import numpy as np
import os
import tensorflow as tf

'''
class DataDeal1：
这是一个处理data的类
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')
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
需要传入的参数有：
head:节点头数   int类型
filename:放置.dat文件的根路径   string类型
'''


class DataDeal1(object):
    voiceArray = []

    def __init__(self, head, filename):
        self.head = head
        self.name = filename
        '''创建一个获取文件夹下所有后缀名为.dat得文件'''
        L = []
        for root, dir, filename in os.walk(self.name):
            for file in filename:
                if os.path.splitext(file)[1] == '.dat':
                    L.append(file)
        self.array = L

    def __call__(self, head, filename, **kwargs):
        k = np.array(self.array)
        result = [[[] * self.head] * k.shape[0]]
        Z = []
        for file in self.array:
            # 构建文件名
            filename = self.name + '/' + file
            Z.append(filename)
        sum0 = [[] for i in range(self.head)]
        sum1 = [[] for i in range(self.head)]
        sum2 = [[] for i in range(self.head)]
        '''sum0=[None]*self.head
        sum1 = [None] * self.head
        sum2 = [None] * self.head
        for i in range(self.head):
            sum0[i] = [0]* 204800
            sum1[i] = [0]* 204800
            sum2[i] = [0]* 204800'''
        z = 0
        for filename in Z:
            # 将二进制文件读成np数组
            each_data = np.fromfile(filename, dtype=np.float32)
            data = np.array(each_data)
            # 创建一个二维空数组
            data_true = [[] for i in range(self.head)]
            # 数据按节点个数分成head个分别存入二维空数组的各行
            for i in range(self.head):
                data_true[i] = data[i::self.head]
                # 如果第一次是空数剧，则无法进行拼接
                if z == 0:
                    sum0[i] = data_true[i]
                if z == 4:
                    sum1[i] = data_true[i]
                if z == 8:
                    sum2[i] = data_true[i]
            # 将二维空数组重新整合成np.array的形式
            data_true = np.array(data_true)
            if z % 12 == 0 or z % 12 == 1 or z % 12 == 2 or z % 12 == 3:
                if z != 0:
                    sum0 = np.vstack((sum0, data_true))
            if z % 12 == 4 or z % 12 == 6 or z % 12 == 7 or z % 12 == 5:
                if z != 4:
                    sum1 = np.vstack((sum1, data_true))
            if z % 12 == 9 or z % 12 == 10 or z % 12 == 11 or z % 12 == 8:
                if z != 8:
                    sum2 = np.vstack((sum2, data_true))
            z = z + 1
        sum0 = np.array(sum0)
        sum1 = np.array(sum1)
        sum2 = np.array(sum2)
        print("sum0:", sum0.shape)
        print("sum1:", sum1.shape)
        print("sum2:", sum2.shape)
        return sum0, sum1, sum2


'''
class DataDeal2：
这是一个处理data的类
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')
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
需要传入的参数有：
head:节点头数   int类型
filename:放置.dat文件的根路径   string类型
'''


class DataDeal2(object):
    voiceArray = []

    def __init__(self, head, filename):
        self.head = head
        self.name = filename
        '''创建一个获取文件夹下所有后缀名为.dat得文件'''
        L = []
        for root, dir, filename in os.walk(self.name):
            for file in filename:
                if os.path.splitext(file)[1] == '.dat':
                    L.append(file)
        self.array = L

    def __call__(self, head, filename, **kwargs):
        k = np.array(self.array)
        Z = []
        for file in self.array:
            # 构建文件名
            filename = self.name + '/' + file
            Z.append(filename)
        sum = [[] for i in range(self.head)]
        z = 0
        for filename in Z:
            # 将二进制文件读成np数组
            each_data = np.fromfile(filename, dtype=np.float32)
            data = np.array(each_data)
            # 创建一个二维空数组
            data_true = [[] for i in range(self.head)]
            # 数据按节点个数分成head个分别存入二维空数组的各行
            for i in range(self.head):
                data_true[i] = data[i::self.head]
                # 如果第一次是空数剧，则无法进行拼接
                if z == 0:
                    sum[i] = data_true[i]
            # 将二维空数组重新整合成np.array的形式
            data_true = np.array(data_true)
            if z != 0:
                sum = np.vstack((sum, data_true))
            z = z + 1
        sum = np.array(sum)
        print("sum:", sum.shape)
        return sum