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Diffstat (limited to 'thirdparty/squish/clusterfit.cpp')
| -rw-r--r-- | thirdparty/squish/clusterfit.cpp | 731 |
1 files changed, 365 insertions, 366 deletions
diff --git a/thirdparty/squish/clusterfit.cpp b/thirdparty/squish/clusterfit.cpp index afea84880c..1610ecb5d8 100644 --- a/thirdparty/squish/clusterfit.cpp +++ b/thirdparty/squish/clusterfit.cpp @@ -1,29 +1,29 @@ /* ----------------------------------------------------------------------------- - Copyright (c) 2006 Simon Brown si@sjbrown.co.uk - Copyright (c) 2007 Ignacio Castano icastano@nvidia.com - - Permission is hereby granted, free of charge, to any person obtaining - a copy of this software and associated documentation files (the - "Software"), to deal in the Software without restriction, including - without limitation the rights to use, copy, modify, merge, publish, - distribute, sublicense, and/or sell copies of the Software, and to - permit persons to whom the Software is furnished to do so, subject to - the following conditions: - - The above copyright notice and this permission notice shall be included - in all copies or substantial portions of the Software. - - THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS - OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF - MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. - IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY - CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, - TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE - SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. - + Copyright (c) 2006 Simon Brown si@sjbrown.co.uk + Copyright (c) 2007 Ignacio Castano icastano@nvidia.com + + Permission is hereby granted, free of charge, to any person obtaining + a copy of this software and associated documentation files (the + "Software"), to deal in the Software without restriction, including + without limitation the rights to use, copy, modify, merge, publish, + distribute, sublicense, and/or sell copies of the Software, and to + permit persons to whom the Software is furnished to do so, subject to + the following conditions: + + The above copyright notice and this permission notice shall be included + in all copies or substantial portions of the Software. + + THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS + OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF + MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. + IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY + CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, + TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE + SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. + -------------------------------------------------------------------------- */ - + #include "clusterfit.h" #include "colourset.h" #include "colourblock.h" @@ -31,363 +31,362 @@ namespace squish { -ClusterFit::ClusterFit( ColourSet const* colours, int flags ) +ClusterFit::ClusterFit( ColourSet const* colours, int flags, float* metric ) : ColourFit( colours, flags ) { - // set the iteration count - m_iterationCount = ( m_flags & kColourIterativeClusterFit ) ? kMaxIterations : 1; - - // initialise the best error - m_besterror = VEC4_CONST( FLT_MAX ); - - // initialise the metric - bool perceptual = ( ( m_flags & kColourMetricPerceptual ) != 0 ); - if( perceptual ) - m_metric = Vec4( 0.2126f, 0.7152f, 0.0722f, 0.0f ); - else - m_metric = VEC4_CONST( 1.0f ); - - // cache some values - int const count = m_colours->GetCount(); - Vec3 const* values = m_colours->GetPoints(); - - // get the covariance matrix - Sym3x3 covariance = ComputeWeightedCovariance( count, values, m_colours->GetWeights() ); - - // compute the principle component - m_principle = ComputePrincipleComponent( covariance ); + // set the iteration count + m_iterationCount = ( m_flags & kColourIterativeClusterFit ) ? kMaxIterations : 1; + + // initialise the metric (old perceptual = 0.2126f, 0.7152f, 0.0722f) + if( metric ) + m_metric = Vec4( metric[0], metric[1], metric[2], 1.0f ); + else + m_metric = VEC4_CONST( 1.0f ); + + // initialise the best error + m_besterror = VEC4_CONST( FLT_MAX ); + + // cache some values + int const count = m_colours->GetCount(); + Vec3 const* values = m_colours->GetPoints(); + + // get the covariance matrix + Sym3x3 covariance = ComputeWeightedCovariance( count, values, m_colours->GetWeights() ); + + // compute the principle component + m_principle = ComputePrincipleComponent( covariance ); } bool ClusterFit::ConstructOrdering( Vec3 const& axis, int iteration ) { - // cache some values - int const count = m_colours->GetCount(); - Vec3 const* values = m_colours->GetPoints(); - - // build the list of dot products - float dps[16]; - u8* order = ( u8* )m_order + 16*iteration; - for( int i = 0; i < count; ++i ) - { - dps[i] = Dot( values[i], axis ); - order[i] = ( u8 )i; - } - - // stable sort using them - for( int i = 0; i < count; ++i ) - { - for( int j = i; j > 0 && dps[j] < dps[j - 1]; --j ) - { - std::swap( dps[j], dps[j - 1] ); - std::swap( order[j], order[j - 1] ); - } - } - - // check this ordering is unique - for( int it = 0; it < iteration; ++it ) - { - u8 const* prev = ( u8* )m_order + 16*it; - bool same = true; - for( int i = 0; i < count; ++i ) - { - if( order[i] != prev[i] ) - { - same = false; - break; - } - } - if( same ) - return false; - } - - // copy the ordering and weight all the points - Vec3 const* unweighted = m_colours->GetPoints(); - float const* weights = m_colours->GetWeights(); - m_xsum_wsum = VEC4_CONST( 0.0f ); - for( int i = 0; i < count; ++i ) - { - int j = order[i]; - Vec4 p( unweighted[j].X(), unweighted[j].Y(), unweighted[j].Z(), 1.0f ); - Vec4 w( weights[j] ); - Vec4 x = p*w; - m_points_weights[i] = x; - m_xsum_wsum += x; - } - return true; + // cache some values + int const count = m_colours->GetCount(); + Vec3 const* values = m_colours->GetPoints(); + + // build the list of dot products + float dps[16]; + u8* order = ( u8* )m_order + 16*iteration; + for( int i = 0; i < count; ++i ) + { + dps[i] = Dot( values[i], axis ); + order[i] = ( u8 )i; + } + + // stable sort using them + for( int i = 0; i < count; ++i ) + { + for( int j = i; j > 0 && dps[j] < dps[j - 1]; --j ) + { + std::swap( dps[j], dps[j - 1] ); + std::swap( order[j], order[j - 1] ); + } + } + + // check this ordering is unique + for( int it = 0; it < iteration; ++it ) + { + u8 const* prev = ( u8* )m_order + 16*it; + bool same = true; + for( int i = 0; i < count; ++i ) + { + if( order[i] != prev[i] ) + { + same = false; + break; + } + } + if( same ) + return false; + } + + // copy the ordering and weight all the points + Vec3 const* unweighted = m_colours->GetPoints(); + float const* weights = m_colours->GetWeights(); + m_xsum_wsum = VEC4_CONST( 0.0f ); + for( int i = 0; i < count; ++i ) + { + int j = order[i]; + Vec4 p( unweighted[j].X(), unweighted[j].Y(), unweighted[j].Z(), 1.0f ); + Vec4 w( weights[j] ); + Vec4 x = p*w; + m_points_weights[i] = x; + m_xsum_wsum += x; + } + return true; } void ClusterFit::Compress3( void* block ) { - // declare variables - int const count = m_colours->GetCount(); - Vec4 const two = VEC4_CONST( 2.0 ); - Vec4 const one = VEC4_CONST( 1.0f ); - Vec4 const half_half2( 0.5f, 0.5f, 0.5f, 0.25f ); - Vec4 const zero = VEC4_CONST( 0.0f ); - Vec4 const half = VEC4_CONST( 0.5f ); - Vec4 const grid( 31.0f, 63.0f, 31.0f, 0.0f ); - Vec4 const gridrcp( 1.0f/31.0f, 1.0f/63.0f, 1.0f/31.0f, 0.0f ); - - // prepare an ordering using the principle axis - ConstructOrdering( m_principle, 0 ); - - // check all possible clusters and iterate on the total order - Vec4 beststart = VEC4_CONST( 0.0f ); - Vec4 bestend = VEC4_CONST( 0.0f ); - Vec4 besterror = m_besterror; - u8 bestindices[16]; - int bestiteration = 0; - int besti = 0, bestj = 0; - - // loop over iterations (we avoid the case that all points in first or last cluster) - for( int iterationIndex = 0;; ) - { - // first cluster [0,i) is at the start - Vec4 part0 = VEC4_CONST( 0.0f ); - for( int i = 0; i < count; ++i ) - { - // second cluster [i,j) is half along - Vec4 part1 = ( i == 0 ) ? m_points_weights[0] : VEC4_CONST( 0.0f ); - int jmin = ( i == 0 ) ? 1 : i; - for( int j = jmin;; ) - { - // last cluster [j,count) is at the end - Vec4 part2 = m_xsum_wsum - part1 - part0; - - // compute least squares terms directly - Vec4 alphax_sum = MultiplyAdd( part1, half_half2, part0 ); - Vec4 alpha2_sum = alphax_sum.SplatW(); - - Vec4 betax_sum = MultiplyAdd( part1, half_half2, part2 ); - Vec4 beta2_sum = betax_sum.SplatW(); - - Vec4 alphabeta_sum = ( part1*half_half2 ).SplatW(); - - // compute the least-squares optimal points - Vec4 factor = Reciprocal( NegativeMultiplySubtract( alphabeta_sum, alphabeta_sum, alpha2_sum*beta2_sum ) ); - Vec4 a = NegativeMultiplySubtract( betax_sum, alphabeta_sum, alphax_sum*beta2_sum )*factor; - Vec4 b = NegativeMultiplySubtract( alphax_sum, alphabeta_sum, betax_sum*alpha2_sum )*factor; - - // clamp to the grid - a = Min( one, Max( zero, a ) ); - b = Min( one, Max( zero, b ) ); - a = Truncate( MultiplyAdd( grid, a, half ) )*gridrcp; - b = Truncate( MultiplyAdd( grid, b, half ) )*gridrcp; - - // compute the error (we skip the constant xxsum) - Vec4 e1 = MultiplyAdd( a*a, alpha2_sum, b*b*beta2_sum ); - Vec4 e2 = NegativeMultiplySubtract( a, alphax_sum, a*b*alphabeta_sum ); - Vec4 e3 = NegativeMultiplySubtract( b, betax_sum, e2 ); - Vec4 e4 = MultiplyAdd( two, e3, e1 ); - - // apply the metric to the error term - Vec4 e5 = e4*m_metric; - Vec4 error = e5.SplatX() + e5.SplatY() + e5.SplatZ(); - - // keep the solution if it wins - if( CompareAnyLessThan( error, besterror ) ) - { - beststart = a; - bestend = b; - besti = i; - bestj = j; - besterror = error; - bestiteration = iterationIndex; - } - - // advance - if( j == count ) - break; - part1 += m_points_weights[j]; - ++j; - } - - // advance - part0 += m_points_weights[i]; - } - - // stop if we didn't improve in this iteration - if( bestiteration != iterationIndex ) - break; - - // advance if possible - ++iterationIndex; - if( iterationIndex == m_iterationCount ) - break; - - // stop if a new iteration is an ordering that has already been tried - Vec3 axis = ( bestend - beststart ).GetVec3(); - if( !ConstructOrdering( axis, iterationIndex ) ) - break; - } - - // save the block if necessary - if( CompareAnyLessThan( besterror, m_besterror ) ) - { - // remap the indices - u8 const* order = ( u8* )m_order + 16*bestiteration; - - u8 unordered[16]; - for( int m = 0; m < besti; ++m ) - unordered[order[m]] = 0; - for( int m = besti; m < bestj; ++m ) - unordered[order[m]] = 2; - for( int m = bestj; m < count; ++m ) - unordered[order[m]] = 1; - - m_colours->RemapIndices( unordered, bestindices ); - - // save the block - WriteColourBlock3( beststart.GetVec3(), bestend.GetVec3(), bestindices, block ); - - // save the error - m_besterror = besterror; - } + // declare variables + int const count = m_colours->GetCount(); + Vec4 const two = VEC4_CONST( 2.0 ); + Vec4 const one = VEC4_CONST( 1.0f ); + Vec4 const half_half2( 0.5f, 0.5f, 0.5f, 0.25f ); + Vec4 const zero = VEC4_CONST( 0.0f ); + Vec4 const half = VEC4_CONST( 0.5f ); + Vec4 const grid( 31.0f, 63.0f, 31.0f, 0.0f ); + Vec4 const gridrcp( 1.0f/31.0f, 1.0f/63.0f, 1.0f/31.0f, 0.0f ); + + // prepare an ordering using the principle axis + ConstructOrdering( m_principle, 0 ); + + // check all possible clusters and iterate on the total order + Vec4 beststart = VEC4_CONST( 0.0f ); + Vec4 bestend = VEC4_CONST( 0.0f ); + Vec4 besterror = m_besterror; + u8 bestindices[16]; + int bestiteration = 0; + int besti = 0, bestj = 0; + + // loop over iterations (we avoid the case that all points in first or last cluster) + for( int iterationIndex = 0;; ) + { + // first cluster [0,i) is at the start + Vec4 part0 = VEC4_CONST( 0.0f ); + for( int i = 0; i < count; ++i ) + { + // second cluster [i,j) is half along + Vec4 part1 = ( i == 0 ) ? m_points_weights[0] : VEC4_CONST( 0.0f ); + int jmin = ( i == 0 ) ? 1 : i; + for( int j = jmin;; ) + { + // last cluster [j,count) is at the end + Vec4 part2 = m_xsum_wsum - part1 - part0; + + // compute least squares terms directly + Vec4 alphax_sum = MultiplyAdd( part1, half_half2, part0 ); + Vec4 alpha2_sum = alphax_sum.SplatW(); + + Vec4 betax_sum = MultiplyAdd( part1, half_half2, part2 ); + Vec4 beta2_sum = betax_sum.SplatW(); + + Vec4 alphabeta_sum = ( part1*half_half2 ).SplatW(); + + // compute the least-squares optimal points + Vec4 factor = Reciprocal( NegativeMultiplySubtract( alphabeta_sum, alphabeta_sum, alpha2_sum*beta2_sum ) ); + Vec4 a = NegativeMultiplySubtract( betax_sum, alphabeta_sum, alphax_sum*beta2_sum )*factor; + Vec4 b = NegativeMultiplySubtract( alphax_sum, alphabeta_sum, betax_sum*alpha2_sum )*factor; + + // clamp to the grid + a = Min( one, Max( zero, a ) ); + b = Min( one, Max( zero, b ) ); + a = Truncate( MultiplyAdd( grid, a, half ) )*gridrcp; + b = Truncate( MultiplyAdd( grid, b, half ) )*gridrcp; + + // compute the error (we skip the constant xxsum) + Vec4 e1 = MultiplyAdd( a*a, alpha2_sum, b*b*beta2_sum ); + Vec4 e2 = NegativeMultiplySubtract( a, alphax_sum, a*b*alphabeta_sum ); + Vec4 e3 = NegativeMultiplySubtract( b, betax_sum, e2 ); + Vec4 e4 = MultiplyAdd( two, e3, e1 ); + + // apply the metric to the error term + Vec4 e5 = e4*m_metric; + Vec4 error = e5.SplatX() + e5.SplatY() + e5.SplatZ(); + + // keep the solution if it wins + if( CompareAnyLessThan( error, besterror ) ) + { + beststart = a; + bestend = b; + besti = i; + bestj = j; + besterror = error; + bestiteration = iterationIndex; + } + + // advance + if( j == count ) + break; + part1 += m_points_weights[j]; + ++j; + } + + // advance + part0 += m_points_weights[i]; + } + + // stop if we didn't improve in this iteration + if( bestiteration != iterationIndex ) + break; + + // advance if possible + ++iterationIndex; + if( iterationIndex == m_iterationCount ) + break; + + // stop if a new iteration is an ordering that has already been tried + Vec3 axis = ( bestend - beststart ).GetVec3(); + if( !ConstructOrdering( axis, iterationIndex ) ) + break; + } + + // save the block if necessary + if( CompareAnyLessThan( besterror, m_besterror ) ) + { + // remap the indices + u8 const* order = ( u8* )m_order + 16*bestiteration; + + u8 unordered[16]; + for( int m = 0; m < besti; ++m ) + unordered[order[m]] = 0; + for( int m = besti; m < bestj; ++m ) + unordered[order[m]] = 2; + for( int m = bestj; m < count; ++m ) + unordered[order[m]] = 1; + + m_colours->RemapIndices( unordered, bestindices ); + + // save the block + WriteColourBlock3( beststart.GetVec3(), bestend.GetVec3(), bestindices, block ); + + // save the error + m_besterror = besterror; + } } void ClusterFit::Compress4( void* block ) { - // declare variables - int const count = m_colours->GetCount(); - Vec4 const two = VEC4_CONST( 2.0f ); - Vec4 const one = VEC4_CONST( 1.0f ); - Vec4 const onethird_onethird2( 1.0f/3.0f, 1.0f/3.0f, 1.0f/3.0f, 1.0f/9.0f ); - Vec4 const twothirds_twothirds2( 2.0f/3.0f, 2.0f/3.0f, 2.0f/3.0f, 4.0f/9.0f ); - Vec4 const twonineths = VEC4_CONST( 2.0f/9.0f ); - Vec4 const zero = VEC4_CONST( 0.0f ); - Vec4 const half = VEC4_CONST( 0.5f ); - Vec4 const grid( 31.0f, 63.0f, 31.0f, 0.0f ); - Vec4 const gridrcp( 1.0f/31.0f, 1.0f/63.0f, 1.0f/31.0f, 0.0f ); - - // prepare an ordering using the principle axis - ConstructOrdering( m_principle, 0 ); - - // check all possible clusters and iterate on the total order - Vec4 beststart = VEC4_CONST( 0.0f ); - Vec4 bestend = VEC4_CONST( 0.0f ); - Vec4 besterror = m_besterror; - u8 bestindices[16]; - int bestiteration = 0; - int besti = 0, bestj = 0, bestk = 0; - - // loop over iterations (we avoid the case that all points in first or last cluster) - for( int iterationIndex = 0;; ) - { - // first cluster [0,i) is at the start - Vec4 part0 = VEC4_CONST( 0.0f ); - for( int i = 0; i < count; ++i ) - { - // second cluster [i,j) is one third along - Vec4 part1 = VEC4_CONST( 0.0f ); - for( int j = i;; ) - { - // third cluster [j,k) is two thirds along - Vec4 part2 = ( j == 0 ) ? m_points_weights[0] : VEC4_CONST( 0.0f ); - int kmin = ( j == 0 ) ? 1 : j; - for( int k = kmin;; ) - { - // last cluster [k,count) is at the end - Vec4 part3 = m_xsum_wsum - part2 - part1 - part0; - - // compute least squares terms directly - Vec4 const alphax_sum = MultiplyAdd( part2, onethird_onethird2, MultiplyAdd( part1, twothirds_twothirds2, part0 ) ); - Vec4 const alpha2_sum = alphax_sum.SplatW(); - - Vec4 const betax_sum = MultiplyAdd( part1, onethird_onethird2, MultiplyAdd( part2, twothirds_twothirds2, part3 ) ); - Vec4 const beta2_sum = betax_sum.SplatW(); - - Vec4 const alphabeta_sum = twonineths*( part1 + part2 ).SplatW(); - - // compute the least-squares optimal points - Vec4 factor = Reciprocal( NegativeMultiplySubtract( alphabeta_sum, alphabeta_sum, alpha2_sum*beta2_sum ) ); - Vec4 a = NegativeMultiplySubtract( betax_sum, alphabeta_sum, alphax_sum*beta2_sum )*factor; - Vec4 b = NegativeMultiplySubtract( alphax_sum, alphabeta_sum, betax_sum*alpha2_sum )*factor; - - // clamp to the grid - a = Min( one, Max( zero, a ) ); - b = Min( one, Max( zero, b ) ); - a = Truncate( MultiplyAdd( grid, a, half ) )*gridrcp; - b = Truncate( MultiplyAdd( grid, b, half ) )*gridrcp; - - // compute the error (we skip the constant xxsum) - Vec4 e1 = MultiplyAdd( a*a, alpha2_sum, b*b*beta2_sum ); - Vec4 e2 = NegativeMultiplySubtract( a, alphax_sum, a*b*alphabeta_sum ); - Vec4 e3 = NegativeMultiplySubtract( b, betax_sum, e2 ); - Vec4 e4 = MultiplyAdd( two, e3, e1 ); - - // apply the metric to the error term - Vec4 e5 = e4*m_metric; - Vec4 error = e5.SplatX() + e5.SplatY() + e5.SplatZ(); - - // keep the solution if it wins - if( CompareAnyLessThan( error, besterror ) ) - { - beststart = a; - bestend = b; - besterror = error; - besti = i; - bestj = j; - bestk = k; - bestiteration = iterationIndex; - } - - // advance - if( k == count ) - break; - part2 += m_points_weights[k]; - ++k; - } - - // advance - if( j == count ) - break; - part1 += m_points_weights[j]; - ++j; - } - - // advance - part0 += m_points_weights[i]; - } - - // stop if we didn't improve in this iteration - if( bestiteration != iterationIndex ) - break; - - // advance if possible - ++iterationIndex; - if( iterationIndex == m_iterationCount ) - break; - - // stop if a new iteration is an ordering that has already been tried - Vec3 axis = ( bestend - beststart ).GetVec3(); - if( !ConstructOrdering( axis, iterationIndex ) ) - break; - } - - // save the block if necessary - if( CompareAnyLessThan( besterror, m_besterror ) ) - { - // remap the indices - u8 const* order = ( u8* )m_order + 16*bestiteration; - - u8 unordered[16]; - for( int m = 0; m < besti; ++m ) - unordered[order[m]] = 0; - for( int m = besti; m < bestj; ++m ) - unordered[order[m]] = 2; - for( int m = bestj; m < bestk; ++m ) - unordered[order[m]] = 3; - for( int m = bestk; m < count; ++m ) - unordered[order[m]] = 1; - - m_colours->RemapIndices( unordered, bestindices ); - - // save the block - WriteColourBlock4( beststart.GetVec3(), bestend.GetVec3(), bestindices, block ); - - // save the error - m_besterror = besterror; - } + // declare variables + int const count = m_colours->GetCount(); + Vec4 const two = VEC4_CONST( 2.0f ); + Vec4 const one = VEC4_CONST( 1.0f ); + Vec4 const onethird_onethird2( 1.0f/3.0f, 1.0f/3.0f, 1.0f/3.0f, 1.0f/9.0f ); + Vec4 const twothirds_twothirds2( 2.0f/3.0f, 2.0f/3.0f, 2.0f/3.0f, 4.0f/9.0f ); + Vec4 const twonineths = VEC4_CONST( 2.0f/9.0f ); + Vec4 const zero = VEC4_CONST( 0.0f ); + Vec4 const half = VEC4_CONST( 0.5f ); + Vec4 const grid( 31.0f, 63.0f, 31.0f, 0.0f ); + Vec4 const gridrcp( 1.0f/31.0f, 1.0f/63.0f, 1.0f/31.0f, 0.0f ); + + // prepare an ordering using the principle axis + ConstructOrdering( m_principle, 0 ); + + // check all possible clusters and iterate on the total order + Vec4 beststart = VEC4_CONST( 0.0f ); + Vec4 bestend = VEC4_CONST( 0.0f ); + Vec4 besterror = m_besterror; + u8 bestindices[16]; + int bestiteration = 0; + int besti = 0, bestj = 0, bestk = 0; + + // loop over iterations (we avoid the case that all points in first or last cluster) + for( int iterationIndex = 0;; ) + { + // first cluster [0,i) is at the start + Vec4 part0 = VEC4_CONST( 0.0f ); + for( int i = 0; i < count; ++i ) + { + // second cluster [i,j) is one third along + Vec4 part1 = VEC4_CONST( 0.0f ); + for( int j = i;; ) + { + // third cluster [j,k) is two thirds along + Vec4 part2 = ( j == 0 ) ? m_points_weights[0] : VEC4_CONST( 0.0f ); + int kmin = ( j == 0 ) ? 