From 2006f7b4a415a5e2bed8d4c964e0668307de0d14 Mon Sep 17 00:00:00 2001 From: Shuming Liu Date: Tue, 22 Sep 2026 10:48:18 +0800 Subject: [PATCH] first commit --- .gitignore | 7 + ... ‡åˆ†æžæˆç»©åŸºç¡€æ•°æ®_5次考试.xlsx | Bin 0 -> 92209 bytes README.md | 38 +++ app/__init__.py | 0 app/__main__.py | 11 + app/config.py | 14 + app/db.py | 83 +++++ app/excel_parse.py | 253 ++++++++++++++++ app/export_xlsx.py | 83 +++++ app/indicators.py | 282 +++++++++++++++++ app/kalman.py | 205 +++++++++++++ app/main.py | 283 ++++++++++++++++++ app/static/css/app.css | 149 +++++++++ app/static/js/app.js | 112 +++++++ app/templates/analysis.html | 263 ++++++++++++++++ app/templates/home.html | 55 ++++ app/templates/login.html | 25 ++ requirements.txt | 6 + run.sh | 8 + 高三指标划定æ“作指引.docx | Bin 0 -> 20728 bytes 20 files changed, 1877 insertions(+) create mode 100644 .gitignore create mode 100644 2024级指标分æžæˆç»©åŸºç¡€æ•°æ®_5次考试.xlsx create mode 100644 README.md create mode 100644 app/__init__.py create mode 100644 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zMS-wU|Nm0j(*=7W__y2pZz=uh_+C2tJy2A={~-GxZtzce{fXZCn@=>~FFyYR%k?LR zKWjdJb4XYG&Ec;K(EtCv4|Dt?{Wl!?zwiA|K=j`|Uj8T9-|*-^hx}(5`ELe5*hF*36IpSnHb{fb@482~720|(&zi}LrZVL|=Uj{l(j z#o`yb`_JLiQ*(GFy#fH*T>yV@3G?_zF3f*x>ff;Pp3y$(6p-I1ef=jFo!Ecm!tzgC zLR_)4D?#e72txn;_Z=~%{v#LGf8t^gEX?Z}0RRk{K>Wc4r{EvCu>Ix&^^#@*ut0yr NAo)ESfGijA{{S1$EGPf~ literal 0 HcmV?d00001 diff --git a/README.md b/README.md new file mode 100644 index 0000000..e44d59d --- /dev/null +++ b/README.md @@ -0,0 +1,38 @@ +# 航标 · ç­çº§è¾¾çº¿æŒ‡æ ‡é¢„ä¼° + +B/S 系统：管ç†å‘˜ä¸Šä¼ åŽ†æ¬¡å¤§è€ƒæ€»åˆ†ï¼Œç³»ç»Ÿç”¨å¡å°”曼滤波估计æ¯ä¸ªå­¦ç”Ÿçš„稳定水平，模拟åŽç»­è€ƒè¯•çš„年级排å，把达线概率加总åŽä¸‹è¾¾å„ç­æŒ‡æ ‡ã€‚下达人数是“按现有轨迹本æ¥ä¼šåˆ°çš„人数â€ï¼Œç­çº§å·¥ä½œæ˜¯è¶…越它。 + +## å¯åŠ¨ + +```bash +python3 -m venv .venv +source .venv/bin/activate +pip install -r requirements.txt +python3 -m app +``` + +æµè§ˆå™¨æ‰“å¼€ http://127.0.0.1:8765 + +默认账å·ï¼š`admin` / `hangbiao2026`（请在 `app/config.py` 修改） + +## æˆç»©è¡¨è¦æ±‚ + +- Excel `.xlsx` +- 至少包å«ï¼šå­¦å·æˆ–姓åã€ç­çº§ã€å¤šæ¬¡è€ƒè¯•æ€»åˆ† +- 建议包å«ï¼šæ–¹å‘（物ç†/历å²ï¼‰ã€é€‰ç§‘ã€å­¦ç±ã€å¼‚动 +- 物ç†/历å²åˆ†è¡¨ã€è‰ºä½“表ã€å¼‚动表都å¯ä»¥ï¼›ç³»ç»Ÿä¼šè¯†åˆ«å¹¶åœ¨ç¬¬äºŒæ­¥è®©ä½ å‹¾é€‰å£å¾„ + +åŒç›®å½•çš„ `2024级指标分æžæˆç»©åŸºç¡€æ•°æ®_5次考试.xlsx` å¯åœ¨é¦–页一键演示。 + +## å››æ­¥åˆ†æž + +1. æ•°æ®ä½“检：读到哪些人ã€å“ªäº›è€ƒè¯•ã€åˆ†æ•°å°ºåº¦ +2. å£å¾„与目标：算è°ã€å¹´çº§æ€»ç›˜å­ã€é¢„估步长 +3. 滤波与回测：Q/R å«ä¹‰ï¼Œä»¥åŠç”¨åŽ†å²è€ƒè¯•éªŒè¯å‡†ä¸å‡† +4. 下达指标：ç­çº§æœŸæœ› / 下达 / ä¿åº• / 冲刺，点ç­çº§çœ‹å­¦ç”Ÿï¼Œç‚¹å­¦ç”Ÿçœ‹è½¨è¿¹ + +## 指标怎么ç†è§£ + +- **下达指标**：滤波期望å–整，åˆè®¡ç­‰äºŽå¹´çº§ç›®æ ‡äººæ•° +- **ä¿åº• / 冲刺**：模拟分布大约 20% / 80% åˆ†ä½ +- **相对最近一次**：预估相对最近一场已在线人数的增å‡ï¼Œç”¨æ¥æ‰¾ä¸Šå‡ç”Ÿå’Œä¸ç¨³çš„在线生 diff --git a/app/__init__.py b/app/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/app/__main__.py b/app/__main__.py new file mode 100644 index 0000000..41be52c --- /dev/null +++ b/app/__main__.py @@ -0,0 +1,11 @@ +import os + +import uvicorn + +if __name__ == "__main__": + uvicorn.run( + "app.main:app", + host="127.0.0.1", + port=int(os.environ.get("PORT", "8765")), + reload=os.environ.get("RELOAD", "1") != "0", + ) diff --git a/app/config.py b/app/config.py new file mode 100644 index 0000000..6a12aef --- /dev/null +++ b/app/config.py @@ -0,0 +1,14 @@ +from pathlib import Path + +BASE_DIR = Path(__file__).resolve().parent.parent +DATA_DIR = BASE_DIR / "data" +UPLOAD_DIR = DATA_DIR / "uploads" +DB_PATH = DATA_DIR / "hangbiao.db" +SAMPLE_XLSX = BASE_DIR / "2024级指标分æžæˆç»©åŸºç¡€æ•°æ®_5次考试.xlsx" + +SECRET_KEY = "hangbiao-dev-secret-change-me" +ADMIN_USER = "admin" +ADMIN_PASSWORD = "hangbiao2026" + +SESSION_MAX_AGE = 60 * 60 * 12 +MAX_UPLOAD_MB = 15 diff --git a/app/db.py b/app/db.py new file mode 100644 index 0000000..1fcd67a --- /dev/null +++ b/app/db.py @@ -0,0 +1,83 @@ +from __future__ import annotations + +import json +import sqlite3 +from datetime import datetime +from pathlib import Path + +from .config import DB_PATH + + +def connect() -> sqlite3.Connection: + DB_PATH.parent.mkdir(parents=True, exist_ok=True) + conn = sqlite3.connect(DB_PATH) + conn.row_factory = sqlite3.Row + return conn + + +def init_db() -> None: + conn = connect() + conn.execute( + """ + CREATE TABLE IF NOT EXISTS analyses ( + id INTEGER PRIMARY KEY AUTOINCREMENT, + title TEXT, + filename TEXT, + created_at TEXT, + step INTEGER DEFAULT 1, + parsed_path TEXT, + settings_json TEXT, + result_path TEXT + ) + """ + ) + conn.commit() + conn.close() + + +def create_analysis(title: str, filename: str, parsed_path: str) -> int: + conn = connect() + cur = conn.execute( + """ + INSERT INTO analyses (title, filename, created_at, step, parsed_path) + VALUES (?, ?, ?, 1, ?) + """, + (title, filename, datetime.now().strftime("%Y-%m-%d %H:%M:%S"), parsed_path), + ) + conn.commit() + aid = cur.lastrowid + conn.close() + return int(aid) + + +def list_analyses() -> list[dict]: + conn = connect() + rows = conn.execute("SELECT * FROM analyses ORDER BY id DESC").fetchall() + conn.close() + return [dict(r) for r in rows] + + +def get_analysis(aid: int) -> dict | None: + conn = connect() + row = conn.execute("SELECT * FROM analyses WHERE id=?", (aid,)).fetchone() + conn.close() + return dict(row) if row else None + + +def update_analysis(aid: int, **fields) -> None: + if not fields: + return + keys = ", ".join(f"{k}=?" for k in fields) + conn = connect() + conn.execute(f"UPDATE analyses SET {keys} WHERE id=?", (*fields.values(), aid)) + conn.commit() + conn.close() + + +def load_json(path: str): + return json.loads(Path(path).read_text(encoding="utf-8")) + + +def save_json(path: str, obj) -> None: + Path(path).parent.mkdir(parents=True, exist_ok=True) + Path(path).write_text(json.dumps(obj, ensure_ascii=False), encoding="utf-8") diff --git a/app/excel_parse.py b/app/excel_parse.py new file mode 100644 index 0000000..9171b70 --- /dev/null +++ b/app/excel_parse.py @@ -0,0 +1,253 @@ +from __future__ import annotations + +import re +from io import BytesIO +from pathlib import Path + +from openpyxl import load_workbook + + +META_ALIASES = { + "sid": ("å­¦å·", "考å·", "id", "学生id"), + "name": ("姓å", "学生姓å", "åå­—"), + "class_name": ("ç­çº§", "ç­", "行政ç­"), + "track": ("æ–¹å‘", "科类", "首选", "首选科目"), + "subjects": ("选科", "å†é€‰", "科目组åˆ"), + "status": ("å­¦ç±", "å­¦ç±ç±»åž‹", "身份"), + "move": ("异动", "备注", "说明"), +} + +EXAM_HINT = re.compile( + r"(总分|期末|è”考|月考|模考|开学|学考|诊断|调研|高考)", + re.I, +) +SKIP_SHEETS = ("说明", "readme", "目录") +ART_RE = re.compile(r"艺术|体育|艺体") +LEAVE_RE = re.compile(r"请å‡|出国|休学|国际|ä¸åœ¨æ ¡|港澳|港ç±.*å‡") + + +def _norm(v) -> str: + if v is None: + return "" + if isinstance(v, float) and v.is_integer(): + return str(int(v)) + return str(v).strip() + + +def _is_exam_header(text: str) -> bool: + t = text.strip() + if not t or t in {"考试次数"}: + return False + if t.endswith("-总分") or t.endswith("总分"): + return True + return bool(EXAM_HINT.search(t)) and "次数" not in t + + +def _map_meta(header: str) -> str | None: + h = header.strip().lower() + for key, aliases in META_ALIASES.items(): + for a in aliases: + if h == a.lower() or h.replace(" ", "") == a.lower(): + return key + return None + + +def _sheet_kind(name: str) -> str: + n = name.lower() + if any(x in n for x in ("艺体", "艺术", "体育")): + return "art" + if "异动" in n: + return "leave" + if "历å²" in n: + return "history" + if "物ç†" in n: + return "physics" + if n in ("全体", "全部", "汇总"): + return "all" + return "other" + + +def parse_workbook(path: Path | BytesIO) -> dict: + wb = load_workbook(path, data_only=True, read_only=True) + sheets = [] + students: list[dict] = [] + exam_order: list[str] = [] + warnings: list[str] = [] + + for ws in wb.worksheets: + kind = _sheet_kind(ws.title) + rows = ws.iter_rows(values_only=True) + try: + header_row = next(rows) + except StopIteration: + continue + headers = [_norm(h) for h in header_row] + if not any(headers): + continue + meta_idx = {} + exam_idx = {} + for i, h in enumerate(headers): + if not h: + continue + mk = _map_meta(h) + if mk: + meta_idx[mk] = i + continue + if _is_exam_header(h): + exam_idx[h] = i + if h not in exam_order: + exam_order.append(h) + if "sid" not in meta_idx and "name" not in meta_idx: + warnings.append(f"工作表「{ws.title}ã€æœªè¯†åˆ«åˆ°å­¦å·/姓å，已跳过") + continue + + count = 0 + for raw in rows: + if raw is None or all(v is None or str(v).strip() == "" for v in raw): + continue + rec = { + "sid": _norm(raw[meta_idx["sid"]]) if "sid" in meta_idx else "", + "name": _norm(raw[meta_idx["name"]]) if "name" in meta_idx else "", + "class_name": _norm(raw[meta_idx["class_name"]]) if "class_name" in meta_idx else "未分ç­", + "track": _norm(raw[meta_idx["track"]]) if "track" in meta_idx else "", + "subjects": _norm(raw[meta_idx["subjects"]]) if "subjects" in meta_idx else "", + "status": _norm(raw[meta_idx["status"]]) if "status" in meta_idx else "", + "move": _norm(raw[meta_idx["move"]]) if "move" in meta_idx else "", + "sheet": ws.title, + "sheet_kind": kind, + "scores": {}, + } + if not rec["sid"] and not rec["name"]: + continue + if not rec["sid"]: + rec["sid"] = f"{ws.title}-{rec['name']}-{count}" + if kind == "physics" and not rec["track"]: + rec["track"] = "物ç†æ–¹å‘" + if kind == "history" and not rec["track"]: + rec["track"] = "历å²æ–¹å‘" + if not rec["track"]: + if "物ç†" in rec["subjects"]: + rec["track"] = "物ç†æ–¹å‘" + elif "历å²" in rec["subjects"]: + rec["track"] = "历å²æ–¹å‘" + for exam, idx in exam_idx.items(): + if idx >= len(raw): + continue + val = raw[idx] + if val is None or str(val).strip() in ("", "缺考", "—", "-", "/"): + rec["scores"][exam] = None + continue + try: + rec["scores"][exam] = float(val) + except (TypeError, ValueError): + rec["scores"][exam] = None + rec["art"] = bool(ART_RE.search(rec["move"]) or ART_RE.search(ws.title)) + rec["leave"] = bool(LEAVE_RE.search(rec["move"])) + students.append(rec) + count += 1 + sheets.append( + { + "name": ws.title, + "kind": kind, + "rows": count, + "exams": list(exam_idx.keys()), + } + ) + + wb.close() + + # Prefer specialized sheets over 全体 to avoid duplicates + has_split = any(s["kind"] in ("physics", "history") for s in sheets) + if has_split: + kept = [] + skipped_all = 0 + for s in students: + if s["sheet_kind"] == "all": + skipped_all += 1 + continue + kept.append(s) + students = kept + if skipped_all: + warnings.append(f"已忽略「全体ã€è¡¨ä¸­çš„ {skipped_all} 行，é¿å…与物ç†/历å²è¡¨é‡å¤") + + # de-duplicate by sid, keep first non-all + seen = {} + uniq = [] + dups = 0 + for s in students: + if s["sid"] in seen: + dups += 1 + continue + seen[s["sid"]] = True + uniq.append(s) + students = uniq + if dups: + warnings.append(f"按学å·åŽ»é‡ {dups} æ¡") + + if not exam_order: + warnings.append("未识别到考试æˆç»©åˆ—，请确认表头å«ã€Œæ€»åˆ†ã€æˆ–「期末/è”考/月考ã€") + + return { + "sheets": sheets, + "students": students, + "exams": exam_order, + "warnings": warnings, + } + + +def summarize_parse(parsed: dict) -> dict: + students = parsed["students"] + exams = parsed["exams"] + tracks = {} + classes = {} + status = {} + art = leave = 0 + exam_present = {e: 0 for e in exams} + for s in students: + tracks[s["track"] or "未分方å‘"] = tracks.get(s["track"] or "未分方å‘", 0) + 1 + classes[s["class_name"]] = classes.get(s["class_name"], 0) + 1 + status[s["status"] or "未填"] = status.get(s["status"] or "未填", 0) + 1 + if s["art"]: + art += 1 + if s["leave"]: + leave += 1 + for e in exams: + if s["scores"].get(e) is not None: + exam_present[e] += 1 + score_scale = [] + for e in exams: + vals = [s["scores"][e] for s in students if s["scores"].get(e) is not None] + if not vals: + continue + score_scale.append( + { + "exam": e, + "n": len(vals), + "min": round(min(vals), 1), + "max": round(max(vals), 1), + "mean": round(sum(vals) / len(vals), 1), + } + ) + return { + "n": len(students), + "n_class": len(classes), + "tracks": tracks, + "classes": dict(sorted(classes.items(), key=lambda kv: _class_key(kv[0]))), + "status": status, + "art": art, + "leave": leave, + "exam_present": exam_present, + "score_scale": score_scale, + "sheets": parsed["sheets"], + "exams": exams, + "warnings": parsed["warnings"], + } + + +def _class_key(name: str): + m = re.search(r"\d+", str(name)) + return (int(m.group()) if m else 999, str(name)) + + +def class_sort_key(name: str): + return _class_key(name) diff --git a/app/export_xlsx.py b/app/export_xlsx.py new file mode 100644 index 0000000..2a3c921 --- /dev/null +++ b/app/export_xlsx.py @@ -0,0 +1,83 @@ +from __future__ import annotations + +from io import BytesIO + +from openpyxl import Workbook +from openpyxl.styles import Alignment, Font, PatternFill, Border, Side + + +def build_export(result: dict) -> bytes: + wb = Workbook() + thin = Border( + left=Side(style="thin", color="D9D1C3"), + right=Side(style="thin", color="D9D1C3"), + top=Side(style="thin", color="D9D1C3"), + bottom=Side(style="thin", color="D9D1C3"), + ) + head = PatternFill("solid", fgColor="12233D") + head_font = Font(color="F4EFE6", bold=True) + wrap = Alignment(wrap_text=True, vertical="center") + + first = True + for g in result["groups"]: + for t in g["targets"]: + title = f"{g['group']}-{t['name']}"[:31] + ws = wb.active if first else wb.create_sheet(title) + if first: + ws.title = title + first = False + ws.append( + ["ç­çº§", "测算人数", "最近一次在线", "滤波期望", "下达指标", "ä¿åº•ä¸‹ç•Œ", "冲刺上界", "相对最近一次"] + ) + for cell in ws[1]: + cell.fill = head + cell.font = head_font + for row in t["classes"]: + ws.append( + [ + row["class_name"], + row["n"], + row["current"], + row["expected"], + row["assigned"], + row["floor"], + row["stretch"], + row["delta"], + ] + ) + ws.append([]) + ws.append(["说明：下达指标为预估中ä½æ°´å¹³ï¼Œç­çº§åº”努力超越该人数。ä¿åº•/冲刺æ¥è‡ªæ¨¡æ‹Ÿåˆ†å¸ƒçš„约20%/80%分ä½ã€‚"]) + + ws = wb.create_sheet("学生明细") + exams = result["exams"] + headers = ["å­¦å·", "姓å", "ç­çº§", "æ–¹å‘", "å­¦ç±", "选科"] + headers += [f"{e}-排å" for e in exams] + # collect target names + tcols = [] + for g in result["groups"]: + for t in g["targets"]: + tcols.append((g["group"], t["id"], f"{g['group']}-{t['name']}概率")) + headers += [c[2] for c in tcols] + headers += ["滤波水平", "预测方差"] + ws.append(headers) + for cell in ws[1]: + cell.fill = head + cell.font = head_font + cell.alignment = wrap + for s in result["students"]: + row = [s["sid"], s["name"], s["class_name"], s["group"], s.get("status") or "", s.get("subjects") or ""] + ranks = s.get("ranks") or [] + for i, _e in enumerate(exams): + row.append(ranks[i] if i < len(ranks) else None) + for gname, tid, _ in tcols: + if s["group"] == gname: + row.append((s.get("probs") or {}).get(tid)) + else: + row.append(None) + row.append(s.get("pred_mean")) + row.append(s.get("pred_var")) + ws.append(row) + + bio = BytesIO() + wb.save(bio) + return bio.getvalue() diff --git a/app/indicators.py b/app/indicators.py new file mode 100644 index 0000000..909b356 --- /dev/null +++ b/app/indicators.py @@ -0,0 +1,282 @@ +from __future__ import annotations + +from collections import defaultdict + +from .excel_parse import class_sort_key +from .kalman import ( + fit_qr, + hamilton, + holdout_hits, + kalman_filter, + monte_carlo, + ranks_desc, + zscores, +) + + +TRACK_DEFAULTS = { + "物ç†": [{"id": "t88", "name": "特控线上", "k": 88}], + "历å²": [ + {"id": "top5", "name": "å°–å­ç”Ÿ", "k": 5}, + {"id": "top12", "name": "600分以上", "k": 12}, + {"id": "top52", "name": "特控线上", "k": 52}, + ], +} + + +def infer_track_group(track: str) -> str: + t = track or "" + if "历å²" in t: + return "历å²" + if "物ç†" in t: + return "物ç†" + return t or "未分方å‘" + + +def default_targets(groups: list[str]) -> dict[str, list[dict]]: + out = {} + for g in groups: + if g in TRACK_DEFAULTS: + out[g] = [dict(x) for x in TRACK_DEFAULTS[g]] + else: + out[g] = [{"id": "top20", "name": "年级å‰20%", "k": 20}] + return out + + +def select_students(parsed: dict, settings: dict) -> list[dict]: + include_art = settings.get("include_art", False) + include_leave = settings.get("include_leave", False) + include_mingyuan = settings.get("include_mingyuan", True) + include_other = settings.get("include_other", True) + exams = settings.get("exams") or parsed["exams"] + selected = [] + for s in parsed["students"]: + if s["art"] and not include_art: + continue + if s["leave"] and not include_leave: + continue + st = s["status"] or "在ç±" + if st == "明远" and not include_mingyuan: + continue + if st not in ("在ç±", "明远", "") and not include_other: + continue + scores = {e: s["scores"].get(e) for e in exams} + if all(v is None for v in scores.values()): + continue + row = dict(s) + row["scores"] = scores + row["group"] = infer_track_group(s["track"]) + selected.append(row) + return selected + + +def _forecast_horizon(q: float, p: float, horizon: int) -> float: + return p + max(1, horizon) * q + + +def analyze(parsed: dict, settings: dict) -> dict: + exams = settings.get("exams") or parsed["exams"] + if not exams: + raise ValueError("没有å¯ç”¨çš„考试列") + horizon = int(settings.get("horizon", 1)) + n_sim = int(settings.get("n_sim", 600)) + selected = select_students(parsed, settings) + groups = sorted({s["group"] for s in selected}) + targets = settings.get("targets") or default_targets(groups) + + # fit Q,R per group on z-scores + group_models = {} + for g in groups: + members = [s for s in selected if s["group"] == g] + z_by_exam = {} + for e in exams: + z_by_exam[e] = zscores([s["scores"].get(e) for s in members]) + for i, s in enumerate(members): + s["z"] = [z_by_exam[e][i] for e in exams] + s["ranks"] = [] + for e in exams: + rk = ranks_desc([s["scores"].get(e) for s in members]) + for i, s in enumerate(members): + s["ranks"].append(rk[i]) + series = [s["z"] for s in members] + q, r, rmse = fit_qr(series) + group_models[g] = {"q": q, "r": r, "rmse": rmse, "n": len(members)} + for s in members: + fr = kalman_filter(s["z"], q, r) + s["kf_x"] = fr.x + s["kf_p"] = fr.p + s["kf_xs"] = fr.xs + s["kf_ps"] = fr.ps + if fr.x is None: + s["pred_mean"] = None + s["pred_var"] = None + else: + s["pred_mean"] = fr.x + s["pred_var"] = _forecast_horizon(q, fr.p if fr.p is not None else r, horizon) + + results = [] + for g in groups: + members = [s for s in selected if s["group"] == g] + g_targets = targets.get(g) or default_targets([g])[g] + model = group_models[g] + eligible = [s for s in members if s["pred_mean"] is not None] + last_ranks = [s["ranks"][-1] if s["ranks"] else None for s in members] + holdouts = [] + if len(exams) >= 3: + series = [s["z"] for s in members] + true_ranks = [s["ranks"][-1] if s["ranks"] else None for s in members] + last_train_ranks = [s["ranks"][-2] if len(s["ranks"]) >= 2 else None for s in members] + for t in g_targets: + k = min(int(t["k"]), max(1, sum(1 for r in true_ranks if r is not None))) + h = holdout_hits( + series, + last_train_ranks, + true_ranks, + model["q"], + model["r"], + k, + ) + h["target_id"] = t["id"] + h["target_name"] = t["name"] + h["k"] = k + holdouts.append(h) + + target_blocks = [] + for t in g_targets: + k = int(t["k"]) + k = max(1, min(k, len(eligible))) + means = [s["pred_mean"] for s in eligible] + variances = [s["pred_var"] for s in eligible] + class_ids = [s["class_name"] for s in eligible] + probs, class_q = monte_carlo(means, variances, class_ids, k, n_sim=n_sim) + for s, p in zip(eligible, probs): + s.setdefault("probs", {})[t["id"]] = p + # current on-line: last exam rank <= k + class_now = defaultdict(int) + class_n = defaultdict(int) + class_exp = defaultdict(float) + class_mingyuan_exp = defaultdict(float) + for s in members: + class_n[s["class_name"]] += 1 + for s in eligible: + class_exp[s["class_name"]] += s["probs"][t["id"]] + if s.get("status") == "明远": + class_mingyuan_exp[s["class_name"]] += s["probs"][t["id"]] + if s["ranks"] and s["ranks"][-1] is not None and s["ranks"][-1] <= k: + class_now[s["class_name"]] += 1 + class_names = sorted(class_n.keys(), key=class_sort_key) + expected = [class_exp[c] for c in class_names] + assigned = hamilton(expected, k) + rows = [] + for c, a in zip(class_names, assigned): + qtl = class_q.get(c, {"p20": 0, "p50": 0, "p80": 0, "mean": 0}) + rows.append( + { + "class_name": c, + "n": class_n[c], + "current": class_now[c], + "expected": round(class_exp[c], 2), + "assigned": a, + "floor": int(qtl["p20"]), + "median": int(qtl["p50"]), + "stretch": int(qtl["p80"]), + "delta": a - class_now[c], + "mingyuan_expected": round(class_mingyuan_exp[c], 2), + } + ) + critical = [] + for s in eligible: + p = s["probs"][t["id"]] + if 0.2 <= p <= 0.8: + critical.append( + { + "sid": s["sid"], + "name": s["name"], + "class_name": s["class_name"], + "p": round(p, 3), + "last_rank": s["ranks"][-1] if s["ranks"] else None, + "status": s.get("status") or "", + } + ) + critical.sort(key=lambda x: -x["p"]) + target_blocks.append( + { + "id": t["id"], + "name": t["name"], + "k": k, + "classes": rows, + "critical_n": len(critical), + "critical": critical[:80], + "sum_expected": round(sum(expected), 2), + } + ) + + results.append( + { + "group": g, + "n": len(members), + "model": { + "q": model["q"], + "r": model["r"], + "rmse": round(model["rmse"], 3) if model["rmse"] is not None else None, + "horizon": horizon, + "n_sim": n_sim, + }, + "holdout": holdouts, + "targets": target_blocks, + } + ) + + student_views = [] + for s in selected: + student_views.append( + { + "sid": s["sid"], + "name": s["name"], + "class_name": s["class_name"], + "group": s["group"], + "track": s["track"], + "subjects": s["subjects"], + "status": s.get("status") or "", + "move": s.get("move") or "", + "art": s["art"], + "leave": s["leave"], + "scores": s["scores"], + "z": s.get("z"), + "ranks": s.get("ranks"), + "kf_xs": s.get("kf_xs"), + "kf_ps": s.get("kf_ps"), + "pred_mean": s.get("pred_mean"), + "pred_var": s.get("pred_var"), + "probs": {k: round(v, 4) for k, v in (s.get("probs") or {}).items()}, + } + ) + + return { + "exams": exams, + "horizon": horizon, + "n_selected": len(selected), + "n_total": len(parsed["students"]), + "groups": results, + "students": student_views, + } + + +def class_comment(row: dict, target_name: str) -> str: + assigned = row["assigned"] + current = row["current"] + expected = row["expected"] + floor = row["floor"] + stretch = row["stretch"] + name = row["class_name"] + bits = [ + f"{name}ç­{target_name}下达 {assigned} 人（滤波期望 {expected:.1f}）。" + ] + if assigned > current: + bits.append(f"比最近一次在线人数多 {assigned - current} 人，ç­çº§é‡Œæœ‰ä¸Šå‡è½¨è¿¹çš„临界生，需è¦æŠŠæ½œåŠ›å…‘现。") + elif assigned < current: + bits.append(f"比最近一次在线人数少 {current - assigned} 人，说明部分当å‰åœ¨çº¿å­¦ç”Ÿè½¨è¿¹ä¸ç¨³ï¼Œé‡ç‚¹æ˜¯ä¿ä½ä¸´ç•Œç”Ÿã€‚") + else: + bits.append("与最近一次在线人数æŒå¹³ï¼ŒæŒ‰çŽ°æœ‰è½¨è¿¹å±žäºŽç»´æŒæ€§ç›®æ ‡ã€‚") + bits.append(f"模拟分布大约在 {floor}–{stretch} 人之间，超越下达人数æ‰ç®—跑赢预估。") + return "".join(bits) diff --git a/app/kalman.py b/app/kalman.py new file mode 100644 index 0000000..e299d0c --- /dev/null +++ b/app/kalman.py @@ -0,0 +1,205 @@ +from __future__ import annotations + +import math +import random +from dataclasses import dataclass + + +def mean_std(values: list[float]) -> tuple[float, float]: + n = len(values) + if n == 0: + return 0.0, 1.0 + mean = sum(values) / n + if n == 1: + return mean, 1.0 + var = sum((x - mean) ** 2 for x in values) / (n - 1) + return mean, math.sqrt(var) if var > 0 