Let's have another look at conformal projections.
I've run into the Lagrange projection before, but hadn't thought much of it, due to the blatant, extreme exaggeration of Antarctica. However, its mention in this thread convinced me to take another look at it, and I realized that I haven't been giving it enough credit.
To start:
dummy_index wrote: ↑Sun Jan 12, 2020 5:12 amI don't know whether Lagrange is minimum total normalized area. But, in
https://en.wikipedia.org/wiki/Fracture_mechanics, it is natural that singular point will appear at the end of
interruption (ex. both pole with cutting 180° meridian.)
But Lagrange is not fit for min/max criterion... [/no conclusion]
I do think Lagrange can be proven to be optimal by this metric. Specifically...
Conjecture: If a region can be conformally mapped to a circle in such a way that the point of minimum scale is at the center, then that map has minimum area of all (normalized) conformal maps of the region.
Sketch of proof: Every conformal map will necessarily have the same
conformal radius at the point which corresponds to the center of the circular projection (when normalized so that scale is the same at this point). (Note that it is possible the point of minimum scale of an arbitrary projection is somewhere other than the center, but since this makes the projection worse, it suffices to show that the projection cannot be better than the circular projection even when this pitfall is ignored.) Therefore, the challenge becomes to determine the shape with the minimum possible area for a fixed conformal radius, or equivalently, the shape with the maximum possible conformal radius for a fixed area.
This is the hard part, because I haven't found any sources that clearly confirm what that shape would be. Conformal radii do not seem to be a well-documented topic. However, there does seem to be a paper (which is hidden behind a paywall, but it's cited in a few other papers that aren't) which proves a theorem that, among n-sided polygons with a fixed area, the one with the maximum conformal radius is the regular polygon. Since any shape can be approximated arbitrarily closely by a many-sided polygon, this does seem to suggest that the overall optimum would be achieved by a circle, even if that's a rather roundabout way of doing things.
So...?
In the case of the meridian-interrupted sphere, the Lagrange projection does indeed map it onto a circle with minimum scale at the center, therefore it should have the minimum possible area of any such projection.
Indeed, Lagrange does end up looking pretty good, as far as conformal projections go. When I visually compare the
Eisenlohr and
Lagrange projections (with central meridian 0) side by side, the Lagrange projection clearly shows less distortion at Alaska, Australia, and East Asia, while (of course) being about the same for Africa. The only place Eisenlohr is really obviously better is Antarctica, and maybe Greenland. However, since the projection space we were optimizing among was "maps interrupted along a single meridian", and such an interruption will always pass through Antarctica, it was a foregone conclusion that Antarctica couldn't possibly end up looking good anyway. (
I would be interested if anyone can calculate the exact contour line of where the Lagrange projection starts having worse distortion than the Eisenlohr projection. I have done so.)
This is really what bugs me about conformal projections: that the parts of the projection which are most heavily distorted (nearest to the interruptions or singularities) are drawn the largest, while the center of the map (which is where you usually try to put the stuff that interests you most) is drawn the smallest, so that an excessive amount of space is wasted on exactly the parts of the map that you
shouldn't be paying attention to.
(At least, for spherical maps. For hyperbolic maps, it's the opposite: the center of the map is drawn the largest. But hyperbolic projections have their own problems.)
...But is that always the case? After all, equal-area maps usually have their point of minimum angle distortion in the center, but as I showed above, that generalization can fail for certain shapes.
And indeed, much as I did with the Hammer projection, it's easy enough to use the opposite of the
Lagrange process (double rather than halve the Mercator projection) to map a quadrant into a circle. Attached below is the resulting projection, showing the same region as before, but now conformally rather than equal-area.

- antilagrange.png (147.96 KiB) Viewed 37600 times
It is easy to see from the graticule that this projection has minimum scale at the top and bottom sides of the map (the poles), and maximum scale at the left and right sides of the map, with intermediate scale in the center. (Note that this is still quite different from having low scale along the
entire boundary of the map, which so far still hasn't been proven either possible or impossible.)
