zipf

Zipf Distribution: How do I measure Zipf Distribution

由 牧云@^-^@ 提交于 2019-12-23 17:21:53
问题 How do I measure or find the Zipf distribution ? For example, I have a corpus of english words. How do I find the Zipf distribution ? I need to find the Zipf ditribution and then plot a graph of it. But I am stuck in the first step which is to find the Zipf distribution. Edit: From the frequency count of each word, it is clear that it obeys the Zipf law. But my aim is to plot a zipf distribution graph. I have no idea about how to calculate the data for the distribution graph 回答1: I don't

Constructing Zipf Distribution with matplotlib, FITTED-LINE

由 本小妞迷上赌 提交于 2019-12-08 18:58:27
I have a list of paragraphs, where I want to run a zipf distribution on their combination. My code is below: from itertools import * from pylab import * from collections import Counter import matplotlib.pyplot as plt paragraphs = " ".join(targeted_paragraphs) for paragraph in paragraphs: frequency = Counter(paragraph.split()) counts = array(frequency.values()) tokens = frequency.keys() ranks = arange(1, len(counts)+1) indices = argsort(-counts) frequencies = counts[indices] loglog(ranks, frequencies, marker=".") title("Zipf plot for Combined Article Paragraphs") xlabel("Frequency Rank of Token

Constructing Zipf Distribution with matplotlib, FITTED-LINE

由 痞子三分冷 提交于 2019-12-08 03:35:05
问题 I have a list of paragraphs, where I want to run a zipf distribution on their combination. My code is below: from itertools import * from pylab import * from collections import Counter import matplotlib.pyplot as plt paragraphs = " ".join(targeted_paragraphs) for paragraph in paragraphs: frequency = Counter(paragraph.split()) counts = array(frequency.values()) tokens = frequency.keys() ranks = arange(1, len(counts)+1) indices = argsort(-counts) frequencies = counts[indices] loglog(ranks,
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