/
gamain.py
executable file
·717 lines (594 loc) · 28.6 KB
/
gamain.py
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#!/usr/bin/env python3
from gi.repository import Gtk, Gdk, GObject
from gi.repository.GdkPixbuf import Pixbuf
import matplotlib.pyplot as plt
import threading
from perceptron import *
import numpy as np
from data_proc import data_proc as dp
from ploting import paper
from racing_map import racing_map
from matplotlib import colors
from racing_map import *
from ga import rbfn
import time
import copy
# color = ["r","b","g","c","m","y","k","w"]
class myDict(dict):
def __init__(self):
self = dict()
def add(self, key, value):
self[key] = value
UI_INFO = """
<ui>
<menubar name='MenuBar'>
<menu action='FileMenu'>
<!--menu action='FileNew'>
<menuitem action='FileNewStandard' />
<menuitem action='FileNewFoo' />
<menuitem action='FileNewGoo' />
</menu-->
<menuitem action='FileOpen' />
<menuitem action='FileSave' />
<separator />
<menuitem action='FileQuit' />
</menu>
<menu action='AboutMenu'>
<menuitem action='About'/>
</menu>
</menubar>
<toolbar name='ToolBar'>
<!--toolitem action='FileNewStandard' /-->
<toolitem action='FileOpen' />
<!--toolitem action='FileSave' /-->
<toolitem action='Run' />
<toolitem action='FileQuit' />
</toolbar>
<!--popup name='PopupMenu'>
<menuitem action='EditCopy' />
<menuitem action='EditPaste' />
<menuitem action='EditSomething' />
</popup-->
</ui>
"""
class info:
class traning_data:
def __init__(self):
self.Iteration_times = 0
self.Error_rate = 0
self.Data_set_size = 0
def reset(self):
self.Iteration_times = 0
self.Error_rate = 0
self.Data_set_size = 0
class testing_data:
def __init__(self):
self.Error_rate = 0
self.Data_set_size = 0
def reset(self):
self.Error_rate = 0
self.Data_set_size = 0
def __init__(self):
self.traning = self.traning_data()
self.testing = self.testing_data()
def reset(self):
self.traning.reset()
self.testing.reset()
class nNetwork(Gtk.Window):
def __init__(self):
self.nnetwork = None
self.dimension = 2
self.train_mode = True
#self.data = []
self.weights = []
self.class_table = {}
self.find_best = False
# self.class_num
self.dataset = dp()
self.training_set = []
self.testing_set = []
self.traning_trainsformed_data = []
self.testing_trainsformed_data = []
# log info
self.nninfo = info()
self.rbfn = None
# wait for ui setup
Gtk.Window.__init__(self, title="Neural Network")
self.set_default_size(800, 700)
# self.set_default_size(800, 700)
# self.connect("key-press-event", self.on_window_key_press_event)
action_group = Gtk.ActionGroup("my_actions")
# menu item
self.add_file_menu_actions(action_group)
self.add_about_menu_actions(action_group)
# create ui manager
uimanager = self.create_ui_manager()
uimanager.insert_action_group(action_group)
menubar = uimanager.get_widget("/MenuBar")
main_ui = Gtk.Box(orientation=Gtk.Orientation.VERTICAL)
self.add(main_ui)
main_ui.pack_start(menubar, False, False, 0)
toolbar = uimanager.get_widget("/ToolBar")
main_ui.pack_start(toolbar, False, False, 0)
# body pannel settings
body_panel = Gtk.Table(2, 4, True)
main_ui.pack_start(body_panel, True, True, 0)
# for
# Settings/*********************************************************/
settings_panel = Gtk.Box(
orientation=Gtk.Orientation.VERTICAL, spacing=10)
body_panel.attach(settings_panel, 0, 1, 0, 2, xpadding=8, ypadding=8)
settings_lab = Gtk.Label("Settings", xalign=0)
settings_panel.pack_start(settings_lab, False, False, 0)
