Knightin todennäköisyys jäädä shakkilaudalle
Kokeile sitä GfG Practicessa 
Lähtö
Lähtö
Lähtö
Koska a n*n shakkilauta ja ritari asema (x y) aina kun ritari liikkuu, se valitsee yhden kahdeksasta mahdollisesta liikkeestä tasaisesti satunnainen (vaikka nappula lähtisi shakkilaudalta) ja liikkeet siellä. Ritari jatkuu liikkuu, kunnes se on tehnyt tarkalleen k liikkuu tai on muutti pois shakkilaudalla. Tehtävänä on löytää the todennäköisyys että ritari jää päällä hallitus sen jälkeen kun on pysähtyi liikkuvat.
Huomautus: Shakkiritari voi tehdä kahdeksan mahdollista siirtoa. Jokainen liike on kaksi solua kardinaalisuunnassa ja yksi solu ortogonaalisessa suunnassa.
Esimerkkejä:
Syöte: n = 8 x = 0 y = 0 k = 1
Lähtö: 0,25
Selitys: Ritari aloittaa kohdasta (0 0) ja yhden askeleen ottamisen jälkeen se makaa laudan sisällä vain kahdessa kahdeksasta asennosta, jotka ovat (1 2) ja (2 1). Tällöin todennäköisyys on 2/8 = 0,25.Syöte: n = 8 x = 0 y = 0 k = 3
Lähtö: 0,125Syöte: n = 4 x = 1 y = 2 k = 4
Lähtö: 0,024414
Sisällysluettelo
- Ylhäältä alas Dp:n käyttö (muistiinmuokkaus) - O(n*n*k) aika ja O(n*n*k) tila
- Alhaalta ylöspäin suuntautuva Dp (taulukko) - O(n*n*k) aika ja O(n*n*k) avaruus
- Avaruuden käyttäminen Optimoitu Dp - O(n*n*k) aika ja O(n*n) avaruus
Ylhäältä alas Dp:n käyttö (muistiinmuokkaus) - O(n*n*k) aika ja O(n*n*k) tila
C++Todennäköisyys, että ritari jää shakkilaudalle k siirron jälkeen, on yhtä suuri kuin ritarin todennäköisyys edellisessä kahdeksassa paikassa k - 1 siirron jälkeen. Vastaavasti todennäköisyys k-1 liikkeen jälkeen riippuu todennäköisyyden keskiarvosta k-2 liikkeen jälkeen. Ideana on käyttää muistiinpano tallentaaksesi aikaisempien liikkeiden todennäköisyydet ja löytääksesi niiden keskiarvon lopputuloksen laskemiseksi.
Luo tätä varten a 3D-taulukkomuistio[][][] jossa muistio[i][j][k] tallentaa todennäköisyyden, että ritari on solussa (i j) k liikkeen jälkeen. Jos k on nolla, eli alkutila on saavutettu paluu 1 muuten tutkia edellistä kahdeksaa paikkaa ja löytää niiden todennäköisyyksien keskiarvo.
// C++ program to find the probability of the // knight to remain inside the chessboard #include using namespace std ; // recursive function to calculate // knight probability double knightProbability ( int n int x int y int k vector < vector < vector < double >>> & memo ){ // Base case initial probability if ( k == 0 ) return 1.0 ; // check if already calculated if ( memo [ x ][ y ][ k ] != -1 ) return memo [ x ][ y ][ k ]; vector < vector < int >> directions = {{ 1 2 } { 2 1 } { 2 -1 } { 1 -2 } { -1 -2 } { -2 -1 } { -2 1 } { -1 2 }}; memo [ x ][ y ][ k ] = 0 ; double cur = 0.0 ; // for every position reachable from (xy) for ( auto d : directions ){ int u = x + d [ 0 ]; int v = y + d [ 1 ]; // if this position lie inside the board if ( u >= 0 && u < n && v >= 0 && v < n ) cur += knightProbability ( n u v k -1 memo ) / 8.0 ; } return memo [ x ][ y ][ k ] = cur ; } // Function to find the probability double findProb ( int n int x int y int k ) { // Initialize memo to store results vector < vector < vector < double >>> memo ( n vector < vector < double >> ( n vector < double > ( k + 1 -1 ))); return knightProbability ( n x y k memo ); } int main (){ int n = 8 x = 0 y = 0 k = 3 ; cout < < findProb ( n x y k ) < < endl ; return 0 ; }
