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Merge branch 'params' of github.com:SheffieldML/GPy into params

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This commit is contained in:
James Hensman 2014-01-24 15:48:49 +00:00
commit 7bb6f4ba4e
17 changed files with 73 additions and 71 deletions
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8
GPy/core/gp.py
View file

@ -309,11 +309,11 @@ class GP(Model):
def getstate(self):
def _getstate(self):
"""
Get the current state of the class, here we return everything that is needed to recompute the model.
"""
return Model.getstate(self) + [self.X,
return Model._getstate(self) + [self.X,
self.num_data,
self.input_dim,
self.kern,
@ -323,7 +323,7 @@ class GP(Model):
self._Xscale,
]
def setstate(self, state):
def _setstate(self, state):
self._Xscale = state.pop()
self._Xoffset = state.pop()
self.output_dim = state.pop()
@ -332,6 +332,6 @@ class GP(Model):
self.input_dim = state.pop()
self.num_data = state.pop()
self.X = state.pop()
Model.setstate(self, state)
Model._setstate(self, state)

12
GPy/core/model.py
View file

@ -40,7 +40,7 @@ class Model(Parameterized):
return g
raise NotImplementedError, "this needs to be implemented to use the model class"
def getstate(self):
def _getstate(self):
"""
Get the current state of the class.
Inherited from Parameterized, so add those parameters to the state
@ -48,24 +48,24 @@ class Model(Parameterized):
:return: list of states from the model.
"""
return Parameterized.getstate(self) + \
return Parameterized._getstate(self) + \
[self.priors, self.optimization_runs,
self.sampling_runs, self.preferred_optimizer]
def setstate(self, state):
def _setstate(self, state):
"""
set state from previous call to getstate
set state from previous call to _getstate
call Parameterized with the rest of the state
:param state: the state of the model.
:type state: list as returned from getstate.
:type state: list as returned from _getstate.
"""
self.preferred_optimizer = state.pop()
self.sampling_runs = state.pop()
self.optimization_runs = state.pop()
self.priors = state.pop()
Parameterized.setstate(self, state)
Parameterized._setstate(self, state)
def set_prior(self, regexp, what):
"""

2
GPy/core/parameterization/param.py
View file

@ -403,7 +403,7 @@ class Param(ObservableArray, Constrainable):
x=self.name_hirarchical)
return name + super(Param, self).__repr__(*args,**kwargs)
def _ties_for(self, rav_index):
size = sum(p.size for p in self._tied_to_)
#size = sum(p.size for p in self._tied_to_)
ties = numpy.empty(shape=(len(self._tied_to_), numpy.size(rav_index)), dtype=Param)
for i, tied_to in enumerate(self._tied_to_):
for t, ind in tied_to._tied_to_me_.iteritems():

11
GPy/core/parameterization/parameter_core.py
View file

@ -21,7 +21,7 @@ class Observable(object):
[callble(self) for callble in self._observers_.itervalues()]
class Pickleable(object):
def getstate(self):
def _getstate(self):
"""
Returns the state of this class in a memento pattern.
The state must be a list-like structure of all the fields
@ -30,13 +30,13 @@ class Pickleable(object):
See python doc "pickling" (`__getstate__` and `__setstate__`) for details.
"""
raise NotImplementedError, "To be able to use pickling you need to implement this method"
def setstate(self, state):
def _setstate(self, state):
"""
Set the state (memento pattern) of this class to the given state.
Usually this is just the counterpart to getstate, such that
Usually this is just the counterpart to _getstate, such that
an object is a copy of another when calling
copy = <classname>.__new__(*args,**kw).setstate(<to_be_copied>.getstate())
copy = <classname>.__new__(*args,**kw)._setstate(<to_be_copied>._getstate())
See python doc "pickling" (`__getstate__` and `__setstate__`) for details.
"""
@ -54,7 +54,7 @@ class Parentable(object):
self._highest_parent_ = highest_parent
def has_parent(self):
return self._direct_parent_ is not None
return self._direct_parent_ is not None and self._highest_parent_ is not None
class Nameable(Parentable):
_name = None
@ -96,6 +96,7 @@ class Constrainable(Nameable):
self._add_constrain(p, transform, warning)
if update:
self.parameters_changed()
def constrain_positive(self, warning=True):
"""
:param warning: print a warning if re-constraining parameters.

