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<?xml version="1.0" encoding="utf-8"?>
<feed xmlns="http://www.w3.org/2005/Atom">
<title>Hexo</title>
<link href="http://raolixiang-up.github.io/atom.xml" rel="self"/>
<link href="http://raolixiang-up.github.io/"/>
<updated>2023-01-10T15:09:15.443Z</updated>
<id>http://raolixiang-up.github.io/</id>
<author>
<name>raolixiang</name>
</author>
<generator uri="https://hexo.io/">Hexo</generator>
<entry>
<title>文献001-预印本网站</title>
<link href="http://raolixiang-up.github.io/2023/01/10/%E6%96%87%E7%8C%AE001-%E9%A2%84%E5%8D%B0%E6%9C%AC%E7%BD%91%E7%AB%99/"/>
<id>http://raolixiang-up.github.io/2023/01/10/%E6%96%87%E7%8C%AE001-%E9%A2%84%E5%8D%B0%E6%9C%AC%E7%BD%91%E7%AB%99/</id>
<published>2023-01-10T14:49:29.000Z</published>
<updated>2023-01-10T15:09:15.443Z</updated>
<content type="html"><![CDATA[<p>这里总结一下预印本和各种免费资源的网站吧，方便以后搜索最新文献。<br>[1] <a href="https://arxiv.org/">arXiv.org e-Print archive</a>: 数学、物理学、计算机等。<br>[2] <a href="http://www.chinaxiv.org/home.htm">ChinaXiv.org 中国科学院科技论文预发布平台</a>: 国产网站，接收中英文文章，比较综合。<br>[3] <a href="https://www.biorxiv.org/">bioRxiv.org - the preprint server for Biology</a>: 仅针对生物学领域。<br>[4] <a href="https://f1000.com/">Open Research Publishing - Advancing Knowledge - F1000</a>:涵盖所有生命科学领域的。<br>[5] <a href="https://figshare.com/">figshare - credit for all your research</a>: 图表、多媒体、海报、论文（包括预印本）和多文件、数据集等。<br>[6] <a href="https://peerj.com/preprints/">PeerJ - Search</a>: 涵盖了生物科学、医学和健康科学的领域。<br>[7] <a href="https://zenodo.org/">Zenodo - Research. Shared.</a>: 刊物、演示文稿、论文集、项目、图像、软件（包括与 GitHub 的集成）以及所有语言的数据。<br>[8] <a href="https://www.ssrn.com/index.cfm/en/">Home :: SSRN</a>:偏社会科学领域。</p>]]></content>
<summary type="html"><p>这里总结一下预印本和各种免费资源的网站吧，方便以后搜索最新文献。<br>[1] <a href="https://arxiv.org/">arXiv.org e-Print archive</a>: 数学、物理学、计算机等。<br>[2] <a href="http://w</summary>
<category term="文献" scheme="http://raolixiang-up.github.io/categories/%E6%96%87%E7%8C%AE/"/>
<category term="预印本" scheme="http://raolixiang-up.github.io/tags/%E9%A2%84%E5%8D%B0%E6%9C%AC/"/>
</entry>
<entry>
<title>ABINIT001-初步学习</title>
<link href="http://raolixiang-up.github.io/2023/01/01/ABINIT001-%E5%88%9D%E6%AD%A5%E5%AD%A6%E4%B9%A0/"/>
<id>http://raolixiang-up.github.io/2023/01/01/ABINIT001-%E5%88%9D%E6%AD%A5%E5%AD%A6%E4%B9%A0/</id>
<published>2023-01-01T13:55:47.000Z</published>
<updated>2023-01-01T14:58:59.482Z</updated>
<content type="html"><![CDATA[<p>因为要计算体系的非线性光学，因此需要学习ABINIT，这里整理一下学习资料，方便日后复习，主要是ABINIT官网和论坛如下所示：<br>[1] <a href="https://www.abinit.org/">Home | ABINIT</a><br>[2] <a href="https://discourse.abinit.org/">ABINIT</a><br>其他的学习资料推荐微信公众号：学术之友，作者有ABINIT开发组的经历，教程质量很高。ABINIT目前学习资源很少，官网感觉很乱相比于vasp官网，这可能就是开源的弊端吧。下面基本操作分享一个b站视频吧，如下：<br><a href="https://www.bilibili.com/video/BV1f34y1j7kQ/?spm_id_from=333.999.0.0&vd_source=a3d30bedf09a03ccbaa078f26da9bdf4">abinit 入门金刚石总能量的计算_哔哩哔哩_bilibili</a></p>]]></content>
<summary type="html"><p>因为要计算体系的非线性光学，因此需要学习ABINIT，这里整理一下学习资料，方便日后复习，主要是ABINIT官网和论坛如下所示：<br>[1] <a href="https://www.abinit.org/">Home | ABINIT</a><br>[2] <a hre</summary>
<category term="DFT" scheme="http://raolixiang-up.github.io/categories/DFT/"/>
<category term="ABINIT" scheme="http://raolixiang-up.github.io/tags/ABINIT/"/>
</entry>
<entry>
<title>机器学习002-决定系数等指标</title>
<link href="http://raolixiang-up.github.io/2022/12/31/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0002/"/>
<id>http://raolixiang-up.github.io/2022/12/31/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0002/</id>
<published>2022-12-31T14:53:34.000Z</published>
<updated>2022-12-31T15:15:34.687Z</updated>
<content type="html"><![CDATA[<p>机器学习中MSE(均方误差)、 RMSE(均方根误差)、 MAE(平均绝对误差)、R2(决定系数)是评判机器学习获得的模型优劣非常重要的指标，这些指标的定义可以百度或者谷歌，这里不赘述了。<br>这里使用python脚本，需要一个具有两列数据的csv文件，一列为真实值，一列为机器学习预测值。</p><figure class="highlight bash"><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><span class="line">25</span><br></pre></td><td class="code"><pre><span class="line"><span class="comment">#导入相应的函数库</span></span><br><span class="line">from sklearn import datasets</span><br><span class="line">from sklearn.model_selection import train_test_split</span><br><span class="line">from sklearn.ensemble import RandomForestRegressor</span><br><span class="line">import numpy as np</span><br><span class="line">import pandas as pd</span><br><span class="line">from math import sqrt</span><br><span class="line">from sklearn.metrics import mean_absolute_error</span><br><span class="line">from sklearn.metrics import mean_squared_error</span><br><span class="line">from sklearn.metrics import r2_score</span><br><span class="line"><span class="comment">#加载数据</span></span><br><span class="line">file_y = pd.read_csv(<span class="string">'y-c44-3-q2-no.csv'</span>) <span class="comment"># csv文件，文件中有两列数，一列是真实值，一列是机器学习预测值</span></span><br><span class="line"><span class="comment"># print(file_y)</span></span><br><span class="line">data1 = file_y[<span class="string">'y_true'</span>] <span class="comment"># 真实值那列的抬头</span></span><br><span class="line">y_true = data1.values.tolist()</span><br><span class="line">data2 = file_y[<span class="string">'y_pred'</span>] <span class="comment"># 机器学习预测值那列的抬头</span></span><br><span class="line">y_pred = data2.values.tolist()</span><br><span class="line"><span class="comment"># print(y_true)</span></span><br><span class="line"><span class="comment"># print(y_pred)</span></span><br><span class="line"></span><br><span class="line"><span class="comment"># 使用sklearn调用衡量线性回归的MSE 、 RMSE、 MAE、r2</span></span><br><span class="line"><span class="built_in">print</span>(<span class="string">"mean_absolute_error:"</span>, mean_absolute_error(y_true, y_pred))</span><br><span class="line"><span class="built_in">print</span>(<span class="string">"mean_squared_error:"</span>, mean_squared_error(y_true, y_pred))</span><br><span class="line"><span class="built_in">print</span>(<span class="string">"rmse:"</span>, sqrt(mean_squared_error(y_true, y_pred)))</span><br><span class="line"><span class="built_in">print</span>(<span class="string">"r2 score:"</span>, r2_score(y_true, y_pred))</span><br></pre></td></tr></table></figure><h2 id="参考资料"><a href="#参考资料" class="headerlink" title="参考资料"></a>参考资料</h2><p>[1] <a href="https://blog.csdn.net/z15818264727/article/details/122638802">Python计算统计分析MSE 、 RMSE、 MAE、r2_zNULLT的博客-CSDN博客_python rmse</a><br>[2] <a href="https://blog.csdn.net/weixin_43245453/article/details/90144226">从csv文件读取列数据保存在列表中_春风若是你的博客-CSDN博客</a></p>]]></content>
<summary type="html"><p>机器学习中MSE(均方误差)、 RMSE(均方根误差)、 MAE(平均绝对误差)、R2(决定系数)是评判机器学习获得的模型优劣非常重要的指标，这些指标的定义可以百度或者谷歌，这里不赘述了。<br>这里使用python脚本，需要一个具有两列数据的csv文件，一列为真实值，一列</summary>
<category term="机器学习" scheme="http://raolixiang-up.github.io/categories/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/"/>
<category term="ML" scheme="http://raolixiang-up.github.io/tags/ML/"/>
</entry>
<entry>
<title>科研代码005-lobsterpy</title>
<link href="http://raolixiang-up.github.io/2022/10/14/%E7%A7%91%E7%A0%94%E4%BB%A3%E7%A0%81005-lobsterpy/"/>
<id>http://raolixiang-up.github.io/2022/10/14/%E7%A7%91%E7%A0%94%E4%BB%A3%E7%A0%81005-lobsterpy/</id>
<published>2022-10-14T15:53:52.000Z</published>
<updated>2022-10-14T16:09:57.326Z</updated>
<content type="html"><![CDATA[<p>lobsterpy为辅助计算COHP的工具，非常简便好用，网址为：<a href="https://github.com/JaGeo/LobsterPy">JaGeo/LobsterPy: Package to automatically analyze Lobster runs</a><br>对于COHP的计算分析相关的帖子已经很多在这里整理一下：</p><ol><li><a href="https://www.bilibili.com/video/BV1Q4411s7AL/?spm_id_from=333.999.0.0&vd_source=a3d30bedf09a03ccbaa078f26da9bdf4">固体与表面第一性原理计算教学14，电子结构分析(六)COOP, COHP_哔哩哔哩_bilibili</a></li><li><a href="http://blog.wangruixing.cn/2019/04/22/cohp/">COOP和COHP简单原理 | 世事如棋</a></li><li><a href="http://www.cohp.de/">COHP Homepage</a><br>以上三个网址可以帮我们掌握COHP基础知识和基本的计算，浪里个浪~~~~~~~~完结</li></ol>]]></content>
<summary type="html"><p>lobsterpy为辅助计算COHP的工具，非常简便好用，网址为：<a href="https://github.com/JaGeo/LobsterPy">JaGeo/LobsterPy: Package to automatically analyze Lobster r</summary>
<category term="科研代码" scheme="http://raolixiang-up.github.io/categories/%E7%A7%91%E7%A0%94%E4%BB%A3%E7%A0%81/"/>
<category term="python" scheme="http://raolixiang-up.github.io/tags/python/"/>
</entry>
<entry>
<title>vasp003-能带计算</title>
<link href="http://raolixiang-up.github.io/2022/07/15/vasp003-%E8%83%BD%E5%B8%A6%E8%AE%A1%E7%AE%97/"/>
