# Updating a QLattice

by: Kevin Broløs & Chris Cave

(Feyn version 3.0 or newer)

A `QLattice`

can be considered as a probability distribution of `Model`

structures, that can be sampled from with the `sample_model`

function. A structure is defined as the input names, function names and their combinations inside a `Model`

. This excludes its weights and biases.

When you update the `QLattice`

with a list of `Model`

s, the probability density function is updated to encourage those structures. Without updating, the QLattice will keep generating models with a random structure.

## Example

Continuing from the previous sections, we now add the `update`

function to our workflow.

```
import feyn
from feyn.datasets import make_classification
train, test = make_classification()
ql = feyn.QLattice()
models = ql.sample_models(train.columns, 'y', 'classification', max_complexity=10)
models = feyn.fit_models(models, train, 'binary_cross_entropy', 'bic', 4)
models = feyn.prune_models(models)
ql.update(
models=models
)
```

`update`

Parameters of ### models

The list of `Model`

s to update the `QLattice`

with.