Closed zhouyi0812 closed 6 months ago
From the docstring:
Run component evaluation. This basically changes the indices for good and bad components.
So the output of ixs_good = df.iloc[index].cnmf.get_good_components() already represents the good components right? If so, what is the evaluation parameters behind?
The caiman docs has some stuff on the eval components:
https://caiman.readthedocs.io/en/latest/Getting_Started.html#component-evaluation
Thank you! But if I want to change it maybe to a higher value, can I follow the steps above? In that case, how to present accepted components and reject components?
Why not just use the visualization in mesviz you can interactively set all the eval params
Because there are too many movies, I think it should be helpful after I check certain number of movies and find a common use parameters for the rest and just looping
Also, I found there is a line connect two components for some cases.
That's one component
If I don't think that's right ROI, if I could delete directly from the evaluation panel? Thank you!
You probably have to increase min_corr to split it.
On Wed, Feb 7, 2024, 13:35 Yi Zhou @.***> wrote:
If I don't think that's the one component, if I could delete directly from the evaluation panel? Thank you!
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Hello! I adjusted the run_eval according to mescore, but the evaluation output is 'nonetype' How should I adjust it? Thank you very much!
min_SNR = 3 # SNR threshold rval_thr = 0.85 # spatial correlation threshold
quality_params = {'min_SNR': min_SNR, 'rval_thr': rval_thr, 'use_cnn': False}
index = 1 eval = df.iloc[index].cnmf.run_eval(quality_params)
print('*****')
print(f"Number accepted: {(len(df.iloc[index].cnmf.get_good_components))}")
print(f"Number rejected: {len(df.iloc[index].cnmf.get_bad_components)}")