Merge branch 'vara-dev' into f-RevisionBinaryMap-SingleRevision

se-sic · Sep 22, 2023 · b56d6a7 · b56d6a7
2 parents 29a14a9 + 3d6b4ff
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diff --git a/docs/source/conf.py b/docs/source/conf.py
@@ -87,6 +87,10 @@
 # modules that require this module before setting the type checking flag.
 import scipy.stats  # isort:skip
 
+# Matplotlib >=3.8 has a type-checking-flag-guarded import of a symbol that does
+# not exist in the shipped version.
+import matplotlib.pyplot  # isort:skip
+
 # The autodocs typehints plugin does not resolve circular imports caused by type
 # annotations, so we have to manually break the circles.
 import rich.console  # isort:skip

diff --git a/docs/source/vara-ts-api/tools/vara-cs-gui.rst b/docs/source/vara-ts-api/tools/vara-cs-gui.rst
@@ -10,6 +10,7 @@ The gui is started by::
 
 The gui provides 3 Strategies to generate case studies:
     - Manual revision selection: Select revision from the revision history of a project. Multiple revisions can be selected by holding `ctrl` and ranges by holding `shift`. Revisions which are blocked because of bugs in the compilation of the project are marked blue.
+
     .. figure:: vara-cs-gui-manual.png
 
     - Random Sampling: Sample a number of revisions using a random a Normal or HalfNormal Distribution.

diff --git a/varats/varats/data/metrics.py b/varats/varats/data/metrics.py
@@ -28,7 +28,7 @@ def gini_coefficient(distribution: pd.Series) -> float:
     Calculates the Gini coefficient of the data.
 
     For more information see online
-    `gini coefficient <https://en.wikipedia.org/wiki/Gini_coefficient>`_.
+    `Gini coefficient <https://en.wikipedia.org/wiki/Gini_coefficient>`_.
 
     Args:
         distribution: sorted series to calculate the Gini coefficient for
@@ -141,10 +141,12 @@ class ConfusionMatrix(tp.Generic[T]):
     """
     Helper class to automatically calculate classification results.
 
-                        |  Predicted Positive (PP)  |  Predicted Negative (PN)
-    --------------------|---------------------------|--------------------------
-    Actual Positive (P) |  True Positive      (TP)  |  False Negative     (FN)
-    Actual Negative (N) |  False Positive     (FP)  |  True Negative      (TN)
+    +---------------------+-------------------------+-------------------------+
+    |                     | Predicted Positive (PP) | Predicted Negative (PN) |
+    +---------------------+-------------------------+-------------------------+
+    | Actual Positive (P) | True Positive      (TP) | False Negative     (FN) |
+    | Actual Negative (N) | False Positive     (FP) | True Negative      (TN) |
+    +---------------------+-------------------------+-------------------------+
 
     Reference: https://en.wikipedia.org/wiki/Precision_and_recall
     """