Examples

The examples are organized by what you’re trying to do, not in a linear “walk forward” order. Pick the track that matches your task. Each notebook is self-contained.

Fitting Workflows

Single-file fitting skills (block 0x):

• examples/fitting_workflows/01_basic_fitting/ Load data, define a model, fit baseline + 2D, visualize results.

• examples/fitting_workflows/02_dependent_parameters/ Link parameters with expressions and physical constraints.

• examples/fitting_workflows/03_multi_cycle_dynamics/ Multi-cycle dynamics with subcycles and frequency.

• examples/fitting_workflows/04_parameter_profiles/ Profile-aware fitting with auxiliary-axis parameter profiles and profile-parameter dynamics.

Post-fit work (block 1x):

• examples/fitting_workflows/10_model_comparison/ Compare two models on the same file (baseline / SbS / 2D).

• examples/fitting_workflows/11_save_load_export/ FitResults HDF5 round-trip, CSV/PNG export, “ship just the winners”.

• examples/fitting_workflows/12_uncertainty_mcmc/ Three tiers of parameter uncertainty (stderr, profiled CIs, MCMC), checked against truth.

Multi-file workflows (block 2x):

• examples/fitting_workflows/20_multi_file_independent_fit/ Multi-file workspace, per-file independent fits (bridge to shared-parameter fitting).

• examples/fitting_workflows/21_multi_file_shared_fit/ Multi-file workspace with shared parameters across files.

Synthetic Data

• examples/synthetic_data/01_simulator/ Synthetic noisy data generation from a known ground truth.

• examples/synthetic_data/02_ml_training_data/ Training dataset generation via parameter-space exploration.

Choose Your Track

• New user, one processed file: start at 01 basic fitting notebook.

• Comparing two models on one file: 10 model comparison notebook.

• Saving, loading, or exporting fit results: 11 save / load / export notebook.

• Estimating uncertainties with MCMC: 12 uncertainty (MCMC) notebook.

• Many files, fit each independently: 20 multi-file independent fit notebook.

• Many files, shared-parameter fit: 21 multi-file shared fit notebook.

• Simulation or ML training data: Simulator data generation notebook or ML training data generation notebook.

All Notebooks

• 01 basic fitting

• 02 dependent parameters

• 03 multi-cycle dynamics

• 04 parameter profiles

• 10 model comparison

• 11 save / load / export

• 12 uncertainty (MCMC)

• 20 multi-file independent fit

• 21 multi-file shared fit

• Simulator data generation

• ML training data generation