Linux - Ubuntu
In order to compile entire CC3D code on Linux (not just the developer zone) you need to miniconda. Once you have this tool it will take care of installing all the dependencies you need to to compie CC3D
Follow instructions from Miniconda website: https://docs.anaconda.com/free/miniconda/
Next let’s install mamba which give you much faster package dependency resolution. Open new terminal and tun the following:
conda install -c conda-forge mamba
Once you have those tools you are ready to create conda environment into which we will install all the libraries and compilers that are needed for CC3D compilation. There are multiple ways to handle the installation of those prerequisites but the easiest one is to use environment.yaml files where we list all needed packages and provide this file to conda which takes care of installing them.
Note
From now on I will assume that all git repositories and files have been saved to /home/m/src-cc3d . You may want to adjust this path so that it corresponds to working folder that exists on your file system. In all commands below you would replace /home/m/src-cc3d with the folder of your choice.
First, let’s clone CompuCell3D, cc3d-player5 and cc3d-twedit5 git repositories to /home/m/src-cc3d
mkdir -p /home/m/src-cc3d
cd /home/m/src-cc3d
git clone https://github.com/CompuCell3D/CompuCell3D.git
git clone https://github.com/CompuCell3D/cc3d-player5.git
git clone https://github.com/CompuCell3D/cc3d-twedit5.git
Next, let’s create file /home/m/src-cc3d/environment.yaml with the following content:
channels:
- conda-forge
- compucell3d
dependencies:
# compile dependencies
- cmake=3.21
- swig>=4
- numpy=1.24
- gcc_linux-64
- gxx_linux-64
- python 3.10
- vtk=9.2
- eigen
- tbb-devel=2021
- boost=1.84
# libxcrypt dependency was discovered during actual compilation - searched pkgs sub-folders for all occurrences of crypt.h
- libxcrypt
- psutil
- deprecated
- cc3d-network-solvers>=0.3.0
# cc3d run dependencies
- scipy
- pandas
- jinja2
- deprecated
- psutil
- simservice
- notebook
- ipywidgets
- ipyvtklink
- sphinx
- graphviz
# player dependencies
- webcolors
- requests
- pyqt=5
- pyqtgraph
# twedit dependencies
- chardet
- pyqtwebkit
- qscintilla2
- pywin32 # [win]
Once we created environment.yaml let’s cd to /home/m/src-cc3d and create environment called cc3d_compile by running the following command:
cd /home/m/src-cc3d
mamba env create -f environment.yaml --name cc3d_compile
The output of of the last command should look something like this
...
+ xorg-xproto 7.0.31 h7f98852_1007 conda-forge/linux-64 Cached
+ xz 5.2.6 h166bdaf_0 conda-forge/linux-64 Cached
+ yaml 0.2.5 h7f98852_2 conda-forge/linux-64 Cached
+ yarl 1.9.4 py310h2372a71_0 conda-forge/linux-64 Cached
+ zeromq 4.3.5 h59595ed_1 conda-forge/linux-64 Cached
+ zipp 3.17.0 pyhd8ed1ab_0 conda-forge/noarch Cached
+ zlib 1.2.13 hd590300_5 conda-forge/linux-64 Cached
+ zstd 1.5.5 hfc55251_0 conda-forge/linux-64 Cached
Summary:
Install: 375 packages
Total download: 49MB
──────────────────────────────────────────────────────────────────────────────────────────────────────────────────
libxslt 254.3kB @ 1.5MB/s 0.2s
ipywidgets 113.6kB @ 671.0kB/s 0.2s
widgetsnbextension 886.4kB @ 2.3MB/s 0.4s
jupyterlab_widgets 187.1kB @ 479.9kB/s 0.4s
pywin32 8.2kB @ 14.4kB/s 0.4s
pyqtgraph 695.0kB @ 983.5kB/s 0.3s
qtwebkit 15.6MB @ 3.9MB/s 3.8s
python 31.3MB @ 4.4MB/s 7.0s
Downloading and Extracting Packages
Preparing transaction: done
Verifying transaction: done
Executing transaction: /
-
done
#
# To activate this environment, use
#
# $ conda activate cc3d_compile
#
# To deactivate an active environment, use
#
# $ conda deactivate
After environment in installed let’s activate this environment - as suggested but above printout by running:
conda activate cc3d_compile
At this point we are ready to configure CompuCell3D for compilation. We will be using CMake.
