# HG changeset patch
# User Daniel Wolff
# Date 1455988464 -3600
# Node ID e34cf1b6fe09e3b4c1cac9c722d86c40e9a4d3c6

commit

diff -r 000000000000 -r e34cf1b6fe09 .hg_archival.txt
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/.hg_archival.txt	Sat Feb 20 18:14:24 2016 +0100
@@ -0,0 +1,6 @@
+repo: 5338cdb8ab02aa075b105d89db072ea3f2a2d411
+node: bf372b30d2e3bbf4ffbd6061ca79676f9d0d233e
+branch: public
+latesttag: null
+latesttagdistance: 280
+changessincelatesttag: 317
diff -r 000000000000 -r e34cf1b6fe09 .hgignore
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/.hgignore	Sat Feb 20 18:14:24 2016 +0100
@@ -0,0 +1,5 @@
+\.orig$
+\.orig\..*$
+\.chg\..*$
+\.rej$
+\.pyc$
diff -r 000000000000 -r e34cf1b6fe09 COPYING
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/COPYING	Sat Feb 20 18:14:24 2016 +0100
@@ -0,0 +1,674 @@
+                    GNU GENERAL PUBLIC LICENSE
+                       Version 3, 29 June 2007
+
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+by the Free Software Foundation.
+
+  If the Program specifies that a proxy can decide which future
+versions of the GNU General Public License can be used, that proxy's
+public statement of acceptance of a version permanently authorizes you
+to choose that version for the Program.
+
+  Later license versions may give you additional or different
+permissions.  However, no additional obligations are imposed on any
+author or copyright holder as a result of your choosing to follow a
+later version.
+
+  15. Disclaimer of Warranty.
+
+  THERE IS NO WARRANTY FOR THE PROGRAM, TO THE EXTENT PERMITTED BY
+APPLICABLE LAW.  EXCEPT WHEN OTHERWISE STATED IN WRITING THE COPYRIGHT
+HOLDERS AND/OR OTHER PARTIES PROVIDE THE PROGRAM "AS IS" WITHOUT WARRANTY
+OF ANY KIND, EITHER EXPRESSED OR IMPLIED, INCLUDING, BUT NOT LIMITED TO,
+THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
+PURPOSE.  THE ENTIRE RISK AS TO THE QUALITY AND PERFORMANCE OF THE PROGRAM
+IS WITH YOU.  SHOULD THE PROGRAM PROVE DEFECTIVE, YOU ASSUME THE COST OF
+ALL NECESSARY SERVICING, REPAIR OR CORRECTION.
+
+  16. Limitation of Liability.
+
+  IN NO EVENT UNLESS REQUIRED BY APPLICABLE LAW OR AGREED TO IN WRITING
+WILL ANY COPYRIGHT HOLDER, OR ANY OTHER PARTY WHO MODIFIES AND/OR CONVEYS
+THE PROGRAM AS PERMITTED ABOVE, BE LIABLE TO YOU FOR DAMAGES, INCLUDING ANY
+GENERAL, SPECIAL, INCIDENTAL OR CONSEQUENTIAL DAMAGES ARISING OUT OF THE
+USE OR INABILITY TO USE THE PROGRAM (INCLUDING BUT NOT LIMITED TO LOSS OF
+DATA OR DATA BEING RENDERED INACCURATE OR LOSSES SUSTAINED BY YOU OR THIRD
+PARTIES OR A FAILURE OF THE PROGRAM TO OPERATE WITH ANY OTHER PROGRAMS),
+EVEN IF SUCH HOLDER OR OTHER PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF
+SUCH DAMAGES.
+
+  17. Interpretation of Sections 15 and 16.
+
+  If the disclaimer of warranty and limitation of liability provided
+above cannot be given local legal effect according to their terms,
+reviewing courts shall apply local law that most closely approximates
+an absolute waiver of all civil liability in connection with the
+Program, unless a warranty or assumption of liability accompanies a
+copy of the Program in return for a fee.
+
+                     END OF TERMS AND CONDITIONS
+
+            How to Apply These Terms to Your New Programs
+
+  If you develop a new program, and you want it to be of the greatest
+possible use to the public, the best way to achieve this is to make it
+free software which everyone can redistribute and change under these terms.
+
+  To do so, attach the following notices to the program.  It is safest
+to attach them to the start of each source file to most effectively
+state the exclusion of warranty; and each file should have at least
+the "copyright" line and a pointer to where the full notice is found.
+
+    <one line to give the program's name and a brief idea of what it does.>
+    Copyright (C) <year>  <name of author>
+
+    This program is free software: you can redistribute it and/or modify
+    it under the terms of the GNU General Public License as published by
+    the Free Software Foundation, either version 3 of the License, or
+    (at your option) any later version.
+
+    This program is distributed in the hope that it will be useful,
+    but WITHOUT ANY WARRANTY; without even the implied warranty of
+    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+    GNU General Public License for more details.
+
+    You should have received a copy of the GNU General Public License
+    along with this program.  If not, see <http://www.gnu.org/licenses/>.
+
+Also add information on how to contact you by electronic and paper mail.
+
+  If the program does terminal interaction, make it output a short
+notice like this when it starts in an interactive mode:
+
+    <program>  Copyright (C) <year>  <name of author>
+    This program comes with ABSOLUTELY NO WARRANTY; for details type `show w'.
+    This is free software, and you are welcome to redistribute it
+    under certain conditions; type `show c' for details.
+
+The hypothetical commands `show w' and `show c' should show the appropriate
+parts of the General Public License.  Of course, your program's commands
+might be different; for a GUI interface, you would use an "about box".
+
+  You should also get your employer (if you work as a programmer) or school,
+if any, to sign a "copyright disclaimer" for the program, if necessary.
+For more information on this, and how to apply and follow the GNU GPL, see
+<http://www.gnu.org/licenses/>.
+
+  The GNU General Public License does not permit incorporating your program
+into proprietary programs.  If your program is a subroutine library, you
+may consider it more useful to permit linking proprietary applications with
+the library.  If this is what you want to do, use the GNU Lesser General
+Public License instead of this License.  But first, please read
+<http://www.gnu.org/philosophy/why-not-lgpl.html>.
diff -r 000000000000 -r e34cf1b6fe09 LICENSES
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/LICENSES	Sat Feb 20 18:14:24 2016 +0100
@@ -0,0 +1,3 @@
+This distribution includes the following components:
+
+SPMF Sequential Pattern Mining Library,GNU General Public License (GPL) v3,http://www.philippe-fournier-viger.com/spmf/
\ No newline at end of file
diff -r 000000000000 -r e34cf1b6fe09 collection_analysis/chord_sequence_mining/chord2function.py
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/collection_analysis/chord_sequence_mining/chord2function.py	Sat Feb 20 18:14:24 2016 +0100
@@ -0,0 +1,328 @@
+# Part of DML (Digital Music Laboratory)
+# Copyright 2014-2015 Daniel Wolff, City University
+ 
+# This program is free software; you can redistribute it and/or
+# modify it under the terms of the GNU General Public License
+# as published by the Free Software Foundation; either version 2
+# of the License, or (at your option) any later version.
+# 
+# This program is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+# GNU General Public License for more details.
+# 
+# You should have received a copy of the GNU General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA  02110-1301  USA
+
+#!/usr/bin/python
+# -*- coding: utf-8 -*-
+__author__="Daniel Wolff"
+
+import re
+
+# these for file reading etc
+import fnmatch
+import os
+import csv
+import spmf
+
+import sys
+sys.path.insert(0, '../tools/')
+import csv2json as c2j
+
+# ---
+# roots
+# ---
+chord_roots = ["C","D","E","F","G","A","B"] 
+
+# create a dictionary for efficiency
+roots_dic = dict(zip(chord_roots, [0,2,4,5,7,9,11]))
+
+mode_lbls = ['major','minor']
+mode_dic = dict(zip(mode_lbls, range(0,2)))
+# ---
+# types
+# ---
+type_labels = ["", "6", "7", "m","m6", "m7", "maj7", "m7b5", "dim", "dim7", "aug"]
+type_dic = dict(zip(type_labels, range(0,len(type_labels))))
+
+base_labels = ["1","","2","b3","3","4","","5","","6","b7","7"]
+#base_dic = dict(zip(base_labels, range(0,len(base_labels))))
+
+# functions
+root_funs_maj = ['I','#I','II','#II','III','IV','#IV','V','#V','VI','#VI','VII']
+root_funs_min = ['I','#I','II','III','#III','IV','#IV','V','VI','#VI','VII','#VII']
+# dan's suggestion
+#root_funs_maj = ['I','#I','II','#II','(M)III','IV','#IV','V','#V','VI','#VI','(M)VII']
+#root_funs_min = ['I','#I','II','(m)III','#III','IV','#IV','V','VI','#VI','(m)VII','#VII']
+
+fun_dic_maj = dict(zip(range(0,len(root_funs_maj)),root_funs_maj))
+fun_dic_min = dict(zip(range(0,len(root_funs_min)),root_funs_min))
+# regex that separates roots and types, and gets chord base
+# this only accepts chords with a sharp (#) and no flats
+p = re.compile(r'(?P<root>[A-G,N](#|b)*)(?P<type>[a-z,0-9]*)(/(?P<base>[A-G](#|b)*))*')
+p2 = re.compile(r'(?P<key>[A-G](#|b)*)(\s/\s[A-G](#|b)*)*\s(?P<mode>[major|minor]+)')
+pclip = re.compile(r'(?P<clipid>[A-Z,0-9]+(\-|_)[A-Z,0-9]+((\-|_)[A-Z,0-9]+)*((\-|_)[A-Z,0-9]+)*)_(?P<type>vamp.*).(?P<ext>(csv|xml|txt|n3)+)')
+
+ftype = {'key': 'vamp_qm-vamp-plugins_qm-keydetector_key', 
+         'chord': 'vamp_nnls-chroma_chordino_simplechord'}
+
+# most simple note2num
+def note2num(notein = 'Cb'):
+    base = roots_dic[notein[0]]
+    if len(notein) > 1:
+        if notein[1] == 'b':
+            return (base - 1) % 12
+        elif notein[1] == '#':
+            return (base + 1) % 12
+        else: 
+            print "Error parsing chord " + notein
+            raise
+    else:
+        return base % 12
+
+
+# convert key to number
+def key2num(keyin = 'C major'):
+    # ---
+    # parse key string: separate root from rest
+    # ---
+    sepstring = p2.match(keyin)
+    if not sepstring:
+        print "Error parsing key " + keyin
+        raise
+    
+    # get relative position of chord and adapt for flats
+    key = sepstring.group('key')      
+    key = note2num(key)
+    
+    # ---
+    # parse mode. care for (unknown) string
+    # ---
+    mode = sepstring.group('mode')   
+    if mode:
+        mode = mode_dic[mode]
+    else:
+        mode = -1
+
+    return (key, mode)
+
+    
+
+# convert chord to relative function
+def chord2function(cin = 'B',key=3, mode=0):
+    # ---
+    # parse chord string: separate root from rest
+    # ---
+    sepstring = p.match(cin)
+    
+    # test for N code -> no chord detected
+    if sepstring.group('root') == 'N':
+        return (-1,-1,-1,-1)
+    
+    # get root and type otherwise 
+    root = note2num(sepstring.group('root'))
+    type = sepstring.group('type') 
+    
+    typ = type_dic[type]
+
+    # get relative position
+    fun = (root - key) % 12
+        
+    #--- do we have a base key?
