@Override
public void setup(EvolutionState state, Parameter base) {
super.setup(state, base);
finalThreshold = state.parameters.getDouble(base.push(P_FINAL_THRESHOLD), null);
thresholdDeviation = state.parameters.getDouble(base.push(P_THRESHOLD_DEVIATION), null);
thresholdChange = state.parameters.getDouble(base.push(P_THRESHOLD_CHANGE), null);
}
public void setup(final EvolutionState state, final Parameter base) {
super.setup(state, base);
F_NOISE = state.parameters.getDouble(base.push(P_FNOISE), null, 0.0);
if (F_NOISE < 0.0)
state.output.fatal(
"Parameter not found, or its value is below 0.0.", base.push(P_FNOISE), null);
}
@Override
public void setup(EvolutionState state, Parameter base) {
// the mean number of generations it will stay on each subpop is roughly 1/changeProb and stdev
// is roughly the same as the mean
this.changeProb = state.parameters.getDouble(base.push(P_CHANGE_PROB), null);
this.currentLeap = -1;
baseScore = state.parameters.getString(base.push(P_BASE_SCORE), null);
leapScore = state.parameters.getString(base.push(P_LEAP_SCORE), null);
}
public void setup(final EvolutionState state, final Parameter base) {
// very important, remember this
super.setup(state, base);
// set up our input -- don't want to use the default base, it's unsafe here
input =
(DoubleData)
state.parameters.getInstanceForParameterEq(base.push(P_DATA), null, DoubleData.class);
input.setup(state, base.push(P_DATA));
}
@Override
public void setup(EvolutionState state, Parameter base) {
super.setup(state, base);
this.fitnessIndex =
state.parameters.getIntWithDefault(
base.push(P_FITNESS_EVAL_INDEX), defaultBase().push(P_FITNESS_EVAL_INDEX), 0);
}
@Override
public void setup(EvolutionState state, Parameter base) {
super.setup(state, base);
outFile = state.parameters.getFile(base.push(P_FILE), null);
outFile = new File(outFile.getParent(), jobPrefix + outFile.getName());
compress = state.parameters.getBoolean(base.push(P_COMPRESS), null, true);
if (compress) {
try {
taos =
new TarArchiveOutputStream(
new GZIPOutputStream(new BufferedOutputStream(new FileOutputStream(outFile))));
} catch (IOException ex) {
Logger.getLogger(SampleSolutionsStat.class.getName()).log(Level.SEVERE, null, ex);
}
}
if (!compress && !outFile.exists()) {
outFile.mkdirs();
}
sampleSize = state.parameters.getInt(base.push(P_SAMPLE_SIZE), null);
}
@Override
public void setup(EvolutionState state, Parameter base) {
if (state == null)
throw new IllegalArgumentException(this.getClass().getSimpleName() + ": state is null.");
if (state.parameters == null)
throw new IllegalArgumentException(
this.getClass().getSimpleName() + ": state.parameters is null.");
if (base == null)
throw new IllegalArgumentException(this.getClass().getSimpleName() + ": base is null.");
idealFitnessValue =
new Option<Double>(state.parameters.getDouble(base.push(P_IDEAL_FITNESS_VALUE), null));
}
public void setup(final EvolutionState state, final Parameter base) {
super.setup(state, base);
String temp;
temp = state.parameters.getStringWithDefault(base.push(P_COMPETE_STYLE), null, "");
if (temp.equalsIgnoreCase("single-elim-tournament")) {
style = STYLE_SINGLE_ELIMINATION;
} else if (temp.equalsIgnoreCase("round-robin")) {
style = STYLE_ROUND_ROBIN;
} else if (temp.equalsIgnoreCase("rand-1-way")) {
style = STYLE_N_RANDOM_COMPETITORS_ONEWAY;
} else if (temp.equalsIgnoreCase("rand-2-way")) {
style = STYLE_N_RANDOM_COMPETITORS_TWOWAY;
} else if (temp.equalsIgnoreCase("rand-2-ways")) {
state.output.fatal(
"'rand-2-ways' is no longer a valid style name: use 'rand-2-way'",
base.push(P_COMPETE_STYLE),
null);
} else {
state.output.fatal(
"Incorrect value for parameter. Acceptable values: "
+ "single-elim-tournament, round-robin, rand-1-way, rand-2-way",
base.push(P_COMPETE_STYLE));
}
if (style == STYLE_N_RANDOM_COMPETITORS_ONEWAY || style == STYLE_N_RANDOM_COMPETITORS_TWOWAY) {
groupSize = state.parameters.getInt(base.push(P_GROUP_SIZE), null, 1);
if (groupSize < 1) {
state.output.fatal("Incorrect value for parameter", base.push(P_GROUP_SIZE));
}
}
allowOverEvaluation = state.parameters.getBoolean(base.push(P_OVER_EVAL), null, false);
}
public void setup(final EvolutionState state, final Parameter base) {
super.setup(state, base);
Parameter def = defaultBase();
// we use size distributions -- did the user specify any?
if (!canPick())
state.output.fatal(
"PTC2 needs a distribution of tree sizes to pick from. You can do this by either setting a distribution (with "
+ P_NUMSIZES
+ ") or with "
+ P_MINSIZE
+ " and "
+ P_MAXSIZE
+ ".",
base,
def);
maxDepth = state.parameters.getInt(base.push(P_MAXDEPTH), def.push(P_MAXDEPTH), 1);
if (maxDepth < 1)
state.output.fatal("Maximum depth must be >= 1", base.push(P_MAXDEPTH), def.push(P_MAXDEPTH));
}
/** Sets up parameters. */
public void setup(final EvolutionState state, final Parameter base) {
if (!(state instanceof EvolutionAgent))
state.output.fatal("DRMStatistics requires an EvolutionAgent", null, null);
EvolutionAgent agent = (EvolutionAgent) state;
super.setup(state, base);
frequency = state.parameters.getIntWithDefault(base.push(P_FREQUENCY), null, 1);
store_best = state.parameters.getBoolean(base.push(P_STORE_BEST), null, true);
// use_collective = state.parameters.getBoolean(base.push(P_COLLECTIVE),null,true);
// If we are root, set up the base filename and the logtable
if (agent.iamroot) {
// I'm not sure that outputting everything to the current directory is right
basefilename =
System.getProperty("user.dir")
+ File.separator
+ state.parameters.getFile(base.push(P_STATISTICS_FILE), null).getName();
logtable = new Hashtable();
} else defaultlog = -3; // Maybe can be useful for recognizing it as a non valid log
creationtime = System.currentTimeMillis();
}
public void setup(final EvolutionState state, final Parameter base) {
super.setup(state, base);
Parameter def = defaultBase();
double val = state.parameters.getDouble(base.push(P_SIZE), def.push(P_SIZE), 1.0);
if (val < 1.0)
state.output.fatal("Tournament size must be >= 1.", base.push(P_SIZE), def.push(P_SIZE));
else if (val > 1 && val < 2) // pick with probability
{
size = 2;
probabilityOfSelection = (val / 2);
} else if (val != (int) val) // it's not an integer
state.output.fatal(
"If >= 2, Tournament size must be an integer.", base.push(P_SIZE), def.push(P_SIZE));
else {
size = (int) val;
probabilityOfSelection = 1.0;
}
val = state.parameters.getDouble(base.push(P_SIZE2), def.push(P_SIZE2), 1.0);
if (val < 1.0)
state.output.fatal("Tournament size2 must be >= 1.", base.push(P_SIZE2), def.push(P_SIZE2));
else if (val > 1 && val < 2) // pick with probability
{
size2 = 2;
probabilityOfSelection2 = (val / 2);
} else if (val != (int) val) // it's not an integer
state.output.fatal(
"If >= 2, Tournament size2 must be an integer.", base.push(P_SIZE2), def.push(P_SIZE2));
else {
size2 = (int) val;
probabilityOfSelection2 = 1.0;
}
doLengthFirst =
state.parameters.getBoolean(base.push(P_DOLENGTHFIRST), def.push(P_DOLENGTHFIRST), true);
