# s2d

From GMKMcharlie v1.0.3
by Charlie Wusuo Liu

##### Sparse to dense conversion

Convert data from sparse representation (list of data frames) to dese representation (matrix).

##### Usage

```
s2d(
X,
d,
zero = 0,
verbose = TRUE
)
```

##### Arguments

- X
A list of size

`N`

, the number of observations.`X[[i]]`

is a 2-column data frame. The 1st column is a sorted integer vector of the indexes of nonzero dimensions. Values in these dimensions are stored in the 2nd column as a numeric vector.- d
An integer. The dimensionality of

`X`

.`d`

MUST be no less than the maximum of all index vectors in`X`

.- zero
A numeric value. In the result matrix, entries not registered in

`X`

will be filled with`zero`

.- verbose
A boolean value.

`TRUE`

prints progress.

##### Value

A `d x N`

numeric matrix.

##### Examples

```
# NOT RUN {
N = 2000L
d = 3000L
X = matrix(rnorm(N * d) + 2, nrow = d)
# Fill many zeros in X:
X = apply(X, 2, function(x) {
x[sort(sample(d, d * runif(1, 0.95, 0.99)))] = 0; x})
# Get the sparse version of X.
sparseX = GMKMcharlie::d2s(X)
# Convert it back to dense.
X2 = GMKMcharlie::s2d(sparseX, d)
range(X - X2)
# }
```

*Documentation reproduced from package GMKMcharlie, version 1.0.3, License: GPL-3*

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