Set yaxis of all subplots to the same range - Matplotlib

31,691

Solution 1

Your 1st line

f, axes = plt.subplots(7, 1, sharex='col', sharey='row', figsize=(15, 30))

has an inappropriate value for the sharey parameter. Using sharey='row' you're asking that all the subplots in each row share the same y axis, but each of your subplots is in a row by itself, so you see no sharing.

If you try sharey=True or sharey='col' you'll get what you want.

Addendum

The following code

In [34]: a = np.random.random(21)

In [35]: b = a+5

In [36]: x = np.arange(21)

In [37]: f, (ax, bx) = plt.subplots(2,1,sharey='row') # like yours

In [38]: ax.plot(x,a)
Out[38]: [<matplotlib.lines.Line2D at 0x7f5b98004f98>]

In [39]: bx.plot(x,b)
Out[39]: [<matplotlib.lines.Line2D at 0x7f5b980238d0>]

In [40]: f, (ax, bx) = plt.subplots(2,1,sharey='col') # like mine

In [41]: ax.plot(x,a)
Out[41]: [<matplotlib.lines.Line2D at 0x7f5b94764dd8>]

In [42]: bx.plot(x,b)
Out[42]: [<matplotlib.lines.Line2D at 0x7f5b98038198>]

In [43]: 

gives me the following two plots. Can you spot a single difference?

Using sharey='row'

Using sharey='col'

Solution 2

You have to add a line axes[i].set_ylim(ymin,ymax) within the main loop where you make the plot. For example, below the following line

axes[i].set_title('Simulation '+str(i+1), fontsize=20)

add:

axes[i].set_ylim(-1,1)

That should solve it.

In your example, you are calling plt.ylim instead, but from the documentation "Get or set the y-limits of the current axes", which in your case correspond to the last axes.

Answer to the minimalist example:

As you see from your plot, all the axis but the last, have the same limits in the y-coordinate. Everytime you call plt.*, you affect the behaviour of the last axis. Your last call to plt.axis('equal') is what affects the last plot. Just remove this line.

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31,691
pceccon
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pceccon

Updated on July 29, 2022

Comments

  • pceccon
    pceccon almost 2 years

    I'm wondering how do I force my subplots to share the y-axis range. This is my code:

    f, axes = plt.subplots(7, 1, sharex='col', sharey='row', figsize=(15, 30))
    distance = []
    
    for i in range(simulations):
        delta = numpy.zeros((simulations+samples, simulations+samples))
        data_x = sample_x[i*samples:(i*samples)+samples] + ensamble_x
        data_y = sample_y[i*samples:(i*samples)+samples] + ensamble_y
        for j in range(simulations+samples):
            for k in range(simulations+samples):
                if j <= k:
                    dist = similarity_measure((data_x[j].flatten(), data_y[j].flatten()), (data_x[k].flatten(), data_y[k].flatten()))
                    delta[j, k] = delta[k, j] = dist
    
        delta = 1-((delta+1)/2)  
        delta /= numpy.max(delta)
        model = manifold.TSNE(n_components=2, random_state=0, metric='precomputed')
        coords = model.fit_transform(delta)
    
        mds = manifold.MDS(n_components=2, max_iter=3000, eps=1e-9, random_state=0,
                       dissimilarity="precomputed", n_jobs=1)
        coords = mds.fit(delta).embedding_
    
        close, far = find_distance(coords[:samples, :], coords[samples+i, :])
    
        distance.append((close, far))
    
        axes[i].scatter(coords[:samples, 0], coords[:samples, 1], marker='x', c=colors[i], s=50, edgecolor='None')
        axes[i].scatter(coords[samples:, 0], coords[samples:, 1], marker='o', c=colors,    s=50, edgecolor='None')
    
        axes[i].scatter(coords[close, 0], coords[close, 1], marker='s', facecolor="none", c=colors[i], s=50, edgecolor='None')
        axes[i].scatter(coords[far, 0]  , coords[far, 1]  , marker='s', facecolor="none", c=colors[i], s=50, edgecolor='None')
    
        axes[i].set_title('Simulation '+str(i+1), fontsize=20)
    
    markers = []
    labels = [str(n+1) for n in range(simulations)]
    for i in range(simulations):
         markers.append(Line2D([0], [0], linestyle='None', marker="o", markersize=10, markeredgecolor="none", markerfacecolor=colors[i]))
    lgd = plt.legend(markers, labels, numpoints=1, bbox_to_anchor=(1.0, -0.055), ncol=simulations) 
    plt.tight_layout()
    plt.ylim(-1, 1)
    plt.axis('equal')
    plt.savefig('Simulations.pdf', bbox_extra_artists=(lgd,), format='pdf', bbox_inches='tight')
    

    And it's result:

    enter image description here

    As can be seen, the y axis limits differs from one subplot to another. I'd like to use the max/min range generated.

    Thank you.

    EDTI: MINIMAL EXAMPLE

    %matplotlib inline
    
    from sklearn.preprocessing import normalize
    from sklearn import manifold
    from matplotlib import pyplot as plt
    from matplotlib.lines import Line2D
    
    import numpy
    import itertools
    
    f, axes = plt.subplots(7, 1, sharex='col', sharey='row', figsize=(15, 30))
    distance = []
    
    for i in range(7):
        delta = numpy.random.randint(0, 100, (100, 100))
    
        axes[i].scatter(delta[:, 0], delta[:, 1], marker='x', c='r', s=50, edgecolor='None')
    
        axes[i].set_title('Simulation '+str(i+1), fontsize=20)
        axes[i].set_ylim(0, 100)
    
    markers = []
    
    plt.tight_layout()
    plt.axis('equal')
    

    enter image description here

  • Alejandro
    Alejandro about 8 years
    Could you please post a minimialist example that allow us to test?
  • pceccon
    pceccon about 8 years
    Done, @Alejandro. (:
  • pceccon
    pceccon about 8 years
    That was my first attempt. Will try without plt.axis('equal').
  • pceccon
    pceccon about 8 years
    It worked. It was my first try but I didn't know this "issue" about the plt calling. Thanks.
  • Alejandro
    Alejandro about 8 years
    This is not an "issue". It is the expected behaviour once you read the documentation.
  • pceccon
    pceccon about 8 years
    Thank you for your answer. (:
  • Dan
    Dan about 3 years
    So much cleaner!! :)