Tag: scipy

How to get up-to-date Python packages without bothering your cluster admin

If you have ever been stuck as a user on an out-of-date cluster without root access it can be frustrating to ask the admin guy to install packages for you. Even if they respond, by the time they get round to it you might have moved onto something else. The moment could be gone.

Luckily, as far as Python is concerned, the pyenv project allows users to install their own local Python version or even assign different versions to different directories/projects.

Sir Andrew Smith - A. Smith: Illustrations of the zoology of South Africa, Reptilia. Smith, Elder, and Co., London 1840 PYTHON NATALENSIS (Southern African Python) (Reptilia Plate 9) in A. Smith: Illustrations of the zoology of South Africa, Reptilia. Smith, Elder, and Co., London 1840

Public domain image.

João Moreira has written a great beginner’s guide on the Amaral Lab homepage in order to get started. I now have the latest version of Python 2 (v2.7.12) installed along with essential packages like Scipy and Pandas, which I added using pip.

Installation of pyenv is easy.

curl -L https://raw.githubusercontent.com/yyuu/pyenv-installer/master/bin/pyenv-installer | bash 

Different versions of python can then be installed with

pyenv install 3.4.0

Switching your global Python version is then as simple as typing

pyenv global 3.4.0

From first impressions I can say I highly recommend pyenv, and will continue to learn about it over the coming days through using it. Please refer to João’s excellent post for more details.




The new default colormap for matplotlib is called “viridis” and it’s great!

It’s probably not news to anyone in data visualization that the most-used “jet” colormap (sic) (sometimes referred to as “rainbow”) is a bad choice for many reasons.

  • Doesn’t work when printed black & white
  • Doesn’t work well for colourblind people
  • Not linear in colour space, so it’s hard to estimate numerical values from the resulting image

The Matlab team recently developed a new colormap called “parula” but amazingly because Matlab is commercially-licensed software no-one else is allowed to use it!
The guys at Matplotlib have therefore developed their own version, based on the principles of colour theory (covered in my own BSc lecture courses on Visualization 🙂 ) that is actually an improvement on parula. The new Matplotlib default colormap is named “viridis” and you can learn all about it in the following lecture from the SciPy 2015 conference (YouTube ):

Viridis will be the new default colour map from Matplotlib 2.0 onwards, but users of v1.5.1 can also choose to use it using the cmap=plt.cm.viridis command.
I don’t know about you, but I like it a lot and will start using it immediately!