# data settings
# *******************************************************/
data_settings_lab = Gtk.Label("Data Settings", xalign=0)
settings_panel.pack_start(data_settings_lab, False, False, 0)
# traning_testing_rate_group
traning_testing_rate_group = Gtk.Table(1, 2, True)
settings_panel.pack_start(traning_testing_rate_group, False, False, 0)
traning_testing_rate_lab = Gtk.Label(
"Traning & Tesgting\ndata rate(%):", xalign=0)
traning_testing_rate_group.attach(traning_testing_rate_lab, 0, 1, 0, 1)
traning_testing_rate_adj = Gtk.Adjustment(60, 0, 100, 5, 0, 0)
self.traning_testing_rate_sb = Gtk.SpinButton()
self.traning_testing_rate_sb.set_alignment(xalign=1)
self.traning_testing_rate_sb.set_adjustment(traning_testing_rate_adj)
traning_testing_rate_group.attach(
self.traning_testing_rate_sb, 1, 2, 0, 1)
self.traning_testing_rate_sb.set_value(66)
# action buttom
data_action_group = Gtk.Box(orientation=Gtk.Orientation.HORIZONTAL)
settings_panel.pack_start(data_action_group, False, False, 0)
generate_button = Gtk.Button(label="generate")
generate_button.connect("clicked", self.on_clicked_generate)
data_action_group.pack_start(generate_button, False, False, 0)
# test_button = Gtk.Button(label = "Test")
# test_button.connect("clicked", self.on_clicked_test)
# data_action_group.pack_start(test_button, False, False, 0)
# network settings*****************************************************
nn_settings_lab = Gtk.Label("Network Settings", xalign=0)
settings_panel.pack_start(nn_settings_lab, False, False, 0)
# Cross over
crossover_rate_group = Gtk.Table(1, 2, True)
settings_panel.pack_start(crossover_rate_group, False, False, 0)
crossover_rate_lab = Gtk.Label("alpha for self best(0.01):", xalign=0)
# crossover_rate_lab = Gtk.Label("crossover rate(0.01):", xalign=0)
crossover_rate_group.attach(crossover_rate_lab, 0, 1, 0, 1)
crossover_rate_adj = Gtk.Adjustment(60, 0, 100, 1, 10, 0)
self.crossover_rate_sb = Gtk.SpinButton()
self.crossover_rate_sb.set_alignment(xalign=1)
self.crossover_rate_sb.set_adjustment(crossover_rate_adj)
crossover_rate_group.attach(self.crossover_rate_sb, 1, 2, 0, 1)
self.crossover_rate_sb.set_value(20)
# mutation rate
mutation_rate_group = Gtk.Table(1, 2, True)
settings_panel.pack_start(mutation_rate_group, False, False, 0)
mutation_rate_lab = Gtk.Label("beta for group best(0.01):", xalign=0)
# mutation_rate_lab = Gtk.Label("mutation rate(0.01):", xalign=0)
mutation_rate_group.attach(mutation_rate_lab, 0, 1, 0, 1)
mutation_rate_adj = Gtk.Adjustment(5, 0, 100, 1, 10, 0)
self.mutation_rate_sb = Gtk.SpinButton()
self.mutation_rate_sb.set_alignment(xalign=1)
self.mutation_rate_sb.set_adjustment(mutation_rate_adj)
mutation_rate_group.attach(self.mutation_rate_sb, 1, 2, 0, 1)
self.mutation_rate_sb.set_value(20)
population_rate_group = Gtk.Table(1, 2, True)
settings_panel.pack_start(population_rate_group, False, False, 0)
population_rate_lab = Gtk.Label("population:", xalign=0)
population_rate_group.attach(population_rate_lab, 0, 1, 0, 1)
population_rate_adj = Gtk.Adjustment(10, 0, 1000, 1, 50, 0)
self.population_rate_sb = Gtk.SpinButton()
self.population_rate_sb.set_alignment(xalign=1)
self.population_rate_sb.set_adjustment(population_rate_adj)
population_rate_group.attach(self.population_rate_sb, 1, 2, 0, 1)
self.population_rate_sb.set_value(50)
layer_size_rate_group = Gtk.Table(1, 2, True)
settings_panel.pack_start(layer_size_rate_group, False, False, 0)
layer_size_rate_lab = Gtk.Label("layer_size rate(0.1):", xalign=0)
