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

# In[1]:


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


# # Scores (`pyannote.core.scores.Scores`)

# In[2]:


from pyannote.core import Scores


# **`Scores`** instances are used to describe classification scores.
# For instance, one can use a **`Scores`** to store the result of speaker identification approach applied on an episode of *The Big Bang Theory* TV series.

# In[3]:


scores = Scores(
    uri='TheBigBangTheory.Season01.Episode01', 
    modality='speaker'
)


# For instance, to represent a dialogue between Penny and Leonard, we could do the following:

# In[4]:


from pyannote.core import Segment
scores[Segment(3, 5), '_', 'Penny'] = 8
scores[Segment(3, 5), '_', 'Leonard'] = 0.15
scores[Segment(3, 5), '_', 'Sheldon'] = 0.05
scores[Segment(5.5, 7), '_', 'Penny'] = 0.4
scores[Segment(5.5, 7), '_', 'Leonard'] = 0.5
scores[Segment(5.5, 7), '_', 'Sheldon'] = 0.1
scores[Segment(8, 10), '_', 'Penny'] = 0.4
scores[Segment(8, 10), '_', 'Leonard'] = 0.25
scores[Segment(8, 10), '_', 'Sheldon'] = -12
scores


# In[5]:


scores.to_annotation()


# In[6]:


from pyannote.core import notebook
subplot(211)
notebook(scores, time=False)
subplot(212)
notebook(scores.to_annotation(), legend=False)