This file contains helpful tips & tricks found in the process of developing this project.
Converting notebooks to restructured text¶
jupyter nbconvert mynotebook.ipynb --to rst
Any images in the notebook will be saved as png files within a newly created
mynotebook_files and automatically referenced within the
For more information, check out here
Helper functions from
Similar to numpy’s log1p, bmorph.evaluation.plotting.log10_1p has been added to address wanting to perform log10 computations on a dataset that contains zeros. It effectively adds 1 to the data, element-wise, and then takes the log10. This is useful in scientific plots where a log10 scale is desired yet zeros reside in the dataset.
Tired of having to constantly reformat you subplots whenever you want to tack on one more plot or scratch off something you didn’t think you wanted? Well bmorph.plotting.evaluation.determine_row_col automates that process for you by calculating the tightest possible square/rectangular dimensions for your subplots. There may be some extra subplots leftover (and therefore we recommend turning off axis past the number you wish to plot), there will be at least enough subplots to fit all that you ask for.
tqdm is a customizable progress bar for iterators, used here in
apply_scbc for example. These allow for an easily updatable status of progress to be printed from your scripts or notebooks. A few helpful arguments include
disable to turn them off,
leave to determine whether to keep the bar after it completes, or
desc to provide a label for the progress bar.
Documentation for this project was done with Sphinx’s reStructuredText. Compiling of the documentation into an HTMl format was performed by Read the Docs. Thanks to through software, documentation was made easily updatable through GitHub version control without needing to develop a website from scratch in HTML itself.