In [1]:

    

import pymaid

rm = pymaid.CatmaidInstance('https://www.your.catmaid-server.org',
                            api_token='YOURTOKEN',
                            http_user='user', # omit if not required
                            http_password='pw') # omit if not required


    

    




INFO  : Global CATMAID instance set. (pymaid.fetch)

In [2]:

    

skids = pymaid.get_skids_by_annotation('glomerulus DL4')
skids


    

    




INFO  : Found 5 skeletons with matching annotation(s) (pymaid)






    
Out[2]:





['6698696', '6170457', '57059', '23829', '483289']

In [3]:

    

tn_table = pymaid.get_treenode_table(skids[0])
tn_table.head()


    

    




INFO  : Retrieving 1 treenode table(s)... (pymaid)
INFO  : 1903 treenodes retrieved. Creating table... (pymaid)






    
Out[3]:







  

    

      

      
skeleton_id
      
treenode_id
      
parent_node_id
      
confidence
      
x
      
y
      
z
      
radius
      
creator
      
last_edited
      
reviewers
      
tags
    
  
  

    

      
0
      
6698696
      
22106010
      
30501406
      
5
      
378008
      
159302
      
158000
      
-1
      
batesa
      
2018-07-12 17:22:16+00:00
      
[]
      
[]
    
    

      
1
      
6698696
      
30501406
      
22106009
      
5
      
378022
      
159331
      
158080
      
-1
      
robertsr
      
2018-07-12 17:22:17+00:00
      
[]
      
[]
    
    

      
2
      
6698696
      
25548795
      
25548717
      
5
      
434298
      
297110
      
59480
      
1625
      
costam
      
2018-03-28 13:59:08+00:00
      
[]
      
[soma]
    
    

      
3
      
6698696
      
25548717
      
25548650
      
5
      
435449
      
296530
      
60680
      
-1
      
costam
      
2018-03-28 13:58:04+00:00
      
[]
      
[]
    
    

      
4
      
6698696
      
25548650
      
25548645
      
5
      
436769
      
296642
      
61240
      
-1
      
costam
      
2018-03-28 13:57:41+00:00
      
[]
      
[]
    
  

In [4]:

    

neuron_list = pymaid.get_neuron ( ['57311','27295'] )


    

In [5]:

    

neuron_list


    

    
Out[5]:







  

    

      

      
neuron_name
      
skeleton_id
      
n_nodes
      
n_connectors
      
n_branch_nodes
      
n_end_nodes
      
open_ends
      
cable_length
      
review_status
      
soma
    
  
  

    

      
0
      
PN glomerulus DA1 57312 LK
      
57311
      
4882
      
429
      
157
      
164
      
105
      
1182.102458
      
NA
      
True
    
    

      
1
      
PN glomerulus DA1 27296 BH
      
27295
      
9975
      
471
      
212
      
219
      
58
      
1591.519823
      
NA
      
True
    
  

In [6]:

    

neuron_list[0]


    

    
Out[6]:







  

    

      

      

    
  
  

    

      
type
      
<class 'pymaid.core.CatmaidNeuron'>
    
    

      
neuron_name
      
PN glomerulus DA1 57312 LK
    
    

      
skeleton_id
      
57311
    
    

      
n_nodes
      
4882
    
    

      
n_connectors
      
429
    
    

      
n_branch_nodes
      
157
    
    

      
n_end_nodes
      
164
    
    

      
n_open_ends
      
105
    
    

      
cable_length
      
1182.1
    
    

      
review_status
      
NA
    
    

      
soma
      
3059181
    
  

In [7]:

    

n = neuron_list[0]

# .nodes is a pandas DataFrame and we can use .head() to show the first couple entries
n.nodes.head()


    

    
Out[7]:







  

    

      

      
treenode_id
      
parent_id
      
creator_id
      
x
      
y
      
z
      
radius
      
confidence
      
type
    
  
  

    

      
0
      
3395047
      
26660885
      
25
      
362196
      
164703
      
150960
      
-1
      
5
      
slab
    
    

      
1
      
26660885
      
3395044
      
117
      
362089
      
164620
      
151160
      
-1
      
5
      
slab
    
    

      
2
      
26171077
      
7688883
      
117
      
366603
      
156742
      
153720
      
-1
      
5
      
end
    
    

      
3
      
7688883
      
26171069
      
123
      
366604
      
156868
      
153800
      
-1
      
5
      
slab
    
    

      
4
      
26171069
      
26171067
      
117
      
366575
      
156826
      
153840
      
-1
      
5
      
slab
    
  

In [8]:

    

n.connectors.head()


    

    
Out[8]:







  

    

      

      
treenode_id
      
connector_id
      
relation
      
x
      
y
      
z
    
  
  

    

      
0
      
1208403
      
29790621
      
1
      
448908
      
150692
      
218040
    
    

      
1
      
1208413
      
29790616
      
0
      
448068
      
150780
      
218160
    
    

      
2
      
26660885
      
26660887
      
0
      
361070
      
163821
      
151160
    
    

      
3
      
26660885
      
26660883
      
0
      
361450
      
164421
      
151160
    
    

      
4
      
3155268
      
26387175
      
0
      
365954
      
157079
      
155080
    
  

In [9]:

    

n.skeleton_id


    

    
Out[9]:





'57311'

In [10]:

    

neuron_list.skeleton_id


    

    
Out[10]:





array(['57311', '27295'], dtype='<U5')

In [11]:

    

neuron_list[0]


    

    
Out[11]:







  

    

      

      

    
  
  

    

      
type
      
<class 'pymaid.core.CatmaidNeuron'>
    
    

      
neuron_name
      
PN glomerulus DA1 57312 LK
    
    

      
skeleton_id
      
57311
    
    

      
n_nodes
      
4882
    
    

      
n_connectors
      
429
    
    

      
n_branch_nodes
      
157
    
    

      
n_end_nodes
      
164
    
    

      
n_open_ends
      
105
    
    

      
cable_length
      
1182.1
    
    

      
review_status
      
NA
    
    

      
soma
      
3059181
    
  

In [12]:

    

neuron_list[0].review_status


    

    
Out[12]:





90

In [13]:

    

neuron_list


    

    
Out[13]:







  

    

      

      
neuron_name
      
skeleton_id
      
n_nodes
      
n_connectors
      
n_branch_nodes
      
n_end_nodes
      
open_ends
      
cable_length
      
review_status
      
soma
    
  
  

    

      
0
      
PN glomerulus DA1 57312 LK
      
57311
      
4882
      
429
      
157
      
164
      
105
      
1182.102458
      
90
      
True
    
    

      
1
      
PN glomerulus DA1 27296 BH
      
27295
      
9975
      
471
      
212
      
219
      
58
      
1591.519823
      
NA
      
True
    
  

In [14]:

    

neuron_list[0].get_review()


    

    
Out[14]:





90

In [15]:

    

neuron_list.review_status


    

    
Out[15]:





array([90, 88])