def testBuckets(self):
testKnowledge = KnowledgeModel({}, [])
individuals = ['i1', 'i2', 'i3']
individualBuckets = {"Known": [], "Unknown": [], "Unclear": [], "Not Asked": individuals}
for j in range(0, 15, 1):
for i in individuals:
testKnowledge.updateIndividualScore({'i1': 1, 'i2':(-1)^j, 'i3':1})
testKnowledge.updateIndividualBuckets()
x = 0
if 'i1' in individualBuckets["Known"]:
x = 1
self.assertEqual(1, x)
if 'i2' in individualBuckets["Unknown"]:
x = 2
self.assertEqual(2, x)
if 'i3' in individualBuckets["Unclear"]:
x = 3
self.assertEqual(3, x)
def testIndividualScore(self):
#Does not use timeStamp, but instead averages all scores
testKnowledge = KnowledgeModel({}, [])
testKnowledge.updateIndividualScore("i1", 5.6)
testKnowledge.updateIndividualScore("i2", 7)
testKnowledge.updateIndividualScore("i3", -4)
testKnowledge.updateIndividualScore("i4", 50)
testKnowledge.updateIndividualScore("i5", 0)
self.assertAlmostEqual(5.6, testKnowledge.calcIndividualScore("i1"))
self.assertEqual(-4, testKnowledge.calcIndividualScore("i3"))
testKnowledge.updateIndividualScore("i3", -5)
testKnowledge.updateIndividualScore("i1", -4.5)
testKnowledge.updateIndividualScore("i2", 0)
self.assertAlmostEqual(-4.5, testKnowledge.calcIndividualScore("i3"))
self.assertAlmostEqual(0.55, testKnowledge.calcIndividualScore("i1")) ##uses almost equal for rounding
self.assertAlmostEqual(3.5, testKnowledge.calcIndividualScore("i2"))