## Class Integers

• ```public final class Integers
extends Object```
Utility methods for ints.
Author:
Hendrik Schreiber
• ### Method Summary

All Methods
Modifier and Type Method Description
`static void` `abs​(int[] array)`
Changes all values to their absolute values.
`static double` `arithmeticMean​(int[] array)`
Computes the arithmetic mean of the array.
`static double` ```arithmeticMean​(int[] array, int start, int end)```
Computes the arithmetic mean of a portion of an array.
`static boolean` `isPowerOfTwo​(int number)`
Indicates whether a number is a power of two.
`static int` `max​(int[] array)`
Calculates the min value of a given array.
`static float` ```maximalAccumulatedSimilarity​(int[] x, int[] y, DistanceFunction<Integer> similarityFunction)```
Computes the dynamic timewarping similarity (i.e.
`static int` `maxIndex​(int[] array)`
Calculates the index of the max value of a given array.
`static int` ```maxIndex​(int[] array, int offset, int length)```
Calculates the index of the max value of a given array.
`static int[]` `maxIndices​(int[] array)`
Calculates the indices of the max values of a given array in descending value order.
`static int[]` ```maxIndices​(int[] array, int offset, int length)```
Calculates the indices of the max values of a given array in descending value order.
`static int` `min​(int[] array)`
Calculates the min value of a given array.
`static float` ```minimalAccumulatedDistance​(int[] x, int[] y, DistanceFunction<Integer> distanceFunction)```
Computes the dynamic timewarping distance (i.e.
`static void` ```normalize​(int[][] arrayOfArrays, int scale)```
Normalizes the values in the given arrays to values `0..scale`.
`static void` ```normalize​(int[] array, int scale)```
Normalizes the values in the given array to values `0..scale`.
`static int[]` ```peaks​(int[] array, int interval, boolean strict)```
Calculates all peaks in the given array.
`static void` `reverse​(int[] array)`
Reverses the order of the `ints` in place.
`static float` `standardDeviation​(int[] data)`
`static float` ```standardDeviation​(int[] data, int offset, int length)```
`static float` `variance​(int[] array)`
`static float` ```variance​(int[] array, int offset, int length)```
• ### Methods inherited from class java.lang.Object

`clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait`
• ### Method Detail

• #### reverse

`public static void reverse​(int[] array)`
Reverses the order of the `ints` in place.
Parameters:
`array` - int array
• #### arithmeticMean

```public static double arithmeticMean​(int[] array,
int start,
int end)```
Computes the arithmetic mean of a portion of an array.
Parameters:
`array` - array
`start` - first index (incl)
`end` - last index (excl)
Returns:
mean
• #### arithmeticMean

`public static double arithmeticMean​(int[] array)`
Computes the arithmetic mean of the array.
Parameters:
`array` - array
Returns:
mean
• #### variance

`public static float variance​(int[] array)`
• #### variance

```public static float variance​(int[] array,
int offset,
int length)```
• #### standardDeviation

`public static float standardDeviation​(int[] data)`
• #### standardDeviation

```public static float standardDeviation​(int[] data,
int offset,
int length)```
• #### abs

`public static void abs​(int[] array)`
Changes all values to their absolute values.
Parameters:
`array` - integer array
• #### min

`public static int min​(int[] array)`
Calculates the min value of a given array.
Parameters:
`array` - integer array
Returns:
minimum
• #### max

`public static int max​(int[] array)`
Calculates the min value of a given array.
Parameters:
`array` - integer array
Returns:
max
• #### maxIndex

```public static int maxIndex​(int[] array,
int offset,
int length)```
Calculates the index of the max value of a given array.
Parameters:
`array` - int array
`offset` - offset into the array
`length` - length
Returns:
max
• #### maxIndices

`public static int[] maxIndices​(int[] array)`
Calculates the indices of the max values of a given array in descending value order.
Parameters:
`array` - int array
Returns:
max indices
• #### maxIndices

```public static int[] maxIndices​(int[] array,
int offset,
int length)```
Calculates the indices of the max values of a given array in descending value order.
Parameters:
`array` - int array
`offset` - offset into the array
`length` - length
Returns:
max indices
• #### peaks

```public static int[] peaks​(int[] array,
int interval,
boolean strict)```
Calculates all peaks in the given array. A peak is defined as a value with at least `interval` values to its left that are strictly less than their direct neighbors to the right, and at least `interval` values to its right that are strictly less than their direct neighbors to the left.
Parameters:
`array` - array
`interval` - number of values to the left and the right that the function has to be increasing or decreasing
`strict` - if true, the shoulders of the peak must be strictly monotonically increasing or decreasing
Returns:
indices of the detected peaks
• #### maxIndex

`public static int maxIndex​(int[] array)`
Calculates the index of the max value of a given array.
Parameters:
`array` - int array
Returns:
max
• #### normalize

```public static void normalize​(int[] array,
int scale)```
Normalizes the values in the given array to values `0..scale`. Note: This method manipulates the provided array.
Parameters:
`array` - array of integers
`scale` - scale
• #### normalize

```public static void normalize​(int[][] arrayOfArrays,
int scale)```
Normalizes the values in the given arrays to values `0..scale`. Note: This method manipulates the provided array.
Parameters:
`arrayOfArrays` - array of double arrays
`scale` - scale
• #### isPowerOfTwo

`public static boolean isPowerOfTwo​(int number)`
Indicates whether a number is a power of two.
Parameters:
`number` - number
Returns:
true, if this number is a power of two (e.g. 4, 8, 16, ...)
• #### minimalAccumulatedDistance

```public static float minimalAccumulatedDistance​(int[] x,
int[] y,
DistanceFunction<Integer> distanceFunction)```
Computes the dynamic timewarping distance (i.e. accumulated cost) between two integer sequences using a given cost function.
Parameters:
`x` - sequence
`y` - sequence
`distanceFunction` - used to compute the local distance between two elements of each sequence
Returns:
total cost of the optimal (i.e. minimal w.r.t cost) warping path between x and y
• #### maximalAccumulatedSimilarity

```public static float maximalAccumulatedSimilarity​(int[] x,
int[] y,
DistanceFunction<Integer> similarityFunction)```
Computes the dynamic timewarping similarity (i.e. accumulated similarity) between two integer sequences using a given similarity function.
Parameters:
`x` - sequence
`y` - sequence
`similarityFunction` - used to compute the local distance between two elements of each sequence
Returns:
total similarity of the optimal (i.e. maximal w.r.t. similarity) warping path between x and y