Skip to main content

Dark Emulator

Anaconda-Server Badge Anaconda-Server Badge Anaconda-Server Badge Anaconda-Server Badge

A repository for a cosmology tool dark_emulator to emulate halo clustering statistics. The code is developed based on Dark Quest simulation suite (https://darkquestcosmology.github.io/). The current version supports the halo mass function and two point correlation function (both halo-halo and halo-matter cross).

Install

In order to install dark emulator package, use pip:

   pip install dark_emulator

or use conda:

   conda install -c nishimichi dark_emulator

Please note that updates on conda are currently halted due to an unresolved issue in conda build. Therefore, we recommend using the version in pip or installing from the source using the following command.

If the above does not work for you, you may download the source files from this repository and install via

python -m pip install -e .

after moving to the top directory of the source tree. In that case, you need to install george (a software package for the Gaussian process) and colossus

conda install -c conda-forge george
pip install colossus

From version 1.1.0, dark_emulator uses FFTLog implementation by Fang et al (2019); arXiv:1911.11947.

Usage

You can then check how Dark Emulator works by running a tutorial notebook at

docs/tutorial.ipynb
docs/tutorial-hod.ipynb

See also the documentation on readthedocs.

Code Paper

The main reference for our halo emulation strategy is: "Dark Quest. I. Fast and Accurate Emulation of Halo Clustering Statistics and Its Application to Galaxy Clustering", by T. Nishimichi et al., ApJ 884, 29 (2019), arXiv:1811.09504. Please also refer to the paper "Cosmological inference from emulator based halo model I: Validation tests with HSC and SDSS mock catalogs", by H. Miyatake et al., arXiv:2101.00113 for the implementation and performance of the halo-galaxy connection routines.

Metadata

Release files for dark-emulator 1.1.2

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for dark-emulator 1.1.2
File Size Uploaded
dark_emulator-1.1.2.tar.gz 3.9 MB Details

Built distribution (wheel)

Table of built distributions (wheels) for dark-emulator 1.1.2
File Interpreter ABI Platform
dark_emulator-1.1.2-py3-none-any.whl Python 3 none any Details

Total release size: 6.8 MB

Release files / dark_emulator-1.1.2.tar.gz

Download URL dark_emulator-1.1.2.tar.gz
Size 3.9 MB
Tags Source
SHA-256 checksum
How to use checksums
0f4f5623d73eb8a3be8325b3c294a5eca39f52f810914e4a5f8e8d8d15048f73
BLAKE2b-256 checksum
How to use checksums
e90d57c810a997c1d7c4cd2fd849145beb20f067d39d4f2105bf4b529fd3d4cc
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/4.0.2 CPython/3.10.7

Release files / dark_emulator-1.1.2-py3-none-any.whl

Download URL dark_emulator-1.1.2-py3-none-any.whl
Size 2.9 MB
Tags Python 3
SHA-256 checksum
How to use checksums
c855d8bb2e37efca79d01dc58c44458f71b26c2fda101c4704d608fcc0438f58
BLAKE2b-256 checksum
How to use checksums
322a2d0bad8a980b3ab1f008869462c502d5fe0314c5654b0fb9922fa47258cb
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/4.0.2 CPython/3.10.7

Release history Release notifications | RSS feed

This release

1.1.2 This release

2 release files

1.1.1

2 release files

1.0.23

2 release files

1.0.22

2 release files

1.0.21

2 release files

1.0.20

2 release files

1.0.19

2 release files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page