void bi::cov(const ExpGaussianPdf<V1, M1>& q, M2 Sigma) {
/* pre-condition */
BI_ASSERT(Sigma.size1() == q.size());
BI_ASSERT(Sigma.size2() == q.size());
Sigma = q.cov();
}
Common_type<Value_type<M1>, Value_type<M2> >
dot_product (const M1 &a, const M2 &b)
{
static_assert (a.order == 1, "");
static_assert (b.order == 1, "");
assert (a.size () == b.size ());
return inner_product (a.begin (), a.end (), b.begin (), size_t (0));
}
void checkMatrixEqual(M1 const& m1, M2 const& m2){
BOOST_REQUIRE_EQUAL(m1.size1(),m2.size1());
BOOST_REQUIRE_EQUAL(m1.size2(),m2.size2());
for(std::size_t i = 0; i != m2.size1(); ++i){
for(std::size_t j = 0; j != m2.size2(); ++j){
BOOST_CHECK_EQUAL(m1(i,j),m2(i,j));
}
}
}
void bi::cov(const M1 X, const V1 mu, M2 Sigma) {
/* pre-conditions */
BI_ASSERT(X.size2() == mu.size());
BI_ASSERT(Sigma.size1() == mu.size() && Sigma.size2() == mu.size());
const int N = X.size1();
typename sim_temp_matrix<M2>::type Y(X.size1(), X.size2());
Y = X;
sub_rows(Y, mu);
syrk(1.0/(N - 1.0), Y, 0.0, Sigma, 'U', 'T');
}
void bi::cross(const M1 X, const M2 Y, const V1 muX, const V2 muY,
M3 SigmaXY) {
/* pre-conditions */
BI_ASSERT(X.size2() == muX.size());
BI_ASSERT(Y.size2() == muY.size());
BI_ASSERT(X.size1() == Y.size1());
BI_ASSERT(SigmaXY.size1() == muX.size() && SigmaXY.size2() == muY.size());
const int N = X.size1();
gemm(1.0/(N - 1.0), X, Y, 0.0, SigmaXY, 'T', 'N');
ger(-N/(N - 1.0), muX, muY, SigmaXY);
}
void expectNear(const M1 & A, const M2 & B, T tolerance, std::string const & message = "")
{
EXPECT_EQ((size_t)A.rows(),(size_t)B.rows()) << message << "\nMatrix A:\n" << A << "\nand matrix B\n" << B << "\nare not the same\n";
EXPECT_EQ((size_t)A.cols(),(size_t)B.cols()) << message << "\nMatrix A:\n" << A << "\nand matrix B\n" << B << "\nare not the same\n";
for(int r = 0; r < A.rows(); r++)
{
for(int c = 0; c < A.cols(); c++)
{
EXPECT_NEAR(A(r,c),B(r,c),tolerance) << message << "\nTolerance comparison failed at (" << r << "," << c << ")\n"
<< "\nMatrix A:\n" << A << "\nand matrix B\n" << B;
}
}
}
void assertEqual(const M1 & A, const M2 & B, std::string const & message = "")
{
ASSERT_EQ((size_t)A.rows(),(size_t)B.rows()) << message << "\nMatrix A:\n" << A << "\nand matrix B\n" << B << "\nare not the same\n";
ASSERT_EQ((size_t)A.cols(),(size_t)B.cols()) << message << "\nMatrix A:\n" << A << "\nand matrix B\n" << B << "\nare not the same\n";
for(int r = 0; r < A.rows(); r++)
{
for(int c = 0; c < A.cols(); c++)
{
ASSERT_EQ(A(r,c),B(r,c)) << message << "\nEquality comparison failed at (" << r << "," << c << ")\n"
<< "\nMatrix A:\n" << A << "\nand matrix B\n" << B;
}
}
}
void bi::standardise(const ExpGaussianPdf<V1,M1>& p, M2 X) {
/* pre-condition */
BI_ASSERT(p.size() == X.size2());
typename sim_temp_vector<M2>::type mu(X.size2());
log_columns(X, p.getLogs());
mean(X, mu);
sub_rows(X, mu);
trsm(1.0, p.std(), X, 'R', 'U');
add_rows(X, mu);
sub_rows(X, p.mean());
exp_columns(X, p.getLogs());
}
bool compare_result(const M1& sm, const M2& m)
{
if(sm.size() != m.size())
return false;
if(sm.line() != m.line())
return false;
for(unsigned int i = 0; i < sm.size(); ++i)
{
if(sm.position(i) != m.position(i))
return false;
if(sm.length(i) != m.length(i))
return false;
}
return true;
}
void check_LU_res(const M1 & m, const M2& lu)
{
GeneralMatrix l(m.M(), m.N());
GeneralMatrix u(m.M(), m.N());
for(int i = 0; i < lu.M(); i++)
{
for(int j = 0; j< lu.N(); j++)
{
if(i>j)
{
l(i, j) = lu(i, j);
u(i, j) = 0;
}
else if(i == j)
{
l(i, j) = 1;
u(i, j) = lu(i, j);
}
else
{
l(i, j) = 0;
u(i, j) = lu(i, j);
}
}
}
bool equal = true;
GeneralMatrix m1(m.M(), m.N());
mul(l, u, m1);
for(int i = 0; i<m.M(); i++)
for(int j = 0; j< m.N(); j++)
{
if(std::abs(m1(i, j) - m(i, j) ) / m(i, j) > 0.1)
{
equal = false;
}
}
if(!check_Matrix(m1,m))
{
std::cout<<"wrong answer!"<<std::endl;
}
else
{
std::cout<<"right answer, wahahahaha!"<<std::endl;
}
}
void assertNear(const M1 & A, const M2 & B, T tolerance, std::string const & message = "")
{
// Note: If these assertions fail, they only abort this subroutine.
