Merge branch '36-estimate-vad'

.gitlab-ci.yml

@@ -84,7 +84,15 @@ deploy:
   only:
     - master
 
-clean_docker :
+push-github:
+  stage: deploy
+  script:
+    - make -e push-github
+  only:
+    - master
+    - triggers
+
+clean :
   stage: clean
   script:
     - make -e clean

Makefile

@@ -12,6 +12,7 @@ DEVPORT=5000
 
 TARNAME=$(NAME)-$(VERSION).tar.gz 
 action="test-${PYMAIN}"
+GITHUB_REPO=git@github.com:gsi-upm/senpy.git
 
 KUBE_CA_PEM_FILE=""
 KUBE_URL=""

senpy/plugins/conversion/emotion/centroids.py

@@ -32,36 +32,58 @@ class CentroidConversion(EmotionConversionPlugin):
                     nv1[aliases.get(k2, k2)] = v2
                 ncentroids[aliases.get(k1, k1)] = nv1
             info['centroids'] = ncentroids
+
         super(CentroidConversion, self).__init__(info)
 
+        self.dimensions = set()
+        for c in self.centroids.values():
+            self.dimensions.update(c.keys())
+        self.neutralPoints = self.get("neutralPoints", dict())
+        if not self.neutralPoints:
+            for i in self.dimensions:
+                self.neutralPoints[i] = self.get("neutralValue", 0)
+
     def _forward_conversion(self, original):
-        """Sum the VAD value of all categories found."""
+        """Sum the VAD value of all categories found weighted by intensity.
+        Intensities are scaled by onyx:maxIntensityValue if it is present, else maxIntensityValue
+        is assumed to be one. Emotion entries that do not have onxy:hasEmotionIntensity specified
+        are assumed to have maxIntensityValue. Emotion entries that do not have
+        onyx:hasEmotionCategory specified are ignored."""
         res = Emotion()
+        maxIntensity = float(original.get("onyx:maxIntensityValue", 1))
         for e in original.onyx__hasEmotion:
-            category = e.onyx__hasEmotionCategory
+            category = e.get("onyx:hasEmotionCategory", None)
-            if category in self.centroids:
+            if not category:
-                for dim, value in self.centroids[category].items():
+                continue
-                    try:
+            intensity = e.get("onyx:hasEmotionIntensity", maxIntensity) / maxIntensity
-                        res[dim] += value
+            if not intensity:
-                    except Exception:
+                continue
-                        res[dim] = value
+            centroid = self.centroids.get(category, None)
+            if centroid:
+                for dim, value in centroid.items():
+                    neutral = self.neutralPoints[dim]
+                    if dim not in res:
+                        res[dim] = 0
+                    res[dim] += (value - neutral) * intensity + neutral
         return res
 
     def _backwards_conversion(self, original):
         """Find the closest category"""
-        dimensions = list(self.centroids.values())[0]
+        centroids = self.centroids
+        neutralPoints = self.neutralPoints
+        dimensions = self.dimensions
 
-        def distance(e1, e2):
+        def distance_k(centroid, original, k):
-            return sum((e1[k] - e2.get(k, 0)) for k in dimensions)
+            # k component of the distance between the value and a given centroid
+            return (centroid.get(k, neutralPoints[k]) - original.get(k, neutralPoints[k]))**2
+
+        def distance(centroid):
+            return sum(distance_k(centroid, original, k) for k in dimensions)
+
+        emotion = min(centroids, key=lambda x: distance(centroids[x]))
 
