Adding roll function for patches

[Nik-P2]

Description

Adding in roll function for patches
based on numpy roll function
an example of this function

import dascore as dc
patch = dc.get_example_patch()
# roll time dimension 5 elements
rolled_patch = patch.roll(time=5, samples=True)

Checklist

I have (if applicable):

• referenced the GitHub issue this PR closes.
• documented the new feature with docstrings or appropriate doc page.
• included a test. See testing guidelines.
• your name has been added to the contributors page (docs/contributors.md).
• added the "ready_for_review" tag once the PR is ready to be reviewed.

[codecov]

Codecov Report

All modified and coverable lines are covered by tests ✅

Project coverage is 99.54%. Comparing base (c2f6ca7) to head (82e143c).

Additional details and impacted files

@@           Coverage Diff           @@
##           master     #382   +/-   ##
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  Coverage   99.54%   99.54%           
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  Files          97       97           
  Lines        7633     7647   +14     
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+ Hits         7598     7612   +14     
  Misses         35       35           

Flag	Coverage Δ
unittests	99.54% <100.00%> (+<0.01%)	⬆️

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[d-chambers]

Looks great!

[ahmadtourei]

Do we need to update the coord as well? Or maybe just adding an optional update_coord argument so when is set True, the function will roll the coord as well?

[d-chambers]

Do we need to update the coord as well? Or maybe just adding an optional update_coord argument so when is set True, the function will roll the coord as well

Ya, good point. Normally Patch.roll would be used to create a new patch that will broadcast with the old one. For example, in cross correlation. In this case you wouldn't want to coords to update, you are purposefully "rolling" the data around stationary coordinates. However, I could also see a case where you might want to roll the coords as well, so an optional argument to do so makes sense.

[d-chambers]

@Nik-P2, do you think you can implement this?

You need to add an optional keyword called update_coord or roll_coord which is False by default. Then if it is True do something like this (haven't tested but this should be enough to get you started):

...
if roll_coord:  # Handle rolling coordinate if needed
    coord = patch.get_coord(dim)
    rolled_coord_array = np.roll(coord.values, value, axis)
    new_coord = coord.update(values=rolled_coord_array)
    patch = patch.update_coords(**{dim: new_coord})

return patch.new(data=roll_arr)

Make sure to write another test case that runs this logic.

[Nik-P2]

Yup, I will work on that now.

[ahmadtourei]

Looks great. Thanks, @Nik-P2 !

[d-chambers]

Hey @Nik-P2,
If you look at the CI that failed (by clicking on the details button above) I see this error message when running the docstests. I think I told you wrong above, the dimensional coordinates are always 1D, so you might try replacing this line:

np.roll(coord.values, value, axis=axis)

with this one:

np.roll(coord.values, value, axis=0)

and see if it works.

[d-chambers]

All green, feel free to press the squash and merge button.