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<a href="/2020/07/07/lagrange-interpolation/" class="post-title-link" itemprop="url">拉格朗日插值法-Python</a>
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<h2 id="数据预处理——缺失值处理"><a href="#数据预处理——缺失值处理" class="headerlink" title="数据预处理——缺失值处理"></a>数据预处理——缺失值处理</h2><p>案例来源：<strong>《Python数据分析与挖掘实战》第6章 电力窃漏电用户自动识别</strong></p>
<p>这里介绍一种缺失值处理手段：插补法，具体是<strong>拉格朗日插值法</strong></p>
<p>拉格朗日插值法补值的具体方法如下：</p>
<p>首先从原始数据集中确定因变量和自变量，取出缺失值前后5个数据（前后数据中遇到数据不存在或者为空的，直接将数据舍去，将仅有的数据组成一组）,根据取出来的10个数据组成一组。然后采用拉格朗日多项式插值公式</p>
<p><img src="https://i.loli.net/2020/07/07/ZqiVEzFQOemxh32.png" alt="image-20200707222902831"></p>
<p><img src="https://i.loli.net/2020/07/07/wLF8MasC9O3JrpZ.png" alt="image-20200707222936410"></p>
<p>其中，x为缺失值对应的下标序号，Ln(x)为缺失值的插值结果，xi为非缺失值yi的下标序号。对全部缺失数据依次进行插补，直到不存在缺失值为止。数据插补代码如代码文件6-1_Lagrange_interpolation.py所示。</p>
<p>配套教材原始代码6-1_Lagrange_interpolation.py</p>
<figure class="highlight plain"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br><span class="line">8</span><br><span class="line">9</span><br><span class="line">10</span><br><span class="line">11</span><br><span class="line">12</span><br><span class="line">13</span><br><span class="line">14</span><br><span class="line">15</span><br><span class="line">16</span><br><span class="line">17</span><br><span class="line">18</span><br><span class="line">19</span><br><span class="line">20</span><br><span class="line">21</span><br><span class="line">22</span><br><span class="line">23</span><br><span class="line">24</span><br></pre></td><td class="code"><pre><span class="line">#-*- coding: utf-8 -*-</span><br><span class="line">#拉格朗日插值代码</span><br><span class="line">import pandas as pd #导入数据分析库Pandas</span><br><span class="line">from scipy.interpolate import lagrange #导入拉格朗日插值函数</span><br><span class="line"></span><br><span class="line">inputfile = '../data/missing_data.xls' #输入数据路径,需要使用Excel格式；</span><br><span class="line">outputfile = '../tmp/missing_data_processed.xls' #输出数据路径,需要使用Excel格式</span><br><span class="line"></span><br><span class="line">data = pd.read_excel(inputfile, header=None) #读入数据</span><br><span class="line"></span><br><span class="line">#自定义列向量插值函数</span><br><span class="line">#s为列向量，n为被插值的位置，k为取前后的数据个数，默认为5</span><br><span class="line">def ployinterp_column(s, n, k=5):</span><br><span class="line"> y = s[list(range(n-k, n)) + list(range(n+1, n+1+k))] #取数</span><br><span class="line"> y = y[y.notnull()] #剔除空值</span><br><span class="line"> return lagrange(y.index, list(y))(n) #插值并返回插值结果</span><br><span class="line"></span><br><span class="line">#逐个元素判断是否需要插值</span><br><span class="line">for i in data.columns:</span><br><span class="line"> for j in range(len(data)):</span><br><span class="line"> if (data[i].isnull())[j]: #如果为空即插值。</span><br><span class="line"> data[i][j] = ployinterp_column(data[i], j)</span><br><span class="line"></span><br><span class="line">data.to_excel(outputfile, header=None, index=False) #输出结果</span><br></pre></td></tr></table></figure>
