Array multidimensi

Pemrograman Paralel dengan Dask di Python

James Fulton

Climate Informatics Researcher

Jenis data multidimensi

Logo HDF

Sebuah folder tunggal

Sebuah folder berisi empat dataset dan beberapa metadata.

import h5py

# Open the HDF5 file
file = h5py.File('data.hdf5')


# Print the available datasets inside the file
print(file.keys())

<KeysViewHDF5 ['A', 'B', 'C', 'D']}>

import h5py

# Open the HDF5 file
file = h5py.File('data.hdf5')


# Select dataset A
dataset_a = file['/A']


print(dataset_a)

<HDF5 dataset "A": shape (10000, 100, 100), type "<f4">

import dask.array as da


# Load dataset into a Dask array
a = da.from_array(dataset_a, chunks=(100, 20, 20))


print(a)

dask.array<array, shape=(10000, 100, 100), dtype=float32, chunksize=(100, 20, 20),
    chunktype=numpy.ndarray>

import dask.array as da

a = da.from_zarr("dataset.zarr", component="A")


print(a)

dask.array<from-zarr, shape=(10000, 100, 100), dtype=float32,
    chunksize=(100, 20, 20), chunktype=numpy.ndarray>

Pemrograman Paralel dengan Dask di Python