INSTALL.md

Installation Instructions

System requirements: GalSim currently only supports Linux and Mac OSX.

Table of Contents:

1. Software required before building GalSim

2. Installing the GalSim Python package

3. Running tests and installing example executables

4. Platform-specific notes

5. More SCons options

6. Software required before building GalSim ===========================================

Please note: Mac users who want to use fink can skip down to Section 4.ii and use that to satisfy all dependencies before installing.

i) Python (2.6 or 2.7 series), with some additional modules installed

The interface to the GalSim code is via the Python package galsim, and its associated modules. Therefore you must have Python installed on your system. Python is free, and available from a number of sources online (see below). Currently GalSim only supports Python versions 2.6.X and 2.7.X, but earlier versions of Python 2.X may be supported in future: please let us know via Github if you need this support.

Many systems have a version of Python pre-installed. To check whether you already have a compatible version, type

python --version

at the terminal prompt. If you get a "Command not found" error, or the reported version is not 2.6.X or 2.7.X, you will need to install 2.6 or 2.7 series Python. In this case you should read the "Getting Python and required modules" section below.

It may be that there is or soon will be more than one version of Python installed on your operating system, in which case please see the "Making sure you are using the right Python" Section below.

Getting Python and required modules

For a list of places to download Python, see http://www.python.org/download/.

The GalSim package also requires

• the numerical Python module NumPy (http://www.numpy.org)

• the astronomical FITS file input/output module PyFITS available either as a standalone package: http://www.stsci.edu/institute/software_hardware/pyfits or as part of the astropy library: http://www.astropy.org/ The latter is preferred, since this is now where all future development of this package is happening.

• Optional dependency: the Python YAML parser and emitter module PyYAML (http://pyyaml.org/wiki/PyYAML) Note: PyYAML is in fact only required for full config file parsing functionality, and can be omitted if users are happy to use JSON-style config parsing or prefer to write python scripts directly.

• Optional dependency: PyAst WCS package. This is a really nice front end for the Starlink AST astrometry code. It seems to support pretty much every WCS encoding there is. (At least every one we tried.) Their preferred installation method is via pip: pip install starlink-pyast For more information, see their website: https://pypi.python.org/pypi/starlink-pyast/ With this installed, you can use the galsim.PyAstWCS class, which in turn means that galsim.FitsWCS will pretty much always work.

• Optional dependency: Astropy WCS package. We already mentioned astropy above for astropy.io.fits. Another package we can use from astropy is their WCS package, astropy.wcs. They cannot read all that many WCS types (compared to PyAst at least), but hopefully the functionality will include in time. Unfortunately, this package has scipy as a dependency, which is kind of a gargantuan package. But if you are willing to install that too, then you can use the galsim.AstropyWCS class.

These should installed onto your Python system so that they can be imported by:

>>> import numpy
>>> import astropy.io.fits  [ Either this (preferred)... ]
>>> import pyfits           [ ... or this.               ]
>>> import yaml             [ if using the galsim executable or otherwise
                              plan to parse .yaml configuration files ]
>>> import starlink.Ast     [ if planning to use PyAstWCS class ]
>>> import astropy.wcs      [ if planning to use AstropyWCS class ]

within Python. You can test this by loading up the Python interpreter for the version of Python you will be using with the GalSim toolkit. This is usually achieved by typing python or /path/to/executable/bin/python if your desired Python is not the system default, and typing the import commands above. If you get no warning message, things are OK.

If you do not have these modules, follow the links above or alternatively try easy_install (or equivalently /path/to/executable/bin/easy_install if your desired Python is not the default).

As an example, if using the default system Python, connected to the internet and with root/admin privileges simply type

easy_install numpy
easy_install pyfits
easy_install pyyaml

at the prompt. If not using an admin account, prefix the commands above with sudo and enter your admin password when prompted. The required modules should then be installed.

See http://packages.python.org/distribute/easy_install.html#using-easy-install for more details about the extremely useful easy_install feature.