+    # if yes return it relative to chord root
+    # ---
+    if sepstring.group('base'):
+        broot = note2num(sepstring.group('base'))
+        bfun = (broot - root) % 12
+    else:
+        # this standard gives 1 as a base key if not specified otherwise
+        bfun = 0
+        
+    
+    # ---
+    # todo: integrate bfun in final type list
+    # ---
+    
+    return (root,fun,typ,bfun)    
+
+# reads in any csv and returns a list of structure
+# time(float), data1, data2 ....data2
+def read_vamp_csv(filein = ''):
+    output = []
+    with open(filein, 'rb') as csvfile:
+        contents = csv.reader(csvfile, delimiter=',', quotechar='"')
+        for row in contents:
+            output.append([float(row[0])] + row[1:])
+    return output
+
+# legacy:: finds featurefile for given piece
+def find_features(clipin = '', type='key'): 
+    # ---
+    # These Parametres are for the high-level parse functions
+    # ---
+    featuredirs =  {'key':'.\qm_vamp_key_standard.n3_50ac9',
+               'chord': '.\chordino_simple.n3_1a812'}
+    
+    # search for featurefile
+    featuredir = featuredirs[type].replace('\\', '/')
+    for file in os.listdir(featuredir):
+        if fnmatch.fnmatch(file, clipin+ '*' + ftype[type] + '*.csv'):
+            return featuredirs[type] + '/' + file
+
+# reads features for given clip and of specified type
+def get_features(clipin = '', type='key', featurefiles = 0):
+    if not featurefiles:
+        featurefiles = find_features(clipin, type)
+    return read_vamp_csv(featurefiles[type])
+        
+# histogram of the last entry in a list
+# returns the most frequently used key
+def histogram(keysin = []):
+    # build histogram 
+    histo = dict()
+    for row in keysin:
+        histo[row[-1]] = histo.get(row[-1], 0) + 1 
+
+    # return most frequent key
+    return (histo, max(histo.iterkeys(), key=(lambda key: histo[key])))
+
+    
+# main function, processes all chords for one song
+def chords2functions(clipin = '1CD0006591_BD11-14',featurefiles = '', constkey = 1):
+    
+    # get keys 
+    keys = get_features(clipin,'key',featurefiles)
+    
+    relchords = []
+    # chords
+    chords = get_features(clipin,'chord',featurefiles)
+    if constkey:
+        # delete 'unknown' keys
+        keys = [(time,knum,key) for (time,knum,key) in keys if not key == '(unknown)']
+
+        # aggregate to one key 
+        (histo, skey) = histogram(keys)
+                    
+        # bet key number
+        (key,mode) = key2num(skey)
+        
+        for (time,chord) in chords:
+            
+            # get chord function
+            (root,fun,typ, bfun) = chord2function(chord, key,mode)
+            
+            # translate into text
+            txt = fun2txt(fun,typ, bfun, mode)
+            #print 'Key: ' + skey + ', chord: ' + chord + ', function: ' + txt
+
+            relchords.append((time,key,mode,fun,typ,bfun))
+    return relchords
+                
+def tracks_in_dir(dirin = ''):
+
+    # ---
+    # we now only search for tracks which have chord data
+    # ---
+    
+    # data is a dictionary that 
+    # for each filename contains the feature
+    # files for chords and keys
+    
+    data = dict();
+    # traverse the file structure and get all track names
+    count = 0
+    errcount = 0
+    for (dirpath, dirnames, filenames) in os.walk(dirin):
+        for file in filenames:
+            #print '\rChecked %d files' % (count), 
+            count = count + 1
+            if file.endswith(".csv"):
+                # parse filename to get clip_id
+                parsed = pclip.match(file)
+                if parsed:
+                    clipin = parsed.group('clipid')
+
+                    # initialise dict if necessary
+                    if not data.has_key(clipin):
+                        data[clipin] = dict()
+
+                    # add data to dictionary
+                    if parsed.group('type') == (ftype['chord']):
+                        data[clipin]['chord'] = os.path.join(dirpath, file).replace('\\', '/')
+                    elif parsed.group('type') == (ftype['key']):
+                        data[clipin]['key'] = os.path.join(dirpath, file).replace('\\', '/')
+                else:
+                    errcount += 1
+                    print "Could not parse " + file
+                    raise
+    return data
+    # return list of tracknames
+    # return list of feature dirs
+    
+    
+def fun2txt(fun,typ, bfun,mode):
+    # now we can interpret this function 
+    # when given the mode of major or minor.
+    if (fun >= 0):
+        if (mode == 1):
+            pfun = fun_dic_min[fun]
+            md = '(m)'
+        elif (mode == 0):
+            pfun = fun_dic_maj[fun] 
+            md = '(M)'
+    else:
+        return 'N'
+
+    #if typ == 'm':
+    #    print 'Key: ' + skey + ', chord: ' + chord + ' function ' + str(fun) + ' type ' + typ + ' bfun ' + str(bfun)
+    type = type_labels[typ] if typ > 0 else ''
+    
+    blb = '/' + base_labels[bfun] if (bfun >= 0 and base_labels[bfun]) else ''
+    return md + pfun + type + blb
+
+def fun2num(fun,typ, bfun,mode):
+    # now we can interpret this function 
+    if not fun == -1:
+        return (mode+1)* 1000000 + (fun+1) * 10000 + (typ+1) * 100 + (bfun+1)
+    else: 
+        return 0
+
+def folder2functions(path):
+    tracks = tracks_in_dir(path)
+    
+    # get chords for all files                    
+    #check for integrity: do we have keys and chords?  
+    output = dict()
+    bfuns = []
+
+    for clip, featurefiles in tracks.iteritems():
+        print clip
+        if len(featurefiles) == 2:
+            output[clip] = chords2functions(clip,featurefiles)
+    return output                
+        
+def folder2histogram(path= './'):
+
+    # get chord functions for the folder
+    tracks = folder2functions(path)
+    
+    # concatenate string form
+    chords = []
+    for track, contents in tracks.iteritems():
+        for (time,key,mode,fun,typ,bfun) in contents:
+            chords.append([fun2num(fun,typ,bfun,mode)])
+        
+    # counts 
+    (v,w) = histogram(chords)        
+    print v 
+    return {"count":v.values(), "index":v.keys()}
+        
+if __name__ == "__main__":
+    #chords2functions()
+    print "Creates a key-independent chord histogram. Usage: chord2function path_vamp_chords path_vamp_keys"
+    # sys.argv[1]
+    result = folder2histogram()
+    print "Please input a description for the chord function histogram"
+    c2j.data2json(result)
\ No newline at end of file
diff -r 000000000000 -r e34cf1b6fe09 collection_analysis/chord_sequence_mining/chordtable_relative.py
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/collection_analysis/chord_sequence_mining/chordtable_relative.py	Sat Feb 20 18:14:24 2016 +0100
@@ -0,0 +1,82 @@
+# Part of DML (Digital Music Laboratory)
+# Copyright 2014-2015 Daniel Wolff, City University
+ 
+# This program is free software; you can redistribute it and/or
+# modify it under the terms of the GNU General Public License
+# as published by the Free Software Foundation; either version 2
+# of the License, or (at your option) any later version.
+# 
+# This program is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+# GNU General Public License for more details.
+# 
+# You should have received a copy of the GNU General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA  02110-1301  USA
+
+#!/usr/bin/python
+# -*- coding: utf-8 -*-
+__author__="Daniel Wolff"
+
+#Generates look-up table for possible chords relative to 
+
+import chord2function as c2f
+import csv
+
+HUMAN_READEABLE = 1;
+
+SAVE_CSV = 1
+SAVE_PICKLE = 0
+SAVE_VOCABULARY = 0
+
+chordmapfilename = 'relative-chordmap.cmap'
+chordmapfilename_csv = 'relative-chordmap.csv'
+chordino_chords_vocabulary = 'relative-chord-vocabulary.txt'
+
+# initialise chord dictionary
+chord_dic = dict();
+
+chord_dic[0] = 'N'
+ # major and minor pieces are separated by chords
+for mode, mode_lbl in enumerate(c2f.mode_lbls):
+    for fun in range(0,len(c2f.root_funs_maj)):
+        for type, type_lbl in enumerate(c2f.type_labels): 
+            for base, base_lbl in enumerate(c2f.base_labels): 
+                if base_lbl:
+                    idx = c2f.fun2num(fun,type, base,mode)
+                    if HUMAN_READEABLE:
+                        chord_dic[idx] = c2f.fun2txt(fun,type, base,mode)
+                    else:
+                        chord_dic[idx] = idx
+	
+print chord_dic
+T = len(chord_dic)
+
+if SAVE_PICKLE:
+	with open(chordmapfilename,'w') as fh:
+		print "Writing chordmap file."
