Revision 0c424d28187e87091d71d74003c806fc3a5b04ab authored by Koustav Chandra on 04 October 2020, 15:43:49 UTC, committed by GitHub on 04 October 2020, 15:43:49 UTC
* Added support for threshold * Update hdf.py * whitespace Co-authored-by: Koustav Chandra <koustav.chandra@ldas-pcdev6.ligo-wa.caltech.edu>
1 parent f0fd8ba
test_correlate.py
# Copyright (C) 2012 Alex Nitz, Josh Willis
#
# 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
#
# =============================================================================
#
"""
These are the unittests for the correlate functions in pycbc.filter.matchedfilter_cpu
"""
import sys
import pycbc
import unittest
import numpy
from pycbc.types import *
from pycbc.scheme import *
from pycbc.filter import *
import pycbc.fft
from utils import parse_args_all_schemes, simple_exit
from pycbc.filter.matchedfilter import BatchCorrelator, Correlator
_scheme, _context = parse_args_all_schemes("correlate")
from pycbc.filter.matchedfilter_cpu import correlate_numpy
trusted_correlate = correlate_numpy
class Testcorrelate(unittest.TestCase):
def setUp(self,*args):
self.context = _context
self.scheme = _scheme
self.tolerance = 1e-6
xr = numpy.random.uniform(low=-1, high=1.0, size=2**20)
yr = numpy.random.uniform(low=-1, high=1.0, size=2**20)
xi = numpy.random.uniform(low=-1, high=1.0, size=2**20)
yi = numpy.random.uniform(low=-1, high=1.0, size=2**20)
self.x = Array(xr + xi * 1.0j, dtype=complex64)
self.y = Array(yr + yi * 1.0j, dtype=complex64)
self.z = zeros(2**20, dtype=complex64)
trusted_correlate(self.x, self.y, self.z)
def test_correlate(self):
with self.context:
z = zeros(2**20, dtype=complex64)
correlate(self.x, self.y, z)
self.assertTrue(self.z.almost_equal_elem(z, self.tolerance))
def test_correlator(self):
x = self.x * 1
y = self.y * 1
z = self.z * 0
corr = Correlator(x, y, z)
corr.correlate()
self.assertTrue(z.almost_equal_elem(self.z, self.tolerance))
def test_batch_correlate(self):
size = len(self.x)
xs = [self.x+0, self.x+1, self.x+2, self.x+3]
zs = [self.z*0, self.z*1, self.z*2, self.z*3]
b = BatchCorrelator(xs, zs, size)
b.execute(self.y)
for i in range(len(xs)):
trusted_correlate(xs[i], self.y, self.z)
self.assertTrue(self.z.almost_equal_elem(zs[i], self.tolerance))
suite = unittest.TestSuite()
suite.addTest(unittest.TestLoader().loadTestsFromTestCase(Testcorrelate))
if __name__ == '__main__':
results = unittest.TextTestRunner(verbosity=2).run(suite)
simple_exit(results)
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