455 lines
21 KiB
Python
455 lines
21 KiB
Python
"""
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dynamics.py
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------
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统一入口：读取 YAML 配置文件 → 运行模拟 → 抽帧 → 绘图（可选）
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用法：
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python dynamics.py # 使用 input/parameters.yaml
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python dynamics.py input/parameters.yaml # 指定配置文件
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python dynamics.py --config input/parameters.yaml --no-plot
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"""
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import os
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import sys
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import subprocess
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import argparse
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from contextlib import contextmanager
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from pathlib import Path
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import yaml
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import numpy as np
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# 导入同目录下的模块
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sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
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import compute
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def read_optional_index(data, key, default_value):
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"""Read an optional integer index from structured txt metadata."""
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if key not in data:
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return default_value
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value = data[key]
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if value is None or int(value) < 0:
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return default_value
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return int(value)
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def load_yaml_config(config_path):
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"""从 YAML 文件加载配置字典。"""
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with open(config_path, 'r', encoding='utf-8') as f:
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config = yaml.safe_load(f)
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return config
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def resolve_path(base_dir, path_value):
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"""Resolve a path relative to the runtime base directory."""
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path = Path(path_value)
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if path.is_absolute():
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return path
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return (Path(base_dir) / path).resolve()
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@contextmanager
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def runtime_dir_overrides(input_dir=None, output_dir=None):
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"""Temporarily override runtime input/output directories for compute helpers."""
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old_input = os.environ.get("DYNAMICS_INPUT_DIR")
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old_output = os.environ.get("DYNAMICS_OUTPUT_DIR")
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try:
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if input_dir is not None:
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os.environ["DYNAMICS_INPUT_DIR"] = str(Path(input_dir).resolve())
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if output_dir is not None:
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os.environ["DYNAMICS_OUTPUT_DIR"] = str(Path(output_dir).resolve())
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yield
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finally:
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if old_input is None:
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os.environ.pop("DYNAMICS_INPUT_DIR", None)
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else:
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os.environ["DYNAMICS_INPUT_DIR"] = old_input
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if old_output is None:
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os.environ.pop("DYNAMICS_OUTPUT_DIR", None)
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else:
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os.environ["DYNAMICS_OUTPUT_DIR"] = old_output
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def build_sample_indices(total_steps, sample_step, sample_start, sample_end):
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"""Validate sampling settings and build frame indices."""
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if sample_step <= 0:
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raise ValueError(f"NSTEP 必须为正整数，实际为 {sample_step}")
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if sample_start < 0:
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raise ValueError(f"sample_start 不能小于 0，实际为 {sample_start}")
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if sample_end > total_steps:
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raise ValueError(
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f"sample_end 不能大于记录步数 {total_steps}，实际为 {sample_end}")
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if sample_start >= sample_end:
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raise ValueError(
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f"sample_start 必须小于 sample_end，实际为 [{sample_start}, {sample_end})")
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n_frames = (sample_end - sample_start) // sample_step
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if n_frames <= 0:
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raise ValueError(
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f"抽帧范围 [{sample_start}, {sample_end}) 过短，按 NSTEP={sample_step} 无法抽出任何帧")
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indices = np.arange(n_frames, dtype=np.int64) * sample_step + sample_start
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return indices
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def save_display_txt(data, out_dir=None):
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"""将抽帧数据保存到 output/display.txt（含所有参数元数据）。"""
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if out_dir is None:
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out_dir = os.path.dirname(os.path.abspath(__file__))
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disp_path = os.path.join(compute.get_output_dir(out_dir), "display.txt")
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compute.save_text_data(disp_path, data)
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print(f"[sample] 显示数组已保存至: {disp_path}")
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return disp_path
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def run_case(config_path, runtime_base, input_dir="input", output_dir="output", no_plot=False):
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"""Run one case with explicit program path, input path, and output path."""
