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64json avatar 64json commented on July 22, 2024 1

Makes sense and feel free to contribute yourself.

FYI none of us are actively maintaining the project. You don't need to tag us on every issue, we will take a look when we get time.

from algorithms.

unfode avatar unfode commented on July 22, 2024

@64json @MarkKoz @nem035 @duaraghav8 @TornjV

from algorithms.

unfode avatar unfode commented on July 22, 2024

Got it. I won't tag you in future issues.

And I will rewrite some algorithm code and make pull requests :-)

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unfode avatar unfode commented on July 22, 2024

Here's a related issue: where should we place code for tracer initialization and tracer.set()?

To me it seems more natural to place tracer code inside the algorithm function. For Breadth-First Search/tree.js, it would be

 // import visualization libraries { 
 const { Tracer, GraphTracer, LogTracer, Layout, VerticalLayout } = require('algorithm-visualizer'); 
 // } 
  
 const G = [ // G[i][j] indicates whether the path from the i-th node to the j-th node exists or not 
   [0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0], 
   [0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0], 
   [0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0], 
   [0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0], 
   [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1], 
   [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], 
   [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], 
   [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], 
   [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], 
   [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], 
   [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], 
 ]; 

 function BFS(G, s) { // s = start node 

   // define tracer variables { 
   const tracer = new GraphTracer(); 
   const logger = new LogTracer(); 
   tracer.log(logger); 
   Layout.setRoot(new VerticalLayout([tracer, logger])); 
   tracer.set(G); 
   tracer.layoutTree(0); 
   Tracer.delay(); 
   // } 

   const Q = []; 
   Q.push(s); // add start node to queue 
   // visualize { 
   tracer.visit(s); 
   Tracer.delay(); 
   // } 
   while (Q.length > 0) { 
     const node = Q.shift(); // dequeue 
     for (let i = 0; i < G[node].length; i++) { 
       if (G[node][i]) { // if current node has the i-th node as a child 
         Q.push(i); // add child node to queue 
         // visualize { 
         tracer.visit(i, node); 
         Tracer.delay(); 
         // } 
       } 
     } 
   } 
 } 
  
 BFS(G, 0); 

The reason is that we may want to trace, say, an array declared inside the algorithm function.

A case in point is the array S in Dijkstra's Shortest Path/code.js (shown below). If we enforce the correspondence between algorithm and function, S should be declared inside the algorithm function, which requires (at least) tracerS.set(S) be placed inside the function.

// import visualization libraries {
const { Tracer, Array1DTracer, GraphTracer, LogTracer, Randomize, Layout, VerticalLayout } = require('algorithm-visualizer');
// }
const G = Randomize.Graph({ N: 5, ratio: 1, directed: false, weighted: true });
const MAX_VALUE = Infinity;
const S = []; // S[end] returns the distance from start node to end node
for (let i = 0; i < G.length; i++) S[i] = MAX_VALUE;
// define tracer variables {
const tracer = new GraphTracer().directed(false).weighted();
const tracerS = new Array1DTracer();
const logger = new LogTracer();
Layout.setRoot(new VerticalLayout([tracer, tracerS, logger]));
tracer.log(logger);
tracer.set(G);
tracerS.set(S);
Tracer.delay();
// }
function Dijkstra(start, end) {
let minIndex;
let minDistance;
const D = []; // D[i] indicates whether the i-th node is discovered or not
for (let i = 0; i < G.length; i++) D.push(false);
S[start] = 0; // Starting node is at distance 0 from itself
// visualize {
tracerS.patch(start, S[start]);
Tracer.delay();
tracerS.depatch(start);
tracerS.select(start);
// }
let k = G.length;
while (k--) {
// Finding a node with the shortest distance from S[minIndex]
minDistance = MAX_VALUE;
for (let i = 0; i < G.length; i++) {
if (S[i] < minDistance && !D[i]) {
minDistance = S[i];
minIndex = i;
}
}
if (minDistance === MAX_VALUE) break; // If there is no edge from current node, jump out of loop
D[minIndex] = true;
// visualize {
tracerS.select(minIndex);
tracer.visit(minIndex);
Tracer.delay();
// }
// For every unvisited neighbour of current node, we check
// whether the path to it is shorter if going over the current node
for (let i = 0; i < G.length; i++) {
if (G[minIndex][i] && S[i] > S[minIndex] + G[minIndex][i]) {
S[i] = S[minIndex] + G[minIndex][i];
// visualize {
tracerS.patch(i, S[i]);
tracer.visit(i, minIndex, S[i]);
Tracer.delay();
tracerS.depatch(i);
tracer.leave(i, minIndex);
Tracer.delay();
// }
}
}
// visualize {
tracer.leave(minIndex);
Tracer.delay();
// }
}
// logger {
if (S[end] === MAX_VALUE) {
logger.println(`there is no path from ${start} to ${end}`);
} else {
logger.println(`the shortest path from ${start} to ${end} is ${S[end]}`);
}
// }
}
const s = Randomize.Integer({ min: 0, max: G.length - 1 }); // s = start node
let e; // e = end node
do {
e = Randomize.Integer({ min: 0, max: G.length - 1 });
} while (s === e);
// logger {
logger.println(`finding the shortest path from ${s} to ${e}`);
Tracer.delay();
// }
Dijkstra(s, e);

from algorithms.

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