@@ -61,7 +61,6 @@ def run(n, backend, datatype, benchmark_mode):
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def transpose (a ):
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return np .permute_dims (a , [1 , 0 ])
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- all_axes = [0 , 1 ]
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init (False )
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elif backend == "numpy" :
@@ -76,7 +75,6 @@ def transpose(a):
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transpose = np .transpose
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fini = sync = lambda x = None : None
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- all_axes = None
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else :
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raise ValueError (f'Unknown backend: "{ backend } "' )
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@@ -240,9 +238,9 @@ def step(u, v, e, u1, v1, e1, u2, v2, e2):
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t = i * dt
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if t >= next_t_export - 1e-8 :
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- _elev_max = np .max (e , all_axes )
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- _u_max = np .max (u , all_axes )
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- _total_v = np .sum (e + h , all_axes )
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+ _elev_max = np .max (e )
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+ _u_max = np .max (u )
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+ _total_v = np .sum (e + h )
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elev_max = float (_elev_max )
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u_max = float (_u_max )
@@ -279,7 +277,7 @@ def step(u, v, e, u1, v1, e1, u2, v2, e2):
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e_exact = exact_elev (t , x_t_2d , y_t_2d , lx , ly )
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err2 = (e_exact - e ) * (e_exact - e ) * dx * dy / lx / ly
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- err_L2 = math .sqrt (float (np .sum (err2 , all_axes )))
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+ err_L2 = math .sqrt (float (np .sum (err2 )))
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info (f"L2 error: { err_L2 :7.5e} " )
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if nx == 128 and ny == 128 and not benchmark_mode :
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