khana/khana/main.py

89 lines
2.9 KiB
Python

import math
from people.models import Gymnast
from objectives.models import Skill
def suggest_routine(
request,
routine_length,
total_difficulty_score=None,
competition=True,
logic=True,
gymnast=None,
last_jump=None,
):
""" Construit et propose des séries.
Args:
routine_length (int): nombre de sauts que doit contenir la série.
total_difficulty_score (int): score de difficulté total souhaité de la série.
competition (bool): indique si la série doit pouvoir être utilisée en compétition.
logic (bool): indique si la série doit suivre certaines règles de logique (sportive).
gymnast (gymnast): gymnaste.
last_jump (skill): dernier saut sélectionné pour la série.
Returns:
??? (list): liste des séries correspondantes aux criètres.
"""
current_routine = []
if last_jump:
skill_list = Skill.objects.filter(
departure=last_jump.landing, difficulty__lte=total_difficulty_score
)
if logic and last_jump.landing == "Debout":
skill_list = skill_list.exclude(rotationType=last_jump.rotationType)
else:
skill_list = Skill.objects.filter(departure__longLabel="Debout")
if competition:
skill_list = skill_list.filter(is_competitive=True)
if logic and total_difficulty_score:
min_difficulty_score = math.ceil(max(0, ((total_difficulty_score / 10) - 5)))
if total_difficulty_score <= 65:
max_difficulty_score = math.ceil(total_difficulty_score / 5) + 1
elif total_difficulty_score <= 120:
max_difficulty_score = math.ceil(total_difficulty_score / 10) + 7
else:
max_difficulty_score = math.ceil(total_difficulty_score / 15) + 11
skill_list = skill_list.filter(
difficulty__gte=min_difficulty_score, difficulty__lte=max_difficulty_score
)
for skill in skill_list:
current_routine.append(skill)
current_routine.append(
self.suggest_routine(
request,
total_difficulty_score - skill.difficulty,
max_difficulty_score,
routine_length - 1,
competition,
logic,
gymnast,
skill,
)
)
current_routine.pop()
# def knapSack(W, wt, val, n):
# K = [[0 for x in range(W+1)] for x in range(n+1)]
# for i in range(n+1):
# for w in range(W+1):
# if i==0 or w==0:
# K[i][w] = 0
# elif wt[i-1] <= w:
# K[i][w] = max(val[i-1] + K[i-1][w-wt[i-1]], K[i-1][w])
# else:
# K[i][w] = K[i-1][w]
# return K[n][W]
# val = [60, 100, 120]
# wt = [10, 20, 30]
# W = 50
# n = len(val)
# print(knapSack(W, wt, val, n))