西儲大學軸承故障數據 python3使用

轉載於：參考鏈接
西儲大學軸承故障數據官網
python2 版本 cwru庫github地址
Github數據下載地址
python2 可以直接安裝使用CWRU庫，該庫的功能是下載數據，並且切分成可供訓練和評估的訓練集和測試集數據

python2安裝方式：

pip安裝：

$ pip install --user cwru

github下載源代碼安裝:
`$ python setup.py install
使用

import cwru
data = cwru.CWRU("12DriveEndFault", "1797", 384)

可以使用data.X_train, data.y_train, data.X_test, data.y_test, data.labels, data.nclasses 來訓練和評估模型

CWRU的參數：

exp：‘12DriveEndFault’, ‘12FanEndFault’, ‘48DriveEndFault’

rpm：‘1797’, ‘1772’, ‘1750’, ‘1730’

length：信號的長度

python3版本：

由於python3 和python2 版本的差異，對原python2代碼修改：
這產生的路徑名和原文不同 生成到項目目錄下

import os
import glob
import errno
import random
import urllib.request as urllib
import numpy as np
from scipy.io import loadmat


class CWRU:
    def __init__(self, exp, rpm, length):
        if exp not in ('12DriveEndFault', '12FanEndFault', '48DriveEndFault'):
            print("wrong experiment name: {}".format(exp))
            exit(1)
        if rpm not in ('1797', '1772', '1750', '1730'):
            print("wrong rpm value: {}".format(rpm))
            exit(1)
        # root directory of all data
        rdir = os.path.join('Data/CWRU')
        print(rdir)
        fmeta = os.path.join(os.path.dirname(__file__), 'metadata.txt')
        all_lines = open(fmeta).readlines()
        lines = []
        for line in all_lines:
            l = line.split()
            if (l[0] == exp or l[0] == 'NormalBaseline') and l[1] == rpm:
                lines.append(l)
        self.length = length  # sequence length
        self._load_and_slice_data(rdir, lines)
        # shuffle training and test arrays
        self._shuffle()
        self.labels = tuple(line[2] for line in lines)
        self.nclasses = len(self.labels)  # number of classes

    def _mkdir(self, path):
        try:
            os.makedirs(path)
        except OSError as exc:
            if exc.errno == errno.EEXIST and os.path.isdir(path):
                pass
            else:
                print("can't create directory '{}''".format(path))
                exit(1)

    def _download(self, fpath, link):
        print("Downloading to: '{}'".format(fpath))
        urllib.URLopener().retrieve(link, fpath)

    def _load_and_slice_data(self, rdir, infos):
        self.X_train = np.zeros((0, self.length))
        self.X_test = np.zeros((0, self.length))
        self.y_train = []
        self.y_test = []
        for idx, info in enumerate(infos):

            # directory of this file
            fdir = os.path.join(rdir, info[0], info[1])
            self._mkdir(fdir)
            fpath = os.path.join(fdir, info[2] + '.mat')
            if not os.path.exists(fpath):
                self._download(fpath, info[3].rstrip('\n'))

            mat_dict = loadmat(fpath)
            # key = filter(lambda x: 'DE_time' in x, mat_dict.keys())[0]
            fliter_i = filter(lambda x: 'DE_time' in x, mat_dict.keys())
            fliter_list = [item for item in fliter_i]
            key = fliter_list[0]
            time_series = mat_dict[key][:, 0]
            idx_last = -(time_series.shape[0] % self.length)
            clips = time_series[:idx_last].reshape(-1, self.length)
            n = clips.shape[0]
            n_split = int((3 * n / 4))
            self.X_train = np.vstack((self.X_train, clips[:n_split]))
            self.X_test = np.vstack((self.X_test, clips[n_split:]))
            self.y_train += [idx] * n_split
            self.y_test += [idx] * (clips.shape[0] - n_split)

    def _shuffle(self):
        # shuffle training samples
        index = list(range(self.X_train.shape[0]))
        random.Random(0).shuffle(index)
        self.X_train = self.X_train[index]
        self.y_train = tuple(self.y_train[i] for i in index)