pickWorst = state.parameters.getBoolean(base.push(P_PICKWORST), def.push(P_PICKWORST), false);
pickWorst2 =
state.parameters.getBoolean(base.push(P_PICKWORST2), def.push(P_PICKWORST2), false);
}
public void setup(final EvolutionState state, final Parameter base) {
super.setup(state, base);
Parameter def = defaultBase();
// create the arrays
minGenes = new double[genomeSize];
maxGenes = new double[genomeSize];
// LOADING GLOBAL MIN/MAX GENES
double minGene =
state.parameters.getDoubleWithDefault(base.push(P_MINGENE), def.push(P_MINGENE), 0);
double maxGene = state.parameters.getDouble(base.push(P_MAXGENE), def.push(P_MAXGENE), minGene);
if (maxGene < minGene)
state.output.fatal(
"FloatVectorSpecies must have a default min-gene which is <= the default max-gene",
base.push(P_MAXGENE),
def.push(P_MAXGENE));
for (int x = 0; x < genomeSize; x++) {
minGenes[x] = minGene;
maxGenes[x] = maxGene;
}
// LOADING SEGMENTS
// Set number of segments to 0 by default
int numSegments = 0;
// Now check to see if segments of genes (genes having the same min and
// max values) exist
if (state.parameters.exists(base.push(P_NUM_SEGMENTS), def.push(P_NUM_SEGMENTS))) {
numSegments =
state.parameters.getIntWithDefault(
base.push(P_NUM_SEGMENTS), def.push(P_NUM_SEGMENTS), 0);
if (numSegments == 0)
state.output.warning(
"The number of genome segments has been defined to be equal to 0.\n"
+ "Hence, no genome segments will be defined.",
base.push(P_NUM_SEGMENTS),
def.push(P_NUM_SEGMENTS));
else if (numSegments < 0)
state.output.fatal(
"Invalid number of genome segments: "
+ numSegments
+ "\nIt must be a nonnegative value.",
base.push(P_NUM_SEGMENTS),
def.push(P_NUM_SEGMENTS));
// read the type of segment definition using the default start value
String segmentType =
state.parameters.getStringWithDefault(
base.push(P_SEGMENT_TYPE), def.push(P_SEGMENT_TYPE), P_SEGMENT_START);
if (segmentType.equalsIgnoreCase(P_SEGMENT_START))
initializeGenomeSegmentsByStartIndices(state, base, def, numSegments, minGene, maxGene);
else if (segmentType.equalsIgnoreCase(P_SEGMENT_END))
initializeGenomeSegmentsByEndIndices(state, base, def, numSegments, minGene, maxGene);
else
state.output.fatal(
"Invalid specification of genome segment type: "
+ segmentType
+ "\nThe "
+ P_SEGMENT_TYPE
+ " parameter must have the value of "
+ P_SEGMENT_START
+ " or "
+ P_SEGMENT_END,
base.push(P_SEGMENT_TYPE),
def.push(P_SEGMENT_TYPE));
}
// LOADING PER-GENE VALUES
boolean foundStuff = false;
boolean warnedMin = false;
boolean warnedMax = false;
for (int x = 0; x < genomeSize; x++) {
if (!state.parameters.exists(
base.push(P_MINGENE).push("" + x), def.push(P_MINGENE).push("" + x))) {
if (foundStuff && !warnedMin) {
state.output.warning(
"FloatVectorSpecies has missing min-gene values for some genes.\n"
+ "The first one is gene #"
+ x
+ ".",
base.push(P_MINGENE).push("" + x),
def.push(P_MINGENE).push("" + x));
warnedMin = true;
}
} else {
minGenes[x] =
state.parameters.getDoubleWithDefault(
base.push(P_MINGENE).push("" + x), def.push(P_MINGENE).push("" + x), minGene);
foundStuff = true;
}
if (!state.parameters.exists(
base.push(P_MAXGENE).push("" + x), def.push(P_MAXGENE).push("" + x))) {
if (foundStuff && !warnedMax) {
state.output.warning(
"FloatVectorSpecies has missing max-gene values for some genes.\n"
+ "The first one is gene #"
+ x
+ ".",
base.push(P_MAXGENE).push("" + x),
def.push(P_MAXGENE).push("" + x));
warnedMax = true;
}
} else {
maxGenes[x] =
state.parameters.getDoubleWithDefault(
base.push(P_MAXGENE).push("" + x), def.push(P_MAXGENE).push("" + x), maxGene);
foundStuff = true;
}
}
// VERIFY
for (int x = 0; x < genomeSize; x++) {
if (maxGenes[x] != maxGenes[x]) // uh oh, NaN
state.output.fatal("FloatVectorSpecies found that max-gene[" + x + "] is NaN");
if (minGenes[x] != minGenes[x]) // uh oh, NaN
state.output.fatal("FloatVectorSpecies found that min-gene[" + x + "] is NaN");
if (maxGenes[x] < minGenes[x])
state.output.fatal(
"FloatVectorSpecies must have a min-gene["
+ x
+ "] which is <= the max-gene["
+ x
+ "]");
// check to see if these longs are within the data type of the particular individual
if (!inNumericalTypeRange(minGenes[x]))
state.output.fatal(
"This FloatvectorSpecies has a prototype of the kind: "
+ i_prototype.getClass().getName()
+ ", but doesn't have a min-gene["
+ x
+ "] value within the range of this prototype's genome's data types");
if (!inNumericalTypeRange(maxGenes[x]))
state.output.fatal(
"This FloatvectorSpecies has a prototype of the kind: "
+ i_prototype.getClass().getName()
+ ", but doesn't have a max-gene["
+ x
+ "] value within the range of this prototype's genome's data types");
}
/// OTHER SETUP
String mtype =
state.parameters.getStringWithDefault(base.push(P_MUTATIONTYPE), null, V_RESET_MUTATION);
mutationType = C_RESET_MUTATION;
if (mtype == null)
state.output.warning(
"No mutation type given for VectorSpecies, assuming 'reset' mutation",
base.push(P_MUTATIONTYPE),
def.push(P_MUTATIONTYPE));
else if (mtype.equalsIgnoreCase(V_RESET_MUTATION)) mutationType = C_RESET_MUTATION; // redundant
else if (mtype.equalsIgnoreCase(V_GAUSS_MUTATION)) mutationType = C_GAUSS_MUTATION;
else
state.output.fatal(
"FloatVectorSpecies given a bad mutation type: " + mtype,
base.push(P_MUTATIONTYPE),
def.push(P_MUTATIONTYPE));
if (mutationType == C_GAUSS_MUTATION) {
double gaussMutationStdev =
state.parameters.getDouble(base.push(P_STDEV), def.push(P_STDEV), 0);
if (gaussMutationStdev <= 0)
state.output.fatal(
"If it's going to use gaussian mutation, FloatvectorSpecies must have a strictly positive standard deviation",
base.push(P_STDEV),
def.push(P_STDEV));
gaussMutationStdevs = new double[genomeSize];
double defaultRange = maxGene - minGene;
double defaultStdev = gaussMutationStdev;
double defaultStdevOverRange = defaultStdev / defaultRange;
for (int x = 0; x < genomeSize; x++) {
gaussMutationStdevs[x] = defaultStdevOverRange * (maxGene(x) - minGene((x)));
}
outOfRangeRetries =
state.parameters.getIntWithDefault(
base.push(P_OUTOFBOUNDS_RETRIES), def.push(P_OUTOFBOUNDS_RETRIES), outOfRangeRetries);
if (outOfRangeRetries < 0) {
state.output.fatal(
"If it's going to use gaussian mutation, FloatvectorSpecies must have a positive number of out-of-bounds retries or 0 (for don't give up)",
base.push(P_OUTOFBOUNDS_RETRIES),
def.push(P_OUTOFBOUNDS_RETRIES));
}
}
/*
//Debugging
for(int i = 0; i < minGenes.length; i++)
System.out.println("Min: " + minGenes[i] + ", Max: " + maxGenes[i]);
*/
}
/** Sets up all the GEPSymbolSet symbols, loading them from the parameter file. */
public void setup(
final EvolutionState state, final Parameter base, final Parameter def, GEPSpecies species) {
// Name of file with the terminal (variable) definitions and training values
String terminalFilename;
// Name of file with the test data values if specified
String testingTerminalFilename;
// keep track of the maximum arity of any function
maxArity = 0;
// What's my name? Don't really use this at this time ...
