# Tutorial

***Currently mattress only supports dense matrices. We are working on supporting sparse and delayed representations.***

## Dense matrices

To convert a numpy dense matrix to tatami representation

```python
import numpy as np
from mattress import tatamize

x = np.random.rand(1000, 100)

tatamat = tatamize(y)
```

### Specify orientation
Additionally you can also specify if the input matrix is a column or row major.

```python
x = np.ones((2, 3), order='F')
tatamat = tatamize(y, order="F")
```

## Methods
Methods are available to access the matrix by `row`, `column`

```python
tatamat.row(0)
tatamat.column(1)
```

and thats it for now. Stay tuned for more updates!!