Given a set of lines represented by a 2-dimensional array arr consisting of slope(m) and intercept(c) respectively and Q queries such that each query contains a value x. The task is to find the maximum value of y for each value of x from all the given a set of lines.
The given lines are represented by the equation y = m*x + c.
Examples:
Input: arr[][2] ={ {1, 1}, {0, 0}, {-3, 3} }, Q = {-2, 2, 1} Output: 9, 3, 2 For query x = -2, y values from the equations are -1, 0, 9. So the maximum value is 9 Similarly, for x = 2, y values are 3, 0, -3. So the maximum value is 3 And for x = 1, values of y = 2, 0, 0. So the maximum value is 2. Input: arr[][] ={ {5, 6}, {3, 2}, {7, 3} }, Q = { 1, 2, 30 } Output: 10, 17, 213
Naive Approach: The naive approach is to substitute the values of x in every line and compute the maximum of all the lines. For each query, it will take O(N) time and so the complexity of the solution becomes O(Q * N) where N is the number of lines and Q is the number of queries. Efficient approach: The idea is to use convex hull trick:
- From the given set of lines, the lines which carry no significance (for any value of x they never give the maximal value y) can be found and deleted thereby reducing the set.
- Now, if the ranges (l, r) can be found where each line gives the maximum value, then each query can be answered using binary search.
- Therefore, a sorted vector of lines, with decreasing order of slopes, is created and the lines are inserted in decreasing order of the slopes.
Below is the implementation of the above approach:
CPP
// C++ implementation of // the above approach #include <bits/stdc++.h> using namespace std; struct Line { int m, c; public : // Sort the line in decreasing // order of their slopes bool operator<(Line l) { // If slopes aren't equal if (m != l.m) return m > l.m; // If the slopes are equal else return c > l.c; } // Checks if line L3 or L1 is better than L2 // Intersection of Line 1 and // Line 2 has x-coordinate (b1-b2)/(m2-m1) // Similarly for Line 1 and // Line 3 has x-coordinate (b1-b3)/(m3-m1) // Cross multiplication will // give the below result bool check(Line L1, Line L2, Line L3) { return (L3.c - L1.c) * (L1.m - L2.m) < (L2.c - L1.c) * (L1.m - L3.m); } }; struct Convex_HULL_Trick { // To store the lines vector<Line> l; // Add the line to the set of lines void add(Line newLine) { int n = l.size(); // To check if after adding the new line // whether old lines are // losing significance or not while (n >= 2 && newLine.check(l[n - 2], l[n - 1], newLine)) { n--; } l.resize(n); // Add the present line l.push_back(newLine); } // Function to return the y coordinate // of the specified line // for the given coordinate int value( int in, int x) { return l[in].m * x + l[in].c; } // Function to Return the maximum value // of y for the given x coordinate int maxQuery( int x) { // if there is no lines if (l.empty()) return INT_MAX; int low = 0, high = ( int )l.size() - 2; // Binary search while (low <= high) { int mid = (low + high) / 2; if (value(mid, x) < value(mid + 1, x)) low = mid + 1; else high = mid - 1; } return value(low, x); } }; // Driver code int main() { Line lines[] = { { 1, 1 }, { 0, 0 }, { -3, 3 } }; int Q[] = { -2, 2, 1 }; int n = 3, q = 3; Convex_HULL_Trick cht; // Sort the lines sort(lines, lines + n); // Add the lines for ( int i = 0; i < n; i++) cht.add(lines[i]); // For each query in Q for ( int i = 0; i < q; i++) { int x = Q[i]; cout << cht.maxQuery(x) << endl; } return 0; } |
Python3
