技术总结 on 极客Vinkey

Cisco AnyConnect优雅脚本与openconnect进阶教程

Fri, 07 Aug 2026 14:12:58 +0000

https://github.com/ma-wenqian/vpn-playbook

概述

一般情况下，能用 Cisco AnyConnect（现称 Cisco Secure Client）的场景，基本都可以用 OpenConnect 替代。从便捷到进阶，本仓库提供了对应的脚本，辅助自动登录学校（或类似配置的）VPN。

目前 Cisco 基本都启用了双重认证：先输入 VPN 地址，然后输入账号、密码，接着输入二次验证码——也就是常见存储在 Google Authenticator、iCloud 钥匙串、Microsoft Authenticator 中的那个 6 位验证码。这个验证码本质上是基于一个固定的 Base32 密钥和当前时间戳计算得到的（TOTP），并没有什么"黑盒"逻辑。因此，只要在绑定 2FA 时提取到这个固定密钥，就可以自己算出验证码，从而实现全程自动登录：

Unix 平台：使用 oathtool 工具，OTP=$(oathtool --totp -b "$SECRET")
Windows 平台：使用 totp-go 命令行工具，totp-go "$SECRET"

⚠️ 请像保管密码一样保管这个密钥！ 任何拿到这个密钥的人都可以无限期地为你的账号生成有效的二次验证码——它不像单次验证码那样会失效。切勿把填入了真实用户名/密码/密钥的配置文件提交到（哪怕是私有的）代码仓库。本仓库中的 config.bat / config.sh 都只是占位模板，请在本地填入真实信息后不要把这部分改动提交到 git。

仓库结构

.
├── Cisco/
│   ├── unix/
│   │   ├── cisco-vpn.sh          # 基于 oathtool + `vpn -s`（脚本化 stdin）实现 connect/disconnect
│   │   ├── config.sh             # 你的 VPN 地址/账号/密码/TOTP 密钥（模板）
│   │   └── install.sh            # 一键安装脚本（curl | bash）
│   └── win/
│       ├── cisco-vpn.bat        # 双击运行的入口脚本，用 totp-go 生成验证码并直接写入 vpncli.exe 的脚本化输入
│       ├── config.bat           # 你的 VPN 地址/账号/密码/TOTP 密钥（模板，变量名与 unix 端一致）
│       ├── icon/                # 桌面快捷方式用到的 connect.ico / disconnect.ico
│       └── install.ps1          # 一键安装脚本，顺带安装 totp-go，还能自动创建桌面快捷方式（irm | iex）
└── Openconnect/
    ├── openconnect-setup.sh       # OpenConnect + microsocks 的 Docker 部署（更轻量）
    └── openconnect-gost-setup.sh  # OpenConnect + gost 的 Docker 部署（功能更全）

移动端

iOS：无法做到完全自动化，顶多是借助自动填充功能填入验证码。
Android：本仓库暂未研究。

Cisco（桌面端，仅命令行）

不要启动 GUI 界面，全部使用命令行实现自动化操作。

Windows快速切换简体繁体拼音输入-Ctrl+Shift+F

Mon, 27 Apr 2026 17:37:23 +0000

新发现：Ctrl+Shift+F

今天不知道电脑怎么突然就变成繁体中文输入法了，我想着也没有下载啥软件、修改系统设置，在网上搜了一下，发现应该是误触了快捷键，那么相当于也知道了一个快速切换的方法：Ctrl+Shift+F

对应系统设置：时间和语言→语言和地区→Microsoft拼音→按键最下方，如果按了没反应，大概率是和其他软件的快捷键冲突了，回到桌面内就可以了。

以后就可以快速通过Ctrl+Shift+F切换简体和繁体中文了~

关于微软输入法变成繁体问题

VSCode+Latex Workshop环境配置

Thu, 04 Dec 2025 17:52:14 +0000

本文总结了在windows 和wsl/Ubuntu平台部署latex环境，在vscode中写文件和编译的过程。

在线版本的overleaf可以免去配置环境，方便进行多人协作。但是在前期写作阶段，我比较倾向于本地环境，方便修改图片，不用反复上传。可以在初稿完成后，上传至overleaf协作修改。

一共两个步骤：

配置对应系统的tex
vscode安装Latex Workshop插件

即可实现一键编译。编译速度上应该是mac>linux>wsl>windows，所以在windows中可以额外配置wsl的latex环境。

安装Tex

这个环节可能要很长时间，可以选择从国内镜像站下载。安装的过程中可以同步进行下一步操作。

Windows

安装texlive，下载install-tl-windows.exe，一键安装。安装过程需要一段时间，可以放在后台等。同样的网络下，wsl中安装速度比windows快了很多。

Ubuntu

根据texlive网页说明，在terminal中运行，

cd /tmp # working directory of your choice
Download: wget https://mirror.ctan.org/systems/texlive/tlnet/install-tl-unx.tar.gz
           or: curl -L -o install-tl-unx.tar.gz https://mirror.ctan.org/systems/texlive/tlnet/install-tl-unx.tar.gz

zcat < install-tl-unx.tar.gz | tar xf - # note final - on that command line
cd install-tl-2*
perl ./install-tl --no-interaction # as root or with writable destination
# may take several hours to run

安装完成后需要添加路径/usr/local/texlive/YYYY/bin/PLATFORM 到 PATH，以实际屏幕显示的路径进行设置。

我的科研绘图调色板

Thu, 27 Nov 2025 18:46:45 +0000

本文收集了一些科研图配色，并提供颜色效果预览和hex、rgb数值。

🌈 我的科研绘图调色板

双色

色块预览	线条预览	HEX 值	RGB 值	颜色名称
		`#b22222`	`(178, 34, 34)`
		`#000080`	`(0, 0, 128)`

色块预览	线条预览	HEX 值	RGB 值	颜色名称
		`#f5a889`	`(245, 168, 137)`
		`#acd6ec`	`(172, 214, 236)`

色块预览	线条预览	HEX 值	RGB 值	颜色名称
		`#148f28`	`(20, 143, 40)`
		`#ea71ae`	`(234, 113, 174)`

三色

马卡龙配色

Matlab绘图代码共享-硕士阶段

Sun, 12 Mar 2023 14:46:54 +0000

拉压弯曲线图及柱状图2022/12

更新于2023.03.13

{% folding child:codeblock open:flase color:yellow 点击展开代码详情 %}

%% 基础信息
% 反复修改的代码简直屎山！
clc;clear
close all


% color1=[77,133,189]/255;
% color2=[247,144,61]/255;
% color3=[89,169,90]/255;

% 马卡龙配色
color1=[147 213 220]/255;
color2=[242 202 201]/255;
color3=[198 223 200]/255;

% color1=[255 230 215]/255;
% color2=[225 240 219]/255;
% color3=[222 234 248]/255;

