TEST(AgradFwdMultiplyLog,Fvar) {
using stan::agrad::fvar;
using std::isnan;
using std::log;
using stan::math::multiply_log;
fvar<double> x(0.5,1.0);
fvar<double> y(1.2,2.0);
fvar<double> z(-0.4,3.0);
double w = 0.0;
double v = 1.3;
fvar<double> a = multiply_log(x, y);
EXPECT_FLOAT_EQ(multiply_log(0.5, 1.2), a.val_);
EXPECT_FLOAT_EQ(1.0 * log(1.2) + 0.5 * 2.0 / 1.2, a.d_);
fvar<double> b = multiply_log(x,z);
isnan(b.val_);
isnan(b.d_);
fvar<double> c = multiply_log(x, v);
EXPECT_FLOAT_EQ(multiply_log(0.5, 1.3), c.val_);
EXPECT_FLOAT_EQ(log(1.3), c.d_);
fvar<double> d = multiply_log(v, x);
EXPECT_FLOAT_EQ(multiply_log(1.3, 0.5), d.val_);
EXPECT_FLOAT_EQ(1.3 * 1.0 / 0.5, d.d_);
fvar<double> e = multiply_log(x, w);
isnan(e.val_);
isnan(e.d_);
}
TEST(AgradFwdHypot,Fvar) {
using stan::agrad::fvar;
using boost::math::hypot;
using std::isnan;
fvar<double> x(0.5,1.0);
fvar<double> y(2.3,2.0);
fvar<double> a = hypot(x, y);
EXPECT_FLOAT_EQ(hypot(0.5, 2.3), a.val_);
EXPECT_FLOAT_EQ((0.5 * 1.0 + 2.3 * 2.0) / hypot(0.5, 2.3), a.d_);
fvar<double> z(0.0,1.0);
fvar<double> w(-2.3,2.0);
fvar<double> b = hypot(x, z);
EXPECT_FLOAT_EQ(0.5, b.val_);
EXPECT_FLOAT_EQ(1.0, b.d_);
fvar<double> c = hypot(x, w);
isnan(c.val_);
isnan(c.d_);
fvar<double> d = hypot(z, x);
EXPECT_FLOAT_EQ(0.5, d.val_);
EXPECT_FLOAT_EQ(1.0, d.d_);
}
TEST(AgradFwdLog,Fvar) {
using stan::agrad::fvar;
using std::log;
using std::isnan;
fvar<double> x(0.5,1.0);
fvar<double> a = log(x);
EXPECT_FLOAT_EQ(log(0.5), a.val_);
EXPECT_FLOAT_EQ(1 / 0.5, a.d_);
fvar<double> b = 2 * log(x) + 4;
EXPECT_FLOAT_EQ(2 * log(0.5) + 4, b.val_);
EXPECT_FLOAT_EQ(2 / 0.5, b.d_);
fvar<double> c = -log(x) + 5;
EXPECT_FLOAT_EQ(-log(0.5) + 5, c.val_);
EXPECT_FLOAT_EQ(-1 / 0.5, c.d_);
fvar<double> d = -3 * log(x) + 5 * x;
EXPECT_FLOAT_EQ(-3 * log(0.5) + 5 * 0.5, d.val_);
EXPECT_FLOAT_EQ(-3 / 0.5 + 5, d.d_);
fvar<double> y(-0.5,1.0);
fvar<double> e = log(y);
isnan(e.val_);
isnan(e.d_);
fvar<double> z(0.0,1.0);
fvar<double> f = log(z);
isnan(f.val_);
isnan(f.d_);
}
TEST(AgradFvar, acosh) {
using stan::agrad::fvar;
using boost::math::acosh;
using std::sqrt;
using std::isnan;
fvar<double> x(1.5);
x.d_ = 1.0;
fvar<double> a = acosh(x);
EXPECT_FLOAT_EQ(acosh(1.5), a.val_);
EXPECT_FLOAT_EQ(1 / sqrt(-1 + (1.5) * (1.5)), a.d_);
fvar<double> y(-1.2);
y.d_ = 1.0;
fvar<double> b = acosh(y);
