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README.rst

The km3io Python package

https://api.codacy.com/project/badge/Grade/0660338483874475ba04f324de2123ec

This software provides a set of Python classes to read KM3NeT ROOT files without having ROOT, Jpp or aanet installed. It only depends on Python 3.5+ and the amazing uproot package and gives you access to the data via numpy arrays.

It's very easy to use and according to the uproot benchmarks, it is able to outperform the ROOT I/O performance.

Note: Beware that this package is in the development phase, so the API will change until version 1.0.0 is released!

Installation

Install km3io using pip:

pip install km3io

To get the latest (stable) development release:

pip install git+https://git.km3net.de/km3py/km3io.git

Reminder: km3io is not dependent on aanet, ROOT or Jpp!

Questions

If you have a question about km3io, please proceed as follows:

  • Read the documentation below.
  • Explore the examples in the documentation.
  • Haven't you found an answer to your question in the documentation, post a git issue with your question showing us an example of what you have tried first, and what you would like to do.
  • Have you noticed a bug, please post it in a git issue, we appreciate your contribution.

Tutorial

Table of contents:

Introduction

Most of km3net data is stored in root files. These root files are either created with Jpp or aanet software. A root file created with Jpp is often referred to as "a Jpp root file". Similarly, a root file created with aanet is often referred to as "an aanet file". In km3io, an aanet root file will always be reffered to as an offline file, while a Jpp root file will always be referred to as a daq file.

km3io is a Python package that provides a set of classes (DAQReader and OfflineReader) to read both daq root files and offline root files without any dependency to aanet, Jpp or ROOT.

Data in km3io is often returned as a "lazyarray", a "jagged lazyarray" or a Numpy array. A lazyarray is an array-like object that reads data on demand! In a lazyarray, only the first and the last chunks of data are read in memory. A lazyarray can be used with all Numpy's universal functions. Here is how a lazyarray looks like:

# <ChunkedArray [5971 5971 5971 ... 5971 5971 5971] at 0x7fb2341ad810>

A jagged array, is a 2+ dimentional array with different arrays lengths. In other words, a jagged array is an array of arrays of different sizes. So a jagged lazyarray is simply a jagged array of lazyarrays with different sizes. Here is how a jagged lazyarray looks like:

# <JaggedArray [[102 102 102 ... 11517 11518 11518] [] [101 101 102 ... 11518 11518 11518] ... [101 101 102 ... 11516 11516 11517] [] [101 101 101 ... 11517 11517 11518]] at 0x7f74b0ef8810>

Overview of daq files

# info needed here

Overview of offline files

# info needed here

DAQ files reader

# an update is needed here?

Currently only events (the KM3NET_EVENT tree) are supported but timeslices and summaryslices will be implemented very soon.

Let's have a look at some ORCA data (KM3NeT_00000044_00005404.root)

To get a lazy ragged array of the events:

import km3io as ki
events = ki.DAQReader("KM3NeT_00000044_00005404.root").events

That's it! Now let's have a look at the hits data:

>>> events
Number of events: 17023
>>> events[23].snapshot_hits.tot
array([28, 22, 17, 29,  5, 27, 24, 26, 21, 28, 26, 21, 26, 24, 17, 28, 23,29, 27, 24, 23, 26, 29, 25, 18, 28, 24, 28, 26, 20, 25, 31, 28, 23, 26, 21, 30, 33, 27, 16, 23, 24, 19, 24, 27, 22, 23, 21, 25, 16, 28, 22, 22, 29, 24, 29, 24, 24, 25, 25, 21, 31, 26, 28, 30, 42, 28], dtype=uint8)

Offline files reader

Let's have a look at some muons data from ORCA 4 lines simulations - run id 5971 (datav6.0test.jchain.aanet.00005971.root).

Note: this file was cropped to 10 events only, so don't be surprised in this tutorial if you see few events in the file.

First, let's read our file:

>>> import km3io as ki
>>> file = 'datav6.0test.jchain.aanet.00005971.root'
>>> r = ki.OfflineReader(file)
<km3io.aanet.OfflineReader at 0x7f24cc2bd550>

and that's it! Note that file can be either an str of your file path, or a path-like object.

