how to plot different plot in a single plot matplotlib

Question

I created 2 different plot in this way:

def first():
    fig, axes = plt.subplots(1, figsize=(10, 5))
    ...
    ...
    return fig, axes

def second():
    fig, axes = plt.subplots(1, figsize=(10, 5))
    ...
    ...
    return fig, axes

What I would like to do is to 'collect' these 2 plots in a single one. I try these solutions:

1:

fig, ax = plt.subplots(2, figsize=(15, 20))
ax[0].plot = first()
ax[1].plot = second()
plt.show()

2:

fig, ax = plt.subplots(2, figsize=(15, 20))
ax[0].plot = first()
ax[1].plot = second()
for ax in ax:
    ax.label_outer()
plt.show()

but anytime I got 3 different figures: one figures with 2 axes but empty and 2 figures with the right plot but not where I wanted to be

Can someone help and suggest what I get wrong in my code? thanks

The simplest approach would be to pass axe as a parameter to each function. Then they will plot your data into the right axis directly. Additionally you can create the axe if no axe are provided. — jlandercy
– jlandercy, Commented Apr 16, 2021 at 12:37

jlandercy · Accepted Answer · 2021-04-16 16:47:43Z

1

Here is a simple example of how you may proceed to achieve what you aim.

Lets create a function having axe switch to cope with existing matplotlib axe or create it if missing.

import matplotlib.pyplot as plt

def first(x, y, axe=None):
    if axe is None:
        fig, axe = plt.subplots()
    axe.plot(x, y)
    axe.set_ylabel("First")
    axe.grid()
    return axe

Similarly we create the second function:

def second(x, y, axe=None):
    if axe is None:
        fig, axe = plt.subplots()
    axe.plot(x, y)
    axe.set_ylabel("Second")
    axe.grid()
    return axe

The we create some synthetic data for display purpose:

import numpy as np

t = np.linspace(0, 2*np.pi, 250)
x1 = 3*np.sin(5*t)
x2 = 0.5*np.cos(15*t)

Then comes the magic, we create both axes and send references to their respective functions:

fig, axe = plt.subplots(2, 1, sharex=True, sharey=True)
first(t, x1, axe=axe[0])
second(t, x2, axe=axe[1])

Afterward we are still able to add features to axes:

axe[0].set_title("Some functional plots")
axe[1].set_xlabel("Time")

Final result looks like:

answered Apr 16, 2021 at 16:47

jlandercy

11.6k3 gold badges48 silver badges73 bronze badges

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

2 Comments

Luca Consorte Over a year ago

I preferred just to pass only axes as parameter since the data are more complex and preferred to select within the function: 'def first(axe=None):'

jlandercy Over a year ago

As you wish but it means your function is dependent of global variable and will not scale easily if you aims to extends their functionalities to other datasets. Choice is yours. I am glad it helped. Cheers.

Collectives™ on Stack Overflow

how to plot different plot in a single plot matplotlib

1 Answer 1

2 Comments

Your Answer

Hot Network Questions

Collectives™ on Stack Overflow

1 Answer 1

2 Comments

Your Answer

Sign up or log in

Post as a guest

Related