Command Line Tools¶
If you’ve installed KM3Pipe via pip
, you have access to some useful
command line utilities out of the box.
KM3Pipe¶
Most of the commands have to be prefixed with km3pipe
to avoid possible
nameclashes and also for an improved overview.
You can for example simply run km3pipe -h
in your shell to see all available
commands:
$ km3pipe --help
KM3Pipe command line utility.
Usage:
km3pipe test
km3pipe update [GIT_BRANCH]
km3pipe createconf [--overwrite] [--dump]
km3pipe detx DET_ID [-m] [-t T0_SET] [-c CALIBR_ID] [-o OUTFILE]
km3pipe detectors [-s REGEX] [--temporary]
km3pipe rundetsn [--temporary] RUN DETECTOR
km3pipe retrieve DET_ID RUN [-o OUTFILE]
km3pipe git
km3pipe git-short
km3pipe (-h | --help)
km3pipe --version
Options:
-h --help Show this screen.
-m Get the MC detector file (flips the sign of DET_ID).
-c CALIBR_ID Geometrical calibration ID (eg. A01466417)
-o OUTFILE Output filename.
-t T0_SET Time calibration ID (eg. A01466431)
-s REGEX Regular expression to filter the runsetup name/id.
--temporary Use a temporary session. [default: False]
--overwrite Overwrite existing config [default: False]
DET_ID Detector ID (eg. D_ARCA001).
DETECTOR Detector (eg. ARCA).
GIT_BRANCH Git branch to pull (eg. develop).
RUN Run number.
update
¶
The command km3pipe update [GIT_BRANCH]
should be used to (once installed)
get latest version of KM3Pipe. If no git branch is specified, it will pull
the master branch, which always holds the stable releases.
If you want to try the newest features, pull the develop branch via
km3pipe update develop
. This is 99.9% stable, since we always do our
experiments in feature/x
branches. However, we might break it sometimes.
Have a look at our git repository to see what we’re working on if you’re
interested.
runtable
¶
To get a list of runs taken with one of the KM3NeT detectors, you can use
the runtable
command.
The following command pulls the last 10 runs which matches the regular
expression PHYS
. In other words, you’ll get a list of physics runs:
km3pipe runtable -n 10 -s PHYS 14
An example output is:
RUN UNIXSTARTTIME STARTTIME_DEFINED RUNSETUPID RUNSETUPNAME T0_CALIBSETID DATETIME
848 3611 1465506000553 Y A01466427 PHYS.1606v1-TMP.HV-SFP.Power-XTRA.700ns 2016-06-09 21:00:00.553000+00:00
849 3612 1465506060554 Y A01466427 PHYS.1606v1-TMP.HV-SFP.Power-XTRA.700ns 2016-06-09 21:01:00.554000+00:00
850 3613 1465509600606 Y A01466427 PHYS.1606v1-TMP.HV-SFP.Power-XTRA.700ns 2016-06-09 22:00:00.606000+00:00
851 3614 1465509660607 Y A01466427 PHYS.1606v1-TMP.HV-SFP.Power-XTRA.700ns 2016-06-09 22:01:00.607000+00:00
852 3615 1465520400799 Y A01466427 PHYS.1606v1-TMP.HV-SFP.Power-XTRA.700ns 2016-06-10 01:00:00.799000+00:00
853 3616 1465520460800 Y A01466427 PHYS.1606v1-TMP.HV-SFP.Power-XTRA.700ns 2016-06-10 01:01:00.800000+00:00
854 3617 1465531200966 Y A01466427 PHYS.1606v1-TMP.HV-SFP.Power-XTRA.700ns 2016-06-10 04:00:00.966000+00:00
855 3618 1465531260967 Y A01466427 PHYS.1606v1-TMP.HV-SFP.Power-XTRA.700ns 2016-06-10 04:01:00.967000+00:00
856 3619 1465542000119 Y A01466427 PHYS.1606v1-TMP.HV-SFP.Power-XTRA.700ns 2016-06-10 07:00:00.119000+00:00
857 3620 1465542060119 Y A01466427 PHYS.1606v1-TMP.HV-SFP.Power-XTRA.700ns 2016-06-10 07:01:00.119000+00:00
triggersetup
¶
Get the trigger setup (description and optical/acoustic DataFilter settings) for a given runsetup ID:
$ triggersetup -h
Prints the trigger information of a given run setup.