Another option for installing these packages is pip. See pypi.python.org for details about getting this installed if you do not already have it on your system. Then

pip install numpy
pip install astropy
pip install pyyaml
pip install starlink-pyast
pip install scipy

Third party-maintained Python packages

There are a number of third party-maintained packages which bundle Python with many of the numerical and scientific libraries that are commonly used, and many of these are free for non-commercial or academic use.

One good example of such a package, which includes all of the Python dependencies required by GalSim (NumPy, PyFITS, PyYAML as well as SCons and nosetests; see Section 2 below) was the Enthought Python Distribution (EPD; see https://enthought.com/products/canopy/academic/ for the academic download instructions).

The new Enthought "Canopy" package, a successor to EPD, provides the same functionality. However, it has been found that Canopy on Mac OSX can give problems building against Boost.Python, another GalSim dependency. A solution to these issues is described here: https://github.com/GalSim-developers/GalSim/wiki/Installation-FAQ#wiki-canopy

Other re-packaged Python downloads can be found at http://www.python.org/download/.

Making sure you are using the right Python

Some users will find they have a few versions of Python around their operating system (determined, for example, using locate python at the prompt). A common way this will happen if there is already an older build (e.g. Python 2.4.X) being used by the operating system and then you install a newer version from one of the sources described above.

It will be important to make sure that the version of Python for which NumPy, PyFITS and PyYAML etc. are installed is also the one being used for GalSim, and that this is the one you want to use GalSim from! Knowing which installed version of Python will be used is also important for the installation of the Boost libraries (see Section 1.v, below).

To check which Python is your default you can identify the location of the executable by, for example, typing

which python

at the prompt. This will tell you the location of the executable, something like /path/to/executable/bin/python

If this is not the Python you want, please edit your startup scripts (e.g. .profile or .bashrc), and be sure to specify where your desired Python version resides when installing the Boost C++ libraries (see Section 1.v).

See Section 4 of this document for some suggestions about getting Python, Boost and all the other dependencies all working well together on your specific system.

ii) SCons (http://www.scons.org)

GalSim uses SCons to configure and run its installation procedures, and so SCons needs to be installed in advance. Versions 2.0 and 2.1 of SCons get reasonable testing with GalSim, but it should also work with 1.x versions. You can check if it is installed, and if so which version, by typing

scons --version

See Section 4 for some more suggestions about installing this on your platform.

iii) FFTW (http://www.fftw.org)

These Fast Fourier Transform libraries must be installed, as GalSim will link to them during the build. We require version 3 (or greater presumably), which is often distributed as fftw3. See Section 4 for some suggestions about installing this on your platform.

iv) TMV (http://code.google.com/p/tmv-cpp/) (version >= 0.72 required)

GalSim uses the TMV library for its linear algebra routines. You should download it from the site above and follow the instructions in its INSTALL file for how to install it. Usually installing TMV just requires the command

scons install PREFIX=<installdir>

but there are additional options you might consider, so you should read the TMV INSTALL file for full details. Also note, you may not need to specify the installation directory if you are comfortable installing it into /usr/local. However, if you are trying to install it into a system directory then you need to use sudo scons install [PREFIX=].

Note: On Mac OS 10.7, the Apple BLAS library has problems when run using multiple processes. So if you have such a system, we recommend getting a different BLAS library, such as ATLAS (and making sure TMV finds it instead of the system BLAS) or compiling TMV with no BLAS library at all (using the SCons option WITH_BLAS=false). Otherwise, Galsim programs may hang when run with multiple processes. e.g. scons tests by default uses multiple processes, and multiple people reported problems using the Apple system BLAS on OS 10.7.

v) Boost C++ (http://www.boost.org)

GalSim makes use of some of the Boost C++ libraries, and these parts of Boost must be installed. It is particularly important that your installed Boost library links to the same version of Python which which you will be using GalSim and on which you have installed NumPy and PyFITS (see Section ii, above). Boost can be downloaded from the above website, and must be installed per the (rather limited) instructions there, which essentially amount to using a command

./bootstrap.sh

(Additional bootstrap.sh options may be necessary to ensure Boost is built against the correct version of Python; see below).

followed by

./b2 link=shared
./b2 --prefix=<INSTALL_DIR> link=shared install

If you are installing to a system directory, the second needs to be run as root, of course: sudo ./b2... Also, you should be aware that if you are running b2 a second time, you should use b2 -a to tell boost to recompile everything rather than use the existing libraries.