Java // Java program to find the probability of the // knight to remain inside the chessboard class GfG { // recursive function to calculate // knight probability static double knightProbability ( int n int x int y int k double [][][] memo ) { // Base case initial probability if ( k == 0 ) return 1.0 ; // check if already calculated if ( memo [ x ][ y ][ k ] != - 1 ) return memo [ x ][ y ][ k ] ; int [][] directions = {{ 1 2 } { 2 1 } { 2 - 1 } { 1 - 2 } { - 1 - 2 } { - 2 - 1 } { - 2 1 } { - 1 2 }}; memo [ x ][ y ][ k ] = 0 ; double cur = 0.0 ; // for every position reachable from (x y) for ( int [] d : directions ) { int u = x + d [ 0 ] ; int v = y + d [ 1 ] ; // if this position lies inside the board if ( u >= 0 && u < n && v >= 0 && v < n ) cur += knightProbability ( n u v k - 1 memo ) / 8.0 ; } return memo [ x ][ y ][ k ] = cur ; } // Function to find the probability static double findProb ( int n int x int y int k ) { // Initialize memo to store results double [][][] memo = new double [ n ][ n ][ k + 1 ] ; for ( int i = 0 ; i < n ; i ++ ) { for ( int j = 0 ; j < n ; j ++ ) { for ( int m = 0 ; m <= k ; m ++ ) { memo [ i ][ j ][ m ] = - 1 ; } } } return knightProbability ( n x y k memo ); } public static void main ( String [] args ) { int n = 8 x = 0 y = 0 k = 3 ; System . out . println ( findProb ( n x y k )); } }
Python # Python program to find the probability of the # knight to remain inside the chessboard # recursive function to calculate # knight probability def knightProbability ( n x y k memo ): # Base case initial probability if k == 0 : return 1.0 # check if already calculated if memo [ x ][ y ][ k ] != - 1 : return memo [ x ][ y ][ k ] directions = [ [ 1 2 ] [ 2 1 ] [ 2 - 1 ] [ 1 - 2 ] [ - 1 - 2 ] [ - 2 - 1 ] [ - 2 1 ] [ - 1 2 ] ] memo [ x ][ y ][ k ] = 0 cur = 0.0 # for every position reachable from (x y) for d in directions : u = x + d [ 0 ] v = y + d [ 1 ] # if this position lies inside the board if 0 <= u < n and 0 <= v < n : cur += knightProbability ( n u v k - 1 memo ) / 8.0 memo [ x ][ y ][ k ] = cur return cur # Function to find the probability def findProb ( n x y k ): # Initialize memo to store results memo = [[[ - 1 for _ in range ( k + 1 )] for _ in range ( n )] for _ in range ( n )] return knightProbability ( n x y k memo ) n x y k = 8 0 0 3 print ( findProb ( n x y k ))
C# // C# program to find the probability of the // knight to remain inside the chessboard using System ; class GfG { // recursive function to calculate // knight probability static double KnightProbability ( int n int x int y int k double [] memo ) { // Base case initial probability if ( k == 0 ) return 1.0 ; // check if already calculated if ( memo [ x y k ] != - 1 ) return memo [ x y k ]; int [] directions = {{ 1 2 } { 2 1 } { 2 - 1 } { 1 - 2 } { - 1 - 2 } { - 2 - 1 } { - 2 1 } { - 1 2 }}; memo [ x y k ] = 0 ; double cur = 0.0 ; // for every position reachable from (x y) for ( int i = 0 ; i < 8 ; i ++ ) { int u = x + directions [ i 0 ]; int v = y + directions [ i 1 ]; // if this position lies inside the board if ( u >= 0 && u < n && v >= 0 && v < n ) { cur += KnightProbability ( n u v k - 1 memo ) / 8.0 ; } } return memo [ x y k ] = cur ; } // Function to find the probability static double FindProb ( int n int x int y int k ) { // Initialize memo to store results double [] memo = new double [ n n k + 1 ]; for ( int i = 0 ; i < n ; i ++ ) { for ( int j = 0 ; j < n ; j ++ ) { for ( int m = 0 ; m <= k ; m ++ ) { memo [ i j m ] = - 1 ; } } } return KnightProbability ( n x y k memo ); } static void Main () { int n = 8 x = 0 y = 0 k = 3 ; Console . WriteLine ( FindProb ( n x y k )); } }
