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"""A simple example of building a virtual dataset.
This makes four 'source' HDF5 files, each with a 1D dataset of 100 numbers.
Then it makes a single 4x100 virtual dataset in a separate file, exposing
the four sources as one dataset.
"""
import h5py
import numpy as np
# create some sample data
data = np.arange(0, 100).reshape(1, 100) + np.arange(1, 9).reshape(8, 1)
# Create source files (0.h5 to 3.h5)
for n in range(4):
with h5py.File(f"{n}.h5", "w") as f:
d = f.create_dataset("data", (2,100,), "i4", data[2*n:2*n+2])
# Assemble virtual dataset
layout = h5py.VirtualLayout(shape=(4, 100), dtype="i4")
for n in range(4):
filename = "{}.h5".format(n)
vsource = h5py.VirtualSource(filename, "data", shape=(2,100,))[1]
layout[n] = vsource
# Add virtual dataset to output file
with h5py.File("VDS.h5", "w", libver="latest") as f:
f.create_virtual_dataset("vdata", layout, fillvalue=-5)
# f.create_dataset("data", data=data, dtype="i4")
# read data back
# virtual dataset is transparent for reader!
with h5py.File("VDS.h5", "r") as f:
print("Virtual dataset:")
print(f["vdata"][:, :10])
# print("Normal dataset:")
# print(f["data"][:, :10])
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