[PYTHON] 100 coups de traitement linguistique (2020): 38

"""
37.Top 10 des mots qui coïncident fréquemment avec "chat"
Affichez 10 mots qui coïncident souvent avec "chat" (fréquence élevée de cooccurrence) et leur fréquence d'apparition dans un graphique (par exemple, un graphique à barres).


sentence_list:
[[{'surface': '', 'base': '*', 'pos': 'BOS/EOS', 'pos1': '*'},
  {'surface': 'un', 'base': 'un', 'pos': 'nom', 'pos1': 'nombre'},
  {'surface': '', 'base': '*', 'pos': 'BOS/EOS', 'pos1': '*'}],
 [{'surface': '', 'base': '*', 'pos': 'BOS/EOS', 'pos1': '*'},
  {'surface': 'je', 'base': 'je', 'pos': 'nom', 'pos1': '代nom'},
  {'surface': 'Est', 'base': 'Est', 'pos': 'Particule', 'pos1': '係Particule'},
  {'surface': 'Chat', 'base': 'Chat', 'pos': 'nom', 'pos1': 'Général'},
  {'surface': 'alors', 'base': 'Est', 'pos': 'Verbe auxiliaire', 'pos1': '*'},
  {'surface': 'y a-t-il', 'base': 'y a-t-il', 'pos': 'Verbe auxiliaire', 'pos1': '*'},
  {'surface': '。', 'base': '。', 'pos': 'symbole', 'pos1': 'Phrase'},
  {'surface': '', 'base': '*', 'pos': 'BOS/EOS', 'pos1': '*'}],

Memo:
    -Fréquence de cooccurrence: https://www.jtp.co.jp/techport/2018-04-18-001/
"""
from collections import defaultdict
from typing import List

import matplotlib.pyplot as plt

import utils

plt.style.use("ggplot")
plt.rcParams["font.family"] = "Hiragino Mincho ProN"  #Support japonais


def get_co_occurrence(sentence_list: List[List[dict]]) -> list:
    sents = [
        [word["surface"] for word in sent[1:-1]] for sent in sentence_list
    ]  # [['un'], ['je', 'Est', 'Chat', 'alors', 'y a-t-il', '。']]
    counter = defaultdict(int)

    for sent in sents:
        if "Chat" in sent:
            for word in sent:
                counter[word] += 1

    del counter["Chat"]

    sorted_counter = {
        k: v for k, v in sorted(counter.items(), key=lambda item: item[1], reverse=True)
    }
    return list(sorted_counter.items())


def plot_co_occurrence(x: list, y: list) -> None:
    x_pos = [i for i, _ in enumerate(x)]

    plt.bar(x, y)
    plt.xlabel("Term")
    plt.ylabel("Frequency")
    plt.title("Co-occurrence with 'Chat'")

    plt.xticks(x_pos, x)

    plt.show()


sentence_list = utils.read_json("30_neko_mecab.json")
counter = get_co_occurrence(sentence_list)
# [('de', 391), ('Est', 272), ('、', 252), ('À', 250), ('À', 232)]

x = [word[0] for word in counter[:10]]
y = [word[1] for word in counter[:10]]
plot_co_occurrence(x, y)
# ![image-20200527193140109](https://raw.githubusercontent.com/LearnXu/images/master/imgs/image-20200527193140109.png)

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