Commit 453b9f32 authored by J. Fernando Sánchez's avatar J. Fernando Sánchez

Fixed bugs in Ekman2VAD

parent 5fb858f5
......@@ -13,6 +13,7 @@ from .api import API_PARAMS, NIF_PARAMS, parse_params
from threading import Thread
import os
import copy
import fnmatch
import inspect
import sys
......@@ -180,7 +181,7 @@ class Senpy(object):
newentries = []
for i in resp.entries:
if output == "full":
newemotions = i.emotions.copy()
newemotions = copy.copy(i.emotions)
else:
newemotions = []
for j in i.emotions:
......
......@@ -10,24 +10,26 @@ import math
class WNA2VAD(EmotionConversionPlugin):
def _ekman_to_vad(self, ekmanSet):
potency = 0
"""Sum the VAD value of all categories found."""
valence = 0
arousal = 0
dominance = 0
for e in ekmanSet.onyx__hasEmotion:
category = e.onyx__hasEmotionCategory
centroid = self.centroids[category]
potency += centroid['V']
valence += centroid['V']
arousal += centroid['A']
dominance += centroid['D']
e = Emotion({'emoml:potency': potency,
e = Emotion({'emoml:valence': valence,
'emoml:arousal': arousal,
'emoml:dominance': dominance})
'emoml:potency': dominance})
return e
def _vad_to_ekman(self, VADEmotion):
"""Find the closest category"""
V = VADEmotion['emoml:valence']
A = VADEmotion['emoml:potency']
D = VADEmotion['emoml:dominance']
A = VADEmotion['emoml:arousal']
D = VADEmotion['emoml:potency']
emotion = ''
value = 10000000000000000000000.0
for state in self.centroids:
......@@ -50,7 +52,7 @@ class WNA2VAD(EmotionConversionPlugin):
e.onyx__hasEmotion.append(self._ekman_to_vad(emotionSet))
elif fromModel == 'emoml:fsre-dimensions':
for i in emotionSet.onyx__hasEmotion:
e.onyx__hasEmotion.append(self._vad_to_ekman(e))
e.onyx__hasEmotion.append(self._vad_to_ekman(i))
else:
raise Error('EMOTION MODEL NOT KNOWN')
yield e
......@@ -7,7 +7,7 @@ onyx:doesConversion:
- onyx:conversionFrom: emoml:big6
onyx:conversionTo: emoml:fsre-dimensions
- onyx:conversionFrom: emoml:fsre-dimensions
onyx:conversionTo: wna:WNAModel
onyx:conversionTo: emoml:big6
centroids:
emoml:big6anger:
A: 6.95
......@@ -31,5 +31,5 @@ centroids:
V: 2.21
aliases:
A: emoml:arousal
V: emoml:potency
V: emoml:valence
D: emoml:dominance
\ No newline at end of file
......@@ -9,4 +9,6 @@ test=pytest
ignore = E402
max-line-length = 100
[bdist_wheel]
universal=1
\ No newline at end of file
universal=1
[tool:pytest]
addopts = --cov=senpy --cov-report term-missing
\ No newline at end of file
from __future__ import print_function
import os
from copy import deepcopy
import logging
try:
......@@ -9,7 +10,7 @@ except ImportError:
from functools import partial
from senpy.extensions import Senpy
from senpy.models import Error
from senpy.models import Error, Results, Entry, EmotionSet, Emotion
from flask import Flask
from unittest import TestCase
......@@ -52,6 +53,7 @@ class ExtensionsTest(TestCase):
assert module
import noop
dir(noop)
self.senpy.install_deps()
def test_installing(self):
""" Enabling a plugin """
......@@ -120,3 +122,42 @@ class ExtensionsTest(TestCase):
def test_load_default_plugins(self):
senpy = Senpy(plugin_folder=self.dir, default_plugins=True)
assert len(senpy.plugins) > 1
def test_convert_emotions(self):
self.senpy.activate_all()
plugin = {
'id': 'imaginary',
'onyx:usesEmotionModel': 'emoml:fsre-dimensions'
}
eSet1 = EmotionSet()
eSet1['onyx:hasEmotion'].append(Emotion({
'emoml:arousal': 1,
'emoml:potency': 0,
'emoml:valence': 0
}))
response = Results({
'entries': [Entry({
'text': 'much ado about nothing',
'emotions': [eSet1]
})]
})
params = {'emotionModel': 'emoml:big6',
'conversion': 'full'}
r1 = deepcopy(response)
self.senpy.convert_emotions(r1,
plugin,
params)
assert len(r1.entries[0].emotions) == 2
params['conversion'] = 'nested'
r2 = deepcopy(response)
self.senpy.convert_emotions(r2,
plugin,
params)
assert len(r2.entries[0].emotions) == 1
assert r2.entries[0].emotions[0]['prov:wasDerivedFrom'] == eSet1
params['conversion'] = 'filtered'
r3 = deepcopy(response)
self.senpy.convert_emotions(r3,
plugin,
params)
assert len(r3.entries[0].emotions) == 1
......@@ -143,7 +143,3 @@ class ModelsTest(TestCase):
print(t)
g = rdflib.Graph().parse(data=t, format='turtle')
assert len(g) == len(triples)
def test_convert_emotions(self):
"""It should be possible to convert between different emotion models"""
pass
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