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"""
gen_init_conditions.py — 从 case 模板生成 N 个 trajectory(不同初始条件)
使用 Latin Hypercube Sampling (LHS) 采样初始条件参数,复制模板目录,
直接生成 0/ 目录下的 alpha.water 和 U 场文件(stokes_wave 除外,
该类型通过修改 waveProperties 和 setFieldsDict 实现参数化)。
四个 case 类型的参数空间:
- dam_break: 水柱宽度、高度
- rising_bubble: 气泡半径、水平位置、垂直位置
- droplet_impact: 液滴半径、水平位置、初始高度、撞击速度
- stokes_wave: 波高、波周期、静水位高度(修改 constant/waveProperties
和 system/setFieldsDict,alpha.water 由 setFields 初始化)
用法:
python3 gen_init_conditions.py --templates /opt/cases-templates --output /opt/output/exp-openfoam-001
输出目录结构:
output_dir/
├── dam_break/
│ ├── t00/ ← 0/, constant/, system/, Allrun
│ ├── t01/
│ └── ...
├── rising_bubble/
│ ├── t00/
│ └── ...
├── droplet_impact/
│ ├── t00/
│ └── ...
├── stokes_wave/
│ ├── t00/
│ └── ...
└── manifest.yaml ← 全局 manifest(case 列表 + 参数记录)
参考文献:
[1] OpenFOAM Foundation. OpenFOAM v9 User Guide, 2021.
[2] Hysing, S. et al. (2009). "Quantitative benchmark computations
of two-dimensional bubble dynamics." Int. J. Numer. Meth. Fluids,
60(11), 1259-1288.
[3] Pasandideh-Fard, M. et al. (1996). "Capillary effects during
droplet impact on a solid surface." Phys. Fluids, 8(3), 650-659.
"""
import argparse
import os
import re
import shutil
import logging
from datetime import datetime, timezone
import numpy as np
from scipy.stats.qmc import LatinHypercube
try:
import yaml
HAS_YAML = True
except ImportError:
HAS_YAML = False
# ─── 全局常量 ────────────────────────────────────────────────────────────
NUM_TRAJS = 50 # 总 trajectory 数(35 train + 8 val + 7 test)
GLOBAL_SEED = 42 # 全局随机种子(可复现)
# ─── OpenFOAM 字段文件生成 ──────────────────────────────────────────────
def write_foam_header(f, obj_name, cls, location="0"):
"""写入 OpenFOAM FoamFile header 块"""
f.write("FoamFile\n{\n")
f.write(" version 2.0;\n")
f.write(" format ascii;\n")
f.write(f" class {cls};\n")
f.write(f" location \"{location}\";\n")
f.write(f" object {obj_name};\n")
f.write("}\n\n")
def write_scalar_field(path, header_comment, internal_values, dims="[0 0 0 0 0 0 0]"):
"""写入 volScalarField(internalField 非均匀列表)"""
n = len(internal_values)
with open(path, "w") as f:
write_foam_header(f, os.path.basename(path), "volScalarField")
f.write(f"dimensions {dims};\n\n")
f.write(f"internalField nonuniform List<scalar>\n{n}\n(\n")
for val in internal_values:
f.write(f" {val:.10e}\n")
f.write(")\n;\n\n")
# 边界条件从模板复制(此处只写 internalField,BC 已在模板 0/ 中)
# 注意:此处覆写整个文件,BC 由 _copy_boundary_conditions 补回
def write_vector_field(path, header_comment, internal_values, dims="[0 1 -1 0 0 0 0]"):
"""写入 volVectorField(internalField 非均匀列表)"""
n = len(internal_values)
with open(path, "w") as f:
write_foam_header(f, os.path.basename(path), "volVectorField")
f.write(f"dimensions {dims};\n\n")
f.write(f"internalField nonuniform List<vector>\n{n}\n(\n")
for vx, vy, vz in internal_values:
