def test_zz_quickstart_usage(self):
import json
import httplib
import numpy
from pydvid import voxels, general
# Open a connection to DVID
connection = httplib.HTTPConnection( "localhost:8000", timeout=5.0 )
# Get detailed dataset info: /api/datasets/info
dataset_details = general.get_repos_info( connection )
# print json.dumps( dataset_details, indent=4 )
# Create a new remote volume
uuid = 'abcde'
voxels_metadata = voxels.VoxelsMetadata.create_default_metadata( (4,0,0,0), numpy.uint8, 'cxyz', 1.0, "" )
voxels.create_new( connection, uuid, "my_volume", voxels_metadata )
# Use the VoxelsAccessor convenience class to manipulate a particular data volume
dvid_volume = voxels.VoxelsAccessor( connection, uuid, "my_volume" )
# print dvid_volume.axiskeys, dvid_volume.dtype, dvid_volume.minindex, dvid_volume.shape
# Add some data
updated_data = numpy.ones( (4,100,100,100), dtype=numpy.uint8 ) # Must include all channels.
dvid_volume[:, 10:110, 20:120, 30:130] = updated_data
# OR:
dvid_volume.post_ndarray( (0,10,20,30), (4,110,120,130), updated_data )
# Read from it (First axis is channel.)
cutout_array = dvid_volume[:, 10:110, 20:120, 30:130]
# OR:
cutout_array = dvid_volume.get_ndarray( (0,10,20,30), (4,110,120,130) )
assert isinstance(cutout_array, numpy.ndarray)
assert cutout_array.shape == (4,100,100,100)
def test_create_volume(self):
"""
Create a new remote volume. Verify that the server created it in the hdf5 file.
"""
volume_name = 'new_volume'
metadata = voxels.VoxelsMetadata.create_default_metadata((4,0,0,0), numpy.uint8, 'cxyz', 1.0, "")
voxels.create_new( self.client_connection, self.data_uuid, volume_name, metadata )
with h5py.File(self.test_filepath, 'r') as f:
volumes_group = "/datasets/{dvid_dataset}/volumes".format( dvid_dataset=self.dvid_dataset )
assert volume_name in f[volumes_group], "Volume wasn't created: {}".format( volumes_group + "/" + volume_name )
metadata_from_file = voxels.VoxelsMetadata.create_from_h5_dataset( f["all_nodes"][self.data_uuid][volume_name] )
assert metadata_from_file == metadata, "New volume has the wrong metadata"
def test_create_volume(self):
"""
Create a new remote volume. Verify that the server created it in the hdf5 file.
"""
volume_name = 'new_volume'
metadata = voxels.VoxelsMetadata.create_default_metadata(
(4, 0, 0, 0), numpy.uint8, 'cxyz', 1.0, "")
voxels.create_new(self.client_connection, self.data_uuid, volume_name,
metadata)
with h5py.File(self.test_filepath, 'r') as f:
volumes_group = "/datasets/{dvid_dataset}/volumes".format(
dvid_dataset=self.dvid_dataset)
assert volume_name in f[
volumes_group], "Volume wasn't created: {}".format(
volumes_group + "/" + volume_name)
metadata_from_file = voxels.VoxelsMetadata.create_from_h5_dataset(
f["all_nodes"][self.data_uuid][volume_name])
assert metadata_from_file == metadata, "New volume has the wrong metadata"
def test_zz_quickstart_usage(self):
import json
import httplib
import numpy
from pydvid import voxels, general
# Open a connection to DVID
connection = httplib.HTTPConnection("localhost:8000", timeout=5.0)
# Get detailed dataset info: /api/datasets/info
dataset_details = general.get_repos_info(connection)
# print json.dumps( dataset_details, indent=4 )
# Create a new remote volume
uuid = 'abcde'
voxels_metadata = voxels.VoxelsMetadata.create_default_metadata(
(4, 0, 0, 0), numpy.uint8, 'cxyz', 1.0, "")
voxels.create_new(connection, uuid, "my_volume", voxels_metadata)
# Use the VoxelsAccessor convenience class to manipulate a particular data volume
dvid_volume = voxels.VoxelsAccessor(connection, uuid, "my_volume")
# print dvid_volume.axiskeys, dvid_volume.dtype, dvid_volume.minindex, dvid_volume.shape
# Add some data
updated_data = numpy.ones(
(4, 100, 100, 100),
dtype=numpy.uint8) # Must include all channels.
dvid_volume[:, 10:110, 20:120, 30:130] = updated_data
# OR:
dvid_volume.post_ndarray((0, 10, 20, 30), (4, 110, 120, 130),
updated_data)
# Read from it (First axis is channel.)
cutout_array = dvid_volume[:, 10:110, 20:120, 30:130]
# OR:
cutout_array = dvid_volume.get_ndarray((0, 10, 20, 30),
(4, 110, 120, 130))
assert isinstance(cutout_array, numpy.ndarray)
assert cutout_array.shape == (4, 100, 100, 100)
