feat: 初始化麦麦智农作物生长模拟平台

- 基于 PCSE/WOFOST 构建作物生长模拟平台
  - 新增 Streamlit 可视化应用（app.py）与模拟引擎（simulator.py）
  - 支持潜在生产（PP）与水分限制生产（WLP）两种模拟模式
  - 支持冬小麦、玉米、春大麦、马铃薯、冬油菜、向日葵 6 种作物
  - 提供 LAI 动态、生物量积累、土壤水分、产量对比等可视化图表
  - 新增 pyproject.toml、justfile、Dockerfile 等工程配置
  - 完善 README.md 项目文档与 .gitignore 忽略规则

simulator.py

@@ -0,0 +1,223 @@
+"""
+麦麦智农 - PCSE 模拟引擎封装
+基于 WOFOST 7.2 潜在生产（PP）与水分限制生产（WLP）模型
+"""
+
+import sqlite3
+from collections import namedtuple
+from typing import Literal
+
+import pandas as pd
+
+import pcse
+from pcse.models import Wofost72_PP, Wofost72_WLP_CWB
+from pcse.settings import settings
+from pcse.base import ParameterProvider
+from pcse.tests.db_input import (
+    GridWeatherDataProvider,
+    fetch_soildata,
+    fetch_sitedata,
+    fetch_cropdata,
+    AgroManagementDataProvider,
+)
+
+
+def namedtuple_factory(cursor, row):
+    fields = [column[0] for column in cursor.description]
+    cls = namedtuple("Row", fields)
+    return cls._make(row)
+
+
+# Demo 数据库配置
+DB_PATH = settings.PCSE_USER_HOME + "/pcse.db"
+
+# 作物映射（crop_no -> 中文名/元数据）
+CROP_META = {
+    1: {"name": "冬小麦", "emoji": "🌾", "color": "#c69c5d", "en": "WINTER WHEAT"},
+    2: {"name": "玉米", "emoji": "🌽", "color": "#e8a93f", "en": "GRAIN MAIZE"},
+    3: {"name": "春大麦", "emoji": "🌿", "color": "#9cb85f", "en": "SPRING BARLEY"},
+    7: {"name": "马铃薯", "emoji": "🥔", "color": "#b8a88a", "en": "POTATO"},
+    10: {"name": "冬油菜", "emoji": "🌻", "color": "#d97836", "en": "WINTER RAPESEED"},
+    11: {"name": "向日葵", "emoji": "🌻", "color": "#f4c430", "en": "SUNFLOWER"},
+}
+
+MODE_LABELS = {
+    "pp": "潜在生产",
+    "wlp": "水分限制生产",
+}
+
+
+def get_db_conn():
+    conn = sqlite3.connect(DB_PATH)
+    conn.row_factory = namedtuple_factory
+    return conn
+
+
+def list_available_years(grid_no: int = 31031) -> list[int]:
+    """返回 Demo 数据库中指定 grid 有气象数据的年份列表。"""
+    conn = get_db_conn()
+    c = conn.cursor()
+    rows = c.execute(
+        "SELECT DISTINCT strftime('%Y', day) as year FROM grid_weather WHERE grid_no=? ORDER BY year",
+        (grid_no,),
+    ).fetchall()
+    conn.close()
+    return [int(r.year) for r in rows]
+
+
+def list_available_crops(grid_no: int = 31031, year: int = 2000) -> list[dict]:
+    """返回指定 grid 与年份有作物日历的作物列表。"""
+    conn = get_db_conn()
+    c = conn.cursor()
+    rows = c.execute(
+        "SELECT crop_no FROM crop_calendar WHERE grid_no=? AND year=? ORDER BY crop_no",
+        (grid_no, year),
+    ).fetchall()
+    conn.close()
+    result = []
+    for r in rows:
+        meta = CROP_META.get(r.crop_no)
+        if meta:
+            result.append({"crop_no": r.crop_no, **meta})
+    return result
+
+
+def run_wofost(
+    grid_no: int = 31031,
+    crop_no: int = 1,
+    year: int = 2000,
+    mode: Literal["pp", "wlp"] = "wlp",
+) -> dict:
+    """
+    运行 WOFOST 模拟，返回包含输出时间序列与关键指标的字典。
+    """
+    conn = get_db_conn()
+    try:
+        agromanagement = AgroManagementDataProvider(conn, grid_no, crop_no, year)
+        sited = fetch_sitedata(conn, grid_no, year)
+        cropd = fetch_cropdata(conn, grid_no, year, crop_no)
+        soild = fetch_soildata(conn, grid_no)
+        parvalues = ParameterProvider(sitedata=sited, soildata=soild, cropdata=cropd)
+        wdp = GridWeatherDataProvider(conn, grid_no=grid_no)
+
+        if mode == "pp":
+            wofsim = Wofost72_PP(parvalues, wdp, agromanagement)
+        else:
+            wofsim = Wofost72_WLP_CWB(parvalues, wdp, agromanagement)
+
+        wofsim.run_till_terminate()
+        output = wofsim.get_output()
+    finally:
+        conn.close()
+
+    df = pd.DataFrame(output)
+    if not df.empty and "day" in df.columns:
+        df = df.set_index("day")
+
+    # 关键指标
+    if not df.empty:
+        last = df.iloc[-1]
+        max_lai = df["LAI"].max() if "LAI" in df.columns else None
+        tagp = last.get("TAGP")
+        twso = last.get("TWSO")
+        sm_end = last.get("SM")
+        dvs_end = last.get("DVS")
+        duration = len(df)
+    else:
+        max_lai = tagp = twso = sm_end = dvs_end = duration = None
+
+    # 生育期里程碑（基于 DVS）
+    milestones = {}
+    if not df.empty and "DVS" in df.columns:
+        dvs_series = df["DVS"]
+        # 出苗/开始生长 DVS ~0（实际在 calendar 开始日）
+        # 开花 DVS ~1.0
+        # 成熟 DVS ~2.0
+        flowering = dvs_series[dvs_series >= 1.0]
+        if not flowering.empty:
+            milestones["flowering"] = flowering.index[0]
+        maturity = dvs_series[dvs_series >= 2.0]
+        if not maturity.empty:
+            milestones["maturity"] = maturity.index[0]
+        # 开始日
+        milestones["start"] = df.index[0]
+        milestones["end"] = df.index[-1]
+
+    meta = CROP_META.get(crop_no, {"name": "未知作物", "emoji": "🌱", "color": "#888"})
+
+    return {
+        "meta": {
+            "grid_no": grid_no,
+            "crop_no": crop_no,
+            "year": year,
+            "mode": mode,
+            **meta,
+            "mode_label": MODE_LABELS.get(mode, mode),
+        },
+        "df": df,
+        "summary": {
+            "tagp": tagp,  # 总地上生物量 kg/ha
+            "twso": twso,  # 经济产量 kg/ha
+            "max_lai": max_lai,
+            "sm_end": sm_end,
+            "dvs_end": dvs_end,
+            "duration": duration,
+            "milestones": milestones,
+        },
+    }
+
+
+def run_multi_crop(
+    grid_no: int = 31031,
+    year: int = 2000,
+    mode: Literal["pp", "wlp"] = "wlp",
+) -> list[dict]:
+    """
+    对指定年份所有可用作物运行模拟，返回各作物汇总结果列表（按 TWSO 排序）。
+    """
+    crops = list_available_crops(grid_no, year)
+    results = []
+    for c in crops:
+        try:
+            res = run_wofost(grid_no=grid_no, crop_no=c["crop_no"], year=year, mode=mode)
+            results.append({
+                "crop_no": c["crop_no"],
+                "name": c["name"],
+                "emoji": c["emoji"],
+                "color": c["color"],
+                "tagp": res["summary"]["tagp"],
+                "twso": res["summary"]["twso"],
+                "max_lai": res["summary"]["max_lai"],
+                "duration": res["summary"]["duration"],
+            })
+        except Exception:
+            # 某些作物可能因数据缺失导致模拟失败，静默跳过
+            continue
+    results.sort(key=lambda x: (x["twso"] if x["twso"] is not None else -1), reverse=True)
+    return results
+
+
+def run_multi_year(
+    grid_no: int = 31031,
+    crop_no: int = 1,
+    mode: Literal["pp", "wlp"] = "wlp",
+) -> list[dict]:
+    """
+    对指定作物在所有可用年份运行模拟，返回各年份汇总结果列表。
+    """
+    years = list_available_years(grid_no)
+    results = []
+    meta = CROP_META.get(crop_no, {"name": "未知作物", "emoji": "🌱", "color": "#888"})
+    for year in years:
+        try:
+            res = run_wofost(grid_no=grid_no, crop_no=crop_no, year=year, mode=mode)
+            results.append({
+                "year": year,
+                "tagp": res["summary"]["tagp"],
+                "twso": res["summary"]["twso"],
+                "max_lai": res["summary"]["max_lai"],
+                "duration": res["summary"]["duration"],
+            })
+        except Exception:
+            continue
+    return results