示例#1
0
 def task(self):
     listP = []
     listData = []
     for i in map(float, xrange(0, 101)):
         listP.append(i / 100.0)
         dblEntropy = dtree.compute_entropy(i, 100.0 - i)
         listData.append(dblEntropy)
     return {
         "chart": {
             "defaultSeriesType": "line"
         },
         "title": {
             "text": "Entropy"
         },
         "xAxis": {
             "title": {
                 "text": "p"
             }
         },
         "yAxis": {
             "title": {
                 "text": "entropy"
             },
             "min": 0,
             "max": 1.1
         },
         "series": [{
             "name": "Entropy",
             "data": zip(listP, listData)
         }]
     }
 def task(self):
     listP = []
     listData = []
     for i in map(float, xrange(0, 101)):
         listP.append(i / 100.0)
         dblEntropy = dtree.compute_entropy(i, 100.0 - i)
         listData.append(dblEntropy)
     return {"chart": {"defaultSeriesType": "line"},
             "title": {"text": "Entropy"},
             "xAxis": {"title": {"text": "p"}},
             "yAxis": {"title": {"text": "entropy"}, "min": 0, "max": 1.1},
             "series": [{"name": "Entropy", "data": zip(listP, listData)}]}
 def test_compute_entropy(self):
     dblK = 1000000.0 * random.random()
     self.assertAlmostEqual(1.0, dtree.compute_entropy(dblK, dblK))
     self.assertAlmostEqual(0.0, dtree.compute_entropy(0.0, dblK))
     self.assertAlmostEqual(0.0, dtree.compute_entropy(dblK, 0.0))
示例#4
0
 def test_compute_entropy(self):
     dblK = 1000000.0*random.random()
     self.assertAlmostEqual(1.0, dtree.compute_entropy(dblK,dblK))
     self.assertAlmostEqual(0.0, dtree.compute_entropy(0.0, dblK))
     self.assertAlmostEqual(0.0, dtree.compute_entropy(dblK, 0.0))