From af4ed3a2003cb92841a86f64ad412003d2b70b0c Mon Sep 17 00:00:00 2001 From: Daniel Weindl Date: Thu, 5 Mar 2026 10:34:55 +0100 Subject: [PATCH] doc: Update GettingStartedExtended.ipynb Add some high-level overview. --- .../GettingStartedExtended.ipynb | 22 ++++++++++++++++++- 1 file changed, 21 insertions(+), 1 deletion(-) diff --git a/doc/examples/getting_started_extended/GettingStartedExtended.ipynb b/doc/examples/getting_started_extended/GettingStartedExtended.ipynb index 9fc598ec28..c1e7a11366 100644 --- a/doc/examples/getting_started_extended/GettingStartedExtended.ipynb +++ b/doc/examples/getting_started_extended/GettingStartedExtended.ipynb @@ -6,7 +6,7 @@ "source": [ "# SBML import, observation model, sensitivity analysis, data export and visualization\n", "\n", - "This is an example using the [model_steadystate_scaled.xml] model to demonstrate:\n", + "This example demonstrates:\n", "\n", "* SBML import\n", "* specifying the observation model\n", @@ -14,6 +14,24 @@ "* exporting and visualizing simulation results" ] }, + { + "metadata": {}, + "cell_type": "markdown", + "source": [ + "## Overview\n", + "\n", + "This example will give you a good overview of the main steps to run simulations in AMICI and how to use the main AMICI objects. The most important AMICI objects when working with the SUNDIALS backend are `Model`, `Solver`, `ExpData` and `ReturnData`. The relationships between these objects are shown in the following figure.\n", + "\n", + "![amici objects](../../gfx/amici_objects.png \"The main AMICI objects and their relationships\")\n", + "\n", + "We will use the `SbmlImporter` to import an SBML model, compile it to a Python module, and then use the generated `Model` to run simulations. We will show how to apply simulation and sensitivity analysis settings via `Solver`. The `ExpData` class will be used to provide experimental data and parameter values.\n", + " The results of the simulations will be stored in a `ReturnData` instance. We will show how to access these results, convert them to `pandas.DataFrame`s, and visualize them using `matplotlib.pyplot` and `amici.sim.sundials.plotting`.\n", + "\n", + "**Further information:**\n", + "Additional `ExpData` features, i.e., presimulation and pre-equilibration, are introduced in [ExampleExperimentalConditions.ipynb](https://amici.readthedocs.io/en/latest/examples/example_presimulation/ExampleExperimentalConditions.html).\n", + "Additional `Solver` settings related to steady-state simulation and sensitivity analysis are explained in the [ExampleEquilibrationLogic.ipynb](https://amici.readthedocs.io/en/latest/examples/example_steady_states/ExampleEquilibrationLogic.html) notebook." + ] + }, { "cell_type": "code", "metadata": {}, @@ -46,6 +64,8 @@ "source": [ "## The example model\n", "\n", + "In this example we use the [model_steadystate_scaled.xml] model, which describes the interconversion of three species (`x1`, `x2` and `x3`) following mass-action kinetics.\n", + "\n", "Here we use `libsbml` to show the reactions and species described by the model (this is independent of AMICI)." ] },