ikr.simlib.statistics

Class Statistics

java.lang.Object

ikr.simlib.statistics.Statistics

public class Statistics
extends java.lang.Object

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static interface	Statistics.Function<Input,Output> generic function with a single input and a single output parameter
static interface	Statistics.Predicate<Input> generic function that maps a single value to a boolean

Constructor Summary

Constructors

Constructor and Description
Statistics()

Method Summary

Methods

Modifier and Type	Method and Description
static <Key,Value> ConditionalUnweightedStatistic<Key,Value>	asConditionalStatistic(UnweightedSampleCollector<Value> stat) wraps an UnweightedSampleCollector so that it implements the interface ConditionalUnweightedStatistic.
static <Key,Value,Weight> ConditionalWeightedStatistic<Key,Value,Weight>	asConditionalStatistic(WeightedSampleCollector<Value,Weight> stat) wraps a WeightedSampleCollector so that it implements the interface ConditionalWeightedStatistic.
static <Key,Value,Weight> ConditionalWeightedStatistic<Key,Value,Weight>	asWeightedStatistic(ConditionalUnweightedStatistic<Key,Value> stat) wraps an UnweightedSampleCollector, so that it accepts a weight but ignores it
static <Value,Weight> WeightedSampleCollector<Value,Weight>	asWeightedStatistic(UnweightedSampleCollector<Value> stat) wraps an UnweightedSampleCollector, so that it accepts a weight but ignores it
static <Key,Value> ConditionalUnweightedStatistic<Key,Value>	combine(ConditionalUnweightedStatistic<? super Key,? super Value>... stats) combines multiple ConditionalUnweightedStatistic instances.
static <Key,Value,Weight> ConditionalWeightedStatistic<Key,Value,Weight>	combine(ConditionalWeightedStatistic<? super Key,? super Value,? super Weight>... stats) combines multiple ConditionalWeightedStatistic instances.
static <Value> UnweightedSampleCollector<Value>	combine(UnweightedSampleCollector<? super Value>... stats) combines multiple UnweightedSampleCollector instances.
static <Value,Weight> WeightedSampleCollector<Value,Weight>	combine(WeightedSampleCollector<? super Value,? super Weight>... stats) combines multiple WeightedSampleCollector instances.
static <Key,Value> ConditionalUnweightedStatistic<Key,Value>	combineCondUnweighted(java.util.Collection<ConditionalUnweightedStatistic<? super Key,? super Value>> stats) combines multiple ConditionalUnweightedStatistic instances.
static <Key,Value,Weight> ConditionalWeightedStatistic<Key,Value,Weight>	combineCondWeighted(java.util.Collection<ConditionalWeightedStatistic<? super Key,? super Value,? super Weight>> stats) combines multiple ConditionalWeightedStatistic instances.
static <Value> UnweightedSampleCollector<Value>	combineUnweighted(java.util.Collection<UnweightedSampleCollector<? super Value>> stats) combines multiple UnweightedSampleCollector instances.
static <Value,Weight> WeightedSampleCollector<Value,Weight>	combineWeighted(java.util.Collection<WeightedSampleCollector<? super Value,? super Weight>> stats) combines multiple WeightedSampleCollector instances.
static <Key,Value> ConditionalUnweightedStatistic<Key,Value>	filter(ConditionalUnweightedStatistic<Key,Value> stat, Statistics.Predicate<Value> filterFunction) Wraps a ConditionalUnweightedStatistic, so that calls to the update() method are only executed when the filterFunction returns true.
static <Key,Value,Weight> ConditionalWeightedStatistic<Key,Value,Weight>	filter(ConditionalWeightedStatistic<Key,Value,Weight> stat, Statistics.Predicate<Value> filterFunction) Wraps a ConditionalWeightedStatistic, so that calls to the update() method are only executed when the filterFunction returns true.
static <Value> UnweightedSampleCollector<Value>	filter(UnweightedSampleCollector<Value> stat, Statistics.Predicate<Value> filterFunction) Wraps an UnweightedSampleCollector, so that calls to the update() method are only executed when the filterFunction returns true.
static <Value,Weight> WeightedSampleCollector<Value,Weight>	filter(WeightedSampleCollector<Value,Weight> stat, Statistics.Predicate<Value> filterFunction) Wraps a WeightedSampleCollector, so that calls to the update() method are only executed when the filterFunction returns true.
static <Key,Value> ConditionalUnweightedStatistic<Key,Value>	filterByKey(ConditionalUnweightedStatistic<Key,Value> stat, Statistics.Predicate<Key> filterFunction) Wraps a ConditionalUnweightedStatistic, so that calls to the update() method are only executed when the filterFunction returns true.
