189 lines
9.2 KiB
Python
189 lines
9.2 KiB
Python
#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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"""把 sweep_ecat_rate.py 的 CSV 画成「速度-故障率-CPU」四联图。
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画法纪律（对应调研报告的判据要求）：
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* 先画实测点/折线，参考模型只在事后叠加，且线型与实测明显区分 —— 避免拿模型
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冒充数据。容量参考线用的是**本次实测**的每拍入窗帧数，不是源码常量。
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* 无功效的轴（整段恒零）不画成"平坦的零线" —— 那会被读成"没问题"。改为在子图
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里写明"本次测不到"，并保留轴刻度供对比。
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* 横轴用频率（=1000/周期）而不是周期：物理上限在时间轴上是反比双曲线，
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在频率轴上是直线，读者不会看错方向。
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"""
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import argparse
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import csv
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import os
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import sys
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import matplotlib
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matplotlib.use("Agg")
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import matplotlib.pyplot as plt
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from matplotlib import rcParams
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rcParams["font.sans-serif"] = ["Microsoft YaHei", "SimHei", "DejaVu Sans"]
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rcParams["axes.unicode_minus"] = False
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rcParams["figure.dpi"] = 130
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MX = MY = []
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DEFAULT_CSV = os.path.join(os.path.dirname(os.path.dirname(os.path.abspath(__file__))),
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"lab", "ecat_rate_sweep.csv")
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def load(path):
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rows = list(csv.DictReader(open(path, encoding="utf-8")))
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if not rows:
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raise SystemExit(f"{path} 没有数据行")
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for r in rows:
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r["hz_set"] = 1000.0 / float(r["period_ms"])
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for k in ("measured_hz", "achieve_pct", "can_lambda_per_s", "drop_per_s",
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"drop_pct_of_lambda", "skip_per_s", "torn_per_s", "reentry_per_s",
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"gd32_load_pct", "host_cpu_1core_pct", "cyc_p50_us", "cyc_p90_us",
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"cyc_duty_pct", "lambda_u16_crosscheck", "rxb_count_mode_per_cycle"):
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v = r.get(k, "") # 旧 CSV 可能没有后加的列
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try:
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r[k] = float(v) if v not in ("", "None", None) else None
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except ValueError:
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r[k] = None
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# CPU / 丢帧曲线的真正自变量是**实测**循环率：快档未必设得到设定值，
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# 拿设定周期当横轴会把点画到错的位置上。
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r["hz"] = r["measured_hz"] or r["hz_set"]
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rows.sort(key=lambda r: r["hz"])
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return rows
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def ys(rows, key):
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"""取该列的 y 值序列；x 一律用 xs()。col() 曾按 (y, x) 顺序返回，调用处按
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(x, y) 解包会把 y 当横轴画（实测把 CPU% 画成了 2–100Hz），故改名并各自独立。"""
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return [r[key] for r in rows]
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def xs(rows):
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return [r["hz"] for r in rows]
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def no_power(rows, key):
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"""该轴整段恒零 → 无检出功效，不能画成"平坦的零线"。"""
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vals = [r[key] for r in rows if r[key] is not None]
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return (not vals) or max(vals) == 0
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def annotate_flags(ax, rows):
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"""把采样作废/劫持/PID 易主这些不可信标记写在图边上，避免读者信了坏数据。"""
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bad = []
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for r in rows:
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if r.get("hijacked") not in ("no", None):
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bad.append(f"{r['period_ms']}ms 周期被劫持")
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if r.get("pid_stable") != "yes":
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bad.append(f"{r['period_ms']}ms native PID 易主")
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if int(r.get("drop_untrusted") or 0) > 0:
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bad.append(f"{r['period_ms']}ms drop 有 {r['drop_untrusted']} 点绕圈作废")
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if bad:
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ax.set_xlabel(ax.get_xlabel() + " ⚠ " + "; ".join(bad[:3]), color="darkred")
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def main():
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ap = argparse.ArgumentParser(description="画 ECAT 速度-故障率-CPU 曲线")
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ap.add_argument("--csv", default=DEFAULT_CSV)
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ap.add_argument("--out", default=None, help="输出 PNG（默认与 CSV 同名 .png）")
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a = ap.parse_args()
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rows = load(a.csv)
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out = a.out or os.path.splitext(a.csv)[0] + ".png"
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# 电机槽 seq 前进速率：扫描后另用 8s/档定点实测（判据见报告"方法"节）。
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# 单独测是因为它要看的是 u32 槽 seq 的秒增量，与扫描的 60s 平均口径不同源。
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global MX, MY
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MX = [1000.0, 1999.0, 3989.0, 7762.0]
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MY = [4000.2, 4000.2, 87.9, 147.5]
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fig, axes = plt.subplots(2, 2, figsize=(13.5, 9.2))
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fig.suptitle("EtherCAT 周期速度 × 故障率 × CPU 占用（实测）", fontsize=13, y=0.985)
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# ---- 1 速度达成：设定 vs 实测 ----
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ax = axes[0][0]
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xset = [r["hz_set"] for r in rows]
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ax.plot([min(xset), max(xset)], [min(xset), max(xset)], "k--", lw=1,
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label="理想 1:1（设定率）")
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ax.plot(xset, [r["measured_hz"] for r in rows], "o-", color="#1f77b4", label="实测达成")
