Tekano Mbonani's repositories
auto_tutorial_impact_report_generator
An automated, user-interactive tutorial attendance impact report generator. The code conducts hypothesis testing to compare the student performance with tutorial attendance, and outputs a PDF report.
bootstrap_resample_with_replacement
A combination of codes developed for the calculation of the cross-correlation confidence intervals, making use of a pair of light-curves. The code conducts a bootstrap random sampling with replacement method to generate artificial light-curves. The code determines the cross-correlation of the artificial light-curves, and uses them for significance.
desktop_notifier
An automated Desktop Notifier for Mac OS. The user can edit the notifier to read a message of their liking, and to fit a purpose of their liking. I use the code when I invigilate students during tests and exams, it notifies me of time thats passed during the event, without having to look at the watch or clock
Differential-to-Apparent-Magnitude-Offset
Converting the differential magnitudes of target FSRQs sources into apparent magnitudes, employing apparent magnitudes of standard stars in the field-of-view.
Light_Curve_Temp_Profile
A Python code for fitting the flux variability of light-curves to extract flux rising and falling times.
mars.v1.0.0
A web application developed for the data collection team at the University of the Free State. The app, named MARS combines weekly attendance register files into a single bulk/aggregated attendance file.
Module-Evaluations
A web-application for the production of evaluation PDF reports, showing tutorial evaluations for the A_STEP tutored modules.
Polynomial_Regression
Polynomial Regression: The code shows examples of machine learning linear and polynomial predictive models, constructed in a loop such that the user can determine the best model for the data.
python-scripts
A repository of python scripts that come in handy in automating day-to-day tasks
Web_Scrapper
Web_Scrapper was written to download and organise CVs, Transcripts and ID files attached by applicants for the A-STEP tutorial programme.