static <Key,Value,Weight> ConditionalWeightedStatistic<Key,Value,Weight>	filterByKey(ConditionalWeightedStatistic<Key,Value,Weight> stat, Statistics.Predicate<Key> filterFunction) Wraps a ConditionalWeightedStatistic, so that calls to the update() method are only executed when the filterFunction returns true.
static <Key,Value,Weight> ConditionalWeightedStatistic<Key,Value,Weight>	filterByWeight(ConditionalWeightedStatistic<Key,Value,Weight> stat, Statistics.Predicate<Weight> filterFunction) Wraps a ConditionalWeightedStatistic, so that calls to the update() method are only executed when the filterFunction returns true.
static <Value,Weight> WeightedSampleCollector<Value,Weight>	filterByWeight(WeightedSampleCollector<Value,Weight> stat, Statistics.Predicate<Weight> filterFunction) Wraps a WeightedSampleCollector, so that calls to the update() method are only executed when the filterFunction returns true.
static <Value> UnweightedSampleCollector<Value>	ignoreValue(UnweightedSampleCollector<java.lang.Void> stat) wraps a UnweightedSampleCollector which accepts no values, so that it accepts any values but ignores those
static <Key,Input,Output> ConditionalUnweightedStatistic<Key,Input>	map(ConditionalUnweightedStatistic<Key,Output> stat, Statistics.Function<Input,Output> mapping) Wraps a ConditionalUnweightedStatistic which accepts values of type O, so that the result accepts values of type I.
static <Key,Input,Weight,Output> ConditionalWeightedStatistic<Key,Input,Weight>	map(ConditionalWeightedStatistic<Key,Output,Weight> stat, Statistics.Function<Input,Output> mapping) Wraps a ConditionalWeightedStatistic which accepts values of type O, so that the result accepts values of type I.
static <Input,Key,Value,Weight> UnweightedSampleCollector<Input>	map(ConditionalWeightedStatistic<Key,Value,Weight> stat, Statistics.Function<Input,Key> keyMapping, Statistics.Function<Input,Value> valueMapping, Statistics.Function<Input,Weight> weightMapping) Wraps a ConditionalWeightedStatistic, so that the result is an UnweightedSampleCollector.
static <Input,Output> UnweightedSampleCollector<Input>	map(UnweightedSampleCollector<Output> stat, Statistics.Function<Input,Output> mapping) Wraps an UnweightedSampleCollector which accepts values of type O, so that the result accepts values of type I.
static <Input,Output,Weight> WeightedSampleCollector<Input,Weight>	map(WeightedSampleCollector<Output,Weight> stat, Statistics.Function<Input,Output> mapping) Wraps a WeightedSampleCollector which accepts values of type O, so that the result accepts values of type I.
static <Input,Value,Weight> UnweightedSampleCollector<Input>	map(WeightedSampleCollector<Value,Weight> stat, Statistics.Function<Input,Value> valueMapping, Statistics.Function<Input,Weight> weightMapping) Wraps a WeightedSampleCollector which accepts values of type V and weights of type W, so that the result is an unweighted statistic which accepts values of type I.
static <Input,Value,Output> ConditionalUnweightedStatistic<Input,Value>	mapKey(ConditionalUnweightedStatistic<Output,Value> stat, Statistics.Function<Input,Output> mapping) Wraps a ConditionalUnweightedStatistic which accepts keys of type O, so that the result accepts keys of type I.
static <Input,Value,Weight,Output> ConditionalWeightedStatistic<Input,Value,Weight>	mapKey(ConditionalWeightedStatistic<Output,Value,Weight> stat, Statistics.Function<Input,Output> mapping) Wraps a ConditionalWeightedStatistic which accepts keys of type O, so that the result accepts keys of type I.
static <Key,Value,Input,Output> ConditionalWeightedStatistic<Key,Value,Input>	mapWeight(ConditionalWeightedStatistic<Key,Value,Output> stat, Statistics.Function<Input,Output> mapping) Wraps a ConditionalWeightedStatistic which accepts weights of type O, so that the result accepts weights of type I.
static <Input,Output,Value> WeightedSampleCollector<Value,Input>	mapWeight(WeightedSampleCollector<Value,Output> stat, Statistics.Function<Input,Output> mapping) Wraps a WeightedSampleCollector which accepts weights of type O, so that the result accepts weights of type I.
static <Value> UnweightedSampleCollector<Value>	weightOneDouble(WeightedSampleCollector<Value,java.lang.Double> stat) wraps a WeightedSampleCollector with weight of type double, so that it implements the interface UnweightedSampleCollector.
static <Value> UnweightedSampleCollector<Value>	weightOneLong(WeightedSampleCollector<Value,java.lang.Long> stat) wraps a WeightedSampleCollector with weight of type long, so that it implements the interface UnweightedSampleCollector.
static <Value> WeightedSampleCollector<Value,java.lang.Long>	weightToMultipleCalls(UnweightedSampleCollector<Value> stat) wraps an UnweightedSampleCollector, so that it accepts a weight.