-        emotion = ''
-        mindistance = 10000000000000000000000.0
-        for state in self.centroids:
-            d = distance(self.centroids[state], original)
-            if d < mindistance:
-                mindistance = d
-                emotion = state
         result = Emotion(onyx__hasEmotionCategory=emotion)
+        result.onyx__algorithmConfidence = distance(centroids[emotion])
         return result
 
     def convert(self, emotionSet, fromModel, toModel, params):

senpy/plugins/conversion/emotion/ekman2fsre.senpy

@@ -1,6 +1,6 @@
 ---
 name: Ekman2FSRE
-module: senpy.plugins.conversion.centroids
+module: senpy.plugins.conversion.emotion.centroids
 description: Plugin to convert emotion sets from Ekman to VAD
 version: 0.1
 # No need to specify onyx:doesConversion because centroids.py adds it automatically from centroids_direction

senpy/plugins/conversion/emotion/ekman2vad.senpy

@@ -1,9 +1,14 @@
 ---
 name: Ekman2PAD
-module: senpy.plugins.conversion.centroids
+module: senpy.plugins.conversion.emotion.centroids
 description: Plugin to convert emotion sets from Ekman to VAD
 version: 0.1
 # No need to specify onyx:doesConversion because centroids.py adds it automatically from centroids_direction
+origin:
+  # Point in VAD space with no emotion (aka Neutral)
+  A: 5.0
+  D: 5.0
+  V: 5.0
 centroids:
   anger:
     A: 6.95
@@ -36,4 +41,4 @@ aliases: # These are aliases for any key in the centroid, to avoid repeating a l
   disgust: emoml:big6disgust
   fear: emoml:big6fear
   happiness: emoml:big6happiness
-  sadness: emoml:big6sadness
+  sadness: emoml:big6sadness

senpy/version.py

@@ -11,7 +11,7 @@ def read_version(versionfile=DEFAULT_FILE):
     try:
         with open(versionfile) as f:
             return f.read().strip()
-    except IOError:
+    except IOError:  # pragma: no cover
         logger.error('Running an unknown version of senpy. Be careful!.')
         return '0.0'
 

tests/test_plugins.py

@@ -6,8 +6,9 @@ import shutil
 import tempfile
 
 from unittest import TestCase
-from senpy.models import Results, Entry
+from senpy.models import Results, Entry, EmotionSet, Emotion
 from senpy.plugins import SentimentPlugin, ShelfMixin
+from senpy.plugins.conversion.emotion.centroids import CentroidConversion
 
 
 class ShelfDummyPlugin(SentimentPlugin, ShelfMixin):
@@ -152,3 +153,52 @@ class PluginsTest(TestCase):
             }
         })
         assert 'example' in a.extra_params
+
+    def test_conversion_centroids(self):
+        info = {
+            "name": "CentroidTest",
+            "description": "Centroid test",
+            "version": 0,
+            "centroids": {
+                "c1": {"V1": 0.5,
+                       "V2": 0.5},
+                "c2": {"V1": -0.5,
+                       "V2": 0.5},
+                "c3": {"V1": -0.5,
+                       "V2": -0.5},
+                "c4": {"V1": 0.5,
+                       "V2": -0.5}},
+            "aliases": {
+                "V1": "X-dimension",
+                "V2": "Y-dimension"
+            },
+            "centroids_direction": ["emoml:big6", "emoml:fsre-dimensions"]
+        }
+        c = CentroidConversion(info)
+
+        es1 = EmotionSet()
+        e1 = Emotion()
+        e1.onyx__hasEmotionCategory = "c1"
+        es1.onyx__hasEmotion.append(e1)
+        res = c._forward_conversion(es1)
+        assert res["X-dimension"] == 0.5
+        assert res["Y-dimension"] == 0.5
+
+        e2 = Emotion()
+        e2.onyx__hasEmotionCategory = "c2"
+        es1.onyx__hasEmotion.append(e2)
+        res = c._forward_conversion(es1)
+        assert res["X-dimension"] == 0
+        assert res["Y-dimension"] == 1
+
+        e = Emotion()
+        e["X-dimension"] = -0.2
+        e["Y-dimension"] = -0.3
+        res = c._backwards_conversion(e)
+        assert res["onyx:hasEmotionCategory"] == "c3"
+
+        e = Emotion()
+        e["X-dimension"] = -0.2
+        e["Y-dimension"] = 0.3
+        res = c._backwards_conversion(e)
+        assert res["onyx:hasEmotionCategory"] == "c2"