Easy Installation

This guide helps you install ACPred-BMF with basic features. We recommend building ACPred-BMF with Docker to avoid dependency issues. We recommend compiling ACPred-BMF(and possibly its requirements) from the source code using the latest compiler for the best performace. You can also deploy ACPred-BMF without building by Docker . Please note that ACPred-BMF only supports Linux; for Windows users, please consider using WSL or docker.

Requirements

ACPred-BMF is developed based on Python . We recommend using Python version 3.8.12 or higher. Below are the prerequisite Python packages with their versions required for this software.

protobuf == 3.19.0
numpy == 1.22.3
pandas == 1.3.4
tensorflow == 2.8.0
scikit-learn == 1.0.1
keras == 2.8.0

We provide a requirements.txt in our GitHub repository which you can use with the command below to obtain these packages directly.

pip install -r requirements.txt

However, if you prefer to skip the process of configuring these packages, we recommend using Docker.

Please refer to our guide on requirements.

Get ACPred-BMF source code

Of course a copy of ACPred-BMF source code is required, which can be obtained via one of the following choices:

  • Clone the whole repo with git: git clone https://github.com/RUC-MIALAB/ACPred-BMF.git

  • Clone the minimum required part of repo: git clone https://github.com/RUC-MIALAB/ACPred-BMF.git --depth=1

  • Get the source code of a latest version from here

Update to latest release

Please check the release page for the release note of a new version.

It is OK to download the new source code from beginning following the previous step.

To update your cloned git repo in-place:

git remote -v
# Check if the output contains the line below
# origin https://github.com/RUC-MIALAB/ACPred-BMF.git (fetch)
# The remote name is marked as "origin" if you clone the repo from your own fork.

git fetch origin
git checkout v0.0.1 # Replace the tag with the latest version
git describe --tags # Verify if the tag has been successfully checked out

Container Deployment

We’ve built a ready-for-use version of ACPred-BMF with dockerfile. For a quick start: download the dockerfile, prepare the data, run container. Instructions on using the image can be accessed in Dockerfile.