Installation

spam works on Python 3.6+ (older python versions are no longer maintained).

There are now a number of ways to run spam:

Before we start, commands for you to execute

$ look -like this

Installing system dependencies

This step is required for both user and developer install. The installation of these required packages (for spam compilation and for some of our Python dependencies). The details of this step is very system-dependent, please see below for your system:

Note: we use R and rpy2 only for the generation of random fields. It’s considered on optional dependency, however test_excursions.py will fail without it.

System dependencies for Debian/Ubuntu Linux

If you’re on Debian/Ubuntu:

$ sudo apt update

$ sudo apt upgrade

$ sudo apt install git python3-dev python3-venv python3-tk gcc g++ libeigen3-dev r-base r-cran-randomfields libicu-dev libgmp-dev libmpfr-dev libcgal-dev gmsh libfreetype6-dev libxml2-dev libxslt-dev

Now you’re ready to go to: Set up a Python virtual environment for spam


System dependencies for Scientific Linux 6.9

Warning: This is probably out of date.

If you’re on Scientific Linux 6.9 (and you don’t want to update to a reasonably modern distribution, e.g., it’s installed on a cluster):

$ sudo yum install epel-release

$ sudo sh -c 'wget -qO- http://people.redhat.com/bkabrda/scl_python27.repo >> /etc/yum.repos.d/scl.repo'

$ sudo yum install git swig python27 python27-python-libs python27-runtime python27-python-devel python-pip python-virtualenv gcc eigen3-devel R gmp-devel mpfr-devel

Now you’re ready to go to: Set up a Python virtual environment for spam


System dependencies to install for other Linux distributions

For other linux installations our dependencies are currently:

Python components:

  • python3 and python3 development files

  • python3 virtual env (highly recommended to not install spam right into the system)

  • python3 tk libraries for matplotlib

Compilation dependencies:

  • gcc and/or g++

  • eigen3 development files

  • CGAL development files

External programs we call:

  • R

  • gmsh

Dependencies of the pip packages we use:

  • libfreetype6-dev (for matplotlib)

  • libxml2-dev

  • libxslt-dev

  • libicu-dev

  • libgmp-dev

  • libmpfr-dev

Once these are install you’re ready to go to: Set up a Python virtual environment for spam


System dependencies for OSX 10.14

  • Install xcode

  • Install the following packages from source e.g., to /usr/local, or with homebrew (e.g., brew install cmake). Homwbrew is recommended for simplicity.

    • cmake

    • eigen3

    • gmsh 4.4.1

    • gmp

    • mpfr

    • cgal

  • install Python 3.7.4 package from python.org for OSX

  • (optional, see above) install R 3.6.1 package from R for OSX. The rpy2 Python module requires llvm to compile correctly (since there is no openMP support in Apple’s clang).

    • Install llvm with homebrew (e.g., brew install llvm) - or the instructions from llvm.org for installing llvm from source (with the clang component), and install openmp from llvm.org as well.

    • llvm may require that you install OSX SDK headers using the following command (which in turn require the Xcode command line tools):

    $ xcode-select --install
$ open /Library/Developer/CommandLineTools/Packages/macOS_SDK_headers_for_macOS_10.14.pkg

  • add the following to ~/.profile:

# general /usr/local variables  , also needed by brew
export PATH=$PATH:/usr/local/bin
export LIBRARY_PATH=$LIBRARY_PATH:/usr/local/lib
export DYLD_FALLBACK_LIBRARY_PATH=$DYLD_FALLBACK_LIBRARY_PATH:/usr/local/lib

###########
# for LLVM:
export LLVM_PREFIX=/usr/local/opt/llvm  # or your llvm install location if not using brew
export PATH=$PATH:$LLVM_PREFIX/bin
export LIBRARY_PATH=$LIBRARY_PATH:$LLVM_PREFIX/lib
export DYLD_FALLBACK_LIBRARY_PATH=$DYLD_FALLBACK_LIBRARY_PATH:$LLVM_PREFIX/lib
export CC=$LLVM_PREFIX/bin/clang
export CXX=$LLVM_PREFIX/bin/clang++
#the following line may not be needed on all installations
export CPLUS_INCLUDE_PATH=$CPLUS_INCLUDE_PATH:/Applications/Xcode.app/Contents/Developer/Toolchains/XcodeDefault.xctoolcha\
in/usr/include/c++/v1
#if LLVM came with brew you may need this too:
export KMP_DUPLICATE_LIB_OK=TRUE
#############

Thanks to Adrian Sheppard, Steve Hall, and Ryan Hurley for these OSX install notes.

Now you’re ready to go to: Set up a Python virtual environment for spam



Set up a Python virtual environment for spam

If the dependencies above installed correctly, now you can go ahead and create a virtual environment for spam. If you’re using Anaconda, please see this note: Installing into Anaconda.

You can create the virtual environment any writable folder on your computer. The virtual environment is created, in the folder you want, using:

$ python3 -m venv spam

This will create a virtual environment called spam in the folder spam. You can then activate the virtual environment:

$ source spam/bin/activate
(spam) $

You should see (spam) written at the beginning of your command line. You will need to activate this virtual environment in the terminal each time you want to use spam – check for the (spam) at the command prompt!

You should then upgrade your virtual environment to the latest version of pip and setuptools:

(spam) $ pip install -U pip setuptools

Congratulations, now that your virtual environment is set up, you can either:


Install spam from pip

Execute the following line…

(spam) $ pip install spam

spam should now be installed! Check whether:

(spam) $ spam-ldic --help

prints out the help for the function, if it does, you’re done!


