def load_network(self):
f = self.gui.open_file(self.winNN, filetypes=[("JSON file", ".json")])
if not f:
return None
def check_network(ntw):
if len(ntw) < 2 or type(ntw) is not list or len(ntw[0]) != len(ntw[1])+1:
return False
for i in range(len(ntw[0])-1):
if ntw[0][i] != len(ntw[1][i]):
return False
for j in range(len(ntw[1][i])):
if ntw[0][i+1] != len(ntw[1][i][j]):
return False
return True
try:
network = json.load(f)
if not check_network(network):
raise ValueError
except ValueError:
self.gui.message("error", "Error!", self.localization("tinn_error"))
return None
funcs = [[f_activation, df_activation]]*len(network[0])
funcs[0] = None
self.network = Net(network[0], funcs)
self.network.w = network[1]
self.new_network_graph(self.frame_neurons_graph)
self.refresh_st_samples()
def new_network(self, layers, bias=0):
try:
arr = layers.split(",")
if len(arr) < 1:
raise ValueError
layers = []
for i in arr:
if int(i) > 0:
layers.append(int(i))
else:
raise ValueError
except ValueError:
self.gui.message("warning", "Warning!", self.localization("ii_error") % (self.localization("menu_net_layers")))
return None
funcs = [[f_activation, df_activation]]*len(layers)
funcs[0] = None
self.network = Net(layers, funcs, bias)
self.new_network_graph(self.frame_neurons_graph)
self.refresh_st_samples()
class NNConstructor:
gui = None
win = None
winNN = None
t_stop_train = {"next": False, "_next": False}
__train = None
samples = []
test_samples = []
p_samples = []
inp = None
outp = None
gui_samples = None
gui_samples_list = None
gui_network_graph = None
gui_graph = None
frame_neurons_graph = None
gui_graph_colors = None
__visible_edit_samples = None
network = None
analysis_process = None
def __init__(self, x=450.0, y=0.0):
self.gui = GUI(self)
self.winNN = self.gui.new_window("Constructor of Neural Networks", x, y, 960, h=720)
self.winNN.iconbitmap('./favicon/constructor.ico')
try:
words = json.load(open("./language.json", "r"))
except IOError:
words = None
except ValueError:
words = None
self.localization = Localization(words).localization
frame = self.gui.frame(self.winNN, x=0, y=0, w=1046, h=768, bind=None, bg="#77AA77")
frame_excel = self.gui.frame(frame, x=10, y=0, w=200, h=350, bind=None, bg="#669966")
frame_newnet = self.gui.frame(frame, x=10, y=360, w=200, h=170, bind=None, bg="#669966")
frame_train = self.gui.frame(frame, x=10, y=540, w=200, h=170, bind=None, bg="#669966")
frame_samples = self.gui.frame(frame, x=220, y=0, w=300, h=370, bind=None, bg="#669966")
self.frame_neurons_graph = self.gui.frame(frame, x=530, y=0, w=420, h=370, bind=None, bg="#669966")
frame_neurons_control = self.gui.frame(frame, x=615, y=380, w=335, h=360, bind=None, bg="#669966")
self.frame_train_graph = self.gui.frame(frame, x=220, y=380, w=385, h=350, bind=None, bg="#669966")
self.gui_network_graph = self.gui.canvas(self.frame_neurons_graph, x=10, y=10, w=400, h=350, bg="#FFFFFF")
self.new_graph()
self.gui.button(self.frame_train_graph, x=10, y=310, w=367, h=25, text=self.localization("graph_button"),
bind=("<Button-1>",
lambda event:
self.new_graph()))
self.new_network_graph(self.frame_neurons_graph)
self.gui.text(frame_samples, x=50, y=5, w=200, h=20, text=self.localization("sample_editor_title"),
bg="#669966", font='Arial 13')
self.gui_samples = self.gui.textarea(frame_samples, x=10, y=30, w=280, h=260)
self.gui_samples_list = self.gui.listbox(frame_samples, x=10, y=30, w=280, h=260, bind=("<<ListboxSelect>>",