JavaScript // JavaScript program to find the probability of the // knight to remain inside the chessboard // recursive function to calculate // knight probability function knightProbability ( n x y k memo ) { // Base case initial probability if ( k === 0 ) return 1.0 ; // check if already calculated if ( memo [ x ][ y ][ k ] !== - 1 ) return memo [ x ][ y ][ k ]; const directions = [ [ 1 2 ] [ 2 1 ] [ 2 - 1 ] [ 1 - 2 ] [ - 1 - 2 ] [ - 2 - 1 ] [ - 2 1 ] [ - 1 2 ] ]; memo [ x ][ y ][ k ] = 0 ; let cur = 0.0 ; // for every position reachable from (x y) for ( let d of directions ) { const u = x + d [ 0 ]; const v = y + d [ 1 ]; // if this position lies inside the board if ( u >= 0 && u < n && v >= 0 && v < n ) { cur += knightProbability ( n u v k - 1 memo ) / 8.0 ; } } return memo [ x ][ y ][ k ] = cur ; } // Function to find the probability function findProb ( n x y k ) { // Initialize memo to store results const memo = Array . from ({ length : n } () => Array . from ({ length : n } () => Array ( k + 1 ). fill ( - 1 ))); return knightProbability ( n x y k memo ). toFixed ( 6 ); } const n = 8 x = 0 y = 0 k = 3 ; console . log ( findProb ( n x y k ));
Lähtö
0.125
Alhaalta ylöspäin suuntautuva Dp (taulukko) - O(n*n*k) aika ja O(n*n*k) avaruus
C++Yllä oleva lähestymistapa voidaan optimoida käyttämällä alhaalta ylöspäin taulukointi vähentää rekursiivisen pinon vaatimaa ylimääräistä tilaa. Ajatuksena on säilyttää 3 D-taulukko dp[][][] jossa dp[i][j][k] tallentaa todennäköisyyden, että ritari on solussa (i j) jälkeen k liikkeet. Alusta 0 tilasta dp arvolla 1 . Jokaista seuraavaa siirtoa varten todennäköisyys ritari tulee olemaan yhtäläinen to keskimäärin todennäköisyydestä edellinen 8 paikkaa jälkeen k-1 liikkeet.
// C++ program to find the probability of the // knight to remain inside the chessboard #include using namespace std ; // Function to find the probability double findProb ( int n int x int y int k ) { // Initialize dp to store results of each step vector < vector < vector < double >>> dp ( n vector < vector < double >> ( n vector < double > ( k + 1 ))); // Initialize dp for step 0 for ( int i = 0 ; i < n ; ++ i ) { for ( int j = 0 ; j < n ; ++ j ) { dp [ i ][ j ][ 0 ] = 1.0 ; } } vector < vector < int >> directions = { { 1 2 } { 2 1 } { 2 -1 } { 1 -2 } { -1 -2 } { -2 -1 } { -2 1 } { -1 2 } }; for ( int move = 1 ; move <= k ; move ++ ) { // find probability for cell (i j) for ( int i = 0 ; i < n ; ++ i ) { for ( int j = 0 ; j < n ; ++ j ) { double cur = 0.0 ; // for every position reachable from (xy) for ( auto d : directions ) { int u = i + d [ 0 ]; int v = j + d [ 1 ]; // if this position lie inside the board if ( u >= 0 && u < n && v >= 0 && v < n ) cur += dp [ u ][ v ][ move - 1 ] / 8.0 ; } // store the result dp [ i ][ j ][ move ] = cur ; } } } // return the result return dp [ x ][ y ][ k ]; } int main (){ int n = 8 x = 0 y = 0 k = 3 ; cout < < findProb ( n x y k ) < < endl ; return 0 ; }
Java // Java program to find the probability of the // knight to remain inside the chessboard import java.util.