Indexing and Selection

Basic Indexing

xamr supports numpy-like indexing at the coarsest AMR level:

import xamr

ds = xamr.AMReXDataset("plt00000")
temp = ds['temperature']

# Point indexing (3D: z, y, x)
temp_point = temp[10, 20, 30]

# 2D case (y, x)
temp_point_2d = temp[20, 30]

Slicing

Use slices to extract regions:

# Slice along each dimension
temp_slice = temp[10:20, :, 50:100]  # z=10-19, all y, x=50-99

# Extract a 2D slice
xy_slice = temp[25, :, :]            # z=25, all y and x
yz_slice = temp[:, :, 50]            # x=50, all z and y

Time Series Indexing

For time series data, time is the leftmost index:

ds = xamr.AMReXDataset("plt*")
temp = ds['temperature']

# Time + spatial indexing
temp_point = temp[0, 10, 20, 30]     # time=0, z=10, y=20, x=30
temp_slice = temp[0, :, :, :]        # time=0, all spatial points

# Time evolution at a point
temp_evolution = temp[:, 10, 20, 30] # all times, specific point

# Time slice
temp_subset = temp[5:10, :, :, :]    # times 5-9, all spatial

Advanced Selection

Use the .sel() method for more sophisticated selection:

# Spatial region selection
region = temp.spatial_select(
    x=slice(0.0, 1.0),
    y=slice(0.0, 0.5)
)

# Alternative syntax
region = temp.sel(x=slice(0.0, 1.0), y=slice(0.0, 0.5))

Level Selection

Select specific AMR levels:

# Select specific refinement level
temp_level2 = temp.level_select(2)

# Multiple levels
temp_levels = temp.level_select([0, 1, 2])

Error Handling

xamr validates indexing operations:

# Too many indices
try:
    temp[0, 1, 2, 3, 4]  # Error for 3D data
except IndexError as e:
    print(f"IndexError: {e}")

# Out of bounds
try:
    temp[1000, 1000, 1000]  # Error if indices exceed array size
except IndexError as e:
    print(f"IndexError: {e}")

Performance Tips

Indexing operates on the coarsest level for speed
Use .values() to get numpy arrays for intensive computation
Cache frequently accessed slices
Use spatial selection for large regions rather than explicit slicing

# Efficient: get numpy array once
temp_array = temp.values()
point1 = temp_array[10, 20, 30]
point2 = temp_array[11, 20, 30]

# Less efficient: repeated indexing
point1 = temp[10, 20, 30]
point2 = temp[11, 20, 30]