Why squared distance

Time it and you'll know. Calculating a square root is an iterative process on its own where the digital computer bits square root converges closer to the real square root of the given number until it's sufficiently close as soon as the difference between each iteration is less than some really small value. There are multiple algorithms out there beside the one the Math library uses and their speed depends on the input and how the algorithm is designed. Stick with Math.

Although this can be done very fast for one square root, there's a definite observable time difference. On a side note: I cannot think of a reason to calculate the square root more than once, usually at the end. Stack Overflow for Teams — Collaborate and share knowledge with a private group. Create a free Team What is Teams?

Collectives on Stack Overflow. Learn more. Actual performance benefits of distance squared vs distance Ask Question. Asked 5 years, 5 months ago. Active 5 years, 5 months ago. Viewed 2k times. Improve this question. The only way to answer this "absolutely" is to benchmark the difference in your code. Obligatory link — Andy Turner.

You mentioned "quarter of the speed" , meaning 4 times difference. However, this method is costly as there involve expensive square and square root operations. One useful observation is that in many data mining applications absolute distance measures are not necessary as long as the distances are used to compare the closeness between various data points. For example, in classification and clustering, we often measure the distances of multiple data points to compare their distances from known classes or from centroids to assign those points in a class or in a cluster.

In this regards, an alternative approach known as Squared Euclidean Distance SED can be used to avoid the computation of square root to get the squared distance between the data points. SED has been used in classification, clustering, image processing, and other areas to save the computational expenses. In this paper, we show how SED can be calculated for the vertical data represented in pTrees. We also analyze its performance and compared it with traditional horizontal data representation.

The code that I was writting was in Max script and making Max script calls. This thread has been automatically closed as it remained inactive for 12 months.

If you wish to continue the discussion, please create a new thread in the appropriate forum. Distance vs squared distance Autodesk.

Can any one shed any light on this? Pjanssen UTC 3. So is a manual pythagorian distance calculation actually faster than the distance function? How do you measure the speed? I assume you take a large number of calculations, rather than time a single calculation?

Concerning your last remark, is this the same for other values? Bobo UTC 4. Dimich UTC 5. Bobo UTC 7.