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runtime_base = Path(runtime_base).resolve()
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input_dir_path = resolve_path(runtime_base, input_dir)
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output_dir_path = resolve_path(runtime_base, output_dir)
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config_path = resolve_path(runtime_base, config_path)
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with runtime_dir_overrides(input_dir_path, output_dir_path):
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# 1. 加载 YAML 配置
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config = load_yaml_config(config_path)
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print(f"[run] 已加载配置: {config_path}")
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# 显示步骤控制信息
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steps_info = {k: config.get(k, 1) for k in ["step_simulate", "step_sample", "step_plot", "step_animation"]}
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step_flags = ", ".join(f"{k}={v}" for k, v in steps_info.items())
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print(f"[run] 步骤开关: {step_flags}")
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warmup = config.get("warmup_steps", 0)
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ss = config.get("sample_start", "从头")
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se = config.get("sample_end", "到尾")
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method = config.get("method", "explicit_euler")
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coord_file = config.get("coord_file", os.path.join("input", "coord.txt"))
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plot_atom = config.get("plot_atom", "第一个原子")
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print(f"[run] 算法: {method}")
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print(f"[run] 坐标文件: {coord_file}")
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print(f"[run] 绘图/动画原子序号: {plot_atom}")
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print(f"[run] 步骤控制: 预热={warmup}步, 抽帧范围=[{ss}, {se})")
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output_dir_abs = compute.get_output_dir(str(runtime_base))
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traj_path = os.path.join(output_dir_abs, "trajectory.txt")
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disp_path = os.path.join(output_dir_abs, "display.txt")
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# ── 自动缓存检测 ───────────────────────────────────────
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# 若 output/ 中 trajectory.txt 和 display.txt 均已存在，
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# 自动跳过模拟和抽帧，直接使用已有结果。
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# 如需强制重新计算，删除 output/ 目录或设 step_simulate: 1 即可。
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output_exists = (
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os.path.isdir(output_dir_abs)
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and os.path.exists(traj_path)
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and os.path.exists(disp_path)
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)
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if output_exists:
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if config.get("step_simulate", 1):
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print(f"[run] 检测到已有输出（{traj_path}），自动跳过模拟与抽帧，直接进入后续步骤")
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config["step_simulate"] = 0
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config["step_sample"] = 0
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else:
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print(f"[run] 已有输出，步骤已被跳过")
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else:
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# 目录存在但文件不全 → 强制重新计算
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if os.path.isdir(output_dir_abs):
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print(f"[run] output/ 目录存在但文件不完整，将重新计算")
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else:
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print(f"[run] output/ 目录不存在，将执行完整流程")
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# 2. 运行物理模拟 → output/trajectory.txt
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if config.get("step_simulate", 1):
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engine = config.get("engine", "python")
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total_steps = config["NT"]
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record_steps = total_steps - (config.get("warmup_steps") or 0)
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print(f"[run] 开始计算 总步数={total_steps} 记录步数={record_steps} DT={config['DT']}")
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if engine == "python":
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traj_x, traj_y, traj_z, traj_vx, traj_vy, traj_vz = compute.run_from_config(config, str(runtime_base))
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print(f"[run] 计算完成，记录 {record_steps} 步")
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compute.save_trajectory_txt(traj_x, traj_y, traj_z, traj_vx, traj_vy, traj_vz, str(runtime_base))
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else:
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# 外部引擎：先加载配置到全局变量，再运行引擎，再用 save_trajectory_txt 补全 metadata
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config["_skip_run"] = True
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compute.run_from_config(config, str(runtime_base))
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config.pop("_skip_run", None)
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input_dir_abs = str(input_dir_path.resolve())
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output_dir_abs = str(output_dir_path.resolve())
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traj_x, traj_y, traj_z, traj_vx, traj_vy, traj_vz = compute.run_engine(
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engine, input_dir_abs, output_dir_abs, config)