Note
It is important to replace /home/m/src-cc3d with the directory into which you cloned the three CompuCell3D repositories repository
Let’s run the following command:
cmake -S /home/m/src-cc3d/CompuCell3D/CompuCell3D -B /home/m/src-cc3d/CompuCell3D_build -DPython3_EXECUTABLE=/home/m/miniconda3/envs/cc3d_compile/bin/python -DNO_OPENCL=ON -DBUILD_STANDALONE=OFF -DOPENGL_gl_LIBRARY=/usr/lib/x86_64-linux-gnu/libGL.so -DOPENGL_glx_LIBRARY=/usr/lib/x86_64-linux-gnu/libGLX.so -G "Unix Makefiles" -DCMAKE_INSTALL_PREFIX=/home/m/src-cc3d/CompuCell3D_install
Let’s explain command line arguments we used when calling cmake command
-S - specifies location of the CompUCdl3D source code and the actual C++ code resides indeed in /home/m/src-cc3d/CompuCell3D/CompuCell3D
-B specifies the location of the temporary compilation files
-DPython3_EXECUTABLE= specifies the location of the python interpreter. Notice that it points to the conda environment we creates (/envs/cc3d_compile/bin/python). Important: depending where you installed your miniconda you may need to replace /home/m/miniconda3 with the path you miniconda installation on your machine
``-DNO_OPENCL=ON `` - is a CC3D-specific setting that tells cmake to skip generating GPU diffusion solvers. Note, the support for OpenCL on OSX is/might be problematic, hence we are using morte conservative setting and skip generation of those solvers
-DBUILD_STANDALONE=OFF - is a CC3D-specific setting that tells cmake to install all python packages to python interpreter directory - i.e. inside /home/m/miniconda3/envs/cc3d_compile
-DCMAKE_INSTALL_PREFIX= - specifies location of installed CompuCell3D binaries
-DOPENGL_gl_LIBRARY=/usr/lib/x86_64-linux-gnu/libGL.so - specifies location of OpenGL libraries
-DOPENGL_glx_LIBRARY=/usr/lib/x86_64-linux-gnu/libGLX.so - - specifies location of OpenGL libraries
-G "Unix Makefiles" instructs cmake to generate unix Makefiles that we will use for compilation of CompuCell3D
Note
The two OpenGL options (-DOPENGL_gl_LIBRARY=/usr/lib/x86_64-linux-gnu/libGL.so and -DOPENGL_glx_LIBRARY=/usr/lib/x86_64-linux-gnu/libGLX.so ) work only on Ubuntu. If you are compiling CC3D on different distribution e.g RedHat you may need to adjust those. Also if you have a better solution for finding those libraries using Cmake commands please share it with us!
After running the las t command the output should look as follows:
...
-- Found X11: /home/m/miniconda3/envs/cc3d_compile/include
-- Looking for XOpenDisplay in /home/m/miniconda3/envs/cc3d_compile/lib/libX11.so;/home/m/miniconda3/envs/cc3d_compile/lib/libXext.so
-- Looking for XOpenDisplay in /home/m/miniconda3/envs/cc3d_compile/lib/libX11.so;/home/m/miniconda3/envs/cc3d_compile/lib/libXext.so - found
-- Looking for gethostbyname
-- Looking for gethostbyname - found
-- Looking for connect
-- Looking for connect - found
-- Looking for remove
-- Looking for remove - found
-- Looking for shmat
-- Looking for shmat - found
-- Looking for IceConnectionNumber in ICE
-- Looking for IceConnectionNumber in ICE - found
-- Found EXPAT: /home/m/miniconda3/envs/cc3d_compile/lib/libexpat.so (found version "2.5.0")
-- Found double-conversion: /home/m/miniconda3/envs/cc3d_compile/lib/libdouble-conversion.so
-- Found LZ4: /home/m/miniconda3/envs/cc3d_compile/lib/liblz4.so (found version "1.9.4")
-- Found LZMA: /home/m/miniconda3/envs/cc3d_compile/lib/liblzma.so (found version "5.2.6")
-- Found JPEG: /home/m/miniconda3/envs/cc3d_compile/lib/libjpeg.so (found version "80")
-- Found TIFF: /home/m/miniconda3/envs/cc3d_compile/lib/libtiff.so (found version "4.6.0")
-- Found Freetype: /home/m/miniconda3/envs/cc3d_compile/lib/libfreetype.so (found version "2.12.1")
VTK_MAJOR_VERSION=9
NUMPY_INCLUDE_DIR
VTK_LIB_DIRS
THIS IS cc3d_py_source_dir: /home/m/src-cc3d/CompuCell3D/CompuCell3D/../cc3d
USING BUNDLE
-- Configuring done
CMake Warning (dev) at compucell3d_cmake_macros.cmake:200 (ADD_LIBRARY):
Policy CMP0115 is not set: Source file extensions must be explicit. Run
"cmake --help-policy CMP0115" for policy details. Use the cmake_policy
command to set the policy and suppress this warning.
