Getting Started

Overview of Requirements


Manual Installation

What follows is a self-contained installation manual, though for problematic installs of any of the sub packages, it’s definitely best to visit the main docs on the main software site (which are always linked below in each subsection).


powderday currently only works with python 2.x with provisional support for python 3.x (i.e. it should work though there may be issues yet outstanding – please do file an issue in on the BitBucket site if you find a 3.x issue)). The code was developed on, and principally tested with python 2.7.

This said, the code will be robust with python 3.x starting in Summer of 2019.

As you will see, powderday currently requires a particular branch of yt. As a result, one path that we have seen work well for users is to set up a different python environment for the powderday installation. This could look something like (assuming a conda installation of python):

>conda create --name pd_environment python=2.7
>source activate pd_environment

(And then when you want to exit the environment, you can type):

>source deactivate pd_environment

Then, whenever you’re in the pd_environment, everything you install will remain contained to that particular installation of python, and not conflict with any of your other installed packages.


You’ll need this to clone powderday using mercurial (hg). If you don’t have mercurial, you can install it in your pd_environment via:

>source activate pd_environment
>conda install mercurial


Simply clone the latest and greatest from the repo:

>hg clone

And that’s it! Once it’s cloned, there’s no subsidiary installation commands.


yt 3.x comes bundled with Hyperion, so it is not necessary to install it on its own. However, as of Summer 2019, development has begun on making powderday use yt 4.x, the ‘demeshed’ version of yt. The powderday - yt 4.x update is in its early stages and is not expected to function properly just yet. That being said, development is taking place on the pd-4.x branch of powderday, and instructions for setting it up to run with yt 4.x are at the bottom of this section.


fsps can be checked out with:

> git clone

and directions to the installation are in the Manual.

It’s likely going to be necessary downstream when installing python-fsps to have the -fPIC flags set in fsps when making. So, in the Makefile of fsps, set:

>F90FLAGS = -O -cpp -fPIC

if your gcc version is lower than 4.3.0, or:

>F90FLAGS = -03 -mtune=native -cpp -fPIC

if gcc is version 4.3.0 or higher. This can be checked with gcc --version. Additionally, at this time powderday doesn’t work with the default MIST Isochrones. To fix this, you’ll need to edit sps_vars.f90 in fsps to look like:

!------set the isochrone library------!
#define MIST 0
!Padova models circa 2008
#define PADOVA 1
#define PARSEC 0
#define BASTI 0
#define GENEVA 0

To explicitly compile:

make clean

Finally, the SPS_HOME variable must be set in your environment to point to the FSPS/src directory. For example, if your environment is bash, in your .bashrc set something along the lines of:

>export SPS_HOME=/Users/desika/fsps/


powderday depends on python hooks for fsps written by Daniel Foreman-Mackey and others called python-fsps. You can install from the GitHub page:

>git clone
>cd python-fsps
>python install

You can test the installation by opening python and typing:

>import fsps


Hyperion is the main work horse of powderday. The full directions for installation are well-described on the main Installation page for Hyperion. Here, we summarize the installation which should get most users through without any real difficulty.

There are two ways to install Hyperion. The first is via conda:

>conda install -c conda-forge hyperion

Note, this will eventually become deprecated for powderday (or at least modified as the Hyperion conda install ships with yt 3.x, and eventual upgrade to yt 4.x is coming in Summer 2019.

The second and manual way to install Hyperion follows: 1. First download the tarball and unpack it.:

>tar -xzvf
  1. Install the fortran dependencies:

    >cd deps/fortran
    >python <prefix>

where <prefix> is where you want the libraries to be installed. To avoid conflicts with other packages, I usually install somewhere like:

>python /usr/local/hyperion

as suggested by the Hyperion docs. Ensure that the following commands return something sensible:

>which mpif90
>which h5fc

if not, your path probably needs to include wherever the <prefix> directory pointed to. 3. Install any remaining python dependencies. These are listed here 4. Install Hyperion itself. To do this:

>python install


>python install --user

if you don’t have root access. At this point:

>import hyperion

from within python should work, and typing:


at the command line should return something along the lines of:

>usage: hyperion [-h] [-f] [-m n_cores] input output
>hyperion: error: too few arguments

if not, check the the path that is near one of the last lines of the installation (that is something associated with the number 755) and make sure it’s in your path. Ir’s most likely to be a python binaries directory.

