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Calculate total chunks

calculate_total_chunks#

def calculate_total_chunks(ds: xr.Dataset, block_size: List[Tuple[str, int]] = None) -> int

Description#

The total number of chunks for an xarray.Dataset is calculated based on specified or default chunk sizes.

Parameters#

  • ds (xarray.Dataset): The dataset for which the total number of chunks will be calculated. The dataset should have dimensions that can be chunked.
  • block_size (Optional[List[Tuple[str, int]]]): A sequence of tuples specifying the block size for each dimension. Each tuple should contain a dimension name and a block size for that dimension. If not provided, the function will use the dataset's default chunk sizes.

Returns#

  • int: The total number of chunks in the dataset based on the specified or default chunk sizes.

Example#

import numpy as np
import xarray as xr
from ml4xcube.utils import calculate_total_chunks

# Example dataset
data = np.random.rand(100, 200, 300)
ds = xr.Dataset({
    'temperature': (('time', 'lat', 'lon'), data),
    'precipitation': (('time', 'lat', 'lon'), data)
})

# Define the block size (chunk size)
block_size = [('time', 10), ('lat', 20), ('lon', 30)]

# Calculate total chunks
total_chunks = calculate_total_chunks(ds, block_size=block_size)
print(f"Total number of chunks: {total_chunks}")
Based on the specified blocks the number of chunks is calculated.

Notes#

  • The block_size parameter allows you to specify custom chunk sizes. If not provided, the function will use the dataset's default chunk sizes.
  • Ensure that the provided block_size values are appropriate for the dimensions of the dataset.