bte.nsr.dataset#

Module Contents#

Classes#

Functions#

sinfunc(x, a, b, c, k)

sigmoidshock(fl, fr, xl, xr, x)

sinshock(fl, fr, xl, xr, x)

class bte.nsr.dataset.Datagenerator[source]#
abstract get_prim(x)[source]#
abstract plot()[source]#
abstract init_value(device='cuda', dtype=torch.float32)[source]#
abstract get(device='cuda', dtype=torch.float32)[source]#
abstract getLR(device='cuda', dtype=torch.float32)[source]#
class bte.nsr.dataset.D1PeriodicCase(config)[source]#

Bases: Datagenerator

plot(x=None)[source]#
init_value(device='cuda', dtype=torch.float32)[source]#
get(device='cuda', dtype=torch.float32)[source]#
getLR(device='cuda', dtype=torch.float32)[source]#
class bte.nsr.dataset.SmoothD1Case(config)[source]#

Bases: D1PeriodicCase

get_prim(x)[source]#
bte.nsr.dataset.sinfunc(x, a, b, c, k)[source]#
class bte.nsr.dataset.SinK(k, knum, seed=0, brange=None, arange=None)[source]#
__call__(x)[source]#
class bte.nsr.dataset.RandomWaveD1Case(config, k, knum, seed=0, *args, **kargs)[source]#

Bases: D1PeriodicCase

get_prim(x)[source]#
class bte.nsr.dataset.D1DirichletCase(config)[source]#
plot(x=None)[source]#
init_value(device='cuda', dtype=torch.float32)[source]#
get(device='cuda', dtype=torch.float32)[source]#
getLR(device='cuda', dtype=torch.float32)[source]#
bte.nsr.dataset.sigmoidshock(fl, fr, xl, xr, x)[source]#
bte.nsr.dataset.sinshock(fl, fr, xl, xr, x)[source]#
class bte.nsr.dataset.SodD1Case(config)[source]#

Bases: D1DirichletCase

get_prim(x)[source]#
class bte.nsr.dataset.D2PeriodicCase(config)[source]#

Bases: Datagenerator

abstract plot(x=None)[source]#
get(device='cuda', dtype=torch.float32)[source]#
getLR(device='cuda', dtype=torch.float32)[source]#
class bte.nsr.dataset.SmoothD2Case(config)[source]#

Bases: D2PeriodicCase

get_prim(x, y)[source]#
class bte.nsr.dataset.SmoothD2Case15(config)[source]#

Bases: D2PeriodicCase

get_prim(x, y)[source]#
class bte.nsr.dataset.SmoothD2Case2(config)[source]#

Bases: D2PeriodicCase

get_prim(x, y)[source]#