345 lines
13 KiB
Python
345 lines
13 KiB
Python
import re
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import statistics
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from datetime import datetime
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from django.db.models import Sum, Avg
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from django.utils import timezone
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from utils.api import APIView
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from account.decorators import login_required
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from account.models import User, UserProfile, AdminType
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from submission.models import Submission, JudgeStatus
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class ClassRankAPI(APIView):
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"""获取班级排名列表"""
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def get(self, request):
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# 获取年级参数
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grade = int(request.GET.get("grade"))
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# 获取所有有用户的班级
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classes = (
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User.objects.filter(
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class_name__isnull=False,
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is_disabled=False,
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admin_type__in=[AdminType.REGULAR_USER, AdminType.ADMIN],
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class_name__startswith=str(grade),
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)
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.values("class_name")
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.distinct()
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)
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class_stats = []
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for class_info in classes:
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class_name = class_info["class_name"]
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users = User.objects.filter(
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class_name=class_name,
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is_disabled=False,
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admin_type__in=[AdminType.REGULAR_USER, AdminType.ADMIN],
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)
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user_ids = list(users.values_list("id", flat=True))
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profiles = UserProfile.objects.filter(user_id__in=user_ids)
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total_ac = profiles.aggregate(total=Sum("accepted_number"))["total"] or 0
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total_submission = (
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profiles.aggregate(total=Sum("submission_number"))["total"] or 0
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)
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avg_ac = profiles.aggregate(avg=Avg("accepted_number"))["avg"] or 0
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user_count = users.count()
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class_stats.append(
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{
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"class_name": class_name,
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"user_count": user_count,
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"total_ac": int(total_ac),
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"total_submission": int(total_submission),
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"avg_ac": round(avg_ac, 2),
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"ac_rate": round(total_ac / total_submission * 100, 2)
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if total_submission > 0
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else 0,
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}
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)
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# 按总AC数排序
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class_stats.sort(key=lambda x: (-x["total_ac"], x["total_submission"]))
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# 添加排名
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for i, stat in enumerate(class_stats):
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stat["rank"] = i + 1
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return self.success(class_stats)
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class UserClassRankAPI(APIView):
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"""获取用户在班级中的排名"""
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@login_required
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def get(self, request):
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user = request.user
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if not user.class_name:
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return self.error("用户没有班级信息")
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scope = request.GET.get("scope", "").lower()
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show_all = scope == "all"
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try:
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limit = int(request.GET.get("limit", "10"))
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except ValueError:
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limit = 10
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if limit <= 0 or limit > 250:
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limit = 10
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try:
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offset = int(request.GET.get("offset", "0"))
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except ValueError:
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offset = 0
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if offset < 0:
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offset = 0
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# 获取同班所有用户
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class_users = User.objects.filter(
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class_name=user.class_name,
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is_disabled=False,
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admin_type__in=[AdminType.REGULAR_USER, AdminType.ADMIN],
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).select_related("userprofile")
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user_ranks = []
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for class_user in class_users:
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profile = class_user.userprofile
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user_ranks.append(
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{
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"user_id": class_user.id,
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"username": class_user.username,
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"accepted_number": profile.accepted_number,
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"submission_number": profile.submission_number,
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}
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)
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# 按AC数排序
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user_ranks.sort(key=lambda x: (-x["accepted_number"], x["submission_number"]))
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# 添加排名
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my_rank = -1
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for i, rank_info in enumerate(user_ranks):
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rank_info["rank"] = i + 1
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if rank_info["user_id"] == user.id:
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my_rank = i + 1
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trimmed_ranks = user_ranks
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if not show_all and my_rank > 0 and len(user_ranks) > 10:
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center_index = my_rank - 1
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start = max(0, center_index - 5)
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end = start + 10
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if end > len(user_ranks):
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end = len(user_ranks)
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start = max(0, end - 10)
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trimmed_ranks = user_ranks[start:end]
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elif show_all:
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trimmed_ranks = user_ranks[offset : offset + limit]
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return self.success(
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{
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"class_name": user.class_name,
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"my_rank": my_rank,
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"total": len(user_ranks),
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"ranks": trimmed_ranks,
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}
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)
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class ClassPKAPI(APIView):
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"""班级PK比较 - 多维度教育评价"""
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def post(self, request):
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class_names = request.data.get("class_name", [])
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if not class_names or len(class_names) < 2:
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return self.error("至少需要选择2个班级进行比较")
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# 获取时间段参数
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start_time = request.data.get("start_time")
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end_time = request.data.get("end_time")
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# 将时间字符串转换为datetime对象
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# 处理空字符串、None 或 undefined 的情况
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if start_time and isinstance(start_time, str) and start_time.strip():
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try:
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start_time = datetime.fromisoformat(start_time.replace("Z", "+00:00"))
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if timezone.is_naive(start_time):
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start_time = timezone.make_aware(start_time)
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except (ValueError, AttributeError):
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start_time = None
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else:
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start_time = None
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if end_time and isinstance(end_time, str) and end_time.strip():
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try:
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end_time = datetime.fromisoformat(end_time.replace("Z", "+00:00"))
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if timezone.is_naive(end_time):
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end_time = timezone.make_aware(end_time)
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except (ValueError, AttributeError):