# Python3 implementation of the above approach class Line: def __init__( self , a = 0 , b = 0 ): self .m = a; self .c = b; # Sort the line in decreasing # order of their slopes def __gt__( self , l): # If slopes arent equal if ( self .m ! = l.m): return self .m > l.m; # If the slopes are equal else : return self .c > l.c; # Checks if line L3 or L1 is better than L2 # Intersection of Line 1 and # Line 2 has x-coordinate (b1-b2)/(m2-m1) # Similarly for Line 1 and # Line 3 has x-coordinate (b1-b3)/(m3-m1) # Cross multiplication will give the below result def check( self , L1, L2, L3): return (L3.c - L1.c) * (L1.m - L2.m) < (L2.c - L1.c) * (L1.m - L3.m); class Convex_HULL_Trick : # To store the lines def __init__( self ): self .l = []; # Add the line to the set of lines def add( self , newLine): n = len ( self .l) # To check if after adding the new line # whether old lines are # losing significance or not while (n > = 2 and newLine.check(( self .l)[n - 2 ], ( self .l)[n - 1 ], newLine)): n - = 1 ; # Add the present line ( self .l).append(newLine); # Function to return the y coordinate # of the specified line for the given coordinate def value( self , ind, x): return ( self .l)[ind].m * x + ( self .l)[ind].c; # Function to Return the maximum value # of y for the given x coordinate def maxQuery( self , x): # if there is no lines if ( len ( self .l) = = 0 ): return 999999999 ; low = 0 high = len ( self .l) - 2 ; # Binary search while (low < = high): mid = int ((low + high) / 2 ); if ( self .value(mid, x) < self .value(mid + 1 , x)): low = mid + 1 ; else : high = mid - 1 ; return self .value(low, x); # Driver code lines = [ Line( 1 , 1 ), Line( 0 , 0 ), Line( - 3 , 3 )] Q = [ - 2 , 2 , 1 ]; n = 3 q = 3 ; cht = Convex_HULL_Trick(); # Sort the lines lines.sort(reverse = True ) # Add the lines for i in range (n): cht.add(lines[i]); # For each query in Q for i in range (q): x = Q[i]; print (cht.maxQuery(x)); # This code is contributed by phasing17. |
C#
// C# implementation of // the above approach using System; using System.Collections.Generic; class Line : IComparable<Line> { public int m, c; public Line( int m1, int c1) { m = m1; c = c1; } // Sort the line in decreasing // order of their slopes public int CompareTo(Line l) { // If slopes aren't equal if (m != l.m) return -m + l.m; // If the slopes are equal else return -c + l.c; } // Checks if line L3 or L1 is better than L2 // Intersection of Line 1 and // Line 2 has x-coordinate (b1-b2)/(m2-m1) // Similarly for Line 1 and // Line 3 has x-coordinate (b1-b3)/(m3-m1) // Cross multiplication will // give the below result public bool check(Line L1, Line L2, Line L3) { return (L3.c - L1.c) * (L1.m - L2.m) < (L2.c - L1.c) * (L1.m - L3.m); } }; class Convex_HULL_Trick { // To store the lines List<Line> l; public Convex_HULL_Trick() { l = new List<Line>(); } // Add the line to the set of lines public void add(Line newLine) { int n = l.Count; // To check if after adding the new line // whether old lines are // losing significance or not while ( n >= 2 && newLine.check(l[n - 2], l[n - 1], newLine)) { n--; } // Add the present line l.Add(newLine); } // Function to return the y coordinate // of the specified line // for the given coordinate public int value( int ind, int x) { return l[ind].m * x + l[ind].c; } // Function to Return the maximum value // of y for the given x coordinate public int maxQuery( int x) { // if there is no lines if (l.Count == 0) return Int32.MaxValue; int low = 0, high = ( int )l.Count - 2; // Binary search while (low <= high) { int mid = (low + high) / 2; if (value(mid, x) < value(mid + 1, x)) low = mid + 1; else high = mid - 1; } return value(low, x); } }; class GFG { public static void Main( string [] args) { Line[] lines = { new Line(1, 1), new Line(0, 0), new Line(-3, 3) }; int [] Q = { -2, 2, 1 }; int n = 3, q = 3; Convex_HULL_Trick cht = new Convex_HULL_Trick(); // Sort the lines Array.Sort(lines); // Add the lines for ( int i = 0; i < n; i++) cht.add(lines[i]); // For each query in Q for ( int i = 0; i < q; i++) { int x = Q[i]; Console.WriteLine(cht.maxQuery(x)); } } } // This code is contributed by phasing17 |
Javascript