<id>http://raolixiang-up.github.io/2022/07/15/vasp003-%E8%83%BD%E5%B8%A6%E8%AE%A1%E7%AE%97/</id>
<published>2022-07-15T02:39:04.000Z</published>
<updated>2022-07-15T04:04:42.274Z</updated>
<content type="html"><![CDATA[<p>能带计算走了很多弯路，主要介绍两种能带计算：PBE能带和HSE能带</p><h2 id="PBE能带"><a href="#PBE能带" class="headerlink" title="PBE能带"></a>PBE能带</h2><p>计算流程分为如下：</p><h3 id="PBE-SCF计算"><a href="#PBE-SCF计算" class="headerlink" title="PBE-SCF计算"></a>PBE-SCF计算</h3><p>这一步生成需要读取的WAVECAR，参考INCAR如下：</p><figure class="highlight bash"><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></pre></td><td class="code"><pre><span class="line">ISTART=0</span><br><span class="line">ICHARG=2</span><br><span class="line">PREC=Accurate</span><br><span class="line">GGA = PE</span><br><span class="line">ADDGRID =.TRUE.</span><br><span class="line"></span><br><span class="line"><span class="comment"># Electronic relaxation</span></span><br><span class="line">ENCUT=500</span><br><span class="line">EDIFF=1E-8</span><br><span class="line">EDIFFG=-0.001</span><br><span class="line"></span><br><span class="line">ISMEAR=0</span><br><span class="line">SIGMA = 0.05</span><br><span class="line">POTIM=0.20</span><br><span class="line">NELM=90</span><br><span class="line">NELMIN=5</span><br><span class="line">NSW=0</span><br><span class="line"></span><br><span class="line"><span class="comment"># Write flags</span></span><br><span class="line">LWAVE=.TRUE.</span><br><span class="line">LCHARG=.TRUE.</span><br></pre></td></tr></table></figure><p>按照自己的需求增添参数</p><h3 id="PBE能带计算"><a href="#PBE能带计算" class="headerlink" title="PBE能带计算"></a>PBE能带计算</h3><p>运行vaspkit -task 303（3D材料）或者302（二维材料）<br>生成KPATH.in 和 HIGH_SYMMETRY_POINTS,可以自行修改，主要修改KPATH.in设置K点路径，更换KPOINTS文件：cp KPATH.in KPOINTS<br>将PBE-SCF计算中的INCAR中ISTART改为1即可，这里不设置ICHARG=11,不读取生成的CHARGCAR，提交任务即可。<br>处理数据如下：<br>vaspkit -task n #根据下面说明自行选择<br>211) Band-Structure<br>212) Projected Band-Structure for Selected Atom<br>213) Projected Band-Structure for Each Element<br>214) The Sum of Projected Band-Structure for Selected Atoms<br>215) Projected Band-Structure by Element Weight</p><h2 id="HSE能带计算"><a href="#HSE能带计算" class="headerlink" title="HSE能带计算"></a>HSE能带计算</h2><p>HSE计算分为两步：</p><h3 id="采用标准的KPOINTS进行HSE的SCF计算"><a href="#采用标准的KPOINTS进行HSE的SCF计算" class="headerlink" title="采用标准的KPOINTS进行HSE的SCF计算"></a>采用标准的KPOINTS进行HSE的SCF计算</h3><p>参考的INCAR如下所示：</p><figure class="highlight bash"><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><span class="line">25</span><br><span class="line">26</span><br><span class="line">27</span><br><span class="line">28</span><br><span class="line">29</span><br><span class="line">30</span><br><span class="line">31</span><br><span class="line">32</span><br><span class="line">33</span><br></pre></td><td class="code"><pre><span class="line">ISTART=0</span><br><span class="line">ICHARG=2</span><br><span class="line">PREC=Accurate</span><br><span class="line">ADDGRID =.TRUE.</span><br><span class="line"></span><br><span class="line"><span class="comment"># Electronic relaxation</span></span><br><span class="line">ENCUT=500</span><br><span class="line">EDIFF=1E-8</span><br><span class="line">EDIFFG=-0.001</span><br><span class="line"></span><br><span class="line">ISMEAR=0</span><br><span class="line">SIGMA = 0.05</span><br><span class="line">POTIM=0.20</span><br><span class="line">NELM=90</span><br><span class="line">NELMIN=5</span><br><span class="line">NSW=0</span><br><span class="line"></span><br><span class="line"><span class="comment"># HSE</span></span><br><span class="line">LHFCALC = TRUE</span><br><span class="line">HFSCREEN = 0.2</span><br><span class="line">GGA = PE</span><br><span class="line">AEXX = 0.14</span><br><span class="line">AGGAX = 0.86</span><br><span class="line">ALGO = Normal</span><br><span class="line">TIME = 0.4</span><br><span class="line"></span><br><span class="line"><span class="comment"># SOC （可选择是否具有自旋轨道耦合，NBANDS要为正常计算的二倍）</span></span><br><span class="line"><span class="comment"># LSORBIT = .TRUE.</span></span><br><span class="line"><span class="comment"># LMAXMIX=4</span></span><br><span class="line"></span><br><span class="line"><span class="comment"># Write flags</span></span><br><span class="line">LWAVE=.TRUE.</span><br><span class="line">LCHARG=.TRUE.</span><br></pre></td></tr></table></figure><p>需要注意的事项，<br>（1）AEXX越大带隙一般越大，AGGAX=1-AEXX；<br>（2）ALGO选择Normal<br>（3）用标准的KPOINTS</p><h3 id="HSE能带计算-1"><a href="#HSE能带计算-1" class="headerlink" title="HSE能带计算"></a>HSE能带计算</h3><p>运行vaspkit -task 303（3D材料）或者302（二维材料）<br>生成KPATH.in 和 HIGH_SYMMETRY_POINTS,可以自行修改，主要修改KPATH.in设置K点路径，然后运行vaspkit -task 251，一步一步输入，生成HSE计算使用的KPOINTS<br>将HSE-SCF计算中的INCAR中ISTART改为1即可，这里不设置ICHARG=11,不读取生成的CHARGCAR，提交任务即可。<br>任务处理命令：<br>vaspkit -task 252</p><h2 id="参考资料"><a href="#参考资料" class="headerlink" title="参考资料"></a>参考资料</h2><p>[1] <a href="http://blog.wangruixing.cn/2019/05/22/vaspkit-hse-band/">Vaspkit做杂化泛函能带计算方法 | 世事如棋</a><br>[2] <a href="http://blog.wangruixing.cn/2019/05/20/hse/">VASP中杂化泛函计算参数设置 | 世事如棋</a></p>]]></content>
<summary type="html"><p>能带计算走了很多弯路，主要介绍两种能带计算：PBE能带和HSE能带</p>
<h2 id="PBE能带"><a href="#PBE能带" class="headerlink" title="PBE能带"></a>PBE能带</h2><p>计算流程分为如下：</p>
<h3</summary>
<category term="vasp" scheme="http://raolixiang-up.github.io/categories/vasp/"/>
<category term="vasp" scheme="http://raolixiang-up.github.io/tags/vasp/"/>
</entry>
<entry>
<title>vasp002-DOS计算</title>
<link href="http://raolixiang-up.github.io/2022/07/09/vasp002-DOS%E8%AE%A1%E7%AE%97/"/>
<id>http://raolixiang-up.github.io/2022/07/09/vasp002-DOS%E8%AE%A1%E7%AE%97/</id>
<published>2022-07-08T16:18:44.000Z</published>
<updated>2022-07-08T16:23:27.908Z</updated>
<content type="html"><![CDATA[<p>vasp计算DOS，李强博士的帖子叙述的非常详细，具体帖子如下：<br><a href="https://www.bigbrosci.com/2018/02/06/ex37/">Ex-37 DOS 计算(一) | Learn VASP The Hard Way</a><br>顺着这个帖子一直学下去DOS计算不会有什么问题，就不再啰嗦复述了</p><h2 id="参考资料"><a href="#参考资料" class="headerlink" title="参考资料"></a>参考资料</h2><p>[1]<a href="https://www.bigbrosci.com/2018/02/06/ex37/">Ex-37 DOS 计算(一) | Learn VASP The Hard Way</a></p>]]></content>
<summary type="html"><p>vasp计算DOS，李强博士的帖子叙述的非常详细，具体帖子如下：<br><a href="https://www.bigbrosci.com/2018/02/06/ex37/">Ex-37 DOS 计算(一) | Learn VASP The Hard Way</a><br</summary>
<category term="vasp" scheme="http://raolixiang-up.github.io/categories/vasp/"/>
<category term="vasp" scheme="http://raolixiang-up.github.io/tags/vasp/"/>
</entry>
<entry>
<title>vasp001-固定轴优化</title>
<link href="http://raolixiang-up.github.io/2022/06/03/vasp001-%E5%9B%BA%E5%AE%9A%E8%BD%B4%E4%BC%98%E5%8C%96/"/>
<id>http://raolixiang-up.github.io/2022/06/03/vasp001-%E5%9B%BA%E5%AE%9A%E8%BD%B4%E4%BC%98%E5%8C%96/</id>
<published>2022-06-03T13:28:46.000Z</published>
<updated>2022-06-03T14:20:24.900Z</updated>
<content type="html"><![CDATA[<p>vasp固定轴优化，将网上的资料总结一下。<br>（1）修改constr_cell_relax.F，编译生成对应的vasp执行文件，见<a href="https://chempeng.github.io/post/2018/03/19/vasp-%E5%9B%BA%E5%AE%9A%E5%9F%BA%E7%9F%A2%E4%BC%98%E5%8C%96%E7%BB%93%E6%9E%84/">VASP 固定基矢优化结构 - chempeng</a><br>修改c方向为例，仅对于正交体系和单斜体系，修改代码如下:</p><figure class="highlight bash"><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><span class="line">25</span><br><span class="line">26</span><br><span class="line">27</span><br><span class="line">28</span><br><span class="line">29</span><br><span class="line">30</span><br><span class="line">31</span><br><span class="line">32</span><br><span class="line">33</span><br><span class="line">34</span><br><span class="line">35</span><br><span class="line">36</span><br><span class="line">37</span><br><span class="line">38</span><br><span class="line">39</span><br><span class="line">40</span><br><span class="line">41</span><br><span class="line">42</span><br><span class="line">43</span><br><span class="line">44</span><br><span class="line">45</span><br></pre></td><td class="code"><pre><span class="line">!-----------------------------------------------------------------------</span><br><span class="line">!</span><br><span class="line">! At present, VASP does not allow to relax the cellshape selectively</span><br><span class="line">! i.e. <span class="keyword">for</span> instance only cell relaxation <span class="keyword">in</span> x direction.</span><br><span class="line">! To be more precisse, this behaviour can not be achived via the INCAR</span><br><span class="line">! or POSCAR file.