SingleDecomposition

class fridom.framework.domain_decomposition.SingleDecomposition(shape: tuple[int], halo: int = 0, periods: tuple[bool] | None = None, shared_axes: tuple[int] | None = None, device_ids: list[int] | None = None)

Bases: DomainDecomposition

__init__(shape: tuple[int], halo: int = 0, periods: tuple[bool] | None = None, shared_axes: tuple[int] | None = None, device_ids: list[int] | None = None)

Methods

__init__(shape[, halo, periods, ...])
create_array([pad, spectral, topo])	Create an array.
create_meshgrid(*args[, pad, spectral])	Create a meshgrid of arrays.
create_random_array([seed, pad, spectral, topo])	Create a random array.
cumsum(arr, axis)	Cumulative sum of an array along a specified axis.
gather(arr[, slc, dest_rank, spectral])	Gather an array to a single process.
inv_cumsum(arr, axis)	Inverse cumulative sum of an array along a specified axis.
max(arr[, axes, spectral])	Find the maximum value of an array across specified axes.
min(arr[, axes, spectral])	Find the minimum value of an array across specified axes.
pad(arr[, flat_axes])	Add padding to an array.
pad_extend(arr)	Extend the array with zeros (for spectral padding)
pad_trim(arr)	Set the padded region to zero (for spectral padding)
parallel_backward_transform(func)	Parallel backward transform.
parallel_forward_transform(func)	Parallel forward transform.
roll(arr, shift, axis)	Roll an array along specified axes.
shard_map(func)	Decorator to apply a function to the active processes only.
sum(arr[, axes, spectral])	Sum an array across specified axes.
sync(arr[, flat_axes])	Synchronize the halo regions of an array across all processes.
sync_multiple(arr)	Synchronize the halo regions of multiple arrays across all processes.
unpad(arr[, flat_axes])	Remove padding from an array.
unpad_extend(arr)	Remove the extension of the array (for spectral padding)

Attributes

device_ids	List of device ids.
halo	Width of the halo region (same for all dimensions).
i_am_active	Whether the current process is active in this domain.
n_dims	Number of dimensions.
p_dims	Number of processes in each dimension.
parallel	Whether the domain is parallel.
periods	Periodic boundaries of the domain.
rank	Rank of the current process.
shape	Shape of the domain (number of grid points).
shared_axes	Axes shared by all processes.
size	Number of processes.

sync(arr: ndarray, flat_axes: list[int] | None = None) → ndarray

Synchronize the halo regions of an array across all processes.

Parameters

arrndarray

The array to synchronize.

flat_axeslist[int] | None

Dimensions which are flat (no halo exchange). If None, all dimensions are exchanged.

pad(arr: ndarray, flat_axes: tuple[int] | None = None) → ndarray

Add padding to an array.

Parameters

arrndarray

The array to pad.

unpad(arr: ndarray, flat_axes: tuple[int] | None = None) → ndarray

Remove padding from an array.

Parameters

arrndarray

The array to unpad.

pad_extend(arr: ndarray) → ndarray

Extend the array with zeros (for spectral padding)

Parameters

arrndarray

The array to pad.

Returns

ndarray

The padded array.

unpad_extend(arr: ndarray) → ndarray

Remove the extension of the array (for spectral padding)

Parameters

arrndarray

The array to unpad.

Returns

ndarray

The unpadded array.

pad_trim(arr: ndarray) → ndarray

Set the padded region to zero (for spectral padding)

Parameters

arrndarray

The array to pad.

gather(arr: ndarray, slc: tuple[slice] | None = None, dest_rank: int | None = None, spectral: bool = False) → ndarray

Gather an array to a single process.

Parameters

arrndarray

The array to gather.

slctuple[slice] (default=None)

The slice of the array to gather. If None, gather the entire array.

dest_rankint (default=None)

The rank of the process to gather to. If None, gather to all processes.

spectralbool

Whether the array is in spectral space.

create_array(pad: bool = True, spectral: bool = False, topo: tuple[bool] | None = None) → ndarray

Create an array.

Parameters

padbool

Whether to add padding to the array.

spectralbool

Whether the array is in spectral space.

topotuple[bool] | None

The topology of the array. Axes with false are flat (only one grid point)

create_random_array(seed: int = 1234, pad: bool = True, spectral: bool = False, topo: tuple[bool] | None = None) → ndarray

Create a random array.

Parameters

seedint

The seed for the random number generator.

padbool

Whether to add padding to the array.

spectralbool

Whether the array is in spectral space.

topotuple[bool] | None

The topology of the array. Axes with false are flat (only one grid point)

create_meshgrid(*args: ndarray, pad: bool = True, spectral: bool = False) → tuple[ndarray]

Create a meshgrid of arrays.

Parameters

argsndarray

The arrays to meshgrid.

padbool

Whether to add padding to the meshgrid.

spectralbool

Whether the meshgrid is in spectral space.

sum(arr: ndarray, axes: list[int] | None = None, spectral: bool = False) → ndarray

Sum an array across specified axes.

Parameters

arrndarray

The array to sum.

axeslist[int] | None

The axes to sum across. If None, sum across all axes.

spectralbool

Whether the array is in spectral space.

max(arr: ndarray, axes: list[int] | None = None, spectral: bool = False) → ndarray

Find the maximum value of an array across specified axes.

Parameters

arrndarray

The array to find the maximum value of.

axeslist[int] | None

The axes to find the maximum value across. If None, find the maximum value across all axes.

spectralbool

Whether the array is in spectral space.

min(arr: ndarray, axes: list[int] | None = None, spectral: bool = False) → ndarray

Find the minimum value of an array across specified axes.

Parameters

arrndarray

The array to find the minimum value of.

axeslist[int] | None

The axes to find the minimum value across. If None, find the minimum value across all axes.

spectralbool

Whether the array is in spectral space.

cumsum(arr: ndarray, axis: int) → ndarray

Cumulative sum of an array along a specified axis.

Parameters

arrndarray

The array to cumsum.

axisint

The axis to cumsum along.

inv_cumsum(arr: ndarray, axis: int) → ndarray

Inverse cumulative sum of an array along a specified axis.

Parameters

arrndarray

The array to inv_cumsum.

axisint

The axis to inv_cumsum along.

roll(arr: ndarray, shift: int | tuple[int], axis: int | tuple[int]) → ndarray

Roll an array along specified axes.

Parameters

arrndarray

The array to roll.

shiftint | tuple[int]

The number of places by which elements are shifted. Rolling the array [1,2,3,4,5] with shift=1 results in [5,1,2,3,4]. If a tuple is given, the axis must also be a tuple of the same length.

axisint | tuple[int]

The axis or axes to roll along. If a tuple is given, the shift must also be a tuple of the same length.