Perl 内部结构详解 -- PerlGuts Illustrated (6 CV)

本文深入探讨了Perl代码的内部结构,通过使用Devel::Peek和Data::Dumper等工具,展示了如何分析函数、参数、局部变量及运行时状态。文章详细解释了SV、RV、PADLIST等关键概念,并通过示例展示了这些概念在实际代码中的应用。

CV

code value,函数的结构,如下图:


下边示例可以看到几个主要参数:

函数所在的Stash & GV。

函数的参数表和临时变量表PADLIST。

D:\Tmp>perl -MDevel::Peek -e "sub a{my ($a,$b,$t); } Dump \&a"
SV = RV(0x3a90f0) at 0x3a90e4
  REFCNT = 1
  FLAGS = (TEMP,ROK)
  RV = 0x285a864
  SV = PVCV(0x285923c) at 0x285a864
    REFCNT = 2
    FLAGS = ()
    COMP_STASH = 0x3a8fd4	"main"
    START = 0x2885fa8 ===> 0
    ROOT = 0x2885f64
    GVGV::GV = 0x285abd4	"main" :: "a"
    FILE = "-e"
    DEPTH = 0
    FLAGS = 0x0
    OUTSIDE_SEQ = 96
    PADLIST = 0x285a874
    PADNAME = 0x285a8a4(0x2865424) PAD = 0x285a974(0x288292c)
       1. 0x285a8c4<1> (96,97) "$a"
       2. 0x285a894<1> (96,97) "$b"
       3. 0x285a904<1> (96,97) "$t"
    OUTSIDE = 0x3a9274 (MAIN)


PAD

PAD是一个列表,为每个函数存储局部变量。第0个slot 存储参数名字,运行时产生新的AV存储实际参数,DEPTH也加深,递归函数观察效果明显。

use Devel::Peek;
use Data::Dumper;

sub test{
	my ($a,$b) = @_;
	Dump \&test;
	test(++$a,--$b) if $b>0;
}

Dump \&test;
test(1,2);


输出:
SV = RV(0x298f50) at 0x298f44
  REFCNT = 1
  FLAGS = (TEMP,ROK)
  RV = 0x182a834
  SV = PVCV(0x1829024) at 0x182a834
    REFCNT = 2
    FLAGS = ()
    COMP_STASH = 0x298e34	"main"
    START = 0x18ba94c ===> 0
    ROOT = 0x18ba4cc
    GVGV::GV = 0x184b34c	"main" :: "test"
    FILE = "tmp.pl"
    DEPTH = 0
    FLAGS = 0x0
    OUTSIDE_SEQ = 535
    PADLIST = 0x182a864
    PADNAME = 0x182a934(0x18c7c6c) PAD = 0x182a8c4(0x18c7be4)
       1. 0x182a854<1> (535,536) "$a"
       2. 0x182a884<1> (535,536) "$b"
    OUTSIDE = 0x299094 (MAIN)
SV = RV(0x298f50) at 0x298f44
  REFCNT = 1
  FLAGS = (TEMP,ROK)
  RV = 0x182a834
  SV = PVCV(0x1829024) at 0x182a834
    REFCNT = 4
    FLAGS = ()
    COMP_STASH = 0x298e34	"main"
    START = 0x18ba94c ===> 0
    ROOT = 0x18ba4cc
    GVGV::GV = 0x184b34c	"main" :: "test"
    FILE = "tmp.pl"
    DEPTH = 1
    FLAGS = 0x0
    OUTSIDE_SEQ = 535
    PADLIST = 0x182a864
    PADNAME = 0x182a934(0x18c7c6c) PAD = 0x182a8c4(0x18c7be4)
       1. 0x182a854<1> (535,536) "$a"
       2. 0x182a884<1> (535,536) "$b"
    OUTSIDE = 0x299094 (MAIN)
SV = RV(0x1899240) at 0x1899234
  REFCNT = 1
  FLAGS = (TEMP,ROK)
  RV = 0x182a834
  SV = PVCV(0x1829024) at 0x182a834
    REFCNT = 4
    FLAGS = ()
    COMP_STASH = 0x298e34	"main"
    START = 0x18ba94c ===> 0
    ROOT = 0x18ba4cc
    GVGV::GV = 0x184b34c	"main" :: "test"
    FILE = "tmp.pl"
    DEPTH = 2
    FLAGS = 0x0
    OUTSIDE_SEQ = 535
    PADLIST = 0x182a864
    PADNAME = 0x182a934(0x18c7c6c) PAD = 0x182a8c4(0x18c7be4)
       1. 0x182a854<1> (535,536) "$a"
       2. 0x182a884<1> (535,536) "$b"
    OUTSIDE = 0x299094 (MAIN)
SV = RV(0x1863a28) at 0x1863a1c
  REFCNT = 1
  FLAGS = (TEMP,ROK)
  RV = 0x182a834
  SV = PVCV(0x1829024) at 0x182a834
    REFCNT = 4
    FLAGS = ()
    COMP_STASH = 0x298e34	"main"
    START = 0x18ba94c ===> 0
    ROOT = 0x18ba4cc
    GVGV::GV = 0x184b34c	"main" :: "test"
    FILE = "tmp.pl"
    DEPTH = 3
    FLAGS = 0x0
    OUTSIDE_SEQ = 535
    PADLIST = 0x182a864
    PADNAME = 0x182a934(0x18c7c6c) PAD = 0x182a8c4(0x18c7be4)
       1. 0x182a854<1> (535,536) "$a"
       2. 0x182a884<1> (535,536) "$b"
    OUTSIDE = 0x299094 (MAIN)

词法变量(my & our)会设置SVs_PADMY/SVs_PADOUR标记,目标设置SVs_PADTMP标记。


内容概要:本文提出了一种基于融合鱼鹰算法和柯西变异的改进麻雀优化算法(OCSSA),用于优化变分模态分解(VMD)的参数,进而结合卷积神经网络(CNN)与双向长短期记忆网络(BiLSTM)构建OCSSA-VMD-CNN-BILSTM模型,实现对轴承故障的高【轴承故障诊断】基于融合鱼鹰和柯西变异的麻雀优化算法OCSSA-VMD-CNN-BILSTM轴承诊断研究【西储大学数据】(Matlab代码实现)精度诊断。研究采用西储大学公开的轴承故障数据集进行实验验证,通过优化VMD的模态数和惩罚因子,有效提升了信号分解的准确性与稳定性,随后利用CNN提取故障特征,BiLSTM捕捉时间序列的深层依赖关系,最终实现故障类型的智能识别。该方法在提升故障诊断精度与鲁棒性方面表现出优越性能。; 适合人群:具备一定信号处理、机器学习基础,从事机械故障诊断、智能运维、工业大数据分析等相关领域的研究生、科研人员及工程技术人员。; 使用场景及目标:①解决传统VMD参数依赖人工经验选取的问题,实现参数自适应优化;②提升复杂工况下滚动轴承早期故障的识别准确率;③为智能制造与预测性维护提供可靠的技术支持。; 阅读建议:建议读者结合Matlab代码实现过程,深入理解OCSSA优化机制、VMD信号分解流程以及CNN-BiLSTM网络架构的设计逻辑,重点关注参数优化与故障分类的联动关系,并可通过更换数据集进一步验证模型泛化能力。
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