slsDetectorPackage/docs/src/installation.rst

Installation

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

Build from source

1. Download Source Code from github

git clone https://github.com/slsdetectorgroup/slsDetectorPackage.git --branch 6.1.1

Pybind for Python
v7.0.0+:
  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.

# 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

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
# then press [g] - generate

Example cmake options	Comment
-DSLS_USE_PYTHON=ON	Python
-DPython_FIND_VIRTUALENV=ONLY	Python from only the conda environment
-DZeroMQ_HINT=/usr/lib64	Use system zmq instead
-DSLS_USE_GUI=ON	GUI

Build using in-built cmk.sh script

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

Usage: ./cmk.sh [-b] [-c] [-d <HDF5 directory>] [e] [g] [-h] [i] [-j <Number of threads>] 
[-k <CMake command>] [-l <Install directory>] [m] [n] [-p] [-q <Zmq hint directory>] 
[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
-q: Zmq hint directory
-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

#To use the system zmq (/usr/lib64) instead
./cmk.sh -cbj5 -q /usr/lib64

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

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 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

Build this documentation

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 sphinx_rtd_theme breathe

# 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