General Convection Stepper¤
exponax.stepper.GeneralConvectionStepper
¤
Bases: BaseStepper
Source code in exponax/stepper/_convection.py
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__init__
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__init__(
num_spatial_dims: int,
domain_extent: float,
num_points: int,
dt: float,
*,
coefficients: tuple[float, ...] = (0.0, 0.0, 0.01),
convection_scale: float = 1.0,
single_channel: bool = False,
order=2,
dealiasing_fraction: float = 2 / 3,
num_circle_points: int = 16,
circle_radius: float = 1.0
)
Timestepper for the d-dimensional (d ∈ {1, 2, 3}
) semi-linear PDEs
consisting of a convection nonlinearity and an arbitrary combination of
(isotropic) linear derivatives.
In 1d, the equation is given by
uₜ + b₁ 1/2 (u²)ₓ = sum_j a_j uₓˢ
with b₁
the convection coefficient and a_j
the coefficients of the
linear operators. uₓˢ
denotes the s-th derivative of u
with respect
to x
. Oftentimes b₁ = 1
.
In the default configuration, the number of channel grows with the number of spatial dimensions. The higher dimensional equation reads
uₜ + b₁ 1/2 ∇ ⋅ (u ⊗ u) = sum_j a_j (1⋅∇ʲ)u
Alternatively, with single_channel=True
, the number of channels can be
kept to constant 1 no matter the number of spatial dimensions.
Depending on the collection of linear coefficients can be represented,
for example:
- Burgers equation with a = (0, 0, 0.01)
with len(a) = 3
- KdV equation with a = (0, 0, 0, 0.01)
with len(a) = 4
Arguments:
- num_spatial_dims
: The number of spatial dimensions d
.
- domain_extent
: The size of the domain L
; in higher dimensions
the domain is assumed to be a scaled hypercube Ω = (0, L)ᵈ
.
- num_points
: The number of points N
used to discretize the
domain. This includes the left boundary point and
excludes the right boundary point. In higher dimensions; the
number of points in each dimension is the same. Hence, the total
number of degrees of freedom is Nᵈ
.
- dt
: The timestep size Δt
between two consecutive states.
- coefficients
(keyword-only): The list of coefficients a_j
corresponding to the derivatives. The length of this tuple
represents the highest occuring derivative. The default value
(0.0, 0.0, 0.01)
corresponds to the Burgers equation (because
of the diffusion)
- convection_scale
(keyword-only): The scale b₁
of the
convection term. Default is 1.0
.
- single_channel
: Whether to use the single channel mode in higher
dimensions. In this case the the convection is b₁ (∇ ⋅ 1)(u²)
.
In this case, the state always has a single channel, no matter
the spatial dimension. Default: False.
- order
: The order of the Exponential Time Differencing Runge
Kutta method. Must be one of {0, 1, 2, 3, 4}. The option 0
only solves the linear part of the equation. Use higher values
for higher accuracy and stability. The default choice of 2
is
a good compromise for single precision floats.
- dealiasing_fraction
: The fraction of the wavenumbers to keep
before evaluating the nonlinearity. The default 2/3 corresponds
to Orszag's 2/3 rule. To fully eliminate aliasing, use 1/2.
Default: 2/3.
- num_circle_points
: How many points to use in the complex contour
integral method to compute the coefficients of the exponential
time differencing Runge Kutta method. Default: 16.
- circle_radius
: The radius of the contour used to compute the
coefficients of the exponential time differencing Runge Kutta
method. Default: 1.0.
Source code in exponax/stepper/_convection.py
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__call__
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__call__(
u: Float[Array, "C ... N"]
) -> Float[Array, "C ... N"]
Performs a check
Source code in exponax/_base_stepper.py
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