156 lines
5.6 KiB
Python
156 lines
5.6 KiB
Python
import numpy as np
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import os
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import tensorflow as tf
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'''
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class DataDeal1：
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这是一个处理data的类
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使用示例：DataDeal1(9, 'E:\data\DDS_data\平行齿轮箱齿轮齿根裂纹故障恒速\DATA')
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作用是将后缀为.dat的文件按节点个数(head)和加载的点数n的不同解析为(3,108,dim/108)维的文件
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需要传入的参数有：
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head:节点头数 int类型
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filename:放置.dat文件的根路径 string类型
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'''
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class DataDeal1(object):
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voiceArray = []
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def __init__(self, head, filename):
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self.head = head
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self.name = filename
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'''创建一个获取文件夹下所有后缀名为.dat得文件'''
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L = []
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for root, dir, filename in os.walk(self.name):
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for file in filename:
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if os.path.splitext(file)[1] == '.dat':
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L.append(file)
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self.array = L
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def __call__(self, head, filename, **kwargs):
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k = np.array(self.array)
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result = [[[] * self.head] * k.shape[0]]
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Z = []
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for file in self.array:
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# 构建文件名
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filename = self.name + '/' + file
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Z.append(filename)
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sum0 = [[] for i in range(self.head)]
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sum1 = [[] for i in range(self.head)]
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sum2 = [[] for i in range(self.head)]
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'''sum0=[None]*self.head
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sum1 = [None] * self.head
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sum2 = [None] * self.head
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for i in range(self.head):
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sum0[i] = [0]* 204800
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sum1[i] = [0]* 204800
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sum2[i] = [0]* 204800'''
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z = 0
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for filename in Z:
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# 将二进制文件读成np数组
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each_data = np.fromfile(filename, dtype=np.float32)
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data = np.array(each_data)
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# 创建一个二维空数组
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data_true = [[] for i in range(self.head)]
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# 数据按节点个数分成head个分别存入二维空数组的各行
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for i in range(self.head):
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data_true[i] = data[i::self.head]
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# 如果第一次是空数剧，则无法进行拼接
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if z == 0:
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sum0[i] = data_true[i]
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if z == 4:
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sum1[i] = data_true[i]
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if z == 8:
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sum2[i] = data_true[i]
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# 将二维空数组重新整合成np.array的形式
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data_true = np.array(data_true)
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if z % 12 == 0 or z % 12 == 1 or z % 12 == 2 or z % 12 == 3:
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if z != 0:
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sum0 = np.vstack((sum0, data_true))
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if z % 12 == 4 or z % 12 == 6 or z % 12 == 7 or z % 12 == 5:
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if z != 4:
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sum1 = np.vstack((sum1, data_true))
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if z % 12 == 9 or z % 12 == 10 or z % 12 == 11 or z % 12 == 8:
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if z != 8:
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sum2 = np.vstack((sum2, data_true))
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z = z + 1
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sum0 = np.array(sum0)
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sum1 = np.array(sum1)
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sum2 = np.array(sum2)
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print("sum0:", sum0.shape)
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print("sum1:", sum1.shape)
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print("sum2:", sum2.shape)
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return sum0, sum1, sum2
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'''
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class DataDeal2：
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这是一个处理data的类
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使用示例：DataDeal2(9, 'E:\data\DDS_data\平行齿轮箱齿轮齿根裂纹故障恒速\DATA')
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作用是将后缀为.dat的文件按节点个数(head)解析为(3*108,dim/108)维的文件
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需要传入的参数有：
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head:节点头数 int类型
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filename:放置.dat文件的根路径 string类型
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'''
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class DataDeal2(object):
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voiceArray = []
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def __init__(self, head, filename):
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self.head = head
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self.name = filename
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'''创建一个获取文件夹下所有后缀名为.dat得文件'''
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L = []
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for root, dir, filename in os.walk(self.name):
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for file in filename:
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if os.path.splitext(file)[1] == '.dat':
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L.append(file)
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self.array = L
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def __call__(self, head, filename, **kwargs):
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k = np.array(self.array)
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Z = []
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for file in self.array:
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# 构建文件名
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filename = self.name + '/' + file
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Z.append(filename)
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sum = [[] for i in range(k.shape[0]//self.head)]
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z = 0
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for filename in Z:
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# 将二进制文件读成np数组
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each_data = np.fromfile(filename, dtype=np.float32)
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data = np.array(each_data)
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# 创建一个二维空数组
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data_true = [[] for i in range(self.head)]
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# 数据按节点个数分成head个分别存入二维空数组的各行
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for i in range(self.head):
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data_true[i] = data[i::self.head]
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data_true = np.array(data_true)
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# 将二维空数组重新整合成np.array的形式
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data_true = data_true[1]
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data_true = np.array(data_true)
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# 创建一个二维空数组
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data_true_new=[[] for i in range(data_true.shape[0]//4096)]
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for i in range(data_true.shape[0]//4096):
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data_true_new[i] = data_true[i::data_true.shape[0]//4096]
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# 如果第一次是空数剧，则无法进行拼接
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if z == 0:
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sum = data_true_new
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data_true_new = np.array(data_true_new)
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# print(data_true_new.shape)
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if z != 0:
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sum = np.vstack((sum, data_true_new))
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z = z + 1
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sum = np.array(sum)
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print("sum:", sum.shape)
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return sum
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if __name__ == '__main__':
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data0 = DataDeal2(9, 'E:\data\DDS_data\平行齿轮箱齿轮齿根裂纹故障恒速\DATA')
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data = np.array(data0(9, 'E:\data\DDS_data\平行齿轮箱齿轮齿根裂纹故障恒速\DATA'))
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print("data:", data.shape)
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