Add software support page

doc/format.rst

@@ -125,7 +125,7 @@ keyword ``array`` in the relevant PEtab table entry.
 Semantically, assigning ``array`` is interpreted as a global assignment to an
 array variable whose potentially condition-specific values are provided in an
 array data file. Therefore, specifying ``array`` is only valid in the
-:ref:`hybridization table <_hybrid_table>` and the
+:ref:`hybridization table <hybrid_table>` and the
 :ref:`parameter Table <parameter_table>`, where assignments apply across all
 PEtab experiments.
 

doc/index.rst

@@ -10,7 +10,7 @@ PEtab SciML - Scientific Machine Learning Format and Tooling
 
    Introduction <introduction>
    Getting Started <examples/getting_started/getting_started.ipynb>
-   trouble
+   software_support
    Contributing <_tmp/CONTRIBUTING>
 
 .. toctree::

doc/introduction.rst

@@ -63,10 +63,11 @@ How to read the documentation
 -----------------------------
 
 If you are new to PEtab SciML, start with the
-:doc:`Getting Started tutorial <tutorial>`. It is a prerequisite for the
-How-to guides, which cover different model scenarios (e.g., Neural ODEs, ML
-model upstream of the ODE). For a complete description of all options when
-defining a SciML problem, see the :doc:`Format specification <format>`.
+:doc:`Getting Started tutorial <examples/getting_started/getting_started>`
+It is a prerequisite for the How-to guides, which cover different model
+scenarios (e.g., Neural ODEs, ML model upstream of the ODE). For a complete
+description of all options when defining a SciML problem, see the
+:doc:`Format specification <format>`.
 
 Why a SciML data format?
 ------------------------
@@ -97,7 +98,6 @@ Getting Help with and Extending PEtab SciML
 
 If you run into problems:
 
-- Check the :doc:`Troubleshooting <trouble>` section of the documentation.
 - If you encounter unexpected behavior or a bug, please open an
   `issue <https://github.com/PEtab-dev/petab_sciml/issues/>`_ on GitHub
 

doc/layers.rst

@@ -1,22 +1,22 @@
 .. _layers_activation:
 
-Supported Layers and Activation Functions
-=======================================================================
+Neural-network YAML format
+==========================
 
-The PEtab SciML NN model YAML format supports numerous
+The PEtab SciML neural network (NN) model YAML format supports numerous
 standard neural network layers and activation functions. Layer names and
-associated keyword arguments follow the PyTorch naming scheme. PyTorch
-is used because it is currently the most popular machine learning
-framework, and its comprehensive documentation makes it easy to look up
-details for any specific layer or activation function.
+associated keyword arguments follow the PyTorch naming scheme. PyTorch is used
+because it is currently the most popular machine learning framework, and its
+comprehensive documentation makes it easy to look up details for any specific
+layer or activation function.
 
-If support is lacking for a layer or activation function you would like
-to see, please file an issue on
+If support is lacking for a layer or activation function you would like to see,
+please file an issue on
 `GitHub <https://github.com/PEtab-dev/petab_sciml/issues>`__.
 
-The table below lists the supported and tested neural network layers
-along with links to their respective PyTorch documentation.
-Additionally, the table indicates which tools support each layer.
+The table below lists the supported and tested neural network layers along with
+links to their respective PyTorch documentation. Additionally, the table
+indicates which tools support each layer.
 
 +--------------------------------------------------------------+----+---+
 | layer                                                        | PE | A |
@@ -122,9 +122,9 @@ Additionally, the table indicates which tools support each layer.
 Supported Activation Function
 -----------------------------
 
-The table below lists the supported and tested activation functions
-along with links to their respective PyTorch documentation.
-Additionally, the table indicates which tools support each layer.
+The table below lists the supported and tested activation functions along with
+links to their respective PyTorch documentation. Additionally, the table
+indicates which tools support each layer.
 
 +--------------------------------------------------------------+----+---+
 | Function                                                     | PE | A |

doc/software_support.rst

@@ -0,0 +1,19 @@
+.. _software_support:
+
+Software support
+================
+
+Tools that support importing PEtab-SciML problems for downstream tasks (e.g.
+simulation and model training), listed alphabetically are:
+
+- `AMICI <https://github.com/ICB-DCM/AMICI/>`__
+  (`Example <https://github.com/ICB-DCM/AMICI/blob/master/python/examples/example_petab/petab.ipynb>`__)
+- `PEtab.jl <https://github.com/sebapersson/PEtab.jl>`__
+  (`Example <https://sebapersson.github.io/PEtab.jl/stable/tutorials/sciml/standard_format/>`__)
+
+If your tool supports PEtab-SciML and you would like it listed here, please
+`open an issue <https://github.com/PEtab-dev/petab_sciml/issues>`__.
+
+Both AMICI and PEtab.jl support the PEtab-SciML neural-network YAML format.
+For supported layers and activation functions, see the
+:ref:`Neural-network YAML format <layers_activation>` page.