Merge pull request 'BUG543-JiWenkai' (#153) from BUG543-JiWenkai into Alpha-snapshot20240618

Reviewed-on: #153
Bug579-LuKangyang
mrlan 2024-08-28 07:50:49 +08:00
commit 262604e761
3 changed files with 74 additions and 19 deletions

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@ -7,7 +7,7 @@
import pickle
import math
from wordfreqCMD import remove_punctuation, freq, sort_in_descending_order, sort_in_ascending_order
from wordfreqCMD import remove_punctuation, freq, sort_in_descending_order, sort_in_ascending_order, map_percentages_to_levels
import snowballstemmer
@ -94,30 +94,58 @@ def revert_dict(d):
return d2
def user_difficulty_level(d_user, d):
def user_difficulty_level(d_user, d, calc_func=0):
'''
two ways to calculate difficulty_level
set calc_func!=0 to use sqrt, otherwise use weighted average
'''
if calc_func != 0:
# calculation function 1: sqrt
d_user2 = revert_dict(d_user) # key is date, and value is a list of words added in that date
geometric = 0
count = 0
for date in sorted(d_user2.keys(),
reverse=True): # most recently added words are more important while determining user's level
lst = d_user2[date] # a list of words
lst2 = [] # a list of tuples, (word, difficulty level)
for word in lst:
if word in d:
lst2.append((word, d[word]))
lst3 = sort_in_ascending_order(lst2) # easiest tuple first
# print(lst3)
for t in lst3:
word = t[0]
hard = t[1]
# print('WORD %s HARD %4.2f' % (word, hard))
geometric = geometric + math.log(hard)
count += 1
return math.exp(geometric / max(count, 1))
# calculation function 2: weighted average
d_user2 = revert_dict(d_user) # key is date, and value is a list of words added in that date
count = 0
geometric = 1
for date in sorted(d_user2.keys(),
reverse=True): # most recently added words are more important while determining user's level
count = {} # number of all kinds of words
percentages = {} # percentages of all kinds of difficulties
total = 0 # total words
for date in d_user2.keys():
lst = d_user2[date] # a list of words
lst2 = [] # a list of tuples, (word, difficulty level)
for word in lst:
if word in d:
lst2.append((word, d[word]))
if d[word] not in count:
count[d[word]] = 0
count[d[word]] += 1
total += 1
lst3 = sort_in_ascending_order(lst2) # easiest tuple first
# print(lst3)
for t in lst3:
word = t[0]
hard = t[1]
# print('WORD %s HARD %4.2f' % (word, hard))
geometric = geometric * (hard)
count += 1
if count >= 10:
return geometric ** (1 / count)
if total == 0:
return 1
for k in count.keys():
percentages[k] = count[k] / total
weight = map_percentages_to_levels(percentages)
sum = 0
for k in weight.keys():
sum += weight[k] * k
return sum
return geometric ** (1 / max(count, 1))
def text_difficulty_level(s, d):

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@ -73,6 +73,7 @@
<button type="button" class="btn-close" data-bs-dismiss="alert" aria-label="Close"></button>
</div>
{% endfor %}
<div class="pagination">
<button class="arrow" id="load_pre_article" onclick="load_pre_article();Reader.stopRead()" title="Previous Article">
<i class="fas fa-chevron-left"></i> 上一篇

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@ -10,6 +10,32 @@ import operator
import os, sys # 引入模块sys因为我要用里面的sys.argv列表中的信息来读取命令行参数。
import pickle_idea
def map_percentages_to_levels(percentages):
'''
功能按照加权平均难度给生词本计算难度分计算权重的规则是(10 - 该词汇难度) * 该难度词汇占总词汇的比例再进行归一化处理
输入难度占比字典键代表难度3~8值代表每种难度的单词的占比
输出权重字典键代表难度3~8值代表每种难度的单词的权重
'''
# 已排序的键
sorted_keys = sorted(percentages.keys())
# 计算权重和权重总和
sum = 0 # 总和
levels_proportions = {}
for k in sorted_keys:
levels_proportions[k] = 10 - k
for k in sorted_keys:
levels_proportions[k] *= percentages[k]
sum += levels_proportions[k]
# 归一化权重到权重总和为1
for k in sorted_keys:
levels_proportions[k] /= sum
return levels_proportions
def freq(fruit):
'''
功能 把字符串转成列表 目的是得到每个单词的频率