin (when expected).

    • Fixed a bug in NFWPotential.from_M200_c() where the incorrect scale radius was computed (Cython does not always use Python 3 division rules for dividing integers!).

    • Fixed a bug in the (C-level/internal) estimation of the 2nd derivative of the potential, used to generate mock streams, that affects non-conservative force fields.

    API changes

    • The Orbit.estimate_period() method now returns period estimates in all phase-space components instead of just the radial period.
    Source code(tar.gz)
    Source code(zip)
  • v1.3(Oct 30, 2020)

  • v1.2(Jul 13, 2020)

  • v0.2.2(Oct 7, 2017)

    gala is an Astropy-affiliated Python package for galactic dynamics. Python enables wrapping low-level languages (e.g., C) for speed without losing flexibility or ease-of-use in the user-interface. The API for gala was designed to provide a class-based and user-friendly interface to fast (C or Cython-optimized) implementations of common operations such as gravitational potential and force evaluation, orbit integration, dynamical transformations, and chaos indicators for nonlinear dynamics. gala also relies heavily on and interfaces well with the implementations of physical units and astronomical coordinate systems in the Astropy package (astropy.units and astropy.coordinates).

    Source code(tar.gz)
    Source code(zip)
  • v0.2.1(Jul 21, 2017)

    Gala is a Python package for Galactic astronomy and gravitational dynamics. The bulk of the package centers around implementations of gravitational potentials, numerical integration, and nonlinear dynamics.

    Source code(tar.gz)
    Source code(zip)
  • v0.1.3(Feb 23, 2017)

    Gala is a Python package for Galactic astronomy and gravitational dynamics. The bulk of the package centers around implementations of gravitational potentials, numerical integration, and nonlinear dynamics.

    Source code(tar.gz)
    Source code(zip)
Owner
Adrian Price-Whelan
Adrian Price-Whelan
Learning to Simulate Dynamic Environments with GameGAN (CVPR 2020)

Learning to Simulate Dynamic Environments with GameGAN PyTorch code for GameGAN Learning to Simulate Dynamic Environments with GameGAN Seung Wook Kim,

199 Dec 26, 2022
Adversarial Robustness Toolbox (ART) - Python Library for Machine Learning Security - Evasion, Poisoning, Extraction, Inference - Red and Blue Teams

Adversarial Robustness Toolbox (ART) is a Python library for Machine Learning Security. ART provides tools that enable developers and researchers to defend and evaluate Machine Learning models and ap

3.4k Jan 04, 2023
Official implementation of the paper Do pedestrians pay attention? Eye contact detection for autonomous driving

Do pedestrians pay attention? Eye contact detection for autonomous driving Official implementation of the paper Do pedestrians pay attention? Eye cont

VITA lab at EPFL 26 Nov 02, 2022
A simple library that implements CLIP guided loss in PyTorch.

pytorch_clip_guided_loss: Pytorch implementation of the CLIP guided loss for Text-To-Image, Image-To-Image, or Image-To-Text generation. A simple libr

Sergei Belousov 74 Dec 26, 2022
Code corresponding to The Introspective Agent: Interdependence of Strategy, Physiology, and Sensing for Embodied Agents

The Introspective Agent: Interdependence of Strategy, Physiology, and Sensing for Embodied Agents This is the code corresponding to The Introspective

0 Jan 10, 2022
4th place solution for the SIGIR 2021 challenge.

SIGIR-2021 (Tinkoff.AI) How to start Download train and test data: https://sigir-ecom.github.io/data-task.html Place it under sigir-2021/data/. Run py

Tinkoff.AI 4 Jul 01, 2022
A framework for using LSTMs to detect anomalies in multivariate time series data. Includes spacecraft anomaly data and experiments from the Mars Science Laboratory and SMAP missions.

Telemanom (v2.0) v2.0 updates: Vectorized operations via numpy Object-oriented restructure, improved organization Merge branches into single branch fo

Kyle Hundman 844 Dec 28, 2022
Image segmentation with private İstanbul Dataset

Image Segmentation This repo was created for academic research and test result. Repo will update after academic article online. This repo contains wei

İrem KÖMÜRCÜ 9 Dec 11, 2022
Easy and Efficient Object Detector

EOD Easy and Efficient Object Detector EOD (Easy and Efficient Object Detection) is a general object detection model production framework. It aim on p

381 Jan 01, 2023
Validated, scalable, community developed variant calling, RNA-seq and small RNA analysis

Validated, scalable, community developed variant calling, RNA-seq and small RNA analysis. You write a high level configuration file specifying your in

Blue Collar Bioinformatics 917 Jan 03, 2023
IA for recognising Traffic Signs using Keras [Tensorflow]

Traffic Signs Recognition ⚠️ 🚦 Fundamentals of Intelligent Systems Introduction 📄 Development of a neural network capable of recognizing nine differ

Sebastián Fernández García 2 Dec 19, 2022
Unofficial & improved implementation of NeRF--: Neural Radiance Fields Without Known Camera Parameters

[Unofficial code-base] NeRF--: Neural Radiance Fields Without Known Camera Parameters [ Project | Paper | Official code base ] ⬅️ Thanks the original

Jianfei Guo 239 Dec 22, 2022
Faune proche - Retrieval of Faune-France data near a google maps location

faune_proche Récupération des données de Faune-France près d'un lieu google maps

4 Feb 15, 2022
Myia prototyping

Myia Myia is a new differentiable programming language. It aims to support large scale high performance computations (e.g. linear algebra) and their g

Mila 456 Nov 07, 2022
Enabling dynamic analysis of Legacy Embedded Systems in full emulated environment

PENecro This project is based on "Enabling dynamic analysis of Legacy Embedded Systems in full emulated environment", published on hardwear.io USA 202

Ta-Lun Yen 10 May 17, 2022
Codes for paper "Towards Diverse Paragraph Captioning for Untrimmed Videos". CVPR 2021

Towards Diverse Paragraph Captioning for Untrimmed Videos This repository contains PyTorch implementation of our paper Towards Diverse Paragraph Capti

Yuqing Song 61 Oct 11, 2022
A LiDAR point cloud cluster for panoptic segmentation

Divide-and-Merge-LiDAR-Panoptic-Cluster A demo video of our method with semantic prior: More information will be coming soon! As a PhD student, I don'

YimingZhao 65 Dec 22, 2022
Reverse engineer your pytorch vision models, in style

🔍 Rover Reverse engineer your CNNs, in style Rover will help you break down your CNN and visualize the features from within the model. No need to wri

Mayukh Deb 32 Sep 24, 2022
A comprehensive and up-to-date developer education platform for Urbit.

curriculum A comprehensive and up-to-date developer education platform for Urbit. This project organizes developer capabilities into a hierarchy of co

Sigilante 36 Oct 04, 2022
The pytorch implementation of the paper "text-guided neural image inpainting" at MM'2020

TDANet: Text-Guided Neural Image Inpainting, MM'2020 (Oral) MM | ArXiv This repository implements the paper "Text-Guided Neural Image Inpainting" by L

LisaiZhang 75 Dec 22, 2022