% color1=[240   181   125]/255;
% color2=[211   225   174]/255;
% color3=[113   171   182]/255;
% 
% color1=[   76   139   192]/255;
% color2=[  232    49    51]/255;
% color3=[   94   183    91]/255;

% 大论文使用的配色
% color1=[  110 158 206]/255;
% color2=[  118 186 128]/255;
% color3=[  230 146 143]/255;

FontSize=13;
color3s={color1;color2;color3};
colors={color1;color1;color1;color2;color2;color2;color3;color3;color3};
colors9=[  
   199    92   100
  240   181   125
  211   225   174
  113   171   182
   75    90   161
   76   139   192
  232    49    51
  163    96   173
   94   183    91]/255;


ki=[ 1	0	0
    0.75	0.25	0
    0.5	0.5	0
    0.25	0.75	0
    0	1	0
    0	0.75	0.25
    0	0.5	0.5
    0	0.25	0.75
    0	0	1];
bar_colors=ki*[color1;color3;color2];

legends=["v=240mm/s  T=210°C  h=0.16mm"
    "v=250mm/s  T=215°C  h=0.20mm"
    "v=260mm/s  T=220°C  h=0.24mm"
    "v=240mm/s  T=215°C  h=0.24mm"
    "v=250mm/s  T=220°C  h=0.16mm"
    "v=260mm/s  T=210°C  h=0.20mm"
    "v=240mm/s  T=220°C  h=0.20mm"
    "v=250mm/s  T=210°C  h=0.24mm"
    "v=260mm/s  T=215°C  h=0.16mm"]';
legends9=[legends;repmat("",5,9)];
%%

hexc=[
'32aeec'
'E3863c'
'E9262e'];

r=hex2dec(hexc(:,[1,2]));
g=hex2dec(hexc(:,[3 4]));
b=hex2dec(hexc(:,[5 6]));
rgb=[r,g,b];
%% 拉伸


Tensile_x=cell(9,6);       % read strain to Tensile_x
Tensile_y=cell(9,6);       % read stress to Tensile_y

% 读取原始数据并储存

% 设置导入选项并导入数据
opts = delimitedTextImportOptions("NumVariables", 8);
% 指定范围和分隔符
opts.DataLines = [8, Inf];
opts.Delimiter = "\t";
% 指定列名称和类型
opts.VariableNames = ["Load", "LoadY", "Position", "Displacement", "Extension", "ExtensionY", "StepIndex", "Time"];
opts.VariableTypes = ["double", "double", "double", "double", "double", "double", "double", "double"];
% 指定文件级属性
opts.ExtraColumnsRule = "ignore";
opts.EmptyLineRule = "read";
T_L0=50;              % 标距L0
T_S0=4*13;     % 横截面积S0
for Gi=1:9
    for ti=1:6
        filesname=sprintf("/Users/mawenqian/Documents/硕士/VSL/科研/小论文1/基本试件打印参数正交试验/G%d/N%d.txt",Gi,ti);
        readdata = readtable(filesname, opts);
        % 转换为输出类型
        readdata = table2array(readdata);
        Tensile_x{Gi,ti}=readdata(:,5)/T_L0*100;   % 应变 6sh/L^2
        Tensile_y{Gi,ti}=readdata(:,1)/T_S0;        % 应力 3Fl/2bh^2
        clear readdata filesname
    end
end
clear opts
save Tensile_raw_data Tensile_x Tensile_y
%%

% 通过下方原始图像人工判断获得，亦可绘制后展示。
Tensile_start_line=[
    133	137	137	144	145	139
    151	151	147	157	160	155
    176	178	177	179	191	174
168	205	143	194	162	192
157	162	163	154	222	170
196	242	175	206	246	174
    143	141	145	130	138	146
    133	129	135	126	130	127
145	150	163	145	138	142];
Tensile_end_line=[
    2022	1764	3568	2073	2596	3338
    2222	1912	2363	3740	1927	1832
    2613	1821	2390	2353	2041	2040
4000	3000	2449	2667	2557	1937
2000	1943	2000	1776	2000	2000
1719	1719	1719	1719	1719	1719
  2312	1975	2537	2161	1730	1979
1407	1238	1345	1260	1593	1684
1656	2419	2000	2000	2000	2000];
Tensile_maxy_line=[
740	709	744	730	755	716
1066	1103	1064	1167	1058	1157
834	709	735	779	779	723
1377	1441	1622	1512	1698	1399
1043	1074	1069	1140	1072	1036
1214	1142	1164	1214	1142	1164
1178	1099	1213	1252	1191	1182
1097	1091	1081	1035	1100	1063
853	903	920	896	891	922];

% ttt=1;
% for Gi=[ 7 8]
% for ti=1:6
%     subplot(4,6,ttt)
% 
% 
% x=Tensile_x{Gi,ti};
% y=Tensile_y{Gi,ti};
% [~,Tensile_maxy_line(Gi,ti)]=max(y);
% plot(y,MarkerIndices=Tensile_end_line(Gi,ti),MarkerSize=6,Marker="*",MarkerFaceColor='r')
% title(sprintf("%d-%d",Gi,ti))
%     ttt=ttt+1;
% end
% 
% end

%%
% % 绘制原始数据图像总图3x3
% figure()
% set(gcf,'unit','centimeters','Position',[5 5 30 30]);
% for Gi=1:9
%     subplot(3,3,Gi)
%     hold on
%     for ti=1:6
%         x=Tensile_x{Gi,ti}(Tensile_start_line(Gi,ti):Tensile_end_line(Gi,ti));x=x-x(1);
%         y=Tensile_y{Gi,ti}(Tensile_start_line(Gi,ti):Tensile_end_line(Gi,ti));y=y-y(1);
% Tensile_x{Gi,ti}=x;
% Tensile_y{Gi,ti}=y;
% plot(Tensile_y{Gi,ti},LineWidth=1.5)
% %         plot(Tensile_x{Gi,ti},Tensile_y{Gi,ti},LineWidth=1.5,Marker='o',MarkerEdgeColor='red',MarkerIndices=[Tensile_start_line(Gi,ti)])
%         %         plot(Tensile_y{Gi,ti},LineWidth=1.5)
%     end
%     xlabel("Strain (%)")
%     ylabel("Stress (MPa)")
% %     xlim([0 0.1])
%     % ylim([0,70])
%     % legend(Location="northwest",Box="off");
%     box('on');
%     title(['Tensile ',num2str(Gi)])
%     set(gca,'FontName','Arial','FontSize',FontSize)
% end
%%
%
% % 分组绘制原始图像9张单独图（应力）
% for Gi=[1 2 3 7 8]
%     figure()
%     set(gcf,'unit','centimeters','Position',[5 5 40 28]);
%     for ti=1:6
%         subplot(2,3,ti)
% %         [~,maxy]=max(Tensile_y{Gi,ti}(1:Tensile_end_line(Gi,ti)));
% %         Tensil_maxy_line(Gi,ti)=maxy;
%         plot(Tensile_y{Gi,ti},LineWidth=1.5,Marker='o',MarkerEdgeColor='red',MarkerIndices=[Tensile_start_line(Gi,ti),Tensil_maxy_line(Gi,ti),Tensile_end_line(Gi,ti)])
%         xlabel("N")
%         ylabel("Stress (MPa)")
%         % xlim([0 10])
%     % ylim([0,70])
% %     legend(Location="northwest",Box="off");
%     box('on');
%
%     title(['Tensile ',num2str(Gi), '-',num2str(ti)])
%     set(gca,'FontName','Arial','FontSize',FontSize)
%     end
% end

% 绘制受拉总图
%%
Tensile_maxy=zeros(9,6);

clear fh1
fh1=figure();
set(gcf,'unit','centimeters','Position',[15 15 15 15]);
axes('parent',fh1,'unit','centimeters','position',[1.5 1.5 12.5 12.5]);
hold on
LineStyles=repmat(["-",":","--"],1,3);
for Gi=1:9
    for ti=1:6
        x=Tensile_x{Gi,ti}(Tensile_start_line(Gi,ti):Tensile_end_line(Gi,ti));x=x-x(1);
        y=Tensile_y{Gi,ti}(Tensile_start_line(Gi,ti):Tensile_end_line(Gi,ti));y=y-y(1);
        Tensile_maxy(Gi,ti)=max(y);
        plot(x,y,LineWidth=1.5,Color=colors{Gi},LineStyle=LineStyles(Gi))
        clear x y
    end
    
    xlabel("Strain (%)")
    ylabel("Stress (MPa)")
    xlim([0 8])
    ylim([0,60])
 legend(legends9,Location="northeast",Box="off");
    box('on');
 
    set(gca,'FontName','Arial','FontSize',FontSize)  
end



%% 压缩1屈服强度
compressive1_x=cell(9,6);       % read strain to compressive1_x
compressive1_y=cell(9,6);       % read stress to compressive1_y
Com1_L0=25.4;                   % 标距L0
Com1_S0=12.7*12.7*pi*0.25;      % 横截面积S0


% 读取原始数据并储存
% 设置导入选项并导入数据
opts = spreadsheetImportOptions("NumVariables", 2);
% 指定工作表和范围
opts.Sheet = "Sheet1";
opts.DataRange = "A2:B2000";
% 指定列名称和类型
opts.VariableNames = ["LoadValue", "PositionValue", "PlayTime", "ExtendValue"];
opts.VariableTypes = ["double", "double", "double", "double"];
for Gi=19:27
    for ti=1:6
        filesname=sprintf("/Users/mawenqian/Documents/硕士/VSL/科研/小论文1/基本试件打印参数正交试验/G%d/N%d.xls",Gi,ti);
        readdata = readtable(filesname, opts);
        % 转换为输出类型
        readdata = table2array(readdata);
        compressive1_x{Gi-18,ti}=readdata(:,2)/Com1_L0*100;  % 应变
        compressive1_y{Gi-18,ti}=readdata(:,1)/Com1_S0;      % 应力
        clear readdata filesname
    end
end
clear opts
% 通过下方原始图像人工判断获得，亦可绘制后展示。
compressive1_start_line=[
    73	78	74	77	12	1
    77	87	79	78	75	77
    82	82	80	82	86	83
    369	70	64	72	72	74
    71	67	66	63	64	66
    70	70	68	67	69	69
    62	6	6	5	4	4
    3	3	3	181	1	7
    65	12	5	4	5	64];
compressive1_end_line=[
    471	413	432	390	303	322
    422	432	413	380	380	378
    471	442	480	390	303	322
    827	529	493	497	503	482
    511	526	453	475	496	496
    513	509	528	486	473	494
    528	516	475	414	463	470
    463	454	519	605	463	457
    619	497	496	365	420	478];
compressive1_maxy_line=[310	307	318	314	234	219
    354	377	344	374	352	345
    321	325	333	324	303	322
    728	412	381	403	404	404
    357	350	340	344	345	347
    349	330	332	341	329	339
    331	295	293	279	286	314
    306	285	300	499	313	293
    436	274	300	289	298	323];
% % 绘制原始数据图像总图3x3
% figure()
% set(gcf,'unit','centimeters','Position',[5 5 30 30]);
% for Gi=19:27
%     subplot(3,3,Gi-18)
%     hold on
%     for ti=1:6
%         [~,maxy]=max(compressive1_y{Gi-18,ti}(1:compressive1_end_line(Gi-18,ti)));
%         plot(compressive1_x{Gi-18,ti},compressive1_y{Gi-18,ti},LineWidth=1.5,Marker='o',MarkerEdgeColor='red',MarkerIndices=[maxy])
%         %         plot(compressive1_y{Gi-18,ti},LineWidth=1.5)
%     end
%     xlabel("Strain (%)")
%     ylabel("Stress (MPa)")
%     % xlim([0 10])
%     % ylim([0,70])
%     %     legend(Location="northwest",Box="off");
%     box('on');
%     title(['compressive1 ',num2str(Gi-18)])
%     set(gca,'FontName','Arial','FontSize',FontSize)
% end
% % 分组绘制原始图像9张单独图（应力）
% for Gi=27:-1:19
%     figure()
%     set(gcf,'unit','centimeters','Position',[5 5 40 28]);
%     for ti=1:6
%         subplot(2,3,ti)
%         [~,maxy]=max(compressive1_y{Gi-18,ti}(1:compressive1_end_line(Gi-18,ti)));
% compressive1_maxy_line(Gi,ti)=maxy;
%         plot(compressive1_y{Gi-18,ti},LineWidth=1.5,Marker='o',MarkerEdgeColor='red',MarkerIndices=[compressive1_start_line(Gi-18,ti),compressive1_maxy_line(Gi,ti),compressive1_end_line(Gi-18,ti)])
%         xlabel("N")
%         ylabel("Stress (MPa)")
%         % xlim([0 10])
%         % ylim([0,70])
%         %     legend(Location="northwest",Box="off");
%         box('on');
%
%         title(['compressive1 ',num2str(Gi-18), '-',num2str(ti)])
%         set(gca,'FontName','Arial','FontSize',FontSize)
%     end
% end



% 绘制受压总图
compressive1_maxy=zeros(9,6);

