#!/usr/bin/env python3
"""
foam_viz.py — OpenFOAM 2D VOF 场可视化。

从 OpenFOAM case 目录读取 alpha.water 与 U 场，
调用 viz_common.plot_snapshots 生成出版质量快照图。

支持串行和并行 (processor*/) case。

用法:
    from foam_viz import parse_scalar, parse_vector, parse_mesh, plot_foam
    python3 foam_viz.py   # 直接运行生成全部案例可视化
"""

import os
import sys
import re
import struct
import numpy as np

from viz_common import CASES, plot_snapshots, SUBPLOT_BASE_W


# ── OpenFOAM 字段解析 ─────────────────────────────────────────────────────────

def parse_scalar(path):
    """读取 OpenFOAM volScalarField，支持 ASCII 和 binary。"""
    with open(path, "rb") as f:
        raw = f.read()

    uniform_marker = b"internalField"
    uniform_pos = raw.find(uniform_marker)
    if uniform_pos != -1:
        after = raw[uniform_pos + len(uniform_marker):]
        j = 0
        while j < len(after) and after[j:j+1] in b" \t\n\r":
            j += 1
        if after[j:j+7] == b"uniform":
            val_str = after[j + 7:]
            semi = val_str.find(b";")
            if semi != -1:
                val_text = val_str[:semi].decode("ascii", errors="replace").strip()
                try:
                    return float(val_text)
                except ValueError:
                    pass

    marker = b"nonuniform List<scalar>"
    pos = raw.find(marker)
    if pos == -1:
        raise ValueError(f"未找到 nonuniform List<scalar>: {path}")

    rest = raw[pos + len(marker):]
    paren = rest.find(b"(")
    if paren == -1:
        raise ValueError(f"未找到 '(': {path}")
    data_start = pos + len(marker) + paren + 1

    i = data_start
    while i < len(raw) and raw[i:i+1] in b" \t\n\r":
        i += 1
    line_end = raw.find(b"\n", i)
    if line_end == -1:
        line_end = len(raw)
    first_token = raw[i:line_end].decode("ascii", errors="ignore").strip()
    try:
        float(first_token)
        return _parse_ascii_scalar(raw, data_start)
    except (ValueError, UnicodeDecodeError):
        return _parse_binary_scalar(raw, data_start)


def _parse_ascii_scalar(raw, data_start):
    text = raw[data_start:].decode("ascii", errors="replace")
    values = []
    for line in text.split("\n"):
        s = line.strip()
        if s == "" or s.startswith("//"):
            continue
        if s.startswith(")"):
            break
        s = s.lstrip("(")
        if not s:
            continue
        try:
            values.append(float(s))
        except ValueError:
            break
    return np.array(values, dtype=np.float64)


def _parse_binary_scalar(raw, data_start):
    paren_pos = data_start - 1
    line_end = paren_pos
    while line_end > 0 and raw[line_end - 1:line_end] in b"\n\r":
        line_end -= 1
    num_end = line_end
    while num_end > 0 and raw[num_end - 1:num_end].isdigit():
        num_end -= 1
    n_cells = int(raw[num_end:line_end])
    p = data_start
    while p < len(raw) and raw[p:p + 1] in b"\n\r":
        p += 1
    data_end = p + n_cells * 8
    values = struct.unpack(f"{n_cells}d", raw[p:data_end])
    return np.array(values, dtype=np.float64)


def parse_vector(path):
    """读取 OpenFOAM volVectorField，支持 ASCII 和 binary。"""
    with open(path, "rb") as f:
        raw = f.read()

    uniform_marker = b"internalField"
    uniform_pos = raw.find(uniform_marker)
    if uniform_pos != -1:
        after = raw[uniform_pos + len(uniform_marker):]
        j = 0
        while j < len(after) and after[j:j+1] in b" \t\n\r":
            j += 1
        if after[j:j+7] == b"uniform":
            val_str = after[j + 7:]
            semi = val_str.find(b";")
            if semi != -1:
                val_text = val_str[:semi].decode("ascii", errors="replace").strip()
                if val_text.startswith("(") and val_text.endswith(")"):
                    parts = val_text[1:-1].split()
                    if len(parts) >= 2:
                        try:
                            uz_val = float(parts[2]) if len(parts) >= 3 else 0.0
                            return float(parts[0]), float(parts[1]), uz_val
                        except ValueError:
                            pass

