This file describes the relationship between files (including source code of

the corresponding git repository - https://github.com/lfmc/pdccoRSOS) and how

they were used in our article.

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Section (3a) - Baseline

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Source:

part_base_sdumont_specific.cpp

part_base_sdumont_specific.srm

Analysis and graphics:

plot_baseline.py

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Input:

part_base_(2*XX-1).param

part_ar_d100.vtk

part_ar_d100_p01.vtk

part_ar_d100_p02.vtk

part_ar_d100_p03.vtk

part_ar_d100_p04.vtk

Output:

part_baseline_seedXX_termYYYY_base.vtp

part_baseline_seedXX_termYYYY_p01.vtp

part_baseline_seedXX_termYYYY_p02.vtp

part_baseline_seedXX_termYYYY_p03.vtp

part_baseline_seedXX_termYYYY_p04.vtp

part_baseline_seedXX_termYYYY_merged.vtp

part_baseline_seedXX_termYYYY_full.vtp

part_baseline_seedXX_termYYYY_merged.csv

part_baseline_seedXX_termYYYY_full.csv

Obs:

XX goes from 01 to 10.

YYYY goes from 0500 to 4500 in steps of 500.

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Section (3b) - Aspect ratio

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Source:

part_ar_sdumont.cpp

part_ar_sdumont.srm

Analysis and graphics:

plot_ar.py

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Input:

part_ar_XX.param

part_ar_dZZZ.vtk

part_ar_dZZZ_p01.vtk

part_ar_dZZZ_p02.vtk

part_ar_dZZZ_p03.vtk

part_ar_dZZZ_p04.vtk

Output:

part_ar_seedXX_dZZZ_base.vtp

part_ar_seedXX_dZZZ_p_01_.vtp

part_ar_seedXX_dZZZ_p_02_.vtp

part_ar_seedXX_dZZZ_p_03_.vtp

part_ar_seedXX_dZZZ_p_04_.vtp

part_ar_seedXX_dZZZ_merged.vtp

part_ar_seedXX_dZZZ_full_.vtp

part_ar_seedXX_dZZZ_merged.csv

part_ar_seedXX_dZZZ_full_.csv

OBS:

XX goes from 01 to 10.

ZZZ is 025, 050, 075, 100, 150 or 200.

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Section (3c) - Multiple Input

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Source: rsMultipleInput.cpp

Analysis and graphics:

comparison.py

bestBalance.py

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Input:

rsMultipleInputhull.vtk

rsMultipleInput_new.cco

rsMultipleInputpWW.vtk

Output:

rsMultipleInput_func_XXXXX_YYYYY_ZZZZZ_base.vtp

rsMultipleInput_func_XXXXX_YYYYY_ZZZZZ_base.csv

rsMultipleInput_func_01000_08000_01000_merged.vtp

rsMultipleInput_func_06000_00000_04000_merged.vtp

rsMultipleInput_func_01000_08000_01000_merged.csv

rsMultipleInput_func_06000_00000_04000_merged.csv

Obs:

WW goes from 01 to 08.

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Section (3d) - Prototypal cerebral cortex

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Step 1 - Generation of base tree

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Source:

100k_base.cpp

100k_base.srm

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Input:

pial_11_03_2021_hull.vtk

Output:

100k_base_pXX.cco

100k_base_pXX.vtp

Obs:

XX is 15, 25 or 36.

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Step 2 - Generation of parallel trees 

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Source:

100k_net_full_direct.srm

100k_parts.cpp

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Input:

100k_base_pXX.cco

network_pXX_YYY.vtk

Output:

100k_pXX_YYY.vtp

Obs:

XX is 15, 25 or 36.

YYY goes from 01 to 0XX.

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Step 3 - Generation of sequential tree

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Source:

100k_sequential.cpp

100k_sequential.srm

100k_sequential_step.sh

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Input:

100k_base_p25.cco

pial_11_03_2021_hull.vtk

Output:

100k_XXXXX_XXXXX.vtp

times.ods

time_processed.csv

Obs:

XXXXX is 1000, 2000, 3000, 4000, 5000, 6000, 7000, 8000, 9000, 10000, 15000,

20000, 25000, 30000 or 35000.

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Step 4 - Generation of merged tree

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Source:

100k_merge.cpp

Analysis and graphics:

plot_100k.py

plot_time.py

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Input:

100k_base_pXX.cco

Output:

100k_merged_pXX.vtp

100k_merged_pXX.csv

comparison_times.ods

pXX_times.ods

Obs:

XX is 15, 25 or 36.

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Section (3e) - Renal vasculature

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Step 1 - Generation of initial tree

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Source:

renal_artery_to_core_2021.cpp

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Input:

renal_arteries_tri_simplified_04_02_2021.cco

left_core_06_07_2020_LFC_decimated.vtk

left_pelvis_06_07_2020_LFC_decimated.vtk

left_pyramids_06_07_2020_LFC_decimated.vtk

Output:

left_kidney_13_pyramids_renal_artery_tri_radius_func_09990_00005_00005_09_02_2021_19_20_21.cco

left_kidney_13_pyramids_renal_artery_tri_radius_func_09990_00005_00005_09_02_2021_19_20_21.vtp

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Step 2 - Generation of base tree

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Source:

kidney_base_power.cpp

kidney_base_power.srm

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Input:

k_base_power_03.param

left_kidney_13_pyramids_renal_artery_tri_radius_func_09990_00005_00005_09_02_2021_19_20_21.cco

left_core_06_07_2020_LFC_decimated.vtk

left_pelvis_06_07_2020_LFC_decimated.vtk

left_pyramids_06_07_2020_LFC_decimated.vtk

left_surface_06_07_2020_LFC_decimated.vtk

left_cortex_06_07_2020_LFC_decimated.vtk

Output:

kidney_base_gam30.cco

kidney_base_gam30.vtp

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Step 3 - Generation of parallel trees

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Source:

kidney_parts_power_specific.cpp

kidney_100k_parts.srm

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Input:

kidney_base_power_03_part.param

left_core_06_07_2020_LFC_decimated.vtk

left_pelvis_06_07_2020_LFC_decimated.vtk

left_pyramids_06_07_2020_LFC_decimated.vtk

left_surface_06_07_2020_LFC_decimated.vtk

left_cortex_region_XX_20_09_2020_cube.vtk

kidney_base_gam30.cco

Output:

kidney_region_XX_gam30.vtp

Obs:

XX goes from 01 to 08.

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Step 4 - Generation of final merged tree

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Source:

kidney_merge_power.cpp

Analysis and graphics:

kidney_rs.py

plot_kidney.py

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Input:

kidney_base_gam30.cco

Output:

kidney_merged_gam30.vtp

kidney_merged_gam30_strahler.vtp

kidney_100k_connectivity_strahler.csv

kidney_100k_summary_strahler.csv

kidney_merged_gam30.csv

kidney_merged_gam30_strahler.csv

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