Linearly scale axes from kilometers to meters for all plots in matplotlib-CodePudding

I am working with data in meters and want to plot positions. Having the ticks in meters is obscuring the readability of the plots, so I want to plot the data in kilometers. I know that it is possible to scale all data d/1000., however, this makes the code less readable in my eyes, especially if you're plotting many different lines, where you have to do this transformation every time.

I am looking for a general way to achieve this type of transformation, I could imagine there is a beautiful way to achieve this in matplotlib.

Some sample code for you:

import matplotlib.pyplot as plt
import numpy as np

x = np.linspace(7500, 30000, 300)
y_ref = np.linspace(5000, 15000, 300)
y_noised = y_ref   np.random.normal(0, 250, size=y_ref.size)

fig = plt.Figure(figsize=(6,6))
ax = fig.add_subplot(1, 1, 1)

ax.plot(x, y_ref, c='r')
ax.scatter(x, y_noised, alpha=0.2)
fig

I would like to have the following figure, without needing to scale x, y_ref and y_noised individually by 1000.

Is there a way to perform this transformation in matplotlib, such that you only need to do it for each figure once, no matter how many lines you plot?

CodePudding user response：

You could use a custom tick formatter like that (passing a function into