Update version and bump release (#226)

* update python

* update reqs

* revert python versions

* update

* fix numpy

* revert docker

* add vscode recommendations

* update versions

.gitignore

@@ -140,9 +140,6 @@ dmypy.json
 .DS_Store
 ._.DS_Store
 
-# VSCode config files
-.vscode
-
 # package specific excludes
 examples/*.png
 # user specific files

.pre-commit-config.yaml

@@ -1,14 +1,10 @@
 repos:
   - repo: https://github.com/charliermarsh/ruff-pre-commit
-    rev: "v0.0.289"
+    rev: "v0.1.6"
     hooks:
       - id: ruff
         args: [--fix, --exit-non-zero-on-fix]
-
-  - repo: https://github.com/psf/black
-    rev: "23.9.1"
-    hooks:
-      - id: black
+      - id: ruff-format
 
   #- repo: https://github.com/pre-commit/mirrors-mypy
   #  rev: "v1.1.1"

.vscode/extensions.json

@@ -0,0 +1,8 @@
+{
+    "recommendations": [
+        "ms-python.python",
+        "njpwerner.autodocstring",
+        "elagil.pre-commit-helper",
+        "charliermarsh.ruff"
+    ]
+}

.vscode/settings.json

@@ -0,0 +1,16 @@
+{
+    "editor.stickyScroll.enabled": true,
+    "autoDocstring.docstringFormat": "numpy",
+    "[python]": {
+        "editor.defaultFormatter": "charliermarsh.ruff",
+        "editor.codeActionsOnSave": {
+            "source.organizeImports": true
+        },
+    },
+    "editor.formatOnSave": true,
+    "files.watcherExclude": {
+        "**/.git/objects/**": true,
+        "**/.git/subtree-cache/**": true,
+        "**/logs/*/**": true
+    }
+}

README.md

@@ -49,7 +49,7 @@ The Docker images are built on GitHub and contain the latest version from the `m
 The container registry with all available tags can be found
 [here](https://gitlab.cern.ch/atlas-flavor-tagging-tools/training-images/puma-images/container_registry/13727).
 
-The `puma:latest` image is based on `python:3.8.15-slim` and is meant for users who want to use the latest version of `puma`. For each release, there is a corresponding tagged image.
+The `puma:latest` image is based on `python:3.8.15` and is meant for users who want to use the latest version of `puma`. For each release, there is a corresponding tagged image.
 You can start an interactive shell in a container with your current working directory
 mounted into the container by using one of the commands provided below.
 

changelog.md

@@ -2,10 +2,14 @@
 
 ### [Latest]
 
+
+### [v0.3.1] (2023/11/27)
+
+- Update versions and add vscode settings [!226](https://github.com/umami-hep/puma/pull/226)
 - Update ratio uncertainty calculation [!225](https://github.com/umami-hep/puma/pull/225)
+- Adding option for initialising histograms with pre-binned distributions. [!221](https://github.com/umami-hep/puma/pull/221)
 - Add NaN filtering for HL plots. Bump atlas-ftag-tools version to 0.1.11. [!220](https://github.com/umami-hep/puma/pull/220)
 - Making Under- and Overflow bins default in histograms [!218](https://github.com/umami-hep/puma/pull/218)
-- Adding "bin_edges" and "sum_squared_weights" parameters to the Histogram constructor to define pre-filled histograms.
 
 ### [v0.3.0] (2023/10/03)
 

puma/__init__.py

@@ -2,7 +2,7 @@
 
 # flake8: noqa
 
-__version__ = "0.3.0"
+__version__ = "0.3.1"
 
 from puma.histogram import Histogram, HistogramPlot
 from puma.integrated_eff import IntegratedEfficiency, IntegratedEfficiencyPlot

puma/histogram.py

@@ -100,9 +100,11 @@ def __init__(
         self.sum_squared_weights = sum_squared_weights
 
         if bin_edges is None and sum_squared_weights is not None:
-            logger.warning("""The Histogram has no bin edges defined and is thus
+            logger.warning(
+                """The Histogram has no bin edges defined and is thus
                               not considered filled. Parameter `sum_squared_weights`
-                              is ignored. """)
+                              is ignored. """
+            )
 
         # This attribute allows to know how to handle the histogram later during
         # plotting

requirements.txt

@@ -1,13 +1,10 @@
 atlasify==0.8.0
-black==23.1.0
-ruff==0.0.254
 coverage==6.3.1
-h5py==3.8.0
-librep==0.0.5
+h5py==3.10.0
 matplotlib==3.5.1
-numpy==1.24.*
+numpy==1.24.4
 pandas[hdf5]==1.5.3
-pre-commit==3.1.1
+pre-commit==3.5.0
 pydot==1.4.2
 pytest-cov==3.0.0
 pytest-randomly==3.11.0