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compute.save_trajectory_txt(traj_x, traj_y, traj_z, traj_vx, traj_vy, traj_vz, str(runtime_base))
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else:
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print("[run] 步骤 [模拟] 已跳过，直接加载已有轨迹")
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if not os.path.exists(traj_path):
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print(f"[run] 错误: trajectory.txt 不存在，无法跳过模拟")
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sys.exit(1)
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# 3. 抽帧 → output/display.txt
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traj_path = os.path.join(output_dir_abs, "trajectory.txt")
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data = compute.load_text_data(traj_path)
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NT = int(data["NT"]); DT = float(data["DT"]); NSTEP = int(data["NSTEP"])
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warmup_steps = int(data.get("warmup_steps", 0))
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plot_atom_row = int(data["plot_atom_row"]) if "plot_atom_row" in data else 0
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plot_atom_id = int(data["plot_atom_id"]) if "plot_atom_id" in data else int(data["atom_ids"][plot_atom_row])
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# 抽帧范围控制
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sample_start = read_optional_index(data, "sample_start", 0)
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sample_end = read_optional_index(data, "sample_end", NT)
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indices = build_sample_indices(NT, NSTEP, sample_start, sample_end)
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n_frames = len(indices)
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print(f"[run] 抽帧范围: [{sample_start}, {sample_end}), 共 {n_frames} 帧")
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traj_x = data["traj_x"]
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traj_y = data["traj_y"]
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traj_z = data["traj_z"]
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traj_vx = data["traj_vx"]
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traj_vy = data["traj_vy"]
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traj_vz = data["traj_vz"]
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if traj_x.ndim == 1:
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selected_x = traj_x
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selected_y = traj_y
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selected_z = traj_z
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selected_vx = traj_vx
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selected_vy = traj_vy
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selected_vz = traj_vz
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all_x = traj_x[:, None]
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all_y = traj_y[:, None]
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all_z = traj_z[:, None]
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all_vx = traj_vx[:, None]
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all_vy = traj_vy[:, None]
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all_vz = traj_vz[:, None]
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else:
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selected_x = traj_x[:, plot_atom_row]
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selected_y = traj_y[:, plot_atom_row]
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selected_z = traj_z[:, plot_atom_row]
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selected_vx = traj_vx[:, plot_atom_row]
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selected_vy = traj_vy[:, plot_atom_row]
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selected_vz = traj_vz[:, plot_atom_row]
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all_x = traj_x
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all_y = traj_y
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all_z = traj_z
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all_vx = traj_vx
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all_vy = traj_vy
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all_vz = traj_vz
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if config.get("step_sample", 1):
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disp_data = {
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"disp_x": selected_x[indices],
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"disp_y": selected_y[indices],
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"disp_z": selected_z[indices],
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"disp_vx": selected_vx[indices],
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"disp_vy": selected_vy[indices],
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"disp_vz": selected_vz[indices],
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"disp_all_x": all_x[indices],
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"disp_all_y": all_y[indices],
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"disp_all_z": all_z[indices],
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"disp_all_vx": all_vx[indices],
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"disp_all_vy": all_vy[indices],
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"disp_all_vz": all_vz[indices],
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"disp_t": indices * DT,
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"disp_step": indices,
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"n_frames": n_frames,
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"NT": NT, "DT": DT, "NSTEP": NSTEP,
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"plot_atom_id": plot_atom_id,
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"plot_atom_row": plot_atom_row,
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"method": str(data["method"]) if "method" in data else "explicit_euler",