    marker = b"nonuniform List<vector>"
    pos = raw.find(marker)
    if pos == -1:
        raise ValueError(f"未找到 nonuniform List<vector>: {path}")

    rest = raw[pos + len(marker):]
    paren = rest.find(b"(")
    if paren == -1:
        raise ValueError(f"未找到 '(': {path}")
    data_start = pos + len(marker) + paren + 1

    i = data_start
    while i < len(raw) and raw[i:i+1] in b" \t\n\r":
        i += 1
    if i < len(raw) and raw[i:i+1] == b"(":
        return _parse_ascii_vector(raw, data_start)
    else:
        return _parse_binary_vector(raw, data_start)


def _parse_ascii_vector(raw, data_start):
    text = raw[data_start:].decode("ascii", errors="replace")
    ux, uy, uz = [], [], []
    for line in text.split("\n"):
        s = line.strip()
        if s == "" or s.startswith("//"):
            continue
        if s.startswith(")"):
            break
        s = s.strip("()")
        s = s.strip()
        if not s:
            continue
        try:
            parts = s.split()
            ux.append(float(parts[0]))
            uy.append(float(parts[1]))
            uz.append(float(parts[2]) if len(parts) >= 3 else 0.0)
        except (ValueError, IndexError):
            break
    return np.array(ux, dtype=np.float64), np.array(uy, dtype=np.float64), np.array(uz, dtype=np.float64)


def _parse_binary_vector(raw, data_start):
    paren_pos = data_start - 1
    line_end = paren_pos
    while line_end > 0 and raw[line_end - 1:line_end] in b"\n\r":
        line_end -= 1
    num_end = line_end
    while num_end > 0 and raw[num_end - 1:num_end].isdigit():
        num_end -= 1
    n_cells = int(raw[num_end:line_end])
    p = data_start
    while p < len(raw) and raw[p:p + 1] in b"\n\r":
        p += 1
    data_end = p + n_cells * 24
    all_vals = struct.unpack(f"{n_cells * 3}d", raw[p:data_end])
    arr = np.array(all_vals, dtype=np.float64).reshape(n_cells, 3)
    return arr[:, 0], arr[:, 1], arr[:, 2]


# ── 网格解析 ──────────────────────────────────────────────────────────────────

def parse_mesh(case_dir):
    """从 blockMeshDict 解析网格信息。"""
    bmd = os.path.join(case_dir, "system", "blockMeshDict")
    if not os.path.isfile(bmd):
        raise FileNotFoundError(f"blockMeshDict 不存在: {bmd}")

    with open(bmd, "r", encoding="utf-8", errors="replace") as f:
        content = f.read()

    v_start = content.find("vertices")
    if v_start == -1:
        raise ValueError("blockMeshDict 中未找到 vertices")
    bracket = content.find("(", v_start)
    depth = 0
    end = bracket
    for ci in range(bracket, len(content)):
        if content[ci] == "(":
            depth += 1
        elif content[ci] == ")":
            depth -= 1
            if depth == 0:
                end = ci
                break
    v_block = content[bracket + 1:end]

    verts = []
    for m in re.finditer(r"\(([^()]+)\)", v_block):
        parts = m.group(1).split()
        if len(parts) >= 3:
            verts.append([float(parts[0]), float(parts[1]), float(parts[2])])
        elif len(parts) >= 2:
            verts.append([float(parts[0]), float(parts[1]), 0.0])

    verts = np.array(verts)
    x0, y0, z0 = verts.min(axis=0)
    x1, y1, z1 = verts.max(axis=0)

    b_start = content.find("blocks")
    if b_start == -1:
        raise ValueError("blockMeshDict 中未找到 blocks")
    b_bracket = content.find("(", b_start)
    depth = 0
    b_end = b_bracket
    for ci in range(b_bracket, len(content)):
        if content[ci] == "(":
            depth += 1
        elif content[ci] == ")":
            depth -= 1
            if depth == 0:
                b_end = ci
                break
    b_block = content[b_bracket + 1:b_end]

    b_tokens = re.findall(r"\(([^()]+)\)", b_block)
    if len(b_tokens) >= 2:
        nums = b_tokens[1].split()
        nx = int(nums[0])
        ny = int(nums[1])
        nz = int(nums[2]) if len(nums) >= 3 else 1
        return {"nx": nx, "ny": ny, "nz": nz,
                "x0": x0, "y0": y0, "x1": x1, "y1": y1,
                "z0": z0, "z1": z1}
    raise ValueError("blockMeshDict 中未解析到 hex block")


