class PCABasisProcessor(object):
def __init__(self,*args, **kwargs):
self.args=args
self.kwargs=kwargs
self.directory=None
def process(self,v):
self.ipca=IncrementalPCAdimred(-1,*self.args, **self.kwargs)
self.ipca.add_train(v)
self.ipca.recompute()
return self.ipca.M
def init(self,odim, burnin=300,*args, **kwargs):
self.pcafilename=self.directory+"/pca.pcl"
try:
self.ipca=IncrementalPCAdimred.load(self.pcafilename)
if (self.ibow==None):
raise Exception
self.model_node.status=genericmodel.STATUS_READY
pycvf_debug(10, "loaded"+ self.pcafilename+"...")
except:
self.ipca=IncrementalPCAdimred(-1,odim,*args, **kwargs)
#self.ibow.set_filename(self.bowfilename)
self.model_node.status=genericmodel.STATUS_NOT_READY
self.totrain=burnin
class IPCAProcessor(object):
def __init__(self,*args, **kwargs):
self.args=args
self.kwargs=kwargs
self.directory=None
def init(self,odim, burnin=300,*args, **kwargs):
self.pcafilename=self.directory+"/pca.pcl"
try:
self.ipca=IncrementalPCAdimred.load(self.pcafilename)
if (self.ibow==None):
raise Exception
self.model_node.status=genericmodel.STATUS_READY
pycvf_debug(10, "loaded"+ self.pcafilename+"...")
except:
self.ipca=IncrementalPCAdimred(-1,odim,*args, **kwargs)
#self.ibow.set_filename(self.bowfilename)
self.model_node.status=genericmodel.STATUS_NOT_READY
self.totrain=burnin
def set_model_node(self,model):
self.model_node=model
self.directory=model.get_directory()
self.init(*self.args,**self.kwargs)
def on_model_destroy(self,model):
self.save()
self.model_node=None
def process(self,v):
if (self.totrain):
q=min(v.shape[0],self.totrain)
self.totrain-=q
self.ipca.add_train(v[:q])
if (self.totrain==0):
self.ipca.recompute()
self.save()
if (v.shape[0]==q):
self.model_node.status=genericmodel.STATUS_NOT_READY
raise NotReady
else:
v=v[q:]
try:
assert(v.ndim==2)
r=self.ipca.dimred(v)
except KeyboardInterrupt:
raise
except Exception,e:
print e
self.model_node.status=genericmodel.STATUS_NOT_READY
raise NotReady
self.model_node.status=genericmodel.STATUS_READY
return r
def process(self,v):
self.ipca=IncrementalPCAdimred(-1,*self.args, **self.kwargs)
self.ipca.add_train(v)
self.ipca.recompute()
return self.ipca.M
