This project was built with create-react-app, material-ui and typescript.

https://www.algovision.io

The Algo Vision project is an extensive algorithm visualizer with the goal of enabling humans to understand and experience the beauty of algorithms past the zeroes and ones. It has been proven that humans respond and process visual data better than any other form of data. In fact, the human computer (the brain) processes images 60,000 times faster than plain text. Humans are so visually oriented that 90 percent of information transmitted to the brain is visual. Hence, Algo Vision was created as a form of "translator", which relays computer processed data into a human comprehensible one. Therefore, as you interact with the program, I urge you to realize the artistry of mere zeroes and ones orchestrated to optimize the world.

A weighted algorithm that guarantees the shortest path. Dijkstra's is one of the most famous algorithms for finding the shortest path between nodes. Some even consider it to be the father of pathinding algorithms. The algorithm finds the shortest distance neighboring node that has been unvisited and updates the distance if it's the shortest one so far. Once it has done this for all the nodes, it picks the shortest one to the target and traces back to the start node to reveal the shortest path.

A weighted algorithm that guarantees the shortest path. Arguably the most efficient way to find a shortest path. A* is derived from Dijkstra's but uses a heuristic (total distance from start node to end node) in order to determine which node to analyze. Analysis becomes even quicker if incorporated with a binary min-heap (utilized in this project).

A weighted algorithm that does not guarantee the shortest path. The Greedy Best-first Search algorithm is similar to A* but rather than using the total distance as the heuristic for determining which nodes to analyze, it uses the distance to the end node. This makes analysis much quicker, but also sacrifices the guarantee of resulting in the optimal path.

A non-weighted algorithm that guarantees the shortest path. This algorithm utilizes a tree data structure in order to traverse and anlayze the nodes. It runs through each nodes starting at the top depth of the tree and works its way to the bottom until it reaches the end node.

A non-weighted algorithm that does not guarantee the shortest path. The Depth-first Search algorithm is similar to BFS, but instead of starting at the top of the tree it starts from the bottom. Tt is not the most efficient algorithm, but it has its use-cases such as topological sorting, scheduling problems, cycle detection, and solving puzzles with exactly one solution like soduku.

This algorithm constructs a maze through a recursive process. A recusive process is basically repeating the same function until an end case is reached. To generate a maze recursively, this algorithm draws a line on a random coordinate leaving one node empty. It then repeats this process until the graph its working with does not allow it to draw any more lines. This algorithm determines whether to draw a horizontal or vertical line depending on the ratio of the remaining graph's width and height.

An interesting mathematical pattern that generates the longest possible maze path on the given grid. Be careful not to get hypnotized!

Places barriers or weights randomly on the grid.