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"coord_file": str(data["coord_file"]) if "coord_file" in data else os.path.join("input", "coord.txt"),
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"atom_ids": data["atom_ids"] if "atom_ids" in data else np.array([1]),
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"atom_masses": data["atom_masses"] if "atom_masses" in data else np.array([float(data["M"])]),
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"atom_radii": data["atom_radii"] if "atom_radii" in data else np.array([float(data["ball_radius"])]),
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"atom_positions": data["atom_positions"] if "atom_positions" in data else np.array([[float(data["X0"]), float(data["Y0"]), float(data["Z0"])]]),
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"atom_velocities": data["atom_velocities"] if "atom_velocities" in data else np.array([[float(data["VX0"]), float(data["VY0"]), float(data["VZ0"])]]),
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"atom_fixed": data["atom_fixed"] if "atom_fixed" in data else np.array([[0, 0, 0]]),
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"bond_pairs": data.get("bond_pairs", np.zeros((0, 2), dtype=np.int64)).tolist(),
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"warmup_steps": warmup_steps,
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"sample_start": sample_start,
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"sample_end": sample_end,
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"X_MIN": float(data["X_MIN"]), "X_MAX": float(data["X_MAX"]),
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"Y_MIN": float(data["Y_MIN"]), "Y_MAX": float(data["Y_MAX"]),
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"Z_MIN": float(data["Z_MIN"]), "Z_MAX": float(data["Z_MAX"]),
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"X0": float(data["X0"]), "Y0": float(data["Y0"]), "Z0": float(data["Z0"]),
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"VX0": float(data["VX0"]), "VY0": float(data["VY0"]), "VZ0": float(data["VZ0"]),
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"M": float(data["M"]) if "M" in data else 1.0,
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"alpha": data["alpha"],
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"ball_radius": float(data["ball_radius"]),
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"ball_color_r": float(data["ball_color_r"]),
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"ball_color_g": float(data["ball_color_g"]),
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"ball_color_b": float(data["ball_color_b"]),
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"box_color_r": float(data["box_color_r"]),
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"box_color_g": float(data["box_color_g"]),
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"box_color_b": float(data["box_color_b"]),
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}
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save_display_txt(disp_data, str(runtime_base))
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print(f"[run] 抽帧完成: {sample_end - sample_start} 步 -> {n_frames} 帧")
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else:
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print("[run] 步骤 [抽帧] 已跳过")
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# 4. 绘图（可选）
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if not no_plot and config.get("step_plot", 1):
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try:
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import matplotlib.pyplot as plt
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# 配置中文字体支持
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plt.rcParams['font.sans-serif'] = ['SimHei', 'Microsoft YaHei', 'WenQuanYi Micro Hei', 'DejaVu Sans']
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plt.rcParams['axes.unicode_minus'] = False
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time = np.arange(NT) * DT
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n_atoms = all_x.shape[1]
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atom_ids_list = data.get("atom_ids", np.arange(n_atoms) + 1)
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fig, axes = plt.subplots(3, 3, figsize=(15, 13))
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fig.suptitle("轨迹与能量分析", fontsize=16)
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# ── 位置 / 速度 6 子图（前 2 行，每行 3 列） ──
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plot_configs = [
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(axes[0, 0], all_x, "x - 时间"),
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(axes[0, 1], all_y, "y - 时间"),
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(axes[0, 2], all_z, "z - 时间"),
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(axes[1, 0], all_vx, "vx - 时间"),
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(axes[1, 1], all_vy, "vy - 时间"),
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(axes[1, 2], all_vz, "vz - 时间"),
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]
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colors = plt.cm.tab10(np.linspace(0, 1, n_atoms))
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for ax, data_arr, title in plot_configs:
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for i in range(n_atoms):
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atom_id = int(atom_ids_list[i])
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ax.plot(time, data_arr[:, i], color=colors[i], linewidth=1.5, label=f"原子 {atom_id}")
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ax.set_title(title)
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ax.set_xlabel("时间 (s)")
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ax.grid(True, alpha=0.3)
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ax.legend()
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# ── 能量计算 ─────────────────────────────────────
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masses = np.array(data["atom_masses"]) # (n_atoms,)
