# Copyright (C) 2012 Alex Nitz
# This program is free software; you can redistribute it and/or modify it
# under the terms of the GNU General Public License as published by the
# Free Software Foundation; either version 3 of the License, or (at your
# option) any later version.
#
# This program is distributed in the hope that it will be useful, but
# WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General
# Public License for more details.
#
# You should have received a copy of the GNU General Public License along
# with this program; if not, write to the Free Software Foundation, Inc.,
# 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.
#
# =============================================================================
#
# Preamble
#
# =============================================================================
#
from pycuda.elementwise import ElementwiseKernel
from pycuda.tools import context_dependent_memoize
from pycuda.tools import dtype_to_ctype
from pycuda.gpuarray import _get_common_dtype
from .matchedfilter import _BaseCorrelator
@context_dependent_memoize
def get_correlate_kernel(dtype_x, dtype_y,dtype_out):
return ElementwiseKernel(
"%(tp_x)s *x, %(tp_y)s *y, %(tp_z)s *z" % {
"tp_x": dtype_to_ctype(dtype_x),
"tp_y": dtype_to_ctype(dtype_y),
"tp_z": dtype_to_ctype(dtype_out),
},
"z[i] = conj(x[i]) * y[i]",
"correlate")
[docs]
def correlate(a, b, out, stream=None):
dtype_out = _get_common_dtype(a,b)
krnl = get_correlate_kernel(a.dtype, b.dtype, dtype_out)
krnl(a.data, b.data, out.data)
[docs]
class CUDACorrelator(_BaseCorrelator):
def __init__(self, x, y, z):
self.x = x.data
self.y = y.data
self.z = z.data
dtype_out = _get_common_dtype(x, y)
self.krnl = get_correlate_kernel(x.dtype, y.dtype, dtype_out)
[docs]
def correlate(self):
self.krnl(self.x, self.y, self.z)
def _correlate_factory(x, y, z):
return CUDACorrelator