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

Statistics

public Statistics()

Method Detail

ignoreValue

public static <Value> UnweightedSampleCollector<Value> ignoreValue(UnweightedSampleCollector<java.lang.Void> stat)

wraps a UnweightedSampleCollector which accepts no values, so that it accepts any values but ignores those

asWeightedStatistic

public static <Value,Weight> WeightedSampleCollector<Value,Weight> asWeightedStatistic(UnweightedSampleCollector<Value> stat)

wraps an UnweightedSampleCollector, so that it accepts a weight but ignores it

asWeightedStatistic

public static <Key,Value,Weight> ConditionalWeightedStatistic<Key,Value,Weight> asWeightedStatistic(ConditionalUnweightedStatistic<Key,Value> stat)

wraps an UnweightedSampleCollector, so that it accepts a weight but ignores it

asConditionalStatistic

public static <Key,Value> ConditionalUnweightedStatistic<Key,Value> asConditionalStatistic(UnweightedSampleCollector<Value> stat)

wraps an UnweightedSampleCollector so that it implements the interface ConditionalUnweightedStatistic. Each time the method update() is called, the key is ignored and the method update() of the UnweightedSampleCollector is called with the value.

asConditionalStatistic

public static <Key,Value,Weight> ConditionalWeightedStatistic<Key,Value,Weight> asConditionalStatistic(WeightedSampleCollector<Value,Weight> stat)

wraps a WeightedSampleCollector so that it implements the interface ConditionalWeightedStatistic. Each time the method update() is called, the key is ignored and the method update() of the WeightedSampleCollector is called with the value and the weight.

weightOneLong

public static <Value> UnweightedSampleCollector<Value> weightOneLong(WeightedSampleCollector<Value,java.lang.Long> stat)

wraps a WeightedSampleCollector with weight of type long, so that it implements the interface UnweightedSampleCollector. Each time the method update() is called, the method update() of the wrapped statistic is called with a weight set to one.

weightOneDouble

public static <Value> UnweightedSampleCollector<Value> weightOneDouble(WeightedSampleCollector<Value,java.lang.Double> stat)

wraps a WeightedSampleCollector with weight of type double, so that it implements the interface UnweightedSampleCollector. Each time the method update() is called, the method update() of the wrapped statistic is called with a weight set to one.

weightToMultipleCalls

public static <Value> WeightedSampleCollector<Value,java.lang.Long> weightToMultipleCalls(UnweightedSampleCollector<Value> stat)

wraps an UnweightedSampleCollector, so that it accepts a weight. The weight is converted to multiple calls of the update() method of the base statistic.

combineUnweighted

public static <Value> UnweightedSampleCollector<Value> combineUnweighted(java.util.Collection<UnweightedSampleCollector<? super Value>> stats)

combines multiple UnweightedSampleCollector instances. Each time the method update() of the wrapping statistic is called, the update() methods of each of the wrapped statistics is called with the same value.

combine

@SafeVarargs
public static <Value> UnweightedSampleCollector<Value> combine(UnweightedSampleCollector<? super Value>... stats)

combines multiple UnweightedSampleCollector instances. Each time the method update() of the wrapping statistic is called, the update() methods of each of the wrapped statistics is called with the same value.

combineWeighted

public static <Value,Weight> WeightedSampleCollector<Value,Weight> combineWeighted(java.util.Collection<WeightedSampleCollector<? super Value,? super Weight>> stats)

combines multiple WeightedSampleCollector instances. Each time the method update() of the wrapping statistic is called, the update() methods of each of the wrapped statistics is called with the same value and weight.

combine

@SafeVarargs
public static <Value,Weight> WeightedSampleCollector<Value,Weight> combine(WeightedSampleCollector<? super Value,? super Weight>... stats)

combines multiple WeightedSampleCollector instances. Each time the method update() of the wrapping statistic is called, the update() methods of each of the wrapped statistics is called with the same value and weight.

