Open ekaterinailin opened 4 years ago
Hi @ekaterinailin ! Weird. Which version of stella are you using? If you're using the version that was pip install stella
then I would believe there would be differences between that and the version now on GitHub.
I will be updating the PyPI version once the referee report is good to go and the associated AJ paper is accepted!
I think I tried both the pip version and the cloned repo. I now reproduced the same result with the most recent master branch version.
Okay great! Yeah I think there was a flub in me working in different branches, but now there's consistency between them. Please close the issue if you're satisfied with the fix!
I got a fresh installation from the master branch now, but unfortunately to no avail. I get a bunch of outputs tothe prompt, not sure if related to the actual issue, but perhaps worth posting anyways. Some I expected from the tutorial, others not:
/home/ekaterina/Documents/000_envs/stella/lib/python3.6/site-packages/lightkurve/lightcurvefile.py:47: LightkurveWarning: `LightCurveFile.header` is deprecated, please use `LightCurveFile.get_header()` instead.
LightkurveWarning)
WARNING: No stella.DataSet object passed in.
Can only use stella.ConvNN.predict().
100%|██████████| 1/1 [00:01<00:00, 1.13s/it]
Finding & Fitting Flares: 0%| | 0/1 [00:00<?, ?it/s]/home/ekaterina/Documents/000_envs/stella/lib/python3.6/site-packages/stella-0.1.0rc1-py3.6.egg/stella/mark_flares.py:92: VisibleDeprecationWarning: Creating an ndarray from ragged nested sequences (which is a list-or-tuple of lists-or-tuples-or ndarrays with different lengths or shapes) is deprecated. If you meant to do this, you must specify 'dtype=object' when creating the ndarray
return np.array(results)
/home/ekaterina/Documents/000_envs/stella/lib/python3.6/site-packages/numpy/lib/nanfunctions.py:1665: RuntimeWarning: Degrees of freedom <= 0 for slice.
keepdims=keepdims)
/home/ekaterina/Documents/000_envs/stella/lib/python3.6/site-packages/numpy/lib/nanfunctions.py:1114: RuntimeWarning: All-NaN slice encountered
overwrite_input=overwrite_input)
Finding & Fitting Flares: 100%|██████████| 1/1 [00:00<00:00, 5.22it/s]
Hi,
I am having the same problem, i find fewer flares than in the tutorial. I have tried both, the pip and the github installation and they all give the same result.
In other cases, although the star I am working with has many obvious flares, it only detect two small ones but not the obvious ones.
Has there been any change that could be causing this?
Thank you!
I get 16 flares as in the tutorial if I don't normalize the light curve and use the remove_nans() function along with the s004 pre-trained model. But the equivalent duration is in seconds now in the most recent version of stella, instead of minutes.
Edit: Not the same 16 flares. There are duplicates! 67 flares, again with many duplicates, if I normalize the light curve.
Hi @afeinstein20 !
I tried to use the
FitFlares
feature, but got stuck at the point where I wanted to show the table with the fitted flares.This is the code I ran (trying to reproduce the Fitting Flares tutorial):
The output is a single flares
which is not what I expected. Based on the
cnn.predictions
I expected a number of flares similar to what your tutorial shows (16?).I tried several models from the quickstart collection, but they either return 1 or zero flares in the
ff.flare_table
.Do you have an idea what I am doing wrong here?
Cheers :) Ekaterina