Run the notebook LeastSquareFit.ipynb to see the code that generated the images in the .pdf.
This repository contains some background examples leading up to our discussion of fitting data.
- CLT.ipynb: example of Central Limit Theorem
- LeastSquareFit[ROOT].ipynb: notebooks describing the exercise using numpy/matplotlib [or ROOT] tools
- LSQFit.C(py): starter code for the Least Squares Fitting exercise
- RandomMeasuresP1.C, RandomGaus.C, RandomMeasuresAndFitP1.C: code to generate movies linked to the class notes
eg. in root:
root> .X RandomMeasuresP1.C
You will turn in an updated version of either LSQFit.C or PSQFit.py containing your work and the plots in the exercise description.
Other files:
- PlottingReview.ipynb a review of basic plot making in matplotlib and ROOT
- Interpolate.ipynb: Jupyter notebook illustrating the Lagrange interpolation and cubic splines.
- Lagrange.cpp: code to perform a Lagrange interpolation