Implemented relative error estimates for adaptive step size selection #515
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brownbaerchen
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#!!!!!!!!!! WARNING: RUFF FAILED !!!!!!!!!!: #pySDC/projects/GPU/analysis_scripts/compare_RBC3D.py:418:9: E722 Do not use bare `except` # | Parallel-in-Time#416 | k[_s > 1e-16], _s[_s > 1e-16], color=last_line.get_color(), ls=last_line.get_linestyle(), label=label Parallel-in-Time#417 | ) Parallel-in-Time#418 | except: # | ^^^^^^ E722 Parallel-in-Time#419 | pass # | # #pySDC/projects/GPU/analysis_scripts/compare_RBC3D.py:517:5: F841 Local variable `Delta_Nu` is assigned to but never used # | Parallel-in-Time#515 | t = data['t'] Parallel-in-Time#516 | avg_Nu = np.array([np.mean(Nu[40 : 40 + i + 1]) for i in range(len(Nu[40:]))]) Parallel-in-Time#517 | Delta_Nu = np.array([abs(avg_Nu[i + 1] - avg_Nu[i]) for i in range(len(avg_Nu) - 1)]) # | ^^^^^^^^ F841 Parallel-in-Time#518 | # ax.plot(data['t'][40:-1], Delta_Nu / avg_Nu[:-1]) Parallel-in-Time#519 | # ax.plot(data['t'], np.abs(avg_Nu - avg_Nu[-1]) / avg_Nu[-1]) # | # = help: Remove assignment to unused variable `Delta_Nu`:
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I should have done this long ago. For the Williamson 5 test case that simulates the Earth, the numbers are so huge, that you really need to look at relative errors. The tutorial for the Gusto coupling will use the Williamson 5 test case and with adaptive step size selection. However, I thought I would do a separate PR for all the non-Gusto related changes that are needed for that.
This PR includes a Firedrake-compatible version of dt-k-adaptivity. The interpolation was done in a NumPy specific way, which I want to keep because it is faster on NumPy and CuPy data than a more generic version. This Firedrake enabled version should actually work with any datatype, but we are not entirely sure if you need to invert the mass matrix during the interpolation. Currently I left in the FE/Firedrake specific bit as a comment. If we become more confident that we don't need to invert the mass matrix, we can eventually rename this to something more general and remove the comment.