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README.md

HNN "Python" install (Mac OS)

Opening a terminal window

  • Open up macOS's terminal.app by searching for terminal in Spotlight (upper right search icon). We will use this terminal for running the commands below.

Run pre-install checks

  • The command below will run a script to check for existing installations of prerequisites. If a compatible version is installed, it will say which steps can be skipped below.

    curl -s "https://raw.githubusercontent.com/jonescompneurolab/hnn/master/installer/mac/check-pre.sh" | bash

Prerequisite 1: Xcode Command Line Tools

The Xcode Command Line Tools package includes utilities for compiling code from the terminal (gcc, make, etc.). This is needed for compiling mod files in NEURON.

  1. To install the package, type the following from a terminal.app window:

    xcode-select --install
    • If you get the following error, you can skip this step. xcode-select: error: command line tools are already installed, use "Software Update" to install updates

  2. Then press Install in the pop-up dialog

Prerequisite 2: Miniconda (Python 3)

  • Run the commands below from a terminal window (as a regular user). This will create a python environment isolated from other installations on the system. You could use homebrew brew install python3 if you wish (has been tested with HNN), but this guide will cover the miniconda version.

    cd /tmp/
curl -O https://repo.anaconda.com/miniconda/Miniconda3-latest-MacOSX-x86_64.sh
sh ./Miniconda3-latest-MacOSX-x86_64.sh -b
rm /tmp/Miniconda3-latest-MacOSX-x86_64.sh

Download HNN source code

  • The following commands will download the hnn source code. We use the directory hnn_source_code for consistency with all of our instructions, but any directory can be used. You can use git if you prefer.

    curl -OL https://github.com/jonescompneurolab/hnn/releases/latest/download/hnn.tar.gz
mkdir hnn_source_code
tar -x --strip-components 1 -f hnn.tar.gz -C hnn_source_code

Prepare the Python environment

  1. Create a conda environment with the Python prerequisites for HNN.

    cd hnn_source_code
curl -O https://raw.githubusercontent.com/jonescompneurolab/hnn/master/environment.yml
conda env create -f environment.yml

  2. Activate the HNN conda environment and install nlopt and NEURON

    source activate hnn
pip install nlopt NEURON

  3. Set the LD_LIBRARY_PATH for openmpi on conda activation. This environnement variable must be set before HNN can run simulations with openmpi. The variable is only useful inside the 'hnn' conda environment, so we will set the variable when conda is activated with source activate hnn. Run the following commands to make this automatic.

    cd ${CONDA_PREFIX}
mkdir -p etc/conda/activate.d etc/conda/deactivate.d
echo "export OLD_DYLD_FALLBACK_LIBRARY_PATH=\$DYLD_FALLBACK_LIBRARY_PATH" >> etc/conda/activate.d/env_vars.sh
echo "export DYLD_FALLBACK_LIBRARY_PATH=\$DYLD_FALLBACK_LIBRARY_PATH:\${CONDA_PREFIX}/lib" >> etc/conda/activate.d/env_vars.sh
echo "export DYLD_FALLBACK_LIBRARY_PATH=\$OLD_DYLD_FALLBACK_LIBRARY_PATH" >> etc/conda/deactivate.d/env_vars.sh
echo "unset OLD_DYLD_FALLBACK_LIBRARY_PATH" >> etc/conda/deactivate.d/env_vars.sh

  4. Open a new terminal window for the settings in the previous step to take effect and activate the HNN conda environment

    source activate hnn

Run post-install checks and compile NEURON mode files

  • Run a post-installation check to ensure that all necessary libraries were successful installed. Finally, we will compile the NEURON mod files.

    curl -s "https://raw.githubusercontent.com/jonescompneurolab/hnn/master/installer/mac/check-post.sh" | bash
cd hnn_source_code
make

Run the HNN model

  1. Start the HNN GUI from a terminal window:

    source activate hnn
python hnn.py

  2. The HNN GUI should show up. Make sure that you can run simulations by clicking the 'Run Simulation' button. This will run a simulation with the default configuration. After it completes, graphs should be displayed in the main window.

  3. When you run simulations for the first time, the following dialog boxes may pop-up and ask you for permission to allow connections through the firewall. Saying 'Deny' is fine since simulations will just run locally on your Mac.

  4. You can now proceed to running the tutorials at https://hnn.brown.edu/index.php/tutorials/ . Some things to note:

    • A directory called "hnn_out" exists in your home directory where the results from your simulations (data and param files) will be stored.

Upgrading to a new version of HNN

HNN Releases can be seen on the GitHub releases page. You can also be notified of new releases by watching the hnn repository on GitHub.

If you downloaded the tar.gz file, simply re-run the steps above, but replace hnn_source_code with a new directory name.

Otherwise, if you are using git, then run git pull origin master from the source code directory.

Troubleshooting

For Mac OS specific issues: please see the Mac OS troubleshooting page

If you run into other issues with the installation, please open an issue on our GitHub. Our team monitors these issues and will investigate possible fixes.

Another option for users that are running into problems with the above methods, we provide a VirtualBox VM pre-installed with HNN.