lambda event:
self.refresh_st_samples(
)))
self.gui.button(frame_samples, x=10, y=300, w=280, h=30, text=self.localization("load_test_button"),
bind=("<Button-1>",
lambda event:
self.load_tsamples()))
self.gui.button(frame_samples, x=10, y=335, w=67, h=30, text=self.localization("edit_samples_button"),
bind=("<Button-1>",
lambda event: self.edit_samples()))
self.gui.button(frame_samples, x=81, y=335, w=67, h=30, text=self.localization("clear_samples_button"),
bind=("<Button-1>",
lambda event: self.clear_samples()))
self.gui.button(frame_samples, x=152, y=335, w=67, h=30, text=self.localization("load_samples_button"),
bind=("<Button-1>",
lambda event: self.load_samples()))
self.gui.button(frame_samples, x=223, y=335, w=67, h=30, text=self.localization("save_samples_button"),
bind=("<Button-1>",
lambda event: self.save_samples()))
self.gui.text(frame_newnet, x=10, y=0, w=180, h=20, text=self.localization("menu_net_title"),
bg="#669966", font='Arial 13')
self.gui.text(frame_newnet, x=10, y=30, w=50, h=20, text=self.localization("menu_net_layers"), bg="#669966")
layers = self.gui.input(frame_newnet, x=80, y=30, w=110, h=20)
self.gui.set_text_input(layers, "")
bias = self.gui.Tkinter.IntVar()
self.gui.checkbox(frame_newnet, x=10, y=60, w=180, h=20, variable=bias,
text=self.localization("check_box_bias"))
self.gui.button(frame_newnet, x=10, y=130, w=85, h=30, text=self.localization("load_network_button"),
bind=("<Button-1>",
lambda event: self.load_network()))
self.gui.button(frame_newnet, x=105, y=130, w=85, h=30, text=self.localization("save_network_button"),
bind=("<Button-1>", lambda event: self.save_network()))
self.gui.button(frame_newnet, x=10, y=90, w=180, h=30, text=self.localization("new_network_button"),
bind=("<Button-1>", lambda event: self.new_network(layers.get(), bias.get())))
self.gui.text(frame_train, x=10, y=0, w=180, h=20, text=self.localization("menu_train_title"),
bg="#669966", font='Arial 13')
self.gui.text(frame_train, x=10, y=25, w=110, h=20, text=self.localization("menu_train_speed"), bg="#669966")
speed = self.gui.input(frame_train, x=120, y=25, w=70, h=20)
self.gui.set_text_input(speed, "")
self.gui.text(frame_train, x=10, y=50, w=110, h=20, text=self.localization("menu_train_iterations"),
bg="#669966")
iterations = self.gui.input(frame_train, x=120, y=50, w=70, h=20)
self.gui.set_text_input(iterations, "")
checkbox = self.gui.Tkinter.IntVar()
self.gui.checkbox(frame_train, x=10, y=75, w=180, h=20, variable=checkbox,
text=self.localization("check_box_change_speed"))
self.gui.button(frame_train, x=10, y=100, w=180, h=30, text=self.localization("train_button"),
bind=("<Button-1>", lambda event: self.train_network(
iterations.get(),
speed.get(),
checkbox.get()
)))
self.gui.button(frame_train, x=10, y=132, w=180, h=30, text=self.localization("stop_train_button"),
bind=("<Button-1>", lambda event: self.stop_train()))
self.gui.text(frame_neurons_control, x=5, y=20, w=240, h=20, text=self.localization("status_sample_error"),
bg="#669966", font='Arial 12')
self.smErr = self.gui.input(frame_neurons_control, x=250, y=20, w=70, h=20)
self.gui.text(frame_neurons_control, x=5, y=60, w=240, h=20, text=self.localization("status_max_error"),
bg="#669966", font='Arial 12')
self.mxErr = self.gui.input(frame_neurons_control, x=250, y=60, w=70, h=20)
self.gui.text(frame_neurons_control, x=5, y=100, w=240, h=20, text=self.localization("status_av_error"),