</span><br><span class="line">! However, it is possible to <span class="built_in">set</span> selected components of the stress tensor</span><br><span class="line">! to zero.</span><br><span class="line">! The most conveninent position to <span class="keyword">do</span> this is the routines</span><br><span class="line">! CONSTR_CELL_RELAX (constraint cell relaxation).</span><br><span class="line">! FCELL contains the forces on the basis vectors.</span><br><span class="line">! These forces are used to modify the basis vectors according</span><br><span class="line">! to the following equations:</span><br><span class="line">!</span><br><span class="line">! A_OLD(1:3,1:3)=A(1:3,1:3) ! F90 style</span><br><span class="line">! DO J=1,3</span><br><span class="line">! DO I=1,3</span><br><span class="line">! DO K=1,3</span><br><span class="line">! A(I,J)=A(I,J) + FCELL(I,K)*A_OLD(K,J)*STEP_SIZE</span><br><span class="line">! ENDDO</span><br><span class="line">! ENDDO</span><br><span class="line">! ENDDO</span><br><span class="line">! <span class="built_in">where</span> A holds the basis vectors (<span class="keyword">in</span> cartesian coordinates).</span><br><span class="line">!</span><br><span class="line">!-----------------------------------------------------------------------</span><br><span class="line"></span><br><span class="line"> SUBROUTINE CONSTR_CELL_RELAX(FCELL)</span><br><span class="line"> USE prec</span><br><span class="line"> REAL(q) FCELL(3,3)</span><br><span class="line"> DO I=1,3</span><br><span class="line"> FCELL(3,I)=0</span><br><span class="line"> FCELL(I,3)=0</span><br><span class="line"> ENDDO</span><br><span class="line">! just one simple example</span><br><span class="line">! relaxation <span class="keyword">in</span> x directions only</span><br><span class="line">! SAVE=FCELL(1,1)</span><br><span class="line">! FCELL=0 ! F90 style: <span class="built_in">set</span> the whole array to zero</span><br><span class="line">! FCELL(1,1)=SAVE</span><br><span class="line">! relaxation <span class="keyword">in</span> z direction only</span><br><span class="line">! SAVE=FCELL(3,3)</span><br><span class="line">! FCELL=0 ! F90 style: <span class="built_in">set</span> the whole array to zero</span><br><span class="line">! FCELL(3,3)=SAVE</span><br><span class="line"></span><br><span class="line"> RETURN</span><br><span class="line"> END SUBROUTINE</span><br></pre></td></tr></table></figure><p>然后重新编译生成vasp执行文件即可。对于其他方向晶格基矢的修改同理：对于a方向基矢，将 FCELL(3,I) 和 FCELL(I,3) 分别改为 FCELL(1,I) 和 FCELL(I,1) ；对于b方向基矢，则分别改为 FCELL(2,I) 和 FCELL(I,2)<br>（2）一次编译需要配置文件控制，见<a href="https://github.com/Chengcheng-Xiao/VASP_OPT_AXIS">Chengcheng-Xiao/VASP_OPT_AXIS: Fix lattice component(s) during relaxation in VASP</a><br>具体步骤参考链接，我测试了一下肖博士的第一种方法，其中需要注意的是OPTCELL文件数字中间如果有空格则优化有问题，没有空格正常。其次推荐教程中第二种方法，只需要在INCAR中加入IOPTCELL参数即可，不引入其他文件。<br>参考文献<br>[1] <a href="https://chempeng.github.io/post/2018/03/19/vasp-%E5%9B%BA%E5%AE%9A%E5%9F%BA%E7%9F%A2%E4%BC%98%E5%8C%96%E7%BB%93%E6%9E%84/">VASP 固定基矢优化结构 - chempeng</a><br>[2] <a href="https://github.com/Chengcheng-Xiao/VASP_OPT_AXIS">Chengcheng-Xiao/VASP_OPT_AXIS: Fix lattice component(s) during relaxation in VASP</a><br>[3] <a href="https://mp.weixin.qq.com/s/fkoqZisI2mPTha0WfxhcLg">VASP固定基矢优化结构最新方法更新</a><br>[4] <a href="http://blog.wangruixing.cn/2019/05/05/constr/">VASP固定基矢优化结构方法 | 世事如棋</a><br>[5] <a href="http://muchong.com/html/201107/3427823_2.html">VASP并行可执行软件包，可对晶胞参数进行部分优化 - 第 2 页 - 第一原理 - 小木虫 - 学术 科研 互动社区</a></p>]]></content>
<summary type="html"><p>vasp固定轴优化，将网上的资料总结一下。<br>（1）修改constr_cell_relax.F，编译生成对应的vasp执行文件，见<a href="https://chempeng.github.io/post/2018/03/19/vasp-%E5%9B%BA%E5%</summary>
<category term="vasp" scheme="http://raolixiang-up.github.io/categories/vasp/"/>
<category term="vasp" scheme="http://raolixiang-up.github.io/tags/vasp/"/>
</entry>
<entry>
<title>科研代码004-vasp输入文件POTCAR的自动生成</title>
<link href="http://raolixiang-up.github.io/2022/05/22/%E7%A7%91%E7%A0%94%E4%BB%A3%E7%A0%81004-vasp%E8%BE%93%E5%85%A5%E6%96%87%E4%BB%B6POTCAR%E7%9A%84%E8%87%AA%E5%8A%A8%E7%94%9F%E6%88%90/"/>
<id>http://raolixiang-up.github.io/2022/05/22/%E7%A7%91%E7%A0%94%E4%BB%A3%E7%A0%81004-vasp%E8%BE%93%E5%85%A5%E6%96%87%E4%BB%B6POTCAR%E7%9A%84%E8%87%AA%E5%8A%A8%E7%94%9F%E6%88%90/</id>
<published>2022-05-22T12:54:06.000Z</published>
<updated>2022-05-22T13:01:42.654Z</updated>
<content type="html"><![CDATA[<h2 id="代码"><a href="#代码" class="headerlink" title="代码"></a>代码</h2><p>vasp输入文件POTCAR的合并生成，网上很多资料简单整理一下。自己写代码也可以，李强博士已经写好了，如下所示：</p><figure class="highlight bash"><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></pre></td><td class="code"><pre><span class="line"><span class="meta">#!/usr/bin/bash</span></span><br><span class="line"><span class="comment"># Create a GGA_PAW POTCAR file</span></span><br><span class="line"><span class="comment"># by BigBro </span></span><br><span class="line"><span class="comment"># To Use it： potcar.sh Cu C H O</span></span><br><span class="line"></span><br><span class="line"><span class="comment"># Define local potpaw_GGA pseudopotentialrepository:</span></span><br><span class="line">repo=<span class="string">"/THFS/home/iciq-lq/bin/pot"</span></span><br><span class="line"></span><br><span class="line"><span class="comment"># Check if older version of POTCAR ispresent</span></span><br><span class="line"><span class="keyword">if</span> [ -f POTCAR ] ; <span class="keyword">then</span></span><br><span class="line"><span class="built_in">mv</span> -f POTCAR old-POTCAR</span><br><span class="line"><span class="built_in">echo</span> <span class="string">" ** Warning: old POTCAR file found and renamed to 'old-POTCAR'."</span></span><br><span class="line"><span class="keyword">fi</span></span><br><span class="line"></span><br><span class="line"><span class="comment"># Main loop - concatenate the appropriatePOTCARs (or archives)</span></span><br><span class="line"><span class="keyword">for</span> i <span class="keyword">in</span> $*</span><br><span class="line"><span class="keyword">do</span></span><br><span class="line"><span class="keyword">if</span> <span class="built_in">test</span> -f <span class="variable">$repo</span>/<span class="variable">$i</span>/POTCAR ; <span class="keyword">then</span></span><br><span class="line"><span class="built_in">cat</span> <span class="variable">$repo</span>/<span class="variable">$i</span>/POTCAR>> POTCAR</span><br><span class="line"><span class="keyword">else</span></span><br><span class="line"><span class="built_in">echo</span> <span class="string">" ** Warning: No suitable POTCAR for element '<span class="variable">$i</span>' found!! Skipped thiselement."</span></span><br><span class="line"><span class="keyword">fi</span></span><br><span class="line"><span class="keyword">done</span></span><br></pre></td></tr></table></figure><p>简单设置一下POTCAR文件所在的路径即可，具体使用见：<a href="https://www.bigbrosci.com/2017/12/21/A05/">自动生成POTCAR的脚本 | Learn VASP The Hard Way</a><br>因为这是比较简单的操作，很多软件都已经具有这个功能，例如vaspkit,qvasp等软件。</p><h2 id="参考资料"><a href="#参考资料" class="headerlink" title="参考资料"></a>参考资料</h2><p>[1] <a href="https://www.bigbrosci.com/2017/12/21/A05/">自动生成POTCAR的脚本 | Learn VASP The Hard Way</a><br>[2] <a href="https://vaspkit.com/">Overview — VASPKIT 1.3 documentation</a><br>[3] <a href="https://www.shangyexinzhi.com/article/528678.html">qvasp更新至v2.2版本（卷纳米管等功能）_学术之友-商业新知</a></p>]]></content>
<summary type="html"><h2 id="代码"><a href="#代码" class="headerlink" title="代码"></a>代码</h2><p>vasp输入文件POTCAR的合并生成，网上很多资料简单整理一下。自己写代码也可以，李强博士已经写好了，如下所示：</p>
<figure </summary>
<category term="科研代码" scheme="http://raolixiang-up.github.io/categories/%E7%A7%91%E7%A0%94%E4%BB%A3%E7%A0%81/"/>
<category term="shell" scheme="http://raolixiang-up.github.io/tags/shell/"/>
</entry>
<entry>
<title>linux-001-slurm和PBS排队调度系统</title>
<link href="http://raolixiang-up.github.io/2022/05/20/linux-slurm%E6%8E%92%E9%98%9F%E8%B0%83%E5%BA%A6%E7%B3%BB%E7%BB%9F/"/>
<id>http://raolixiang-up.github.io/2022/05/20/linux-slurm%E6%8E%92%E9%98%9F%E8%B0%83%E5%BA%A6%E7%B3%BB%E7%BB%9F/</id>
<published>2022-05-19T16:27:00.000Z</published>
<updated>2022-05-19T16:28:07.219Z</updated>