isnan(b.val_);
isnan(b.d_);
fvar<double> z(0.5);
z.d_ = 1.0;
fvar<double> c = acosh(z);
isnan(c.val_);
isnan(c.d_);
}
TEST(AgradFvar, pow) {
using stan::agrad::fvar;
using std::pow;
using std::log;
using std::isnan;
fvar<double> x(0.5);
x.d_ = 1.0;
double y = 5.0;
fvar<double> a = pow(x, y);
EXPECT_FLOAT_EQ(pow(0.5, 5.0), a.val_);
EXPECT_FLOAT_EQ(5.0 * pow(0.5, 5.0 - 1.0), a.d_);
fvar<double> b = pow(y, x);
EXPECT_FLOAT_EQ(pow(5.0, 0.5), b.val_);
EXPECT_FLOAT_EQ(log(5.0) * pow(5.0, 0.5), b.d_);
fvar<double> z(1.2);
z.d_ = 2.0;
fvar<double> c = pow(x, z);
EXPECT_FLOAT_EQ(pow(0.5, 1.2), c.val_);
EXPECT_FLOAT_EQ((2.0 * log(0.5) + 1.2 * 1.0 / 0.5) * pow(0.5, 1.2), c.d_);
fvar<double> w(-0.4);
w.d_ = 1.0;
fvar<double> d = pow(w, x);
isnan(d.val_);
isnan(d.d_);
}
bool qrReader::handlePossibleCenter(int stateCount[], int i, int j) {
int stateCountTotal = stateCount[0] + stateCount[1] + stateCount[2] + stateCount[3] + stateCount[4];
float centerJ = centerFromEnd(stateCount, j);
float centerI = crossCheckVertical(i, (int)centerJ, stateCount[2], stateCountTotal);
if(!isnan(centerI)) {
// Cross check against the horizontal
centerJ = crossCheckHorizontal((int)centerJ, (int)centerI, stateCount[2], stateCountTotal);
// Do we have a center?
if(!isnan(centerJ)) {
float estimatedModuleSize = (float)stateCountTotal/7.0f;
bool found = false;
for(unsigned int index=0;index<this->possibleCenters.size();index++) {
FinderPattern *center = this->possibleCenters[index];
if(center->aboutEquals(estimatedModuleSize, centerI, centerJ)) {
this->possibleCenters[index] = center->combineEstimate(centerI, centerJ, estimatedModuleSize);
found = true;
break;
}
}
if(!found) {
FinderPattern *newCenter = new FinderPattern(centerJ, centerI, estimatedModuleSize);
printf("Created new center: (%f, %f)\n", newCenter->getX(), newCenter->getY());
possibleCenters.push_back(newCenter);
}
return true;
}
}
printf("Returning false\n");
return false;
}
TEST(AgradFwdLog10,Fvar) {
using stan::math::fvar;
using std::log;
using std::isnan;
using std::log10;
fvar<double> x(0.5,1.0);
fvar<double> a = log10(x);
EXPECT_FLOAT_EQ(log10(0.5), a.val_);
EXPECT_FLOAT_EQ(1 / (0.5 * log(10)), a.d_);
fvar<double> b = 2 * log10(x) + 4;
EXPECT_FLOAT_EQ(2 * log10(0.5) + 4, b.val_);
EXPECT_FLOAT_EQ(2 / (0.5 * log(10)), b.d_);
fvar<double> c = -log10(x) + 5;