bg="#669966", font='Arial 12')
self.avErr = self.gui.input(frame_neurons_control, x=250, y=100, w=70, h=20)
self.gui.text(frame_neurons_control, x=5, y=140, w=240, h=20, text=self.localization("status_max_test_error"),
bg="#669966", font='Arial 12')
self.tmxErr = self.gui.input(frame_neurons_control, x=250, y=140, w=70, h=20)
self.gui.text(frame_neurons_control, x=5, y=180, w=240, h=20, text=self.localization("status_av_test_error"),
bg="#669966", font='Arial 12')
self.ttErr = self.gui.input(frame_neurons_control, x=250, y=180, w=70, h=20)
self.gui.button(frame_neurons_control, x=30, y=250, w=80, h=30, text=self.localization("module_1_button"),
bind=("<Button-1>", lambda event: self.load_module("_module_1")))
self.gui.button(frame_neurons_control, x=120, y=250, w=80, h=30, text=self.localization("module_2_button"),
bind=("<Button-1>", lambda event: self.load_module("_module_2")))
self.gui.button(frame_neurons_control, x=210, y=250, w=80, h=30, text=self.localization("module_3_button"),
bind=("<Button-1>", lambda event: self.load_module("_module_3")))
self.gui.text(frame_excel, x=50, y=5, w=100, h=20, text=self.localization("analysis_title"),
bg="#669966", font='Arial 13')
self.gui.text(frame_excel, x=5, y=35, w=120, h=20, text=self.localization("analysis_name_of_file"),
bg="#669966")
book_name = self.gui.input(frame_excel, x=120, y=35, w=70, h=20)
self.gui.text(frame_excel, x=5, y=70, w=120, h=20, text=self.localization("analysis_layers"), bg="#669966")
layers_pat = self.gui.input(frame_excel, x=120, y=70, w=70, h=20)
self.gui.text(frame_excel, x=5, y=100, w=120, h=20, text=self.localization("analysis_ch_speed"), bg="#669966")
ch_layers = self.gui.input(frame_excel, x=120, y=100, w=70, h=20)
self.gui.text(frame_excel, x=5, y=135, w=120, h=20, text=self.localization("analysis_iterations"), bg="#669966")
iter = self.gui.input(frame_excel, x=120, y=135, w=70, h=20)
self.gui.text(frame_excel, x=5, y=170, w=120, h=20, text=self.localization("analysis_data_size"), bg="#669966")
data = self.gui.input(frame_excel, x=120, y=170, w=70, h=20)
self.gui.text(frame_excel, x=5, y=205, w=120, h=20, text=self.localization("analysis_speed"), bg="#669966")
speed_cof = self.gui.input(frame_excel, x=120, y=205, w=70, h=20)
checkbox = self.gui.Tkinter.IntVar()
self.gui.checkbox(frame_excel, x=10, y=240, w=180, h=20, variable=checkbox,
text=self.localization("check_box_ch_speed"))
progressbar = self.gui.progressbar(frame_excel, x=10, y=310, w=180, h=30,
orient='horizontal', mode='indeterminate')
self.gui.button(frame_excel, x=10, y=270, w=85, h=30, text=self.localization("start_analysis_button"),
bind=("<Button-1>", lambda event: self.analysis_start(book_name.get(),
layers_pat.get(),
ch_layers.get(),
iter.get(),
data.get(),
speed_cof.get(),
checkbox.get(),
progressbar)))
self.gui.button(frame_excel, x=105, y=270, w=85, h=30, text=self.localization("stop_analysis_button"),
bind=("<Button-1>", lambda event: self.analysis_stop(progressbar)))
def open(self):
self.gui.mainloop()
def close(self):
self.gui.close()
def stop_all(self):
self.stop_train()
time.sleep(0.5)
def load_module(self, name):
try:
module = __import__(name)
if "main" in dir(module):
module.main(self)
else:
self.gui.message("warning", "Warning!", self.localization("fminf_error"))
except ImportError:
self.gui.message("error", "Error!", self.localization("minf_error") % name)
