scipy.interpolate.interp1d 折叠 map

Question

I am plotting the result of an interpolation in a periodic domain, namely, the earth mercator projection map, [0,2*pi] or [0,360] is the domain for longitude. As you can see on the picture below, I'm plotting a groundtrack.

I am getting first r , ie position, and then I'm projecting that right onto earth. Since the coordinate transformations involves trigonometric functions, the results that I obtain are certainly restricted to a domain, where the inverse is bijective. To obtain this plot I've used atan2 in order to obtain a non bijective inverse function, as well as manipulating arccos in order to extend the domain of the inverse function.

All good up to now. The fact is that when I interpolate the resulting points, naturally, the function that returns does not interpret the domain folding property.

I just wanted to know if there is any way around this, apart from manipulating my data and representing it in a non periodic domain, interpolate it, and after that applying %(2*np.pi) . These option, even if is doable, implies touching even more those inverse functions. The other option I thought was interpolating in chunks of only increasing values, ie and concatenating them.

Nothing found on the scipy documentation.

Answer 1

Solved the issue implementing something like the following. Notice that I am using astropy units module.

adder = 2*np.pi*u.rad
for i in range(1,len(lons)):
    if lons[i].value-lons[i-1].value > 1:
        sgn=np.sign(lons[i].value-lons[i-1].value)
        lons[i:] -= sgn*adder

after doing this, apply the %

f_lons = interp1d(t,lons)
lons = f_lons(new_t) % (2*np.pi)