[matplotlib]: understanding "set_ydata" method

Question

I am trying to understand how to use "set_ydata" method, I found many examples on matplotlib webpages but I found only codes in which "set_ydata" is "drowned" in large and difficult to understand codes.

I would like a short and easy to understand code that help me understanding how "set_ydata" works. Here a short code that provide the plot underneath

import matplotlib.pyplot as plt
import numpy as np

x = np.arange(-3, 3, 0.01)
j = 1
y = np.sin( np.pi*x*j ) / ( np.pi*x*j )
fig = plt.figure()
ax = fig.add_subplot(111)
line, = ax.plot(x, y)
plt.show()

Now, with the following code, I delete the line drawn on the "ax" subplot, I use "set_ydata" to modify the plot and finally I would like to draw the line again, but I don't find anything that do the last step

line.remove()
j = 2
y = np.sin( np.pi*x*j ) / ( np.pi*x*j )
line.set_ydata(y)

not "plt.draw()" neither "plt.show()" draw anything. Could you suggest me anything that draw the new line?

Answer 1

It is not surprising that you see nothing if you remove the line that you set the data to.

As the name of the function set_data suggests, it sets the data points of a Line2D object. set_ydata is a special case which does only set the ydata.

The use of set_data mostly makes sense when updating a plot, as in your example (just without removing the line).

import matplotlib.pyplot as plt
import numpy as np

x = np.arange(-3, 3, 0.01)
j = 1
y = np.sin( np.pi*x*j ) / ( np.pi*x*j )
fig = plt.figure()
ax = fig.add_subplot(111)
#plot a line along points x,y
line, = ax.plot(x, y)
#update data
j = 2
y2 = np.sin( np.pi*x*j ) / ( np.pi*x*j )
#update the line with the new data
line.set_ydata(y2)

plt.show()

It is obvious that it would have been much easier to directly plot ax.plot(x, y2). Therefore set_data is commonly only used in cases where it makes sense and to which you refer as "large and difficult to understand codes".