64 lines
1.8 KiB
Python
64 lines
1.8 KiB
Python
import os
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import re
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import sys
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import pandas as pd
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import matplotlib.pyplot as plt
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def main(csv_path: str):
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# 更健壮的读取
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df = pd.read_csv(csv_path, sep=None, engine="python", comment="#")
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if 't' not in df.columns:
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raise RuntimeError("CSV missing 't' column")
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# ——严格区分列名——
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# 允许列名形如：q0, q1, ... | qd0, qd1, ... | qdd0, qdd1, ...
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def grep(pattern):
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r = re.compile(pattern)
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return [c for c in df.columns if r.fullmatch(c)]
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q_cols = grep(r"q\d+")
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qd_cols = grep(r"qd\d+")
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qdd_cols = grep(r"qdd\d+")
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# 如果你的列名不是纯数字后缀（比如 q_joint1），把上面的正则改成更宽松的：
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# q_cols = [c for c in df.columns if c.startswith("q") and not c.startswith(("qd","qdd"))]
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# qd_cols = [c for c in df.columns if c.startswith("qd") and not c.startswith("qdd")]
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# qdd_cols = [c for c in df.columns if c.startswith("qdd")]
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t = df['t'].values
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# 位置
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plt.figure()
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for c in q_cols:
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plt.plot(t, df[c].values, label=c)
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plt.xlabel('time [s]')
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plt.ylabel('position [rad]')
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plt.title('Joint Positions')
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plt.legend()
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plt.grid(True)
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# 速度（只画 qd*）
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plt.figure()
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for c in qd_cols:
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plt.plot(t, df[c].values, label=c)
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plt.xlabel('time [s]')
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plt.ylabel('velocity [rad/s]')
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plt.title('Joint Velocities')
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plt.legend()
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plt.grid(True)
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# 加速度（只画 qdd*）
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plt.figure()
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for c in qdd_cols:
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plt.plot(t, df[c].values, label=c)
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plt.xlabel('time [s]')
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plt.ylabel('acceleration [rad/s^2]')
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plt.title('Joint Accelerations')
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plt.legend()
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plt.grid(True)
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plt.show()
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if __name__ == '__main__':
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main("/home/lgv/cmvr/0-workspace/cmvr-es/data/planner/traj.csv")
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