Consistent bin-width in histograms summarising multiple images #524
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Closes #479 Contrary to the title `plotting.py`, which uses Seaborn, produces consistent bin-width when the range of values differs between images. The Jupyter Notebook (`notebooks/02-Summary-statistics-and-plots.ipynb`) uses Pandas for loading data and plotting it (a deliberate choice to reduce the number of packages users would encounter) and it is Pandas which produces the different bin-widths (see [#22222 ENH: groupby.hist bins don't match](pandas-dev/pandas#22222)). The Notebook has been updated to show how to use `np.linspace()` across the total range of data. Docstrings of `tests/test_plotting.py` have also been improved.
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## main #524 +/- ##
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+ Coverage 80.02% 80.08% +0.06%
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Files 19 19
Lines 2783 2792 +9
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+ Hits 2227 2236 +9
Misses 556 556
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SylviaWhittle
approved these changes
Apr 13, 2023
Jean-Du
reviewed
Apr 13, 2023
Jean-Du
reviewed
Apr 13, 2023
Jean-Du
reviewed
Apr 13, 2023
Jean-Du
reviewed
Apr 13, 2023
|
Good catches on the commented code and grammar @Jean-Du thanks. Thanks for the approval @SylviaWhittle Merged 🎉 |
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Closes #479
Contrary to the title
plotting.py, which uses Seaborn, produces consistent bin-width when the range of values differs between images. The Jupyter Notebook (notebooks/02-Summary-statistics-and-plots.ipynb) uses Pandas for loading data and plotting it (a deliberate choice to reduce the number of packages users would encounter) and it is Pandas which produces the different bin-widths (see #22222 ENH: groupby.hist bins don't match).The Notebook has been updated to show how to use
np.linspace()across the total range of data.Docstrings of
tests/test_plotting.pyhave also been improved.