EXPECT_FLOAT_EQ(-log10(0.5) + 5, c.val_);
EXPECT_FLOAT_EQ(-1 / (0.5 * log(10)), c.d_);
fvar<double> d = -3 * log10(x) + 5 * x;
EXPECT_FLOAT_EQ(-3 * log10(0.5) + 5 * 0.5, d.val_);
EXPECT_FLOAT_EQ(-3 / (0.5 * log(10)) + 5, d.d_);
fvar<double> y(-0.5,1.0);
fvar<double> e = log10(y);
isnan(e.val_);
isnan(e.d_);
fvar<double> z(0.0,1.0);
fvar<double> f = log10(z);
isnan(f.val_);
isnan(f.d_);
}
TEST(AgradFwdOperatorDivision, Fvar) {
using stan::agrad::fvar;
using std::isnan;
fvar<double> x1(0.5,1.0);
fvar<double> x2(0.4,2.0);
fvar<double> a = x1 / x2;
EXPECT_FLOAT_EQ(0.5 / 0.4, a.val_);
EXPECT_FLOAT_EQ((1.0 * 0.4 - 2.0 * 0.5) / (0.4 * 0.4), a.d_);
fvar<double> b = -x1 / x2;
EXPECT_FLOAT_EQ(-0.5 / 0.4, b.val_);
EXPECT_FLOAT_EQ((-1 * 0.4 + 2.0 * 0.5) / (0.4 * 0.4), b.d_);
fvar<double> c = -3 * x1 / x2;
EXPECT_FLOAT_EQ(-3 * 0.5 / 0.4, c.val_);
EXPECT_FLOAT_EQ(3 * (-1 * 0.4 + 2.0 * 0.5) / (0.4 * 0.4), c.d_);
fvar<double> x3(0.5,1.0);
double x4 = 2.0;
fvar<double> e = x4 / x3;
EXPECT_FLOAT_EQ(2 / 0.5, e.val_);
EXPECT_FLOAT_EQ(-2 * 1.0 / (0.5 * 0.5), e.d_);
fvar<double> f = x3 / -2;
EXPECT_FLOAT_EQ(0.5 / -2, f.val_);
EXPECT_FLOAT_EQ(1.0 / -2, f.d_);
fvar<double> x5(0.0,1.0);
fvar<double> g = x3/x5;
isnan(g.val_);
isnan(g.d_);
}
TEST(AgradFwdCbrt,Fvar) {
using stan::agrad::fvar;
using boost::math::cbrt;
using std::isnan;
fvar<double> x(0.5,1.0);
fvar<double> a = cbrt(x);
EXPECT_FLOAT_EQ(cbrt(0.5), a.val_);
EXPECT_FLOAT_EQ(1 / (3 * pow(0.5, 2.0 / 3.0)), a.d_);
fvar<double> b = 3 * cbrt(x) + x;
EXPECT_FLOAT_EQ(3 * cbrt(0.5) + 0.5, b.val_);
EXPECT_FLOAT_EQ(3 / (3 * pow(0.5, 2.0 / 3.0)) + 1, b.d_);
fvar<double> c = -cbrt(x) + 5;
EXPECT_FLOAT_EQ(-cbrt(0.5) + 5, c.val_);
EXPECT_FLOAT_EQ(-1 / (3 * pow(0.5, 2.0 / 3.0)), c.d_);
fvar<double> d = -3 * cbrt(x) + 5 * x;
EXPECT_FLOAT_EQ(-3 * cbrt(0.5) + 5 * 0.5, d.val_);
EXPECT_FLOAT_EQ(-3 / (3 * pow(0.5, 2.0 / 3.0)) + 5, d.d_);
fvar<double> e = -3 * cbrt(-x) + 5 * x;
EXPECT_FLOAT_EQ(-3 * cbrt(-0.5) + 5 * 0.5, e.val_);
EXPECT_FLOAT_EQ(3 / (3 * cbrt(-0.5) * cbrt(-0.5)) + 5, e.d_);
fvar<double> y(0.0,1.0);
fvar<double> f = cbrt(y);
EXPECT_FLOAT_EQ(cbrt(0.0), f.val_);
isnan(f.d_);
}
int luaV_tostring (lua_State *L, StkId obj) {
if (!ttisnumber(obj))
return 0;
else {
char s[LUAI_MAXNUMBER2STR];
lua_Number n = nvalue(obj);
// SPRING -- synced safety change
// -- need a custom number formatter?