Since the point of minimum scale is not at the center, the above conjecture does not apply here. It is not at all obvious what the optimal projection would be for this region (or other digons), either by the Eisenlohr criterion (minimize ratio of maximum to minimum scale / have constant scale along the boundary) or the Lagrange criterion (minimize total area). The latter
might still be this projection, or not. The former is extremely unlikely to have anywhere near convenient formulae (the Eisenlohr projection's formulae are already pretty nasty, even if they're technically closed-form). Maybe
dummy_index could wrangle a numerical approximation.
dummy_index wrote: ↑Tue Jan 07, 2020 6:38 amNeedless to say, Eisenlohr projection is a projection least area-error in the meaning of "infinity norm." In contrast, attempt to minimize "Entire strain energy" is "Euclidean norm" context and may lead differ answer (parhaps August projection, or maybe Lagrange projection.)
daan wrote: ↑Sat Jan 11, 2020 1:39 amCould you elaborate on how a least area-error metric could (or should) depend on anything except total normalized area? Why would any norm be relevant? Thanks.
I do understand what dummy_index is doing here.
For any p, it is possible to define the following metric:
metric = (integral_over_the_sphere(scale^p) / (4*pi))^(1/p) / minimum_over_the_sphere(scale)
Or for regional maps:
metric = ((integral_over_the_region(scale^p) / area_of_the_region)^(1/p) / minimum_over_the_region(scale)
(Where, of course, area_of_the_region = integral_over_the_region(1).)
Note that this can be mathematically understood as
the (renormalized for better behavior) p-norm of a vector space of uncountably-infinite dimension, hence the use of the "norm" terminology.
When p = 1, then this metric is simply the total area of the projection, and so it is minimized (among meridian-interrupted maps) by the Lagrange projection. The Eisenlohr projection is not minimal by this metric, but it is at least finite, unlike the Mercator projection.
When p = infinity (or in the limit as p goes to infinity, if you want to be pedantic), then this metric is the ratio of maximum to minimum scale, and so it is minimized (among meridian-interrupted maps) by the Eisenlohr projection. The Lagrange projection is pessimal, as despite having finite total area, the scale factor approaches inifinity near the polar singularities.
It is in principle possible to choose any other value of p, for example 2, and attempt to minimize the resulting metric, though this metric will not have as obvious a practical "meaning" as the p = 1 and p = infinity cases. It's only a true norm for p >= 1, but the metric is actually well-defined for any real value of p, as well as positive and negative infinity. (Though the case of negative infinity is trivial, as the metric as defined is always equal to 1. This suggests the possibility of taking the ratio of two p-norms to create an even more extended family of metrics...)
By taking p as a parameter for the projection, one could, in theory, produce a generalized Lagrange-Eisenlohr projection that allows a smooth transition between the two extremes, although, once again, it is extremely unlikely to have convenient math. (And it probably still won't include the August epicycloidal projection, which really has no justification beyond "one guy thought this looks good".)
One could also combine this with varying the length of the interruption,
as investigated by dummy_index, for a two-parameter projection (or three-parameter projection, if you run with the ratio-of-two-norms idea). In the special cases where the interruption is either just a single point or an entire great circle, I'm pretty sure that the resulting projection is simply the stereographical projection
regardless of the choice of p.
Of course there exist still more possible ways to measure the worth of a map, for example one could attempt to apply a p-norm to
logarithmic scale rather than the scale itself, so even this generalized Lagrange-Eisenlohr projection doesn't encompass
all of the conformal projections anyone could want. (And optimization isn't everything. For example, the Mercator projection is useful not for optimizing any particular numerical value, but rather because it is the only conformal cylindrical projection, and therefore the only projection which preserves compass directions.)
Though actually, it turns out that one case of logarithmic scale is already included. If you take the limit as p goes to 0, then the 0-"norm" (it's not a true norm) of scale equals the 1-norm of logarithmic scale. I'm not sure if any other logarithmic norm is really worth using anyway...
All this is specific to conformal projections. One could attempt to apply similar metrics to general-case projections, but this requires a little more careful thinking of exactly what property is being integrated or minimized. Maybe more on that later.