Interpolationssuche
Bei einem sortierten Array von n gleichmäßig verteilten Werten arr[] schreiben Sie eine Funktion, um nach einem bestimmten Element x im Array zu suchen.
Die lineare Suche findet das Element in O(n)-Zeit Sprungsuche dauert O(n) Zeit und Binäre Suche dauert O(log n) Zeit.
Die Interpolationssuche ist eine Verbesserung gegenüber Binäre Suche zum Beispiel, wenn die Werte in einem sortierten Array gleichmäßig verteilt sind. Durch Interpolation werden neue Datenpunkte innerhalb des Bereichs einer diskreten Menge bekannter Datenpunkte erstellt. Die binäre Suche geht zur Überprüfung immer zum mittleren Element. Andererseits kann die Interpolationssuche je nach Wert des gesuchten Schlüssels an verschiedenen Orten erfolgen. Wenn der Wert des Schlüssels beispielsweise näher am letzten Element liegt, beginnt die Interpolationssuche wahrscheinlich mit der Suche am Ende.
Um die zu suchende Position zu finden, wird die folgende Formel verwendet.
// Die Idee der Formel besteht darin, einen höheren Wert von pos zurückzugeben
// wenn das zu durchsuchende Element näher an arr[hi] liegt. Und
// kleinerer Wert, wenn näher an arr[lo]arr[] ==> Array, in dem nach Elementen gesucht werden muss
x ==> Zu durchsuchendes Element
lo ==> Startindex in arr[]
Hallo ==> Endindex in arr[]
nach = das +
Es gibt viele verschiedene Interpolationsmethoden und eine davon ist die sogenannte lineare Interpolation. Bei der linearen Interpolation werden zwei Datenpunkte benötigt, die wir als (x1y1) und (x2y2) annehmen, und die Formel lautet: am Punkt (xy).
Dieser Algorithmus funktioniert so, wie wir nach einem Wort in einem Wörterbuch suchen. Der Interpolationssuchalgorithmus verbessert den binären Suchalgorithmus. Die Formel zum Ermitteln eines Werts lautet: K = > K ist eine Konstante, die zur Einengung des Suchraums verwendet wird. Bei der binären Suche lautet der Wert für diese Konstante: K=(niedrig+hoch)/2.
Die Formel für pos kann wie folgt abgeleitet werden.
Let's assume that the elements of the array are linearly distributed.
General equation of line : y = m*x + c.
y is the value in the array and x is its index.
Now putting value of lohi and x in the equation
arr[hi] = m*hi+c ----(1)
arr[lo] = m*lo+c ----(2)
x = m*pos + c ----(3)
m = (arr[hi] - arr[lo] )/ (hi - lo)
subtracting eqxn (2) from (3)
x - arr[lo] = m * (pos - lo)
lo + (x - arr[lo])/m = pos
pos = lo + (x - arr[lo]) *(hi - lo)/(arr[hi] - arr[lo])Algorithmus
Der Rest des Interpolationsalgorithmus ist bis auf die obige Partitionslogik derselbe.
- Schritt 1: Berechnen Sie in einer Schleife den Wert von „pos“ mithilfe der Sondenpositionsformel.
- Schritt 2: Wenn es eine Übereinstimmung gibt, geben Sie den Index des Elements zurück und beenden Sie den Vorgang.
- Schritt 3: Wenn das Element kleiner als arr[pos] ist, berechnen Sie die Sondenposition des linken Unterarrays. Andernfalls berechnen Sie dasselbe im rechten Unterarray.
- Schritt 4: Wiederholen Sie diesen Vorgang, bis eine Übereinstimmung gefunden wird oder das Unterarray auf Null reduziert wird.
Nachfolgend finden Sie die Implementierung des Algorithmus.
