semeru/text-code-CodeSummarization · Datasets at Hugging Face

input stringlengths 10 828	output stringlengths 5 107
public void save file file throws ioexception write attribute weights file tools get default encoding	saves the attribute weights into an xml file
private void set title if hostname null try hostname inet address get local host get host name catch unknown host exception e hostname file file null if this process null synchronized process file this process get process file if file null set title title hostname file get name changed else set title title hostname	sets the window title rapid miner filename an asterisk if process was
public string to string return attribute weights containing weights for weight map size attributes	returns a string representation of this object
public object clone return new attribute weights this	returns a deep clone of the attribute weights which provides the same
public void normalize double weight min double positive infinity double weight max double negative infinity for string name get attribute names double weight math abs get weight name weight min math min weight min weight weight max math max weight max weight iterator attribute weight w weight map values iterator double diff weight max weight min while w has next attribute weight attribute weight w next double new weight 1 0d if diff 0 0d new weight math abs attribute weight get weight weight min diff attribute weight set weight new weight	this method normalizes all weights to the range 0 to 1
public component get visualization component iocontainer container data table data table create data table return new data table viewer data table plotter panel weight plotter selection	returns a visualisation component which allows sorting of the attribute
public string transform new value string value return value	this method will be invoked by the parameters after a parameter was set
public boolean is expert return is optional expert	returns true if this parameter can only be seen in expert mode
public void register dependency condition parameter condition condition this conditions add condition	registers the given dependency condition
public boolean is optional boolean become mandatory false for parameter condition condition conditions if condition dependency met become mandatory condition become mandatory else become mandatory false break return become mandatory	returns true if this parameter is optional
public string to string object value if value null return else return value to string	returns a string representation of this value
public void illegal value object illegal object corrected log service get global log illegal value illegal for parameter key has been corrected to corrected to string log service warning	can be called in order to report an illegal parameter value which is
public int compare to object o if o instanceof parameter type return 0 else return this key compare to parameter type o key	parameter types are compared by key
public configuration wizard creator get wizard creator configuration wizard creator creator null try creator wizard creator class new instance creator set parameters parameters catch instantiation exception e log service get global log problem during creation of wizard e get message log service warning catch illegal access exception e log service get global log problem during creation of wizard e get message log service warning return creator	returns a new instance of the wizard creator
public preview creator get preview creator preview creator creator null try creator preview creator class new instance catch instantiation exception e log service get global log problem during creation of previewer e get message log service warning catch illegal access exception e log service get global log problem during creation of previewer e get message log service warning return creator	returns a new instance of the wizard creator
public object clone parameters clone new parameters iterator string i key to value map key set iterator while i has next string key i next string value key to value map get key parameter type type key to type map get key if type null clone key to value map put key value i key to type map key set iterator while i has next string key i next clone key to type map put key key to type map get key clone keys clear for string key this keys clone keys add key return clone	performs a deep clone on this parameters object
public boolean set parameter string key string value boolean known type true if value null key to value map remove key else parameter type type key to type map get key if type null value type transform new value value known type true key to value map put key value return known type	sets the parameter for the given key after performing a range check
public void update recent file list recent files menu remove all list recent files rapid miner gui get recent files iterator i recent files iterator int j 1 while i has next final file recent file file i next jmenu item menu item new jmenu item j recent file get path menu item set mnemonic 0 j menu item add action listener new action listener public void action performed action event e open recent file recent files menu add menu item j	updates the list of recently used files
private void parse arguments string argv process file null for int i 0 i argv length i if argv i equals l show logo true else process file argv i if process file null print usage	parses the commandline arguments
public string get xml string indent boolean hide default string buffer result new string buffer iterator string i keys iterator while i has next string key i next string value key to value map get key parameter type type key to type map get key if type null result append type get xml indent key value hide default else result append indent parameter key key tvalue value to string tools get line separator return result to string	writes a portion of the xml configuration file specifying the parameters
public void write char bytes int offset int length throws ioexception for int i 0 i writer length i writer i write bytes offset length	implements the abstract method of the superclass
public void close throws ioexception for int i 0 i writer length i writer i close	closes all writers
public void add double value double weight if value map contains key value value map put value value map get value weight else value map put value weight	add a value with a weight to the set
public void flush throws ioexception for int i 0 i writer length i writer i flush	flushes all writers
public void add double value add value 1 0d	add a value to the set
public boolean contains double value return value map contains key value	returns whether the set contains the given value
public e get int index return array index	returns the array element at the specified single dimension
public int size return value map size	returns the number of values in the set