You then have to install the Fortran Binaries:

>./configure  --prefix=prefix
>make install

where the prefix is wherever you installed the Fortran libraries before. Make sure this works by typing at the command line:


which should return something like:

>Usage: hyperion_sph [-f] input_file output_file

.. _Hyperion_dust:

Hyperion Dust Files

Unless you’ve written your own dust files, you will likely want to use the pre-compiled dust files developed by Tom Robitaille (though don’t ship with Hyperion due to their size). To install these download them here: Then to install:

>tar -xvzf hyperion-dust-xxx.tar.gz
>cd hyperion-dust-0.1.0
>python build_dust

If you want to use the PAH model in powderday, you’ll additionally need these files in the same dust directory. To download, click on the link, then click ‘raw’ on the right side of each page.


Please note the caveat that the PAH files are generated using some approxmations described in Robitaille et al., and we encourage the user of these PAH files to read this paper, especially section 3.4.2.

yt-4.x configuration [WIP]

First, it is recommended to make a new python environment in which to run the 4.x development branch:

> conda create -n pd4env python=2.7
> conda activate pd4env

Since Hyperion comes with yt 3.x, it must be installed using the --no-deps flag, since you will install the dependencies manually in the next step:

> conda install --no-deps -c conda-forge hyperion

Now, install all of the dependencies Hyperion needs, except yt:

> conda install -c conda-forge astropy atomicwrites attrs backports backports.functools_lru_cache backports.shutil_get_terminal_size backports_abc configparser contextlib2 cycler cython dbus decorator enum34 expat fastcache fontconfig freetype funcsigs functools32 futures gettext glib gmp gmpy2 gst-plugins-base gstreamer h5py hdf5 hyperion-fortran icu importlib_metadata ipython ipython_genutils jpeg kiwisolver libblas libcblas libgfortran-ng libiconv liblapack libpng libuuid libxcb libxml2 linecache2 matplotlib more-itertools mpc mpfr mpi mpich mpmath numpy openblas packaging pathlib2 pcre pexpect pickleshare pluggy prompt_toolkit pthread-stubs ptyprocess py pygments pyparsing pyqt pytest python-dateutil pytz qt scandir simplegeneric singledispatch sip six subprocess32 sympy tornado traceback2 traitlets unittest2 wcwidth xorg-libxau xorg-libxdmcp xz zipp

Now, clone the 4.x development branch from the yt source repository and build it:

> git clone
> cd yt/
> git checkout yt-4.0
> python develop

Now, to check that everything worked, make sure the output of the following commands look something like this:

> which yt

> ipython
In [1]: import yt
In [2]: yt.__version__
Out[2]: '4.0.dev0'

As long as the rest of powderday’s dependencies have been installed, at this point you should be good to go.

Troubleshooting your Installation

python-fsps installation issues

1. python-fsps can’t find f2py

f2py is a numpy package that is sometimes named f2py2.7 by numpy. At the same time, python-fsps expects it to be called f2py (as it sometimes is; for example in Anaconda). So, you might need to locate f2py (it ships with yt, so if you for example use the yt python) you need to link the following files:

>cd /Users/desika/yt-x86_64/bin
>ln -s f2py2.7 f2py


>cd /Users/desika/yt-x86_64/lib/python2.7/site-packages
>ln -s numpy/f2py/ f2py

This should hopefully fix it.

  1. Issues with ‘f2py’ in the python-fsps installation:

    Numpy has made some changes to f2py in the 1.10.x version of numpy. The easiest fix is to use a non 1.10.* version of numpy (thanks to Ben Johnson for finding this).

3. python-fsps has mysterious installation failures. Often this has to do with a bad FSPS compilation. Even if it seems like FSPS has compiled, it may not actually execute properly if the correct compilers aren’t set in the MakeFile. Thanks to Ena Choi for pointing this one out.

Hyperion Installation Issues

  1. Manual installations seem to not be fully updated from the Hyperion website. The following issues are known (uncovered by Katarina Kraljic)

    1. Hyperion-0.9.10 does not contain the /deps/fortran directory. It will be necesary to take this from version 0.9.9

    2. /deps/fortran/ hardcodes some links that do not exist anymore. The URLs should be updated as:

      ZLIB_URL = “” HDF5_URL = ‘

    3. Hyperions configure file doesn’t have an option for an MPI

    compiler that is mpif90.openmpi. One option is to add this to the configure file around line 1940:

    if test "$mpi_compiler" == mpif90.openmpi
          mpi_compiler=`basename $(mpif90 -show | awk {'print $1'})`