class TestPatternSentiment(unittest.TestCase):
def setUp(self):
self.analyzer = PatternAnalyzer()
def test_kind(self):
assert_equal(self.analyzer.kind, CONTINUOUS)
def test_analyze(self):
p1 = "I feel great this morning."
n1 = "This is a terrible car."
p1_result = self.analyzer.analyze(p1)
n1_result = self.analyzer.analyze(n1)
assert_true(p1_result[0] > 0)
assert_true(n1_result[0] < 0)
assert_equal(p1_result.polarity, p1_result[0])
assert_equal(p1_result.subjectivity, p1_result[1])
def test_analyze_assessments(self):
p1 = "I feel great this morning."
n1 = "This is a terrible car."
p1_result = self.analyzer.analyze(p1, keep_assessments=True)
n1_result = self.analyzer.analyze(n1, keep_assessments=True)
p1_assessment = p1_result.assessments[0]
n1_assessment = n1_result.assessments[0]
assert_true(p1_assessment[1] > 0)
assert_true(n1_assessment[1] < 0)
assert_equal(p1_result.polarity, p1_assessment[1])
assert_equal(p1_result.subjectivity, p1_assessment[2])
class TestPatternSentiment(unittest.TestCase):
def setUp(self):
self.analyzer = PatternAnalyzer()
def test_kind(self):
assert_equal(self.analyzer.kind, CONTINUOUS)
def test_analyze(self):
p1 = "I feel great this morning."
n1 = "This is a terrible car."
p1_result = self.analyzer.analyze(p1)
n1_result = self.analyzer.analyze(n1)
assert_true(p1_result[0] > 0)
assert_true(n1_result[0] < 0)
assert_equal(p1_result.polarity, p1_result[0])
assert_equal(p1_result.subjectivity, p1_result[1])
def test_analyze_assessments(self):
p1 = "I feel great this morning."
n1 = "This is a terrible car."
p1_result = self.analyzer.analyze(p1,keep_assessments=True)
n1_result = self.analyzer.analyze(n1,keep_assessments=True)
p1_assessment = p1_result.assessments[0]
n1_assessment = n1_result.assessments[0]
assert_true(p1_assessment[1] > 0)
assert_true(n1_assessment[1] < 0)
assert_equal(p1_result.polarity, p1_assessment[1])
assert_equal(p1_result.subjectivity, p1_assessment[2])
class TestPatternSentiment(unittest.TestCase):
def setUp(self):
self.analyzer = PatternAnalyzer()
def test_kind(self):
assert_equal(self.analyzer.kind, CONTINUOUS)
def test_analyze(self):
p1 = "I feel great this morning."
n1 = "This is a terrible car."
assert_true(self.analyzer.analyze(p1)[0] > 0)
assert_true(self.analyzer.analyze(n1)[0] < 0)
class TestPatternSentiment(unittest.TestCase):
def setUp(self):
self.analyzer = PatternAnalyzer()
def test_kind(self):
assert_equal(self.analyzer.kind, CONTINUOUS)
def test_analyze(self):
p1 = "I feel great this morning."
n1 = "This is a terrible car."
assert_true(self.analyzer.analyze(p1)[0] > 0)
assert_true(self.analyzer.analyze(n1)[0] < 0)
def test_can_get_subjectivity_and_polarity_with_different_analyzer(self):
blob = tb.TextBlob("I love this car.", analyzer=NaiveBayesAnalyzer())
pattern = PatternAnalyzer()
assert_equal(blob.polarity, pattern.analyze(str(blob))[0])
assert_equal(blob.subjectivity, pattern.analyze(str(blob))[1])
def test_can_get_subjectivity_and_polarity_with_different_analyzer(self):
blob = tb.TextBlob("I love this car.", analyzer=NaiveBayesAnalyzer())
pattern = PatternAnalyzer()
assert_equal(blob.polarity, pattern.analyze(str(blob))[0])
assert_equal(blob.subjectivity, pattern.analyze(str(blob))[1])
def sentiment(tweet):
#return textblob.TextBlob(tweet).sentiment.polarity
sentiment_analyzer = PatternAnalyzer()
return sentiment_analyzer.analyze(tweet).polarity
self.ax.plot(self.angle, np.r_[sdata, sdata[0]], *args, **kw)
def fill(self, data, *args, **kw):
sdata = _scale_data(data, self.ranges)
self.ax.fill(self.angle, np.r_[sdata, sdata[0]], *args, **kw)
if __name__ == "__main__":
start = timeit.default_timer()
# init the analyzers
analyzerBayes = NaiveBayesAnalyzer()
analyzerPattern = PatternAnalyzer()
#training first
resultBayes = analyzerBayes.analyze("train this")
resultPattern = analyzerPattern.analyze("train this")
sc = SparkContext(appName="MovieSentiment")
# map reduce
lines = sc.textFile("movieData.txt")
posNneg = lines.map(sentimentAnalysis) \
.reduceByKey(lambda a, b: (a[0] + b[0], a[1] + b[1]))
output = posNneg.collect()
ScoreDict = {}
for (feature, posAndNeg) in output:
print(feature, posAndNeg)
order="relevance",
textFormat="plainText",
videoId=mat2)
res = req1.execute()
# print(res)
bags = []
for item in res['items']:
comment = item['snippet']['topLevelComment']['snippet']['textDisplay']
# print(comment)
bags.append(comment)
comments = ''
sentences = comments.join(bags)
sentiment_analyzer = PatternAnalyzer()
# print(sentences)
# print(sentiment_analyzer.analyze(sentences))
vv = sentiment_analyzer.analyze(sentences)
vv1 = vv.polarity
# print(vv1)
if vv1 > 0.5:
print("Positive")
# print(bags)
# if bags == item.values():
# # print(bags['textDisplay'])
# comments = ''
# sentences = comments.join(bags)
# print(sentences)
# sentiment_analyzer = PatternAnalyzer()
# print(sentiment_analyzer.analyze(sentences))
# blob = TextBlob(sentences)
# for sentence in blob.sentences:
