pyinterp.dask.descriptive_statistics

pyinterp.dask.descriptive_statistics#

pyinterp.dask.descriptive_statistics(values, weights=None, axis=None, *, dtype=None)[source]#

Compute descriptive statistics on a dask array.

This function computes statistics (mean, variance, skewness, kurtosis, etc.) on a dask array by processing each block independently and then merging the results.

Parameters:

  • values (dask.array.Array) – Input dask array of values.

  • weights (dask.array.Array | None) – Optional dask array of weights with the same shape as values.

  • axis (list[int] | None) – Axis or axes along which to compute statistics. If None, statistics are computed over all axes.

  • dtype (str | type | np.dtype | None) – Data type for computation. Can be “float32”, “float64”, np.float32, np.float64, or None (defaults to float64).

Returns:

A DescriptiveStatistics instance containing the computed statistics.

Raises:
Return type:

core.DescriptiveStatisticsHolder

Example

>>> import dask.array as da
>>> import pyinterp.dask as dask_stats
>>> values = da.random.random((10000,), chunks=1000)
>>> stats = dask_stats.descriptive_statistics(values)
>>> print(f"Mean: {stats.mean():.4f}")
>>> print(f"Std: {np.sqrt(stats.variance()):.4f}")