// see: http://code.google.com/p/googletest/wiki/AdvancedGuide#Using_Assertions_in_Sub-routines
// \todo better handling of this
ASSERT_EQ((size_t)A.rows(),(size_t)B.rows()) << message << "\nMatrix A:\n" << A << "\nand matrix B\n" << B << "\nare not the same\n";
ASSERT_EQ((size_t)A.cols(),(size_t)B.cols()) << message << "\nMatrix A:\n" << A << "\nand matrix B\n" << B << "\nare not the same\n";
for(int r = 0; r < A.rows(); r++)
{
for(int c = 0; c < A.cols(); c++)
{
ASSERT_NEAR(A(r,c),B(r,c),tolerance) << message << "\nTolerance comparison failed at (" << r << "," << c << ")\n"
<< "\nMatrix A:\n" << A << "\nand matrix B\n" << B;
}
}
}
void bi::cov(const M1 X, const V1 w, const V2 mu, M2 Sigma) {
/* pre-conditions */
BI_ASSERT(X.size2() == mu.size());
BI_ASSERT(X.size1() == w.size());
BI_ASSERT(Sigma.size1() == mu.size() && Sigma.size2() == mu.size());
typedef typename V1::value_type T;
typename sim_temp_matrix<M2>::type Y(X.size1(), X.size2());
typename sim_temp_matrix<M2>::type Z(X.size1(), X.size2());
typename sim_temp_vector<V2>::type v(w.size());
T Wt = sum_reduce(w);
Y = X;
sub_rows(Y, mu);
sqrt_elements(w, v);
gdmm(1.0, v, Y, 0.0, Z);
syrk(1.0/Wt, Z, 0.0, Sigma, 'U', 'T');
// alternative weight: 1.0/(Wt - W2t/Wt)
}
void bi::distance(const M1 X, const real h, M2 D) {
/* pre-conditions */
BI_ASSERT(D.size1() == D.size2());
BI_ASSERT(D.size1() == X.size1());
BI_ASSERT(!M2::on_device);
typedef typename M1::value_type T1;
FastGaussianKernel K(X.size2(), h);
typename temp_host_vector<T1>::type d(X.size2());
int i, j;
for (j = 0; j < D.size2(); ++j) {
for (i = 0; i <= j; ++i) {
d = row(X, i);
axpy(-1.0, row(X, j), d);
D(i, j) = K(dot(d));
}
}
}
void checkDenseMatrixEqual(M1 const& m1, M2 const& m2){
BOOST_REQUIRE_EQUAL(m1.size1(),m2.size1());
BOOST_REQUIRE_EQUAL(m1.size2(),m2.size2());
//indexed access
for(std::size_t i = 0; i != m2.size1(); ++i){
for(std::size_t j = 0; j != m2.size2(); ++j){
BOOST_CHECK_EQUAL(m1(i,j),m2(i,j));
}
}
//iterator access rows
for(std::size_t i = 0; i != m2.size1(); ++i){
typedef typename M1::const_row_iterator Iter;
BOOST_REQUIRE_EQUAL(m1.row_end(i)-m1.row_begin(i), m1.size2());
std::size_t k = 0;
for(Iter it = m1.row_begin(i); it != m1.row_end(i); ++it,++k){
BOOST_CHECK_EQUAL(k,it.index());
BOOST_CHECK_EQUAL(*it,m2(i,k));
}
//test that the actual iterated length equals the number of elements
BOOST_CHECK_EQUAL(k, m1.size2());
}
//iterator access columns
for(std::size_t i = 0; i != m2.size2(); ++i){
typedef typename M1::const_column_iterator Iter;
BOOST_REQUIRE_EQUAL(m1.column_end(i)-m1.column_begin(i), m1.size1());
std::size_t k = 0;
for(Iter it = m1.column_begin(i); it != m1.column_end(i); ++it,++k){
BOOST_CHECK_EQUAL(k,it.index());
BOOST_CHECK_EQUAL(*it,m2(k,i));
}
//test that the actual iterated length equals the number of elements
BOOST_CHECK_EQUAL(k, m1.size1());
}
}
void bi::cross(const M1 X, const M2 Y, const V1 w, const V2 muX,
const V3 muY, M3 SigmaXY) {
/* pre-conditions */
BI_ASSERT(X.size2() == muX.size());
BI_ASSERT(Y.size2() == muY.size());
BI_ASSERT(X.size1() == Y.size1());
BI_ASSERT(X.size1() == w.size());
BI_ASSERT(Y.size1() == w.size());
BI_ASSERT(SigmaXY.size1() == muX.size() && SigmaXY.size2() == muY.size());
typedef typename V1::value_type T;
typename sim_temp_matrix<M3>::type Z(X.size1(), X.size2());
T Wt = sum_reduce(w);
T Wt2 = std::pow(Wt, 2);
T W2t = sumsq_reduce(w);
gdmm(1.0, w, X, 0.0, Z);
gemm(1.0/Wt, Z, Y, 0.0, SigmaXY, 'T', 'N');
ger(-1.0, muX, muY, SigmaXY);
matrix_scal(1.0/(1.0 - W2t/Wt2), SigmaXY);
}
static constexpr auto equal_impl(M1 m1, M2 m2) {
return m1.nrows() == m2.nrows() &&
m1.ncolumns() == m2.ncolumns() &&
all_of(zip_with(_==_, m1.rows_, m2.rows_));
}
