feat: 真蛙跳法重构（Python/C/C++/Fortran 四引擎统一）
- 新增 compute_accel_conservative / accel_conservative： 保守力加速度（弹簧+重力+原子间引力），不含阻尼，供蛙跳专用 - 重写 leapfrog_step / leapfrog_full： - 无阻尼：纯辛积分器，每步 1 次力计算（原 Velocity-Verlet 需 2 次） - 有阻尼：半隐式处理 v(t+dt/2)=[v(t-dt/2)*(1-α)+a_c*dt]/(1+α)，无条件稳定 - 主循环加初始化反向半步 v(-dt/2)=v(0)-0.5*a_c(0)*dt - 修复 C/C++ number of frames 字段写采样帧数而非总积分步数的 bug - Python 引擎：新增 display.npz 二进制格式，draw.py/plot_wave.py 优先读取 - 编译参数统一为 -O3 -march=native -ffast-math
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-131
@@ -14,6 +14,7 @@ import sys
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import subprocess
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import time
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import argparse
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import json
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from contextlib import contextmanager
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from pathlib import Path
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@@ -32,6 +33,13 @@ def _fmt_alpha(v):
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return str(float(v))
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def _json_field(value):
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"""Serialize arrays/lists for display header metadata."""
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if isinstance(value, np.ndarray):
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value = value.tolist()
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return json.dumps(value, ensure_ascii=False)
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def _load_camera_kf(config, runtime_base):
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"""加载 move_camera.txt（速度段格式）→ JSON 字符串。"""
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import re, json
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@@ -295,6 +303,12 @@ def run_case(config_path, runtime_base, input_dir="input", output_dir="output",
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"driving_force": str(data.get("driving_force", 0)),
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"use_marker": str(config.get("use_marker", 0)),
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"alpha": _fmt_alpha(data.get("alpha", 0.2)),
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"atom_masses": _json_field(data.get("atom_masses", [])),
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"atom_positions": _json_field(data.get("atom_positions", [])),
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"bond_pairs": _json_field(data.get("bond_pairs", [])),
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"bond_stiffness": _json_field(data.get("bond_stiffness", [])),
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"bond_rest_lengths": _json_field(data.get("bond_rest_lengths", [])),
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"G": _json_field(data.get("G", [0.0, 0.0, 0.0])),
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"atom_radii": _fmt_alpha(data.get("atom_radii", [])),
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"camera_distance": str(config.get("camera_distance", 40.0)),
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"camera_elevation": str(config.get("camera_elevation", 0)),
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@@ -320,137 +334,8 @@ def run_case(config_path, runtime_base, input_dir="input", output_dir="output",
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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_arr = 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_arr, 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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gravity_field_enabled = int(data.get("gravity_field", 1))
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gravity_interaction_enabled = int(data.get("gravity_interaction", 0))
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gravity_strength = float(data.get("gravity_strength", 1.0))
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elastic_force_enabled = int(data.get("elastic_force", 1))
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damping_force_enabled = int(data.get("damping_force", 0))
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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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# 均匀重力场势能 Ug = -m G·r
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ug = np.zeros_like(ek)
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if gravity_field_enabled:
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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 elastic_force_enabled and 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_each = 0.5 * bond_stiffness[b_idx] * stretch**2
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us[:, i] += us_each # 将整根键的势能记给 i
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# 万有引力势能 Ug_grav = -G_grav * m_i * m_j / r
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ug_grav = np.zeros_like(ek)
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if gravity_interaction_enabled:
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n_atoms_en = len(masses)
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for i in range(n_atoms_en):
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for j in range(i + 1, n_atoms_en):
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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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dist = np.maximum(dist, 1e-12)
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pair_pe = -gravity_strength * masses[i] * masses[j] / dist
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ug_grav[:, i] += 0.5 * pair_pe
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ug_grav[:, j] += 0.5 * pair_pe
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# 各原子总能量
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e_total = ek + ug + us + ug_grav # (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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ug_grav_sys = np.sum(ug_grav, axis=1)
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e_sys = ek_sys + ug_sys + us_sys + ug_grav_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_arr, 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 ──
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ax_sys = axes[2, 1]
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ax_sys.plot(time_arr, ek_sys, 'b-', linewidth=1.5, label="系统动能")
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ax_sys.plot(time_arr, ug_sys, 'g-', linewidth=1.5, label="均匀重力势能")
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if elastic_force_enabled and bond_pairs is not None and len(bond_pairs) > 0:
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ax_sys.plot(time_arr, us_sys, color='orange', linewidth=1.5, label="系统弹性势能")
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if gravity_interaction_enabled:
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ax_sys.plot(time_arr, ug_grav_sys, color='purple', linewidth=1.5, label="万有引力势能")
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ax_sys.plot(time_arr, e_sys, 'r--', linewidth=1.5, label="系统总能量")
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ax_sys.set_title("系统总能量")
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ax_sys.set_xlabel("时间 (s)")
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ax_sys.set_ylabel("能量")
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ax_sys.grid(True, alpha=0.3)
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ax_sys.legend(loc="upper right")
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# 隐藏第 3 行第 3 列空子图
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axes[2, 2].set_visible(False)
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plt.tight_layout(rect=[0, 0.03, 1, 0.95])
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plot_path = os.path.join(output_dir_abs, "trajectory_plots.png")
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plt.savefig(plot_path, dpi=300, bbox_inches="tight")
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print(f"[run] 轨迹图表已保存至: {plot_path}")
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plt.show()
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except ImportError:
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print("[run] 警告: 未安装 matplotlib，跳过绘图")
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print("[run] 注意: 旧版 step_plot 绘图路径依赖完整轨迹局部变量，当前已暂时跳过。")
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print("[run] 如需波形/能量动画，请使用 step_plot_wave: 1。")
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print(f"[run] 完成！输出目录: {output_dir_abs}")
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