#!/usr/bin/env python
# coding: utf-8

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get_ipython().run_line_magic('pylab', 'inline')


# # Diarization evaluation metrics

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from pyannote.core import Annotation, Segment


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reference = Annotation()
reference[Segment(0, 10)] = 'A'
reference[Segment(12, 20)] = 'B'
reference[Segment(24, 27)] = 'A'
reference[Segment(30, 40)] = 'C'
reference


# In[21]:


hypothesis = Annotation()
hypothesis[Segment(2, 13)] = 'a'
hypothesis[Segment(13, 14)] = 'd'
hypothesis[Segment(14, 20)] = 'b'
hypothesis[Segment(22, 38)] = 'c'
hypothesis[Segment(38, 40)] = 'd'
hypothesis


# ## Diarization error rate

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from pyannote.metrics.diarization import DiarizationErrorRate
diarizationErrorRate = DiarizationErrorRate()
print("DER = {0:.3f}".format(diarizationErrorRate(reference, hypothesis, uem=Segment(0, 40))))


# ### Optimal mapping

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reference


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hypothesis


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diarizationErrorRate.optimal_mapping(reference, hypothesis)


# ### Details

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diarizationErrorRate(reference, hypothesis, detailed=True, uem=Segment(0, 40))


# ## Clusters purity and coverage

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from pyannote.metrics.diarization import DiarizationPurity
purity = DiarizationPurity()
print("Purity = {0:.3f}".format(purity(reference, hypothesis, uem=Segment(0, 40))))


# In[28]:


from pyannote.metrics.diarization import DiarizationCoverage
coverage = DiarizationCoverage()
print("Coverage = {0:.3f}".format(coverage(reference, hypothesis, uem=Segment(0, 40))))