<content type="html"><![CDATA[<p>整理一下slurm和PBS简单使用的教程。<br>slurm:</p><ol><li><a href="https://zhuanlan.zhihu.com/p/356415669">Slurm 作业调度系统使用指南 - 知乎</a></li><li><a href="https://slurm.schedmd.com/quickstart.html">Slurm Workload Manager - Quick Start User Guide</a><br>PBS:</li><li><a href="https://kevinzjy.github.io/2018/08/13/180813-Server-PBS/">PBS作业管理系统使用技巧 | Kevinzjy’s Blog</a></li><li><a href="https://www.jianshu.com/p/2f6c799ca147">PBS 作业管理系统 - 简书</a><br>简单的操作，够用即可~~~~~~~~~~~~~~~~~~~~</li></ol>]]></content>
<summary type="html"><p>整理一下slurm和PBS简单使用的教程。<br>slurm:</p>
<ol>
<li><a href="https://zhuanlan.zhihu.com/p/356415669">Slurm 作业调度系统使用指南 - 知乎</a></li>
<li><a href=</summary>
<category term="linux" scheme="http://raolixiang-up.github.io/categories/linux/"/>
<category term="slurm-PBS" scheme="http://raolixiang-up.github.io/tags/slurm-PBS/"/>
</entry>
<entry>
<title>cohp高通量计算005-静态自洽计算是否正常结束的统计</title>
<link href="http://raolixiang-up.github.io/2022/05/14/cohp%E9%AB%98%E9%80%9A%E9%87%8F%E8%AE%A1%E7%AE%97005-%E9%9D%99%E6%80%81%E8%87%AA%E6%B4%BD%E8%AE%A1%E7%AE%97%E6%98%AF%E5%90%A6%E6%AD%A3%E5%B8%B8%E7%BB%93%E6%9D%9F%E7%9A%84%E7%BB%9F%E8%AE%A1/"/>
<id>http://raolixiang-up.github.io/2022/05/14/cohp%E9%AB%98%E9%80%9A%E9%87%8F%E8%AE%A1%E7%AE%97005-%E9%9D%99%E6%80%81%E8%87%AA%E6%B4%BD%E8%AE%A1%E7%AE%97%E6%98%AF%E5%90%A6%E6%AD%A3%E5%B8%B8%E7%BB%93%E6%9D%9F%E7%9A%84%E7%BB%9F%E8%AE%A1/</id>
<published>2022-05-14T13:24:23.000Z</published>
<updated>2022-05-14T13:51:02.799Z</updated>
<content type="html"><![CDATA[<p>总是要写很多稀奇古怪的脚本，因为计算cohp需要一步静态自洽计算，因此判定静态自洽是否正常结束非常重要。因为任务数目过多，所以需要写一个批量判定脚本。</p><h2 id="编写思路"><a href="#编写思路" class="headerlink" title="编写思路"></a>编写思路</h2><p>对静态自洽的步数和INCAR中设置的步数进行比较如果不等，表明静态自洽计算正常结束。如果相等，静态自洽有可能没有正常结束，此时要比较OSZICAR中的dE和INCAR中的EDIFF。如果dE小于EDIFF则正常结束，反之，则未收敛。</p><h2 id="脚本代码"><a href="#脚本代码" class="headerlink" title="脚本代码"></a>脚本代码</h2><p>脚本ls-st-convergence.sh要和批量任务放在一个文件夹内，静态自洽的INCAR中等号=两边有空格，代码如下：</p><figure class="highlight bash"><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></pre></td><td class="code"><pre><span class="line"><span class="meta">#!/usr/bin/bash</span></span><br><span class="line"></span><br><span class="line"><span class="keyword">for</span> i <span class="keyword">in</span> A*</span><br><span class="line"><span class="keyword">do</span></span><br><span class="line"></span><br><span class="line">N=$(<span class="built_in">tail</span> -n 2 <span class="variable">${i}</span>/static/OSZICAR | awk <span class="string">'NR==1 {print $2}'</span>)</span><br><span class="line">dE=$(<span class="built_in">tail</span> -n 2 <span class="variable">${i}</span>/static/OSZICAR | awk <span class="string">'NR==1 {print $4}'</span>) </span><br><span class="line">NELM=$(<span class="built_in">cat</span> <span class="variable">${i}</span>/static/INCAR | awk <span class="string">'NR==13 {print $3}'</span>) <span class="comment"># 参考自己的INCAR提取</span></span><br><span class="line">EDIFF=$(<span class="built_in">cat</span> <span class="variable">${i}</span>/static/INCAR | awk <span class="string">'NR==1 {print $3}'</span>) <span class="comment"># 参考自己的INCAR提取</span></span><br><span class="line"></span><br><span class="line"></span><br><span class="line"><span class="keyword">if</span> [ <span class="string">"<span class="variable">${N}</span>"</span> = <span class="string">"<span class="variable">${NELM}</span>"</span> ];<span class="keyword">then</span></span><br><span class="line"><span class="built_in">echo</span> <span class="variable">${i}</span> <span class="variable">${N}</span> <span class="variable">${NELM}</span> <span class="variable">${dE}</span> <span class="variable">${EDIFF}</span> >> no-st-convergence_result.dat</span><br><span class="line"><span class="keyword">else</span></span><br><span class="line">convergence_result=<span class="string">"No"</span></span><br><span class="line"><span class="built_in">echo</span> <span class="variable">${i}</span> <span class="variable">${N}</span> <span class="variable">${NELM}</span> <span class="variable">${dE}</span> <span class="variable">${EDIFF}</span> >> yes-st-convergence_result.dat</span><br><span class="line"><span class="keyword">fi</span></span><br><span class="line"></span><br><span class="line"><span class="keyword">done</span></span><br><span class="line">sed -i <span class="string">'1i system N NEM dE EDIFF'</span> no-convergence_result.dat</span><br><span class="line">sed -i <span class="string">'1i system N NEM dE EDIFF'</span> yes-convergence_result.dat</span><br></pre></td></tr></table></figure><p>这里不收敛的结构在no-st-convergence_result.dat中，收敛的结果在yes-convergence_result.dat。如果执行脚本时出现下列语句：</p><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">sed：无法读取 no-st-convergence_result.dat：没有那个文件或目录</span><br></pre></td></tr></table></figure><p>那么恭喜你，你的所有静态自洽计算都是收敛的。如有错误，欢迎指正~~~~~~~~~~</p><h2 id="参考资料"><a href="#参考资料" class="headerlink" title="参考资料"></a>参考资料</h2><p>[1] <a href="https://www.cnblogs.com/kaishirenshi/p/9729800.html">shell中的if语句 - 开始认识 - 博客园</a><br>[2] <a href="https://www.runoob.com/linux/linux-comm-awk.html">Linux awk 命令 | 菜鸟教程</a><br>[3] <a href="https://blog.csdn.net/fengfeifengfei/article/details/40371935">(5条消息) awk妙用（如何取出某行某列的某个元素）_god_is_my的博客-CSDN博客</a></p>]]></content>
<summary type="html"><p>总是要写很多稀奇古怪的脚本，因为计算cohp需要一步静态自洽计算，因此判定静态自洽是否正常结束非常重要。因为任务数目过多，所以需要写一个批量判定脚本。</p>
<h2 id="编写思路"><a href="#编写思路" class="headerlink" title="编</summary>
<category term="机器学习" scheme="http://raolixiang-up.github.io/categories/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/"/>
<category term="ML" scheme="http://raolixiang-up.github.io/tags/ML/"/>
</entry>
<entry>
<title>科研代码003-收敛性测试</title>
<link href="http://raolixiang-up.github.io/2022/05/12/%E7%A7%91%E7%A0%94%E4%BB%A3%E7%A0%81003-%E6%94%B6%E6%95%9B%E6%80%A7%E6%B5%8B%E8%AF%95/"/>
<id>http://raolixiang-up.github.io/2022/05/12/%E7%A7%91%E7%A0%94%E4%BB%A3%E7%A0%81003-%E6%94%B6%E6%95%9B%E6%80%A7%E6%B5%8B%E8%AF%95/</id>
<published>2022-05-12T15:41:17.000Z</published>
<updated>2022-05-13T09:32:53.438Z</updated>
<content type="html"><![CDATA[<p>收敛性测试，可以自己编写代码，也可以使用现成的代码，这里分享一个脚本vaspup。</p><h2 id="vaspup程序"><a href="#vaspup程序" class="headerlink" title="vaspup程序"></a>vaspup程序</h2><p>vaspup下载安装见：<a href="https://github.com/kavanase/vaspup2.0">kavanase/vaspup2.0: VASP Convergence Testing for Energy & Dielectric Constants</a><br>使用教程见程序给的例子和上述链接。<br>##注意事项<br>INCAR中等号=两边有一个空格。仅仅测试的关键词满足即可。KPOINTS也一样</p><h2 id="参考资料"><a href="#参考资料" class="headerlink" title="参考资料"></a>参考资料</h2><p>[1] <a href="https://github.com/kavanase/vaspup2.0">kavanase/vaspup2.0: VASP Convergence Testing for Energy & Dielectric Constants</a></p>]]></content>
<summary type="html"><p>收敛性测试，可以自己编写代码，也可以使用现成的代码，这里分享一个脚本vaspup。</p>
<h2 id="vaspup程序"><a href="#vaspup程序" class="headerlink" title="vaspup程序"></a>vaspup程序</h2></summary>
<category term="科研代码" scheme="http://raolixiang-up.github.io/categories/%E7%A7%91%E7%A0%94%E4%BB%A3%E7%A0%81/"/>
<category term="github" scheme="http://raolixiang-up.github.io/tags/github/"/>
</entry>
<entry>
<title>cohp高通量计算004-结构优化是否收敛的统计</title>
<link href="http://raolixiang-up.github.io/2022/05/12/cohp%E9%AB%98%E9%80%9A%E9%87%8F%E8%AE%A1%E7%AE%97/"/>
<id>http://raolixiang-up.github.io/2022/05/12/cohp%E9%AB%98%E9%80%9A%E9%87%8F%E8%AE%A1%E7%AE%97/</id>
<published>2022-05-11T19:53:27.000Z</published>
<updated>2022-05-13T09:18:53.679Z</updated>