# ── 并行 case 支持 ────────────────────────────────────────────────────────────

def _detect_parallel(case_dir, nx, ny):
    """检测并行 case，返回 (proc_dirs, proc_blocks) 或 None。"""
    proc_dirs = sorted(
        [d for d in os.listdir(case_dir)
         if os.path.isdir(os.path.join(case_dir, d)) and d.startswith("processor")],
        key=lambda d: int(re.search(r"\d+", d).group()),
    )
    if not proc_dirs:
        return None

    ref_dir = os.path.join(case_dir, proc_dirs[0])
    t_entries = sorted(os.listdir(ref_dir))
    first_n = nx * ny
    for entry in t_entries:
        if entry == "0":
            continue
        u_path = os.path.join(ref_dir, entry, "U")
        if os.path.isdir(os.path.join(ref_dir, entry)) and os.path.exists(u_path):
            with open(u_path, "rb") as f:
                raw = f.read()
            m = re.search(r"nonuniform\s+List<\w+>\s+(\d+)", raw.decode("latin-1"))
            if m:
                first_n = int(m.group(1))
            break
    else:
        return None

    n_procs = len(proc_dirs)
    total = nx * ny
    if first_n >= total:
        return proc_dirs[:1], [(nx, ny, slice(0, ny), slice(0, nx))]

    dict_path = os.path.join(case_dir, "system", "decomposeParDict")
    n_x, n_y = n_procs, 1
    if os.path.exists(dict_path):
        with open(dict_path, "r", encoding="latin-1") as f:
            content = f.read()
        m = re.search(r"n\s*\(\s*(\d+)\s+(\d+)\s+(\d+)\s*\)", content)
        if m:
            nx_f, ny_f = int(m.group(1)), int(m.group(2))
            if nx_f * ny_f == n_procs:
                n_x, n_y = nx_f, ny_f

    blocks = []
    if n_y > 1:
        block_nx = nx // n_x
        block_ny = ny // n_y
        for pid in range(n_procs):
            gx = pid % n_x
            gy = pid // n_x
            bx0, by0 = gx * block_nx, gy * block_ny
            bx1 = min(bx0 + block_nx, nx) if gx < n_x - 1 else nx
            by1 = min(by0 + block_ny, ny) if gy < n_y - 1 else ny
            blocks.append((bx1 - bx0, by1 - by0, slice(by0, by1), slice(bx0, bx1)))
    else:
        boundaries = [0]
        base, rem = divmod(nx, n_x)
        for p in range(n_x):
            boundaries.append(boundaries[-1] + base + (1 if p < rem else 0))
        for pid in range(n_procs):
            pnx = boundaries[pid + 1] - boundaries[pid]
            blocks.append((pnx, ny, slice(0, ny), slice(boundaries[pid], boundaries[pid + 1])))

    return proc_dirs, blocks


def _read_parallel_field(proc_dirs, blocks, case_dir, t_dir, field_name, is_vector, ny, nx):
    """从 processor 目录组装完整场。"""
    if is_vector:
        full = np.zeros((ny, nx, 3), dtype=np.float64)
    else:
        full = np.zeros((ny, nx), dtype=np.float64)

    for proc_dir, (pnx, pny, rows, cols) in zip(proc_dirs, blocks):
        fpath = os.path.join(case_dir, proc_dir, t_dir, field_name)
        if is_vector:
            ux, uy, uz = parse_vector(fpath)
            if isinstance(ux, (float, int)):
                ux = np.full(pnx * pny, ux)
                uy = np.full(pnx * pny, uy)
                uz = np.full(pnx * pny, uz)
            expected = pnx * pny
            if len(ux) > expected:
                ux_2d = ux.reshape(ny, nx)
                uy_2d = uy.reshape(ny, nx)
                uz_2d = uz.reshape(ny, nx)
                ux = ux_2d[rows, cols].ravel()
                uy = uy_2d[rows, cols].ravel()
                uz = uz_2d[rows, cols].ravel()
            local = np.column_stack([ux, uy, uz]).reshape(pny, pnx, 3)
            full[rows, cols, :] = local
        else:
            val = parse_scalar(fpath)
            if isinstance(val, (float, int)):
                val = np.full(pnx * pny, val)
            expected = pnx * pny
            if len(val) > expected:
                val_2d = val.reshape(ny, nx)
                val = val_2d[rows, cols].ravel()
            full[rows, cols] = val.reshape(pny, pnx)

