yt.utilities.amr_kdtree.amr_kdtree module¶
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class
yt.utilities.amr_kdtree.amr_kdtree.
AMRKDTree
(ds, min_level=None, max_level=None, data_source=None)[source]¶ Bases:
yt.utilities.parallel_tools.parallel_analysis_interface.ParallelAnalysisInterface
A KDTree for AMR data.
Not applicable to particle or octree-based datasets.
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comm
= None¶
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fields
= None¶
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get_dependencies
(fields)¶
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locate_neighbors
(grid, ci)[source]¶ Given a grid and cell index, finds the 26 neighbor grids and cell indices.
- Parameters
grid (Grid Object) – Grid containing the cell of interest
ci (array-like) – The cell index of the cell of interest
- Returns
grids (Numpy array of Grid objects)
cis (List of neighbor cell index tuples)
Both of these are neighbors that, relative to the current cell
index (i,j,k), are ordered as
(i-1, j-1, k-1), (i-1, j-1, k ), (i-1, j-1, k+1), …
(i-1, j , k-1), (i-1, j , k ), (i-1, j , k+1), …
(i+1, j+1, k-1), (i-1, j-1, k ), (i+1, j+1, k+1)
That is they start from the lower left and proceed to upper
right varying the third index most frequently. Note that the
center cell (i,j,k) is omitted.
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locate_neighbors_from_position
(position)[source]¶ Given a position, finds the 26 neighbor grids and cell indices.
This is a mostly a wrapper for locate_neighbors.
- Parameters
position (array-like) – Position of interest
- Returns
grids (Numpy array of Grid objects)
cis (List of neighbor cell index tuples)
Both of these are neighbors that, relative to the current cell
index (i,j,k), are ordered as
(i-1, j-1, k-1), (i-1, j-1, k ), (i-1, j-1, k+1), …
(i-1, j , k-1), (i-1, j , k ), (i-1, j , k+1), …
(i+1, j+1, k-1), (i-1, j-1, k ), (i+1, j+1, k+1)
That is they start from the lower left and proceed to upper
right varying the third index most frequently. Note that the
center cell (i,j,k) is omitted.
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log_fields
= None¶
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no_ghost
= True¶
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partition_index_2d
(axis)¶
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partition_index_3d
(ds, padding=0.0, rank_ratio=1)¶
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partition_index_3d_bisection_list
()¶ Returns an array that is used to drive _partition_index_3d_bisection, below.
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partition_region_3d
(left_edge, right_edge, padding=0.0, rank_ratio=1)¶ Given a region, it subdivides it into smaller regions for parallel analysis.
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