def DataConv_click():
inputPath = __filePath__(txtConv_1.get())
learnPath = __filePath__(txtConv_2.get())
testPath = __filePath__(txtConv_3.get())
digit = str(10**-int(txtConv_4.get()))
io = csvIO()
v = io.open_twoD_array(inputPath)
v = io.twoD_FroatToStr(v, digit=digit)
l_array = io.Get_AnytwoD_array(v, col_range_end=3)
t_array = io.Get_AnytwoD_array(v, col_range_first=4, col_range_end=7)
io.csv_write(learnPath, l_array)
io.csv_write(testPath, t_array)
def DataInput():
xPath = __filePath__(txt_6.get())
tPath = __filePath__(txt_7.get())
io = csvIO()
x = io.open_twoD_array(xPath)
t = io.open_twoD_array(tPath)
x = io.twoD_FroatToStr(x, digit=0.01)
t = io.twoD_FroatToStr(t, digit=0.01)
x = io.twoD_Numpy(x)
t = io.twoD_Numpy(t)
print('読み込みに成功')
return x, t
# cording: utf-8
import sys, os
sys.path.append(os.getcwd())
from common.squential import *
from common.layers import *
from common.csvIO import csvIO
import matplotlib.pyplot as plt
# データを読み込む
io = csvIO()
learn_file = io.open_twoD_array('./data/learn.csv')
test_file = io.open_twoD_array('./data/test.csv')
learn_data = io.twoD_Numpy(learn_file)
test_data = io.twoD_Numpy(test_file)
model = Sequential()
model.add(InputLayer(input_shape=(3, ))) #3, 128
model.add(Dense(50, activation='sigmoid', weight_initializer='sigmoid'))
model.add(Dense(50, activation='sigmoid', weight_initializer='sigmoid'))
model.add(Dense(3, activation='linear'))
model.compile(loss='mean_squared_error', optimizer='sgd', metrics=['accuracy'])
#学習
epochs = 20
batch_size = 128
history = model.fit(learn_data, test_data, batch_size, epochs)
print(history['loss'])