Sensitivity analysis in Python
from jpype import *
classpath = 'C:\\Program Files\\Bayes Server\\Bayes Server 9.2\\API\\Java\\bayesserver-9.2.jar'
startJVM(getDefaultJVMPath(), '-Djava.class.path=%s' % classpath, convertStrings=False)
bayes = JPackage('com.bayesserver')
bayes_data = bayes.data
bayes_inference = bayes.inference
bayes_analysis = bayes.analysis
network_path = 'C:\\ProgramData\\Bayes Server 8.19\\Sample Networks\\Asia.bayes'
network = bayes.Network()
network.load(network_path)
variables = network.getVariables()
visit_to_asia = variables.get('Visit to Asia', True)
has_lung_cancer = variables.get('Has Lung Cancer', True)
tuberculosis_or_cancer = variables.get('Tuberculosis or Cancer', True)
smoker = variables.get('Smoker', True)
has_tuberculosis = variables.get('Has Tuberculosis', True)
dyspnea = variables.get('Dyspnea', True)
xray_result = variables.get('XRay Result', True)
has_bronchitis = variables.get('Has Bronchitis', True)
xRayResultAbnormal = xray_result.getStates().get('Abnormal', True)
smokerFalse = smoker.getStates().get('False', True)
hasLungCancerFalse = has_lung_cancer.getStates().get('False', True)
evidence = bayes_inference.DefaultEvidence(network)
sensitivity = bayes_analysis.SensitivityToParameters(network, bayes_inference.RelevanceTreeInferenceFactory())
parameter = bayes_analysis.ParameterReference(has_lung_cancer.getNode(), [smokerFalse, hasLungCancerFalse])
oneWay = sensitivity.oneWay(
evidence,
xRayResultAbnormal,
parameter
)
print('Parameter value = {}'.format(oneWay.getParameterValue()))
print('Sensitivity value = {}'.format(oneWay.getSensitivityValue()))
print('P(Abnormal | e) = {}'.format(oneWay.getProbabilityHypothesisGivenEvidence()))
print('Alpha = {}'.format(oneWay.getAlpha()))
print('Beta = {}'.format(oneWay.getBeta()))
print('Delta = {}'.format(oneWay.getDelta()))
print('Gamma = {}'.format(oneWay.getGamma()))
print('Eval(0.2) = {}'.format(oneWay.evaluate(0.2)))
print('Eval\'(0.2) = {}'.format(oneWay.evaluateDeriv(0.2)))