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add word frequencies from the Reddit 2007-2015 corpus
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wordfreq_builder/lib/jq-linux64
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wordfreq_builder/lib/jq-linux64
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@ -13,7 +13,7 @@
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# contains the programatically-defined dependency graph.
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# Variables
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DATA = ./data
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JQ = lib/jq-linux64
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# How to build the build.ninja file itself. (Use the Makefile to get it the
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# first time.)
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@ -99,3 +99,6 @@ rule freqs2cB
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rule cat
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command = cat $in > $out
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rule extract_reddit
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command = bunzip2 -c $in | $JQ -r '.body' | fgrep -v '[deleted]' | sed 's/>/>/g' | sed 's/</</g' | sed 's/&/\&/g' > $out
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@ -5,7 +5,7 @@ import argparse
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def merge_lists(input_names, output_name):
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count_dicts = []
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for input_name in input_names:
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values, total = read_values(input_name, cutoff=0)
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values, total = read_values(input_name, cutoff=0, max_size=1000000)
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count_dicts.append(values)
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merged = merge_counts(count_dicts)
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write_wordlist(merged, output_name)
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@ -40,7 +40,8 @@ CONFIG = {
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],
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'subtlex-en': ['en'],
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'subtlex-other': ['de', 'nl', 'zh'],
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'jieba': ['zh']
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'jieba': ['zh'],
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'reddit': ['en'],
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},
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# Subtlex languages that need to be pre-processed
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'wordlist_paths': {
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@ -52,6 +53,7 @@ CONFIG = {
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'subtlex-en': 'generated/subtlex/subtlex_{lang}.{ext}',
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'subtlex-other': 'generated/subtlex/subtlex_{lang}.{ext}',
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'jieba': 'generated/jieba/jieba_{lang}.{ext}',
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'reddit': 'generated/reddit/reddit_{lang}.{ext}',
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'combined': 'generated/combined/combined_{lang}.{ext}',
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'combined-dist': 'dist/combined_{lang}.{ext}',
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'twitter-dist': 'dist/twitter_{lang}.{ext}',
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@ -77,6 +77,10 @@ def make_ninja_deps(rules_filename, out=sys.stdout):
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data_filename('source-lists/subtlex'),
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CONFIG['sources']['subtlex-other']
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),
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reddit_deps(
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data_filename('raw-input/reddit'),
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CONFIG['sources']['reddit']
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),
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jieba_deps(
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data_filename('source-lists/jieba'),
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CONFIG['sources']['jieba']
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@ -232,6 +236,27 @@ def jieba_deps(dirname_in, languages):
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return lines
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def reddit_deps(dirname_in, languages):
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lines = []
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if not languages:
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return lines
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assert languages == ['en']
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processed_files = []
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path_in = pathlib.Path(dirname_in)
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for filepath in path_in.glob('*/*.bz2'):
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base = filepath.name[:-4]
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transformed_file = wordlist_filename('reddit', 'en', base + '.txt')
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add_dep(lines, 'extract_reddit', str(filepath), transformed_file)
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count_file = wordlist_filename('reddit', 'en', base + '.counts.txt')
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add_dep(lines, 'count', transformed_file, count_file)
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processed_files.append(count_file)
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output_file = wordlist_filename('reddit', 'en', 'counts.txt')
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add_dep(lines, 'merge_counts', processed_files, output_file)
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return lines
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# Which columns of the SUBTLEX data files do the word and its frequency appear
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# in?
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SUBTLEX_COLUMN_MAP = {
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@ -33,7 +33,7 @@ def count_tokens(filename):
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return counts
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def read_values(filename, cutoff=0, lang=None):
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def read_values(filename, cutoff=0, max_size=1e8, lang=None):
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"""
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Read words and their frequency or count values from a CSV file. Returns
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a dictionary of values and the total of all values.
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@ -52,7 +52,7 @@ def read_values(filename, cutoff=0, lang=None):
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for key, strval in csv.reader(infile):
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val = float(strval)
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key = fix_text(key)
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if val < cutoff:
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if val < cutoff or len(values) >= max_size:
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break
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tokens = tokenize(key, lang) if lang is not None else simple_tokenize(key)
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for token in tokens:
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@ -76,7 +76,7 @@ def read_freqs(filename, cutoff=0, lang=None):
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If lang is given, read_freqs will apply language specific preprocessing
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operations.
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"""
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values, total = read_values(filename, cutoff, lang)
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values, total = read_values(filename, cutoff, lang=lang)
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for word in values:
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values[word] /= total
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