@@ -118,7 +118,8 @@ def test_setup_multi_index_advection_diffusion_benchmark(self):
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sigma = 1
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nvars = 5
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- config_values = [2 * np .arange (1 , 11 ), 2 * np .arange (1 , 11 )]
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+ # config_values = [2*np.arange(1, 11), 2*np.arange(1, 11)]
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+ config_values = [2 * np .arange (1 , 16 ), 2 * np .arange (1 , 16 )]
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benchmark = setup_benchmark (
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"multi_index_advection_diffusion" , kle_nvars = nvars ,
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kle_length_scale = length_scale , kle_stdev = sigma ,
@@ -160,6 +161,7 @@ def test_setup_multi_index_advection_diffusion_benchmark(self):
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print (rel_diffs )
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assert (rel_diffs .max () > 1e-1 and rel_diffs .min () < 3e-5 )
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# ndof = (config_samples+1).prod(axis=0)
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+ # import matplotlib.pyplot as plt
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# plt.loglog(
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# ndof[:-1], np.abs((qoi_means[-1]-qoi_means[:-1])/qoi_means[-1]))
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# plt.show()
@@ -178,7 +180,7 @@ def test_setup_transient_multi_index_advection_diffusion_benchmark(self):
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# "init_sol_fun": partial(full_fun_axis_1, 0),
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"sink" : [50 , 0.1 , [0.75 , 0.75 ]]
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}
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- nlevels = 8
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+ nlevels = 9
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config_values = [2 * np .arange (4 , 4 + nlevels ), 2 * np .arange (4 , 4 + nlevels ),
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final_time / (2 ** np .arange (1 , 1 + nlevels )* 2 )]
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# np.array([final_time/(2**5*2)]*nlevels)]
@@ -252,11 +254,12 @@ def test_setup_transient_multi_index_advection_diffusion_benchmark(self):
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ntsteps = time_scenario ["final_time" ]/ config_samples [2 ]
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print (ntsteps )
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print (time_scenario ["final_time" ]- config_samples [2 ]* ntsteps )
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- ndof = (config_samples [:2 ]+ 1 ).prod (axis = 0 )* ntsteps
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+ # ndof = (config_samples[:2]+1).prod(axis=0)*ntsteps
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+ # import matplotlib.pyplot as plt
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# plt.loglog(
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# ndof[:-1], np.abs((qoi_means[-1]-qoi_means[:-1])/qoi_means[-1]))
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# plt.show()
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- assert (rel_diffs .max () > 4e-2 and rel_diffs .min () < 8e -5 )
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+ assert (rel_diffs .max () > 4e-2 and rel_diffs .min () < 9.1e -5 )
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if __name__ == "__main__" :
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