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Revert "Don't prune discovered checks"
Both Lucas re-test and Jean-Francois confirrm it is a regression. Here Jean-Francois's results after 3600 games : Score of96d3b1c92bvs3b87314: 690 - 729 - 2181 [0.495] 3600 ELO: -3.86 +- 99%: 14.94 95%: 11.35 LOS: 15.03% Wins: 690 Losses: 729 Draws: 2181 Total: 3600 Bench: 5404066
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+3
-7
@@ -483,8 +483,7 @@ namespace {
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Depth ext, newDepth;
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Value bestValue, value, ttValue;
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Value eval, nullValue, futilityValue;
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CheckType givesCheck;
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bool inCheck, pvMove, singularExtensionNode;
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bool inCheck, givesCheck, pvMove, singularExtensionNode;
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bool captureOrPromotion, dangerous, doFullDepthSearch;
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int moveCount, playedMoveCount;
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@@ -816,7 +815,7 @@ split_point_start: // At split points actual search starts from here
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if (PvNode && dangerous)
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ext = ONE_PLY;
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else if (givesCheck && (givesCheck == DISCO_CHECK || pos.see_sign(move) >= 0))
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else if (givesCheck && pos.see_sign(move) >= 0)
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ext = ONE_PLY / 2;
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// Singular extension search. If all moves but one fail low on a search of
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@@ -883,7 +882,6 @@ split_point_start: // At split points actual search starts from here
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// Prune moves with negative SEE at low depths
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if ( predictedDepth < 2 * ONE_PLY
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&& givesCheck != DISCO_CHECK
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&& pos.see_sign(move) < 0)
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{
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if (SpNode)
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@@ -1104,8 +1102,7 @@ split_point_start: // At split points actual search starts from here
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Key posKey;
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Move ttMove, move, bestMove;
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Value bestValue, value, ttValue, futilityValue, futilityBase;
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CheckType givesCheck;
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bool enoughMaterial, evasionPrunable, fromNull;
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bool givesCheck, enoughMaterial, evasionPrunable, fromNull;
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Depth ttDepth;
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ss->currentMove = bestMove = MOVE_NONE;
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@@ -1237,7 +1234,6 @@ split_point_start: // At split points actual search starts from here
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if ( !PvNode
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&& (!InCheck || evasionPrunable)
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&& move != ttMove
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&& givesCheck != DISCO_CHECK
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&& type_of(move) != PROMOTION
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&& pos.see_sign(move) < 0)
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continue;
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