Comments (2)
For record keeping, a simple downgrading numpy version solves the issue.
conda install -c conda-forge numpy=1.23
from replay_trajectory_classification.
If you upgrade to the latest track_linearization, it should solve this problem.
from replay_trajectory_classification.
Related Issues (20)
- Tutorial for using clusterless spikes, and applying this library to neuropixels HOT 3
- Fix tutorial notebook to show clusterless features
- Update tutorials to have more realistic parameters HOT 1
- Add occupancy threshold for extracting track interior HOT 1
- Handle multiple spikes per bin for clusterless
- Fix diffusion boundaries
- Add in 'local' state
- Add ability to select electrodes or cells by state
- Provide convenience function to make spike indicator
- Handle missing data
- Visual repr for Environment class
- `model.predict` fails
- Numpy 1.24 incompatability HOT 2
- Compatability with open field 2D data HOT 6
- Translating API from 0.x to 1.x HOT 1
- reshape seems incorrect for the posterior xarray for 2D decoding? HOT 3
- How to decode with speed HOT 3
- unit in movement_var HOT 2
- spiking likelihood HOT 1
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from replay_trajectory_classification.