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Simpler solution for wellplate exercise #323

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@JeremyPike JeremyPike commented Apr 30, 2024

This PR contains a couple minor suggestions and a simpler solution to the wellplate exercise which uses np.loadtxt() to load the .txt file containing the well coordinates. In my experience this has been much easier for learners to understand. Let me know what you think :)

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github-actions bot commented Apr 30, 2024

Thank you!

Thank you for your pull request 😃

🤖 This automated message can help you check the rendered files in your submission for clarity. If you have any questions, please feel free to open an issue in {sandpaper}.

If you have files that automatically render output (e.g. R Markdown), then you should check for the following:

  • 🎯 correct output
  • 🖼️ correct figures
  • ❓ new warnings
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Rendered Changes

🔍 Inspect the changes: https://github.com/datacarpentry/image-processing/compare/md-outputs..md-outputs-PR-323

The following changes were observed in the rendered markdown documents:

 02-image-basics.md   | 10 +++++-----
 03-skimage-images.md |  2 ++
 04-drawing.md        | 26 +++++++++++++++-----------
 md5sum.txt           |  6 +++---
 4 files changed, 25 insertions(+), 19 deletions(-)
What does this mean?

If you have source files that require output and figures to be generated (e.g. R Markdown), then it is important to make sure the generated figures and output are reproducible.

This output provides a way for you to inspect the output in a diff-friendly manner so that it's easy to see the changes that occur due to new software versions or randomisation.

⏱️ Updated at 2024-04-30 15:01:19 +0000

@@ -436,7 +436,7 @@ a mapped continuum of intensities: greyscale.

```python
fig, ax = plt.subplots()
ax.imshow(three_colours,cmap=plt.cm.gray)
ax.imshow(three_colours, cmap="gray")
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For consistency with the rest of the material

github-actions bot pushed a commit that referenced this pull request Apr 30, 2024
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