First pass at DRC RTree functionality
This implements a copper-layer RTree with functions for iterating over the elements in a copper layer and providing Nearest Neighbor returns for BOARD_CONNECTED_ITEMS
This commit is contained in:
Seth Hillbrand
parent
fedc6519cd
commit
7c455f2357
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@ -124,7 +124,7 @@ public:
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*/
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virtual bool Collide( const VECTOR2I& aP, int aClearance = 0, int* aActual = nullptr ) const
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{
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return Collide( SEG( aP, aP ), aClearance );
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return Collide( SEG( aP, aP ), aClearance, aActual );
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}
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/**
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@ -115,11 +115,21 @@ bool SHAPE_COMPOUND::IsSolid() const
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bool SHAPE_COMPOUND::Collide( const SEG& aSeg, int aClearance, int* aActual ) const
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{
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int dist = std::numeric_limits<int>::max();
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for( auto& item : m_shapes )
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{
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if( item->Collide( aSeg, aClearance, aActual ) )
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return true;
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{
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if( !aActual || *aActual == 0 )
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return true;
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dist = std::min( dist, *aActual );
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}
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}
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return false;
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if( aActual )
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*aActual = dist;
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return dist != std::numeric_limits<int>::max();
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}
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@ -66,6 +66,7 @@ include_directories(
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${CMAKE_SOURCE_DIR}/pcbnew/dialogs
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${CMAKE_SOURCE_DIR}/polygon
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${CMAKE_SOURCE_DIR}/common/geometry
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${CMAKE_SOURCE_DIR}/libs/kimath/include/math
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${CMAKE_SOURCE_DIR}/qa/common
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${CMAKE_SOURCE_DIR}/qa
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${CMAKE_SOURCE_DIR}/qa/qa_utils
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@ -0,0 +1,308 @@
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/*
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* This program source code file is part of KiCad, a free EDA CAD application.
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*
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* Copyright (C) 2019 KiCad Developers, see AUTHORS.txt for contributors.
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* Copyright (C) 2020 CERN
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*
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* This program is free software; you can redistribute it and/or
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* modify it under the terms of the GNU General Public License
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* as published by the Free Software Foundation; either version 3
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* of the License, or (at your option) any later version.
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*
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* This program is distributed in the hope that it will be useful,
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* but WITHOUT ANY WARRANTY; without even the implied warranty of
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* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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* GNU General Public License for more details.
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*
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* You should have received a copy of the GNU General Public License
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* along with this program; if not, you may find one here:
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* http://www.gnu.org/licenses/old-licenses/gpl-3.0.html
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* or you may search the http://www.gnu.org website for the version 3 license,
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* or you may write to the Free Software Foundation, Inc.,
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* 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA
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*/
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#ifndef DRC_RTREE_H_
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#define DRC_RTREE_H_
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#include <eda_rect.h>
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#include <board_connected_item.h>
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#include <set>
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#include <vector>
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#include <geometry/rtree.h>
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#include <vector2d.h>
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/**
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* DRC_RTREE -
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* Implements an R-tree for fast spatial and layer indexing of connectable items.
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* Non-owning.
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*/
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class DRC_RTREE
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{
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private:
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using drc_rtree = RTree<BOARD_CONNECTED_ITEM*, int, 2, double>;
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public:
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DRC_RTREE()
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{
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for( int layer : LSET::AllCuMask().Seq() )
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m_tree[layer] = new drc_rtree();
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m_count = 0;
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}
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~DRC_RTREE()
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{
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for( auto tree : m_tree )
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delete tree;
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}
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/**
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* Function Insert()
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* Inserts an item into the tree. Item's bounding box is taken via its GetBoundingBox() method.