<content type="html"><![CDATA[<h2 id="问题描述"><a href="#问题描述" class="headerlink" title="问题描述"></a>问题描述</h2><p>搞了很久，仍然卡在一个很奇葩的点上，我清楚的知道问题，但是没找到教程，弱爆了。问题如下所示：<br>result1=$(grep “reached” ${i}/GO/OUTCAR | tail -1)输出的字符串与”reached required accuracy - stopping structural energy minimisation”字符串不等价，目前还没找到解决方案。<br>这绝不是一个很难问题，只是我还没找到解决问题的路径。</p><h2 id="脚本代码"><a href="#脚本代码" class="headerlink" title="脚本代码"></a>脚本代码</h2><p>我采用另一种方式解决了这个问题，代码如下：</p><figure class="highlight bash"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br><span class="line">8</span><br><span class="line">9</span><br><span class="line">10</span><br><span class="line">11</span><br><span class="line">12</span><br><span class="line">13</span><br><span class="line">14</span><br><span class="line">15</span><br><span class="line">16</span><br><span class="line">17</span><br><span class="line">18</span><br></pre></td><td class="code"><pre><span class="line"><span class="meta">#!/usr/bin/bash</span></span><br><span class="line"></span><br><span class="line"><span class="keyword">for</span> i <span class="keyword">in</span> A*</span><br><span class="line"><span class="keyword">do</span></span><br><span class="line"><span class="built_in">cd</span> <span class="variable">${i}</span>/GO/</span><br><span class="line">result1=$(grep <span class="string">"reached"</span> <span class="variable">${i}</span>/GO/OUTCAR | <span class="built_in">tail</span> -1)</span><br><span class="line">result2=$(grep <span class="string">"reached"</span> A001*/GO/OUTCAR | <span class="built_in">tail</span> -1) <span class="comment">##找个确定收敛的OUTCAR</span></span><br><span class="line"><span class="comment"># final=`tail -1 out.vasp | awk '{print $1,$2}'`</span></span><br><span class="line"><span class="comment"># if [ "$final"x == "1 F="x ];then</span></span><br><span class="line"><span class="keyword">if</span> [ <span class="string">"<span class="variable">${result1}</span>"</span>x == <span class="string">"<span class="variable">${result2}</span>"</span>x ];<span class="keyword">then</span></span><br><span class="line">convergence_result=<span class="string">"Yes"</span></span><br><span class="line"><span class="keyword">else</span></span><br><span class="line">convergence_result=<span class="string">"No"</span></span><br><span class="line"><span class="built_in">echo</span> <span class="variable">${i}</span> <span class="variable">${convergence_result}</span> >> convergence_result.dat</span><br><span class="line"><span class="keyword">fi</span></span><br><span class="line"></span><br><span class="line"><span class="keyword">done</span></span><br><span class="line">sed -i <span class="string">'1i system convergence_result'</span> convergence_result.dat </span><br></pre></td></tr></table></figure><p>结构达到收敛的就不再统计，只统计结构优化未收敛的结果。找一个确定收敛的OUTCAR，提取关键语句，赋值在result2,然后其他的提取结果都与result2比较，顺利解决问题.<br>如有错误，欢迎指正~~~~~~~</p><h2 id="参考资料"><a href="#参考资料" class="headerlink" title="参考资料"></a>参考资料</h2><p>[1] <a href="https://www.runoob.com/linux/linux-shell-variable.html">Shell 变量 | 菜鸟教程</a><br>[2] <a href="https://www.cnblogs.com/kaishirenshi/p/9729800.html">shell中的if语句 - 开始认识 - 博客园</a><br>[3] <a href="https://blog.csdn.net/Mr_LeeHY/article/details/76383091">(5条消息) Shell字符串比较相等、不相等方法小结_Howie Lee的博客-CSDN博客_shell 字符串不相等</a><br>[4] <a href="https://blog.csdn.net/kobejayandy/article/details/13291525">(5条消息) Linux下的文本dos格式转Unix格式,去除^M符号_kobejayandy的博客-CSDN博客_dos格式和unix格式</a></p>]]></content>
<summary type="html"><h2 id="问题描述"><a href="#问题描述" class="headerlink" title="问题描述"></a>问题描述</h2><p>搞了很久，仍然卡在一个很奇葩的点上，我清楚的知道问题，但是没找到教程，弱爆了。问题如下所示：<br>result1=$(gr</summary>
<category term="机器学习" scheme="http://raolixiang-up.github.io/categories/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/"/>
<category term="ML" scheme="http://raolixiang-up.github.io/tags/ML/"/>
</entry>
<entry>
<title>科研代码002-任务收敛情况监控脚本</title>
<link href="http://raolixiang-up.github.io/2022/05/12/%E6%9F%A5%E7%9C%8B%E4%BB%BB%E5%8A%A1%E6%94%B6%E6%95%9B%E6%83%85%E5%86%B5/"/>
<id>http://raolixiang-up.github.io/2022/05/12/%E6%9F%A5%E7%9C%8B%E4%BB%BB%E5%8A%A1%E6%94%B6%E6%95%9B%E6%83%85%E5%86%B5/</id>
<published>2022-05-11T16:04:07.000Z</published>
<updated>2022-05-11T16:36:02.905Z</updated>
<content type="html"><![CDATA[<p>在任务运行过程中监测任务的收敛情况，有两个脚本。</p><h2 id="rsgrad"><a href="#rsgrad" class="headerlink" title="rsgrad"></a>rsgrad</h2><p>vasp计算监控程序，使用rust语言编写，具体详情见主页：<a href="https://github.com/Ionizing/rsgrad">Ionizing/rsgrad: A VASP calculation monitor. Written in Rust</a><br>安装包下载地址：<a href="https://github.com/Ionizing/rsgrad/releases/tag/0.3.6">Release 0.3.6 · Ionizing/rsgrad</a>，直接使用预编译二进制文件即可。<br>运行指令如下：</p><figure class="highlight bash"><table><tr><td class="gutter"><pre><span class="line">1</span><br></pre></td><td class="code"><pre><span class="line">rsgrad rlx <span class="comment"># 监控结构弛豫过程</span></span><br></pre></td></tr></table></figure><p>具体详细信息见主页。</p><h2 id="extforce-sh和screenfore-py脚本监控"><a href="#extforce-sh和screenfore-py脚本监控" class="headerlink" title="extforce.sh和screenfore.py脚本监控"></a>extforce.sh和screenfore.py脚本监控</h2><p>extforce.sh脚本的思路：<br>1）从OUTCAR中提取所有的TOTAL-FORCE部分信息（每个原子上的force vectors）；<br>2）用for循环调用screenforce.py筛选出每一个离子步受力大于EDIFFG的原子，及对应的原子序号，存储在lt_ediffg_${i}.dat，i为相应的离子步数。然后可以用p4vasp软件查看 具体是哪些原子没有达到力收敛标准。<br>预设的参数：<br>1）在extforce.sh里设置体系的原子数（N_atoms）；<br>2）在screenforce.py里设置一下EDIFFG（ediffg）。<br>需用python3，如果只有python2的话可以把screenforce.py的print那几行改成py2的格式即可，使用时将extforce.sh, screenforce.py, OUTCAR放在同一目录下，执行./extforce.sh即可。<br>相关介绍见：<a href="http://bbs.keinsci.com/thread-19985-1-1.html">分享从OUTCAR查看原子受力的小脚本 - 第一性原理 (First Principle) - 计算化学公社</a><br>对extforce.sh进行了简单的修改，直接从POSCAR获得原子总数，代码如下：</p><figure class="highlight bash"><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><span class="line">25</span><br><span class="line">26</span><br><span class="line">27</span><br><span class="line">28</span><br><span class="line">29</span><br><span class="line">30</span><br><span class="line">31</span><br><span class="line">32</span><br><span class="line">33</span><br><span class="line">34</span><br></pre></td><td class="code"><pre><span class="line"><span class="meta">#!/bin/bash</span></span><br><span class="line"><span class="comment"># Written by qmlearner at Homestay Uni.</span></span><br><span class="line"></span><br><span class="line"><span class="comment">######################################################</span></span><br><span class="line"><span class="comment">#Define the number of atoms (N_atoms) of your system.#</span></span><br><span class="line"><span class="comment">######################################################</span></span><br><span class="line">N_atoms=`<span class="built_in">cat</span> POSCAR | sed -n <span class="string">'7p'</span> | awk <span class="string">'{ for(i=1;i<=NF;i++) sum+=$i; print sum}'</span>`</span><br><span class="line">N_Lines_1=$(<span class="built_in">echo</span> <span class="string">"<span class="variable">${N_atoms}</span>+1"</span> | bc)</span><br><span class="line">N_Lines_2=$(<span class="built_in">echo</span> <span class="string">"<span class="variable">${N_atoms}</span>+2"</span> | bc)</span><br><span class="line"></span><br><span class="line"><span class="comment">########################################</span></span><br><span class="line"><span class="comment">#Extract the force vectors of each atom# </span></span><br><span class="line"><span class="comment">#for each ionic step. #</span></span><br><span class="line"><span class="comment">########################################</span></span><br><span class="line"><span class="keyword">if</span> [ ! -f <span class="string">"OUTCAR"</span> ]; <span class="keyword">then</span></span><br><span class="line"> <span class="built_in">echo</span> <span class="string">"Does not find OUTCAR."</span></span><br><span class="line"><span class="keyword">else</span></span><br><span class="line"> sed -n <span class="string">"/TOTAL-FORCE/,+<span class="variable">${N_Lines_1}</span>p"</span> OUTCAR > forcevectors.dat</span><br><span class="line"><span class="keyword">fi</span></span><br><span class="line"></span><br><span class="line">N_ionic_steps=$(grep -o <span class="string">'TOTAL-FORCE'</span> forcevectors.dat | <span class="built_in">wc</span> -l)</span><br><span class="line"></span><br><span class="line"><span class="built_in">cp</span> forcevectors.dat forcevectors-back.dat</span><br><span class="line"></span><br><span class="line"><span class="keyword">for</span> ((i=1;i<=<span class="variable">${N_ionic_steps}</span>;i++));</span><br><span class="line"><span class="keyword">do</span></span><br><span class="line"> sed -n <span class="string">"3,<span class="variable">${N_Lines_2}</span>p"</span> forcevectors.dat | awk <span class="string">'{printf "%10s %10s %10s \n",$4,$5,$6}'</span> > sep_forcevectors.dat</span><br><span class="line"> sed <span class="string">"1,<span class="variable">${N_Lines_2}</span>d"</span> forcevectors.dat > forcevectors_del.dat</span><br><span class="line"> <span class="built_in">mv</span> forcevectors_del.dat forcevectors.dat</span><br><span class="line"> python screenforce.py</span><br><span class="line"> <span class="built_in">mv</span> lt_ediffg.dat lt_ediffg_<span class="variable">${i}</span>.dat</span><br><span class="line"><span class="keyword">done</span></span><br><span class="line"></span><br><span