combineCondUnweighted

public static <Key,Value> ConditionalUnweightedStatistic<Key,Value> combineCondUnweighted(java.util.Collection<ConditionalUnweightedStatistic<? super Key,? super Value>> stats)

combines multiple ConditionalUnweightedStatistic instances. Each time the method update() of the wrapping statistic is called, the update() methods of each of the wrapped statistics is called with the same key and value.

combine

@SafeVarargs
public static <Key,Value> ConditionalUnweightedStatistic<Key,Value> combine(ConditionalUnweightedStatistic<? super Key,? super Value>... stats)

combines multiple ConditionalUnweightedStatistic instances. Each time the method update() of the wrapping statistic is called, the update() methods of each of the wrapped statistics is called with the same key and value.

combineCondWeighted

public static <Key,Value,Weight> ConditionalWeightedStatistic<Key,Value,Weight> combineCondWeighted(java.util.Collection<ConditionalWeightedStatistic<? super Key,? super Value,? super Weight>> stats)

combines multiple ConditionalWeightedStatistic instances. Each time the method update() of the wrapping statistic is called, the update() methods of each of the wrapped statistics is called with the same key, value, and weight.

combine

@SafeVarargs
public static <Key,Value,Weight> ConditionalWeightedStatistic<Key,Value,Weight> combine(ConditionalWeightedStatistic<? super Key,? super Value,? super Weight>... stats)

combines multiple ConditionalWeightedStatistic instances. Each time the method update() of the wrapping statistic is called, the update() methods of each of the wrapped statistics is called with the same key, value, and weight.

map

public static <Input,Output> UnweightedSampleCollector<Input> map(UnweightedSampleCollector<Output> stat,
                                                  Statistics.Function<Input,Output> mapping)

Wraps an UnweightedSampleCollector which accepts values of type O, so that the result accepts values of type I. The specified mapping function has the input type I and the output type O. It is used to convert each value.

map

public static <Input,Value,Weight> UnweightedSampleCollector<Input> map(WeightedSampleCollector<Value,Weight> stat,
                                                        Statistics.Function<Input,Value> valueMapping,
                                                        Statistics.Function<Input,Weight> weightMapping)

Wraps a WeightedSampleCollector which accepts values of type V and weights of type W, so that the result is an unweighted statistic which accepts values of type I. The first mapping function has the input type I and the output type V. It is used to convert each value. The second mapping function (types I, W) is used to map the input to the weight.

map

public static <Input,Output,Weight> WeightedSampleCollector<Input,Weight> map(WeightedSampleCollector<Output,Weight> stat,
                                                              Statistics.Function<Input,Output> mapping)

Wraps a WeightedSampleCollector which accepts values of type O, so that the result accepts values of type I. The specified mapping function has the input type I and the output type O. It is used to convert each value. The weight is not mapped.

mapWeight

public static <Input,Output,Value> WeightedSampleCollector<Value,Input> mapWeight(WeightedSampleCollector<Value,Output> stat,
                                                                  Statistics.Function<Input,Output> mapping)

Wraps a WeightedSampleCollector which accepts weights of type O, so that the result accepts weights of type I. The specified mapping function has the input type I and the output type O. It is used to convert each weight. The value is not mapped.

It is not allowed to use the update() method without weight any more. In case it is used, a runtime exception is thrown.

map

public static <Key,Input,Output> ConditionalUnweightedStatistic<Key,Input> map(ConditionalUnweightedStatistic<Key,Output> stat,
                                                               Statistics.Function<Input,Output> mapping)

Wraps a ConditionalUnweightedStatistic which accepts values of type O, so that the result accepts values of type I. The specified mapping function has the input type I and the output type O. It is used to convert each value. The key is not mapped.

mapKey

public static <Input,Value,Output> ConditionalUnweightedStatistic<Input,Value> mapKey(ConditionalUnweightedStatistic<Output,Value> stat,
                                                                      Statistics.Function<Input,Output> mapping)

Wraps a ConditionalUnweightedStatistic which accepts keys of type O, so that the result accepts keys of type I. The specified mapping function has the input type I and the output type O. It is used to convert each key. The value is not mapped.

map

public static <Key,Input,Weight,Output> ConditionalWeightedStatistic<Key,Input,Weight> map(ConditionalWeightedStatistic<Key,Output,Weight> stat,
                                                                           Statistics.Function<Input,Output> mapping)

Wraps a ConditionalWeightedStatistic which accepts values of type O, so that the result accepts values of type I. The specified mapping function has the input type I and the output type O. It is used to convert each value. The key and the weight are not mapped.