if (isfinite(n)) {
lua_number2str(s, n);
}
else {
if (isnan(n)) {
strcpy(s, "nan");
}
else {
const int inf_type = isinf(n);
if (inf_type == 1) {
strcpy(s, "+inf");
} else if (inf_type == -1) {
strcpy(s, "-inf");
} else {
strcpy(s, "weird_number");
}
}
}
setsvalue2s(L, obj, luaS_new(L, s));
return 1;
}
}
TEST(AgradFwdFmin,Fvar) {
using stan::agrad::fvar;
using stan::agrad::fmin;
using std::isnan;
fvar<double> x(2.0,1.0);
fvar<double> y(-3.0,2.0);
fvar<double> a = fmin(x, y);
EXPECT_FLOAT_EQ(-3.0, a.val_);
EXPECT_FLOAT_EQ(2.0, a.d_);
fvar<double> b = fmin(2 * x, y);
EXPECT_FLOAT_EQ(-3.0, b.val_);
EXPECT_FLOAT_EQ(2.0, b.d_);
fvar<double> c = fmin(y, x);
EXPECT_FLOAT_EQ(-3.0, c.val_);
EXPECT_FLOAT_EQ(2.0, c.d_);
fvar<double> d = fmin(x, x);
EXPECT_FLOAT_EQ(2.0, d.val_);
isnan(d.d_);
double z = 1.0;
fvar<double> e = fmin(x, z);
EXPECT_FLOAT_EQ(1.0, e.val_);
EXPECT_FLOAT_EQ(0.0, e.d_);
fvar<double> f = fmin(z, x);
EXPECT_FLOAT_EQ(1.0, f.val_);
EXPECT_FLOAT_EQ(0.0, f.d_);
}
TEST(AgradFvar, fmax) {
using stan::agrad::fvar;
using std::isnan;
fvar<double> x(2.0);
fvar<double> y(-3.0);
x.d_ = 1.0;
y.d_ = 2.0;
fvar<double> a = fmax(x, y);
EXPECT_FLOAT_EQ(2.0, a.val_);
EXPECT_FLOAT_EQ(1.0, a.d_);
fvar<double> b = fmax(2 * x, y);
EXPECT_FLOAT_EQ(4.0, b.val_);
EXPECT_FLOAT_EQ(2 * 1.0, b.d_);
fvar<double> c = fmax(y, x);
EXPECT_FLOAT_EQ(2.0, c.val_);
EXPECT_FLOAT_EQ(1.0, c.d_);
fvar<double> d = fmax(x, x);
EXPECT_FLOAT_EQ(2.0, d.val_);
isnan(d.d_);
double z = 1.0;
fvar<double> e = fmax(x, z);
EXPECT_FLOAT_EQ(2.0, e.val_);
EXPECT_FLOAT_EQ(1.0, e.d_);
fvar<double> f = fmax(z, x);
EXPECT_FLOAT_EQ(2.0, f.val_);
EXPECT_FLOAT_EQ(1.0, f.d_);
}
TEST(AgradFwdAcos,Fvar) {
using stan::math::fvar;
using std::acos;
using std::sqrt;
using std::isnan;
using stan::math::NEGATIVE_INFTY;
fvar<double> x(0.5,1.0);
fvar<double> a = acos(x);
EXPECT_FLOAT_EQ(acos(0.5), a.val_);
EXPECT_FLOAT_EQ(1 / -sqrt(1 - 0.5 * 0.5), a.d_);
fvar<double> b = 2 * acos(x) + 4;
EXPECT_FLOAT_EQ(2 * acos(0.5) + 4, b.val_);
EXPECT_FLOAT_EQ(2 / -sqrt(1 - 0.5 * 0.5), b.d_);
fvar<double> c = -acos(x) + 5;
EXPECT_FLOAT_EQ(-acos(0.5) + 5, c.val_);
EXPECT_FLOAT_EQ(-1 / -sqrt(1 - 0.5 * 0.5), c.d_);
fvar<double> d = -3 * acos(x) + 5 * x;
EXPECT_FLOAT_EQ(-3 * acos(0.5) + 5 * 0.5, d.val_);
EXPECT_FLOAT_EQ(-3 / -sqrt(1 - 0.5 * 0.5) + 5, d.d_);
fvar<double> y(3.4);
y.d_ = 1.0;
fvar<double> e = acos(y);
isnan(e.val_);
isnan(e.d_);
fvar<double> z(1.0);
z.d_ = 1.0;
fvar<double> f = acos(z);
EXPECT_FLOAT_EQ(acos(1.0), f.val_);
EXPECT_FLOAT_EQ(NEGATIVE_INFTY, f.d_);
fvar<double> z2(1.0+stan::math::EPSILON,1.0);
fvar<double> f2 = acos(z2);
EXPECT_TRUE(boost::math::isnan(f2.val_));
EXPECT_TRUE(boost::math::isnan(f2.d_));
fvar<double> z3(-1.0-stan::math::EPSILON,1.0);
fvar<double> f3 = acos(z3);
EXPECT_TRUE(boost::math::isnan(f3.val_));
EXPECT_TRUE(boost::math::isnan(f3.d_));
}