layer_size_rate_group.attach(layer_size_rate_lab, 0, 1, 0, 1)
layer_size_rate_adj = Gtk.Adjustment(15, 0, 100, 1, 1, 0)
self.layer_size_rate_sb = Gtk.SpinButton()
self.layer_size_rate_sb.set_alignment(xalign=1)
self.layer_size_rate_sb.set_adjustment(layer_size_rate_adj)
layer_size_rate_group.attach(self.layer_size_rate_sb, 1, 2, 0, 1)
self.layer_size_rate_sb.set_value(3)
# traning times
training_times_group = Gtk.Table(1, 2, True)
settings_panel.pack_start(training_times_group, False, False, 0)
training_times_lab = Gtk.Label("Traning times:", xalign=0)
training_times_group.attach(training_times_lab, 0, 1, 0, 1)
training_times_adj = Gtk.Adjustment(50, 0, 10000, 20, 0, 0)
self.training_times_sb = Gtk.SpinButton()
self.training_times_sb.set_alignment(xalign=1)
self.training_times_sb.set_adjustment(training_times_adj)
training_times_group.attach(self.training_times_sb, 1, 2, 0, 1)
self.training_times_sb.set_value(50)
# training_err_rate_group
# training_err_rate_group = Gtk.Table(1, 2, True)
# settings_panel.pack_start(training_err_rate_group, False, False, 0)
# training_err_rate_lab = Gtk.Label("Traning error rate(%):", xalign=0)
# training_err_rate_group.attach(training_err_rate_lab, 0, 1, 0, 1)
# training_err_rate_adj = Gtk.Adjustment(10, 0, 100, 5, 0, 0)
# self.training_err_rate_sb = Gtk.SpinButton()
# self.training_err_rate_sb.set_alignment(xalign=1)
# self.training_err_rate_sb.set_adjustment(training_err_rate_adj)
# training_err_rate_group.attach(self.training_err_rate_sb, 1, 2, 0, 1)
# self.training_err_rate_sb.set_value(5)
# mlp structure
# mlp_structure_group = Gtk.Box(orientation=Gtk.Orientation.VERTICAL)
# settings_panel.pack_start(mlp_structure_group, False, False, 0)
# mlp_structure_lab = Gtk.Label(
# "Specify mlp structure(3,5,1...)", xalign=0)
# mlp_structure_group.pack_start(mlp_structure_lab, True, True, 0)
# self.mlp_structure_ety = Gtk.Entry()
# self.mlp_structure_ety.set_alignment(xalign=1)
# self.mlp_structure_ety.set_text("2,1")
# mlp_structure_group.pack_start(self.mlp_structure_ety, True, True, 0)
# action buttom
action_group = Gtk.Box(orientation=Gtk.Orientation.HORIZONTAL)
settings_panel.pack_start(action_group, False, False, 0)
new_button = Gtk.Button(label="New")
new_button.connect("clicked", self.on_clicked_new)
action_group.pack_start(new_button, False, False, 0)
tarin_button = Gtk.Button(label="Train")
tarin_button.connect("clicked", self.on_clicked_train)
action_group.pack_start(tarin_button, False, False, 0)
test_button = Gtk.Button(label="Test")
test_button.connect("clicked", self.on_clicked_test)
action_group.pack_start(test_button, False, False, 0)
drive_button = Gtk.Button(label="Drive")
drive_button.connect("clicked", self.on_clicked_drive)
action_group.pack_start(drive_button, False, False, 0)
# draw_button = Gtk.Button(label = "Draw")
# draw_button.connect("clicked", self.on_clicked_draw)
# action_group.pack_start(draw_button, False, False, 0)
# /*******************************************************************/
# info*****************************************************************/
info_panel = Gtk.Box(orientation=Gtk.Orientation.VERTICAL, spacing=10)
body_panel.attach(info_panel, 1, 2, 0, 2)
info_lab = Gtk.Label("Information", xalign=0)
info_panel.pack_start(info_lab, False, False, 0)
# data info
dataset_info_lab = Gtk.Label("#Data Info", xalign=0)
info_panel.pack_start(dataset_info_lab, False, False, 0)