f.write(f" ({vx:.10e} {vy:.10e} {vz:.10e})\n")
f.write(")\n;\n\n")
def _copy_boundary_conditions(src_path, dst_path):
"""从模板文件复制 boundaryField 块追加到目标文件"""
with open(src_path, "r") as f:
content = f.read()
# 提取 boundaryField 块(从 boundaryField 到末尾)
m = re.search(r"(boundaryField\s*\{[\s\S]*\})", content)
if m:
with open(dst_path, "a") as f:
f.write("\n")
f.write(m.group(1))
f.write("\n")
def has_simulation_data(output_dir):
"""检查目录是否包含仿真结果(log.interFoam 或 0 以外的时间步目录)"""
if not os.path.exists(output_dir):
return False
# 检查 log.interFoam
if os.path.exists(os.path.join(output_dir, "log.interFoam")):
return True
# 检查是否有 0/ 以外的时间步目录
for entry in os.listdir(output_dir):
full = os.path.join(output_dir, entry)
if os.path.isdir(full) and re.match(r"^\d+(\.\d+)?$", entry):
if entry != "0":
return True
return False
def copy_template(template_dir, output_dir, force=False):
"""复制 case 模板到输出目录(含 0/ 目录下的所有模板场文件)
参数:
force: 若为 False 且 output_dir 已有仿真数据,跳过并返回 False;
若为 True,强制覆盖。
返回:
bool: True 表示复制成功,False 表示跳过
"""
if os.path.exists(output_dir):
if not force and has_simulation_data(output_dir):
logging.info(f" 跳过(已有仿真数据): {output_dir}")
return False
shutil.rmtree(output_dir)
shutil.copytree(template_dir, output_dir)
return True
# ─── blockMeshDict 解析 ─────────────────────────────────────────────────
def parse_block_mesh(case_dir):
"""从 system/blockMeshDict 解析网格参数
返回:
dict: {
"nx": int, "ny": int, "nz": int,
"x0": float, "y0": float,
"dx": float, "dy": float,
"Lx": float, "Ly": float
}
"""
bmd_path = os.path.join(case_dir, "system", "blockMeshDict")
with open(bmd_path, "r") as f:
content = f.read()
# 解析 vertices:取第 0 号 (x0, y0, z0) 和第 2 号 (x1, y1, z0)
verts = re.findall(r"\(\s*([\d.eE+\-]+)\s+([\d.eE+\-]+)\s+([\d.eE+\-]+)\s*\)", content)
if len(verts) < 3:
raise ValueError(f"blockMeshDict vertices 不足: {bmd_path}")
x0, y0 = float(verts[0][0]), float(verts[0][1])
x1, y1 = float(verts[2][0]), float(verts[2][1])
# 解析 blocks hex (... ) (nx ny nz)
m = re.search(r"hex\s+\([^)]+\)\s+\(\s*(\d+)\s+(\d+)\s+(\d+)\s*\)", content)
if not m:
raise ValueError(f"无法解析 blockMeshDict blocks: {bmd_path}")
nx, ny, nz = int(m.group(1)), int(m.group(2)), int(m.group(3))
Lx = x1 - x0
Ly = y1 - y0
dx = Lx / nx
dy = Ly / ny
return {
"nx": nx, "ny": ny, "nz": nz,
"x0": x0, "y0": y0,
"dx": dx, "dy": dy,
"Lx": Lx, "Ly": Ly
}
def compute_cell_centers(mesh):
"""计算 cell 中心坐标
返回:
x_centers: np.ndarray, shape (ny, nx) — X 坐标
y_centers: np.ndarray, shape (ny, nx) — Y 坐标
flat_idx: np.ndarray, shape (ny*nx,) — 展平索引(行主序)
"""
nx, ny = mesh["nx"], mesh["ny"]
dx, dy = mesh["dx"], mesh["dy"]
x0, y0 = mesh["x0"], mesh["y0"]
# Cell 中心: x_i = x0 + (i + 0.5) * dx, y_j = y0 + (j + 0.5) * dy
# 行主序: k = j * nx + i (j=Y方向索引, i=X方向索引)
x_1d = np.array([x0 + (i + 0.5) * dx for i in range(nx)])
y_1d = np.array([y0 + (j + 0.5) * dy for j in range(ny)])
