five

Numerical experiments for "Rank-adaptive dynamical low-rank integrators for first-order and second-order matrix differential equations"

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DataCite Commons2023-11-15 更新2025-04-16 收录
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https://radar.kit.edu/radar/en/dataset/diuGWkRCSxYcTxQV
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##### Instructions: The scripts inside the subfolder are intended to reproduce the figures from the preprint ###### Rank-adaptive dynamical low-rank integrators for first-order and second-order matrix differential equations by Marlis Hochbruck, Markus Neher, and Stefan Schrammer We provide two different versions of the code: - Code_rad_wo_ref.zip provides the scripts for computing and plotting the data for all numerical experiments. - Code_rad_incl_all.zip additionally provides the reference solutions as well as the low-rank approximations as hdf5-files. ##### Requirements The codes are tested with Ubuntu 20.04.2 LTS and Python 3.8.5 and the following version of its modules: numpy 1.19.2 scipy 1.5.2 numba 0.51.2 colorama 0.4.4 h5py 2.10.0 matplotlib 3.3.2 tikzplotlib 0.9.6 ###### Generation of figures (tikz files containing the data are also created) In the folder fracginz open a console and run the commands to create the data for Figures (1) and (2) python3 fgl.py to create Figures (1) and (2) python3 fgl_results.py In the folder fracschr open a console and run the commands to create the data for Figure (3) python3 fsr.py to create Figure (3) python3 fsr_results.py In the folder laserplasma open a console and run the commands to create the data for Figures (4) and (5) python3 lpi.py to create Figures (4) and (5) python3 lpi_globalerr.py python3 lpi_svals_maxint.py In the folder sinegordon open a console and run the commands to create the data for Figures (6) and (7) python3 sineg.py to create Figures (6) and (7) python3 sineg_globalerr_ranks.py
提供机构:
Karlsruhe Institute of Technology
创建时间:
2023-06-21
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