Analysis tools for multi-technique astronomical data and hdust models
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Analysis tools for multi-technique astronomical data and hdust models.

Full documentation at

About hdust code: Carciofi & Bjorkman (2006, 2008).

pyhdust should be independent of plataform (Linux, Mac, Windows) and compatible with any version of Python (superior to 2.7).

How to install/uninstall

I strongly suggest users to use the pip plataform:

pip install pyhdust

If your are not the root of the system, add the flag --user to the command above. Dependencies (as filters efficiency and stellar evolution models) are included in the subdirectories.


Never combine sudo with --user! Otherwise you will face critical permission problems for your packages!


To use the pyhdust scripts, the binaries path of your pip installation directory must be in system PATH. If you don't find them, adapt the following command to your $HOME/.bashrc:


pyhdust requires numpy and six modules. Optionally, it makes use of:

  • matplotlib
  • pyfits
  • emcee
  • pIDLy
  • scipy
  • pyqt_fit

To only update the package:

pip install -U --no-deps pyhdust

-U forces the upgrade and --no-deps do not reinstall the dependent packages.

For other options, consult the full documentation.

How to use the modules

To make use of all routines, the suggestion is to import them as follows:

import pyhdust as hdt
import pyhdust.beatlas as bat
import pyhdust.fieldstars as fls
import pyhdust.images as img
import pyhdust.input as inp
import pyhdust.interftools as intt
import pyhdust.jdcal as jdcal
import pyhdust.poltools as polt
import pyhdust.phc as phc
import pyhdust.rotstars as rot
import pyhdust.singscat as sst
import pyhdust.spectools as spt
import pyhdust.stats as stt


The code is free, available under the terms of the GNU GPL v3.0 license.