# meshgrid: x_centers[j, i], y_centers[j, i]
x_centers, y_centers = np.meshgrid(x_1d, y_1d) # shape (ny, nx)
flat_idx = np.arange(nx * ny)
return x_centers, y_centers, flat_idx
# ─── Case 特定场生成 ───────────────────────────────────────────────────
def _generate_dam_break_fields(case_dir, params, mesh, x_centers, y_centers):
"""生成 dam_break 的 alpha.water 和 U 初始场
参数:
params: dict {"width": float, "height": float}
- width: 水柱宽度 [m], 默认 (0.08, 0.40)
- height: 水柱高度 [m], 默认 (0.15, 0.50)
"""
nx, ny = mesh["nx"], mesh["ny"]
x0, y0 = mesh["x0"], mesh["y0"]
Lx, Ly = mesh["Lx"], mesh["Ly"]
width = params["width"]
height = params["height"]
x_wall = x0 + width # 水柱右边界
# alpha.water: 水柱区域内 = 1, 外部 = 0
alpha = np.where(
(x_centers <= x_wall) & (y_centers <= y0 + height),
1.0, 0.0
).ravel()
# U: 全零初始速度
u_field = np.zeros((nx * ny, 3))
# 写入场文件
alpha_path = os.path.join(case_dir, "0", "alpha.water")
template_alpha = os.path.join(case_dir, "0", "alpha.water.template")
write_scalar_field(alpha_path, "alpha.water", alpha)
_copy_boundary_conditions(template_alpha, alpha_path)
u_path = os.path.join(case_dir, "0", "U")
template_u = os.path.join(case_dir, "0", "U.template")
write_vector_field(u_path, "U", u_field)
_copy_boundary_conditions(template_u, u_path)
def _generate_rising_bubble_fields(case_dir, params, mesh, x_centers, y_centers):
"""生成 rising_bubble 的 alpha.water 和 U 初始场
参数:
params: dict {"radius": float, "cx": float, "cy": float}
- radius: 气泡半径 [m], 固定 0.25(对齐 Hysing Case 1)
- cx: 水平中心 [m], 默认 (0.30, 0.70)
- cy: 垂直中心 [m], 默认 (0.30, 0.80)
"""
nx, ny = mesh["nx"], mesh["ny"]
radius = params["radius"]
cx = params["cx"]
cy = params["cy"]
# alpha.water: 气泡内部 (alpha=0), 外部 (alpha=1)
dist = np.sqrt((x_centers - cx)**2 + (y_centers - cy)**2)
alpha = np.where(dist <= radius, 0.0, 1.0).ravel()
# U: 全零初始速度
u_field = np.zeros((nx * ny, 3))
# 写入场文件
alpha_path = os.path.join(case_dir, "0", "alpha.water")
template_alpha = os.path.join(case_dir, "0", "alpha.water.template")
write_scalar_field(alpha_path, "alpha.water", alpha)
_copy_boundary_conditions(template_alpha, alpha_path)
u_path = os.path.join(case_dir, "0", "U")
template_u = os.path.join(case_dir, "0", "U.template")
write_vector_field(u_path, "U", u_field)
_copy_boundary_conditions(template_u, u_path)
def _generate_droplet_impact_fields(case_dir, params, mesh, x_centers, y_centers):
"""生成 droplet_impact 的 alpha.water 和 U 初始场
参数:
params: dict {"radius": float, "cx": float, "cy": float, "v_impact": float}
- radius: 液滴半径 [m], 默认 (0.015, 0.06)
- cx: 水平中心 [m], 默认域宽 0.4-0.6
- cy: 初始高度 [m] (液滴中心 Y 坐标), 默认 (0.10, 0.25)
- v_impact: 撞击速度 [m/s], 默认 (0.5, 2.0)
参考: Pasandideh-Fard et al. (1996)
液滴为完整圆形,底部距壁面留有 1.5 cell 间隙,避免与壁面单元重叠。
"""
nx, ny = mesh["nx"], mesh["ny"]
radius = params["radius"]
cx = params["cx"]
v_impact = params["v_impact"]
# 完整圆形液滴,底部距壁面 = 1.5 个网格高度(确保 VOF 界面有足够空间)
dy = mesh["dy"]