Usage:
triggersetup RUNSETUP_OID
triggersetup (-h | --help)
triggersetup --version
Options:
RUNSETUP_OID The run setup identifier (e.g. A02004580)
-h --help Show this screen.
triggermap
¶
Shows a histogram (similar to the one on the online monitoring pages) of the trigger contribution for events:
$ triggermap -h
This script creates histogram which shows the trigger contribution for events.
Usage:
triggermap [-d DET_ID -p PLOT_FILENAME -u DU] FILENAME
triggermap --version
Option:
FILENAME Name of the input file.
-u DU Only plot for the given DU.
-d DET_ID Detector ID [default: 29].
-p PLOT_FILENAME The filename of the plot [default: trigger_map.png].
-h --help Show this screen.
DataBase¶
streamds
¶
The utility streamds
can be used to
interact with the database directly from the shell:
$ streamds --help
Access the KM3NeT StreamDS DataBase service.
Usage:
streamds
streamds list
streamds upload [-q] CSV_FILE
streamds info STREAM
streamds get STREAM [PARAMETERS...]
streamds (-h | --help)
streamds --version
Options:
STREAM Name of the stream.
CSV_FILE Tab separated data for the runsummary tables.
PARAMETERS List of parameters separated by space (e.g. detid=29).
-q Dryrun! This will upload the parameters with a TEST_ prefix.
-h --help Show this screen.
PipeInspector¶
PipeInspector is a tool to inspect different kinds of data formats used within the KM3NeT collaboration. It utilises the KM3Pipe framework to deal with data I/O and allows easy access to the stored information.
It is currently in an early alpha status, but already able to handle the DAQ binary data, ROOT and Aanet-ROOT format.
If you installed KM3Pipe via pip, you’ll be able to launch pipeinspector directly from the terminal:
pipeinspector /path/to/data/file.ext
HDF5 CLI Utils¶
tohdf
¶
Convert an aanet/root/evt/jpp file to hdf5.
Example:
tohdf5 --aa-fmt=jevt_jgandalf some_jgandalf_file.aa.root
Help output:
$ tohdf5 --help
Convert ROOT and EVT files to HDF5.
Usage:
tohdf5 [options] FILE...
tohdf5 (-h | --help)
tohdf5 --version
Options:
-h --help Show this screen.
-n EVENTS Number of events/runs.
-o OUTFILE Output file.
-j --jppy (Jpp): Use jppy (not aanet) for Jpp readout
-l --with-timeslice-hits (Jpp) Include timeslice-hits [default: False]
-s --with-summaryslices (Jpp) Include summary slices [default: False]
--aa-format=<fmt> (Aanet): Which aanet subformat ('minidst',
'orca_recolns', 'gandalf', 'gandalf_new',
'generic_track') [default: None]
--aa-lib=<lib.so> (Aanet): path to aanet binary (for old
versions which must be loaded via
`ROOT.gSystem.Load()` instead of `import aa`)
--aa-old-mc-id (aanet): read mc id as `evt.mc_id`, instead
of the newer `mc_id = evt.frame_index - 1`
--aa-run-id-from-header (Aanet) read run id from header, not event.
--correct-zed (Aanet) Correct offset in mc tracks (aanet)
[default: False]
--do-not-correct-mc-times (Aanet) Don't correct MC times.
--skip-header (Aanet) don't read the full header.
Entries like `genvol` and `neventgen` will
still be retrived. This switch enables
skipping the `get_aanet_header` function only.
[default: False]
--ignore-hits Don't read the hits, please [default: False].
-e --expected-rows NROWS Approximate number of events. Providing a
rough estimate for this (100, 10000000, ...)
will greatly improve reading/writing speed and
memory usage. Strongly recommended if the
table/array size is >= 100 MB. [default: 10000]
calibrate
¶
Apply calibration and time calibration to an HDF5 file.
Example:
calibrate km3net_jul13_90m_r1494.detx km3net_jul13_90m_muatm10T23.h5
$ calibrate -h
Apply calibration and time calibration from a DETX to an HDF5 file.
