Avoid overhead in 2-D (or higher) hist operations

[SimonHeybrock]

hist uses bin when more than 1 dimension is involved. If there are many auxiliary coordinates that do not participate in the bin or subsequent hist operation then bin has to handle them, i.e., copy all the elements, etc. This can become costly:

import scipp as sc

da = sc.data.table_xyz(100_000_000)
da.variances = da.values
da.masks["mask1"] = da.coords["y"] > 0.5 * sc.Unit("m")
da.masks["mask2"] = da.coords["z"] > 0.5 * sc.Unit("m")

dummy = [f"dummy{i}" for i in range(10)]
for name in dummy:
    da.coords[name] = da.coords["x"].copy()

x = sc.linspace('x', 0, 1, 14*32+1, unit='m')
da.hist(x=x, y=100)  # 2 s
da.drop_coords(dummy).hist(x=x, y=100)  # 1 s

It should be simply do avoid this by changing the implementation of hist on the Python side.

[jokasimr]

Ping #3439