which loss function (if any) optimizes the calibration graph
Log-loss optimizes your predictions in terms of their probability so in essence, yes it should be optimizing your calibration curve.  i.e. if you predict probability of 0% but it's actually labelled as the true class, this is penalised more than probability of 5% being true when it is the true class and so forth.