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*/
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void insert( BOARD_CONNECTED_ITEM* aItem )
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{
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const EDA_RECT& bbox = aItem->GetBoundingBox();
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const int mmin[2] = { bbox.GetX(), bbox.GetY() };
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const int mmax[2] = { bbox.GetRight(), bbox.GetBottom() };
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for( int layer : aItem->GetLayerSet().Seq() )
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m_tree[layer]->Insert( mmin, mmax, aItem );
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m_count++;
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}
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/**
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* Function Remove()
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* Removes an item from the tree. Removal is done by comparing pointers, attempting
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* to remove a copy of the item will fail.
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*/
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bool remove( BOARD_CONNECTED_ITEM* aItem )
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{
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// First, attempt to remove the item using its given BBox
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const EDA_RECT& bbox = aItem->GetBoundingBox();
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const int mmin[2] = { bbox.GetX(), bbox.GetY() };
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const int mmax[2] = { bbox.GetRight(), bbox.GetBottom() };
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bool removed = false;
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for( auto layer : aItem->GetLayerSet().Seq() )
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{
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// If we are not successful ( true == not found ), then we expand
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// the search to the full tree
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if( m_tree[int( layer )]->Remove( mmin, mmax, aItem ) )
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{
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// N.B. We must search the whole tree for the pointer to remove
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// because the item may have been moved before we have the chance to
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// delete it from the tree
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const int mmin2[2] = { INT_MIN, INT_MIN };
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const int mmax2[2] = { INT_MAX, INT_MAX };
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if( m_tree[int( layer )]->Remove( mmin2, mmax2, aItem ) )
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continue;
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}
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removed = true;
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}
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m_count -= int( removed );
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return removed;
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}
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/**
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* Function RemoveAll()
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* Removes all items from the RTree
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*/
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void clear()
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{
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for( auto tree : m_tree )
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tree->RemoveAll();
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m_count = 0;
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}
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/**
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* Determine if a given item exists in the tree. Note that this does not search the full tree
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* so if the item has been moved, this will return false when it should be true.
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*
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* @param aItem Item that may potentially exist in the tree
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* @param aRobust If true, search the whole tree, not just the bounding box
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* @return true if the item definitely exists, false if it does not exist within bbox
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*/
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bool contains( BOARD_CONNECTED_ITEM* aItem, bool aRobust = false )
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{
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const EDA_RECT& bbox = aItem->GetBoundingBox();
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const int mmin[2] = { bbox.GetX(), bbox.GetY() };
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const int mmax[2] = { bbox.GetRight(), bbox.GetBottom() };
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bool found = false;
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auto search = [&found, &aItem]( const BOARD_CONNECTED_ITEM* aSearchItem ) {
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if( aSearchItem == aItem )
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{
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found = true;
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return false;
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}
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return true;
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};
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for( int layer : aItem->GetLayerSet().Seq() )
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{
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m_tree[layer]->Search( mmin, mmax, search );
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if( found )
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break;
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}
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if( !found && aRobust )
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{
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for( int layer : LSET::AllCuMask().Seq() )
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{
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// N.B. We must search the whole tree for the pointer to remove
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// because the item may have been moved. We do not expand the item
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// layer search as this should not change.
