private void setupFromNBT(NBTTagCompound tagCompound) { terrainType = TerrainType.values()[tagCompound.getInteger("terrain")]; featureTypes = toEnumSet(getIntArraySafe(tagCompound, "features"), FeatureType.values()); structureTypes = toEnumSet(getIntArraySafe(tagCompound, "structures"), StructureType.values()); effectTypes = toEnumSet(getIntArraySafe(tagCompound, "effects"), EffectType.values()); biomes.clear(); for (int a : getIntArraySafe(tagCompound, "biomes")) { BiomeGenBase biome = BiomeGenBase.getBiome(a); if (biome != null) { biomes.add(biome); } else { // Protect against deleted biomes (i.e. a mod with biomes gets removed and this dimension // still uses it). // We will pick a replacement biome here. biomes.add(BiomeGenBase.plains); } } if (tagCompound.hasKey("controller")) { controllerType = ControllerType.values()[tagCompound.getInteger("controller")]; } else { // Support for old type. if (biomes.isEmpty()) { controllerType = ControllerType.CONTROLLER_DEFAULT; } else { controllerType = ControllerType.CONTROLLER_SINGLE; } } digitString = tagCompound.getString("digits"); forcedDimensionSeed = tagCompound.getLong("forcedSeed"); baseSeed = tagCompound.getLong("baseSeed"); worldVersion = tagCompound.getInteger("worldVersion"); baseBlockForTerrain = getBlockMeta(tagCompound, "baseBlock"); tendrilBlock = getBlockMeta(tagCompound, "tendrilBlock"); canyonBlock = getBlockMeta(tagCompound, "canyonBlock"); fluidForTerrain = (Block) Block.blockRegistry.getObjectById(tagCompound.getInteger("fluidBlock")); hugeLiquidSphereFluids = readFluidsFromNBT(tagCompound, "hugeLiquidSphereFluids"); hugeLiquidSphereBlocks = readBlockArrayFromNBT(tagCompound, "hugeLiquidSphereBlocks"); // Support for the old format with only one liquid block. Block oldLiquidSphereFluid = (Block) Block.blockRegistry.getObjectById(tagCompound.getInteger("liquidSphereFluid")); liquidSphereFluids = readFluidsFromNBT(tagCompound, "liquidSphereFluids"); if (liquidSphereFluids.length == 0) { liquidSphereFluids = new Block[] {oldLiquidSphereFluid}; } // Support for the old format with only one sphere block. BlockMeta oldLiquidSphereBlock = getBlockMeta(tagCompound, "liquidSphereBlock"); liquidSphereBlocks = readBlockArrayFromNBT(tagCompound, "liquidSphereBlocks"); if (liquidSphereBlocks.length == 0) { liquidSphereBlocks = new BlockMeta[] {oldLiquidSphereBlock}; } pyramidBlocks = readBlockArrayFromNBT(tagCompound, "pyramidBlocks"); if (pyramidBlocks.length == 0) { pyramidBlocks = new BlockMeta[] {BlockMeta.STONE}; } // Support for the old format with only one sphere block. BlockMeta oldSphereBlock = getBlockMeta(tagCompound, "sphereBlock"); sphereBlocks = readBlockArrayFromNBT(tagCompound, "sphereBlocks"); if (sphereBlocks.length == 0) { sphereBlocks = new BlockMeta[] {oldSphereBlock}; } hugeSphereBlocks = readBlockArrayFromNBT(tagCompound, "hugeSphereBlocks"); extraOregen = readBlockArrayFromNBT(tagCompound, "extraOregen"); fluidsForLakes = readFluidsFromNBT(tagCompound, "lakeFluids"); peaceful = tagCompound.getBoolean("peaceful"); noanimals = tagCompound.getBoolean("noanimals"); shelter = tagCompound.getBoolean("shelter"); respawnHere = tagCompound.getBoolean("respawnHere"); if (tagCompound.hasKey("celestialAngle")) { celestialAngle = tagCompound.getFloat("celestialAngle"); } else { celestialAngle = null; } if (tagCompound.hasKey("timeSpeed")) { timeSpeed = tagCompound.getFloat("timeSpeed"); } else { timeSpeed = null; } probeCounter = tagCompound.getInteger("probes"); actualRfCost = tagCompound.getInteger("actualCost"); skyDescriptor = new