def run():
import blosc
import blosc.toplevel
blosc.print_versions()
suite = unittest.TestLoader().loadTestsFromTestCase(TestCodec)
# If in the future we split this test file in several, the auto-discover
# might be interesting
# suite = unittest.TestLoader().discover(start_dir='.', pattern='test*.py')
suite.addTests(unittest.TestLoader().loadTestsFromModule(blosc.toplevel))
unittest.TextTestRunner(verbosity=2).run(suite)
def run():
import blosc
import blosc.toplevel
blosc.print_versions()
suite = unittest.TestLoader().loadTestsFromTestCase(TestCodec)
# If in the future we split this test file in several, the auto-discover
# might be interesting
# suite = unittest.TestLoader().discover(start_dir='.', pattern='test*.py')
suite.addTests(unittest.TestLoader().loadTestsFromModule(blosc.toplevel))
unittest.TextTestRunner(verbosity=2).run(suite)
"""
Small benchmark that compares a plain NumPy array copy against
compression through different compressors in Blosc.
"""
from __future__ import print_function
import numpy as np
import time
import blosc
import ctypes
N = int(1e8)
clevel = 5
Nexp = np.log10(N)
blosc.print_versions()
print("Creating NumPy arrays with 10**%d int64/float64 elements:" % Nexp)
arrays = ((np.arange(N, dtype=np.int64), "the arange linear distribution"),
(np.linspace(0, 1000, N), "the linspace linear distribution"),
(np.random.random_integers(0, 1000, N), "the random distribution")
)
in_ = arrays[0][0]
# cause page faults here
out_ = np.full(in_.size, fill_value=0, dtype=in_.dtype)
t0 = time.time()
#out_ = np.copy(in_)
out_ = ctypes.memmove(out_.__array_interface__['data'][0],
in_.__array_interface__['data'][0], N*8)
tcpy = time.time() - t0
"""
Small benchmark that compares a plain NumPy array copy against
compression through different compressors in Blosc.
"""
from __future__ import print_function
import numpy as np
import time
import blosc
N = 1e8
clevel = 5
Nexp = np.log10(N)
blosc.print_versions()
print("Creating a large NumPy array with 10**%d int64 elements:" % Nexp)
in_ = np.arange(N, dtype=np.int64) # the trivial linear distribution
#in_ = np.linspace(0, 100, N) # another linear distribution
#in_ = np.random.random_integers(0, 100, N) # random distribution
print(" ", in_)
tic = time.time()
out_ = np.copy(in_)
toc = time.time()
print(" Time for copying array with np.copy(): %.3f s" % (toc-tic,))
print()
for cname in blosc.compressor_list():
print("Using *** %s *** compressor::" % cname)