dataset_info_group = Gtk.Table(1, 2, False)
info_panel.pack_start(dataset_info_group, False, False, 0)
self.dataset_info_title_lab = Gtk.Label(
"FileName:\nData set size:\nDimension:\nClassification number:", xalign=0, yalign=0)
dataset_info_group.attach(self.dataset_info_title_lab, 0, 1, 0, 1)
self.dataset_info_msg_lab = Gtk.Label("", xalign=0, yalign=0)
dataset_info_group.attach(self.dataset_info_msg_lab, 1, 2, 0, 1)
# taning log
traning_log_lab = Gtk.Label("#Traning Log", xalign=0)
info_panel.pack_start(traning_log_lab, False, False, 0)
traning_log_group = Gtk.Table(1, 2, False)
info_panel.pack_start(traning_log_group, False, False, 0)
self.traning_log_title_lab = Gtk.Label(
"MSE:", xalign=0, yalign=0)
traning_log_group.attach(self.traning_log_title_lab, 0, 1, 0, 1)
self.traning_log_msg_lab = Gtk.Label("0", xalign=0, yalign=0)
traning_log_group.attach(self.traning_log_msg_lab, 1, 2, 0, 1)
# testing log
# testing_log_lab = Gtk.Label("#Testing Log", xalign=0, yalign=0)
# info_panel.pack_start(testing_log_lab, False, False, 0)
# testing_log_group = Gtk.Table(1, 2, False)
# info_panel.pack_start(testing_log_group, False, False, 0)
# self.testing_title_log_lab = Gtk.Label(
# "Accuracy rate:\nTesting set size:", xalign=0, yalign=0)
# testing_log_group.attach(self.testing_title_log_lab, 0, 1, 0, 1)
# self.testing_log_msg_lab = Gtk.Label("", xalign=0, yalign=0)
# testing_log_group.attach(self.testing_log_msg_lab, 1, 2, 0, 1)
# ori_draw_panel = Gtk.Box(10, 2, True)
# info_panel.pack_start(ori_draw_panel, True, True, 0)
#
# self.ori_paper = paper(title="After normalization(data set)")
# ori_draw_panel.pack_start(self.ori_paper.canvas, True, True, 0)
# *********************************************************************/
# drawing
# traning_draw_draw_panel = Gtk.Box(10, 2, True)
# body_panel.attach(traning_draw_draw_panel, 2, 3, 0, 1)
#
# self.traning_draw_paper = paper(title="Traning set")
# traning_draw_draw_panel.pack_start(
# self.traning_draw_paper.canvas, True, True, 0)
# self.traning_draw_paper.resetpaper()
#
# testing_draw_draw_panel = Gtk.Box(10, 2, True)
# body_panel.attach(testing_draw_draw_panel, 2, 3, 1, 2)
#
# self.testing_draw_paper = paper(title="Testing set")
# testing_draw_draw_panel.pack_start(
# self.testing_draw_paper.canvas, True, True, 0)
# self.testing_draw_paper.resetpaper()
# car drawing
map_draw_panel = Gtk.Box(10, 2, True)
body_panel.attach(map_draw_panel, 2, 4, 0, 2)
self.map_draw_paper = racing_map(title="Car Map")
map_draw_panel.pack_start(self.map_draw_paper.canvas, True, True, 0)
self.map_draw_paper.resetpaper()
# post init
self.log_refresh()
# self.classifier = None
def add_file_menu_actions(self, action_group):
action_filemenu = Gtk.Action("FileMenu", "File", None, None)
action_group.add_action(action_filemenu)
action_filenewmenu = Gtk.Action("FileNew", None, None, Gtk.STOCK_NEW)
action_group.add_action(action_filenewmenu)
action_new = Gtk.Action("FileNewStandard", "_New",
"Create a new file", Gtk.STOCK_NEW)
action_new.connect("activate", self.on_menu_file_new_generic)
action_group.add_action_with_accel(action_new, None)
action_group.add_actions([
("FileNewFoo", None, "New Foo", None, "Create new foo",
self.on_menu_file_new_generic),
("FileNewGoo", None, "_New Goo", None, "Create new goo",
self.on_menu_file_new_generic),
])
action_fileopen = Gtk.Action("FileOpen", "Open", None, Gtk.STOCK_OPEN)
action_fileopen.connect("activate", self.on_menu_file_open)
action_group.add_action(action_fileopen)