gap = dy * 1.5
cy = radius + gap
# alpha.water: 完整圆形液滴 (alpha=1), 外部 (alpha=0)
dist = np.sqrt((x_centers - cx)**2 + (y_centers - cy)**2)
is_droplet = dist <= radius
alpha = np.where(is_droplet, 1.0, 0.0).ravel()
# U: 液滴区域有向下的初始速度
is_droplet_flat = is_droplet.ravel()
u_field = np.zeros((nx * ny, 3))
u_field[is_droplet_flat, 1] = -v_impact # Uy = -v_impact
# 写入场文件
alpha_path = os.path.join(case_dir, "0", "alpha.water")
template_alpha = os.path.join(case_dir, "0", "alpha.water.template")
write_scalar_field(alpha_path, "alpha.water", alpha)
_copy_boundary_conditions(template_alpha, alpha_path)
u_path = os.path.join(case_dir, "0", "U")
template_u = os.path.join(case_dir, "0", "U.template")
write_vector_field(u_path, "U", u_field)
_copy_boundary_conditions(template_u, u_path)
def _generate_stokes_wave_fields(case_dir, params, mesh, x_centers, y_centers):
"""生成 stokes_wave 的 waveProperties 和 setFieldsDict 配置
stokes_wave 不直接生成 alpha.water / U 场文件,而是通过修改
constant/waveProperties 和 system/setFieldsDict 来参数化波浪初始条件。
alpha.water 由 setFields 在运行时初始化(Allrun 中已含 runParallel setFields)。
参数:
params: dict {"waveHeight": float, "wavePeriod": float, "waterLevel": float}
- waveHeight: 波高 [m], 默认 (0.04, 0.16)
- wavePeriod: 波周期 [s], 默认 (1.2, 3.0)
- waterLevel: 静水位高度 [m], 默认 (0.30, 0.50)
"""
wave_height = params["waveHeight"]
wave_period = params["wavePeriod"]
water_level = params["waterLevel"]
# --- 修改 constant/waveProperties ---
wp_path = os.path.join(case_dir, "constant", "waveProperties")
with open(wp_path, "r") as f:
wp_content = f.read()
# 替换 waveHeight 值(保留缩进和尾部注释/分号)
wp_content = re.sub(
r"(waveHeight\s+)[\d.eE+-]+(\s*;.*)",
lambda m: f"{m.group(1)}{wave_height}{m.group(2)}",
wp_content,
)
# 替换 wavePeriod 值
wp_content = re.sub(
r"(wavePeriod\s+)[\d.eE+-]+(\s*;.*)",
lambda m: f"{m.group(1)}{wave_period}{m.group(2)}",
wp_content,
)
with open(wp_path, "w") as f:
f.write(wp_content)
# --- 修改 system/setFieldsDict ---
sf_path = os.path.join(case_dir, "system", "setFieldsDict")
with open(sf_path, "r") as f:
sf_content = f.read()
# 替换 box 定义中的 z 坐标(第三个分量)
# box 格式: box (0 0 0) (30.0 1.0 0.4) —— 替换最后一个数字
sf_content = re.sub(
r"(box\s+\([^)]+\)\s+\(\s*[\d.eE+-]+\s+[\d.eE+-]+\s+)[\d.eE+-]+(\s*\))",
lambda m: f"{m.group(1)}{water_level}{m.group(2)}",
sf_content,
)
with open(sf_path, "w") as f:
f.write(sf_content)
# ─── 参数空间定义 ────────────────────────────────────────────────────────
PARAM_BOUNDS = {
# 参考: OpenFOAM Foundation. OpenFOAM v9 User Guide, 2021.
"dam_break": {
"width": (0.08, 0.40), # 水柱宽度 [m]
"height": (0.15, 0.50), # 水柱高度 [m]
},
# 参考: Hysing, S. et al. (2009). Int. J. Numer. Meth. Fluids, 60(11), 1259-1288.
"rising_bubble": {
"radius": (0.25, 0.25), # 气泡半径 [m],固定 R=0.25m(对齐 Hysing Case 1)
"cx": (0.30, 0.70), # 水平中心 [m] (域宽 1m, R=0.25 → cx∈[0.25,0.75])
"cy": (0.30, 0.80), # 垂直中心 [m](域高 2m,Hysing 初始 y=0.5;采样域下半部确保有上升空间)