name = state.parameters.getString(base.push(P_NAME), def.push(P_NAME));
if (name == null || name.equals(""))
state.output.warning(
"No name was given for this GEP symbol set...not required at this time.",
base.push(P_NAME),
def.push(P_NAME));
// How many functions do I have?
numberOfFunctions =
state.parameters.getInt(base.push(P_FUNCTIONSIZE), def.push(P_FUNCTIONSIZE), 1);
numberOfSymbols = numberOfFunctions;
// How many terminals do I have? Check for a data file first ...
// if time series problem type and using raw time series data then
// number of terminals will be specified in the embedding dimension value
// provided in the parameter file
// else if a file specified
// get the 1st line of the file and count the fields in it (#terminals is number of fields
// minus
// the number of chromosomes/dependent variables)
// else
// use the number of terminals specified in the parameter file
terminalFilename =
state.parameters.getStringWithDefault(
base.push(P_TERMINALFILENAME), def.push(P_TERMINALFILENAME), "");
testingTerminalFilename =
state.parameters.getStringWithDefault(
base.push(P_TESTINGTERMINALFILENAME), def.push(P_TESTINGTERMINALFILENAME), "");
String terminalSymbolsfromFile[] = null;
CsvReader terminalFileCSV = null;
CsvReader testingTerminalFileCSV = null;
// Are we processing raw time series data?
boolean timeseriesWithRawDataValues =
species.problemType == GEPSpecies.PT_TIMESERIES && species.timeseriesEmbeddingDimension > 0;
if (!terminalFilename.equals("")) {
String defaultTerminalFileSeparator = ","; // default field separator is comma
try {
// allow for gzip files .... end with .gz or .gzip\
if (terminalFilename.endsWith(".gz") || terminalFilename.endsWith(".gzip")) {
terminalFileCSV =
new CsvReader(
(InputStream) (new GZIPInputStream(new FileInputStream(terminalFilename))),
Charset.forName("ISO-8859-1"));
// set terminal file name to be the one with gzip or gz removed from the end
if (terminalFilename.endsWith(".gz"))
terminalFilename = terminalFilename.substring(0, terminalFilename.length() - 3);
else terminalFilename = terminalFilename.substring(0, terminalFilename.length() - 5);
} else terminalFileCSV = new CsvReader(terminalFilename);
} catch (FileNotFoundException e) {
state.output.fatal(
"The file with terminal definitions and/or values ("
+ terminalFilename
+ ") could not be found",
base.push(P_TERMINALFILENAME),
def.push(P_TERMINALFILENAME));
} catch (IOException e) {
state.output.fatal(
"The file with terminal definitions and/or values ("
+ terminalFilename
+ ") could not be found or the expected GZIP file could nor be opened",
base.push(P_TERMINALFILENAME),
def.push(P_TERMINALFILENAME));
}
// if filename has extension .dat it is space delimited, if .csv (or anything else
// for that matter) it is comma delimited
// (separator can still be changed with the terminalfileseparator parameter)
if (terminalFilename.endsWith(".dat")) defaultTerminalFileSeparator = "space";
// if using a file for the terminals and their values then check for a non-default separator
String terminalFileSeparator =
state.parameters.getStringWithDefault(
base.push(P_TERMINALFILESEPARATOR),
def.push(P_TERMINALFILESEPARATOR),
defaultTerminalFileSeparator);
if (terminalFileSeparator.toLowerCase().equals("comma")) terminalFileSeparator = ",";
else if (terminalFileSeparator == "\\t" || terminalFileSeparator.toLowerCase().equals("tab"))
terminalFileSeparator = "\t";
else if (terminalFileSeparator == "space") terminalFileSeparator = " ";
terminalFileCSV.setDelimiter(terminalFileSeparator.charAt(0));
// let's check for a testing data file at this time as well .. if no file for
// names and training data no need to worry about this one.
if (!testingTerminalFilename.equals("")) {
try {
// allow for gzip files .... end with .gz or .gzip\
if (testingTerminalFilename.endsWith(".gz") || testingTerminalFilename.endsWith(".gzip"))
testingTerminalFileCSV =
new CsvReader(
(InputStream)
(new GZIPInputStream(new FileInputStream(testingTerminalFilename))),
Charset.forName("ISO-8859-1"));
else testingTerminalFileCSV = new CsvReader(testingTerminalFilename);
testingTerminalFileCSV.setDelimiter(terminalFileSeparator.charAt(0));
} catch (FileNotFoundException e) {
state.output.fatal(
"The file with testing data values ("
+ testingTerminalFilename
+ ") could not be found",
base.push(P_TERMINALFILENAME),
def.push(P_TERMINALFILENAME));
} catch (IOException e) {
state.output.fatal(
"The file with testing data values ("
+ terminalFilename
+ ") could not be found or the expected GZIP file could nor be opened",
base.push(P_TERMINALFILENAME),
def.push(P_TERMINALFILENAME));
}
}
}
if (timeseriesWithRawDataValues) numberOfTerminals = species.timeseriesEmbeddingDimension;
else if (terminalFileCSV != null) {
// get the terminal symbols for the independent and dependent variables
try {
terminalFileCSV.readHeaders();
terminalSymbolsfromFile = terminalFileCSV.getHeaders();
} catch (IOException e) {
state.output.fatal(
"The file with variable (terminal) definitions and values ("
+ terminalFilename
+ ") failed to read the headers"
+ e,
base.push(P_TERMINALFILENAME),
def.push(P_TERMINALFILENAME));
}
// 1 less for each dependent variable (number of chromosomes) at the end
numberOfTerminals = terminalSymbolsfromFile.length - species.numberOfChromosomes;
if (numberOfTerminals < 1)
state.output.fatal(
"The file with terminal definitions and data values ("
+ terminalFilename
+ ") has no independent variables specified in record 1",
base.push(P_TERMINALFILENAME),
def.push(P_TERMINALFILENAME));
// if using a file for the terminals and their values then check for a non-default separator
} else {
numberOfTerminals =
state.parameters.getInt(base.push(P_TERMINALSIZE), def.push(P_TERMINALSIZE), 1);
}
numberOfSymbols += numberOfTerminals;
if (numberOfSymbols < 1)
state.output.error(
"The GEPSymbolSet \"" + name + "\" have at least 1 terminal symbol defined.",
base.push(P_TERMINALSIZE),
def.push(P_TERMINALSIZE));
// add a special Symbol for constants if we are using them ... it will be added to the
// end of the array of symbols!
