Installation and dependencies

The benefits of using a Python package manager (distribution), such as (ana)conda, are many. Mainly, it brings easy and robust package management and avoids messing up with your system’s default python. An alternative is to use package managers like apt-get for Ubuntu or Homebrew/MacPorts/Fink for macOS. We recommend using Miniconda.

VIP depends on existing packages from the Python ecosystem, such as numpy, scipy, matplotlib, pandas, astropy, scikit-learn, scikit-image, photutils and others. There are different ways of installing VIP suitable for different scenarios.

Before installing the package, it is highly recommended to create a dedicated conda environment to not mess up with the package versions in your base environment. This can be done easily with (replace vipenv by the name you want for your environment):

$ conda create -n vipenv python=3.10 ipython

Note

Installing ipython while creating the environment, as in the example above, will avoid a commonly reported issue which stems from trying to import VIP from within a base python2.7 ipython console.

For users not planning to contribute:

Once within your new environment, the easiest way to install VIP is through the Python Package Index, aka PyPI, with the pip package manager. Simply run:

$ pip install vip_hci

With pip you can easily uninstall, upgrade or install a specific version of VIP. For upgrading the package, run:

$ pip install --upgrade vip_hci

For potential contributors:

If you plan to contribute or experiment with the code you need to make a fork of the repository (click on the fork button in the top right corner) and clone it:

$ git clone https://github.com/<replace-by-your-username>/VIP.git

If you do not create a fork, you can still benefit from the git syncing functionalities by cloning the repository (but will not be able to contribute):

$ git clone https://github.com/vortex-exoplanet/VIP.git

To install VIP, then simply cd into your local VIP directory, and run the installation in editable mode pointing to developer requirements:

$ cd VIP
$  pip install -e . -r requirements-dev.txt

If cloned from your fork, make sure to link your VIP directory to the upstream source, to be able to easily update your local copy when a new version comes out or a bug is fixed:

$ git add remote upstream https://github.com/vortex-exoplanet/VIP.git

If you plan to develop VIP or use it intensively, it is highly recommended to also install the optional dependencies listed below.

Optional dependencies

The following dependencies are not automatically installed upon installation of VIP but may significantly improve your experience:

  • VIP contains a class vip_hci.vip_ds9 that enables, through pyds9, the interaction with a DS9 window (displaying numpy arrays, controlling the display options, etc). To enable this feature, pyds9 must be installed from the latest development version: pip install git+git://github.com/ericmandel/pyds9.git#egg=pyds9
  • VIP image operations (e.g. shifts, rotations, scaling) can be performed using OpenCV instead of the default FFT-based methods. While flux are less well preserved, OpenCV offers a significant speed improvement (up to a factor 50x), in particular for image rotations, which can be useful to get quick results. Installation: pip install opencv-python.
  • Also, you can install the Intel Math Kernel Library (mkl) optimizations (provided that you have a recent version of conda) or openblas libraries. Either of them can be installed with conda install.
  • VIP offers the possibility of computing SVDs on GPU by using CuPy (starting from version 0.8.0) or PyTorch (from version 0.9.2). These remain as optional requirements, to be installed by the user, as well as a proper CUDA environment (and a decent GPU card).
  • Bad pixel correction routines can be optimised with Numba, which converts some Python code, particularly NumPy, into fast machine code. A factor up to ~50x times speed improvement can be obtained on large images compared to NumPy. Numba can be installed with conda install numba.
  • Finally, robust contrast curves and contrast grids can be calculated with applefy. Example usage is provided in VIP tutorial 4. See more details in Bonse et al. (2023).

Loading VIP

Finally, start Python (or IPython or a Jupyter notebook if you prefer) and check that you are able to import VIP:

import vip_hci as vip

If everything went fine with the installation, you should not get any error message upon importation, and you can start finding exoplanets!