mapKey

public static <Input,Value,Weight,Output> ConditionalWeightedStatistic<Input,Value,Weight> mapKey(ConditionalWeightedStatistic<Output,Value,Weight> stat,
                                                                                  Statistics.Function<Input,Output> mapping)

Wraps a ConditionalWeightedStatistic which accepts keys of type O, so that the result accepts keys of type I. The specified mapping function has the input type I and the output type O. It is used to convert each key. The value and the weight are not mapped.

mapWeight

public static <Key,Value,Input,Output> ConditionalWeightedStatistic<Key,Value,Input> mapWeight(ConditionalWeightedStatistic<Key,Value,Output> stat,
                                                                               Statistics.Function<Input,Output> mapping)

Wraps a ConditionalWeightedStatistic which accepts weights of type O, so that the result accepts weights of type I. The specified mapping function has the input type I and the output type O. It is used to convert each weight. The key and the value are not mapped.

map

public static <Input,Key,Value,Weight> UnweightedSampleCollector<Input> map(ConditionalWeightedStatistic<Key,Value,Weight> stat,
                                                            Statistics.Function<Input,Key> keyMapping,
                                                            Statistics.Function<Input,Value> valueMapping,
                                                            Statistics.Function<Input,Weight> weightMapping)

Wraps a ConditionalWeightedStatistic, so that the result is an UnweightedSampleCollector. Key, value, and weight of the wrapped statistics are generated from the single input value of the UnweightedSampleCollector by three different functions.

filter

public static <Value> UnweightedSampleCollector<Value> filter(UnweightedSampleCollector<Value> stat,
                                              Statistics.Predicate<Value> filterFunction)

Wraps an UnweightedSampleCollector, so that calls to the update() method are only executed when the filterFunction returns true. The output of the filterFunction is a function of the value.

filter

public static <Value,Weight> WeightedSampleCollector<Value,Weight> filter(WeightedSampleCollector<Value,Weight> stat,
                                                          Statistics.Predicate<Value> filterFunction)

Wraps a WeightedSampleCollector, so that calls to the update() method are only executed when the filterFunction returns true. The output of the filterFunction is a function of the value.

filterByWeight

public static <Value,Weight> WeightedSampleCollector<Value,Weight> filterByWeight(WeightedSampleCollector<Value,Weight> stat,
                                                                  Statistics.Predicate<Weight> filterFunction)

Wraps a WeightedSampleCollector, so that calls to the update() method are only executed when the filterFunction returns true. The output of the filterFunction is a function of the weight.

It is not allowed to use the update() method without weight any more. In case it is used, a runtime exception is thrown.

filter

public static <Key,Value> ConditionalUnweightedStatistic<Key,Value> filter(ConditionalUnweightedStatistic<Key,Value> stat,
                                                           Statistics.Predicate<Value> filterFunction)

Wraps a ConditionalUnweightedStatistic, so that calls to the update() method are only executed when the filterFunction returns true. The output of the filterFunction is a function of the value.

filterByKey

public static <Key,Value> ConditionalUnweightedStatistic<Key,Value> filterByKey(ConditionalUnweightedStatistic<Key,Value> stat,
                                                                Statistics.Predicate<Key> filterFunction)

Wraps a ConditionalUnweightedStatistic, so that calls to the update() method are only executed when the filterFunction returns true. The output of the filterFunction is a function of the key.

filter

public static <Key,Value,Weight> ConditionalWeightedStatistic<Key,Value,Weight> filter(ConditionalWeightedStatistic<Key,Value,Weight> stat,
                                                                       Statistics.Predicate<Value> filterFunction)

Wraps a ConditionalWeightedStatistic, so that calls to the update() method are only executed when the filterFunction returns true. The output of the filterFunction is a function of the value.

filterByWeight

public static <Key,Value,Weight> ConditionalWeightedStatistic<Key,Value,Weight> filterByWeight(ConditionalWeightedStatistic<Key,Value,Weight> stat,
                                                                               Statistics.Predicate<Weight> filterFunction)

Wraps a ConditionalWeightedStatistic, so that calls to the update() method are only executed when the filterFunction returns true. The output of the filterFunction is a function of the weight.

filterByKey

public static <Key,Value,Weight> ConditionalWeightedStatistic<Key,Value,Weight> filterByKey(ConditionalWeightedStatistic<Key,Value,Weight> stat,
                                                                            Statistics.Predicate<Key> filterFunction)

Wraps a ConditionalWeightedStatistic, so that calls to the update() method are only executed when the filterFunction returns true. The output of the filterFunction is a function of the key.