/* solve a multi contact problem by using a global successive overrelaxation method
* with a local nonlinear solver
*/
prox_result reference_sequential_g_sor_prox::solve_multi_contact_problem_sor() {
bool converged = false;
bool diverged = false;
unsigned int iteration = 0;
while(!converged && !diverged && iteration < m_max_global_iterations) {
converged = true;
for(index_t i = 0; i < m_contacts.size(); ++i) {
contact & ci = m_contacts[i];
vec3 rhs = ci.c;
index_t cbegin = m_gij_rows[i];
index_t cend = m_gij_rows[i + 1];
//step 0. get contributions from all the other contacts (gij off-diagonal terms)
for(index_t j = cbegin; j < cend; ++j) {
index_t cj = m_gij_columns[j];
rhs = rhs + m_gij_blocks[j] * m_percussions[cj];
}
vec3 pold = m_percussions[i];
//step 1. solve a single contact under the assumption, that all others are known
vec3 pnew = solve_one_contact_problem_alart_curnier(ci, pold, rhs, m_tol_rel, m_tol_abs);
using std::abs;
//step 2. check for global convergence
converged &=
abs(pnew[0] - pold[0]) <= m_tol_rel * abs(pnew[0]) + m_tol_abs
&& abs(pnew[1] - pold[1]) <= m_tol_rel * abs(pnew[1]) + m_tol_abs
&& abs(pnew[2] - pold[2]) <= m_tol_rel * abs(pnew[2]) + m_tol_abs;
//and check whether a force became infinite or NaN
using std::isinf; using std::isnan;
diverged
|= isinf(pnew[0]) || isnan(pnew[0])
|| isinf(pnew[1]) || isnan(pnew[1])
|| isinf(pnew[2]) || isnan(pnew[2]);
m_percussions[i] = pnew;
}
++iteration;
}
std::cout << "done\n # iterations = " << iteration << std::endl;
return
converged ? CONVERGED
: (diverged ? DIVERGED
: (!(iteration < m_max_global_iterations) ? ITERATION_LIMIT_REACHED
/*: (time_limit_reached ? TIME_LIMIT_REACHED */: OOPS/*)*/));
}
TEST(AgradFwdFdim,FvarVar_FvarVar_2ndDeriv) {
using stan::math::fvar;
using stan::math::var;
using stan::math::fdim;
using std::floor;
using std::isnan;
fvar<var> x(2.5,1.3);
fvar<var> z(1.5,1.0);
fvar<var> a = fdim(x,z);
AVEC y = createAVEC(x.val_,z.val_);
VEC g;
a.d_.grad(y,g);
isnan(g[0]);
isnan(g[1]);
}
std::pair<bool, bool> multicolor_parallel_g_sor_prox::work_function(
sub_problem const & sub,
index_t & l_i,
index_t & g_i,
index_t l_end,
std::vector<vec3> & percussions,
real tol_rel, real tol_abs,
index_t max_local_iterations
) {
bool diverged = false;
bool converged = true;
for(; l_i < l_end; ++l_i, ++g_i) {
contact const & ci = sub.contacts[l_i];
vec3 rhs = ci.c;
index_t cbegin = sub.gij_rows[l_i];
index_t cend = sub.gij_rows[l_i + 1];
//step 0. get contributions from all the other contacts (gij off-diagonal terms)
for(index_t j = cbegin; j < cend; ++j) {
index_t g_j = sub.gij_columns[j];
rhs = rhs + sub.gij_blocks[j] * percussions[g_j];
}
vec3 pold = percussions[g_i];
//step 1. solve a single contact under the assumption, that all others are known
vec3 pnew = solve_one_contact_problem_alart_curnier(ci, pold, rhs, tol_rel, tol_abs, max_local_iterations);
using std::abs;
//step 2. check for global convergence
