def readText(text_file_path):
    with open(text_file_path, encoding='gbk') as f: #
        content = f.read()
    return content

def getRecommondArticleKeyword(text_content,  key_word_need_num = 10, custom_words = [], stop_words =[], query_pattern = 'searchEngine'):
    '''
    :param text_content: 文本字符串
    :param key_word_need_num: 需要的關(guān)鍵詞數(shù)量
    :param custom_words: 自定義關(guān)鍵詞
    :param stop_words: 不查詢關(guān)鍵詞
    :param query_pattern:
    precision:精確模式————試圖將句子最精確地切開，適合文本分析；
    entire：全模式————把句子中所有的可以成詞的詞語都掃描出來, 速度非常快，但是不能解決歧義；
    searchEngine:搜索引擎模式————在精確模式的基礎(chǔ)上，對(duì)長詞再次切分，提高召回率，適合用于搜索引擎分詞；
    paddle模式————利用PaddlePaddle深度學(xué)習(xí)框架，訓(xùn)練序列標(biāo)注（雙向GRU）網(wǎng)絡(luò)模型實(shí)現(xiàn)分詞。同時(shí)支持詞性標(biāo)注。
    :return:
    '''
    # jieba.enable_paddle()
    # paddle.fluid.install_check.run_check()
    if not isinstance(text_content, str):
        raise ValueError('文本字符串類型錯(cuò)誤！')
    if not isinstance(key_word_need_num, int):
        raise ValueError('關(guān)鍵詞個(gè)數(shù)類型錯(cuò)誤！')
    if not isinstance(custom_words, list):
        raise ValueError('自定義關(guān)鍵詞類型錯(cuò)誤！')
    if not isinstance(stop_words, list):
        raise ValueError('屏蔽關(guān)鍵詞類型錯(cuò)誤！')
    if not isinstance(query_pattern, str):
        raise ValueError('查詢模式類型錯(cuò)誤！')

    # 添加自定義關(guān)鍵詞
    for word in custom_words:
        jieba.add_word(word)

    if query_pattern == 'searchEngine':
        key_words = jieba.cut_for_search(text_content)
    elif query_pattern == 'entire':
        key_words = jieba.cut(text_content, cut_all=True, use_paddle=True)
    elif query_pattern == 'precision':
        key_words = jieba.cut(text_content, cut_all=False, use_paddle=True)
    else:
        return []

    # print("拆分后的詞: %s" % " ".join(key_words))

    # 過濾后的關(guān)鍵詞
    stop_words = set(stop_words)
    word_count = Counter()
    for word in key_words:
        if len(word) > 1 and word not in stop_words:
            word_count[word] += 1

    # res_words = list()
    # for data in word_count.most_common(key_word_need_num):
    #     res_words.append(data[0])
    # return res_words

    return word_count

def drawWordsCloud(word_count, save_img_filePath='', img_mask_filePath=''):
    # print(word_count)
    # print(type(word_count))

    if len(img_mask_filePath) != 0:
        img_mask = np.array(Image.open(img_mask_filePath)) #打開遮罩圖片,將圖片轉(zhuǎn)換為數(shù)組
        wc = wordcloud.WordCloud(font_path='/Library/Fonts/Arial Unicode.ttf',# 設(shè)置中文字體，詞云默認(rèn)字體是“DroidSansMono.ttf字體庫”，不支持中文
                                 background_color="white",  # 設(shè)置背景顏色
                                 max_words=200,  # 設(shè)置最大顯示的字?jǐn)?shù)
                                 max_font_size=50,  # 設(shè)置字體最大值
                                 random_state=30,  # 設(shè)置有多少種隨機(jī)生成狀態(tài)，即有多少種配色方案
                                 width=400,
                                 height=200,
                                 mask=img_mask
                                 )
    else:
        wc = wordcloud.WordCloud(font_path='/Library/Fonts/Arial Unicode.ttf',# 設(shè)置中文字體，詞云默認(rèn)字體是“DroidSansMono.ttf字體庫”，不支持中文
                                 background_color="white",  # 設(shè)置背景顏色
                                 max_words=200,  # 設(shè)置最大顯示的字?jǐn)?shù)
                                 max_font_size=50,  # 設(shè)置字體最大值
                                 random_state=30,  # 設(shè)置有多少種隨機(jī)生成狀態(tài)，即有多少種配色方案
                                 width=400,
                                 height=200
                                 )
    # 繪圖
    wc.generate_from_frequencies(word_count)   #從字典生成詞云
    plt.imshow(wc)      #顯示詞云
    plt.axis('off')     #關(guān)閉坐標(biāo)軸
    plt.show()          #顯示圖像

    # 保存圖片
    if len(save_img_filePath) != 0:
        wc.to_file(save_img_filePath)
    else:
        pass

#-*- coding : utf-8-*-
import jieba
from collections import Counter
import paddle

import wordcloud    #詞云展示庫
import matplotlib.pyplot as plt     #圖像展示庫

import time

from PIL import Image
import numpy as np

def timer(func):
    def calculateTime(*args, **kwargs):
        t = time.perf_counter()
        result = func(*args, **kwargs)
        print(f'func {func.__name__} coast time:{time.perf_counter() - t:.8f} s')
        return result
    return calculateTime

def readText(text_file_path):
    with open(text_file_path, encoding='gbk') as f: #
        content = f.read()
    return content

