def dispersion():
corpus = load_hobbies()
target_words = ["Game", "player", "score", "oil", "Man"]
oz = DispersionPlot(target_words, ax=newfig())
oz.fit([doc.split() for doc in corpus.data])
savefig(oz, "dispersion")
def tsne():
corpus = load_hobbies()
docs = TfidfVectorizer().fit_transform(corpus.data)
oz = TSNEVisualizer(ax=newfig())
oz.fit(docs, corpus.target)
savefig(oz, "corpus_tsne")
def freqdist():
corpus = load_hobbies()
vecs = CountVectorizer()
docs = vecs.fit_transform(corpus.data)
oz = FreqDistVisualizer(features=vecs.get_feature_names(), ax=newfig())
oz.fit(docs)
savefig(oz, "freqdist")
def test_quick_method(self):
"""
Test for tsne quick method with hobbies dataset
"""
corpus = load_hobbies()
tfidf = TfidfVectorizer()
X = tfidf.fit_transform(corpus.data)
y = corpus.target
viz = tsne(X, y, show=False)
self.assert_images_similar(viz, tol=50)
def test_topic_modeling_k_means(self):
"""
Test topic modeling k-means on the hobbies corpus
"""
corpus = load_hobbies()
tfidf = TfidfVectorizer()
docs = tfidf.fit_transform(corpus.data)
visualizer = KElbowVisualizer(KMeans(), k=(4, 8))
visualizer.fit(docs)
visualizer.finalize()
self.assert_images_similar(visualizer)
def test_quick_method(self):
"""
Test for umap quick method with hobbies dataset
"""
corpus = load_hobbies()
tfidf = TfidfVectorizer()
X = tfidf.fit_transform(corpus.data)
y = corpus.target
viz = umap(X, y, show=False)
assert isinstance(viz, UMAPVisualizer)
self.assert_images_similar(viz, tol=50)
## Imports
##########################################################################
import pytest
import matplotlib.pyplot as plt
from yellowbrick.exceptions import YellowbrickValueError
from yellowbrick.datasets import load_hobbies
from yellowbrick.text.dispersion import DispersionPlot, dispersion
from tests.base import VisualTestCase
##########################################################################
## Data
##########################################################################
corpus = load_hobbies()
##########################################################################
## DispersionPlot Tests
##########################################################################
class TestDispersionPlot(VisualTestCase):
def test_quick_method(self):
"""
Assert no errors occur when using the quick method
"""
_, ax = plt.subplots()
text = [doc.split() for doc in corpus.data]
search_terms = ["Game", "player", "score", "oil", "Man"]
def load_document_representation():
corpus = load_hobbies()
tfidf = TfidfVectorizer()
docs = tfidf.fit_transform(corpus.data)
return docs, corpus.target
