4. Приклади бібліотек Python

colors = 'rgbcmyk' # red, green, blue, cyan, magenta, yellow, black

def bar_chart(categories, words, counts):

"Plot a bar chart showing counts for each word by category"

import pylab

ind = pylab.arange(len(words))

width = 1 / (len(categories) + 1)

bar_groups = []

for c in range(len(categories)):

bars = pylab.bar(ind+c*width, counts[categories[c]], width,

color=colors[c % len(colors)])

bar_groups.append(bars)

pylab.xticks(ind+width, words)

pylab.legend([b[0] for b in bar_groups], categories, loc='upper left')

pylab.ylabel('Frequency')

pylab.title('Frequency of Six Modal Verbs by Genre')

pylab.show()

>>> genres = ['news', 'religion', 'hobbies', 'government', 'adventure']

>>> modals = ['can', 'could', 'may', 'might', 'must', 'will']

>>> cfdist = nltk.ConditionalFreqDist(

... (genre, word)

... for genre in genres

... for word in nltk.corpus.brown.words(categories=genre)

... if word in modals)

...

>>> counts = {}

>>> for genre in genres:

... counts[genre] = [cfdist[genre][word] for word in modals]

>>> bar_chart(genres, modals, counts)

import networkx as nx

import matplotlib

from nltk.corpus import wordnet as wn

def traverse(graph, start, node):

graph.depth[node.name] = node.shortest_path_distance(start)

for child in node.hyponyms():

graph.add_edge(node.name, child.name) #1

traverse(graph, start, child) #2

def hyponym_graph(start):

G = nx.Graph() #3

G.depth = {}

traverse(G, start, start)

return G

def graph_draw(graph):

nx.draw_graphviz(graph,

node_size = [16 * graph.degree(n) for n in graph],

node_color = [graph.depth[n] for n in graph],

with_labels = False)

matplotlib.pyplot.show()

>>> dog = wn.synset('dog.n.01')

>>> graph = hyponym_graph(dog)

>>> graph_draw(graph)