<p>运行之后出现</p>
<img src="https://i.loli.net/2020/07/07/6RpJEyAUbrwtv3n.png" alt="image-20200707224536149" style="zoom: 67%;" />
<p><img src="https://i.loli.net/2020/07/07/PtWmGLjDQe2EH5X.png" alt="image-20200707224457575"></p>
<figure class="highlight plain"><table><tr><td class="gutter"><pre><span class="line">1</span><br></pre></td><td class="code"><pre><span class="line">KeyError: 'Passing list-likes to .loc or [] with any missing labels is no longer supported, see https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#deprecate-loc-reindex-listlike'</span><br></pre></td></tr></table></figure>
<p>我的解决过程：</p>
<ol>
<li><p>将上面出错内容进行搜索，找到以下有用的内容</p>
<p><a href="https://stackoverflow.com/questions/61291741/passing-list-likes-to-loc-or-with-any-missing-labels-is-no-longer-supported" target="_blank" rel="noopener">尝试reindex</a></p>
</li>
<li><p>改写代码</p>
<p>将</p>
<figure class="highlight plain"><table><tr><td class="gutter"><pre><span class="line">1</span><br></pre></td><td class="code"><pre><span class="line">y = s[list(range(n-k, n)) + list(range(n+1, n+1+k))]</span><br></pre></td></tr></table></figure>
<p>改写成</p>
<figure class="highlight plain"><table><tr><td class="gutter"><pre><span class="line">1</span><br></pre></td><td class="code"><pre><span class="line">y = s.reindex(list(range(n - k, n)) + list(range(n + 1, n + 1 + k)))</span><br></pre></td></tr></table></figure></li>
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<h1 id="电力窃漏电用户自动识别"><a href="#电力窃漏电用户自动识别" class="headerlink" title="电力窃漏电用户自动识别"></a>电力窃漏电用户自动识别</h1><p><img src="https://i.loli.net/2020/07/07/wEd6oM982vczO3Y.png" alt="image-20200707110145129"></p>
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<p>git命令思维导图</p>
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<a href="/2020/06/16/modelpredictivecontrol/" class="post-title-link" itemprop="url">无人驾驶车辆模型预测控制-读书笔记01</a>
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<h1 id="1-4-本书内容与结构说明"><a href="#1-4-本书内容与结构说明" class="headerlink" title="1.4 本书内容与结构说明"></a>1.4 本书内容与结构说明</h1><p>假设：本书假定无人驾驶车辆的感知系统能够对行驶环境进行充分的理解，能够得到障碍物、道路条件等环境信息，同时具备全局路径规划能力；车辆平台具备具备自动驾驶控制能力，横向与纵向控制系统能够控制车辆转向与速度，并且能向控制系统反馈车辆外部与内部信息。</p>
<h1 id="各章节内容"><a href="#各章节内容" class="headerlink" title="各章节内容"></a>各章节内容</h1><p><img src="https://i.loli.net/2020/06/16/RAJXcGP8uV5qKzf.png" alt="image-20200616144952579"></p>
<h1 id="轮胎模型"><a href="#轮胎模型" class="headerlink" title="*轮胎模型"></a>*轮胎模型</h1><h2 id="魔术公式"><a href="#魔术公式" class="headerlink" title="魔术公式**"></a>魔术公式**</h2><p><img src="https://i.loli.net/2020/06/16/xwAXrTtcaElPYhg.png" alt="image-20200616160431692"></p>
<h1 id="3-模型预测控制算法基础与仿真分析"><a href="#3-模型预测控制算法基础与仿真分析" class="headerlink" title="3 模型预测控制算法基础与仿真分析"></a>3 模型预测控制算法基础与仿真分析</h1><h2 id="3-1-2-控制理论中的描述"><a href="#3-1-2-控制理论中的描述" class="headerlink" title="3.1.2 控制理论中的描述"></a>3.1.2 控制理论中的描述</h2><p>模型预测控制在实现过程中有3个关键步骤，一般被称为3项基本原理，分别是预测模型、滚动优化和反馈校正。</p>
