pySAC Guide

pySAC is a python package that is designed to enable analysis and plotting of VAC (Verstatile Advection Code) and SAC (Sheffield Advanced Code) as well as smaug, the GPGPU port of SAC.


pySAC is contained inside a DVS version control system called git, with a hosted repository on BitBucket. To obtain the latest version of the source code you can clone the git repository thus:

git clone

which you can then install using the included python setup script. There are two options at this point, you can install the code permantly or you can install it in ‘develop’ mode which enable you to edit the code in the directory in which you have just cloned it. To install in devlop mode do the following:

python develop

which, under linux you will need to run as root.

The following python packages are required to use pySAC:

  • matplotlib >= 1.1
  • h5py
  • numpy
  • scipy

Basic Usage

Once installed pySAC can be used by importing the component you wish to use in a python script or interpreter:

>>> import

to open a SAC file you can no do:

>>> myfile ="mysacfile.h5")

myfile now contains various routines to read the data in the file, as we shall see in more detail later.


The first role of pySAC is to enable the reading and writing of SAC or VAC files in either the VAC style fortran unformatted binary file type or the newer HDF5 file structures.

The basic components of any VAC/SAC filetype are:

  • x array: An array containing all coordinates at any point in the domain

  • y array: An array containing all the computed variables

  • header: A header, stored in some form consisting of at:
    • filehead - A not so descriptive file string
    • iteration number
    • physical time
    • number of dimensions
    • number of constant parameters in the equations
    • number of physcical varibles being solved for (in w array)
    • nx
    • the equation parameters
    • names for the varibles in the w array

pySAC implements a ‘VACdata’ class that will read either the VAC fortran type files or HDF5 files containing VAC/SAC data. There is a specification of VACdata to SACdata for SAC files with magnetic field and pertubation and background varibles in the w array.

SACdata implemetes methods to extract primative variables such as temperature and pressure.

File Description

Header Contents

The header of VAC / SAC files contains the same information irrespective of the file type. When saving a file using pySAC the routines will automatically reformat the header to fit the file. The keys in the header and examples are listed below:

header = {
            'filehead': '3Dmhd_33',
            'ndim': 3,
            'it': 0,
            't': 0,
            'nw': 13,
            'nx': [128,128,128],
            'varnames': ['z', 'x', 'y', 'h', 'm1', 'm2', 'm3', 'e', 'b1', 'b2', 'b3',
                         'eb', 'rhob', 'bg1', 'bg2', 'bg3', 'gamma', 'eta',
                         'grav1', 'grav2', 'grav3'],
            'neqpar': 7,
            'eqpar': [1.66666667, 0.0, 1.0, -274.0, 0.0, 0.0, 0.0]

Some extra parameters can be added for HDF5 files, namely: ‘filedesc’ which is a file desciption.

‘varnames’ should contain a label for each corrdinate dimension, a label for each varible in the w array, followed by each equation parameter. So

len(header['varnames']) == nx + nw + neqpar

The above example is not consitent with this.

VAC File Description

The unformatted FORTRAN binary files have the following format for each time step stored a header of the following form preceeds the data:

  • ‘filehead’ a string describing the file i.e. ‘2D_mhd22’

  • ‘params’ a list containing:

    iteration number, physical time, ndim, number of equation params, number of vars in w array i.e. [10, 11.2541, 2, 7, 9], [int, float, int, int, int]

  • nx coord dimensions e.g. [128,128,128]

  • ‘eqpar’ - equation parameters, neqpars floats.

  • varnames a list of strings nw long. Holds the names for all the w vars.

  • x array

  • w array

SAC HDF5 File Specification

A new file format to replace the unformatted FORTRAN binary files has been developed. The advantages of HDF5 are that it is a modern portable binary data format, that is well specified and has bany bindings for many different languages. The structure of a HDF5 file is very similar to a UNIX file system, where you have constructs like directories, each can contain sub-directories and also have metadata associated with them.

Below is the file structure for a SAC HDF5 file, attributes (metadata) are indicated with a - and data arrays are indicated with a +.


    -final t




It should be noted that any code written for this file structure should not use the names of the w arrays for any reason, they should be read with the sequential operators of the HDF5 library because there is no specification reason why they have to be numbered, and could definatley exceed 99999.


In this section we shall look at reading files using pySAC


These are the defualt binary file type that VAC/SAC uses.

WARNING: These files are compiler and machine dependant, they are not portable and should not be used over the far superior HDF5 files.

SAC HDF5 Files

This file type has been added to SAC to make the output standard and portable, also to enable parallel I/O.


Output in is done by writing out the current state of the VACdata object. To create a new file with data from elsewhere you would create a VACdata object with mode=’w’ and then assign data and the header:

myfile = sacio.VACdata("myoutfile.h5")
myfile.header = header
myfile.w = w_arr
myfile.x = x_arr

Each time step can then be written by a call to write_step:


remember to close the file when you are done:


for hdf5 files, close writes extra meta information to the file, so it is very important that it is called.

The output routines will automatically determine the file type.

It is also possible to save out to a different file, or file_type by first reading in a file:

myfile = sacio.VACdata("myinfile.h5")

then calling init_file() and write_step() for each iteration in the file:

for i in range(num_records):