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utils.py
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utils.py
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import pickle
import time
import regex as re
import pathlib
import bokeh.plotting
import bokeh.models
import bokeh.layouts
import pandas as pd
import threading
import lxml
import queue
import socket
import tempfile
import random
TOOLS = "hover, pan, reset, wheel_zoom, zoom_in, zoom_out"
JAVASCRIPT = """
var f = cb_obj.value;
var options = %s;
f = f.replace(/[!\"#$&\'()*+,-.:;<=>?@^_`{}~]/g, "");
f = f.replace(/\s/g, "");
for (var i in options) {
if (f == options[i]) {
console.log("Visible: " + options[i])
eval(options[i]).visible = true;
}
else {
console.log("Unvisible: " + options[i])
eval(options[i]).visible = false;
}
}
"""
def compress(data, filepath):
"""
Dumps generated data.
"""
with open(filepath, "wb") as file:
pickle.dump(data, file)
def decompress(filepath):
"""
Loads dumped data.
"""
with open(filepath, "rb") as file:
return pickle.load(file)
def load_data(tempdir):
"""
Loads the generated data.
"""
data_path = str(pathlib.Path(tempdir, "data.pickle"))
parameter_path = str(pathlib.Path(tempdir, "parameter.csv"))
topics_path = str(pathlib.Path(tempdir, "topics.csv"))
data = decompress(data_path)
parameter = pd.read_csv(parameter_path, index_col=0, encoding="utf-8", sep=";")
parameter.columns = [""] # remove column names
topics = pd.read_csv(topics_path, index_col=0, encoding="utf-8", sep=";")
data["parameter"] = [parameter.to_html(classes="parameter", border=0)]
data["topics"] = [topics.to_html(classes="topics")]
return data
def remove_markup(content):
"""
Removes markup from text. If lxml fails, a simple regex is used.
"""
try:
parser = lxml.etree.XMLParser(recover=True)
tree = lxml.etree.parse(content, parser=parser)
ns = dict(tei="http://www.tei-c.org/ns/1.0")
lxml.etree.strip_elements(tree, "speaker", with_tail=False)
lxml.etree.strip_elements(tree, "note", with_tail=False)
lxml.etree.strip_elements(tree, "stage", with_tail=False)
lxml.etree.strip_elements(tree, "head", with_tail=False)
text = tree.xpath("//text()")
text = "\n".join(text)
text = re.sub(" ", "", text)
text = re.sub(" ", "", text)
text = re.sub("\n{1,6}", "\n", text)
text = re.sub("\n \n", "\n", text)
text = re.sub("\t\n", "", text)
return text
except:
text = []
for line in content:
line = re.sub("<.*?>", "", line)
line = re.sub("(<.[^(><.)]+>)|<.?>", "", line)
line = re.sub("\\n", "", line)
line = re.sub("[ ]{2,}", " ", line)
line = re.sub("<?(.*?)?>", "", line)
text.append(line)
return "".join(text)
def boxplot(stats):
"""
Creates a boxplot for corpus statistics.
"""
x_labels = ["Document size (clean)", "Document size (raw)"]
groups = stats.groupby("group")
q1 = groups.quantile(q=0.25)
q2 = groups.quantile(q=0.5)
q3 = groups.quantile(q=0.75)
iqr = q3 - q1
upper = q3 + 1.5 * iqr
lower = q1 - 1.5 * iqr
def outliers(group):
cat = group.name
return group[(group.score > upper.loc[cat]["score"]) |
(group.score < lower.loc[cat]["score"])]["score"]
out = groups.apply(outliers).dropna()
fig = bokeh.plotting.figure(tools="", background_fill_color="#EFE8E2",
title="", x_range=x_labels, logo=None,
sizing_mode="fixed", plot_width=500,
plot_height=350)
qmin = groups.quantile(q=0.00)
qmax = groups.quantile(q=1.00)
upper.score = [min([x, y]) for (x, y) in zip(list(qmax.loc[:, "score"]), upper.score)]
lower.score = [max([x, y]) for (x, y) in zip(list(qmin.loc[:, "score"]), lower.score)]
fig.segment(x_labels, upper.score, x_labels, q3.score, line_color="black")
fig.segment(x_labels, lower.score, x_labels, q1.score, line_color="black")
fig.vbar(x_labels, 0.7, q2.score, q3.score, fill_color="#729fcf", line_color="black")
fig.vbar(x_labels, 0.7, q1.score, q2.score, fill_color="#729fcf", line_color="black")
fig.rect(x_labels, lower.score, 0.2, 0.01, line_color="black")
fig.rect(x_labels, upper.score, 0.2, 0.01, line_color="black")
fig.yaxis.axis_label = "Tokens"
fig.xgrid.grid_line_color = None
fig.ygrid.grid_line_color = "white"
fig.grid.grid_line_width = 2
fig.xaxis.major_label_text_font_size = "11pt"
fig.yaxis.major_label_text_font_size = "9pt"
return fig
def barchart(document_topics, height, topics=None, script=JAVASCRIPT, tools=TOOLS):
"""
Creates an interactive barchart for document-topics proportions.
