# NumPy - Matrix Library

NumPy package contains a Matrix library numpy.matlib. This module has functions that return matrices instead of ndarray objects.

## matlib.empty()

The matlib.empty() function returns a new matrix without initializing the entries. The function takes the following parameters.

```numpy.matlib.empty(shape, dtype, order)
```

Where,

Sr.No. Parameter & Description
1

shape

int or tuple of int defining the shape of the new matrix

2

Dtype

Optional. Data type of the output

3

order

C or F

### Example

```import numpy.matlib
import numpy as np

print np.matlib.empty((2,2))
# filled with random data
```

It will produce the following output −

```[[ 2.12199579e-314,   4.24399158e-314]
[ 4.24399158e-314,   2.12199579e-314]]
```

## numpy.matlib.zeros()

This function returns the matrix filled with zeros.

```import numpy.matlib
import numpy as np
print np.matlib.zeros((2,2))
```

It will produce the following output −

```[[ 0.  0.]
[ 0.  0.]]
```

## numpy.matlib.ones()

This function returns the matrix filled with 1s.

```import numpy.matlib
import numpy as np
print np.matlib.ones((2,2))
```

It will produce the following output −

```[[ 1.  1.]
[ 1.  1.]]
```

## numpy.matlib.eye()

This function returns a matrix with 1 along the diagonal elements and the zeros elsewhere. The function takes the following parameters.

```numpy.matlib.eye(n, M,k, dtype)
```

Where,

Sr.No. Parameter & Description
1

n

The number of rows in the resulting matrix

2

M

The number of columns, defaults to n

3

k

Index of diagonal

4

dtype

Data type of the output

### Example

```import numpy.matlib
import numpy as np
print np.matlib.eye(n = 3, M = 4, k = 0, dtype = float)
```

It will produce the following output −

```[[ 1.  0.  0.  0.]
[ 0.  1.  0.  0.]
[ 0.  0.  1.  0.]]
```

## numpy.matlib.identity()

The numpy.matlib.identity() function returns the Identity matrix of the given size. An identity matrix is a square matrix with all diagonal elements as 1.

```import numpy.matlib
import numpy as np
print np.matlib.identity(5, dtype = float)
```

It will produce the following output −

```[[ 1.  0.  0.  0.  0.]
[ 0.  1.  0.  0.  0.]
[ 0.  0.  1.  0.  0.]
[ 0.  0.  0.  1.  0.]
[ 0.  0.  0.  0.  1.]]
```

## numpy.matlib.rand()

The numpy.matlib.rand() function returns a matrix of the given size filled with random values.

### Example

```import numpy.matlib
import numpy as np
print np.matlib.rand(3,3)
```

It will produce the following output −

```[[ 0.82674464  0.57206837  0.15497519]
[ 0.33857374  0.35742401  0.90895076]
[ 0.03968467  0.13962089  0.39665201]]
```

Note that a matrix is always two-dimensional, whereas ndarray is an n-dimensional array. Both the objects are inter-convertible.

### Example

```import numpy.matlib
import numpy as np

i = np.matrix('1,2;3,4')
print i
```

It will produce the following output −

```[[1  2]
[3  4]]
```

### Example

```import numpy.matlib
import numpy as np

j = np.asarray(i)
print j
```

It will produce the following output −

```[[1  2]
[3  4]]
```

### Example

```import numpy.matlib
import numpy as np

k = np.asmatrix (j)
print k
```

It will produce the following output −

```[[1  2]
[3  4]]
```