class="line"><span class="built_in">rm</span> forcevectors.dat sep_forcevectors.dat atomicforce.dat</span><br></pre></td></tr></table></figure><p>screenforce.py的代码如下：</p><figure class="highlight bash"><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><span class="line">25</span><br><span class="line">26</span><br><span class="line">27</span><br><span class="line">28</span><br><span class="line">29</span><br><span class="line">30</span><br><span class="line">31</span><br><span class="line">32</span><br><span class="line">33</span><br><span class="line">34</span><br><span class="line">35</span><br><span class="line">36</span><br><span class="line">37</span><br><span class="line">38</span><br><span class="line">39</span><br><span class="line">40</span><br><span class="line">41</span><br><span class="line">42</span><br><span class="line">43</span><br><span class="line">44</span><br><span class="line">45</span><br><span class="line">46</span><br><span class="line">47</span><br><span class="line">48</span><br><span class="line">49</span><br><span class="line">50</span><br><span class="line">51</span><br><span class="line">52</span><br><span class="line">53</span><br><span class="line">54</span><br><span class="line">55</span><br><span class="line">56</span><br><span class="line">57</span><br><span class="line">58</span><br><span class="line">59</span><br><span class="line">60</span><br><span class="line">61</span><br><span class="line">62</span><br><span class="line">63</span><br><span class="line">64</span><br><span class="line">65</span><br><span class="line">66</span><br><span class="line">67</span><br><span class="line">68</span><br><span class="line">69</span><br><span class="line">70</span><br><span class="line">71</span><br><span class="line">72</span><br><span class="line">73</span><br><span class="line">74</span><br><span class="line">75</span><br><span class="line">76</span><br><span class="line">77</span><br></pre></td><td class="code"><pre><span class="line"><span class="meta">#!/usr/bin/python -u </span></span><br><span class="line"><span class="comment"># -*- coding: utf-8 -*-</span></span><br><span class="line"><span class="comment"># Calculate the force of each atom. Screen the force not fullfil convergence criteria and the </span></span><br><span class="line"><span class="comment"># corresponding atom number.</span></span><br><span class="line"><span class="comment"># Written by qmlearner at Homestay Uni. </span></span><br><span class="line"></span><br><span class="line"></span><br><span class="line"><span class="comment">#import math </span></span><br><span class="line"><span class="comment">#import numpy as np</span></span><br><span class="line"><span class="comment">#import re</span></span><br><span class="line">import os</span><br><span class="line"></span><br><span class="line">a=open(<span class="string">'sep_forcevectors.dat'</span>,<span class="string">'r+'</span>)</span><br><span class="line"></span><br><span class="line">af=<span class="string">'atomicforce.dat'</span></span><br><span class="line"></span><br><span class="line"><span class="keyword">if</span> os.path.exists(af):</span><br><span class="line"> <span class="built_in">print</span>(<span class="string">"---------------------------------------------"</span>)</span><br><span class="line"> <span class="built_in">print</span>(<span class="string">"%s file already exists. It will be deleted."</span> %(af)) </span><br><span class="line"> <span class="built_in">print</span>(<span class="string">"---------------------------------------------"</span>)</span><br><span class="line"> os.remove(af)</span><br><span class="line"></span><br><span class="line">b=open(af,<span class="string">'a'</span>)</span><br><span class="line"></span><br><span class="line"></span><br><span class="line">la=a.readlines()</span><br><span class="line"></span><br><span class="line"><span class="comment">###############################################</span></span><br><span class="line"><span class="comment">#Calculate the force performing on each atom###</span></span><br><span class="line"><span class="comment">###############################################</span></span><br><span class="line"><span class="keyword">for</span> i <span class="keyword">in</span> range(len(la)):</span><br><span class="line"> x=<span class="built_in">float</span>(la[i].strip().<span class="built_in">split</span>()[0])</span><br><span class="line"> y=<span class="built_in">float</span>(la[i].strip().<span class="built_in">split</span>()[1])</span><br><span class="line"> z=<span class="built_in">float</span>(la[i].strip().<span class="built_in">split</span>()[2])</span><br><span class="line"> </span><br><span class="line"> F=(x**2 + y**2 + z**2)**0.5</span><br><span class="line"> b.write(str(F))</span><br><span class="line"> b.write(<span class="string">'\n'</span>)</span><br><span class="line"></span><br><span class="line">a.close()</span><br><span class="line">b.close()</span><br><span class="line"></span><br><span class="line"><span class="comment">################################################</span></span><br><span class="line"><span class="comment">#Output the force that does not fulfill #</span></span><br><span class="line"><span class="comment">#convergence criteria. #</span></span><br><span class="line"><span class="comment">################################################</span></span><br><span class="line"></span><br><span class="line">c=open(<span class="string">'atomicforce.dat'</span>,<span class="string">'r'</span>)</span><br><span class="line"></span><br><span class="line">ce=<span class="string">'lt_ediffg.dat'</span></span><br><span class="line"></span><br><span class="line"><span class="keyword">if</span> os.path.exists(ce):</span><br><span class="line"> <span class="built_in">print</span>(<span class="string">"------------------------------------------"</span>)</span><br><span class="line"> <span class="built_in">print</span>(<span class="string">"%s file already exists. It will be deleted."</span> %(ce)) </span><br><span class="line"> <span class="built_in">print</span>(<span class="string">"------------------------------------------"</span>)</span><br><span class="line"> os.remove(ce)</span><br><span class="line"></span><br><span class="line">d=open(ce,<span class="string">'a'</span>)</span><br><span class="line"></span><br><span class="line"></span><br><span class="line">lc=c.readlines()</span><br><span class="line"></span><br><span class="line"><span class="comment">##################################################</span></span><br><span class="line"><span class="comment">#Change the ediffg according to your own settings#</span></span><br><span class="line"><span class="comment">##################################################</span></span><br><span class="line">ediffg=0.01</span><br><span class="line"></span><br><span class="line"><span class="keyword">for</span> i <span class="keyword">in</span> range(len(lc)):</span><br><span class="line"> F=<span class="built_in">float</span>(lc[i].strip()) </span><br><span class="line"> <span class="keyword">if</span> F >= ediffg:</span><br><span class="line"> d.write(str(i+1))</span><br><span class="line"> d.write(<span class="string">'\t'</span>)</span><br><span class="line"> d.write(str(F))</span><br><span class="line"> d.write(<span class="string">'\n'</span>)</span><br><span class="line"></span><br><span class="line">c.close()</span><br><span class="line">d.close()</span><br></pre></td></tr></table></figure><h2 id="参考资料"><a href="#参考资料" class="headerlink" title="参考资料"></a>参考资料</h2><p>[1] <a href="https://github.com/Ionizing/rsgrad">Ionizing/rsgrad: A VASP calculation monitor. Written in Rust</a><br>[2] <a href="http://bbs.keinsci.com/thread-19985-1-1.html">分享从OUTCAR查看原子受力的小脚本 - 第一性原理 (First Principle) - 计算化学公社</a><br>[3] <a href="https://blog.csdn.net/chenxieyy/article/details/53786313">(5条消息) linux 一行数值累加求和_yychenxie21的博客-CSDN博客_linux 累加</a></p>]]></content>
<summary type="html"><p>在任务运行过程中监测任务的收敛情况，有两个脚本。</p>
<h2 id="rsgrad"><a href="#rsgrad" class="headerlink" title="rsgrad"></a>rsgrad</h2><p>vasp计算监控程序，使用rust语言编写，</summary>
<category term="科研代码" scheme="http://raolixiang-up.github.io/categories/%E7%A7%91%E7%A0%94%E4%BB%A3%E7%A0%81/"/>
