With scikit-learn, one is able to compute the precision values as well the predicted probability output. To compute the precision values, the sklearn precision/recall function takes the true target values as well as the predicted target probability (can be target scores or non-thresholded measure of decisions) as an input, however the computed precision array does not have the same length as the the given predicted probability (precision length = n_thresholds + 1).
Is it somehow possible to compute the precision at a given probability output?