if (species.useConstants) {
numberOfTerminals++; // special constant terminal
numberOfSymbols++;
}
symbols = new GEPSymbol[numberOfSymbols];
int numberOfSymbolsWithoutConstantSymbol = numberOfSymbols;
if (species.useConstants) // add the constant terminal symbol to the end
{
symbols[numberOfSymbols - 1] = (GEPSymbol) (new GEPConstantTerminalSymbol());
symbols[numberOfSymbols - 1].id = numberOfSymbols - 1;
numberOfSymbolsWithoutConstantSymbol--;
}
Parameter pTerminal = base.push(P_TERMINAL);
Parameter pdefTerminal = def.push(P_TERMINAL);
Parameter pFunction = base.push(P_FUNCTION);
Parameter pdefFunction = def.push(P_FUNCTION);
// create hashtable of names of terminals and hash table with names of functions
// so we can easily check that they are not duplicates
Hashtable functionHT = new Hashtable();
Hashtable terminalHT = new Hashtable();
// process the functions
for (int x = 0; x < numberOfFunctions; x++) {
Parameter pp = pFunction.push("" + x);
Parameter ppdef = pdefFunction.push("" + x);
String function = state.parameters.getStringWithDefault(pp, ppdef, "");
if (function.equals("")) // no name for the function
state.output.fatal("Invalid function specifier: '" + function + "'", pp, ppdef);
// make sure not specifying the same function more than once
if (functionHT.get(function) != null)
state.output.fatal(
"Function '" + function + "' was specified more than once in list of function symbols");
else functionHT.put(function, function);
GEPFunctionSymbol fs = null;
try {
Class classDefinition = Class.forName(LOCATION_OF_FUNCTION_CLASSES + "." + function);
fs = (GEPFunctionSymbol) classDefinition.newInstance();
} catch (InstantiationException e) {
state.output.fatal(
"Unable to create GEPFunctionSymbol class for function '" + function + "'. " + e);
} catch (IllegalAccessException e) {
state.output.fatal(
"Unable to create GEPFunctionSymbol class for function '" + function + "' " + e);
} catch (ClassNotFoundException e) {
state.output.fatal(
"Unable to create GEPFunctionSymbol class for function '" + function + "' " + e);
}
// if using a logical function must be a logical problem
if (fs.isLogicalFunction() && (species.problemType != GEPSpecies.PT_LOGICAL))
state.output.fatal(
"Can only use logical functions with a logical problem type. Function "
+ function
+ " is a logical function.",
pp,
ppdef);
// if using a numerical function must be an non logical problem
if (!fs.isLogicalFunction() && (species.problemType == GEPSpecies.PT_LOGICAL))
state.output.fatal(
"Can only use logical functions with a non logical problem type. Function "
+ function
+ " is a numerical function.",
pp,
ppdef);
symbols[x] = (GEPSymbol) fs;
// symbols[x].setup(state, base);
if (fs.arity < 1) state.output.fatal("Arity must be > 0 for a GEPTerminalSymbol)", pp, ppdef);
symbols[x].id = x;
int weight =
state.parameters.getInt(pp.push(P_FUNCTIONWEIGHT), ppdef.push(P_FUNCTIONWEIGHT), 1);
if (weight < 1) {
state.output.warning(
"Weight for GEP Function must be > 0; defaulting to 1)",
pp.push(P_FUNCTIONWEIGHT),
ppdef.push(P_FUNCTIONWEIGHT));
weight = 1;
}
symbols[x].weight = weight;
if (symbols[x].arity > maxArity) maxArity = symbols[x].arity;
}
// process the terminals ... defined by default for timeseries data, in the
// CSV file if specified and not timeseries, or in the params file if neither of those.
for (int x = numberOfFunctions;
x < numberOfSymbolsWithoutConstantSymbol;
x++) { // load the terminal symbols
int index = x - numberOfFunctions;
String terminal = "";
if (timeseriesWithRawDataValues) {
// terminals get default names v0, v1, v2, v3, ... vn-1
terminal = "v" + index;
} else if (terminalFileCSV == null) // terminals defined in param file
{
Parameter pp = pTerminal.push("" + index);
Parameter ppdef = pdefTerminal.push("" + index);
terminal = state.parameters.getStringWithDefault(pp, ppdef, "");
} else { // terminals defined in CSV file
terminal = terminalSymbolsfromFile[index];
}
if (terminal.equals("")) // no name for the terminal
state.output.fatal("Invalid terminal specifier: '" + terminal + "' for terminal # " + index);
// make sure not specifying the same function more than once
if (terminalHT.get(terminal) != null)
state.output.fatal(
"Terminal symbol (indep var) '"
+ terminal
+ "' was specified more than once in list of terminal symbols (independent variables)");
else terminalHT.put(terminal, terminal);
GEPTerminalSymbol ts = new GEPTerminalSymbol(terminal, this);
symbols[x] = (GEPSymbol) ts;
// symbols[x].setup(state, base);
if (ts.arity != 0) // cannot happen
state.output.fatal("Arity must be exactly 0 for a GEPTerminalSymbol)");
symbols[x].id = x;
symbols[x].weight = 1; // all Terminal symbols have weight of 1
}
// must be at least 1 Terminal symbol in the SymbolSet.
// If not then the user didn't specify the terminals in the param file or in the data file
if (numberOfTerminals < 1)
state.output.fatal(
"Must be at least one Terminal Symbol in the set of GEPSymbols\n"
+ "Either did not specify the terminal symbols in the param file or\n"
+ "did not specify the appropriate data file with the terminals specified in the first line.");
// collect the id's (indices) of the terminal and function symbols that
// are in the set of symbols
terminals = new int[numberOfTerminals];
int terminalNum = 0;
functions = new int[numberOfFunctions];
int functionNum = 0;
for (int x = 0; x < numberOfSymbols; x++) {
if (symbols[x] instanceof GEPConstantTerminalSymbol) terminals[terminalNum++] = x;
else if (symbols[x] instanceof GEPTerminalSymbol) terminals[terminalNum++] = x;
else if (symbols[x] instanceof GEPFunctionSymbol) functions[functionNum++] = x;
}
// collect the weights for symbols and terminals and normalize and cumulate them.
// Then we can use these arrays to pick appropriate symbols or terminals according to
// their weights ... using the RandomChooser.PickFromDistribution
cumulativeNormalizedSymbolWeights = new float[numberOfSymbols];
cumulativeNormalizedTerminalWeights = new float[numberOfTerminals];
cumulativeNormalizedFunctionWeights = new float[numberOfFunctions];
int j = 0, k = 0;
for (int i = 0; i < numberOfSymbols; i++) {
float weight = (float) (symbols[i].weight);
cumulativeNormalizedSymbolWeights[i] = weight;
if (symbols[i] instanceof GEPTerminalSymbol
|| symbols[i] instanceof GEPConstantTerminalSymbol)
cumulativeNormalizedTerminalWeights[j++] = weight;
if (symbols[i] instanceof GEPFunctionSymbol)
cumulativeNormalizedFunctionWeights[k++] = weight;
}
RandomChoice.organizeDistribution(cumulativeNormalizedSymbolWeights);
RandomChoice.organizeDistribution(cumulativeNormalizedTerminalWeights);
RandomChoice.organizeDistribution(cumulativeNormalizedFunctionWeights);
// use the 2/3 rule if fewer functions else the 1/2 rule (don't count the constant
// terminal here)
if (numberOfFunctions < (numberOfTerminals - (species.useConstants ? 1 : 0)))
probabilityOfChoosingFunction = 2.0 / 3.0;
else probabilityOfChoosingFunction = 0.5;
// ... and finally get the training and testing data values for the terminals and dependent
// variable
// and put them into the Terminal instances (creating a 'special' Terminal Symbol to
// hold the dependent variable training and testing values)
// If this is a time series problem AND we are using the raw time series data then
// we named the terminals v1, v2, ..., nn where n is the number of independent
// variables as specified in the embedding dimension (which) was used to
// determine the number of terminals. But we have to process the time series data
// to get the values for each terminal ... get the raw data from the CSV file
// if specified or from the user program ... then process it into rows of data
// representing the independent variables and the dependent variable.