SkyDescriptor.Builder().fromNBT(tagCompound).build(); calculateCelestialBodyDescriptors(); patreon1 = tagCompound.getLong("patreon1"); weatherDescriptor = new WeatherDescriptor.Builder().fromNBT(tagCompound).build(); extraMobs.clear(); NBTTagList list = tagCompound.getTagList("mobs", Constants.NBT.TAG_COMPOUND); for (int i = 0; i < list.tagCount(); i++) { NBTTagCompound tc = list.getCompoundTagAt(i); String className = tc.getString("class"); int chance = tc.getInteger("chance"); int minGroup = tc.getInteger("minGroup"); int maxGroup = tc.getInteger("maxGroup"); int maxLoaded = tc.getInteger("maxLoaded"); Class<? extends EntityLiving> c = null; try { c = (Class<? extends EntityLiving>) Class.forName(className); } catch (ClassNotFoundException e) { throw new RuntimeException(e); } MobDescriptor mob = new MobDescriptor(null, c, chance, minGroup, maxGroup, maxLoaded); extraMobs.add(mob); } String ds = tagCompound.getString("dimensionTypes"); dimensionTypes = StringUtils.split(ds, ","); if (dimensionTypes == null) { dimensionTypes = new String[0]; } }
public DimensionInformation(String name, DimensionDescriptor descriptor, ByteBuf buf) { this.name = name; this.descriptor = descriptor; terrainType = NetworkTools.readEnum(buf, TerrainType.values()); NetworkTools.readEnumCollection(buf, featureTypes, FeatureType.values()); NetworkTools.readEnumCollection(buf, structureTypes, StructureType.values()); NetworkTools.readEnumCollection(buf, effectTypes, EffectType.values()); biomes.clear(); int size = buf.readInt(); for (int i = 0; i < size; i++) { BiomeGenBase biome = BiomeGenBase.getBiome(buf.readInt()); if (biome != null) { biomes.add(biome); } else { biomes.add(BiomeGenBase.plains); } } controllerType = NetworkTools.readEnum(buf, ControllerType.values()); digitString = NetworkTools.readString(buf); forcedDimensionSeed = buf.readLong(); baseSeed = buf.readLong(); worldVersion = buf.readInt(); Block block = (Block) Block.blockRegistry.getObjectById(buf.readInt()); int meta = buf.readInt(); baseBlockForTerrain = new BlockMeta(block, meta); block = (Block) Block.blockRegistry.getObjectById(buf.readInt()); meta = buf.readInt(); tendrilBlock = new BlockMeta(block, meta); pyramidBlocks = readBlockArrayFromBuf(buf); sphereBlocks = readBlockArrayFromBuf(buf); hugeSphereBlocks = readBlockArrayFromBuf(buf); liquidSphereBlocks = readBlockArrayFromBuf(buf); liquidSphereFluids = readFluidArrayFromBuf(buf); hugeLiquidSphereBlocks = readBlockArrayFromBuf(buf); hugeLiquidSphereFluids = readFluidArrayFromBuf(buf); block = (Block) Block.blockRegistry.getObjectById(buf.readInt()); meta = buf.readInt(); canyonBlock = new BlockMeta(block, meta); fluidForTerrain = (Block) Block.blockRegistry.getObjectById(buf.readInt()); extraOregen = readBlockArrayFromBuf(buf); fluidsForLakes = readFluidArrayFromBuf(buf); peaceful = buf.readBoolean(); noanimals = buf.readBoolean(); shelter = buf.readBoolean(); respawnHere = buf.readBoolean(); celestialAngle = NetworkTools.readFloat(buf); timeSpeed = NetworkTools.readFloat(buf); probeCounter = buf.readInt(); actualRfCost = buf.readInt(); skyDescriptor = new SkyDescriptor.Builder().fromBytes(buf).build(); calculateCelestialBodyDescriptors(); weatherDescriptor = new WeatherDescriptor.Builder().fromBytes(buf).build(); patreon1 = buf.readLong(); extraMobs.clear(); size = buf.readInt(); for (int i = 0; i < size; i++) { String className = NetworkTools.readString(buf); try { Class<? extends EntityLiving> c = (Class<? extends EntityLiving>) Class.forName(className); int chance = buf.readInt(); int minGroup = buf.readInt(); int maxGroup = buf.readInt(); int maxLoaded = buf.readInt(); MobDescriptor mob = new MobDescriptor(null, c, chance, minGroup, maxGroup, maxLoaded); extraMobs.add(mob); } catch (ClassNotFoundException e) { e.printStackTrace(); } } size = buf.readInt(); dimensionTypes = new String[size]; for (int i = 0; i < size; i++) { dimensionTypes[i] = NetworkTools.readString(buf); } setupBiomeMapping(); }
