* Fixes numpy#23110

* the histogram `norm` variable is used to determine the bin
index of input values, and `norm` is calculated in some cases
by dividing `n_equal_bins` by the range of the data; when the
range of the data is extraordinarily small, the `norm` can become
floating point infinity

* in this patch, we delay calculating `norm` to increase resistance
to the generation of infinite values--for example, a really small
input value divided by a really small range is more resistant
to generating infinity, so we effectively just change the order
of operations a bit

* however, I haven't considered whether this is broadly superior
for resisting floating point non-finite values for other `histogram`
input/extreme value permutations--one might speculate that this is just
patching one extreme case that happened to show up in the wild, but
may increase likelihood of some other extreme case that isn't in our
testsuite yet

* the main logic for this patch is that it fixes an issue that
occurred in the wild and adds a test for
it--if another extreme value case eventually pops up, at least
this case will have a regression guard to keep guiding us in the right
direction