+		pickle.dump(chord_dic,fh)
+
+if SAVE_CSV:
+	csvfile = open(chordmapfilename_csv, "w+b") #opens the file for updating
+	w = csv.writer(csvfile, delimiter='\t')
+	w.writerow(["chordid"] + ["chordlabel"])
+	for chordid,chordlabel in chord_dic.items():
+		w.writerow(["%s"%chordid] + ["%s"%chordlabel])		
+	csvfile.close()
+	print("CSV chord map file %s written."%chordmapfilename_csv)	
+
+if SAVE_VOCABULARY:
+	#creates a file with each chords on separate lines to have a vocabulary which can be used with topic modeling techniques
+	#(e.g. turbotopics)
+	csvfile = open(chordino_chords_vocabulary, "w+b") #opens the file for updating
+	w = csv.writer(csvfile, delimiter='\t')
+	for chordid,chordlabel in chord_dic.items():
+		w.writerow(["%s"%chordlabel])		
+	csvfile.close()
+	print("Chord vocabulary file %s written."%chordino_chords_vocabulary)
+
+
+
+
diff -r 000000000000 -r e34cf1b6fe09 collection_analysis/chord_sequence_mining/relative-chordmap.csv
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/collection_analysis/chord_sequence_mining/relative-chordmap.csv	Sat Feb 20 18:14:24 2016 +0100
@@ -0,0 +1,2378 @@
+chordid	chordlabel
+0	N
+1040401	(M)#IIm/1
+1040403	(M)#IIm/2
+1040404	(M)#IIm/b3
+1040405	(M)#IIm/3
+1040406	(M)#IIm/4
+1040408	(M)#IIm/5
+1040410	(M)#IIm/6
+1040411	(M)#IIm/b7
+1040412	(M)#IIm/7
+2080801	(m)Vm7b5/1
+2080803	(m)Vm7b5/2
+2080804	(m)Vm7b5/b3
+2080805	(m)Vm7b5/3
+2080806	(m)Vm7b5/4
+2080808	(m)Vm7b5/5
+2080810	(m)Vm7b5/6
+2080811	(m)Vm7b5/b7
+2080812	(m)Vm7b5/7
+1040501	(M)#IIm6/1
+1040503	(M)#IIm6/2
+1040504	(M)#IIm6/b3
+1040505	(M)#IIm6/3
+1040506	(M)#IIm6/4
+1040508	(M)#IIm6/5
+1040510	(M)#IIm6/6
+1040511	(M)#IIm6/b7
+1040512	(M)#IIm6/7
+2080901	(m)Vdim/1
+2080903	(m)Vdim/2
+2080904	(m)Vdim/b3
+2080905	(m)Vdim/3
+2080906	(m)Vdim/4
+2080908	(m)Vdim/5
+2080910	(m)Vdim/6
+2080911	(m)Vdim/b7
+2080912	(m)Vdim/7
+1040601	(M)#IIm7/1
+1040603	(M)#IIm7/2
+1040604	(M)#IIm7/b3
+1040605	(M)#IIm7/3
+1040606	(M)#IIm7/4
+1040608	(M)#IIm7/5
+1040610	(M)#IIm7/6
+1040611	(M)#IIm7/b7
+1040612	(M)#IIm7/7
+2081001	(m)Vdim7/1
+2081003	(m)Vdim7/2
+2081004	(m)Vdim7/b3
+2081005	(m)Vdim7/3
+2081006	(m)Vdim7/4
+2081008	(m)Vdim7/5
+2081010	(m)Vdim7/6
+2081011	(m)Vdim7/b7
+2081012	(m)Vdim7/7
+2040101	(m)III/1
+2040103	(m)III/2
+2040104	(m)III/b3
+2040105	(m)III/3
+2040106	(m)III/4
+2040108	(m)III/5
+2040110	(m)III/6
+2040111	(m)III/b7
+2040112	(m)III/7
+1040701	(M)#IImaj7/1
+1040703	(M)#IImaj7/2
+1040704	(M)#IImaj7/b3
+1040705	(M)#IImaj7/3
+1040706	(M)#IImaj7/4
+1040708	(M)#IImaj7/5
+1040710	(M)#IImaj7/6
+1040711	(M)#IImaj7/b7
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+2121105	(m)#VIIaug/3
+2121106	(m)#VIIaug/4
+2121108	(m)#VIIaug/5
+2121110	(m)#VIIaug/6
+2121111	(m)#VIIaug/b7
+2121112	(m)#VIIaug/7
+2031001	(m)IIdim7/1
+2031003	(m)IIdim7/2
+2031004	(m)IIdim7/b3
+2031005	(m)IIdim7/3
+2031006	(m)IIdim7/4
+2031008	(m)IIdim7/5
+2031010	(m)IIdim7/6
+2031011	(m)IIdim7/b7
+2031012	(m)IIdim7/7
+2080201	(m)V6/1
+2080203	(m)V6/2
+2080204	(m)V6/b3
+2080205	(m)V6/3
+2080206	(m)V6/4
+2080208	(m)V6/5
+2080210	(m)V6/6
+2080211	(m)V6/b7
+2080212	(m)V6/7
+1080801	(M)Vm7b5/1
+1080803	(M)Vm7b5/2
+1080804	(M)Vm7b5/b3
+1080805	(M)Vm7b5/3
+1080806	(M)Vm7b5/4
+1080808	(M)Vm7b5/5
+1080810	(M)Vm7b5/6
+1080811	(M)Vm7b5/b7
+1080812	(M)Vm7b5/7
+2031101	(m)IIaug/1
+2031103	(m)IIaug/2
+2031104	(m)IIaug/b3
+2031105	(m)IIaug/3
+2031106	(m)IIaug/4
+2031108	(m)IIaug/5
+2031110	(m)IIaug/6
+2031111	(m)IIaug/b7
+2031112	(m)IIaug/7
+2080301	(m)V7/1
+2080303	(m)V7/2
+2080304	(m)V7/b3
+2080305	(m)V7/3
+2080306	(m)V7/4
+2080308	(m)V7/5
+2080310	(m)V7/6
+2080311	(m)V7/b7
+2080312	(m)V7/7
+1080901	(M)Vdim/1
+1080903	(M)Vdim/2
+1080904	(M)Vdim/b3
+1080905	(M)Vdim/3
+1080906	(M)Vdim/4
+1080908	(M)Vdim/5
+1080910	(M)Vdim/6
+1080911	(M)Vdim/b7
+1080912	(M)Vdim/7
+2080401	(m)Vm/1
+2080403	(m)Vm/2
+2080404	(m)Vm/b3
+2080405	(m)Vm/3
+2080406	(m)Vm/4
+2080408	(m)Vm/5
+2080410	(m)Vm/6
+2080411	(m)Vm/b7
+2080412	(m)Vm/7
+1081001	(M)Vdim7/1
+1081003	(M)Vdim7/2
+1081004	(M)Vdim7/b3
+1081005	(M)Vdim7/3
+1081006	(M)Vdim7/4
+1081008	(M)Vdim7/5
+1081010	(M)Vdim7/6
+1081011	(M)Vdim7/b7
+1081012	(M)Vdim7/7
+1040101	(M)#II/1
+1040103	(M)#II/2
+1040104	(M)#II/b3
+1040105	(M)#II/3
+1040106	(M)#II/4
+1040108	(M)#II/5
+1040110	(M)#II/6
+1040111	(M)#II/b7
+1040112	(M)#II/7
+2080501	(m)Vm6/1
+2080503	(m)Vm6/2
+2080504	(m)Vm6/b3
+2080505	(m)Vm6/3
+2080506	(m)Vm6/4
+2080508	(m)Vm6/5
+2080510	(m)Vm6/6
+2080511	(m)Vm6/b7
+2080512	(m)Vm6/7
+1081101	(M)Vaug/1
+1081103	(M)Vaug/2
+1081104	(M)Vaug/b3
+1081105	(M)Vaug/3
+1081106	(M)Vaug/4
+1081108	(M)Vaug/5
+1081110	(M)Vaug/6
+1081111	(M)Vaug/b7
+1081112	(M)Vaug/7
+1040201	(M)#II6/1
+1040203	(M)#II6/2
+1040204	(M)#II6/b3
+1040205	(M)#II6/3
+1040206	(M)#II6/4
+1040208	(M)#II6/5
+1040210	(M)#II6/6
+1040211	(M)#II6/b7
+1040212	(M)#II6/7
+2080601	(m)Vm7/1
+2080603	(m)Vm7/2
+2080604	(m)Vm7/b3
+2080605	(m)Vm7/3
+2080606	(m)Vm7/4
+2080608	(m)Vm7/5
+2080610	(m)Vm7/6
+2080611	(m)Vm7/b7
+2080612	(m)Vm7/7
+1040301	(M)#II7/1
+1040303	(M)#II7/2
+1040304	(M)#II7/b3
+1040305	(M)#II7/3
+1040306	(M)#II7/4
+1040308	(M)#II7/5
+1040310	(M)#II7/6
+1040311	(M)#II7/b7
+1040312	(M)#II7/7
+2080701	(m)Vmaj7/1
+2080703	(m)Vmaj7/2
+2080704	(m)Vmaj7/b3
+2080705	(m)Vmaj7/3
+2080706	(m)Vmaj7/4
+2080708	(m)Vmaj7/5
+2080710	(m)Vmaj7/6
+2080711	(m)Vmaj7/b7
+2080712	(m)Vmaj7/7
\ No newline at end of file
diff -r 000000000000 -r e34cf1b6fe09 collection_analysis/chord_sequence_mining/spmf.jar
Binary file collection_analysis/chord_sequence_mining/spmf.jar has changed
diff -r 000000000000 -r e34cf1b6fe09 collection_analysis/chord_sequence_mining/spmf.py
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/collection_analysis/chord_sequence_mining/spmf.py	Sat Feb 20 18:14:24 2016 +0100
@@ -0,0 +1,220 @@
+# Part of DML (Digital Music Laboratory)
+# Copyright 2014-2015 Daniel Wolff, City University
+ 
+# This program is free software; you can redistribute it and/or
+# modify it under the terms of the GNU General Public License
+# as published by the Free Software Foundation; either version 2
+# of the License, or (at your option) any later version.
+# 
+# This program is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+# GNU General Public License for more details.
+# 
+# You should have received a copy of the GNU General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA  02110-1301  USA
+
+#!/usr/bin/python
+# -*- coding: utf-8 -*-
+#
+# This is a data conversion wrapper for the spmf toolkit.