To explore all the available branches in our offline file:

>>> r.keys
Events keys are:
      id
      det_id
      mc_id
      run_id
      mc_run_id
      frame_index
      trigger_mask
      trigger_counter
      overlays
      hits
      trks
      w
      w2list
      w3list
      mc_t
      mc_hits
      mc_trks
      comment
      index
      flags
      t.fSec
      t.fNanoSec
Hits keys are:
      hits.id
      hits.dom_id
      hits.channel_id
      hits.tdc
      hits.tot
      hits.trig
      hits.pmt_id
      hits.t
      hits.a
      hits.pos.x
      hits.pos.y
      hits.pos.z
      hits.dir.x
      hits.dir.y
      hits.dir.z
      hits.pure_t
      hits.pure_a
      hits.type
      hits.origin
      hits.pattern_flags
Tracks keys are:
      trks.fUniqueID
      trks.fBits
      trks.id
      trks.pos.x
      trks.pos.y
      trks.pos.z
      trks.dir.x
      trks.dir.y
      trks.dir.z
      trks.t
      trks.E
      trks.len
      trks.lik
      trks.type
      trks.rec_type
      trks.rec_stages
      trks.status
      trks.mother_id
      trks.fitinf
      trks.hit_ids
      trks.error_matrix
      trks.comment
Mc hits keys are:
      mc_hits.id
      mc_hits.dom_id
      mc_hits.channel_id
      mc_hits.tdc
      mc_hits.tot
      mc_hits.trig
      mc_hits.pmt_id
      mc_hits.t
      mc_hits.a
      mc_hits.pos.x
      mc_hits.pos.y
      mc_hits.pos.z
      mc_hits.dir.x
      mc_hits.dir.y
      mc_hits.dir.z
      mc_hits.pure_t
      mc_hits.pure_a
      mc_hits.type
      mc_hits.origin
      mc_hits.pattern_flags
Mc tracks keys are:
      mc_trks.fUniqueID
      mc_trks.fBits
      mc_trks.id
      mc_trks.pos.x
      mc_trks.pos.y
      mc_trks.pos.z
      mc_trks.dir.x
      mc_trks.dir.y
      mc_trks.dir.z
      mc_trks.t
      mc_trks.E
      mc_trks.len
      mc_trks.lik
      mc_trks.type
      mc_trks.rec_type
      mc_trks.rec_stages
      mc_trks.status
      mc_trks.mother_id
      mc_trks.fitinf
      mc_trks.hit_ids
      mc_trks.error_matrix
      mc_trks.comment

In an offline file, there are 5 main trees with data:

  • events tree
  • hits tree
  • tracks tree
  • mc hits tree
  • mc tracks tree

with km3io, these trees can be accessed with a simple tab completion:

https://git.km3net.de/km3py/km3io/raw/master/examples/pictures/events.png

In the following, we will explore each tree using km3io package.

reading events data

to read data in events tree with km3io:

>>> r.events
<OfflineEvents: 10 parsed events>

to get the total number of events in the events tree:

>>> len(r.events)
10

the branches stored in the events tree in an offline file can be easily accessed with a tab completion as seen below:

https://git.km3net.de/km3py/km3io/raw/master/examples/pictures/events.png

to get data from the events tree, chose any branch of interest with the tab completion, the following is a non exaustive set of examples.

to get event ids:

>>> r.events.id
<ChunkedArray [1 2 3 ... 8 9 10] at 0x7f249eeb6f10>

to get detector ids:

>>> r.events.det_id
<ChunkedArray [44 44 44 ... 44 44 44] at 0x7f249eeba050>

to get frame_index:

>>> r.events.frame_index
<ChunkedArray [182 183 202 ... 185 185 204] at 0x7f249eeba410>

to get snapshot hits:

>>> r.events.hits
<ChunkedArray [176 125 318 ... 84 255 105] at 0x7f249eebaa10>

to illustrate the strength of this data structure, we will play around with r.events.hits using Numpy universal functions.