% figure()
% set(gcf,'unit','centimeters','Position',[5 5 30 30]);
% for Gi=19:27
%     Gi=Gi-18;
%     subplot(3,3,Gi)
% 
%     hold on
%     for ti=1:6
%         compressive1_maxy(Gi,ti)=compressive1_y{Gi,ti}(compressive1_maxy_line(Gi,ti))-compressive1_x{Gi,ti}(compressive1_start_line(Gi,ti));
%         x=compressive1_x{Gi,ti}(compressive1_start_line(Gi,ti):compressive1_end_line(Gi,ti));x=x-x(1);
%         y=compressive1_y{Gi,ti}(compressive1_start_line(Gi,ti):compressive1_end_line(Gi,ti));y=y-y(1);
%         compressive1_maxy(Gi,ti)=max(y);
%         plot(x,y,LineWidth=1.5,Color=colors{Gi})
%     end
%     xlabel("Strain (%)")
%     ylabel("Stress (MPa)")
%     xlim([0 8])
%     ylim([0,60])
% 
%     legend(legends(Gi),Location="north",Box="off");
%     box('on');
%     title(['Compressive ',num2str(Gi)])
%     set(gca,'FontName','Arial','FontSize',FontSize)
% end

clear fh1
fh1=figure();
set(gcf,'unit','centimeters','Position',[15 15 15 15]);
axes('parent',fh1,'unit','centimeters','position',[1.5 1.5 12.5 12.5]);
hold on
LineStyles=repmat(["-",":","--"],1,3);
for Gi=19:27
    Gi=Gi-18;
    hold on
    for ti=1:6
        x=compressive1_x{Gi,ti}(compressive1_start_line(Gi,ti):compressive1_end_line(Gi,ti));x=x-x(1);
        y=compressive1_y{Gi,ti}(compressive1_start_line(Gi,ti):compressive1_end_line(Gi,ti));y=y-y(1);
        compressive1_maxy(Gi,ti)=max(y);
        plot(x,y,LineWidth=1.5,Color=colors{Gi},LineStyle=LineStyles(Gi))
    end
    xlabel("Strain (%)")
    ylabel("Stress (MPa)")
    xlim([0 8])
    ylim([0,60])
 legend(legends9,Location="southeast",Box="off");
    box('on');
%     title('Compressive')
    set(gca,'FontName','Arial','FontSize',FontSize)
end
%% 弯曲


Flexural_x=cell(9,6);       % read strain to Flexural_x
Flexural_y=cell(9,6);       % read stress to Flexural_y

% 读取原始数据并储存

% 设置导入选项并导入数据
opts = delimitedTextImportOptions("NumVariables", 8);
% 指定范围和分隔符
opts.DataLines = [8, Inf];
opts.Delimiter = "\t";
% 指定列名称和类型
opts.VariableNames = ["Load", "LoadY", "Position", "Displacement", "Extension", "ExtensionY", "StepIndex", "Time"];
opts.VariableTypes = ["double", "double", "double", "double", "double", "double", "double", "double"];
% 指定文件级属性
opts.ExtraColumnsRule = "ignore";
opts.EmptyLineRule = "read";
L0=6*3.2/52^2;              % 标距L0
S0=3*52/(2*12.7*3.2^2);     % 横截面积S0
for Gi=10:18
    for ti=1:6
        filesname=sprintf("/Users/mawenqian/Documents/硕士/VSL/科研/小论文1/基本试件打印参数正交试验/G%d/N%d.txt",Gi,ti);
        readdata = readtable(filesname, opts);
        % 转换为输出类型
        readdata = table2array(readdata);
        Flexural_x{Gi-9,ti}=readdata(:,4).*L0*100;   % 应变 6sh/L^2
        Flexural_y{Gi-9,ti}=readdata(:,1).*S0;        % 应力 3Fl/2bh^2
        clear readdata filesname
    end
end
clear opts
% 通过下方原始图像人工判断获得，亦可绘制后展示。
Flexural_start_line=[
    467	518	522	779	368	484
    519	337	270	390	415	252
    517	357	717	515	553	654
    770	553	453	344	498	318
    498	521	569	667	510	417
    360	431	407	364	472	358
    308	493	677	617	648	471
    379	529	641	781	915	439
    693	701	745	696	734	744];
Flexural_maxy_line=[
    4554	4543	4534	4729	4459	4457
    4391	4252	4080	4298	4264	4114
    4496	4306	4691	4533	4453	4458
    4431	4205	4134	3991	4242	4116
    4529	4633	4710	4794	4624	4509
    4078	4153	4095	4148	4172	4140
    4059	4267	4356	4334	4289	4146
    4165	4235	4366	4562	4611	4207
    4725	4725	4725	4725	4725	4725];

% % 绘制原始数据图像总图3x3
% figure()
% set(gcf,'unit','centimeters','Position',[5 5 30 30]);
% for Gi=10:18
%     subplot(3,3,Gi-9)
%     hold on
%     for ti=1:6
%         plot(Flexural_x{Gi-9,ti},Flexural_y{Gi-9,ti},LineWidth=1.5,Marker='o',MarkerEdgeColor='red',MarkerIndices=[Flexural_start_line(Gi-9,ti)])
%         %         plot(Flexural_y{Gi-9,ti},LineWidth=1.5)
%     end
%     xlabel("Strain (%)")
%     ylabel("Stress (MPa)")
%     % xlim([0 10])
%     % ylim([0,70])
%     % legend(Location="northwest",Box="off");
%     box('on');
%     title(['Flexural ',num2str(Gi)])
%     set(gca,'FontName','Arial','FontSize',FontSize)
% end
%
% % 分组绘制原始图像9张单独图（应力）
% for Gi=18:-1:10
%     figure()
%     set(gcf,'unit','centimeters','Position',[5 5 40 28]);
%     for ti=1:6
%         subplot(2,3,ti)
%         [~,maxy]=max(Flexural_y{Gi-9,ti});
%         Flexural_maxy_line(Gi-9,ti)=maxy;
%         plot(Flexural_y{Gi-9,ti},LineWidth=1.5,Marker='o',MarkerEdgeColor='red',MarkerIndices=[Flexural_start_line(Gi-9,ti),Flexural_maxy_line(Gi-9,ti)])
%         xlabel("N")
%         ylabel("Stress (MPa)")
%         % xlim([0 10])
%     % ylim([0,70])
% %     legend(Location="northwest",Box="off");
%     box('on');
%
%     title(['Flexural ',num2str(Gi-9), '-',num2str(ti)])
%     set(gca,'FontName','Arial','FontSize',FontSize)
%     end
% end

% 绘制受弯总图
Flexural_maxy=zeros(9,6);