<category term="github" scheme="http://raolixiang-up.github.io/tags/github/"/>
</entry>
<entry>
<title>cohp高通量计算003-批量重命名</title>
<link href="http://raolixiang-up.github.io/2022/05/06/cohp%E9%AB%98%E9%80%9A%E9%87%8F%E8%AE%A1%E7%AE%97003-%E6%89%B9%E9%87%8F%E9%87%8D%E5%91%BD%E5%90%8D/"/>
<id>http://raolixiang-up.github.io/2022/05/06/cohp%E9%AB%98%E9%80%9A%E9%87%8F%E8%AE%A1%E7%AE%97003-%E6%89%B9%E9%87%8F%E9%87%8D%E5%91%BD%E5%90%8D/</id>
<published>2022-05-06T01:59:08.000Z</published>
<updated>2022-05-06T02:12:46.557Z</updated>
<content type="html"><![CDATA[<p>爬取完数据，因为mpid需要按顺序排列，方便以后数据爬取，因此需要给下载的结构文件重命名。python使用很不熟练，命令代码也不熟悉，任务还比较着急。因此，直接搜索“文件批量重命名”，顺利找到解决方案。</p><h2 id="使用工具"><a href="#使用工具" class="headerlink" title="使用工具"></a>使用工具</h2><p>软件名称：Renamer Lite (免安装解压即用)<br>下载地址：<br><a href="https://www.den4b.com/products/renamer">ReNamer « Products « den4b.com</a><br><a href="https://m.majorgeeks.com/files/details/renamer.html">Download ReNamer Lite - MajorGeeks</a><br>使用这个工具顺利解决我的问题</p><h2 id="参考资料"><a href="#参考资料" class="headerlink" title="参考资料"></a>参考资料</h2><p>[1] <a href="https://www.den4b.com/products/renamer">ReNamer « Products « den4b.com</a><br>[2] <a href="https://m.majorgeeks.com/files/details/renamer.html">Download ReNamer Lite - MajorGeeks</a><br>[3] <a href="https://zhuanlan.zhihu.com/p/100779917">ReNamer批量重命名文件教程 - 知乎</a></p>]]></content>
<summary type="html"><p>爬取完数据，因为mpid需要按顺序排列，方便以后数据爬取，因此需要给下载的结构文件重命名。python使用很不熟练，命令代码也不熟悉，任务还比较着急。因此，直接搜索“文件批量重命名”，顺利找到解决方案。</p>
<h2 id="使用工具"><a href="#使用工具" c</summary>
<category term="机器学习" scheme="http://raolixiang-up.github.io/categories/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/"/>
<category term="ML" scheme="http://raolixiang-up.github.io/tags/ML/"/>
</entry>
<entry>
<title>科研代码001-sumo</title>
<link href="http://raolixiang-up.github.io/2022/05/05/%E7%A7%91%E7%A0%94%E4%BB%A3%E7%A0%81001/"/>
<id>http://raolixiang-up.github.io/2022/05/05/%E7%A7%91%E7%A0%94%E4%BB%A3%E7%A0%81001/</id>
<published>2022-05-05T13:10:46.000Z</published>
<updated>2022-05-05T13:23:11.982Z</updated>
<content type="html"><![CDATA[<p>sumo程序可以简化vasp计算数据的后处理，这里收集一下大佬分享的使用代码吧。</p><h2 id="程序安装"><a href="#程序安装" class="headerlink" title="程序安装"></a>程序安装</h2><p>sumo简介和安装见：SMTG-UCL/sumo: <a href="https://github.com/SMTG-UCL/sumo">Heavyweight plotting tools for ab initio calculations</a><br>安装命令如下：</p><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">$ pip install --user sumo</span><br></pre></td></tr></table></figure><h2 id="程序使用"><a href="#程序使用" class="headerlink" title="程序使用"></a>程序使用</h2><p>a) 声子谱（DFPT方法）</p><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">$ sumo-phonon-bandplot -f FORCE_CONSTANTS --primitive-auto --pymatgen --format tiff --dim 2 2 2</span><br></pre></td></tr></table></figure><p>b) 声子谱（冷冻声子法）</p><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">$ sumo-phonon-bandplot --primitive-auto --pymatgen --format tiff --dim 2 2 2</span><br></pre></td></tr></table></figure><p>c) 一键画态密度图</p><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">$ sumo-dosplot --orbitals Os.d --elements Os.d --atoms Os.1 --no-total</span><br></pre></td></tr></table></figure><p>d) 一键画能带图</p><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">$ sumo-bandplot --project Os.d,O.p,Os.s --mode stacked --circle-size 90</span><br></pre></td></tr></table></figure><h2 id="参考资料"><a href="#参考资料" class="headerlink" title="参考资料"></a>参考资料</h2><p>[1] <a href="https://github.com/SMTG-UCL/sumo">Heavyweight plotting tools for ab initio calculations</a><br>[2] <a href="https://smtg-ucl.github.io/sumo/index.html">Sumo — sumo 2.3.0 documentation</a></p>]]></content>
<summary type="html"><p>sumo程序可以简化vasp计算数据的后处理，这里收集一下大佬分享的使用代码吧。</p>
<h2 id="程序安装"><a href="#程序安装" class="headerlink" title="程序安装"></a>程序安装</h2><p>sumo简介和安装见：SMT</summary>
<category term="科研代码" scheme="http://raolixiang-up.github.io/categories/%E7%A7%91%E7%A0%94%E4%BB%A3%E7%A0%81/"/>
<category term="github" scheme="http://raolixiang-up.github.io/tags/github/"/>
</entry>
<entry>
<title>shell001-反向删除</title>
<link href="http://raolixiang-up.github.io/2022/05/05/shell001/"/>
<id>http://raolixiang-up.github.io/2022/05/05/shell001/</id>
<published>2022-05-04T17:39:45.000Z</published>
<updated>2022-05-04T18:03:44.668Z</updated>
<content type="html"><![CDATA[<p>我咋特别喜欢揪着不常用的命令花费大量时间死磕呢，不是一个好习惯。</p><h2 id="shell反向删除"><a href="#shell反向删除" class="headerlink" title="shell反向删除"></a>shell反向删除</h2><h3 id="方法1"><a href="#方法1" class="headerlink" title="方法1"></a>方法1</h3><p>花了很长时间终于找到解决方案。<br> <figure class="highlight bash"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br></pre></td><td class="code"><pre><span class="line">$ <span class="built_in">shopt</span> -s extglob <span class="comment">#（打开extglob模式）</span></span><br><span class="line">$ <span class="built_in">rm</span> -rf !(file1) 或者 <span class="built_in">rm</span> -rf !(file1|file2|...) -删除多个文件</span><br></pre></td></tr></table></figure><br>顺利反向删除</p><h3 id="方法2"><a href="#方法2" class="headerlink" title="方法2"></a>方法2</h3><p>当前文件夹中结合使用grep和xargs来处理文件名：ls | grep -v keep | xargs rm #删除keep文件之外的所有文件<br>说明：ls先得到当前的所有文件和文件夹的名字，grep -v keep，进行grep正则匹配查找keep，-v参数决定了结果为匹配之外的结果，也就是的到了keep之外的所有文件名，然后 xargs用于从 标准输入获得参数 并且传递给后面的命令，这里使用的命令是 rm，然后由rm删除前面选择的文件。<br>好处：使用了grep来正则表达式来匹配文件名字，可以一次保留多个文件，从而进行更加准确的处理。</p><h3 id="方法3"><a href="#方法3" class="headerlink" title="方法3"></a>方法3</h3><p>使用find命令代替ls，改进方法3从而能够处理制定文件夹的文件：<br>find ./test/ | grep -v keep | xargs rm #删除当前test文件夹中keep文件之外的所有文件<br>说明，用grep而不用find -name选取名字，因为find选取名字时比较麻烦，对正则表达式支持不够，无法排除指定文件名。</p><h2 id="参考资料"><a href="#参考资料" class="headerlink" title="参考资料"></a>参考资料</h2><p>[1] <a href="https://blog.csdn.net/taiyang1987912/article/details/41488395">linux shell下除了某个文件外的其他文件全部删除的命令_乌托邦2号的博客-CSDN博客_linux删除除了某个文件的其他文件</a><br>[2] <a href="https://blog.csdn.net/youcijibi/article/details/103674402">rm -rf 排除指定文件夹或文件_youcijibi的博客-CSDN博客_rm 排除目录</a><br>[3] <a href="https://cloud.tencent.com/developer/article/1849817">Linux下使用rm删除文件，并排除指定文件 - 云+社区 - 腾讯云</a></p>]]></content>
<summary type="html"><p>我咋特别喜欢揪着不常用的命令花费大量时间死磕呢，不是一个好习惯。</p>
<h2 id="shell反向删除"><a href="#shell反向删除" class="headerlink" title="shell反向删除"></a>shell反向删除</h2><h3 i</summary>
<category term="shell" scheme="http://raolixiang-up.github.io/categories/shell/"/>
<category term="bash" scheme="http://raolixiang-up.github.io/tags/bash/"/>
</entry>
<entry>
<title>科研追踪001</title>
<link href="http://raolixiang-up.github.io/2022/05/04/%E7%A7%91%E7%A0%94%E8%BF%BD%E8%B8%AA001/"/>
<id>http://raolixiang-up.github.io/2022/05/04/%E7%A7%91%E7%A0%94%E8%BF%BD%E8%B8%AA001/</id>
<published>2022-05-04T08:28:59.000Z</published>
<updated>2022-10-15T06:06:21.400Z</updated>
<content type="html"><![CDATA[<p>搜集一下需要关注的课题组主页吧，会更新。</p><h2 id="研究类"><a href="#研究类" class="headerlink" title="研究类"></a>研究类</h2><ol><li><a href="http://www.jiawanghong.org/index.html">Jiawang Hong Research Group</a>—-自己所属课题组，必须关注</li><li><a href="https://ombe.nju.edu.cn/main.htm">氧化物分子束外延及电子结构表征实验室</a>—聂越峰老师课题组</li><li><a href="https://sites.google.com/site/zrfbuaa/home">Website of Dr. Ruifeng Zhang</a>—张瑞丰老师课题组</li><li><a href="https://crystal.nju.edu.cn/zh/">功能晶体材料实验室</a>—陈彦彬老师课题组</li><li><a href="http://www.comates.group/">Computational Materials Science Group : Wan-Jian Yin (尹万健) Group</a></li><li><a href="https://pld.nju.edu.cn/">PLD Lab</a>—刘俊明老师课题组</li><li><a href="https://physics.seu.edu.cn/sdong/">东南大学量子材料物理研究组-Welcome to the PQM Group</a>—董帅老师课题组</li><li><a href="https://www.labxing.com/lucheng">卢成课题组 | 中国地质大学（武汉） | LabXing</a></li><li><a href="https://stokes.byu.edu/stokes/stokes.html">Harold T. Stokes</a></li><li><a href="https://fenniegroup.org/">Fennie Group Materials Physics</a></li><li><a href="http://thermoelectrics.matsci.northwestern.edu/">Thermoelectrics at Northwestern</a></li><li><a href="https://www.x-mol.com/groups/ROuyang">欧阳润海课题组</a></li><li><a href="http://enlaigao.whu.edu.cn/">Home | Enlai Gao’s Webpage</a>—高恩来老师课题组</li><li><a href="https://zhangruanlab.com/people/">People – Zhang & Ruan Lab</a>—张远波和阮威课题组</li><li><a href="http://www.shuaigroup.net/">Home - shuaigroup</a>—帅志刚老师课题组</li><li><a href="https://people.sissa.it/~dalcorso/">Home page of Andrea Dal Corso</a>—Andrea Dal Corso课题组QE软件</li></ol><h2 id="工具类"><a href="#工具类" class="headerlink" title="工具类"></a>工具类</h2><ol><li><a href="https://harzing.com/home">Harzing.com</a>—文献情报搜索类，很多软件</li></ol>]]></content>