public double get mode double mode double na n double max weight double negative infinity for entry double double entry value map entry set double weight entry get value if weight max weight max weight weight mode entry get key return mode	returns the most common of the values in the set
public e get int indices return array get index indices	returns the array element at the position specified by the
public void set int index e e array index e	sets the array element at the specified single dimension
public void set int indices e e array get index indices e	sets the array element at the position specified by the given
public int get index int indices return sum product indices combinations	computes the single dimension array index from the given
public void write int b throws ioexception for int i 0 i out length i out i write b	implements the abstract method of the superclass
public void close throws ioexception for int i 0 i out length i if system out equals out i system err equals out i out i close	closes all writers
private int sum product int first indices int second indices int first length first indices length int second length second indices length int length second length first length first length second length int product 0 for int i 0 i length i product first indices i second indices i return product	calculates the sum product of two int arrays
public void flush throws ioexception for int i 0 i out length i out i flush	flushes all writers
public boolean is a int child int parent while child parent child parent id child if child 1 return false return true	returns true if child is a parent
public int map name string name for int i 0 i names length i if names i equals name return i return 1	maps the name of a class to its index or 1 if unknown
public string map index int index if index 0 index names length return names index else return null	maps an index to its name
public boolean is distance return true	this method returns a boolean wheter this measure is a distance measure
public double calculate distance example first example example second example attributes attributes first example get attributes double first values new double attributes size double second values new double attributes size int i 0 for attribute attribute attributes first values i first example get value attribute second values i second example get value attribute i return calculate distance first values second values	this is a convinient method for calculating the distance between examples
public double calculate similarity example first example example second example attributes attributes first example get attributes double first values new double attributes size double second values new double attributes size int i 0 for attribute attribute attributes first values i first example get value attribute second values i second example get value attribute i return calculate similarity first values second values	this is a convinient method for calculating the similarity between examples
public boolean accept element probability double not required elements counter double population counter if probability random value population counter not required elements counter return false else population counter probability 1 random value 1 random generator next double return true	include element in the sample
public void add vector average vector av vector list add av	adds a new average vector
public average vector get vector int index return vector list get index	returns the average vector with index i
public int size return averages list size	returns the number of averages in the list
public array list get vector list return vector list	returns all average vectors as list
public int size return vector list size	returns the number of average vectors
public average vector average try average vector output average vector get vector 0 clone for int i 1 i size i average vector av get vector i for int j 0 j av size j output get averagable j build average av get averagable j return output catch clone not supported exception e throw new runtime exception clone of average vector is not supported e get message	calculates the mean value of the averagables of the average vectors and
public averagable get averagable int index return averages list get index	returns the averagable by index
public double calculate distance double x1 double x2 return inner product x1 x2	subclasses must implement this method
public averagable get averagable string name iterator averagable i averages list iterator while i has next averagable a i next if a get name equals name return a return null	returns the averagable by name
public int get size return averages list size	returns the number of averagables in this vector
public double calculate distance double x1 double x2 k tanh a x y b double prod a inner product x1 x2 b double e1 math exp prod double e2 math exp prod return e1 e2 e1 e2	subclasses must implement this method
public double calculate distance double x1 double x2 return math exp this gamma norm2 x1 x2 gamma params gamma	calculates kernel value of vectors x and y
public double calculate distance double x1 double x2 double expression norm2 x1 x2 sigma if expression 1 return 0 0d else double minus 1 0d expression return math pow minus degree	calculates kernel value of vectors x and y
public void set polynomial parameters double degree double shift this degree degree this shift shift	sets the used polynomial parameters
public double calculate distance double x1 double x2 double prod inner product x1 x2 shift double result prod for int i 1 i degree i result prod return result	subclasses must implement this method
public void init example set example set this example set example set int example set size example set size if example set size 8000 this cache new full cache example set this else this cache new map based cache example set size	calculates all distances and store them in a matrix to speed up
public double get distance int x1 int x2 double result cache get x1 x2 if double is na n result result calculate distance get attribute values x1 get attribute values x2 cache store x1 x2 result return result	returns the distance between the examples with the given indices
public double calculate distance double x1 double x2 double norm2 norm2 x1 x2 double exp1 sigma1 0 0d 0 0d math exp 1 norm2 sigma1 double exp2 sigma2 0 0d 0 0d math exp 1 norm2 sigma2 double exp3 sigma3 0 0d 0 0d math exp 1 norm2 sigma3 return exp1 exp2 exp3	calculates kernel value of vectors x and y
public double calculate distance double x1 double x2 return math sqrt norm2 x1 x2 sigma shift shift	calculates kernel value of vectors x and y
public double inner product double x1 double x2 double result 0 0d for int i 0 i x1 length i result x1 i x2 i return result	calculates the inner product of the given vectors
public double norm2 double x1 double x2 double result 0 for int i 0 i x1 length i double factor x1 i x2 i result factor factor return result	calculates the l2 norm i
public double get sum collection support vectors double current x double sum 0 0d iterator i support vectors iterator while i has next support vector sv support vector i next sum sv get y sv get alpha calculate distance sv get x current x return sum	calculates w x from the given support vectors using this kernel function
