I use the version you give for the 13 TeV Tutorial for Education Ubuntu 18.4.3 Root 6.18 and ATLAS-Open-Data-ubuntu-v4 from Zenodo
This works well with the 13 TeV data
This does not work with the 13 TeV 2025 beta Tutorial you give. It seems that it is a problem of root version and (or) C++ compiler.
What can i do?
We also tried to resolve this by email, but for the record here as well, this can be done via docker:
# Start the docker container
docker run -it -p 8888:8888 ghcr.io/atlas-outreach-data-tools/notebooks-collection-opendata:latest /usr/bin/bash
# This is only necessary if you don’t have a local version of the repository already
git clone https://github.com/atlas-outreach-data-tools/atlas-outreach-cpp-framework-13tev.git
cd atlas-outreach-cpp-framework-13tev/Analysis/TTbarAnalysis
# If you need to make any changes to e.g. where the files are stored, do that now
./run.sh
In addition, if there are local files you’d like to use, for example to mount the directory in my system /path/to/directory so that it’s available in the Docker container as /something, then I can instead run:
docker run -it -p 8888:8888 --mount type=bind,src=/path/to/directory,dst=/something ghcr.io/atlas-outreach-data-tools/notebooks-collection-opendata:latest /usr/bin/bash
You can use multiple --mount options to mount multiple directories, for example if one area holds code, another area holds input files, and a third area is where you would like to store your output files.
We’ll update our documentation on this point shortly.
Cheers,
Zach
Thanks
The uproot versions wiith Anaconda works well but are too slow for gaming labtops
The C++ version can use the multicore labtops with very shorter execution time
For Oracle VM
perhaps there is a more recent of ATLAS-Open-Data-Ubuntu-2020-v4 .ova Zenodo file
wich have (6.18.03) root version:
which install the good Root and Gcc versions to run 2025 data
GCC Version: 11.5.0 ROOT Version: 6.34.06 as you said to run 2025 data
Our newer notebooks, including the H>mu mu and ttbar analysis ones, should run in a multicore mode as well:
The H>gamma gamma and H>ZZ notebooks should run in under 10-15 minutes, but they rely on a fast internet connection to read samples. With a local copy of the data, it should run faster than that.
We don’t currently intend to support VMs further.
Cheers,
Zach
I get this error in mybinder
IndexError Traceback (most recent call last)
Cell In[17], line 3
1 data_all_2 = {
2 “Data”: {
----> 3 “Weight”: ak.Array([1/2] * 2 * len(data_all[“Data”][“mtop_2”])),
4 “mtop”: ak.flatten([data_all[“Data”][“mtop_1”], data_all[“Data”][“mtop_2”]])
5 },
6 “ttbar”: {
7 “Weight”: ak.flatten([data_all[“ttbar”][“Weight”], data_all[“ttbar”][“Weight”]]) / 2,
8 “mtop”: ak.flatten([data_all[“ttbar”][“mtop_1”], data_all[“ttbar”][“mtop_2”]])
9 },
10 “diboson”: {
11 “Weight”: ak.flatten([data_all[“diboson”][“Weight”], data_all[“diboson”][“Weight”]]) / 2,
12 “mtop”: ak.flatten([data_all[“diboson”][“mtop_1”], data_all[“diboson”][“mtop_2”]])
13 },
14 “single_top”: {
15 “Weight”: ak.flatten([data_all[“single_top”][“Weight”], data_all[“single_top”][“Weight”]]) / 2,
16 “mtop”: ak.flatten([data_all[“single_top”][“mtop_1”], data_all[“single_top”][“mtop_2”]])
17 }
18 }
File /srv/conda/envs/notebook/lib/python3.11/site-packages/awkward/highlevel.py:1105, in Array.getitem(self, where)
676 def getitem(self, where):
677 “”"
678 Args:
679 where (many types supported; see below): Index of positions to
(…)
1103 have the same dimension as the array being indexed.
1104 “”"
→ 1105 with ak.errors.SlicingErrorContext(self, where):
1106 # Handle named axis
1107 (, ndim) = self._layout.minmax_depth
1108 named_axis = _get_named_axis(self)
File /srv/conda/envs/notebook/lib/python3.11/site-packages/awkward/_errors.py:80, in ErrorContext.exit(self, exception_type, exception_value, traceback)
78 self._slate.dict.clear()
79 # Handle caught exception
—> 80 raise self.decorate_exception(exception_type, exception_value)
81 else:
82 # Step out of the way so that another ErrorContext can become primary.
83 if self.primary() is self:
File /srv/conda/envs/notebook/lib/python3.11/site-packages/awkward/highlevel.py:1113, in Array.getitem(self, where)
1109 where = _normalize_named_slice(named_axis, where, ndim)
1111 NamedAxis.mapping = named_axis
→ 1113 indexed_layout = prepare_layout(self._layout._getitem(where, NamedAxis))
1115 if NamedAxis.mapping:
1116 return ak.operations.ak_with_named_axis._impl(
1117 indexed_layout,
1118 named_axis=NamedAxis.mapping,
(…)
1121 attrs=self._attrs,
1122 )
File /srv/conda/envs/notebook/lib/python3.11/site-packages/awkward/contents/content.py:551, in Content._getitem(self, where, named_axis)
548 return self._getitem((where,), named_axis)
550 elif isinstance(where, str):
→ 551 return self._getitem_field(where)
553 elif where is np.newaxis:
554 return self._getitem((where,), named_axis)
File /srv/conda/envs/notebook/lib/python3.11/site-packages/awkward/contents/emptyarray.py:192, in EmptyArray._getitem_field(self, where, only_fields)
189 def _getitem_field(
190 self, where: str | SupportsIndex, only_fields: tuple[str, …] = ()
191 ) → Content:
→ 192 raise ak._errors.index_error(self, where, “not an array of records”)
IndexError: cannot slice EmptyArray (of length 0) with ‘mtop_2’: not an array of records
This error occurred while attempting to slice
<Array [] type='0 * unknown'>
with
'mtop_2'
Which notebook are you trying to run, and have you made any changes to it?
Cheers,
Zach
ttbar analysis with no change