#beta= 0.5 p= 2 num clusters= 3
linkage completed in  10.664654970169067
#cluster  3 with weight 0.7195
Learned cluster center of cluster 3:  {1: 0, 2: 1, 3: 1, 4: 1, 5: 1, 6: 1, 7: 1, 8: 1, 9: 1, 10: 1, 11: 1} [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]
learned probs [2.64613439e-41 4.14085440e-01 2.51155515e-01 1.52333520e-01
 9.23949506e-02 5.60403704e-02 3.39902028e-02 0.00000000e+00
 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00] [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]
cluster label 3 learned center: 
 
sigma= [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]
learned probs (dictionary):

probs= {0: np.float64(1.9038936900832814e-41), 1: np.float64(0.2979344743819586), 2: np.float64(0.180706393298026), 3: np.float64(0.10960396794134232), 4: np.float64(0.06647816698258467), 5: np.float64(0.04032104647643369), 6: np.float64(0.024455950919655068), 7: np.float64(0.0), 8: np.float64(0.0), 9: np.float64(0.0), 10: np.float64(0.0), 11: np.float64(0.0)}
#cluster  2 with weight 0.25125
Learned cluster center of cluster 2:  {1: 0, 2: 2, 3: 2, 4: 2, 6: 2, 8: 2, 9: 2, 100: 1} [1, 100, 2, 3, 4, 6, 8, 9]
learned probs [8.28072272e-42 8.28072272e-42 5.21744641e-01 0.00000000e+00
 2.17632126e-01 1.32000557e-01 8.00623850e-02 4.85602912e-02
 0.00000000e+00 0.00000000e+00] [5, 0, 1, 100, 2, 3, 4, 6, 8, 9]
cluster label 2 learned center: 
 
sigma= [1, 100, 2, 3, 4, 6, 8, 9]
learned probs (dictionary):

probs= {5: np.float64(2.0805315839214482e-42), 0: np.float64(2.0805315839214482e-42), 1: np.float64(0.13108834096570923), 100: np.float64(0.0), 2: np.float64(0.05468007169881535), 3: np.float64(0.03316513996061656), 4: np.float64(0.020115674219774584), 6: np.float64(0.012200773155084294), 8: np.float64(0.0), 9: np.float64(0.0)}
#cluster  1 with weight 0.02925
Learned cluster center of cluster 1:  {1: 0, 2: 3, 3: 1, 5: 1, 6: 2, 7: 1, 10: 5, 12: 5, 15: 9, 16: 8, 17: 7, 18: 8, 21: 8, 24: 10, 30: 10, 100: 2} [1, 3, 5, 7, 6, 100, 2, 10, 12, 17, 16, 18, 21, 15, 24, 30]
learned probs [2.35799347e-40 2.35799347e-40 4.60491861e-01 2.79302433e-01
 1.69405489e-01 0.00000000e+00 6.59186539e-02 0.00000000e+00
 2.48815634e-02 0.00000000e+00 0.00000000e+00 0.00000000e+00
 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00
 0.00000000e+00] [4, 0, 1, 3, 5, 7, 6, 100, 2, 10, 12, 17, 16, 18, 21, 15, 24]
cluster label 1 learned center: 
 
sigma= [1, 3, 5, 7, 6, 100, 2, 10, 12, 17, 16, 18, 21, 15, 24]
learned probs (dictionary):

probs= {4: np.float64(6.897130910225085e-42), 0: np.float64(6.897130910225085e-42), 1: np.float64(0.013469386947891853), 3: np.float64(0.008169596151429582), 5: np.float64(0.004955110543312375), 7: np.float64(0.0), 6: np.float64(0.0019281206268536438), 100: np.float64(0.0), 2: np.float64(0.0007277857305125546), 10: np.float64(0.0), 12: np.float64(0.0), 17: np.float64(0.0), 16: np.float64(0.0), 18: np.float64(0.0), 21: np.float64(0.0), 15: np.float64(0.0), 24: np.float64(0.0)}
