issue with tutorial line returning The truth value of an array with more than one element is ambiguous. Use a.any() or a.all() about lightkurve HOT 11 CLOSED

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I have the same issue. I get the same error when trying to apply any custom mask (only specifying 'pipeline' works for me).
The error appears when just plotting too (targetpixelfile.plot(aperture_mask=...)).
Using version 2.4. Python 3.10. On a Ubuntu machine.

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@cheesyminecart

Thank you very much for posting this issue.
Could you please provide me with a little more information regarding the environment you are using lightkurve in.

Environment
platform (e.g. Linux, OSX, Windows):
lightkurve version (e.g. 1.0b6):
installation method (e.g. pip, conda, source):

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@davidedionese

Thank you very much for posting your issue. Could you please send me an example of the code and the problem that you are finding. Thank you.

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Yes indeed.
My code (I am basically following the tutorial for the SNR of the periodogram):

import lightkurve as lk
import matplotlib.pyplot as plt
import numpy as np
import astropy.units as u

TARGET = "EPIC 211416749"
tpf = lk.search_targetpixelfile(TARGET, author="K2", campaign=5, cadence='short').download()

target_mask = tpf.create_threshold_mask(threshold = 10, reference_pixel = 'center')
tpf.plot(scale='log', aperture_mask=target_mask)

After the last line I get the following error:

ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()

The line:

tpf.plot(scale='log', aperture_mask=tpf.pipeline_mask)

as suggested in the tutorial throws the same error.

Then I also try:

lc = tpf.to_lightcurve()

and I get the exact same error.
I am working in a conda environment, installing all packages through conda.
lightkurve version 2.4.0
Linux machine.
Running in Jupyter notebook.

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@davidedionese

Thank you very much for this code and your environment set up.
Unfortunately i am not able to reproduce your error. To aid me in determining what is happening would you mind providing me with a bit more information, specifically:

• The conda environment
• Your version of python
• Could you please print out what your target_mask looks like i.e., the array.

Thank you

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• Python version: 3.11.4
• Numpy version: 1.25.2 (maybe it matters)
• matplotlib version: 3.7.1
  Only these packages (and dependencies) are installed in the environment.
  Conda version: 23.7.2.
  The custom mask looks like this:

array([[False, False, False, False, False, False, False, False, False, False, False],
       [False, False, False, False, False, False, False, False, False, False, False],
       [False, False, False, False,  True,  True, False, False, False, False, False],
       [False, False, False, False,  True,  True,  True, False, False, False, False],
       [False, False, False, False,  True,  True,  True,  True, False, False, False],
       [False, False, False, False,  True,  True,  True,  True, False, False, False],
       [False, False, False, False,  True,  True,  True,  True,  True, False, False],
       [False, False, False, False, False,  True,  True,  True, False, False, False],
       [False, False, False, False, False, False,  True, False, False, False, False],
       [False, False, False, False, False, False, False, False, False, False, False],
       [False, False, False, False, False, False, False, False, False, False, False]])

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Dear Rebekah,
Thanks for the reply! Sorry I wasn't able to give my own contribution to the discussion, though I am willing to provide the necessary details for a quick bugfix.

platform: OSX
installation: pip3
lk version: 2.4.0

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Dear @cheesyminecart & @davidedionese

After much investigation by myself and my colleagues we have determined that this issue is related to the most recent version of numpy - version 1.25.0.

Within this version there was deprecation expiration and now an array of all True or all False is returned when values are fundamentally not comparable (e.g. have different dtypes). An example is:

np.array(["a"]) ==np.array([1])

You can read more about this here.

We are working on a fix for this issue, but in the meantime it might be worthwhile installing an older version of numpy.

Thank you once again for posting this issue and please let us know there are any more issues.

from lightkurve.

Dear @rebekah9969,

I tried with an older version of Numpy and indeed it works fine.

Thank you very much to you and your colleagues for your patience and your time!

from lightkurve.

@davidedionese, @cheesyminecart, please try updating to the newest version of lightkurve which is 2.4.1, and report back here if this does not solve your issue!

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