},
# 参考: Pasandideh-Fard, M. et al. (1996). Phys. Fluids, 8(3), 650-659.
"droplet_impact": {
"radius": (0.002, 0.004), # 液滴半径 [m],下界确保 ≥20 cells 直径
"cx": (0.016, 0.034), # 水平中心 [m] (域宽 0.05m)
"v_impact": (0.5, 1.5), # 撞击速度 [m/s](Pasandideh-Fard 1996 范围)
},
"stokes_wave": {
"waveHeight": (0.04, 0.16), # 波高 [m], deep water limit H < 0.78*d=0.624m, keep small
"wavePeriod": (1.2, 3.0), # 波周期 [s], keep within 5th-order Stokes range
"waterLevel": (0.30, 0.50), # 静水位高度 [m], domain height=0.8m
},
}
# 约束条件:避免参数组合导致数值问题
CONSTRAINTS = {
"dam_break": lambda p: p["width"] * p["height"] < 0.20,
"rising_bubble": lambda p: True, # R 固定 0.25m,cx/cy 范围已约束,无需额外过滤
"droplet_impact": lambda p: p["radius"] > 0, # cy 由函数内部自动计算
"stokes_wave": lambda p: True, # waveHeight/wavePeriod/waterLevel 相互独立
}
# Case 类型 → 场生成函数
FIELD_GENERATORS = {
"dam_break": _generate_dam_break_fields,
"rising_bubble": _generate_rising_bubble_fields,
"droplet_impact": _generate_droplet_impact_fields,
"stokes_wave": _generate_stokes_wave_fields,
}
def generate_case_params(case_type, n_samples, seed=GLOBAL_SEED):
"""使用 LHS 生成 case 参数
返回:
list[dict]: 每个元素是一个参数字典,键为参数名,值为采样值
"""
bounds = PARAM_BOUNDS[case_type]
param_names = list(bounds.keys())
n_dims = len(param_names)
sampler = LatinHypercube(d=n_dims, seed=seed)
raw_samples = sampler.random(n=n_samples)
# 缩放到实际参数范围
params_list = []
for row in raw_samples:
p = {}
for i, name in enumerate(param_names):
lo, hi = bounds[name]
p[name] = lo + row[i] * (hi - lo)
params_list.append(p)
# 应用约束过滤(不满足约束的重新采样)
constraint = CONSTRAINTS.get(case_type)
if constraint:
rng = np.random.default_rng(seed + 1000)
for i, p in enumerate(params_list):
attempts = 0
while not constraint(p) and attempts < 100:
# 重新采样该点
new_sample = rng.random(n_dims)
for j, name in enumerate(param_names):
lo, hi = bounds[name]
p[name] = lo + new_sample[j] * (hi - lo)
attempts += 1
if attempts >= 100:
logging.warning(f" 约束过滤超时: sample {i}, 使用当前参数")
return params_list
# ─── 主流程 ─────────────────────────────────────────────────────────────
def generate_trajectories(templates_dir, output_dir, num_trajs=NUM_TRAJS,
case_types=None, force=False):
"""为指定 case 类型生成 trajectory
参数:
templates_dir: 模板根目录
output_dir: 输出目录
num_trajs: 每个 case 类型的 trajectory 数
case_types: 要生成的 case 类型列表(None = 全部四个)
流程:
1. 从模板复制 constant/ 和 system/ 目录
2. 复制 0/ 模板作为 .template 备份
3. 解析 blockMeshDict 获取网格参数
4. LHS 采样初始条件参数
5. 直接生成 0/alpha.water 和 0/U 场文件
6. 写入 manifest.yaml
"""
os.makedirs(output_dir, exist_ok=True)
all_case_types = ["dam_break", "rising_bubble", "droplet_impact", "stokes_wave"]
if case_types is None:
case_types = all_case_types
else:
# 验证输入
for ct in case_types:
if ct not in all_case_types:
raise ValueError(f"未知 case 类型: {ct},可选: {all_case_types}")
manifest_entries = []
for case_type in case_types:
template_path = os.path.join(templates_dir, case_type, "base")
if not os.path.isdir(template_path):
logging.error(f"模板目录不存在: {template_path}")
continue
logging.info(f"=== 生成 {case_type} ({num_trajs} trajectories) ===")
# 生成参数
params_list = generate_case_params(case_type, num_trajs)
# 打印参数统计
for name in params_list[0].keys():
vals = [p[name] for p in params_list]
logging.info(f" {name}: min={min(vals):.6f}, max={max(vals):.6f}, "
f"mean={np.mean(vals):.6f}")
skipped = 0
for traj_idx, params in enumerate(params_list):
traj_name = f"t{traj_idx:02d}"
case_dir = os.path.join(output_dir, case_type, traj_name)
# 1. 复制模板(已有仿真数据时跳过,除非 --force)
if not copy_template(template_path, case_dir, force=force):
skipped += 1
continue
