Exemplo n.º 1
0
    def createWidgets(self):
        self.selectLabel = ttk.Label(self, text = "Select:")
        self.selectLabel.grid(column = 0, row = 0, padx = 10, pady = 5)
        self.select = Select(self, textvariable = self.selectVar)
        self.select.grid(column = 1, row = 0, sticky = (E, W))

        self.searchLabel = ttk.Label(self, text = "Search:")
        self.searchLabel.grid(column = 2, row = 0, padx = 10, pady = 5)
        self.search = Search(self, textvariable = self.searchVar)
        self.search.grid(column = 3, row = 0, sticky = (E, W))

        self.filestorage = FileStorage(self)
        self.filetree = FileTree(self)
        self.filetree.grid(column = 0, row = 1, rowspan = 4, sticky = (N, S, E, W), columnspan = 4)

        self.scrollbar = ttk.Scrollbar(self, orient = VERTICAL, command = self.filetree.yview)
        self.scrollbar.grid(column = 4, row = 1, rowspan = 4, sticky = (N, S, E))
        self.filetree.configure(yscrollcommand = self.scrollbar.set)

        self.tags = Tags(self)
        self.tags.grid(column = 5, row = 2, sticky = (E, W), padx = 5)

        self.tagsLab = ttk.Label(text = "Tags")
        self.tagsLab.grid(column = 5, row = 1, padx = 5, pady = 2)

        self.notes = Notes(self)
        self.notes.grid(column = 5, row = 4, sticky = (N, S, E, W), padx = 5)

        self.notesLab = ttk.Label(text = "Notes")
        self.notesLab.grid(column = 5, row = 3, padx = 5, pady = 2)

        self.scrollNotes = ttk.Scrollbar(self, orient = VERTICAL, command = self.notes.yview)
        self.scrollNotes.grid(column = 6, row = 4, sticky = (N, S, W))
        self.notes.configure(yscrollcommand = self.scrollNotes.set)

        self.buttons = Buttons(self)
        self.buttons.grid(row = 5, column = 0, columnspan = 5, pady = 5, sticky = (E, W))

        self.statusBar = StatusBar(self)
        self.statusBar.grid(row = 6, column = 0, columnspan = 5, padx = 5, pady = 5, sticky = (E, W))        
Exemplo n.º 2
0
    def cul_single(self, person):
        other1 = person.columns[1]
        target_ron = PredModel.predFunc(person.drop(other1, axis=1), 1)
        true_target = person.iloc[0, 0]
        print('本样本真实ron损失:', true_target)
        print('预测模型认为的ron损失', target_ron)
        print(
            '\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n'
        )