>>> import numpy as np
>>> np.log(r.events.hits)
<ChunkedArray [5.170483995038151 4.8283137373023015 5.762051382780177 ... 4.430816798843313 5.541263545158426 4.653960350157523] at 0x7f249b8ebb90>

to get all data from one specific event (for example event 0):

>>> r.events[0]
offline event:
      id                  :               1
      det_id              :              44
      mc_id               :               0
      run_id              :            5971
      mc_run_id           :               0
      frame_index         :             182
      trigger_mask        :              22
      trigger_counter     :               0
      overlays            :              60
      hits                :             176
      trks                :              56
      w                   :              []
      w2list              :              []
      w3list              :              []
      mc_t                :             0.0
      mc_hits             :               0
      mc_trks             :               0
      comment             :             b''
      index               :               0
      flags               :               0
      t_fSec              :      1567036818
      t_fNanoSec          :       200000000

to get a specific value from event 0, for example the number of overlays:

>>> r.events[0].overlays
60

or the number of hits:

>>> r.events[0].hits
176

reading hits data

to read data in hits tree with km3io:

>>> r.hits
<OfflineHits: 10 parsed elements>

this shows that in our offline file, there are 10 events, with each event is associated a hits trees.

to have access to all data in a specific branche from the hits tree, you can use the tab completion:

https://git.km3net.de/km3py/km3io/raw/master/examples/pictures/hits.png

to get ALL the dom ids in all hits trees in our offline file:

>>> r.hits.dom_id
<ChunkedArray [[806451572 806451572 806451572 ... 809544061 809544061 809544061] [806451572 806451572 806451572 ... 809524432 809526097 809544061] [806451572 806451572 806451572 ... 809544061 809544061 809544061] ... [806451572 806455814 806465101 ... 809526097 809544058 809544061] [806455814 806455814 806455814 ... 809544061 809544061 809544061] [806455814 806455814 806455814 ... 809544058 809544058 809544061]] at 0x7f249eebac50>

to get ALL the time over threshold (tot) in all hits trees in our offline file:

>>> r.hits.tot
<ChunkedArray [[24 30 22 ... 38 26 23] [29 26 22 ... 26 28 24] [27 19 13 ... 27 24 16] ... [22 22 9 ... 27 32 27] [30 32 17 ... 30 24 29] [27 41 36 ... 29 24 28]] at 0x7f249eec9050>

if you are interested in a specific event (let's say event 0), you can access the corresponding hits tree by doing the following:

>>> r[0].hits
<OfflineHits: 176 parsed elements>

notice that now there are 176 parsed elements (as opposed to 10 elements parsed when r.hits is called). This means that in event 0 there are 176 hits! To get the dom ids from this event:

>>> r[0].hits.dom_id
array([806451572, 806451572, 806451572, 806451572, 806455814, 806455814,
   806455814, 806483369, 806483369, 806483369, 806483369, 806483369,
   806483369, 806483369, 806483369, 806483369, 806483369, 806487219,
   806487226, 806487231, 806487231, 808432835, 808435278, 808435278,
   808435278, 808435278, 808435278, 808447180, 808447180, 808447180,
   808447180, 808447180, 808447180, 808447180, 808447180, 808447186,
   808451904, 808451904, 808472265, 808472265, 808472265, 808472265,
   808472265, 808472265, 808472265, 808472265, 808488895, 808488990,
   808488990, 808488990, 808488990, 808488990, 808489014, 808489014,
   808489117, 808489117, 808489117, 808489117, 808493910, 808946818,
   808949744, 808951460, 808951460, 808951460, 808951460, 808951460,
   808956908, 808956908, 808959411, 808959411, 808959411, 808961448,
   808961448, 808961504, 808961504, 808961655, 808961655, 808961655,
   808964815, 808964815, 808964852, 808964908, 808969857, 808969857,
   808969857, 808969857, 808969857, 808972593, 808972698, 808972698,
   808972698, 808974758, 808974758, 808974758, 808974758, 808974758,
   808974758, 808974758, 808974758, 808974758, 808974758, 808974758,
   808974773, 808974773, 808974773, 808974773, 808974773, 808974972,
   808974972, 808976377, 808976377, 808976377, 808979567, 808979567,
   808979567, 808979721, 808979721, 808979721, 808979721, 808979721,
   808979721, 808979721, 808979729, 808979729, 808979729, 808981510,
   808981510, 808981510, 808981510, 808981672, 808981672, 808981672,
   808981672, 808981672, 808981672, 808981672, 808981672, 808981672,
   808981672, 808981672, 808981672, 808981672, 808981672, 808981672,
   808981672, 808981672, 808981812, 808981812, 808981812, 808981864,
   808981864, 808982005, 808982005, 808982005, 808982018, 808982018,
   808982018, 808982041, 808982041, 808982077, 808982077, 808982547,
   808982547, 808982547, 808997793, 809006037, 809524432, 809526097,
   809526097, 809544061, 809544061, 809544061, 809544061, 809544061,
   809544061, 809544061], dtype=int32

