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"""Count the frequencies of words in a string"""
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from __future__ import division
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import cmath as math
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def wordfreq(text, is_filename=False):
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"""Return a dictionary of words and word counts in a string."""
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if is_filename:
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with open(text) as f:
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text = f.read()
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freqs = {}
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for word in text.split():
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lword = word.lower()
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freqs[lword] = freqs.get(lword, 0) + 1
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return freqs
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def print_wordfreq(freqs, n=10):
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"""Print the n most common words and counts in the freqs dict."""
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words, counts = freqs.keys(), freqs.values()
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items = zip(counts, words)
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items.sort(reverse=True)
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for (count, word) in items[:n]:
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print word, count
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def wordfreq_to_weightsize(worddict, minsize=25, maxsize=50, minalpha=0.5, maxalpha=1.0):
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mincount = min(worddict.itervalues())
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maxcount = max(worddict.itervalues())
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weights = {}
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for k, v in worddict.iteritems():
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w = (v-mincount)/(maxcount-mincount)
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alpha = minalpha + (maxalpha-minalpha)*w
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size = minsize + (maxsize-minsize)*w
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weights[k] = (alpha, size)
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return weights
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def tagcloud(worddict, n=10, minsize=25, maxsize=50, minalpha=0.5, maxalpha=1.0):
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from matplotlib import pyplot as plt
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import random
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worddict = wordfreq_to_weightsize(worddict, minsize, maxsize, minalpha, maxalpha)
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fig = plt.figure()
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ax = fig.add_subplot(111)
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ax.set_position([0.0,0.0,1.0,1.0])
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plt.xticks([])
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plt.yticks([])
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words = worddict.keys()
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alphas = [v[0] for v in worddict.values()]
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sizes = [v[1] for v in worddict.values()]
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items = zip(alphas, sizes, words)
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items.sort(reverse=True)
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for alpha, size, word in items[:n]:
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# xpos = random.normalvariate(0.5, 0.3)
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# ypos = random.normalvariate(0.5, 0.3)
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xpos = random.uniform(0.0,1.0)
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ypos = random.uniform(0.0,1.0)
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ax.text(xpos, ypos, word.lower(), alpha=alpha, fontsize=size)
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ax.autoscale_view()
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return ax
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