// C++ program to implement interpolation // search with recursion #include using namespace std ; // If x is present in arr[0..n-1] then returns // index of it else returns -1. int interpolationSearch ( int arr [] int lo int hi int x ) { int pos ; // Since array is sorted an element present // in array must be in range defined by corner if ( lo <= hi && x >= arr [ lo ] && x <= arr [ hi ]) { // Probing the position with keeping // uniform distribution in mind. pos = lo + ((( double )( hi - lo ) / ( arr [ hi ] - arr [ lo ])) * ( x - arr [ lo ])); // Condition of target found if ( arr [ pos ] == x ) return pos ; // If x is larger x is in right sub array if ( arr [ pos ] < x ) return interpolationSearch ( arr pos + 1 hi x ); // If x is smaller x is in left sub array if ( arr [ pos ] > x ) return interpolationSearch ( arr lo pos - 1 x ); } return -1 ; } // Driver Code int main () { // Array of items on which search will // be conducted. int arr [] = { 10 12 13 16 18 19 20 21 22 23 24 33 35 42 47 }; int n = sizeof ( arr ) / sizeof ( arr [ 0 ]); // Element to be searched int x = 18 ; int index = interpolationSearch ( arr 0 n - 1 x ); // If element was found if ( index != -1 ) cout < < 'Element found at index ' < < index ; else cout < < 'Element not found.' ; return 0 ; } // This code is contributed by equbalzeeshan
C // C program to implement interpolation search // with recursion #include // If x is present in arr[0..n-1] then returns // index of it else returns -1. int interpolationSearch ( int arr [] int lo int hi int x ) { int pos ; // Since array is sorted an element present // in array must be in range defined by corner if ( lo <= hi && x >= arr [ lo ] && x <= arr [ hi ]) { // Probing the position with keeping // uniform distribution in mind. pos = lo + ((( double )( hi - lo ) / ( arr [ hi ] - arr [ lo ])) * ( x - arr [ lo ])); // Condition of target found if ( arr [ pos ] == x ) return pos ; // If x is larger x is in right sub array if ( arr [ pos ] < x ) return interpolationSearch ( arr pos + 1 hi x ); // If x is smaller x is in left sub array if ( arr [ pos ] > x ) return interpolationSearch ( arr lo pos - 1 x ); } return -1 ; } // Driver Code int main () { // Array of items on which search will // be conducted. int arr [] = { 10 12 13 16 18 19 20 21 22 23 24 33 35 42 47 }; int n = sizeof ( arr ) / sizeof ( arr [ 0 ]); int x = 18 ; // Element to be searched int index = interpolationSearch ( arr 0 n - 1 x ); // If element was found if ( index != -1 ) printf ( 'Element found at index %d' index ); else printf ( 'Element not found.' ); return 0 ; }
Java // Java program to implement interpolation // search with recursion import java.util.* ; class GFG { // If x is present in arr[0..n-1] then returns // index of it else returns -1. public static int interpolationSearch ( int arr [] int lo int hi int x ) { int pos ; // Since array is sorted an element // present in array must be in range // defined by corner if ( lo <= hi && x >= arr [ lo ] && x <= arr [ hi ] ) { // Probing the position with keeping // uniform distribution in mind. pos = lo + ((( hi - lo ) / ( arr [ hi ] - arr [ lo ] )) * ( x - arr [ lo ] )); // Condition of target found if ( arr [ pos ] == x ) return pos ; // If x is larger x is in right sub array if ( arr [ pos ] < x ) return interpolationSearch ( arr pos + 1 hi x ); // If x is smaller x is in left sub array if ( arr [ pos ] > x ) return interpolationSearch ( arr lo pos - 1 x ); } return - 1 ; } // Driver Code public static void main ( String [] args ) { // Array of items on which search will // be conducted. int arr [] = { 10 12 13 16 18 19 20 21 22 23 24 33 35 42 47 }; int n = arr . length ; // Element to be searched int x = 18 ; int index = interpolationSearch ( arr 0 n - 1 x ); // If element was found if ( index != - 1 ) System . out . println ( 'Element found at index ' + index ); else System . out . println ( 'Element not found.' ); } } // This code is contributed by equbalzeeshan
Python # Python3 program to implement # interpolation search # with recursion # If x is present in arr[0..n-1] then # returns index of it else returns -1. def interpolationSearch ( arr lo hi x ): # Since array is sorted an element present # in array must be in range defined by corner if ( lo <= hi and x >= arr [ lo ] and x <= arr [ hi ]): # Probing the position with keeping # uniform distribution in mind. pos = lo + (( hi - lo ) // ( arr [ hi ] - arr [ lo ]) * ( x - arr [ lo ])) # Condition of target found if arr [ pos ] == x : return pos # If x is larger x is in right subarray if arr [ pos ] < x : return interpolationSearch ( arr pos + 1 hi x ) # If x is smaller x is in left subarray if arr [ pos ] > x : return interpolationSearch ( arr lo pos - 1 x ) return - 1 # Driver code # Array of items in which # search will be conducted arr = [ 10 12 13 16 18 19 20 21 22 23 24 33 35 42 47 ] n = len ( arr ) # Element to be searched x = 18 index = interpolationSearch ( arr 0 n - 1 x ) if index != - 1 : print ( 'Element found at index' index ) else : print ( 'Element not found' ) # This code is contributed by Hardik Jain
