def test_anno_minmal(self):
"""Upload a minimal and maximal annotation. Verify fields."""
# Create an in-memory HDF5 file
tmpfile = tempfile.NamedTemporaryFile()
h5fh = h5py.File ( tmpfile.name )
# Create the top level annotation id namespace
idgrp = h5fh.create_group ( str(0) )
h5fh.flush()
tmpfile.seek(0)
p.annoid = putAnnotation(p, tmpfile)
h5ret = getAnnotation(p)
idgrpret = h5ret.get(str(p.annoid))
assert idgrpret
assert ( idgrpret['ANNOTATION_TYPE'][0] == 1 )
assert not idgrpret.get('RESOLUTION')
assert not idgrpret.get('XYZOFFSET')
assert not idgrpret.get('VOXELS')
assert not idgrpret.get('CUTOUT')
mdgrpret = idgrpret['METADATA']
assert mdgrpret
assert ( mdgrpret['CONFIDENCE'][0] == 0.0 )
assert ( mdgrpret['STATUS'][0] == 0 )
assert ( mdgrpret['KVPAIRS'][:] == '' )
assert ( mdgrpret['AUTHOR'][:] == 'unknown' )
def test_neuron(self):
"""Make a multiple segments that overlap and then query them as a neuron"""
# create neuron
makeAnno(p, 5)
neuronid = p.annoid
# create annotations
for i in range(0, 3):
# create annotations
makeAnno(p, 4)
f = setField(p, 'neuron', neuronid)
# add data
p.args = (3000, 3100, 4000, 4100, 100 + 2 * i, 100 + 2 * i + 3)
image_data = np.ones([1, 3, 100, 100], dtype=np.uint32) * p.annoid
response = postNPZ(p, image_data)
# get the neuron annotation
p.annoid = neuronid
p.field = 'tight_cutout'
h5ret = getAnnotation(p)
idgrp = h5ret.get(str(p.annoid))
# count the voxels to make sure they remapped correctly
assert (np.unique(np.array(idgrp['CUTOUT'][:, :, :])) == [0, neuronid
]).all()
assert (len(np.nonzero(np.array(
idgrp['CUTOUT'][:, :, :]))[0]) == 70000)
def test_anno_minmal(self):
"""Upload a minimal and maximal annotation. Verify fields."""
# Create an in-memory HDF5 file
tmpfile = tempfile.NamedTemporaryFile()
h5fh = h5py.File(tmpfile.name)
# Create the top level annotation id namespace
idgrp = h5fh.create_group(str(0))
h5fh.flush()
tmpfile.seek(0)
p.annoid = putAnnotation(p, tmpfile)
h5ret = getAnnotation(p)
idgrpret = h5ret.get(str(p.annoid))
assert idgrpret
assert (idgrpret['ANNOTATION_TYPE'][0] == 1)
assert not idgrpret.get('RESOLUTION')
assert not idgrpret.get('XYZOFFSET')
assert not idgrpret.get('VOXELS')
assert not idgrpret.get('CUTOUT')
mdgrpret = idgrpret['METADATA']
assert mdgrpret
assert (mdgrpret['CONFIDENCE'][0] == 0.0)
assert (mdgrpret['STATUS'][0] == 0)
assert (mdgrpret['KVPAIRS'][:] == '')
assert (mdgrpret['AUTHOR'][:] == 'unknown')
def test_neuron (self):
"""Make a multiple segments that overlap and then query them as a neuron"""
# create neuron
makeAnno(p,5)
neuronid = p.annoid
# create annotations
for i in range(0,3):
# create annotations
makeAnno(p,4)
f = setField(p,'neuron',neuronid)
# add data
p.args = (3000,3100,4000,4100,100+2*i,100+2*i+3)
image_data = np.ones( [1,3,100,100], dtype=np.uint32 ) * p.annoid
response = postNPZ(p, image_data)
# get the neuron annotation
p.annoid = neuronid
p.field = 'tight_cutout'
h5ret = getAnnotation(p)
idgrp = h5ret.get(str(p.annoid))
# count the voxels to make sure they remapped correctly
assert ( np.unique(np.array(idgrp['CUTOUT'][:,:,:])) == [0,neuronid] ).all()