* ; class GfG { // Function to find the probability static double findProb ( int n int x int y int k ) { // Initialize dp to store results of each step double [][][] dp = new double [ n ][ n ][ k + 1 ] ; for ( int i = 0 ; i < n ; i ++ ) { for ( int j = 0 ; j < n ; j ++ ) { dp [ i ][ j ][ 0 ] = 1 ; } } int [][] directions = { { 1 2 } { 2 1 } { 2 - 1 } { 1 - 2 } { - 1 - 2 } { - 2 - 1 } { - 2 1 } { - 1 2 } }; for ( int move = 1 ; move <= k ; move ++ ) { // find probability for cell (i j) for ( int i = 0 ; i < n ; ++ i ) { for ( int j = 0 ; j < n ; ++ j ) { double cur = 0.0 ; // for every position reachable from (x y) for ( int [] d : directions ) { int u = i + d [ 0 ] ; int v = j + d [ 1 ] ; // if this position lies inside the board if ( u >= 0 && u < n && v >= 0 && v < n ) { cur += dp [ u ][ v ][ move - 1 ] / 8.0 ; } } // store the result dp [ i ][ j ][ move ] = cur ; } } } // return the result return dp [ x ][ y ][ k ] ; } public static void main ( String [] args ) { int n = 8 x = 0 y = 0 k = 3 ; System . out . println ( findProb ( n x y k )); } }
Python # Python program to find the probability of the # knight to remain inside the chessboard # Function to find the probability def findProb ( n x y k ): # Initialize dp to store results of each step dp = [[[ 0 for _ in range ( k + 1 )] for _ in range ( n )] for _ in range ( n )] for i in range ( n ): for j in range ( n ): dp [ i ][ j ][ 0 ] = 1.0 directions = [[ 1 2 ] [ 2 1 ] [ 2 - 1 ] [ 1 - 2 ] [ - 1 - 2 ] [ - 2 - 1 ] [ - 2 1 ] [ - 1 2 ]] for move in range ( 1 k + 1 ): # find probability for cell (i j) for i in range ( n ): for j in range ( n ): cur = 0.0 # for every position reachable from (x y) for d in directions : u = i + d [ 0 ] v = j + d [ 1 ] # if this position lies inside the board if 0 <= u < n and 0 <= v < n : cur += dp [ u ][ v ][ move - 1 ] / 8.0 # store the result dp [ i ][ j ][ move ] = cur # return the result return dp [ x ][ y ][ k ] if __name__ == '__main__' : n x y k = 8 0 0 3 print ( findProb ( n x y k ))
C# // C# program to find the probability of the // knight to remain inside the chessboard using System ; class GfG { // Function to find the probability static double findProb ( int n int x int y int k ) { // Initialize dp to store results of each step double [] dp = new double [ n n k + 1 ]; for ( int i = 0 ; i < n ; i ++ ) { for ( int j = 0 ; j < n ; j ++ ) { dp [ i j 0 ] = 1.0 ; } } int [] directions = {{ 1 2 } { 2 1 } { 2 - 1 } { 1 - 2 } { - 1 - 2 } { - 2 - 1 } { - 2 1 } { - 1 2 }}; for ( int move = 1 ; move <= k ; move ++ ) { // find probability for cell (i j) for ( int i = 0 ; i < n ; ++ i ) { for ( int j = 0 ; j < n ; ++ j ) { double cur = 0.0 ; // for every position reachable from (x y) for ( int d = 0 ; d < directions . GetLength ( 0 ); d ++ ) { int u = i + directions [ d 0 ]; int v = j + directions [ d 1 ]; // if this position lies inside the board if ( u >= 0 && u < n && v >= 0 && v < n ) { cur += dp [ u v move - 1 ] / 8.0 ; } } // store the result dp [ i j move ] = cur ; } } } // return the result return dp [ x y k ]; } static void Main ( string [] args ) { int n = 8 x = 0 y = 0 k = 3 ; Console . WriteLine ( findProb ( n x y k )); } }
JavaScript // JavaScript program to find the probability of the // knight to remain inside the chessboard // Function to find the probability function findProb ( n x y k ) { // Initialize dp to store results of each step let dp = Array . from ({ length : n } () => Array . from ({ length : n } () => Array ( k + 1 ). fill ( 0 )) ); // Initialize dp for step 0 for ( let i = 0 ; i < n ; ++ i ) { for ( let j = 0 ; j < n ; ++ j ) { dp [ i ][ j ][ 0 ] = 1.0 ; } } let directions = [[ 1 2 ] [ 2 1 ] [ 2 - 1 ] [ 1 - 2 ] [ - 1 - 2 ] [ - 2 - 1 ] [ - 2 1 ] [ - 1 2 ]]; for ( let move = 1 ; move <= k ; move ++ ) { // find probability for cell (i j) for ( let i = 0 ; i < n ; i ++ ) { for ( let j = 0 ; j < n ; j ++ ) { let cur = 0.0 ; // for every position reachable from (x y) for ( let d of directions ) { let u = i + d [ 0 ]; let v = j + d [ 1 ]; // if this position lies inside the board if ( u >= 0 && u < n && v >= 0 && v < n ) { cur += dp [ u ][ v ][ move - 1 ] / 8.0 ; } } // store the result dp [ i ][ j ][ move ] = cur ; } } } // return the result return dp [ x ][ y ][ k ]. toFixed ( 6 ); } let n = 8 x = 0 y = 0 k = 3 ; console . log ( findProb ( n x y k ));