C# // C# program to implement // interpolation search using System ; class GFG { // If x is present in // arr[0..n-1] then // returns index of it // else returns -1. static int interpolationSearch ( int [] arr int lo int hi int x ) { int pos ; // Since array is sorted an element // present in array must be in range // defined by corner if ( lo <= hi && x >= arr [ lo ] && x <= arr [ hi ]) { // Probing the position // with keeping uniform // distribution in mind. pos = lo + ((( hi - lo ) / ( arr [ hi ] - arr [ lo ])) * ( x - arr [ lo ])); // Condition of // target found if ( arr [ pos ] == x ) return pos ; // If x is larger x is in right sub array if ( arr [ pos ] < x ) return interpolationSearch ( arr pos + 1 hi x ); // If x is smaller x is in left sub array if ( arr [ pos ] > x ) return interpolationSearch ( arr lo pos - 1 x ); } return - 1 ; } // Driver Code public static void Main () { // Array of items on which search will // be conducted. int [] arr = new int []{ 10 12 13 16 18 19 20 21 22 23 24 33 35 42 47 }; // Element to be searched int x = 18 ; int n = arr . Length ; int index = interpolationSearch ( arr 0 n - 1 x ); // If element was found if ( index != - 1 ) Console . WriteLine ( 'Element found at index ' + index ); else Console . WriteLine ( 'Element not found.' ); } } // This code is contributed by equbalzeeshan
JavaScript < script > // Javascript program to implement Interpolation Search // If x is present in arr[0..n-1] then returns // index of it else returns -1. function interpolationSearch ( arr lo hi x ){ let pos ; // Since array is sorted an element present // in array must be in range defined by corner if ( lo <= hi && x >= arr [ lo ] && x <= arr [ hi ]) { // Probing the position with keeping // uniform distribution in mind. pos = lo + Math . floor ((( hi - lo ) / ( arr [ hi ] - arr [ lo ])) * ( x - arr [ lo ]));; // Condition of target found if ( arr [ pos ] == x ){ return pos ; } // If x is larger x is in right sub array if ( arr [ pos ] < x ){ return interpolationSearch ( arr pos + 1 hi x ); } // If x is smaller x is in left sub array if ( arr [ pos ] > x ){ return interpolationSearch ( arr lo pos - 1 x ); } } return - 1 ; } // Driver Code let arr = [ 10 12 13 16 18 19 20 21 22 23 24 33 35 42 47 ]; let n = arr . length ; // Element to be searched let x = 18 let index = interpolationSearch ( arr 0 n - 1 x ); // If element was found if ( index != - 1 ){ document . write ( `Element found at index ${ index } ` ) } else { document . write ( 'Element not found' ); } // This code is contributed by _saurabh_jaiswal < /script>
PHP // PHP program to implement $erpolation search // with recursion // If x is present in arr[0..n-1] then returns // index of it else returns -1. function interpolationSearch ( $arr $lo $hi $x ) { // Since array is sorted an element present // in array must be in range defined by corner if ( $lo <= $hi && $x >= $arr [ $lo ] && $x <= $arr [ $hi ]) { // Probing the position with keeping // uniform distribution in mind. $pos = ( int )( $lo + ((( double )( $hi - $lo ) / ( $arr [ $hi ] - $arr [ $lo ])) * ( $x - $arr [ $lo ]))); // Condition of target found if ( $arr [ $pos ] == $x ) return $pos ; // If x is larger x is in right sub array if ( $arr [ $pos ] < $x ) return interpolationSearch ( $arr $pos + 1 $hi $x ); // If x is smaller x is in left sub array if ( $arr [ $pos ] > $x ) return interpolationSearch ( $arr $lo $pos - 1 $x ); } return - 1 ; } // Driver Code // Array of items on which search will // be conducted. $arr = array ( 10 12 13 16 18 19 20 21 22 23 24 33 35 42 47 ); $n = sizeof ( $arr ); $x = 47 ; // Element to be searched $index = interpolationSearch ( $arr 0 $n - 1 $x ); // If element was found if ( $index != - 1 ) echo 'Element found at index ' . $index ; else echo 'Element not found.' ; return 0 ; #This code is contributed by Susobhan Akhuli ?>
Ausgabe
Element found at index 4
Zeitkomplexität: O(log 2 (Protokoll 2 n)) für den Durchschnittsfall und O(n) für den schlechtesten Fall
Komplexität des Hilfsraums: O(1)
Ein anderer Ansatz:-
Dies ist der Iterationsansatz für die Interpolationssuche.
