diff --git a/src/main/java/com/extendedae_plus/content/ScaledProcessingPattern.java b/src/main/java/com/extendedae_plus/content/ScaledProcessingPattern.java index 27a7c5a..0b672ff 100644 --- a/src/main/java/com/extendedae_plus/content/ScaledProcessingPattern.java +++ b/src/main/java/com/extendedae_plus/content/ScaledProcessingPattern.java @@ -17,27 +17,21 @@ import java.util.Objects; */ public final class ScaledProcessingPattern implements IPatternDetails { - private final AEProcessingPattern original; // 原始样板引用 - private final AEItemKey definition; // 样板物品 - private final GenericStack[] sparseInputs; // 缩放后的稀疏输入 - private final GenericStack[] sparseOutputs; // 缩放后的稀疏输出 - private final IInput[] inputs; // 缩放后的压缩输入 - private final GenericStack[] condensedOutputs; // 缩放后的压缩输出 + // 最小化实例字段：只保留原始样板引用、定义和倍数 + private final AEProcessingPattern original; // 原始样板引用 + private final AEItemKey definition; // 样板物品（直接委托自 original） + private final long multiplier; // 乘数（外部可视为视图参数） - public ScaledProcessingPattern( - AEProcessingPattern original, - AEItemKey definition, - GenericStack[] sparseInputs, - GenericStack[] sparseOutputs, - IInput[] inputs, - GenericStack[] condensedOutputs - ) { + // 延迟计算缓存（轻量化实例时避免在构造器中分配大数组） + private transient volatile IInput[] inputsCache; + private transient volatile GenericStack[] outputsCache; + private transient volatile GenericStack[] sparseInputsCache; + private transient volatile GenericStack[] sparseOutputsCache; + + public ScaledProcessingPattern(AEProcessingPattern original, AEItemKey definition, long multiplier) { this.original = Objects.requireNonNull(original); this.definition = Objects.requireNonNull(definition); - this.sparseInputs = Objects.requireNonNull(sparseInputs); - this.sparseOutputs = Objects.requireNonNull(sparseOutputs); - this.inputs = Objects.requireNonNull(inputs); - this.condensedOutputs = Objects.requireNonNull(condensedOutputs); + this.multiplier = multiplier <= 0 ? 1L : multiplier; } /* -------------------- API 实现 -------------------- */ @@ -53,25 +47,91 @@ public final class ScaledProcessingPattern implements IPatternDetails { @Override public IInput[] getInputs() { - return inputs; + IInput[] cached = this.inputsCache; + if (cached == null) { + synchronized (this) { + cached = this.inputsCache; + if (cached == null) { + var base = original.getInputs(); + IInput[] arr = new IInput[base.length]; + for (int i = 0; i < base.length; i++) { + var in = base[i]; + // 不复制 template 数组，直接复用原始的 possible inputs；仅放大 multiplier + arr[i] = new Input(in.getPossibleInputs(), in.getMultiplier() * this.multiplier); + } + this.inputsCache = arr; + cached = arr; + } + } + } + return cached; } @Override public GenericStack[] getOutputs() { - return condensedOutputs; + GenericStack[] cached = this.outputsCache; + if (cached == null) { + synchronized (this) { + cached = this.outputsCache; + if (cached == null) { + var baseOutputs = original.getOutputs(); + GenericStack[] arr = new GenericStack[baseOutputs.length]; + for (int i = 0; i < baseOutputs.length; i++) { + var o = baseOutputs[i]; + if (o != null) arr[i] = new GenericStack(o.what(), o.amount() * this.multiplier); + } + this.outputsCache = arr; + cached = arr; + } + } + } + return cached; } public GenericStack[] getSparseInputs() { - return sparseInputs; + GenericStack[] cached = this.sparseInputsCache; + if (cached == null) { + synchronized (this) { + cached = this.sparseInputsCache; + if (cached == null) { + var base = original.getSparseInputs(); + GenericStack[] arr = new GenericStack[base.length]; + for (int i = 0; i < base.length; i++) { + var v = base[i]; + if (v != null) arr[i] = new GenericStack(v.what(), v.amount() * this.multiplier); + } + this.sparseInputsCache = arr; + cached = arr; + } + } + } + return cached; } public GenericStack[] getSparseOutputs() { - return sparseOutputs; + GenericStack[] cached = this.sparseOutputsCache; + if (cached == null) { + synchronized (this) { + cached = this.sparseOutputsCache; + if (cached == null) { + var base = original.getSparseOutputs(); + GenericStack[] arr = new GenericStack[base.length]; + for (int i = 0; i < base.length; i++) { + var v = base[i]; + if (v != null) arr[i] = new GenericStack(v.what(), v.amount() * this.multiplier); + } + this.sparseOutputsCache = arr; + cached = arr; + } + } + } + return cached; } @Override public GenericStack getPrimaryOutput() { - if (condensedOutputs.length > 0) return condensedOutputs[0]; + var outs = getOutputs(); + if (outs.length > 0 && outs[0] != null) return outs[0]; return original.getPrimaryOutput(); } @@ -82,26 +142,29 @@ public final class ScaledProcessingPattern implements IPatternDetails { @Override public void pushInputsToExternalInventory(KeyCounter[] inputHolder, PatternInputSink