import numpy as np
import matplotlib.pyplot as plt
import time
@interact
def _(f=(1,10,1)):
plt.cla()
n = 100
T = 1
dt = T/n
x = np.arange(1, step=dt)
W = np.zeros(n, np.dtype(float))
t = np.arange(2.8,3.0,0.1)
l = np.sqrt(2*t*ln(ln(t)))
plt.plot(l) # <= add subplot
# Z variable, N(0,1)
mu, sig = 0, 1
for ITER in range(1, f+1):
for i in range(1, len(W)):
W[i] = W[i-1] + np.random.normal(mu, sig) * np.sqrt(dt)
plt.plot(x,W)
plt.show()
show many graphics in one plot (sage)
Pergunta
Hello could you please help me, how to .show() in same grid, nor a new plot each iteration.
import numpy as np
import matplotlib.pyplot as plt
import time
# Time step
n = 100 # Number of end-points
T = 1 # Length of [0,T] in time units
Delta = T/n
# Create a vector as for x-axis
x = np.arange(0, 1, .01)
# Create an empty vector W of the desired length
W = np.zeros(n, np.dtype(float))
# Z variable, N(0,1)
mu, sig = 0, 1
# The simulated path
for I in range(1, 4):
for i in range(1, len(W)):
W[i] = W[i-1] + np.random.normal(mu, sig) * np.sqrt(.01)
plt.subplot(2,2,2)
plt.plot(x,W)
time.sleep(2)
plt.show()
I definitely can not understand, why if I put plt.show() in loop => there would be as much plots as in loop range.
What should I do to get N plots appear in same subplot after some delay?
Thanks.
Solução
Licenciado em: CC-BY-SA com atribuição
Não afiliado a StackOverflow