知微
fa45d8aa5f
- health_checklist.json: 192.168.1.122→node122
- ocr_client.py: docstring IP→node122
- docs/market-data-requirements.md: IP→node122
- 所有API调用通过ProxyHandler({})绕过系统代理
Privoxy对node122:18003返回500，直连正常
37 lines
921 B
Python
37 lines
921 B
Python
# Natural Language Toolkit: Wordfreq Application
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#
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# Copyright (C) 2001-2026 NLTK Project
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# Author: Sumukh Ghodke <sghodke@csse.unimelb.edu.au>
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# URL: <https://www.nltk.org/>
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# For license information, see LICENSE.TXT
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from matplotlib import pylab
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from nltk.corpus import gutenberg
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from nltk.text import Text
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def plot_word_freq_dist(text):
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fd = text.vocab()
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samples = [item for item, _ in fd.most_common(50)]
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values = [fd[sample] for sample in samples]
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values = [sum(values[: i + 1]) * 100.0 / fd.N() for i in range(len(values))]
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pylab.title(text.name)
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pylab.xlabel("Samples")
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pylab.ylabel("Cumulative Percentage")
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pylab.plot(values)
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pylab.xticks(range(len(samples)), [str(s) for s in samples], rotation=90)
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pylab.show()
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def app():
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t1 = Text(gutenberg.words("melville-moby_dick.txt"))
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plot_word_freq_dist(t1)
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if __name__ == "__main__":
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app()
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__all__ = ["app"]
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