+# The toolkit has been released under GPL3 at www.philippe-fournier-viger.com/spmf
+
+__author__="Daniel Wolff"
+
+import chord2function as c2f
+import csv
+import re
+
+# takes a dictionary of chords for one or multiple files 
+# in the form of dict[clipid] = [ (time,key,mode,fun,typ,bfun) ]
+# and converts it into spmf
+def folder2spmf(folderin = 'D:/mirg/Chord_Analysis20141216/', fileout = 'D:/mirg/Chord_Analysis20141216/Beethoven.spmf'):
+
+    # get chords for all files                    
+    output  = c2f.folder2functions(folderin)
+
+    # open log
+    logfile = fileout + '.dic'
+    csvfile = open(logfile, "w+b") #opens the file for updating
+    w = csv.writer(csvfile)
+    w.writerow(["track","key","mode","sequence length"])
+    
+    # open spmf file
+    fspmf = open(fileout,'w')
+    # ---
+    # this is writing the spmf format
+    for track,trackdata in output.iteritems():
+        # write chord sequence as one line in spmf file
+        for (time,key,mode,fun,typ,bfun) in trackdata:
+            chord = c2f.fun2num(fun,typ,bfun,mode)
+            
+            # -1 is the spearator of items or itemsets
+            fspmf.write(str(chord) + ' -1 ') 
+            
+        # the sequence is closed with -2
+        fspmf.write('-2\n') 
+        w.writerow([track, str(key), str(mode),str(len(trackdata))])
+            
+    fspmf.close()
+    csvfile.close()
+
+# read an spmf file
+# def parsespmf(filein = 'D:/mirg/Chord_Analysis20141216/Beethoven.txt'):
+
+# string sourcefile path to the source spmf file with chords from records
+# string patternfile path to the pattern spmf file
+# matches each of the patterns in patternfile
+#  to the chord sequences in sourcefile
+def match(sourcefile = 'D:/mirg/Chord_Analysis20141216/Beethoven.spmf',sourcedict = 'D:/mirg/Chord_Analysis20141216/Beethoven.spmf.dic', patternfile = 'D:/mirg/Chord_Analysis20141216/Beethoven_70.txt'):
+    
+    # define regular expressions for matching
+    # closed sequence
+    
+    # ---
+    # we here assume that there are more files than patterns,
+    # as display of patterns is somehow limited
+    # therefore parallelisation will be 1 pattern/multiple files
+    # per instance
+    # ---
+    
+    patterns = []
+    patterns_raw = []
+    # read all patterns
+    f = open(patternfile, 'r')
+    for line in f:
+        # a line looks like this:
+        # 1120401 -1 1120101 -1 #SUP: 916
+       
+
+        # save pattern
+        #patterns.append(pattern)
+        #numeric? or just regex?
+        # we'll use string, so any representation works
+        
+        pattern,support = readPattern(line)
+        patterns.append(pattern)
+        
+        # here's the regex
+        # first the spacer
+        #spacer = '((\s-1\s)|((\s-1\s)*[0-9]+\s-1\s)+)'
+        #repattern = r'(' + spacer + '*' + spacer.join(pattern) + spacer + '*' + '.*)'
+        #print repattern
+        #patterns.append(re.compile(repattern))
+        
+    # ---
+    # now for the input sequences
+    # ---
+    # first: read track dictionary and get the input sequence names
+    tracks = getClipDict(sourcedict)
+       
+    # read the input sequences
+    source = open(sourcefile, 'r')
+    patterns_tracks = dict()
+    tracks_patterns = dict()
+    
+    # iterate over all tracks - to be parallelised
+    for track,count in tracks.iteritems():
+        sequence = readSequence(next(source))
+        print track
+        for p in range(0,len(patterns)):
+            # match open or closed pattern
+            if openPatternInSequence(sequence,patterns[p]):
+                if patterns_tracks.has_key(p):
+                    patterns_tracks[p].append(track)
+                else:
+                    patterns_tracks[p] = [track]
+
+                if tracks_patterns.has_key(track):
+                    tracks_patterns[track].append(p)
+                else:
+                    tracks_patterns[track] = [p]  
+    
+    # write clip index to files
+    writeAllPatternsForClips('D:/mirg/Chord_Analysis20141216/',tracks_patterns)
+    #print patterns_tracks[p]
+
+# writes results to disk per key
+def writeAllPatternsForClips(path = 'D:/mirg/Chord_Analysis20141216/',tracks_patterns = dict()):
+
+    for name, contents in tracks_patterns.iteritems():
+        # create new file
+        csvfile = open(path + '/' + name + '_patterns.csv', "w+b") #opens the file for updating
+        w = csv.writer(csvfile)
+   
+        # compress pattern data ?
+        # e.g. 2 columns from-to for the long series of atomic increments
+        
+        w.writerow(contents)
+        csvfile.close()
+        
+
+# @param line: reads a line in the spmf output file with frequent patterns
+# returns list of strings "pattern" and int "support"
+def readPattern(line):
+    # locate support 
+    suploc = line.find('#SUP:')
+    support = int(line[suploc+5:-1])
+
+    # extract pattern
+    pattern = line[:suploc].split(' -1 ')[:-1]
+    return (pattern,support)
+   
+# @param line: reads a line in the spmf input file with chord sequence
+# returns list of strings "pattern" and int "support"
+def readSequence(line):
+    # locate support 
+    suploc = line.find('-2')
+
+    # extract pattern
+    sequence = line[:suploc].split(' -1 ')[:-1] 
+    return sequence
+
+# finds open pattern in sequences
+# @param [string] sequence input sequence
+# @param [string] pattern pattern to be found
+def openPatternInSequence(sequence,pattern):
+    patidx = 0
+    for item in sequence:
+        if item == pattern[patidx]:
+            patidx +=1
+            
+            # did we complet the pattern?
+            if patidx >= (len(pattern)-1):
+                # could also return the start index
+                return 1
+    # finished the sequence before finishing pattern
+    return 0
+            
+# finds closed pattern in sequences
+# @param [string] sequence input sequence
+# @param [string] pattern pattern to be found
+def closedPatternInSequence(sequence,pattern):
+    # alternatively use KnuthMorrisPratt with unsplit string
+    return ''.join(map(str, pattern)) in ''.join(map(str, sequence))  
+            
+# reads all track names from the dictionary created by folder2spmf
+# @param sourcedict path to dictionary
+def getClipDict(sourcedict):
+    
+    f = open(sourcedict, 'rt')
+    reader = csv.reader(f)
+    
+    # skip first roow that contains legend
+    next(reader)
+    
+    # get following rows
+    tracks = dict()
+    for (track,key,mode,seqlen) in reader:
+        tracks[track]= (key,mode,seqlen)
+        #tracks.append((track,count))
+    
+    f.close()
+    return tracks 
+    
+            
+# run spmf afterwards with java -jar spmf.jar run CM-SPADE Beethoven.spmf output.txt 50% 3
+if __name__ == "__main__":
+    #folder2spmf()
+    match()
\ No newline at end of file
diff -r 000000000000 -r e34cf1b6fe09 collection_analysis/tools/csv2json.py
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/collection_analysis/tools/csv2json.py	Sat Feb 20 18:14:24 2016 +0100
@@ -0,0 +1,101 @@
+# Part of DML (Digital Music Laboratory)
+# Copyright 2014-2015 Daniel Wolff, City University
+ 
+# This program is free software; you can redistribute it and/or
+# modify it under the terms of the GNU General Public License
+# as published by the Free Software Foundation; either version 2
+# of the License, or (at your option) any later version.
+# 
+# This program is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+# GNU General Public License for more details.
+# 
+# You should have received a copy of the GNU General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA  02110-1301  USA
+
+#!/usr/bin/python
+# -*- coding: utf-8 -*-
+
+# this file converts data (csv) to the final web api json format.
+
+__author__="Daniel Wolff"
+__date__ ="$11-Feb-2015 16:32:09$"
+
+import sys
+import csv
+import json
+
+
+# global data format version
+dv=str(1)
+
+
+def getIdentifiers():
+    # collect collection and perspective id
+    cid = raw_input("Please Input Collection Identifier:")
+    pid = raw_input("Please Input Perspective / Analyisis Identifier:")
+    
+    # additional parameters
+    params = raw_input("Input further parameters as string 'parameter1=value1_parameter2=value2...'")
+    return (cid,pid,params)
+
+def makeUrl(cid,pid,params):
+    #"getCollectionPerspective_pid=chordSequences_cid=jazz_limit=100.json"
+    s = "_"
+    if not params == '':
+        url = s.join(['getCollectionPerspective','pid='+ pid,'cid=' + cid,params,"dv="+dv])
+    else:
+        url = s.join(['getCollectionPerspective','pid='+ pid,'cid=' + cid,'dv='+dv])
+ 
+    return url
+
+
+# reads in any csv and returns a list of structure
+# time(float), data1, data2 ....data2
+def read_csv(filein = ''):
+    output = []
+    with open(filein, 'rb') as csvfile:
+        contents = csv.reader(csvfile, delimiter=',', quotechar='"')
+        for row in contents:
+            output.append(row)
+    return output
+
+# write data into object formatted and create json output
+def data2apijson(data,cid,pid,params):
+    url = makeUrl(cid,pid,params)
+    if not type(data)=='dict':
+        obj = {"query":url, "result": {pid:data}}
+    else:
+        obj = {"query":url, "result": data}
+    return (json.dumps(obj), url)
+
+# writes json to file
+def writejsonfile(jstring,url):
+    f = open(url + ".json", "w");
+    f.write(jstring)
+    f.close
+
+def data2json(data):
+    # get further needed data such as url
+    (cid,pid,params) = getIdentifiers()
+    (jsondat,url) = data2apijson(data,cid,pid,params)
+    
+    # write to file
+    writejsonfile(jsondat,url)
+    
+#call this with csv input
+if __name__ == "__main__":
+    # load data in file
+    try:
+        if len(sys.argv) < 2:
+            csvfile = 'test.csv'
+        else:
+            csvfile = sys.argv[1]
+        data = read_csv(csvfile)
+    except:
+        print "Please provide input csv file as command-line argument"  
+        quit()
+
+    data2json(data)
diff -r 000000000000 -r e34cf1b6fe09 collection_analysis/tools/test.csv
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/collection_analysis/tools/test.csv	Sat Feb 20 18:14:24 2016 +0100
@@ -0,0 +1,3 @@
+1,2,3
+2,A#,5
+4,A,4
diff -r 000000000000 -r e34cf1b6fe09 collection_analysis/tools/vampstats.py
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/collection_analysis/tools/vampstats.py	Sat Feb 20 18:14:24 2016 +0100
@@ -0,0 +1,166 @@
+# Part of DML (Digital Music Laboratory)
+# Copyright 2014-2015 Daniel Wolff, City University
+ 
+# This program is free software; you can redistribute it and/or
+# modify it under the terms of the GNU General Public License
+# as published by the Free Software Foundation; either version 2
+# of the License, or (at your option) any later version.
