import numpy as np
import h5py
import dask.array as da
filename = '/Users/pbw/data/sample_A/sample_A_20160501.hdf'
source_data = h5py.File(filename, 'r')
raw = np.asarray(source_data['volumes/raw'])
labels = np.asarray(source_data['volumes/labels/neuron_ids'])
raw_dask = da.from_array(raw, chunks=(1, 1250, 1250))
da.to_zarr(raw_dask, 'raw.zarr')
labels_dask = da.from_array(labels, chunks=(1, 1250, 1250))
da.to_zarr(labels_dask, 'labels.zarr')

2113e51e79c5778b11745a6c66b4a391d90704e4
<mask token>

<mask token>
da.to_zarr(raw_dask, 'raw.zarr')
<mask token>
da.to_zarr(labels_dask, 'labels.zarr')

<mask token>
filename = '/Users/pbw/data/sample_A/sample_A_20160501.hdf'
source_data = h5py.File(filename, 'r')
raw = np.asarray(source_data['volumes/raw'])
labels = np.asarray(source_data['volumes/labels/neuron_ids'])
raw_dask = da.from_array(raw, chunks=(1, 1250, 1250))
da.to_zarr(raw_dask, 'raw.zarr')
labels_dask = da.from_array(labels, chunks=(1, 1250, 1250))
da.to_zarr(labels_dask, 'labels.zarr')

import numpy as np
import h5py
import dask.array as da
filename = '/Users/pbw/data/sample_A/sample_A_20160501.hdf'
source_data = h5py.File(filename, 'r')
raw = np.asarray(source_data['volumes/raw'])
labels = np.asarray(source_data['volumes/labels/neuron_ids'])
raw_dask = da.from_array(raw, chunks=(1, 1250, 1250))
da.to_zarr(raw_dask, 'raw.zarr')
labels_dask = da.from_array(labels, chunks=(1, 1250, 1250))
da.to_zarr(labels_dask, 'labels.zarr')
