Add a parameter to name kink image in thresh_peaks

[julianstanley]

Explain your changes:

I am using this pipeline on real data and am calculating Z scores for multiple files, like this:

There's two issues here: (1) it combines the kink plots from all the files, so I just added plt.figure() to my wrapper,

and (2) it saves all the images as kink.png, so it overwrites previous ones.

No problem, let's just add a parameter to thresh_peaks to let us name the image files so I can save them each with the name of their associated wig file.

Does this close any issues?

Any comments? Anything in particular you need feedback on?

PR checklist

• I have written tests for my changes where needed and made sure they pass locally.

[codecov-commenter]

Codecov Report

Merging #44 (0eba2d2) into main (727fada) will not change coverage.
The diff coverage is 100.00%.

@@           Coverage Diff           @@
##             main      #44   +/-   ##
=======================================
  Coverage   77.68%   77.68%           
=======================================
  Files           8        8           
  Lines         802      802           
=======================================
  Hits          623      623           
  Misses        179      179           

Flag	Coverage Δ
unittests	77.68% <100.00%> (ø)

Flags with carried forward coverage won't be shown. Click here to find out more.

Impacted Files	Coverage Δ
rendseq/make_peaks.py	99.07% <100.00%> (ø)

📣 We’re building smart automated test selection to slash your CI/CD build times. Learn more

[julianstanley]

It's a shame that matplotlib doesn't make it easy to save plots as variables, like in R/ggplot. That would make it easier for that plot to just be an additional return

[miraep8]

This sounds very reasonable haha. As a sidenote, I think we might actually be able to return the plot by doing something like this actually (though this might not be what you had in mind):

import numpy as np
from matplotlib import pyplot as plt

def gen_plot():
    my_fig = plt.figure()
    plt.scatter([i for i in range(20)], [i for i in range(20)])
    return my_fig

f = gen_plot()

plt.show(f)

Just request me for a review when you are ready to merge! :)

[miraep8]

By the way, just revisiting this very reasonable PR. Any reason not to merge? I think I was originally holding off because it was a draft PR (so I wasn't sure if there was more to it) but I am happy with it as is! :)