Predictions should work even if there is no experimental reference provided. This is currently not the case and using 0.00 everywhere fails when numpy tries to compute the correlation coefficient or the kernel density estimate (because the array is constant).
PearsonRConstantInputWarning: An input array is constant; the correlation coefficent is not defined.
UserWarning: Data must have variance to compute a kernel density estimate.
Predictions should work even if there is no experimental reference provided. This is currently not the case and using
0.00everywhere fails whennumpytries to compute the correlation coefficient or the kernel density estimate (because the array is constant).