Matplotlib autoscale

autoscale.py

def autoscale(ax=None, axis='y', margin=0.1):
    '''Autoscales the x or y axis of a given matplotlib ax object
    to fit the margins set by manually limits of the other axis,
    with margins in fraction of the width of the plot
    
    Defaults to current axes object if not specified.
    '''
    import matplotlib.pyplot as plt
    import numpy as np
    if ax is None:
        ax = plt.gca()
    newlow, newhigh = np.inf, -np.inf

    for artist in ax.collections + ax.lines:
        x,y = get_xy(artist)
        if axis == 'y':
            setlim = ax.set_ylim
            lim = ax.get_xlim()
            fixed, dependent = x, y
        else:
            setlim = ax.set_xlim
            lim = ax.get_ylim()
            fixed, dependent = y, x

        low, high = calculate_new_limit(fixed, dependent, lim)
        newlow = low if low < newlow else newlow
        newhigh = high if high > newhigh else newhigh

    margin = margin*(newhigh - newlow)

    setlim(newlow-margin, newhigh+margin)
    
def calculate_new_limit(fixed, dependent, limit):
    '''Calculates the min/max of the dependent axis given 
    a fixed axis with limits
    '''
    if len(fixed) > 2:
        mask = (fixed>limit[0]) & (fixed < limit[1])
        window = dependent[mask]
        low, high = window.min(), window.max()
    else:
        low = dependent[0]
        high = dependent[-1]
        if low == 0.0 and high == 1.0:
            # This is a axhline in the autoscale direction
            low = np.inf
            high = -np.inf
    return low, high

def get_xy(artist):
    '''Gets the xy coordinates of a given artist
    '''
    if "Collection" in str(artist):
        x, y = artist.get_offsets().T
    elif "Line" in str(artist):
        x, y = artist.get_xdata(), artist.get_ydata()
    else:
        raise ValueError("This type of object isn't implemented yet")
    return x, y

# To test
fig, axes = plt.subplots(ncols = 4, figsize=(12,3))
(ax1, ax2, ax3, ax4) = axes

x = np.linspace(0,100,300)
noise = np.random.normal(scale=0.1, size=x.shape)
y = 2*x + 3 + noise

for ax in axes:
    ax.plot(x, y)
    ax.scatter(x,y, color='red')
    ax.axhline(50., ls='--', color='green')
for ax in axes[1:]:
    ax.set_xlim(20,21)
    ax.set_ylim(40,45)

autoscale(ax3, 'y', margin=0.1)
autoscale(ax4, 'x', margin=0.1)

ax1.set_title('Raw data')
ax2.set_title('Specificed limits')
ax3.set_title('Autoscale y')
ax4.set_title('Autoscale x')
plt.tight_layout()
fig.savefig('autoscale.png', dpi=400)

Thanks for the code, have found it on the Stackoverflow, works great on the sample example. I've tried to expand it to subplots, i.e. when one zooms a subplot with mouse, all other y axes auto-adjust or auto-scale as well, something like this:

import numpy as np
import matplotlib.pyplot as plt

x = np.linspace(0,100,1001)
y = np.sin(x/16) + np.cumsum(np.random.randn(1001))/30.

nb_subs = 2
fig, axs = plt.subplots(nb_subs,1,sharex=True)
for ax in axs:
    ax.plot(x,y)
    autoscale(ax, 'y', margin=0.1)
    
plt.show()

But have not managed to make it work, I realized my programming knowledge pretty limited. Have also searched a lot on web, also explored links that point to/from the Stack post. Would appreciate some help here to expand it to all subplots, thank you!

@smjure that's the same problem I've been trying to face.

It looks like there's no immediate solution. The problem is that autoscale will run once, at the beginning, but not every time someone zooms into the plots. You can repeatedly call autoscale whenever you need it, on all of your axes, but I'm sure that's not a desirable solution.

The other option is to add event-based callbacks to the figure. So if you click in the figure window, you run the code. You'd need to use something like this: https://matplotlib.org/3.2.1/api/_as_gen/matplotlib.pyplot.connect.html. For example, https://stackoverflow.com/a/33641336/6828087.