Update expected figures to use matplotlib 3.5 (#590)

* Change to `pytest` instead of `py.test`

* Silence a warning

* Update test images to use matplotlib 3.5

* Add to release notes

* Set "older" matplotlib version in dependency-tests to current version

.github/workflows/pytest-dependency.yml

@@ -25,7 +25,7 @@ jobs:
     - name: Install specific out-dated version of dependencies
       # Update the package requirements when changing minimum dependency versions
       # Please also add a section "Dependency changes" to the release notes
-      run: pip install pandas==1.1.1 numpy==1.19.0 matplotlib==3.2.0 iam-units==2020.4.21 xlrd==2.0
+      run: pip install pandas==1.1.1 numpy==1.19.0 matplotlib==3.5.0 iam-units==2020.4.21 xlrd==2.0
 
     - name: Install other dependencies and package
       run: pip install -e .[tests,deploy,optional_plotting,optional_io_formats,tutorials]

RELEASE_NOTES.md

@@ -1,5 +1,8 @@
 # Next release
 
+- [#590](https://github.com/IAMconsortium/pyam/pull/590) Update expected figures of plotting tests to use matplotlib 3.5
+- [#586](https://github.com/IAMconsortium/pyam/pull/586) Improve error reporting for non-numeric data in any value column
+
 # Release v1.2.0
 
 ## Highlights
@@ -16,7 +19,6 @@ was added as a dependency.
 
 ## Individual updates
 
-- [#586](https://github.com/IAMconsortium/pyam/pull/586) Improve error reporting for non-numeric data in any value column
 - [#585](https://github.com/IAMconsortium/pyam/pull/585) Include revisions to the ORE manuscript source code following acceptance/publication 
 - [#583](https://github.com/IAMconsortium/pyam/pull/583) Add profiler module for performance benchmarking
 - [#579](https://github.com/IAMconsortium/pyam/pull/579) Increase performance of IamDataFrame initialization

install.bat

@@ -1,7 +1,7 @@
 
 python setup.py install
 
-py.test tests
+pytest tests
 
 pause
 exit

pyam/plotting.py

@@ -437,7 +437,7 @@ def stack(
 
     def as_series(index, name):
         _idx = [i[0] for i in index]
-        return pd.Series([0] * len(index), index=_idx, name=name)
+        return pd.Series([0] * len(index), index=_idx, name=name, dtype="int")
 
     # determine all time-indices where a timeseries crosses 0 and add to data
     _rows = pd.concat(

tests/README.md

@@ -16,11 +16,11 @@ to be the same version.
 ## Creating Baseline Images
 
 ```
-py.test --mpl-generate-path=expected_figs test_plotting.py
+pytest --mpl-generate-path=expected_figs test_plotting.py
 ```
 
 ## Running tests
 
 ```
-py.test --mpl
+pytest --mpl
 ```