public double get false positives return false positives	returns the number of false positives not the rate
public double get true positives return true positives	returns the number of true positives not the rate
public double get magnitude int n return 2 0d math sqrt real real imaginary imaginary n	normalizes the amplitude to the correct value
public void add all collection individual new individuals individuals add all new individuals	adds all individuals from the given collection
public void next iteration throws operator exception	this method is invoked after each evaluation
public void sort comparator individual comparator collections sort individuals comparator	sorts the individuals in ascending order according to their performance
protected population create initial population int pop size int individual size population init pop new population pop size individual size for int i 0 i pop size i double values new double individual size for int j 0 j values length j values j random next double in range min value max value init pop set values i values return init pop	creates the initial population
private void evaluate population population throws operator exception performance vector fitness values new performance vector population get number of individuals for int i 0 i fitness values length i double individual population get values i fitness values i evaluate individual individual population set fitness vector fitness values	calculates the fitness for all individuals and gives the fitness values
public int get generation return population get generation	returns the current generation
public double get best fitness in generation return population get best fitness in generation	returns the best fitness in the current generation
public double get best fitness ever return population get best fitness ever	returns the best fitness ever
public void enable actions if swing utilities is event dispatch thread enable actions now else swing utilities invoke later new runnable public void run enable actions now	enables and disables all actions according to the current state
public performance vector get best performance ever return population get best performance ever	returns the best performance vector ever
public double calculate double values reset for int i 0 i values length i update values i return get value	resets the counters and computes the aggregation function
public double calculate double values double weights reset if values length weights length return double na n for int i 0 i values length i update values i weights i return get value	resets the counters and computes the aggregation function
public double get best fitness in generation individual individual population get current best if individual null return individual get fitness values 0 else return double na n	returns the best fitness in the current generation
public double get best fitness ever individual individual population get best ever if individual null return individual get fitness values 0 else return double na n	returns the best fitness ever
public big integer get number of combinations left return num left	return number of combinations not yet generated
public performance vector get best performance ever individual individual population get best ever if individual null return individual get fitness else return null	returns the best performance vector ever
private population create min start population population population new population for int p 0 p this population size p double alphas new double this individual size for int j 0 j alphas length j alphas j this min j population add new individual alphas return population	randomly creates the initial population
private population create max start population population population new population for int p 0 p this population size p double alphas new double this individual size for int j 0 j alphas length j alphas j this max j population add new individual alphas return population	randomly creates the initial population
private population create fixed start population double fixed value population population new population for int p 0 p this population size p double alphas new double this individual size for int j 0 j alphas length j alphas j fixed value population add new individual alphas return population	randomly creates the initial population
public void remove menu int index menu bar remove menu bar get menu index	this methods provide plugins the possibility to modify the menus
public double get distance int point1 int point2 int dimensions double distance 0 for int i 0 i point1 length i int coord1 point1 i 0 dimensions i point1 i point1 i wrapping around if incoming coordinate is negative int coord2 point2 i 0 dimensions i point2 i point2 i double diff math min math abs coord1 coord2 coord1 dimensions i coord2 dimensions i distance diff diff distance math sqrt distance return distance	integer distance calculation regards the wrap around of the net hypertorus
private boolean is ok peak series int current int index if series current get magnitude series index get magnitude return false else return true	in the minimum case this method returns true if the current value is
public int get average count return this average count	returns the number of averagables used to create this averagable
public double get best threshold return best threshold	the best threshold will automatically be determined during the calculation of the
public component get visualization component iocontainer io container jpanel info panel new jpanel new flow layout flow layout left jtext pane info text new jtext pane info text set editable false info text set background info panel get background info text set font info text get font derive font font bold info text set text to result string info panel add info text info panel set border border factory create etched border return info panel	this default implementation returns a framed text pane containing the string
public boolean format percent return false	indicates wether or not percentage format should be used in the
public object clone return new group tree this	returns a deep clone of this tree
public string get main group name if get parent null return root else if get parent get parent null return get name else return get parent get main group name	returns the main group name i
private void set parent group tree parent this parent parent	sets the parent of this group
private group tree get parent return parent	returns the parent of this group
public double next double in range double lower bound double upper bound if upper bound lower bound throw new illegal argument exception random generator next double in range the upper bound of the random number range should be greater than the lower bound return next double upper bound lower bound lower bound	returns the next pseudorandom uniformly distributed code double code