The link=shared is necessary to ensure that they are built as shared libraries; this is automatic on some platforms, but not all.

Note: if you do not want to install everything related to Boost (which takes a while), you can restrict to Boost Python and math by using --with-python --with-math on the ./b2 commands. Currently we are only using Boost Python and parts of the math library so compiling and installing these two will likely be sufficient for the foreseeable future.

Once you have installed Boost, you can check that it links to the version of Python that will be used for GalSim and on which you have installed NumPy and PyFITS by typing

ldd <YOUR_BOOST_LIB_DIR>/libboost_python<POSSIBLE_SUFFIX>.so (Linux)
otool -L <YOUR_BOOST_LIB_DIR>/libboost_python<POSSIBLE_SUFFIX>.dylib (OSX)

(If the ldd command on Linux does not show the Python version, the command ls -l <YOUR_BOOST_LIB_LOCATION>/libboost_python* may show the version of libboost_python.so linked to, for example, libboost_python_py26.so.1.40.0. In such a case you can tell both the Python and Boost versions being used, 2.6 and 1.40.0, respectively, in this example.) On some Linux systems, ldd will not indicate the Python library against which boost was compiled; in this case, continue with the installation procedure and any issues will be revealed at a later stage.

If the Python library listed is the one you will be using, all is well. If not, Boost can be forced to use a different version by specifying the following options to the ./bootstrap.sh installation script (defaults in [] brackets):

• --with-python=PYTHON specify the Python executable [python]

• --with-python-root=DIR specify the root of the Python installation [automatically detected, but some users have found they have to force it to use a specific one because it detected the wrong one]

2. Installing the GalSim Python package =======================================

Once you have installed all the dependencies described above, you are ready to build GalSim. From the GalSim base directory (in which this INSTALL.md file is found) type

scons

If everything above was installed in fairly standard locations, this may work the first time. Otherwise, you may have to tell SCons where to find some of those libraries. There are quite a few options that you can use to tell SCons where to look, as well as other things about the build process. To see a list of options you can pass to SCons, type

scons -h

(See also Section 5 below.)

As an example, to specify where your TMV library is located, you can type

scons TMV_DIR=<tmv-dir>

where <tmv-dir> would be the same as the PREFIX you specified when installing TMV, i.e. The TMV library and include files are installed in <tmv-dir>/lib and <tmv-dir>/include. Some important options that you may need to set are:

• TMV_DIR: Explicitly give the TMV prefix

• FFTW_DIR: Explicitly give the FFTW prefix

• BOOST_DIR: Explicitly give the Boost prefix

• EXTRA_LIBS: Additional libraries to send to the linker

• EXTRA_INCLUDE_PATH: Extra paths for header files (separated by : if more than 1)

• EXTRA_FLAGS: Extra flags to send to the compiler other than what is automatically used. (e.g. -m64 to force 64 bit compilation)

Again, you can see the full list of options using scons -h.

Another common option is CXX=<c++compiler>. So, to compile with icpc rather than the default g++, type

scons CXX=icpc

One nice feature of SCons is that once you have specified a parameter, it will save that value for future builds in the file gs_scons.conf, so once you have the build process working, for later builds you only need to type scons. It can also be useful to edit this file directly -- mostly if you want to unset a parameter and return to the default value, it can be easier to just delete the line from this file, rather than explicitly set it back to the default value.

