Note

Click here to download the full example code

This example demonstrates how to use the analyze function to process data prior to plotting. The data is a list of numpy arrays representing multi-voxel activity patterns (columns) over time (rows). First, analyze function normalizes the columns of each matrix (within each matrix). Then the data is reduced using PCA (10 dims) and finally it is aligned with hyperalignment. We can then plot the data with hyp.plot, which further reduces it so that it can be visualized.

```
# Code source: Andrew Heusser
# License: MIT
# load hypertools
import hypertools as hyp
# load the data
geo = hyp.load('weights')
data = geo.get_data()
# process the data
data = hyp.analyze(data, normalize='within', reduce='PCA', ndims=10,
align='hyper')
# plot it
hyp.plot(data)
```

**Total running time of the script:** ( 0 minutes 0.000 seconds)