root_numpy.array2tree¶

root_numpy.array2tree(arr, name='tree', tree=None)¶

Convert a numpy structured array into a ROOT TTree.

Fields of basic types, strings, and fixed-size subarrays of basic types are supported. np.object and np.float16 are currently not supported.

Parameters:

arr : array

A numpy structured array

name : str (optional, default=’tree’)

Name of the created ROOT TTree if tree is None.

tree : ROOT TTree (optional, default=None)

An existing ROOT TTree to be extended by the numpy array. Any branch with the same name as a field in the numpy array will be extended as long as the types are compatible, otherwise a TypeError is raised. New branches will be created and filled for all new fields.

Returns:

root_tree : a ROOT TTree

Notes

When using the tree argument to extend and/or add new branches to an existing tree, note that it is possible to create branches of different lengths. This will result in a warning from ROOT when root_numpy calls the tree’s SetEntries() method. Beyond that, the tree should still be usable. While it might not be generally recommended to create branches with differing lengths, this behaviour could be required in certain situations. root_numpy makes no attempt to prevent such behaviour as this would be more strict than ROOT itself. Also see the note about converting trees that have branches of different lengths into numpy arrays in the documentation of tree2array().

Examples

Convert a numpy array into a tree:

>>> from root_numpy import array2tree
>>> import numpy as np
>>>
>>> a = np.array([(1, 2.5, 3.4),
...               (4, 5, 6.8)],
...              dtype=[('a', np.int32),
...                     ('b', np.float32),
...                     ('c', np.float64)])
>>> tree = array2tree(a)
>>> tree.Scan()
************************************************
*    Row   *         a *         b *         c *
************************************************
*        0 *         1 *       2.5 *       3.4 *
*        1 *         4 *         5 *       6.8 *
************************************************

Add new branches to an existing tree (continuing from the example above):

>>> b = np.array([(4, 10),
...               (3, 5)],
...              dtype=[('d', np.int32),
...                     ('e', np.int32)])
>>> array2tree(b, tree=tree)
<ROOT.TTree object ("tree") at 0x1449970>
>>> tree.Scan()
************************************************************************
*    Row   *         a *         b *         c *         d *         e *
************************************************************************
*        0 *         1 *       2.5 *       3.4 *         4 *        10 *
*        1 *         4 *         5 *       6.8 *         3 *         5 *
************************************************************************