- Schritt 1: Berechnen Sie in einer Schleife den Wert von „pos“ mithilfe der Sondenpositionsformel.
- Schritt 2: Wenn es eine Übereinstimmung gibt, geben Sie den Index des Elements zurück und beenden Sie den Vorgang.
- Schritt 3: Wenn das Element kleiner als arr[pos] ist, berechnen Sie die Sondenposition des linken Unterarrays. Andernfalls berechnen Sie dasselbe im rechten Unterarray.
- Schritt 4: Wiederholen Sie diesen Vorgang, bis eine Übereinstimmung gefunden wird oder das Unterarray auf Null reduziert wird.
Nachfolgend finden Sie die Implementierung des Algorithmus.
C++ // C++ program to implement interpolation search by using iteration approach #include using namespace std ; int interpolationSearch ( int arr [] int n int x ) { // Find indexes of two corners int low = 0 high = ( n - 1 ); // Since array is sorted an element present // in array must be in range defined by corner while ( low <= high && x >= arr [ low ] && x <= arr [ high ]) { if ( low == high ) { if ( arr [ low ] == x ) return low ; return -1 ; } // Probing the position with keeping // uniform distribution in mind. int pos = low + ((( double )( high - low ) / ( arr [ high ] - arr [ low ])) * ( x - arr [ low ])); // Condition of target found if ( arr [ pos ] == x ) return pos ; // If x is larger x is in upper part if ( arr [ pos ] < x ) low = pos + 1 ; // If x is smaller x is in the lower part else high = pos - 1 ; } return -1 ; } // Main function int main () { // Array of items on whighch search will // be conducted. int arr [] = { 10 12 13 16 18 19 20 21 22 23 24 33 35 42 47 }; int n = sizeof ( arr ) / sizeof ( arr [ 0 ]); int x = 18 ; // Element to be searched int index = interpolationSearch ( arr n x ); // If element was found if ( index != -1 ) cout < < 'Element found at index ' < < index ; else cout < < 'Element not found.' ; return 0 ; } //this code contributed by Ajay Singh
Java // Java program to implement interpolation // search with recursion import java.util.* ; class GFG { // If x is present in arr[0..n-1] then returns // index of it else returns -1. public static int interpolationSearch ( int arr [] int lo int hi int x ) { int pos ; if ( lo <= hi && x >= arr [ lo ] && x <= arr [ hi ] ) { // Probing the position with keeping // uniform distribution in mind. pos = lo + ((( hi - lo ) / ( arr [ hi ] - arr [ lo ] )) * ( x - arr [ lo ] )); // Condition of target found if ( arr [ pos ] == x ) return pos ; // If x is larger x is in right sub array if ( arr [ pos ] < x ) return interpolationSearch ( arr pos + 1 hi x ); // If x is smaller x is in left sub array if ( arr [ pos ] > x ) return interpolationSearch ( arr lo pos - 1 x ); } return - 1 ; } // Driver Code public static void main ( String [] args ) { // Array of items on which search will // be conducted. int arr [] = { 10 12 13 16 18 19 20 21 22 23 24 33 35 42 47 }; int n = arr . length ; // Element to be searched int x = 18 ; int index = interpolationSearch ( arr 0 n - 1 x ); // If element was found if ( index != - 1 ) System . out . println ( 'Element found at index ' + index ); else System . out . println ( 'Element not found.' ); } }