SCons caches the results of the various checks it does for the required external libraries (TMV, Boost, etc.). This is usually very helpful, since they do not generally change, so it makes later builds much faster. However, sometimes (rarely) SCons can get confused and not realized that things on your system have changed, which might cause problems for you. You can delete everything scons knows about what it has tried to build previously with

/bin/rm -rf .scon*

This will force SCons to recheck and recompile everything from scratch.

Once you have a successful build, you can install the GalSim library, Python modules, and header files into standard locations (like /usr/local and your Python site-packages directory) with

scons install

or

sudo scons install

If you want to install into a different location, the prefix for the library and header files can be specified with PREFIX=<installdir>, and the location for the Python modules can be specified with PYPREFIX=<pythondir>. So the command would be

scons install PREFIX=<installdir> PYPREFIX=<pythondir>

Note: if you specify a specific directory for the Python modules with PYPREFIX, this directory should be in the sys.path search path for the version of Python you are using. You can check with

python -c "import sys; print sys.path"

If your PYPREFIX directory is not there, then Python will not be able to find the installed galsim module. You should therefore add this directory to your PYTHONPATH environment variable. For example, if you use bash, then you should add the line

export PYTHONPATH=$PYTHONPATH:<pythondir>

where <pythondir> is the same directory you used above for PYPREFIX.

The installed files can be removed with the command

scons uninstall

Finally, to clean all compiled objects from the GalSim directory, you can use

scons -c

This is rather like a make clean command.

If you are having trouble with installing, you may find some helpful hints at the GalSim Installation FAQ page on the Wiki: https://github.com/GalSim-developers/GalSim/wiki/Installation%20FAQ

You can ask also about your particular problem on stackoverflow.com. Some of the GalSim developers have automatic alerts set up for the tag 'galsim'. So yout can ask your question there, and there is a good chance that it will be answered. You might also try searching that site to see if anyone else asked about the same problem.

If you are still having trouble, please consider opening a new issue on the GalSim Github page at https://github.com/GalSim-developers/GalSim/issues explaining what your particular problem is, and hopefully someone can help you figure out a solution.

3. Running tests and installing example executables ===================================================

You can run our test suite by typing

scons tests

This should compile the test suite and run it. The tests of our C++ library will always be run, but we use nosetests for our Python test suite, so that will only be run if nosetests is present on your system. We do not require this as a dependency, since you can still do everything with the GalSim library without this. But it is required for a complete run of the test suite.

To install nosetests, you can also use easy_install as described in Section 1 above (see also http://nose.readthedocs.org/en/latest/). Many third party- maintained Python distributions, such as the Enthought Python Distribution, include nosetests.

Note: if your system does not have nosetests installed, and you do not want to install it, you can run all the Python tests with the script run_all_tests in the tests directory. If this finishes without an error, then all the tests have passed.

4. Running example scripts ==========================

The examples directory has a series of demo scripts:

demo1.py, demo2.py, ...

These can be considered a tutorial on getting up to speed with GalSim. Reading through these in order will introduce you to how to use most of the features of GalSim in Python. To run these scripts, type (e.g.):

python demo1.py

You can also create executable versions of these scripts if you prefer by typing

scons examples

This will put executable versions (with the first line #!/bin/env python) in the examples_bin directory. (We do not include that first line by default, since you might specify a different python to be used. Running scons examples will put whatever python executable you specify after #!.)

There are also a corresponding set of config files:

demo1.yaml, demo2.yaml, ...

These files can be run using the executable galsim, and will produce the same output images as the Python scripts:

galsim demo1.yaml

They are also well commented, and can be considered a parallel tutorial for learning the config file usage of GalSim.

All demo scripts are designed to be run in the GalSim/examples directory. Some of them access files in subdirectories of the examples directory, so they would not work correctly from other locations.

4. Platform-specific notes ==========================

i) Linux

The vast majority of Linux distributions provide installable packages for most of our dependencies. In many cases, however, it is also necessary to install "-devel" or "-dev" packages (e.g. python-dev or libboost-dev on Debian- derivatives). However, as above we stress that you should make sure that the version of Python that Boost is built against must be the same as that you intend to use for running GalSim.

