def test_no_soma():
rdw = swc.read(os.path.join(SWC_PATH, 'Single_apical_no_soma.swc'),
has_soma=False)
nt.eq_(rdw.fmt, 'SWC')
nt.eq_(len(rdw.data_block), 211)
nt.eq_(np.shape(rdw.data_block), (211, 7))
nt.assert_not_equal(rdw.data_block[0][4], 0)
def test_read_split_soma():
rdw = swc.read(os.path.join(SWC_PATH, 'split_soma_single_neurites.swc'))
nt.eq_(rdw.neurite_root_section_ids(), [1, 3])
nt.eq_(len(rdw.soma_points()), 3)
nt.eq_(len(rdw.sections), 4)
ref_ids = [[-1, 0], [0, 1, 2, 3, 4], [0, 5, 6], [6, 7, 8, 9, 10], []]
for s, r in zip(rdw.sections, ref_ids):
nt.eq_(s.ids, r)
def test_read_contour_soma_neuron():
rdw = swc.read(os.path.join(SWC_SOMA_PATH, 'contour_soma_neuron.swc'))
nt.eq_(rdw.neurite_root_section_ids(), [3, 4, 5])
nt.eq_(len(rdw.soma_points()), 8)
nt.eq_(len(rdw.sections), 7) # includes one empty section
ref_ids = [[-1, 0, 1, 2], [2, 3, 4, 5], [5, 6, 7], [2, 8, 9, 10, 11, 12],
[5, 13, 14, 15, 16, 17], [7, 18, 19, 20, 21, 22], []]
for s, r in zip(rdw.sections, ref_ids):
nt.eq_(s.ids, r)
def test_read_split_soma():
rdw = swc.read(os.path.join(SWC_PATH, 'split_soma_single_neurites.swc'))
nt.eq_(rdw.neurite_root_section_ids(), [1, 3])
nt.eq_(len(rdw.soma_points()), 3)
nt.eq_(len(rdw.sections), 4)
ref_ids = [[-1, 0],
[0, 1, 2, 3, 4],
[0, 5, 6],
[6, 7, 8, 9, 10],
[]]
for s, r in zip(rdw.sections, ref_ids):
nt.eq_(s.ids, r)
def test_read_contour_split_soma_neuron():
rdw = swc.read(os.path.join(SWC_SOMA_PATH, 'contour_split_soma_neuron.swc'))
nt.eq_(rdw.neurite_root_section_ids(), [1, 4, 5])
nt.eq_(len(rdw.soma_points()), 8)
nt.eq_(len(rdw.sections), 7) # includes one empty section
ref_ids = [[-1, 0, 1, 2],
[2, 3, 4, 5, 6, 7],
[2, 8, 9, 10],
[10, 11, 12],
[10, 13, 14, 15, 16, 17],
[12, 18, 19, 20, 21, 22],
[]]
for s, r in zip(rdw.sections, ref_ids):
nt.eq_(s.ids, r)
def main(conn, argv):
parser = argparse.ArgumentParser()
parser.add_argument("image", help="Image ID")
args = parser.parse_args(argv)
image_id = args.image
data = swc.read(
"20200628-ftp/RL_35_guassian_4_4_80.tif_x94_y327_z241_app2_(GSBT).swc"
).data_block
# img_name = 'FADU_tumour_Lectin_substack_deconvolved_RL_35iters_guassian_psf_4_4_80.tif'
image = conn.getObject("Image", image_id)
# delete existing ROIs
roi_service = conn.getRoiService()
result = roi_service.findByImage(image.id, None)
roi_ids = [roi.id.val for roi in result.rois]
if roi_ids:
print("Deleting ROIs...")
conn.deleteObjects("Roi", roi_ids, wait=True)
size_y = image.getSizeY()
paths = parse_swc(data, size_y)
red_int = int.from_bytes([255, 0, 0, 255], byteorder="big", signed=True)
for count, path in enumerate(paths):
points = []
for zyx in path:
z, y, x = zyx
point = PointI()
point.x = rdouble(x)
point.y = rdouble(y)
point.theZ = rint(round(z))
point.strokeColor = rint(red_int)
points.append(point)
print(f"{count}/{len(paths)} Creating ROI with {len(points)} points")
create_roi(image, points)
import napari
from neurom.io import swc
import numpy as np
def parse_swc(data):
break_points = [0] + list(np.nonzero(np.diff(data[:, 6]) < 0)[0]+1) + [len(data)-1]
paths = []
for i in range(len(break_points)-1):
if break_points[i+1] - break_points[i] > 2:
paths.append(data[break_points[i]:break_points[i+1], :3])
return paths
# def parse_swc_extra(data):
# break_points = [0] + list(np.nonzero(np.diff(data[:, 6]) < 0)[0]+1) + [len(data)-1]
# paths = []
# for i in range(1, len(break_points)-1):
# if break_points[i+1] - break_points[i] > 2:
# paths.append(data[[break_points[i-1], break_points[i]], :3])
# return paths
data = swc.read('data/neuromorphology/204-2-6nj.CNG.swc').data_block
paths = parse_swc(data)
# extra_paths = parse_swc_extra(data)
with napari.gui_qt():
# create an empty viewer
viewer = napari.view_shapes(paths, shape_type='path',
edge_color='blue', ndisplay=3)
# viewer.add_shapes(extra_paths, shape_type='path',
# edge_color='red')
def test_simple_reversed():
rdw = swc.read(os.path.join(SWC_PATH, 'simple_reversed.swc'))
nt.eq_(rdw.neurite_root_section_ids(), [5, 6])
nt.eq_(len(rdw.soma_points()), 1)
nt.eq_(len(rdw.sections), 7)
def test_read_single_neurite():
rdw = swc.read(os.path.join(SWC_PATH, 'point_soma_single_neurite.swc'))
nt.eq_(rdw.neurite_root_section_ids(), [1])
nt.eq_(len(rdw.soma_points()), 1)
nt.eq_(len(rdw.sections), 2)
def test_custom_type():
rdw = swc.read(os.path.join(SWC_PATH, 'custom_type.swc'))
nt.eq_(rdw.fmt, 'SWC')
nt.eq_(len(rdw.data_block), 53)
nt.eq_(np.shape(rdw.data_block), (53, 7))
nt.ok_(rdw.data_block[:, 4].any() <= 4 and rdw.data_block[:, 4].any() >= 0)
def setup(self):
self.data = swc.read(
os.path.join(SWC_PATH, 'sequential_trunk_off_42_16pt.swc'))
self.first_id = int(self.data.data_block[0][COLS.ID])
def test_read_swc_basic_with_offset_42():
"""ID numbering starting at 42."""