converged &=
abs(pnew[0] - pold[0]) <= tol_rel * abs(pnew[0]) + tol_abs
&& abs(pnew[1] - pold[1]) <= tol_rel * abs(pnew[1]) + tol_abs
&& abs(pnew[2] - pold[2]) <= tol_rel * abs(pnew[2]) + tol_abs;
//and check whether a force became infinite or NaN
using std::isinf; using std::isnan;
diverged
|= isinf(pnew[0]) || isnan(pnew[0])
|| isinf(pnew[1]) || isnan(pnew[1])
|| isinf(pnew[2]) || isnan(pnew[2]);
percussions[g_i] = pnew;
}
return std::make_pair(converged, diverged);
}
TEST(AgradFwdFdim,Double_FvarVar_1stDeriv) {
using stan::math::fvar;
using stan::math::var;
using stan::math::fdim;
using std::floor;
using std::isnan;
double x(2.5);
fvar<var> z(1.5,1.0);
fvar<var> a = fdim(x,z);
EXPECT_FLOAT_EQ(fdim(2.5,1.5), a.val_.val());
isnan(a.d_.val());
AVEC y = createAVEC(z.val_);
VEC g;
a.val_.grad(y,g);
isnan(g[0]);
}
// function that standarize printing NaN and Inf values on
// Windows (where they are in 1.#INF, 1.#NAN format) and all
// others platform
inline void
safe_double_print (double val)
{
if (isnan (val))
std::cout << "nan";
else if (isinf (val))
std::cout << "inf";
else
std::cout << val;
std::cout << '\n';
}
TEST(AgradFwdLog1p,Fvar) {
using stan::agrad::fvar;
using stan::math::log1p;
using std::isnan;
fvar<double> x(0.5,1.0);
fvar<double> y(-1.0,2.0);
fvar<double> z(-2.0,3.0);
fvar<double> a = log1p(x);
EXPECT_FLOAT_EQ(log1p(0.5), a.val_);
EXPECT_FLOAT_EQ(1 / (1 + 0.5), a.d_);
fvar<double> b = log1p(y);
isnan(b.val_);
isnan(b.d_);
fvar<double> c = log1p(z);
isnan(c.val_);
isnan(c.d_);
}
void DPmatrix::compute_Pr_sum_all_paths()
{
const int I = size1()-1;
const int J = size2()-1;
double total = 0.0;
for(int state1=0;state1<nstates();state1++)
total += (*this)(I,J,state1)*GQ(state1,endstate());
Pr_total = pow(efloat_t(2.0),scale(I,J)) * total;
assert(not isnan(log(Pr_total)) and isfinite(log(Pr_total)));
}
void Params::param_value_changed( iterator itr , double value , ProbeType pt )
{
if( itr.itr == params.end() ) {
sz_log(1, "Value changed of undefined param %s", itr->c_str() );
return;
}
using std::isnan;
auto pvalue = itr.itr->second->get_value( pt );
if( pt.get_type() == ProbeType::Type::LIVE
&& (value == pvalue || (isnan(value) && isnan(pvalue))) )
/**
* With LIVE probes if values are equal even
* if both are NaNs do nothing. For other probe
* types always send update.
*/
return;
itr.itr->second->set_value( value , pt );
emit_value_changed( itr.itr->second , value , pt );
}
TEST(AgradFvar, asin) {
using stan::agrad::fvar;
using std::asin;
using std::isnan;
using std::sqrt;
using stan::math::INFTY;
fvar<double> x(0.5);
x.d_ = 1.0; // derivatives w.r.t. x
fvar<double> a = asin(x);
EXPECT_FLOAT_EQ(asin(0.5), a.val_);
EXPECT_FLOAT_EQ(1 / sqrt(1 - 0.5 * 0.5), a.d_);
fvar<double> b = 2 * asin(x) + 4;
EXPECT_FLOAT_EQ(2 * asin(0.5) + 4, b.val_);
EXPECT_FLOAT_EQ(2 / sqrt(1 - 0.5 * 0.5), b.d_);
fvar<double> c = -asin(x) + 5;
