class MidpointNormalize(Normalize):

`MidpointNormalize` is a custom normalization class in Python that inherits from `Normalize` class. It is used to normalize data such that the midpoint of the color range corresponds to a specified value.

The `Normalize` class is a matplotlib class used for normalizing scalar data into the 0-1 range for color mapping. It takes two arguments, `vmin` and `vmax`, which specify the minimum and maximum values of the scalar data.

In the `MidpointNormalize` class, we add an additional argument `vcenter`, which specifies the midpoint value of the color range. We then override the `__call__` method of the `Normalize` class to normalize the data such that the midpoint value corresponds to 0.5 in the normalized range.

Here's an example of how to use `MidpointNormalize`:

import matplotlib.pyplot as plt
from matplotlib.colors import MidpointNormalize

data = [[-1, 0, 1], [2, 3, 4], [5, 6, 7]]

fig, ax = plt.subplots()
im = ax.imshow(data, cmap='coolwarm', norm=MidpointNormalize(vmin=-1, vmax=7, vcenter=3))

plt.colorbar(im)
plt.show()

In this example, we create a 3x3 matrix `data` with values ranging from -1 to 7. We then create a heatmap of this data using `imshow` function and specify the colormap as `coolwarm`. We also specify the normalization to be `MidpointNormalize` with `vmin=-1`, `vmax=7`, and `vcenter=3`. This means that the color range will be from blue to red, with white corresponding to the value of 3.