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NIRSpec IFU Demo Notebook #7
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Check out this pull request on See visual diffs & provide feedback on Jupyter Notebooks. Powered by ReviewNB |
Just adding a quick note that it would be best to pause testing of this PR for a little while until we've got a template notebook finalized and can discuss content and overall design prior to digging into more technical details. |
I have updated the notebook to follow the example template. I will upload the replacement to a new PR for now since the format of the notebook has changed. Once I do we can close this PR or if preferred I can add the notebook to this existing PR and close the new one. |
This notebook was previously part of a JDAT notebook PR. This PR includes one notebooks developed by the NIRSpec team demonstrating IFU data reduction.
This notebook checklist has been made available to us by the the Notebooks For All team.
Its purpose is to serve as a guide for both the notebook author and the technical reviewer highlighting critical aspects to consider when striving to develop an accessible and effective notebook.
The First Cell
<h1>
or# in markdown
).1., 2.,
etc. in Markdown).The Rest of the Cells
#
in Markdown) used in the notebook.Text
Code
Images
All images (jpg, png, svgs) have an image description. This could be
alt
property)alt
attribute with no value)Any text present in images exists in a text form outside of the image (this can be alt text, captions, or surrounding text.)
Visualizations
All visualizations have an image description. Review the previous section, Images, for more information on how to add it.
Visualization descriptions include
All visualizations and their parts have enough color contrast (color contrast checker) to be legible. Remember that transparent colors have lower contrast than their opaque versions.
All visualizations convey information with more visual cues than color coding. Use text labels, patterns, or icons alongside color to achieve this.
All visualizations have an additional way for notebook readers to access the information. Linking to the original data, including a table of the data in the same notebook, or sonifying the plot are all options.