Parameter estimation

Notebooks for CHME 5137 (2026): fitting models to data, after Lectures 12 and 13.

Notebook	What it is
batch-reactor-regression.ipynb	The regression homework: A ⇌ B in a batch reactor, fitted with curve_fit

Each notebook has a paired .py file holding the same cells as plain text (see Jupytext below).

Getting started

1. Fork this repository to your own GitHub account (button at top right).
2. Clone your fork, not this one:

   git clone git@github.com:YOUR-USERNAME/parameter-estimation.git   # SSH, e.g. on Explorer
   # or
   git clone https://github.com/YOUR-USERNAME/parameter-estimation.git

   On Explorer, clone it into /courses/CHME5137.202710/students/$USER/.
3. Open batch-reactor-regression.ipynb and work through it, using your own kernel (chme5137 on Explorer). Commit and push as you go:

   git add batch-reactor-regression.ipynb batch-reactor-regression.py
   git commit -m "Task 1: fit kf and kr at 298 K"
   git push

   This is your own fork, so committing on main is fine. Don't open a pull request back to CHME5137/parameter-estimation: that would publish your answers to everyone.

Jupytext

jupytext.toml pairs each notebook with a .py script in the percent format, as in the differential-equations and kinetic-monte-carlo repositories. Saving the notebook updates the .py as well. If the two get out of step, jupytext --sync batch-reactor-regression.ipynb brings them back in line.

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Written with Claude Code (Claude Opus 5.5) and checked by Prof. West.