        # 初始化随机种群
        buildings = []
        value_record = []
        s_record = []
        best_param = [i * 0 for i in range(34)]
        percent_record = []
        # 20为种群内个体数
        for i in range(32):
            p = random.uniform(0.01, 0.99)
            temp = []
            for j in range(19):
                base_value = person.iloc[0, 2 + j]
                right_value = define.limit[j][1] - person.iloc[0, 2 + j]
                left_value = person.iloc[0, 2 + j] - define.limit[j][0]
                if random.randint(0, 1):
                    value = base_value + p * right_value
                else:
                    value = base_value - p * left_value
                # value = random.uniform(define.limit[j][0], define.limit[j][1])
                temp.append(value)
            for j in range(19, 30):
                temp.append(person.iloc[0, j + 2])
            buildings.append(temp)
        # 进化次数250次,建议不少于200次
        a = time.time()
        for i in range(1000):
            # 计算每个个体的适应度函数的值
            value, s_value = Fit(buildings, person).fitness()
            temp_min = min(value)
            value_record.append(temp_min)
            index = value.index(temp_min)
            temp_s = s_value[index]
            s_record.append(temp_s)
            reduce_percent = (target_ron - temp_min) / target_ron
            percent_record.append(reduce_percent)
            if reduce_percent > 0.301 and temp_s < 5:
                # if temp_min <= min(value_record) and temp_s < 5:
                #     best_param = [buildings[index], temp_min, reduce_percent, temp_s, i]
                best_param = buildings[index] + [
                    temp_min, reduce_percent, temp_s, i
                ]
                break
            print('本轮最小RON损失:', temp_min)
            print('RON损失降幅:{:.1f}%'.format(reduce_percent * 100))
            print('对应硫含量:', temp_s)
            print('================round', i, 'finished==================\n')
            # t用于存储最优个体的适应度,用以绘制最后的进化图像
            # record用于存储每次进化最优的个体,方便最后打印最优基因型
            # Select函数决定本代哪些个体可以活到下一代
            buildings_new = Select(buildings, value, s_value).selection()
            # 活下来的个体以0.7的概率进行交配产生子代,交配概率动态降低
            children = Cross(buildings_new,
                             self.cross_p *
                             max(1 - reduce_percent / 0.4, 0.1)).crossover()
            # 子代以0.3的基准概率基因突变,突变概率动态降低
            buildings = Mutate(
                children,
                self.mutate_p * max(1 - reduce_percent / 0.4, 0.1)).mutation()
        b = time.time()
        print(b - a)
        # print('\n最佳优化参数:', best_param[0], '\nRON损失:', best_param[1], '\n损失降幅:', best_param[2],
        #       '\n产品硫含量:', best_param[3], '\n所在轮次:', best_param[4])
        print(best_param)
        plt.title('RON损失值')
        plt.grid(ls='--')
        plt.xlabel("进化轮次", fontsize=14)
        plt.ylabel("RON损失", fontsize=14)
        plt.plot(value_record)
        # plt.show()

        plt.title('产品硫含量')
        plt.grid(ls='--')
        plt.xlabel("进化轮次", fontsize=14)
        plt.ylabel("硫含量", fontsize=14)
        plt.plot(s_record)
        # plt.show()

        plt.title('RON损失降低比率')
        plt.grid(ls='--')
        plt.xlabel("进化轮次", fontsize=14)
        plt.ylabel("降损比例", fontsize=14)
        plt.plot(percent_record)
        # plt.show()
        resultframe = pd.DataFrame([best_param])
        resultframe.to_csv('./result/opt_result.csv',
                           mode='a',
                           index=False,
                           header=None)
Exemplo n.º 3
0
prefer = input('请输入设计的传统性【0/1】:0为现代性强,1为传统性强: ')

t = []
record = []
# 进化次数250次,建议不少于200次
for i in range(250):
    # 计算每个个体的适应度函数的值
    value = Fit(buildings, rain, land, money, location, prefer).fitness()
    temp_max = max(value)
    # t用于存储最优个体的适应度,用以绘制最后的进化图像
    t.append(temp_max)
    index = value.index(temp_max)
    # record用于存储每次进化最优的个体,方便最后打印最优基因型
    record.append(buildings[index])
    # Select函数决定本代哪些个体可以活到下一代
    buildings_new = Select(buildings, value).selection()
    # 活下来的个体以0.7的概率进行交配产生子代(交叉概率0.7)
    children = Cross(buildings_new, 0.7).crossover()
    # 子代以0.02的概率基因突变
    buildings = Mutate(children, 0.02).mutation()

# 提取最优解的基因型
value_max = Fit(record, rain, land, money, location, prefer).fitness()
temp_max = max(value_max)
index = value_max.index(temp_max)
# 把最优解的基因型从数字编码翻译成题设给的字母,打印输出
result = translate(record[index])
print('最优解的基因型为:', result)