def analysis_start(self, fn, layers, ch_layers, iter, data, speed, ch_speed, pb):
def parse_str(s):
arr_s = s.replace(" ", "").split(",")
if arr_s[0] == '':
arr_s = []
arr = []
if len(arr_s) == 1:
arr_s = arr_s[0].split(":")
elif len(arr_s) > 1:
arr = [float(i) for i in arr_s]
arr_s = []
if len(arr_s) == 1:
arr = [float(arr_s[0])]
elif len(arr_s) == 3:
i = float(arr_s[0])
while i <= float(arr_s[1]):
arr.append(i)
i += float(arr_s[2])
return arr
if len(fn) < 1:
self.gui.message("warning", "Warning!", self.localization("ii_error")
% (self.localization("analysis_name_of_file")))
return None
for i in ['\\', '/', ':', '*', '.', '?', '"', '<', '>', '|']:
if i in fn:
self.gui.message("warning", "Warning!", self.localization("fcncc_error"))
return None
layers = layers.replace(" ", "").split(",")
if layers[0] == '':
self.gui.message("warning", "Warning!", self.localization("ii_error")
% (self.localization("analysis_layers")))
return None
try:
ch_layers = parse_str(ch_layers)
except ValueError:
self.gui.message("warning", "Warning!", self.localization("ii_error")
% self.localization("analysis_ch_speed"))
return None
try:
iter = parse_str(iter)
except ValueError:
self.gui.message("warning", "Warning!", self.localization("ii_error")
% (self.localization("analysis_iterations")))
return None
try:
data = parse_str(data)
except ValueError:
self.gui.message("warning", "Warning!", self.localization("ii_error")
% (self.localization("analysis_data_size")))
return None
try:
speed = parse_str(speed)
except ValueError:
self.gui.message("warning", "Warning!", self.localization("ii_error")
% (self.localization("analysis_speed")))
return None
samples = self.samples[:]
test_samples = self.test_samples[:] if len(self.test_samples) > 0 else samples
len_samples = len(samples)
len_test_samples = len(test_samples)
if len_samples < 1:
self.gui.message("warning", "Warning!", self.localization("sinl_error"))
return None
def main():
wb = openpyxl.Workbook()
test_wb = openpyxl.Workbook() if not (samples == test_samples) else None
self.analysis_process = True
pb.start(5)
column = 1
for i in ch_layers:
row = 1
for j in iter:
for k in data:
sample = samples[:int(k)] if (int(k) > 0) and (int(k) < len_samples) else samples
test_sample = test_samples[:int(k)] \
if (int(k) > 0) and (int(k) < len_test_samples) else test_samples
for z in speed:
if self.analysis_process is not True:
return None
nn = analysis.NN([int(i) if t == 'x' else int(t) for t in layers])
nn.train(sample, int(j), z, z/100 if ch_speed else z)
err = nn.get_error(sample, test_sample)
del nn
sheet = "col_data "+str(int(k))+" speed "+str(z)
if not (sheet in wb):
wb.create_sheet(1, sheet)
wb[sheet].cell(row=row, column=column).value = err[0]
if test_wb is not None:
if not (sheet in test_wb):
test_wb.create_sheet(1, sheet)
test_wb[sheet].cell(row=row, column=column).value = err[1]
row += 1
column += 1
pb.stop()
wb.save("./sheets/%s.xlsx" % fn)
if test_wb is not None:
test_wb.save("./sheets/%s_test.xlsx" % fn)
threading.Thread(target=main).start()
def analysis_stop(self, pb):
self.analysis_process = False
pb.stop()
def new_network(self, layers, bias=0):
try:
arr = layers.split(",")
if len(arr) < 1:
raise ValueError
layers = []
for i in arr:
if int(i) > 0:
layers.append(int(i))
else:
raise ValueError
except ValueError:
self.gui.message("warning", "Warning!", self.localization("ii_error") % (self.localization("menu_net_layers")))
