私は再帰に頭を悩ませています。私ができる単純な再帰ですが、これは私にとって簡単ではありません。ここでの私の目標は、この検索アルゴリズムを高速化することです。再帰が役立つと思います。子を持つ単純な 43 ノード ツリーで 15 秒かかります。以下は、機能するコードの展開された再帰形式です。
var nodeList = new Array();
var removeList = new Array();
var count = 0;
var foundInThisNodeTree;
var find = function ( condition )
{
}
while ( this.treeIDMap.igTree( "nodeByPath", count ).data() )
{
var foundInThisNodeTree = false;
var n;
n = this.treeIDMap.igTree( "nodeFromElement", this.treeIDMap.igTree( "nodeByPath", count ) )
if ( n.data.ITEM.indexOf( filter ) > -1 ) { foundInThisNodeTree = true; }
else {//look deeper
var i = 0;
while ( this.treeIDMap.igTree( "nodeByPath", count + "_" + i ).data() )
{
n = this.treeIDMap.igTree( "nodeFromElement", this.treeIDMap.igTree( "nodeByPath", count + "_" + i ) );
if ( n.data.ITEM.indexOf( filter ) > -1 ) { foundInThisNodeTree = true; break; }
else {//look deeper
var j = 0;
while ( this.treeIDMap.igTree( "nodeByPath", count + "_" + i + "_" + j ).data() )
{
n = this.treeIDMap.igTree( "nodeFromElement", this.treeIDMap.igTree( "nodeByPath", count + "_" + i + "_" + j ) );
if ( n.data.ITEM.indexOf( filter ) > -1 ) { foundInThisNodeTree = true; break; }
else {//look deeper
var k = 0;
while ( this.treeIDMap.igTree( "nodeByPath", count + "_" + i + "_" + j + "_" + k ).data() )
{
n = this.treeIDMap.igTree( "nodeFromElement", this.treeIDMap.igTree( "nodeByPath", count + "_" + i + "_" + j + "_" + k ) );
if ( n.data.ITEM.indexOf( filter ) > -1 ) { foundInThisNodeTree = true; break; }
k++;
}
}
j++;
}
}
i++;
}
}
if ( !foundInThisNodeTree ) this.treeIDMap.igTree("removeAt", ""+count )
else count++;
}
** * Mirco Ellmann によって提案された 2 番目の改訂* ****
var nodeList = new Array();
var removeList = new Array();
var count = 0;
var foundInThisNodeTree;
filter = filter.toLowerCase();
while ( this.treeIDMap.igTree( "nodeByPath", count ).data() )
{
var foundInThisNodeTree = false;
var n;
n = this.treeIDMap.igTree( "nodeFromElement", this.treeIDMap.igTree( "nodeByPath", count ) )
if ( n.data.ITEM.toLowerCase().indexOf( filter ) > -1 ) { foundInThisNodeTree = true; }
else {//look deeper
var i = 0;
n = this.treeIDMap.igTree( "childrenByPath", count );
while ( n[i] )
{
if ( n[i].data.ITEM.indexOf( filter ) > -1 ) { foundInThisNodeTree = true; break; }
var j = 0;
n = this.treeIDMap.igTree( "childrenByPath", count + "_" + i );
while ( n[j] )
{
if ( n[j].data.ITEM.indexOf( filter ) > -1 ) { foundInThisNodeTree = true; break; }
var k = 0;
n = this.treeIDMap.igTree( "childrenByPath", count + "_" + i + "_" + j);
while ( n[k] )
{
if ( n[k].data.ITEM.indexOf( filter ) > -1 ) { foundInThisNodeTree = true; break; }
k++;
}
j++;
}
i++;
}
}
if ( !foundInThisNodeTree ) this.treeIDMap.igTree("removeAt", ""+count )
else count++;
}
****分岐可能なツリーを使用してデータを取得するため、ツリーを呼び出す必要はありません* ***
var count = 0;
var foundInThisNodeTree;
filter = filter.toLowerCase();
while ( this.treeIDMap.igTree( "nodeByPath", count ).data() )
{
var foundInThisNodeTree = false;
var n;
n = this.treeIDMap.igTree( "nodeFromElement", this.treeIDMap.igTree( "nodeByPath", count ) )
if ( n.data.ITEM.toLowerCase().indexOf( filter ) > -1 ) { foundInThisNodeTree = true; }
if ( n.data.branch )//look at all childer under the root node
{
var i = 0;
n = n.data.branch;
while ( n[i] )//look at all childer under the root node
{
if ( n[i].ITEM.toLowerCase().indexOf( filter ) > -1 ) { foundInThisNodeTree = true; break; }
while ( n[i].branch )//look deeper
{
var j = 0;
n = n[i].branch;
if ( n[j].ITEM.toLowerCase().indexOf( filter ) > -1 ) { foundInThisNodeTree = true; break; }
while ( n[j].branch )//look deeper
{
var k = 0;
n = n[j].branch;
if ( n[k].ITEM.toLowerCase().indexOf( filter ) > -1 ) { foundInThisNodeTree = true; break; }
k++;
}
j++;
}
i++;
}
}
if ( !foundInThisNodeTree ) this.treeIDMap.igTree("removeAt", ""+count )
else count++;
}