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const int mmin2[2] = { INT_MIN, INT_MIN };
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const int mmax2[2] = { INT_MAX, INT_MAX };
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m_tree[layer]->Search( mmin2, mmax2, search );
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if( found )
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break;
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}
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}
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return found;
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}
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std::vector<std::pair<int, BOARD_CONNECTED_ITEM*>> GetNearest( const wxPoint &aPoint,
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PCB_LAYER_ID aLayer,
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int aLimit )
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{
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const int point[2] = { aPoint.x, aPoint.y };
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auto result = m_tree[int( aLayer )]->NearestNeighbors( point,
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[aLimit]( std::size_t a_count, int a_maxDist ) -> bool
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{
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return a_count >= aLimit;
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},
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[]( BOARD_CONNECTED_ITEM* aElement) -> bool
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{
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// Don't remove any elements from the list
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return false;
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},
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[aLayer]( const int* a_point, BOARD_CONNECTED_ITEM* a_data ) -> int
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{
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switch( a_data->Type() )
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{
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case PCB_TRACE_T:
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{
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TRACK* track = static_cast<TRACK*>( a_data );
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SEG seg( track->GetStart(), track->GetEnd() );
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return seg.Distance( VECTOR2I( a_point[0], a_point[1] ) ) -
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( track->GetWidth() + 1 ) / 2;
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}
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case PCB_VIA_T:
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{
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VIA* via = static_cast<VIA*>( a_data );
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return ( VECTOR2I( via->GetPosition() ) -
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VECTOR2I( a_point[0], a_point[1] ) ).EuclideanNorm() -
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( via->GetWidth() + 1 ) / 2;
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}
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default:
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{
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VECTOR2I point( a_point[0], a_point[1] );
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int dist = 0;
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auto shape = a_data->GetEffectiveShape( aLayer );
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// Here we use a hack to get the distance by colliding with a large area
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// However, we can't use just MAX_INT because we will overflow the collision calculations
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shape->Collide( point, std::numeric_limits<int>::max() / 2, &dist);
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return dist;
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}
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}
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return 0;
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});
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return result;
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}
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/**
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* Returns the number of items in the tree
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* @return number of elements in the tree;
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*/
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size_t size()
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{
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return m_count;
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}
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bool empty()
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{
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return m_count == 0;
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}
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using iterator = typename drc_rtree::Iterator;
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/**
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* The DRC_LAYER struct provides a layer-specific auto-range iterator to the RTree. Using
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* this struct, one can write lines like:
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*
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* for( auto item : rtree.OnLayer( In1_Cu ) )
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*
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* and iterate over only the RTree items that are on In1
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*/
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struct DRC_LAYER
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{
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DRC_LAYER( drc_rtree* aTree ) : layer_tree( aTree )
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{
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m_rect = { { INT_MIN, INT_MIN }, { INT_MAX, INT_MAX } };
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};
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DRC_LAYER( drc_rtree* aTree, const EDA_RECT aRect ) : layer_tree( aTree )
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{
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m_rect = { { aRect.GetX(), aRect.GetY() },
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{ aRect.GetRight(), aRect.GetBottom() } };
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};
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drc_rtree::Rect m_rect;
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drc_rtree* layer_tree;
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iterator begin()
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{
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return layer_tree->begin( m_rect );
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}
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iterator end()
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{
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return layer_tree->end( m_rect );
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}
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};
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DRC_LAYER OnLayer( PCB_LAYER_ID aLayer )
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{
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return DRC_LAYER( m_tree[int( aLayer )] );
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}
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DRC_LAYER Overlapping( PCB_LAYER_ID aLayer, const wxPoint& aPoint, int aAccuracy = 0 )
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{
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EDA_RECT rect( aPoint, wxSize( 0, 0 ) );
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rect.Inflate( aAccuracy );
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return DRC_LAYER( m_tree[int( aLayer )], rect );
