chore: pre-commit run

docs/modules/data_indices.rst

@@ -2,100 +2,121 @@
  Data Indices
 ##############
 
-Data routing with a DataIndex system that knows where data is passed based on config entries.
+Data routing with a DataIndex system that knows where data is passed
+based on config entries.
 
-This documentation aims to first explain the user side (configs), and then goes into detail for developers.
+This documentation aims to first explain the user side (configs), and
+then goes into detail for developers.
 
 Good news first: You don't need to know the index of data in your Zarr
 
-*************
+*******************
  Usage Information
-*************
+*******************
 
 The routing information can be changed in the config in data.
 
 There are currently three types of data with respect to the model:
 
-- Prognostic: Data that is input into and output from the model
-- Forcing: Data that informs the model as auxiliary information but isn't output nor fed to the loss
-- Diagnostic: Data that is not input into the model, but is produced in the inference. (It's pseudo-diagnostic, as it is fed to the loss during training, so the model is still conditioned on this data.)
+-  Prognostic: Data that is input into and output from the model
 
-The default in Anemoi Models is that data is prognostic. But data can be switched to forcing or diagnostic by adding the value to the existing config entry:
+-  Forcing: Data that informs the model as auxiliary information but
+   isn't output nor fed to the loss
 
-.. code-block:: yaml
+-  Diagnostic: Data that is not input into the model, but is produced in
+   the inference. (It's pseudo-diagnostic, as it is fed to the loss
+   during training, so the model is still conditioned on this data.)
 
-    data:
-      forcing:
-        - "lsm"
-        - "sdor"
-      diagnostic:
-        - "tp"
-        - "cp"
+The default in Anemoi Models is that data is prognostic. But data can be
+switched to forcing or diagnostic by adding the value to the existing
+config entry:
+
+.. code:: yaml
+
+   data:
+     forcing:
+       - "lsm"
+       - "sdor"
+     diagnostic:
+       - "tp"
+       - "cp"
 
 .. figure:: ../schemas/data_indices.png
    :alt: Schematic of IndexCollection with Data Indexing on Data and Model levels.
    :align: center
 
 The are two Index-levels:
 
-- Data: The data at "Zarr"-level provided by Anemoi-Datasets
-- Model: The "squeezed" tensors with irrelevant parts missing.
+-  Data: The data at "Zarr"-level provided by Anemoi-Datasets
+-  Model: The "squeezed" tensors with irrelevant parts missing.
 
 These are both split into two versions:
 
-- Input: The data going into training / model
-- Output: The data produced by training / model
+-  Input: The data going into training / model
+-  Output: The data produced by training / model
 
-Each of these four indices has four integer Tensors available to slice into the data:
+Each of these four indices has four integer Tensors available to slice
+into the data:
 
-- full: The indices of all "relevant" data, i.e. prognostic and forcing for the input data.
-- diagnostic: The indices for data that is "output only" and not fed to the model.
-- prognostic: The indices for data that is in both the input and output for the training and model.
-- forcing: The indices for data that is only input into the model but doesn't exist in the forecast state.
+-  full: The indices of all "relevant" data, i.e. prognostic and forcing
+   for the input data.
+-  diagnostic: The indices for data that is "output only" and not fed to
+   the model.
+-  prognostic: The indices for data that is in both the input and output
+   for the training and model.
+-  forcing: The indices for data that is only input into the model but
+   doesn't exist in the forecast state.
 
 The data can be accessed via dot notation in such a way that:
 
-.. code-block:: python
+.. code:: python
 
    data_indices.<model/data>.<input/output>.<full/diagnostic/prognostic/forcing>
 
 Examples:
 
+.. code:: python
 
-.. code-block:: python
-
-    data_indices.data.input.full
-    data_indices.model.output.diagnostic
+   data_indices.data.input.full
+   data_indices.model.output.diagnostic
 
-The name_to_index dictionary is available for each of the four indices, which provides a mapping from variable name to index at that level. These are useful for providing users an interface in the config that does not rely on the knowledge of index-locations in the data. Generally, hard-coded locations are to be avoided.
+The name_to_index dictionary is available for each of the four indices,
+which provides a mapping from variable name to index at that level.
+These are useful for providing users an interface in the config that
+does not rely on the knowledge of index-locations in the data.
+Generally, hard-coded locations are to be avoided.
 