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G_vec = np.array(data.get("G", [0.0, 0.0, -9.8])) # [gx, gy, gz]
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# 动能 Ek = ½ m v²
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ek = 0.5 * masses[np.newaxis, :] * (all_vx**2 + all_vy**2 + all_vz**2)
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# 重力势能 Ug = -m G·r
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ug = -masses[np.newaxis, :] * (
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G_vec[0] * all_x + G_vec[1] * all_y + G_vec[2] * all_z
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)
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# 弹性势能 Us = ½ k (d - d₀)²
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us = np.zeros_like(ek)
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bond_pairs = data.get("bond_pairs")
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bond_stiffness = data.get("bond_stiffness")
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bond_rest_lengths = data.get("bond_rest_lengths")
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if bond_pairs is not None and len(bond_pairs) > 0:
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for b_idx in range(len(bond_pairs)):
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i, j = bond_pairs[b_idx]
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dx = all_x[:, j] - all_x[:, i]
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dy = all_y[:, j] - all_y[:, i]
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dz = all_z[:, j] - all_z[:, i]
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dist = np.sqrt(dx**2 + dy**2 + dz**2)
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stretch = dist - bond_rest_lengths[b_idx]
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us[:, i] += 0.5 * bond_stiffness[b_idx] * stretch**2
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us[:, j] += 0.5 * bond_stiffness[b_idx] * stretch**2
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# 各原子总能量
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e_total = ek + ug + us # (NT, n_atoms)
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# 系统能量分量
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ek_sys = np.sum(ek, axis=1)
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ug_sys = np.sum(ug, axis=1)
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us_sys = np.sum(us, axis=1)
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e_sys = ek_sys + ug_sys + us_sys
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# ── 第 3 行左：各原子总能量 ──
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ax_e = axes[2, 0]
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for i in range(n_atoms):
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aid = int(atom_ids_list[i])
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ax_e.plot(time, e_total[:, i], color=colors[i], linewidth=1.5, label=f"原子 {aid}")
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ax_e.set_title("各原子总能量")
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ax_e.set_xlabel("时间 (s)")
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ax_e.set_ylabel("能量")
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ax_e.grid(True, alpha=0.3)
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ax_e.legend(loc="upper right")
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# ── 第 3 行右：系统总能量 ──
|
||
ax_sys = axes[2, 1]
|
||
ax_sys.plot(time, ek_sys, 'b-', linewidth=1.5, label="系统动能")
|
||
ax_sys.plot(time, ug_sys, 'g-', linewidth=1.5, label="系统重力势能")
|
||
if bond_pairs is not None and len(bond_pairs) > 0:
|
||
ax_sys.plot(time, us_sys, color='orange', linewidth=1.5, label="系统弹性势能")
|
||
ax_sys.plot(time, e_sys, 'r--', linewidth=1.5, label="系统总能量")
|
||
ax_sys.set_title("系统总能量")
|
||
ax_sys.set_xlabel("时间 (s)")
|
||
ax_sys.set_ylabel("能量")
|
||
ax_sys.grid(True, alpha=0.3)
|
||
ax_sys.legend(loc="upper right")
|
||
|
||
# 隐藏第 3 行第 3 列空子图
|
||
axes[2, 2].set_visible(False)
|
||
|
||
plt.tight_layout(rect=[0, 0.03, 1, 0.95])
|
||
plot_path = os.path.join(output_dir_abs, "trajectory_plots.png")
|
||
plt.savefig(plot_path, dpi=300, bbox_inches="tight")
|
||
print(f"[run] 轨迹图表已保存至: {plot_path}")
|
||
plt.show()
|
||
except ImportError:
|
||
print("[run] 警告: 未安装 matplotlib，跳过绘图")
|
||
|
||
print(f"[run] 完成！输出目录: {output_dir_abs}")
|
||
|
||
# 5. 自动播放动画（可选）
|
||
if config.get("step_animation", 0):
|
||
draw_script = os.path.join(os.path.dirname(os.path.abspath(__file__)), "draw.py")
|
||
if os.path.exists(draw_script):
|
||
try:
|
||
print("[run] 正在启动 VisPy 3D 动画窗口…")
|
||
subprocess.Popen(
|
||
[sys.executable, draw_script],
|
||
cwd=runtime_base,
|
||
stdout=subprocess.DEVNULL,
|
||
stderr=subprocess.DEVNULL,
|
||
)
|
||
except Exception as e:
|
||
print(f"[run] 启动动画失败: {e}")
|
||
else:
|
||
print(f"[run] 未找到动画脚本: {draw_script}")
|
||
else:
|
||
print("[run] 运行 python draw.py 查看动画。")
|
||
|
||
|
||
def main():
|
||
parser = argparse.ArgumentParser(description="物理模拟统一入口")
|
||
parser.add_argument("config_file", nargs="?", default=os.path.join("input", "parameters.yaml"),
|
||
help="YAML 配置文件路径（默认: input/parameters.yaml）")
|
||
parser.add_argument("--config", dest="config_override",
|
||
help="YAML 配置文件路径（可选，优先于位置参数）")
|
||
parser.add_argument("--input-dir", default="input",
|
||
help="输入目录路径（默认: input）")
|
||
parser.add_argument("--output-dir", default="output",
|
||
help="输出目录路径（默认: output）")
|
||
parser.add_argument("--runtime-base", default=".",
|
||
help="案例运行根目录（默认: 当前目录）")
|
||
parser.add_argument("--no-plot", action="store_true",
|
||
help="跳过 matplotlib 绘图")
|
||
args = parser.parse_args()
|
||
|
||
config_path = args.config_override or args.config_file
|
||
runtime_base = resolve_path(os.getcwd(), args.runtime_base)
|
||
config_path_abs = resolve_path(runtime_base, config_path)
|
||
if not os.path.exists(config_path_abs):
|
||
print(f"错误: 配置文件不存在: {config_path_abs}")
|
||
sys.exit(1)
|
||
run_case(
|
||
config_path=config_path_abs,
|
||
runtime_base=runtime_base,
|
||
input_dir=args.input_dir,
|
||
output_dir=args.output_dir,
|
||
no_plot=args.no_plot,
|
||
)
|
||
|
||
|
||
if __name__ == "__main__":
|
||
main()
|