# arrays – Root mean square of a function in python

## arrays – Root mean square of a function in python

Im going to assume that you want to compute the expression given by the following pseudocode:

```
ms = 0
for i = 1 ... N
ms = ms + y[i]^2
ms = ms / N
rms = sqrt(ms)
```

i.e. the square root of the mean of the squared values of elements of `y`

.

In numpy, you can simply square `y`

, take its mean and then its square root as follows:

```
rms = np.sqrt(np.mean(y**2))
```

So, for example:

```
>>> y = np.array([0, 0, 1, 1, 0, 1, 0, 1, 1, 1]) # Six 1s
>>> y.size
10
>>> np.mean(y**2)
0.59999999999999998
>>> np.sqrt(np.mean(y**2))
0.7745966692414834
```

Do clarify your question if you mean to ask something else.

You could use the sklearn function

```
from sklearn.metrics import mean_squared_error
rmse = mean_squared_error(y_actual,[0 for _ in y_actual], squared=False)
```