public void save file file throws ioexception write attribute weights file tools get default encoding

saves the attribute weights into an xml file

private void set title if hostname null try hostname inet address get local host get host name catch unknown host exception e hostname file file null if this process null synchronized process file this process get process file if file null set title title hostname file get name changed else set title title hostname

sets the window title rapid miner filename an asterisk if process was

public string to string return attribute weights containing weights for weight map size attributes

returns a string representation of this object

public object clone return new attribute weights this

returns a deep clone of the attribute weights which provides the same

public void normalize double weight min double positive infinity double weight max double negative infinity for string name get attribute names double weight math abs get weight name weight min math min weight min weight weight max math max weight max weight iterator attribute weight w weight map values iterator double diff weight max weight min while w has next attribute weight attribute weight w next double new weight 1 0d if diff 0 0d new weight math abs attribute weight get weight weight min diff attribute weight set weight new weight

this method normalizes all weights to the range 0 to 1

public component get visualization component iocontainer container data table data table create data table return new data table viewer data table plotter panel weight plotter selection

returns a visualisation component which allows sorting of the attribute

public string transform new value string value return value

this method will be invoked by the parameters after a parameter was set

public boolean is expert return is optional expert

returns true if this parameter can only be seen in expert mode

public void register dependency condition parameter condition condition this conditions add condition

registers the given dependency condition

public boolean is optional boolean become mandatory false for parameter condition condition conditions if condition dependency met become mandatory condition become mandatory else become mandatory false break return become mandatory

returns true if this parameter is optional

public string to string object value if value null return else return value to string

returns a string representation of this value

public void illegal value object illegal object corrected log service get global log illegal value illegal for parameter key has been corrected to corrected to string log service warning

can be called in order to report an illegal parameter value which is

public int compare to object o if o instanceof parameter type return 0 else return this key compare to parameter type o key

