Plotting subplots from a nested for loop in Python

Question

I am trying to plot line plots(Drifted brownian motion) for different values of mu and sigma, I have a function that iterates a list of possible mu values and possible sigma values and it's supposed to then return the resulting plots. The problem is I am unsure how to make the subplots return the required number of rows. I have given it the correct nrows and ncols but the problem comes in with the indexing. Does anyone have a trick to solve this?

I have provided the code and the error message below,

# Drifted BM for varying values mu and sigma respectively

def DriftedBMTest2(nTraj=50,T=5.0,dt=0.01,n=5, sigma = [0.1,1.0,2], mulist=[0,0.5,1,1.5], ValFSize=(18,14)):

    nMu = len(mulist)
    nSigma = len(mulist)
    # Discretize, dt =  time step = $t_{j+1}- t_{j}$
    dt = T/(n-1)

    # Loop on different value sigma
    for z in range(nSigma): 
        # Loop on different value Mu
        for k in range(nMu):

            n=int(T/dt)
            x=np.zeros(n+1,float)

            # Create plot space 
            temp = nSigma*nMu/2
            plt.subplot(temp,2,k+1)
            plt.title("Drifted BM $\sigma$={}, $\mu$={}".format(sigma[z],mulist[k])) 
            plt.xlabel(r'$t$')
            plt.ylabel(r'$W_t$');

            # Container for colours for each trajectory
            colors = plt.cm.jet(np.linspace(0,1,nTraj))
            # Generate many trajectories
            for j in range(nTraj):

                # Time simulation
                # Add the time * constant(mu)
                for i in range(n):
                    x[i+1]=x[i]+np.sqrt(dt)*np.random.randn() + i*mulist[k]

                # Scale Each Tradjectory
                x = x * sigma[z]
                # Plot trajectory just computed
                plt.plot(np.linspace(0,T,n+1),x,'b-',alpha=0.3, color=colors[j], lw=3.0)

DriftedBMTest2( sigma = [1,2], mulist=[-2,1] )

I then get the first two plots but not all of them and the error below.

MatplotlibDeprecationWarning: Adding an axes using the same arguments as a previous axes currently reuses the earlier instance.  In a future version, a new instance will always be created and returned.  Meanwhile, this warning can be suppressed, and the future behavior ensured, by passing a unique label to each axes instance.

Sorry if this is a bad question, I am new to Python but any help would be appreciated.

Sheldore · Accepted Answer · 2020-04-11 23:34:00Z

1

Try adding fig = plt.figure() between the two for loops

for z in range(nSigma): 
    # Loop on different value Mu
    fig = plt.figure()   # <---- Line added here
    for k in range(nMu):

If that doesn't give the desired layout, you can try moving it to the inner for loop as

for z in range(nSigma): 
    # Loop on different value Mu
    for k in range(nMu):
        fig = plt.figure()  # <---- Line added here

answered Apr 11, 2020 at 23:34

Sheldore

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1 Comment

user4933 Over a year ago

Thanks @Sheldore, the first suggestion worked. The second one does something similar but not exactly what I was aiming for, it breaks the subgroups into 1 column of plots for all the plots.

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