# 输出收敛过程及最大值的函数图像
plt.plot(t)
Exemplo n.º 4
0
class GUI(Tk):
    "represents GUI"
    def __init__(self):
        super().__init__()
   
        self.option_add("*tearOff", FALSE)
        self.initialized = False
        self.title("Papyer")
        
        x, y = 1500, 500
        self.minsize(x, y)
        placeWindow(self, x, y)
        
        self.options = Options(self)
        self["menu"] = TopMenu(self)        

        self.protocol("WM_DELETE_WINDOW", self.closeFun)

        self.base = os.getcwd()

        self.selectVar = StringVar()
        self.searchVar = StringVar()

        self.createWidgets()

        self.columnconfigure(1, weight = 1)
        self.columnconfigure(3, weight = 1)
        self.columnconfigure(5, weight = 1)
        self.rowconfigure(4, weight = 1)

        self.bind("<Control-d>", lambda e: self.filetree.keepDuplicates())
        self.bind("<Control-a>", lambda e: self.filetree.selectAll())
        
        self.mainloop()



    def refresh(self):
        # do in a smarter way - check changes in the files
        self.filestorage.save()
        self.filetree.saveSettings()
        selected = self.filetree.selection()
        self.createWidgets()
        self.filetree.selection_set(selected)


    def createWidgets(self):
        self.selectLabel = ttk.Label(self, text = "Select:")
        self.selectLabel.grid(column = 0, row = 0, padx = 10, pady = 5)
        self.select = Select(self, textvariable = self.selectVar)
        self.select.grid(column = 1, row = 0, sticky = (E, W))

        self.searchLabel = ttk.Label(self, text = "Search:")
        self.searchLabel.grid(column = 2, row = 0, padx = 10, pady = 5)
        self.search = Search(self, textvariable = self.searchVar)
        self.search.grid(column = 3, row = 0, sticky = (E, W))

        self.filestorage = FileStorage(self)
        self.filetree = FileTree(self)
        self.filetree.grid(column = 0, row = 1, rowspan = 4, sticky = (N, S, E, W), columnspan = 4)

        self.scrollbar = ttk.Scrollbar(self, orient = VERTICAL, command = self.filetree.yview)
        self.scrollbar.grid(column = 4, row = 1, rowspan = 4, sticky = (N, S, E))
        self.filetree.configure(yscrollcommand = self.scrollbar.set)

        self.tags = Tags(self)
        self.tags.grid(column = 5, row = 2, sticky = (E, W), padx = 5)

        self.tagsLab = ttk.Label(text = "Tags")
        self.tagsLab.grid(column = 5, row = 1, padx = 5, pady = 2)

        self.notes = Notes(self)
        self.notes.grid(column = 5, row = 4, sticky = (N, S, E, W), padx = 5)

        self.notesLab = ttk.Label(text = "Notes")
        self.notesLab.grid(column = 5, row = 3, padx = 5, pady = 2)

        self.scrollNotes = ttk.Scrollbar(self, orient = VERTICAL, command = self.notes.yview)
        self.scrollNotes.grid(column = 6, row = 4, sticky = (N, S, W))
        self.notes.configure(yscrollcommand = self.scrollNotes.set)

        self.buttons = Buttons(self)
        self.buttons.grid(row = 5, column = 0, columnspan = 5, pady = 5, sticky = (E, W))

        self.statusBar = StatusBar(self)
        self.statusBar.grid(row = 6, column = 0, columnspan = 5, padx = 5, pady = 5, sticky = (E, W))        
        

    def closeFun(self):
        "ask for saving files on exit"
        self.filetree.saveSettings()
        self.filestorage.save()
        self.options.save()
        self.destroy()
Exemplo n.º 5
0
bestsIndividuos = [[], []]
bestsIndividuosCrossing = [[], []]
individuoMutation = [[], []]
fits = []
fit1 = []
fit2 = []
porcent = 3
meta = 28
quantGenes = 36
quantIndividuos = 100
geracao = 300
contGeracao = 0
melhorFit1 = 0
melhorFit2 = 0
individuo = Population()
selecao = Select()


def convert_bin(listaBits):

    copylistaBits = listaBits.copy()
    copylistaBits.reverse()
    new_list = []
    count = 0
    decimal = 0
    newlist = []
    base = 0
    for bit in copylistaBits:
        base = bit * 2
        if base != 0:
            decimal = decimal + base**count