def _new_operator1(shape, **kwargs):
infield = DenseData(name='infield', shape=shape, dtype=np.int32)
infield.data[:] = np.arange(reduce(mul, shape), dtype=np.int32).reshape(shape)
outfield = DenseData(name='outfield', shape=shape, dtype=np.int32)
stencil = Eq(outfield.indexify(), outfield.indexify() + infield.indexify()*3.0)
# Run the operator
op = Operator(stencil, **kwargs)
op(infield=infield, outfield=outfield)
return outfield, op
def symbol(name, dimensions, value=0., mode='function'):
"""Short-cut for symbol creation to test "function"
and "indexed" API."""
assert(mode in ['function', 'indexed'])
s = DenseData(name=name, dimensions=dimensions)
s.data[:] = value
return s.indexify() if mode == 'indexed' else s
def test_arithmetic_deep(expr, result):
"""Tests basic point-wise arithmetic on multi-dimensional data"""
i = Dimension(name='i', size=3)
j = Dimension(name='j', size=4)
k = Dimension(name='k', size=5)
l = Dimension(name='l', size=6)
a = DenseData(name='a', dimensions=(i, j, k, l))
a.data[:] = 2.
ai = a.indexify()
b = DenseData(name='b', dimensions=(j, k))
b.data[:] = 3.
bi = b.indexify()
eqn = eval(expr)
StencilKernel(eqn)(ai.base.function, bi.base.function)
assert np.allclose(ai.base.function.data, result, rtol=1e-12)
def bi(x, y, name='b', value=3.):
b = DenseData(name=name, dimensions=(x, y))
b.data[:] = value
return b.indexify()
def ai(x, y, name='a', value=2.):
a = DenseData(name=name, dimensions=(x, y))
a.data[:] = value
return a.indexify()