can someone please help me to realize a grid stretching in one direction via grid-mapping to extended the farfield in one direction.
import Grid_mapping as Gm
Nc = len(xc[:,0])
xe = xc[-1,0]
dxl = a*(xc[1,0]-xc[0,0])
for i in range(1,Nc):
xc[i,:] = xc[0,:] + dxl*i
k = Gm.min(0,xk,xc[:,0],Nc)
c = dxl*(Nc-k-2)/(xe-xc[k,0]-dxl)
for j in range(Nc-k):
xc[k+j,:] = (c*xe*j+xc[k,:]*(Nc-1-k-j))/(Nc-1-k+j*(c-1.))
return [xc,yc]
resulting in the blue graph (bottom left).

Comparing the maximum density at 12 microseconds with and without a grid-mapping (see figure 2),
a clear distinction is visible.

I have already used different grid-mappings and different Euler solvers,
but the error between these two cases remains nearly constant.
I have also considered the solver "euler_mapgrid_rpt2", however here the simulation simply froze,
indepent of claw.tfinal.
I would really appreciate it if someone is able to point out any errors
or can show me a working grid-mapping for the "rpn2_euler_hlle.f90" solver
or a solver where my solution doesnt freeeze and can correct the induced error by the grid-mapping.