Skip to main content

Galaxian Luminosity Function Constructor package using the 1/Vmax estimator and Schechter model.

Project description

Luminosity Function Constructor and Modeller

This packag allows the user to construct and model Galaxian Luminosity Functions using the $\frac{1}{V_{max}}$ estimator and Schechter function.

PyPI PyPI - Python Version PyPI - Downloads GitHub issues GitHub stars GitHub forks GitHub license

Installation

Use the package manager pip to install lumfunc.

pip install lumfunc

Usage

import lumfunc as lf
import numpy as np

lf.get_maggy(np.array([10, 100, 20])) # returns maggy values
get_maggy( )

Converts magnitudes into maggies.

lf.get_maggy(np.array([10, 100, 20])) 
# returns array([1.e-04, 1.e-40, 1.e-08])

get_patches( )

Divides survey into equally distributed and equally sized patches. Returns labels for patches from RA, Dec, number of patches and patch center guesses.

lf.get_patches(np.array([20, 21, 22, 20, 21, 22]),
            np.array([20, 21, 22, 20, 21, 22]),
            3,
            np.array([[20, 21], [22, 20], [21, 22], [20, 21], [22, 20],
                      [21, 22]]),
            survey='kids',
            numba_installed=True,
            plot_savename='test_patches.png')
# Displays the plot

get_patches

Dependencies

PyPI PyPI PyPI PyPI

Contributing

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

Please make sure to update tests as appropriate.

License

MIT

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

lumfunc-0.2.1.tar.gz (2.1 MB view details)

Uploaded Source

Built Distribution

lumfunc-0.2.1-py3-none-any.whl (13.2 kB view details)

Uploaded Python 3

File details

Details for the file lumfunc-0.2.1.tar.gz.

File metadata

  • Download URL: lumfunc-0.2.1.tar.gz
  • Upload date:
  • Size: 2.1 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.5.0.1 requests/2.23.0 setuptools/42.0.2 requests-toolbelt/0.9.1 tqdm/4.43.0 CPython/3.7.6

File hashes

Hashes for lumfunc-0.2.1.tar.gz
Algorithm Hash digest
SHA256 75100340fb901f58eddae821b0ba47258e0e28a56da16c4d310037464ab49e80
MD5 7b06822680300ed4059963517bc44b8a
BLAKE2b-256 4f03ef59623e10221b624fecbdb6adf24a28ee66384474249b5550f5c042b335

See more details on using hashes here.

File details

Details for the file lumfunc-0.2.1-py3-none-any.whl.

File metadata

  • Download URL: lumfunc-0.2.1-py3-none-any.whl
  • Upload date:
  • Size: 13.2 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.5.0.1 requests/2.23.0 setuptools/42.0.2 requests-toolbelt/0.9.1 tqdm/4.43.0 CPython/3.7.6

File hashes

Hashes for lumfunc-0.2.1-py3-none-any.whl
Algorithm Hash digest
SHA256 f9ce68920b4caa54571145c7652f2cbaae9e7b9761278084a655b594c252f49a
MD5 89362c86e81b08db54b26d44dd95df89
BLAKE2b-256 6183a42d84fcf755b1ed9860b3eed1ffa67b36ca19b2679ad4ba1620eb6283ad

See more details on using hashes here.

Supported by

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