Cppxfel Installation

This details the installation instructions for cppxfel on Linux and Mac OS X. cppxfel relies on three components:

• Boost libraries (thread and system) - these allow C++ to access threading over multiple cores.
• DIALS distribution - provides the cctbx libraries for L-BFGS refinement and some crystallographic functions, and the indexing algorithms from DIALS itself.
• cppxfel distribution - primarily written in C++, but some Python scripts to automate DIALS indexing and prepare the results for input into cppxfel.

These installation instructions are not finished and will not currently result in a working version of cppxfel.

Installing the boost libraries

The boost library is a dependency of cppxfel allowing it to run on multiple threads from within C++. Either download source and compile from boost website, or if you have user privileges, you can use a package manager.

With user privileges

You can use a package distributor to install the appropriate Boost package according to your OS flavour:

CentOS	Ubuntu	Mac OS X
yum install boost boost-devel	apt-get install libboost-all-dev	Install brew, then: brew install boost

We need to make sure the boost library is visible to the DIALS/cppxfel installation. To see where the boost library was installed:

locate libboost_thread-mt.so

This will show a directory e.g.

/usr/lib64/libboost_thread-mt.so

This should be set to the environment variable BOOST_LOCATION.

Bash shell	Csh shell
export BOOST_LOCATION="/usr/lib64/"	setenv BOOST_LOCATION /usr/lib64

Without user privileges

Download the Boost source code from the Boost website. For example, [Version 1.59.0]. Follow the instructions in Section 5 in Boost's [Getting Started - Unix Variants] page to compile the boost libraries required by cppxfel. Install these files to a suitable location by specifying an appropriate prefix that you have write privileges to.

Because you do not have user privileges and cannot install the libraries to a standard place, you will have to set the environment variable LD_LIBRARY_PATH to the path of the library, and you will also have to set the environment variable BOOST_LOCATION in order that cppxfel can find your boost libraries. You may want to append these to your .bashrc or .cshrc files.

Bash shell	Csh shell
export BOOST_LOCATION="/path/to/boost/lib/"	setenv BOOST_LOCATION /path/to/boost/lib/
export LD_LIBRARY_PATH=$LD_LIBRARY_PATH":/path/to/boost/lib/"	setenv LD_LIBRARY_PATH $LD_LIBRARY_PATH:/path/to/boost/lib/
Enter last line into ~/.bashrc	Enter last line into ~/.cshrc

DIALS distribution

Download the DIALS distribution for your flavour of OS from [the DIALS website]. Extract the dials-installer-dev to a new location. Navigate into this directory.

cd dials-installer-dev

Start the install command to a new directory to which you have write access.

./install --prefix=/absolute/path/to/dials

cppxfel distribution

The cppxfel source code must be downloaded into the modules directory.

cd /absolute/path/to/dials/modules

The repository can be cloned from the GitHub link for cppxfel.

git clone https://github.com/cppxfel/cppxfel.git

The DIALS distribution must be configured to compile the cppxfel code, and then the distribution must be compiled.

libtbx.configure cppxfel
cd ../build
make

Set the paths to the DIALS and cppxfel command line tools (bash):

. /absolute/path/to/dials/build/setpaths.sh

Bash shell	Csh shell
. /absolute/path/to/dials/build/setpaths.sh	source /absolute/path/to/dials/build/setpaths.csh

This needs to be repeated every time a new shell is started. Alternatively, place this in your appropriate file (bash)

Bash shell	Csh shell
test -r /absolute/path/to/dials/build/setpaths.sh && \ . /absolute/path/to/dials/build/setpaths.sh	test -r /absolute/path/to/dials/build/setpaths.csh && \ source /absolute/path/to/dials/build/setpaths.csh
to ~/.bashrc	to ~/.cshrc

Confirm that cppxfel runs:

cppxfel.run

The output should look something like this:

Welcome to cppxfel version 1.0!
Please refer to & cite paper in Journal of Applied Crystallography (unpublished)

Command order for regular structure solution:
	cppxfel.run_dials shot*.pickle
	cppxfel.input_gen
	cppxfel.run -i integrate.txt
	cppxfel.run -i refine.txt
	cppxfel.run -i merge.txt

Other functions for assessing data quality:

Correlation between two MTZ files:

	cppxfel.run -cc firstFile.mtz secondFile.mtz [ambiguity] [lowRes] [highRes] [bins]

ambiguity: 0, 1, 2 or 3 - will compare different indexing solutions where the Bravais lattice symmetry is higher than that of the point group for certain space groups. Default 0
lowRes and highRes: set to resolution in Angstroms to bound the results, or set to 0 to take lowest/highest resolution data. Default 0, 0
bins: number of bins to report correlation statistics. Default 20.

Partiality CSV files:

	cppxfel.run -partiality reference.mtz ref-img-shot-number.mtz [highRes]

highRes: 0, 1, 2 or 3 - highest resolution reflection to report results on. Default 1.4
This outputs partiality_[m].csv where m is bin number, which can be imported into other graphing softwares such as R.

Merging statistics:

	cppxfel.run -rpim unmerged_file.mtz [lowRes] [highRes] [bins]
	cppxfel.run -rmeas unmerged_file.mtz [lowRes] [highRes] [bins]
	cppxfel.run -rmerge unmerged_file.mtz [lowRes] [highRes] [bins]

lowRes and highRes: set to resolution in Angstroms to bound the results, or set to 0 to take lowest/highest resolution data. Default 0, 0
bins: number of bins to report correlation statistics. Default 20.

If you see this, cppxfel has been installed. A pointer to the CCP4 symmetry libraries is required.

CCP4 Symmetry libraries

The cppxfel distribution requires the CCP4 symmetry libraries. This needs to be pointed to by the SYMINFO environment variable. To set this:

Bash shell	Csh shell
export SYMINFO="/absolute/path/to/cctbx/modules/ccp4io/libccp4/data/syminfo.lib"	setenv SYMINFO /absolute/path/to/cctbx/modules/ccp4io/libccp4/data/syminfo.lib

This will prevent run-time errors from the CCP4 library functions not being able to find its symmetry information library.

Next steps

Try running the tutorial on a set of 1000 images from CPV, starting with indexing.