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end_time = None
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else:
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end_time = None
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class_comparisons = []
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for class_name in class_names:
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users = User.objects.filter(
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class_name=class_name,
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is_disabled=False,
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admin_type__in=[AdminType.REGULAR_USER, AdminType.ADMIN],
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)
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user_ids = list(users.values_list("id", flat=True))
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# 获取所有学生的AC数列表（用于统计计算）
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profiles = UserProfile.objects.filter(user_id__in=user_ids)
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ac_list = sorted([p.accepted_number for p in profiles], reverse=True)
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submission_list = sorted(
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[p.submission_number for p in profiles], reverse=True
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)
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user_count = len(ac_list)
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if user_count == 0:
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continue
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# 基础统计
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total_ac = sum(ac_list)
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total_submission = sum(submission_list)
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avg_ac = statistics.mean(ac_list) if ac_list else 0
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# 中位数和分位数
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median_ac = statistics.median(ac_list) if ac_list else 0
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q1_ac = statistics.quantiles(ac_list, n=4)[0] if len(ac_list) > 1 else 0
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q3_ac = statistics.quantiles(ac_list, n=4)[2] if len(ac_list) > 1 else 0
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iqr = q3_ac - q1_ac
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# 标准差
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std_dev = statistics.stdev(ac_list) if len(ac_list) > 1 else 0
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# 前10名和后10名统计
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top_10_count = min(10, user_count)
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bottom_10_count = min(10, user_count)
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top_10_avg = (
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statistics.mean(ac_list[:top_10_count]) if top_10_count > 0 else 0
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)
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bottom_10_avg = (
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statistics.mean(ac_list[-bottom_10_count:])
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if bottom_10_count > 0
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else 0
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)
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# 前25%和后25%统计
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top_25_count = max(1, user_count // 4)
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bottom_25_count = max(1, user_count // 4)
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top_25_avg = (
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statistics.mean(ac_list[:top_25_count]) if top_25_count > 0 else 0
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)
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bottom_25_avg = (
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statistics.mean(ac_list[-bottom_25_count:])
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if bottom_25_count > 0
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else 0
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)
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# 优秀率（AC数 >= 中位数 + 标准差）
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# 使用中位数+标准差方法，既不受极端值影响，又能反映班级差异
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excellent_threshold = (
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median_ac + std_dev if std_dev > 0 else median_ac * 1.5
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)
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excellent_count = sum(1 for ac in ac_list if ac >= excellent_threshold)
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excellent_rate = (
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(excellent_count / user_count * 100) if user_count > 0 else 0
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)
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# 及格率（AC数 >= 平均值的0.5倍）
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pass_threshold = avg_ac * 0.5
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pass_count = sum(1 for ac in ac_list if ac >= pass_threshold)
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pass_rate = (pass_count / user_count * 100) if user_count > 0 else 0
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# 参与度（有提交记录的学生比例）
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active_count = sum(1 for sub in submission_list if sub > 0)
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active_rate = (active_count / user_count * 100) if user_count > 0 else 0
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# 时间段内的统计（如果提供了时间段）
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recent_stats = {}
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if start_time and end_time:
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submissions = Submission.objects.filter(
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user_id__in=user_ids,
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create_time__gte=start_time,
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create_time__lte=end_time,
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)
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recent_ac = (
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submissions.filter(result=JudgeStatus.ACCEPTED)
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.values("user_id", "problem_id")
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.distinct()
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.count()
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)
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recent_submission = submissions.count()
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# 时间段内的用户AC数列表
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recent_user_ac = {}
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for user_id in user_ids:
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user_recent_ac = (
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submissions.filter(user_id=user_id, result=JudgeStatus.ACCEPTED)
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.values("problem_id")
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.distinct()
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.count()
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)
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recent_user_ac[user_id] = user_recent_ac
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recent_ac_list = sorted(recent_user_ac.values(), reverse=True)
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if recent_ac_list:
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recent_stats = {
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"recent_total_ac": recent_ac,
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"recent_total_submission": recent_submission,
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"recent_avg_ac": statistics.mean(recent_ac_list),
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"recent_median_ac": statistics.median(recent_ac_list),
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"recent_top_10_avg": statistics.mean(
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recent_ac_list[: min(10, len(recent_ac_list))]
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)
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if recent_ac_list
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else 0,
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"recent_active_count": sum(
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1 for ac in recent_ac_list if ac > 0
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),
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}
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class_comparisons.append(
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{
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"class_name": class_name,
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"user_count": user_count,
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# 基础统计
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"total_ac": int(total_ac),
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"total_submission": int(total_submission),
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"avg_ac": round(avg_ac, 2),
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# 中位数和分位数
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"median_ac": round(median_ac, 2),
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"q1_ac": round(q1_ac, 2),
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"q3_ac": round(q3_ac, 2),
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"iqr": round(iqr, 2),
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# 标准差
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"std_dev": round(std_dev, 2),
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# 分层统计
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"top_10_avg": round(top_10_avg, 2),
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"bottom_10_avg": round(bottom_10_avg, 2),
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"top_25_avg": round(top_25_avg, 2),
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"bottom_25_avg": round(bottom_25_avg, 2),
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# 比率统计
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"excellent_rate": round(excellent_rate, 2),
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"pass_rate": round(pass_rate, 2),
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"active_rate": round(active_rate, 2),
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# 正确率
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"ac_rate": round(total_ac / total_submission * 100, 2)
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if total_submission > 0
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else 0,
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# 时间段统计（如果有）
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**recent_stats,
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}
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)
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# 按总AC数排序
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class_comparisons.sort(key=lambda x: (-x["total_ac"], x["total_submission"]))
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return self.success(
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{
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"comparisons": class_comparisons,
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"has_time_range": bool(start_time and end_time),
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}
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)
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