コード例 #1
0
ファイル: StatsTest.cpp プロジェクト: pombredanne/BICEPS
void test()
{
    Stats::vector_type a(2);
    a(0) = 1;
    a(1) = 2;

    Stats::vector_type b(2);
    b(0) = 3;
    b(1) = 4;

    Stats::vector_type c(2);
    c(0) = 5;
    c(1) = 6;

    Stats::data_type data;
    data.push_back(a);
    data.push_back(b);
    data.push_back(c);

    Stats stats(data);
    if (os_) *os_ << "mean: " << stats.mean() << endl;
    if (os_) *os_ << "covariance: " << stats.covariance() << endl;

    // mean & covariance computed using good old-fashioned reckoning
    Stats::vector_type mean(2);
    mean(0) = 3;
    mean(1) = 4;
    Stats::matrix_type covariance(2,2);
    covariance(0,0) = covariance(0,1) = covariance(1,0) = covariance(1,1) = 8/3.;

    // verify results
    const double epsilon = 1e-12;
    unit_assert_vectors_equal(stats.mean(), mean, epsilon);
    unit_assert_matrices_equal(stats.covariance(), covariance, epsilon);

    double rms0_good = sqrt(35./3);
    double rms1_good = sqrt(56./3);
    double rms0_test = sqrt(stats.meanOuterProduct()(0,0));
    double rms1_test = sqrt(stats.meanOuterProduct()(1,1));
    unit_assert_equal(rms0_test, rms0_good, epsilon);
    unit_assert_equal(rms1_test, rms1_good, epsilon);
}
コード例 #2
0
ファイル: Stats.cpp プロジェクト: lgatto/proteowizard
void Stats::Impl::computeSums(const Stats::data_type& data)
{
    if (data.size()>0) D_ = data[0].size();
    sumData_ = Stats::vector_type(D_);
    sumOuterProducts_ = Stats::matrix_type(D_, D_);

    sumData_.clear();
    sumOuterProducts_.clear();

    for (Stats::data_type::const_iterator it=data.begin(); it!=data.end(); ++it)
    {
        if (it->size() != D_)
        {
            ostringstream message;
            message << "[Stats::Impl::computeSums()] " << D_ << "-dimensional data expected: " << *it; 
            throw runtime_error(message.str());
        } 

        sumData_ += *it;
        sumOuterProducts_ += outer_prod(*it, *it);
    }
}
コード例 #3
0
ファイル: simnoise.cpp プロジェクト: AlexandreBurel/pwiz-mzdb
void processTLP(const TruncatedLorentzianParameters& tlp, int trialCount, bool verbose)
{
    if (verbose) 
        cout << tlp << "\n\n\n";
    else
        cout << columnHeader_ << endl; 

    for (double snr=2; snr<=10; snr+=.5)
    for (double gridOffset=-.5; gridOffset<=.5; gridOffset+=.1)
/*
    double snr = 100;
    double gridOffset = 0;
*/
    {
        if (verbose)
        {
            cout << fixed;
            cout << "signal-to-noise ratio: " << snr << endl; 
            cout << "relative grid offset: " << gridOffset << endl;
        }

        Stats::data_type data;
        double crBound = 0;

        for (int i=0; i<trialCount; i++)
        {
            try
            {
                Stats::vector_type result = runTrial(tlp, snr, gridOffset, crBound); 
                data.push_back(result);
            }
            catch (exception& e)
            {
                cerr << e.what() << endl;
                cerr << "Caught exception, continuing.\n";
            }
        }

        if (verbose)
        {
            cout << endl <<
                setw(13) << "err_f0_pred" <<
                setw(14) << "err_f0" <<
                setw(14) << "err_tau" <<
                setw(14) << "err_magnitude" << 
                setw(14) << "err_phase" << 
                setw(14) << "model_error" << 
                setw(14) << "z-score" << 
                endl;

            for (Stats::data_type::iterator it=data.begin(); it!=data.end(); ++it)
                outputVector(*it);
        }

        Stats stats(data);
        double mean_f0 = stats.mean()(F0);
        double variance_f0 = stats.covariance()(F0,F0);
        double expectedF0Squared = stats.meanOuterProduct()(F0,F0);

        if (verbose)
        {
            outputStats(stats);
            cout << endl;

            cout << fixed << noshowpos;
            cout << "<err_f0^2>: " << expectedF0Squared << endl;
            cout << "Cramer-Rao bound: " << crBound << endl << endl;

            cout << columnHeader_ << endl; 
        }

        cout << noshowpos << fixed << setprecision(3) 
            << setw(7) << snr << " " << 
            setw(7) << gridOffset << " " << 
            setprecision(10) << 
            setw(14) << mean_f0 << " " << 
            setw(14) << variance_f0 << " " << 
            setw(14) << sqrt(variance_f0) << " " <<
            setw(14) << expectedF0Squared << " " << 
            setw(14) << crBound << endl; 

        if (verbose)
            cout << "\n\n";
    }
}
コード例 #4
0
ファイル: Stats.cpp プロジェクト: lgatto/proteowizard
Stats::Impl::Impl(const Stats::data_type& data)
:   D_(0),
    N_(data.size())
{
    computeSums(data);
}