def query_for_split_decision(self, inds1, inds2, vectorizer, vectors, vector_names):
print display_vector_index_details(inds1, vectors, vector_names, vectorizer)
print display_vector_index_details(inds2, vectors, vector_names, vectorizer)
print "Overlap:"
print display_shared_vector_indeces_details([inds1, inds2], vectors, vector_names, vectorizer)
response = raw_input("Should {0} and {1} be in the same cluster? (Y/N)".format(vector_names[inds1], vector_names[inds2]))
if response.upper() == "Y" or response.upper() == "YES":
return False # If users think the two should be in one cluster, we don't split, so return False
if response.upper() == "N" or response.upper() == "NO":
return True # vice versa
transformed_vectors = pca.fit_transform(vectors)
plot_color = np.array(['#636363'] * n_samples)
markers = np.array(["circle"] * n_samples)
source = ColumnDataSource(
dict(
x=clusteringnmap.interactive_state._reduced_vectors[:, 0],
y=clusteringnmap.interactive_state._reduced_vectors[:, 1],
color=plot_color,
size=np.ones(n_samples) * 15,
marker=markers,
alpha=np.ones(n_samples) * 0.6,
ip=clusteringnmap.interactive_state._vector_names,
features=[
display_vector_index_details(
index,
clusteringnmap.interactive_state._vectors,
clusteringnmap.interactive_state._vector_names,
clusteringnmap.interactive_state._vectorizer
) for index in xrange(len(clusteringnmap.interactive_state._vector_names))
],
)
)
# hover over tool, define what to display when hovering over a point
hover = HoverTool(
tooltips="""
<div style="font-size:10px;max-width: 640px; border-width:0; background:#2f2f2f; color:rgb(256,256,256); overflow-x: auto;">
<div>
<span style="font-size: 17px; font-weight: bold;">@ip</span>
<span style="font-size: 15px; color: #966;">($x, $y)</span>
</div>
<div>
pca = PCA(n_components=2)
transformed_vectors = pca.fit_transform(vectors)
plot_color = np.array(['#636363'] * n_samples)
markers = np.array(["circle"] * n_samples)
source = ColumnDataSource(
dict(
x=clusteringnmap.interactive_state._reduced_vectors[:, 0],
y=clusteringnmap.interactive_state._reduced_vectors[:, 1],
color=plot_color,
size=np.ones(n_samples) * 15,
marker=markers,
alpha=np.ones(n_samples) * 0.6,
ip=clusteringnmap.interactive_state._vector_names,
features=[
display_vector_index_details(
index, clusteringnmap.interactive_state._vectors,
clusteringnmap.interactive_state._vector_names,
clusteringnmap.interactive_state._vectorizer)
for index in xrange(
len(clusteringnmap.interactive_state._vector_names))
],
))
# hover over tool, define what to display when hovering over a point
hover = HoverTool(tooltips="""
<div style="font-size:10px;max-width: 640px; border-width:0; background:#2f2f2f; color:rgb(256,256,256); overflow-x: auto;">
<div>
<span style="font-size: 17px; font-weight: bold;">@ip</span>
<span style="font-size: 15px; color: #966;">($x, $y)</span>
</div>
<div>
<span><div id="feature-data-$index" style="display: none;">@features</div>