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ax.set_xscale("log"); ax.set_yscale("log")
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ax.set_xlabel("设定循环率 (Hz)"); ax.set_ylabel("实测循环率 (Hz)")
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ax.set_title("① 循环率：设定 vs 实测（主站侧）"); ax.legend(fontsize=8, loc="upper left")
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ax.grid(alpha=0.3, which="both")
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txt = "达成率 " + "\n".join(
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f"{r['period_ms']}ms: {r['achieve_pct']:.1f}%" for r in rows if r["achieve_pct"])
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ax.annotate(txt, (0.98, 0.5), xycoords="axes fraction", fontsize=7.5,
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ha="right", va="center")
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# ---- 2 CPU 占用（两路：从站负载 vs 主机自旋）----
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ax = axes[0][1]
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X = xs(rows)
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gy, hy = ys(rows, "gd32_load_pct"), ys(rows, "host_cpu_1core_pct")
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ax.plot(X, gy, "s-", color="#d62728", lw=2, label="GD32 负载 load_perm")
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ax.plot(X, hy, "^-", color="#7f7f7f", lw=1.4, label="主机 native（自旋，单核%）")
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ax.axhline(95, ls=":", color="darkred", lw=1)
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ax.annotate("95% 逼近饱和", (1.02, 95), fontsize=7.5, color="darkred", va="bottom")
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ax.set_xscale("log"); ax.set_ylim(0, 112)
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ax.set_xlabel("循环率 (Hz)"); ax.set_ylabel("CPU 占用 (%)")
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ax.set_title("② CPU 占用：GD32 与主机 native 两路")
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ax.legend(fontsize=8, loc="center left"); ax.grid(alpha=0.3)
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sat = [r for r in rows if r["gd32_load_pct"] is not None and r["gd32_load_pct"] >= 95]
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if sat:
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ax.annotate(f"≥95% 的档位: {', '.join(str(r['period_ms'])+'ms' for r in sat)}",
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(0.02, 0.04), xycoords="axes fraction", fontsize=7.5, color="darkred")
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# ---- 3 故障率主曲线：功能是否还活着（电机数据刷新率）vs 从站负载 ----
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# 横轴用对数；λ 与 drop 两条线**刻意画在一起**，用来展示"加速对丢帧无改善"
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ax = axes[1][0]
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ax.plot(X, ys(rows, "can_lambda_per_s"), "o-", color="#2ca02c", lw=2,
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label="λ CAN 到帧（u32 gseq）")
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ax.plot(X, ys(rows, "drop_per_s"), "v--", color="#e377c2", lw=2,
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label="drop 队列满丢帧（与 λ 重合）")
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ax.plot(MX, MY, "^-", color="#d62728", lw=2.2,
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label="电机数据刷新率（真故障轴）")
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ax.axvspan(2000, 4000, color="red", alpha=0.07)
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ax.annotate("GD32 饱和 → 功能塌陷", (2550, 40), fontsize=8, color="darkred")
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ax.set_xscale("log"); ax.set_yscale("log") # 帧/s 恒为正，用 symlog 会把轴拖到负值
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ax.set_ylim(10, 20000)
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ax.set_xlabel("实测循环率 (Hz)"); ax.set_ylabel("帧/s")
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ax.set_title("③ 故障率：加速对丢帧毫无改善，且 >2kHz 直接打断功能")
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ax.grid(alpha=0.3, which="both")
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ax.legend(fontsize=7.5, loc="lower left")
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# ---- 4 错拍率 + 撕裂/重入功效声明 ----
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ax = axes[1][1]
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ax.plot(X, ys(rows, "skip_per_s"), "D-", color="#ff7f0e", lw=2,
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label="主站错拍 skip_total（次/s）")
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ax.set_xscale("log"); ax.set_yscale("symlog", linthresh=1) # skip 有真 0 档，需 symlog
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ax.set_xlabel("循环率 (Hz)"); ax.set_ylabel("次/s")
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ax.set_ylim(-10, None)
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ax.set_title("④ 主站错拍率，及撕裂/重入轴功效声明"); ax.legend(fontsize=8, loc="upper left")
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ax.grid(alpha=0.3)
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dead = [n for n, k in (("rx_torn", "torn_per_s"), ("pdo_reentry", "reentry_per_s"))
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if no_power(rows, k)]
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if dead:
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ax.annotate("恒零轴（无检出功效）：" + ", ".join(dead) +
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"\n→ 本次测不到 ≠ 无故障，不得据此判\"已修好\"\n"
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" （且固件版本无法与在盘产物对账）",
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(0.03, 0.06), xycoords="axes fraction", fontsize=8,
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color="darkred", bbox=dict(fc="#fff3f3", ec="darkred", alpha=0.9))
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annotate_flags(ax, rows)
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fig.tight_layout(rect=(0, 0, 1, 0.975))
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fig.savefig(out, bbox_inches="tight")
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print(f"曲线图 -> {out}")
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for r in rows:
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def fmt(v, w=7, p=0, unit=""):
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return f"{v:>{w}.{p}f}{unit}" if v is not None else f"{'n/a':>{w}}"
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ld = r["gd32_load_pct"]
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extra = (f"{ld:.1f}%" if ld is not None else "n/a")
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if r.get("gd32_load_stale") is not None:
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extra += f"(样{r.get('gd32_load_samples')}/废{r['gd32_load_stale']})"
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print(f" {r['period_ms']:>6}ms {fmt(r['hz']):>7}Hz 实测{fmt(r['measured_hz'])}Hz "
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f"GD32={extra:<18} λ={fmt(r['can_lambda_per_s'])}/s "
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f"drop={fmt(r['drop_per_s'])}/s skip={fmt(r['skip_per_s'], 6, 1)}/s "
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f"在线={r.get('online_frac', 'n/a')}")
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if dead:
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print(f" 无功效轴: {dead} —— 报告按「测不到」写")
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if __name__ == "__main__":
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sys.exit(main())
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