<h3 id="（1）-预测模型"><a href="#（1）-预测模型" class="headerlink" title="（1） 预测模型"></a>（1） 预测模型</h3><p>预测模型是模型预测控制的基础。其主要功能是根据对象的历史信息和未来输入，预测系统未来的输出。对预测模型的形式没有做严格的限定，状态方程、传递函数这类传统的模型都可以作为预测模型。对于线性稳定系统，阶跃响应、脉冲响应这类非参数模型，也可以直接作为预测模型来使用。</p>
<h3 id="（2）滚动优化"><a href="#（2）滚动优化" class="headerlink" title="（2）滚动优化"></a>（2）滚动优化</h3><p>模型预测控制通过某一性能指标的最优来确定控制作用，但优化不是一次离线作用，而是反复在线进行的。这就是滚动优化的含义，也是模型预测控制区别于传统最优控制的根本点。</p>
<h3 id="（3）反馈校正"><a href="#（3）反馈校正" class="headerlink" title="（3）反馈校正"></a>（3）反馈校正</h3><p>为了防止模型失配或者环境干扰引起控制对理想状态的偏离，在新的采样时刻，首先检测对象的实际输出，并利用这一实时信息对基于模型的预测结果进行修正，然后再进行新的优化。</p>
<p>基于这3个要素，模型预测控制的基本原理可以用图3.4表示</p>
<p><img src="https://i.loli.net/2020/06/16/z7PlfMVq6eIud3y.png" alt="image-20200616160539575"></p>
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<p>太阳和月亮<br>一个炽热<br>一个温柔<br>我也有太阳和月亮<br>一面炽热一面温柔<br>太阳和月亮<br>一个白天<br>一个夜晚<br>我也有白天和夜晚<br>一页日记一天生活</p>
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<a href="/2020/06/09/markdown-01/" class="post-title-link" itemprop="url">Markdown 教程(一）</a>
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<h1 id="简单介绍"><a href="#简单介绍" class="headerlink" title="简单介绍"></a>简单介绍</h1><p>Markdown是一种轻量级标记语言，它允许人们使用易读易写的纯文本格式编写文档。<br>Markdown 语言在 2004 由约翰·格鲁伯（英语：John Gruber）创建。<br>Markdown 编写的文档可以导出 HTML 、Word、图像、PDF、Epub 等多种格式的文档。<br>Markdown 编写的文档后缀为 .md, .markdown。</p>
<h1 id="应用"><a href="#应用" class="headerlink" title="应用"></a>应用</h1><p>当前许多网站都广泛使用 Markdown 来撰写帮助文档或是用于论坛上发表消息。例如：GitHub、简书、reddit、Diaspora、Stack Exchange、OpenStreetMap 、SourceForge等。</p>
<h1 id="标题"><a href="#标题" class="headerlink" title="标题"></a>标题</h1><p>markdown标题有两种格式。</p>
<h2 id="1、使用-和-标记一级和二级标题"><a href="#1、使用-和-标记一级和二级标题" class="headerlink" title="1、使用 = 和 - 标记一级和二级标题"></a>1、使用 = 和 - 标记一级和二级标题</h2><p>本教程将使用简书的md编辑器来讲解 Markdown 的语法，当然你们也可以使用其他软件代替，比如 <a href="https://www.typora.io/" target="_blank" rel="noopener">Typora</a>编辑器</p>
<p><img src="https://i.loli.net/2020/06/09/UZhnBxbaEFR1MkX.png" alt="简书编辑1.png"><br><img src="https://i.loli.net/2020/06/09/Y3vE5BfsNlVLjri.png" alt="简书预览1.png"></p>
<h2 id="2、使用-号标记"><a href="#2、使用-号标记" class="headerlink" title="2、使用 # 号标记"></a>2、使用 # 号标记</h2><p>使用 # 号可表示 1-6 级标题，一级标题对应一个 # 号，二级标题对应两个 # 号，以此类推。</p>
<p><img src="https://i.loli.net/2020/06/09/UZfVSsPERWzNabv.png" alt="简书编辑2.png"><br><img src="https://i.loli.net/2020/06/09/TJyP6GFQtYUVczo.png" alt="简书预览2.png"></p>
<h1 id="段落"><a href="#段落" class="headerlink" title="段落"></a>段落</h1><p>段落没有特殊格式，直接编写文本即可。<br><strong>段落的换行是使用2个以上空格加上enter键</strong><br>当然也可以在段落后面使用一个空行来表示重新开始一个段落。</p>
<h2 id="1、字体"><a href="#1、字体" class="headerlink" title="1、字体"></a>1、字体</h2><p>Markdown 可以使用以下几种字体：<br><img src="https://i.loli.net/2020/06/09/ecudzrg7EMiCwRI.png" alt="简书编辑3"><br><img src="https://i.loli.net/2020/06/09/EuDv2OJMnqeNwYi.png" alt="简书预览3"></p>
<h2 id="2、分割线"><a href="#2、分割线" class="headerlink" title="2、分割线"></a>2、分割线</h2><p>你可以在一行中用三个以上的星号、减号、底线来建立一个分隔线，行内不能有其他东西。你也可以在星号、减号、底线中间插入空格。下面每种写法都可以建立分隔线：</p>
