bte.utils.limiter#

Module Contents#

Functions#

van_leer_limiter(r)

van_leer_limiter

limiter_minmod(theta)

limiter_minmod

limiter_superbee(theta)

limiter_superbee

limiter_mc(theta)

limiter_mc

limiter_zero(theta)

limiter_zero Always return 0. Linear reconstruction with limiter_zero is equal to constant reconstruction.

bte.utils.limiter.van_leer_limiter(r)[source]#

van_leer_limiter

\[\phi _{{vl}}(r)={\frac {r+\left|r\right|}{1+\left|r\right|}}\]
Parameters:

r (torch.Tensor) – [description]

Returns:

[description]

Return type:

torch.Tensor

bte.utils.limiter.limiter_minmod(theta)[source]#

limiter_minmod

Parameters:

theta (torch.Tensor) – [description]

Return type:

torch.Tensor

\[\phi _{{mm}}(r)=\max \left[0,\min \left(1,r\right)\right]\]
Returns:

[description]

Return type:

torch.Tensor

Parameters:

theta (torch.Tensor) –

bte.utils.limiter.limiter_superbee(theta)[source]#

limiter_superbee

Parameters:

theta (torch.Tensor) – [description]

Return type:

torch.Tensor

\[\phi _{{sb}}(r)=\max \left[0,\min \left(2r,1\right),\min \left(r,2\right)\right]\]
Returns:

[description]

Return type:

torch.Tensor

Parameters:

theta (torch.Tensor) –

bte.utils.limiter.limiter_mc(theta)[source]#

limiter_mc

Parameters:

theta (torch.Tensor) – [description]

Return type:

torch.Tensor

\[\phi _{{mc}}(r)=\max \left[0,\min \left(2r,0.5(1+r),2\right)\right]\]
Returns:

[description]

Return type:

torch.Tensor

Parameters:

theta (torch.Tensor) –

bte.utils.limiter.limiter_zero(theta)[source]#

limiter_zero Always return 0. Linear reconstruction with limiter_zero is equal to constant reconstruction.

\[\phi _{{0}}(r)=0\]
Parameters:

theta (torch.Tensor) – [description]

Returns:

zeros tensor shape same with theta.

Return type:

torch.Tensor