Evaluation adjustment for different eval types

Gives different eval scaling parameters for the three different types
of evaluation (bignet, smallnet, psqtOnly).

Passed STC:
https://tests.stockfishchess.org/tests/view/65f4b0020ec64f0526c4a3bd
LLR: 2.96 (-2.94,2.94) <0.00,2.00>
Total: 168064 W: 43507 L: 42987 D: 81570
Ptnml(0-2): 662, 19871, 42445, 20393, 661

Passed LTC:
https://tests.stockfishchess.org/tests/view/65f6be1a0ec64f0526c4c361
LLR: 2.94 (-2.94,2.94) <0.50,2.50>
Total: 162564 W: 41188 L: 40604 D: 80772
Ptnml(0-2): 120, 18112, 44216, 18732, 102

closes #5122

Bench: 2113576

src/evaluate.cpp

@@ -52,22 +52,35 @@ Value Eval::evaluate(const Eval::NNUE::Networks& networks, const Position& pos,
     int  simpleEval = simple_eval(pos, pos.side_to_move());
     bool smallNet   = std::abs(simpleEval) > SmallNetThreshold;
     bool psqtOnly   = std::abs(simpleEval) > PsqtOnlyThreshold;
-
-    int nnueComplexity;
+    int  nnueComplexity;
+    int  v;
 
     Value nnue = smallNet ? networks.small.evaluate(pos, true, &nnueComplexity, psqtOnly)
                           : networks.big.evaluate(pos, true, &nnueComplexity, false);
 
-    // Blend optimism and eval with nnue complexity and material imbalance
-    optimism += optimism * (nnueComplexity + std::abs(simpleEval - nnue)) / 524;
-    nnue -= nnue * (nnueComplexity + std::abs(simpleEval - nnue)) / 31950;
-
-    int npm = pos.non_pawn_material() / 64;
-    int v   = (nnue * (927 + npm + 9 * pos.count<PAWN>()) + optimism * (159 + npm)) / 1000;
-
-    // Damp down the evaluation linearly when shuffling
-    int shuffling = pos.rule50_count();
-    v             = v * (195 - shuffling) / 228;
+    const auto adjustEval = [&](int optDiv, int nnueDiv, int pawnCountConstant, int pawnCountMul,
+                                int npmConstant, int evalDiv, int shufflingConstant,
+                                int shufflingDiv) {
+        // Blend optimism and eval with nnue complexity and material imbalance
+        optimism += optimism * (nnueComplexity + std::abs(simpleEval - nnue)) / optDiv;
+        nnue -= nnue * (nnueComplexity + std::abs(simpleEval - nnue)) / nnueDiv;
+
+        int npm = pos.non_pawn_material() / 64;
+        v       = (nnue * (npm + pawnCountConstant + pawnCountMul * pos.count<PAWN>())
+             + optimism * (npmConstant + npm))
+          / evalDiv;
+
+        // Damp down the evaluation linearly when shuffling
+        int shuffling = pos.rule50_count();
+        v             = v * (shufflingConstant - shuffling) / shufflingDiv;
+    };
+
+    if (!smallNet)
+        adjustEval(513, 32395, 919, 11, 145, 1036, 178, 204);
+    else if (psqtOnly)
+        adjustEval(517, 32857, 908, 7, 155, 1019, 224, 238);
+    else
+        adjustEval(499, 32793, 903, 9, 147, 1067, 208, 211);
 
     // Guarantee evaluation does not hit the tablebase range
     v = std::clamp(v, VALUE_TB_LOSS_IN_MAX_PLY + 1, VALUE_TB_WIN_IN_MAX_PLY - 1);

src/evaluate.h

@@ -29,7 +29,7 @@ class Position;
 
 namespace Eval {
 
-constexpr inline int SmallNetThreshold = 1136, PsqtOnlyThreshold = 2656;
+constexpr inline int SmallNetThreshold = 1050, PsqtOnlyThreshold = 2500;
 
 // The default net name MUST follow the format nn-[SHA256 first 12 digits].nnue
 // for the build process (profile-build and fishtest) to work. Do not change the