to get all data of a specific hit (let's say hit 0) from event 0:

>>>r[0].hits[0]
offline hit:
      id                  :               0
      dom_id              :       806451572
      channel_id          :               8
      tdc                 :               0
      tot                 :              24
      trig                :               1
      pmt_id              :               0
      t                   :      70104010.0
      a                   :             0.0
      pos_x               :             0.0
      pos_y               :             0.0
      pos_z               :             0.0
      dir_x               :             0.0
      dir_y               :             0.0
      dir_z               :             0.0
      pure_t              :             0.0
      pure_a              :             0.0
      type                :               0
      origin              :               0
      pattern_flags       :               0

to get a specific value from hit 0 in event 0, let's say for example the dom id:

>>>r[0].hits[0].dom_id
806451572

reading tracks data

to read data in tracks tree with km3io:

>>> r.tracks
<OfflineTracks: 10 parsed elements>

this shows that in our offline file, there are 10 parsed elements (events), each event is associated with tracks data.

to have access to all data in a specific branche from the tracks tree, you can use the tab completion:

https://git.km3net.de/km3py/km3io/raw/master/examples/pictures/tracks.png

to get ALL the cos(zenith angle) in all tracks tree in our offline file:

>>> r.tracks.dir_z
<ChunkedArray [[-0.872885221293917 -0.872885221293917 -0.872885221293917 ... -0.6631226836266504 -0.5680647731737454 -0.5680647731737454] [-0.8351996698137462 -0.8351996698137462 -0.8351996698137462 ... -0.7485107718446855 -0.8229838871876581 -0.239315690284641] [-0.989148723802379 -0.989148723802379 -0.989148723802379 ... -0.9350162572437829 -0.88545604390297 -0.88545604390297] ... [-0.5704611045902105 -0.5704611045902105 -0.5704611045902105 ... -0.9350162572437829 -0.4647231989130516 -0.4647231989130516] [-0.9779941383490359 -0.9779941383490359 -0.9779941383490359 ... -0.88545604390297 -0.88545604390297 -0.8229838871876581] [-0.7396916780974963 -0.7396916780974963 -0.7396916780974963 ... -0.6631226836266504 -0.7485107718446855 -0.7485107718446855]] at 0x7f249eed2090>

to get ALL the tracks likelihood in our offline file:

>>> r.tracks.lik
<ChunkedArray [[294.6407542676734 294.6407542676734 294.6407542676734 ... 67.81221253265059 67.7756405143316 67.77250505700384] [96.75133289411137 96.75133289411137 96.75133289411137 ... 39.21916536442286 39.184645826013806 38.870325146341884] [560.2775306614813 560.2775306614813 560.2775306614813 ... 118.88577278801066 118.72271313687405 117.80785995187605] ... [71.03251451148226 71.03251451148226 71.03251451148226 ... 16.714140573909347 16.444395245214945 16.34639241716669] [326.440133294878 326.440133294878 326.440133294878 ... 87.79818671079849 87.75488082571873 87.74839444768625] [159.77779654216795 159.77779654216795 159.77779654216795 ... 33.8669134999348 33.821631538334984 33.77240735670646]] at 0x7f249eed2590>

if you are interested in a specific event (let's say event 0), you can access the corresponding tracks tree by doing the following:

