"""
This example shows how to read and write data to a dataset using
gzip compression (also called zlib or deflate).  The program first
writes integers to a dataset using gzip, then closes the file.  Next, it
reopens the file, reads back the data, and outputs the type of
compression and the maximum value in the dataset to the screen.
"""
import numpy as np
import h5py

FILE = "h5ex_d_gzip.h5"
DATASET = "DS1"

DIM0 = 32
DIM1 = 64
CHUNK0 = 4
CHUNK1 = 8

def run():

    # Initialize the data.
    wdata = np.zeros((DIM0, DIM1), dtype=np.int32)
    for i in range(DIM0):
        for j in range(DIM1):
            wdata[i][j] = i * j - j

    with h5py.File(FILE, 'w') as f:
        dset = f.create_dataset(DATASET, (DIM0, DIM1), chunks=(CHUNK0, CHUNK1),
                                compression='gzip', dtype='<i4')
        dset[...] = wdata


    with h5py.File(FILE) as f:
        dset = f[DATASET]
        print("Filter type for {0} is {1}".format(DATASET, dset.compression))

        rdata = np.zeros((DIM0, DIM1))
        dset.read_direct(rdata)

        # Verify that the dataset was read correctly.
        np.testing.assert_array_equal(rdata, wdata)
        print("Maximum value in DS1 is:  %d" % rdata.max())

if __name__ == "__main__":
    run()