nodeH1_R1 = ntc.newnode('MaxInundation_Houses', 0, net_p)
ntc.setnodelevels(nodeH1_R1, 4, np.asarray([0, 0, 0.5, 1, 2], dtype='float64'))
ntc.setnodetitle(nodeH1_R1, 'Houses - Max. Inundation depth (m)')
nodeC1_R1 = ntc.newnode('RelativeDamage_Houses', 0, net_p)
ntc.setnodelevels(nodeC1_R1, 4,
np.asarray([0, 0, 23.5, 47, 50], dtype='float64'))
ntc.setnodetitle(nodeC1_R1, 'Houses - Relative Damage (%)')
# define links
ntc.addlink(parent=nodeBC1, child=nodeH1_R1)
ntc.addlink(parent=nodeBC2, child=nodeH1_R1)
ntc.addlink(parent=nodeR1, child=nodeH1_R1)
ntc.addlink(parent=nodeH1_R1, child=nodeC1_R1)
ntc.setnodeprobs(nodeH1_R1, np.asarray([0, 0, 0], dtype='int'),
np.asarray([16.7, 44.7, 22.6, 16.1], dtype='float32'))
# obtain node list
#nl_p = ntc.getnetnodes(net_p)
# train with cas file
# ntc.revisecptsbycasefile(filename='BNcases.cas', nl_p=nl_p, updating=0, degree=1)
# compile the net
ntc.compilenet(net_p)
ntc.getnodeprobs(nodeH1_R1,
np.zeros(20,
dtype='int')) #np.asarray([0, 0, 0], dtype='int'))
# enable auto updating
ntc.setautoupdate(net_p)
ntc.setnodestatenames(Cancer, "present, absent") ntc.setnodestatenames(TbOrCa, "true, false") ntc.setnodestatenames(XRay, "abnormal,normal") # define links ntc.addlink(parent=VisitAsia, child=Tuberculosis) ntc.addlink(parent=Smoking, child=Cancer) ntc.addlink(parent=Tuberculosis, child=TbOrCa) ntc.addlink(parent=Cancer, child=TbOrCa) ntc.addlink(parent=TbOrCa, child=XRay) # set node probs parent_states = np.empty((1, ), dtype='int32') probs = np.array([0.01, 0.99], dtype='float32') ntc.setnodeprobs(VisitAsia, parent_states, probs) parent_states = np.array([0], dtype='int32') probs = np.array([0.05, 0.95], dtype='float32') ntc.setnodeprobs(Tuberculosis, parent_states, probs) parent_states = np.array([1], dtype='int32') probs = np.array([0.01, 0.99], dtype='float32') ntc.setnodeprobs(Tuberculosis, parent_states, probs) parent_states = np.empty((1, ), dtype='int32') probs = np.array([0.50, 0.50], dtype='float32') ntc.setnodeprobs(Smoking, parent_states, probs) parent_states = np.array([0], dtype='int32') probs = np.array([0.10, 0.90], dtype='float32') ntc.setnodeprobs(Cancer, parent_states, probs)
ntc.setnodestatenames(Cancer, "present, absent"); ntc.setnodestatenames(TbOrCa, "true, false"); ntc.setnodestatenames(XRay, "abnormal,normal"); # define links ntc.addlink(parent=VisitAsia, child=Tuberculosis) ntc.addlink(parent=Smoking, child=Cancer) ntc.addlink(parent=Tuberculosis, child=TbOrCa) ntc.addlink(parent=Cancer, child=TbOrCa) ntc.addlink(parent=TbOrCa, child=XRay) # set node probs parent_states = np.empty((1,),dtype='int32') probs = np.array([0.01, 0.99], dtype='float32') ntc.setnodeprobs (VisitAsia, parent_states, probs) parent_states = np.array([0],dtype='int32') probs = np.array([0.05, 0.95], dtype='float32') ntc.setnodeprobs (Tuberculosis, parent_states, probs) parent_states = np.array([1],dtype='int32') probs = np.array([0.01, 0.99], dtype='float32') ntc.setnodeprobs (Tuberculosis, parent_states, probs) parent_states = np.empty((1,),dtype='int32') probs = np.array([0.50, 0.50], dtype='float32') ntc.setnodeprobs (Smoking, parent_states, probs) parent_states = np.array([0],dtype='int32') probs = np.array([0.10, 0.90], dtype='float32') ntc.setnodeprobs (Cancer, parent_states, probs)
nodeH1_R1 = ntc.newnode('MaxInundation_Houses', 0, net_p)
ntc.setnodelevels(nodeH1_R1, 4, np.asarray([0, 0, 0.5, 1, 2], dtype='float64'))
ntc.setnodetitle(nodeH1_R1,'Houses - Max. Inundation depth (m)')
nodeC1_R1 = ntc.newnode('RelativeDamage_Houses', 0, net_p)
ntc.setnodelevels(nodeC1_R1, 4, np.asarray([0, 0, 23.5, 47, 50], dtype='float64'))
ntc.setnodetitle(nodeC1_R1,'Houses - Relative Damage (%)')
# define links
ntc.addlink(parent=nodeBC1, child=nodeH1_R1)
ntc.addlink(parent=nodeBC2, child=nodeH1_R1)
ntc.addlink(parent=nodeR1, child=nodeH1_R1)
ntc.addlink(parent=nodeH1_R1, child=nodeC1_R1)
ntc.setnodeprobs(nodeH1_R1, np.asarray([0, 0, 0], dtype='int'), np.asarray([16.7,44.7,22.6,16.1],dtype='float32'))
# obtain node list
#nl_p = ntc.getnetnodes(net_p)
# train with cas file
# ntc.revisecptsbycasefile(filename='BNcases.cas', nl_p=nl_p, updating=0, degree=1)
# compile the net
ntc.compilenet(net_p)
ntc.getnodeprobs(nodeH1_R1, np.zeros(20, dtype='int')) #np.asarray([0, 0, 0], dtype='int'))
# enable auto updating
ntc.setautoupdate(net_p)
