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finish tie framework restructure and add more tests
This commit is contained in:
Zhenwen Dai
parent
077232c26f
commit
c279da4c75
3 changed files with 45 additions and 113 deletions
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@ -97,7 +97,6 @@ class Tie(Parameterized):
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else:
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val = tieparam[tieparam.tie==l]
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p[p.tie==l] = val
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for p in plist:
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self._traverse_param(_sync_val_p, (p,self.tied_param,read), [])
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@ -112,6 +111,7 @@ class Tie(Parameterized):
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cons = [c[0] if len(c)>0 else None for c in self.tied_param.constraints.properties_for(range(self.tied_param.size))]
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def _sync_constraints_p(p, tieparam, read, cons):
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if p.tie is not None:
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p = p._original_
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labels = np.unique(p.tie)
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labels = labels[labels>0]
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for l in labels:
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@ -127,6 +127,7 @@ class Tie(Parameterized):
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p[p.tie==l].constrain(c)
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if c != cons[idx]:
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tieparam[idx:idx+1].constrain(c)
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cons[idx] = c
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read[tieparam.tie==l] = 1
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else:
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if cons[idx] is None:
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@ -134,7 +135,6 @@ class Tie(Parameterized):
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p[p.tie==l].unconstrain()
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else:
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if len(conslist)!=1 or conslist.keys()[0]!=cons[idx] or len(conslist[cons[idx]])!= (p.tie==l).sum():
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print cons[idx]
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p[p.tie==l].constrain(cons[idx])
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for p in plist:
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self._traverse_param(_sync_constraints_p, (p,self.tied_param,read, cons), [])
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@ -152,10 +152,10 @@ class Tie(Parameterized):
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labels = p.ties._get_labels([p])
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labels = labels[labels>0]
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if len(labels)>0:
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p._expand_tie_param(len(labels))
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vals = p.ties._get_sync_val(p, labels)
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p.tied_param[:] = vals
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p.tied_param.tie[:] = labels
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p.ties._expand_tie_param(len(labels))
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p.ties.tied_param.tie[:] = labels
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p.ties._sync_val([p],toTiedParam=True)
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p.ties._sync_constraints([p], toTiedParam=True)
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p._update_label_buf()
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p.update_model(True)
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@ -192,59 +192,6 @@ class Tie(Parameterized):
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self._update_label_buf()
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p._update_label_buf()
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self.update_model(True)
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def _get_sync_val(self, p, labels):
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vals = np.empty((labels.size,))
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read = np.zeros((labels.size,),dtype=np.uint8)
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def _get_sync_v(p, labels, vals, read):
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for i in xrange(labels.size):
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if read[i]==1:
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p[p.tie==labels[i]] = vals[i]
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elif np.any(p.tie==labels[i]):
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vals[i] = p[p.tie==labels[i]][0]
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p[p.tie==labels[i]][0] = vals[i]
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read[i] = 1
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self._traverse_param(_get_sync_v, (p,labels,vals,read), [])
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return vals
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def _sync_val_group(self, plist):
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val = np.hstack([p.param_array.flat for p in plist]).mean()
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def _set_val(p):
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p[:] = val
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for p in plist:
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self._traverse_param(_set_val, (p,), [])
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return val
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def _sync_constraint_group(self, plist, hastie=False, tie_con=None, warning=True):
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if not hastie:
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cons = []
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for p in plist:
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cons.extend(p.constraints.properties())
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cons = list(set(cons))
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if len(cons)==0:
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tie_con = None
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else:
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tie_con = cons[0]
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if tie_con is not None:
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for p in plist:
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if len(p.constraints.properties())!=1 or p.constraints[tie_con].size != p.size:
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print 'WARNING: '+p.name+' have different constraints! They will be constrained '+str(tie_con)+'!'
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p.constrain(tie_con)
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return tie_con
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elif hastie:
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for p in plist:
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if p.constraints.size>0:
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print 'WARNING: '+p.name+' have different constraints! They will be unconstrained!'
