mirror of https://gitlab.crans.org/bde/nk20
302 lines
12 KiB
Python
302 lines
12 KiB
Python
# Copyright (C) 2018-2023 by BDE ENS Paris-Saclay
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# SPDX-License-Identifier: GPL-3.0-or-later
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import time
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from functools import lru_cache
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from random import Random
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from django import forms
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from django.db import transaction
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from django.db.models import Q
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from django.utils.translation import gettext_lazy as _
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from .base import WEISurvey, WEISurveyInformation, WEISurveyAlgorithm, WEIBusInformation
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from ...models import WEIMembership
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WORDS = {
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"ambiance":["Question", {1:"réponse 1", 2:"réponse 2", 3:"réponse 3", 4:"réponse 4", 5:"réponse 5"}],
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"musique":["Question", {1:"réponse 1", 2:"réponse 2", 3:"réponse 3", 4:"réponse 4", 5:"réponse 5"}],
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"boisson":["Question", {1:"réponse 1", 2:"réponse 2", 3:"réponse 3", 4:"réponse 4", 5:"réponse 5"}],
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"beauferie":["Question", {1:"réponse 1", 2:"réponse 2", 3:"réponse 3", 4:"réponse 4", 5:"réponse 5"}],
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"sommeil":["Question", {1:"réponse 1", 2:"réponse 2", 3:"réponse 3", 4:"réponse 4", 5:"réponse 5"}],
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"vacances":["Question", {1:"réponse 1", 2:"réponse 2", 3:"réponse 3", 4:"réponse 4", 5:"réponse 5"}],
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"activite":["Question", {1:"réponse 1", 2:"réponse 2", 3:"réponse 3", 4:"réponse 4", 5:"réponse 5"}],
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"hygiene":["Question", {1:"réponse 1", 2:"réponse 2", 3:"réponse 3", 4:"réponse 4", 5:"réponse 5"}],
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"animal":["Question", {1:"réponse 1", 2:"réponse 2", 3:"réponse 3", 4:"réponse 4", 5:"réponse 5"}],
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"fensfoire":["Question", {1:"réponse 1", 2:"réponse 2", 3:"réponse 3", 4:"réponse 4", 5:"réponse 5"}],
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"kokarde":["Question", {1:"réponse 1", 2:"réponse 2", 3:"réponse 3", 4:"réponse 4", 5:"réponse 5"}],
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"copain":["Question", {1:"réponse 1", 2:"réponse 2", 3:"réponse 3", 4:"réponse 4", 5:"réponse 5"}],
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"vie":["Question", {1:"réponse 1", 2:"réponse 2", 3:"réponse 3", 4:"réponse 4", 5:"réponse 5"}],
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"jeux":["Question", {1:"réponse 1", 2:"réponse 2", 3:"réponse 3", 4:"réponse 4", 5:"réponse 5"}],
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"calin":["Question", {1:"réponse 1", 2:"réponse 2", 3:"réponse 3", 4:"réponse 4", 5:"réponse 5"}],
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"vommi":["Question", {1:"réponse 1", 2:"réponse 2", 3:"réponse 3", 4:"réponse 4", 5:"réponse 5"}],
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"kfet":["Question", {1:"réponse 1", 2:"réponse 2", 3:"réponse 3", 4:"réponse 4", 5:"réponse 5"}],
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"fatigue":["Question", {1:"réponse 1", 2:"réponse 2", 3:"réponse 3", 4:"réponse 4", 5:"réponse 5"}],
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"duree trajet":["Question", {1:"réponse 1", 2:"réponse 2", 3:"réponse 3", 4:"réponse 4", 5:"réponse 5"}],
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"scolarite":["Question", {1:"réponse 1", 2:"réponse 2", 3:"réponse 3", 4:"réponse 4", 5:"réponse 5"}]
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}
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class WEISurveyForm2023(forms.Form):
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"""
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Survey form for the year 2023.
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Members answer 20 question, from which we calculate the best associated bus.
