Apply myelin labels to basket cell axon

This example uses the plotting package PyVista for interactive rendering. Any rendering program that takes vertices and edges can work.

import pandas as pd
import numpy as np

from caveclient import CAVEclient
import pyvista as pv
import cloudvolume 
import seaborn as sns

Query a myelinated cell

# Set version to first data release with manual myelination labels
client = CAVEclient("minnie65_public")
client.version = 1078

# Load the myelin values 
myelin_df = client.materialize.tables.vortex_manual_myelination_v0().query(
    desired_resolution=[1,1,1])

# Load the nodes of Ranvier
nodes_df = client.materialize.tables.vortex_manual_nodes_of_ranvier().query(
    desired_resolution=[1,1,1])
Table Owner Notice on vortex_manual_myelination_v0: Myelination status assessed for the axon of the VALID_ID, not the pt_root_id.
Table Owner Notice on vortex_manual_nodes_of_ranvier: Nodes and myelination assessed for the VALID_ID; if pt_root_id does not match valid_id, the segment has undergone proofreading. Proceed with caution.
myelin_df.valid_id.unique()
array([864691135808631069, 864691136210378684, 864691135639556411,
       864691135162983725, 864691136724881917])
# select an example myelinated basket cell
root_id = 864691136210378684

Load the static mesh for one cell

# Set the static segmentaiton source to the most recent flat segmentation where that root id is valid
seg_source = 'precomputed://gs://iarpa_microns/minnie/minnie65/seg_m943'

# load from cloudvolume
cv = cloudvolume.CloudVolume(seg_source, progress=False, use_https=True)
mesh = cv.mesh.get(root_id, lod=2)[root_id]
# Render the mesh vertices for pyvista
vertices = mesh.vertices
faces = mesh.faces

# add a column of all 3s to the faces
padded_faces = np.concatenate([np.full((faces.shape[0], 1), 3), faces], axis=1)

mesh_poly = pv.PolyData(vertices, faces=padded_faces)

# Flip with y axis
mesh_poly.points[:, 1] *= -1
# Format the myelin annotations 
myelin_points = np.vstack(myelin_df.query(f"(valid_id=={root_id}) & (tag=='t')").pt_position.to_numpy()).astype(float)
myelin_poly = pv.PolyData(myelin_points)

# Flip with y axis
myelin_poly.points[:, 1] *= -1
# Format the node annotations 
ranvier_points = np.vstack(nodes_df.query(f"(valid_id=={root_id})").pt_position.to_numpy()).astype(float)
ranvier_poly = pv.PolyData(ranvier_points)

# Flip with y axis
ranvier_poly.points[:, 1] *= -1

Initialize plotting object, add mesh and annotations

pv.set_jupyter_backend("client")
plotter = pv.Plotter(image_scale=10)

silhouette = dict(
    color=[.06, .48, .67],
    line_width=0.5,
)

plotter.add_mesh(mesh_poly, color=[.06, .48, .67], opacity=0.75, silhouette=silhouette)
plotter.add_mesh(myelin_poly, point_size=6, color="orange", opacity=0.5)

plotter.camera_position = 'zy'
plotter.camera.zoom(1.0)
plotter.set_background('#fbfbfb')

plotter.show()
Interactive: Myelination (yellow) annotated along basket cell axon (blue)
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