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f | 1 | { | f | 1 | { |
2 | "author": "Schrammer, Stefan", | 2 | "author": "Schrammer, Stefan", | ||
3 | "author_email": "", | 3 | "author_email": "", | ||
4 | "creator_user_id": "17755db4-395a-4b3b-ac09-e8e3484ca700", | 4 | "creator_user_id": "17755db4-395a-4b3b-ac09-e8e3484ca700", | ||
5 | "doi": "10.35097/1408", | 5 | "doi": "10.35097/1408", | ||
6 | "doi_date_published": "2023", | 6 | "doi_date_published": "2023", | ||
7 | "doi_publisher": "", | 7 | "doi_publisher": "", | ||
8 | "doi_status": "True", | 8 | "doi_status": "True", | ||
9 | "groups": [], | 9 | "groups": [], | ||
10 | "id": "00c5177f-4c1f-4113-b6ca-c8ada96ab049", | 10 | "id": "00c5177f-4c1f-4113-b6ca-c8ada96ab049", | ||
11 | "isopen": false, | 11 | "isopen": false, | ||
12 | "license_id": "CC BY-NC-SA 4.0 | 12 | "license_id": "CC BY-NC-SA 4.0 | ||
13 | Attribution-NonCommercial-ShareAlike", | 13 | Attribution-NonCommercial-ShareAlike", | ||
14 | "license_title": "CC BY-NC-SA 4.0 | 14 | "license_title": "CC BY-NC-SA 4.0 | ||
15 | Attribution-NonCommercial-ShareAlike", | 15 | Attribution-NonCommercial-ShareAlike", | ||
16 | "metadata_created": "2023-08-04T08:50:44.116995", | 16 | "metadata_created": "2023-08-04T08:50:44.116995", | ||
t | 17 | "metadata_modified": "2023-08-04T08:50:44.117000", | t | 17 | "metadata_modified": "2023-08-04T08:52:02.498057", |
18 | "name": "rdr-doi-10-35097-1408", | 18 | "name": "rdr-doi-10-35097-1408", | ||
19 | "notes": "TechnicalRemarks: ##### Instructions:\r\n\r\nThe scripts | 19 | "notes": "TechnicalRemarks: ##### Instructions:\r\n\r\nThe scripts | ||
20 | inside the subfolder are intended to reproduce the figures from | 20 | inside the subfolder are intended to reproduce the figures from | ||
21 | the\r\npreprint\r\n\r\n###### Rank-adaptive dynamical low-rank | 21 | the\r\npreprint\r\n\r\n###### Rank-adaptive dynamical low-rank | ||
22 | integrators for first-order and second-order matrix differential | 22 | integrators for first-order and second-order matrix differential | ||
23 | equations\r\n\r\nby Marlis Hochbruck, Markus Neher, and Stefan | 23 | equations\r\n\r\nby Marlis Hochbruck, Markus Neher, and Stefan | ||
24 | Schrammer\r\n\r\nWe provide two different versions of the | 24 | Schrammer\r\n\r\nWe provide two different versions of the | ||
25 | code:\r\n\r\n - Code_rad_wo_ref.zip provides the scripts for | 25 | code:\r\n\r\n - Code_rad_wo_ref.zip provides the scripts for | ||
26 | computing and plotting the data for all numerical\r\n | 26 | computing and plotting the data for all numerical\r\n | ||
27 | experiments.\r\n - Code_rad_incl_all.zip additionally provides the | 27 | experiments.\r\n - Code_rad_incl_all.zip additionally provides the | ||
28 | reference solutions as well as the low-rank\r\n approximations as | 28 | reference solutions as well as the low-rank\r\n approximations as | ||
29 | hdf5-files.\r\n\r\n##### Requirements\r\n\r\nThe codes are tested | 29 | hdf5-files.\r\n\r\n##### Requirements\r\n\r\nThe codes are tested | ||
30 | with\r\n\r\nUbuntu 20.04.2 LTS and Python 3.8.5 and the following | 30 | with\r\n\r\nUbuntu 20.04.2 LTS and Python 3.8.5 and the following | ||
31 | version of its modules:\r\n\r\n numpy 1.19.2\r\n scipy | 31 | version of its modules:\r\n\r\n numpy 1.19.2\r\n scipy | ||
32 | 1.5.2\r\n numba 0.51.2\r\n colorama 0.4.4\r\n h5py | 32 | 1.5.2\r\n numba 0.51.2\r\n colorama 0.4.4\r\n h5py | ||
33 | 2.10.0\r\n matplotlib 3.3.2\r\n tikzplotlib 0.9.6\r\n\r\n###### | 33 | 2.10.0\r\n matplotlib 3.3.2\r\n tikzplotlib 0.9.6\r\n\r\n###### | ||
34 | Generation of figures (tikz files containing the data are also | 34 | Generation of figures (tikz files containing the data are also | ||
35 | created)\r\n\r\nIn the folder fracginz open a console and run the | 35 | created)\r\n\r\nIn the folder fracginz open a console and run the | ||
36 | commands\r\n\r\n to create the data for Figures (1) and (2)\r\n | 36 | commands\r\n\r\n to create the data for Figures (1) and (2)\r\n | ||
37 | python3 fgl.py\r\n to create Figures (1) and (2)\r\n python3 | 37 | python3 fgl.py\r\n to create Figures (1) and (2)\r\n python3 | ||
38 | fgl_results.py\r\n\r\nIn the folder fracschr open a console and run | 38 | fgl_results.py\r\n\r\nIn the folder fracschr open a console and run | ||
39 | the commands\r\n\r\n to create the data for Figure (3)\r\n | 39 | the commands\r\n\r\n to create the data for Figure (3)\r\n | ||
40 | python3 fsr.py\r\n to create Figure (3)\r\n python3 | 40 | python3 fsr.py\r\n to create Figure (3)\r\n python3 | ||
41 | fsr_results.py\r\n\r\nIn the folder laserplasma open a console and run | 41 | fsr_results.py\r\n\r\nIn the folder laserplasma open a console and run | ||
42 | the commands\r\n\r\n to create the data for Figures (4) and (5)\r\n | 42 | the commands\r\n\r\n to create the data for Figures (4) and (5)\r\n | ||
43 | python3 lpi.py\r\n to create Figures (4) and (5)\r\n python3 | 43 | python3 lpi.py\r\n to create Figures (4) and (5)\r\n python3 | ||
44 | lpi_globalerr.py\r\n python3 lpi_svals_maxint.py\r\n\r\nIn the | 44 | lpi_globalerr.py\r\n python3 lpi_svals_maxint.py\r\n\r\nIn the | ||
45 | folder sinegordon open a console and run the commands\r\n\r\n to | 45 | folder sinegordon open a console and run the commands\r\n\r\n to | ||
46 | create the data for Figures (6) and (7)\r\n python3 sineg.py\r\n | 46 | create the data for Figures (6) and (7)\r\n python3 sineg.py\r\n | ||
47 | to create Figures (6) and (7)\r\n python3 | 47 | to create Figures (6) and (7)\r\n python3 | ||
48 | sineg_globalerr_ranks.py", | 48 | sineg_globalerr_ranks.py", | ||
49 | "num_resources": 0, | 49 | "num_resources": 0, | ||
50 | "num_tags": 0, | 50 | "num_tags": 0, | ||
51 | "orcid": "0000-0002-4837-5536", | 51 | "orcid": "0000-0002-4837-5536", | ||
52 | "organization": { | 52 | "organization": { | ||
53 | "approval_status": "approved", | 53 | "approval_status": "approved", | ||
54 | "created": "2023-01-12T13:30:23.238233", | 54 | "created": "2023-01-12T13:30:23.238233", | ||
55 | "description": "RADAR (Research Data Repository) is a | 55 | "description": "RADAR (Research Data Repository) is a | ||
56 | cross-disciplinary repository for archiving and publishing research | 56 | cross-disciplinary repository for archiving and publishing research | ||
57 | data from completed scientific studies and projects. The focus is on | 57 | data from completed scientific studies and projects. The focus is on | ||
58 | research data from subjects that do not yet have their own | 58 | research data from subjects that do not yet have their own | ||
59 | discipline-specific infrastructures for research data management. ", | 59 | discipline-specific infrastructures for research data management. ", | ||
60 | "id": "013c89a9-383c-4200-8baa-0f78bf1d91f9", | 60 | "id": "013c89a9-383c-4200-8baa-0f78bf1d91f9", | ||
61 | "image_url": "radar-logo.svg", | 61 | "image_url": "radar-logo.svg", | ||
62 | "is_organization": true, | 62 | "is_organization": true, | ||
63 | "name": "radar", | 63 | "name": "radar", | ||
64 | "state": "active", | 64 | "state": "active", | ||
65 | "title": "RADAR", | 65 | "title": "RADAR", | ||
66 | "type": "organization" | 66 | "type": "organization" | ||
67 | }, | 67 | }, | ||
68 | "owner_org": "013c89a9-383c-4200-8baa-0f78bf1d91f9", | 68 | "owner_org": "013c89a9-383c-4200-8baa-0f78bf1d91f9", | ||
69 | "private": false, | 69 | "private": false, | ||
70 | "production_year": "2022", | 70 | "production_year": "2022", | ||
71 | "publication_year": "2023", | 71 | "publication_year": "2023", | ||
72 | "publishers": [ | 72 | "publishers": [ | ||
73 | { | 73 | { | ||
74 | "publisher": "Karlsruhe Institute of Technology" | 74 | "publisher": "Karlsruhe Institute of Technology" | ||
75 | } | 75 | } | ||
76 | ], | 76 | ], | ||
77 | "relationships_as_object": [], | 77 | "relationships_as_object": [], | ||
78 | "relationships_as_subject": [], | 78 | "relationships_as_subject": [], | ||
79 | "repository_name": "RADAR (Research Data Repository)", | 79 | "repository_name": "RADAR (Research Data Repository)", | ||
80 | "resources": [], | 80 | "resources": [], | ||
81 | "services_used_list": "", | 81 | "services_used_list": "", | ||
82 | "source_metadata_created": "2023", | 82 | "source_metadata_created": "2023", | ||
83 | "source_metadata_modified": "", | 83 | "source_metadata_modified": "", | ||
84 | "state": "active", | 84 | "state": "active", | ||
85 | "subject_areas": [ | 85 | "subject_areas": [ | ||
86 | { | 86 | { | ||
87 | "subject_area_additional": "", | 87 | "subject_area_additional": "", | ||
88 | "subject_area_name": "Mathematics" | 88 | "subject_area_name": "Mathematics" | ||
89 | } | 89 | } | ||
90 | ], | 90 | ], | ||
91 | "tags": [], | 91 | "tags": [], | ||
92 | "title": "Numerical experiments for \"rank-adaptive dynamical | 92 | "title": "Numerical experiments for \"rank-adaptive dynamical | ||
93 | low-rank integrators for first-order and second-order matrix | 93 | low-rank integrators for first-order and second-order matrix | ||
94 | differential equations\"", | 94 | differential equations\"", | ||
95 | "type": "vdataset", | 95 | "type": "vdataset", | ||
96 | "url": "https://doi.org/10.35097/1408" | 96 | "url": "https://doi.org/10.35097/1408" | ||
97 | } | 97 | } |