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View Code? Open in Web Editor NEWA general framework for interpreting wide-band neural activity
License: MIT License
A general framework for interpreting wide-band neural activity
License: MIT License
Hi there,
I'm facing an error when the training starts (deepinsight.train.run_from_path)
error:
OSError: Unable to open file (unable to lock file, errno = 35, error message = 'Resource temporarily unavailable')
I did change the tensorflow version in the "requirements.txt" when installing it
tensorflow==1.13.0-rc1
I'm not sure if that could be the issue.
Any insights?
Thanks in advance
Hello, I tried running the ephys example notebook you provided but am getting an installation error. I'm getting a similar error when I try to install it locally via anaconda.
input: !pip install -e git+https://github.com/CYHSM/DeepInsight.git
Output:
Obtaining DeepInsight from git+https://github.com/CYHSM/DeepInsight.git#egg=DeepInsight
Cloning https://github.com/CYHSM/DeepInsight.git to ./src/deepinsight
Running command git clone --filter=blob:none --quiet https://github.com/CYHSM/DeepInsight.git /content/src/deepinsight
Resolved https://github.com/CYHSM/DeepInsight.git to commit e5a66be
Preparing metadata (setup.py) ... done
Collecting tensorflow-gpu (from DeepInsight)
Downloading tensorflow-gpu-2.12.0.tar.gz (2.6 kB)
error: subprocess-exited-with-error
× python setup.py egg_info did not run successfully.
│ exit code: 1
╰─> See above for output.
note: This error originates from a subprocess, and is likely not a problem with pip.
Preparing metadata (setup.py) ... error
error: metadata-generation-failed
× Encountered error while generating package metadata.
╰─> See above for output.
When I try to run the available example codes in Google Colab i get the following errors:
UnimplementedError: 2 root error(s) found.
(0) UNIMPLEMENTED: DNN library is not found.
[[{{node time_distributed/conv_tsr0/Conv2D}}]]
[[loss/AddN/_519]]
(1) UNIMPLEMENTED: DNN library is not found.
[[{{node time_distributed/conv_tsr0/Conv2D}}]]
0 successful operations.
0 derived errors ignored.
Meanwhile it is running fine on my personal laptop. Do you know any solution for this problem?
Hi,
The file in the jupyter notebook:
!wget https://ndownloader.figshare.com/files/20150468 -O ./example_data/processed_R2478.h5
is not available
Thank you for this interesting paper and work!
I had a question regarding the decoder here coded:
Is it correct that your model takes as input wavelet powers for a temporal window "T=64 (corresponding to 2.13s)" (which are in fact down-sampled M=1000 times over the temporal dimension from the original wavelet powers matrix), and output one value for each behavioral variable?
Should it not decode 64*(nb of behavioral variable) values, one for each time-step, since over 2.13s the variable can really change a lot (for example, for the head-direction speed of a mouse, an order of magnitude is 40deg/s).
Thank you for your help!
Hi Dr. Frey,
Thank you for your article. As your results are amazing I wanted to give Deepinsight a try on my lab data. However, I encouter an issue concerning the preprocessing of the input data.
After running the deepinsight.preprocess.preprocess_input( ) function with our electrophysiology data (which have a 30.000Hz sampling rate), the result of the wavelet transform is unexpected. The frequency bands used to compute the wavelet transform return as follows:
deepinsight.preprocess.preprocess_input(fp_deepinsight, input_data, sampling_rate=sampling_rate, channels=channels)
hdf5_file = h5py.File(fp_deepinsight, mode='r')
frequencies = np.round(hdf5_file['inputs/fourier_frequencies'], 3)
print(list(frequencies))
It returns:
[inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, 58.6, 41.44, 29.3, 20.72, 14.65, 10.36, 7.324, 5.18, 3.662, 2.59]
I assume that the wavelet transform functions automatically determines the best frequency bands to perform the transform, so I do not understand the origin of these "inf" values.
Do you have any idea about what is wrong, or on how to constrain the frequency bands ?
Thank you in advance,
Allan Muller
Hi Markus,
I really liked this paper, and want to give it a try with other datasets.
I have two questions:
Hi Markus,
Would it be possible to get the sample .nwb file or some explanation about the data structure expected by DeepInsight (for the channels, timestamps, position, etc)? I have data from a different recording system (Neuralynx) and would be very interested in trying to use it.
Thanks and happy holidays,
Elhanan
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