<?xml version="1.0" encoding="utf-8" ?><rss version="2.0"><channel><title><![CDATA[enjoy_learn的博客]]></title><description><![CDATA[]]></description><link>https://blog.youkuaiyun.com/enjoy_learn</link><language>zh-cn</language><generator>https://blog.youkuaiyun.com/</generator><copyright><![CDATA[Copyright &copy; enjoy_learn]]></copyright><item><title><![CDATA[python 读取中文文件路径、文件内容]]></title><link>https://blog.youkuaiyun.com/enjoy_learn/article/details/102660939</link><guid>https://blog.youkuaiyun.com/enjoy_learn/article/details/102660939</guid><author>enjoy_learn</author><pubDate>Mon, 21 Oct 2019 17:15:09 +0800</pubDate><description><![CDATA[-- coding: utf-8 --
“”"
Created on Mon Oct 21 11:22:13 2019
功能：测试读取中文txt文件名，含中文字符串内容
@author: Acer201209
“”"
import pandas as pd
# 文件路径为中文处理
path1 ='D:\\XXXXXXXXXX_加速度.txt' 
path2 = 'XXXXXXXXXX_加速度.tx...]]></description><category></category></item><item><title><![CDATA[TensorBoard使用]]></title><link>https://blog.youkuaiyun.com/enjoy_learn/article/details/98992678</link><guid>https://blog.youkuaiyun.com/enjoy_learn/article/details/98992678</guid><author>enjoy_learn</author><pubDate>Fri, 09 Aug 2019 21:30:09 +0800</pubDate><description><![CDATA[from keras.callbacks import TensorBoard, ModelCheckpoint
from datetime import datetime
TIMESTAMP = "{0:%Y-%m-%dT%H-%M-%S/}".format(datetime.now())
train_log_dir = '/home/Predict/logs/train/' + TIMESTA...]]></description><category></category></item><item><title><![CDATA[ARMA-预测步骤]]></title><link>https://blog.youkuaiyun.com/enjoy_learn/article/details/98505946</link><guid>https://blog.youkuaiyun.com/enjoy_learn/article/details/98505946</guid><author>enjoy_learn</author><pubDate>Mon, 05 Aug 2019 18:20:37 +0800</pubDate><description><![CDATA[（1）数据剔除：找到2倍标准差外的数据；并用均值替代；
（2）去趋势、去周期；差分，矩形窗滤波；
（3）平稳性检验；autocorr;
（4）平稳序列去均值-&gt;零均值平稳序列；
（5）计算有偏、无偏自相关系数；
（6）计算偏相关系数；
根据自相关、偏相关确定拖尾性、截尾性、确定模型选择；-观察图形 or 函数 判断；

...]]></description><category></category></item><item><title><![CDATA[python  csv转json格式]]></title><link>https://blog.youkuaiyun.com/enjoy_learn/article/details/92704294</link><guid>https://blog.youkuaiyun.com/enjoy_learn/article/details/92704294</guid><author>enjoy_learn</author><pubDate>Mon, 17 Jun 2019 20:40:07 +0800</pubDate><description><![CDATA[参考网上资料，原创地址忘记…
import csv
import json
import pandas as pd
csvfile = open('x.csv','r')#,encoding="gbk",errors='ignore'
jsonfile = open('x.json','w')
namesss= pd.read_csv('x.csv')
fieldnames1=namesss.co...]]></description><category></category></item><item><title><![CDATA[python矩阵距离计算]]></title><link>https://blog.youkuaiyun.com/enjoy_learn/article/details/90783957</link><guid>https://blog.youkuaiyun.com/enjoy_learn/article/details/90783957</guid><author>enjoy_learn</author><pubDate>Tue, 04 Jun 2019 17:21:14 +0800</pubDate><description><![CDATA[源代码：July在线数据分析班第一讲大林老师讲解python运算速度时，曾举例到一矩阵计算速度的例子，不是python的运算速度慢，而是跟选取的方法有关，如都说C 比python快，但是用python多线程与C的单线程比，肯定是python快。
说矩阵计算的例子：正好工作中用到距离计算，试了下果然好用：

课程源代码：官网可去：https://www.julyedu.com/查询课程资料
例子代码...]]></description><category></category></item><item><title><![CDATA[CLAPACK库矩阵计算库使用]]></title><link>https://blog.youkuaiyun.com/enjoy_learn/article/details/90757178</link><guid>https://blog.youkuaiyun.com/enjoy_learn/article/details/90757178</guid><author>enjoy_learn</author><pubDate>Mon, 03 Jun 2019 19:03:34 +0800</pubDate><description><![CDATA[参考：官方http://www.netlib.org/clapack/
使用例子http://www.pianshen.com/article/5143103566/
matlab、python底层进行线性代数计算都调用了clapak的C的计算封装库；
利用C写矩阵的LU分解、SVD分解、求解特征值、求矩阵的逆等可用调用上述库进行计算；
首先下载：file CLAPACK-3.1.1-Visual...]]></description><category></category></item><item><title><![CDATA[matlab结构体数组获取变量名]]></title><link>https://blog.youkuaiyun.com/enjoy_learn/article/details/90750328</link><guid>https://blog.youkuaiyun.com/enjoy_learn/article/details/90750328</guid><author>enjoy_learn</author><pubDate>Mon, 03 Jun 2019 13:00:21 +0800</pubDate><description><![CDATA[sheetnames_nf=fieldnames(data.data);
name1=sheetnames_nf{1};
name2=sheetnames_nf{2};
normal_data=getfield(data.data,name1);