return None
funcs = [[f_activation, df_activation]]*len(layers)
funcs[0] = None
self.network = Net(layers, funcs, bias)
self.new_network_graph(self.frame_neurons_graph)
self.refresh_st_samples()
def train_network(self, iterations, speed, dspeed):
if self.__train is not None and self.__train.isAlive():
self.gui.message("warning", "Warning!", self.localization("ptsb_error"))
return None
if self.network is None:
self.gui.message("warning", "Warning!", self.localization("ninl_error"))
return None
if len(self.samples) < 1:
self.gui.message("warning", "Warning!", self.localization("sinl_error"))
return None
if not self.network.check_sample(self.samples):
self.gui.message("warning", "Warning!", self.localization("sinl_error"))
return None
if not self.network.check_sample(self.test_samples) and self.test_samples != [] and self.test_samples != self.samples:
self.gui.message("warning", "Warning!", self.localization("tsinl_error"))
return None
try:
iterations = int(iterations)
if iterations < 1:
raise ValueError
except ValueError:
self.gui.message("warning", "Warning!", self.localization("ii_error")
% (self.localization("menu_train_iterations")))
return None
try:
speed = float(speed)
except ValueError:
self.gui.message("warning", "Warning!", self.localization("ii_error")
% (self.localization("menu_train_speed")))
return None
self.graph[3] = iterations
if len(self.gui_graph_colors) == 0:
self.new_graph()
color = self.gui_graph_colors.pop()
start = time.time()
self.__train = threading.Thread(target=lambda: self.network.train(self.samples, iterations, speed, dspeed,
func=lambda i, error, terror:
self.picture_graph(
i=i,
error=error,
terror=terror,
iterations=iterations,
color=color
),
test=self.test_samples,
stop=self.t_stop_train,
callback=lambda: self.new_network_graph(
self.frame_neurons_graph
) or self.refresh_st_samples(st=True)))
self.__train.start()
def stop_train(self):
self.t_stop_train["_next"] = True
self.t_stop_train["next"] = True
def save_network(self):
if self.network is None:
return None
self.set_samples()
f = self.gui.save_file(self.winNN, filetypes=[("JSON file", ".json")])
if not f:
return None
try:
json.dump([self.network.n, self.network.w], f)
except ValueError:
self.gui.message("error", "Error!", self.localization("io_error"))
return None
def load_network(self):
f = self.gui.open_file(self.winNN, filetypes=[("JSON file", ".json")])
if not f:
return None
def check_network(ntw):
if len(ntw) < 2 or type(ntw) is not list or len(ntw[0]) != len(ntw[1])+1:
return False
for i in range(len(ntw[0])-1):
if ntw[0][i] != len(ntw[1][i]):
return False
for j in range(len(ntw[1][i])):
if ntw[0][i+1] != len(ntw[1][i][j]):
return False
return True
try:
network = json.load(f)
if not check_network(network):
raise ValueError
except ValueError:
self.gui.message("error", "Error!", self.localization("tinn_error"))
return None
funcs = [[f_activation, df_activation]]*len(network[0])
funcs[0] = None
self.network = Net(network[0], funcs)
self.network.w = network[1]
self.new_network_graph(self.frame_neurons_graph)
self.refresh_st_samples()
def new_graph(self):
if self.gui_graph is not None:
self.gui_graph.space.destroy()
del self.gui_graph
self.gui_graph = self.gui.canvas(self.frame_train_graph, x=10, y=10, w=365, h=300, bg="#99BB99")
self.graph = [None, (40.0, 270.0, 300.0, 260.0, 0.2), None, 1]
self.gui_graph.line(int(self.graph[1][0]),
int(self.graph[1][1]),