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"""
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def __init__(self,**kwargs):
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super().__init__(**kwargs)
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for question in WORDS:
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self.fields[question] = forms.ChoiceField(
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label=WORDS[question][0]+question,
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widget=forms.RadioSelect(),
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)
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def set_registration(self, registration):
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"""
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Filter the bus selector with the buses of the current WEI.
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"""
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information = WEISurveyInformation2023(registration)
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if not information.seed:
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information.seed = int(1000 * time.time())
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information.save(registration)
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registration._force_save = True
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registration.save()
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# if self.data:
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# for question in WORDS:
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# self.fields[question].choices = [answer for answer in WORDS[question][1]]
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# if self.is_valid():
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# return
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# rng = Random(information.seed) # add someting if it's alwais the same
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# questions = list(WORDS.keys())
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# rng.shuffle(questions)
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# for question in questions:
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for question in WORDS:
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answers = [(answer, WORDS[question][1][answer]) for answer in WORDS[question][1]]
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self.fields[question].choices = answers
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class WEIBusInformation2023(WEIBusInformation):
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"""
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For each question, the bus has ordered answers
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"""
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scores: dict
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def __init__(self, bus):
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self.scores = {}
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for question in WORDS:
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self.scores[question] = []
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super().__init__(bus)
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class WEISurveyInformation2023(WEISurveyInformation):
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"""
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We store the id of the selected bus. We store only the name, but is not used in the selection:
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that's only for humans that try to read data.
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"""
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# Random seed that is stored at the first time to ensure that words are generated only once
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seed = 0
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def __init__(self, registration):
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for question in WORDS:
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setattr(self, str(question), None)
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super().__init__(registration)
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class WEISurvey2023(WEISurvey):
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"""
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Survey for the year 2023.
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"""
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@classmethod
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def get_year(cls):
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return 2023
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@classmethod
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def get_survey_information_class(cls):
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return WEISurveyInformation2023
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def get_form_class(self):
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return WEISurveyForm2023
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def update_form(self, form):
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"""
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Filter the bus selector with the buses of the WEI.
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"""
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form.set_registration(self.registration)
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@transaction.atomic
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def form_valid(self, form):
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for question in WORDS:
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answer = form.cleaned_data[question]
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setattr(self.information, question, answer)
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self.save()
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@classmethod
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def get_algorithm_class(cls):
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return WEISurveyAlgorithm2023
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def is_complete(self) -> bool:
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"""
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The survey is complete once the bus is chosen.
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"""
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for question in WORDS:
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if not getattr(self.information, question):
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return False
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return True
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@classmethod
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@lru_cache()
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def word_mean(cls, word):
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"""
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Calculate the mid-score given by all buses.
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"""
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buses = cls.get_algorithm_class().get_buses()
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return sum([cls.get_algorithm_class().get_bus_information(bus).scores[word] for bus in buses]) / buses.count()
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@lru_cache()
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def score(self, bus):
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if not self.is_complete():
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raise ValueError("Survey is not ended, can't calculate score")
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bus_info = self.get_algorithm_class().get_bus_information(bus)
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# Score is the given score by the bus subtracted to the mid-score of the buses.
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s = sum(bus_info.scores[getattr(self.information, 'word' + str(i))]
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- self.word_mean(getattr(self.information, 'word' + str(i))) for i in range(1, 21)) / 20
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return s
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@lru_cache()
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def scores_per_bus(self):
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return {bus: self.score(bus) for bus in self.get_algorithm_class().get_buses()}
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@lru_cache()
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def ordered_buses(self):
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values = list(self.scores_per_bus().items())
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values.sort(key=lambda item: -item[1])
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return values
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@classmethod
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def clear_cache(cls):
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cls.word_mean.cache_clear()
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return super().clear_cache()
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class WEISurveyAlgorithm2023(WEISurveyAlgorithm):
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"""
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The algorithm class for the year 2023.
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We use Gale-Shapley algorithm to attribute 1y students into buses.
