try:
x = allread('reflectance').Frequency_trans_reflect_TDS(
'/Users/ryoya/kawaseken/20190123/2019_0123_{0}mm_{1}.txt'.
format(i, j),
'/Users/ryoya/kawaseken/20190123/2019_0123_ref_1.txt', 1.40,
1.60)
if flag == 0:
x_all = x
flag += 1
else:
x_all = np.append(x_all, x, axis=0)
y_all.append(i)
except FileNotFoundError as e:
print(e)
#train_test_split(特徴量,目的関数,1つの厚さにおけるtrainデータの数)
train_x, train_y, test_x, test_y = train_test_split(x_all, y_all, 1)
#print(train_x)
#print(train_y)
#print(test_x)
#print(test_y)
#print(x_all)
#print(y_all)
#referenceのカラーコード
#カラーコードのタグの数width=4,length=4の場合16個のタグに対応
width = 4
length = 4
colorcode(test_y, width, length)
#SVM
best_pred = svm(train_x, train_y, test_x, test_y)
colorcode(best_pred, width, length)
if flag == 0:
x_all = x
flag += 1
else:
x_all = np.append(x_all, x, axis=0)
y_all.append(l)
except FileNotFoundError as e:
print(e)
l = l + 1
mm = preprocessing.MinMaxScaler()
x_all_2 = mm.fit_transform(x_all)
print(x_all_2)
print(x_all)
#train_test_split(特徴量,目的関数,1つの厚さにおけるtrainデータの数)
train_x,train_y,test_x,test_y = train_test_split(x_all_2,y_all,1)
print(y_all)
#print(train_x)
print(train_y)
#print(test_x)
#print(test_y)
#print(x_all)
#print(y_all)
#referenceのカラーコード
#カラーコードのタグの数width=4,length=4の場合16個のタグに対応
width = 3
length = 4
#colorcode(test_y,width,length)
#SVM
best_pred=svm(train_x,train_y,test_x,test_y)