pip install pyfits==3.5

[DEPRECATED] Please use astropy.io.fits instead.

Source
Among top 5% packages on PyPI.
Over 19.6K downloads in the last 90 days.

Commonly used with pyfits

Based on how often these packages appear together in public requirements.txt files on GitHub.

catalyst

Catalyst. PyTorch framework for DL research and development.

segmentation-models-pytorch

Image segmentation models with pre-trained backbones. PyTorch.

casadi

CasADi -- framework for algorithmic differentiation and numeric optimization

deeptoolsintervals

A python module creating/accessing GTF-based interval trees with associated meta-data

py2bit

A package for accessing 2bit files using lib2bit

interval

Python interval and interval set implementation

hyperspectral

A frugal python package with some hyperspectral data goodies.

nb2plots

Converting between ipython notebooks and sphinx docs

pyFFTW

A pythonic wrapper around FFTW, the FFT library, presenting a unified interface for all the supported transforms.

extinctions

Extinction laws, maps and corrections

spanner

An accumulation of utilities / convenience functions for python

shape

UNKNOWN

dask-ms

xarray Datasets from CASA Tables.

pymbar

Python implementation of the multistate Bennett acceptance ratio (MBAR) method.

mcpartools

Set of tools to parallelize MC calculations on clusters

sdeint

Numerical integration of stochastic differential equations (SDE)

fodeint

Numerical integration of fractional ordinary differential equations (FODE)

distob

Distributed computing made easier, using remote objects

beprof

Beam Profile Analysing Tools

Version usage of pyfits

Proportion of downloaded versions in the last 3 months (only versions over 1%).

3.5

14.90%

3.3

5.99%

3.2.4

3.88%

3.2.3

3.81%

3.1.6

3.54%

3.2.2

3.40%

3.2

3.26%

3.2.1

3.26%

3.1.5

3.07%

3.1.2

3.04%

3.1.3

3.02%

3.4

2.93%

3.0.13

2.90%

3.0.12

2.88%

3.1

2.84%

3.1.4

2.80%

3.0.11

2.77%

3.1.1

2.67%

3.0.7

2.50%

3.0.6

2.48%

3.0.9

2.48%

3.0.10

2.47%

3.0.8

2.45%

3.0.5

2.44%

3.0.4

2.43%

3.0.2

2.40%

3.0.3

2.39%

3.0

2.37%

3.0.1

2.37%

2.4.0

1.16%

2.3.1

1.11%