/**
* Aggregate 0 observations into adjacent smaller bin and compress +group tail.
**/
void logistic_normal::aggregate_and_compress_arrays()
{
m_nB2.allocate(m_y1,m_y2);
int i;
for( i = m_y1; i <= m_y2; i++ )
{
int n = m_b1-1; // index for maximum column each year for ragged objects
for(int j = m_b1; j <= m_b2; j++ )
{
double op = m_O(i,j)/sum(m_O(i));
if( op > m_dMinimumProportion )
{
n ++;
}
}
m_nB2(i) = n;
}
m_nAgeIndex.allocate(m_y1,m_y2,m_b1,m_nB2);
m_Op.allocate(m_y1,m_y2,m_b1,m_nB2);
m_Ep.allocate(m_y1,m_y2,m_b1,m_nB2);
m_Op.initialize();
m_Ep.initialize();
for( i = m_y1; i <= m_y2; i++ )
{
dvector oo = m_O(i) / sum(m_O(i));
dvar_vector ee = m_E(i) / sum(m_E(i));
int k=m_b1;
for(int j = m_b1; j <= m_b2; j++ )
{
if( oo(j) <= m_dMinimumProportion ) // Check this < gives -Inf need to compress left tails as well.
{
m_Op(i)(k) += oo(j);
m_Ep(i)(k) += ee(j);
}
else
{
m_Op(i)(k) += oo(j);
m_Ep(i)(k) += ee(j);
if( k <=m_nB2(i) ) m_nAgeIndex(i,k) = k;
if( k < m_nB2(i) ) k++;
}
}
}
}
/**
* Add small constant (eps) and renormalize arrays
**/
void logistic_normal::add_constant(const double& eps)
{
int i;
m_Op.allocate(m_O);
m_Ep.allocate(m_E);
m_nB2.allocate(m_y1,m_y2);
m_nB2 = m_Op.colmax();
m_nAgeIndex.allocate(m_y1,m_y2,m_b1,m_nB2);
for( i = m_y1; i <= m_y2; i++ )
{
m_O(i) = m_O(i) + eps;
m_Op(i) = m_O(i) / sum(m_O(i));
m_E(i) = m_E(i) + eps;
m_Ep(i) = m_E(i) / sum(m_E(i));
m_nAgeIndex(i).fill_seqadd(m_b1,1);
}
}
void
lm_env_stepwise::init_matrix_with_snp(const snp_row &row, arma::uvec &missing, bool *valid)
{
arma::uvec counts = arma::zeros<arma::uvec>( 2 + 2*m_E.n_cols );
for(int i = 0; i < row.size( ); i++)
{
if( row[ i ] == 3 )
{
missing[ i ] = 1;
continue;
}
double s1 = row[ i ] == 1 ? 1.0 : 0.0;
double s2 = row[ i ] == 2 ? 1.0 : 0.0;
m_snp_matrix( i, 1 ) = s1;
m_snp_matrix( i, 2 ) = s2;
m_add_matrix( i, 1 ) = s1;
m_add_matrix( i, 2 ) = s2;
m_alt_matrix( i, 1 ) = s1;
m_alt_matrix( i, 2 ) = s2;
m_alt_matrix.row( i ).cols( 1 + 2 + m_E.n_cols, 1 + 2 + 2*m_E.n_cols - 1 ) = m_E.row( i ) * s1;
m_alt_matrix.row( i ).cols( 1 + 2 + 2*m_E.n_cols, 1+ 2 + 3*m_E.n_cols - 1 ) = m_E.row( i ) * s2;
counts[ 0 ] += s1;
counts[ 1 ] += s2;
for(int j = 0; j < m_E.n_cols; j++)
{
double e = ( std::abs( m_E( i, j ) ) > 0.0 ) ? 1.0 : 0.0;
counts[ 2 + j ] += e * s1;
counts[ 2 + m_E.n_cols + j ] += e * s2;
}
}
*valid = counts.min( ) >= 20;
}
void btMaterial::computeE()
{
const btScalar c = m_e/((1+m_nu)*(1-2*m_nu));
m_E.setZero();
m_E(0,0)=c*(1-m_nu), m_E(0,1)=c*m_nu, m_E(0,2)=c*m_nu, m_E(0,3)=0, m_E(0,4)=0, m_E(0,5)=0;
m_E(1,0)=c*m_nu, m_E(1,1)=c*(1-m_nu), m_E(1,2)=c*m_nu, m_E(1,3)=0, m_E(1,4)=0, m_E(1,5)=0;
m_E(2,0)=c*m_nu, m_E(2,1)=c*m_nu, m_E(2,2)=c*(1-m_nu), m_E(2,3)=0, m_E(2,4)=0, m_E(2,5)=0;
m_E(3,0)=0, m_E(3,1)=0, m_E(3,2)=0, m_E(3,3)=c*(0.5f-m_nu), m_E(3,4)=0, m_E(3,5)=0;
m_E(4,0)=0, m_E(4,1)=0, m_E(4,2)=0, m_E(4,3)=0, m_E(4,4)=c*(0.5f-m_nu), m_E(4,5)=0;
m_E(5,0)=0, m_E(5,1)=0, m_E(5,2)=0, m_E(5,3)=0, m_E(5,4)=0, m_E(5,5)=c*(0.5f-m_nu);
}