int(self.graph[1][0]),
int(self.graph[1][1]-self.graph[1][3]),
arrow=self.gui.Tkinter.LAST)
self.gui_graph.line(int(self.graph[1][0]),
int(self.graph[1][1]),
int(self.graph[1][0]+self.graph[1][2]),
int(self.graph[1][1]),
arrow=self.gui.Tkinter.LAST)
self.gui_graph_colors = ["red", "blue", "black", "orange", "purple"]
text_cords = self.gui_graph.text(x=0, y=0, text="")
self.gui_graph.space.bind("<B1-Motion>", lambda event: self.gui_graph.space.coords(text_cords, event.x-(
-40 if event.x < self.graph[1][2]/2 else 40), event.y+7) or self.gui_graph.space.itemconfigure(
text_cords, text=str(int((event.x-self.graph[1][0])/self.graph[1][2]*self.graph[3]))+" / "+str(
round((self.graph[1][1]-event.y)/self.graph[1][3]*self.graph[1][4], 2))))
self.gui_graph.text(x=self.graph[1][0]-20, y=self.graph[1][1]-self.graph[1][3]+10, text="Q")
self.gui_graph.text(x=self.graph[1][0]+self.graph[1][2]-20, y=self.graph[1][1]+20, text="N")
self.gui_graph.space.bind("<B1-ButtonRelease>", lambda e: self.gui_graph.space.coords(text_cords, -10, -10))
cx, cy = 5, 5
for i in range(1, cy):
self.gui_graph.line(self.graph[1][0]-5, self.graph[1][1]-self.graph[1][3]/cy*i,
self.graph[1][0]+5, self.graph[1][1]-self.graph[1][3]/cy*i,
fill="red")
for i in range(1, cx):
self.gui_graph.space.create_line(self.graph[1][0]+self.graph[1][2]/cx*i,
self.graph[1][1]+5, self.graph[1][0]+self.graph[1][2]/cx*i,
self.graph[1][1]-5, width=1, fill="red")
def picture_graph(self, i=0, error=0, terror=0, iterations=0, color=None):
if not color:
return None
if self.graph[0] is None or i < 5:
self.graph[0] = (i*1.0, error)
self.graph[2] = (i*1.0, terror)
else:
self.gui_graph.space.create_line(
self.graph[1][0]+i*1.0/iterations*self.graph[1][2],
self.graph[1][1]-error/self.graph[1][4]*self.graph[1][3],
self.graph[1][0]+self.graph[0][0]/iterations*self.graph[1][2],
self.graph[1][1]-self.graph[0][1]/self.graph[1][4]*self.graph[1][3],
width=2, fill=color
)
if terror:
self.gui_graph.space.create_oval(
self.graph[1][0]+i*1.0/iterations*self.graph[1][2]-2,
self.graph[1][1]-terror/self.graph[1][4]*self.graph[1][3]-2,
self.graph[1][0]+i*1.0/iterations*self.graph[1][2]+2,
self.graph[1][1]-terror/self.graph[1][4]*self.graph[1][3]+2,
fill=color
)
self.graph[0] = (i*1.0, error)
self.graph[2] = (i*1.0, terror)
def new_network_graph(self, frame_neurons_graph):
if not self.network:
return None
if self.gui_network_graph is not None:
self.gui_network_graph.space.destroy()
del self.gui_network_graph
self.gui_network_graph = self.gui.canvas(frame_neurons_graph, x=10, y=10, w=400, h=350, bg="#FFFFFF")
n = self.network.n
for i in range(len(n)-1):
for j in range(n[i]):
for k in range(n[i+1]):
self.gui_network_graph.line(400/(len(n)+1)*(i+1), 350/(n[i]+1)*(j+1),
400/(len(n)+1)*(i+2), 350/(n[i+1]+1)*(k+1),
fill="#%x%x%x" % (15/(1+math.exp(
-self.network.w[i][j][k]*5)), 0, 15/(
1+math.exp(self.network.w[i][j][k]*5))))
for i in range(len(n)):
for j in range(n[i]):
self.gui_network_graph.circle(400/(len(n)+1)*(i+1), 350/(n[i]+1)*(j+1), 4,
tags=("neurons", "neuron-%d-%d" % (i, j)), fill="green")
def refresh_st_samples(self, st=False):
if self.network is None or (self.__train is not None and self.__train.isAlive() and not st) \
or len(self.samples) < 1:
return None
if not self.network.check_sample(self.samples):
return None
if not self.network.check_sample(self.test_samples):
return None
smp_cl = int(self.gui_samples_list.curselection()[0]) if len(self.gui_samples_list.curselection()) > 0 else 0
