From 0bb9553e2c58d225c05e9ff3bd1fc6934fb1e64e Mon Sep 17 00:00:00 2001
From: Tamas Gal <tgal@km3net.de>
Date: Thu, 13 Feb 2020 20:06:39 +0100
Subject: [PATCH] Update
---
talks/premiere.org | 43 +++++++++++++++++++++++++++----------------
1 file changed, 27 insertions(+), 16 deletions(-)
diff --git a/talks/premiere.org b/talks/premiere.org
index 3f6e093..a86bae0 100644
--- a/talks/premiere.org
+++ b/talks/premiere.org
@@ -51,21 +51,31 @@ pip install -e ~/Dev/km3io
- *Goal*: provide a **standalone**, **independent** access to KM3NeT data
- Uses the [[https://github.com/scikit-hep/uproot][uproot]] library to access ROOT data
- Provides convenient wrapper classes
-- Maximum performance due to numpy and numba
+- Maximum performance due to [[https://www.numpy.org][numpy]] and [[http://numba.pydata.org][numba]]
- Data are read lazily:
- only loaded into memory when directly accessed
- apply several cut masks on huge datasets without reading them into the memory
+** uproot
+- Describe the projec
+- describe Scikit-HEP
+- thanks to Jim
+- etc.
+
** Installation
- Dependencies:
- Python 3.5+
- uproot (a small Python package, installed automatically via ~pip~)
+ - no binaries!
- *No ROOT, Jpp or aanet* required to read ROOT files
- Releases are published on the official Python package repository:
- ~pip install km3io~
** Why is it so cool?
- Runs on Linux, macOS, Windows, as long as Python 3.5+ is installed
- Every data is a ~numpy~ array or ~awkward~ array (~numpy~ compatible array of complex data structures)
+** awkward arrays?
+- some details on it
+- maybe the link to the talk which Jim gave on a HEP conference about awkward arrays
* Accessing Online (DAQ) Data
** km3io supports the following DAQ datatypes
@@ -85,7 +95,8 @@ pip install -e ~/Dev/km3io
*** Opening a run file
#+BEGIN_SRC python :results output replace :session km3io :exports both
import km3io
-f = km3io.DAQReader("KM3NeT_00000044_00006880.root") # Random run from iRODS
+# A run from iRODS
+f = km3io.DAQReader("KM3NeT_00000044_00006880.root")
print(f.events)
print(f.summaryslices)
print(f.timeslices)
@@ -94,7 +105,7 @@ print(f.timeslices)
#+RESULTS:
: Number of events: 115038
: Number of summaryslices: 182668
-: Available timeslice streams: SN, L1
+: Available timeslice streams: L1, SN
*** Investigating timeslice frames
@@ -121,6 +132,8 @@ print(a_timeslice.frames[806451572].pmt[:42])
*** Checking the number of UDP packets in summary slices
+- functions to parse binary masks and bit positions from the KM3NeT format definitions
+
#+BEGIN_SRC python :results output replace :session km3io :exports both
f = km3io.DAQReader("KM3NeT_00000044_00006880.root")
sumslice = f.summaryslices.slices[23]
@@ -144,14 +157,15 @@ print(km3io.daq.get_number_udp_packets(sumslice.dq_status))
* Offline (MC/reco) Data
** Reading offline files (aka aanet-ROOT files)
-#+ATTR_REVEAL: :frag (appear)
- Events
- header information
- hits
- - tracks (from reconstruction)
- - MC tracks
- MC information
+ - MC tracks
+ - MC hits
- Reco information
+ - tracks
+ - reconstruction info and parameters
** Opening a reconstructed MUPAGE file
#+BEGIN_SRC python :results output replace :session km3io :exports both
@@ -160,7 +174,7 @@ print(f)
#+END_SRC
#+RESULTS:
-: <km3io.offline.OfflineReader object at 0x7f8eeb436e20>
+: <km3io.offline.OfflineReader object at 0x1155bde50>
** Investigating events and tracks
#+BEGIN_SRC python :results output replace :session km3io :exports both
@@ -210,7 +224,7 @@ offline hit:
pattern_flags : 0
#+end_example
-*** Tracks
+*** Tracks :noexportpresentation:
#+BEGIN_SRC python :results output replace :session km3io :exports both
print(f[0].tracks[0])
@@ -262,18 +276,15 @@ offline track:
** Extracting the energy of every first reco track in each event
#+BEGIN_SRC python :results output replace :session km3io :exports both
+# from irods:mc/v5.2/mcv5.2.mupage_10T.sirene.jte.1186.root
f = km3io.OfflineReader("mupage.root")
-print(f.mc_tracks)
-print(f.mc_tracks.id.counts)
-mask = f.mc_tracks.id.counts > 0
+print(f.events)
+# number of tracks per event
+print(f.mc_tracks.E.counts)
+mask = f.mc_tracks.E.counts > 0
print(f.mc_tracks.E[mask, 0])
#+END_SRC
-#+RESULTS:
-: Number of tracks: 12236
-: [11 2 3 ... 10 1 4]
-: [17.72 73.213 10884.78 1694.332 1221.061 22945.123 11019.418 ...]
-
* ORCA DU4 RBR Analysis Example
** A tiny function to extract track attributes from a list of files
--
GitLab