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from django.db import models
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# Create your models here.
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from django.db import models
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from django.db.models import Model, Max, Min
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import random
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from django.db.models import F
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class Student(models.Model):
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name = models.CharField(max_length=32)
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sid = models.CharField(max_length=20)
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credit = models.FloatField()
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class_name = models.CharField(max_length=32)
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probability = models.FloatField()
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max = models.FloatField()
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min = models.FloatField()
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def prob(self,class_name,credit): #由积分求概率
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stu = Student.objects.filter(class_name=class_name)
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credits = [student.credit for student in stu]
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max_credit = max(credits)
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min_credit = max(credits)
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if max_credit == min_credit:
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return 1
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else:
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return (credit - min_credit)/(max_credit - min_credit)
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def callstu(self,class_name,num,mode): #点名的函数，输入要点的人数，返回这些人的学号姓名，不重复,（基础模式）
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sts = Student.objects.filter(class_name=class_name)
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probabilities = []
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if mode == 1 or mode == 2: #基础模式和得分加倍的筛选概率不变
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probabilities = [student.probability for student in sts]
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elif mode == 3 : #三五成群
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for s1 in sts:
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if (int(s1.credit) % 3 == 0 or int(s1.credit) % 5 == 0) and s1.credit != 0:
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probabilities.append(2*s1.probability)
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else:
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probabilities.append(s1.probability)
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else: #六六大顺
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for s1 in sts:
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if int(s1.credit) % 6 == 0 and s1.credit != 0:
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probabilities.append(2*s1.probability)
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else:
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probabilities.append(s1.probability)
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if probabilities:
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max_probability = max(probabilities)
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min_probability = min(probabilities)
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else:
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max_probability = -1
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min_probability = -1
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if num > sts.count():
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data = {'message':0}
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return data
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else:
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result = {}
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if mode == 1 or mode == 2:
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time = 0 #筛选出一个学生需要生成的随机数的次数 （刚开始比较稀疏，要避免一直不能完成抽取条件的情况）设置上限为10
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while len(result) < num: #基础模式和得分加倍模式
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if time == 10: #当为了筛选一个人而生成了10次随机数后，由于太浪费时间，直接筛选剩下的人
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flag = 0
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while flag == 0:
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s = sts.order_by('?').first()
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if s.sid not in result:
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result[s.name] = s.sid
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time = 0
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flag += 1
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else:
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random_probability = random.uniform(min_probability, max_probability)
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time += 1
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s = sts.filter(probability__gte = random_probability).order_by('?').first()
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if s.sid not in result:
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result[s.name] = s.sid
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time = 0 #当筛选出一个的时候，为下一次的筛选置为0
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elif mode == 3: #三五成群
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time = 0 # 筛选出一个学生需要生成的随机数的次数 （刚开始比较稀疏，要避免一直不能完成抽取条件的情况）设置上限为10
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while len(result) < num: #一个随机数就选出一个学生
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if time == 10:
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flag = 0
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while flag == 0:
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s = sts.order_by('?').first()
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if s.sid not in result:
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result[s.name] = s.sid
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time = 0
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flag += 1
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else:
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random_probability = random.uniform(min_probability, max_probability)
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# print(random_probability)
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ss1 = [student for student in sts if ( int(student.credit) % 5 == 0
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or int(student.credit) % 3 == 0 )and student.probability > random_probability/2]
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ss2 =[student for student in sts if student.credit > random_probability]
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ss = list(set(ss1+ss2))
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random_student = random.choice(ss)
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if random_student.id not in result:
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result[random_student.name] = random_student.sid
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time = 0
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print(result)
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elif mode == 4: #六六大顺
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time = 0 # 筛选出一个学生需要生成的随机数的次数 （刚开始比较稀疏，要避免一直不能完成抽取条件的情况）设置上限为10
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while len(result) < num: #一个随机数就选出一个学生
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if time == 10:
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flag = 0
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while flag == 0:
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s = sts.order_by('?').first()
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if s.sid not in result:
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result[s.name] = s.sid
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time = 0
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flag += 1
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else:
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random_probability = random.uniform(min_probability, max_probability)
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ss1 = [student for student in sts if int(student.credit) % 6 == 0 and student.probability > random_probability/2]
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ss2 = [student for student in sts if student.credit > random_probability]
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ss = list(set(ss1+ss2))
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random_student = random.choice(ss)
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if random_student.id not in result:
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result[random_student.name] = random_student.sid
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time = 0
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data = {'message':1,
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'result':result}
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return data
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def updateinfor (self,point,class_name,sid,style): #更新积分和概率
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if style == 1 :
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point = point
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if style == 2 :
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point = point * 2
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#先改变该学生的积分值
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current_s = Student.objects.filter(class_name=class_name, sid=sid).first()
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current_credit = current_s.credit
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current_s.credit = current_credit + point
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current_s.save()
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#查找最新的最大或最小值，与原来写在表中的上次更新的最大值和最小值做对比
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max_credit = Student.objects.filter(class_name=class_name).aggregate(max_credit=Max('credit'))['max_credit']
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min_credit = Student.objects.filter(class_name=class_name).aggregate(min_credit=Min('credit'))['min_credit']
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s = Student.objects.filter(class_name=class_name).first() #找未更新的值
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max_credit0 = s.max
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min_credit0 = s.min
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fm = max_credit - min_credit #最新的分母
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#如果不影响2个最值，仅改变单个学生的概率
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if max_credit == max_credit0 and min_credit == min_credit0:
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if fm == 0:
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prob = 1.0
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else:
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prob = 1 - (current_s.credit - min_credit)/fm
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current_s.probability = prob # 直接设置字段的值
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current_s.save() # 调用 save 方法保存更改
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#影响积分最大值和最小值其中的一个时，所有学生的概率都需要改变，先将最新的最大值和最小值写入数据库
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else:
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#将最新的最大值和最小值写入数据库
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sts = Student.objects.filter(class_name=class_name)
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sts.update(min = min_credit, max = max_credit)
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#更新所有学生的概率
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if fm == 0 :
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sts.update(probability = 1.0)
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else:
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sts.update(probability = (1 - (F('credit') - min_credit)/fm))
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#耗时最大，性能改进前的代码
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# def updateinfor (self,point,class_name,sid,style): #更新积分和概率
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# if style == 1 :
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# point = point
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# if style == 2 :
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# point = point * 2
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# #先改变该学生的积分值
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# current_s = Student.objects.filter(class_name=class_name, sid=sid).first()
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# current_credit = current_s.credit
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# current_s.credit = current_credit + point
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# current_s.save()
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# #查找最新的最大或最小值，与原来写在表中的上次更新的最大值和最小值做对比
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# max_credit = Student.objects.filter(class_name=class_name).aggregate(max_credit=Max('credit'))['max_credit']
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# min_credit = Student.objects.filter(class_name=class_name).aggregate(min_credit=Min('credit'))['min_credit']
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# fm = max_credit - min_credit #最新的分母
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# sts = Student.objects.filter(class_name=class_name)
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# sts.update(min=min_credit, max=max_credit)
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# # 更新所有学生的概率
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# if fm == 0:
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# sts.update(probability=1.0)
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# else:
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# sts.update(probability=(1 - (F('credit') - min_credit) / fm))
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