Node labeling affects persistence diagram outcome

[bluebrain]

Node labeling affects persistence diagram outcome

[lidakanari]

Hello, thanks a lot for your message. Indeed, you are correct, this is an assumption according to the "standard swc": http://www.neuronland.org/NLMorphologyConverter/MorphologyFormats/SWC/Spec.html.

Parent samples should appear before any child samples.

According to this assumption the second file is not "standard" (see for example node 3 has as parent node 8), and therefore it is not loaded as expected.

I am aware however, that often data do not follow the correct specifications. I would be glad to modify the code to add a per-processing step to fix this issue, this step should be at the loading of the neuron. However, we are planning to integrate a proper IO library that will resolve this kind of issues (https://github.com/BlueBrain/MorphIO). If you have data that are in a non standard format I would suggest as a quick fix to use MorphIO to save the data in the "expected" format.

Example code:

import morphio
m = morphio.mut.Morphology('test2.swc')
m.write('test3.swc')

Result:

1           1     0.000000     0.000000     0.000000     0.500000          -1
2           3     0.000000     1.000000     0.000000     0.500000           1
3           3     0.000000     2.000000     0.000000     0.500000           2
4           3     0.000000     3.000000     0.000000     0.500000           3
5           3     0.000000     4.000000     0.000000     0.500000           4
6           3     0.000000     3.200000     0.500000     0.500000           4
7           3     0.000000     2.500000     0.500000     0.500000           3
8           3     0.000000     1.000000     0.000000     0.500000           1
9           3     0.000000     1.500000     1.000000     0.500000           8
10           3     0.000000     2.500000     1.300000     0.500000           9
11           3     0.000000     1.500000     2.000000     0.500000           9