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# This script compares reading from an array in a loop using the
# tables.Array.read method. In the first case, read is used without supplying
# an 'out' argument, which causes a new output buffer to be pre-allocated
# with each call. In the second case, the buffer is created once, and then
# reused.
from time import perf_counter as clock
import numpy as np
import tables as tb
def create_file(array_size):
array = np.ones(array_size, dtype="i8")
with tb.open_file("test.h5", "w") as fobj:
array = fobj.create_array("/", "test", array)
print(f"file created, size: {array.size_on_disk / 1e6} MB")
def standard_read(array_size):
n = 10
with tb.open_file("test.h5", "r") as fobj:
array = fobj.get_node("/", "test")
start = clock()
for i in range(n):
output = array.read(0, array_size, 1)
end = clock()
assert np.all(output == 1)
print(f"standard read \t {(end - start) / n:5.5f}")
def pre_allocated_read(array_size):
n = 10
with tb.open_file("test.h5", "r") as fobj:
array = fobj.get_node("/", "test")
start = clock()
output = np.empty(array_size, "i8")
for i in range(n):
array.read(0, array_size, 1, out=output)
end = clock()
assert np.all(output == 1)
print(f"pre-allocated read\t {(end - start) / n:5.5f}")
if __name__ == "__main__":
array_num_bytes = [10**5, 10**6, 10**7, 10**8]
for array_bytes in array_num_bytes:
array_size = array_bytes // 8
create_file(array_size)
standard_read(array_size)
pre_allocated_read(array_size)
print()
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