#!/bin/env python 3.6 # -*- encoding: utf-8 -*- #============================================================================== # Author: 胡伟锋 # Created: 2018-06-22 # Version: 2.1.0 # E-mail: [email protected] # Purpose: {建文件夹；txt转csv；分割；裁剪；均值；去背景；归一化；降维；生成标签} #============================================================================== #import sys #sys.setrecursionlimit(1000000000) import mlAPI as api import mlFunctions as f import data_information as di disi = di.SampleInformation() #================================GUI参数绑定==================================== #定义传入参数 #txt_dir="\\原始数据20170417" txt_dir = "\\Null" #back数据 back_data_s = 'n' back_data_e = 'n' back_data = [] #sample数据 sample_data_s = 'n' sample_data_e = 'n' sample_data = [] #通道数据 channel_s = 'n' channel_e = 'n'
from sklearn.model_selection import cross_val_score
from sklearn.decomposition import PCA
from sklearn.decomposition import NMF
from sklearn.decomposition import LatentDirichletAllocation
from sklearn.decomposition import IncrementalPCA
from sklearn.preprocessing import label_binarize
from sklearn.metrics import confusion_matrix
from sklearn.metrics import classification_report
from sklearn.metrics import cohen_kappa_score
from sklearn.metrics import matthews_corrcoef
from sklearn.metrics import roc_curve, auc
from sklearn.metrics import precision_recall_curve
from sklearn.metrics import average_precision_score
#导入前置信息，后续若要进一步重构代码可考虑从此处入手
import data_information
disi=data_information.SampleInformation()
class FolderProcessing():
"""1.创建、删除文件夹，用于分类存放数据(file)、图表(graph)"""
def __init__(self):
self.folder_1="file_output\\"#输出并行file
self.folder_2="file_temp\\"#输出临时串行file
self.folder_3="graph_output\\"#输出评估结果图
self.folder_4="graph_demo\\"#分析时临时绘图
#自动建立文件夹以存放文件。
def create_folder(self,path):
folder = os.path.exists(path)
#判断是否存在文件夹,不存在则创建
if not folder:
os.makedirs(path)