import matplotlib.pyplot as plt
import numpy as np
from matplotlib.transforms import Transform

class TransformDemo(Transform):
    
    def __init__(self):
        
        super().__init__()
        
        self.input_dims = 2
        self.output_dims = 2
        self.is_separable = False
        
    def transform_non_affine(self, values):
        output = np.empty_like(values)
        output[:, 0] = values[:, 0]
        output[:, 1] = 100 + values[:, 1] / (1 + np.abs(values[:, 0]))
        
        return output

# Make some random data
y = np.random.randn(1000)
x = np.arange(len(y))

fig, ax = plt.subplots(ncols=2)

T = TransformDemo()

# First with plot, everything works as expected
ax[0].plot(x, y, transform=T + ax[0].transData)

# With fill_between, limits are not inferred correctly
ax[1].fill_between(x, -np.abs(y), np.abs(y), transform=T + ax[1].transData)

ax[1].set_ylim(ax[0].get_ylim())