Installation

Requirements

Python Distribution (Python 3.6)/ Anaconda
NVIDIA GPU with at least 1024 threads
CUDA SDK 9.0+ already installed and configured.

If CUDA is not yet installed in the system, follow instructions in:

https://developer.nvidia.com/cuda-downloads

1. Installing a Python distribution

If there is no Python distribution installed on your system, we recommend installing Anaconda. Otherwise, skip to step 2.

1.1 Download Anaconda:

Download anaconda from their website https://www.anaconda.com/distribution/. Alternatively on Linux, use wget to download Miniconda (a minimalist version of Anaconda) -

wget https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh -O miniconda.sh

1.2 Install Anaconda :

(Windows) Just double click on the installer and follow instructions.

(Linux) Run the *.sh script that you downloaded (e.g. ./miniconda.sh or ./Anaconda3-2019.10-Linux-x86_64.sh)

2. Install SuRVoS from conda channel

We recommend creating a Python 3.6 conda environment for installation of SuRVoS.

On linux, open a terminal. On windows open Anaconda Prompt.

$> conda create -n survos-env python=3.6

Once this is installed, activate this new environment:

$> conda activate survos-env

Check that you are now using Python 3.6:

$> python --version
Python 3.6.7

Install SuRVoS from the survos conda channel

$> conda install -c conda-forge -c numba -c ccpi survos

Because of an issue with the matplotlib library, you need to downgrade to version 3.2.2

$> conda install matplotlib-base=3.2.2

To run SuRVoS, make sure you have your survos-env environment activated (“conda activate survos-env”) and type ‘SuRVoS’ to run.

$> SuRVoS

3. Install SuRVoS from source

3.1 Download SuRVoS

Navigate in a terminal (using cd) to a folder where you want to save SuRVoS and type the following commands

$> git clone https://github.com/DiamondLightSource/SuRVoS.git
$> cd SuRVoS

3.2 Using Anaconda

3.2.1 Windows

$> conda create -n ccpi python=3.6
$> activate ccpi
$[ccpi]> conda build conda-recipe -c conda-forge -c numba --python=3.6
$[ccpi]> conda install --use-local survos -c conda-forge -c numba --python=3.6

3.2.2 Linux

Replace the <CUDA_HOME> with the path to the CUDA install directory. Generally CUDA SDK 9.0 is installed in /usr/local/cuda-9.0.

$> conda create -n ccpi python=3.6
$> source activate ccpi
$[ccpi]> export PATH=<CUDA_HOME>/bin:$PATH
$[ccpi]> export LD_LIBRARY_PATH=<CUDA_HOME>/lib64:$LD_LIBRARY_PATH
$[ccpi]> conda build conda-recipe -c conda-forge -c numba --python=3.6
$[ccpi]> conda install --use-local survos -c conda-forge -c numba --python=3.6

3.2.3 MacOSX

Replace the <CUDA_HOME> with the path to the CUDA install directory. Generally CUDA SDK 9.0 is installed in /Developer/NVIDIA/CUDA-9.1/.

$> conda create -n ccpi python=3.6
$> source activate ccpi
$[ccpi]> export PATH=<CUDA_HOME>/bin:$PATH
$[ccpi]> conda build conda-recipe -c conda-forge -c numba --python=3.6
$[ccpi]> conda install --use-local survos -c conda-forge -c numba --python=3.6

3.3 Using standard python

3.3.1 Windows

NOTE Not yet supported.

3.3.2 Linux

This step requires CUDA already installed and NVCC compiler in the path (type which nvcc to verify it).

$> export PATH=<CUDA_HOME>/bin:$PATH
$> export LD_LIBRARY_PATH=<CUDA_HOME>/lib64:$LD_LIBRARY_PATH
$> python -m venv ccpi
$> . ccpi/bin/activate
$(ccpi)> pip install cmake cython numpy scipy matplotlib h5py pyqt5==5.8.2 tifffile networkx scikit-image scikit-learn seaborn 
$(ccpi)> cmake -G "Unix Makefiles" -DBUILD_SHARED_LIBS=ON -DCMAKE_BUILD_TYPE=Release -DCMAKE_INSTALL_PREFIX="${VIRTUAL_ENV}" -DINSTALL_BIN_DIR="${VIRTUAL_ENV}/bin" -DINSTALL_LIB_DIR="${VIRTUAL_ENV}/lib64" survos/lib/src
$(ccpi)> make
$(ccpi)> make install
$(ccpi)> python setup.py build
$(ccpi)> python setup.py install
$(ccpi)> export LD_LIBRARY_PATH=${VIRTUAL_ENV}/lib64:$LD_LIBRARY_PATH
$(ccpi)> SuRVoS

3.3.3 MacOSX

This step requires CUDA already installed and NVCC compiler in the path (type which nvcc to verify it).

$> export PATH=<CUDA_HOME>/bin:$PATH
$> export DYLD_LIBRARY_PATH=${CUDA_HOME}/lib64:${DYLD_LIBRARY_PATH}
$> python -m venv ccpi
$> . ccpi/bin/activate
$(ccpi)> pip install cmake cython numpy scipy matplotlib h5py pyqt5==5.8.2 tifffile networkx scikit-image scikit-learn seaborn 
$(ccpi)> cmake -G "Unix Makefiles" -DBUILD_SHARED_LIBS=ON -DCMAKE_BUILD_TYPE=Release -DCMAKE_INSTALL_PREFIX="${VIRTUAL_ENV}" -DINSTALL_BIN_DIR="${VIRTUAL_ENV}/bin" -DINSTALL_LIB_DIR="${VIRTUAL_ENV}/lib64" survos/lib/src
$(ccpi)> make
$(ccpi)> make install
$(ccpi)> python setup.py build
$(ccpi)> python setup.py install
$(ccpi)> export DYLD_LIBRARY_PATH=${VIRTUAL_ENV}/lib64:${DYLD_LIBRARY_PATH}
$(ccpi)> SuRVoS

4. Run SuRVoS

From the SuRVoS folder:

$> SuRVoS