The solution may be to install Boost C++ manually. This can be done by following the instructions of Section 1.v), above.

ii) Mac OSX 10.8 and earlier

a) Use of Fink -- the fink (http://www.finkproject.org) package management software is popular with Mac users. Once it is installed, you can get either most or all of the prerequisites using it, depending on whether you want to use GalSim with the fink version of Python (e.g. that in /sw/bin/python) or the system Python (/usr/bin/python) or something else still.

It is in general a good idea to update fink prior to installing any new modules:

fink selfupdate
fink update-all

If you are happy with running GalSim using the fink version of python 2.7, you can install everything with the following command:

fink install galsim

and it should just work. However, there are some caveats that are worth knowing about (assuming your fink installation is in /sw):

1. This will install GalSim as a module of the python2.7 installed by fink.
   This is not the default Python (usually /usr/bin/python or some other package, such as EPD, if installed). Any Python scripts you write that use the galsim module should therefore have #!/sw/bin/python2.7 as the first line rather than the usual #!/usr/bin/env python. Similarly, if you want to use galsim in an interactive Python session, you should run /sw/bin/python2.7 (simply python2.7 may also work) rather than just python. (Of course, you can always change your PATH environment variable to make the fink Python the system default if you wish...)

2. The executable galsim, which parses YAML or JSON configuration files, will be installed in /sw/bin. You should not need to do anything special to use these, since /sw/bin should already be in your path if using fink.

3. If you want to run through the example scripts (such as the demo tutorials demo1.py, demo2.py etc. and the .yaml and .json config versions of the same demos), you will still need to download the GalSim tarball. But you can skip all the instructions above about installation and just use the fink version. So python2.7 demo1.py (assuming which python2.7 is the fink one) and galsim demo1.yaml should run those scripts for you.

4. If you want to work with GalSim as a developer, rather than just a user, then you cannot use the fink-installed GalSim. However, the process above will have installed all the prerequisites. So fink uninstall galsim will leave you able to install GalSim using the master branch with:

   scons TMV_DIR=/sw PYTHON=/sw/bin/python2.7

from within the repository base directory.

To run the unit tests, you will also need nosetests, which you can also get from fink:

fink install nose-py27
scons tests NOSETESTS=/sw/bin/nosetests

If you want to use the system Python, or some other version, then the fink Python installations will not work. You will need to manually install NumPy, PyFITS, PyYAML and nose, for example using easy_install, with your chosen Python.

For the system Python, you can use fink for Boost, but you will want a different package than the boost1.35.python27 that gets installed using fink install galsim above:

fink install scons fftw3 tmv0 boost1.46.1.cmake
scons TMV_DIR=/sw

For other Python versions, the fink-installed Boost usually will not work, so you can only use fink for SCons, FFTW and TMV. So you will probably need to install Boost manually. This can be done by following the instructions of Section 1.v), above.

b) MacPorts -- this is another popular Mac package management project (http://www.macports.org/) with similar functionality to fink. Neither TMV nor GalSim are currently on the official MacPorts distribution list, so users cannot find them by searching the MacPorts site. However, it is possible to install both TMV and GalSim, plus the other dependencies of GalSim, using MacPorts following the instructions below.

It is in general a good idea to upgrade all modules, prior to installing any new modules:

sudo port selfupdate
sudo port upgrade outdated

Below is a list of steps to take to install GalSim using MacPorts:

i) Take the `Portfiles` from the GalSim repository:
https://github.com/GalSim-developers/GalSim/blob/master/devel/ports.tar.gz
(If you do not clone the repository, there is a "copy" button on the website
that you can use to download the file directly.)
ii) Place the file in your home directory.
iii) `tar xvzf ports.tar.gz`
iv) `cd ports`
v) `sudo portindex`
vi) `sudo port install python27`
vii) `sudo port select --set python python27`
viii) `sudo sh -c "echo file:///Users/username/ports >>
      /opt/local/etc/macports/sources.conf"`
ix) `sudo port install galsim`
x) Add /opt/local/lib to DYLD_LIBRARY_PATH

Some users may find that the last step results in an inability to import the GalSim module. In that case, you can clear that addition to DYLD_LIBRARY_PATH and instead add /opt/local/lib to DYLD_FALLBACK_LIBRARY_PATH.

