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Copy pathfsGUI.py
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156 lines (134 loc) · 6.46 KB
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# -*- coding: utf-8 -*-
from Tkinter import *
import tkFileDialog as tkfile
import os
import tkMessageBox
import pandas as pd
from PIL import Image, ImageTk
from alg514 import *
from paperlib import *
from autoWeight import *
class FeatureSelection():
def __init__(self, master):
self.weight_list = [2,3,1]
# set up the main frame
self.parent = master
self.parent.title("Feature Selection")
self.frame = Frame(self.parent)
self.frame.pack(fill = BOTH, expand = 1)
# self.frame.pack()
# self.parent.resizable(width = FALSE, height = FALSE)
self.menubar = Menu(self.parent)
self.algorithms = None
#创建下拉菜单File，然后将其加入到顶级的菜单栏中
self.algmenu = Menu(self.menubar,tearoff=0)
self.algmenu.add_command(label="KMeans", command=self.alg1)
self.algmenu.add_command(label="ReliefF", command=self.alg2)
self.algmenu.add_command(label="MI", command=self.alg3)
self.algmenu.add_command(label="Ensemble", command=self.alg4)
self.menubar.add_cascade(label="算法", menu=self.algmenu)
self.parent.config(menu=self.menubar)
self.label = Label(self.frame, text = "原始数据集路径:")
self.label.grid(row = 0, column = 0, sticky = W, padx = 10)
self.entry = Listbox(self.frame, height = 1,width=50)
self.entry.grid(row = 0, column = 1, sticky = W)
# self.loadButton = Button(self.frame, text = "Load dataSet", width = 10)
self.loadButton = Button(self.frame, text = "设置", width = 20, command = self.LoadDataDir)
self.loadButton.grid(row = 0, column = 2, sticky = W+E, padx = 20, pady = 5)
self.label2 = Label(self.frame, text = "结果数据集输出路径:")
self.label2.grid(row = 1, column = 0, sticky = W, padx = 10)
self.entry2 = Listbox(self.frame, height = 1,width=50)
self.entry2.grid(row = 1, column = 1, sticky = W)
self.loadButton = Button(self.frame, text = "设置", width = 10, command = self.OutDataDir)
self.loadButton.grid(row = 1, column = 2, sticky = W+E, padx = 20, pady = 5)
self.bboxlabel = Label(self.frame, text = "提取特征数目:")
self.bboxlabel.grid(row = 2, column = 0, sticky = W,padx = 10)
self.entrylabel = Entry(self.frame, width = 50,textvariable=StringVar())
self.entrylabel.grid(row = 2,column = 1, sticky = W, padx = 0)
self.loadButton = Button(self.frame, text = "确定", width = 10, command = self.getFeatureNum)
self.loadButton.grid(row = 2, column = 2, sticky = W+E, padx = 20, pady = 5)
self.loadButton = Button(self.frame, text = "绘制参考曲线", width = 35, command = self.save_plotImage)
self.loadButton.grid(row = 3,column=1,sticky = W+E, padx = 20, pady = 5)
self.loadButton = Button(self.frame, text = "输出结果特征文件", width = 2,command = self.algorithms)
self.loadButton.grid(row = 4,column=1,sticky = W+E, padx = 20, pady = 5)
def alg1(self):
self.algorithms = "kmeans"
tkMessageBox.showinfo("Warning","选择的特征选择算法是:KMeans")
def alg2(self):
self.algorithms = "relieff"
tkMessageBox.showinfo("Warning","选择的特征选择算法是:ReliefF")
def alg3(self):
self.algorithms = "mi"
tkMessageBox.showinfo("Warning","选择的特征选择算法是:MI")
def alg4(self):
self.algorithms = "ensemble"
tkMessageBox.showinfo("Warning","选择的特征选择算法是:ensemble")
def save_plotImage(self):
weightList = self.weight_list
datapath = self.datadir
alg_name = self.algorithms
plot_image(datapath,alg_name,weightList)
# self.LoadImage()
def LoadImage(self):
window =Toplevel()
window.title('picture result')
canvas = Canvas(window,cursor = "tcross", width=500,height=500)
canvas.pack(expand=YES,fill=BOTH)
imagepath = './test.png'
pro_image = Image.open(imagepath)
self.cur_img = ImageTk.PhotoImage(pro_image)
canvas.create_image(0, 0,image = self.cur_img, anchor = NW)
def LoadDataDir(self):
self.datadir = tkfile.askopenfilename()
self.entry.insert(0, self.datadir)
self.LoadData()
def LoadData(self):
datapath = self.datadir
# tkMessageBox.showinfo('imageMessage',datapath)
df = pd.read_csv(datapath,header=None)
featureNum = int(len(df.columns)-1)
tkMessageBox.showinfo("Warning","数据集一共有%d个特征,请输入小于%d的特征数目"%(featureNum,featureNum))
def OutDataDir(self):
self.dataoutdir = tkfile.askdirectory()
self.entry2.insert(0, self.dataoutdir)
tkMessageBox.showinfo('imageMessage',self.dataoutdir)
def getFeatureNum(self):
self.featureNum = self.entrylabel.get()
tkMessageBox.showinfo('特征选择数目',self.featureNum)
def algorithms(self):
fsNumStr = str(self.featureNum)
fsNum = int(self.featureNum)
dataPath = self.datadir
algorithms = self.algorithms
weightList = self.weight_list
outName = str(dataPath)
outName = outName.split('/')[-1]
outName = outName.split('.')[0]
# print outName
outPath = self.dataoutdir
outPath = os.path.join(outPath,'%s_%s_%s.csv'%(outName,algorithms,fsNumStr))
if(algorithms=="kmeans"):
y,topN = gen_evalList(dataPath,fsNum)
if(algorithms=="relieff"):
y,topN = fsReliefF(dataPath,fsNum)
if(algorithms=="mi"):
y,topN = fsMI(dataPath,fsNum)
if(algorithms=="ensemble"):
y,topN = fsEnsemble(dataPath,weightList,fsNum)
df = pd.read_csv(dataPath,header=None)
arraySelected = df.values[:,topN+[-1]] # contain the features and the label
# print arraySelected
outFile = open(outPath,'w')
lineLen = len(arraySelected[0])
for line in arraySelected:
for i in range(lineLen):
if(i==lineLen-1):
outFile.write(str(line[i])+'\n')
else:
outFile.write(str(line[i])+',')
outFile.close()
tkMessageBox.showinfo('Message','successful!')
if __name__ == "__main__":
root = Tk()
tool = FeatureSelection(root)
root.mainloop()