.. _MERMachineLearningModels:


Machine Learning Models Product
===============================

Metadata
______________________

+------------------------------------------------+----------------------------------------------------------------------------------------------+
| Data product name                              | DpdMerMachineLearningModels                                                                  |
+------------------------------------------------+----------------------------------------------------------------------------------------------+
| Data product custodian                         | MER                                                                                          |
+------------------------------------------------+----------------------------------------------------------------------------------------------+
| Name of the Schema file                        | .. raw:: html                                                                                |
|                                                |                                                                                              |
|                                                | `euc-mer-MachineLearningModels.xsd <https://gitlab.euclid-sgs.uk/ST-DM/ST_DataModel/-/blob/1 |
|                                                | 0.1.2/ST_DM_Schema/auxdir/ST_DM_Schema/dpd/mer/euc-mer-MachineLearningModels.xsd>`_          |
+------------------------------------------------+----------------------------------------------------------------------------------------------+
| Last Edited for DPDD Version                   | 2.0                                                                                          |
+------------------------------------------------+----------------------------------------------------------------------------------------------+
| Processing Element(s) creating/using the data  | **Creators:**                                                                                |
| product                                        |                                                                                              |
|                                                | * This is an input product that is generated manually or using some dedicated                |
|                                                | scripts.                                                                                     |
|                                                |                                                                                              |
|                                                | **Consumers:**                                                                               |
|                                                |                                                                                              |
|                                                | * All MER :term:`Processing Element`\s.                                                      |
+------------------------------------------------+----------------------------------------------------------------------------------------------+
| Processing function using the data product     | MER                                                                                          |
+------------------------------------------------+----------------------------------------------------------------------------------------------+
| Proposed for inclusion in EAS/SAS              | This product is proposed for inclusion in the SAS: maybe.                                    |
|                                                |                                                                                              |
|                                                | This product contains trained machine learning models that are used in different             |
|                                                | steps of the MER pipeline. It could be useful to have them in the SAS in case                |
|                                                | scientists want to replicate some of the MER classifications.                                |
+------------------------------------------------+----------------------------------------------------------------------------------------------+

Data Product Elements
_____________________
+--------------+----------------------------------------------+
| Header       | object of type sys:genericHeader             |
+--------------+----------------------------------------------+
| Data         | object of type mer:merMachineLearningModels  |
+--------------+----------------------------------------------+
| QualityFlags | object of type dqc:sqfPlaceHolder            |
+--------------+----------------------------------------------+
| Parameters   | object of type ppr:genericKeyValueParameters |
+--------------+----------------------------------------------+


Detailed Description of the Data Product
________________________________________
.. DetailedDescStart

This product is an input to the MER :term:`Pipeline`. It contains a list of 
trained machine learning (ML) models used in one or several of the MER 
processing steps.

The product currently contains a ML model trained to detect spurious sources,
and the Zoobot model used to classify sources according to their morphology 
(see the :ref:`MER morphology cookbook <MERMorphologyCookbook>` for more 
details).

The main elements inside this product are:

* **TileIndex** (optional): The MER tile index to which the machine learning
  models should be associated.
* **PatchId** (optional): The sky patch id to which the machine learning models
  should be associated.
* **CalblockId** (optional): The calibration block id to which the machine 
  learning models should be associated.
* **CalblockVariant** (optional): The calibration block variant to which the
  machine learning models should be associated.
* **ProcessingMode** (optional): The MER pipeline processing mode (e.g. WIDE,
  DEEP) to which the machine learning models should be associated.
* **Model** (one to infinity): The model name and the file containing the 
  trained model.

.. DetailedDescEnd