15
GPy/core/parameterization/parameterized.py
View file

@ -218,7 +218,7 @@ class Parameterized(Constrainable, Pickleable, Observable):
p._direct_parent_ = self
p._parent_index_ = i
i += 1
for pi in p.flattened_parameters:
for pi in p._parameters_:
pi._highest_parent_ = self
not_unique = []
sizes.append(p.size+sizes[-1])
@ -233,6 +233,7 @@ class Parameterized(Constrainable, Pickleable, Observable):
elif not (pname in not_unique):
self.__dict__[pname] = p
self._added_names_.add(pname)
#===========================================================================
# Pickling operations
#===========================================================================
@ -253,24 +254,24 @@ class Parameterized(Constrainable, Pickleable, Observable):
return copy.deepcopy(self)
def __getstate__(self):
if self._has_get_set_state():
return self.getstate()
return self._getstate()
return self.__dict__
def __setstate__(self, state):
if self._has_get_set_state():
self.setstate(state) # set state
self._setstate(state) # set state
#self._set_params(self._get_params()) # restore all values
return
self.__dict__ = state
def _has_get_set_state(self):
return 'getstate' in vars(self.__class__) and 'setstate' in vars(self.__class__)
def getstate(self):
return '_getstate' in vars(self.__class__) and '_setstate' in vars(self.__class__)
def _getstate(self):
"""
Get the current state of the class,
here just all the indices, rest can get recomputed
For inheriting from Parameterized:
Allways append the state of the inherited object
and call down to the inherited object in setstate!!
and call down to the inherited object in _setstate!!
"""
return [
self._fixes_,
@ -280,7 +281,7 @@ class Parameterized(Constrainable, Pickleable, Observable):
self._added_names_,
]
def setstate(self, state):
def _setstate(self, state):
self._added_names_ = state.pop()
self._name = state.pop()
self._parameters_ = state.pop()

8
GPy/core/sparse_gp.py
View file

@ -183,20 +183,20 @@ class SparseGP(GP):
else:
raise NotImplementedError, "Cannot define a frame with more than two input dimensions"
def getstate(self):
def _getstate(self):
"""
Get the current state of the class,
here just all the indices, rest can get recomputed
"""
return GP.getstate(self) + [self.Z,
return GP._getstate(self) + [self.Z,
self.num_inducing,
self.has_uncertain_inputs,
self.X_variance]
def setstate(self, state):
def _setstate(self, state):
self.X_variance = state.pop()
self.has_uncertain_inputs = state.pop()
self.num_inducing = state.pop()
self.Z = state.pop()
GP.setstate(self, state)
GP._setstate(self, state)

8
GPy/core/svigp.py
View file

@ -90,9 +90,9 @@ class SVIGP(GP):
self._param_steplength_trace = []
self._vb_steplength_trace = []
def getstate(self):
def _getstate(self):
steplength_params = [self.hbar_t, self.tau_t, self.gbar_t, self.gbar_t1, self.gbar_t2, self.hbar_tp, self.tau_tp, self.gbar_tp, self.adapt_param_steplength, self.adapt_vb_steplength, self.vb_steplength, self.param_steplength]
return GP.getstate(self) + \
return GP._getstate(self) + \
[self.get_vb_param(),
self.Z,
self.num_inducing,
@ -116,7 +116,7 @@ class SVIGP(GP):
self.iterations
]
def setstate(self, state):
def _setstate(self, state):
self.iterations = state.pop()
self._permutation = state.pop()
self.Y = state.pop()
@ -139,7 +139,7 @@ class SVIGP(GP):
self.num_inducing = state.pop()
self.Z = state.pop()
vb_param = state.pop()
GP.setstate(self, state)
GP._setstate(self, state)
self.set_vb_param(vb_param)
def _compute_kernel_matrices(self):

8
GPy/kern/kern.py
View file

@ -50,25 +50,25 @@ class kern(Parameterized):
def connect_input(self, Xparam):
[p.connect_input(Xparam) for p in self._parameters_]
def getstate(self):
def _getstate(self):
"""
Get the current state of the class,
here just all the indices, rest can get recomputed
"""
return Parameterized.getstate(self) + [#self._parameters_,
return Parameterized._getstate(self) + [#self._parameters_,
#self.num_params,
self.input_dim,
self.input_slices,
self._param_slices_
]
def setstate(self, state):
def _setstate(self, state):
self._param_slices_ = state.pop()
self.input_slices = state.pop()
self.input_dim = state.pop()
#self.num_params = state.pop()
#self._parameters_ = state.pop()
Parameterized.setstate(self, state)
Parameterized._setstate(self, state)
def plot_ARD(self, fignum=None, ax=None, title='', legend=False):

8
GPy/models/bayesian_gplvm.py
View file

@ -51,17 +51,17 @@ class BayesianGPLVM(SparseGP, GPLVM):
self.add_parameter(self.q, gradient=self._dbound_dmuS, index=0)
self.ensure_default_constraints()
def getstate(self):
def _getstate(self):
"""
Get the current state of the class,
here just all the indices, rest can get recomputed
"""
return SparseGP.getstate(self) + [self.init]
return SparseGP._getstate(self) + [self.init]
def setstate(self, state):
def _setstate(self, state):
self._const_jitter = None
self.init = state.pop()
SparseGP.setstate(self, state)
SparseGP._setstate(self, state)
# def _get_param_names(self):
# X_names = sum([['X_%i_%i' % (n, q) for q in range(self.input_dim)] for n in range(self.num_data)], [])