Notes on MacPorts with Mac OS X 10.8: The use of sudo in the above commands may elicit an error message that says "dyld: DYLD_ environment variables being ignored because main executable (/usr/bin/sudo) is setuid or setgid". This is the result of a bug in Mac OS X 10.8, and will not prevent the installation of GalSim with the above steps from being successful.

Notes on MacPorts version of gcc with Mac OS X 10.5.8: If you have installed a MacPorts version of gcc (e.g., "mp-gcc47"), it may not link correctly with the other MacPorts installed modules, which are compiled in the system gcc versions. To check what gcc versions are available to you, try the command

port select --list gcc

then switch to the system gcc version (either 4.0 or 4.2) with

sudo port select --set gcc gcc42

and compile GalSim with the system gcc.

c) Homebrew (http://mxcl.github.com/homebrew/) -- another package manager for Max OSX. Currently GalSim is available on homebrew, so it (plus dependencies) should be installable via

brew tap camphogg/science
brew install gal-sim

iii) Mac OSX 10.9 (Mavericks)

Most of what applies above for earlier Mac OSX versions seems to apply for GalSim on Mavericks too, although not all combinations have yet been tested.

However, it has been found that GalSim and its dependencies can be sensitive (e.g. Issue #483) to the fact that under Mavericks the system gcc is NOT in fact the Gnu Compiler Collection, but in fact Clang masquerading as such. This can lead to problems when linking libraries, as described in the following GalSim Wiki FAQ item: https://github.com/GalSim-developers/GalSim/wiki/Installation-FAQ#wiki-what-should-i-do-about-undefined-symbols-for-architecture-x86_64-errors

The best success seems to be achieved in Mavericks by explicitly specifying clang and clang++ as the compiler to GalSim and all its dependencies when building (as in the example above).

5. More SCons options =====================

Here is a fairly complete list of the options you can pass to SCons to control the build process. The options are listed with their default value. You change them simply by specifying a different value on the command line.

For example:

scons CXX=icpc TMV_DIR=~

(Unlike autotools, SCons correctly expands ~ to your home directory.) You can list these options from the command line with

scons -h

Basic flags about the C++ compilation (default values in parentheses)

• CXX (g++) specifies which C++ compiler to use.

• FLAGS ('') specifies the basic flags to pass to the compiler. The default behavior is to automatically choose good flags to use according to which kind of compiler you are using. This option overrides that and lets you specify exactly what flags to use.

• EXTRA_FLAGS ('') specifies some extra flags that you want to use in addition to the defaults that SCons determines on its own. Unlike the above option, this do not override the defaults, it just adds to them.

• DEBUG (True) specifies whether to keep the debugging assert statements in the compiled library code. They are not much of a performance hit, so it is generally worth keeping them in, but if you need to squeeze out every last bit of performance, you can set this to False.

• WARN (False) specifies whether to add warning compiler flags such as -Wall.

• PYTHON (/usr/bin/env python) specifies which version of Python you are planning to use GalSim with. If you choose not to use the default here, then you need to remember to use the correct Python version

Flags about where to install the library and modules

• PREFIX (/usr/local) specifies where to install the library when running scons install.

• PYPREFIX ([your python dir]/site-packages) specifies where to install the Python modules when running scons install.

• FINAL_PREFIX (PREFIX) specifies the final installation prefix if different from PREFIX. (This is only needed for things like fink, where they install into a staging area first before copying over to the final location.)

Flags that specify where to look for external libraries

• TMV_DIR ('') specifies the location of TMV if it is not in a standard location. This should be the same value as you used for PREFIX when installing TMV.

• TMV_LINK ('') specifies the location of the tmv-link file. Normally, this is in TMV_DIR/share, but if not, you can specify the correct location here.

• FFTW_DIR ('') specifies the root location of FFTW. The header files should be in FFTW_DIR/include and the library files in FFTW_DIR/lib.

• BOOST_DIR ('') specifies the root location of BOOST The header files should be in BOOST_DIR/include/boost and the library files in BOOST_DIR/lib.

• EXTRA_INCLUDE_PATH ('') specifies extra directories in which to search for header files in addition to the standard locations such as /usr/include and /usr/local/include and the ones derived from the above options. Sometimes the above options do not quite work, so you may need to specify other locations, which is what this option is for. These directories are specified as -I flags to the compiler. If you are giving multiple directories, they should be separated by colons.

• EXTRA_LIB_PATH ('') specifies extra directories in which to search for libraries in addition to the standard locations such as /usr/lib and /usr/local/lib. These directories are specified as -L flags to the linker. If you are giving multiple directories, they should be separated by colons. To add the library /blah/libfoo.a, specify EXTRA_LIB_PATH=/blah/ EXTRA_LIBS=foo.

• EXTRA_PATH ('') specifies directories in which to search for executables (notably the compiler, although you can also just give the full path in the CXX parameter) in addition to the standard locations such as /usr/bin and /usr/local/bin. If you are giving multiple directories, they should be separated by colons.

• IMPORT_PATHS (False) specifies whether to import extra path directories from the environment variables: PATH, C_INCLUDE_PATH, LD_LIBRARY_PATH and LIBRARY_PATH. If you have a complicated setup in which you use these environment variables to control everything, this can be an easy way to let SCons know about these locations.

• IMPORT_ENV (True) specifies whether to import the entire environment from the calling shell. The default is for SCons to use the same environment as the shell from which it is called. However, sometimes it can be useful to start with a clean environment and manually add paths for various things, in which case you would want to set this to False.

• EXTRA_LIBS ('') specifies libraries to use in addition to what SCons finds on its own. This might be useful if you have a non-standard name for one of the external libraries. e.g. If you want to use the Intel MKL library for the FFTW library, SCons will not automatically try that, so you could add those libraries here. If there is more than one, they should be quoted with spaces between the different libraries. e.g. EXTRA_LIBS="mkl_intel mkl_intel_thread mkl_core"

• IMPORT_PREFIX (True) specifies whether to include the directories PREFIX/include, PREFIX/lib and PREFIX/bin as part of the standard path lists. Normally, you install everything in the same place, so it is useful to search those locations for some of the prerequisite packages, so the default is True. But occasionally, this might be inconvenient, so you can turn this feature off.

Miscellaneous flags

• NOSETESTS (nosetests) specifies which version of nosetests you want to use for running the unit tests. If you specified a non-default Python, then there is a possibility that the standard nosetests executable in your path will not work (since it might be for a different version of Python). In that case, specify the correct nosetests here.

• CACHE_LIB (True) specifies whether to cache the results of the library checks. While you are working one getting the prerequisites installed properly, it can be useful to set this to False to force SCons to redo all of its library checks each time. Once you have a successful build, you should set it back to True so that later builds can skip those checks.

• WITH_PROF (False) specifies whether to use the compiler flag -pg to include profiling info for gprof.

• MEM_TEST (False) specifies whether to test the code for memory leaks.

• TMV_DEBUG (False) specifies whether to turn on extra (slower) debugging statements within the TMV library.

• WITH_OPENMP (False) specifies whether to use OpenMP to parallelize some parts of the code. (Note: We do not actually use OpenMP currently, so this does not do anything.)

• USE_UNKNOWN_VARS (False) specifies whether to accept scons parameters other than the ones listed here. Normally, another name would indicate a typo, so we catch it and let you know. But if you want to use other scons options that we did not list here, you would want to also set this to True.