+# 
+# This program is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+# GNU General Public License for more details.
+# 
+# You should have received a copy of the GNU General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA  02110-1301  USA
+
+#!/usr/bin/python
+# -*- coding: utf-8 -*-
+
+# creates a histogram from given input files or folder
+
+__author__="Daniel Wolff"
+__date__ ="$11-Feb-2015 18:18:47$"
+
+import sys
+import os
+import csv
+import numpy
+import csv2json as c2j
+import re
+
+
+# global feature extensions
+#ext = tuple([".n3",".csv",".mid"])
+ext = tuple([".csv"])
+
+floater = re.compile("((\d+)(.\d+)*)")
+# reads in any csv and returns a list of structure
+# time(float), data1, data2 ....data2
+def read_vamp_csv(filein = '', datapos = 0):
+    output = []
+    badcount = 0
+    with open(filein, 'rb') as csvfile:
+        contents = csv.reader(csvfile, delimiter=',', quotechar='"')
+        for row in contents:
+	    if len(row) >= datapos + 2:
+	        output.append([float(row[0])] + row[1:])
+            else: 
+                badcount += 1
+    print "Ignored " + str(badcount) + " short rows" 
+    return output
+
+#calculates the histogram
+def histogram(data, datapos = 1, nbins = -1):
+    
+    # symbols or numerical input?
+    if not nbins == -1:
+        
+        #convert to numpy data
+	ddata = string2numpy(data,datapos)
+        
+        count,index = numpy.histogram(ddata,nbins-1)
+        count = count.tolist()
+        index = index.tolist()
+        
+    # here for strings
+    else: 
+        # build histogram on strings
+        histo = dict()
+        for row in data:
+            histo[row[datapos+1]] = histo.get(row[datapos+1], 0) + 1 
+            index = histo.keys()
+            count = histo.values()
+            
+    # return histogram
+    return {"count":count, "index":index}
+    
+#calculates statistics for  numerical input
+def numstats(data,datapos):
+    
+    #convert to numpy data
+    ddata = string2numpy(data,datapos)
+
+    avg = numpy.average(ddata).tolist()
+    med = numpy.median(ddata).tolist()
+    std = numpy.std(ddata).tolist()
+    
+    # return data
+    return {"average": avg, "median": med, "std": std}
+
+def featurefilesinpath(path):
+    # ---
+    # we traverse the file structure
+    # and list files to copy
+    # ---
+    files = []
+    for (dirpath, dirnames, filenames) in os.walk(path):
+        for file in filenames:        
+            # we copy all requested files and the transform files as well!
+            if (file.endswith(ext)):
+                source = os.path.join(dirpath, file).replace('\\','/')
+                files.append(source)
+    return files
+
+# convert to numpy
+def string2numpy(data,datapos):
+    try:
+        ddata = numpy.array(data, dtype=float)[:, datapos+1]
+    except:
+        edata = []
+        for row in data:
+            # account for verbatim units
+            m = re.search("[a-zA-Z]", row[datapos+1])
+            if m is not None:
+                # take only the specified column datapos+1
+                edata.append(row[datapos+1][:(m.start()-1)])
+            else:
+                # take only the specified column datapos+1
+                edata.append(row[datapos+1])
+        ddata = numpy.array(edata,dtype=float)
+    return ddata
+
+# main entry point
+if __name__ == "__main__":
+    print "Usage: vampstats datapos nbins file1/dir1 file2/dir2 ...."
+    print "datapos: column of data after timecode to process"
+    print "nbins: -1 for categorical data, otherwise number of bins for histogram"
+    
+    datapos = int(sys.argv[1])
+    nbins = int(sys.argv[2])
+    
+    # check and collate files
+    files = []
+    for path in sys.argv[3:]:
+        if os.path.isdir(path):
+            files.extend(featurefilesinpath(path))
+        else: 
+            if os.path.isfile(path):
+                files.extend(path)
+    print "Number of files now loading: " + str(len(files))
+    
+    # we collate all data first and then count. 
+    # @todo: read all files and create dictionary first for large tasks
+    data = []
+    for file in files:
+        print file
+        data.extend(read_vamp_csv(file, datapos))
+    
+    print "Total data size in memory: " + str(sys.getsizeof(data))
+    
+    # now get the histogram for all data
+    histo = histogram(data,datapos,nbins)
+    print histo
+    print "Please input a description for the histogram analysis features"
+    c2j.data2json(histo)
+    
+    # further numerical analysis if this is not categorical data
+    if not nbins == -1: 
+        ns = numstats(data,datapos)
+        print ns
+        print "Please input a description for the general statistics features"
+        c2j.data2json(ns)
+        
+        
+        
diff -r 000000000000 -r e34cf1b6fe09 collection_analysis/tools/vampstats_pitch_weighted.py
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/collection_analysis/tools/vampstats_pitch_weighted.py	Sat Feb 20 18:14:24 2016 +0100
@@ -0,0 +1,172 @@
+# Part of DML (Digital Music Laboratory)
+# Copyright 2014-2015 Daniel Wolff, City University
+ 
+# This program is free software; you can redistribute it and/or
+# modify it under the terms of the GNU General Public License
+# as published by the Free Software Foundation; either version 2
+# of the License, or (at your option) any later version.
+# 
+# This program is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+# GNU General Public License for more details.
+# 
+# You should have received a copy of the GNU General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA  02110-1301  USA
+
+#!/usr/bin/python
+# -*- coding: utf-8 -*-
+
+# creates a histogram from given input files or folder
+
+__author__="Daniel Wolff, Dan"
+__date__ ="$11-Feb-2015 18:18:47$"
+
+import sys
+import os
+import csv
+import numpy
+import csv2json as c2j
+import re
+
+
+# global feature extensions
+#ext = tuple([".n3",".csv",".mid"])
+ext = tuple([".csv"])
+
+floater = re.compile("((\d+)(.\d+)*)")
+# reads in any csv and returns a list of structure
+# time(float), data1, data2 ....data2
+def read_vamp_csv(filein = '', datapos = 0):
+    output = []
+    badcount = 0
+    with open(filein, 'rb') as csvfile:
+        contents = csv.reader(csvfile, delimiter=',', quotechar='"')
+        for row in contents:
+	    if len(row) >= datapos + 2:
+	        output.append([float(row[0])] + row[1:])
+            else: 
+                badcount += 1
+    print "Ignored " + str(badcount) + " short rows" 
+    return output
+
+#calculates the histogram
+def histogram(data, datapos = 1, nbins = -1):
+    
+    # symbols or numerical input?
+    if not nbins == -1:
+        
+        #convert to numpy data\
+        ddata = string2numpy(data,datapos)
+    
+        # get time weights
+        tw_data = string2numpy(data,2)
+ 
+        # get loudness weights
+        lw_data = string2numpy(data,3)
+        
+        count,index = numpy.histogram(ddata,nbins-1, weights=numpy.multiply(tw_data,lw_data))
+        count = count.tolist()
+        index = index.tolist()
+        
+    # here for strings
+    else: 
+        # build histogram on strings
+        histo = dict()
+        for row in data:
+            histo[row[datapos+1]] = histo.get(row[datapos+1], 0) + 1 
+            index = histo.keys()
+            count = histo.values()
+            
+    # return histogram
+    return {"count":count, "index":index}
+    
+#calculates statistics for  numerical input
+def numstats(data,datapos):
+    
+    #convert to numpy data
+    ddata = string2numpy(data,datapos)
+
+    avg = numpy.average(ddata).tolist()
+    med = numpy.median(ddata).tolist()
+    std = numpy.std(ddata).tolist()
+    
+    # return data
+    return {"average": avg, "median": med, "std": std}
+
+def featurefilesinpath(path):
+    # ---
+    # we traverse the file structure
+    # and list files to copy
+    # ---
+    files = []
+    for (dirpath, dirnames, filenames) in os.walk(path):
+        for file in filenames:        
+            # we copy all requested files and the transform files as well!
+            if (file.endswith(ext)):
+                source = os.path.join(dirpath, file).replace('\\','/')
+                files.append(source)
+    return files
+
+# convert to numpy
+def string2numpy(data,datapos):
+    try:
+        ddata = numpy.array(data, dtype=float)[:, datapos+1]
+    except:
+        edata = []
+        for row in data:
+            #edata.append(float(floater.match(row[datapos+1]).group(1)))
+            m = re.search("[a-zA-Z]", row[datapos+1])
+            if m is not None:
+                # take onlly the specified column datapos+1
+                edata.append(row[datapos+1][:(m.start()-1)])
+            else:
+                # take onlly the specified column datapos+1
+                edata.append(row[datapos+1])
+        ddata = numpy.array(edata,dtype=float)
+    return ddata
+
+# main entry point
+if __name__ == "__main__":
+    print "Usage: vampstats datapos nbins file1/dir1 file2/dir2 ...."
+    print "datapos: column of data after timecode to process"
+    print "nbins: -1 for categorical data, otherwise number of bins for histogram"
+    
+    datapos = int(sys.argv[1])
+    nbins = int(sys.argv[2])
+    
+    # check and collate files
+    files = []
+    for path in sys.argv[3:]:
+        if os.path.isdir(path):
+            files.extend(featurefilesinpath(path))
+        else: 
+            if os.path.isfile(path):
+                files.extend(path)
+    print "Number of files now loading: " + str(len(files))
+    
+    # we collate all data first and then count. 
+    # @todo: read all files and create dictionary first for large tasks
+    data = []
+    for file in files:
+        print file
+        data.extend(read_vamp_csv(file, datapos))
+    
+    print "Total data size in memory: " + str(sys.getsizeof(data))
+    
+    # now get the histogram for all data
+    histo = histogram(data,datapos,nbins)
+    print histo
+    print "Please input a description for the histogram analysis features"
+    c2j.data2json(histo)
+    
+    # further numerical analysis if this is not categorical data
+    if not nbins == -1: 
+        ns = numstats(data,datapos)
+        print ns
+        print "Please input a description for the general statistics features"
+        c2j.data2json(ns)
+        
+        
+        
diff -r 000000000000 -r e34cf1b6fe09 ipcluster/benchmark/start_benchmark.py
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/ipcluster/benchmark/start_benchmark.py	Sat Feb 20 18:14:24 2016 +0100
@@ -0,0 +1,90 @@
+# Part of DML (Digital Music Laboratory)
+# Copyright 2014-2015 Daniel Wolff, City University
+ 
+# This program is free software; you can redistribute it and/or
+# modify it under the terms of the GNU General Public License
+# as published by the Free Software Foundation; either version 2
+# of the License, or (at your option) any later version.