else 1.0 + + +def zscores(values: list[float | None]) -> list[float | None]: + present = [v for v in values if v is not None] + mean, std = mean_std(present) + out: list[float | None] = [] + for v in values: + if v is None: + out.append(None) + else: + out.append((v - mean) / std) + return out + + +def ranks_desc(values: list[float | None]) -> list[int | None]: + indexed = [(i, v) for i, v in enumerate(values) if v is not None] + indexed.sort(key=lambda iv: -iv[1]) + out: list[int | None] = [None] * len(values) + for rank, (i, _) in enumerate(indexed, 1): + out[i] = rank + return out + + +@dataclass +class FilterResult: + x: float | None + p: float | None + xs: list[float | None] + ps: list[float | None] + + +def kalman_filter(zs: list[float | None], q: float, r: float) -> FilterResult: + x = None + p = None + xs: list[float | None] = [] + ps: list[float | None] = [] + for z in zs: + if x is None: + if z is None: + xs.append(None) + ps.append(None) + continue + x, p = z, r + xs.append(x) + ps.append(p) + continue + x_pred = x + p_pred = p + q + if z is None: + x, p = x_pred, p_pred + xs.append(x) + ps.append(p) + continue + k = p_pred / (p_pred + r) + x = x_pred + k * (z - x_pred) + p = (1 - k) * p_pred + xs.append(x) + ps.append(p) + return FilterResult(x=x, p=p, xs=xs, ps=ps) + + +def one_step_rmse(series_list: list[list[float | None]], q: float, r: float) -> float | None: + se = 0.0 + n = 0 + for zs in series_list: + x = None + p = None + for z in zs: + if x is None: + if z is None: + continue + x, p = z, r + continue + x_pred = x + p_pred = p + q + if z is None: + x, p = x_pred, p_pred + continue + se += (x_pred - z) ** 2 + n += 1 + k = p_pred / (p_pred + r) + x = x_pred + k * (z - x_pred) + p = (1 - k) * p_pred + if n == 0: + return None + return math.sqrt(se / n) + + +def fit_qr(series_list: list[list[float | None]]) -> tuple[float, float, float]: + usable = [s for s in series_list if sum(1 for z in s if z is not None) >= 2] + best = (1e9, 0.08, 0.25) + for q in (0.03, 0.05, 0.08, 0.10, 0.15, 0.22, 0.30): + for r in (0.12, 0.18, 0.25, 0.32, 0.40, 0.55): + rmse = one_step_rmse(usable, q, r) + if rmse is not None and rmse < best[0]: + best = (rmse, q, r) + return best[1], best[2], best[0] + + +def holdout_hits( + series_list: list[list[float | None]], + last_ranks: list[int | None], + true_ranks: list[int | None], + q: float, + r: float, + target_k: int, +) -> dict: + preds: list[tuple[int, float]] = [] + last_pred: list[tuple[int, int]] = [] + for i, zs in enumerate(series_list): + if true_ranks[i] is None: + continue + train = zs[:-1] + result = kalman_filter(train, q, r) + if result.x is None: + continue + preds.append((i, result.x)) + if last_ranks[i] is not None: + last_pred.append((i, last_ranks[i])) + preds.sort(key=lambda t: -t[1]) + kf_set = {i for i, _ in preds[:target_k]} + last_pred.sort(key=lambda t: t[1]) + last_set = {i for i, _ in last_pred[:target_k]} + actual = {i for i, rk in enumerate(true_ranks) if rk is not None and rk <= target_k} + kf_hit = len(kf_set & actual) + last_hit = len(last_set & actual) + return { + "n_actual": len(actual), + "kf_hit": kf_hit, + "last_hit": last_hit, + "kf_precision": kf_hit / target_k if target_k else 0, + "last_precision": last_hit / target_k if target_k else 0, + } + + +def monte_carlo( + means: list[float], + variances: list[float], + class_ids: list[str], + target_k: int, + n_sim: int = 600, + seed: int = 42, +) -> tuple[list[float], dict[str, dict]]: + rng = random.Random(seed) + n = len(means) + hits = [0] * n + sigmas = [math.sqrt(max(v, 1e-8)) for v in variances] + unique = list(dict.fromkeys(class_ids)) + buckets = {c: [] for c in unique} + for _ in range(n_sim): + zs = [means[i] + sigmas[i] * rng.gauss(0, 1) for i in range(n)] + order = sorted(range(n), key=lambda i: zs[i], reverse=True) + counts = {c: 0 for c in unique} + for i in order[:target_k]: + hits[i] += 1 + counts[class_ids[i]] += 1 + for c, v in counts.items(): + buckets[c].append(v) + out = {} + for c, arr in buckets.items(): + arr.sort() + m = n_sim + out[c] = { + "p20": arr[max(0, int(0.20 * m) - 1)], + "p50": arr[max(0, int(0.50 * m) - 1)], + "p80": arr[max(0, int(0.80 * m) - 1)], + "mean": sum(arr) / m, + } + return [h / n_sim for h in hits], out + + +def hamilton(values: list[float], total: int) -> list[int]: + if total <= 0 or not values: + return [0] * len(values) + s = sum(values) + if s <= 0: + out = [0] * len(values) + return out + scaled = [v * total / s for v in values] + floors = [int(math.floor(v + 1e-9)) for v in scaled] + remain = total - sum(floors) + order = sorted( + range(len(scaled)), + key=lambda i: (scaled[i] - floors[i], scaled[i]), + reverse=True, + ) + for i in order[: max(0, remain)]: + floors[i] += 1 + return floors diff --git a/app/main.py b/app/main.py new file mode 100644 index 0000000..3f7d76f --- /dev/null +++ b/app/main.py @@ -0,0 +1,283 @@ +from __future__ import annotations + +import json +import shutil +import uuid +from pathlib import Path +from urllib.parse import quote + +from fastapi import FastAPI, File, Form, Request, UploadFile +from fastapi.responses import HTMLResponse, RedirectResponse, Response +from fastapi.staticfiles import StaticFiles +from fastapi.templating import Jinja2Templates +from starlette.middleware.sessions import SessionMiddleware + +from .config import ( + ADMIN_PASSWORD, + ADMIN_USER, + DATA_DIR, + MAX_UPLOAD_MB, + SAMPLE_XLSX, + SECRET_KEY, + UPLOAD_DIR, +) +from .db import ( + create_analysis, + get_analysis, + init_db, + list_analyses, + load_json, + save_json, + update_analysis, +) +from .excel_parse import parse_workbook, summarize_parse +from .export_xlsx import build_export +from .indicators import analyze, class_comment, default_targets, infer_track_group, select_students + +app = FastAPI(title="航标 · ç­çº§è¾¾çº¿æŒ‡æ ‡é¢„ä¼°") +app.add_middleware(SessionMiddleware, secret_key=SECRET_KEY, max_age=60 * 60 * 12) +app.mount("/static", StaticFiles(directory=Path(__file__).parent / "static"), name="static") +templates = Jinja2Templates(directory=str(Path(__file__).parent / "templates")) +templates.env.globals["class_comment"] = class_comment + + +def render(request: Request, name: str, **ctx): + ctx["request"] = request + ctx.setdefault("user", current_user(request)) + return templates.TemplateResponse(request, name, ctx) + + +@app.on_event("startup") +def startup(): + DATA_DIR.mkdir(parents=True, exist_ok=True) + UPLOAD_DIR.mkdir(parents=True, exist_ok=True) + init_db() + + +def current_user(request: Request) -> str | None: + return request.session.get("user") + + +def require_login(request: Request): + if not current_user(request): + return RedirectResponse("/login", status_code=303) + return None + + +@app.get("/login", response_class=HTMLResponse) +def login_page(request: Request): + if current_user(request): + return RedirectResponse("/", status_code=303) + return render(request, "login.html", error=None) + + +@app.post("/login", response_class=HTMLResponse) +def login_submit(request: Request, username: str = Form(...), password: str = Form(...)): + if username.strip() == ADMIN_USER and password == ADMIN_PASSWORD: + request.session["user"] = username.strip() + return RedirectResponse("/", status_code=303) + return render(request, "login.html", error="è´¦å·æˆ–密ç ä¸æ­£ç¡®") + + +@app.post("/logout") +def logout(request: Request): + request.session.clear() + return RedirectResponse("/login", status_code=303) + + +@app.get("/", response_class=HTMLResponse) +def home(request: Request): + if (redir := require_login(request)): + return redir + items = list_analyses() + return render(request, "home.html", items=items, has_sample=SAMPLE_XLSX.exists()) + + +def _store_parsed(title: str, filename: str, source: Path) -> int: + parsed = parse_workbook(source) + summary = summarize_parse(parsed) + token = uuid.uuid4().hex[:10] + parsed_path = str(DATA_DIR / f"parsed_{token}.json") + # keep a lighter parsed blob + save_json(parsed_path, parsed) + aid = create_analysis(title, filename, parsed_path) + update_analysis(aid, settings_json=json.dumps({"summary": summary}, ensure_ascii=False)) + return aid + + +@app.post("/upload") +async def upload(request: Request, file: UploadFile = File(...)): + if (redir := require_login(request)): + return redir + raw = await file.read() + if len(raw) > MAX_UPLOAD_MB * 1024 * 1024: + return HTMLResponse("文件过大，请压缩到 15MB 以内。", status_code=400) + suffix = Path(file.filename or "scores.xlsx").suffix.lower() + if suffix not in (".xlsx", ".xlsm"): + return HTMLResponse("请上传 .xlsx æˆç»©è¡¨ã€‚", status_code=400) + dest = UPLOAD_DIR / f"{uuid.uuid4().hex}{suffix}" + dest.write_bytes(raw) + aid = _store_parsed(Path(file.filename).stem, file.filename or dest.name, dest) + return RedirectResponse(f"/analysis/{aid}?step=1", status_code=303) + + +@app.post("/demo") +def demo(request: Request): + if (redir := require_login(request)): + return redir + if not SAMPLE_XLSX.exists(): + return HTMLResponse("未找到示例æˆç»©è¡¨ã€‚", status_code=404) + dest = UPLOAD_DIR / f"{uuid.uuid4().hex}.xlsx" + shutil.copy2(SAMPLE_XLSX, dest) + aid = _store_parsed("2024级示例数æ®", SAMPLE_XLSX.name, dest) + return RedirectResponse(f"/analysis/{aid}?step=1", status_code=303) + + +def _settings_from(parsed: dict, stored: dict | None) -> dict: + summary = summarize_parse(parsed) + groups = sorted({infer_track_group(s["track"]) for s in parsed["students"]}) + base = { + "exams": parsed["exams"], + "include_art": False, + "include_leave": False, + "include_mingyuan": True, + "include_other": True, + "horizon": 1, + "targets": default_targets(groups), + } + if stored: + for k in ("exams", "include_art", "include_leave", "include_mingyuan", "include_other", "horizon", "targets"): + if k in stored: + base[k] = stored[k] + base["summary"] = summary + base["groups"] = groups + return base + + +@app.get("/analysis/{aid}", response_class=HTMLResponse) +def analysis_page(request: Request, aid: int, step: int = 1): + if (redir := require_login(request)): + return redir + item = get_analysis(aid) + if not item: + return HTMLResponse("分æžä¸å­˜åœ¨", status_code=404) + parsed = load_json(item["parsed_path"]) + stored_settings = json.loads(item["settings_json"] or "{}") + settings = _settings_from(parsed, stored_settings) + result = load_json(item["result_path"]) if item.get("result_path") else None + preview_n = None + if step == 2: + preview_n = len(select_students(parsed, settings)) + return render( + request, + "analysis.html", + item=item, + step=step, + settings=settings, + summary=settings["summary"], + result=result, + preview_n=preview_n, + ) + + +@app.post("/analysis/{aid}/settings") +async def save_settings(request: Request, aid: int): + if (redir := require_login(request)): + return redir + item = get_analysis(aid) + if not item: + return HTMLResponse("分æžä¸å­˜åœ¨", status_code=404) + parsed = load_json(item["parsed_path"]) + form = await request.form() + exams = form.getlist("exams") + if not exams: + exams = parsed["exams"] + groups = sorted({infer_track_group(s["track"]) for s in parsed["students"]}) + targets = {} + for g in groups: + names = form.getlist(f"t_name_{g}") + ks = form.getlist(f"t_k_{g}") + ids = form.getlist(f"t_id_{g}") + rows = [] + for i, name in enumerate(names): + k_raw = ks[i] if i < len(ks) else "0" + try: + k = int(float(k_raw)) + except ValueError: + k = 0 + tid = ids[i] if i < len(ids) and ids[i] else f"t{i+1}" + if name.strip() and k > 0: + rows.append({"id": tid, "name": name.strip(), "k": k}) + targets[g] = rows or default_targets([g])[g] + settings = { + "exams": list(exams), + "include_art": form.get("include_art") == "on", + "include_leave": form.get("include_leave") == "on", + "include_mingyuan": form.get("include_mingyuan") == "on", + "include_other": form.get("include_other") == "on", + "horizon": int(form.get("horizon") or 1), + "targets": targets, + } + update_analysis(aid, settings_json=json.dumps(settings, ensure_ascii=False), step=2) + action = form.get("action") or "next" + if action == "compute": + result = analyze(parsed, settings) + token = uuid.uuid4().hex[:10] + result_path = str(DATA_DIR / f"result_{token}.json") + save_json(result_path, result) + update_analysis(aid, result_path=result_path, step=3) + return RedirectResponse(f"/analysis/{aid}?step=3", status_code=303) + return RedirectResponse(f"/analysis/{aid}?step=2", status_code=303) + + +@app.get("/analysis/{aid}/api/student/{sid}") +def student_api(request: Request, aid: int, sid: str): + if not current_user(request): + return Response("unauthorized", status_code=401) + item = get_analysis(aid) + if not item or not item.get("result_path"): + return Response("not found", status_code=404) + result = load_json(item["result_path"]) + for s in result["students"]: + if str(s["sid"]) == str(sid): + return s + return Response("not found", status_code=404) + + +@app.get("/analysis/{aid}/api/class") +def class_api(request: Request, aid: int, group: str, target: str, class_name: str): + if not current_user(request): + return Response("unauthorized", status_code=401) + item = get_analysis(aid) + if not item or not item.get("result_path"): + return Response("not found", status_code=404) + result = load_json(item["result_path"]) + rows = [ + s + for s in result["students"] + if s["group"] == group and s["class_name"] == class_name + ] + rows.sort(key=lambda s: -((s.get("probs") or {}).get(target) or 0)) + return {"exams": result["exams"], "students": rows[:80], "n": len(rows)} + + +@app.get("/analysis/{aid}/export") +def export_analysis(request: Request, aid: int): + if (redir := require_login(request)): + return redir + item = get_analysis(aid) + if not item or not item.get("result_path"): + return HTMLResponse("请先完æˆæµ‹ç®—", status_code=400) + result = load_json(item["result_path"]) + data = build_export(result) + ascii_name = f"hangbiao-{aid}.xlsx" + star = quote(f"{item['title']}-下达指标.xlsx") + return Response( + content=data, + media_type="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet", + headers={"Content-Disposition": f"attachment; filename={ascii_name}; filename*=UTF-8''{star}"}, + ) + + +# Jinja 3 / FastAPI 0.115+ TemplateResponse signature is (request, name, context) +# Keep compatibility if older: handled by FastAPI version we pin. diff --git a/app/static/css/app.css b/app/static/css/app.css new file mode 100644 index 0000000..fc852cf --- /dev/null +++ b/app/static/css/app.css @@ -0,0 +1,149 @@ +:root { + --ink: #12233d; + --ink-soft: #3a4a63; + --paper: #f3eee4; + --card: #fffdf8; + --line: #d8cfbf; + --teal: #1c6f63; + --teal-2: #2a9a86; + --amber: #c47b17; + --rose: #b44a4a; + --good: #2f7d4a; + --shadow: 0 18px 40px rgba(18, 35, 61, 0.08); + --font: "Avenir Next", "Segoe UI", "PingFang SC", "Hiragino Sans GB", sans-serif; +} +* { box-sizing: border-box; } +html, body { margin: 0; padding: 0; } +body { + font-family: var(--font); + color: var(--ink); + background: + radial-gradient(1200px 500px at -10% -20%, #e7f3ee 0%, transparent 50%), + radial-gradient(900px 400px at 110% 0%, #f8e9d2 0%, transparent 46%), + var(--paper); + min-height: 100vh; +} +a { color: var(--teal); } +.topbar { + display: flex; align-items: center; justify-content: space-between; + padding: 16px 28px; + border-bottom: 1px solid var(--line); + background: rgba(255,253,248,0.86); + backdrop-filter: blur(10px); + position: sticky; top: 0; z-index: 10; +} +.brand { display: flex; gap: 12px; align-items: center; text-decoration: none; color: var(--ink); } +.mark { + width: 36px; height: 36px; border-radius: 50%; + border: 2px solid var(--ink); + display: grid; place-items: center; + font-size: 11px; letter-spacing: 0.08em; +} +.brand b { display: block; font-size: 16px; } +.brand span { display: block; font-size: 12px; color: var(--ink-soft); font-weight: 400; } +.topbar form { margin: 0; } +.ghost, .btn, .primary { + border: 1px solid var(--ink); background: transparent; color: var(--ink); + padding: 8px 14px; border-radius: 999px; cursor: pointer; font: inherit; + text-decoration: none; display: inline-flex; align-items: center; gap: 8px; +} +.primary { background: var(--ink); color: var(--paper); } +.btn.teal { background: var(--teal); border-color: var(--teal); color: white; } +.wrap { width: min(1180px, calc(100% - 40px)); margin: 28px auto 64px; } +.hero, .card, .login-card { + background: var(--card); + border: 1px solid var(--line); + border-radius: 22px; + box-shadow: var(--shadow); +} +.hero { padding: 28px; display: grid; grid-template-columns: 1.4fr 1fr; gap: 24px; } +.hero h1 { margin: 0 0 8px; font-size: 30px; letter-spacing: 0.02em; } +.hero p { margin: 0; color: var(--ink-soft); line-height: 1.7; } +.drop { + border: 1.5px dashed var(--teal); + border-radius: 18px; padding: 22px; background: #f4fbf8; +} +.drop h3 { margin: 0 0 8px; } +.muted { color: var(--ink-soft); font-size: 13px; line-height: 1.6; } +.list { margin-top: 22px; display: grid; gap: 10px; } +.item { + background: var(--card); border: 1px solid var(--line); border-radius: 14px; + padding: 14px 16px; display: flex; justify-content: space-between; align-items: center; +} +.login-wrap { min-height: 100vh; display: grid; place-items: center; padding: 24px; } +.login-card { width: min(440px, 100%); padding: 32px; } +.login-card h1 { margin: 8px 0 4px; } +label { display: block; font-size: 13px; margin: 14px 0 6px; color: var(--ink-soft); } +input[type=text], input[type=password], input[type=number], select { + width: 100%; padding: 10px 12px; border-radius: 10px; + border: 1px solid var(--line); font: inherit; background: white; +} +.err { color: var(--rose); font-size: 13px; margin-top: 8px; } +.layout { display: grid; grid-template-columns: 250px 1fr; gap: 22px; } +.rail { + background: var(--ink); color: #e8e2d6; border-radius: 22px; padding: 20px 16px; + height: fit-content; position: sticky; top: 88px; +} +.rail h2 { font-size: 14px; margin: 0 0 16px; font-weight: 600; } +.step { + display: grid; grid-template-columns: 28px 1fr; gap: 10px; padding: 10px 8px; + border-radius: 12px; color: #c9c1b3; text-decoration: none; +} +.step b { display: block; color: inherit; font-size: 14px; } +.step span { display: block; font-size: 12px; opacity: 0.8; } +.dot { + width: 28px; height: 28px; border-radius: 50%; border: 1px solid #7d8796; + display: grid; place-items: center; font-size: 12px; +} +.step.on { background: rgba(255,255,255,0.06); color: white; } +.step.on .dot { background: var(--teal-2); border-color: var(--teal-2); color: white; } +.panel { padding: 24px 26px 30px; } +.panel h1 { margin: 0 0 6px; font-size: 26px; } +.kpis { display: grid; grid-template-columns: repeat(4, 1fr); gap: 12px; margin: 18px 0; } +.kpi { border: 1px solid var(--line); border-radius: 14px; padding: 12px 14px; background: #fbfaf6; } +.kpi em { display: block; font-style: normal; font-size: 12px; color: var(--ink-soft); } +.kpi strong { font-size: 22px; } +.table { width: 100%; border-collapse: collapse; font-size: 14px; } +.table th { text-align: left; font-size: 12px; color: var(--ink-soft); font-weight: 600; padding: 8px 6px; border-bottom: 1px solid var(--line); } +.table td { padding: 9px 6px; border-bottom: 1px solid #eee6d8; } +.chips { display: flex; flex-wrap: wrap; gap: 8px; margin: 10px 0 4px; } +.chip { background: #efe8da; border-radius: 999px; padding: 4px 10px; font-size: 12px; } +.warn { background: #fff4e6; border: 1px solid #f1d2a3; color: #8a5a12; padding: 10px 12px; border-radius: 12px; margin: 8px 0; font-size: 13px; } +.grid-2 { display: grid; grid-template-columns: 1fr 1fr; gap: 16px; } +.check { display: flex; gap: 8px; align-items: flex-start; margin: 8px 0; font-size: 14px; } +.check input { margin-top: 3px; } +.actions { display: flex; gap: 10px; margin-top: 22px; } +.explain { + background: linear-gradient(180deg, #f7fbf9, #fff); + border: 1px solid #cfe3dc; border-radius: 16px; padding: 16px 18px; line-height: 1.7; +} +.route { display: flex; gap: 8px; flex-wrap: wrap; margin: 12px 0 4px; } +.route i { + font-style: normal; background: var(--ink); color: var(--paper); + border-radius: 999px; padding: 6px 10px; font-size: 12px; +} +.route i.alt { background: var(--teal); } +.bar-wrap { height: 10px; background: #efe8da; border-radius: 99px; overflow: hidden; } +.bar { height: 100%; background: var(--teal); } +.delta-up { color: var(--good); } +.delta-down { color: var(--rose); } +.tag { font-size: 11px; padding: 2px 7px; border-radius: 99px; background: #efe8da; } +.tag.mid { background: #f8e3bf; color: #8a5a12; } +.tag.high { background: #d8f0e5; color: #1c6f63; } +.drawer-bg { + position: fixed; inset: 0; background: rgba(18,35,61,0.35); display: none; + align-items: stretch; justify-content: flex-end; z-index: 20; +} +.drawer-bg.show { display: flex; } +.drawer { + width: min(560px, 100%); background: var(--card); padding: 22px; + overflow: auto; box-shadow: -20px 0 40px rgba(18,35,61,0.15); +} +.spark { width: 100%; height: 220px; } +.tiny { font-size: 12px; color: var(--ink-soft); } +.clickable { cursor: pointer; } +.clickable:hover { background: #f7f3ea; } +@media (max-width: 900px) { + .hero, .layout, .grid-2, .kpis { grid-template-columns: 1fr; } + .rail { position: static; } +} diff --git a/app/static/js/app.js b/app/static/js/app.js new file mode 100644 index 0000000..a8cd9cf --- /dev/null +++ b/app/static/js/app.js @@ -0,0 +1,112 @@ +function closeDrawer() { + const el = document.getElementById("drawer"); + if (el) el.classList.remove("show"); +} + +function sparkline(svg, exams, zs, xs, lastRank) { + const w = 520, h = 220, pad = 28; + const vals = []; + zs.forEach((z, i) => { if (z !== null && z !== undefined) vals.push(z); }); + xs.forEach((z) => { if (z !== null && z !== undefined) vals.push(z); }); + if (!vals.length) return; + const min = Math.min(...vals, -0.5) - 0.3; + const max = Math.max(...vals, 0.5) + 0.3; + const xAt = (i) => pad + (i * (w - pad * 2)) / Math.max(exams.length - 1, 1); + const yAt = (v) => pad + (max - v) * (h - pad * 2) / (max - min); + const pts = (arr) => arr.map((v, i) => v == null ? null : `${xAt(i)},${yAt(v)}`).filter(Boolean).join(" "); + let raw = ""; + zs.forEach((v, i) => { + if (v == null) return; + raw += ``; + }); + const pathXs = xs.map((v, i) => (v == null ? null : [xAt(i), yAt(v)])).filter(Boolean); + let d = ""; + pathXs.forEach((p, i) => { d += (i === 0 ? `M${p[0]} ${p[1]}` : ` L${p[0]} ${p[1]}`); }); + const labels = exams.map((e, i) => { + const short = String(e).replace("-总分", "").replace("高", ""); + return `${short}`; + }).join(""); + svg.setAttribute("viewBox", `0 0 ${w} ${h}`); + svg.innerHTML = ` + + + ${raw} + ${labels} + 标准分轨迹 · 橙点考试，绿线滤波估计 + `; +} + +async function openStudent(aid, sid) { + const res = await fetch(`/analysis/${aid}/api/student/${encodeURIComponent(sid)}`); + if (!res.ok) return; + const s = await res.json(); + const box = document.getElementById("drawer"); + const body = document.getElementById("drawer-body"); + const probs = Object.entries(s.probs || {}).map(([k, v]) => `${k}: ${(v * 100).toFixed(1)}%`).join("　"); + body.innerHTML = ` +
+
+