EXPECT_FLOAT_EQ(-asin(0.5) + 5, c.val_);
EXPECT_FLOAT_EQ(-1 / sqrt(1 - 0.5 * 0.5), c.d_);
fvar<double> d = -3 * asin(x) + 5 * x;
EXPECT_FLOAT_EQ(-3 * asin(0.5) + 5 * 0.5, d.val_);
EXPECT_FLOAT_EQ(-3 / sqrt(1 - 0.5 * 0.5) + 5, d.d_);
fvar<double> y(3.4);
y.d_ = 1.0;
fvar<double> e = asin(y);
isnan(e.val_);
isnan(e.d_);
fvar<double> z(1.0);
z.d_ = 1.0;
fvar<double> f = asin(z);
EXPECT_FLOAT_EQ(asin(1.0), f.val_);
EXPECT_FLOAT_EQ(INFTY, f.d_);
}
void DPmatrixConstrained::compute_Pr_sum_all_paths()
{
const int I = size1()-1;
const int J = size2()-1;
double total = 0.0;
for(int s1=0;s1<states(J).size();s1++) {
int S1 = states(J)[s1];
total += (*this)(I,J,S1)*GQ(S1,endstate());
}
Pr_total = pow(efloat_t(2.0),scale(I,J)) * total;
assert(not isnan(log(Pr_total)) and isfinite(log(Pr_total)));
}
TEST_F(AgradFwdLogit,Fvar) {
using stan::agrad::fvar;
using stan::math::logit;
using std::isnan;
fvar<double> x(0.5,1.0);
fvar<double> a = logit(x);
EXPECT_FLOAT_EQ(logit(0.5), a.val_);
EXPECT_FLOAT_EQ(1 / (0.5 - 0.5 * 0.5), a.d_);
fvar<double> y(-1.2,1.0);
fvar<double> b = logit(y);
isnan(b.val_);
isnan(b.d_);
fvar<double> z(1.5,1.0);
fvar<double> c = logit(z);
isnan(c.val_);
isnan(c.d_);
}
TEST(AgradFwdSqrt, Fvar) {
using stan::agrad::fvar;
using std::sqrt;
using std::isnan;
fvar<double> x(0.5,1.0);
fvar<double> a = sqrt(x);
EXPECT_FLOAT_EQ(sqrt(0.5), a.val_);
EXPECT_FLOAT_EQ(1 / (2 * sqrt(0.5)), a.d_);
fvar<double> b = 3 * sqrt(x) + x;
EXPECT_FLOAT_EQ(3 * sqrt(0.5) + 0.5, b.val_);
EXPECT_FLOAT_EQ(3 / (2 * sqrt(0.5)) + 1, b.d_);
fvar<double> c = -sqrt(x) + 5;
EXPECT_FLOAT_EQ(-sqrt(0.5) + 5, c.val_);
EXPECT_FLOAT_EQ(-1 / (2 * sqrt(0.5)), c.d_);
fvar<double> d = -3 * sqrt(x) + 5 * x;
EXPECT_FLOAT_EQ(-3 * sqrt(0.5) + 5 * 0.5, d.val_);
EXPECT_FLOAT_EQ(-3 / (2 * sqrt(0.5)) + 5, d.d_);
fvar<double> y(-0.5,1.0);
fvar<double> e = sqrt(-y);
EXPECT_FLOAT_EQ(sqrt(0.5), e.val_);
EXPECT_FLOAT_EQ(-1 / (2 * sqrt(0.5)), e.d_);
fvar<double> f = sqrt(y);
isnan(f.val_);
isnan(f.d_);
fvar<double> z(0.0,1.0);
fvar<double> g = sqrt(z);
EXPECT_FLOAT_EQ(sqrt(0.0), g.val_);
isnan(g.d_);
}
String::String(const double d) {
if (isinf(d)) {
if (copysign(1.0, d) == -1.0) {
fromAscii("-Infinity");
} else {
fromAscii("Infinity");
}
} else if (isnan(d)) {
fromAscii("NaN");
} else {
char * buf = static_cast<char*>(GC_MALLOC_ATOMIC(20));
sprintf(buf,"%.16g",d);
fromAscii(buf);
}
}
String::String(const float f) {
if (isinf(f)) {
if (copysign(1.0, f) == -1.0) {
fromAscii("-Infinity");
} else {
fromAscii("Infinity");
}
} else if (isnan(f)) {
fromAscii("NaN");
} else {
char * buf = static_cast<char*>(GC_MALLOC_ATOMIC(20));
sprintf(buf,"%.7g",f);
fromAscii(buf);
}
}
void
KneserNeySmoothing::_Estimate(ProbVector &probs, ProbVector &bows) {
const IndexVector &hists(_pLM->hists(_order));
const IndexVector &backoffs(_pLM->backoffs(_order));
const ProbVector & boProbs(_pLM->probs(_order - 1));
// Compute discounts.