"""
y_range = document_topics.columns.tolist()
fig = bokeh.plotting.figure(y_range=y_range, plot_height=height, tools=tools,
toolbar_location="right", sizing_mode="scale_width",
logo=None)
plots = {}
options = document_topics.index.tolist()
for i, option in enumerate(options):
x_axis = document_topics.loc[option]
source = bokeh.models.ColumnDataSource(dict(Describer=y_range, Proportion=x_axis))
option = re.sub(" ", "_", option)
bar = fig.hbar(y="Describer", right="Proportion", source=source,
height=0.5, color="#053967")
if i == 0:
bar.visible = True
else:
bar.visible = False
plots[exclude_punctuations(option)] = bar
fig.xgrid.grid_line_color = None
fig.x_range.start = 0
fig.select_one(bokeh.models.HoverTool).tooltips = [("Proportion", "@Proportion")]
fig.xaxis.axis_label = "Proportion"
fig.xaxis.major_label_text_font_size = "9pt"
fig.yaxis.major_label_text_font_size = "9pt"
options = list(plots.keys())
callback = bokeh.models.CustomJS(args=plots, code=script % options)
if len(options) < 11:
if topics is not None:
selection = [" ".join(topics.iloc[i].tolist()) + " ..." for i in range(topics.shape[0])]
menu = [(select, option) for select, option in zip(selection, options)]
label = "Select topic to display proportions"
else:
menu = [(select, option) for select, option in zip(document_topics.index, options)]
label = "Select document to display proportions"
dropdown = bokeh.models.widgets.Dropdown(label=label, menu=menu, callback=callback)
return bokeh.layouts.column(dropdown, fig, sizing_mode="scale_width")
else:
if topics is not None:
what = "topic"
else:
what = "document"
textfield = bokeh.models.widgets.AutocompleteInput(completions=document_topics.index.tolist(),
placeholder="Type a {}, press enter".format(what),
css_classes=["customTextInput"],
callback=callback)
return bokeh.layouts.row(fig, textfield, sizing_mode="scale_width")
def read_logfile(logfile, total_iterations):
"""
Reads a logfile and returns the current number of iterations.
"""
time.sleep(3)
pattern = re.compile("-?\d+")
with open(logfile, "r", encoding="utf-8") as file:
text = file.readlines()
line = text[-1][:-1]
wait = "Still initializing LDA topic model ..."
info = "Iteration {0} of {1} ..."
if "likelihood" in line:
i = pattern.findall(line)[0]
return i, info.format(i, total_iterations)
elif "n_documents" in line:
return 0, wait
elif "vocab_size" in line:
return 0, wait
elif "n_words" in line:
return 0, wait
elif "n_topics" in line:
return 0, wait
elif "n_iter" in line:
return 0, wait
else:
return 0, None
def enthread(target, args):
"""
Threads a process.
"""
q = queue.Queue()
def wrapper():
q.put(target(*args))
t = threading.Thread(target=wrapper)
t.start()
return q
def is_connected(host="8.8.8.8", port=53, timeout=3):
"""
Checks if your machine is connected to the internet.
Host: 8.8.8.8 (google-public-dns-a.google.com)
OpenPort: 53/tcp
Service: domain (DNS/TCP)
"""
try:
socket.setdefaulttimeout(timeout)
socket.socket(socket.AF_INET, socket.SOCK_STREAM).connect((host, port))
return "include"
except:
return "exclude"
def exclude_punctuations(s):
"""
Excludes punctuations from a string.
"""
exclude = set("!\"#$&'()*+,-.:;<=>?@^_`{}~")
s = "".join(c for c in s if c not in exclude)
return re.sub(" ", "", s)
def unlink_content(directory, pattern="*"):
"""
Deletes the content of a directory.
"""
for p in pathlib.Path(directory).rglob(pattern):
if p.is_file():
p.unlink()
def get_tempdirs(make=False):
"""
Gets paths (and makes) temporary folders.
"""
tempdir = tempfile.gettempdir()
dumpdir = pathlib.Path(tempdir, "topicsexplorerdump")
archivedir = pathlib.Path(tempdir, "topicsexplorerdata")
if make:
dumpdir.mkdir(exist_ok=True)
archivedir.mkdir(exist_ok=True)
return dumpdir, archivedir