${s.name} ${s.sid}

+
${s.class_name}ç­ Â· ${s.group} · ${s.status || "在ç±"} · ${s.subjects || ""}
+
+ +
+

+ 绿线是å¡å°”曼估计的稳定水平。如果橙点çªç„¶è·³å¼€ç»¿çº¿ï¼Œç³»ç»Ÿä¼šå½“æˆå‘挥波动，ä¸ä¼šç«‹åˆ»æ”¹åˆ¤æ–­ã€‚ + 达线概率 ${probs || "—"}。 +

+ + + + +
考试分数方å‘内å次标准分滤波
+ `; + const rows = document.getElementById("spark-rows"); + (s.z || []).forEach((z, i) => { + const exam = (window.HB_EXAMS || [])[i] || `第${i + 1}次`; + const score = s.scores ? s.scores[exam] : ""; + const rank = (s.ranks || [])[i]; + const kf = (s.kf_xs || [])[i]; + rows.insertAdjacentHTML("beforeend", ` + ${exam}${score ?? "缺考"}${rank ?? "—"} + ${z == null ? "—" : z.toFixed(2)} + ${kf == null ? "—" : kf.toFixed(2)} + `); + }); + sparkline(document.getElementById("spark"), window.HB_EXAMS || [], s.z || [], s.kf_xs || []); + box.classList.add("show"); +} + +async function openClass(aid, group, target, className) { + const url = `/analysis/${aid}/api/class?group=${encodeURIComponent(group)}&target=${encodeURIComponent(target)}&class_name=${encodeURIComponent(className)}`; + const res = await fetch(url); + if (!res.ok) return; + const data = await res.json(); + const box = document.getElementById("drawer"); + const body = document.getElementById("drawer-body"); + const rows = data.students.map((s) => { + const p = ((s.probs || {})[target] || 0) * 100; + const tag = p >= 80 ? "high" : p >= 20 ? "mid" : ""; + return ` + ${s.name}${s.status || ""} + ${(s.ranks || []).slice(-1)[0] ?? "—"} + ${p.toFixed(1)}% + `; + }).join(""); + body.innerHTML = ` +
+

${className}ç­å­¦ç”Ÿæ¦‚率

+ +
+

点击学生å¯çœ‹æˆç»©è½¨è¿¹ã€‚å…± ${data.n} 人，下列按达线概率排åºã€‚

+ + + ${rows} +
姓åå­¦ç±æœ€è¿‘å次达线概率
+ `; + box.classList.add("show"); +} + +document.addEventListener("click", (e) => { + if (e.target.id === "drawer") closeDrawer(); +}); diff --git a/app/templates/analysis.html b/app/templates/analysis.html new file mode 100644 index 0000000..47efd2b --- /dev/null +++ b/app/templates/analysis.html @@ -0,0 +1,263 @@ + + + + + + {{ item.title }} · 航标 + + + +
+ +
航
+
航标{{ item.title }}
+ +
+ {% if result %} + 导出 Excel + {% endif %} +
+
+
+
+ + +
+ {% if step == 1 %} +

第一步：æˆç»©è¡¨ä½“检

+

先确认系统读到的是你想算的那批人。分数é‡çº²å¯ä»¥ä¸åŒï¼Œç³»ç»Ÿç¨åŽä¼šåœ¨æ¯æ¬¡è€ƒè¯•å†…部标准化。

+
+
识别学生{{ summary.n }}
+
ç­çº§{{ summary.n_class }}
+
考试次数{{ summary.exams|length }}
+
艺体 / 请å‡ç±»{{ summary.art }} / {{ summary.leave }}
+
+ {% for w in summary.warnings %} +
{{ w }}
+ {% endfor %} +
+
+

工作表

+ + + + {% for sh in summary.sheets %} + + {% endfor %} + +
表å类型行数
{{ sh.name }}{{ sh.kind }}{{ sh.rows }}
+

æ–¹å‘ / å­¦ç±

+
+ {% for k,v in summary.tracks.items() %}{{ k or "未分方å‘" }} {{ v }}{% endfor %} +
+
+ {% for k,v in summary.status.items() %}{{ k }} {{ v }}{% endfor %} +
+
+
+

考试识别与分数尺度

+ + + + {% for e in summary.score_scale %} + + + + + {% endfor %} + +
考试有效人数最低最高平å‡
{{ e.exam }}{{ e.n }}{{ e.min }}{{ e.max }}{{ e.mean }}
+

å¹³å‡åˆ†ä»Žé«˜ä¸€åˆ°é«˜ä¸‰æ˜Žæ˜¾ä¸‹é™æ˜¯æ­£å¸¸çš„（试å·ç»“æž„ä¸åŒï¼‰ï¼Œæ‰€ä»¥ä¸èƒ½ç›´æŽ¥æ¯”原始分，åªèƒ½æ¯”åŒæ¬¡è€ƒè¯•é‡Œçš„相对ä½ç½®ã€‚

+
+
+

å„ç­äººæ•°

+
+ {% for k,v in summary.classes.items() %}{{ k }}ç­ {{ v }}人{% endfor %} +
+
+ å£å¾„看起æ¥å¯¹ï¼Œä¸‹ä¸€æ­¥ +
+ {% endif %} + + {% if step == 2 %} +