//
// timeseries-delay -- if 1 uses each time series value, if 2 uses every other one, etc.
// timeseries-embeddingdimension -- determines the number of timeseries points to use
// as independent variables when transforming the set of time series data. Another
// data point is used as the dependent variable value. So the time series 'raw' data
// consisting of a list of single values is processed by splitting the data into
// groups (rows) of size embeddingdimension+1. From the end of the time series data
// embeddingdimension+1 values are chosen (if delay is 1 all values are chosen, if
// 2 every other one is chosen). The last value is the independent variable value.
// Then the next row is selected by moving 'delay'
// values from the end and chosing embeddingdimension+1 values. This is repeated
// until no more sets of size embeddingdimension+1 can be chosen. If this produces
// n sets of data then testingprediction of them are used for testing and
// (n - testingpredictions) are used for training.
//
// So if we had the data:
// 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21
// and delay was 1 and embeddingdimension was 4 then we'd process the set into
// the following 17 data sets. If testingpredictions was 6 then the 1st 11
// would be used for training and the last 6 for testing
// iv1 iv2 iv3 iv4 dv
// 1 2 3 4 5
// 2 3 4 5 6
// 3 4 5 6 7
// . . .
// 14 15 16 17 18
// 15 16 17 18 19
// 16 17 18 19 20
// 17 18 19 20 21
// If delay was 2 then 7 sets would be formed as:
// iv1 iv2 iv3 iv4 dv
// 1 3 5 7 9
// 3 5 7 9 11
// . . .
// 9 11 13 15 17
// 11 13 15 17 19
// 13 15 17 19 21
// timeseries-testingpredictions -- specifies the number of sets of data to devote to testing
if (timeseriesWithRawDataValues) {
GEPDependentVariable.symbol = "dependentVariable";
double rawTimeSeriesValues[] = null;
if (terminalFileCSV == null)
rawTimeSeriesValues = ((GEPProblem) state.evaluator.p_problem).getTimeSeriesDataValues();
else rawTimeSeriesValues = getRawTimeSeriesValuesFromCSVfile(state, terminalFileCSV);
if (rawTimeSeriesValues == null)
state.output.fatal("Unable to get time series data values from User Program or CSV file");
Vector values[] = processRawTimeSeriesValues(state, species, rawTimeSeriesValues);
// have an array of vectors; 1 vector for each indep variable and the dep variable(s)
for (int i = 0; i < values.length; i++) {
// get the values for training ... and testing (specified by timeseriesTestingPredictions)
int sizeOfTrainingData = values[i].size() - species.timeseriesTestingPredictions;
double v[] = new double[sizeOfTrainingData];
double testingV[] = new double[species.timeseriesTestingPredictions];
for (int m = 0; m < v.length; m++) v[m] = ((Double) values[i].elementAt(m)).doubleValue();
for (int n = 0; n < testingV.length; n++)
testingV[n] = ((Double) values[i].elementAt(n + sizeOfTrainingData)).doubleValue();
int depVarIndex = i - values.length + species.numberOfChromosomes;
if (depVarIndex >= 0) // last column(s) in file is(are) the dependent variable(s)
{
GEPDependentVariable.trainingData.setValues(v, depVarIndex);
GEPDependentVariable.testingData.setValues(testingV, depVarIndex);
} else {
((GEPTerminalSymbol) symbols[numberOfFunctions + i]).setTrainingValues(v);
((GEPTerminalSymbol) symbols[numberOfFunctions + i]).setTestingValues(testingV);
}
}
}
// else If there is a file with the terminals and dep variable(s) use this else ask for
// the values from the User Program (problem).
else if (terminalFileCSV != null) // terminals defined in CSV file
{
GEPDependentVariable.symbol = terminalSymbolsfromFile[terminalSymbolsfromFile.length - 1];
// get all the values into an array of vectors (each vector holds the values for a
// single terminal (dep or indep variable)
Vector values[] = new Vector[terminalSymbolsfromFile.length];
for (int i = 0; i < terminalSymbolsfromFile.length; i++) values[i] = new Vector();
try {
while (terminalFileCSV.readRecord()) {
for (int i = 0; i < terminalSymbolsfromFile.length; i++)
values[i].add(terminalFileCSV.get(i));
}
} catch (IOException e) {
state.output.fatal(
"The file with terminal definitions/values failed when reading records. " + e);
}
for (int i = 0; i < terminalSymbolsfromFile.length; i++) {
double v[] = new double[values[i].size()];
for (int m = 0; m < v.length; m++)
try {
v[m] = Double.parseDouble((String) values[i].elementAt(m));
} catch (Exception e) {
state.output.fatal(
"Failed trying to read a training data set value. The field is supposed to be a number but was the string '"
+ (String) values[i].elementAt(m)
+ "'.\n"
+ e);
}
int jj = terminalSymbolsfromFile.length - species.numberOfChromosomes;
if (i >= jj) // last column(s) in file is(are) the dependent variable(s)
GEPDependentVariable.trainingData.setValues(v, i - jj);
else ((GEPTerminalSymbol) symbols[numberOfFunctions + i]).setTrainingValues(v);
}
// get the testing data as well if a file was specified
if (testingTerminalFileCSV != null) // testing data defined in CSV file
{
// get all the values into an array of vectors (each vector holds the values for a
// single terminal (dep or indep variable)
Vector testingValues[] = new Vector[terminalSymbolsfromFile.length];
for (int i = 0; i < terminalSymbolsfromFile.length; i++) testingValues[i] = new Vector();
try {
while (testingTerminalFileCSV.readRecord()) {
for (int i = 0; i < terminalSymbolsfromFile.length; i++)
testingValues[i].add(testingTerminalFileCSV.get(i));
}
} catch (IOException e) {
state.output.fatal(
"The file with testing data values failed when reading records. "
+ "\nMake sure the file has the same column separators as the testing data file."
+ "\nAlso check that it has the same as the number of columns as the testing file"
+ e);
}
for (int i = 0; i < terminalSymbolsfromFile.length; i++) {
double v[] = new double[testingValues[i].size()];
for (int m = 0; m < v.length; m++)
try {
v[m] = Double.parseDouble((String) testingValues[i].elementAt(m));
} catch (Exception e) {
state.output.fatal(
"Failed trying to read a testing data set value. The field is supposed to be a number but was the string '"
+ (String) testingValues[i].elementAt(m)
+ "'.\n"
+ e);
}
int jj = terminalSymbolsfromFile.length - species.numberOfChromosomes;
if (i >= jj) // last column(s) in file is(are) the dependent variable(s)
GEPDependentVariable.testingData.setValues(v, i - jj);
else ((GEPTerminalSymbol) symbols[numberOfFunctions + i]).setTestingValues(v);
}
}
}
// else terminals were defined in the param file and no CSV file
// defined so .... ask User Problem for the values, training and testing (if there are any)
else {
GEPDependentVariable.symbol = "dependentVariable";
GEPProblem prob = (GEPProblem) state.evaluator.p_problem;
double vals[] = null;
for (int i = numberOfFunctions; i < numberOfSymbolsWithoutConstantSymbol; i++) {
GEPTerminalSymbol ts = (GEPTerminalSymbol) symbols[i];
vals = prob.getDataValues(ts.symbol);
if (vals == null)
state.output.fatal(
"Expecting user problem (GEPProblem/ProblemForm) to supply training data values for terminal symbol '"
+ ts
+ "'.");
ts.setTrainingValues(vals);
vals = prob.getTestingDataValues(ts.symbol);
if (vals != null) // don't have to supply testing data
ts.setTestingValues(vals);
}
// if just one dep var then ask user by requesting with getdataValues("dependentVariable")
// and if more than one dep var (more than 1 chromosome) then ask for dep variables
// with getDataValues("dependentVariable0"), getDataValues("dependentVariable1"), ...
