Sample feature abundance values from the given distributions. This function
is used internally by `simphony()`

, and should not usually need to be
called directly.

## Usage

```
getSampledAbund(
abundDt,
logOdds = FALSE,
family = c("gaussian", "negbinom", "bernoulli", "poisson"),
inplace = FALSE
)
```

## Arguments

- abundDt
`data.table`

of expected abundance. If`family`

is 'gaussian', required columns are`feature`

,`sample`

,`mu`

, and`sd`

. If`family`

is 'negbinom', required columns are`feature`

,`sample`

,`mu`

,`dispFunc`

,`cond`

, and`group`

. If`family`

is 'bernoulli' or 'poisson', required columns are`feature`

,`sample`

, and`mu`

.- logOdds
Logical for whether

`mu`

corresponds to log-odds. Only used if`family`

is 'bernoulli'.- family
Character string for the family of distributions from which to sample the abundance values.

`simphony`

will give a warning if it tries to sample from a distribution outside the region in which the distribution is defined: \(\mu < 0\) for negative binomial and Poisson, and \(\mu < 0\) or \(\mu > 1\) for Bernoulli.- inplace
Logical for whether to modify

`abundDt`

in-place, adding a column`abund`

containing the abundance values.

## Value

Matrix of abundance values, where rows correspond to features and columns correspond to samples.

## Examples

```
library('data.table')
set.seed(6022)
abundDt = data.table(feature = 'feature_1', sample = c('sample_1', 'sample_2'),
mu = c(0, 5), sd = 1)
abundMat = getSampledAbund(abundDt)
```