Jupyter notebooks for PhD class on data languages.
Installing python
The easiest way to install python on any OS is to use anaconda python. This will install a local version of python on your system so you don't need to worry about needing admin to install new packages. Most of the packages listed above are installed by default with anaconda. For this class we will be using python 3, and I recommend you use this version for you research.
Packages to install (in addition to anaconda's defaults)
numpyro
tinygp
graphviz
pip install numpyro tinygp graphviz
Class 1
Git.ipynb
: Git and Git-HubGeneral_Python.ipynb
: General python informationUnit_testing.ipynb
: Writing unit tests in python
Class 2
General_plotting.ipynb
: How to make publication ready plotsmpl_style.py
: How to make amatplotlib
styleUncertainty_plotting.ipynb
: Making plots with errorbarsAstropy_fitting.ipynb
: usingastropy
to model and fit data
Class 3
mcmc_fit_with_outliers_numpyro.ipynb
: fitting a line to data while rejecting outliers using MCMC (numpyro)Gaussian_process_theory.ipynb
: introduction to GPsGaussian_process_regression_numpyro.ipynb
: fitting data without defining a functional form