예제 #1
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    def test_2d_1cluster(self):
        #create simple data:
        a = range(0, 11)
        print a
        d = []
        for i in a:
            for j in a:
                d.append([i * 1.0, j * 1.0])

        dbscanner = Dbscan(np.array(d), 3, 2.0)
        dbscanner.run()
        plotting.plotting(dbscanner.getClusterList(), dbscanner.getNoise())
예제 #2
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    def test_2d_1cluster(self):
        #create simple data:
        a = range(0, 11)
        print a
        d = []
        for i in a:
            for j in a:
                d.append([i*1.0, j*1.0])

        dbscanner = Dbscan(np.array(d), 3, 2.0)
        dbscanner.run()
        plotting.plotting(dbscanner.getClusterList(),dbscanner.getNoise())
예제 #3
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 def test_plotting(self):
     #some dummy data
     number, x_coordinate, y_coordinate = loadtxt('testdata/eps3-minpts5-cluster5-noise20.dat', unpack = True)
     D=[None]*len(x_coordinate)
     for ii in range(len(x_coordinate)):
         D[ii]=[x_coordinate[ii],y_coordinate[ii]]
     #put in the data we want to use
     minNeighbors = 5
     epsilon = 3.
     data = np.array(D, dtype=np.float64)
     # use dbscan
     dbscanner = Dbscan(data, minNeighbors, epsilon)
     dbscanner.run()
     # use plotting
     plotting.plotting(dbscanner.getClusterList(),dbscanner.getNoise())
예제 #4
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 def test_plotting(self):
     #some dummy data
     number, x_coordinate, y_coordinate = loadtxt(
         'testdata/eps3-minpts5-cluster5-noise20.dat', unpack=True)
     D = [None] * len(x_coordinate)
     for ii in range(len(x_coordinate)):
         D[ii] = [x_coordinate[ii], y_coordinate[ii]]
     #put in the data we want to use
     minNeighbors = 5
     epsilon = 3.
     data = np.array(D, dtype=np.float64)
     # use dbscan
     dbscanner = Dbscan(data, minNeighbors, epsilon)
     dbscanner.run()
     # use plotting
     plotting.plotting(dbscanner.getClusterList(), dbscanner.getNoise())
예제 #5
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 def test_dbscan2(self):
     testdata2='testdata/eps0p01-minpts1-cluster0-noise100.dat'
     number, x_coordinate, y_coordinate      = np.loadtxt(testdata2, unpack = True)
     D=[None]*len(x_coordinate)
     for ii in range(len(x_coordinate)):
         D[ii]=[x_coordinate[ii],y_coordinate[ii]]
     D=np.array(D)
     epsilon=0.01
     minNeighbors=1
     dbscanner = Dbscan(D, minNeighbors, epsilon)
     dbscanner.run()
     datennoise=dbscanner.getNoise()
     datennoise=np.array(datennoise)
     b=[]
     cluster1=dbscanner.getClusterList()
     np.testing.assert_array_equal(cluster1,b)
     np.testing.assert_array_equal(datennoise,D)
예제 #6
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 def test_dbscan2(self):
     testdata2 = 'testdata/eps0p01-minpts1-cluster0-noise100.dat'
     number, x_coordinate, y_coordinate = np.loadtxt(testdata2, unpack=True)
     D = [None] * len(x_coordinate)
     for ii in range(len(x_coordinate)):
         D[ii] = [x_coordinate[ii], y_coordinate[ii]]
     D = np.array(D)
     epsilon = 0.01
     minNeighbors = 1
     dbscanner = Dbscan(D, minNeighbors, epsilon)
     dbscanner.run()
     datennoise = dbscanner.getNoise()
     datennoise = np.array(datennoise)
     b = []
     cluster1 = dbscanner.getClusterList()
     np.testing.assert_array_equal(cluster1, b)
     np.testing.assert_array_equal(datennoise, D)
예제 #7
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 def test_dbscan1(self):
     testdata='testdata/eps2-minpts3-cluster1-noise0.dat'
     number, x_coordinate, y_coordinate      = np.loadtxt(testdata, unpack = True)
     D=[None]*len(x_coordinate)
     for ii in range(len(x_coordinate)):
         D[ii]=[x_coordinate[ii],y_coordinate[ii]]
     D=np.array(D)
     epsilon=4.0
     minNeighbors=3
     dbscanner = Dbscan(D, minNeighbors, epsilon)
     dbscanner.run()
     datennoise=dbscanner.getNoise()
     Dresultall=[]
     for daten in dbscanner.getClusterList():
         Dresult=[]
         for item in daten:
             Dresult.append(item)
         Dresultall.append(Dresult)  #
     #assert D==a
     Dr=np.array(Dresultall)
     a=np.array([])
     np.testing.assert_array_equal(a,datennoise)
예제 #8
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 def test_dbscan1(self):
     testdata = 'testdata/eps2-minpts3-cluster1-noise0.dat'
     number, x_coordinate, y_coordinate = np.loadtxt(testdata, unpack=True)
     D = [None] * len(x_coordinate)
     for ii in range(len(x_coordinate)):
         D[ii] = [x_coordinate[ii], y_coordinate[ii]]
     D = np.array(D)
     epsilon = 4.0
     minNeighbors = 3
     dbscanner = Dbscan(D, minNeighbors, epsilon)
     dbscanner.run()
     datennoise = dbscanner.getNoise()
     Dresultall = []
     for daten in dbscanner.getClusterList():
         Dresult = []
         for item in daten:
             Dresult.append(item)
         Dresultall.append(Dresult)  #
     #assert D==a
     Dr = np.array(Dresultall)
     a = np.array([])
     np.testing.assert_array_equal(a, datennoise)