My Github page: www.github.com/gregfutia
Codes on github are mostly Csharp and Matlab.
I wrote many of the CSharp codes when I was a Master’s student. At CSU I bought C# into the Bartel’s lab for data acquisition. This is over ten years old now but the codes may still be useful. There are some libraries, Lab.Motors and Lab.Motors.Test codes for interfacing with motors in the optics lab. Drivers I’ve interfaced to so far are a ASI LV4000 motor controller, a Newport ESP100 motor controller, and Zaber Motor controllers.
Notable CSharp Programs:
Sparrow is one I am particularly proud of. It’s a down sampling power spectral density analyzer. It’s useful for characterizing noise as it allows you to record frequency that span from the MHz into the sub hertz on a logarithmic frequency and amplitude axis. The slope of these traces specify what kind of noise you are measuring. Noise is well characterized by it’s pinkness in the spectral domain. I wrote it for characterizing coupling noise between polarization maintaining and non polarization maintaining optical fiber. The slope of the power spectrum as it approaches DC on a logarithmic scale tells you its type.
Squid is a data acquisition program used to acquire Spatial Freuquency modulated imaging (SPIFI) traces, images really. I used it to acquire the data for my Master’s thesis and other students and staff have used it to acquire data for follow up work.
Bullet is a laser beam profiler. It’s designed to take knife edge measurements and it them to an ERF function. It can do two beams simultaneously to find cross over.
Matlab codes:
matlab-imagej-image-cytometry is software I wrote for my PhD to perform 4 channel image analysis (image cytometry) of model circulating tumor cell data to create feature sets for each cell.
ctc-cytometry-analysis-v1 is software I wrote to analyze the image cytometry data and plot receiver operating characteristics for the data. This code also will perform feature selection with regression to attempt to create a combination biomarker with improved identification accuracy.