This tutorial illustrates the conversion of STL vectors and TVec to numpy
arrays without copying the data.
The memory-adoption is achieved by the dictionary **array_interface**, which
is added dynamically to the Python objects by PyROOT.

**Author:** Stefan Wunsch

*This notebook tutorial was automatically generated with ROOTBOOK-izer from the macro found in the ROOT repository on Thursday, June 04, 2020 at 02:46 AM.*

In [1]:

```
import ROOT
from sys import exit
try:
import numpy as np
except:
exit()
```

Create a vector ROOT object and assign values Note that this works as well with a TVec

In [2]:

```
vec = ROOT.std.vector("float")(2)
vec[0] = 1
vec[1] = 2
print("Content of the ROOT vector object: {}".format([x for x in vec]))
```

Interface ROOT vector with a numpy array

In [3]:

```
array = np.asarray(vec)
print("Content of the associated numpy array: {}".format([x for x in array]))
```

The numpy array adopts the memory of the vector without copying the content. Note that the first entry of the numpy array changes when assigning a new value to the first entry of the ROOT vector.

In [4]:

```
vec[0] = 42
print(
"Content of the numpy array after changing the first entry of the ROOT vector: {}".
format([x for x in array]))
```

Use numpy features on data of ROOT objects

In [5]:

```
print("Mean of the numpy array entries: {}".format(np.mean(array)))
```