rdw = swc.read(os.path.join(SWC_PATH, 'sequential_trunk_off_42_16pt.swc'))
nt.eq_(rdw.fmt, 'SWC')
nt.eq_(len(rdw.data_block), 16)
nt.eq_(np.shape(rdw.data_block), (16, 7))
def test_read_swc_basic():
rdw = swc.read(os.path.join(SWC_PATH, 'random_trunk_off_0_16pt.swc'))
check_single_section_random_swc(rdw.data_block, rdw.fmt)
def setup(self):
self.data = swc.read(
os.path.join(SWC_PATH, 'sequential_trunk_off_42_16pt.swc'))
self.first_id = int(self.data.data_block[0][COLS.ID])
def test_consistency_between_h5_swc():
h5_data = hdf5.read(os.path.join(H5V1_PATH, 'Neuron.h5'), remove_duplicates=True)
swc_data = swc.read(os.path.join(SWC_PATH, 'Neuron.swc'))
nt.ok_(np.allclose(h5_data.data_block.shape, swc_data.data_block.shape))
def test_read_swc_basic():
rdw = swc.read(
os.path.join(SWC_PATH,
'random_trunk_off_0_16pt.swc'))
check_single_section_random_swc(rdw.data_block, rdw.fmt)
def test_read_swc_basic_with_offset_1():
"""More normal ID numbering, starting at 1."""
rdw = swc.read(Path(SWC_PATH, 'sequential_trunk_off_1_16pt.swc'))
nt.eq_(rdw.fmt, 'SWC')
nt.eq_(len(rdw.data_block), 16)
nt.eq_(np.shape(rdw.data_block), (16, 7))
def test_consistency_between_h5_swc():
h5_data = hdf5.read(Path(H5V1_PATH, 'Neuron.h5'), remove_duplicates=True)
swc_data = swc.read(Path(SWC_PATH, 'Neuron.swc'))
nt.ok_(np.allclose(h5_data.data_block.shape, swc_data.data_block.shape))
def test_read_swc_basic_with_offset_0():
"""first ID = 0, rare to find."""
rdw = swc.read(os.path.join(SWC_PATH, 'sequential_trunk_off_0_16pt.swc'))
nt.eq_(rdw.fmt, 'SWC')
nt.eq_(len(rdw.data_block), 16)
nt.eq_(np.shape(rdw.data_block), (16, 7))
def read_swc(filename):
'''Lazy loading of SWC reader'''
from neurom.io import swc
from .swc import SWCDataWrapper
return swc.read(filename, data_wrapper=SWCDataWrapper)
def test_read_single_neurite():
rdw = swc.read(os.path.join(SWC_PATH, 'point_soma_single_neurite.swc'))
nt.eq_(rdw.neurite_root_section_ids(), [1])
nt.eq_(len(rdw.soma_points()), 1)
nt.eq_(len(rdw.sections), 2)
def test_read_swc_basic_with_offset_0():
'''first ID = 0, rare to find'''
rdw = swc.read(os.path.join(SWC_PATH, 'sequential_trunk_off_0_16pt.swc'))
nt.eq_(rdw.fmt, 'SWC')
nt.eq_(len(rdw.data_block), 16)
nt.eq_(np.shape(rdw.data_block), (16, 7))
def test_simple_reversed():
rdw = swc.read(os.path.join(SWC_PATH, 'simple_reversed.swc'))
nt.eq_(rdw.neurite_root_section_ids(), [5, 6])
nt.eq_(len(rdw.soma_points()), 1)
nt.eq_(len(rdw.sections), 7)
def test_read_swc_basic_with_offset_42():
'''ID numbering starting at 42'''
rdw = swc.read(os.path.join(SWC_PATH, 'sequential_trunk_off_42_16pt.swc'))
nt.eq_(rdw.fmt, 'SWC')
nt.eq_(len(rdw.data_block), 16)
nt.eq_(np.shape(rdw.data_block), (16, 7))