assert ( len(np.nonzero(np.array(idgrp['CUTOUT'][:,:,:]))[0]) == 70000 )
def test_anno_update(self):
"""Upload a Updated file with new data"""
tmpfile = tempfile.NamedTemporaryFile()
h5fh = h5py.File(tmpfile.name)
# Create the top level annotation id namespace
idgrp = h5fh.create_group(str(p.annoid))
# Create a metadata group
mdgrp = idgrp.create_group("METADATA")
# now lets add a bunch of random values for the specific annotation type
ann_status = random.randint(0, 4)
ann_confidence = random.random()
ann_author = 'unittest_author2'
# Annotation type
idgrp.create_dataset("ANNOTATION_TYPE", (1, ), np.uint32, data=1)
# Set Annotation specific metadata
mdgrp.create_dataset("STATUS", (1, ), np.uint32, data=ann_status)
mdgrp.create_dataset("CONFIDENCE", (1, ),
np.float,
data=ann_confidence)
mdgrp.create_dataset("AUTHOR", (1, ),
dtype=h5py.special_dtype(vlen=str),
data=ann_author)
h5fh.flush()
tmpfile.seek(0)
p.field = 'update'
p.annoid = putAnnotation(p, tmpfile)
p.field = None
h5ret = getAnnotation(p)
idgrpret = h5ret.get(str(p.annoid))
assert idgrpret
assert (idgrpret['ANNOTATION_TYPE'][0] == 1)
assert not idgrpret.get('RESOLUTION')
assert not idgrpret.get('XYZOFFSET')
assert not idgrpret.get('VOXELS')
assert not idgrpret.get('CUTOUT')
mdgrpret = idgrpret['METADATA']
assert mdgrpret
assert (abs(mdgrpret['CONFIDENCE'][0] - ann_confidence) < 0.0001)
#assert ( mdgrpret['CONFIDENCE'][0] == ann_confidence )
assert (mdgrpret['STATUS'][0] == ann_status)
assert (mdgrpret['AUTHOR'][:] == ann_author)
def test_anno_update (self):
"""Upload a Updated file with new data"""
tmpfile = tempfile.NamedTemporaryFile()
h5fh = h5py.File ( tmpfile.name )
# Create the top level annotation id namespace
idgrp = h5fh.create_group ( str(p.annoid) )
# Create a metadata group
mdgrp = idgrp.create_group ( "METADATA" )
# now lets add a bunch of random values for the specific annotation type
ann_status = random.randint(0,4)
ann_confidence = random.random()
ann_author = 'unittest_author2'
# Annotation type
idgrp.create_dataset ( "ANNOTATION_TYPE", (1,), np.uint32, data=1 )
# Set Annotation specific metadata
mdgrp.create_dataset ( "STATUS", (1,), np.uint32, data=ann_status )
mdgrp.create_dataset ( "CONFIDENCE", (1,), np.float, data=ann_confidence )
mdgrp.create_dataset ( "AUTHOR", (1,), dtype=h5py.special_dtype(vlen=str), data=ann_author )
h5fh.flush()
tmpfile.seek(0)
p.field = 'update'
p.annoid = putAnnotation(p, tmpfile)
p.field = None
h5ret = getAnnotation(p)
idgrpret = h5ret.get(str(p.annoid))
assert idgrpret
assert ( idgrpret['ANNOTATION_TYPE'][0] == 1 )
assert not idgrpret.get('RESOLUTION')
assert not idgrpret.get('XYZOFFSET')
assert not idgrpret.get('VOXELS')
assert not idgrpret.get('CUTOUT')
mdgrpret = idgrpret['METADATA']
assert mdgrpret
assert ( abs(mdgrpret['CONFIDENCE'][0] - ann_confidence) < 0.0001 )
#assert ( mdgrpret['CONFIDENCE'][0] == ann_confidence )
assert ( mdgrpret['STATUS'][0] == ann_status )
assert ( mdgrpret['AUTHOR'][:] == ann_author )