]]></description><category></category></item><item><title><![CDATA[振动]]></title><link>https://blog.youkuaiyun.com/enjoy_learn/article/details/90742455</link><guid>https://blog.youkuaiyun.com/enjoy_learn/article/details/90742455</guid><author>enjoy_learn</author><pubDate>Sun, 02 Jun 2019 19:33:48 +0800</pubDate><description><![CDATA[mooc-中国笔记
单自由度系统：
多自由度系统：
质量矩阵、刚度矩阵
固有频率，振型
主振型矩阵、模态矩阵；
正则振型：
多阶振动系统的固有频率、正则阵型、阻尼比；
理论分析、数值计算（有限元）、实验分析；

...]]></description><category></category></item><item><title><![CDATA[matlab 画图时日期格式坐标轴的处理]]></title><link>https://blog.youkuaiyun.com/enjoy_learn/article/details/90710981</link><guid>https://blog.youkuaiyun.com/enjoy_learn/article/details/90710981</guid><author>enjoy_learn</author><pubDate>Fri, 31 May 2019 09:54:11 +0800</pubDate><description><![CDATA[引自：http://blog.sina.com.cn/s/blog_6328ac360102wk5n.html
matlab作图时经常会遇到X轴为时间的情况，

查了下可用用datenum（）与datetick(‘x’,6);实现坐标轴的时间刻度绘制；


...]]></description><category></category></item><item><title><![CDATA[python-笔记]]></title><link>https://blog.youkuaiyun.com/enjoy_learn/article/details/88095519</link><guid>https://blog.youkuaiyun.com/enjoy_learn/article/details/88095519</guid><author>enjoy_learn</author><pubDate>Sun, 03 Mar 2019 22:37:44 +0800</pubDate><description><![CDATA[import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
fig = plt.figure()
ax = Axes3D(fig)
X = np.arange(-4, 4, 0.25)
Y = np.arange(-4, 4, 0.25)
X, Y = np.meshgrid(...]]></description><category></category></item><item><title><![CDATA[修改matlab读取文件夹名字顺序]]></title><link>https://blog.youkuaiyun.com/enjoy_learn/article/details/88050650</link><guid>https://blog.youkuaiyun.com/enjoy_learn/article/details/88050650</guid><author>enjoy_learn</author><pubDate>Fri, 01 Mar 2019 10:34:59 +0800</pubDate><description><![CDATA[dirOutput1=dir(fullfile(str_path,’*XX’));%匹配XX；
file_path_24=sortObj(dirOutput1);
function file=sortObj(file)
for i=1:length(file)
A{i}=file(i).name;
end
% [~, ind]=natsortfiles(A);
% [~, ind]=natsort...]]></description><category></category></item><item><title><![CDATA[相关计算xcorr]]></title><link>https://blog.youkuaiyun.com/enjoy_learn/article/details/85716523</link><guid>https://blog.youkuaiyun.com/enjoy_learn/article/details/85716523</guid><author>enjoy_learn</author><pubDate>Thu, 03 Jan 2019 20:03:43 +0800</pubDate><description><![CDATA[参考自：https://blog.youkuaiyun.com/u010592995/article/details/79841108
N=256;
di=20;
x1=test(1+di-10:N+di-10);%x1延后x2 10个点
x2=test(1+di:N+di)
时域相关计算：
N =length(x2);
[xc,zuobiao]= xcorr(x1,x2);
[k,ind] = max(xc...]]></description><category></category></item><item><title><![CDATA[matlab卷积]]></title><link>https://blog.youkuaiyun.com/enjoy_learn/article/details/85079177</link><guid>https://blog.youkuaiyun.com/enjoy_learn/article/details/85079177</guid><author>enjoy_learn</author><pubDate>Tue, 18 Dec 2018 20:57:21 +0800</pubDate><description><![CDATA[参考自：http://sepwww.stanford.edu/data/media/public/sep//prof/index.html
free book Earth Sounding Analysis Processing Vers.pdf
y0=x0b0;
y1=x1b0+x0b1;
y2=x2b0+x1b1+x0b2;
y3=x3b0+x2b1+x1*b2;
…
卷积定义：
functi...]]></description><category></category></item><item><title><![CDATA[envelope包络与findpeaks求极值点包络对比]]></title><link>https://blog.youkuaiyun.com/enjoy_learn/article/details/84728145</link><guid>https://blog.youkuaiyun.com/enjoy_learn/article/details/84728145</guid><author>enjoy_learn</author><pubDate>Sun, 02 Dec 2018 21:24:29 +0800</pubDate><description><![CDATA[matlab 自带函数：function [upperEnv,lowerEnv] = envelope(x, n, method)
函数可使用三种方式计算：如下matlab帮助文档：
%   [YUPPER,YLOWER] = ENVELOPE(X,N,ENVTYPE) specifies the type of envelope
%   to return. The default is 'an...]]></description><category></category></item><item><title><![CDATA[matlab画一个圆，并均分角度]]></title><link>https://blog.youkuaiyun.com/enjoy_learn/article/details/84572111</link><guid>https://blog.youkuaiyun.com/enjoy_learn/article/details/84572111</guid><author>enjoy_learn</author><pubDate>Tue, 27 Nov 2018 19:39:46 +0800</pubDate><description><![CDATA[作图画一个圆，并标注角度；
clc;clear
close all
R=1;
t=0:pi/20:2*pi;
x=R*cos(t);y=R*sin(t);
plot(x,y),axis equal
n=72;a=2*pi/n;
% for k=0:n-1
% hold on
% plot([-cos(pi+k*a),cos(pi+k*a)],[-sin(pi+k*a),sin(pi+k*a)]),...]]></description><category></category></item><item><title><![CDATA[matlab滤波器]]></title><link>https://blog.youkuaiyun.com/enjoy_learn/article/details/81138106</link><guid>https://blog.youkuaiyun.com/enjoy_learn/article/details/81138106</guid><author>enjoy_learn</author><pubDate>Fri, 20 Jul 2018 20:19:08 +0800</pubDate><description><![CDATA[懒得写了，贴这

