How do I place extents on the `colorbar`

in a `hist2d`

?

What I need is a fixed range for the colorbar, so that various plots are all comparable. How do I achieve this?

EDIT: adding code that shows the issue:

```
import matplotlib.pyplot as plt
from matplotlib.colors import LogNorm
from numpy.random import default_rng
import numpy as np
RG = default_rng()
NORMZ = LogNorm()
SIDE = 6
GRATIO = 1.5
FIG, AXES = plt.subplots(2, constrained_layout=True, figsize=(SIDE, SIDE))
SAMPLES_X1 = RG.lognormal(3.0, 5.0, 5000)
SAMPLES_Y1 = RG.lognormal(3.0, 5.0, 5000)
BIN_EDGES_X = np.histogram_bin_edges(np.log10(SAMPLES_X1), bins=100)
BIN_EDGES_X = np.power(10, BIN_EDGES_X)
BIN_EDGES_Y = np.histogram_bin_edges(np.log10(SAMPLES_Y1), bins=100)
BIN_EDGES_Y = np.power(10, BIN_EDGES_Y)
IM = AXES[0].hist2d(SAMPLES_X1, SAMPLES_Y1, [BIN_EDGES_X, BIN_EDGES_Y],
cmap='cool', density=True, norm=NORMZ)
print(np.min(IM[0][np.nonzero(IM[0])]), np.max(IM[0]))
print(IM[1][0], IM[1][-1])
print(IM[2][0], IM[2][-1])
FIG.colorbar(IM[3], ax=AXES)
SAMPLES_X2 = RG.lognormal(3.0, 7.0, 5000)
SAMPLES_Y2 = RG.lognormal(3.0, 7.0, 5000)
BIN_EDGES_X = np.histogram_bin_edges(np.log10(SAMPLES_X2), bins=100)
BIN_EDGES_X = np.power(10, BIN_EDGES_X)
BIN_EDGES_Y = np.histogram_bin_edges(np.log10(SAMPLES_Y2), bins=100)
BIN_EDGES_Y = np.power(10, BIN_EDGES_Y)
IM = AXES[1].hist2d(SAMPLES_X2, SAMPLES_Y2, [BIN_EDGES_X, BIN_EDGES_Y],
cmap='cool', density=True, norm=NORMZ)
print(np.min(IM[0][np.nonzero(IM[0])]), np.max(IM[0]))
print(IM[1][0], IM[1][-1])
print(IM[2][0], IM[2][-1])
#FIG.colorbar(IM[3], ax=AXES)
AXES[0].tick_params(length=9, labelsize=15)
AXES[0].set_yscale('log')
AXES[0].set_xscale('log')
AXES[1].tick_params(length=9, labelsize=15)
AXES[1].set_yscale('log')
AXES[1].set_xscale('log')
plt.show()
```