finalize DFE development docs; closes #1085

.github/ISSUE_TEMPLATE/dfe-qc-issue-template.md

@@ -0,0 +1,17 @@
+---
+name: DFE QC issue template
+about: Quality control process for DFE addition
+title: QC for {dfe_id} ({species})
+labels: DFE QC
+assignees: ''
+
+---
+
+**PR for new model:** {link to Pull Request}
+**Original paper:** {ink to original paper}
+**Parameter values:** {reference to where parameter values can be found}
+
+**Potential issues that might lead to differences between the model implementations:**
+{description of any potential issues}
+
+**QC'er requests:** {tag potential developers to QC the model}

docs/development.rst

@@ -1652,7 +1652,7 @@ Testing your DFE model and submitting a PR
 
 After you finished your implementation, and specified all the
 necessary citations,
-we recommend that you run some basic local tests to see that
+we recommend that you run some basic local checks to see that
 the model was successfully loaded to ``stdpopsim``.
 You may follow the process outlined for `Testing your demographic model and submitting a PR`_.
 
@@ -1667,24 +1667,31 @@ of the development team before it is fully incorporated into ``stdpopsim``.
 This will likely require additional feedback from you,
 so, stay tuned for discussion during the review process.
 
+To facilitate this, there is one more step: please open a
+`new issue <https://github.com/popsim-consortium/stdpopsim/issues/new>`__,
+using the "DFE QC" template.
+The template asks for the basic information that someone will need
+to independently verify the implemented DFE.
+
 ---------------------
 Reviewing a DFE model
 ---------------------
 
-The review process for DFE models is currently being developed.
-For now, we suggest that you
-`open a new blank issue <https://github.com/popsim-consortium/stdpopsim/issues/new>`__
-and specify the following information:
+The process for reviewing a DFE is essentially the same
+as for reviewing a demographic model (see `Overview of the stdpopsim review process`_).
+Briefly, you will re-implement the DFE "blind", i.e., without looking at the DFE
+implementation already added to the code.
+Then, the unit tests check whether the implementations are equivalent.
+To do this, you add your implementation to ``stdpopsim/qc/<SPECIES_ID>.py``,
+followed by a call like
+
+.. code-block:: python
 
-1. **PR for new model:**
-2. **Original paper:**
-3. **Parameter values:**
-4. **Potential issues:**
-5. **QC'er requests:**
+    _species.get_dfe(_MODEL_ID_).register_qc(_your_review_function())
 
-A reviewer will be assigned to check your implementation and approve it.
-All discussion about the review can be conducted in the **QC issue**
-mentioned above.
+where ``_MODEL_ID_`` is the string specified as the ID for the original DFE,
+and ``_your_review_function()`` is the function you've added to the QC file
+that returns a DFE object.
 
 ****************
 Coding standards