function y=bandp(x,f1,f3,fsl,fsh,rp,rs,Fs) 
%带通滤波 
%使用注意事项：通带或阻带的截止频率与采样率的选取范围是不能超过采样率的一半 
%即，f1,f3,fs1,fsh,的值小于 Fs/2 
%x:需要带通滤波的序列 
% f 1：通带左边界100 
% f 3：通带右边界 
% fs1：衰减截止左边界 
% fsh：衰变截止右边界 ...]]></description><category></category></item><item><title><![CDATA[libsvm工具箱使用]]></title><link>https://blog.youkuaiyun.com/enjoy_learn/article/details/81137889</link><guid>https://blog.youkuaiyun.com/enjoy_learn/article/details/81137889</guid><author>enjoy_learn</author><pubDate>Fri, 20 Jul 2018 19:57:06 +0800</pubDate><description><![CDATA[Libsvm工具箱安装： 
https://www.csie.ntu.edu.tw/~cjlin/libsvm/  
下载：libsvm-3.2.22.zip包；放入matlab toolbox目录 
并执行： 
cd (‘D:\Program Files\MATLAB\R2012a\toolbox\libsvm-3.22\matlab’) 
mex -setup 
make

读入变量利用SVM...]]></description><category></category></item><item><title><![CDATA[关于fft相位]]></title><link>https://blog.youkuaiyun.com/enjoy_learn/article/details/80536159</link><guid>https://blog.youkuaiyun.com/enjoy_learn/article/details/80536159</guid><author>enjoy_learn</author><pubDate>Fri, 01 Jun 2018 12:49:19 +0800</pubDate><description><![CDATA[参考：这里写链接内容

angle与phase的区别：源地址： 
http://www.ilovematlab.cn/thread-259049-1-1.html

phase 和 angle 在输入为单个标量数据时，没有差别，二者都是用 atan2 函数来求输入数据的四象限辐角。但是对于向量或矩阵数据输入时，二者差别非常大。


phase 只支持标量和一维（行、列）向量输入，不支持二维或高维矩...]]></description><category></category></item><item><title><![CDATA[形态滤波]]></title><link>https://blog.youkuaiyun.com/enjoy_learn/article/details/80510112</link><guid>https://blog.youkuaiyun.com/enjoy_learn/article/details/80510112</guid><author>enjoy_learn</author><pubDate>Wed, 30 May 2018 14:54:13 +0800</pubDate><description><![CDATA[形态开闭运算　：抑制波形中的异常冲击；

matlab code:



function f_gg=kaibilvbo(f,g,flag_1)
%求f与g的开-闭滤波与闭-开滤波;，
%flag_1值为1代表开-闭滤波，flag_1值为2代表闭-开滤波,%幅值变低，
lengthf=length(f);
lengthg=length(g);
if flag_1=='1'
for n=1:leng...]]></description><category></category></item><item><title><![CDATA[滑动平均滤波]]></title><link>https://blog.youkuaiyun.com/enjoy_learn/article/details/80509866</link><guid>https://blog.youkuaiyun.com/enjoy_learn/article/details/80509866</guid><author>enjoy_learn</author><pubDate>Wed, 30 May 2018 14:42:05 +0800</pubDate><description><![CDATA[滑动平均滤波，窗口长度为6； 


matlab窗口长度6进行滤波，输入为512点，输出为507点，最后几个点未进行处理； 
滑动平均后，波形中的小波动消失； 


用于平滑噪声： 
matlab :code



function T1 = huadong( d_temp )
%UNTITLED Summary of this function goes here
%   Detailed ex...]]></description><category></category></item></channel></rss>