% figure()
% set(gcf,'unit','centimeters','Position',[5 5 30 30]);
% for Gi=10:18
%     Gi=Gi-9;
%  subplot(3,3,Gi)
% 
%     hold on
%     for ti=1:6
%         Flexural_maxy(Gi,ti)=Flexural_y{Gi,ti}(Flexural_maxy_line(Gi,ti))-Flexural_x{Gi,ti}(Flexural_start_line(Gi,ti));
%         x=Flexural_x{Gi,ti}(Flexural_start_line(Gi,ti):end);x=x-x(1);
%         y=Flexural_y{Gi,ti}(Flexural_start_line(Gi,ti):end);y=y-y(1);
%         Flexural_maxy(Gi,ti)=max(y);
%         plot(x,y,LineWidth=1.5,Color=colors{Gi})
%     end
%     xlabel("Strain (%)")
%     ylabel("Stress (MPa)")
%     xlim([0 8])
%     ylim([0,70])
% 
%     legend(legends(Gi),Location="north",Box="off");
%     box('on');
%     title(['Flexural ',num2str(Gi)])
%     set(gca,'FontName','Arial','FontSize',FontSize)
% end
% 
% 
clear fh1
fh1=figure();
set(gcf,'unit','centimeters','Position',[15 15 15 15]);
axes('parent',fh1,'unit','centimeters','position',[1.5 1.5 12.5 12.5]);
hold on
LineStyles=repmat(["-",":","--"],1,3);
for Gi=10:18
    Gi=Gi-9;

    hold on
    for ti=1:6
        x=Flexural_x{Gi,ti}(Flexural_start_line(Gi,ti):end);x=x-x(1);
        y=Flexural_y{Gi,ti}(Flexural_start_line(Gi,ti):end);y=y-y(1);
        Flexural_maxy(Gi,ti)=max(y);
        plot(x,y,LineWidth=1.5,Color=colors{Gi},LineStyle=LineStyles(Gi))
    end

end

xlabel("Strain (%)")
    ylabel("Stress (MPa)")
    xlim([0 8])
    ylim([0,70])

    legend(legends9,Location="southeast",Box="off");
    box('on');
%     title(['Flexural'])
    set(gca,'FontName','Arial','FontSize',FontSize)

%% 汇总柱状图
% close all
com_bar=figure();
set(gcf,'unit','centimeters','Position',[5 5 28 28]);
axes('parent',com_bar,'unit','centimeters','position',[1.5 1.5 25 25],'fontsize',20);

x=1:9;
all_mean=reshape(mean([Tensile_maxy;compressive1_maxy;Flexural_maxy],2),9,3)';
all_mean_std=reshape(std([Tensile_maxy;compressive1_maxy;Flexural_maxy],0,2),9,3)';

bar_fig= bar(x,all_mean,FaceColor="flat",BarWidth=0.8);
hold on


for typei=1:3

    set(bar_fig(typei),'FaceColor',color3s{typei});

    errorbar(x+0.225*(typei-2),all_mean(typei,:),all_mean_std(typei,:),'LineStyle','none',LineWidth=1.5,Color=[0.5 0.5 0.5]);

    xtips = bar_fig(typei).XEndPoints;
    ytips = bar_fig(typei).YEndPoints+all_mean_std(typei,:);
    label = string(vpa(bar_fig(typei).YData,3));
    text(xtips,ytips,label,'HorizontalAlignment','center','VerticalAlignment','bottom','FontSize',12)
end
legend(["Tensile Yield Strength" "Compressive Yield Strength" "Flexural Yield Strength" ],Location="northwest",box="on")

%     xlabel("Type")
ylabel("Stress (MPa)")
set(gca,'FontName','Arial','FontSize',14)
%% 单独柱状图
figure();
ti=1;
set(gcf,'unit','centimeters','Position',[3 3 15 15]);
axes('unit','centimeters','position',[1.5 1.5 12.5 12.5]);
bar_fig_i= bar(x,all_mean(ti,:),BarWidth=0.8,FaceColor=color2);
hold on
errorbar(x,all_mean(ti,:),all_mean_std(ti,:),'LineStyle','none',LineWidth=1.5,Color=[0.5 0.5 0.5]);

xtips = bar_fig_i.XEndPoints;
ytips = bar_fig_i.YEndPoints+all_mean_std(ti,:);
label = string(vpa(bar_fig_i.YData,3));
text(xtips,ytips,label,'HorizontalAlignment','center','VerticalAlignment','bottom')


ylabel("Stress (MPa)")
set(gca,'FontName','Arial','FontSize',FontSize)
%% 保存计算获得的应力矩阵
all_sigma=[Tensile_maxy(:),compressive1_maxy(:),Flexural_maxy(:)];

save sigma_mat all_sigma all_mean all_mean_std  Tensile_maxy compressive1_maxy Flexural_maxy


%% 加载应力矩阵
load('sigma_mat.mat')
A=repmat([1	1	1	2	2	2	3	3	3]',6,1);
B=repmat([1	2	3	1	2	3	1	2	3]',6,1);
C=repmat([1	2	3	2	3	1	3	1	2]',6,1);
D=repmat([1	2	3	3	1	2	2	3	1]',6,1);
save taguchi9_mat A B C D % 保存相关变量
%% SN方差分析
sn=-10*log10(1./all_sigma.^2);
anova_soure_tbl= [{'A','B','C','D','Tensile','Compressive','Flexural'};[num2cell([A B C D]), num2cell(sn)]];
all_anova=cell(3,1);
for ni=1:3
    [~,tbli]=anovan(sn(:,ni),{A,B,C,D},"varnames",{'A','B','C','D'});
    tbli{1,1}='Factor';
    percent_source=cell2mat(tbli(2:6,5));
    percent=[{'Contribution'};num2cell(round(100*[percent_source;sum(percent_source)]./sum(percent_source),2))];


    all_anova{ni}=[tbli(:,[1 2 3 5 6 7]),percent];

end
save anovan_mat  all_anova anova_soure_tbl

%% 信噪比分析（采用越大越好计算公式）
all_sigma2square=1./all_sigma.^2;
all_sn=cell(3,1);
% all_ki=cell(3,1);
for ni=1:3
    [tbl_A,grp_A]=grpstats(all_sigma2square(:,ni),A,["mean","gname"]);
    [tbl_B,grp_B]=grpstats(all_sigma2square(:,ni),B,["mean","gname"]);
    [tbl_C,grp_C]=grpstats(all_sigma2square(:,ni),C,["mean","gname"]);
    [tbl_D,grp_D]=grpstats(all_sigma2square(:,ni),D,["mean","gname"]);

    sni=-10*log10([tbl_A,tbl_B,tbl_C,tbl_D]);
    sni_delta=max(sni)-min(sni);
    [~,sni_sort]=sort(sni_delta,'descend'); % 降序排列
    [~,sni_sort]=sort(sni_sort);           % 获得排位
    all_sn{ni}=cell(size(sni)+[3 1]);
    all_sn{ni}(1,:)={'Level' 'A','B','C','D'};
    all_sn{ni}(2:end,1)={'1' '2' '3' 'Delta' 'Rank'};
    all_sn{ni}(2:end,2:end)=[num2cell([sni;sni_delta]);num2cell(sni_sort)];

