Plot multiple graphs without using a for loop

Question

So, my question may not be exactly what is in the title.

I have a function

y = a*x + b

And I want to plot y whith different values of b.

I know that I can do the following:

import numpy as np
import matplotlib.pyplot as plt

a = 2
x = np.array([0,1,2,3,4])
b = 0

for i in range(10):
    y = a*x + b
    b = b+1
    plt.plot(x,y)

And that returns exactly what I want.

But, there is someway that I can make this by using b = np.array([0,1,2,3,4,5,6,7,8,9])? So, then my code could look something like:

import numpy as np
import matplotlib.pyplot as plt

a = 2
x = np.array([0,1,2,3,4])
b = np.array([0,1,2,3,4,5,6,7,8,9])

y = a*x + b
plt.plot(x,y)

Diziet Asahi · Accepted Answer · 2020-09-17T15:21:13.810

1

Yes, you can use matrix operations to create a 2D matrix with the result of the operation y = a*x + b.

a = 2
x = np.array([0,1,2,3,4])
b = np.array([0,1,2,3,4,5,6,7,8,9])

y = a*x[:,None]+b
plt.plot(x, y)

EDIT: I'm shwing the solution provided by @Quang Hoang which is much simpler than mine. original code was:

y = np.tile(a*x, (b.size,1)) + b[:,np.newaxis]
plt.plot(x, y.T)

edited Sep 17 '20 at 15:21

answered Sep 16 '20 at 18:53

Diziet Asahi

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also `y = a*x[:, None] + b` and `plt.plot(x,y)` – Quang Hoang Sep 16 '20 at 19:18
@QuangHoang of course, much simpler. Don't know why I went the other direction. Thanks for that – Diziet Asahi Sep 16 '20 at 21:03
Cool! But, I dont think I understand what is happening here. Isnt that the same of `y = a*np.transpose(x) + b`? – David Daminelli Sep 17 '20 at 14:37
No, you need to transform your vector to a 2D matrix. The transpose of a vector is the same vector. See https://stackoverflow.com/questions/29241056/how-does-numpy-newaxis-work-and-when-to-use-it – Diziet Asahi Sep 17 '20 at 15:17

Plot multiple graphs without using a for loop

1 Answers1