parameter types are compared by key

public configuration wizard creator get wizard creator configuration wizard creator creator null try creator wizard creator class new instance creator set parameters parameters catch instantiation exception e log service get global log problem during creation of wizard e get message log service warning catch illegal access exception e log service get global log problem during creation of wizard e get message log service warning return creator

returns a new instance of the wizard creator

public preview creator get preview creator preview creator creator null try creator preview creator class new instance catch instantiation exception e log service get global log problem during creation of previewer e get message log service warning catch illegal access exception e log service get global log problem during creation of previewer e get message log service warning return creator

returns a new instance of the wizard creator

public object clone parameters clone new parameters iterator string i key to value map key set iterator while i has next string key i next string value key to value map get key parameter type type key to type map get key if type null clone key to value map put key value i key to type map key set iterator while i has next string key i next clone key to type map put key key to type map get key clone keys clear for string key this keys clone keys add key return clone

performs a deep clone on this parameters object

public boolean set parameter string key string value boolean known type true if value null key to value map remove key else parameter type type key to type map get key if type null value type transform new value value known type true key to value map put key value return known type

sets the parameter for the given key after performing a range check

public void update recent file list recent files menu remove all list recent files rapid miner gui get recent files iterator i recent files iterator int j 1 while i has next final file recent file file i next jmenu item menu item new jmenu item j recent file get path menu item set mnemonic 0 j menu item add action listener new action listener public void action performed action event e open recent file recent files menu add menu item j

updates the list of recently used files

private void parse arguments string argv process file null for int i 0 i argv length i if argv i equals l show logo true else process file argv i if process file null print usage

parses the commandline arguments

public string get xml string indent boolean hide default string buffer result new string buffer iterator string i keys iterator while i has next string key i next string value key to value map get key parameter type type key to type map get key if type null result append type get xml indent key value hide default else result append indent parameter key key tvalue value to string tools get line separator return result to string

writes a portion of the xml configuration file specifying the parameters

public void write char bytes int offset int length throws ioexception for int i 0 i writer length i writer i write bytes offset length

implements the abstract method of the superclass

public void close throws ioexception for int i 0 i writer length i writer i close

closes all writers

public void add double value double weight if value map contains key value value map put value value map get value weight else value map put value weight

add a value with a weight to the set

public void flush throws ioexception for int i 0 i writer length i writer i flush

flushes all writers

public void add double value add value 1 0d

add a value to the set

public boolean contains double value return value map contains key value

returns whether the set contains the given value

public e get int index return array index

returns the array element at the specified single dimension

public int size return value map size

returns the number of values in the set

public double get mode double mode double na n double max weight double negative infinity for entry double double entry value map entry set double weight entry get value if weight max weight max weight weight mode entry get key return mode

returns the most common of the values in the set

public e get int indices return array get index indices

returns the array element at the position specified by the

public void set int index e e array index e

sets the array element at the specified single dimension

public void set int indices e e array get index indices e

sets the array element at the position specified by the given

public int get index int indices return sum product indices combinations

computes the single dimension array index from the given

public void write int b throws ioexception for int i 0 i out length i out i write b

implements the abstract method of the superclass

public void close throws ioexception for int i 0 i out length i if system out equals out i system err equals out i out i close

closes all writers

private int sum product int first indices int second indices int first length first indices length int second length second indices length int length second length first length first length second length int product 0 for int i 0 i length i product first indices i second indices i return product

calculates the sum product of two int arrays

public void flush throws ioexception for int i 0 i out length i out i flush

flushes all writers

public boolean is a int child int parent while child parent child parent id child if child 1 return false return true

returns true if child is a parent

public int map name string name for int i 0 i names length i if names i equals name return i return 1

maps the name of a class to its index or 1 if unknown

public string map index int index if index 0 index names length return names index else return null

maps an index to its name

public boolean is distance return true

this method returns a boolean wheter this measure is a distance measure

public double calculate distance example first example example second example attributes attributes first example get attributes double first values new double attributes size double second values new double attributes size int i 0 for attribute attribute attributes first values i first example get value attribute second values i second example get value attribute i return calculate distance first values second values

