Implementation of Kadane Algorithm
Kadane algorithm is used to find the maximum sum subarray in an array and maximum sum subarray problem is the task of finding a contiguous subarray with the largest sum
-
+
Algorithm
The simple idea of the algorithm is to search for all positive contiguous segments of the array and keep track of maximum sum contiguous segment among all positive segments(curr_sum is used for this) Each time we get a positive sum we compare it with max_sum and update max_sum if it is greater than curr_sum
- Author
- Ayush Singh
diff --git a/dc/de1/recursive__tree__traversal_8cpp.html b/dc/de1/recursive__tree__traversal_8cpp.html
index 0cdbc33a4..d2b987507 100644
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@@ -155,17 +155,17 @@ Functions
Recursive version of Inorder, Preorder, and Postorder [Traversal of the Tree] (https://en.wikipedia.org/wiki/Tree_traversal)
-
+
Iterative Inorder Traversal of a tree
For traversing a (non-empty) binary tree in an inorder fashion, we must do these three things for every node n starting from the tree’s root:
(L) Recursively traverse its left subtree. When this step is finished, we are back at n again. (N) Process n itself. (R) Recursively traverse its right subtree. When this step is finished, we are back at n again.
In normal inorder traversal, we visit the left subtree before the right subtree. If we visit the right subtree before visiting the left subtree, it is referred to as reverse inorder traversal.
-
+
Iterative Preorder Traversal of a tree
For traversing a (non-empty) binary tree in a preorder fashion, we must do these three things for every node n starting from the tree’s root:
(N) Process n itself. (L) Recursively traverse its left subtree. When this step is finished, we are back at n again. (R) Recursively traverse its right subtree. When this step is finished, we are back at n again.
In normal preorder traversal, visit the left subtree before the right subtree. If we visit the right subtree before visiting the left subtree, it is referred to as reverse preorder traversal.
-
+
Iterative Postorder Traversal of a tree
For traversing a (non-empty) binary tree in a postorder fashion, we must do these three things for every node n starting from the tree’s root:
(L) Recursively traverse its left subtree. When this step is finished, we are back at n again. (R) Recursively traverse its right subtree. When this step is finished, we are back at n again. (N) Process n itself.
diff --git a/dd/d47/namespacemath.html b/dd/d47/namespacemath.html
index 0032ac58d..cb5348d52 100644
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for std::cin and std::cout
Mathematical algorithms
Given a recurrence relation; evaluate the value of nth term. For e.g., For fibonacci series, recurrence series is f(n) = f(n-1) + f(n-2) where f(0) = 0 and f(1) = 1. Note that the method used only demonstrates recurrence relation with one variable (n), unlike nCr problem, since it has two (n, r)
-
+
Algorithm
This problem can be solved using matrix exponentiation method.
- See also
- here for simple number exponentiation algorithm or explaination here.
- Author
- Ashish Daulatabad for assert for IO operations for std::vector STL
diff --git a/df/d66/vector__cross__product_8cpp.html b/df/d66/vector__cross__product_8cpp.html
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The direction ratios (DR) are calculated as follows: 1st DR, J: (b * z) - (c * y) 2nd DR, A: -((a * z) - (c * x)) 3rd DR, N: (a * y) - (b * x)
Therefore, the direction ratios of the cross product are: J, A, N The following C++ Program calculates the direction ratios of the cross products of two vector. The program uses a function, cross() for doing so. The direction ratios for the first and the second vector has to be passed one by one seperated by a space character.
Magnitude of a vector is the square root of the sum of the squares of the direction ratios.
-
+
Example:
An example of a running instance of the executable program:
Pass the first Vector: 1 2 3
Pass the second Vector: 4 5 6 The cross product is: -3 6 -3 Magnitude: 7.34847
diff --git a/index.html b/index.html
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Overview
This repository is a collection of open-source implementation of a variety of algorithms implemented in C++ and licensed under MIT License. These algorithms span a variety of topics from computer science, mathematics and statistics, data science, machine learning, engineering, etc.. The implementations and the associated documentation are meant to provide a learning resource for educators and students. Hence, one may find more than one implementation for the same objective but using a different algorithm strategies and optimizations.
-
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Features
- The repository provides implementations of various algorithms in one of the most fundamental general purpose languages - C++.
@@ -116,12 +116,12 @@ Features
Self-checks within programs ensure correct implementations with confidence.
Modular implementations and OpenSource licensing enable the functions to be utilized conveniently in other applications.
-
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Documentation
Online Documentation is generated from the repository source codes directly. The documentation contains all resources including source code snippets, details on execution of the programs, diagrammatic representation of program flow, and links to external resources where necessary. The documentation also introduces interactive source code with links to documentation for C++ STL library functions used. Click on Files menu to see the list of all the files documented with the code.
Documentation of Algorithms in C++ by The Algorithms Contributors is licensed under CC BY-SA 4.0



-
+
Contributions
As a community developed and maintained repository, we welcome new un-plagiarized quality contributions. Please read our Contribution Guidelines.
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