Would you mind uploading the example data used in "Data preparation" in Tutorial.ipynb?

[gomingchen]

Hi there,

Excellent work! I am trying to use this method to study the learning process of echolocating bats on a two-choice platform. I ran the Tutorial.ipynb, but it's stuck at the lack of example data in "Data preparation". Would you mind uploading the data? Or where else can I find it?

Thank you!
Best,
Chen

[gavinmischler]

@gomingchen I don't think he'll be able to upload the data itself since it comes from patients. If you want to mimic it with random numbers so the rest of the code will run, it would look like this:

trial_lengths = [6047, 5053, 6500] # the first three trial lengths in samples
# Y is a list of length num_trials, each containing the responses by all electrodes (time * electrode)
channels = 220
Y = [torch.from_numpy(np.random.rand(L, channels)) for L in trial_lengths]
# X should be a list of the same length as Y containing the spectrogram (time * frequency) for each trial's stimulus
freq_bins = 64
X = [torch.from_numpy(np.random.rand(L, freq_bins)) for L in trial_lengths]

[gomingchen]

Hi Gavin, Thank you very much for the reply. I will try next week and let you know if I have problems. Best, Chen

…

On Wed, May 25, 2022 at 2:09 AM Gavin Mischler ***@***.***> wrote: @gomingchen <https://github.com/gomingchen> I don't think he'll be able to upload the data itself since it comes from patients. If you want to mimic it with random numbers so the rest of the code will run, it would look like this: trial_lengths = [6047, 5053, 6500] # the first three trial lengths in samples# Y is a list of length num_trials, each containing the responses by all electrodes (time * electrode)channels = 220Y = [np.random.rand(L, channels) for L in trial_lengths]# X should be a list of the same length as Y containing the spectrogram (time * frequency) for each trial's stimulusfreq_bins = 64X = [np.random.rand(L, freq_bins) for L in trial_lengths] — Reply to this email directly, view it on GitHub <#1 (comment)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/ANJN3QTYOAFMWRTAUDIBNSDVLW7ZNANCNFSM5OY4EURA> . You are receiving this because you were mentioned.Message ID: ***@***.***>