Examples
========

These examples demonstrate typical workflows for fitting and data generation.

Fitting Workflows
-----------------

- ``examples/fitting_workflows/01_basic_fitting/``
  Basic workflow for loading data, defining models, fitting, and visualization.
- ``examples/fitting_workflows/02_dependent_parameters/``
  Parameter-linking workflows using expressions and physical constraints.
- ``examples/fitting_workflows/03_multi_cycle/``
  Multi-cycle, time-dependent modeling workflows.
- ``examples/fitting_workflows/04_par_profiles/``
  Profile-aware fitting with auxiliary-axis parameter profiles and profile-parameter dynamics.
- ``examples/fitting_workflows/05_project_level_fitting/``
  Project-level fitting with shared parameters across multiple files.

Data Generation
---------------

- ``examples/data_generation/simulator/``
  Synthetic noisy data generation for testing and validation.
- ``examples/data_generation/ml_training/``
  Training dataset generation via parameter-space exploration.

Notebooks
---------

- `01 basic fitting notebook <../../examples/fitting_workflows/01_basic_fitting/example.ipynb>`_
- `02 dependent parameters notebook <../../examples/fitting_workflows/02_dependent_parameters/example.ipynb>`_
- `03 multi-cycle notebook <../../examples/fitting_workflows/03_multi_cycle/example.ipynb>`_
- `04 parameter profiles notebook <../../examples/fitting_workflows/04_par_profiles/example.ipynb>`_
- `05 project-level fitting notebook <../../examples/fitting_workflows/05_project_level_fitting/example.ipynb>`_
- `Simulator data generation notebook <../../examples/data_generation/simulator/example.ipynb>`_
- `ML training data generation notebook <../../examples/data_generation/ml_training/example.ipynb>`_