import numpy as np
import zarr
zarr.__version__
'2.0.1'
z = zarr.empty(shape=100000000, chunks=200000, dtype='i8')
data = np.arange(100000000, dtype='i8')
%timeit z[:] = data
%timeit z[:]
print(z)
assert np.all(z[:] == data)
10 loops, best of 3: 110 ms per loop 1 loop, best of 3: 235 ms per loop Array((100000000,), int64, chunks=(200000,), order=C) nbytes: 762.9M; nbytes_stored: 11.2M; ratio: 67.8; initialized: 500/500 compressor: Blosc(cname='lz4', clevel=5, shuffle=1) store: dict
z = zarr.empty(shape=100000000, chunks=200000, dtype='f8')
data = np.random.normal(size=100000000)
%timeit z[:] = data
%timeit z[:]
print(z)
assert np.all(z[:] == data)
1 loop, best of 3: 331 ms per loop 1 loop, best of 3: 246 ms per loop Array((100000000,), float64, chunks=(200000,), order=C) nbytes: 762.9M; nbytes_stored: 724.8M; ratio: 1.1; initialized: 500/500 compressor: Blosc(cname='lz4', clevel=5, shuffle=1) store: dict
import numpy as np
import sys
sys.path.insert(0, '..')
import zarr
zarr.__version__
'2.0.2.dev0+dirty'
z = zarr.empty(shape=100000000, chunks=200000, dtype='i8')
data = np.arange(100000000, dtype='i8')
%timeit z[:] = data
%timeit z[:]
print(z)
assert np.all(z[:] == data)
10 loops, best of 3: 92.7 ms per loop 1 loop, best of 3: 230 ms per loop Array((100000000,), int64, chunks=(200000,), order=C) nbytes: 762.9M; nbytes_stored: 11.2M; ratio: 67.8; initialized: 500/500 compressor: Blosc(cname='lz4', clevel=5, shuffle=1) store: dict
z = zarr.empty(shape=100000000, chunks=200000, dtype='f8')
data = np.random.normal(size=100000000)
%timeit z[:] = data
%timeit z[:]
print(z)
assert np.all(z[:] == data)
1 loop, best of 3: 338 ms per loop 1 loop, best of 3: 253 ms per loop Array((100000000,), float64, chunks=(200000,), order=C) nbytes: 762.9M; nbytes_stored: 724.8M; ratio: 1.1; initialized: 500/500 compressor: Blosc(cname='lz4', clevel=5, shuffle=1) store: dict