# Why Does MATLAB Have the Function hypot? 7

Posted by **Loren Shure**,

Sometimes I am asked questions like "why did you introduce function `xyz` into MATLAB? And sometimes I have a compelling answer, even for something that looks simple on the surface. Consider the
function `hypot`.

### Contents

### What Does hypot Compute?

`hypot` essentially computes the square root of the sum of the squares of 2 inputs. So what's the big deal, right? For "reasonable"
input values, there is no big issue.

fhypot = @(a,b) sqrt(abs(a).^2+abs(b).^2);

### Other Ways to Compute hypot

Let's create a set of values and compute `hypot` 3 ways for these: with `hypot`, `fhypot`, and `sqrt(2)*x`. These should all give the same answers, provide `a` is real and positive.

```
a = logspace(0,5,6)
format long
aHypot = hypot(a,a)
aFhypot = fhypot(a,a)
aSqrt2 = sqrt(2)*a
```

a = 1 10 100 1000 10000 100000 aHypot = 1.0e+005 * Columns 1 through 3 0.000014142135624 0.000141421356237 0.001414213562373 Columns 4 through 6 0.014142135623731 0.141421356237310 1.414213562373095 aFhypot = 1.0e+005 * Columns 1 through 3 0.000014142135624 0.000141421356237 0.001414213562373 Columns 4 through 6 0.014142135623731 0.141421356237310 1.414213562373095 aSqrt2 = 1.0e+005 * Columns 1 through 3 0.000014142135624 0.000141421356237 0.001414213562373 Columns 4 through 6 0.014142135623731 0.141421356237310 1.414213562373095

### Results

The results are the same, to within round-off, for the 3 methods here. But what happens if the magnitude of `a` is larger, near `realmax` perhaps?

realmax

ans = 1.797693134862316e+308

For my computer, a 32-bit Windows machine, `realmax` for doubles is on the order of 10^308. Let's see what happens if a value nearly that large is used with the different versions
of `hypot`.

a = 1e308 aHypot = hypot(a,a) aFhypot = fhypot(a,a) aSqrt2 = sqrt(2)*a

a = 1.000000000000000e+308 aHypot = 1.414213562373095e+308 aFhypot = Inf aSqrt2 = 1.414213562373095e+308

What you can see is that the straight-forward method returns `Inf` instead of a finite answer. And that's why `hypot` was added to MATLAB, to compute the hypotenuse robustly, avoiding both underflow and overflow.

Get
the MATLAB code

Published with MATLAB® 7.5

**Category:**- Less Used Functionality,
- Robustness

## 7 CommentsOldest to Newest

**1**of 7

That was a pretty interesting post Loren. I’m not sure if it will affect the way I do things around here, but it’s something that could come in useful in the future. Thanks for the tip!

**2**of 7

Before hypot existed, I used a=abs(complex(a,b)); In doing so, I was able to tap the robustness of the abs() function.

**3**of 7

Duane-

Thanks for pointing out that abs is also implemented robustly.

–Loren

**4**of 7

Loren,

Does hypot(a,a) any different from norm([a a])?

Hal

**5**of 7

Hal-

norm is also careful to scale results, like abs and hypot.

–Loren

**6**of 7

Hi Loren

I have a binary image and I want to find the distance between every object. I have already computed the centroid for every object. Can Hypot be used for many objects ???

**7**of 7

Shahn-

You can use hypot if that is what makes sense. Here’s the help page. And here’s a few details from it:

c = hypot(a,b) returns the element-wise result of the following equation, computed to avoid underflow and overflow:

c = sqrt(abs(a).^2 + abs(b).^2)

Inputs a and b must follow these rules:

* Both a and b must be single- or double-precision, floating-point arrays.

* The sizes of the a and b arrays must either be equal, or one a scalar and the other nonscalar. In the latter case, hypot expands the scalar input to match the size of the nonscalar input.

Best wishes,

Loren

## Recent Comments