AMReXDataArray

class xamr.AMReXDataArray(parent_ds: AMReXDataset, field_name: str, selection_obj=None)

Bases: object

xarray-like DataArray for AMR fields

Supports indexing at the coarsest refinement level with time as the leftmost index.

Indexing examples:

# Single time step data[10, 20] # z=10, y=20 (for 2D) data[10, 20, 30] # z=10, y=20, x=30 (for 3D)

# Time series data[0, 10, 20] # time=0, z=10, y=20 (for 2D) data[0, 10, 20, 30] # time=0, z=10, y=20, x=30 (for 3D)

# Slicing data[0, :, :] # time=0, all z,y (for 2D) data[:, 10, :] # all times, z=10, all y (for 2D)

Methods

__init__(parent_ds, field_name[, selection_obj])
__getitem__(key)	Index into the coarsest level data
level_select(level)	Select specific AMR level(s)
spatial_select(**kwargs)	Select spatial region across all levels
sel(**kwargs)	xarray-like selection (spatial only for AMR)
max(**kwargs)	Maximum across AMR structure
min(**kwargs)	Minimum across AMR structure
mean(**kwargs)	Volume-weighted mean across AMR structure
values([level])	Get values as numpy array for a specific refinement level

Properties

data	Lazy load AMR data - returns yt YTArray
coords	Get coordinate arrays for this data
dims
shape	Shape of the data at coarsest level

Private Methods

_load_coarsest_data()

Load data at coarsest level for all time steps

__init__(parent_ds: AMReXDataset, field_name: str, selection_obj=None)

__getitem__(key)

Index into the coarsest level data

Parameters:

key – Index or slice. For time series, time index is leftmost. Spatial indices follow yt convention (z, y, x for 3D).

Returns:

Scalar value or numpy array depending on indexing

property data

Lazy load AMR data - returns yt YTArray

property coords

Get coordinate arrays for this data

property dims

property shape

Shape of the data at coarsest level

level_select(level: int | List[int]) → AMReXDataArray

Select specific AMR level(s)

spatial_select(**kwargs) → AMReXDataArray

Select spatial region across all levels

sel(**kwargs)

xarray-like selection (spatial only for AMR)

max(**kwargs)

Maximum across AMR structure

min(**kwargs)

Minimum across AMR structure

mean(**kwargs)

Volume-weighted mean across AMR structure

values(level: int | None = None) → numpy.ndarray

Get values as numpy array for a specific refinement level

Parameters:

level – AMR level to extract values from. If None, uses coarsest level (level 0). Must be between 0 and max_level.

Returns:

Field values at the specified level. For time series data,

returns array with time as first dimension.

Return type:

numpy.ndarray

Raises:

ValueError – If level is out of range