
import os.path as op
import h5py
from contextlib import closing
import numpy as np

project_id = 1
stack_id = 1
filepath = '/home/stephan/dev/CATMAID/django/hdf5'

with closing(h5py.File(op.join(filepath, '%s_%s.hdf' % (project_id, stack_id)), 'w')) as hfile:
    mesh=hfile.create_group('meshes')
    midline=mesh.create_group('midline')
    midline.create_dataset("vertices", data=np.array( [4900,  40, 0, 5230,  70, 4131, 5250,7620,4131, 4820,7630,0] , dtype = np.float32 ) )
    # faces are coded according to the three.js JSONLoader standard.
    # See https://github.com/mrdoob/three.js/blob/master/src/extras/loaders/JSONLoader.js
    midline.create_dataset("faces", data=np.array( [0, 0, 1, 2,  0,2,3,0] , dtype = np.uint32 ) )


import os.path as op
import h5py
from contextlib import closing
import numpy as np

project_id = 1
stack_id = 2
filepath = '/home/stephan/dev/CATMAID/django/hdf5'

with closing(h5py.File(op.join(filepath, '%s_%s.hdf' % (project_id, stack_id)), 'w')) as hfile:
    mesh=hfile.create_group('meshes')
    midline=mesh.create_group('midline')
    midline.create_dataset("vertices", data=np.array( [61200,  15200, 26750,63920,  26400, 76800, 66800,57600,76800, 69200,53120,26750] , dtype = np.float32 ) )
    # faces are coded according to the three.js JSONLoader standard.
    # See https://github.com/mrdoob/three.js/blob/master/src/extras/loaders/JSONLoader.js
    midline.create_dataset("faces", data=np.array( [0, 0, 1, 2,  0,2,3,0] , dtype = np.uint32 ) )

Change in coordinates in the NeuroHDF create
Change in coordinates in the NeuroHDF create

  
  import os.path as op
  import h5py
  from contextlib import closing
  import numpy as np
  
  project_id = 1
- stack_id = 1
+ stack_id = 2
  filepath = '/home/stephan/dev/CATMAID/django/hdf5'
  
  with closing(h5py.File(op.join(filepath, '%s_%s.hdf' % (project_id, stack_id)), 'w')) as hfile:
      mesh=hfile.create_group('meshes')
      midline=mesh.create_group('midline')
-     midline.create_dataset("vertices", data=np.array( [4900,  40, 0, 5230,  70, 4131, 5250,7620,4131, 4820,7630,0] , dtype = np.float32 ) )
+     midline.create_dataset("vertices", data=np.array( [61200,  15200, 26750,63920,  26400, 76800, 66800,57600,76800, 69200,53120,26750] , dtype = np.float32 ) )
      # faces are coded according to the three.js JSONLoader standard.
      # See https://github.com/mrdoob/three.js/blob/master/src/extras/loaders/JSONLoader.js
      midline.create_dataset("faces", data=np.array( [0, 0, 1, 2,  0,2,3,0] , dtype = np.uint32 ) )
  
Change in coordinates in the NeuroHDF create
## Code Before:

import os.path as op
import h5py
from contextlib import closing
import numpy as np

project_id = 1
stack_id = 1
filepath = '/home/stephan/dev/CATMAID/django/hdf5'

with closing(h5py.File(op.join(filepath, '%s_%s.hdf' % (project_id, stack_id)), 'w')) as hfile:
    mesh=hfile.create_group('meshes')
    midline=mesh.create_group('midline')
    midline.create_dataset("vertices", data=np.array( [4900,  40, 0, 5230,  70, 4131, 5250,7620,4131, 4820,7630,0] , dtype = np.float32 ) )
    # faces are coded according to the three.js JSONLoader standard.
    # See https://github.com/mrdoob/three.js/blob/master/src/extras/loaders/JSONLoader.js
    midline.create_dataset("faces", data=np.array( [0, 0, 1, 2,  0,2,3,0] , dtype = np.uint32 ) )

## Instruction:
Change in coordinates in the NeuroHDF create
## Code After:

import os.path as op
import h5py
from contextlib import closing
import numpy as np

project_id = 1
stack_id = 2
filepath = '/home/stephan/dev/CATMAID/django/hdf5'

with closing(h5py.File(op.join(filepath, '%s_%s.hdf' % (project_id, stack_id)), 'w')) as hfile:
    mesh=hfile.create_group('meshes')
    midline=mesh.create_group('midline')
    midline.create_dataset("vertices", data=np.array( [61200,  15200, 26750,63920,  26400, 76800, 66800,57600,76800, 69200,53120,26750] , dtype = np.float32 ) )
    # faces are coded according to the three.js JSONLoader standard.
    # See https://github.com/mrdoob/three.js/blob/master/src/extras/loaders/JSONLoader.js
    midline.create_dataset("faces", data=np.array( [0, 0, 1, 2,  0,2,3,0] , dtype = np.uint32 ) )