<summary type="html"><p>搜集一下需要关注的课题组主页吧，会更新。</p>
<h2 id="研究类"><a href="#研究类" class="headerlink" title="研究类"></a>研究类</h2><ol>
<li><a href="http://www.jiawanghong.</summary>
<category term="科研追踪" scheme="http://raolixiang-up.github.io/categories/%E7%A7%91%E7%A0%94%E8%BF%BD%E8%B8%AA/"/>
<category term="课题组" scheme="http://raolixiang-up.github.io/tags/%E8%AF%BE%E9%A2%98%E7%BB%84/"/>
</entry>
<entry>
<title>cohp的高通量计算002-爬取POSCAR</title>
<link href="http://raolixiang-up.github.io/2022/05/02/cohp%E7%9A%84%E9%AB%98%E9%80%9A%E9%87%8F%E8%AE%A1%E7%AE%97002/"/>
<id>http://raolixiang-up.github.io/2022/05/02/cohp%E7%9A%84%E9%AB%98%E9%80%9A%E9%87%8F%E8%AE%A1%E7%AE%97002/</id>
<published>2022-05-02T14:47:33.000Z</published>
<updated>2022-05-11T19:57:11.869Z</updated>
<content type="html"><![CDATA[<p>作了个大死，越是任务紧急越是东瞅西瞅，效率低到姥姥家。同时，在一些小点上竟然花费那么长时间了，一直卡bug。最后的成果就是能够通过mpid批量爬取数据。</p><h2 id="成果（通过mpid批量爬取数据）"><a href="#成果（通过mpid批量爬取数据）" class="headerlink" title="成果（通过mpid批量爬取数据）"></a>成果（通过mpid批量爬取数据）</h2><p>代码如下：</p><figure class="highlight bash"><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></pre></td><td class="code"><pre><span class="line">import pymatgen.core as mg</span><br><span class="line">from pymatgen.io.vasp import Poscar</span><br><span class="line">from pymatgen.ext.matproj import MPRester</span><br><span class="line">import csv</span><br><span class="line"></span><br><span class="line">with open(<span class="string">'structureid.csv'</span>,<span class="string">'r'</span>,encoding=<span class="string">'UTF-8-sig'</span>) as csv_file:</span><br><span class="line"> content = csv.reader(csv_file)</span><br><span class="line"> structure_id = list(content)[0]</span><br><span class="line"> <span class="built_in">print</span>(structure_id)</span><br><span class="line"> <span class="keyword">for</span> mpid <span class="keyword">in</span> structure_id:</span><br><span class="line"> mpr = MPRester(<span class="string">"API-MP"</span>)</span><br><span class="line"> strctr = mpr.get_structure_by_material_id(mpid)</span><br><span class="line"> poscar = Poscar(strctr)</span><br><span class="line"> poscar.write_file(<span class="string">'POSCAR_{0}'</span>.format(mpid))</span><br></pre></td></tr></table></figure><p>写了一点代码，因为已经知道所有mpid，因此就通过mpid来爬取POSCAR结构，但是有483个结构。因此，采用for循环遍历483个mpid。总不能一个一个输，因此采用读取csv文件的方式生成一个列表。这里，用到csv库的reader命令，然后我就在这里卡bug，走不动了。reader把每行都搞成一个列表，每行的元素直接逗号隔开，最终生成的列表中的元素都是行所组成的列表，for… in…无法遍历。<br>搜了很多资料，一开始都放弃csv文件转投text文件，折腾很久的原因就是自己对概念理解不清，一些关键的功能根本不知道 。最后采用以下步骤解决：<br>（1）csv中的mpid排列转为行排列（excel复制粘贴就可以，注意复制的区域和粘贴的区域大小一致）；<br>（2）采用structure_id = list(content)[0]，只提取第一行形成的数组；<br>（3）一个小细节就是encoding=’UTF-8-sig’，一定要加-sig，不然输出列表的第一个元素会有\ufeff特殊字符；<br>（4）盲目相信教程，列表中的单双引号都可以，我竟然作死去折腾把列表中的单引号转为双引号，当然以失败告终。<br>（5）从materials project爬取数据，把VPN关掉，使用conda或者pip安装一些包的时候也一样。血泪教训，目前搞不清为啥要关闭。<br>这样就完成了爬取数据，现在搞清楚了感觉很简单，但我搞了好久。分析一下原因：<br>（1）基本是参考别人的脚本，对python基础概念理解不清，关键细节更是只能通过搜索看到关键信息点才会有突破，本质就是解题思路不清晰；<br>（2）很要命的一点，就是反复死磕一个点，耗费太多精力发现是死胡同，还得另寻他路，不过也是在拼命搜索过程中找到岔路口；<br>（3）还有一点就是思路不清晰，搞多线程，同时尝试去解决很多个点，精力分散，结果就是按下葫芦浮起瓢。</p><h2 id="后续工作安排"><a href="#后续工作安排" class="headerlink" title="后续工作安排"></a>后续工作安排</h2><p>按照LobsterAutomation教程接下来就是atomate和FireWorks两个高通量软件的调用了，他们可以监控和检查计算结果。如果搞明白应该可以加快脚本书写进度。下面工作流程如下：<br>（1）解读调用的atomate的包<br>（2）解读调用的FireWorks包</p><h2 id="参考资料"><a href="#参考资料" class="headerlink" title="参考资料"></a>参考资料</h2><p>[1] <a href="https://atomate.org/index.html">atomate (Materials Science Workflows) — atomate 1.0.3 documentation</a><br>[2] <a href="https://materialsproject.github.io/fireworks/">Introduction to FireWorks (workflow software) — FireWorks 2.0.3 documentation</a><br>[3] <a href="https://pymatgen.org/">Introduction — pymatgen 2022.4.26 documentation</a><br>[4] <a href="https://www.cnblogs.com/zqifa/p/python-9.html">python去除\ufeff、\xa0、\u3000 - zqifa - 博客园</a></p>]]></content>
<summary type="html"><p>作了个大死，越是任务紧急越是东瞅西瞅，效率低到姥姥家。同时，在一些小点上竟然花费那么长时间了，一直卡bug。最后的成果就是能够通过mpid批量爬取数据。</p>
<h2 id="成果（通过mpid批量爬取数据）"><a href="#成果（通过mpid批量爬取数据）" cl</summary>
<category term="机器学习" scheme="http://raolixiang-up.github.io/categories/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/"/>
<category term="ML" scheme="http://raolixiang-up.github.io/tags/ML/"/>
</entry>
<entry>
<title>cohp的高通量计算001-基本工具</title>
<link href="http://raolixiang-up.github.io/2022/05/01/cohp%E7%9A%84%E9%AB%98%E9%80%9A%E9%87%8F%E8%AE%A1%E7%AE%97001/"/>
<id>http://raolixiang-up.github.io/2022/05/01/cohp%E7%9A%84%E9%AB%98%E9%80%9A%E9%87%8F%E8%AE%A1%E7%AE%97001/</id>
<published>2022-05-01T15:58:43.000Z</published>
<updated>2022-05-11T19:57:09.576Z</updated>
<content type="html"><![CDATA[<p>最近学习机器学习，第一个任务是关于数据挖掘和高通量计算，为机器学习准备素材，没有编程基础很难受，这一天浏览了python的基本操作，进行简单的算例模仿，工作还是没啥进展，先把用到的资料总结一下吧</p><h2 id="使用的工具"><a href="#使用的工具" class="headerlink" title="使用的工具"></a>使用的工具</h2><p>（1）jupyter notebook或者jupyter lab，jupyter lab我用的很不稳定，因此大量测试学习采用jupyter notebook;<br>（2）文本编辑器：BowPad，挺好用，可以替代notepad++。</p><h2 id="参考资料"><a href="#参考资料" class="headerlink" title="参考资料"></a>参考资料</h2><p>自己搜寻资料的能力太弱了，真的有待加强，基本都是大佬提供的</p><ol><li><a href="https://github.com/MasterLegend/PyML/tree/main/%E7%AC%AC06%E6%9C%9F%202022.04.25-04.29">PyML/第06期 2022.04.25-04.29 at main · MasterLegend/PyML</a></li><li><a href="https://hackingmaterials.lbl.gov/matminer/index.html">matminer (Materials Data Mining) — matminer 0.7.6 documentation</a></li><li><a href="https://materialsproject.org/dashboard">Materials Project</a></li><li><a href="https://github.com/JaGeo/LobsterAutomation">JaGeo/LobsterAutomation: This is a package to reproduce the publication on Lobster automation</a></li><li><a href="https://github.com/JaGeo/LobsterPy">JaGeo/LobsterPy: Package to automatically analyze Lobster runs</a></li><li><a href="https://pymatgen.org/">Introduction — pymatgen 2022.4.26 documentation</a></li><li><a href="https://wiki.fysik.dtu.dk/ase/index.html">Atomic Simulation Environment — ASE documentation</a></li><li><a href="https://zhuanlan.zhihu.com/p/470592188">ASE-LOBSTER联用进行批量COHP成键分析 - 知乎</a></li><li><a href="http://blog.wangruixing.cn/2019/06/12/pymatgen-api/">pymatgen API的使用-高通量计算初探 | 世事如棋</a></li></ol>]]></content>
<summary type="html"><p>最近学习机器学习，第一个任务是关于数据挖掘和高通量计算，为机器学习准备素材，没有编程基础很难受，这一天浏览了python的基本操作，进行简单的算例模仿，工作还是没啥进展，先把用到的资料总结一下吧</p>
<h2 id="使用的工具"><a href="#使用的工具" cla</summary>
<category term="机器学习" scheme="http://raolixiang-up.github.io/categories/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/"/>
<category term="ML" scheme="http://raolixiang-up.github.io/tags/ML/"/>
</entry>
<entry>
<title>Hexo个人博客(006)-评论系统设置</title>
<link href="http://raolixiang-up.github.io/2022/04/29/Hexo%E4%B8%AA%E4%BA%BA%E5%8D%9A%E5%AE%A2006-%E8%AF%84%E8%AE%BA%E7%B3%BB%E7%BB%9F%E8%AE%BE%E7%BD%AE/"/>
<id>http://raolixiang-up.github.io/2022/04/29/Hexo%E4%B8%AA%E4%BA%BA%E5%8D%9A%E5%AE%A2006-%E8%AF%84%E8%AE%BA%E7%B3%BB%E7%BB%9F%E8%AE%BE%E7%BD%AE/</id>
<published>2022-04-29T07:40:46.000Z</published>
<updated>2022-04-30T07:48:22.660Z</updated>
<content type="html"><![CDATA[<p>搭建完博客，希望能及时跟同行一起交流，所以鼓捣一下评论系统。</p><h2 id="问题检索"><a href="#问题检索" class="headerlink" title="问题检索"></a>问题检索</h2><p>搜索关键词“hexo pure 评论系统”，“hexo pure valine”</p><p>希望评论系统好用<br>希望评论系统好用+1<br>希望评论系统好用+2<br>希望评论系统好用+3<br>希望评论系统好用+4<br>希望评论系统好用+5<br>希望评论系统好用+6<br>希望评论系统好用+7<br>希望评论系统好用+8<br>希望评论系统好用+9<br>希望评论系统好用+10<br>希望评论系统好用+11<br>希望评论系统好用+12<br>希望评论系统好用+13<br>希望评论系统好用+14<br>希望评论系统好用+15<br>希望评论系统好用+16<br>希望评论系统好用+17<br>希望评论系统好用+18<br>希望评论系统好用+19<br>希望评论系统好用+20</p><h2 id="参考资料"><a href="#参考资料" class="headerlink" title="参考资料"></a>参考资料</h2><p>[1] <a href="https://hwame.top/20200520/hello-hexo-optimization.html">Hexo博客搭建(3)——优化评论系统 | 鴻塵</a><br>[2] <a href="https://hwame.top/20200520/hello-hexo-configuration.html">Hexo博客搭建(2)——主题配置 | 鴻塵</a><br>[3] <a href="https://zhuanlan.zhihu.com/p/149540221">Hexo博客使用valine评论系统无效果及终极解决方案 - 知乎</a><br>[4] <a href="https://valine.js.org/">介绍 | Valine 一款快速、简洁且高效的无后端评论系统</a></p>]]></content>
<summary type="html"><p>搭建完博客，希望能及时跟同行一起交流，所以鼓捣一下评论系统。</p>
<h2 id="问题检索"><a href="#问题检索" class="headerlink" title="问题检索"></a>问题检索</h2><p>搜索关键词“hexo pure 评论系统”，“h</summary>
<category term="hexo博客" scheme="http://raolixiang-up.github.io/categories/hexo%E5%8D%9A%E5%AE%A2/"/>
<category term="hexo" scheme="http://raolixiang-up.github.io/tags/hexo/"/>
</entry>
</feed>