def test_basic(self) -> None:
mapper = bmm.LinearColorMapper()
check_properties_existence(
mapper,
[
"palette", "domain", "low", "high", "low_color", "high_color",
"nan_color"
],
)
vocab = cv.get_feature_names()
for i, topic_dist in enumerate(topic_word):
topic_words = np.array(vocab)[np.argsort(topic_dist)][:-(n_top_words +
1):-1] # get!
topic_summaries.append(' '.join(topic_words)) # append!
print(topic_summaries)
dfb = pd.DataFrame()
dfb['content'] = df[idx_max].text.values.tolist()
dfb['topic_key'] = np.array(lda_keys)
dfb['X_tsne'] = tsne_lda[:, 0]
dfb['Y_tsne'] = tsne_lda[:, 1]
source = ColumnDataSource(dfb)
color_mapper = mappers.LinearColorMapper(palette=palettes.Category20_20,
low=dfb.topic_key.min(),
high=dfb.topic_key.max())
p = figure(plot_width=1200,
plot_height=1000,
title='t-SNE Lord of the Rings Topics',
x_axis_label='X-coord',
y_axis_label='Y-coord',
tools="pan,wheel_zoom,box_zoom,reset,hover,previewsave",
toolbar_location='above',
min_border=1)
p.scatter(x='X_tsne',
y='Y_tsne',
color={
'field': 'topic_key',
'transform': color_mapper