TypeError: Wrong type for labels. Please either set labels to the number of variables or provide the axis labels as a single string of characters (like "ts" for time and stimulus)

[victoris93]

Hi,

I'm trying to run dPCA on this dataset. I suppose that my problem stems either from the shape of the input array or from my erroneous understanding of labels. The shape of the input array is (127, 2, 2, 6, 6). So I've got 127 average cell firing rates for trials with 4 variables having 2, 2, 6 and 6 levels. Is the shape correct? The labels defined below don't seem to cut it. Thanks a bunch!

from dPCA import dPCA

labels = ['cdfo'] # choice, decision, spatial frequency, orientation
dpca = dPCA.dPCA(labels, 5, regularizer = "auto")
demixed_mouse1 = dpca.fit_transform(dPCADataMouse1T5)

UPD: the same error is thrown when no labels are specified:

dpca = dPCA.dPCA()
demixed_mouse1 = dpca.fit_transform(dPCADataMouse1T5)

[QiqiXian]

Hi,

The shape of the input array should be: (trial_num_for_each_condition, neuron_num, other_dims), where neuron_num is the dimension that will be reduced.
The length of labels should match the number of other_dims.
If you use regularizer = "auto", you should call the function as: dpca.fit_transform(data.mean(0), data). Here data is a single-trial input matrix and data.mean(0) is a trial-average matrix.

Hope this helps!