>>> r[0].tracks
<OfflineTracks: 56 parsed elements>

notice that now there are 56 parsed elements (as opposed to 10 elements parsed when r.tracks is called). This means that in event 0 there is data about 56 possible tracks! To get the tracks likelihood from this event:

>>> r[0].tracks.lik
array([294.64075427, 294.64075427, 294.64075427, 291.64653113,
   291.27392663, 290.69031512, 289.19290546, 289.08449217,
   289.03373947, 288.19030836, 282.92343367, 282.71527118,
   282.10762402, 280.20553861, 275.93183966, 273.01809111,
   257.46433694, 220.94357656, 194.99426403, 190.47809685,
    79.95235686,  78.94389763,  78.90791169,  77.96122466,
    77.9579604 ,  76.90769883,  75.97546175,  74.91530508,
    74.9059469 ,  72.94007716,  72.90467038,  72.8629316 ,
    72.81280833,  72.80229533,  72.78899435,  71.82404165,
    71.80085542,  71.71028058,  70.91130096,  70.89150223,
    70.85845637,  70.79081796,  70.76929743,  69.80667603,
    69.64058976,  68.93085058,  68.84304037,  68.83154232,
    68.79944298,  68.79019375,  68.78581291,  68.72340328,
    67.86628937,  67.81221253,  67.77564051,  67.77250506])

to get all data of a specific track (let's say track 0) from event 0:

>>>r[0].tracks[0]
offline track:
      fUniqueID                      :                           0
      fBits                          :                    33554432
      id                             :                           1
      pos_x                          :            445.835395997812
      pos_y                          :           615.1089636184813
      pos_z                          :           125.1448339836911
      dir_x                          :          0.0368711082700674
      dir_y                          :        -0.48653048395923415
      dir_z                          :          -0.872885221293917
      t                              :           70311446.46401498
      E                              :           99.10458562488608
      len                            :                         0.0
      lik                            :           294.6407542676734
      type                           :                           0
      rec_type                       :                        4000
      rec_stages                     :                [1, 3, 5, 4]
      status                         :                           0
      mother_id                      :                          -1
      hit_ids                        :                          []
      error_matrix                   :                          []
      comment                        :                           0
      JGANDALF_BETA0_RAD             :        0.004957442219414389
      JGANDALF_BETA1_RAD             :        0.003417848024252858
      JGANDALF_CHI2                  :          -294.6407542676734
      JGANDALF_NUMBER_OF_HITS        :                       142.0
      JENERGY_ENERGY                 :           99.10458562488608
      JENERGY_CHI2                   :     1.7976931348623157e+308
      JGANDALF_LAMBDA                :      4.2409761837248484e-12
      JGANDALF_NUMBER_OF_ITERATIONS  :                        10.0
      JSTART_NPE_MIP                 :           24.88469697331908
      JSTART_NPE_MIP_TOTAL           :           55.88169412579765
      JSTART_LENGTH_METRES           :           98.89582506402911
      JVETO_NPE                      :                         0.0
      JVETO_NUMBER_OF_HITS           :                         0.0
      JENERGY_MUON_RANGE_METRES      :           344.9767431592819
      JENERGY_NOISE_LIKELIHOOD       :         -333.87773581129136
      JENERGY_NDF                    :                      1471.0
      JENERGY_NUMBER_OF_HITS         :                       101.0

to get a specific value from track 0 in event 0, let's say for example the liklihood:

>>>r[0].tracks[0].lik
294.6407542676734

reading mc hits data

to read mc hits data:

>>>r.mc_hits
<OfflineHits: 10 parsed elements>

that's it! All branches in mc hits tree can be accessed in the exact same way described in the section reading hits data . All data is easily accesible and if you are stuck, hit tab key to see all the available branches:

https://git.km3net.de/km3py/km3io/raw/master/examples/pictures/mc_hits.png

reading mc tracks data

to read mc tracks data:

>>>r.mc_tracks
<OfflineTracks: 10 parsed elements>

that's it! All branches in mc tracks tree can be accessed in the exact same way described in the section reading tracks data . All data is easily accesible and if you are stuck, hit tab key to see all the available branches:

https://git.km3net.de/km3py/km3io/raw/master/examples/pictures/mc_tracks.png