Install spam from git

1. Clone spam

It can be cloned anywhere on the computer. For example in a folder ~/bin. Before cloning go to the directory:

$ cd ~/bin/

Then clone the repository:

$ git clone https://gricad-gitlab.univ-grenoble-alpes.fr/ttk/spam.git

Now cd into the spam directory that has been downloaded:

$ cd spam

2. Set up virtual environment

Activate the previously-created virtual environment:

$ source path/to/virtualenv/spam/bin/activate
(spam) $

Install pip requirements:

(spam) $ pip install -r requirements.txt

and (optionally) the development tools to calculate coverage, rpy2, and build documentation:

(spam) $ pip install -r requirements-dev.txt

3. Install spam into the virtualenv

(spam) $ python setup.py install

In the future, when you do

(spam) $ git pull

to download the latest version of the code, you’ll have to repeat setup install above.


Installing Jupyter for use with spam (optional)

You need to install Jupyter (with pip or you package manager).

If you work in a virtualenv, you have to add ipykernel in it :

(spam) $ pip install ipykernel

and declare your virtualenv in Jupyter :

(spam) $ python -m ipykernel install --user --name=spam

Then you should be able to select this kernel from Jupyter and download the Jupyter Notebook files from the examples.


Installing into Anaconda

If you’re using an Anaconda Python environment, and you want to install spam, there is now a conda-forge package.

Install anaconda (or miniconda), then do (we’re using mamba to solve the environment otherwise it si very slow, but this is optional):

$ conda create -n spam python=3.7
$ conda activate spam
(spam) $ conda config --add channels conda-forge
(spam) $ conda install mamba -c conda-forge
(spam) $ mamba install spam

To have graphical things working, you might also have to do:

(spam) $ pip install PyQt5 qimage2ndarray

Running spam with docker

With this method you don’t need to install spam to run it. You only need to install docker.

We’ve created a docker image based on stretch and python 3.7 with spam and all its dependencies already installed on it. This way you won’t have to install anything to run your programs.

1. Pull the image

$ docker pull gricad-registry.univ-grenoble-alpes.fr/ttk/docker-ttk/spam

2. Input/output folder on the host

On your computer (the host), have a folder with all your input data and scripts. The output files will be written in this folder too, as if you were running your script directly on the host.

WARNING: avoid reading and writing outside of this directory.

For example your folder can look like this:

/home/user/myfolder/
    im1.tif
    im2.tif
    myscript.py

3. Run your script

You can now run you script with the following command (change /home/user/myfolder/) with the actual path of your folder on the host.

$ docker run --rm -v /home/user/myfolder:/r --workdir /r gricad-registry.univ-grenoble-alpes.fr/ttk/docker-ttk/spam python myscript.py

You can also directly use spam commands

$ docker run --rm -v /home/user/myfolder:/r --workdir /r gricad-registry.univ-grenoble-alpes.fr/ttk/docker-ttk/spam spam-ldic --help

4. Jupyter notebooks

Finally you can run the image as a jupyter notebook server accessible at http://127.0.0.1:8888 with the command

$ docker run --rm -p 8888:8888 -v /home/user/myfolder:/work/notebooks/myfolder gricad-registry.univ-grenoble-alpes.fr/ttk/docker-ttk/spam

where -v /home/user/myfolder:/work/notebooks/myfolder binds your host folder with the container. It means that all inputs/outputs will be read/written in /home/user/myfolder.

5. Development

It is possible to develop spam with the help of docker to avoid having to install all dependencies on your computer. You only need to clone the source on your host:

[/home/user] $ git  clone git@gricad-gitlab.univ-grenoble-alpes.fr:ttk/spam.git

which will put the source code in

/home/user/spam

Then you can run a spam container (with all dependencies) and bind your source code folder with the container (only modify /home/user/spam to meet your actual path):

$ docker run -it --rm -v /home/user/spam:/work --workdir /work gricad-registry.univ-grenoble-alpes.fr/ttk/docker-ttk/spam bash

which will lead you to a bash terminal on the container in the spam source folder. The workflow can be as follow:

  • On the container: compile and execute spam

  • On the host: modify spam with your IDE, look at output files and handle git.

__Note:__ there is no need to keep a container alive and you can use standalone command for each step on the container:

$ # install
$ docker run -it --rm -v /home/user/spam:/work --workdir /work gricad-registry.univ-grenoble-alpes.fr/ttk/docker-ttk/spam python setup.py install
$ # test
$ docker run -it --rm -v /home/user/spam:/work --workdir /work gricad-registry.univ-grenoble-alpes.fr/ttk/docker-ttk/spam pytest
$ # doc
$ docker run -it --rm -v /home/user/spam:/work --workdir /work gricad-registry.univ-grenoble-alpes.fr/ttk/docker-ttk/spam python setup build_sphinx

Installing docker

We recommend following the official instructions to install docker. However on debian based systems you can follow these steps:

$ sudo apt-get remove docker docker-engine docker.io containerd runc
$ sudo apt-get update
$ sudo apt-get install ca-certificates curl gnupg lsb-release
$ curl -fsSL https://download.docker.com/linux/debian/gpg | sudo gpg --dearmor -o /usr/share/keyrings/docker-archive-keyring.gpg
$ echo "deb [arch=$(dpkg --print-architecture) signed-by=/usr/share/keyrings/docker-archive-keyring.gpg] https://download.docker.com/linux/debian $(lsb_release -cs) stable" | sudo tee /etc/apt/sources.list.d/docker.list > /dev/null
$ sudo apt-get update
$ sudo apt-get install docker-ce docker-ce-cli containerd.io

$ sudo chmod 666 /var/run/docker.sock