Co-plotting CATMAID skeleton with flywire dataset
This section contains example of fetching skeleton from a public catmaid instance and co-plotting with a flywire instance
Import neccesary library modules now
[1]:
import navis
import fafbseg
import pymaid
[2]:
import pandas as pd
import numpy as np
import os
from copy import deepcopy
[3]:
from pyroglancer.localserver import startdataserver, closedataserver
from pyroglancer.flywire import flywireurl2dict, add_flywirelayer, set_flywireviewerstate
from pyroglancer.ngviewer import openviewer
Set configurations to fetch from data from CATMAID
[4]:
publicurl = 'https://fafb.catmaid.virtualflybrain.org/'
[5]:
working_rm = pymaid.CatmaidInstance(publicurl, api_token=None, project_id = 1)
INFO : Global CATMAID instance set. Caching is ON. (pymaid)
INFO - 2021-05-19 23:30:41,498 - client - Global CATMAID instance set. Caching is ON.
Get sample skids and neuropil meshes from CATMAID
[6]:
catmiad_neuronlist=pymaid.get_neuron('/DA1 lPN',remote_instance = working_rm) #get some DA1 PNs..
WARNING - 2021-05-19 23:30:42,839 - connectionpool - Connection pool is full, discarding connection: fafb.catmaid.virtualflybrain.org
WARNING - 2021-05-19 23:30:42,887 - connectionpool - Connection pool is full, discarding connection: fafb.catmaid.virtualflybrain.org
WARNING - 2021-05-19 23:30:43,086 - connectionpool - Connection pool is full, discarding connection: fafb.catmaid.virtualflybrain.org
WARNING - 2021-05-19 23:30:43,132 - connectionpool - Connection pool is full, discarding connection: fafb.catmaid.virtualflybrain.org
WARNING - 2021-05-19 23:30:43,178 - connectionpool - Connection pool is full, discarding connection: fafb.catmaid.virtualflybrain.org
INFO - 2021-05-19 23:30:43,574 - utils - NumExpr defaulting to 8 threads.
[7]:
vols = pymaid.get_volume(['v14.neuropil', 'AL_R'], color=(255, 0, 0, .2))
Transform them to flywire space
[8]:
flywire_neuron=navis.xform_brain(catmiad_neuronlist,source='FAFB14', target='FLYWIRE')
Transform path: FAFB14 -> FAFB14raw -> FLYWIREraw -> FLYWIRE
[9]:
flywirevol = {}
flywirevol['v14.neuropil']=navis.xform_brain(vols['v14.neuropil'],source='FAFB14', target='FLYWIRE')
flywirevol['AL_R']=navis.xform_brain(vols['AL_R'],source='FAFB14', target='FLYWIRE')
Transform path: FAFB14 -> FAFB14raw -> FLYWIREraw -> FLYWIRE
Transform path: FAFB14 -> FAFB14raw -> FLYWIREraw -> FLYWIRE
[10]:
flywirevol['v14.neuropil'].id = 200
flywirevol['AL_R'].id = 300
flywirevol
[10]:
{'v14.neuropil': <navis.Volume(name=None, id=200, color=(0.85, 0.85, 0.85, 0.2), vertices.shape=(8997, 3), faces.shape=(18000, 3))>,
'AL_R': <navis.Volume(name=None, id=300, color=(0.85, 0.85, 0.85, 0.2), vertices.shape=(622, 3), faces.shape=(1240, 3))>}
Start the dataserver to host precomputed data
[11]:
startdataserver()
Serving data from: /var/folders/_l/lrfvj_8j3ps0c37ncbr3c8dh0000gn/T/tmp_5o756gr
Get the url from flywire to append data onto
[12]:
shorturl = 'https://ngl.flywire.ai/?json_url=https://globalv1.flywire-daf.com/nglstate/5644175227748352'
#This flywire segments has some stuff similar to the DA1 PNs, you will notice their closeness in the final plot
Serving directory at http://127.0.0.1:8000
Add skids to flywire layers
[13]:
tmpviewer = add_flywirelayer(flywireurl2dict(shorturl), layer_kws = {'type': 'skeletons',
'source': flywire_neuron[7:9],
'name': 'catmaid_skels',
'color': 'red'})
#'alpha': 0.3, doesn't work yet in skeleton layers..
/private/var/folders/_l/lrfvj_8j3ps0c37ncbr3c8dh0000gn/T/tmp_5o756gr/precomputed/catmaid_skels/skeletons/57323
/private/var/folders/_l/lrfvj_8j3ps0c37ncbr3c8dh0000gn/T/tmp_5o756gr/precomputed/catmaid_skels/skeletons/57353
creating: /private/var/folders/_l/lrfvj_8j3ps0c37ncbr3c8dh0000gn/T/tmp_5o756gr/precomputed/catmaid_skels/skeletons/seg_props
{'57323': ['#ff0000'], '57353': ['#ff0000']}
flywire url at: https://ngl.flywire.ai/?json_url=https://globalv1.flywire-daf.com/nglstate/5174672299655168
Add neuropil meshes to flywire layers
[14]:
shorturl = tmpviewer
[15]:
tmpviewer = add_flywirelayer(flywireurl2dict(shorturl), layer_kws = {'type': 'volumes',
'source': [flywirevol['v14.neuropil'],
flywirevol['AL_R']],
'name': 'catmaid_neuropils',
'color': ['grey', 'magenta'],
'alpha': 0.3})
mesh/200
Seg id is: 200
Full filepath: /private/var/folders/_l/lrfvj_8j3ps0c37ncbr3c8dh0000gn/T/tmp_5o756gr/precomputed/catmaid_neuropils/mesh/200
mesh/300
Seg id is: 300
Full filepath: /private/var/folders/_l/lrfvj_8j3ps0c37ncbr3c8dh0000gn/T/tmp_5o756gr/precomputed/catmaid_neuropils/mesh/300
creating: /private/var/folders/_l/lrfvj_8j3ps0c37ncbr3c8dh0000gn/T/tmp_5o756gr/precomputed/catmaid_neuropils/mesh/segment_properties
creating: /private/var/folders/_l/lrfvj_8j3ps0c37ncbr3c8dh0000gn/T/tmp_5o756gr/precomputed/catmaid_neuropils/mesh/segment_names
flywire url at: https://ngl.flywire.ai/?json_url=https://globalv1.flywire-daf.com/nglstate/6708937697001472
[16]:
shorturl = tmpviewer
[17]:
layout = {'type':'xy-3d','orthographicProjection':'True'}
[18]:
tmpviewer,shorturl = set_flywireviewerstate(shorturl, axis_lines=False, bounding_box=False, layout = layout)
flywire url at: https://ngl.flywire.ai/?json_url=https://globalv1.flywire-daf.com/nglstate/4984286184734720
Screenshot of the flywire instance
The grey mesh is the v14.1 neuropil, magenta is the Antenna lobe (Right), you can see the skeletons from CATMAID (red) plotted in the skeleton layer, and some similar neurons (meshes) of the flywire dataset plotted in green and yellow
Add synapses and other annotations to flywire layers (not yet working)
[ ]:
ngdict = flywireurl2dict(shorturl)
[ ]:
tmpviewer = add_flywirelayer(ngdict, layer_kws = {'type': 'synapses','source': flywire_neuron,
'ngspace': 'FAFBv14.1'})
[ ]:
temp_pts = pd.DataFrame([[123072, 47001, 3375]],columns=['x','y','z'])
temp_pts = pd.DataFrame([[123072, 47001, 3375], [120000, 17001, 3000]], columns=['x', 'y', 'z'])
temp_pts['description'] = ['center_pt','above_pt']
[ ]:
#plot landmarks..
tmpviewer = add_flywirelayer(ngdict, layer_kws = {'type': 'points','name': 'landmarks',
'ngspace': 'FAFBv14.1',
'source': temp_pts,'color': 'red'})
[ ]:
tmpviewer
Close the dataserver
[19]:
closedataserver()
Closing server at http://127.0.0.1:8000
Cleaning directory at /private/var/folders/_l/lrfvj_8j3ps0c37ncbr3c8dh0000gn/T/tmp_5o756gr