this is a convinient method for calculating the distance between examples

public double calculate similarity example first example example second example attributes attributes first example get attributes double first values new double attributes size double second values new double attributes size int i 0 for attribute attribute attributes first values i first example get value attribute second values i second example get value attribute i return calculate similarity first values second values

this is a convinient method for calculating the similarity between examples

public boolean accept element probability double not required elements counter double population counter if probability random value population counter not required elements counter return false else population counter probability 1 random value 1 random generator next double return true

include element in the sample

public void add vector average vector av vector list add av

adds a new average vector

public average vector get vector int index return vector list get index

returns the average vector with index i

public int size return averages list size

returns the number of averages in the list

public array list get vector list return vector list

returns all average vectors as list

public int size return vector list size

returns the number of average vectors

public average vector average try average vector output average vector get vector 0 clone for int i 1 i size i average vector av get vector i for int j 0 j av size j output get averagable j build average av get averagable j return output catch clone not supported exception e throw new runtime exception clone of average vector is not supported e get message

calculates the mean value of the averagables of the average vectors and

public averagable get averagable int index return averages list get index

returns the averagable by index

public double calculate distance double x1 double x2 return inner product x1 x2

subclasses must implement this method

public averagable get averagable string name iterator averagable i averages list iterator while i has next averagable a i next if a get name equals name return a return null

returns the averagable by name

public int get size return averages list size

returns the number of averagables in this vector

public double calculate distance double x1 double x2 k tanh a x y b double prod a inner product x1 x2 b double e1 math exp prod double e2 math exp prod return e1 e2 e1 e2

subclasses must implement this method

public double calculate distance double x1 double x2 return math exp this gamma norm2 x1 x2 gamma params gamma

calculates kernel value of vectors x and y

public double calculate distance double x1 double x2 double expression norm2 x1 x2 sigma if expression 1 return 0 0d else double minus 1 0d expression return math pow minus degree

calculates kernel value of vectors x and y

public void set polynomial parameters double degree double shift this degree degree this shift shift

sets the used polynomial parameters

public double calculate distance double x1 double x2 double prod inner product x1 x2 shift double result prod for int i 1 i degree i result prod return result

subclasses must implement this method

public void init example set example set this example set example set int example set size example set size if example set size 8000 this cache new full cache example set this else this cache new map based cache example set size

calculates all distances and store them in a matrix to speed up

public double get distance int x1 int x2 double result cache get x1 x2 if double is na n result result calculate distance get attribute values x1 get attribute values x2 cache store x1 x2 result return result

returns the distance between the examples with the given indices

public double calculate distance double x1 double x2 double norm2 norm2 x1 x2 double exp1 sigma1 0 0d 0 0d math exp 1 norm2 sigma1 double exp2 sigma2 0 0d 0 0d math exp 1 norm2 sigma2 double exp3 sigma3 0 0d 0 0d math exp 1 norm2 sigma3 return exp1 exp2 exp3

calculates kernel value of vectors x and y

public double calculate distance double x1 double x2 return math sqrt norm2 x1 x2 sigma shift shift

calculates kernel value of vectors x and y

public double inner product double x1 double x2 double result 0 0d for int i 0 i x1 length i result x1 i x2 i return result

calculates the inner product of the given vectors

public double norm2 double x1 double x2 double result 0 for int i 0 i x1 length i double factor x1 i x2 i result factor factor return result

calculates the l2 norm i

public double get sum collection support vectors double current x double sum 0 0d iterator i support vectors iterator while i has next support vector sv support vector i next sum sv get y sv get alpha calculate distance sv get x current x return sum

calculates w x from the given support vectors using this kernel function

public double get false positives return false positives

returns the number of false positives not the rate

public double get true positives return true positives

returns the number of true positives not the rate

public double get magnitude int n return 2 0d math sqrt real real imaginary imaginary n

normalizes the amplitude to the correct value

public void add all collection individual new individuals individuals add all new individuals

adds all individuals from the given collection

public void next iteration throws operator exception

this method is invoked after each evaluation

public void sort comparator individual comparator collections sort individuals comparator

