Leomigotto em 21h51min de 29 de setembro de 2022

2022-09-29T21:51:30Z

← Edição anterior		Edição das 18h51min de 29 de setembro de 2022
Linha 22:		Linha 22:
	cc = irfft(cct)		cc = irfft(cct)
	return cc		return cc
			#SEMENTE UTILIZADA NA FIGURA DA PÁGINA: 4
	np.random.seed(4)		np.random.seed(4)

Leomigotto: Criou página com ' import numpy as np import matplotlib.pyplot as plt from scipy.fft import rfft, irfft, rfftfreq import os def cahnexp1d(cc, c1, c2): cc1 = np.copy(...'

2022-09-29T02:30:50Z

Criou página com '<source lang = "python"> import numpy as np import matplotlib.pyplot as plt from scipy.fft import rfft, irfft, rfftfreq import os def cahnexp1d(cc, c1, c2): cc1 = np.copy(...'

Página nova

<source lang = "python">
import numpy as np
import matplotlib.pyplot as plt
from scipy.fft import rfft, irfft, rfftfreq
import os
def cahnexp1d(cc, c1, c2):
cc1 = np.copy(cc)*c1
cc2 = np.copy(cc)*c2
cc3 = np.copy(cc**3)*c1
for i in range(l):
n = i - 2
cc[n] = ( 2*(cc1[n] - cc3[n]) + (cc3[n-1] + cc3[n+1] -1*(cc1[n-1] + cc1[n+1]))
-1*(cc2[n-2] + cc2[n+2] + 6*cc2[n])
+(4*cc2[n-1] + 4*cc2[n+1])
) + cc[n]
return cc

def cahnfourier1d(cc, k2, k4):
cct = rfft(cc)
cct3 = rfft(cc**3 - cc)
cct = cct + difd*dt*(-k2*(cct3) - k4*cct)
cc = irfft(cct)
return cc

np.random.seed(4)

xmin = 0

xmax = 1

tmin = 0

tmax = 1

dt = 1/22000000

dx = 1/128

difd = 1

gamma = (3.4/128)**2

l = int((xmax/dx))

k = rfftfreq(l, dx/(2*np.pi))

c1 = difd*dt/(dx**2)

c2 = gamma*c1/(dx**2)

k2 = k**2

k4 = (k2**2)*gamma

ccexp = np.random.rand(l)*2 - 1

ccfourier = np.copy(ccexp)

xx = np.linspace(0, xmax, l)

t = 0

u = 0

tamanho = l/2
plt.figure(figsize=(8, 8))
os.makedirs(f".\\1d", exist_ok = True)
while (t < tmax):
plt.cla()
plt.title(f"Tempo: {t:.7f}, maior erro: {np.amax(abs(ccexp-ccfourier)):.7f}")
plt.axhline(0, c = "red", alpha = 0.5)
plt.ylim(-1.1, 1.1)
plt.xlim(xmin, xmax)
plt.scatter(xx, ccexp, c = "orange", alpha = 0.6, label = "FTCS")
plt.plot(xx, ccexp, c = "orange", alpha = 0.4)
plt.scatter(xx, ccfourier, c = "blue", alpha = 0.4, label = "FFT")
plt.plot(xx, ccfourier, c = "blue", alpha = 0.6)
plt.scatter(xx, abs(ccexp-ccfourier), c = "red", alpha = 0.4, label = "Erro")
plt.legend(loc = 1)
if u%100 == 0:
plt.savefig(f".\\1d\\{t:.6f}.png", dpi = tamanho)
if u ==10000:
break
ccfourier = cahnfourier1d(ccfourier, k2, k4)
ccexp = cahnexp1d(ccexp, c1, c2)
t = round(t + dt, int(-np.log10(dt) + 1))
u+=1
</source>

Cahn1dcompare - Histórico de revisão

Leomigotto em 21h51min de 29 de setembro de 2022

Leomigotto: Criou página com ' import numpy as np import matplotlib.pyplot as plt from scipy.fft import rfft, irfft, rfftfreq import os def cahnexp1d(cc, c1, c2): cc1 = np.copy(...'