    return full


def _find_parallel_timesteps(case_dir, proc_dirs):
    """从 processor0 发现所有数值时间步目录名。"""
    ref = os.path.join(case_dir, proc_dirs[0])
    t_dirs = []
    for entry in os.listdir(ref):
        if os.path.isdir(os.path.join(ref, entry)):
            try:
                float(entry)
                t_dirs.append(entry)
            except ValueError:
                continue
    t_dirs.sort(key=lambda x: float(x))
    return t_dirs


def _find_closest_parallel_timestep(t_dirs, t):
    best, best_diff = t_dirs[0], abs(float(t_dirs[0]) - t)
    for td in t_dirs:
        diff = abs(float(td) - t)
        if diff < best_diff:
            best, best_diff = td, diff
    return best, float(best)


def _find_closest_timestep(case_dir, t):
    available = []
    for name in os.listdir(case_dir):
        full = os.path.join(case_dir, name)
        if os.path.isdir(full):
            try:
                available.append((float(name), name))
            except ValueError:
                continue
    if not available:
        raise FileNotFoundError(f"无时间步目录: {case_dir}")
    closest_val, closest_name = min(available, key=lambda x: abs(x[0] - t))
    return closest_name, closest_val


# ── 绘图入口 ──────────────────────────────────────────────────────────────────

def plot_foam(case_dir, timesteps, title, outpath,
              max_aspect=None, axis_labels=("x", "y"), arrow_cfg=None):
    """从 OpenFOAM case 目录生成快照图。"""
    mesh = parse_mesh(case_dir)
    nx, ny = mesh["nx"], mesh["ny"]
    nz = mesh.get("nz", 1)

    is_xz = (ny == 1 and nz > 1)
    if is_xz:
        ncols, nrows = nx, nz
        d0, d1 = mesh["x0"], mesh["z0"]
        d2, d3 = mesh["x1"], mesh["z1"]
        mesh_label = f"{nx}x{nz}"
    else:
        ncols, nrows = nx, ny
        d0, d1 = mesh["x0"], mesh["y0"]
        d2, d3 = mesh["x1"], mesh["y1"]
        mesh_label = f"{nx}x{ny}"

    Ld = d2 - d0
    Lh = d3 - d1
    domain_label = f"{Ld:.3f}x{Lh:.3f}"

    # 检测并行
    parallel = _detect_parallel(case_dir, nx, ny if not is_xz else nz)
    par_t_dirs = None
    if parallel:
        proc_dirs, proc_blocks = parallel
        par_t_dirs = _find_parallel_timesteps(case_dir, proc_dirs)

    # 组装 frames
    frames = []
    for t in timesteps:
        if parallel:
            ts_name, ts_val = _find_closest_parallel_timestep(par_t_dirs, t)
            alpha_flat = _read_parallel_field(
                proc_dirs, proc_blocks, case_dir, ts_name,
                "alpha.water", False, nrows, ncols,
            )
            u_full = _read_parallel_field(
                proc_dirs, proc_blocks, case_dir, ts_name,
                "U", True, nrows, ncols,
            )
            if is_xz:
                alpha_2d = alpha_flat if alpha_flat.ndim == 2 else alpha_flat[:, :, 0]
                u_2d, v_2d = u_full[:, :, 0], u_full[:, :, 2]
            else:
                alpha_2d = alpha_flat if alpha_flat.ndim == 2 else alpha_flat[:, :, 0]
                u_2d, v_2d = u_full[:, :, 0], u_full[:, :, 1]
        else:
            ts_name, ts_val = _find_closest_timestep(case_dir, t)
            ts_dir = os.path.join(case_dir, ts_name)
            n_cells = ncols * nrows
            alpha_raw = parse_scalar(os.path.join(ts_dir, "alpha.water"))
            if isinstance(alpha_raw, (float, int)):
                alpha_raw = np.full(n_cells, alpha_raw)
            alpha_2d = alpha_raw.reshape(nrows, ncols)

