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author | Adrian Kummerlaender | 2019-10-21 18:42:24 +0200 |
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committer | Adrian Kummerlaender | 2019-10-21 18:48:38 +0200 |
commit | 82a44e0d64afb8818ea98d68dc08108885d503c2 (patch) | |
tree | 6e8f08acd83b2886cd296ed3831acc83e309906c /boltzgen/utility/ndindex.py | |
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Pull in basics from symlbm_playground
It's time to extract the generator-part of my GPU LBM playground and turn it
into a nice reusable library. The goal is to produce a framework that can be
used to generate collision and streaming programs from symbolic descriptions.
i.e. it should be possible to select a LB model, the desired boundary
conditions as well as a data structure / streaming model and use this
information to automatically generate matching OpenCL / CUDA / C++
programs.
Diffstat (limited to 'boltzgen/utility/ndindex.py')
-rw-r--r-- | boltzgen/utility/ndindex.py | 14 |
1 files changed, 14 insertions, 0 deletions
diff --git a/boltzgen/utility/ndindex.py b/boltzgen/utility/ndindex.py new file mode 100644 index 0000000..0c5ed9b --- /dev/null +++ b/boltzgen/utility/ndindex.py @@ -0,0 +1,14 @@ +import numpy +from numpy.lib.stride_tricks import as_strided +import numpy.core.numeric as _nx + +class ndindex(numpy.ndindex): + pass + + def __init__(self, *shape, order): + if len(shape) == 1 and isinstance(shape[0], tuple): + shape = shape[0] + x = as_strided(_nx.zeros(1), shape=shape, + strides=_nx.zeros_like(shape)) + self._it = _nx.nditer(x, flags=['multi_index', 'zerosize_ok'], + order=order) |