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https://github.com/gsi-upm/senpy
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Better centroid conversion
Also added **simple** tests for backward and forward conversion. In future versions we should add thorough tests. Should close gsi-upm/senpy#31
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senpy/plugins/conversion/emotion/__init__.py
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senpy/plugins/conversion/emotion/__init__.py
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@ -44,32 +44,27 @@ class CentroidConversion(EmotionConversionPlugin):
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self.neutralPoints[i] = self.get("neutralValue", 0)
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def _forward_conversion(self, original):
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"""Sum the VAD value of all categories found weighted by intensity.
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Intensities are scaled by onyx:maxIntensityValue if it is present, else maxIntensityValue is assumed to be one.
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Emotion entries that do not have onxy:hasEmotionIntensity specified are assumed to have maxIntensityValue.
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Emotion entries that do not have onyx:hasEmotionCategory specified are ignored."""
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"""Sum the VAD value of all categories found weighted by intensity.
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Intensities are scaled by onyx:maxIntensityValue if it is present, else maxIntensityValue
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is assumed to be one. Emotion entries that do not have onxy:hasEmotionIntensity specified
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are assumed to have maxIntensityValue. Emotion entries that do not have
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onyx:hasEmotionCategory specified are ignored."""
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res = Emotion()
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maxIntensity = float(original.get("onyx__maxIntensityValue",1))
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neutralPoint = self.get("origin",None)
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maxIntensity = float(original.get("onyx:maxIntensityValue", 1))
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for e in original.onyx__hasEmotion:
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category = e.get("onyx__hasEmotionCategory", None)
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if category is None:
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category = e.get("onyx:hasEmotionCategory", None)
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if not category:
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continue
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intensity = e.get("onyx__hasEmotionIntensity",maxIntensity)/maxIntensity
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if intensity == 0:
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intensity = e.get("onyx:hasEmotionIntensity", maxIntensity) / maxIntensity
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if not intensity:
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continue
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centoid = self.centroids.get(category,None)
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centroid = self.centroids.get(category, None)
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if centroid:
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for dim, value in centroid.items():
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if neutralPoint:
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value -= neutralPoint[dim]
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try:
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res[dim] += value * intensity
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except KeyError:
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res[dim] = value * intensity
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if neutralPoint:
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for dim in res:
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res[dim] += neutralPoint[dim]
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neutral = self.neutralPoints[dim]
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if dim not in res:
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res[dim] = 0
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res[dim] += (value - neutral) * intensity + neutral
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return res
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def _backwards_conversion(self, original):
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@ -88,6 +83,7 @@ class CentroidConversion(EmotionConversionPlugin):
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emotion = min(centroids, key=lambda x: distance(centroids[x]))
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result = Emotion(onyx__hasEmotionCategory=emotion)
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result.onyx__algorithmConfidence = distance(centroids[emotion])
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return result
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def convert(self, emotionSet, fromModel, toModel, params):
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@ -1,6 +1,6 @@
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---
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name: Ekman2FSRE
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module: senpy.plugins.conversion.centroids
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module: senpy.plugins.conversion.emotion.centroids
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description: Plugin to convert emotion sets from Ekman to VAD
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version: 0.1
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# No need to specify onyx:doesConversion because centroids.py adds it automatically from centroids_direction
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@ -1,6 +1,6 @@
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---
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name: Ekman2PAD
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module: senpy.plugins.conversion.centroids
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module: senpy.plugins.conversion.emotion.centroids
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description: Plugin to convert emotion sets from Ekman to VAD
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version: 0.1
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# No need to specify onyx:doesConversion because centroids.py adds it automatically from centroids_direction
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@ -6,8 +6,9 @@ import shutil
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import tempfile
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from unittest import TestCase
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from senpy.models import Results, Entry
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from senpy.models import Results, Entry, EmotionSet, Emotion
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from senpy.plugins import SentimentPlugin, ShelfMixin
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from senpy.plugins.conversion.emotion.centroids import CentroidConversion
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class ShelfDummyPlugin(SentimentPlugin, ShelfMixin):
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@ -152,3 +153,52 @@ class PluginsTest(TestCase):
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}
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})
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assert 'example' in a.extra_params
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def test_conversion_centroids(self):
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info = {
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"name": "CentroidTest",
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"description": "Centroid test",
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"version": 0,
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"centroids": {
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"c1": {"V1": 0.5,
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"V2": 0.5},
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"c2": {"V1": -0.5,
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"V2": 0.5},
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"c3": {"V1": -0.5,
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"V2": -0.5},
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"c4": {"V1": 0.5,
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"V2": -0.5}},
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"aliases": {
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"V1": "X-dimension",
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"V2": "Y-dimension"
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},
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"centroids_direction": ["emoml:big6", "emoml:fsre-dimensions"]
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}
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c = CentroidConversion(info)
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es1 = EmotionSet()
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e1 = Emotion()
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e1.onyx__hasEmotionCategory = "c1"
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es1.onyx__hasEmotion.append(e1)
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res = c._forward_conversion(es1)
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assert res["X-dimension"] == 0.5
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assert res["Y-dimension"] == 0.5
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e2 = Emotion()
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e2.onyx__hasEmotionCategory = "c2"
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es1.onyx__hasEmotion.append(e2)
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res = c._forward_conversion(es1)
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assert res["X-dimension"] == 0
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assert res["Y-dimension"] == 1
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e = Emotion()
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e["X-dimension"] = -0.2
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e["Y-dimension"] = -0.3
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res = c._backwards_conversion(e)
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assert res["onyx:hasEmotionCategory"] == "c3"
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e = Emotion()
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e["X-dimension"] = -0.2
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e["Y-dimension"] = 0.3
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res = c._backwards_conversion(e)
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assert res["onyx:hasEmotionCategory"] == "c2"
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