Skip to main content

A framework for generating deep-learning SKA radio telescope & cosmological hydrodynamical simulation data

Project description

#+AUTHOR: phdenzel
#+TITLE: skais-mapper
#+DATE: 2022-09-06 Tue
#+OPTIONS: author:nil title:t date:nil timestamp:nil toc:nil num:nil \n:nil

[[https://pypi.org/project/skais-mapper][https://img.shields.io/pypi/v/skais-mapper.svg]]
[[https://pypi.org/project/skais-mapper][https://img.shields.io/pypi/pyversions/skais-mapper.svg]]
[[https://www.gnu.org/licenses/gpl-3.0][https://img.shields.io/badge/License-GPL%20v3-blue.svg]]


*** Table of Contents

- [[#requirements][Requirements]]
- [[#install][Install]]
- [[#usage][Usage]]
- [[#data][Data]]
- [[#license][License]]



~skais-mapper~ is a tool for generating, plotting, and pre-processing
hydrodynamics simulation (image) data for state-of-the-art generative
AI models.


** Requirements

~skais-mapper~ is mostly built on python, but also includes some C
extensions for the compute-intensive raytracing (building and
visualizing datasets). Building from scratch thus requires ~cython~,
however ~skais~ ships with pre-compiled C files, making the minimal
requirements

- ~python >= 3.10~
- ~gcc~ (on linux) / ~clang~ (on macOS)

Also see ~pyproject.toml~ for the relevant python packages.


** Install

It is recommended to install ~skais-mapper~ in a virtual environment
via ~uv~. For this, run

#+begin_src shell
uv sync
#+end_src

Alternatively, you can simply run

#+begin_src shell
python setup.py build_ext --inplace
pip install [-e] .
#+end_src

If you want to compile the C extension from the cython files directly,
run in advance to the above

#+begin_src shell
python setup.py build_c [-a]
#+end_src


*** On Nix(OS)

For Nix(OS) users, the repository includes a ~flake.nix~ file. It
allows to create a development environment compatible with standard
~uv~ use.


** Usage

~skais-mapper~ implements a few sub-commands for generating and
manipulating simulation data. Use the following to see what valid
sub-commands exist:

#+begin_src shell
[uv run] skais-mapper -h
#+end_src

~skais-mapper~ sub-commands implement the hydra configuration
management framework. For more information on sub-command usage,
inspect the ~skais_mapper/configs/~ directory, or use:

#+begin_src shell
[uv run] skais-mapper [sub-command] -h
#+end_src

For instance, the command to generate 1000 images from snapshot 50 is
as follows:

#+begin_src shell
[uv run] skais-mapper generate +experiment=tng50-1-50-2D-0000-1000
#+end_src


** Data

Currently, this framework is fully compatible with SPH data from the
AREPO simulator, in particular the
[[https://www.tng-project.org/data/][IllustrisTNG suite]]. It
provides utility routines to fetch isolated halos from simulations
snapshots and various raytracing algorithms for 2D column density
projections of these halos and its galaxies. The framework generates
HDF5 files with image datasets of various galactic properties, such as
dark matter, star, or gas column density distributions.


** License

~skais-mapper~ is distributed under the terms of the
[[https://spdx.org/licenses/GPL-3.0-or-later.html][GNU General Public
License v3.0 or later]] license.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

skais_mapper-0.1.16.tar.gz (270.5 kB view details)

Uploaded Source

Built Distributions

If you're not sure about the file name format, learn more about wheel file names.

skais_mapper-0.1.16-cp312-cp312-musllinux_1_2_x86_64.whl (901.0 kB view details)

Uploaded CPython 3.12musllinux: musl 1.2+ x86-64

skais_mapper-0.1.16-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl (897.0 kB view details)

Uploaded CPython 3.12manylinux: glibc 2.17+ x86-64manylinux: glibc 2.28+ x86-64

skais_mapper-0.1.16-cp311-cp311-musllinux_1_2_x86_64.whl (907.1 kB view details)

Uploaded CPython 3.11musllinux: musl 1.2+ x86-64

skais_mapper-0.1.16-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl (901.5 kB view details)

Uploaded CPython 3.11manylinux: glibc 2.17+ x86-64manylinux: glibc 2.28+ x86-64

skais_mapper-0.1.16-cp310-cp310-musllinux_1_2_x86_64.whl (866.5 kB view details)

Uploaded CPython 3.10musllinux: musl 1.2+ x86-64

skais_mapper-0.1.16-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl (862.1 kB view details)

Uploaded CPython 3.10manylinux: glibc 2.17+ x86-64manylinux: glibc 2.28+ x86-64

File details

Details for the file skais_mapper-0.1.16.tar.gz.