sorts the individuals in ascending order according to their performance

protected population create initial population int pop size int individual size population init pop new population pop size individual size for int i 0 i pop size i double values new double individual size for int j 0 j values length j values j random next double in range min value max value init pop set values i values return init pop

creates the initial population

private void evaluate population population throws operator exception performance vector fitness values new performance vector population get number of individuals for int i 0 i fitness values length i double individual population get values i fitness values i evaluate individual individual population set fitness vector fitness values

calculates the fitness for all individuals and gives the fitness values

public int get generation return population get generation

returns the current generation

public double get best fitness in generation return population get best fitness in generation

returns the best fitness in the current generation

public double get best fitness ever return population get best fitness ever

returns the best fitness ever

public void enable actions if swing utilities is event dispatch thread enable actions now else swing utilities invoke later new runnable public void run enable actions now

enables and disables all actions according to the current state

public performance vector get best performance ever return population get best performance ever

returns the best performance vector ever

public double calculate double values reset for int i 0 i values length i update values i return get value

resets the counters and computes the aggregation function

public double calculate double values double weights reset if values length weights length return double na n for int i 0 i values length i update values i weights i return get value

resets the counters and computes the aggregation function

public double get best fitness in generation individual individual population get current best if individual null return individual get fitness values 0 else return double na n

returns the best fitness in the current generation

public double get best fitness ever individual individual population get best ever if individual null return individual get fitness values 0 else return double na n

returns the best fitness ever

public big integer get number of combinations left return num left

return number of combinations not yet generated

public performance vector get best performance ever individual individual population get best ever if individual null return individual get fitness else return null

returns the best performance vector ever

private population create min start population population population new population for int p 0 p this population size p double alphas new double this individual size for int j 0 j alphas length j alphas j this min j population add new individual alphas return population

randomly creates the initial population

private population create max start population population population new population for int p 0 p this population size p double alphas new double this individual size for int j 0 j alphas length j alphas j this max j population add new individual alphas return population

randomly creates the initial population

private population create fixed start population double fixed value population population new population for int p 0 p this population size p double alphas new double this individual size for int j 0 j alphas length j alphas j fixed value population add new individual alphas return population

randomly creates the initial population

public void remove menu int index menu bar remove menu bar get menu index

this methods provide plugins the possibility to modify the menus

public double get distance int point1 int point2 int dimensions double distance 0 for int i 0 i point1 length i int coord1 point1 i 0 dimensions i point1 i point1 i wrapping around if incoming coordinate is negative int coord2 point2 i 0 dimensions i point2 i point2 i double diff math min math abs coord1 coord2 coord1 dimensions i coord2 dimensions i distance diff diff distance math sqrt distance return distance

integer distance calculation regards the wrap around of the net hypertorus

private boolean is ok peak series int current int index if series current get magnitude series index get magnitude return false else return true

in the minimum case this method returns true if the current value is

public int get average count return this average count

returns the number of averagables used to create this averagable

public double get best threshold return best threshold

the best threshold will automatically be determined during the calculation of the

public component get visualization component iocontainer io container jpanel info panel new jpanel new flow layout flow layout left jtext pane info text new jtext pane info text set editable false info text set background info panel get background info text set font info text get font derive font font bold info text set text to result string info panel add info text info panel set border border factory create etched border return info panel

this default implementation returns a framed text pane containing the string

public boolean format percent return false

indicates wether or not percentage format should be used in the

public object clone return new group tree this

returns a deep clone of this tree

public string get main group name if get parent null return root else if get parent get parent null return get name else return get parent get main group name

returns the main group name i

private void set parent group tree parent this parent parent

sets the parent of this group

private group tree get parent return parent

returns the parent of this group

public double next double in range double lower bound double upper bound if upper bound lower bound throw new illegal argument exception random generator next double in range the upper bound of the random number range should be greater than the lower bound return next double upper bound lower bound lower bound

returns the next pseudorandom uniformly distributed code double code