/** * ProfileData acts as a data store facility for the results of the test performed by the Profile * object. This data includes the number of trials and number of successes among those trials (i.e., * the number of times the correct answer was selected) broken down by algorithm type and question * profile (i.e., by combination of features). * * @author jjohnson346 */ public class ProfileData { private int[][] successCounts; // stores the number of successes for each // question profile, // for each algo. public final int[] trialCounts; // stores the number of trials for each // question profile. public final double[][] successProbs; // the prob of success for each algo, // for each question profile // IMPORTANT: note that it is PUBLIC private final int NUM_ALGOS = AlgorithmType.values().length; // the number // of algos // to store // data for private final int NUM_FEATURES = FeatureType.values().length; // the number // of // features // identified private final int NUM_FEATURE_COMBOS = (int) Math.pow(2.0, NUM_FEATURES); // the // number // of // combos // of // features, // assume // true/false // value // for // each. /** * constructor initializes the successCounts, trialCounts and successProbs arrays according to the * number of algos, number of features, and the consequent number of feature combinations. */ public ProfileData() { successCounts = new int[NUM_FEATURE_COMBOS][NUM_ALGOS]; trialCounts = new int[NUM_FEATURE_COMBOS]; successProbs = new double[NUM_FEATURE_COMBOS][NUM_ALGOS]; } /** * inserts the results data for a question into the data store. That is, this function inserts for * each algorithm, the results of applying that algorithm on the question, as given by the array, * results, passed in as an input argument. This data is inserted the location of the data store * corresponding to the profile for the given question. * * @param question the question for which to insert the data, the profile is the pertinent info, * here. * @param results an array of booleans giving whether the corresponding algo was successful on the * question. */ public void insert(CFEExamQuestion question, boolean[] results) { // get the profile for the question passed in as an input parm. int profileIndex = question.getProfile().getProfileIndex(); // increment the number of trials for the index corresponding to the // question's profile. trialCounts[profileIndex]++; // increment the success count in the successCounts array for those // algos that were successful. for (int j = 0; j < successCounts[profileIndex].length; j++) { if (results[j]) successCounts[profileIndex][j]++; } } /** * calculates the probability of success for a each algorithm on each question profile and stores * the results in a public array, successProbs, which is used by the CFEExamAgent to determine on * each question it confronts which algo to use. That is, it picks the algo with highest * probability of success given the profile of the current question. */ public void calculate() { for (int i = 0; i < NUM_FEATURE_COMBOS; i++) { for (int j = 0; j < NUM_ALGOS; j++) { if (trialCounts[i] != 0) successProbs[i][j] = (double) successCounts[i][j] / trialCounts[i]; else