File:
/home/m/src-cc3d/CompuCell3D/CompuCell3D/core/CompuCell3D/steppables/PDESolvers/hpppdesolvers.h
Call Stack (most recent call first):
core/CompuCell3D/steppables/PDESolvers/CMakeLists.txt:187 (ADD_COMPUCELL3D_STEPPABLE)
This warning is for project developers. Use -Wno-dev to suppress it.
-- Generating done
-- Build files have been written to: /home/m/src-cc3d/CompuCell3D_build
At this point we are ready to compile CC3D:
cd /home/m/src-cc3d/CompuCell3D_build
make -j 8
We are changing to the “build directory” where or cmake, Makefile, and transient compilation files are stored and we are running make command with 8 parallel compilation threads to speed up the compilation process. The successful compilation printout should look something like that:
[ 99%] Linking CXX shared module _PlayerPython.so
[ 99%] Built target PlayerPythonNew
16 warnings generated.
[100%] Linking CXX shared module _CompuCell.so
[100%] Built target CompuCell
After the compilation is done we will call ``make install
make install
The installed files will be placed in /home/m/src-cc3d/CompuCell3D_install , exactly as we specified in the cmake command - -DCMAKE_INSTALL_PREFIX=/home/m/src-cc3d/CompuCell3D_install
At this point we we need to copy all .so files from /home/m/src-cc3d/CompuCell3D_install/lib to /home/m/miniconda3/envs/cc3d_compile/lib
cp /home/m/src-cc3d/CompuCell3D_install/lib/*.so /home/m/miniconda3/envs/cc3d_compile/lib
Assuming we are still in cc3d_compile conda environment (run conda activate cc3d_compile if you opened new terminal) we can run our first simulation using newly compiled CompuCell3D. We will run it without the player first and next we will show you how to get player and twedit++ working.
python -m cc3d.run_script -i /home/m/src-cc3d/CompuCell3D/CompuCell3D/core/Demos/Models/cellsort/cellsort_2D/cellsort_2D.cc3d
Note
First time you execute run command on OSX it takes a while to load all the libraries. Subsequent runs start much faster
The output of the run should look something like this (remember to adjust all paths that start with /home/m/src-cc3d to you file system folders):
(cc3d_compile) m@tuf:~/src-cc3d/CompuCell3D_build$ python -m cc3d.run_script -i /home/m/src-cc3d/CompuCell3D/CompuCell3D/core/Demos/Models/cellsort/cellsort_2D/cellsort_2D.cc3d
#################################################
# CompuCell3D Version: 4.5.0 Revision: 2
Commit Label: f8ddda9
#################################################
<cc3d.core.CC3DSimulationDataHandler.CC3DSimulationData object at 0x7f0cfd2316f0>
Random number generator: MersenneTwister
WILL RUN SIMULATION FROM BEGINNING
CALLING FINISH
------------------PERFORMANCE REPORT:----------------------
-----------------------------------------------------------
TOTAL RUNTIME 5 s : 688 ms = 5.688 s
-----------------------------------------------------------
-----------------------------------------------------------
PYTHON STEPPABLE RUNTIMES
cellsort_2DSteppable: 0.01 ( 0.2%)
-----------------------------------------------------------
Total Steppable Time: 0.01 ( 0.2%)
Compiled Code (C++) Run Time: 5.60 (98.5%)
Other Time: 0.08 ( 1.4%)
-----------------------------------------------------------
Using Player
To run the above simulation using player we need to make player code available to the Python interpreter from which we are running our simulation. In my case this will boil down to either copying directory /home/m/src-cc3d/cc3d-player5/cc3d/player5 inside /home/m/miniconda3_arm64/envs/cc3d_compile/lib/python3.10/site-packages/cc3d/player5
or making a softlink. I prefer the softlink and I run:
ln -s /home/m/src-cc3d/cc3d-player5/cc3d/player5 /home/m/miniconda3/envs/cc3d_compile/lib/python3.10/site-packages/cc3d/player5
After this step I am ready to run previous simulation using the Player:
python -m cc3d.player5
and then we would use File->Open... menu to select our .cc3d project /home/m/src-cc3d/CompuCell3D/CompuCell3D/core/Demos/Models/cellsort/cellsort_2D/cellsort_2D.cc3d