1 : j; + for( int k = kmin;; ) + { + // last cluster [k,count) is at the end + Vec4 part3 = m_xsum_wsum - part2 - part1 - part0; + + // compute least squares terms directly + Vec4 const alphax_sum = MultiplyAdd( part2, onethird_onethird2, MultiplyAdd( part1, twothirds_twothirds2, part0 ) ); + Vec4 const alpha2_sum = alphax_sum.SplatW(); + + Vec4 const betax_sum = MultiplyAdd( part1, onethird_onethird2, MultiplyAdd( part2, twothirds_twothirds2, part3 ) ); + Vec4 const beta2_sum = betax_sum.SplatW(); + + Vec4 const alphabeta_sum = twonineths*( part1 + part2 ).SplatW(); + + // compute the least-squares optimal points + Vec4 factor = Reciprocal( NegativeMultiplySubtract( alphabeta_sum, alphabeta_sum, alpha2_sum*beta2_sum ) ); + Vec4 a = NegativeMultiplySubtract( betax_sum, alphabeta_sum, alphax_sum*beta2_sum )*factor; + Vec4 b = NegativeMultiplySubtract( alphax_sum, alphabeta_sum, betax_sum*alpha2_sum )*factor; + + // clamp to the grid + a = Min( one, Max( zero, a ) ); + b = Min( one, Max( zero, b ) ); + a = Truncate( MultiplyAdd( grid, a, half ) )*gridrcp; + b = Truncate( MultiplyAdd( grid, b, half ) )*gridrcp; + + // compute the error (we skip the constant xxsum) + Vec4 e1 = MultiplyAdd( a*a, alpha2_sum, b*b*beta2_sum ); + Vec4 e2 = NegativeMultiplySubtract( a, alphax_sum, a*b*alphabeta_sum ); + Vec4 e3 = NegativeMultiplySubtract( b, betax_sum, e2 ); + Vec4 e4 = MultiplyAdd( two, e3, e1 ); + + // apply the metric to the error term + Vec4 e5 = e4*m_metric; + Vec4 error = e5.SplatX() + e5.SplatY() + e5.SplatZ(); + + // keep the solution if it wins + if( CompareAnyLessThan( error, besterror ) ) + { + beststart = a; + bestend = b; + besterror = error; + besti = i; + bestj = j; + bestk = k; + bestiteration = iterationIndex; + } + + // advance + if( k == count ) + break; + part2 += m_points_weights[k]; + ++k; + } + + // advance + if( j == count ) + break; + part1 += m_points_weights[j]; + ++j; + } + + // advance + part0 += m_points_weights[i]; + } + + // stop if we didn't improve in this iteration + if( bestiteration != iterationIndex ) + break; + + // advance if possible + ++iterationIndex; + if( iterationIndex == m_iterationCount ) + break; + + // stop if a new iteration is an ordering that has already been tried + Vec3 axis = ( bestend - beststart ).GetVec3(); + if( !ConstructOrdering( axis, iterationIndex ) ) + break; + } + + // save the block if necessary + if( CompareAnyLessThan( besterror, m_besterror ) ) + { + // remap the indices + u8 const* order = ( u8* )m_order + 16*bestiteration; + + u8 unordered[16]; + for( int m = 0; m < besti; ++m ) + unordered[order[m]] = 0; + for( int m = besti; m < bestj; ++m ) + unordered[order[m]] = 2; + for( int m = bestj; m < bestk; ++m ) + unordered[order[m]] = 3; + for( int m = bestk; m < count; ++m ) + unordered[order[m]] = 1; + + m_colours->RemapIndices( unordered, bestindices ); + + // save the block + WriteColourBlock4( beststart.GetVec3(), bestend.GetVec3(), bestindices, block ); + + // save the error + m_besterror = besterror; + } } } // namespace squish |