<?xml version="1.0" encoding="utf-8" ?><rss version="2.0"><channel><title><![CDATA[Yao_Shi_Fighting的博客]]></title><description><![CDATA[]]></description><link>https://blog.youkuaiyun.com/Yao_Shi_Fighting</link><language>zh-cn</language><generator>https://blog.youkuaiyun.com/</generator><copyright><![CDATA[Copyright &copy; Yao_Shi_Fighting]]></copyright><item><title><![CDATA[VSCode编写Cython安装与配置]]></title><link>https://blog.youkuaiyun.com/Yao_Shi_Fighting/article/details/139441142</link><guid>https://blog.youkuaiyun.com/Yao_Shi_Fighting/article/details/139441142</guid><author>Yao_Shi_Fighting</author><pubDate>Tue, 04 Jun 2024 14:07:33 +0800</pubDate><description><![CDATA[然后新建一个，加入以下cl.exe的地址（一般是在这）“(安装根目录，根据你自己的位置改)\Microsoft Visual Studio\2022\Community\VC\Tools\MSVC\14.40.33807\bin\Hostx64\x64”，cl.exe就在这个目录下。如果已经有了，则更新至最新的地址，因为需要与C++ compiler的版本匹配。编写后缀为.pyx的文件后撰写对应的setup.py进行编译，可以得到.pyd结尾的动态链文件。点击做下角python"了解更多→"]]></description><category></category></item><item><title><![CDATA[MoviePy AudioFileClip.to_soundarray 报错 TypeError: arrays to stack must be passed as a “sequence“]]></title><link>https://blog.youkuaiyun.com/Yao_Shi_Fighting/article/details/139237611</link><guid>https://blog.youkuaiyun.com/Yao_Shi_Fighting/article/details/139237611</guid><author>Yao_Shi_Fighting</author><pubDate>Mon, 27 May 2024 16:19:01 +0800</pubDate><description><![CDATA[MoviePy AudioFileClip.to_soundarray 报错 TypeError: arrays to stack must be passed as a "sequence" type such as list or tuple 的解决方案.]]></description><category></category></item><item><title><![CDATA[使用H5py将MATLAB Cell嵌套Cell类型转化为Python数据类型 (列表list复合矩阵numpy.ndarray)]]></title><link>https://blog.youkuaiyun.com/Yao_Shi_Fighting/article/details/135541833</link><guid>https://blog.youkuaiyun.com/Yao_Shi_Fighting/article/details/135541833</guid><author>Yao_Shi_Fighting</author><pubDate>Fri, 12 Jan 2024 00:33:20 +0800</pubDate><description><![CDATA[如图中的all_to_all_indexes，是个1*26的Cell，点进入发现，每个Cell又是个维数不规则的n*26 Cell。此种情形，即所谓的Cell嵌套Cell。将MATLAB的Cell数据类型转化为Python类型非常繁琐，参考。如何将这一复杂数据结构转化为Python数据类型，非常令人头疼。每个Cell内部又是不均一的内容，如下。]]></description><category></category></item><item><title><![CDATA[H5py将MATLAB Cell对象转化为NumPy矩阵的方法 (Transform MATLAB Cell Object into NumPy matrix by utilizing h5py)]]></title><link>https://blog.youkuaiyun.com/Yao_Shi_Fighting/article/details/135504738</link><guid>https://blog.youkuaiyun.com/Yao_Shi_Fighting/article/details/135504738</guid><author>Yao_Shi_Fighting</author><pubDate>Wed, 10 Jan 2024 15:45:46 +0800</pubDate><description><![CDATA[需要转化为2588*26*26 numpy.ndarray实例。这篇文章介绍了 1*10 Cell的情况，我提供T*1的情况。]]></description><category></category></item><item><title><![CDATA[‘numpy.float64‘ object cannot be interpreted as an integer]]></title><link>https://blog.youkuaiyun.com/Yao_Shi_Fighting/article/details/126943681</link><guid>https://blog.youkuaiyun.com/Yao_Shi_Fighting/article/details/126943681</guid><author>Yao_Shi_Fighting</author><pubDate>Mon, 19 Sep 2022 22:41:14 +0800</pubDate><description><![CDATA[numpy.float64' object cannot be interpreted as an integer]]></description><category></category></item><item><title><![CDATA[plt.plot() marker 一览表 （散点图）]]></title><link>https://blog.youkuaiyun.com/Yao_Shi_Fighting/article/details/126875275</link><guid>https://blog.youkuaiyun.com/Yao_Shi_Fighting/article/details/126875275</guid><author>Yao_Shi_Fighting</author><pubDate>Thu, 15 Sep 2022 17:03:32 +0800</pubDate><description><![CDATA[plt.plot画散点图]]></description><category></category></item><item><title><![CDATA[快速 Pearson Correlation 计算]]></title><link>https://blog.youkuaiyun.com/Yao_Shi_Fighting/article/details/126626167</link><guid>https://blog.youkuaiyun.com/Yao_Shi_Fighting/article/details/126626167</guid><author>Yao_Shi_Fighting</author><pubDate>Wed, 31 Aug 2022 17:57:46 +0800</pubDate><description><![CDATA[利用numpy重写pearson相关性以缩减大规模运算的时间复杂度。]]></description><category></category></item><item><title><![CDATA[np.dot 浮点类型运算远快于整型运算]]></title><link>https://blog.youkuaiyun.com/Yao_Shi_Fighting/article/details/126559191</link><guid>https://blog.youkuaiyun.com/Yao_Shi_Fighting/article/details/126559191</guid><author>Yao_Shi_Fighting</author><pubDate>Sat, 27 Aug 2022 16:34:29 +0800</pubDate><description><![CDATA[np.dot()中np.ndarray数据的元素类型为浮点型（np.float, np.float32, np.float64）时运算速度远快于整型（np.int, np.int32, np.int64），且矩阵乘法两矩阵元素类型不一致速度也会变慢（但对于浮点类型运算而言这并非主要原因）...]]></description><category></category></item><item><title><![CDATA[Matplotlib 循环绘制图片内存、速率优化方法]]></title><link>https://blog.youkuaiyun.com/Yao_Shi_Fighting/article/details/125986535</link><guid>https://blog.youkuaiyun.com/Yao_Shi_Fighting/article/details/125986535</guid><author>Yao_Shi_Fighting</author><pubDate>Tue, 26 Jul 2022 02:43:05 +0800</pubDate><description><![CDATA[matplotlib 绘图速度、内存优化]]></description><category></category></item><item><title><![CDATA[Spikeforest2 用于 Spike Sorting 的尝试：模块安装、函数调用， 结果分析等]]></title><link>https://blog.youkuaiyun.com/Yao_Shi_Fighting/article/details/123266036</link><guid>https://blog.youkuaiyun.com/Yao_Shi_Fighting/article/details/123266036</guid><author>Yao_Shi_Fighting</author><pubDate>Wed, 08 Jun 2022 12:23:43 +0800</pubDate><description><![CDATA[前言