ProbVector discounts(probs.length(), 0.0); // Reuse probs vector for discounts.
discounts = _discParams[min(_effCounts, _discOrder)];
// Compute backoff weights.
bows.set(0);
BinWeight(hists, discounts, bows);
// if (_order == 4) std::cerr << bows[hists[8]] << std::endl;
// bows = CondExpr(_invHistCounts == 0, 1, bows * _invHistCounts);
bows = bows * _invHistCounts;
assert(allTrue(isfinite(_invHistCounts)));
assert(allTrue(isfinite(bows)));
// Compute interpolated probabilities.
if (_order == 1 && !_pLM->vocab().IsFixedVocab())
probs = CondExpr(!_effCounts, 0,
(_effCounts - discounts) * _invHistCounts[hists]
+ boProbs[backoffs] * bows[hists]);
else
probs = CondExpr(!_effCounts, 0,
(_effCounts - discounts) * _invHistCounts[hists])
+ boProbs[backoffs] * bows[hists]
;
// if (_order == 4) std::cerr << probs[8]
// << "\t" << _effCounts[8]
// << "\t" << discounts[8]
// << "\t" << (1/_invHistCounts[hists[8]])
// << "\t" << backoffs[8]
// << "\t" << boProbs[backoffs[8]]
// << "\t" << bows[hists[8]]
// << std::endl;
// if (_order == 4) std::cerr << probs[9]
// << "\t" << _effCounts[9]
// << "\t" << discounts[9]
// << "\t" << (1/_invHistCounts[hists[9]])
// << "\t" << backoffs[9]
// << "\t" << boProbs[backoffs[9]]
// << "\t" << bows[hists[9]]
// << std::endl;
// if (_order == 4) std::cerr << _discParams << std::endl;
assert(!anyTrue(isnan(probs)));
}
TEST(AgradFwdFdim,Double_FvarVar_2nd_Deriv) {
using stan::math::fvar;
using stan::math::var;
using stan::math::fdim;
using std::floor;
using std::isnan;
double x(2.5);
fvar<var> z(1.5,1.0);
fvar<var> a = fdim(x,z);
AVEC y = createAVEC(z.val_);
VEC g;
a.d_.grad(y,g);
isnan(g[0]);
}
// and do some processing
void multiThreadProcessImages(OfxRectI procWindow)
{
assert(nComponents == 1 || nComponents == 3 || nComponents == 4);
assert(_dstImg);
float tmpPix[nComponents];
for (int y = procWindow.y1; y < procWindow.y2; y++) {
if (_effect.abort()) {
break;
}
PIX *dstPix = (PIX *) _dstImg->getPixelAddress(procWindow.x1, y);
for (int x = procWindow.x1; x < procWindow.x2; x++) {
const PIX *srcPix = (const PIX *) (_srcImg ? _srcImg->getPixelAddress(x, y) : 0);
if (nComponents == 1 || nComponents == 3) {
// RGB and Alpha: don't premult/unpremult, just apply curves
// normalize/denormalize properly
for (int c = 0; c < nComponents; ++c) {
tmpPix[c] = (float)interpolate(c, srcPix ? (srcPix[c] / (float)maxValue) : 0.f) * maxValue;
assert((!srcPix || (!isnan(srcPix[c]) && !isnan(srcPix[c]))) &&
!isnan(tmpPix[c]) && !isnan(tmpPix[c]));
}
// ofxsMaskMix expects denormalized input
ofxsMaskMixPix<PIX, nComponents, maxValue, true>(tmpPix, x, y, srcPix, _doMasking, _maskImg, (float)_mix, _maskInvert, dstPix);
} else {
//assert(nComponents == 4);
float unpPix[nComponents];
ofxsUnPremult<PIX, nComponents, maxValue>(srcPix, unpPix, _premult, _premultChannel);
// ofxsUnPremult outputs normalized data
for (int c = 0; c < nComponents; ++c) {
tmpPix[c] = interpolate(c, unpPix[c]);
assert(!isnan(unpPix[c]) && !isnan(unpPix[c]) &&
!isnan(tmpPix[c]) && !isnan(tmpPix[c]));
}
// ofxsPremultMaskMixPix expects normalized input
ofxsPremultMaskMixPix<PIX, nComponents, maxValue, true>(tmpPix, _premult, _premultChannel, x, y, srcPix, _doMasking, _maskImg, (float)_mix, _maskInvert, dstPix);
}
// increment the dst pixel
dstPix += nComponents;
}
}
}
