Prepare v3.1.0

RELEASE_NOTES.rst

@@ -1,9 +1,11 @@
-Next release
-============
+v3.1.0 (2020-08-28)
+===================
 
 All changes
 -----------
 
+ixmp v3.1.0 coincides with message_ix v3.1.0.
+
 - :pull:`345`: Fix a bug in :meth:`.read_excel` when parameter data is spread across multiple sheets.
 - :pull:`363`: Expand documentation and revise installation instructions.
 - :pull:`362`: Raise Python exceptions from :class:`.JDBCBackend`.

rixmp/DESCRIPTION

@@ -1,7 +1,7 @@
 Package: rixmp
 Type: Package
 Title: R Interface to the IX Modeling Platform
-Version: 3.0.0.9000
+Version: 3.1.0
 Authors@R: c(
     person("Adriano", "Vinca", email = "[email protected]",
            role = c("aut", "cre")),

tutorial/README.rst

@@ -13,8 +13,8 @@ This problem finds a least cost shipping schedule that meets demand requirements
 The tutorials are provided as Jupyter notebooks for both Python and R, and are identical as far as possible.
 
 - Tutorial 1:
-  in `Python <https://github.com/iiasa/ixmp/blob/master/tutorial/transport/py_transport.ipynb>`__,
-  or in `R <https://github.com/iiasa/ixmp/blob/master/tutorial/transport/R_transport.ipynb>`__.
+  in `Python <https://github.com/iiasa/ixmp/blob/v3.1.0/tutorial/transport/py_transport.ipynb>`__,
+  or in `R <https://github.com/iiasa/ixmp/blob/v3.1.0/tutorial/transport/R_transport.ipynb>`__.
 
   This tutorial walks through the following steps:
 
@@ -25,7 +25,7 @@ The tutorials are provided as Jupyter notebooks for both Python and R, and are i
   5. Display the solution (variables and equation).
 
 - Tutorial 2:
-  in `Python <https://github.com/iiasa/ixmp/blob/master/tutorial/transport/py_transport_scenario.ipynb>`__,
-  or in `R <https://github.com/iiasa/ixmp/blob/master/tutorial/transport/R_transport_scenario.ipynb>`__.
+  in `Python <https://github.com/iiasa/ixmp/blob/v3.1.0/tutorial/transport/py_transport_scenario.ipynb>`__,
+  or in `R <https://github.com/iiasa/ixmp/blob/v3.1.0/tutorial/transport/R_transport_scenario.ipynb>`__.
 
   This tutorial creates an alternate or ‘counterfactual’ scenario of the transport problem; solves it; and compares the results to the original or reference scenario.