+# 
+# This program is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+# GNU General Public License for more details.
+# 
+# You should have received a copy of the GNU General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA  02110-1301  USA
+
+#!/usr/bin/python
+# -*- coding: utf-8 -*-#
+
+#
+# This is a benchmark that funs calculations
+# on distributed nodes and reports the
+# average time the calculation needs.
+# Used to determine efficitncy of virtualisation 
+#
+
+# parameters
+import sys
+import time
+import numpy 
+from IPython.parallel import Client
+#import numpy as np
+
+def approxPi(error):
+    def nth_term(n):
+        return 4 / (2.0 * n + 1) * (-1) ** n
+    prev = nth_term(0)  # First term
+    current = nth_term(0) + nth_term(1)  # First + second terms
+    n = 2  # Starts at third term
+
+    while abs(prev - current) > error:
+        prev = current
+        current += nth_term(n)
+        n += 1
+
+    return current
+
+        
+def main(niters = 1,hardness = 1e-7):
+    # connect to client
+    i = 0
+    while i< 5 :
+        try :
+            i = i+1
+            rc = Client()
+            nb_core = numpy.size(rc.ids)
+            lview = rc.load_balanced_view()
+            lview.block = True
+            dview = rc[:]
+            dview.block = True
+            break
+        except Exception :
+            print 'Client not started yet (Waiting for 5 sec...)'
+            time.sleep(5)
+    if i == 5 :
+        return 'Cannot connect to cluster'
+    time.sleep(2)
+
+
+    #with dview.sync_imports():
+    #    import start_benchmark
+
+    print 'Benchmarking pi approximation on ' + str(nb_core) + ' engines.'
+    ticc = time.clock()
+    tic = time.time()
+    result = numpy.mean(lview.map(approxPi,numpy.ones(nb_core*niters) * hardness))
+    toc = time.time()-tic
+    tocc = time.clock()-ticc
+    print 'Result: ' + str(result)
+    print 'Time used: ' + str(toc)
+    print 'CPU Time passed: ' + str(nb_core) + "*" + str(toc)
+    
+if __name__ == "__main__":
+    if len(sys.argv) >= 3:
+        main(sys.argv[1],sys.argv[2])
+    else:
+        main()
+
+
diff -r 000000000000 -r e34cf1b6fe09 ipcluster/sonic_annotator_vamp.py
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/ipcluster/sonic_annotator_vamp.py	Sat Feb 20 18:14:24 2016 +0100
@@ -0,0 +1,149 @@
+# Part of DML (Digital Music Laboratory)
+# Copyright 2014-2015 Daniel Wolff, City University
+ 
+# This program is free software; you can redistribute it and/or
+# modify it under the terms of the GNU General Public License
+# as published by the Free Software Foundation; either version 2
+# of the License, or (at your option) any later version.
+# 
+# This program is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+# GNU General Public License for more details.
+# 
+# You should have received a copy of the GNU General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA  02110-1301  USA
+
+#!/usr/bin/python
+# -*- coding: utf-8 -*-
+
+from __future__ import division
+
+import matplotlib.pyplot as plt
+import numpy as np
+import sys
+import shutil
+import os
+import errno
+import subprocess
+import time 
+import random
+import hashlib
+
+
+# uses a separate console process to achieve the file conversion
+def vamp_host_process(argslist):
+    #"""Call sonic annotator"""
+
+    vamp_host = 'sonic-annotator'
+    command = [vamp_host]
+    command.extend(argslist)
+    
+    # which sa version?
+    #p = subprocess.Popen([vamp_host, '-v'], stdout=subprocess.PIPE, stderr=subprocess.STDOUT)
+    #print(p.stdout.read())
+
+
+    #stdout = subprocess.check_output(command, stderr=subprocess.STDOUT)
+    p = subprocess.Popen(command, stdout=subprocess.PIPE, stderr=subprocess.STDOUT)
+    text = p.stdout.read()
+    retcode = p.wait()
+    if (retcode==0):
+        print "Finished " 
+        return 1
+    else:
+        print "Error "  + text
+        return text
+    
+    # time.sleep(random.random()*1.0)
+    #res = subprocess.call(command)
+    return res
+
+
+# processes the given file using a vamp plugin and sonic annotator
+# @param string wav_file file to be processed
+def transform((wav_file, transform_file, hash, out_path)):
+
+    # get filename of transform
+    tpath = os.path.split(transform_file)
+    
+    # prepare output directory:
+    # get audio file subpath
+    # create directory _Features for output if doesnt exist
+    spath = os.path.split(wav_file)
+    
+    if out_path == '':
+        featpath = spath[0] + '/_Analysis/' + tpath[1] + "_" + hash[:5]
+    else:
+        folders = spath[0].split('/')
+        featpath = out_path + folders[-1] + '/' + tpath[1] + "_" + hash[:5]
+
+    #if not os.path.exists(featpath):
+    #    os.makedirs(featpath)
+    print 'Creating directory' + featpath
+    try:
+        os.makedirs(featpath)
+    except OSError as exception:
+        if exception.errno!= errno.EEXIST:
+            raise   
+    
+    # copy transform file into directory
+    try:
+        shutil.copy(transform_file, featpath + '/' +  tpath[1][:-3] + '_' + hash[:5] + '.n3')
+    except OSError as exception:
+        v = 2 # dummy statement
+
+    #./sonic-annotator -t silvet_settings.n3 input.wav -w csv
+    # prepare arguments
+    
+    # this is the standard output for now
+    args = ['-t', transform_file, wav_file, '-w', 'csv', '-w', 'rdf',
+            '--rdf-basedir',featpath,'--csv-basedir',featpath, '--rdf-many-files', '--rdf-append']
+    
+    # csv only
+    # args = ['-t', transform_file, wav_file, '-w', 'csv','--csv-basedir',featpath]
+        
+    # rdf only
+    # args = ['-t', transform_file, wav_file, '-w', 'rdf','--rdf-basedir',featpath,
+    #        '--rdf-many-files', '--rdf-append']
+    
+    # ---
+    # below would also output midi 
+    # @todo: make language, e.g. bnased on dictionaries, that defines vamp parameters per plugin
+    # ---
+    #args = ['-t', transform_file, wav_file, '-w', 'csv', '-w', 'rdf', '-w', 'midi',
+    #        '--rdf-basedir',featpath,'--csv-basedir',featpath, '--rdf-many-files', '--rdf-append']
+    #args = ['-t', transform_file, wav_file, '-w', 'csv', '--csv-force','--csv-basedir',featpath]
+
+
+    print "Analysing " + wav_file
+    
+    result = vamp_host_process(args)
+    # execute vamp host
+    return [wav_file, result]
+
+# entry function only for testing
+# provide filename, uses fixed transform
+if __name__ == "__main__":
+
+    transform_file = 'silvet_settings_fast_finetune_allinstruments.n3'
+    
+    # get transform hash
+    BLOCKSIZE = 65536
+    hasher = hashlib.sha1()
+    with open(transform_file, 'rb') as afile:
+        buf = afile.read(BLOCKSIZE)
+        while len(buf) > 0:
+            hasher.update(buf)
+            buf = afile.read(BLOCKSIZE)
+    hash = str(hasher.hexdigest())
+    transform(sys.argv[1])
+    
+    if len(sys.argv) >= 2:
+        wav_file = sys.argv[1]
+    else:
+        wav_file = 'sweep.flac'
+    
+    transform((wav_file,transform_file,hash))
+        
diff -r 000000000000 -r e34cf1b6fe09 ipcluster/test_sonic_annotator_notimeside.py
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/ipcluster/test_sonic_annotator_notimeside.py	Sat Feb 20 18:14:24 2016 +0100
@@ -0,0 +1,144 @@
+# Part of DML (Digital Music Laboratory)
+# Copyright 2014-2015 Daniel Wolff, City University
+ 
+# This program is free software; you can redistribute it and/or
+# modify it under the terms of the GNU General Public License
+# as published by the Free Software Foundation; either version 2
+# of the License, or (at your option) any later version.
+# 
+# This program is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+# GNU General Public License for more details.
+# 
+# You should have received a copy of the GNU General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA  02110-1301  USA
+
+#!/usr/local/spark-1.0.0-bin-hadoop2/bin/spark-submit
+# -*- coding: utf-8 -*-
+__author__="wolffd"
+__date__ ="$11-Jul-2014 15:31:01$"
+import sys
+import time
+import os
+import hashlib
+from IPython.parallel import Client
+
+# this is the main routine to be submmitted as a spark job
+#
+#
+# Running python applications through ./bin/pyspark is deprecated as of Spark 1.0.
+# Use ./bin/spark-submit <python file> --py-files sonic_annotator_vamp.py
+# you can also provide a zip of all necessary python files
+#
+# @param string audiopath root of the folder structure to be traversed
+# @param string transform_file path to the .n3 turtle file describing the transform
+#def main(audiopath = './',
+#         transform_file = 'silvet_settings.n3',
+#         masterip = '0.0.0.0):
+
+def main(audiopath, transform_path, out_path = ''):
+    print "iPCluster implementation for Vamp processing"
+    
+    # ---
+    # initialise ipcluster
+    # ---
+    #time.sleep(20)
+    rc = Client()
+    nb_core = len(rc.ids)
+    lview = rc.load_balanced_view()
+    lview.block = False # asynch now
+    dview = rc[:]
+    dview.block = True
+    
+    # import libraries
+    with dview.sync_imports():
+        import sys
+        import os
+        import sonic_annotator_vamp
+    
+    # here traverse the file structure
+    data = []
+    count = 0
+    for (dirpath, dirnames, filenames) in os.walk(audiopath):
+        for file in filenames:
+            print '\rChecked %d files' % (count), 
+            count = count + 1
+            if file.endswith(".wav") or file.endswith(".mp3") or file.endswith(".flac"):
+                data.append(os.path.join(dirpath, file).replace('\\','/'))
+    # count jobs
+    njobs = len(data)
+
+    
+    # we now allow
+    if transform_path.endswith(".n3"):
+        transform_files = [transform_path]
+    else:
+        transform_files = []
+        for file in os.listdir(transform_path):
+            if file.endswith(".n3"):
+                transform_files.append(transform_path + file)
+    
+    for transform_file in transform_files:
+        # get transform hash
+        BLOCKSIZE = 65536
+        hasher = hashlib.sha1()
+        with open(transform_file, 'rb') as afile:
+            buf = afile.read(BLOCKSIZE)
+            while len(buf) > 0:
+                hasher.update(buf)
+                buf = afile.read(BLOCKSIZE)
+        hash = str(hasher.hexdigest())
+        
+        # create action containing data and parameter file
+        action = [(x,transform_file,hash,out_path) for x in data]
+        
+        # output the current task
+        tpath = os.path.split(transform_file)
+        print "Using " + tpath[1] + " on " + str(njobs) + " files"
+        
+        # ---
+        # do the work!