8
GPy/models/gp_regression.py
View file

@ -29,8 +29,8 @@ class GPRegression(GP):
super(GPRegression, self).__init__(X, Y, kernel, likelihood, name='GP regression')
def getstate(self):
return GP.getstate(self)
def _getstate(self):
return GP._getstate(self)
def setstate(self, state):
return GP.setstate(self, state)
def _setstate(self, state):
return GP._setstate(self, state)

8
GPy/models/gplvm.py
View file

@ -41,11 +41,11 @@ class GPLVM(GP):
Xr[:PC.shape[0], :PC.shape[1]] = PC
return Xr
def getstate(self):
return GP.getstate(self)
def _getstate(self):
return GP._getstate(self)
def setstate(self, state):
GP.setstate(self, state)
def _setstate(self, state):
GP._setstate(self, state)
# def _get_param_names(self):
# return sum([['X_%i_%i' % (n, q) for q in range(self.input_dim)] for n in range(self.num_data)], []) + GP._get_param_names(self)

8
GPy/models/mrd.py
View file

@ -79,8 +79,8 @@ class MRD(Model):
Model.__init__(self)
self.ensure_default_constraints()
def getstate(self):
return Model.getstate(self) + [self.names,
def _getstate(self):
return Model._getstate(self) + [self.names,
self.bgplvms,
self.gref,
self.nparams,
@ -90,7 +90,7 @@ class MRD(Model):
self.NQ,
self.MQ]
def setstate(self, state):
def _setstate(self, state):
self.MQ = state.pop()
self.NQ = state.pop()
self.num_data = state.pop()
@ -100,7 +100,7 @@ class MRD(Model):
self.gref = state.pop()
self.bgplvms = state.pop()
self.names = state.pop()
Model.setstate(self, state)
Model._setstate(self, state)
@property
def X(self):

8
GPy/models/sparse_gp_classification.py
View file

@ -46,11 +46,11 @@ class SparseGPClassification(SparseGP):
SparseGP.__init__(self, X, likelihood, kernel, Z=Z, normalize_X=normalize_X)
self.ensure_default_constraints()
def getstate(self):
return SparseGP.getstate(self)
def _getstate(self):
return SparseGP._getstate(self)
def setstate(self, state):
return SparseGP.setstate(self, state)
def _setstate(self, state):
return SparseGP._setstate(self, state)
pass

8
GPy/models/sparse_gp_regression.py
View file

@ -49,11 +49,11 @@ class SparseGPRegression(SparseGP):
self.ensure_default_constraints()
pass
def getstate(self):
return SparseGP.getstate(self)
def _getstate(self):
return SparseGP._getstate(self)
def setstate(self, state):
return SparseGP.setstate(self, state)
def _setstate(self, state):
return SparseGP._setstate(self, state)
pass

8
GPy/models/sparse_gplvm.py
View file

@ -28,12 +28,12 @@ class SparseGPLVM(SparseGPRegression, GPLVM):
SparseGPRegression.__init__(self, X, Y, kernel=kernel, num_inducing=num_inducing)
self.ensure_default_constraints()
def getstate(self):
return SparseGPRegression.getstate(self)
def _getstate(self):
return SparseGPRegression._getstate(self)
def setstate(self, state):
return SparseGPRegression.setstate(self, state)
def _setstate(self, state):
return SparseGPRegression._setstate(self, state)
def _get_param_names(self):

8
GPy/models/svigp_regression.py
View file

@ -43,10 +43,10 @@ class SVIGPRegression(SVIGP):
SVIGP.__init__(self, X, likelihood, kernel, Z, q_u=q_u, batchsize=batchsize)
self.load_batch()
def getstate(self):
return GPBase.getstate(self)
def _getstate(self):
return GPBase._getstate(self)
def setstate(self, state):
return GPBase.setstate(self, state)
def _setstate(self, state):
return GPBase._setstate(self, state)

8
GPy/models/warped_gp.py
View file

@ -30,12 +30,12 @@ class WarpedGP(GP):
GP.__init__(self, X, likelihood, kernel, normalize_X=normalize_X)
self._set_params(self._get_params())
def getstate(self):
return GP.getstate(self)
def _getstate(self):
return GP._getstate(self)
def setstate(self, state):
return GP.setstate(self, state)
def _setstate(self, state):
return GP._setstate(self, state)
def _scale_data(self, Y):