In [18]:

skids = pymaid.get_neurons_in_volume('AL_L')
nl = pymaid.get_neurons(skids)
nl.head()

Out[18]:

	neuron_name	skeleton_id	n_nodes	n_connectors	n_branch_nodes	n_end_nodes	open_ends	cable_length	review_status	soma
0	neuron 4562948	4562947	2	0	0	1	1	3.945403	NA	False
1	neuron 7094282 MWP Hogeweg	7094281	4267	64	56	57	42	1537.999647	NA	True
2	neuron 8216644 NS	8216643	5934	140	163	166	141	2330.199132	NA	False
3	Multiglomerular PN mALT 57431 IJA ECM	57430	5436	205	101	106	87	1389.803214	NA	True
4	aSP-g tract 6725720 KMS	6725719	2251	29	79	84	38	842.488107	NA	True

In [20]:

subset = nl[nl.n_nodes > 6000]
subset.head()

Out[20]:

	neuron_name	skeleton_id	n_nodes	n_connectors	n_branch_nodes	n_end_nodes	open_ends	cable_length	review_status	soma
0	Multiglomerular bilateral PN mALT 57435 LK	57434	8582	155	161	168	82	1415.474701	NA	True
1	PBG5-EBw-gall (right) neuron 341414 EWN AW	4210786	29397	3107	1886	1955	0	4875.387524	NA	True
2	Multiglomerular PN mALT bilateral 57476 IJA	57475	6737	174	192	196	63	1236.637869	NA	True
3	putative OA mALT 57480 GA FML	57479	8558	226	202	207	116	1965.510890	NA	True
4	PN glomerulus VL1 57500 ML	57499	6551	530	303	322	111	1854.932978	NA	True

In [28]:

subset = nl[nl.soma != None]
subset.head()

Out[28]:

	neuron_name	skeleton_id	n_nodes	n_connectors	n_branch_nodes	n_end_nodes	open_ends	cable_length	review_status	soma
0	neuron 7094282 MWP Hogeweg	7094281	4267	64	56	57	42	1537.999647	NA	True
1	Multiglomerular PN mALT 57431 IJA ECM	57430	5436	205	101	106	87	1389.803214	NA	True
2	aSP-g tract 6725720 KMS	6725719	2251	29	79	84	38	842.488107	NA	True
3	Multiglomerular bilateral PN mALT 57435 LK	57434	8582	155	161	168	82	1415.474701	NA	True
4	PBG5-EBw-gall (right) neuron 341414 EWN AW	4210786	29397	3107	1886	1955	0	4875.387524	NA	True

In [22]:

subset = nl.skid['57499']
subset

Out[22]:


type	<class 'pymaid.core.CatmaidNeuron'>
neuron_name	PN glomerulus VL1 57500 ML
skeleton_id	57499
n_nodes	6551
n_connectors	530
n_branch_nodes	303
n_end_nodes	322
n_open_ends	111
cable_length	1854.93
review_status	NA
soma	3247378

In [23]:

subset = nl.skid [[57499, 57479]]
subset

Out[23]:

	neuron_name	skeleton_id	n_nodes	n_connectors	n_branch_nodes	n_end_nodes	open_ends	cable_length	review_status	soma
0	putative OA mALT 57480 GA FML	57479	8558	226	202	207	116	1965.510890	NA	True
1	PN glomerulus VL1 57500 ML	57499	6551	530	303	322	111	1854.932978	NA	True

In [24]:

subset = nl['PN glomerulus VL1 57500 ML']
subset

Out[24]:

	neuron_name	skeleton_id	n_nodes	n_connectors	n_branch_nodes	n_end_nodes	open_ends	cable_length	review_status	soma
0	PN glomerulus VL1 57500 ML	57499	6551	530	303	322	111	1854.932978	NA	True

In [26]:

subset = nl.has_annotation('LH_DONE', intersect=False)
subset.head()

Out[26]:

	neuron_name	skeleton_id	n_nodes	n_connectors	n_branch_nodes	n_end_nodes	open_ends	cable_length	review_status	soma
0	PN glomerulus VL1 57500 ML	57499	6551	530	303	322	111	1854.932978	NA	True
1	Multiglomerular PN mALT 57537 LK-NM	57536	14654	1233	850	906	278	3193.380472	NA	True
2	PN glomerulus VL1 73938 LK	73937	5273	452	259	274	119	1610.767540	NA	True
3	AL.L(DA1) -{mALT}-> CAL.L-LH.L 2319458 PN036 D...	2319457	10209	964	431	458	90	1747.511710	NA	True
4	PN glomerulus DA2 2467660 RJVR	2467659	2855	266	54	56	8	726.656270	NA	True

In [27]:

subset = nl.has_annotation('~LH_DONE', intersect=False)
subset.head()

Out[27]:

	neuron_name	skeleton_id	n_nodes	n_connectors	n_branch_nodes	n_end_nodes	open_ends	cable_length	review_status	soma
0	neuron 4562948	4562947	2	0	0	1	1	3.945403	NA	False
1	neuron 7094282 MWP Hogeweg	7094281	4267	64	56	57	42	1537.999647	NA	True
2	neuron 8216644 NS	8216643	5934	140	163	166	141	2330.199132	NA	False
3	Multiglomerular PN mALT 57431 IJA ECM	57430	5436	205	101	106	87	1389.803214	NA	True
4	aSP-g tract 6725720 KMS	6725719	2251	29	79	84	38	842.488107	NA	True

In [29]:

subset = nl.has_annotation(['LH_DONE', 'glomerulus DL1'], intersect=False)
subset.head()

Out[29]:

	neuron_name	skeleton_id	n_nodes	n_connectors	n_branch_nodes	n_end_nodes	open_ends	cable_length	review_status	soma
0	PN glomerulus VL1 57500 ML	57499	6551	530	303	322	111	1854.932978	NA	True
1	Multiglomerular PN mALT 57537 LK-NM	57536	14654	1233	850	906	278	3193.380472	NA	True
2	PN glomerulus VL1 73938 LK	73937	5273	452	259	274	119	1610.767540	NA	True
3	AL.L(DA1) -{mALT}-> CAL.L-LH.L 2319458 PN036 D...	2319457	10209	964	431	458	90	1747.511710	NA	True
4	PN glomerulus DA2 2467660 RJVR	2467659	2855	266	54	56	8	726.656270	NA	True

In [30]:

subset = nl.has_annotation(['LH_DONE', 'glomerulus DL1'], intersect=True)
subset.head()

Out[30]:

	neuron_name	skeleton_id	n_nodes	n_connectors	n_branch_nodes	n_end_nodes	open_ends	cable_length	review_status	soma
0	PN glomerulus DL1 5269365 GSXEJ	5269364	3477	893	167	181	58	1228.339971	NA	True
1	PN glomerulus DL1 5305038 ARJ	5305037	2818	898	128	138	15	1050.094319	NA	True