centroids.py 2.91 KB
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from senpy.plugins import EmotionConversionPlugin
from senpy.models import EmotionSet, Emotion, Error

import logging
logger = logging.getLogger(__name__)


class CentroidConversion(EmotionConversionPlugin):
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    def __init__(self, info):
        if 'centroids' not in info:
            raise Error('Centroid conversion plugins should provide '
                        'the centroids in their senpy file')
        if 'onyx:doesConversion' not in info:
            if 'centroids_direction' not in info:
                raise Error('Please, provide centroids direction')

            cf, ct = info['centroids_direction']
            info['onyx:doesConversion'] = [{
                'onyx:conversionFrom': cf,
                'onyx:conversionTo': ct
            }, {
                'onyx:conversionFrom': ct,
                'onyx:conversionTo': cf
            }]

        if 'aliases' in info:
            aliases = info['aliases']
            ncentroids = {}
            for k1, v1 in info['centroids'].items():
                nv1 = {}
                for k2, v2 in v1.items():
                    nv1[aliases.get(k2, k2)] = v2
                ncentroids[aliases.get(k1, k1)] = nv1
            info['centroids'] = ncentroids
        super(CentroidConversion, self).__init__(info)
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    def _forward_conversion(self, original):
        """Sum the VAD value of all categories found."""
        res = Emotion()
        for e in original.onyx__hasEmotion:
            category = e.onyx__hasEmotionCategory
            if category in self.centroids:
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                for dim, value in self.centroids[category].items():
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                    try:
                        res[dim] += value
                    except Exception:
                        res[dim] = value
        return res

    def _backwards_conversion(self, original):
        """Find the closest category"""
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        dimensions = set(c.keys() for c in centroids.values())
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        neutralPoint = self.get("origin", None)
        neutralPoint = {k:neutralPoint[k] if k in neturalPoint else 0}
        
        def distance(centroid):
            return sum((centroid.get(k, neutralPoint[k]) - original.get(k, neutralPoint[k]))**2 for k in dimensions)
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        emotion = min(centroids, key=lambda x: distance(centroids[x])
                
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        result = Emotion(onyx__hasEmotionCategory=emotion)
        return result

    def convert(self, emotionSet, fromModel, toModel, params):

        cf, ct = self.centroids_direction
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        logger.debug(
            '{}\n{}\n{}\n{}'.format(emotionSet, fromModel, toModel, params))
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        e = EmotionSet()
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        if fromModel == cf and toModel == ct:
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            e.onyx__hasEmotion.append(self._forward_conversion(emotionSet))
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        elif fromModel == ct and toModel == cf:
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            for i in emotionSet.onyx__hasEmotion:
                e.onyx__hasEmotion.append(self._backwards_conversion(i))
        else:
            raise Error('EMOTION MODEL NOT KNOWN')
        yield e