<p><img src="https://i.loli.net/2020/06/09/Biv9KfzIbG2LZRM.png" alt="简书编辑4"><br><img src="https://i.loli.net/2020/06/09/n3isYlhjvWC1QHa.png" alt="简书预览4"></p>
<h2 id="3、删除线"><a href="#3、删除线" class="headerlink" title="3、删除线"></a>3、删除线</h2><p>段落上的文字要添加删除线，只需要在文字的两端加上两个波浪线 ~~ 即可<br><img src="https://i.loli.net/2020/06/09/QzufCvaS3ZybB9d.png" alt="简书编辑5"><br><img src="https://i.loli.net/2020/06/09/Uy9qFksTXW3NGdh.png" alt="简书预览5"></p>
<h2 id="4、下划线"><a href="#4、下划线" class="headerlink" title="4、下划线"></a>4、下划线</h2><p>下划线可以通过 HTML 的 <u> 标签来实现：（简书编辑器预览效果中无法实现，这里用<a href="https://www.typora.io/" target="_blank" rel="noopener">Typora</a>编辑器演示一下）</p>
<p><u>需要带下划线的文本</u><br><img src="https://i.loli.net/2020/06/09/RN36wiCfs2cZDWT.png" alt="Typora编辑器示例" style="zoom:50%;" /></p>
<h2 id="5、脚注"><a href="#5、脚注" class="headerlink" title="5、脚注"></a>5、脚注</h2><p>脚注是对文本的补充说明。<br>格式如下：<br><img src="https://i.loli.net/2020/06/09/1RfGPYzIdjVi4T7.png" alt="Typora编辑器示例"></p>
<p>未完待续，有空更新~</p>
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<a href="/2020/06/07/trucksim_s_function/" class="post-title-link" itemprop="url">TruckSim8.1与Matlab2018a联合仿真找不到TruckSim S-Function的解决办法</a>
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<h2 id="划重点：F5-或者-刷新Simulink-Library-Browser"><a href="#划重点：F5-或者-刷新Simulink-Library-Browser" class="headerlink" title="划重点：F5 或者 刷新Simulink Library Browser"></a>划重点：F5 或者 刷新Simulink Library Browser</h2><h3 id="1、在TruckSim中点击Send-to-Simulink"><a href="#1、在TruckSim中点击Send-to-Simulink" class="headerlink" title="1、在TruckSim中点击Send to Simulink"></a>1、在TruckSim中点击Send to Simulink</h3><p><img src="https://i.loli.net/2020/06/09/28TOdLlz7JR4SED.png" alt="1.png"></p>
<h3 id="2、待Simulink打开之后，点击Simulink-Library-Browser"><a href="#2、待Simulink打开之后，点击Simulink-Library-Browser" class="headerlink" title="2、待Simulink打开之后，点击Simulink Library Browser"></a>2、待Simulink打开之后，点击Simulink Library Browser</h3><p><img src="https://i.loli.net/2020/06/09/1FEhVk9e4l3wt8p.png" alt="2.png"></p>
<h3 id="3、出现Simulink-Library-Browser-如果没有出现TruckSim-S-Funciton也没有出现提醒信息“Fix”；则右键任意条目点击Refresh刷新或者F5；出现提醒信息“Fix”则直接点击Fix"><a href="#3、出现Simulink-Library-Browser-如果没有出现TruckSim-S-Funciton也没有出现提醒信息“Fix”；则右键任意条目点击Refresh刷新或者F5；出现提醒信息“Fix”则直接点击Fix" class="headerlink" title="3、出现Simulink Library Browser 如果没有出现TruckSim S-Funciton也没有出现提醒信息“Fix”；则右键任意条目点击Refresh刷新或者F5；出现提醒信息“Fix”则直接点击Fix"></a>3、出现Simulink Library Browser 如果没有出现TruckSim S-Funciton也没有出现提醒信息“Fix”；则右键任意条目点击Refresh刷新或者F5；出现提醒信息“Fix”则直接点击Fix</h3><p><img src="https://i.loli.net/2020/06/09/QprgJX1dKyYVSIu.png" alt="3.png"></p>
<p><img src="https://i.loli.net/2020/06/09/HcBsK5mjGb9zT8R.png" alt="4.png"></p>
<h3 id="4、最终出现了TruckSim-S-Function。（掌声）"><a href="#4、最终出现了TruckSim-S-Function。（掌声）" class="headerlink" title="4、最终出现了TruckSim S-Function。（掌声）"></a>4、最终出现了TruckSim S-Function。（掌声）</h3><p><img src="https://i.loli.net/2020/06/09/HuCrWQneXOijo7k.png" alt="5.png"></p>
