Dependencies

Before building from source make sure that you have the software wiki installed. If installing using conda, conda will manage the dependencies. Avoid also installing packages with pip.

Documentaion

Detailed documentation including installation can be found in the software wiki.

Different releases can be found on the official site.

Firmware compatiblity can be found in firmware page

Installation

1. Install binaries using conda

Conda is not only useful to manage python environments but can also be used as a user space package manager. Dates in the tag (for eg. 2020.07.23.dev0) are from the developer branch. Please use released tags for stability.

We have three different packages available:

• slsdetlib shared libraries and command line utilities
• slsdetgui GUI
• slsdet Python bindings

#Add channels for dependencies and our library
conda config --add channels conda-forge
conda config --add channels slsdetectorgroup
conda config --set channel_priority strict

#create and activate an environment with our library
#replace 6.1.1 with the required tag
conda create -n myenv slsdetlib=6.1.1
conda activate myenv

#ready to use
sls_detector_get exptime
etc ...

# List available versions
# lib and binaries
conda search slsdetlib
# python
conda search slsdet
# gui
conda search slsdetgui

2. Build from source

2.1 Download Source Code from github

git clone https://github.com/slsdetectorgroup/slsDetectorPackage.git --branch 7.0.0

Note: For v6.x.x of slsDetectorPackage and older, refer pybind11 notes on cloning.

2.2 Build from source

Build using CMake

# outside slsDetecorPackage folder
mkdir build && cd build

# configure & generate Makefiles using cmake
# by listing all your options (alternately use ccmake described below)
# cmake3 for some systems
cmake ../slsDetectorPackage -DCMAKE_INSTALL_PREFIX=/your/install/path

# compiled to the build/bin directory
make -j12 #or whatever number of cores you are using to build

# install headers and libs in /your/install/path directory
make install

Instead of the cmake command, one can use ccmake to get a list of options to configure and generate Makefiles at ease.

# ccmake3 for some systems
ccmake ..
 
# choose the options
# first press [c] - configure (unil you see [g])
# then press [g] - generate

Example cmake options	Comment
-DSLS_USE_PYTHON=ON	Python
-DPython_FIND_VIRTUALENV=ONLY	Python from only the conda env
-DSLS_USE_GUI=ON	GUI
-DSLS_USE_HDF5=ON	HDF5
-DSLS_USE_SIMULATOR=ON	Simulator

Note: For v7.x.x of slsDetectorPackage and older, refer zeromq notes for cmake option to hint library location.

Build using in-built cmk.sh script

The binaries are generated in slsDetectorPackage/build/bin directory.

Usage: $0 [-b] [-c] [-d <HDF5 directory>] [-e] [-g] [-h] [-i]
[-j <Number of threads>] [-k <CMake command>] [-l <Install directory>]
[-m] [-n] [-p] [-r] [-s] [-t] [-u] [-z]
-[no option]: only make
-b: Builds/Rebuilds CMake files normal mode
-c: Clean
-d: HDF5 Custom Directory
-e: Debug mode
-g: Build/Rebuilds gui
-h: Builds/Rebuilds Cmake files with HDF5 package
-i: Builds tests
-j: Number of threads to compile through
-k: CMake command
-l: Install directory
-m: Manuals
-n: Manuals without compiling doxygen (only rst)
-p: Builds/Rebuilds Python API
-r: Build/Rebuilds only receiver
-s: Simulator
-t: Build/Rebuilds only text client
-u: Chip Test Gui
-z: Moench zmq processor


# display all options
./cmk.sh -?

# new build and compile in parallel (recommended basic option):
./cmk.sh -cbj5

# new build, python and compile in parallel:
./cmk.sh -cbpj5

#For rebuilding only certain sections
./cmk.sh -tg #only text client and gui
./cmk.sh -r #only receiver

Note: For v7.x.x of slsDetectorPackage and older, refer zeromq notes for cmk script option to hint library location.