+        # ---
+        ar = lview.map(sonic_annotator_vamp.transform, action)
+
+        # asynch process output
+        tic = time.time()
+        while True:
+            
+            # update time used
+            toc = time.time()-tic
+            
+            # update progress
+            msgset = set(ar.msg_ids)
+            completed = len(msgset.difference(rc.outstanding))
+            pending = len(msgset.intersection(rc.outstanding))
+            
+            if completed > 0:
+                timerem = ((toc/completed) * pending) / 3600.0
+                print '\rRunning %3.2f hrs: %3.2f percent. %d done, %d pending, approx %3.2f hrs' % (toc / 3600.0, completed/(pending+completed*1.0) * 100.0,completed, pending, timerem),
+            
+            if ar.ready():
+                print '\n'
+                break
+            time.sleep(1)
+            
+        toc = time.time()-tic
+        #print ar.get()
+        print '\rProcessed %d files in %3.2f hours.' % (njobs,toc / 3600.0)
+        print '\n'
+    
+    # output
+    #print(result)
+    #thefile = open(audiopath + tpath[1] + '.txt', 'w')
+    #for item in result:
+    #    thefile.write("%s\n" % item)
+    #close(thefile)
+
+if __name__ == "__main__":
+    if len(sys.argv) >= 3:
+        main(sys.argv[1],sys.argv[2])
+    else:
+        main(audiopath = '/audio', transform_path = 'dml_processing/sonic_annotator/vamp_plugins/bbc_speechmusic.n3', out_path = './')
+       
\ No newline at end of file
diff -r 000000000000 -r e34cf1b6fe09 ipcluster/tools/copy_features.py
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/ipcluster/tools/copy_features.py	Sat Feb 20 18:14:24 2016 +0100
@@ -0,0 +1,120 @@
+#!/usr/local/python
+# -*- coding: utf-8 -*-
+__author__="wolffd"
+import os
+import sys
+import time
+import shutil
+import hashlib
+import re
+import errno
+
+
+# this copies  features which used to be stored with the audio    
+# usage: copy_features source_path dest_path transform_substr ext move?
+# params:
+#        transfrom_substr can be either a substring or hash of the transform file
+#                         or the filename.n3 of a transform file
+# 
+# e.g. : D:\tools>python copy_features.py "D:/_Audio/" "D:/Chord_Analysis/" "1a812" ".csv" 0
+
+def main(audiopath, out_path, transform_substr = "", ext = "", move = 0):
+    # check move input
+    if move == 1:
+        print "Move script for VAMP features on the BL server"
+        v = raw_input("Do you really want to move files? (y/n)")
+        if not (v == 'y'):
+            return
+    else:
+        print "Copy script for VAMP features on the BL server"
+    
+    # replace transform_substr by pluginhash 
+    if transform_substr.endswith (".n3"):
+        BLOCKSIZE = 65536
+        hasher = hashlib.sha1()
+        with open(transform_substr, 'rb') as afile:
+            buf = afile.read(BLOCKSIZE)
+            while len(buf) > 0:
+                hasher.update(buf)
+                buf = afile.read(BLOCKSIZE)
+        transform_substr = str(hasher.hexdigest())
+        
+    # define valid extensions
+    if not ext:
+        ext = tuple([".n3",".csv",".mid"])
+    else:
+        ext = tuple([ext])
+    
+    # ---
+    # we traverse the file structure
+    # and list files to copy
+    # ---
+    data = []
+    count = 0
+    count2 = 0
+    for (dirpath, dirnames, filenames) in os.walk(audiopath):
+        for file in filenames:
+            print '\rChecked %d, gathered %d files' % (count, count2), 
+            count += 1
+            
+            # we copy all requested files and the transform files as well!
+            if (file.endswith(ext) or (transform_substr and (transform_substr in file))) and (transform_substr in dirpath):
+                source = os.path.join(dirpath, file).replace('\\','/')
+                data.append(source)
+                count2 +=1
+    
+    # count jobs
+    njobs = len(data)
+    print '\nAbout to copy or move %d files' % (njobs) 
+    
+               
+    count = 0
+    # copy individual items
+    for x in data:
+        spath = os.path.split(x)
+        folders = spath[0].split('/')
+        
+        # we remove the first folder that contains "_Analysis" from the path 
+        max_depth = -3
+        skip = -2
+        for i in range(1, -max_depth+1):
+            if "_Analysis" in folders[-i]:
+                skip = -i
+                break
+        
+        u = [folders[j] for j in range(max_depth,skip) +  range(skip+1,0)]
+        featpath = out_path + '/'.join([folders[j] for j in range(max_depth,skip) +  range(skip+1,0)])
+    
+        # create the target folder
+        try:
+            os.makedirs(featpath)
+        except OSError as exception:
+            if exception.errno!= errno.EEXIST:
+                raise   
+            
+        # copy stuff        
+        try:
+            dest = featpath + '/' + spath[1]
+            if move == 1:
+                #print '\rMoving %s to %s' % (x,dest)
+                shutil.move(x, dest )
+            else:
+                #print '\rCopying %s to %s' % (x,dest)
+                shutil.copy(x, dest )
+            count = count + 1
+        except:
+            continue
+        # progress indicator
+        print '\r%3.2f percent. %d done, %d pending' % (count/(njobs*1.0) * 100.0,count, njobs-count),
+        
+    print '\rCopied %d of %d files.' % (count,njobs)
+    print '\n'
+    
+
+
+if __name__ == "__main__":
+    if len(sys.argv) >= 5:
+        main(sys.argv[1],sys.argv[2], sys.argv[3],sys.argv[4], int(sys.argv[5]))
+    else:
+        main(audiopath = 'D:/_Audio/',out_path = 'D:/_Audio_Analysis/', transform_substr = "",  ext = "")
+       
\ No newline at end of file
diff -r 000000000000 -r e34cf1b6fe09 ipcluster/tools/copy_features_folderwise.py
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/ipcluster/tools/copy_features_folderwise.py	Sat Feb 20 18:14:24 2016 +0100
@@ -0,0 +1,118 @@
+#!/usr/local/python
+# -*- coding: utf-8 -*-
+__author__="wolffd"
+import os
+import sys
+import time
+import shutil
+import hashlib
+import re
+import errno
+
+
+# this copies  features which used to be stored with the audio    
+# usage: copy_features source_path dest_path transform_substr ext move?
+# params:
+#        transfrom_substr can be either a substring or hash of the transform file
+#                         or the filename.n3 of a transform file
+# 
+# e.g. : D:\tools>python copy_features_folderwise.py "D:/_Audio/" "D:/Chord_Analysis/" "1a812"  0
+
+def main(audiopath, out_path, transform_substr = "", move = 0):
+    # check move input
+    if move == 1:
+        print "Move script for VAMP features on the BL server"
+        v = raw_input("Do you really want to move folders? (y/n)")
+        if not (v == 'y'):
+            return
+    else:
+        print "Copy script for VAMP features on the BL server"
+    
+    # replace transform_substr by pluginhash 
+    if transform_substr.endswith (".n3"):
+        BLOCKSIZE = 65536
+        hasher = hashlib.sha1()
+        with open(transform_substr, 'rb') as afile:
+            buf = afile.read(BLOCKSIZE)
+            while len(buf) > 0:
+                hasher.update(buf)
+                buf = afile.read(BLOCKSIZE)
+        transform_substr = str(hasher.hexdigest())
+
+    # ---
+    # we traverse the file structure
+    # and list files to copy
+    # ---
+    data = []
+    count = 0
+    count2 = 0
+    for (dirpath, dirnames, filenames) in os.walk(audiopath):
+        for dir in dirnames:
+            print '\rChecked %d, gathered %d folders' % (count, count2), 
+            count += 1
+            
+            # we copy all requested files and the transform files as well!