@timer
def getRecommondArticleKeyword(text_content,  key_word_need_num = 10, custom_words = [], stop_words =[], query_pattern = 'searchEngine'):
    '''
    :param text_content: 文本字符串
    :param key_word_need_num: 需要的關(guān)鍵詞數(shù)量
    :param custom_words: 自定義關(guān)鍵詞
    :param stop_words: 不查詢關(guān)鍵詞
    :param query_pattern:
    precision:精確模式————試圖將句子最精確地切開，適合文本分析；
    entire：全模式————把句子中所有的可以成詞的詞語都掃描出來, 速度非?？欤遣荒芙鉀Q歧義；
    searchEngine:搜索引擎模式————在精確模式的基礎(chǔ)上，對(duì)長詞再次切分，提高召回率，適合用于搜索引擎分詞；
    paddle模式————利用PaddlePaddle深度學(xué)習(xí)框架，訓(xùn)練序列標(biāo)注（雙向GRU）網(wǎng)絡(luò)模型實(shí)現(xiàn)分詞。同時(shí)支持詞性標(biāo)注。
    :return:
    '''
    # jieba.enable_paddle()
    # paddle.fluid.install_check.run_check()
    if not isinstance(text_content, str):
        raise ValueError('文本字符串類型錯(cuò)誤！')
    if not isinstance(key_word_need_num, int):
        raise ValueError('關(guān)鍵詞個(gè)數(shù)類型錯(cuò)誤！')
    if not isinstance(custom_words, list):
        raise ValueError('自定義關(guān)鍵詞類型錯(cuò)誤！')
    if not isinstance(stop_words, list):
        raise ValueError('屏蔽關(guān)鍵詞類型錯(cuò)誤！')
    if not isinstance(query_pattern, str):
        raise ValueError('查詢模式類型錯(cuò)誤！')

    # 添加自定義關(guān)鍵詞
    for word in custom_words:
        jieba.add_word(word)

    if query_pattern == 'searchEngine':
        key_words = jieba.cut_for_search(text_content)
    elif query_pattern == 'entire':
        key_words = jieba.cut(text_content, cut_all=True, use_paddle=True)
    elif query_pattern == 'precision':
        key_words = jieba.cut(text_content, cut_all=False, use_paddle=True)
    else:
        return []

    # print("拆分后的詞: %s" % " ".join(key_words))

    # 過濾后的關(guān)鍵詞
    stop_words = set(stop_words)
    word_count = Counter()
    for word in key_words:
        if len(word) > 1 and word not in stop_words:
            word_count[word] += 1

    # res_words = list()
    # for data in word_count.most_common(key_word_need_num):
    #     res_words.append(data[0])
    # return res_words

    return word_count

def drawWordsCloud(word_count, save_img_filePath='', img_mask_filePath=''):
    # print(word_count)
    # print(type(word_count))

    if len(img_mask_filePath) != 0:
        img_mask = np.array(Image.open(img_mask_filePath)) #打開遮罩圖片,將圖片轉(zhuǎn)換為數(shù)組
        wc = wordcloud.WordCloud(font_path='/Library/Fonts/Arial Unicode.ttf',# 設(shè)置中文字體，詞云默認(rèn)字體是“DroidSansMono.ttf字體庫”，不支持中文
                                 background_color="white",  # 設(shè)置背景顏色
                                 max_words=200,  # 設(shè)置最大顯示的字?jǐn)?shù)
                                 max_font_size=50,  # 設(shè)置字體最大值
                                 random_state=30,  # 設(shè)置有多少種隨機(jī)生成狀態(tài)，即有多少種配色方案
                                 width=400,
                                 height=200,
                                 mask=img_mask
                                 )
    else:
        wc = wordcloud.WordCloud(font_path='/Library/Fonts/Arial Unicode.ttf',# 設(shè)置中文字體，詞云默認(rèn)字體是“DroidSansMono.ttf字體庫”，不支持中文
                                 background_color="white",  # 設(shè)置背景顏色
                                 max_words=200,  # 設(shè)置最大顯示的字?jǐn)?shù)
                                 max_font_size=50,  # 設(shè)置字體最大值
                                 random_state=30,  # 設(shè)置有多少種隨機(jī)生成狀態(tài)，即有多少種配色方案
                                 width=400,
                                 height=200
                                 )
    # 繪圖
    wc.generate_from_frequencies(word_count)   #從字典生成詞云
    plt.imshow(wc)      #顯示詞云
    plt.axis('off')     #關(guān)閉坐標(biāo)軸
    plt.show()          #顯示圖像

    # 保存圖片
    if len(save_img_filePath) != 0:
        wc.to_file(save_img_filePath)
    else:
        pass



if __name__ == '__main__':
    pass
    # /Users/mac/Downloads/work/retailSoftware/公司項(xiàng)目/test.txt
    text_file_path = "/Users/mac/Downloads/電子書/編程思想/相約星期二/相約星期二.txt"
    # text_file_path = "/Users/mac/Downloads/work/retailSoftware/公司項(xiàng)目/test3.txt"
    text_content = readText(text_file_path)
    # print(text_content)
    # print(JNI_API_getRecommondArticleKeyword(text_content))
    img_mask_filePath = '/Users/mac/Desktop/截屏2021-08-20 下午4.02.10.png'
    img_save_filePath = '/Users/mac/Downloads/test9.png'
    drawWordsCloud(getRecommondArticleKeyword(text_content), img_save_filePath, img_mask_filePath)