1. Creating a grid of matplotlib figures

    Sun 13 December 2015 | tags: python

    Whenever I'm analyzing a dataset, I tend to create lots of different plots (e.g., y-axis transforms, different x-variables, etc.). Usually, it's a lot more instructive to view all these plots at once so that differences can be readily viewed. Since it rapidly becomes tedious to manually position/resize the automatically-created plotting windows, I created a tool called matplotgrid that tiles the windows.

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  2. Pi and Pythagoras

    This post contains a derivation of a recurrence relation that can be used to calculate $\pi$. While it's not useful for the purpose of calculating to any decimal place imaginable, what's notable is that it only uses the Pythagorean thereom and should therefore be easy to follow. Unsurprisingly, the recurrence relation is neither original nor unique because it falls under the category of using polygons to compute $\pi$ (attributed to Archimedes). At the end of the notebook, the derived recurrence relation is implemented in code and run.

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  3. Gauss's law as used in MOS derivations

    There are two applications of Gauss's Law used in MOS derivations for computing the surface potential equation (SPE). One of the applications is also used in the formulation of semiconductor charge per unit area from the surface field that is found during the solution of Poisson's equation. This post presents both applications of Gauss's law, which are required to complete the MOS capacitor analysis.

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  4. Electrical characteristics of the MOS capacitor

    An IPython notebook showing the derivation of the electrical characteristics of the idealized MOS capacitor by using the one-dimensional solution of Poisson's equation. The results of the derivation are entirely physics-based and are coded in Python. The code is used to generate plots showing the derived quantities.

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