Speed up fourier py

[matteobachetti]

In generate_indices_of_segment_boundaries_unbinned:

• Avoid unnecessary check for array sortedness. This saves ~1/3 of computing time in large, memory mapped arrays
• Use numpy.searchsorted only once

[codecov]

Codecov Report

All modified and coverable lines are covered by tests ✅

Project coverage is 96.43%. Comparing base (7377187) to head (9341db0).

Additional details and impacted files

@@           Coverage Diff           @@
##             main     #808   +/-   ##
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  Coverage   96.42%   96.43%           
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  Files          45       45           
  Lines        9016     9027   +11     
=======================================
+ Hits         8694     8705   +11     
  Misses        322      322           

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[eleonoraveronica]

Nice work @matteobachetti, and thank you for pushing me to make my first review. I hope it would be somehow useful :) I selected "Approve" the changes, since I only suggest a possible one that is not essential.

[eleonoraveronica]

I totally agree with the idea of adding a check on the data sorting. It speeds up the code, and it leaves the choice to the user. In my opinion, when the user can choose, is always happier :)

[eleonoraveronica]

This line seems a bit complicated to me. If possible, I would simplify it: is list necessary? To my understanding, set applies to the ndarray in output from np.concatenate, then np.array should transform the ndarray directly in a numpy array. Would np.sort(np.array(set(np.concatenate([start, stop])))) work in the same way?

[matteobachetti]

It's a bit confusing, I agree 😅 . However, set does not return an iterable that numpy.array recognizes as such. When you create an array from a set, it just creates an object array with a single element (the whole set).

In [1]: import numpy as np

In [2]: start = np.arange(5)

In [3]: stop = np.arange(1, 6)

In [4]: np.array(set(np.concatenate([start, stop])))
Out[4]: array({0, 1, 2, 3, 4, 5}, dtype=object)

In [5]: np.sort(np.array(set(np.concatenate([start, stop]))))
---------------------------------------------------------------------------
AxisError                                 Traceback (most recent call last)
Cell In[5], line 1
----> 1 np.sort(np.array(set(np.concatenate([start, stop]))))

File ~/opt/anaconda3/envs/py311/lib/python3.11/site-packages/numpy/core/fromnumeric.py:1017, in sort(a, axis, kind, order)
   1015 else:
   1016     a = asanyarray(a).copy(order="K")
-> 1017 a.sort(axis=axis, kind=kind, order=order)
   1018 return a

AxisError: axis -1 is out of bounds for array of dimension 0

The line above just shows that the array has dimension 0, it's just a single object.

list transforms the set into an iterable that numpy.array understands, and the line above has the expected behavior.

In [6]: np.array(list(set(np.concatenate([start, stop]))))
Out[6]: array([0, 1, 2, 3, 4, 5])

In [7]: np.sort(np.array(list(set(np.concatenate([start, stop])))))
Out[7]: array([0, 1, 2, 3, 4, 5])

[matteobachetti]

@Vele89 I added comments to explain each passage