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;
}
}