err = 0.0
if len(self.samples) > smp_cl:
sample = self.samples[smp_cl]
self.network.update(sample[0])
for k in range(len(sample[1])):
err += abs(sample[1][k]-self.network.a[-1][k])
err /= len(sample[1])
self.gui.set_text_input(self.smErr, str(round(err, 5)))
averr = 0.0
mxerr = 0.0
for p in self.samples:
self.network.update(p[0])
_averr = 0.0
for k in range(len(p[1])):
_averr += abs(p[1][k]-self.network.a[-1][k])
_averr /= len(p[1])
averr += _averr
if _averr > mxerr:
mxerr = _averr
averr /= len(self.samples)
t_averr = 0.0
t_mxerr = 0.0
for p in self.test_samples:
self.network.update(p[0])
_averr = 0.0
for k in range(len(p[1])):
_averr += abs(p[1][k]-self.network.a[-1][k])
_averr /= len(p[1])
t_averr += _averr
if _averr > t_mxerr:
t_mxerr = _averr
t_averr /= len(self.test_samples) or 1
self.gui.set_text_input(self.avErr, str(round(averr, 5)))
self.gui.set_text_input(self.mxErr, str(round(mxerr, 5)))
self.gui.set_text_input(self.ttErr, str(round(t_averr, 5)))
self.gui.set_text_input(self.tmxErr, str(round(t_mxerr, 5)))
return (err, averr, mxerr, t_averr, t_mxerr)
def edit_samples(self):
if self.__visible_edit_samples is None:
self.__visible_edit_samples = 30
self.gui_samples_list.place(y=-500)
else:
try:
if self.set_samples() is not False:
self.get_samples()
self.gui_samples_list.place(y=self.__visible_edit_samples)
self.__visible_edit_samples = None
self.gui_samples_list.focus()
except IndexError:
self.gui.message("warning", "Warning!", self.localization("tsinc_error"))
return None
def clear_samples(self):
self.samples = []
self.get_samples()
self.refresh_st_samples()
def get_samples(self):
self.gui.set_text_textarea(self.gui_samples, data_samples(self.samples))
samples, k = "", 0
for i in self.samples:
samples += "%2d: " % k
k += 1
for j in i[0]:
samples += "% .2f " % round(j, 2)
samples += " -> "
for j in i[1]:
samples += "% .2f " % round(j, 2)
samples += "\n"
self.gui.set_text_listbox(self.gui_samples_list, samples)
def set_samples(self):
try:
self.samples = parse_samples(self.gui.get_text(self.gui_samples))
except ValueError:
self.gui.message("warning", "Warning!", self.localization("tsinc_error"))
return False
self.refresh_st_samples()
def load_samples(self):
f = self.gui.open_file(self.winNN, filetypes=[("JSON file", ".json")])
if not f:
return 0
try:
self.samples = json.load(f)
if type(self.samples) is not list:
raise ValueError
self.refresh_st_samples()
self.get_samples()
except ValueError:
self.gui.message("warning", "Warning!", self.localization("tins_error"))
return None
except TypeError:
self.gui.message("warning", "Warning!", self.localization("tins_error"))
return None
def load_tsamples(self):
f = self.gui.open_file(self.winNN, filetypes=[("JSON file", ".json")])
if not f:
return 0
try:
self.test_samples = json.load(f)
if type(self.test_samples) is not list:
raise ValueError
self.refresh_st_samples()
self.get_samples()
except ValueError:
self.gui.message("warning", "Warning!", self.localization("tints_error"))
return None
except TypeError:
self.gui.message("warning", "Warning!", self.localization("tints_error"))
return None
def save_samples(self):
self.set_samples()
f = self.gui.save_file(self.winNN, filetypes=[("JSON file", ".json")])
if not f:
return 0
try:
json.dump(self.samples, f)
except ValueError:
self.gui.message("error", "Error!", self.localization("io_error"))
return None
