def __init__(self,
flux,
inputs,
mask=None,
p0=None,
kernel=None,
splits=[],
tr_nrandom=200,
tr_bspan=50,
tr_nblocks=6):
self.data = DtData(flux, inputs, mask)
self.kernel = kernel or BasicKernel()
self.gp = SplitGP(self.kernel,
splits) if splits is not None else GeorgeGP(
self.kernel)
self.tr_data = self.data.create_training_set(tr_nrandom, tr_bspan,
tr_nblocks)
self.gp.set_inputs(self.tr_data.masked_inputs)