Lähtö
0.125
Avaruuden käyttäminen Optimoitu Dp - O(n*n*k) aika ja O(n*n) avaruus
C++Yllä oleva lähestymistapa vaatii vain edellinen todennäköisyyksien tila laskea nykyinen ilmaista näin vain the edellinen myymälä on varastoitava. Ajatuksena on luoda kaksi 2d-taulukot prevMove[][] ja currMove[][] jossa
- prevMove[i][j] tallentaa todennäköisyyden, että ritari on kohdassa (i j) edelliseen siirtoon asti. Se alustetaan alkutilan arvolla 1.
- currMove[i][j] tallentaa nykyisen tilan todennäköisyyden.
Toimi samalla tavalla kuin yllä oleva lähestymistapa ja klo loppu jokaisesta iteraatiosta päivitä prevMove[][] johon on tallennettu arvo currMove[][].
// C++ program to find the probability of the // knight to remain inside the chessboard #include using namespace std ; // Function to find the probability double findProb ( int n int x int y int k ) { // dp to store results of previous move vector < vector < double >> prevMove ( n vector < double > ( n 1 )); // dp to store results of current move vector < vector < double >> currMove ( n vector < double > ( n 0 )); vector < vector < int >> directions = { { 1 2 } { 2 1 } { 2 -1 } { 1 -2 } { -1 -2 } { -2 -1 } { -2 1 } { -1 2 } }; for ( int move = 1 ; move <= k ; move ++ ) { // find probability for cell (i j) for ( int i = 0 ; i < n ; ++ i ) { for ( int j = 0 ; j < n ; ++ j ) { double cur = 0.0 ; // for every position reachable from (xy) for ( auto d : directions ) { int u = i + d [ 0 ]; int v = j + d [ 1 ]; // if this position lie inside the board if ( u >= 0 && u < n && v >= 0 && v < n ) cur += prevMove [ u ][ v ] / 8.0 ; } // store the result currMove [ i ][ j ] = cur ; } } // update previous state prevMove = currMove ; } // return the result return prevMove [ x ][ y ]; } int main (){ int n = 8 x = 0 y = 0 k = 3 ; cout < < findProb ( n x y k ) < < endl ; return 0 ; }
Java // Java program to find the probability of the // knight to remain inside the chessboard class GfG { // Function to find the probability static double findProb ( int n int x int y int k ) { // dp to store results of previous move double [][] prevMove = new double [ n ][ n ] ; for ( int i = 0 ; i < n ; i ++ ) { for ( int j = 0 ; j < n ; j ++ ) { prevMove [ i ][ j ] = 1.0 ; } } // dp to store results of current move double [][] currMove = new double [ n ][ n ] ; int [][] directions = { { 1 2 } { 2 1 } { 2 - 1 } { 1 - 2 } { - 1 - 2 } { - 2 - 1 } { - 2 1 } { - 1 2 } }; for ( int move = 1 ; move <= k ; move ++ ) { // find probability for cell (i j) for ( int i = 0 ; i < n ; ++ i ) { for ( int j = 0 ; j < n ; ++ j ) { double cur = 0.0 ; // for every position reachable from (xy) for ( int [] d : directions ) { int u = i + d [ 0 ] ; int v = j + d [ 1 ] ; // if this position lies inside the board if ( u >= 0 && u < n && v >= 0 && v < n ) cur += prevMove [ u ][ v ] / 8.0 ; } // store the result currMove [ i ][ j ] = cur ; } } // update previous state for ( int i = 0 ; i < n ; i ++ ) { System . arraycopy ( currMove [ i ] 0 prevMove [ i ] 0 n ); } } // return the result return prevMove [ x ][ y ] ; } public static void main ( String [] args ) { int n = 8 x = 0 y = 0 k = 3 ; System . out . println ( findProb ( n x y k )); } }