action_filesave = Gtk.Action("FileSave", "Save", None, Gtk.STOCK_SAVE)
action_group.add_action(action_filesave)
action_run = Gtk.Action("Run", "Run", None, Gtk.STOCK_MEDIA_PLAY)
action_run.connect("activate", self.on_clicked_run)
action_group.add_action(action_run)
action_filequit = Gtk.Action("FileQuit", None, None, Gtk.STOCK_QUIT)
action_filequit.connect("activate", self.on_menu_file_quit)
action_group.add_action(action_filequit)
def add_about_menu_actions(self, action_group):
action_aboutmenu = action_group.add_action(Gtk.Action("AboutMenu", "About", None,
None))
action_aboutmenu = Gtk.Action(
"About", "About", None, self.on_menu_others)
action_group.add_action(action_aboutmenu)
def create_ui_manager(self):
uimanager = Gtk.UIManager()
# Throws exception if something went wrong
uimanager.add_ui_from_string(UI_INFO)
# Add the accelerator group to the toplevel window
accelgroup = uimanager.get_accel_group()
self.add_accel_group(accelgroup)
return uimanager
def on_menu_file_new_generic(self, widget):
print("A File|New menu item was selected.")
def on_menu_file_quit(self, widget):
Gtk.main_quit()
def on_menu_file_open(self, widget):
dialog = Gtk.FileChooserDialog("Please choose a file", self,
Gtk.FileChooserAction.OPEN,
(Gtk.STOCK_CANCEL, Gtk.ResponseType.CANCEL,
Gtk.STOCK_OPEN, Gtk.ResponseType.OK))
self.add_filters(dialog)
response = dialog.run()
if response == Gtk.ResponseType.OK:
# reset
self.nninfo.reset()
self.log_refresh()
print("Open clicked")
print("File selected: " + dialog.get_filename())
print(self.traning_testing_rate_sb.get_value() / 100)
self.dataset.set_file_name(dialog.get_filename())
self.dataset.open_file()
# log info
file_name = dialog.get_filename().split('/')[-1]
if self.dataset.get_data_size() > 100:
print("tt rate\t", self.traning_testing_rate_sb.get_value())
self.training_set = self.dataset.get_data(
self.traning_testing_rate_sb.get_value() / 100, approach="func")
self.training_set = (dp.to_ndata(
self.training_set[0]), self.training_set[1])
self.testing_set = self.dataset.get_data(
1 - self.traning_testing_rate_sb.get_value() / 100, approach="func")
self.testing_set = (dp.to_ndata(
self.testing_set[0]), self.testing_set[1])
else:
self.training_set = self.dataset.get_data(
1, approach="func", is_random=False)
self.training_set = (dp.to_ndata(
self.training_set[0]), self.training_set[1])
self.testing_set = self.dataset.get_data(1, approach="func")
self.testing_set = (dp.to_ndata(
self.testing_set[0]), self.testing_set[1])
self.nninfo.traning.Data_set_size = len(self.training_set[1])
self.nninfo.testing.Data_set_size = len(self.testing_set[1])
print(self.training_set)
self.dataset_info_msg_lab.set_text((file_name[0:18] + "..." if len(file_name) > 20 else file_name) + " \n" + self.dataset.get_data_size(
).__str__() + " \n" + self.dataset.get_data_dimension().__str__() + " \n" + self.dataset.get_data_classification_num().__str__() + " ")
# self.traning_draw_paper.resetpaper()
# self.testing_draw_paper.resetpaper()
elif response == Gtk.ResponseType.CANCEL:
print("Cancel clicked")
#print(self.data, ", ", self.class_table, ", ", tmp_table)
dialog.destroy()
def add_filters(self, dialog):
filter_text = Gtk.FileFilter()
filter_text.set_name("Text files")
filter_text.add_mime_type("text/plain")
dialog.add_filter(filter_text)
filter_py = Gtk.FileFilter()
filter_py.set_name("Python files")
filter_py.add_mime_type("text/x-python")
dialog.add_filter(filter_py)