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}
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DRC_LAYER Overlapping( PCB_LAYER_ID aLayer, const EDA_RECT& aRect )
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{
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return DRC_LAYER( m_tree[int( aLayer )], aRect );
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}
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private:
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drc_rtree* m_tree[MAX_CU_LAYERS];
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size_t m_count;
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};
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#endif /* DRC_RTREE_H_ */
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@ -36,6 +36,7 @@
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#include <drc_proto/drc_engine.h>
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#include <drc_proto/drc_item.h>
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#include <drc_proto/drc_rtree.h>
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#include <drc_proto/drc_rule.h>
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#include <drc_proto/drc_test_provider_clearance_base.h>
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@ -59,15 +60,15 @@ public:
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{
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}
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virtual ~DRC_TEST_PROVIDER_COPPER_CLEARANCE()
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virtual ~DRC_TEST_PROVIDER_COPPER_CLEARANCE()
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{
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}
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virtual bool Run() override;
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virtual const wxString GetName() const override
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virtual const wxString GetName() const override
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{
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return "clearance";
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return "clearance";
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};
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virtual const wxString GetDescription() const override
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@ -110,7 +111,7 @@ bool test::DRC_TEST_PROVIDER_COPPER_CLEARANCE::Run()
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ReportAux( "Worst clearance : %d nm", m_largestClearance );
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//m_largestClearance =
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//m_largestClearance =
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ReportStage( ("Testing pad copper clerances"), 0, 2 );
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testPadClearances();
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@ -430,7 +431,7 @@ void test::DRC_TEST_PROVIDER_COPPER_CLEARANCE::doTrackDrc( TRACK* aRefSeg, TRACK
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SHAPE_SEGMENT trackSeg( track->GetStart(), track->GetEnd(), track->GetWidth() );
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int actual;
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if( OPT_VECTOR2I intersection = refSeg.GetSeg().Intersect( trackSeg.GetSeg() ) )
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{
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DRC_ITEM* drcItem = DRC_ITEM::Create( DRCE_TRACKS_CROSSING );
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@ -538,7 +539,7 @@ void test::DRC_TEST_PROVIDER_COPPER_CLEARANCE::testPadClearances( )
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ReportAux("Testing %d pads...", sortedPads.size() );
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for( auto p : sortedPads )
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if( sortedPads.empty() )
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return;
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@ -815,7 +816,7 @@ void test::DRC_TEST_PROVIDER_COPPER_CLEARANCE::testZones()
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MessageTextFromValue( userUnits(), conflict.second, true ) );
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drcItem->SetErrorMessage( msg );
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}
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drcItem->SetViolatingRule( rule );
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@ -15,10 +15,32 @@
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// * 2004 Templated C++ port by Greg Douglas
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// * 2013 CERN (www.cern.ch)
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// * 2020 KiCad Developers - Add std::iterator support for searching
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// * 2020 KiCad Developers - Add container nearest neighbor based on Hjaltason & Samet
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//
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//LICENSE:
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//
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// Entirely free for all uses. Enjoy!
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/*
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* This program source code file is part of KiCad, a free EDA CAD application.
|
||||
*
|
||||
* Copyright (C) 2020 KiCad Developers, see AUTHORS.txt for contributors.
|
||||
* Copyright (C) 2013 CERN
|
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*
|
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* This program is free software; you can redistribute it and/or
|
||||
* modify it under the terms of the GNU General Public License
|
||||
* as published by the Free Software Foundation; either version 3
|
||||
* of the License, or (at your option) any later version.
|
||||
*
|
||||
* This program is distributed in the hope that it will be useful,
|
||||
* but WITHOUT ANY WARRANTY; without even the implied warranty of
|
||||
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
|
||||
* GNU General Public License for more details.
|
||||
*
|
||||
* You should have received a copy of the GNU General Public License
|
||||
* along with this program; if not, you may find one here:
|
||||
* http://www.gnu.org/licenses/old-licenses/gpl-3.0.html
|
||||
* or you may search the http://www.gnu.org website for the version 3 license,
|
||||
* or you may write to the Free Software Foundation, Inc.,
|
||||
* 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA
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||||
*/
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#ifndef RTREE_H
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#define RTREE_H
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@ -35,6 +57,8 @@
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#include <array>
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#include <functional>
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#include <iterator>
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#include <queue>
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#include <vector>
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#ifdef DEBUG
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#define ASSERT assert // RTree uses ASSERT( condition )
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@ -202,23 +226,19 @@ public:
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/// Save tree contents to stream
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bool Save( RTFileStream& a_stream );
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/// Find the nearest neighbor of a specific point.
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/// It uses the MINDIST method, simplifying the one from "R-Trees: Theory and Applications" by Yannis Manolopoulos et al.
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/// The bounding rectangle is used to calculate the distance to the DATATYPE.
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/// \param a_point point to start the search
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/// \return Returns the DATATYPE located closest to a_point, 0 if the tree is empty.