# 2. 复制 0/ 模板文件作为 .template 备份
template_0 = os.path.join(template_path, "0")
for fname in ["alpha.water", "U"]:
src = os.path.join(template_0, fname)
if os.path.exists(src):
dst = os.path.join(case_dir, "0", f"{fname}.template")
shutil.copy2(src, dst)
# 3. 解析网格
mesh = parse_block_mesh(case_dir)
x_centers, y_centers, _ = compute_cell_centers(mesh)
# 4. 生成初始场
generator = FIELD_GENERATORS[case_type]
generator(case_dir, params, mesh, x_centers, y_centers)
# 5. 记录 manifest
entry = {
"traj_idx": traj_idx,
"traj_name": traj_name,
"case_type": case_type,
"case_dir": case_dir,
"params": {k: float(v) for k, v in params.items()},
"mesh": {
"nx": mesh["nx"],
"ny": mesh["ny"],
"Lx": mesh["Lx"],
"Ly": mesh["Ly"],
},
"split": "train" if traj_idx < 35 else ("val" if traj_idx < 43 else "test"),
}
manifest_entries.append(entry)
logging.info(f" {case_type} 完成: {num_trajs - skipped} trajectories 生成, {skipped} 跳过")
# 写入 manifest
manifest = {
"generated_at": datetime.now(timezone.utc).isoformat(),
"generator": "gen_init_conditions.py",
"global_seed": GLOBAL_SEED,
"num_trajs_per_case": num_trajs,
"split": {
"train": "indices 0-34",
"val": "indices 35-42",
"test": "indices 43-49",
},
"references": [
"OpenFOAM Foundation. OpenFOAM v9 User Guide, 2021.",
"Hysing, S. et al. (2009). Int. J. Numer. Meth. Fluids, 60(11), 1259-1288.",
"Pasandideh-Fard, M. et al. (1996). Phys. Fluids, 8(3), 650-659.",
],
"cases": manifest_entries,
}
if HAS_YAML:
manifest_path = os.path.join(output_dir, "manifest.yaml")
with open(manifest_path, "w") as f:
yaml.dump(manifest, f, default_flow_style=False, allow_unicode=True, sort_keys=False)
logging.info(f"Manifest 写入: {manifest_path}")
else:
# 无 yaml 模块时写入 JSON 格式
import json
manifest_path = os.path.join(output_dir, "manifest.json")
with open(manifest_path, "w") as f:
json.dump(manifest, f, indent=2)
logging.info(f"Manifest 写入 (JSON): {manifest_path}")
def main():
parser = argparse.ArgumentParser(
description="从 case 模板生成 N 个 trajectory(LHS 参数采样)"
)
parser.add_argument(
"--templates", type=str, default="/mnt/f/agent-workspace/paper2/Exp/data/templates",
help="Case 模板根目录(含 dam_break/, rising_bubble/, droplet_impact/, stokes_wave/ 子目录)"
)
parser.add_argument(
"--output", type=str, default="/mnt/f/agent-workspace/paper2/Exp/data/raw",
help="输出目录"
)
parser.add_argument(
"--num-trajs", type=int, default=NUM_TRAJS,
help=f"每个 case 的 trajectory 数(默认 {NUM_TRAJS})"
)
parser.add_argument(
"--seed", type=int, default=GLOBAL_SEED,
help=f"全局随机种子(默认 {GLOBAL_SEED})"
)
parser.add_argument(
"--case-types", type=str, nargs="+", default=None,
choices=["dam_break", "rising_bubble", "droplet_impact", "stokes_wave"],
help="要生成的 case 类型(默认全部)。可选: dam_break, rising_bubble, droplet_impact, stokes_wave"
)
parser.add_argument(
"--force", action="store_true",
help="强制覆盖已有仿真数据(默认跳过已有数据的 case)"
)
parser.add_argument(
"-v", "--verbose", action="store_true",
help="详细日志输出"
)
args = parser.parse_args()
logging.basicConfig(
level=logging.DEBUG if args.verbose else logging.INFO,
format="%(asctime)s [%(levelname)s] %(message)s",
datefmt="%Y-%m-%d %H:%M:%S",
)
logging.info(f"模板目录: {args.templates}")
logging.info(f"输出目录: {args.output}")
logging.info(f"Trajectory 数: {args.num_trajs}")
logging.info(f"随机种子: {args.seed}")
if args.case_types:
logging.info(f"Case 类型: {args.case_types}")
generate_trajectories(args.templates, args.output, args.num_trajs,
case_types=args.case_types, force=args.force)
logging.info("=== 全部完成 ===")
if __name__ == "__main__":
main()
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