filter_any = Gtk.FileFilter()
filter_any.set_name("Any files")
filter_any.add_pattern("*")
dialog.add_filter(filter_any)
def on_find_best_activated(self, switch, gparam):
if switch.get_active():
self.find_best = True
else:
self.find_best = False
def log_refresh(self, widget=None, pannel="ALL"):
tmp_str = ""
if pannel == "ALL":
tmp_str = format(self.nninfo.traning.Error_rate * 100, '.4f') + "\n"
self.traning_log_msg_lab.set_text(tmp_str)
elif pannel == "Training":
tmp_str = format(100 - self.nninfo.traning.Error_rate, '.4f')
def test(self, test):
while(test < 100):
test += 1
print(test)
print("finished")
def _on_clicked_drive(self, racing_map):
mycar = Car()
count = 0
# self.rbfn.set_test()
# racing_map.test_sensor()
# return
# print("middle\t", self.rbfn.testing(np.array([0.5,0.1,0.1])))
# print("right\t", self.rbfn.testing(np.array([0.1,0.5,0.1])))
# print("left\t", self.rbfn.testing(np.array([0.1,0.1,0.5])))
# return
while(True):
racing_map.update_sensor(mycar)
theta = self.rbfn.testing(
np.array([mycar.sensor_middle, mycar.sensor_right, mycar.sensor_left]))
theta = theta if theta < 40 else 40
theta = theta if theta > -40 else -40
print([mycar.sensor_middle, mycar.sensor_right,
mycar.sensor_left], theta)
mycar.step_forward((theta * 80 - 40) * 0.0174533)
# print(self.rbfn.testing(np.array([15.716004895815198, 9.406684048849488, 23.538679933233805])))
# racing_map.update_sensor(mycar)
# theta = self.rbfn.testing(np.array([mycar.sensor_middle * 30, mycar.sensor_right * 30, mycar.sensor_left * 30]))
# print([mycar.sensor_middle * 30, mycar.sensor_right * 30, mycar.sensor_left * 30], (theta))
# mycar.step_forward((theta) * 0.0174533)
racing_map.draw(mycar)
# time.sleep(0.1)
if(mycar.sensor_middle < 0.05 or mycar.sensor_right <0.05 or mycar.sensor_left < 0.05 or mycar.pos[1] > 37):
return
# if(count == 15):
# mycar.dir = 0.001
# elif count == 40:
# mycar.dir = 1.57
def on_clicked_drive(self, widget=None):
# threading.Thread(target=self._on_clicked_drive(self.map_draw_paper)).start()
self._on_clicked_drive(self.map_draw_paper)
def on_clicked_train(self, widget):
print("on click train")
# print(self.layer_size_rate_sb.get_value(), self.training_times_sb.get_value(
# ), self.population_rate_sb.get_value(), self.crossover_rate_sb.get_value()/100, self.mutation_rate_sb.get_value()/100)
self.traning_log_msg_lab.set_text((1 / (self.rbfn.traning(iteration=int(self.training_times_sb.get_value())) + 0.00000001) / len(self.training_set) * 2).__str__())
def on_clicked_new(self, widget):
print("on click new")
self.rbfn = rbfn(self.training_set, int(self.layer_size_rate_sb.get_value()), population=int(self.population_rate_sb.get_value()), alpha=self.crossover_rate_sb.get_value()/100, beta=self.mutation_rate_sb.get_value()/100)
def on_clicked_test(self, widget):
for _ in range(10):
# print("population:")
# for i in range(1,11):
# myrbfn = rbfn(self.training_set, int(self.layer_size_rate_sb.get_value()), population=50 * i, alpha=0.5, beta=0.5)
# print("population , ",i, ", ", myrbfn.traning(iteration=int(self.training_times_sb.get_value())))
print("alpha:")
myrbfn = rbfn(self.training_set, int(self.layer_size_rate_sb.get_value()), population=50, alpha=0.1, beta=0.1)
pool = myrbfn.get_pool()
for i in range(1,11):
myrbfn = rbfn(self.training_set, int(self.layer_size_rate_sb.get_value()), population=50, alpha=i/10, beta=0.8)
myrbfn.set_pool(pool)
print("population , ",i, ", ", myrbfn.traning(iteration=int(self.training_times_sb.get_value())))