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DATATYPE NearestNeighbor( const ELEMTYPE a_point[NUMDIMS] );
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/// Find the nearest neighbor of a specific point.
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/// It uses the MINDIST method, simplifying the one from "R-Trees: Theory and Applications" by Yannis Manolopoulos et al.
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/// It receives a callback function to calculate the distance to a DATATYPE object, instead of using the bounding rectangle.
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/// \param a_point point to start the search
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/// \param a_squareDistanceCallback function that performs the square distance calculation for the selected DATATYPE.
|
||||
/// \param a_squareDistance Pointer in which the square distance to the nearest neighbour will be returned.
|
||||
/// \return Returns the DATATYPE located closest to a_point, 0 if the tree is empty.
|
||||
DATATYPE NearestNeighbor( const ELEMTYPE a_point[NUMDIMS],
|
||||
ELEMTYPE a_squareDistanceCallback( const ELEMTYPE a_point[NUMDIMS], DATATYPE a_data ),
|
||||
ELEMTYPE* a_squareDistance );
|
||||
/**
|
||||
* Gets an ordered vector of the nearest data elements to a specified point
|
||||
* @param aPoint coordinate to measure against
|
||||
* @param aTerminate Callback routine to check when we have gathered sufficient elements
|
||||
* @param aFilter Callback routine to remove specific elements from the query results
|
||||
* @param aSquaredDist Callback routine to measure the distance from the point to the data element
|
||||
* @return vector of matching elements and their distance to the point
|
||||
*/
|
||||
std::vector<std::pair<ELEMTYPE, DATATYPE>> NearestNeighbors(
|
||||
const ELEMTYPE aPoint[NUMDIMS],
|
||||
std::function<bool( const std::size_t aNumResults, const ELEMTYPE aMinDist )> aTerminate,
|
||||
std::function<bool( const DATATYPE aElement )> aFilter,
|
||||
std::function<ELEMTYPE( const ELEMTYPE a_point[NUMDIMS], const DATATYPE a_data )> aSquaredDist );
|
||||
|
||||
public:
|
||||
/// Iterator is not remove safe.
|
||||
|
|
@ -495,6 +515,12 @@ protected:
|
|||
Branch m_branch;
|
||||
ELEMTYPE minDist;
|
||||
bool isLeaf;
|
||||
|
||||
inline bool operator<(const NNNode &other) const
|
||||
{
|
||||
/// This is reversed on purpose to use std::priority_queue
|
||||
return other.minDist < minDist;
|
||||
}
|
||||
};
|
||||
|
||||
Node* AllocNode();
|
||||
|
|
@ -531,8 +557,7 @@ protected:
|
|||
void FreeListNode( ListNode* a_listNode );
|
||||
static bool Overlap( Rect* a_rectA, Rect* a_rectB );
|
||||
void ReInsert( Node* a_node, ListNode** a_listNode );
|
||||
ELEMTYPE MinDist( const ELEMTYPE a_point[NUMDIMS], Rect* a_rect );
|
||||
void InsertNNListSorted( std::vector<NNNode*>* nodeList, NNNode* newNode );
|
||||
ELEMTYPE MinDist( const ELEMTYPE a_point[NUMDIMS], const Rect& a_rect );
|
||||
|
||||
bool Search( Node * a_node, Rect * a_rect, int& a_foundCount,
|
||||
std::function<bool (const DATATYPE&)> a_callback ) const;
|
||||
|
|
@ -815,58 +840,67 @@ int RTREE_QUAL::Search( const ELEMTYPE a_min[NUMDIMS], const ELEMTYPE a_max[NUMD
|
|||
|
||||
|
||||
RTREE_TEMPLATE
|
||||
DATATYPE RTREE_QUAL::NearestNeighbor( const ELEMTYPE a_point[NUMDIMS] )
|
||||
std::vector<std::pair<ELEMTYPE, DATATYPE>> RTREE_QUAL::NearestNeighbors(
|
||||
const ELEMTYPE a_point[NUMDIMS],
|
||||