            ux, uy, uz = parse_vector(os.path.join(ts_dir, "U"))
            if isinstance(ux, (float, int)):
                ux = np.full(n_cells, ux)
                uy = np.full(n_cells, uy)
                uz = np.full(n_cells, uz)
            if is_xz:
                u_2d = ux.reshape(nrows, ncols)
                v_2d = uz.reshape(nrows, ncols)
            else:
                u_2d = ux.reshape(nrows, ncols)
                v_2d = uy.reshape(nrows, ncols)

        frames.append({"alpha": alpha_2d, "u": u_2d, "v": v_2d, "t": ts_val})

    plot_snapshots(
        frames, outpath, title, mesh_label, domain_label,
        extent=[d0, d2, d1, d3],
        axis_labels=axis_labels, max_aspect=max_aspect, arrow_cfg=arrow_cfg,
    )


# ── 测试入口 ──────────────────────────────────────────────────────────────────

if __name__ == "__main__":
    _cwd = os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "..", ".."))
    _candidate = os.path.join(_cwd, "Exp", "data")
    if os.path.isdir(os.path.join(_candidate, "raw")):
        BASE_DIR = os.path.join(_candidate, "raw")
        OUT_DIR = os.path.join(_candidate, "visualizations")
    elif sys.platform == "win32":
        BASE_DIR = r"F:\agent-workspace\paper2\Exp\data\raw"
        OUT_DIR = r"F:\agent-workspace\paper2\Exp\data\visualizations"
    else:
        BASE_DIR = "/mnt/f/agent-workspace/paper2/Exp/data/raw"
        OUT_DIR = "/mnt/f/agent-workspace/paper2/Exp/data/visualizations"
    os.makedirs(OUT_DIR, exist_ok=True)

    def _auto_select_timesteps(case_dir, requested, nx, ny):
        parallel = _detect_parallel(case_dir, nx, ny)
        if parallel:
            proc_dirs, _ = parallel
            available = sorted([float(t) for t in _find_parallel_timesteps(case_dir, proc_dirs)])
        else:
            available = []
            for name in os.listdir(case_dir):
                full = os.path.join(case_dir, name)
                if os.path.isdir(full):
                    try:
                        available.append(float(name))
                    except ValueError:
                        continue
            available.sort()
        if not available:
            return requested
        t_min, t_max = available[0], available[-1]
        valid = [t for t in requested if t_min - 0.01 <= t <= t_max + 0.01]
        if len(valid) >= 3:
            return valid
        n_show = min(5, len(available))
        indices = np.linspace(0, len(available) - 1, n_show, dtype=int)
        return [available[i] for i in indices]

    for case_name, cfg in CASES.items():
        print(f"\n{'='*60}")
        print(f"  {cfg['title']} ({case_name})")
        print(f"{'='*60}")

        case_dir = os.path.join(BASE_DIR, case_name, "t00")
        if not os.path.isdir(case_dir):
            print(f"  [SKIP] {case_dir}")
            continue

        mesh = parse_mesh(case_dir)
        nz = mesh.get("nz", 1)
        ncols_vis = mesh["nx"]
        nrows_vis = nz if (mesh["ny"] == 1 and nz > 1) else mesh["ny"]
        if nz > 1:
            print(f"  mesh: {mesh['nx']}x{mesh['ny']}x{nz}, "
                  f"domain: {mesh['x1']-mesh['x0']:.3f}x{mesh['y1']-mesh['y0']:.3f}x{mesh['z1']-mesh['z0']:.3f} m")
        else:
            print(f"  mesh: {mesh['nx']}x{mesh['ny']}, "
                  f"domain: {mesh['x1']-mesh['x0']:.3f}x{mesh['y1']-mesh['y0']:.3f} m")

        timesteps = _auto_select_timesteps(case_dir, cfg["timesteps"], ncols_vis, nrows_vis)
        if timesteps != cfg["timesteps"]:
            print(f"  可用时间步: [{timesteps[0]:.2f}...{timesteps[-1]:.2f}], 选取 {len(timesteps)} 个")

        outpath = os.path.join(OUT_DIR, f"{case_name}_foam.png")
        plot_foam(
            case_dir=case_dir,
            timesteps=timesteps,
            title=cfg["title"],
            outpath=outpath,
            max_aspect=cfg.get("max_aspect"),
            axis_labels=cfg.get("axis_labels", ("x", "y")),
            arrow_cfg=cfg.get("arrow_cfg"),
        )
        print(f"  -> {outpath}")

    print(f"\n全部完成。输出: {OUT_DIR}")