-*************
+*******************
  Index Collections
-*************
+*******************
 
-The Index Collections module provides a collection of indices, which are used to index and slice the data.
+The Index Collections module provides a collection of indices, which are
+used to index and slice the data.
 
 .. automodule:: anemoi.models.data_indices.collection
    :members:
    :no-undoc-members:
    :show-inheritance:
 
-*************
+*******
  Index
-*************
+*******
 
-The Index module provides all data indices and methods for indexing and slicing the data.
+The Index module provides all data indices and methods for indexing and
+slicing the data.
 
 .. automodule:: anemoi.models.data_indices.index
    :members:
    :no-undoc-members:
    :show-inheritance:
 
-*************
+********
  Tensor
-*************
+********
 
-This provides the underlying data structure for the indices. It creates a tensor of the appropriate size and shape, and provides methods for indexing and slicing the data.
+This provides the underlying data structure for the indices. It creates
+a tensor of the appropriate size and shape, and provides methods for
+indexing and slicing the data.
 
 .. automodule:: anemoi.models.data_indices.tensor
    :members:

docs/modules/layers.rst

@@ -2,18 +2,18 @@
  Layers
 ########
 
-********
+*********
  Mappers
-********
+*********
 
 .. automodule:: anemoi.models.layers.mapper
    :members:
    :no-undoc-members:
    :show-inheritance:
 
-********
+************
  Processors
-********
+************
 
 .. automodule:: anemoi.models.layers.processor
    :members:
@@ -38,45 +38,45 @@
    :no-undoc-members:
    :show-inheritance:
 
-********
+*******
  Graph
-********
+*******
 
 .. automodule:: anemoi.models.layers.graph
    :members:
    :no-undoc-members:
    :show-inheritance:
 
-********
+******
  Conv
-********
+******
 
 .. automodule:: anemoi.models.layers.conv
    :members:
    :no-undoc-members:
    :show-inheritance:
 
-********
+***********
  Attention
-********
+***********
 
 .. automodule:: anemoi.models.layers.attention
    :members:
    :no-undoc-members:
    :show-inheritance:
 
-********
+************************
  Multi-Layer Perceptron
-********
+************************
 
 .. automodule:: anemoi.models.layers.mlp
    :members:
    :no-undoc-members:
    :show-inheritance:
 
-********
+*******
  Utils
-********
+*******
 
 .. automodule:: anemoi.models.layers.utils
    :members:

docs/modules/models.rst

@@ -2,11 +2,12 @@
  Models
 ########
 
-*************
+*********************************
  Encoder Processor Decoder Model
-*************
+*********************************
 
-The model defines a graph neural network architecture with configurable encoder, processor, and decoder.
+The model defines a graph neural network architecture with configurable
+encoder, processor, and decoder.
 
 .. automodule:: anemoi.models.models.encoder_processor_decoder
    :members:

docs/modules/preprocessing.rst

@@ -2,30 +2,32 @@
  Preprocessing
 ###############
 
-The preprocessing module is used to pre- and post-process the data.
-The module contains the following classes:
+The preprocessing module is used to pre- and post-process the data. The
+module contains the following classes:
 
 .. automodule:: anemoi.models.preprocessing
    :members:
    :no-undoc-members:
    :show-inheritance:
 
-***********
+************
  Normalizer
-***********
+************
 
-The normalizer module is used to normalize the data. The module contains the following classes:
+The normalizer module is used to normalize the data. The module contains
+the following classes:
 
 .. automodule:: anemoi.models.preprocessing.normalizer
    :members:
    :no-undoc-members:
    :show-inheritance:
 
-***********
+*********
  Imputer
-***********
+*********
 
-The imputer module is used to impute the data. The module contains the following classes:
+The imputer module is used to impute the data. The module contains the
+following classes:
 
 .. automodule:: anemoi.models.preprocessing.imputer
    :members: