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    <p>Ok, I've made a somewhat satisfactory solution. It is wordy and still a bit hackish, but it works! It provides a <strong>fixed display offset</strong> around each point, it stands against interactive stuff - zooming, panning etc - and maintains the same display offset whatever you do.</p> <p>It works by creating a custom <code>matplotlib.transforms.Transform</code> object for each line patch in a plot. It is certainly a slow solution, but plots of this kind are not intended to be used with hundreds or thousands of points, so I guess performance is not such a big deal.</p> <p>Ideally, all those patches are needed to be combined into one single "plot-line", but it suits me as it is.</p> <pre><code>import numpy as np import matplotlib as mpl import matplotlib.pyplot as plt class MyTransform(mpl.transforms.Transform): input_dims = 2 output_dims = 2 def __init__(self, base_point, base_transform, offset, *kargs, **kwargs): self.base_point = base_point self.base_transform = base_transform self.offset = offset super(mpl.transforms.Transform, self).__init__(*kargs, **kwargs) def transform_non_affine(self, values): new_base_point = self.base_transform.transform(self.base_point) t = mpl.transforms.Affine2D().translate(-new_base_point[0], -new_base_point[1]) values = t.transform(values) x = values[:, 0:1] y = values[:, 1:2] r = np.sqrt(x**2+y**2) new_r = r-self.offset new_r[new_r&lt;0] = 0.0 new_x = new_r/r*x new_y = new_r/r*y return t.inverted().transform(np.concatenate((new_x, new_y), axis=1)) def my_plot(X,Y): ax = plt.gca() line, = ax.plot(X, Y, marker='o', linestyle='') color = line.get_color() size = X.size for i in range(1,size): mid_x = (X[i]+X[i-1])/2 mid_y = (Y[i]+Y[i-1])/2 # this transform takes data coords and returns display coords t = ax.transData # this transform takes display coords and # returns them shifted by `offset' towards `base_point' my_t = MyTransform(base_point=(mid_x, mid_y), base_transform=t, offset=10) # resulting combination of transforms t_end = t + my_t line, = ax.plot( [X[i-1], X[i]], [Y[i-1], Y[i]], linestyle='-', color=color) line.set_transform(t_end) fig = plt.figure(figsize=(8,6)) axes = plt.subplot(111) X = np.linspace(0,2*np.pi, 8) Y = np.sin(X) my_plot(X,Y) plt.show() </code></pre> <p><img src="https://i.stack.imgur.com/9jphL.png" alt="enter image description here"></p>
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