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//
// $Id$
//
//
// Original author: Darren Kessner <darren@proteowizard.org>
//
// Copyright 2007 Spielberg Family Center for Applied Proteomics
// Cedars Sinai Medical Center, Los Angeles, California 90048
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
//
#include "MatchedFilter.hpp"
#include "pwiz/utility/misc/unit.hpp"
#include "pwiz/utility/misc/Std.hpp"
#include <complex>
#include <cstring>
#include <typeinfo>
using namespace pwiz::math;
using namespace pwiz::util;
ostream* os_ = 0;
void test_SampledData()
{
if (os_) *os_ << "test_SampledData()\n";
using namespace MatchedFilter;
SampledData<DxD> sd;
sd.domain = make_pair(0.0, 2.0);
sd.samples.push_back(10);
sd.samples.push_back(11);
sd.samples.push_back(12);
sd.samples.push_back(13);
sd.samples.push_back(14);
if (os_) *os_ << sd << endl;
if (os_) *os_ << "domainWidth: " << sd.domainWidth() << endl;
unit_assert(sd.domainWidth() == 2.0);
if (os_) *os_ << "dx: " << sd.dx() << endl;
unit_assert(sd.dx() == .5);
for (unsigned int i=0; i<sd.samples.size(); i++)
{
if (os_) *os_ << "x(" << i << "): " << sd.x(i) << endl;
unit_assert(sd.x(i) == i * .5);
}
unsigned int count = 0;
for (double x=-.2; x<2.3; x+=.1, count++)
{
//if (os_) *os_ << "sampleIndex(" << x << "): " << sd.sampleIndex(x) << endl;
unit_assert(sd.sampleIndex(x) == count/5);
//if (os_) *os_ << "sample(" << x << "): " << sd.sample(x) << endl;
unit_assert(sd.sample(x) == 10 + count/5);
}
}
// Kernel types defined as objects must define space_type in the class definition,
// or in a specialization of KernelTraitsBase<>.
struct OneMinusAbs
{
typedef MatchedFilter::DxD space_type;
double operator()(double d) const {return (d>=-1 && d<=1) ? 1 - abs(d) : 0;}
};
// KernelTraitsBase<> has default specialization for function pointer types
complex<double> OneMinusAbsComplex(double d)
{
return (d>=-1 && d<=1) ? 1 - abs(d) : 0;
}
template <typename Kernel>
void test_createFilter(const Kernel& f)
{
using namespace MatchedFilter;
if (os_) *os_ << "test_createFilter() " << typeid(f).name() << endl;
int sampleRadius = 4;
double dx = .25;
double shift = 0;
typedef typename KernelTraits<Kernel>::filter_type filter_type;
typedef typename KernelTraits<Kernel>::abscissa_type abscissa_type;
typedef typename KernelTraits<Kernel>::ordinate_type ordinate_type;
filter_type filter = details::createFilter(f, sampleRadius, dx, shift);
if (os_)
{
copy(filter.begin(), filter.end(), ostream_iterator<ordinate_type>(*os_, " "));
*os_ << endl;
}
unit_assert((int)filter.size() == sampleRadius*2 + 1);
for (int i=-sampleRadius; i<=sampleRadius; ++i)
unit_assert(filter[sampleRadius+i] == f(i*dx - shift));
if (os_) *os_ << endl;
}
template <typename Kernel>
void test_createFilters(const Kernel& f)
{
using namespace MatchedFilter;
if (os_) *os_ << "test_createFilters() " << typeid(f).name() << endl;
int sampleRadius = 2;
int subsampleFactor = 4;
double dx = 1;
typedef typename KernelTraits<Kernel>::filter_type filter_type;
typedef typename KernelTraits<Kernel>::ordinate_type ordinate_type;
vector<filter_type> filters = details::createFilters(f,
sampleRadius,
subsampleFactor,
dx);
// verify filter count
unit_assert((int)filters.size() == subsampleFactor);
for (typename vector<filter_type>::const_iterator it=filters.begin(); it!=filters.end(); ++it)
{
if (os_)
{
copy(it->begin(), it->end(), ostream_iterator<ordinate_type>(*os_, " "));
*os_ << endl;
}
// verify filter size
unit_assert((int)it->size() == sampleRadius*2 + 1);
// verify filter normalization
double sum = 0;
for (typename filter_type::const_iterator jt=it->begin(); jt!=it->end(); ++jt)
sum += norm(complex<double>(*jt));
unit_assert_equal(sum, 1, 1e-14);
}
if (os_) *os_ << endl;
}
template <typename Kernel>
void test_compute(const Kernel& f)
{
using namespace MatchedFilter;
if (os_) *os_ << "test_compute() " << typeid(f).name() << endl;
typename KernelTraits<Kernel>::sampled_data_type data;
data.domain = make_pair(0, 10);
data.samples.resize(11);
data.samples[5] = 1.;
if (os_) *os_ << "data: " << data << endl;
int sampleRadius = 2;
int sampleFactor = 4;
typedef typename KernelTraits<Kernel>::correlation_data_type CorrelationData;
CorrelationData correlationData =
computeCorrelationData(data, f, sampleRadius, sampleFactor);
if (os_) *os_ << "correlationData: " << correlationData << endl;
unit_assert(correlationData.samples.size() == 41);
unit_assert(abs(correlationData.samples[20].dot - 1.) < 1e-12);
}
template <typename Kernel>
void test_kernel(const Kernel& kernel)
{
if (os_) *os_ << "***************************************************************\n";
if (os_) *os_ << "test_kernel() " << typeid(kernel).name() << endl;
if (os_) *os_ << "***************************************************************\n";
if (os_) *os_ << endl;
test_createFilter(kernel);
test_createFilters(kernel);
test_compute(kernel);
}
int main(int argc, char* argv[])
{
TEST_PROLOG(argc, argv)
try
{
if (argc>1 && !strcmp(argv[1],"-v")) os_ = &cout;
if (os_) *os_ << "MatchedFilterTest\n";
test_SampledData();
test_kernel(OneMinusAbs());
test_kernel(&OneMinusAbsComplex);
}
catch (exception& e)
{
TEST_FAILED(e.what())
}
catch (...)
{
TEST_FAILED("Caught unknown exception.")
}
TEST_EPILOG
}
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