std::function<bool( const std::size_t aNumResults, const ELEMTYPE aMinDist )> aTerminate,
|
||||
std::function<bool( const DATATYPE aElement )> aFilter,
|
||||
std::function<ELEMTYPE( const ELEMTYPE a_point[NUMDIMS], const DATATYPE a_data )> aSquaredDist )
|
||||
{
|
||||
return this->NearestNeighbor( a_point, 0, 0 );
|
||||
}
|
||||
std::vector<std::pair<ELEMTYPE, DATATYPE>> result;
|
||||
std::priority_queue<NNNode> search_q;
|
||||
|
||||
|
||||
RTREE_TEMPLATE
|
||||
DATATYPE RTREE_QUAL::NearestNeighbor( const ELEMTYPE a_point[NUMDIMS],
|
||||
ELEMTYPE a_squareDistanceCallback( const ELEMTYPE a_point[NUMDIMS], DATATYPE a_data ),
|
||||
ELEMTYPE* a_squareDistance )
|
||||
{
|
||||
std::vector<NNNode*> nodeList;
|
||||
Node* node = m_root;
|
||||
NNNode* closestNode = 0;
|
||||
while( !closestNode || !closestNode->isLeaf )
|
||||
for( int i = 0; i < m_root->m_count; ++i )
|
||||
{
|
||||
//check every node on this level
|
||||
for( int index = 0; index < node->m_count; ++index )
|
||||
if( m_root->IsLeaf() )
|
||||
{
|
||||
NNNode* newNode = new NNNode;
|
||||
newNode->isLeaf = node->IsLeaf();
|
||||
newNode->m_branch = node->m_branch[index];
|
||||
if( newNode->isLeaf && a_squareDistanceCallback )
|
||||
newNode->minDist = a_squareDistanceCallback( a_point, newNode->m_branch.m_data );
|
||||
else
|
||||
newNode->minDist = this->MinDist( a_point, &(node->m_branch[index].m_rect) );
|
||||
|
||||
//TODO: a custom list could be more efficient than a vector
|
||||
this->InsertNNListSorted( &nodeList, newNode );
|
||||
search_q.push( NNNode{ m_root->m_branch[i],
|
||||
aSquaredDist( a_point, m_root->m_branch[i].m_data ),
|
||||
m_root->IsLeaf() });
|
||||
}
|
||||
if( nodeList.size() == 0 )
|
||||
else
|
||||
{
|
||||
return 0;
|
||||
search_q.push( NNNode{ m_root->m_branch[i],
|
||||
MinDist(a_point, m_root->m_branch[i].m_rect),
|
||||
m_root->IsLeaf() });
|
||||
}
|
||||
closestNode = nodeList.back();
|
||||
node = closestNode->m_branch.m_child;
|
||||
nodeList.pop_back();
|
||||
free(closestNode);
|
||||
}
|
||||
|
||||
// free memory used for remaining NNNodes in nodeList
|
||||
for( auto node_it : nodeList )
|
||||
while( !search_q.empty() )
|
||||
{
|
||||
NNNode* nnode = node_it;
|
||||
free(nnode);
|
||||
const NNNode curNode = search_q.top();
|
||||
|
||||
if( aTerminate( result.size(), curNode.minDist ) )
|
||||
break;
|
||||
|
||||
search_q.pop();
|
||||
|
||||
if( curNode.isLeaf )
|
||||
{
|
||||
if( aFilter( curNode.m_branch.m_data ) )
|
||||
result.emplace_back( curNode.minDist, curNode.m_branch.m_data );
|
||||
}
|
||||
else
|
||||
{
|
||||
Node* node = curNode.m_branch.m_child;
|
||||
|
||||
for( int i = 0; i < node->m_count; ++i )
|
||||
{
|
||||
NNNode newNode;
|
||||
newNode.isLeaf = node->IsLeaf();
|
||||
newNode.m_branch = node->m_branch[i];
|
||||
if( newNode.isLeaf )
|
||||
newNode.minDist = aSquaredDist( a_point, newNode.m_branch.m_data );
|
||||
else
|
||||
newNode.minDist = this->MinDist( a_point, node->m_branch[i].m_rect );
|
||||
|
||||
search_q.push( newNode );
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
*a_squareDistance = closestNode->minDist;
|
||||
return closestNode->m_branch.m_data;
|
||||
return result;
|
||||
}
|
||||
|
||||
|
||||
RTREE_TEMPLATE
|
||||
int RTREE_QUAL::Count()
|
||||
{
|
||||
|
|
@ -1895,7 +1929,7 @@ void RTREE_QUAL::ReInsert( Node* a_node, ListNode** a_listNode )
|
|||
}
|
||||
|
||||
|
||||
// Search in an index tree or subtree for all data retangles that overlap the argument rectangle.