第二步：å£å¾„与目标线

+

下达指标å‰å…ˆæŠŠâ€œç®—è°ã€çž„哪æ¡çº¿â€é’‰æ­»ã€‚默认排除艺体和长期请å‡ï¼Œæ˜Žè¿œç”Ÿå¯å‚与年级排å。

+
+

用于滤波的考试

+

建议全选。系统会自动让近考æƒé‡å¤§ã€æ—©è€ƒæƒé‡å°ï¼›ä¸æ˜¯æŠŠäº”次考试简å•å¹³å‡ã€‚

+ {% for e in summary.exams %} + + {% endfor %} +
+
+

纳入测算

+ + + + + {% if preview_n is not none %}

按当å‰å£å¾„约 {{ preview_n }} 人进入测算。

{% endif %} +
+
+

预估多远

+ + +

步长越远，ä¸ç¡®å®šæ€§è¶Šå¤§ï¼Œä¸´ç•Œç”Ÿä¼šå˜å¤šï¼Œä¸‹è¾¾äººæ•°ä»æŒ‰æœŸæœ›å–整到目标总é‡ã€‚

+
+
+

å„æ–¹å‘目标人数

+

这是年级总盘å­ã€‚ç­çº§æŒ‡æ ‡ç”±ä¸ªäººè¾¾çº¿æ¦‚率加总åŽå†å–整，åˆè®¡ç­‰äºŽè¿™é‡Œçš„人数。

+ {% for g in settings.groups %} +
+ {{ g }} + {% for t in settings.targets[g] %} +
+ +
+
+
+ {% endfor %} +
+ {% endfor %} +
+ + +
+
+ {% endif %} + + {% if step == 3 %} +

第三步：滤波在åšä»€ä¹ˆ

+ {% if not result %} +

还没有测算结果。请回到第二步点击「开始滤波测算ã€ã€‚

+ 去设置å£å¾„ + {% else %} +
+ 原始分åŒæ¬¡æ ‡å‡†åŒ–å¡å°”曼估计水平模拟下一次排å个人概率ç­çº§åŠ æ€»å–æ•´ +
+

+ 把æ¯æ¬¡è€ƒè¯•çœ‹æˆä¸€æ¬¡å¸¦å™ªå£°çš„定ä½ï¼šå‘挥好å是测é‡å™ªå£° R，真实进步是过程噪声 Q。 + R 相对大时，系统ä¸ä¼šåªä¿¡æœ€è¿‘一次；Q 相对大时，会更快跟上近期趋势。这就是导航里“既看 GPS，也看车自己开的方å‘â€ã€‚ +

+ {% for g in result.groups %} +

{{ g.group }} · 模型å‚æ•°

+
+
过程噪声 Q（真实水平会å˜ï¼‰{{ g.model.q }}
+
测é‡å™ªå£° R（å‘挥波动）{{ g.model.r }}
+
一步预测 RMSE{{ g.model.rmse }}
+
测算人数 / 模拟次数{{ g.n }} / {{ g.model.n_sim }}
+
+ {% if g.holdout %} +

留出最近一次考试åšå¯¹ç…§ï¼šç”¨æ›´æ—©çš„æˆç»©é¢„估最近一次，看滤波是å¦æ¯”“åªçœ‹ä¸Šä¸€åœºå次â€æ›´å‡†ã€‚

+ + + + {% for h in g.holdout %} + + + + + + + {% endfor %} + +
目标K滤波命中åªçœ‹æœ€è¿‘一次
{{ h.target_name }}{{ h.k }}{{ h.kf_hit }} / {{ h.k }}（{{ '%.0f'|format(h.kf_precision * 100) }}%）{{ h.last_hit }} / {{ h.k }}（{{ '%.0f'|format(h.last_precision * 100) }}%）
+ {% endif %} + {% endfor %} +
+ 看å„ç­ä¸‹è¾¾æŒ‡æ ‡ +
+ {% endif %} + {% endif %} + + {% if step == 4 %} +

第四步：下达指标

+ {% if not result %} +

还没有测算结果。请先完æˆç¬¬äºŒæ­¥æµ‹ç®—。

+ {% else %} +

+ 「下达指标ã€æ˜¯æ»¤æ³¢æœŸæœ›å–æ•´åŽçš„人数，å«ä¹‰æ˜¯ï¼šè‹¥å­¦ç”ŸæŒ‰çŽ°æœ‰è½¨è¿¹èµ°ï¼Œè¿™ä¸ªç­æœ¬æ¥åº”当到线的人数。 + ç­ä¼šç›®æ ‡æ˜¯è¶…越它，而ä¸æ˜¯åˆšå¥½æ‰“平。ä¿åº• / 冲刺是模拟分布的大约 20% / 80% 分ä½ï¼Œç”¨æ¥çœ‹æŠŠæ¡è€Œä¸æ˜¯å¦ä¸‹ä¸¤å¥—考核。 +

+ {% for g in result.groups %} + {% for t in g.targets %} +

{{ g.group }} · {{ t.name }}（年级 {{ t.k }} 人）

+

期望åˆè®¡ {{ t.sum_expected }}，临界生（概率 20%–80%）{{ t.critical_n }} 人。点击ç­çº§çœ‹å­¦ç”Ÿæ¦‚率，点击学生看轨迹。

+ + + + + + + + + {% for row in t.classes %} + + + + + + + + + + + + + + {% endfor %} + +
ç­çº§æµ‹ç®—人数最近在线滤波期望下达指标ä¿åº•å†²åˆºç›¸å¯¹æœ€è¿‘
{{ row.class_name }}ç­{{ row.n }}{{ row.current }}{{ '%.2f'|format(row.expected) }}{{ row.assigned }}{{ row.floor }}{{ row.stretch }} + {% if row.delta > 0 %}+{{ row.delta }}{% else %}{{ row.delta }}{% endif %} +
{{ class_comment(row, t.name) }}
+ {% if t.critical %} +

临界生（优先关注）

+ + + + {% for s in t.critical[:15] %} + + + + + + {% endfor %} + +
姓åç­æœ€è¿‘å次达线概率
{{ s.name }}{{ s.class_name }}{{ s.last_rank or "—" }}{{ '%.1f'|format(s.p * 100) }}%
+ {% endif %} + {% endfor %} + {% endfor %} +
+ 导出下达表 + 调整å£å¾„å†ç®— +
+ {% endif %} + {% endif %} +
+
+ +
+
+
+ + + + diff --git a/app/templates/home.html b/app/templates/home.html new file mode 100644 index 0000000..53b16af --- /dev/null +++ b/app/templates/home.html @@ -0,0 +1,55 @@ + + + + + + 航标 · ç­çº§è¾¾çº¿æŒ‡æ ‡é¢„ä¼° + + + +
+ +
航
+
航标ç­çº§è¾¾çº¿æŒ‡æ ‡é¢„估系统
+ +
+
+
+
+
+

把历å²æˆç»©å½“æˆå¯¼èˆªè½¨è¿¹ï¼Œ
而ä¸æ˜¯ä¸€å¼ é™æ€æŽ’å表。

+

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+ +
+ +
+
+
+ {% if has_sample %} +
+ +
+ {% endif %} +
+ {% for it in items %} + +
+ {{ it.title }} +
{{ it.filename }} · {{ it.created_at }}
+
+ 继续第 {{ it.step or 1 }} 步 + + {% else %} +
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+ {% endfor %} +
+
+ + diff --git a/app/templates/login.html b/app/templates/login.html new file mode 100644 index 0000000..126b0f5 --- /dev/null +++ b/app/templates/login.html @@ -0,0 +1,25 @@ + + + + + + 登录 · 航标 + + + + + + diff --git a/requirements.txt b/requirements.txt new file mode 100644 index 0000000..6ff6ff7 --- /dev/null +++ b/requirements.txt @@ -0,0 +1,6 @@ +fastapi>=0.115 +uvicorn>=0.32 +python-multipart>=0.0.9 +jinja2>=3.1 +itsdangerous>=2.2.0 +openpyxl>=3.1 diff --git a/run.sh b/run.sh new file mode 100755 index 0000000..63c9567 --- /dev/null +++ b/run.sh @@ -0,0 +1,8 @@ +#!/bin/zsh +cd "$(dirname "$0")" +if [ ! -x .venv/bin/python ]; then + python3 -m venv .venv + .venv/bin/pip install -r requirements.txt +fi +export PORT="${PORT:-8765}" +exec .venv/bin/python -m app diff --git a/高三指标划定æ“作指引.docx b/高三指标划定æ“作指引.docx new file mode 100644 index 0000000000000000000000000000000000000000..c9e4126a8a54986c93763614d73e09578f09590a GIT binary patch literal 20728 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