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<p>Welcome to <a href="https://hexo.io/" target="_blank" rel="noopener">Hexo</a>! This is your very first post. Check <a href="https://hexo.io/docs/" target="_blank" rel="noopener">documentation</a> for more info. If you get any problems when using Hexo, you can find the answer in <a href="https://hexo.io/docs/troubleshooting.html" target="_blank" rel="noopener">troubleshooting</a> or you can ask me on <a href="https://github.com/hexojs/hexo/issues" target="_blank" rel="noopener">GitHub</a>.</p>
<h2 id="Quick-Start"><a href="#Quick-Start" class="headerlink" title="Quick Start"></a>Quick Start</h2><h3 id="Create-a-new-post"><a href="#Create-a-new-post" class="headerlink" title="Create a new post"></a>Create a new post</h3><figure class="highlight bash"><table><tr><td class="gutter"><pre><span class="line">1</span><br></pre></td><td class="code"><pre><span class="line">$ hexo new <span class="string">"My New Post"</span></span><br></pre></td></tr></table></figure>
<p>More info: <a href="https://hexo.io/docs/writing.html" target="_blank" rel="noopener">Writing</a></p>
<h3 id="Run-server"><a href="#Run-server" class="headerlink" title="Run server"></a>Run server</h3><figure class="highlight bash"><table><tr><td class="gutter"><pre><span class="line">1</span><br></pre></td><td class="code"><pre><span class="line">$ hexo server</span><br></pre></td></tr></table></figure>
<p>More info: <a href="https://hexo.io/docs/server.html" target="_blank" rel="noopener">Server</a></p>
<h3 id="Generate-static-files"><a href="#Generate-static-files" class="headerlink" title="Generate static files"></a>Generate static files</h3><figure class="highlight bash"><table><tr><td class="gutter"><pre><span class="line">1</span><br></pre></td><td class="code"><pre><span class="line">$ hexo generate</span><br></pre></td></tr></table></figure>
<p>More info: <a href="https://hexo.io/docs/generating.html" target="_blank" rel="noopener">Generating</a></p>
<h3 id="Deploy-to-remote-sites"><a href="#Deploy-to-remote-sites" class="headerlink" title="Deploy to remote sites"></a>Deploy to remote sites</h3><figure class="highlight bash"><table><tr><td class="gutter"><pre><span class="line">1</span><br></pre></td><td class="code"><pre><span class="line">$ hexo deploy</span><br></pre></td></tr></table></figure>
<p>More info: <a href="https://hexo.io/docs/one-command-deployment.html" target="_blank" rel="noopener">Deployment</a></p>
<h3 id="Github-免密码登录"><a href="#Github-免密码登录" class="headerlink" title="Github 免密码登录"></a>Github 免密码登录</h3><figure class="highlight bash"><table><tr><td class="gutter"><pre><span class="line">1</span><br></pre></td><td class="code"><pre><span class="line">$ ssh -T [email protected]</span><br></pre></td></tr></table></figure>
<p><strong>注意：这一步放在 hexo deploy前面执行。</strong></p>
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