Tutorials
We will have several computational tutorials throughout the course. As the course progresses, these materials will be posted below. Note: In some browsers (Firefox primarily), the end of each sentence is clipped off, making it difficult to read. If this is occurring, please try using another browser (Chrome, Safari, etc).
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Tutorial 0a: Configuring your computer | This tutorial will walk you through how to install a Python 3.7 scientific computing environment.
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Tutorial 0b: Using the Jupyter notebook | This tutorial will teach you how to write code and text in Jupyter notebooks.
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Tutorial 0c: A Primer on Python Syntax | This tutorial will walk you through the basics of programming in Python.
Data sets
Please download the following data sets, unzip them, and place them in your pboc/data folder as described in the setting up Python tutorial.
Python utilities
As sometimes syntax can be difficult, we have written a file with a few functions written in Python that will make some of the in-class exercises less cumbersome. Please download them below and place them in your root pboc folder.
- pboc_utilities.py | Course utilities.
Exercises
As we progress through the course, the code written in class will be posted here, along with the polished version of the same material.
- Tutorial 1 | Numerical Integration of Biological Growth
- Tutorial 2 | Measuring Bacterial Growth Via Microscopy
- Tutorial 3 | Stochastic Simulations
- Tutorial 4 | Integrating the Master Equation
External resources
Below is a list of useful online resources for learning the Python programming language and principles of programming in general.
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How bad is your colormap. Interesting blog that discusses how the jet colormap is actually bad for displaying data.
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A better default colormap. Talk at the Scipy 2015 meeting where they explain the caveats behind colormaps.