for (int i = 0; i < species.numberOfChromosomes; i++) {
String depVarSym = GEPDependentVariable.symbol;
if (species.numberOfChromosomes > 1) depVarSym = depVarSym + i;
vals = prob.getDataValues(depVarSym);
if (vals == null)
state.output.fatal(
"Expecting user problem (GEPProblem/ProblemForm) to supply training data values for dependent variable '"
+ depVarSym
+ "'.");
GEPDependentVariable.trainingData.setValues(vals, i);
vals = prob.getTestingDataValues(depVarSym);
if (vals != null) // don't have to supply testing data
GEPDependentVariable.testingData.setValues(vals, i);
}
}
// Some checking of data values to ensure they meet the requirements for the various problem
// types.
// For all problem types need to make sure all indep vars and the dep var have the same number
// of values!
int numValues = GEPDependentVariable.trainingData.values[0].length;
for (int i = numberOfFunctions; i < numberOfSymbolsWithoutConstantSymbol; i++)
if (((GEPTerminalSymbol) symbols[i]).trainingValues.length != numValues)
state.output.fatal(
"Must have same number of values for all independent variables and the dependent variable."
+ "/nNumber of values for Dependent Variable is: "
+ numValues
+ "/nNumber of values for Independent Variable '"
+ symbols[i].symbol
+ "' is: "
+ ((GEPTerminalSymbol) symbols[i]).trainingValues.length);
// For Classification and logical problems all dependent variable values must be either 0 or 1
if (species.problemType == GEPSpecies.PT_CLASSIFICATION
|| species.problemType == GEPSpecies.PT_LOGICAL) {
double dvVals[] = GEPDependentVariable.trainingData.values[0];
for (int i = 0; i < numValues; i++)
if (dvVals[i] != 0.0 && dvVals[i] != 1.0)
state.output.fatal(
"For classification/logical problems all dependent variable values must be either 1 or 0.\nFound value "
+ dvVals[i]
+ " at index "
+ i
+ "in the values.");
}
// For Logical problems all independent variable values must be 0 or 1
if (species.problemType == GEPSpecies.PT_LOGICAL) { // for each indep variable symbol
for (int i = numberOfFunctions; i < numberOfSymbolsWithoutConstantSymbol; i++) {
double ivVals[] = ((GEPTerminalSymbol) symbols[i]).trainingValues;
for (int m = 0; m < numValues; m++)
if (ivVals[m] != 0.0 && ivVals[m] != 1.0)
state.output.fatal(
"For logical problems all independent variable values must be either 1 or 0.\nFound value "
+ ivVals[m]
+ " at index '"
+ m
+ "' in the variable '"
+ ((GEPTerminalSymbol) symbols[i]).symbol
+ "'.");
}
}
state.output.exitIfErrors();
}
public void setup(final EvolutionState state, final Parameter base) {
super.setup(state, base);
Parameter def = defaultBase();
Parameter p = base.push(P_NODESELECTOR).push("0");
Parameter d = def.push(P_NODESELECTOR).push("0");
nodeselect1 =
(GPNodeSelector) (state.parameters.getInstanceForParameter(p, d, GPNodeSelector.class));
nodeselect1.setup(state, p);
p = base.push(P_NODESELECTOR).push("1");
d = def.push(P_NODESELECTOR).push("1");
if (state.parameters.exists(p, d) && state.parameters.getString(p, d).equals(V_SAME))
// can't just copy it this time; the selectors
// use internal caches. So we have to clone it no matter what
nodeselect2 = (GPNodeSelector) (nodeselect1.clone());
else {
nodeselect2 =
(GPNodeSelector) (state.parameters.getInstanceForParameter(p, d, GPNodeSelector.class));
nodeselect2.setup(state, p);
}
numTries = state.parameters.getInt(base.push(P_NUM_TRIES), def.push(P_NUM_TRIES), 1);
if (numTries == 0)
state.output.fatal(
"GPCrossover Pipeline has an invalid number of tries (it must be >= 1).",
base.push(P_NUM_TRIES),
def.push(P_NUM_TRIES));
maxDepth = state.parameters.getInt(base.push(P_MAXDEPTH), def.push(P_MAXDEPTH), 1);
if (maxDepth == 0)
state.output.fatal(
"GPCrossover Pipeline has an invalid maximum depth (it must be >= 1).",
base.push(P_MAXDEPTH),
def.push(P_MAXDEPTH));
maxSize = NO_SIZE_LIMIT;
if (state.parameters.exists(base.push(P_MAXSIZE), def.push(P_MAXSIZE))) {
maxSize = state.parameters.getInt(base.push(P_MAXSIZE), def.push(P_MAXSIZE), 1);
if (maxSize < 1) state.output.fatal("Maximum tree size, if defined, must be >= 1");
}
tree1 = TREE_UNFIXED;
if (state.parameters.exists(base.push(P_TREE).push("" + 0), def.push(P_TREE).push("" + 0))) {
tree1 =
state.parameters.getInt(base.push(P_TREE).push("" + 0), def.push(P_TREE).push("" + 0), 0);
if (tree1 == -1) state.output.fatal("Tree fixed value, if defined, must be >= 0");
}
tree2 = TREE_UNFIXED;
if (state.parameters.exists(base.push(P_TREE).push("" + 1), def.push(P_TREE).push("" + 1))) {
tree2 =
state.parameters.getInt(base.push(P_TREE).push("" + 1), def.push(P_TREE).push("" + 1), 0);
if (tree2 == -1) state.output.fatal("Tree fixed value, if defined, must be >= 0");
}
tossSecondParent = state.parameters.getBoolean(base.push(P_TOSS), def.push(P_TOSS), false);
}
private void initializeGenomeSegmentsByEndIndices(
final EvolutionState state,
final Parameter base,
final Parameter def,
int numSegments,
double minGene,
double maxGene) {
boolean warnedMin = false;
boolean warnedMax = false;
double currentSegmentMinGeneValue = Double.MAX_VALUE;
double currentSegmentMaxGeneValue = Double.MIN_VALUE;
int previousSegmentEnd = -1;
int currentSegmentEnd = 0;
// iterate over segments and set genes values for each segment
for (int i = 0; i < numSegments; i++) {
// check if the segment data exist
if (state.parameters.exists(
base.push(P_SEGMENT).push("" + i).push(P_SEGMENT_END),
def.push(P_SEGMENT).push("" + i).push(P_SEGMENT_END))) {
// Read the index of the end gene specifying current segment
currentSegmentEnd =
state.parameters.getInt(
base.push(P_SEGMENT).push("" + i).push(P_SEGMENT_END),
def.push(P_SEGMENT).push("" + i).push(P_SEGMENT_END));
} else {
state.output.fatal(
"Genome segment "
+ i
+ " has not been defined!"
