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examples: Update expected output
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@FabioLuporini
FabioLuporini committed Jan 17, 2024
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34 changes: 21 additions & 13 deletions examples/userapi/01_dsl.ipynb
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" provided, shape and dimensions must be given. For MPI execution, a\n",
" Grid is compulsory.\n",
" space_order : int or 3-tuple of ints, optional\n",
" Discretisation order for space derivatives. Defaults to 1. ``space_order`` also\n",
" impacts the number of points available around a generic point of interest. By\n",
" default, ``space_order`` points are available on both sides of a generic point of\n",
" interest, including those nearby the grid boundary. Sometimes, fewer points\n",
" suffice; in other scenarios, more points are necessary. In such cases, instead of\n",
" an integer, one can pass a 3-tuple ``(o, lp, rp)`` indicating the discretization\n",
" order (``o``) as well as the number of points on the left (``lp``) and right\n",
" (``rp``) sides of a generic point of interest.\n",
" Discretisation order for space derivatives. Defaults to 1.\n",
" `space_order` also impacts the number of points available around a\n",
" generic point of interest. By default, `space_order` points are\n",
" available on both sides of a generic point of interest, including those\n",
" nearby the grid boundary. Sometimes, fewer points suffice; in other\n",
" scenarios, more points are necessary. In such cases, instead of an\n",
" integer, one can pass:\n",
" * a 3-tuple `(o, lp, rp)` indicating the discretization order\n",
" (`o`) as well as the number of points on the left (`lp`) and\n",
" right (`rp`) sides of a generic point of interest;\n",
" * a 2-tuple `(o, ((lp0, rp0), (lp1, rp1), ...))` indicating the\n",
" discretization order (`o`) as well as the number of points on\n",
" the left/right sides of a generic point of interest for each\n",
" SpaceDimension.\n",
" shape : tuple of ints, optional\n",
" Shape of the domain region in grid points. Only necessary if ``grid`` isn't given.\n",
" Shape of the domain region in grid points. Only necessary if `grid`\n",
" isn't given.\n",
" dimensions : tuple of Dimension, optional\n",
" Dimensions associated with the object. Only necessary if ``grid`` isn't given.\n",
" Dimensions associated with the object. Only necessary if `grid` isn't\n",
" given.\n",
" dtype : data-type, optional\n",
" Any object that can be interpreted as a numpy data type. Defaults\n",
" to ``np.float32``.\n",
" to `np.float32`.\n",
" staggered : Dimension or tuple of Dimension or Stagger, optional\n",
" Define how the Function is staggered.\n",
" initializer : callable or any object exposing the buffer interface, optional\n",
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" Notes\n",
" -----\n",
" The parameters must always be given as keyword arguments, since SymPy\n",
" uses ``*args`` to (re-)create the dimension arguments of the symbolic object.\n",
" uses `*args` to (re-)create the dimension arguments of the symbolic object.\n",
" \n"
]
}
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"} ;\n",
"\n",
"\n",
"int Kernel(const float dt, const float h_x, const float h_y, struct dataobj *restrict u_vec, const int time_M, const int time_m, const int x_M, const int x_m, const int y_M, const int y_m, struct profiler * timers)\n",
"int Kernel(struct dataobj *restrict u_vec, const float dt, const float h_x, const float h_y, const int time_M, const int time_m, const int x_M, const int x_m, const int y_M, const int y_m, struct profiler * timers)\n",
"{\n",
" float (*restrict u)[u_vec->size[1]][u_vec->size[2]] __attribute__ ((aligned (64))) = (float (*)[u_vec->size[1]][u_vec->size[2]]) u_vec->data;\n",
"\n",
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