Python # Python program to find the probability of the # knight to remain inside the chessboard def findProb ( n x y k ): # dp to store results of previous move prevMove = [[ 1.0 ] * n for _ in range ( n )] # dp to store results of current move currMove = [[ 0.0 ] * n for _ in range ( n )] directions = [ [ 1 2 ] [ 2 1 ] [ 2 - 1 ] [ 1 - 2 ] [ - 1 - 2 ] [ - 2 - 1 ] [ - 2 1 ] [ - 1 2 ] ] for move in range ( 1 k + 1 ): # find probability for cell (i j) for i in range ( n ): for j in range ( n ): cur = 0.0 # for every position reachable from (xy) for d in directions : u v = i + d [ 0 ] j + d [ 1 ] # if this position lies inside the board if 0 <= u < n and 0 <= v < n : cur += prevMove [ u ][ v ] / 8.0 # store the result currMove [ i ][ j ] = cur # update previous state prevMove = [ row [:] for row in currMove ] # return the result return prevMove [ x ][ y ] if __name__ == '__main__' : n x y k = 8 0 0 3 print ( findProb ( n x y k ))
C# // C# program to find the probability of the // knight to remain inside the chessboard using System ; class GfG { // Function to find the probability static double findProb ( int n int x int y int k ) { // dp to store results of previous move double [] prevMove = new double [ n n ]; for ( int i = 0 ; i < n ; i ++ ) for ( int j = 0 ; j < n ; j ++ ) prevMove [ i j ] = 1.0 ; // dp to store results of current move double [] currMove = new double [ n n ]; int [] directions = { { 1 2 } { 2 1 } { 2 - 1 } { 1 - 2 } { - 1 - 2 } { - 2 - 1 } { - 2 1 } { - 1 2 } }; for ( int move = 1 ; move <= k ; move ++ ) { // find probability for cell (i j) for ( int i = 0 ; i < n ; ++ i ) { for ( int j = 0 ; j < n ; ++ j ) { double cur = 0.0 ; // for every position reachable from (xy) for ( int d = 0 ; d < directions . GetLength ( 0 ); d ++ ) { int u = i + directions [ d 0 ]; int v = j + directions [ d 1 ]; // if this position lies inside the board if ( u >= 0 && u < n && v >= 0 && v < n ) cur += prevMove [ u v ] / 8.0 ; } // store the result currMove [ i j ] = cur ; } } // update previous state Array . Copy ( currMove prevMove n * n ); } // return the result return prevMove [ x y ]; } static void Main () { int n = 8 x = 0 y = 0 k = 3 ; Console . WriteLine ( findProb ( n x y k )); } }
JavaScript // JavaScript program to find the probability of the // knight to remain inside the chessboard function findProb ( n x y k ) { // dp to store results of previous move let prevMove = Array . from ({ length : n } () => Array ( n ). fill ( 1.0 )); // dp to store results of current move let currMove = Array . from ({ length : n } () => Array ( n ). fill ( 0.0 )); const directions = [ [ 1 2 ] [ 2 1 ] [ 2 - 1 ] [ 1 - 2 ] [ - 1 - 2 ] [ - 2 - 1 ] [ - 2 1 ] [ - 1 2 ] ]; for ( let move = 1 ; move <= k ; move ++ ) { // find probability for cell (i j) for ( let i = 0 ; i < n ; i ++ ) { for ( let j = 0 ; j < n ; j ++ ) { let cur = 0.0 ; // for every position reachable from (xy) for ( let d of directions ) { let u = i + d [ 0 ]; let v = j + d [ 1 ]; // if this position lies inside the board if ( u >= 0 && u < n && v >= 0 && v < n ) cur += prevMove [ u ][ v ] / 8.0 ; } // store the result currMove [ i ][ j ] = cur ; } } // update previous state prevMove = currMove . map ( row => [... row ]); } // return the result return prevMove [ x ][ y ]. toFixed ( 6 ); } let n = 8 x = 0 y = 0 k = 3 ; console . log ( findProb ( n x y k ));
Lähtö
0.125Luo tietokilpailu
