Software Installation

First, download a zip file or clone the repository to your computer with git clone.
To run OCRA, you need three main files:

• A bit file for the FPGA
• A server running on the Red Pitaya
• A client (Python GUI) running on your local computer

The bit file is provided, all you need to do is copy it onto the Red Pitaya and cat it to /dev/xdevcfg. But first, you need to set up the Vivado environment for the Red Pitaya.

Vivado Environment and Compiling

We followed Pavel Demin’s Pulsed NMR project in setting up ours.

1. First, you need a Linux-based machine for Vivado. If you have one already, simply install “Vivado HLx 2018.1: All OS installer Single-File Download” from the Xilinx page. If you need to set one up, follow these instructions. Note that you don’t need this particular development machine - Ubuntu 16.04 LTS in VirtualBox also works.
2. To compile code for the Red Pitaya, you need to use the ARM cross-compiler arm-linux-gnueabihf-gcc. This is provided by Vivado. To compile the code, run:

    source /opt/Xilinx/Vivado/2016.2/settings64.sh
    arm-linux-gnueabihf-gcc -static -O3 -march=armv7-a -mcpu=cortex-a9 -mtune=cortex-a9 -mfpu=neon -mfloat-abi=hard /path/to/input.c -o output_file -lm
       
   

   This will output a binary executable file that you can run on the Red Pitaya. Use this command to compile the server code.

Server

The server is a program in C that runs on the Red Pitaya. It listens for a client (the Python GUI) over an Ethernet connection. The server needs a static IP address for the client to connect to it. Set a static IP address following the Red Pitaya documentation.

Once you’ve done this, you can run the server. The file is mri_lab_rt.c in the server folder. We have also provided the compiled binary mri_lab_rt. First cat the bitfile:

 cat pulsed_nmr_planB_05192018.bit > /dev/xdevcfg

Now run the server:

 ./server/mri_lab_rt 60 32200

The first argument, 60, is the length of the 90 degree hard RF pulse in samples. The second argument, 32200, is the amplitude of the pulse (arbitrary units). These are the optimal RF pulse parameters for our system.

Client

For the client, you will need Python3 and the following packages: pyqt5, matplotlib, numpy, and scipy. You can install these yourself, but it is easier to use anaconda or miniconda. We’ve provided a conda environment (environment.yml) that already has the dependencies installed. To set up the environment in anaconda or miniconda:

1. Install anaconda or miniconda. Installation instructions are here. Make sure that the installer successfully adds miniconda to the PATH and PYTHONPATH environment variables.

2. Create a conda environment:

    conda env create -f environment.yml 
   

   The name of the environment is in the first line of the yml file, ocra_env.

3. Activate the new environment.
   Windows: activate ocra_env
   macOS and Linux: source activate ocra_env
   Make sure that the environment installed correctly by typing conda list. Among others, you should see numpy, scipy, pyqt, and matplotlib.

4. Test that the GUI opens by running

    python runMRI.py
   

   If this doesn’t work, make sure that you’re in the correct directory. You should see a window like this:

   

5. Test that the dropdown bar works. You should see something like:
   
   If you don’t, try clicking on the Terminal window running the python script first, then clicking on the dropdown bar.

Now you are ready to run the GUI!