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removed pyldavis functions
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sina.bock@stud-mail.uni-wuerzburg.de committed Aug 2, 2017
1 parent 3a96618 commit 99de185
Showing 1 changed file with 0 additions and 191 deletions.
191 changes: 0 additions & 191 deletions dariah_topics/visualization.py
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import numpy as np
import os
import pandas as pd
#import pyLDAvis.gensim
import regex


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logging.basicConfig(level = logging.ERROR,
format = '%(levelname)s %(name)s: %(message)s')

class Visualization:
def __init__(self, lda_model, corpus, dictionary, doc_labels, interactive=False):
"""Loads Gensim output for further processing.
The output folder should contain ``corpus.mm``, ``corpus.lda``, as well as
``corpus_doclabels.txt`` (for heatmap) or ``corpus.dict`` (for interactive
visualization).
Args:
lda_model: Path to output folder.
corpus:
dictionary:
doc_labels:
interactive (bool, optional): True if interactive visualization,
False if heatmap is desired. Defaults to False.
Returns:
If `interactive == False`: corpus, model, doc_labels.
If `interactive == True`: corpus, model, dictionary.
Raises:
OSError: If directory or files not found.
ValueError: If no matching values found.
Unexpected error: Everything else.
Note: Currently not in use due to dependencies
"""
try:
log.info("Accessing corpus ...")
self.corpus = corpus
log.debug("Corpus available.")

log.info("Accessing model ...")
self.model = lda_model
log.debug("Model available.")

if interactive == False:
log.debug(":param: interactive == False.")
log.info("Accessing doc_labels ...")
self.doc_labels = doc_labels
log.debug("doc_labels accessed.")

elif interactive == True:
log.debug(":param: interactive == True.")
log.info("Accessing dictionary ...")
self.dictionary = dictionary
log.debug("Dictionary available.")
log.debug("Corpus, model and dictionary available.")

except OSError as err:
log.error("OS error: {0}".format(err))
raise
except ValueError:
log.error("Value error: No matching value found.")
raise
except:
import sys
log.error("Unexpected error:", sys.exc_info()[0])
sys.exit(1)
raise

def make_heatmap(self):
"""Generates heatmap from LDA model.
The ingested data (e.g. with `load_gensim_output()`) has to be transmitted
as parameters.
Args:
corpus: Corpus created by Gensim, e.g. corpus.mm.
model: LDA model created by Gensim, e.g. corpus.lda.
doc_labels (list[str]): List of document labels, e.g. corpus_doclabels.txt.
Returns:
Matplotlib heatmap figure.
ToDo:
* add colorbar
* create figure dynamically?
http://stackoverflow.com/questions/23058560/plotting-dynamic-data-using-matplotlib
Note: Currently not in use due to dependencies
"""
no_of_topics = self.model.num_topics
no_of_docs = len(self.doc_labels)
doc_topic = np.zeros((no_of_docs, no_of_topics))

log.info("Accessing topic distribution and topic probability ...")
for doc, i in zip(self.corpus, range(no_of_docs)):
topic_dist = self.model.__getitem__(doc)
for topic in topic_dist: # topic_dist is a list of tuples (topic_id, topic_prob)
doc_topic[i][topic[0]] = topic[1]
log.debug("Topic distribution and topic probability available.")

log.info("Accessing plot labels ...")
topic_labels = []
for i in range(no_of_topics):
topic_terms = [x[0] for x in self.model.show_topic(i, topn=3)] # show_topic() returns tuples (word_prob, word)
topic_labels.append(" ".join(topic_terms))
log.debug("%s plot labels available.", len(topic_labels))

log.info("Creating heatmap figure ...")
if no_of_docs > 20 or no_of_topics > 20:
fig = plt.figure(figsize=(20,20)) # if many items, enlarge figure
else:
fig = plt.figure()
ax = fig.add_subplot(1,1,1)
ax.pcolor(doc_topic, norm=None, cmap='Reds')
ax.set_yticks(np.arange(doc_topic.shape[0])+1.0)
ax.set_yticklabels(self.doc_labels)
ax.set_xticks(np.arange(doc_topic.shape[1])+0.5)
ax.set_xticklabels(topic_labels, rotation='90')
ax.invert_yaxis()
fig.tight_layout()
self.heatmap_vis = fig
log.debug("Heatmap figure available.")

def save_heatmap(self, path, filename='heatmap', ext='png', dpi=200):
"""Saves Matplotlib heatmap figure.
The created visualization (e.g. with `make_heatmap()`) has to be
transmitted as parameter.
Args:
heatmap: plt.figure created by ``matplotlib.pyplot``.
path(str): Path to output folder. Defaults to global variable `path`.
Returns:
~/out/corpus_heatmap.png
Note: Currently not in use due to dependencies
"""
log.info("Saving heatmap figure...")
try:
if not os.path.exists(path):
os.makedirs(path)
self.heatmap_vis.savefig(os.path.join(path, filename + '.' + ext), dpi=dpi)
log.debug("Heatmap figure available at %s/%s.%s", path, filename, ext)
except AttributeError:
log.error("Run make_heatmap() before save_heatmp()")
raise
except FileNotFoundError:
pass

def make_interactive(self):
"""Generates interactive visualization from LDA model.
The ingested data (e.g. with `load_gensim_output()`) has to be transmitted
as parameters.
Args:
corpus: Corpus created by Gensim, e.g. corpus.mm.
model: LDA model created by Gensim, e.g. corpus.lda.
dictionary(dict): Dictionary created by Gensim, e.g. corpus.dict.
Returns:
pyLDAvis visualization.
Note: Currently not in use due to dependencies
"""
log.info("Accessing model, corpus and dictionary ...")
self.interactive_vis = pyLDAvis.gensim.prepare(self.model, self.corpus, self.dictionary)
log.debug("Interactive visualization available.")

def save_interactive(self, path, filename='corpus_interactive'):
"""Saves interactive visualization.
The created visualization (e.g. with `make_interactive()`) has to be
transmitted as parameter.
Args:
vis: Interactive visualization created by pyLDAvis.
path(str): Path to output folder. Defaults to global variable `path`.
Returns:
~/out/corpus_interactive.html
~/out/corpus_interactive.json
"""
try:
if not os.path.exists(path):
os.makedirs(path)
log.info("Saving interactive visualization ...")
pyLDAvis.save_html(self.interactive_vis, os.path.join(path, 'corpus_interactive.html'))
pyLDAvis.save_json(self.interactive_vis, os.path.join(path, 'corpus_interactive.json'))
pyLDAvis.prepared_data_to_html(self.interactive_vis)
log.debug("Interactive visualization available at %s/corpus_interactive.html and %s/corpus_interactive.json", path, path)
except AttributeError:
log.error("Running make_interactive() before save_interactive() ...")
raise
except FileNotFoundError:
pass

def create_doc_topic(corpus, model, doc_labels):
# Adapted from code by Stefan Pernes
"""Creates a document-topic data frame.
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