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p.unconstrain()
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return None
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def _sync_constraint_vector(self, p1, p2, expandlist, idxlist, warning=True):
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if p1.constraints.items() != p2.constraints.properties():
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print 'WARNING: '+p1.name+' and '+p2.name+' have different constraints! Only the constraints of '+p1.name+' will be considered!'
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for c,ind in p1.constraints.iteritems():
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idx = idxlist[np.in1d(expandlist,ind)]
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self.tied_param[idx].constrain(c)
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def _traverse_param(self, func, p, res):
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"""
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@ -295,20 +242,7 @@ class Tie(Parameterized):
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else:
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for p in plist:
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self._traverse_param(_set_list, (p,[0]), [])
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def _get_vals(self, p):
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vals = []
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self._traverse_param(lambda x: x.flat, (p,), vals)
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return np.hstack(vals)
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def _sync_val_pair(self,p1,p2):
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p1val = self._get_vals(p1)
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def _set_val(p, offset, p2):
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p.flat[:] = p2[offset[0]:offset[0]+p.size]
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offset[0] = offset[0]+ p.size
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self._traverse_param(_set_val, (p2, [0], p1val), [])
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return p1val
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def _replace_labels(self, p, label_pairs):
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def _replace_l(p):
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for l1,l2 in label_pairs:
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@ -416,46 +350,21 @@ class Tie(Parameterized):
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self._sync_constraints(plist, toTiedParam)
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self._update_label_buf()
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self.update_model(True)
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# def tie_together(self,plist):
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# """tie a list of parameters"""
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# self.update_model(False)
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# labels = self._get_labels(plist)
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# val = self._sync_val_group(plist)
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# if labels[0]==0 and labels.size==1:
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# # None of parameters in plist has been tied before.
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# tie_labels,_ = self._expand_tie_param(1)
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# self._set_labels(plist, tie_labels)
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# tie_con = self._sync_constraint_group(plist)
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# if tie_con is not None:
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# self.tied_param[self.tied_param.tie==tie_labels[0]].constrain(tie_con)
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# else:
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# # Some of parameters has been tied already.
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# # Merge the tie param
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# tie_labels = labels[labels>0]
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# if tie_labels.size>1:
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# self._merge_tie_labels(tie_labels)
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# self._set_labels(plist, [tie_labels[0]])
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# tie_p = self.tied_param[self.tied_param.tie==tie_labels[0]]
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# tie_con = tie_p.constraints.properties()[0] if tie_p.constraints.size>0 else None
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# self._sync_constraint_group(plist, True, tie_con)
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# self._update_label_buf()
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# self.tied_param[self.tied_param.tie==tie_labels[0]] = val
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# self.update_model(True)
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def tie_vector(self, p1, p2):
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"""tie a pair of vectors"""
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self.update_model(False)
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expandlist,removelist,labellist = self._get_labels_vector(p1, p2)
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p1vals = self._sync_val_pair(p1,p2)
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p_split = self._keepParamList([p1,p2])
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if len(expandlist)>0:
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tie_labels,idxlist = self._expand_tie_param(len(expandlist))
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labellist[expandlist] = tie_labels
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self.tied_param[idxlist] = p1vals[expandlist]
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if len(removelist[0])>0:
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self._merge_tie_labelpair(removelist)
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p1,p2 = self._updateParamList(p_split)
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self._set_labels([p1,p2], labellist)
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self._sync_constraint_vector(p1,p2,expandlist,idxlist)
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self._sync_val([p1,p2],toTiedParam=True)
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self._sync_constraints([p1,p2], toTiedParam=True)
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self._update_label_buf()
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self.update_model(True)
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@ -515,11 +424,15 @@ class Tie(Parameterized):
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for i in xrange(self.tied_param.size):