successProbs[i][j] = 0.0; } } } /** * loads profile data from file, profile data.txt, and stores the contents in the public array, * successProbs. successProbs is the critical array used by the CFEExamAgent for selecting the * algo to use on each question it confronts. */ public void load() throws FileNotFoundException { // change backslashes to forward slashes for mac version. // Scanner scanner = new Scanner(new // File("profile data\\profile data.txt")); Scanner scanner = new Scanner(new File("profile data//profile data.txt")); // skip first 2 header lines. scanner.nextLine(); scanner.nextLine(); for (int i = 0; i < NUM_FEATURE_COMBOS; i++) { // skip first column showing the index. scanner.nextInt(); trialCounts[i] = scanner.nextInt(); for (int j = 0; j < NUM_ALGOS; j++) { successProbs[i][j] = scanner.nextDouble(); } } scanner.close(); } /** * returns a pretty formatted version of the contents of number of trials and successProb for each * question profile. */ @Override public String toString() { StringBuilder sb = new StringBuilder(); sb.append(toStringTrueFalse()); sb.append("\n\n"); sb.append(toStringMultipleChoice()); return new String(sb); // StringBuilder sb = new StringBuilder(); // // final int COLUMN_WIDTH = 14; // String formatString = "%" + COLUMN_WIDTH + "s"; // // // make header. // sb.append(String.format(formatString, "Index")); // sb.append(String.format(formatString, "Trials")); // // for (AlgorithmType t : AlgorithmType.values()) { // sb.append(String.format(formatString, t)); // } // sb.append(String.format(formatString, "Agent")); // sb.append(String.format(formatString, "Description")); // sb.append("\n"); // for (int i = 0; i < AlgorithmType.values().length + 4; i++) // sb.append(String.format(formatString, "-------------")); // sb.append("\n"); // // // display values. // for (int i = 0; i < NUM_FEATURE_COMBOS; i++) { // // 2016/01/05 - version 2.0.0 - added condition for // // trial counts > 0 in order to remove the "zero" rows, // // i.e., rows showing profile indices where there are no // // trials. // if (trialCounts[i] > 0) { // sb.append(String.format(formatString, i)); // sb.append(String.format(formatString, trialCounts[i])); // // for (int j = 0; j < AlgorithmType.values().length; j++) { // sb.append(String.format("%" + COLUMN_WIDTH + ".3f", successProbs[i][j])); // } // sb.append(String.format("%" + COLUMN_WIDTH + ".3f", maxSuccessProb(successProbs[i]))); // sb.append(Profile.getDescription(i)); // sb.append("\n"); // } // } // // // display total trial count // int totalCount = 0; // for (int i = 0; i < trialCounts.length; i++) { // totalCount += trialCounts[i]; // } // sb.append(String.format("%" + COLUMN_WIDTH + "s%" + COLUMN_WIDTH // + "d\n", "Total Count:", totalCount)); // // return new String(sb); } private String toStringMultipleChoice() { StringBuilder sb = new StringBuilder(); final int COLUMN_WIDTH = 14; String formatString = "%" + COLUMN_WIDTH + "s"; // make header. sb.append("Multiple Choice:\n----------------\n"); sb.append(String.format(formatString, "Index")); sb.append(String.format(formatString, "Trials")); for (AlgorithmType t : AlgorithmType.values()) { sb.append(String.format(formatString, t)); } sb.append(String.format(formatString, "Agent")); sb.append(String.format(formatString, "Description")); sb.append("\n"); for (int i = 0; i < AlgorithmType.values().length + 4; i++) sb.append(String.format(formatString, "-------------")); sb.append("\n"); int totalCount = 0; // for displaying the total count at the bottom. double weightedAgentAccuracy = 0; // for calculating weighted accuracy rate across all question profiles. // display values. for (int i = 0; i < NUM_FEATURE_COMBOS; i++) { // 2016/01/05 - version 2.0.0 - added condition for // trial counts > 0 in order to remove the "zero" rows, // i.e., rows showing profile indices where there are no // trials. // Also, added the !hasFeature(truefalse) condition. if (trialCounts[i] > 0 && !Profile.hasFeature(i, FeatureType.TRUE_FALSE.ordinal())) { sb.append(String.format(formatString, i)); sb.append(String.format(formatString, trialCounts[i])); for (int j = 0; j < AlgorithmType.values().length; j++) { sb.append(String.format("%" + COLUMN_WIDTH + ".3f", successProbs[i][j])); } double agentAccuracy = maxSuccessProb(successProbs[i]); sb.append(String.format("%" + COLUMN_WIDTH + ".3f", maxSuccessProb(successProbs[i]))); sb.append(Profile.getDescription(i)); sb.append("\n"); totalCount += trialCounts[i]; weightedAgentAccuracy += trialCounts[i] * agentAccuracy; } } weightedAgentAccuracy /= totalCount; // display total trial count sb.append( String.format( "%" + COLUMN_WIDTH + "s%" + COLUMN_WIDTH + "d%" + COLUMN_WIDTH * 9 + "s%" + COLUMN_WIDTH + ".3f\n", "Total Count:", totalCount, " ", weightedAgentAccuracy)); return new String(sb); } private String toStringTrueFalse() { StringBuilder sb = new StringBuilder(); final int COLUMN_WIDTH = 14; String formatString = "%" + COLUMN_WIDTH + "s"; // make header. sb.append("True-False: \n-----------\n"); sb.append(String.format(formatString, "Index")); sb.append(String.format(formatString, "Trials")); for (AlgorithmType t : AlgorithmType.values()) { sb.append(String.format(formatString, t)); } sb.append(String.format(formatString, "Agent")); sb.append(String.format(formatString, "Description")); sb.append("\n"); for (int i = 0; i < AlgorithmType.values().length + 4; i++) sb.append(String.format(formatString, "-------------")); sb.append("\n"); int totalCount = 0; // for displaying the total count at the bottom. double weightedAgentAccuracy = 0; // for calculating weighted accuracy rate across all question profiles. // display values. for (int i = 0; i < NUM_FEATURE_COMBOS; i++) { // 2016/01/05 - version 2.0.0 - added condition for // trial counts > 0 in order to remove the "zero" rows, // i.e., rows showing profile indices where there are no // trials. // Also, added the hasFeature(truefalse) condition. if (trialCounts[i] > 0 && Profile.hasFeature(i, FeatureType.TRUE_FALSE.ordinal())) { sb.append(String.format(formatString, i)); sb.append(String.format(formatString, trialCounts[i])); for (int j = 0; j < AlgorithmType.values().length; j++) { sb.append(String.format("%" + COLUMN_WIDTH + ".3f", successProbs[i][j])); } double agentAccuracy = maxSuccessProb(successProbs[i]); sb.append(String.format("%" + COLUMN_WIDTH + ".3f", agentAccuracy)); sb.append(Profile.getDescription(i)); sb.append("\n"); totalCount += trialCounts[i]; weightedAgentAccuracy += trialCounts[i] * agentAccuracy; } } weightedAgentAccuracy /= totalCount; // display total trial count // sb.append(String.format("%" + COLUMN_WIDTH + "s%" + COLUMN_WIDTH // + "d\n", "Total Count:", totalCount)); sb.append( String.format( "%" + COLUMN_WIDTH + "s%" + COLUMN_WIDTH + "d%" + COLUMN_WIDTH * 9 + "s%" + COLUMN_WIDTH + ".3f\n", "Total Count:", totalCount, " ", weightedAgentAccuracy)); return new String(sb); } private double maxSuccessProb(double[] successProbs) { double max = successProbs[0]; for (int i = 1; i < successProbs.length; i++) { if (successProbs[i] > max) max = successProbs[i]; } return max; } }