|
||||
// Search in an index tree or subtree for all data rectangles that overlap the argument rectangle.
|
||||
RTREE_TEMPLATE
|
||||
bool RTREE_QUAL::Search( Node* a_node, Rect* a_rect, int& a_foundCount,
|
||||
std::function<bool (const DATATYPE&)> a_callback ) const
|
||||
|
|
@ -1939,44 +1973,34 @@ bool RTREE_QUAL::Search( Node* a_node, Rect* a_rect, int& a_foundCount,
|
|||
|
||||
|
||||
//calculate the minimum distance between a point and a rectangle as defined by Manolopoulos et al.
|
||||
//it uses the square distance to avoid the use of ELEMTYPEREAL values, which are slower.
|
||||
// returns Euclidean norm to ensure value fits in ELEMTYPE
|
||||
RTREE_TEMPLATE
|
||||
ELEMTYPE RTREE_QUAL::MinDist( const ELEMTYPE a_point[NUMDIMS], Rect* a_rect )
|
||||
ELEMTYPE RTREE_QUAL::MinDist( const ELEMTYPE a_point[NUMDIMS], const Rect& a_rect )
|
||||
{
|
||||
ELEMTYPE *q, *s, *t;
|
||||
q = (ELEMTYPE*) a_point;
|
||||
s = a_rect->m_min;
|
||||
t = a_rect->m_max;
|
||||
int minDist = 0;
|
||||
const ELEMTYPE *q, *s, *t;
|
||||
q = a_point;
|
||||
s = a_rect.m_min;
|
||||
t = a_rect.m_max;
|
||||
double minDist = 0.0;
|
||||
|
||||
for( int index = 0; index < NUMDIMS; index++ )
|
||||
{
|
||||
int r = q[index];
|
||||
|
||||
if( q[index] < s[index] )
|
||||
{
|
||||
r = s[index];
|
||||
}
|
||||
else if( q[index] >t[index] )
|
||||
else if( q[index] > t[index] )
|
||||
{
|
||||
r = t[index];
|
||||
}
|
||||
int addend = q[index] - r;
|
||||
|
||||
double addend = q[index] - r;
|
||||
minDist += addend * addend;
|
||||
}
|
||||
return minDist;
|
||||
}
|
||||
|
||||
|
||||
//insert a NNNode in a list sorted by its minDist (desc.)
|
||||
RTREE_TEMPLATE
|
||||
void RTREE_QUAL::InsertNNListSorted( std::vector<NNNode*>* nodeList, NNNode* newNode )
|
||||
{
|
||||
auto iter = nodeList->begin();
|
||||
while( iter != nodeList->end() && (*iter)->minDist > newNode->minDist )
|
||||
{
|
||||
++iter;
|
||||
}
|
||||
|
||||
nodeList->insert(iter, newNode);
|
||||
return std::lround( std::sqrt( minDist ) );
|
||||
}
|
||||
|
||||
|
||||
|
|
|
|||
Loading…
Reference in New Issue