Installation

Dependencies

Hyperbox-brain requires:

  • Python (>= 3.6)

  • Scikit-learn (>= 0.24.0)

  • NumPy (>= 1.14.6)

  • SciPy (>= 1.1.0)

  • joblib (>= 0.11)

  • threadpoolctl (>= 2.0.0)

  • Pandas (>= 0.25.0)

Hyperbox-brain plotting capabilities (i.e., functions start with show_ or draw_) require Matplotlib (>= 2.2.3) and Plotly (>= 4.10.0). For running the examples Matplotlib >= 2.2.3 and Plotly >= 4.10.0 are required. A few examples require pandas >= 0.25.0.

conda installation

You need a working conda installation. Get the correct miniconda for your system from here.

To install hyperbox-brain, you need to use the conda-forge channel:

conda install -c conda-forge hyperbox-brain

We recommend to use a conda virtual environment.

pip installation

If you already have a working installation of numpy, scipy, pandas, matplotlib, and scikit-learn, the easiest way to install hyperbox-brain is using pip:

pip install -U hyperbox-brain

Again, we recommend to use a virtual environment for this.

From source

If you would like to use the most recent additions to hyperbox-brain or help development, you should install hyperbox-brain from source.

Using conda

To install hyperbox-brain from source using conda, proceed as follows:

git clone https://github.com/UTS-CASLab/hyperbox-brain.git
cd hyperbox-brain
conda env create
source activate hyperbox-brain
pip install .

Using pip

For pip, follow these instructions instead:

git clone https://github.com/UTS-CASLab/hyperbox-brain.git
cd hyperbox-brain
# create and activate a virtual environment
pip install -r requirements.txt
# install hyperbox-brain version for your system (see below)
pip install .

Testing

After installation, you can launch the test suite from outside the source directory (you will need to have pytest >= 5.0.1 installed):

pytest hbbrain