    % 直观分析计算过程（不采用）
    % tbl_A=grpstats(all_sigma(:,ni),A,@(x)sum(x,1));
    % tbl_B=grpstats(all_sigma(:,ni),B,@(x)sum(x,1));
    % tbl_C=grpstats(all_sigma(:,ni),C,@(x)sum(x,1));
    % tbl_D=grpstats(all_sigma(:,ni),D,@(x)sum(x,1));
    % all_ki{ni}=[tbl_A,tbl_B,tbl_C,tbl_D];

end
save all_sn_mat all_sn
%% 绘制信噪比SN曲线
close all
which_sigma=1; % 1:Tensile 2:Compressive1 3:Flexural
y1=cell2mat(all_sn{which_sigma}(2:4,2));
y2=cell2mat(all_sn{which_sigma}(2:4,3));
y3=cell2mat(all_sn{which_sigma}(2:4,4));
y4=cell2mat(all_sn{which_sigma}(2:4,5));
% y1=[0 0 0 ];
% y2=[0 0 0 ];
% y3=[0 0 0 ];
% y4=[0 0 0 ];
plot([y1;y2;y3;y4])
ylim_range=[18 32]; % set ylim range from the upper figure


FontSize=13;
fh1=figure();
set(gcf,'unit','centimeters','Position',[2 2 23 11]);

axes('parent',fh1,'unit','centimeters','position',[2 2 5 8],'fontsize',10);
plot([1 2 3],y1,'linewidth',3,'Marker','.','MarkerSize',30);
xlim([0.5 3.5])
ylim(ylim_range)
set(gca,'XTick',[1 2 3],'yTickLabel',num2str(get(gca,'yTick')','%.1f'));
xlabel("Filament","FontSize",FontSize,'FontName','Arial')
ylabel("Mean of SN Radio","FontSize",FontSize,'FontName','Arial')
box off

axes('parent',fh1,'unit','centimeters','position',[7 2 5 8],'fontsize',10);
plot([240 250 260],y2,'linewidth',3,'Marker','.','MarkerSize',30);
xlim([235 265])
ylim(ylim_range)
set(gca,'XTick',[240 250 260],'YTickLabel','')
xlabel("Speed(mm/s)","FontSize",FontSize,'FontName','Arial')
box off

axes('parent',fh1,'unit','centimeters','position',[12 2 5 8],'fontsize',10);
plot([210 215 220],y3,'linewidth',3,'Marker','.','MarkerSize',30)
xlim([205 225])
ylim(ylim_range)
set(gca,'XTick',[210 215 220],'YTickLabel','')
xlabel("Temperature(\circC)","FontSize",FontSize,'FontName','Arial')
box off

axes('parent',fh1,'unit','centimeters','position',[17 2 5 8],'fontsize',10);
plot([0.16 0.20 0.24],y4,'linewidth',3,'Marker','.','MarkerSize',30)
xlim([0.14 0.26])
ylim(ylim_range)
set(gca,'XTick',[0.16 0.20 0.24],'YTickLabel','')
xlabel("Layer thickness(mm)","FontSize",FontSize,'FontName','Arial')
box off

ax2 = axes('parent',fh1,'unit','centimeters','position',[2 2 20 8],...  
           'XAxisLocation','top',...  
           'YAxisLocation','right',...  
           'Color','none',...  
           'XColor','k','YColor','k');  
set(ax2,'YTick', []);  
set(ax2,'XTick', []); 
%% 线性回归预测
X=[ones(size(A)) A B C D];
all_regress=cell(3,1);
for ni=1:3
    [b,~,~,~,stats] = regress(all_sigma(:,ni),X);
    all_regress{ni}=[{'' 'A' 'B' 'C' 'D' 'R^2' 'p-value'}',num2cell([b;stats([1 3])'])];
end

save all_regress_mat all_regress

{% endfolding %}

Matlab 命令记录

Fri, 27 May 2022 14:46:54 +0000

cell

定义空cell

定义一个2✖️3的元胞结构数组

>> x=cell(2,3)

x =

  2×3 cell 数组

    {0×0 double}    {0×0 double}    {0×0 double}
    {0×0 double}    {0×0 double}    {0×0 double}

cell读取时{}()的区别

()读取得到的是元包结构，即cell数组
{}读取得到的是数据本身的内容，例如字符串

% 这个例子
>> title={{'pitch-RAO'} {'T'}    {'heave-波能俘获效率'} }

title =

  1×3 cell 数组

    {1×1 cell}    {1×1 cell}    {1×1 cell}

>> title(1)

ans =

  1×1 cell 数组

    {1×1 cell}

>> title{1}

ans =

  1×1 cell 数组

    {'pitch-RAO'}

>> title(1)(1)
错误:  无效的数组索引。
 
>> title(1){1}
错误:  无效的数组索引。
 
>> title{1}{1}

ans =

    'pitch-RAO'

>> title{1}(1)

ans =

  1×1 cell 数组

    {'pitch-RAO'}

坐标轴科学记数法表示与轴范围的影响

xlim([xmin xmax]) x轴显示范围
ylim([ymin ymax]) y轴显示范围
xticklabel xtick x坐标轴标签
yticklabel ytick x坐标轴标签

python-CAD绘制路基横断面

Tue, 24 May 2022 22:37:22 +0000

基于python的CAD路基横断面绘制

源代码

# _*_ coding:utf-8- _*_

from pyautocad import APoint, Autocad, aDouble
import win32com.client
import numpy as np
"""
设计高程：(2)1654.0m
填土边坡与路堑边坡坡率：(1)填方上部1:1.2(高度≤8m)，填方下部1:1.4(高度≤12m) ；挖方1:0.9(高度≤20m)
路基宽度：(2) 路面宽7.0米，硬路肩宽0.75米，土路肩宽0.75米
以下数据单位：m
"""
design_height = 1654.0  # 设计高程
slop_fill_up = 1.2      # 坡率填方上部(高度≤8m)
slop_fill_down = 1.4    # 坡率填方下部(高度≤12m)
slop_cut = 0.9          # 坡率挖方(高度≤20m)
surface_width = 7.0     # 路面宽
hard_shoulder = 0.75    # 硬路肩宽
dirt_shoulder = 0.75    # 土路肩宽

ctfs = 10               # 出图坐标放缩倍数
distance_sections = 60  # 修改为出图时横断面桩号间距
# 连接excel读取数据

xlapp = win32com.client.Dispatch("Excel.Application")
wb = xlapp.ActiveWorkbook
ws = xlapp.ActiveWorkbook.ActiveSheet


# points是原始地面点高程
ground_points = []
row = 2
while row <= 20:
    i = 6               # 左侧数据
    j = 8               # 右侧数据

    # 桩号点绘图坐标
    x0 = 0 + (distance_sections * (row - 2))//3
    y0 = ws.cells(row, 7).value
    p0 = APoint(x0, y0)
    pts = []
    pts.append(p0)


