def nabla(self, mesh, m, g):
if PAR.CREEPING:
G, grid = mesh2grid(g, mesh)
DG = nabla(G, order=2)
dg = grid2mesh(DG, grid, mesh)
return -dg/np.mean(m)
else:
M, grid = mesh2grid(m, mesh)
DM = nabla(M, order=2)
dm = grid2mesh(DM, grid, mesh)
return dm/np.mean(m)
def nabla(self, mesh, m, g):
if PAR.CREEPING:
G, grid = mesh2grid(g, mesh)
DG = nabla(G, order=1)
dg = grid2mesh(DG, grid, mesh)
return -dg / np.mean(m)
else:
M, grid = mesh2grid(m, mesh)
DM = nabla(M, order=1)
dm = grid2mesh(DM, grid, mesh)
return dm / np.mean(m)
def write_damping_term(self, parameter):
path_coords = PATH.OUTPUT+'/'+'model_init'
path_input = PATH.GRAD+'/'+'model'
path_output = PATH.MUMFORD_SHAH_OUTPUT
path_run = PATH.SUBMIT
x = sem.read(path_coords, 'x', 0)
z = sem.read(path_coords, 'z', 0)
mesh = stack(x,z)
m, grid = mesh2grid(sem.read(path_input, parameter, 0), mesh)
nu, _ = mesh2grid(sem.read(path_output, parameter+'_nu', 0), mesh)
grad_m = grad(m)
grad_nu = grad(nu)
V = -2.*(grad_m[0]*grad_nu[0] + grad_m[1]*grad_nu[1]) +\
-nu**2 * nabla2(m)
v = grid2mesh(V, grid, mesh)
sem.write(v, path_output, parameter+'_dm', 0)
def nabla(self, mesh, m, g):
M, grid = mesh2grid(g, mesh)
DM = tv(M, epsilon=PAR.EPSILON)
dm = grid2mesh(DM, grid, mesh)
return dm/np.mean(m)
def nabla(self, mesh, m, g):
M, grid = mesh2grid(g, mesh)
DM = tv(M, epsilon=PAR.EPSILON)
dm = grid2mesh(DM, grid, mesh)
return dm / np.mean(m)
