Vectorizing matplotlib axes

Question

I am trying to avoid using "for" loops in some matplotlib plots. For this, I have tried the following code:

t=np.linspace(0,1,1000)
signals=[]

for k in range(8):  
    signals.append(np.sin(2*np.pi*t*k))
signals=np.array(signals)
    
units=np.array(['V', 'V', 'V', 'V', 'A', 'A', 'A', 'A'])
fig, axes = plt.subplots(8, 1,figsize=(10, 16))
# axes.plot(t,signals[units=="V",:])

The last commented line throws an error, because axes is a numpy array, which has no attribute "plot". I was trying to assign each axe to the plot of each signal.

How can I make this line with vectorization?

Thanks.

cheersmate · Accepted Answer · 2023-01-27 13:44:01Z

1

You cannot vectorize the creation of multiple subplots, but you can use a loop:

fig, axes = plt.subplots(signals.shape[0], 1, figsize=(8, signals.shape[0] * 2.5))

for i in range(signals.shape[0]):
    axes[i].plot(signals[i, ...])
    axes[i].set_ylabel('x(t) (unit: V)')
    ...

What you can do is plot everything into the same axes (simply use ax.plot(signals.T)).

answered Jan 27, 2023 at 13:44

cheersmate

2,6394 gold badges23 silver badges38 bronze badges

Sign up to request clarification or add additional context in comments.

Collectives™ on Stack Overflow

Vectorizing matplotlib axes

1 Answer 1

Comments

Your Answer

Hot Network Questions

Collectives™ on Stack Overflow

1 Answer 1

Comments

Your Answer

Sign up or log in

Post as a guest

Related