    #  拾取左侧点数据
    while i >= 1:
        try:
            y_ = ws.cells(row, i).value
            x_ = - ws.cells(row + 1, i).value
            pti = pts[0] + (x_, y_, 0)
            pts.insert(0, pti)
        except:
            pass
        i -= 1
    #  拾取右侧点数据
    while ws.cells(row, j).value:
        y_ = ws.cells(row, j).value
        x_ = ws.cells(row + 1, j).value
        ptj = pts[-1] + (x_, y_, 0)
        pts.append(ptj)
        j += 1
    ground_points.append(pts)

    for i in pts:
        print(i)
    print("")
    row = row + 3



# 连接cad，并输出结果

acad = Autocad(create_if_not_exists=True)
acad.prompt("connect with the Autocad successfully.")
print("connect with the Autocad successfully.")

dwg = acad.ActiveDocument
"原始地面线"
# 定义原始地面线 图层
ysdmx = acad.doc.layers.add("原始地面线")
ysdmx.color = 7
ysdmx.LineWeight = 25
dwg.ActiveLayer = ysdmx
# 绘制原始地面线，使用多段线（PLine）
for line_pts in ground_points:
    pt = aDouble([j for i in line_pts  for j in i * ctfs])
    acad.model.AddPolyLine(pt).LineWeight = 25

"路基线"
# 绘制路基线，所有横断面路基线按一样绘制，手动修改
# 生成路基线关键点坐标
orginal_middl_pts = []
pt0 = APoint(0, design_height)
orginal_middl_pts.append(pt0)
rightpts = [(surface_width/2, 0), (hard_shoulder, 0), (dirt_shoulder, 0), (0.6, - 0.6), (0.6, 0), (0.6, 0.6), (1, 0), (20 * slop_cut, 20)]
leftpts = [(surface_width/2, 0), (hard_shoulder, 0), (dirt_shoulder, 0), (8 * slop_fill_up, 8), (2, 0), (12 * slop_fill_down, 12)]


for i in leftpts:
    pti = orginal_middl_pts[0] - (i[0], i[1], 0)
    orginal_middl_pts.insert(0, pti)
for j in rightpts:
    ptj = orginal_middl_pts[-1] + (j[0], j[1], 0)
    orginal_middl_pts.append(ptj)
# 定义路基线 图层
ljx = acad.doc.layers.add("路基线")
ljx.color = 1
ljx.LineWeight = 100
dwg.ActiveLayer = ljx
# 绘制路基，使用多段线（PLine）
pt = aDouble([i for j in orginal_middl_pts  for i in j * ctfs])
ljx_drawn = acad.model.AddPolyLine(pt)
ljx_drawn.LineWeight = 100




"道路中心线"
# 得到坐标

# 定义图层属性
zxj = acad.doc.layers.add("道路中心线")
zxj.color = 2
zxj.LineWeight = 25
try:
    acad.ActiveDocument.Linetypes.Load("ACAD_ISO10W100", "acadiso.lin")
except:
    pass
zxj.Linetype = "ACAD_ISO10W100"
dwg.ActiveLayer = zxj
# 绘制中线
zxj_drewn = acad.model.addline(ctfs * (pt0 - (0, 2, 0)), ctfs * (pt0 + (0, 2, 0)))
zxj_drewn.LineWeight = 25
# [中心线、路基线]向右复制6次
for i in range(6):
    _ = ljx_drawn.copy()
    _.Move(APoint(0, 0), APoint(distance_sections * (i + 1), 0) * ctfs)
    del _
    _ = zxj_drewn.copy()
    _.Move(APoint(0, 0), APoint(distance_sections * (i + 1), 0) * ctfs)

"添加桩号标注"
# 得到坐标
# 定义图层
zh = acad.doc.layers.add("桩号标注")
dwg.ActiveLayer = zh
# 添加注释
for i in range(7):
    text_string = "K58+%d" % (70 + 10 * i)
    insertpt = APoint((distance_sections * i), design_height - 7) * ctfs
    height = 2.5 * ctfs
    textobj = acad.model.addtext(text_string, insertpt, height)
    textobj.Alignment = 7
    textobj.textalignmentpoint = insertpt

python-CAD绘制等高线

Tue, 24 May 2022 22:07:53 +0000

基于python的CAD等高线绘制

这是我本科在做《路基工程课程设计》挡土墙设计的时候，老师只给了原始地面数据点，因为疫情在家时间充裕，我就摸索了python画CAD，最终实现了绘制不同等高距的等高线绘制。 python面向对象编程。

基础知识

我这个代码只适合地面趋势简单的，通过差值得到固定整数高程点，然后将相同高程点依次连接。

note：

当时是在windows先写的代码，因为要用到win32com.client这个库，所以我估计 Mac下应该用不了，但可以修改代码绘制dxf文件，不调用CAD。
后续我再补充 Excel文件、输出CAD的文件及效果图

源代码

# _*_ coding:utf-8- _*_

from pyautocad import APoint, Autocad, aDouble
import win32com.client
import numpy as np

dgj = 0.5       # 等高距
ctfs = 10       # 放大倍数，本身采取m为单位绘制，可能放大10倍后输出效果好些

"""
等高线计算
"""
#连接excel读取数据，这个地方可以做一个前处理，直接把excel数据作为数组或者numpy数组进行处理

xlapp = win32com.client.Dispatch("Excel.Application")
wb = xlapp.ActiveWorkbook
ws = xlapp.ActiveWorkbook.ActiveSheet
"""
K58+70向右走为前进方向，绘制在
"""

"""
First
定义一个类，输入 list，其元素为APoint
内部函数得到插值的数据点，打印点数据
"""
class nei_cha:
    def __init__(self, pnts = [APoint(0,1)], dgj = 0.5, gu_ding_cha_zhi = "X" ):
        # gu_ding_cz = "X" 意思是不进行固定插值操作
        self.pnts = pnts
        self.dgj = dgj
        self.gu_ding_cha_zhi = gu_ding_cha_zhi

