-
Notifications
You must be signed in to change notification settings - Fork 0
Commit
This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
- Loading branch information
1 parent
f79d74f
commit 3363349
Showing
1 changed file
with
50 additions
and
0 deletions.
There are no files selected for viewing
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Original file line number | Diff line number | Diff line change |
---|---|---|
@@ -0,0 +1,50 @@ | ||
from .db import get_random_tocfl_choices_from_db | ||
import discord | ||
from typing import List, Tuple | ||
import pandas as pd | ||
from random import shuffle | ||
from .chewing import to_chewing | ||
|
||
# sys.path.append(str(Path(__file__).parent.parent.parent)) # I hate python imports | ||
from modules.quiz.multiple_choice import MultipleChoiceView, QuizChoice | ||
|
||
|
||
def _db_results_to_df(results: List[dict]) -> pd.DataFrame: | ||
df = pd.DataFrame(results) | ||
# for "vocab" and "pinyin" columns: only keep the first part of the string | ||
df["vocab"] = df["vocab"].apply(lambda x: x.split("/")[0]) | ||
df["pinyin"] = df["pinyin"].apply(lambda x: x.split("/")[0]) | ||
# add zhuyin column | ||
df["zhuyin"] = df["pinyin"].apply(to_chewing).str.replace("\u3000", " ") # replace full-width space with half-width space for now | ||
# add "pronunciation" column as a combination of pinyin and zhuyin | ||
df["pronunciation"] = df["pinyin"] + " / " + df["zhuyin"] | ||
# drop the "pinyin" and "zhuyin" columns | ||
df.drop(columns=["pinyin", "zhuyin"], inplace=True) | ||
return df.set_index("id") | ||
|
||
def df_results_to_choices(df: pd.DataFrame, | ||
num_choices:int, | ||
is_ask_pronunciation:bool=True | ||
) -> Tuple[List[QuizChoice], str]: | ||
col_to_display, col_to_ask = ("pronunciation", "vocab") if is_ask_pronunciation else ("vocab", "pronunciation") | ||
# select one row as the correct answer | ||
correct_row_index = df.sample().index[0] | ||
vocab_to_display = df.loc[correct_row_index, col_to_ask] | ||
# convert to QuizChoice object | ||
correct_choice = QuizChoice(df.loc[correct_row_index, col_to_display], is_correct=True) | ||
# select incorrect choices as rows that do not have the same pronunciation as the correct answer | ||
incorrect_rows = df[df[col_to_display] != correct_choice.label].sample(num_choices-1) | ||
incorrect_choices = [QuizChoice(row[col_to_display], is_correct=False) for _, row in incorrect_rows.iterrows()] | ||
# shuffle the choices | ||
choices = [correct_choice] + incorrect_choices | ||
shuffle(choices) | ||
return choices, vocab_to_display | ||
|
||
|
||
if __name__ == "__main__": | ||
num_choices = 4 | ||
choices = get_random_tocfl_choices_from_db(num_choices=num_choices) | ||
df = _db_results_to_df(choices) | ||
choices, vocab_to_ask = df_results_to_choices(df, num_choices, is_ask_pronunciation=False) | ||
print(f"Choose the correct answer for: {vocab_to_ask}") | ||
print(f"Choices:\n{'\n'.join(['* ' + choice.label for choice in choices])}") |