// JS implementation of // the above approach class Line { constructor(a = 0, b = 0 ) { this .m = a this .c = b } // Sort the line in decreasing // order of their slopes compare (l) { // If slopes aren't equal if ( this .m != l.m) return this .m > l.m; // If the slopes are equal else return this .c > l.c; } // Checks if line L3 or L1 is better than L2 // Intersection of Line 1 and // Line 2 has x-coordinate (b1-b2)/(m2-m1) // Similarly for Line 1 and // Line 3 has x-coordinate (b1-b3)/(m3-m1) // Cross multiplication will // give the below result check(L1, L2, L3) { return (L3.c - L1.c) * (L1.m - L2.m) < (L2.c - L1.c) * (L1.m - L3.m); } }; class Convex_HULL_Trick { // To store the lines constructor() { this .l = new Array(); } // Add the line to the set of lines add( newLine) { let n = ( this .l).length; // To check if after adding the new line // whether old lines are // losing significance or not while (n >= 2 && newLine.check(( this .l)[n - 2], ( this .l)[n - 1], newLine)) { n--; } while (( this .l).length > n) ( this .l).pop(); while (( this .l).length < n) ( this .l).push( new Line()); // Add the present line ( this .l).push(newLine); } // Function to return the y coordinate // of the specified line // for the given coordinate value(ind, x) { return ( this .l)[ind].m * x + ( this .l)[ind].c; } // Function to Return the maximum value // of y for the given x coordinate maxQuery( x) { // if there is no lines if (( this .l).length == 0) return 999999999; let low = 0, high = ( this .l).length - 2; // Binary search while (low <= high) { let mid = Math.floor((low + high) / 2); if ( this .value(mid, x) < this .value(mid + 1, x)) low = mid + 1; else high = mid - 1; } return this .value(low, x); } }; // Driver code let lines = [ new Line(1, 1), new Line(0, 0), new Line(-3, 3)] let Q = [ -2, 2, 1 ]; let n = 3, q = 3; let cht = new Convex_HULL_Trick(); // Sort the lines lines.sort( function (a, b) { if (a.m == b.m) return a.c < b.c; return a.m < b.c; }) // Add the lines for ( var i = 0; i < n; i++) cht.add(lines[i]); // For each query in Q for ( var i = 0; i < q; i++) { var x = Q[i]; console.log(cht.maxQuery(x)) } // This code is contributed by phasing17 |
Java
// Java implementation of // the above approach import java.util.*; class GFG { static class Line implements Comparable<Line> { public int m, c; public Line( int m1, int c1) { m = m1; c = c1; } // Sort the line in decreasing // order of their slopes public int compareTo(Line l) { // If slopes aren't equal if (m != l.m) return -m + l.m; // If the slopes are equal else return -c + l.c; } // Checks if line L3 or L1 is better than L2 // Intersection of Line 1 and // Line 2 has x-coordinate (b1-b2)/(m2-m1) // Similarly for Line 1 and // Line 3 has x-coordinate (b1-b3)/(m3-m1) // Cross multiplication will // give the below result public boolean check(Line L1, Line L2, Line L3) { return (L3.c - L1.c) * (L1.m - L2.m) < (L2.c - L1.c) * (L1.m - L3.m); } }; static class Convex_HULL_Trick { // To store the lines ArrayList<Line> l; public Convex_HULL_Trick() { l = new ArrayList<Line>(); } // Add the line to the set of lines public void add(Line newLine) { int n = l.size(); // To check if after adding the new line // whether old lines are // losing significance or not while ( n >= 2 && newLine.check(l.get(n - 2 ), l.get(n - 1 ), newLine)) { n--; } // Add the present line l.add(newLine); } // Function to return the y coordinate // of the specified line // for the given coordinate public int value( int ind, int x) { return (l.get(ind)).m * x + (l.get(ind)).c; } // Function to Return the maximum value // of y for the given x coordinate public int maxQuery( int x) { // if there is no lines if (l.size() == 0 ) return Integer.MAX_VALUE; int low = 0 , high = ( int )l.size() - 2 ; // Binary search while (low <= high) { int mid = (low + high) / 2 ; if (value(mid, x) < value(mid + 1 , x)) low = mid + 1 ; else high = mid - 1 ; } return value(low, x); } }; public static void main(String[] args) { Line[] lines = { new Line( 1 , 1 ), new Line( 0 , 0 ), new Line(- 3 , 3 ) }; int [] Q = { - 2 , 2 , 1 }; int n = 3 , q = 3 ; Convex_HULL_Trick cht = new Convex_HULL_Trick(); // Sort the lines Arrays.sort(lines); // Add the lines for ( int i = 0 ; i < n; i++) cht.add(lines[i]); // For each query in Q for ( int i = 0 ; i < q; i++) { int x = Q[i]; System.out.println(cht.maxQuery(x)); } } } // This code is contributed by phasing17 |
9 3 2
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