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self._highest_parent_.param_array[self.label_buf==self.label_buf[self.buf_idx[i]]] = self.tied_param[i]
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self._PROPAGATE_VAL_ = True
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#=========================================
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# Functions for checking consistency
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#=========================================
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def checkValueConsistence(self):
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def checkValueConsistency(self):
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return not self._check_change()
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def checkConstraintConsistence(self):
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def checkConstraintConsistency(self):
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if self.tied_param is not None:
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tlist = self.getTiedParamList()
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for l in tlist:
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@ -439,7 +439,7 @@ def sparse_GP_regression_2D(num_samples=400, num_inducing=50, max_iters=100, opt
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if plot:
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m.plot()
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print m
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#print m
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return m
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def uncertain_inputs_sparse_regression(max_iters=200, optimize=True, plot=True):
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@ -2,7 +2,6 @@
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# Licensed under the BSD 3-clause license (see LICENSE.txt)
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import unittest
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import numpy as np
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import GPy
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class TieTests(unittest.TestCase):
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@ -10,8 +9,8 @@ class TieTests(unittest.TestCase):
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m = GPy.examples.regression.sparse_GP_regression_1D(optimize=False, plot=False, checkgrad=False)
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m.Z.constrain_positive(warning=False)
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m.Z.tie_together()
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self.assertTrue(m.ties.checkValueConsistence())
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self.assertTrue(m.ties.checkValueConsistence())
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self.assertTrue(m.ties.checkValueConsistency())
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self.assertTrue(m.ties.checkConstraintConsistency())
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self.assertTrue(m.ties.checkTieTogether([m.Z]))
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self.assertTrue(m.checkgrad())
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@ -22,8 +21,8 @@ class TieTests(unittest.TestCase):
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m.Z[2:4].tie_together()
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self.assertTrue(m.ties.checkTieTogether([m.Z[:2]]))
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self.assertTrue(m.ties.checkTieTogether([m.Z[2:4]]))
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self.assertTrue(m.ties.checkValueConsistence())
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self.assertTrue(m.ties.checkValueConsistence())
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self.assertTrue(m.ties.checkValueConsistency())
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self.assertTrue(m.ties.checkConstraintConsistency())
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self.assertTrue(m.checkgrad())
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def test_tie_together_merge(self):
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@ -32,8 +31,28 @@ class TieTests(unittest.TestCase):
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m.Z[:2].tie_together()
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m.Z[1:3].tie_together()
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self.assertTrue(m.ties.checkTieTogether([m.Z[:3]]))
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self.assertTrue(m.ties.checkValueConsistence())
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self.assertTrue(m.ties.checkValueConsistence())
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self.assertTrue(m.ties.checkValueConsistency())
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self.assertTrue(m.ties.checkConstraintConsistency())
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self.assertTrue(m.checkgrad())
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def test_tie_vector(self):
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m = GPy.examples.regression.sparse_GP_regression_1D(optimize=False, plot=False, checkgrad=False)
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m.Z.constrain_positive(warning=False)
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m.Z[:2].tie_vector(m.Z[2:4])
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self.assertTrue(m.ties.checkValueConsistency())
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self.assertTrue(m.ties.checkConstraintConsistency())
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self.assertTrue(m.ties.checkTieVector([m.Z[:2],m.Z[2:4]]))
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self.assertTrue(m.checkgrad())
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def test_tie_vector_merge(self):
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m = GPy.examples.regression.sparse_GP_regression_2D(optimize=False, plot=False)
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m.Z.constrain_positive(warning=False)
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m.Z[:10].tie_vector(m.Z[10:20])
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m.Z[20:30].tie_vector(m.Z[30:40])
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m.Z[10:20].tie_vector(m.Z[20:30])
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self.assertTrue(m.ties.checkValueConsistency())
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self.assertTrue(m.ties.checkConstraintConsistency())
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self.assertTrue(m.ties.checkTieVector([m.Z[:10],m.Z[10:20],m.Z[20:30],m.Z[30:40]]))
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self.assertTrue(m.checkgrad())
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if __name__ == "__main__":
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