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io_benchmarks.py
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import os
import threading
import multiprocessing
import zarr
import numpy as np
import z5py
import h5py
import tifffile
import dask.array as da
import xarray as xr
import time as timer
from numcodecs import GZip, BZ2
from shutil import rmtree
def write_speed(t1, t2):
print('Write speed: ' + str(data.size*2/10**6/(t2-t1)) + ' MB/sec')
def write_tiff_data(idx, data, blockSize):
for i in range(idx, idx+blockSize):
tifffile.imsave('C:\\benchmark\\tiff\\' + str(i) + '.tiff', data[i])
def write_data(idx, zdata, data, blockSize):
zdata[idx:idx+blockSize] = data[idx:idx+blockSize]
def write_zarr(data, chunks, compressor, parallel, mode):
if mode == 'n5':
store = zarr.N5Store('C:\\benchmark\\zarr.n5')
else:
store = zarr.DirectoryStore('C:\\benchmark\\zarr.zr')
t1=timer.time()
blockSize = 2*chunks[0]
zdata = zarr.zeros(store = store, overwrite = True, shape = data.shape, chunks = chunks, dtype = data.dtype, compressor = compressor)
if parallel == True:
threads = []
for idx in np.arange(0, data.shape[0], blockSize):
thread = threading.Thread(target = write_data, args=(idx, zdata, data, blockSize))
thread.start()
threads.append(thread)
for t in threads:
t.join()
else:
zdata[:] = data[:]
t2=timer.time()
write_speed(t1,t2)
def write_zarr_xarray(data, chunks, compressor, chunked, mode):
if mode == 'n5':
store = zarr.N5Store('C:\\benchmark\\zarr_xarray.n5')
else:
store = zarr.DirectoryStore('C:\\benchmark\\zarr_xarray.zr')
t1=timer.time()
blockSize = 2*chunks[0]
darray = da.from_array(data, chunks = chunks)
xdataset = xr.Dataset({'i': (('z','x','y'), darray)})
xdataset.to_zarr(store, compute=False, encoding={'i': {'compressor': compressor}})
if chunked == True:
for idx in range(0, data.shape[0], blockSize):
selection = {'z': slice(idx, idx + blockSize)}
xdataset.isel(selection).to_zarr(store, region = selection)
else:
xdataset.to_zarr(store, encoding={'i': {'compressor': compressor}})
t2=timer.time()
write_speed(t1,t2)
def write_zarr_dask(data, chunks, compressor, mode):
if mode == 'n5':
store = zarr.N5Store('C:\\benchmark\\zarr_dask.n5')
else:
store = zarr.DirectoryStore('C:\\benchmark\\zarr_dask.zr')
t1=timer.time()
darray = da.from_array(data, chunks = chunks)
darray.to_zarr(store, compressor = compressor)
t2=timer.time()
write_speed(t1,t2)
def write_z5py(data, chunks, compressor, parallel, mode):
if mode == 'n5':
f = z5py.File('C:\\benchmark\\z5py.n5', use_zarr_format=False)
else:
f = z5py.File('C:\\benchmark\\z5py.zr', use_zarr_format=True)
t1=timer.time()
blockSize = 2*chunks[0]
zdata = f.create_dataset('test', shape=data.shape, chunks=chunks, dtype=data.dtype, compression=compressor)
if parallel == True:
threads = []
for idx in np.arange(0, data.shape[0], blockSize):
thread = threading.Thread(target = write_data, args=(idx, zdata, data, blockSize))
thread.start()
threads.append(thread)
for t in threads:
t.join()
else:
zdata[:] = data[:]
t2=timer.time()
write_speed(t1,t2)
def write_h5py(data, chunks, compressor):
t1=timer.time()
f = h5py.File('C:\\benchmark\\h5py.h5','w')
zdata = f.create_dataset('test', shape = data.shape, chunks = chunks, dtype = data.dtype, compression = compressor)
zdata[:] = data
t2=timer.time()
write_speed(t1,t2)
def write_tiff(data, blockSize, parallel):
t1=timer.time()
if parallel == True:
os.mkdir('C:\\benchmark\\tiff')
threads = []
for idx in np.arange(0, data.shape[0], blockSize):
thread = threading.Thread(target = write_tiff_data, args=(idx, data, blockSize))
thread.start()
threads.append(thread)
for t in threads:
t.join()
else:
tifffile.imsave('C:\\benchmark\\tiff.tiff', data, bigtiff = True)
t2=timer.time()
write_speed(t1,t2)
if __name__ == '__main__':
cores = multiprocessing.cpu_count()
chunks = (32, 256, 256)
data = np.random.randint(0, 2000, size = [cores*chunks[0],2048,2048]).astype('uint16')
if os.path.exists('C:\\benchmark'):
rmtree('C:\\benchmark')
os.mkdir('C:\\benchmark')
write_z5py(data, chunks = chunks, compressor = 'raw', parallel = True, mode = 'zarr')
write_z5py(data, chunks = chunks, compressor = 'raw', parallel = True, mode = 'n5')
write_zarr(data, chunks = chunks, compressor = None, parallel = True, mode = 'zarr')
write_zarr(data, chunks = chunks, compressor = None, parallel = True, mode = 'n5')
write_zarr_dask(data, chunks = chunks, compressor = None, mode = 'zarr')
write_zarr_dask(data, chunks = chunks, compressor = None, mode = 'n5')
write_zarr_xarray(data, chunks = chunks, compressor = None, chunked = True, mode = 'zarr')
write_zarr_xarray(data, chunks = chunks, compressor = None, chunked = True, mode = 'n5')
write_h5py(data, chunks = chunks, compressor = None)
write_tiff(data, blockSize = 64, parallel = True)
write_tiff(data, blockSize = 64, parallel = False)