        # shuffle test samples
        index = list(range(self.X_test.shape[0]))
        random.Random(0).shuffle(index)
        self.X_test = self.X_test[index]
        self.y_test = tuple(self.y_test[i] for i in index)

由於下載出現302錯誤，所以自己打包下載了相關鏈接中的所有數據並且進行了數據轉換

#include <bits/stdc++.h>
#include <io.h>
#include <string>
#include <vector>
#include <fstream>
using namespace std;
char a[100],b[100],c[100],d[100];
void getAllFiles(string path, vector<string>& files)
{
    // 文件句柄
    long hFile = 0;
    // 文件信息
    struct _finddata_t fileinfo;

    string p;

    if ((hFile = _findfirst(p.assign(path).append("\\*").c_str(), &fileinfo)) != -1)
    {
        do
        {
            // 保存文件的全路徑
            files.push_back(p.assign(path).append("\\").append(fileinfo.name));

        }
        while (_findnext(hFile, &fileinfo) == 0);   //尋找下一個，成功返回0，否則-1

        _findclose(hFile);
    }
}
void make_dir(string dir)
{
    if (_access(dir.c_str(), 0) == -1)
    {
        cout << dir << " is not existing" << endl;
        int flag = _mkdir(dir.c_str());

        if (flag == 0)
        {
            cout << "make successfully" << endl;
        }
        else
        {
            cout << "make fsiled" << endl;
        }
    }
    else if (_access(dir.c_str(), 0) == 0)
    {
        cout << dir << " exists" << endl;
    }
    else
    {
        cout<<"erro!"<<endl;
    }
}

int CopyFile(string SourceFile,string NewFile)
{
    ifstream in;
    ofstream out;
    in.open(SourceFile,ios::binary);//打開源文件
    if(in.fail())//打開源文件失敗
    {
        cout<<"Error 1: Fail to open the source file."<<endl;
        in.close();
        out.close();
        return 0;
    }
    out.open(NewFile,ios::binary);//創建目標文件
    if(out.fail())//創建文件失敗
    {
        cout<<"Error 2: Fail to create the new file."<<endl;
        out.close();
        in.close();
        return 0;
    }
    else//複製文件
    {
        out<<in.rdbuf();
        out.close();
        in.close();
        return 1;
    }
}

int main()
{
    freopen("metadata.txt","r",stdin);
    int count1 = 0,count2 =0;
    while(scanf("%s %s %s %s",&a,&b,&c,&d)!=EOF)
    {
        count2++;
        int len=strlen(d),x=0;
        for(int i=0; i<len; i++)
            if(d[i]<='9' && d[i] >='0')
                x=x*10+d[i]-'0';
        string A=string(a),B=string(b),C=string(c);
        cout<<A<<" "<<B<<" "<<C<<" "<<x<<endl;
        string filePath1 = "D:\\ACM_CODE\\ACMtask\\data";
        string filePath2 = "D:\\ACM_CODE\\ACMtask\\datas";
        vector<string> temp;
        int y=0;
        getAllFiles(filePath1, temp);
        for (int i = 0; i < temp.size(); i++ )
        {
            y=0;
            //  cout<<i<<"  "<<temp[i]<<endl;
            for(int j=0; j<temp[i].length(); j++)
            {
                if(temp[i][j] >= '0' && temp[i][j] <= '9')
                    y=y*10+temp[i][j]-'0';
                else if(temp[i][j] =='.' && temp[i][j+1] =='m' &&
                        temp[i][j+2] =='a' && temp[i][j+3] =='t')
                {
                    break;
                }
                else
                    y=0;
            }
            if(x == y)
            {
                y=i;
                break;
            }
        }
        cout<<y<<"  "<<temp[y]<<endl;
        string dir=filePath2+"\\"+A;
        make_dir(dir);
        dir=dir+"\\"+B;
        make_dir(dir);
        string source=temp[y];
        string NewFile=dir+"\\"+C+".mat";
        if(CopyFile(source,NewFile))
        {
            cout<<"文件已成功複製..."<<endl;
            count1++;
        }
        else
        {
            cout<<"文件複製失敗..."<<endl;

        }
    }
    printf("YES %d %d\n",count1,count2);
    return 0;
}

這裏提供下載分類好的數據集合
下載鏈接