Stacking two-dimensional arrays in dask is similar to stacking one-dimensional arrays, but with an additional parameter specifying the axis along which to stack.
Let's say we have two two-dimensional arrays of earthquake data, one with magnitudes and one with depths, and we want to stack them vertically to create a new two-dimensional array:
import dask.array as dawith h5py.File('earthquake_data.h5', 'r') as f: magnitudes = da.from_array(f['magnitudes'], chunks='auto') depths = da.from_array(f['depths'], chunks='auto')data = da.stack([magnitudes, depths], axis=0) |
In this example, we use da.from_array() to create dask arrays from the magnitudes and depths datasets in the HDF5 file. We pass chunks='auto' to let dask determine the optimal chunk size based on the size of the data.
We then use da.stack() to stack the magnitudes and depths arrays vertically along the first axis, which creates a new array with 2 rows (one for magnitudes and one for depths) and M x N columns, where M and N are the dimensions of the input arrays.
We can also stack two-dimensional arrays horizontally by passing axis=1 to da.stack(). This would create a new array with M rows and 2N columns, where M and N are the dimensions of the input arrays.