+ "\nYou must specify end indices for "
+ numSegments
+ " segment(s)",
base.push(P_SEGMENT).push("" + i).push(P_SEGMENT_END),
base.push(P_SEGMENT).push("" + i).push(P_SEGMENT_END));
}
// check if the end index is valid
if (currentSegmentEnd <= previousSegmentEnd || currentSegmentEnd >= genomeSize)
state.output.fatal(
"Invalid end index value for segment "
+ i
+ ": "
+ currentSegmentEnd
+ "\nThe value must be greater than "
+ previousSegmentEnd
+ " and smaller than "
+ genomeSize);
// check if the index of the final segment is equal to the genomeSize
if (i == numSegments - 1 && currentSegmentEnd != (genomeSize - 1))
state.output.fatal(
"Invalid end index value for the last segment "
+ i
+ ": "
+ currentSegmentEnd
+ "\nThe value must be equal to the index of the last gene in the genome: "
+ (genomeSize - 1));
// get min and max values of genes in this segment
if (!state.parameters.exists(
base.push(P_SEGMENT).push("" + i).push(P_MINGENE),
base.push(P_SEGMENT).push("" + i).push(P_MINGENE))) {
if (!warnedMin) {
state.output.warning(
"IntegerVectorSpecies has missing min-gene values for some segments.\n"
+ "The first segment is #"
+ i
+ ".",
base.push(P_SEGMENT).push("" + i),
base.push(P_SEGMENT).push("" + i));
warnedMin = true;
}
// the min-gene value has not been defined for this segment so assume the global min value
currentSegmentMinGeneValue = minGene;
} else // get the min value for this segment
{
currentSegmentMinGeneValue =
state.parameters.getDoubleWithDefault(
base.push(P_SEGMENT).push("" + i).push(P_MINGENE),
base.push(P_SEGMENT).push("" + i).push(P_MINGENE),
minGene);
// check if the value is in range
if (!inNumericalTypeRange(currentSegmentMinGeneValue))
state.output.error(
"This IntegerVectorSpecies has a prototype of the kind: "
+ i_prototype.getClass().getName()
+ ", but doesn't have a min-gene "
+ " value for segment "
+ i
+ " within the range of this prototype's genome's data types",
base.push(P_SEGMENT).push("" + i).push(P_MINGENE),
base.push(P_SEGMENT).push("" + i).push(P_MINGENE));
}
if (!state.parameters.exists(
base.push(P_SEGMENT).push("" + i).push(P_MAXGENE),
base.push(P_SEGMENT).push("" + i).push(P_MAXGENE))) {
if (!warnedMax) {
state.output.warning(
"IntegerVectorSpecies has missing max-gene values for some segments.\n"
+ "The first segment is #"
+ i
+ ".",
base.push(P_SEGMENT).push("" + i),
base.push(P_SEGMENT).push("" + i));
warnedMax = true;
}
// the max-gen value has not been defined for this segment so assume the global max value
currentSegmentMaxGeneValue = maxGene;
} else // get the max value for this segment
{
currentSegmentMaxGeneValue =
state.parameters.getDoubleWithDefault(
base.push(P_SEGMENT).push("" + i).push(P_MAXGENE),
base.push(P_SEGMENT).push("" + i).push(P_MAXGENE),
maxGene);
// check if the value is in range
if (!inNumericalTypeRange(currentSegmentMaxGeneValue))
state.output.fatal(
"This IntegerVectorSpecies has a prototype of the kind: "
+ i_prototype.getClass().getName()
+ ", but doesn't have a max-gene "
+ " value for segment "
+ i
+ " within the range of this prototype's genome's data types",
base.push(P_SEGMENT).push("" + i).push(P_MAXGENE),
base.push(P_SEGMENT).push("" + i).push(P_MAXGENE));
}
// check is min is smaller than or equal to max
if (currentSegmentMaxGeneValue < currentSegmentMinGeneValue)
state.output.fatal(
"IntegerVectorSpecies must have a min-gene value for segment "
+ i
+ " which is <= the max-gene value",
base.push(P_SEGMENT).push("" + i).push(P_MAXGENE),
base.push(P_SEGMENT).push("" + i).push(P_MAXGENE));
// and assign min and max values for all genes in this segment
for (int j = previousSegmentEnd + 1; j <= currentSegmentEnd; j++) {
minGenes[j] = currentSegmentMinGeneValue;
maxGenes[j] = currentSegmentMaxGeneValue;
}
previousSegmentEnd = currentSegmentEnd;
}
}
public void setup(final EvolutionState state, final Parameter base) {
super.setup(state, base);
Parameter def = defaultBase();
tossSecondParent = state.parameters.getBoolean(base.push(P_TOSS), def.push(P_TOSS), false);
}
public void setup(final EvolutionState state, final Parameter base) {
super.setup(state, base);
Parameter def = defaultBase();
int numSelects = state.parameters.getInt(base.push(P_NUMSELECTS), def.push(P_NUMSELECTS), 1);
if (numSelects == 0)
state.output.fatal(
"The number of MultiSelection sub-selection methods must be >= 1).",
base.push(P_NUMSELECTS),
def.push(P_NUMSELECTS));
// make our arrays
selects = new SelectionMethod[numSelects];
float total = 0.0f;
for (int x = 0; x < numSelects; x++) {
Parameter p = base.push(P_SELECT).push("" + x);
Parameter d = def.push(P_SELECT).push("" + x);
selects[x] =
(SelectionMethod) (state.parameters.getInstanceForParameter(p, d, SelectionMethod.class));
selects[x].setup(state, p);
// now check probability
if (selects[x].probability < 0.0)
state.output.error(
"MultiSelection select #" + x + " must have a probability >= 0.0",
p.push(P_PROB),
d.push(P_PROB));
else total += selects[x].probability;
}
state.output.exitIfErrors();
// Now check for valid probability
if (total <= 0.0)
state.output.fatal("MultiSelection selects do not sum to a positive probability", base);
if (total != 1.0) {
state.output.message("Must normalize probabilities for " + base);
for (int x = 0; x < numSelects; x++) selects[x].probability /= total;
}
// totalize
float tmp = 0.0f;
for (int x = 0; x < numSelects - 1; x++) // yes, it's off by one
{
tmp += selects[x].probability;
selects[x].probability = tmp;
}
selects[numSelects - 1].probability = 1.0f;
}
public void setup(final EvolutionState state, final Parameter base) {
Parameter def = defaultBase();
int size;
// do we load from a file?
loadInds = state.parameters.getFile(base.push(P_FILE), null);
// what species do we use?
species =
(Species)
state.parameters.getInstanceForParameter(
base.push(P_SPECIES), def.push(P_SPECIES), Species.class);
species.setup(state, base.push(P_SPECIES));
// how big should our subpopulation be?
size = state.parameters.getInt(base.push(P_SUBPOPSIZE), def.push(P_SUBPOPSIZE), 1);
if (size <= 0)
state.output.fatal(
"Subpopulation size must be an integer >= 1.\n",
base.push(P_SUBPOPSIZE),
def.push(P_SUBPOPSIZE));
// How often do we retry if we find a duplicate?
numDuplicateRetries = state.parameters.getInt(base.push(P_RETRIES), def.push(P_RETRIES), 0);
if (numDuplicateRetries < 0)
state.output.fatal(
"The number of retries for duplicates must be an integer >= 0.\n",
base.push(P_RETRIES),
def.push(P_RETRIES));
individuals = new Individual[size];
}
/** This must be called <i>after</i> the GPTypes have been set up. */
public final void setup(final EvolutionState state, final Parameter base) {
// What's my name?
name = state.parameters.getString(base.push(P_NAME), null);
if (name == null)
state.output.fatal("No name was given for this node constraints.", base.push(P_NAME));
// Register me
GPNodeConstraints old_constraints =
(GPNodeConstraints)
(((GPInitializer) state.initializer).nodeConstraintRepository.put(name, this));
if (old_constraints != null)
state.output.fatal(
"The GP node constraint \"" + name + "\" has been defined multiple times.",
base.push(P_NAME));
// What's my return type?