Usage:
calibrate DETXFILE HDF5FILE
calibrate (-h | --help)
calibrate --version
Options:
-h --help Show this screen.
hdf2root
¶
Convert a HDF5 file to a plain ROOT file (requires rootpy
+ root_numpy
).
Example:
hdf52root FOO.h5 BAR.h5
$ hdf2root --help
Convert HDF5 to vanilla ROOT.
Usage:
hdf2root FILES...
hdf2root (-h | --help)
Options:
-h --help Show this screen.
h5info
¶
Show some H5 metadata (KM3 H5 version, km3pipe version, etc).
Example:
$ h5info km3net_jul13_90m_muatm50T655.km3_v5r1.JTE_r2356.root.0-499.h5
format_version: b'4.1'
km3pipe: b'7.1.2.dev'
pytables: b'3.4.0'
$ h5info --help
Show the km3pipe etc. version used to write a H5 file.
Usage:
h5info FILE [-r]
h5info (-h | --help)
h5info --version
Options:
FILE Input file.
-r --raw Dump raw metadata.
-h --help Show this screen.
h5tree
¶
Print the structure of a H5 file + minimal metadata.
For a less pretty, more verbose output, use the ptdump
util instead.
Example:
$ h5tree elec.h5
KM3HDF5 v4.2
Number of Events: 169163
├── hits
│ ├── _indices
│ ├── channel_id
│ ├── dom_id
│ ├── event_id
│ ├── time
│ ├── tot
│ └── triggered
├── mc_hits
│ ├── _indices
│ ├── a
│ ├── event_id
│ ├── origin
│ ├── pmt_id
│ └── time
├── reco
│ └── gandalf
├── talala
ptdump
(from PyTables)¶
Inspect the contents of a HDF5 file, walking through all the subgroups.
Read the PyTables docs for more details.
Example output:
┌─[moritz@averroes ~/km3net/data ]
└─╼ ptdump nueCC.h5
/ (RootGroup) ''
/event_info (Table(121226,), shuffle, zlib(5)) ''
/hits (Table(0,), shuffle, zlib(5)) ''
/mc_hits (Table(0,), shuffle, zlib(5)) ''
/mc_tracks (Table(242452,), shuffle, zlib(5)) ''
/reco (Group) ''
/reco/aa_shower_fit (Table(121226,), shuffle, zlib(5)) ''
/reco/dusj (Table(121226,), shuffle, zlib(5)) ''
/reco/j_gandalf (Table(121226,), shuffle, zlib(5)) ''
/reco/q_strategy (Table(121226,), shuffle, zlib(5)) ''
/reco/reco_lns (Table(121226,), shuffle, zlib(5)) ''
/reco/thomas_features (Table(121226,), shuffle, zlib(5)) ''
pttree
(from PyTables)¶
Show the memory consumption of a HDF5 file. As you can see below, the overwhelming majority of space is used by the hits, as expected.
Example output:
┌─[moritz@ceres ~/pkg/km3pipe/examples/data ]
└─╼ pttree km3net_jul13_90m_muatm50T655.km3_v5r1.JTE_r2356.root.0-499.h5
------------------------------------------------------------
/ (RootGroup)
+--hits (Group)
| ... 7 leaves, mem=35.0MiB, disk=8.1MiB [66.3%]
+--mc_hits (Group)
| ... 6 leaves, mem=15.2MiB, disk=3.8MiB [31.6%]
+--mc_tracks (Table)
| mem=858.4KiB, disk=251.6KiB [ 2.0%]
`--event_info (Table)
mem=56.6KiB, disk=6.3KiB [ 0.1%]
------------------------------------------------------------
Total branch leaves: 15
Total branch size: 51.2MiB in memory, 12.2MiB on disk
Mean compression ratio: 0.24
HDF5 file size: 12.5MiB
------------------------------------------------------------
km3h5concat
¶
This tool can be used to merge HDF5 files:
$ km3h5concat -h
Concatenate KM3HDF5 files via pipeline.
Usage:
km3h5concat [options] OUTFILE FILE...
km3h5concat (-h | --help)
km3h5concat --version
Options:
-h --help Show this screen.
--verbose Print more output.
--debug Print everything.
-n=NEVENTS Number of events; if not given, use all.