print("beta:")
for i in range(1,11):
myrbfn = rbfn(self.training_set, int(self.layer_size_rate_sb.get_value()), population=50, alpha=0.8, beta=i/10)
myrbfn.set_pool(pool)
print("population , ",i, ", ", myrbfn.traning(iteration=int(self.training_times_sb.get_value())))
return
def draw_area(self):
cm = self.dataset.get_class_middle()
self.ori_paper.resetpaper()
self.ori_paper.draw_2d_point(self.dataset.get_data(1), cm)
self.ori_paper.expend_lim()
density = 100
# x = np.linspace(0,1,density)
# y = np.linspace(0,1,density)
x = np.linspace(-0.02, 1.02, density)
y = np.linspace(-0.02, 1.02, density)
x, y = np.meshgrid(x, y)
area_data = []
tmp_x = []
tmp_y = []
tmp_data = []
for i in x:
tmp_x.extend(list(i))
for i in y:
tmp_y.extend(list(i))
for i, j in zip(tmp_x, tmp_y):
tmp_data.append([i, j])
z = self.nnetwork.classifier(tmp_data)
zp = []
for i in cm:
if z.count(i) == 0:
return
for c in z:
zp.extend([cm.index(c)])
z = zp
# print("x len", len(x))
tmp = []
for j in range(len(y)):
# print(j * len(x), ", ", j * (len(x)) + len(x) - 1)
tmp.append(z[j * density:j * density + density])
# print("z", z, ", ", len(tmp), ", ", len(tmp[0]))
z = np.vstack(tmp)
cMap = colors.ListedColormap(
["r", "b", "g", "c", "m", "y", "k", "w"][0:len(cm)])
self.ori_paper.ax.pcolormesh(x, y, z, cmap=cMap, alpha=0.4)
self.ori_paper.draw()
def on_clicked_run(self, widget):
self.on_clicked_train(widget)
self.on_clicked_test(widget)
@staticmethod
def on_clicked_draw(draw_paper, suc, err, class_middle):
draw_paper.resetpaper()
draw_paper.draw_2d_point(suc, class_middle)
draw_paper.draw_2d_point(err, class_middle, 'x')
draw_paper.expend_lim()
draw_paper.draw()
def on_window_key_press_event(self, window, event):
print(event.keyval)
if event.keyval == 122:
print("z")
def on_clicked_generate(self, widght):
if self.dataset.get_data_size() > 100:
print("tt rate\t", self.traning_testing_rate_sb.get_value())
self.training_set = self.dataset.get_data(
self.traning_testing_rate_sb.get_value() / 100)
self.training_set = (dp.to_ndata(
self.training_set[0]), self.training_set[1])
self.testing_set = self.dataset.get_data(
1 - self.traning_testing_rate_sb.get_value() / 100)
self.testing_set = (dp.to_ndata(
self.testing_set[0]), self.testing_set[1])
else:
self.training_set = self.dataset.get_data(1)
self.training_set = (dp.to_ndata(
self.training_set[0]), self.training_set[1])
self.testing_set = self.dataset.get_data(1)
self.testing_set = (dp.to_ndata(
self.testing_set[0]), self.testing_set[1])
self.nninfo.traning.Data_set_size = len(self.training_set[1])
self.nninfo.testing.Data_set_size = len(self.testing_set[1])
def on_menu_others(self, widget):
print("Menu item " + widget.get_name() + " was selected")
#
# def on_menu_choices_changed(self, widget, current):
# print(current.get_name() + " was selected.")
#
# def on_menu_choices_toggled(self, widget):
# if widget.get_active():
# print(widget.get_name() + " activated")
# else:
# print(widget.get_name() + " deactivated")
#
# def on_button_press_event(self, widget, event):
# # Check if right mouse button was preseed
# if event.type == Gdk.EventType.BUTTON_PRESS and event.button == 3:
# self.popup.popup(None, None, None, None, event.button, event.time)
# return True # event has been handled
def main():
GObject.threads_init()
window = nNetwork()
window.connect("delete-event", Gtk.main_quit)
window.show_all()
Gtk.main()
if __name__ == '__main__':
main()