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"""
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@classmethod
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def get_survey_class(cls):
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return WEISurvey2023
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@classmethod
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def get_bus_information_class(cls):
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return WEIBusInformation2023
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def run_algorithm(self, display_tqdm=False):
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"""
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Gale-Shapley algorithm implementation.
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We modify it to allow buses to have multiple "weddings".
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"""
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surveys = list(self.get_survey_class()(r) for r in self.get_registrations()) # All surveys
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surveys = [s for s in surveys if s.is_complete()] # Don't consider invalid surveys
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# Don't manage hardcoded people
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surveys = [s for s in surveys if not hasattr(s.information, 'hardcoded') or not s.information.hardcoded]
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# Reset previous algorithm run
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for survey in surveys:
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survey.free()
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survey.save()
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non_men = [s for s in surveys if s.registration.gender != 'male']
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men = [s for s in surveys if s.registration.gender == 'male']
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quotas = {}
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registrations = self.get_registrations()
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non_men_total = registrations.filter(~Q(gender='male')).count()
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for bus in self.get_buses():
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free_seats = bus.size - WEIMembership.objects.filter(bus=bus, registration__first_year=False).count()
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# Remove hardcoded people
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free_seats -= WEIMembership.objects.filter(bus=bus, registration__first_year=True,
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registration__information_json__icontains="hardcoded").count()
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quotas[bus] = 4 + int(non_men_total / registrations.count() * free_seats)
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tqdm_obj = None
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if display_tqdm:
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from tqdm import tqdm
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tqdm_obj = tqdm(total=len(non_men), desc="Non-hommes")
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# Repartition for non men people first
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self.make_repartition(non_men, quotas, tqdm_obj=tqdm_obj)
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quotas = {}
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for bus in self.get_buses():
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free_seats = bus.size - WEIMembership.objects.filter(bus=bus, registration__first_year=False).count()
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free_seats -= sum(1 for s in non_men if s.information.selected_bus_pk == bus.pk)
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# Remove hardcoded people
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free_seats -= WEIMembership.objects.filter(bus=bus, registration__first_year=True,
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registration__information_json__icontains="hardcoded").count()
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quotas[bus] = free_seats
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if display_tqdm:
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tqdm_obj.close()
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from tqdm import tqdm
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tqdm_obj = tqdm(total=len(men), desc="Hommes")
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self.make_repartition(men, quotas, tqdm_obj=tqdm_obj)
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if display_tqdm:
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tqdm_obj.close()
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# Clear cache information after running algorithm
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WEISurvey2023.clear_cache()
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def make_repartition(self, surveys, quotas=None, tqdm_obj=None):
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free_surveys = surveys.copy() # Remaining surveys
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while free_surveys: # Some students are not affected
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survey = free_surveys[0]
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buses = survey.ordered_buses() # Preferences of the student
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for bus, current_score in buses:
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if self.get_bus_information(bus).has_free_seats(surveys, quotas):
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# Selected bus has free places. Put student in the bus
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survey.select_bus(bus)
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survey.save()
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free_surveys.remove(survey)
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break
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else:
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# Current bus has not enough places. Remove the least preferred student from the bus if existing
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least_preferred_survey = None
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least_score = -1
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# Find the least student in the bus that has a lower score than the current student
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for survey2 in surveys:
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if not survey2.information.valid or survey2.information.get_selected_bus() != bus:
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continue
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score2 = survey2.score(bus)
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if current_score <= score2: # Ignore better students
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continue
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if least_preferred_survey is None or score2 < least_score:
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least_preferred_survey = survey2
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least_score = score2
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if least_preferred_survey is not None:
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# Remove the least student from the bus and put the current student in.
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# If it does not exist, choose the next bus.
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least_preferred_survey.free()
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least_preferred_survey.save()
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free_surveys.append(least_preferred_survey)
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survey.select_bus(bus)
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survey.save()
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free_surveys.remove(survey)
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break
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else:
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raise ValueError(f"User {survey.registration.user} has no free seat")
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if tqdm_obj is not None:
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tqdm_obj.n = len(surveys) - len(free_surveys)
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tqdm_obj.refresh()
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