我手头的数据非常简单：

“单通道(Monotrode), 25,000Hz，1227264*1 的数组”

这是一个很简单的样本，并且清楚的知道这段sequence中只有两个神经元（因为这是某校计算神经科学课的作业）。这种情况下其实只需要设定Threshold为某特定值，即可区分出两个神经元（当然，是放电幅度有显著差异时）。但我想尝试一下其他的方法。



关于 Spikeforest2

这个方法来自文章：https://elifesciences.org/articles/55167，DOI:]]></description><category></category></item><item><title><![CDATA[No module named ‘brainpy‘]]></title><link>https://blog.youkuaiyun.com/Yao_Shi_Fighting/article/details/125181373</link><guid>https://blog.youkuaiyun.com/Yao_Shi_Fighting/article/details/125181373</guid><author>Yao_Shi_Fighting</author><pubDate>Wed, 08 Jun 2022 12:18:04 +0800</pubDate><description><![CDATA[brainpy的安装与No module named 'brainpy'问题的解决方案。]]></description><category></category></item><item><title><![CDATA[ERROR：Session/line number was not unique in database. History logging moved to new session.]]></title><link>https://blog.youkuaiyun.com/Yao_Shi_Fighting/article/details/124143496</link><guid>https://blog.youkuaiyun.com/Yao_Shi_Fighting/article/details/124143496</guid><author>Yao_Shi_Fighting</author><pubDate>Wed, 13 Apr 2022 11:32:03 +0800</pubDate><description><![CDATA[摘要：遇到此类错误，可以通过分段调试的方法找到引发错误的位置。]]></description><category></category></item><item><title><![CDATA[OpenCV.ml 决策树训练 Vector too long 的问题]]></title><link>https://blog.youkuaiyun.com/Yao_Shi_Fighting/article/details/119969023</link><guid>https://blog.youkuaiyun.com/Yao_Shi_Fighting/article/details/119969023</guid><author>Yao_Shi_Fighting</author><pubDate>Sat, 28 Aug 2021 16:00:12 +0800</pubDate><description><![CDATA[看 Machine Learning for OpenCV 4 second Edition, Aditya Sharma et al(中文名: 机器学习-使用OpenCV、Python和scikit-learn进行智能图像处理(原书第二版), 刘冰 译, 机械工业出版社)

5.2.1 P96

该章节是根据患者年龄、性别、血压、胆固醇浓度等因素(data)判断应当开什么药(target)的建立决策树的机器学习过程，代码在github是开源的，因此在这不加引用的给出：


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