Prediction on held-out data about mofapy2 HOT 3 OPEN

Copying over from a slack thread to hopefully boost visibility. I understand the way to do this is through the entry_point.predict_factor method. When I tried this it throws the following error. It doesn't appear to matter whether I pass in a new set of covariates or just call the method with no arguments. According to the trace the error occurs on this line.

ValueError: all the input array dimensions for the concatenation axis must match exactly, but along dimension 0, the array at index 0 has size 1000 and the array at index 1 has size 2363

For context, 1000 is the number of inducing points and 2363 is the number of observations in the training data.

from mofapy2.

Hi Will,
thanks for reporting this bug.
This should be fixed now on the dev branch (pip install git+https://github.com/bioFAM/mofapy2@dev) and will be part of the next mofapy2 version.

from mofapy2.

Hi!

Has this been fixed on the latest version (entry_point.predict_factor on held out data) please?

from mofapy2.