def Convolution(img):
os.system('clear')
Kernel = None
InpStr = ""
InpInt = 0
print("1) [[1, 1, 1], [1, 1, 1], [1, 1, 1]] / 9")
print(
"2) [[1, 1, 1, 1, 1], [1, 1, 1, 1, 1], [1, 1, 1, 1, 1], [1, 1, 1, 1, 1], [1, 1, 1, 1, 1]] / 25"
)
print()
print("3) [[1, 1, 1], [1, 2, 1], [1, 1, 1]] / 10")
print("4) [[1, 2, 1], [2, 4, 2], [1, 2, 1]] / 16")
print("5) [[1, 1, 1], [1, 0, 1], [1, 1, 1]] / 9")
print()
print(
"6) [[1, 4, 7, 4, 1], [4, 16, 26, 16, 4], [7, 26, 41, 26, 7], [4, 16, 26, 16, 4],[1, 4, 7, 4, 1]] / 273"
)
print()
print("7) [[-1, -2, -1], [0, 0, 0], [1, 2, 1]]")
print("8) [[-1, 0, 1], [-2, 0, 2], [-1, 0, 1]]")
print()
print("9) [[1 * 129] * 129]]")
print()
print("10) [[1], [-1]]")
print("11) [[1, -1]]")
print("12) [[0, 1], [-1, 0]]")
print("13) [[1, 0], [0, -1]]")
print()
print("14) [[1, 1, 1,], [0, 0, 0], [-1, -1, -1]]")
print("15) [[1, 0, -1], [1, 0, -1], [1, 0, -1]]")
print()
print("16) [[0, 1, 0], [1, -4, 1], [0, 1, 0]]")
print("17) [[1, 1, 1], [1, -8, 1], [1, 1, 1]]")
print(
"18) [[0, 0, 1, 0, 0], [0, 1, 2, 1, 0], [1, 2, -16, 2, 1], [0, 1, 2, 1, 0], [0, 0, 1, 0 ,0]]"
)
print(
"19) [[2, 4, 5, 4, 2], [4, 9, 12, 9, 4], [5, 12, 15, 12, 5], [4, 9, 12, 9, 4], [2, 4, 5, 4, 2]]"
)
print()
print("20) High-boost [0, -1, 0], [-1, 8, -1], [0, -1, 0]")
print("21) High-boost [-1, -1, -1], [-1, 16, -1], [-1, -1, -1]")
print("0) EXIT")
while 1:
InpStr = input("Input the kernal number you need: ")
try:
InpInt = int(InpStr)
except:
print("Input Error")
continue
else:
if InpInt < 0 or InpInt > 30:
print("Input Error")
continue
else:
break
if InpInt == 0:
return img
if InpInt == 1:
Kernel = np.array([[1, 1, 1], [1, 1, 1], [1, 1, 1]]) / 9
if InpInt == 2:
Kernel = np.array([[1, 1, 1, 1, 1], [1, 1, 1, 1, 1], [1, 1, 1, 1, 1],
[1, 1, 1, 1, 1], [1, 1, 1, 1, 1]]) / 25
if InpInt == 3:
Kernal = np.array([[1, 1, 1], [1, 2, 1], [1, 1, 1]]) / 10
if InpInt == 4:
Kernel = np.array([[1, 2, 1], [2, 4, 2], [1, 2, 1]]) / 16
if InpInt == 5:
Kernel = np.array([[1, 1, 1], [1, 0, 1], [1, 1, 1]]) / 9
if InpInt == 6:
Kernel = np.array([[1, 4, 7, 4, 1], [4, 16, 26, 16, 4],
[7, 26, 41, 26, 7], [4, 16, 26, 16, 4],
[1, 4, 7, 4, 1]]) / 273
if InpInt == 7:
Kernel = np.array([[-1, -2, -1], [0, 0, 0], [1, 2, 1]])
if InpInt == 8:
Kernel = np.array([[-1, 0, 1], [-2, 0, 2], [-1, 0, 1]])
if InpInt == 9:
Kernel = np.array([[1 for n in range(129)] for n in range(129)]) / 129
if InpInt == 10:
Kernel = np.array([[1], [-1]])
if InpInt == 11:
Kernel = np.array([[1, -1]])
if InpInt == 12:
Kernel = np.array([[0, 1], [-1, 0]])
if InpInt == 13:
Kernel = np.array([[1, 0], [0, -1]])
if InpInt == 14:
Kernel = np.array([[
1,
1,
1,
], [0, 0, 0], [-1, -1, -1]])
if InpInt == 15:
Kernel = np.array([[1, 0, -1], [1, 0, -1], [1, 0, -1]])
if InpInt == 16:
Kernel = np.array([[0, 1, 0], [1, -4, 1], [0, 1, 0]])
if InpInt == 17:
Kernel = np.array([[1, 1, 1], [1, -8, 1], [1, 1, 1]])
if InpInt == 18:
Kernel = np.array([[0, 0, 1, 0, 0], [0, 1, 2, 1, 0], [1, 2, -16, 2, 1],
[0, 1, 2, 1, 0], [0, 0, 1, 0, 0]])
if InpInt == 19:
Kernel = np.array([[2, 4, 5, 4, 2], [4, 9, 12, 9, 4], [
5, 12, 15, 12, 5
], [4, 9, 12, 9, 4], [2, 4, 5, 4, 2]]) / 115
if InpInt == 20:
Kernel = np.array([[0, -1, 0], [-1, 8, -1], [0, -1, 0]])
if InpInt == 21:
Kernel = np.array([[-1, -1, -1], [-1, 16, -1], [-1, -1, -1]])
#Kernel = np.array([[]])
#Kernel = np.array([[]])
"""
InpInt = 0
print("1) Normal Convolution method")
print("2) FFT-IFFT Method")
while 1:
InpStr = input("Now input the way to convolution: ")
try:
InpInt = int(InpStr)
except:
print("Input Error")
continue
else:
if InpInt < 0 or InpInt > 2:
print("Input Error")
continue
else:
break
if InpInt == 1:
img = NormalConvolution(img, Kernel)
else:
NewImg = D2FFT(img, Kernel)
for i in range(0, len(img)):
for j in range(0, len(img[0])):
try:
img[i][j] = NewImg[i+1][j+1]
except:
print("Error")
return [0]
"""
NewImg = D2FFT(img, Kernel)
for i in range(0, len(img)):
for j in range(0, len(img[0])):
try:
img[i][j] = NewImg[i + 1][j + 1]
except:
print("Error")
return [0]
Init.ArrOutput(img)
return img
def main(OutputFile=False, initial_val=[], old_information="", Calc_Jaco=True):
map_model = False
File = 0
if OutputFile:
FileName = os.path.join(
"Output", model.model_name + str(Init.GetTime()) + ".model")
File = open(FileName, "a")
if len(initial_val) == 0:
initial_val = model.initial_val
initial_t = model.initial_t
final_t = model.final_t
delta_t = model.delta_t
information = model.information
if type(delta_t) == int:
map_model = True
delta_t = float(delta_t)
if len(old_information) != 0:
if information != old_information:
while 1:
print(
"WARNING, you may used wrong model because old model information is different from new one."
)
print(old_information)
print(information)
inp_str = input("Continue? (y/n)")
if inp_str == "y":
break
elif inp_str == "n":
sys.exit()
else:
os.system("clear")
print("Input error")
continue
String = information
String += "\n"
String += str(initial_t) + " "
String += str(final_t) + " "
String += str(delta_t) + " \n"
print(String)
print("Data generate")
if map_model == False:
Val_set = Runge_Kutta("model.f", initial_val, initial_t, final_t,
delta_t)
Val_set = Val_set.tolist()
if OutputFile:
String += Init.ArrOutput(Val_set, Mode=0, Save_File=False)
String = write_str(File, String)
else:
Val_set = map_calculator("model.f", initial_val, initial_t, final_t,
delta_t)
Val_set = Val_set.tolist()
if OutputFile:
String += Init.ArrOutput(Val_set, Mode=0, Save_File=False)
String = write_str(File, String)
Jaco_set = []
if Calc_Jaco:
print("Jacobian generate")
pool = multiprocessing.Pool(processes=MULTI_CORE)
Jaco_set = pool.map(model.Jf, Val_set)
pool.close()
pool.join()
if OutputFile:
String = write_str(File, String)
if OutputFile:
print("Model Output")
tmp = []
for i in range(0, len(Jaco_set)):
tmp.append(
np.resize(Jaco_set[i],
(len(initial_val) * len(initial_val))).tolist())
String += Init.ArrOutput(tmp, Mode=0, Save_File=False)
String = write_str(File, String)
File.close()
if CAL_ERROR:
Data_block = []
for kase in range(0, len(Jaco_set) - 1):
Jaco = Jaco_set[kase].tolist()
tmp_block = []
tmp_block.append(Jaco)
tmp_block.append(Val_set[kase])
tmp_block.append(Val_set[kase + 1])
tmp_block.append(len(initial_val))
Data_block.append(tmp_block)
pool = multiprocessing.Pool(processes=MULTI_CORE)
error_meow = pool.map(Cal_error_meow, Data_block)
pool.close()
pool.join()
print(error_meow)
FileName = os.path.join(
"Output",
model.model_name + "-error" + str(Init.GetTime()) + ".model")
File = open(FileName, "w")
File.write(str(error_meow))
File.close()
x = [n + 1 for n in range(len(Jaco_set) - 1)]
fig = plt.gcf()
plt.grid(True)
plt.plot(x, error_meow)
plt.show()
return information, initial_val, initial_t, final_t, delta_t, Val_set, Jaco_set