File metadata

  • Download URL: skais_mapper-0.1.16.tar.gz
  • Upload date:
  • Size: 270.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.12.9

File hashes

Hashes for skais_mapper-0.1.16.tar.gz
Algorithm Hash digest
SHA256 aa3c4c9164952bd635491cf97e078ef53829f5f62498d869b4b2638a9166da97
MD5 34d2ebfb870ca5f990847c45002ed2d3
BLAKE2b-256 77a1d9b859e4a64c16d31c3efd6f9432d2267df4a3db981162a97653b27acd7f

See more details on using hashes here.

File details

Details for the file skais_mapper-0.1.16-cp312-cp312-musllinux_1_2_x86_64.whl.

File metadata

File hashes

Hashes for skais_mapper-0.1.16-cp312-cp312-musllinux_1_2_x86_64.whl
Algorithm Hash digest
SHA256 0a658a11a7e04e7bdf97ef07cbb84bf640954eb1cd071682f43a6fad728d2610
MD5 774e819e0020c7215ee90ca272774869
BLAKE2b-256 b5aa3fa7a0bc5c6c703447a67f9209ddfab422c95f513ce35eed5db9483a87a0

See more details on using hashes here.

File details

Details for the file skais_mapper-0.1.16-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for skais_mapper-0.1.16-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 91f2c141f91162a8700e360df7cdade221deebda5dace0c43c87a1e5b7712e38
MD5 515a73162d117e96d19db00c1714b6d3
BLAKE2b-256 364668227b0a340a2b20861e145c9355f62f2515f21e14e3172afe8e8d33b7a7

See more details on using hashes here.

File details

Details for the file skais_mapper-0.1.16-cp311-cp311-musllinux_1_2_x86_64.whl.

File metadata

File hashes

Hashes for skais_mapper-0.1.16-cp311-cp311-musllinux_1_2_x86_64.whl
Algorithm Hash digest
SHA256 8eb3575771af3492697d1da29bfaa198451f9c86ffa271248aaf0db2639b3c6c
MD5 0054870e67b1d6c8b06f4729997d2e9d
BLAKE2b-256 70b19afd19a0329de99aeecb0327ee7745531627e16f1c7be01ebfab1fd96bb3

See more details on using hashes here.

File details

Details for the file skais_mapper-0.1.16-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for skais_mapper-0.1.16-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 7a0d8b0a9bd95c9048a4eec63ef93baa04b708037bdfee723160261f6d366f7b
MD5 a539fe17ec0e518daf5c23e478526cc4
BLAKE2b-256 d913cd4f6fbfa60661c7a4b5e625908c34012b284b43d5355c4fe2ff559fca56

See more details on using hashes here.

File details

Details for the file skais_mapper-0.1.16-cp310-cp310-musllinux_1_2_x86_64.whl.

File metadata

File hashes

Hashes for skais_mapper-0.1.16-cp310-cp310-musllinux_1_2_x86_64.whl
Algorithm Hash digest
SHA256 4386a59f5d5c09a4b9f0ee3792d0b92e47b4cea4cfdd8d55f9ba82a967d73278
MD5 e9692d6dac7bc1dfff75ef590d2ef856
BLAKE2b-256 9958be17e974628886c243f8988cfce5a22d69d30c25913fc174982bda15aaf1

See more details on using hashes here.

File details

Details for the file skais_mapper-0.1.16-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for skais_mapper-0.1.16-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 7326d83c8e9aff23c3d172d18d358f197d3d635d214e7f8137e92340e0fdaee3
MD5 30f4c7c7d9e12d6a3da547165627560a
BLAKE2b-256 3f98d4750b8eb546fcebb2943d5a97e9eae9b775913b209cfb63f1c1ebd37286

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page