Dataset for "Numerical methods for the detection of phase defect structures in excitable media"
Authors/Creators
- 1. KU Leuven, LUMC
- 2. KU Leuven
- 3. U Ghent
Description
This archive contains the numerical methods presented in the publication "Numerical methods for the detection of phase defect structures in excitable media" as well as the data sets these methods have been applied on. The Python module for Ithildin (py_ithildin.zip) contains the actual Python source code of those methods. Additional Python scripts have been used to generate the figures in the paper (scripts-pdl-detection.zip). The optical voltage mapping data (optical_*) has been slightly pre-processed (noise reduction, re-scaling, etc). The second variable for the optical data (optical_20200204114234_v.npy) is a delayed version of the first variable. The other files contain simulation results from several finite differences simulations of the mono-domain model. For details, see our paper.
Numerical methods for the detection of phase defect structures in excitable media
Kabus D, Arno L, Leenknegt L, Panfilov AV, Dierckx H (2022) Numerical methods for the detection of phase defect structures in excitable media. PLOS ONE 17(7): e0271351. https://doi.org/10.1371/journal.pone.0271351
Files
forcePDL_62_log.txt
Files
(5.6 GB)
| Name | Size | Download all |
|---|---|---|
|
md5:d62da2095d1a8278ed96e2ea626bf707
|
810.0 kB | Download |
|
md5:7b948cd230c10f56e02cd607dc77e6cf
|
1.7 kB | Preview Download |
|
md5:2a223f3845d279001e8a631775c96757
|
12.6 kB | Preview Download |
|
md5:6af2de63ba5918c56a52d12ee2e3be34
|
405.8 MB | Download |
|
md5:4b94a8950633771281e42e147e8a81ab
|
405.8 MB | Download |
|
md5:2bca7c4faf2ffbff85eb8efb90b910a6
|
405.8 MB | Download |
|
md5:a41a9eee4a1fb34b179ac6a91da150a6
|
10.1 kB | Download |
|
md5:dd98ada3c96a73c08c6e8afeac9ca6c1
|
650 Bytes | Preview Download |
|
md5:c58c0d497332a7a03d85d7c0118574fa
|
81.9 MB | Download |
|
md5:7a0982ea8635216afeef12182a072c1f
|
81.9 MB | Download |
|
md5:eb88cc2fd6827d6b91a20e0f14185aa0
|
1.5 kB | Preview Download |
|
md5:a6fd3c3abfe60f03120951946cf616ae
|
581.8 MB | Download |
|
md5:eebbd26df64357a5c13c5231dd1f2c13
|
226.9 kB | Preview Download |
|
md5:9c9c44d81f37f90ab6945d3679e253d8
|
581.8 MB | Download |
|
md5:ac0bf36c0432ceba5d990c70da9ddff4
|
581.8 MB | Download |
|
md5:8d395b3b7ae47b19792c0decefd981f9
|
581.8 MB | Download |
|
md5:a21ab4f8d22d26cde5db6ae5bb5374f0
|
1.8 kB | Preview Download |
|
md5:a42d482f33cfe4e5a215e45425af1d43
|
48.9 kB | Preview Download |
|
md5:4a8211b737c80a017083add6c4652edc
|
405.0 MB | Download |
|
md5:52a33973a5f6215d1eff2e9e39ffd277
|
405.0 MB | Download |
|
md5:be9169f090f87ddad463f06cfbeab033
|
405.0 MB | Download |
|
md5:0d5f18630236783734ed3c732cc3bb6a
|
1.7 kB | Preview Download |
|
md5:43ee091e4579769d4086910cf897688e
|
81.8 kB | Preview Download |
|
md5:d0aefa4a3913c383129db261e57d61d7
|
320.0 MB | Download |
|
md5:730a05e0c8491da87a025c3666dc5b89
|
320.0 MB | Download |
|
md5:41a407ff2344b256000fd5e4e401dbb8
|
96.1 kB | Preview Download |
|
md5:98a5b049b78ac96965b5b97a24e93231
|
44.2 kB | Preview Download |
Additional details
Related works
- Is supplement to
- Journal article: 10.1371/journal.pone.0271351 (DOI)