Merge branch 'release/6.8.1'

.zenodo.json

@@ -0,0 +1,30 @@
+{
+    "description": "<p>KM3Pipe - pipeline framework for KM3NeT.</p>", 
+    "license": "MIT", 
+    "title": "tamasgal/km3pipe: KM3Pipe 6.8.0", 
+    "upload_type": "software", 
+    "publication_date": "2017-06-14", 
+    "creators": [
+        {
+            "affiliation": "Erlangen Centre for Astroparticle Physics (ECAP)", 
+            "name": "Tamas Gal"
+        }, 
+        {
+            "affiliation": "Instituto de Física Corpuscular (IFIC)", 
+            "name": "Moritz Lotze"
+        }
+    ], 
+    "access_right": "open", 
+    "related_identifiers": [
+        {
+            "scheme": "url", 
+            "identifier": "https://github.com/tamasgal/km3pipe/tree/v6.8.0", 
+            "relation": "isSupplementTo"
+        }, 
+        {
+            "scheme": "doi", 
+            "identifier": "10.5281/zenodo.808829", 
+            "relation": "isPartOf"
+        }
+    ]
+}

CHANGELOG.rst

@@ -2,6 +2,11 @@ Unreleased changes
 ------------------
 
 
+6.8.1 / 2017-06-15
+------------------
+- DOI citation added
+- tohdf5: aa pump: make zed correction (mc tracks) optional
+
 6.8.0 / 2017-06-13
 ------------------
 * minor bugfixes

README.rst

@@ -3,12 +3,14 @@ KM3Pipe
 
 .. image:: https://travis-ci.org/tamasgal/km3pipe.svg?branch=develop
     :target: https://travis-ci.org/tamasgal/km3pipe
+.. image:: https://zenodo.org/badge/24634697.svg
+   :target: https://zenodo.org/badge/latestdoi/24634697
 
 KM3Pipe is a framework for KM3NeT related stuff including MC, data files, live access to detectors and databases, parsers for different file formats and an easy to use framework for batch processing.
 
 The framework tries to standardise the way the data is processed within our collaboration by providing a Pipeline-class, which can be used to put together different built-in or user made Pumps and Modules. Pumps act as data readers/parsers (from files, memory or even socket connections) and Modules take care of data processing and output. Such a Pipeline setup can then be used to iteratively process data in a file. In our case for example we store several thousands of neutrino interaction events in a bunch of files and KM3Pipe is used to put together an analysis chain which processes each event one-by-one.
 
-Although it is mainly designed for the KM3NeT neutrino detectors, it can easily be extended to support any kind of data formats. Feel free to get in touch if you’re looking for a small, versatile framework which provides a quite straightforward module system to make code exchange between your project members as easy as possible. KM3Pipe already comes with several types of Pumps (the modules which act as a data-parser/reader) so it should be easy to find an example to implement your owns. As of version 1.2.3 you find Pumps based on popular formats like HDF5 (https://www.hdfgroup.org), ROOT (https://root.cern.ch) but also some very specialised project internal binary data formats, which on the other hand can act templates for your own ones. Just have a look at the io subpackage and of course the documention if you’re interested!
+Although it is mainly designed for the KM3NeT neutrino detectors, it can easily be extended to support any kind of data formats. Feel free to get in touch if you’re looking for a small, versatile framework which provides a quite straightforward module system to make code exchange between your project members as easy as possible. KM3Pipe already comes with several types of Pumps (the modules which act as a data-parser/reader) so it should be easy to find an example to implement your owns. As of version 6.8.0 you find Pumps based on popular formats like HDF5 (https://www.hdfgroup.org), ROOT (https://root.cern.ch) but also some very specialised project internal binary data formats, which on the other hand can act templates for your own ones. Just have a look at the io subpackage and of course the documention if you’re interested!
 
 Read the docs at http://km3pipe.readthedocs.io (Currently outdated due to scipy compile issues)
 

docs/index.rst

@@ -11,6 +11,9 @@
 .. image:: https://img.shields.io/badge/docs-latest-brightgreen.svg?style=flat
     :target: http://km3pipe.readthedocs.io/en/latest/
 
+.. image:: https://zenodo.org/badge/24634697.svg
+   :target: https://zenodo.org/badge/latestdoi/24634697
+
 .. include:: summary.rst
 
 .. toctree::

docs/version.txt

@@ -1,2 +1,2 @@
-KM3Pipe 6.8.0
+KM3Pipe 6.8.1
 =============

km3pipe/__version__.py

@@ -28,7 +28,7 @@
 
 log = logging.getLogger(__name__)  # pylint: disable=C0103
 
-version_info = (6, 8, 0, 'final', 0)
+version_info = (6, 8, 1, 'final', 0)
 
 
 def _get_version(version_info):

km3pipe/io/aanet.py

@@ -43,6 +43,8 @@ class AanetPump(Pump):
         ``'minidst', 'jevt_jgandalf', 'generic_track', 'ancient_recolns'``
     use_aart_sps_lib: bool, optional [default=False]
         Use Aart's local SPS copy (@ Lyon) via ``gSystem.Load``?
+    apply_zed_correction: bool, optional [default=False]
+        correct ~400m offset in mc tracks.
     """
 
     def __init__(self, **context):
@@ -55,6 +57,7 @@ def __init__(self, **context):
         self.format = self.get('aa_fmt')
         self.use_id = self.get('use_id') or False
         self.use_aart_sps_lib = self.get('use_aart_sps_lib') or False
+        self.apply_zed_correction = self.get('apply_zed_correction') or False
         if self.additional:
             self.id = self.get('id')
             self.return_without_match = self.get("return_without_match")
@@ -171,7 +174,7 @@ def blob_generator(self):
 
     def _read_event(self, event, filename):
         try:
-            if event.det_id <= 0:  # apply ZED correction
+            if self.apply_zed_correction:  #if event.det_id <= 0:  # apply ZED correction
                 for track in event.mc_trks:
                     track.pos.z += 405.93
         except AttributeError:

km3pipe/utils/tohdf5.py

@@ -4,7 +4,7 @@
 Convert ROOT and EVT files to HDF5.
 
 Usage:
-    tohdf5 [-o OUTFILE] [-n EVENTS] [-e NROWS] [--aa-format=<fmt>] [--aa-lib=<lib.so>] FILE...
+    tohdf5 [-o OUTFILE] [-n EVENTS] [-e NROWS] [--correct-zed] [--aa-format=<fmt>] [--aa-lib=<lib.so>] FILE...
     tohdf5 [-o OUTFILE] [-n EVENTS] [-e NROWS] [-j] [-s] [-l] FILE...
     tohdf5 (-h | --help)
     tohdf5 --version
@@ -22,6 +22,7 @@
     -n EVENTS/RUNS             Number of events/runs.
     -o OUTFILE                 Output file.
     -s --with-summaryslices    Include summary slices [default: False]
+    --correct-zed              Correc toffset in mc tracks (aanet) [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
@@ -87,6 +88,7 @@ def main():
     aa_lib = args['--aa-lib']
     with_summaryslices = args['--with-summaryslices']
     with_timeslice_hits = args['--with-timeslice-hits']
+    correct_zed = args['--correct-zed']
     tohdf5(infiles,
            outfile,
            n,
@@ -96,4 +98,5 @@ def main():
            with_summaryslices=with_summaryslices,
            with_timeslice_hits=with_timeslice_hits,
            n_rows_expected=n_rows_expected,
+           apply_zed_correction=correct_zed,
            )