String s = state.parameters.getString(base.push(P_RETURNS), null);
if (s == null)
state.output.fatal(
"No return type given for the GPNodeConstraints " + name, base.push(P_RETURNS));
returntype = GPType.typeFor(s, state);
// Load probability of selection
if (state.parameters.exists(base.push(P_PROBABILITY), null)) {
float f = state.parameters.getFloat(base.push(P_PROBABILITY), null, 0);
if (f < 0)
state.output.fatal(
"The probability of selection is < 0, which is not valid.",
base.push(P_PROBABILITY),
null);
probabilityOfSelection = f;
} else probabilityOfSelection = DEFAULT_PROBABILITY;
// How many child types do I have?
int x = state.parameters.getInt(base.push(P_SIZE), null, 0);
if (x < 0)
state.output.fatal(
"The number of children types for the GPNodeConstraints " + name + " must be >= 0.",
base.push(P_SIZE));
childtypes = new GPType[x];
Parameter p = base.push(P_CHILD);
// Load my children
for (x = 0; x < childtypes.length; x++) {
s = state.parameters.getString(p.push("" + x), null);
if (s == null)
state.output.fatal(
"Type #" + x + " is not defined for the GPNodeConstraints " + name + ".",
base.push("" + x));
childtypes[x] = GPType.typeFor(s, state);
}
// ...because I promised when I called typeFor(...)
state.output.exitIfErrors();
}
public void setup(final EvolutionState state, final Parameter base) {
Parameter def = defaultBase();
terminalProbability =
state.parameters.getDoubleWithMax(
base.push(P_TERMINAL_PROBABILITY), def.push(P_TERMINAL_PROBABILITY), 0.0, 1.0);
if (terminalProbability == -1.0)
state.output.fatal(
"Invalid terminal probability for KozaNodeSelector ",
base.push(P_TERMINAL_PROBABILITY),
def.push(P_TERMINAL_PROBABILITY));
nonterminalProbability =
state.parameters.getDoubleWithMax(
base.push(P_NONTERMINAL_PROBABILITY), def.push(P_NONTERMINAL_PROBABILITY), 0.0, 1.0);
if (nonterminalProbability == -1.0)
state.output.fatal(
"Invalid nonterminal probability for KozaNodeSelector ",
base.push(P_NONTERMINAL_PROBABILITY),
def.push(P_NONTERMINAL_PROBABILITY));
rootProbability =
state.parameters.getDoubleWithMax(
base.push(P_ROOT_PROBABILITY), def.push(P_ROOT_PROBABILITY), 0.0, 1.0);
if (rootProbability == -1.0)
state.output.fatal(
"Invalid root probability for KozaNodeSelector ",
base.push(P_ROOT_PROBABILITY),
def.push(P_ROOT_PROBABILITY));
if (rootProbability + terminalProbability + nonterminalProbability > 1.0f)
state.output.fatal(
"The terminal, nonterminal, and root for KozaNodeSelector"
+ base
+ " may not sum to more than 1.0. ("
+ terminalProbability
+ " "
+ nonterminalProbability
+ " "
+ rootProbability
+ ")",
base);
reset();
}
public void setup(final EvolutionState state, final Parameter base) {
super.setup(state, base);
Parameter def = defaultBase();
Parameter p = base.push(P_NODESELECTOR).push("0");
Parameter d = def.push(P_NODESELECTOR).push("0");
nodeselect1 =
(GPNodeSelector) (state.parameters.getInstanceForParameter(p, d, GPNodeSelector.class));
nodeselect1.setup(state, p);
p = base.push(P_NODESELECTOR).push("1");
d = def.push(P_NODESELECTOR).push("1");
if (state.parameters.exists(p, d) && state.parameters.getString(p, d).equals(V_SAME))
// can't just copy it this time; the selectors
// use internal caches. So we have to clone it no matter what
nodeselect2 = (GPNodeSelector) (nodeselect1.clone());
else {
nodeselect2 =
(GPNodeSelector) (state.parameters.getInstanceForParameter(p, d, GPNodeSelector.class));
nodeselect2.setup(state, p);
}
numTries = state.parameters.getInt(base.push(P_NUM_TRIES), def.push(P_NUM_TRIES), 1);
if (numTries == 0)
state.output.fatal(
"GPCrossover Pipeline has an invalid number of tries (it must be >= 1).",
base.push(P_NUM_TRIES),
def.push(P_NUM_TRIES));
maxDepth = state.parameters.getInt(base.push(P_MAXDEPTH), def.push(P_MAXDEPTH), 1);
if (maxDepth == 0)
state.output.fatal(
"GPCrossover Pipeline has an invalid maximum depth (it must be >= 1).",
base.push(P_MAXDEPTH),
def.push(P_MAXDEPTH));
maxSize = NO_SIZE_LIMIT;
if (state.parameters.exists(base.push(P_MAXSIZE), def.push(P_MAXSIZE))) {
maxSize = state.parameters.getInt(base.push(P_MAXSIZE), def.push(P_MAXSIZE), 1);
if (maxSize < 1) state.output.fatal("Maximum tree size, if defined, must be >= 1");
}
tree1 = TREE_UNFIXED;
if (state.parameters.exists(base.push(P_TREE).push("" + 0), def.push(P_TREE).push("" + 0))) {
tree1 =
state.parameters.getInt(base.push(P_TREE).push("" + 0), def.push(P_TREE).push("" + 0), 0);
if (tree1 == -1) state.output.fatal("Tree fixed value, if defined, must be >= 0");
}
tree2 = TREE_UNFIXED;
if (state.parameters.exists(base.push(P_TREE).push("" + 1), def.push(P_TREE).push("" + 1))) {
tree2 =
state.parameters.getInt(base.push(P_TREE).push("" + 1), def.push(P_TREE).push("" + 1), 0);
if (tree2 == -1) state.output.fatal("Tree fixed value, if defined, must be >= 0");
}
tossSecondParent = state.parameters.getBoolean(base.push(P_TOSS), def.push(P_TOSS), false);
GPInitializer initializer = ((GPInitializer) state.initializer);
fs = initializer.treeConstraints[0].functionset;
templateTree = (GPNode) (((GPNode[]) fs.nodesByName.get("+"))[0]).lightClone();
GPNode left = (GPNode) (((GPNode[]) fs.nodesByName.get("*"))[0]).lightClone();
GPNode right = (GPNode) (((GPNode[]) fs.nodesByName.get("*"))[0]).lightClone();
// RegERC ercNode1 = (RegERC)((((GPNode[])fs.nodesByName.get("ERC"))[0]).lightClone());
//
// generate TR node that will be replated by random tree
// GPNode TRNode = new GPNode();
// ercNode.constraints = 6;
// ercNode.children = new GPNode[0];
templateTree.children = new GPNode[2];
templateTree.children[0] = left;
templateTree.children[1] = right;
left.children = new GPNode[2];
left.children[0] = null;
left.children[1] = null;
right.children = new GPNode[2];
right.children[0] = null;
right.children[1] = null;
}
/** Read additional parameters for the spatially-embedded subpopulation. */
public void setup(final EvolutionState state, final Parameter base) {
super.setup(state, base);
// by default, the space is toroidal
toroidal = state.parameters.getBoolean(base.push(P_TOROIDAL), null, true);
}
