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Fixes docs break with matplotlib >=3.8 #837

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Sep 22, 2023
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Fixes docs break with matplotlib >=3.8 #837

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23f8dd3
Docs: import matplotlib without type checking
boehmseb Sep 18, 2023
e2198ca
Docs: Fix confusion matrix table.
boehmseb Sep 18, 2023
97bb750
Docs: Add missing newline
boehmseb Sep 18, 2023
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4 changes: 4 additions & 0 deletions docs/source/conf.py
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Original file line number Diff line number Diff line change
Expand Up @@ -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
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1 change: 1 addition & 0 deletions docs/source/vara-ts-api/tools/vara-cs-gui.rst
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Expand Up @@ -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.
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12 changes: 7 additions & 5 deletions varats/varats/data/metrics.py
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Expand Up @@ -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
Expand Down Expand Up @@ -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
"""
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