CODEWITHSUNDEEP
pythonmatplotlibseabornscientific-computing
JohnGoodWill
JohnGoodWill

Reputation: 83

Python: Update plot instead of creating a new one

I am trying to code the Ising Model using Python.

I think, I've coded it correctly, but I have a problem with the animation or the plotting. I seem to plot a new image of every configuration, instead of updating the existing one, resulting in a lot of saved images that I don't need. I just want a single plot that is being updated, if that's possible.

I know, I am plotting inside the loop, but I don't recall that being an issue, when I want to plot every iteration. Can it be a problem with Seaborn's heatmap?

I've attached my code:

import numpy as np
import numpy.random as npr
import matplotlib.pyplot as plt
import seaborn as sns

#Constants
J = 1
h = 1
kbT = 1
beta = 1

#Grid
L = 20 #Dimensions
N = L**2 #Total number of grid points


#Initial configuration
spins = 2*np.random.randint(2, size = (L,L))-1


E = []
i = 0
plt.figure()

while i < 100000:
    for i in range(1,N):
        i += 1
        s = tuple(npr.randint(0, L, 2)) # Random initial coordinate
    
        # x and y coordinate
        (sx, sy) = s
        # Periodic boundary condition
        sl = (sx-1, sy) 
        sr = ((sx+1)%L, sy)
        sb = (sx, sy-1)
        st = (sx, (sy+1)%L)
        # Energy
        E =   spins[s] * ( spins[sl] + spins[sr] + spins[sb] + spins[st] )
        if E <= 0 : # If negative, flip
            spins[s] *= -1
        else:
            x = np.exp(-E/kbT) # If positve, check condition
            q = npr.rand()
            if x > q: 
                spins[s] *= -1
    # Plot (heatmap)
    sns.heatmap(spins, cmap = 'magma')
    plt.pause(10e-10)
    plt.draw()
    plt.show()

Upvotes: 1

Views: 2111

Answers (1)

Carlo Zanocco
Carlo Zanocco

Reputation: 2019

I think the function ion and clf could do the trick.

import numpy as np
import numpy.random as npr
import matplotlib.pyplot as plt
import seaborn as sns

#Constants
J = 1
h = 1
kbT = 1
beta = 1

#Grid
L = 20 #Dimensions
N = L**2 #Total number of grid points

#Initial configuration
spins = 2*np.random.randint(2, size = (L,L))-1

E = []
i = 0

plt.ion()
plt.figure()
plt.show()

while i < 100000:
    for i in range(1,N):
        i += 1
        s = tuple(npr.randint(0, L, 2)) # Random initial coordinate
    
        # x and y coordinate
        (sx, sy) = s
        # Periodic boundary condition
        sl = (sx-1, sy) 
        sr = ((sx+1)%L, sy)
        sb = (sx, sy-1)
        st = (sx, (sy+1)%L)
        # Energy
        E =   spins[s] * ( spins[sl] + spins[sr] + spins[sb] + spins[st] )
        if E <= 0 : # If negative, flip
            spins[s] *= -1
        else:
            x = np.exp(-E/kbT) # If positve, check condition
            q = npr.rand()
            if x > q: 
                spins[s] *= -1
    # Plot (heatmap)
    plt.clf()
    sns.heatmap(spins, cmap = 'magma')
    plt.pause(10e-10)

With the function ion you are making interactive the plot, so you need to:

  • Make it interactive
  • Show the plot
  • Clear the plot in your cycle

Here the reference for the ion function.

Reference for clf is here

Upvotes: 1

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