Restore QM in docs
-Toolkit module
-==============
+Preprocessing module
+====================
-The :py:mod:`spiketinterface.toolkit` module includes tools to process SI objects throughout your analysis.
-
-
-Preprocessing
--------------
-
-The :py:mod:`~spikeinterface.toolkit.preprocessing` sub-module includes preprocessing steps to apply before spike
+The :py:mod:`~spikeinterface.toolkit.preprocessing` module includes preprocessing steps to apply before spike
sorting. Preprocessors are *lazy*, meaning that no computation is performed until it is required (usually at the
spike sorting step). This enables one to build preprocessing chains to be applied in sequence to a
:code:`RecordingExtractor` object.
@@ -41,7 +35,7 @@ CMR and save it to a binary file in the "preprocessed" folder. The :code:`record
Postprocessing module
=====================
-After spike sorting, we can use the :py:mod:`~spikeinterface.toolkit.postprocessing` sub-module to further post-process
+After spike sorting, we can use the :py:mod:`~spikeinterface.toolkit.postprocessing` module to further post-process
the spike sorting output. Most of the post-processing functions require a
:py:class:`~spikeinterface.core.WaveformExtractor` as input. Available postprocessing tools are:
@@ -77,6 +71,7 @@ For more details about each metric and it's availability and use within SpikeInt
.. toctree::
:maxdepth: 1
:glob:
+ quality_metrics/*
Quality metrics allows to quantitatively assess to *goodness* of a spike sorting output. The
:py:mod:`~spikeinterface.toolkit.qualitymetrics` sub-module includes functions to compute a large variety of available
