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box_smooth.pyx
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box_smooth.pyx
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########################################################################
########################################################################
# Copyright (c) 2013,2014 Svetlin Tassev
# Princeton University,Harvard University
#
# This file is part of pyCOLA.
#
# pyCOLA 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.
#
# pyCOLA 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 pyCOLA. If not, see <http://www.gnu.org/licenses/>.
#
########################################################################
########################################################################
import numpy as np
cimport numpy as np
cimport cython
@cython.boundscheck(False)
@cython.wraparound(False)
@cython.cdivision(True)
@cython.embedsignature(True)
def box_smooth(
np.ndarray[np.float32_t, ndim=3] arr,
np.ndarray[np.float32_t, ndim=3] arr1
):
"""
:math:`\\vspace{-1mm}`
Do a 3x3x3 boxcar smoothing.
**Arguments**:
* ``arr`` -- a 3-dim float32 array serving as input.
* ``arr1`` -- a 3-dim float32 array serving as output.
.. note:: This should really be replaced with a Gaussian smoothing,
so that one can change the amount of smoothing. Gaussian
smoothing can be trivially implemented by modifying
:func:`potential.get_phi` as indicated in the source file of
that function. Not done here as this worked well enough for the
paper.
"""
cdef int i,j,k
cdef int ngrid_x,ngrid_y,ngrid_z
ngrid_x=arr.shape[0]
ngrid_y=arr.shape[1]
ngrid_z=arr.shape[2]
from cython.parallel cimport prange,parallel
cdef int nthreads
from multiprocessing import cpu_count
nthreads=cpu_count()
#print 'nthreads,npart_x = ', nthreads,npart_x
if ngrid_x-2>nthreads:
chunksize=(ngrid_x-2)//nthreads
else:
chunksize=1
arr1[:]=arr[:]
with nogil, parallel(num_threads=nthreads):
for i in prange(1,ngrid_x-1,schedule='static',chunksize=chunksize):
for j in range(1,ngrid_y-1):
for k in range(1,ngrid_z-1):
arr1[i,j,k]+=arr[i-1, j, k]
arr1[i,j,k]+=arr[i, j-1, k]
arr1[i,j,k]+=arr[i, j, k-1]
arr1[i,j,k]+=arr[i-1, j-1, k]
arr1[i,j,k]+=arr[i-1, j, k-1]
arr1[i,j,k]+=arr[i, j-1, k-1]
arr1[i,j,k]+=arr[i-1, j-1, k-1]
arr1[i,j,k]+=arr[i+1, j, k]
arr1[i,j,k]+=arr[i, j+1, k]
arr1[i,j,k]+=arr[i, j, k+1]
arr1[i,j,k]+=arr[i+1, j+1, k]
arr1[i,j,k]+=arr[i+1, j, k+1]
arr1[i,j,k]+=arr[i, j+1, k+1]
arr1[i,j,k]+=arr[i+1, j+1, k+1]
arr1[i,j,k]+=arr[i-1, j+1, k]
arr1[i,j,k]+=arr[i+1, j-1, k]
arr1[i,j,k]+=arr[i+1, j, k-1]
arr1[i,j,k]+=arr[i-1, j, k+1]
arr1[i,j,k]+=arr[i, j+1, k-1]
arr1[i,j,k]+=arr[i, j-1, k+1]
arr1[i,j,k]+=arr[i+1, j-1, k-1]
arr1[i,j,k]+=arr[i-1, j+1, k-1]
arr1[i,j,k]+=arr[i-1, j-1, k+1]
arr1[i,j,k]+=arr[i-1, j+1, k+1]
arr1[i,j,k]+=arr[i+1, j-1, k+1]
arr1[i,j,k]+=arr[i+1, j+1, k-1]
arr1[i,j,k]/=27.0