    # 输入两个三维坐标，x/y是相等的，内插得到所需高程
    # 返回的是，该区间内得到的点组成的list
    def do_two_points(self, p1 = APoint(0), p2 = APoint(0)):
        if self.gu_ding_cha_zhi == "X":
            nmax = int(max(p1.z, p2.z) // self.dgj)
            nmin = int(min(p1.z, p2.z) // self.dgj)
            if nmax == nmin:        # 这两个点之间内插不出来
                return 0
        else:
            nmax = self.gu_ding_cha_zhi
            nmin = self.gu_ding_cha_zhi - 1
            if (p1.z - nmax) * (p2.z - nmin) > 0:        # 固定插值不在区间内
                return 0

        if p1.x == p2.x:        # x坐标一样，需要内插Z到y
            """
            求直线方程，y
            """
            k = (p1.y - p2.y)/(p1.z - p2.z)
            b = p1.y - k * p1.z

            if self.gu_ding_cha_zhi == "X":
                ni = np.array(range(nmin, nmax)).reshape(int(nmax - nmin), 1)
                zi = (ni + 1) * self.dgj
            else:
                ni = np.array([self.gu_ding_cha_zhi]).reshape(int(nmax - nmin), 1)
                zi = ni
            yi = np.around(k * zi + b, 3)
            #yi = np.interp(zi, [p1.z, p2.z], [p1.y, p2.y])
            xi = np.full((len(yi), 1), p1.x)
            pts_np = np.hstack((xi, yi, zi))
            return  pts_np

        else:                   # y坐标一样，需要内插Z得到x
            return 0
    def do_it(self):
        pnts_np = np.array([])
        for i in range(len(self.pnts) - 1):

            p_np_i = self.do_two_points(self.pnts[i], self.pnts[i+1])
            if type(p_np_i) != type(0):
                try:
                    pnts_np = np.vstack((pnts_np, p_np_i))
                except:
                    pnts_np = p_np_i
        if len(pnts_np) != len(np.array([])):
            return pnts_np
        else:
            return 0



# points是原始地面点高程
ground_points = []
row = 2

while row <= 20:
    i = 6               # 左侧数据
    j = 8               # 右侧数据

    # 桩号点绘图坐标
    x0 = ((row - 2) / 3) * 10 + 70
    y0 = 0
    z0 = ws.cells(row, 7).value
    p0 = APoint(x0, y0, z0)
    pts = []
    pts.append(p0)


    #  拾取左侧点数据
    while i >= 1:
        try:
            z_ = ws.cells(row, i).value
            y_ = ws.cells(row + 1, i).value
            pti = pts[-1] + (0, y_, z_)
            pts.append(pti)
        except:
            pass
        i -= 1
    #  拾取右侧点数据
    while ws.cells(row, j).value:
        try:
            z_ = ws.cells(row, j).value
            y_ = - ws.cells(row + 1, j).value
            ptj = pts[0] + (0, y_, z_)
            pts.insert(0, ptj)
        except:
            print("右侧点拾取失败了：cells(%d,%d)"% (row, j))
            pass
        j += 1
    ground_points.append(pts)

    for i in pts:
        print(i)
    print("")
    row = row + 3

# 利用上方点开始使用类进行，插值
all_np = []
for i in ground_points:
    cha_zhi_la = nei_cha(i, dgj)
    a = cha_zhi_la.do_it()
    try:
        all_np = np.vstack((all_np, a))
    except:
        all_np = a
pts_all = [APoint(list(i)) for i in all_np]
pts_all.sort(key = lambda x:x.z)
del all_np

h_min = pts_all[0].z
h_max = pts_all[-1].z


zzzi = h_min
sorted_pts = []
while zzzi <= h_max:
    _ = [i for i in pts_all if i.z == zzzi]
    _.sort(key = lambda x:x[0])
    sorted_pts.append(_)
    zzzi += dgj
del pts_all
for i in sorted_pts:
    elevation = i[0].z
    print("高程为 %s 的数据点"% elevation)
    for l_ in i:
        print(l_)
# 连接cad，并输出结果

del sorted_pts[0:11]
del sorted_pts[-10:-1]
acad = Autocad(create_if_not_exists=True)
acad.prompt("connect with the Autocad successfully.")
print("connect with the Autocad successfully.")

dwg = acad.ActiveDocument

# 定义等高线图层
dgx = acad.doc.layers.add("等高线")
dgx.LineWeight = 25
dwg.ActiveLayer = dgx
dgxbz = acad.doc.layers.add("等高线标注")


for m in range(len(sorted_pts)):
    i = sorted_pts[m]
    elevation = i[0].z
    print("高程为 %s 的数据点"% elevation)
    for l_ in i:
        print(l_)
    try:


        for j in i:
            j.z = 0
        pt = aDouble([j for _ in i for j in _ * ctfs])
        hl = acad.model.AddPolyLine(pt)
        hl.LineWeight = 25
        hl.Elevation = elevation
        hl.Thickness = 900
        if m % 5 == 0:
            hl.LineWeight = 100
            hl.color = 1
            text_string = elevation
            insertpt = i[0] * ctfs
            textobj = acad.model.addMtext(insertpt, 26, text_string)
            textobj.Height = 8
            textobj.BackgroundFill = True
            textobj.color = 1
            textobj.layer = "等高线标注"

    except:
        print('*' * 10, "高程为 %s 的数据点不足，跳过绘制此等高线"% elevation)
        pass

结构可靠度理论代码共享

Sat, 14 May 2022 22:45:14 +0000

本文将记录《结构可靠度理论》的一些代码及课堂笔记，采用Matlab编程

1 概率分布密度（pdf、cdf）

自己编写函数

clc
clear
close all
% unif
a=1;
b=3;
x=1:0.1:3;
for i=1:length(x)
    fx(i)=1/(b-a);
    Fx(i)=(x(i)-a)/(b-a);
end
h1=figure(1);
ax1=axes('Parent',h1,'Position',[0.1,0.4,0.35,0.35],'FontSize',10);
plot(x,fx,'r-')
xlabel('x','fontsize',10)
ylabel('pdf','FontSize',10)

ax2=axes('Parent',h1,'Position',[0.55,0.4,0.35,0.35],'FontSize',10);
plot(x,Fx,'r-')
xlabel('x','fontsize',10)
ylabel('cdf','FontSize',10)

%-------
mux=1;sigx=1;
x=-2:0.1:4;
syms t
for i=1:length(x)
    tx=x(i);
    a1=1/(sigx*(2*pi)^0.5);
    b1=exp(-0.5*((tx-mux)/sigx)^2);
    fx(i)=a1*b1;
    c1=int(exp(-0.5*((t-mux)/sigx)^2),t,-inf,tx);
    Fx(i)=a1*c1;
end

h1=figure(2);
ax1=axes('Parent',h1,'Position',[0.1,0.4,0.35,0.35],'FontSize',10);
plot(x,fx,'r-')
xlabel('x','fontsize',10)
ylabel('pdf','FontSize',10)

ax2=axes("Parent",h1,"Position",[0.55,0.4,0.35,0.35],"FontSize",10);
plot(x,Fx,'r-')
xlabel('x','fontsize',10)
ylabel('cdf','FontSize',10)

调用Matlab自带函数

clc
clear
close all
%-----
a=1;b=3;
x=-2:0.1:5;
fx=unifpdf(x,a,b);
Fx=unifcdf(x,a,b);
figure(1)
plot(x,fx,'-r')
hold on
plot(x,Fx,'--b')

%---------
mux=0;sigx=1;
x=-3:0.1:3;
fx=normpdf(x,mux,sigx);
Fx=normcdf(x,mux,sigx);

figure(2)
plot(x,fx,'r-')
hold on
plot(x,Fx,'r-')