Python # Python equivalent of above C++ code # Python program to implement interpolation search by using iteration approach def interpolationSearch ( arr n x ): # Find indexes of two corners low = 0 high = ( n - 1 ) # Since array is sorted an element present # in array must be in range defined by corner while low <= high and x >= arr [ low ] and x <= arr [ high ]: if low == high : if arr [ low ] == x : return low ; return - 1 ; # Probing the position with keeping # uniform distribution in mind. pos = int ( low + ((( float ( high - low ) / ( arr [ high ] - arr [ low ])) * ( x - arr [ low ])))) # Condition of target found if arr [ pos ] == x : return pos # If x is larger x is in upper part if arr [ pos ] < x : low = pos + 1 ; # If x is smaller x is in lower part else : high = pos - 1 ; return - 1 # Main function if __name__ == '__main__' : # Array of items on whighch search will # be conducted. arr = [ 10 12 13 16 18 19 20 21 22 23 24 33 35 42 47 ] n = len ( arr ) x = 18 # Element to be searched index = interpolationSearch ( arr n x ) # If element was found if index != - 1 : print ( 'Element found at index' index ) else : print ( 'Element not found' )
C# // C# program to implement interpolation search by using // iteration approach using System ; class Program { // Interpolation Search function static int InterpolationSearch ( int [] arr int n int x ) { int low = 0 ; int high = n - 1 ; while ( low <= high && x >= arr [ low ] && x <= arr [ high ]) { if ( low == high ) { if ( arr [ low ] == x ) return low ; return - 1 ; } int pos = low + ( int )((( float )( high - low ) / ( arr [ high ] - arr [ low ])) * ( x - arr [ low ])); if ( arr [ pos ] == x ) return pos ; if ( arr [ pos ] < x ) low = pos + 1 ; else high = pos - 1 ; } return - 1 ; } // Main function static void Main ( string [] args ) { int [] arr = { 10 12 13 16 18 19 20 21 22 23 24 33 35 42 47 }; int n = arr . Length ; int x = 18 ; int index = InterpolationSearch ( arr n x ); if ( index != - 1 ) Console . WriteLine ( 'Element found at index ' + index ); else Console . WriteLine ( 'Element not found' ); } } // This code is contributed by Susobhan Akhuli
JavaScript // JavaScript program to implement interpolation search by using iteration approach function interpolationSearch ( arr n x ) { // Find indexes of two corners let low = 0 ; let high = n - 1 ; // Since array is sorted an element present // in array must be in range defined by corner while ( low <= high && x >= arr [ low ] && x <= arr [ high ]) { if ( low == high ) { if ( arr [ low ] == x ) { return low ; } return - 1 ; } // Probing the position with keeping // uniform distribution in mind. let pos = Math . floor ( low + ((( high - low ) / ( arr [ high ] - arr [ low ])) * ( x - arr [ low ]))); // Condition of target found if ( arr [ pos ] == x ) { return pos ; } // If x is larger x is in upper part if ( arr [ pos ] < x ) { low = pos + 1 ; } // If x is smaller x is in lower part else { high = pos - 1 ; } } return - 1 ; } // Main function let arr = [ 10 12 13 16 18 19 20 21 22 23 24 33 35 42 47 ]; let n = arr . length ; let x = 18 ; // Element to be searched let index = interpolationSearch ( arr n x ); // If element was found if ( index != - 1 ) { console . log ( 'Element found at index' index ); } else { console . log ( 'Element not found' ); }
Ausgabe
Element found at index 4
Zeitkomplexität: O(log2(log2 n)) für den Durchschnittsfall und O(n) für den schlechtesten Fall
Komplexität des Hilfsraums: O(1)