inputSink) { - // 保持和 AEProcessingPattern 一致，用 sparseInputs 驱动 - if (sparseInputs.length == inputs.length) { + // 使用 lazy 计算的 sparseInputs 与 inputs 来驱动；当两者长度一致时直接委托 + GenericStack[] sInputs = getSparseInputs(); + IInput[] ins = getInputs(); + if (sInputs.length == ins.length) { IPatternDetails.super.pushInputsToExternalInventory(inputHolder, inputSink); - } else { - KeyCounter allInputs = new KeyCounter(); - for (KeyCounter counter : inputHolder) { - allInputs.addAll(counter); - } - for (GenericStack sparseInput : sparseInputs) { - if (sparseInput != null) { - AEKey key = sparseInput.what(); - long amount = sparseInput.amount(); - long available = allInputs.get(key); - if (available < amount) { - throw new RuntimeException("Expected at least %d of %s when pushing scaled pattern, but only %d available" - .formatted(amount, key, available)); - } - inputSink.pushInput(key, amount); - allInputs.remove(key, amount); + return; + } + + KeyCounter allInputs = new KeyCounter(); + for (KeyCounter counter : inputHolder) { + allInputs.addAll(counter); + } + for (GenericStack sparseInput : sInputs) { + if (sparseInput != null) { + AEKey key = sparseInput.what(); + long amount = sparseInput.amount(); + long available = allInputs.get(key); + if (available < amount) { + throw new RuntimeException("Expected at least %d of %s when pushing scaled pattern, but only %d available" + .formatted(amount, key, available)); } + inputSink.pushInput(key, amount); + allInputs.remove(key, amount); } } } @@ -117,18 +180,22 @@ public final class ScaledProcessingPattern implements IPatternDetails { this.multiplier = multiplier; } + @Override public GenericStack[] getPossibleInputs() { return this.template; } + @Override public long getMultiplier() { return this.multiplier; } + @Override public boolean isValid(AEKey input, Level level) { return input.matches(this.template[0]); } + @Override public @Nullable AEKey getRemainingKey(AEKey template) { return null; } diff --git a/src/main/java/com/extendedae_plus/util/PatternScaler.java b/src/main/java/com/extendedae_plus/util/PatternScaler.java index 65aa98f..4624e27 100644 --- a/src/main/java/com/extendedae_plus/util/PatternScaler.java +++ b/src/main/java/com/extendedae_plus/util/PatternScaler.java @@ -71,48 +71,7 @@ public final class PatternScaler { // 配置读取异常时不施加上限 } - // 构建压缩输入（将每个输入的 multiplier 翻倍，保留每个模板的原始数量） - IInput[] scaledInputs = new IInput[baseInputs.length]; - for (int i = 0; i < baseInputs.length; i++) { - var in = baseInputs[i]; - var template = in.getPossibleInputs(); - GenericStack[] scaledTemplates = new GenericStack[template.length]; - for (int j = 0; j < template.length; j++) { - scaledTemplates[j] = new GenericStack(template[j].what(), template[j].amount()); - } - scaledInputs[i] = new ScaledProcessingPattern.Input(scaledTemplates, in.getMultiplier() * multiplier); - } - - /* 4. 构建压缩输出 */ - GenericStack[] scaledCondensedOutputs = new GenericStack[baseOutputs.length]; - for (int i = 0; i < baseOutputs.length; i++) { - GenericStack out = baseOutputs[i]; - if (out != null) { - scaledCondensedOutputs[i] = new GenericStack(out.what(), out.amount() * multiplier); - } - } - - // 构建并打印稀疏表示（直接按 multiplier 放大） - GenericStack[] scaledSparseInputs = new GenericStack[baseSparseInputs.length]; - for (int i = 0; i < baseSparseInputs.length; i++) { - var in = baseSparseInputs[i]; - if (in != null) { - scaledSparseInputs[i] = new GenericStack(in.what(), in.amount() * multiplier); - } - } - GenericStack[] scaledSparseOutputs = new GenericStack[baseSparseOutputs.length]; - for (int i = 0; i < baseSparseOutputs.length; i++) { - var out = baseSparseOutputs[i]; - if (out != null) { - scaledSparseOutputs[i] = new GenericStack(out.what(), out.amount() * multiplier); - } - } - - return new ScaledProcessingPattern(base, - base.getDefinition(), - scaledSparseInputs, - scaledSparseOutputs, - scaledInputs, - scaledCondensedOutputs); + // 仅使用 multiplier 构建轻量化 ScaledProcessingPattern（具体视图按需计算） + return new ScaledProcessingPattern(base, base.getDefinition(), multiplier); } } diff --git a/src/main/resources/extendedae_plus.mixins.json b/src/main/resources/extendedae_plus.mixins.json index 6e1c457..ce2f7a0 100644 --- a/src/main/resources/extendedae_plus.mixins.json +++ b/src/main/resources/extendedae_plus.mixins.json @@ -42,7 +42,6 @@ "ae2.autopattern.CraftingTreeNodeMixin", "ae2.autopattern.CraftingTreeProcessMixin", "ae2.autopattern.PatternProviderLogicContainsRedirectMixin", - "ae2.autopattern.adaptation.AdvPatternProviderLogicContainsRedirectMixin", "ae2.helpers.PatternProviderLogicAdvancedMixin", "ae2.helpers.PatternProviderLogicDoublingMixin", "ae2.menu.ContainerPatternEncodingTermMenuMixin",