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[missing data] general implementation for subsetting data

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This commit is contained in:
Max Zwiessele 2014-10-08 12:03:51 +01:00
parent d93fac8c13
commit fa7807ee6f
7 changed files with 329 additions and 108 deletions
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14
GPy/core/sparse_gp_mpi.py
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@ -34,15 +34,15 @@ class SparseGP_MPI(SparseGP):
"""
def __init__(self, X, Y, Z, kernel, likelihood, variational_prior=None, inference_method=None, name='sparse gp mpi', Y_metadata=None, mpi_comm=None, normalizer=False):
def __init__(self, X, Y, Z, kernel, likelihood, variational_prior=None, inference_method=None, name='sparse gp mpi', Y_metadata=None, mpi_comm=None, normalizer=False, missing_data=False):
self._IN_OPTIMIZATION_ = False
if mpi_comm != None:
if inference_method is None:
inference_method = VarDTC_minibatch(mpi_comm=mpi_comm)
else:
assert isinstance(inference_method, VarDTC_minibatch), 'inference_method has to support MPI!'
super(SparseGP_MPI, self).__init__(X, Y, Z, kernel, likelihood, inference_method=inference_method, name=name, Y_metadata=Y_metadata, normalizer=normalizer)
super(SparseGP_MPI, self).__init__(X, Y, Z, kernel, likelihood, inference_method=inference_method, name=name, Y_metadata=Y_metadata, normalizer=normalizer, missing_data=missing_data)
self.update_model(False)
self.link_parameter(self.X, index=0)
if variational_prior is not None:
@ -75,18 +75,18 @@ class SparseGP_MPI(SparseGP):
return dc
#=====================================================
# The MPI parallelization
# The MPI parallelization
# - can move to model at some point
#=====================================================
@SparseGP.optimizer_array.setter
def optimizer_array(self, p):
if self.mpi_comm != None:
if self._IN_OPTIMIZATION_ and self.mpi_comm.rank==0:
self.mpi_comm.Bcast(np.int32(1),root=0)
self.mpi_comm.Bcast(p, root=0)
self.mpi_comm.Bcast(p, root=0)
SparseGP.optimizer_array.fset(self,p)
def optimize(self, optimizer=None, start=None, **kwargs):
self._IN_OPTIMIZATION_ = True
if self.mpi_comm==None: