Note

Click here to download the full example code

Quick demonstration that you can easily use bnpy to
perform mixed membership modeling of grouped data with *any* likelihood.

The basic idea is that we use the same Gaussian mixture model for each
group of data, but the *appearance probabilities* are allowed to be
learned in a customized way for each group.

Here, we’ll analyze motion capture data from 6 different sequences of an individual actor peforming different exercises.

Although this data is inherently sequential in nature and it is smart to
use a model that accounts for time, we’ll ignore that for now and
focus on the dataset’s *grouped* nature.

That is, we can compare the following two models:

- Baseline: Gaussian mixture model that pools all observations from all sequences
- Smarter alternative: Latent Dirichlet Allocation with a Gaussian likelihood

That is, we treat each sequence as a separate collection of data examples,
modeled by *group* specific appearance probabilities but *shared* cluster
means and covariances.

```
# sphinx_gallery_thumbnail_number = 1
import bnpy
import numpy as np
import os
from matplotlib import pylab
import seaborn as sns
FIG_SIZE = (5, 5)
LANDSCAPE_FIG_SIZE = (15, 5)
pylab.rcParams['figure.figsize'] = FIG_SIZE
np.set_printoptions(precision=3, suppress=1, linewidth=200)
```

Load dataset from file

```
dataset_path = os.path.join(bnpy.DATASET_PATH, 'mocap6')
dataset = bnpy.data.GroupXData.read_npz(
os.path.join(dataset_path, 'dataset.npz'))
```

```
def show_single_sequence(seq_id):
start = dataset.doc_range[seq_id]
stop = dataset.doc_range[seq_id + 1]
pylab.figure(figsize=LANDSCAPE_FIG_SIZE)
for dim in xrange(12):
X_seq = dataset.X[start:stop]
pylab.plot(X_seq[:, dim], '.-')
pylab.xlabel('time')
pylab.ylabel('angle')
pylab.tight_layout()
```

```
show_single_sequence(0)
```

```
K = 10 # Number of clusters/states
alpha = 0.25 # group-level Dirichlet concentration parameter
gamma = 5.0 # top-level Dirichlet concentration parameter (used by HDP only)
sF = 1.0 # Set observation model prior so E[covariance] = identity
ECovMat = 'eye'
nLap = 200
```

We’ll take the best of 3 independent inits (‘tasks’)

```
mix_model, mix_info_dict = bnpy.run(
dataset, 'FiniteMixtureModel', 'DiagGauss', 'memoVB',
output_path='/tmp/mocap6/test-model=FiniteMixtureModel+DiagGauss-ECovMat=1*eye/',
nLap=nLap, nTask=3, nBatch=1, convergeThr=0.0001,
gamma=1.0,
sF=sF, ECovMat=ECovMat,
K=K, initname='randexamples',
)
```

Out:

```
Dataset Summary:
GroupXData
total size: 6 units
batch size: 6 units
num. batches: 1
Allocation Model: Finite mixture model. Dir prior param 1.00
Obs. Data Model: Gaussian with diagonal covariance.
Obs. Data Prior: independent Gauss-Wishart prior on each dimension
Wishart params
nu = 14 ...
beta = [ 12 12] ...
Expectations
E[ mean[k]] =
[ 0 0] ...
E[ covar[k]] =
[[1. 0.]
[0. 1.]] ...
Initialization:
initname = randexamples
K = 10 (number of clusters)
seed = 1607680
elapsed_time: 0.0 sec
Learn Alg: memoVB | task 1/3 | alg. seed: 1607680 | data order seed: 8541952
task_output_path: /tmp/mocap6/test-model=FiniteMixtureModel+DiagGauss-ECovMat=1*eye/1
1.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.892221921e+00 |
2.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.793128859e+00 | Ndiff 70.741
3.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.744872834e+00 | Ndiff 54.945
4.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.728928355e+00 | Ndiff 36.565
5.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.723943088e+00 | Ndiff 21.439
6.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.720839494e+00 | Ndiff 19.301
7.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.716886499e+00 | Ndiff 27.316
8.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.712988461e+00 | Ndiff 29.509
9.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.710101014e+00 | Ndiff 26.563
10.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.708338808e+00 | Ndiff 20.288
11.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.707223572e+00 | Ndiff 14.712
12.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.706484641e+00 | Ndiff 11.584
13.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.706034786e+00 | Ndiff 9.396
14.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.705729766e+00 | Ndiff 7.152
15.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.705504466e+00 | Ndiff 6.297
16.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.705319760e+00 | Ndiff 6.572
17.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.705112506e+00 | Ndiff 6.841
18.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.704838851e+00 | Ndiff 7.164
19.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.704355597e+00 | Ndiff 7.952
20.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.703328946e+00 | Ndiff 8.251
21.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.702259036e+00 | Ndiff 8.680
22.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.700921542e+00 | Ndiff 13.756
23.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.699599200e+00 | Ndiff 14.619
24.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.699098383e+00 | Ndiff 7.905
25.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.698964052e+00 | Ndiff 3.030
26.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.698910375e+00 | Ndiff 2.941
27.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.698876899e+00 | Ndiff 2.963
28.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.698850387e+00 | Ndiff 2.877
29.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.698826486e+00 | Ndiff 2.796
30.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.698803026e+00 | Ndiff 2.754
31.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.698778550e+00 | Ndiff 2.758
32.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.698751763e+00 | Ndiff 2.809
33.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.698721045e+00 | Ndiff 2.904
34.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.698683416e+00 | Ndiff 3.044
35.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.698630921e+00 | Ndiff 3.241
36.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.698535167e+00 | Ndiff 3.532
37.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.698290137e+00 | Ndiff 4.008
38.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.697335718e+00 | Ndiff 4.769
39.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.693949604e+00 | Ndiff 10.713
40.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.688868616e+00 | Ndiff 14.061
41.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.686366624e+00 | Ndiff 10.183
42.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.685490235e+00 | Ndiff 13.059
43.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.685007421e+00 | Ndiff 11.536
44.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.684710512e+00 | Ndiff 9.055
45.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.684531557e+00 | Ndiff 6.729
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47.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.684341666e+00 | Ndiff 3.509
48.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.684275038e+00 | Ndiff 2.569
49.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.684212748e+00 | Ndiff 1.945
50.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.684158998e+00 | Ndiff 1.549
51.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.684123182e+00 | Ndiff 1.296
52.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.684105203e+00 | Ndiff 1.087
53.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.684097308e+00 | Ndiff 0.854
54.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.684093801e+00 | Ndiff 0.627
55.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.684092161e+00 | Ndiff 0.442
56.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.684091364e+00 | Ndiff 0.307
57.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.684090968e+00 | Ndiff 0.212
58.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.684090769e+00 | Ndiff 0.146
59.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.684090668e+00 | Ndiff 0.101
60.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.684090616e+00 | Ndiff 0.070
61.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.684090590e+00 | Ndiff 0.050
62.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.684090577e+00 | Ndiff 0.035
63.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.684090570e+00 | Ndiff 0.025
64.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.684090566e+00 | Ndiff 0.018
65.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.684090565e+00 | Ndiff 0.013
66.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.684090564e+00 | Ndiff 0.009
67.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.684090563e+00 | Ndiff 0.006
68.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.684090563e+00 | Ndiff 0.005
69.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.684090563e+00 | Ndiff 0.003
70.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.684090563e+00 | Ndiff 0.002
71.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.684090563e+00 | Ndiff 0.002
72.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.684090563e+00 | Ndiff 0.001
73.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.684090563e+00 | Ndiff 0.001
74.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.684090563e+00 | Ndiff 0.001
75.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.684090563e+00 | Ndiff 0.000
76.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.684090563e+00 | Ndiff 0.000
77.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.684090563e+00 | Ndiff 0.000
78.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.684090563e+00 | Ndiff 0.000
79.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.684090563e+00 | Ndiff 0.000
80.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.684090563e+00 | Ndiff 0.000
... done. converged.
Learn Alg: memoVB | task 2/3 | alg. seed: 6454144 | data order seed: 7673856
task_output_path: /tmp/mocap6/test-model=FiniteMixtureModel+DiagGauss-ECovMat=1*eye/2
1.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.890179326e+00 |
2.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.777472898e+00 | Ndiff 83.721
3.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.750123362e+00 | Ndiff 62.267
4.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.739479839e+00 | Ndiff 46.042
5.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.734531114e+00 | Ndiff 29.583
6.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.731782967e+00 | Ndiff 22.825
7.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.729979871e+00 | Ndiff 16.224
8.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.726701094e+00 | Ndiff 10.764
9.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.721833333e+00 | Ndiff 16.579
10.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.717508780e+00 | Ndiff 13.991
11.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.716224141e+00 | Ndiff 8.496
12.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.715641630e+00 | Ndiff 6.731
13.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.715114046e+00 | Ndiff 5.898
14.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.714301987e+00 | Ndiff 6.464
15.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.712860954e+00 | Ndiff 7.549
16.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.710737689e+00 | Ndiff 7.573
17.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.709692612e+00 | Ndiff 4.068
18.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.709106222e+00 | Ndiff 5.517
19.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.708533753e+00 | Ndiff 5.528
20.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.708164056e+00 | Ndiff 3.957
21.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.707928604e+00 | Ndiff 3.853
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23.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.707572126e+00 | Ndiff 3.949
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25.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.707176718e+00 | Ndiff 3.756
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34.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.704053332e+00 | Ndiff 2.452
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38.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.702596961e+00 | Ndiff 2.246
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50.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.702318273e+00 | Ndiff 0.294
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52.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.702310122e+00 | Ndiff 0.228
53.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.702306074e+00 | Ndiff 0.228
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60.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.702220312e+00 | Ndiff 0.931
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80.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.699888944e+00 | Ndiff 0.732
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88.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.699875657e+00 | Ndiff 0.062
89.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.699875539e+00 | Ndiff 0.058
90.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.699875431e+00 | Ndiff 0.055
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100.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.699874147e+00 | Ndiff 0.076
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108.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.699871581e+00 | Ndiff 0.125
109.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.699871088e+00 | Ndiff 0.131
110.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.699870566e+00 | Ndiff 0.134
111.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.699870026e+00 | Ndiff 0.137
112.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.699869484e+00 | Ndiff 0.137
113.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.699868955e+00 | Ndiff 0.134
114.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.699868454e+00 | Ndiff 0.130
115.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.699867995e+00 | Ndiff 0.123
116.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.699867586e+00 | Ndiff 0.114
117.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.699867230e+00 | Ndiff 0.104
118.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.699866929e+00 | Ndiff 0.098
119.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.699866679e+00 | Ndiff 0.091
120.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.699866474e+00 | Ndiff 0.084
121.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.699866308e+00 | Ndiff 0.077
122.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.699866176e+00 | Ndiff 0.070
123.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.699866071e+00 | Ndiff 0.065
124.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.699865987e+00 | Ndiff 0.061
125.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.699865922e+00 | Ndiff 0.057
126.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.699865870e+00 | Ndiff 0.053
127.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.699865830e+00 | Ndiff 0.049
128.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.699865799e+00 | Ndiff 0.045
129.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.699865775e+00 | Ndiff 0.041
130.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.699865756e+00 | Ndiff 0.037
131.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.699865741e+00 | Ndiff 0.034
132.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.699865730e+00 | Ndiff 0.031
133.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.699865721e+00 | Ndiff 0.027
134.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.699865715e+00 | Ndiff 0.025
135.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.699865709e+00 | Ndiff 0.022
136.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.699865706e+00 | Ndiff 0.020
137.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.699865703e+00 | Ndiff 0.017
138.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.699865700e+00 | Ndiff 0.015
139.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.699865699e+00 | Ndiff 0.014
140.000/200 after 4 sec. | 242.0 MiB | K 10 | loss 3.699865697e+00 | Ndiff 0.012
141.000/200 after 4 sec. | 242.0 MiB | K 10 | loss 3.699865696e+00 | Ndiff 0.011
142.000/200 after 4 sec. | 242.0 MiB | K 10 | loss 3.699865696e+00 | Ndiff 0.009
143.000/200 after 4 sec. | 242.0 MiB | K 10 | loss 3.699865695e+00 | Ndiff 0.008
144.000/200 after 4 sec. | 242.0 MiB | K 10 | loss 3.699865695e+00 | Ndiff 0.007
145.000/200 after 4 sec. | 242.0 MiB | K 10 | loss 3.699865694e+00 | Ndiff 0.006
146.000/200 after 4 sec. | 242.0 MiB | K 10 | loss 3.699865694e+00 | Ndiff 0.005
147.000/200 after 4 sec. | 242.0 MiB | K 10 | loss 3.699865694e+00 | Ndiff 0.005
148.000/200 after 4 sec. | 242.0 MiB | K 10 | loss 3.699865694e+00 | Ndiff 0.004
149.000/200 after 4 sec. | 242.0 MiB | K 10 | loss 3.699865694e+00 | Ndiff 0.004
150.000/200 after 4 sec. | 242.0 MiB | K 10 | loss 3.699865694e+00 | Ndiff 0.003
151.000/200 after 4 sec. | 242.0 MiB | K 10 | loss 3.699865694e+00 | Ndiff 0.003
152.000/200 after 4 sec. | 242.0 MiB | K 10 | loss 3.699865694e+00 | Ndiff 0.002
153.000/200 after 4 sec. | 242.0 MiB | K 10 | loss 3.699865694e+00 | Ndiff 0.002
154.000/200 after 4 sec. | 242.0 MiB | K 10 | loss 3.699865694e+00 | Ndiff 0.002
155.000/200 after 4 sec. | 242.0 MiB | K 10 | loss 3.699865694e+00 | Ndiff 0.002
156.000/200 after 4 sec. | 242.0 MiB | K 10 | loss 3.699865694e+00 | Ndiff 0.001
157.000/200 after 4 sec. | 242.0 MiB | K 10 | loss 3.699865694e+00 | Ndiff 0.001
158.000/200 after 4 sec. | 242.0 MiB | K 10 | loss 3.699865693e+00 | Ndiff 0.001
159.000/200 after 4 sec. | 242.0 MiB | K 10 | loss 3.699865693e+00 | Ndiff 0.001
160.000/200 after 4 sec. | 242.0 MiB | K 10 | loss 3.699865693e+00 | Ndiff 0.001
161.000/200 after 4 sec. | 242.0 MiB | K 10 | loss 3.699865693e+00 | Ndiff 0.001
162.000/200 after 4 sec. | 242.0 MiB | K 10 | loss 3.699865693e+00 | Ndiff 0.001
163.000/200 after 4 sec. | 242.0 MiB | K 10 | loss 3.699865693e+00 | Ndiff 0.001
164.000/200 after 4 sec. | 242.0 MiB | K 10 | loss 3.699865693e+00 | Ndiff 0.000
165.000/200 after 4 sec. | 242.0 MiB | K 10 | loss 3.699865693e+00 | Ndiff 0.000
166.000/200 after 4 sec. | 242.0 MiB | K 10 | loss 3.699865693e+00 | Ndiff 0.000
167.000/200 after 4 sec. | 242.0 MiB | K 10 | loss 3.699865693e+00 | Ndiff 0.000
168.000/200 after 4 sec. | 242.0 MiB | K 10 | loss 3.699865693e+00 | Ndiff 0.000
169.000/200 after 4 sec. | 242.0 MiB | K 10 | loss 3.699865693e+00 | Ndiff 0.000
170.000/200 after 4 sec. | 242.0 MiB | K 10 | loss 3.699865693e+00 | Ndiff 0.000
171.000/200 after 4 sec. | 242.0 MiB | K 10 | loss 3.699865693e+00 | Ndiff 0.000
172.000/200 after 4 sec. | 242.0 MiB | K 10 | loss 3.699865693e+00 | Ndiff 0.000
173.000/200 after 4 sec. | 242.0 MiB | K 10 | loss 3.699865693e+00 | Ndiff 0.000
174.000/200 after 4 sec. | 242.0 MiB | K 10 | loss 3.699865693e+00 | Ndiff 0.000
175.000/200 after 4 sec. | 242.0 MiB | K 10 | loss 3.699865693e+00 | Ndiff 0.000
... done. converged.
Learn Alg: memoVB | task 3/3 | alg. seed: 6168832 | data order seed: 7360256
task_output_path: /tmp/mocap6/test-model=FiniteMixtureModel+DiagGauss-ECovMat=1*eye/3
1.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.967149643e+00 |
2.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.828051356e+00 | Ndiff 79.117
3.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.796678874e+00 | Ndiff 51.355
4.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.782958585e+00 | Ndiff 34.942
5.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.772865919e+00 | Ndiff 33.222
6.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.768379291e+00 | Ndiff 18.402
7.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.765922644e+00 | Ndiff 9.243
8.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.763522049e+00 | Ndiff 12.443
9.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.759687240e+00 | Ndiff 18.742
10.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.758329562e+00 | Ndiff 15.307
11.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.757284595e+00 | Ndiff 14.151
12.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.755332671e+00 | Ndiff 16.539
13.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.751936044e+00 | Ndiff 19.374
14.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.749232109e+00 | Ndiff 18.939
15.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.745412591e+00 | Ndiff 18.269
16.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.741711477e+00 | Ndiff 20.402
17.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.739209544e+00 | Ndiff 18.430
18.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.737744024e+00 | Ndiff 13.082
19.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.737042157e+00 | Ndiff 10.524
20.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.736410038e+00 | Ndiff 8.500
21.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.735755836e+00 | Ndiff 6.634
22.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.734903519e+00 | Ndiff 5.964
23.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.733948260e+00 | Ndiff 5.787
24.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.732926027e+00 | Ndiff 5.839
25.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.731979439e+00 | Ndiff 5.735
26.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.731382239e+00 | Ndiff 5.591
27.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.731262368e+00 | Ndiff 5.144
28.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.731165872e+00 | Ndiff 4.593
29.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.731086681e+00 | Ndiff 4.064
30.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.731027897e+00 | Ndiff 3.407
31.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.730989046e+00 | Ndiff 2.691
32.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.730964762e+00 | Ndiff 2.058
33.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.730949343e+00 | Ndiff 1.571
34.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.730938956e+00 | Ndiff 1.216
35.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.730931280e+00 | Ndiff 0.956
36.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.730924798e+00 | Ndiff 0.760
37.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.730918563e+00 | Ndiff 0.606
38.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.730912654e+00 | Ndiff 0.476
39.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.730908305e+00 | Ndiff 0.360
40.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.730905994e+00 | Ndiff 0.260
41.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.730904916e+00 | Ndiff 0.181
42.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.730904381e+00 | Ndiff 0.122
43.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.730904090e+00 | Ndiff 0.080
44.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.730903919e+00 | Ndiff 0.057
45.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.730903813e+00 | Ndiff 0.050
46.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.730903744e+00 | Ndiff 0.044
47.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.730903698e+00 | Ndiff 0.038
48.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.730903665e+00 | Ndiff 0.033
49.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.730903641e+00 | Ndiff 0.029
50.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.730903623e+00 | Ndiff 0.025
51.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.730903609e+00 | Ndiff 0.022
52.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.730903598e+00 | Ndiff 0.019
53.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.730903589e+00 | Ndiff 0.016
54.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.730903582e+00 | Ndiff 0.014
55.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.730903575e+00 | Ndiff 0.012
56.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.730903570e+00 | Ndiff 0.011
57.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.730903565e+00 | Ndiff 0.010
58.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.730903561e+00 | Ndiff 0.009
59.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.730903557e+00 | Ndiff 0.008
60.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.730903554e+00 | Ndiff 0.008
61.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.730903550e+00 | Ndiff 0.007
62.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.730903547e+00 | Ndiff 0.007
63.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.730903544e+00 | Ndiff 0.007
64.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.730903541e+00 | Ndiff 0.006
65.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.730903538e+00 | Ndiff 0.006
66.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.730903535e+00 | Ndiff 0.006
67.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.730903532e+00 | Ndiff 0.006
68.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.730903528e+00 | Ndiff 0.006
69.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.730903525e+00 | Ndiff 0.006
70.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.730903521e+00 | Ndiff 0.006
71.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.730903517e+00 | Ndiff 0.007
72.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.730903513e+00 | Ndiff 0.007
73.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.730903508e+00 | Ndiff 0.007
74.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.730903502e+00 | Ndiff 0.008
75.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.730903495e+00 | Ndiff 0.009
76.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.730903488e+00 | Ndiff 0.009
77.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.730903478e+00 | Ndiff 0.010
78.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.730903466e+00 | Ndiff 0.011
79.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.730903451e+00 | Ndiff 0.013
80.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.730903431e+00 | Ndiff 0.015
81.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.730903405e+00 | Ndiff 0.017
82.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.730903367e+00 | Ndiff 0.020
83.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.730903312e+00 | Ndiff 0.025
84.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.730903227e+00 | Ndiff 0.030
85.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.730903088e+00 | Ndiff 0.039
86.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.730902847e+00 | Ndiff 0.051
87.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.730902397e+00 | Ndiff 0.068
88.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.730901499e+00 | Ndiff 0.096
89.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.730899644e+00 | Ndiff 0.136
90.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.730896100e+00 | Ndiff 0.185
91.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.730891244e+00 | Ndiff 0.217
92.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.730887713e+00 | Ndiff 0.198
93.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.730886264e+00 | Ndiff 0.145
94.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.730885689e+00 | Ndiff 0.098
95.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.730885409e+00 | Ndiff 0.086
96.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.730885256e+00 | Ndiff 0.074
97.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.730885166e+00 | Ndiff 0.064
98.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.730885111e+00 | Ndiff 0.054
99.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.730885076e+00 | Ndiff 0.045
100.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.730885053e+00 | Ndiff 0.038
101.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.730885038e+00 | Ndiff 0.031
102.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.730885028e+00 | Ndiff 0.026
103.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.730885022e+00 | Ndiff 0.022
104.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.730885017e+00 | Ndiff 0.018
105.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.730885014e+00 | Ndiff 0.015
106.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.730885012e+00 | Ndiff 0.012
107.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.730885010e+00 | Ndiff 0.010
108.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.730885009e+00 | Ndiff 0.008
109.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.730885008e+00 | Ndiff 0.007
110.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.730885007e+00 | Ndiff 0.006
111.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.730885007e+00 | Ndiff 0.005
112.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.730885007e+00 | Ndiff 0.004
113.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.730885007e+00 | Ndiff 0.003
114.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.730885006e+00 | Ndiff 0.003
115.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.730885006e+00 | Ndiff 0.002
116.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.730885006e+00 | Ndiff 0.002
117.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.730885006e+00 | Ndiff 0.002
118.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.730885006e+00 | Ndiff 0.001
119.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.730885006e+00 | Ndiff 0.001
120.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.730885006e+00 | Ndiff 0.001
121.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.730885006e+00 | Ndiff 0.001
122.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.730885006e+00 | Ndiff 0.001
123.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.730885006e+00 | Ndiff 0.001
124.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.730885006e+00 | Ndiff 0.000
125.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.730885006e+00 | Ndiff 0.000
126.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.730885006e+00 | Ndiff 0.000
127.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.730885006e+00 | Ndiff 0.000
128.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.730885006e+00 | Ndiff 0.000
129.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.730885006e+00 | Ndiff 0.000
130.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.730885006e+00 | Ndiff 0.000
131.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.730885006e+00 | Ndiff 0.000
132.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.730885006e+00 | Ndiff 0.000
133.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.730885006e+00 | Ndiff 0.000
... done. converged.
```

We’ll take the best of 3 independent inits (‘tasks’)

```
finite_model, finite_info_dict = bnpy.run(
dataset, 'FiniteTopicModel', 'DiagGauss', 'memoVB',
output_path='/tmp/mocap6/test-model=FiniteTopicModel+DiagGauss-ECovMat=1*eye/',
nLap=nLap, nTask=3, nBatch=1, convergeThr=0.0001,
alpha=alpha,
sF=sF, ECovMat=ECovMat,
K=K, initname='randexamples',
)
```

Out:

```
Dataset Summary:
GroupXData
total size: 6 units
batch size: 6 units
num. batches: 1
Allocation Model: Finite LDA model with K=0 comps. alpha=0.25
Obs. Data Model: Gaussian with diagonal covariance.
Obs. Data Prior: independent Gauss-Wishart prior on each dimension
Wishart params
nu = 14 ...
beta = [ 12 12] ...
Expectations
E[ mean[k]] =
[ 0 0] ...
E[ covar[k]] =
[[1. 0.]
[0. 1.]] ...
Initialization:
initname = randexamples
K = 10 (number of clusters)
seed = 1607680
elapsed_time: 0.0 sec
Learn Alg: memoVB | task 1/3 | alg. seed: 1607680 | data order seed: 8541952
task_output_path: /tmp/mocap6/test-model=FiniteTopicModel+DiagGauss-ECovMat=1*eye/1
1.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.891536742e+00 |
2.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.786835062e+00 | Ndiff 100.168
3.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.737768323e+00 | Ndiff 54.412
4.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.727530929e+00 | Ndiff 36.160
5.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.723599603e+00 | Ndiff 26.974
6.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.720184656e+00 | Ndiff 22.499
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123.000/200 after 4 sec. | 242.0 MiB | K 10 | loss 3.658907896e+00 | Ndiff 0.003
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159.000/200 after 5 sec. | 242.0 MiB | K 10 | loss 3.658907895e+00 | Ndiff 0.000
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169.000/200 after 5 sec. | 242.0 MiB | K 10 | loss 3.658907895e+00 | Ndiff 0.000
170.000/200 after 5 sec. | 242.0 MiB | K 10 | loss 3.658907895e+00 | Ndiff 0.000
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172.000/200 after 5 sec. | 242.0 MiB | K 10 | loss 3.658907895e+00 | Ndiff 0.000
173.000/200 after 5 sec. | 242.0 MiB | K 10 | loss 3.658907895e+00 | Ndiff 0.000
... done. converged.
Learn Alg: memoVB | task 2/3 | alg. seed: 6454144 | data order seed: 7673856
task_output_path: /tmp/mocap6/test-model=FiniteTopicModel+DiagGauss-ECovMat=1*eye/2
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50.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.675204290e+00 | Ndiff 5.243
51.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.675093495e+00 | Ndiff 7.577
52.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.674877831e+00 | Ndiff 11.020
53.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.674494204e+00 | Ndiff 15.319
54.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.674002187e+00 | Ndiff 18.736
55.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.673459444e+00 | Ndiff 20.095
56.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.672940405e+00 | Ndiff 18.174
57.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.672466743e+00 | Ndiff 15.318
58.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.671825477e+00 | Ndiff 14.597
59.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.671050065e+00 | Ndiff 13.869
60.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.670432981e+00 | Ndiff 12.032
61.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.669861634e+00 | Ndiff 10.912
62.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.669261301e+00 | Ndiff 10.844
63.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.667301180e+00 | Ndiff 11.473
64.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.667137918e+00 | Ndiff 3.900
65.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.667105076e+00 | Ndiff 2.261
66.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.667096981e+00 | Ndiff 1.481
67.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.667094652e+00 | Ndiff 1.299
68.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.667093899e+00 | Ndiff 1.140
69.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.667093665e+00 | Ndiff 0.996
70.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.667093628e+00 | Ndiff 0.868
71.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.667093673e+00 | Ndiff 0.756
72.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.667093757e+00 | Ndiff 0.658
73.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.667093860e+00 | Ndiff 0.573
74.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.667093971e+00 | Ndiff 0.499
75.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.667094084e+00 | Ndiff 0.436
76.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.667094196e+00 | Ndiff 0.381
77.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.667094304e+00 | Ndiff 0.333
78.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.667094408e+00 | Ndiff 0.291
79.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.667094505e+00 | Ndiff 0.255
80.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.667094596e+00 | Ndiff 0.224
81.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.667094680e+00 | Ndiff 0.197
82.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.667094757e+00 | Ndiff 0.173
83.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.667094829e+00 | Ndiff 0.152
84.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.667094894e+00 | Ndiff 0.134
85.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.667094953e+00 | Ndiff 0.118
86.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.667095007e+00 | Ndiff 0.104
87.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.667095056e+00 | Ndiff 0.091
88.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.667095100e+00 | Ndiff 0.081
89.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.667095140e+00 | Ndiff 0.071
90.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.667095176e+00 | Ndiff 0.063
91.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.667095209e+00 | Ndiff 0.056
92.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.667095238e+00 | Ndiff 0.049
93.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.667095264e+00 | Ndiff 0.043
94.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.667095287e+00 | Ndiff 0.038
95.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.667095309e+00 | Ndiff 0.034
96.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.667095327e+00 | Ndiff 0.030
97.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.667095344e+00 | Ndiff 0.026
98.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.667095359e+00 | Ndiff 0.023
99.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.667095373e+00 | Ndiff 0.021
100.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.667095385e+00 | Ndiff 0.018
101.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.667095396e+00 | Ndiff 0.016
102.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.667095406e+00 | Ndiff 0.014
103.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.667095414e+00 | Ndiff 0.013
104.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.667095422e+00 | Ndiff 0.011
105.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.667095429e+00 | Ndiff 0.010
106.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.667095435e+00 | Ndiff 0.009
107.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.667095440e+00 | Ndiff 0.008
108.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.667095445e+00 | Ndiff 0.007
109.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.667095449e+00 | Ndiff 0.006
110.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.667095453e+00 | Ndiff 0.005
111.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.667095457e+00 | Ndiff 0.005
112.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.667095460e+00 | Ndiff 0.004
113.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.667095463e+00 | Ndiff 0.004
114.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.667095465e+00 | Ndiff 0.003
115.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.667095467e+00 | Ndiff 0.003
116.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.667095469e+00 | Ndiff 0.003
117.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.667095471e+00 | Ndiff 0.002
118.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.667095472e+00 | Ndiff 0.002
119.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.667095474e+00 | Ndiff 0.002
120.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.667095475e+00 | Ndiff 0.002
121.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.667095476e+00 | Ndiff 0.001
122.000/200 after 4 sec. | 242.0 MiB | K 10 | loss 3.667095477e+00 | Ndiff 0.001
123.000/200 after 4 sec. | 242.0 MiB | K 10 | loss 3.667095478e+00 | Ndiff 0.001
124.000/200 after 4 sec. | 242.0 MiB | K 10 | loss 3.667095479e+00 | Ndiff 0.001
125.000/200 after 4 sec. | 242.0 MiB | K 10 | loss 3.667095479e+00 | Ndiff 0.001
126.000/200 after 4 sec. | 242.0 MiB | K 10 | loss 3.667095480e+00 | Ndiff 0.001
127.000/200 after 4 sec. | 242.0 MiB | K 10 | loss 3.667095480e+00 | Ndiff 0.001
128.000/200 after 4 sec. | 242.0 MiB | K 10 | loss 3.667095481e+00 | Ndiff 0.001
129.000/200 after 4 sec. | 242.0 MiB | K 10 | loss 3.667095481e+00 | Ndiff 0.001
130.000/200 after 4 sec. | 242.0 MiB | K 10 | loss 3.667095482e+00 | Ndiff 0.000
131.000/200 after 4 sec. | 242.0 MiB | K 10 | loss 3.667095482e+00 | Ndiff 0.000
132.000/200 after 4 sec. | 242.0 MiB | K 10 | loss 3.667095482e+00 | Ndiff 0.000
133.000/200 after 4 sec. | 242.0 MiB | K 10 | loss 3.667095482e+00 | Ndiff 0.000
134.000/200 after 4 sec. | 242.0 MiB | K 10 | loss 3.667095483e+00 | Ndiff 0.000
135.000/200 after 4 sec. | 242.0 MiB | K 10 | loss 3.667095483e+00 | Ndiff 0.000
136.000/200 after 4 sec. | 242.0 MiB | K 10 | loss 3.667095483e+00 | Ndiff 0.000
137.000/200 after 4 sec. | 242.0 MiB | K 10 | loss 3.667095483e+00 | Ndiff 0.000
138.000/200 after 4 sec. | 242.0 MiB | K 10 | loss 3.667095483e+00 | Ndiff 0.000
139.000/200 after 4 sec. | 242.0 MiB | K 10 | loss 3.667095484e+00 | Ndiff 0.000
140.000/200 after 4 sec. | 242.0 MiB | K 10 | loss 3.667095484e+00 | Ndiff 0.000
141.000/200 after 4 sec. | 242.0 MiB | K 10 | loss 3.667095484e+00 | Ndiff 0.000
142.000/200 after 4 sec. | 242.0 MiB | K 10 | loss 3.667095484e+00 | Ndiff 0.000
143.000/200 after 4 sec. | 242.0 MiB | K 10 | loss 3.667095484e+00 | Ndiff 0.000
... done. converged.
Learn Alg: memoVB | task 3/3 | alg. seed: 6168832 | data order seed: 7360256
task_output_path: /tmp/mocap6/test-model=FiniteTopicModel+DiagGauss-ECovMat=1*eye/3
1.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.960889382e+00 |
2.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.812954811e+00 | Ndiff 106.901
3.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.775678774e+00 | Ndiff 68.748
4.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.760183281e+00 | Ndiff 29.861
5.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.752879371e+00 | Ndiff 25.952
6.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.749282461e+00 | Ndiff 24.923
7.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.741353570e+00 | Ndiff 30.374
8.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.734628562e+00 | Ndiff 12.783
9.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.733089112e+00 | Ndiff 9.680
10.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.729618996e+00 | Ndiff 11.796
11.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.728491286e+00 | Ndiff 3.954
12.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.728005826e+00 | Ndiff 4.496
13.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.727627474e+00 | Ndiff 2.491
14.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.727448628e+00 | Ndiff 1.857
15.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.727142224e+00 | Ndiff 2.028
16.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.726427129e+00 | Ndiff 5.899
17.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.724227916e+00 | Ndiff 9.490
18.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.723804571e+00 | Ndiff 3.002
19.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.723565436e+00 | Ndiff 2.800
20.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.723446675e+00 | Ndiff 2.095
21.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.723273245e+00 | Ndiff 2.483
22.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.722684880e+00 | Ndiff 3.864
23.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.721978561e+00 | Ndiff 2.712
24.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.721938966e+00 | Ndiff 0.670
25.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.721935848e+00 | Ndiff 0.248
26.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.721934654e+00 | Ndiff 0.148
27.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.721933859e+00 | Ndiff 0.112
28.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.721932594e+00 | Ndiff 0.086
29.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.721925386e+00 | Ndiff 0.125
30.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.721787282e+00 | Ndiff 0.511
31.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.721646191e+00 | Ndiff 0.232
32.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.721534458e+00 | Ndiff 0.503
33.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.721204789e+00 | Ndiff 0.529
34.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.721199428e+00 | Ndiff 0.232
35.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.721197505e+00 | Ndiff 0.160
36.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.721196629e+00 | Ndiff 0.113
37.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.721196193e+00 | Ndiff 0.092
38.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.721195962e+00 | Ndiff 0.076
39.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.721195834e+00 | Ndiff 0.064
40.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.721195760e+00 | Ndiff 0.053
41.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.721195715e+00 | Ndiff 0.045
42.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.721195687e+00 | Ndiff 0.038
43.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.721195668e+00 | Ndiff 0.032
44.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.721195656e+00 | Ndiff 0.028
45.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.721195648e+00 | Ndiff 0.026
46.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.721195643e+00 | Ndiff 0.023
47.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.721195639e+00 | Ndiff 0.020
48.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.721195636e+00 | Ndiff 0.018
49.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.721195634e+00 | Ndiff 0.016
50.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.721195632e+00 | Ndiff 0.014
51.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.721195631e+00 | Ndiff 0.012
52.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.721195631e+00 | Ndiff 0.011
53.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.721195630e+00 | Ndiff 0.009
54.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.721195630e+00 | Ndiff 0.008
55.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.721195629e+00 | Ndiff 0.007
56.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.721195629e+00 | Ndiff 0.006
57.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.721195629e+00 | Ndiff 0.005
58.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.721195629e+00 | Ndiff 0.005
59.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.721195629e+00 | Ndiff 0.004
60.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.721195629e+00 | Ndiff 0.003
61.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.721195629e+00 | Ndiff 0.003
62.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.721195628e+00 | Ndiff 0.003
63.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.721195628e+00 | Ndiff 0.002
64.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.721195628e+00 | Ndiff 0.002
65.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.721195628e+00 | Ndiff 0.002
66.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.721195628e+00 | Ndiff 0.001
67.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.721195628e+00 | Ndiff 0.001
68.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.721195628e+00 | Ndiff 0.001
69.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.721195628e+00 | Ndiff 0.001
70.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.721195628e+00 | Ndiff 0.001
71.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.721195628e+00 | Ndiff 0.001
72.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.721195628e+00 | Ndiff 0.001
73.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.721195628e+00 | Ndiff 0.001
74.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.721195628e+00 | Ndiff 0.000
75.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.721195628e+00 | Ndiff 0.000
76.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.721195628e+00 | Ndiff 0.000
77.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.721195628e+00 | Ndiff 0.000
78.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.721195628e+00 | Ndiff 0.000
79.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.721195628e+00 | Ndiff 0.000
80.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.721195628e+00 | Ndiff 0.000
81.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.721195628e+00 | Ndiff 0.000
82.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.721195628e+00 | Ndiff 0.000
83.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.721195628e+00 | Ndiff 0.000
84.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.721195628e+00 | Ndiff 0.000
85.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.721195628e+00 | Ndiff 0.000
... done. converged.
```

We’ll take the best of 3 independent inits (‘tasks’)

```
hdp_topic_model, hdp_info_dict = bnpy.run(
dataset, 'HDPTopicModel', 'DiagGauss', 'memoVB',
output_path='/tmp/mocap6/test-model=HDPTopicModel+DiagGauss-ECovMat=1*eye/',
nLap=nLap, nTask=3, nBatch=1, convergeThr=0.0001,
gamma=gamma, alpha=alpha,
sF=sF, ECovMat=ECovMat,
K=K, initname='randexamples',
moves='shuffle',
)
```

Out:

```
Dataset Summary:
GroupXData
total size: 6 units
batch size: 6 units
num. batches: 1
Allocation Model: HDP model with K=0 active comps. gamma=5.00. alpha=0.25
Obs. Data Model: Gaussian with diagonal covariance.
Obs. Data Prior: independent Gauss-Wishart prior on each dimension
Wishart params
nu = 14 ...
beta = [ 12 12] ...
Expectations
E[ mean[k]] =
[ 0 0] ...
E[ covar[k]] =
[[1. 0.]
[0. 1.]] ...
Initialization:
initname = randexamples
K = 10 (number of clusters)
seed = 1607680
elapsed_time: 0.0 sec
Learn Alg: memoVB | task 1/3 | alg. seed: 1607680 | data order seed: 8541952
task_output_path: /tmp/mocap6/test-model=HDPTopicModel+DiagGauss-ECovMat=1*eye/1
1.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.892295970e+00 |
2.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.787474069e+00 | Ndiff 167.893
3.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.738420912e+00 | Ndiff 108.155
4.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.728232794e+00 | Ndiff 36.020
5.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.724249654e+00 | Ndiff 78.033
6.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.721009176e+00 | Ndiff 87.093
7.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.717815642e+00 | Ndiff 110.105
8.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.716133498e+00 | Ndiff 17.207
9.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.715152039e+00 | Ndiff 108.292
10.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.714666091e+00 | Ndiff 3.784
11.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.714242891e+00 | Ndiff 3.528
12.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.713537978e+00 | Ndiff 8.000
13.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.710603627e+00 | Ndiff 35.132
14.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.708700954e+00 | Ndiff 16.257
15.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.706776744e+00 | Ndiff 75.015
16.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.703666205e+00 | Ndiff 42.738
17.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.700832620e+00 | Ndiff 27.477
18.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.699218948e+00 | Ndiff 23.414
19.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.698514238e+00 | Ndiff 52.198
20.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.698213092e+00 | Ndiff 9.303
21.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.698031745e+00 | Ndiff 6.076
22.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.697593507e+00 | Ndiff 6.353
23.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.697312701e+00 | Ndiff 5.777
24.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.697000999e+00 | Ndiff 5.781
25.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.696799733e+00 | Ndiff 6.540
26.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.696450679e+00 | Ndiff 8.455
27.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.695590334e+00 | Ndiff 12.813
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137.000/200 after 5 sec. | 242.0 MiB | K 10 | loss 3.659487153e+00 | Ndiff 0.001
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170.000/200 after 6 sec. | 242.0 MiB | K 10 | loss 3.659487153e+00 | Ndiff 0.000
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172.000/200 after 6 sec. | 242.0 MiB | K 10 | loss 3.659487153e+00 | Ndiff 0.000
173.000/200 after 6 sec. | 242.0 MiB | K 10 | loss 3.659487153e+00 | Ndiff 0.000
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176.000/200 after 6 sec. | 242.0 MiB | K 10 | loss 3.659487153e+00 | Ndiff 0.000
... done. converged.
Learn Alg: memoVB | task 2/3 | alg. seed: 6454144 | data order seed: 7673856
task_output_path: /tmp/mocap6/test-model=HDPTopicModel+DiagGauss-ECovMat=1*eye/2
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69.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.667639812e+00 | Ndiff 1.005
70.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.667640267e+00 | Ndiff 0.876
71.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.667640685e+00 | Ndiff 0.763
72.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.667641052e+00 | Ndiff 0.665
73.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.667641372e+00 | Ndiff 0.579
74.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.667641652e+00 | Ndiff 0.505
75.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.667641898e+00 | Ndiff 0.441
76.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.667642118e+00 | Ndiff 0.385
77.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.667642313e+00 | Ndiff 0.337
78.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.667642488e+00 | Ndiff 0.295
79.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.667642644e+00 | Ndiff 0.259
80.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.667642785e+00 | Ndiff 0.227
81.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.667642911e+00 | Ndiff 0.199
82.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.667643024e+00 | Ndiff 0.175
83.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.667643126e+00 | Ndiff 0.154
84.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.667643218e+00 | Ndiff 0.136
85.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.667643300e+00 | Ndiff 0.119
86.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.667643374e+00 | Ndiff 313.637
87.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.667643527e+00 | Ndiff 0.101
88.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.667643638e+00 | Ndiff 284.695
89.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.667643784e+00 | Ndiff 0.082
90.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.667643880e+00 | Ndiff 0.071
91.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.667643942e+00 | Ndiff 0.061
92.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.667643990e+00 | Ndiff 0.054
93.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.667644030e+00 | Ndiff 0.047
94.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.667644064e+00 | Ndiff 0.042
95.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.667644095e+00 | Ndiff 0.037
96.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.667644121e+00 | Ndiff 0.033
97.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.667644145e+00 | Ndiff 0.029
98.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.667644166e+00 | Ndiff 0.025
99.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.667644184e+00 | Ndiff 0.023
100.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.667644201e+00 | Ndiff 0.020
101.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.667644215e+00 | Ndiff 0.018
102.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.667644228e+00 | Ndiff 0.016
103.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.667644240e+00 | Ndiff 0.014
104.000/200 after 4 sec. | 242.0 MiB | K 10 | loss 3.667644250e+00 | Ndiff 0.012
105.000/200 after 4 sec. | 242.0 MiB | K 10 | loss 3.667644259e+00 | Ndiff 0.011
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107.000/200 after 4 sec. | 242.0 MiB | K 10 | loss 3.667644274e+00 | Ndiff 0.009
108.000/200 after 4 sec. | 242.0 MiB | K 10 | loss 3.667644281e+00 | Ndiff 0.008
109.000/200 after 4 sec. | 242.0 MiB | K 10 | loss 3.667644286e+00 | Ndiff 0.007
110.000/200 after 4 sec. | 242.0 MiB | K 10 | loss 3.667644292e+00 | Ndiff 0.006
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112.000/200 after 4 sec. | 242.0 MiB | K 10 | loss 3.667644300e+00 | Ndiff 0.005
113.000/200 after 4 sec. | 242.0 MiB | K 10 | loss 3.667644304e+00 | Ndiff 0.004
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118.000/200 after 4 sec. | 242.0 MiB | K 10 | loss 3.667644316e+00 | Ndiff 0.002
119.000/200 after 4 sec. | 242.0 MiB | K 10 | loss 3.667644318e+00 | Ndiff 0.002
120.000/200 after 4 sec. | 242.0 MiB | K 10 | loss 3.667644320e+00 | Ndiff 0.002
121.000/200 after 4 sec. | 242.0 MiB | K 10 | loss 3.667644321e+00 | Ndiff 0.002
122.000/200 after 4 sec. | 242.0 MiB | K 10 | loss 3.667644322e+00 | Ndiff 0.001
123.000/200 after 4 sec. | 242.0 MiB | K 10 | loss 3.667644323e+00 | Ndiff 0.001
124.000/200 after 4 sec. | 242.0 MiB | K 10 | loss 3.667644324e+00 | Ndiff 0.001
125.000/200 after 4 sec. | 242.0 MiB | K 10 | loss 3.667644325e+00 | Ndiff 0.001
126.000/200 after 4 sec. | 242.0 MiB | K 10 | loss 3.667644326e+00 | Ndiff 0.001
127.000/200 after 4 sec. | 242.0 MiB | K 10 | loss 3.667644327e+00 | Ndiff 0.001
128.000/200 after 4 sec. | 242.0 MiB | K 10 | loss 3.667644327e+00 | Ndiff 0.001
129.000/200 after 4 sec. | 242.0 MiB | K 10 | loss 3.667644328e+00 | Ndiff 0.001
130.000/200 after 4 sec. | 242.0 MiB | K 10 | loss 3.667644328e+00 | Ndiff 0.001
131.000/200 after 4 sec. | 242.0 MiB | K 10 | loss 3.667644329e+00 | Ndiff 0.000
132.000/200 after 4 sec. | 242.0 MiB | K 10 | loss 3.667644329e+00 | Ndiff 0.000
133.000/200 after 4 sec. | 242.0 MiB | K 10 | loss 3.667644330e+00 | Ndiff 0.000
134.000/200 after 4 sec. | 242.0 MiB | K 10 | loss 3.667644330e+00 | Ndiff 0.000
135.000/200 after 4 sec. | 242.0 MiB | K 10 | loss 3.667644330e+00 | Ndiff 0.000
136.000/200 after 4 sec. | 242.0 MiB | K 10 | loss 3.667644330e+00 | Ndiff 0.000
137.000/200 after 5 sec. | 242.0 MiB | K 10 | loss 3.667644331e+00 | Ndiff 0.000
138.000/200 after 5 sec. | 242.0 MiB | K 10 | loss 3.667644331e+00 | Ndiff 0.000
139.000/200 after 5 sec. | 242.0 MiB | K 10 | loss 3.667644331e+00 | Ndiff 0.000
140.000/200 after 5 sec. | 242.0 MiB | K 10 | loss 3.667644331e+00 | Ndiff 0.000
141.000/200 after 5 sec. | 242.0 MiB | K 10 | loss 3.667644331e+00 | Ndiff 0.000
142.000/200 after 5 sec. | 242.0 MiB | K 10 | loss 3.667644331e+00 | Ndiff 0.000
143.000/200 after 5 sec. | 242.0 MiB | K 10 | loss 3.667644331e+00 | Ndiff 0.000
144.000/200 after 5 sec. | 242.0 MiB | K 10 | loss 3.667644331e+00 | Ndiff 0.000
... done. converged.
Learn Alg: memoVB | task 3/3 | alg. seed: 6168832 | data order seed: 7360256
task_output_path: /tmp/mocap6/test-model=HDPTopicModel+DiagGauss-ECovMat=1*eye/3
1.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.961512682e+00 |
2.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.813561471e+00 | Ndiff 163.068
3.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.776258956e+00 | Ndiff 240.881
4.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.760790644e+00 | Ndiff 282.557
5.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.753457390e+00 | Ndiff 25.948
6.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.749857849e+00 | Ndiff 24.919
7.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.741928990e+00 | Ndiff 30.360
8.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.735207406e+00 | Ndiff 12.788
9.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.733663979e+00 | Ndiff 9.696
10.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.730193088e+00 | Ndiff 14.819
11.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.729061704e+00 | Ndiff 3.956
12.000/200 after 0 sec. | 242.0 MiB | K 10 | loss 3.728573893e+00 | Ndiff 4.488
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15.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.727711958e+00 | Ndiff 2.028
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18.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.724377310e+00 | Ndiff 2.981
19.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.724107513e+00 | Ndiff 103.930
20.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.723983831e+00 | Ndiff 2.098
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22.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.723203621e+00 | Ndiff 3.888
23.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.722513644e+00 | Ndiff 2.643
24.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.722476542e+00 | Ndiff 0.654
25.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.722473498e+00 | Ndiff 0.245
26.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.722472317e+00 | Ndiff 0.147
27.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.722471519e+00 | Ndiff 0.111
28.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.722470216e+00 | Ndiff 0.086
29.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.722462530e+00 | Ndiff 0.129
30.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.722315355e+00 | Ndiff 0.523
31.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.722183071e+00 | Ndiff 0.218
32.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.722065842e+00 | Ndiff 0.515
33.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.721742168e+00 | Ndiff 0.515
34.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.721736951e+00 | Ndiff 0.230
35.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.721735062e+00 | Ndiff 0.159
36.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.721734200e+00 | Ndiff 0.112
37.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.721733770e+00 | Ndiff 0.091
38.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.721733543e+00 | Ndiff 0.076
39.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.721733417e+00 | Ndiff 0.063
40.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.721733344e+00 | Ndiff 0.053
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42.000/200 after 1 sec. | 242.0 MiB | K 10 | loss 3.721733271e+00 | Ndiff 0.037
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45.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.721733233e+00 | Ndiff 0.025
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50.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.721733218e+00 | Ndiff 0.014
51.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.721733217e+00 | Ndiff 0.012
52.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.721733216e+00 | Ndiff 0.010
53.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.721733215e+00 | Ndiff 0.009
54.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.721733215e+00 | Ndiff 0.008
55.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.721733215e+00 | Ndiff 0.007
56.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.721733215e+00 | Ndiff 0.006
57.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.721733214e+00 | Ndiff 0.005
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59.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.721733214e+00 | Ndiff 0.004
60.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.721733214e+00 | Ndiff 0.003
61.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.721733214e+00 | Ndiff 0.003
62.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.721733214e+00 | Ndiff 0.003
63.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.721733214e+00 | Ndiff 0.002
64.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.721733214e+00 | Ndiff 0.002
65.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.721733214e+00 | Ndiff 0.002
66.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.721733214e+00 | Ndiff 0.001
67.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.721733214e+00 | Ndiff 0.001
68.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.721733214e+00 | Ndiff 0.001
69.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.721733214e+00 | Ndiff 0.001
70.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.721733214e+00 | Ndiff 0.001
71.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.721733214e+00 | Ndiff 0.001
72.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.721733214e+00 | Ndiff 0.001
73.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.721733214e+00 | Ndiff 0.001
74.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.721733214e+00 | Ndiff 0.000
75.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.721733214e+00 | Ndiff 0.000
76.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.721733214e+00 | Ndiff 0.000
77.000/200 after 2 sec. | 242.0 MiB | K 10 | loss 3.721733214e+00 | Ndiff 0.000
78.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.721733214e+00 | Ndiff 0.000
79.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.721733214e+00 | Ndiff 0.000
80.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.721733214e+00 | Ndiff 0.000
81.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.721733214e+00 | Ndiff 0.000
82.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.721733214e+00 | Ndiff 0.000
83.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.721733214e+00 | Ndiff 0.000
84.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.721733214e+00 | Ndiff 0.000
85.000/200 after 3 sec. | 242.0 MiB | K 10 | loss 3.721733214e+00 | Ndiff 0.000
... done. converged.
```

We’ll notice that the simple mixture performs noticeably worse than the more flexible models that allow group-specific cluster weights

```
pylab.figure()
pylab.plot(
mix_info_dict['lap_history'],
mix_info_dict['loss_history'], 'k--',
label='mix + diag gauss')
pylab.plot(
finite_info_dict['lap_history'],
finite_info_dict['loss_history'], 'm.-',
label='LDA + diag gauss')
pylab.plot(
hdp_info_dict['lap_history'],
hdp_info_dict['loss_history'], 'r.-',
label='HDP + diag gauss')
pylab.legend(loc='upper right')
pylab.xlabel('num. laps')
pylab.ylabel('loss')
pylab.xlim([0, 200]) # avoid early iterations
pylab.ylim([3.5, 3.7]) # handpicked
pylab.draw()
pylab.tight_layout()
```

```
np.set_printoptions(precision=3, suppress=1, linewidth=200)
## Compute approx. posterior parameter 'resp' for each example
# resp : 2D array, n_examples x n_clusters
# resp[n] defines Discrete probability of using clusters to explain each example
LP = mix_model.calc_local_params(dataset)
resp_NK = LP['resp']
## Compute the per-sequence average usage.
avg_resp_DK = np.zeros((dataset.nDoc, K))
for d in range(dataset.nDoc):
start = dataset.doc_range[d]
stop = dataset.doc_range[d+1]
avg_resp_DK[d] = np.mean(resp_NK[start:stop], axis=0)
print("Baseline mixture model: per-sequence average cluster usage")
print(avg_resp_DK)
nnz = np.sum(avg_resp_DK < 0.001)
print("Sparsity level: %d/%d entries close-to-zero" % (
nnz, avg_resp_DK.size))
print("")
```

Out:

```
Baseline mixture model: per-sequence average cluster usage
[[0.045 0.14 0.193 0.086 0.097 0.088 0.085 0.057 0.14 0.07 ]
[0.014 0.245 0.081 0.114 0.098 0.169 0. 0.035 0.166 0.077]
[0.085 0.125 0.232 0.071 0. 0.143 0.037 0.056 0.149 0.103]
[0.065 0.053 0.045 0.085 0.051 0.102 0.123 0.109 0.316 0.052]
[0.097 0.001 0.283 0.094 0.07 0.125 0.088 0.049 0.133 0.06 ]
[0.211 0.004 0.216 0.069 0. 0.068 0.034 0.048 0.234 0.115]]
Sparsity level: 4/60 entries close-to-zero
```

```
# Compute approx. posterior parameter 'theta' for each document
LP = finite_model.calc_local_params(dataset)
resp_NK = LP['resp']
avg_resp_DK = np.zeros((dataset.nDoc, K))
for d in range(dataset.nDoc):
start = dataset.doc_range[d]
stop = dataset.doc_range[d+1]
avg_resp_DK[d] = np.mean(resp_NK[start:stop], axis=0)
print("LDA mixed membership model: per-sequence average cluster usage")
print(avg_resp_DK)
nnz = np.sum(avg_resp_DK < 0.001)
print("Sparsity level: %d/%d entries close-to-zero" % (
nnz, avg_resp_DK.size))
print("")
# theta : 2D array, n_docs x n_clusters
# theta[d] defines Dirichlet parameters for d-th document
theta_DK = LP['theta']
# Compute expected probabilities
E_pi_DK = theta_DK / np.sum(theta_DK, axis=1)[:,np.newaxis]
print("LDA mixed membership model: per-sequence cluster probabilities")
print(E_pi_DK)
```

Out:

```
LDA mixed membership model: per-sequence average cluster usage
[[0.126 0.168 0.181 0.085 0.106 0.083 0.05 0.048 0. 0.154]
[0.063 0.296 0.057 0.111 0.117 0.158 0. 0.024 0. 0.174]
[0.161 0.144 0.224 0.063 0.008 0.123 0. 0.036 0. 0.241]
[0. 0.043 0.027 0.081 0.058 0.101 0.068 0.043 0.502 0.078]
[0. 0. 0.283 0.091 0.077 0.124 0.077 0.045 0.201 0.103]
[0.175 0. 0.206 0.067 0. 0.067 0. 0.041 0.22 0.223]]
Sparsity level: 11/60 entries close-to-zero
LDA mixed membership model: per-sequence cluster probabilities
[[0.126 0.168 0.181 0.085 0.106 0.083 0.05 0.048 0. 0.154]
[0.063 0.296 0.057 0.111 0.117 0.158 0. 0.024 0. 0.174]
[0.161 0.144 0.224 0.063 0.008 0.123 0. 0.036 0. 0.241]
[0. 0.043 0.027 0.081 0.058 0.101 0.068 0.043 0.502 0.078]
[0. 0. 0.282 0.091 0.077 0.124 0.077 0.045 0.201 0.103]
[0.175 0. 0.206 0.067 0. 0.067 0. 0.041 0.22 0.223]]
```

**Total running time of the script:** ( 0 minutes 35.172 seconds)