Build on old distributions

If your linux distribution doesn't come with a C++11 compiler (gcc>4.8) then it's possible to install a newer gcc using conda and build the slsDetectorPackage using this compiler

#Create an environment with the dependencies
conda create -n myenv gxx_linux-64 cmake zmq
conda activate myenv

# outside slsDetecorPackage folder
mkdir build && cd build
cmake ../slsDetectorPackage -DCMAKE_PREFIX_PATH=$CONDA_PREFIX
make -j12

Note: For v7.x.x of slsDetectorPackage and older, refer zeromq notes for dependencies for conda.

Build slsDetectorGui (Qt5)

1. Using pre-built binary on conda

conda create -n myenv slsdetgui=7.0.0
conda activate myenv

2. Using system installation on RHEL7

yum install qt5-qtbase-devel.x86_64
yum install qt5-qtsvg-devel.x86_64 

3. Using system installation on RHEL8

yum install qt5-qtbase-devel.x86_64
yum install qt5-qtsvg-devel.x86_64 
yum install expat-devel.x86_64

4. Using conda

#Add channels for dependencies and our library
conda config --add channels conda-forge
conda config --add channels slsdetectorgroup
conda config --set channel_priority strict

# create environment to compile
# on rhel7
conda create -n slsgui zeromq gxx_linux-64 gxx_linux-64 mesa-libgl-devel-cos6-x86_64 qt
# on fedora or newer systems
conda create -n slsgui zeromq qt

# when using conda compilers, would also need libgl, but no need for it on fedora unless maybe using it with ROOT

# activate environment
conda activate slsgui

# compile with cmake outside slsDetecorPackage folder
mkdir build && cd build
cmake ../slsDetectorPackage -DSLS_USE_GUI=ON
make -j12

# or compile with cmk.sh
cd slsDetectorPackage
./cmk.sh -cbgj9

Note: For v7.x.x of slsDetectorPackage and older, refer zeromq notes for dependencies for conda.

Build documentation from package

The documentation for the slsDetectorPackage is build using a combination of Doxygen, Sphinx and Breathe. The easiest way to install the dependencies is to use conda

conda create -n myenv python=3.12 sphinx sphinx_rtd_theme breathe doxygen numpy

# using cmake or ccmake to enable DSLS_BUILD_DOCS
# outside slsDetecorPackage folder
mkdir build && cd build
cmake ../slsDetectorPackage -DSLS_BUILD_DOCS=ON

make docs # generate API docs and build Sphinx RST
make rst # rst only, saves time in case the API did not change

Pybind and Zeromq

Pybind11 for Python

v8.0.0+: pybind11 is built

• by default from tar file in repo (libs/pybind/v2.1x.0.tar.gz)
• or use advanced option SLS_FETCH_PYBIND11_FROM_GITHUB [link].
  • v9.0.0+: pybind11 (v2.13.6)
  • v8.x.x : pybind11 (v2.11.0)

v7.x.x: pybind11 packaged into ‘libs/pybind’. No longer a submodule. No need for “recursive” or “submodule update”.

Older versions: pybind11 is a submodule. Must be cloned using “recursive” and updated when switching between versions using the following commands.

# Note: Only for v6.x.x versions and older

# clone using recursive to get pybind11 submodule
git clone --recursive https://github.com/slsdetectorgroup/slsDetectorPackage.git

# update submodule when switching between releases
cd slsDetectorPackage
git submodule update --init

Zeromq

v8.0.0+: zeromq (v4.3.4) is built

• by default from tar file in repo (libs/libzmq/libzmq-4.3.4.tar.gz)
• or use advanced option SLS_FETCH_ZMQ_FROM_GITHUB [link].

v7.x.x and older: zeromq-devel must be installed and one can hint its location using

• cmake option:’-DZeroMQ_HINT=/usr/lib64’ or
• option ‘-q’ in cmk.sh script: : ./cmk.sh -cbj5 -q /usr/lib64
• ‘zeromq’ dependency added when installing using conda

Support

[email protected]
[email protected]