+            if (transform_substr and (transform_substr in dir)):
+                source = os.path.join(dirpath, dir).replace('\\','/')
+                data.append(source)
+                count2 +=1
+    
+    # count jobs
+    njobs = len(data)
+    print '\nAbout to copy or move %d directories' % (njobs) 
+    
+               
+    count = 0
+    # copy individual items
+    for x in data:
+    
+        spath = os.path.split(x)
+        folders = spath[0].split('/')
+        
+        # if exists, we remove the first folder 
+        # which contains "_Analysis" from the path 
+        # maxdepth contains the maximum depth of folders structure to keep,
+        # counted from the most specific folder level
+        max_depth = -2
+        skip = -2
+        for i in range(1, -max_depth+1):
+            if "_Analysis" in folders[-i]:
+                skip = -i
+                break
+
+        folderbase = [folders[j] for j in range(max_depth,skip) + range(skip+1,0)]
+        featpath = out_path + '/'.join(folderbase)
+    
+        # create the target folder
+        try:
+            os.makedirs(featpath)
+        except OSError as exception:
+            if exception.errno!= errno.EEXIST:
+                raise   
+            
+        # copy stuff        
+
+        dest = featpath + '/' + spath[1]
+        if move == 1:
+            #print '\rMoving %s to %s' % (x,dest)
+            shutil.move(x, dest )
+
+        if move == 0:
+            #print '\rCopying %s to %s' % (x,dest)
+            shutil.copytree(x, dest )
+
+        count = count + 1
+        
+        # progress indicator
+        print '\r%3.2f percent. %d done, %d pending' % (count/(njobs*1.0) * 100.0,count, njobs-count),
+        
+    print '\rCopied %d of %d folders.' % (count,njobs)
+    print '\n'
+    
+
+if __name__ == "__main__":
+    if len(sys.argv) >= 5:
+        main(sys.argv[1],sys.argv[2], sys.argv[3], int(sys.argv[4]))
+    else:
+        main(audiopath = 'D:/_Audio/',out_path = 'D:/_Audio_Analysis/', transform_substr = "",  ext = "")
+       
diff -r 000000000000 -r e34cf1b6fe09 ipcluster/tools/turtle2rdf.py
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/ipcluster/tools/turtle2rdf.py	Sat Feb 20 18:14:24 2016 +0100
@@ -0,0 +1,19 @@
+# this file transforms an n3 file to rdf
+
+import rdflib
+
+def rdf2n3(in,out):
+    # create empty graph
+    g = rdflib.Graph
+
+    # import data
+    result = g.parse(in, format="n3")
+    result = g.serialise(out)
+    return result
+    
+if __name__ == "__main__":
+    if len(sys.argv) >= 3:
+        rdf2n3(sys.argv[1],sys.argv[2])
+    else:
+        print "Usage: rdf2n3 filein.n3 fileout.rdf"
+    
\ No newline at end of file
diff -r 000000000000 -r e34cf1b6fe09 ipcluster/tools/zip_features_folderwise.py
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/ipcluster/tools/zip_features_folderwise.py	Sat Feb 20 18:14:24 2016 +0100
@@ -0,0 +1,113 @@
+#!/usr/local/python
+# -*- coding: utf-8 -*-
+__author__="wolffd"
+import os
+import sys
+import time
+import shutil
+import hashlib
+import re
+import errno
+import subprocess
+
+
+# this copies  features which used to be stored with the audio    
+# usage: copy_features source_path dest_path transform_substr ext move?
+# params:
+#        transfrom_substr can be either a substring or hash of the transform file
+#                         or the filename.n3 of a transform file
+
+
+def main(audiopath, out_path, transform_substr = "", move = 0):
+    
+    
+    
+    # replace transform_substr by pluginhash 
+    if transform_substr.endswith (".n3"):
+        BLOCKSIZE = 65536
+        hasher = hashlib.sha1()
+        with open(transform_substr, 'rb') as afile:
+            buf = afile.read(BLOCKSIZE)
+            while len(buf) > 0:
+                hasher.update(buf)
+                buf = afile.read(BLOCKSIZE)
+        transform_substr = str(hasher.hexdigest())
+
+    # ---
+    # we traverse the file structure
+    # and list files to copy
+    # ---
+    data = []
+    count = 0
+    count2 = 0
+    for (dirpath, dirnames, filenames) in os.walk(audiopath):
+        for dir in dirnames:
+            print '\rChecked %d, gathered %d files' % (count, count2), 
+            count += 1
+            
+            # we copy all requested files and the transform files as well!
+            if (transform_substr and (transform_substr in dir)):
+                source = os.path.join(dirpath, dir).replace('\\','/')
+                data.append(source)
+                count2 +=1
+#        if count2 > 1:
+#            break
+    
+    # count jobs
+    njobs = len(data)
+    print '\r\nAbout to copy %d directories' % (njobs) 
+    
+               
+    count = 0
+    # copy individual items
+    for x in data:
+        spath = os.path.split(x)
+        folders = spath[0].split('/')
+        
+        collectionname = folders[-1]
+
+         # create the target folder
+        #try:
+        #    os.makedirs(out_path)
+        #except OSError as exception:
+        #    if exception.errno!= errno.EEXIST:
+        #        raise   
+                
+        command = '7z -r -mmt=30 -mx5 -v50g -mm=bzip2 a '  + '"' + os.path.join(out_path,collectionname + '_'+ transform_substr + '.zip') +  '"' + ' ' + x
+        print command
+        print " Currently zipping " + collectionname
+        
+        p = subprocess.Popen(command, stdout=subprocess.PIPE, stderr=subprocess.STDOUT, shell=True)
+        text = p.stdout.read()
+        retcode = p.wait()
+        if not (retcode==0):
+            print "Error: "  + text
+        
+        #os.system(command)
+        #print 'Removing ' + dest
+        #shutil.rmtree(dest)
+            
+        count = count + 1
+        
+        # progress indicator
+        print '\r%3.2f percent. %d done, %d pending' % (count/(njobs*1.0) * 100.0,count, njobs-count),
+        
+    print '\rCopied %d of %d files.' % (count,njobs)
+    print '\n'
+    
+def copytree(src, dst, symlinks=False, ignore=None):
+    for item in os.listdir(src):
+        s = os.path.join(src, item)
+        d = os.path.join(dst, item)
+        if os.path.isdir(s):
+            shutil.copytree(s, d, symlinks, ignore)
+        else:
+            os.makedirs(d)
+            shutil.copy2(s, d)
+
+if __name__ == "__main__":
+    if len(sys.argv) >= 5:
+        main(sys.argv[1],sys.argv[2], sys.argv[3], int(sys.argv[4]))
+    else:
+        main(audiopath = 'D:/_Audio/',out_path = 'D:/_Audio_Analysis/', transform_substr = "",  ext = "")
+       
diff -r 000000000000 -r e34cf1b6fe09 pyspark/Makefile
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/pyspark/Makefile	Sat Feb 20 18:14:24 2016 +0100
@@ -0,0 +1,5 @@
+release:
+	tar czf dml-cla.tar.gz dml-analyser.* n3Parser.py ontologies transforms
+
+unrelease:
+	tar xzf dml-cla.tar.gz
diff -r 000000000000 -r e34cf1b6fe09 pyspark/csvParser.py
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/pyspark/csvParser.py	Sat Feb 20 18:14:24 2016 +0100
@@ -0,0 +1,113 @@
+# Part of DML (Digital Music Laboratory)
+#
+# This program is free software; you can redistribute it and/or
+# modify it under the terms of the GNU General Public License
+# as published by the Free Software Foundation; either version 2
+# of the License, or (at your option) any later version.
+# 
+# This program is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+# GNU General Public License for more details.
+# 
+# You should have received a copy of the GNU General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA  02110-1301  USA
+
+# -*- coding: utf-8 -*-
+__author__="Daniel Wolff"
+
+import codecs
+import warnings
+import numpy
+import csv
+from n3Parser import uri2path
+
+
+# reads csv file into a table,
+# the first column, containing "time" is converted to float, the rest is left at strings
+# data formats are for example:
+# for silvet pitch output:['time','duration','pitch','velocity','label']
+# for qm_vamp_key_standard output: ['time','keynr','label']
+# for qm_vamp_key_standard_tonic output: ['time','keynr','label']
+#
+# data can be nicely traversed:
+# for time, duration,pitch,velocity,label 
+def get_array_from_csv(input_f_file):
+
+    output = []
+    badcount = 0
+    
+    # keep track of column names
+    ncols = 0
+    with open(uri2path(input_f_file), 'rb') as csvfile:
+        contents = csv.reader(csvfile, delimiter=',', quotechar='"')
+        for row in contents:
+            if ncols == 0:
+                ncols = len(row)
+                
+	    if len(row) >= ncols:
+                # we assume format time , ...
+	        output.append([float(row[0])] + row[1:])
+            else: 
+                badcount += 1
+                
+    if badcount > 0:
+        warnings.warn("Incomplete csv file, ignoring " + str(badcount) + " entries")
+        
+    return output
+
+
+
+
+
+# converts csv input to dictionary with entities named as in "columtype".
+#
+# first value (time) is assumed to be float
+# for silvet pitch output call_
+#  csv_to_dict(input_f_file, columtype = ['time','duration','pitch','velocity','label'])
+# for qm_vamp_key_standard output call 
+#    csv_to_dict(input_f_file, columtype = ['time','keynr','label'])
+# for qm_vamp_key_standard_tonic output call 
+#    csv_to_dict(input_f_file, columtype = ['time','keynr','label'])
+def get_dict_from_csv(input_f_file, columtype = ['time']):
+    
+    output = []
+    badcount = 0
+    
+    # keep track of column names
+    ncols = 0
+    with open(uri2path(input_f_file), 'rb') as csvfile:
+        contents = csv.reader(csvfile, delimiter=',', quotechar='"')
+        for row in contents:
+            
+            # initialise the column name
+            if ncols == 0:
+                ncols = len(row)
+                
+                # get number of descriptors, and append if left empty
+                ncoldescr = len(columtype)
+                if ncoldescr < ncols:
+                    warnings.warn("Column types missing")
+                    columtype.extend(['data'+str(i) for i in range(ncoldescr+1, ncols+1)])
+
+	    if len(row) == ncols:
+                # parse the csv data into dict
+                rowdict = dict()
+                for i,col in enumerate(columtype):
+                    # first value (time) is transformed to float
+                    if i == 0:
+                        rowdict[col] = float(row[i])
+                    else:
+                        rowdict[col] = row[i]
+                
+                # append dictionary to output
+                output.append(rowdict)
+                
+            else: 
+                badcount += 1
+                
+    if badcount > 0:
+        warnings.warn("Incomplete csv file, ignoring " + str(badcount) + " entries")
+
+    return output
diff -r 000000000000 -r e34cf1b6fe09 pyspark/decode_to_wav.py
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/pyspark/decode_to_wav.py	Sat Feb 20 18:14:24 2016 +0100
@@ -0,0 +1,45 @@
+# Part of DML (Digital Music Laboratory)
+#
+# This program is free software; you can redistribute it and/or
+# modify it under the terms of the GNU General Public License
+# as published by the Free Software Foundation; either version 2
+# of the License, or (at your option) any later version.
+# 
+# This program is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+# GNU General Public License for more details.
+# 
+# You should have received a copy of the GNU General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA  02110-1301  USA
+
+#!/usr/bin/python
+# -*- coding: utf-8 -*-
+
+__author__="wolffd"
+__date__ ="$21-Jul-2014 15:36:41$"
+
+# -*- coding: utf-8 -*-
+#from timeside.decoder import *
+#from timeside.encoder import *
+#import os.path
+#import sys
+# now use a regular timeside installation, e.g. installed by 
+#sys.path.append(os.getcwd() + '/../TimeSide/')
+
+from timeside.decoder.file import *
+from timeside.encoder.wav import *
+
+def decode_to_wav(source = 'sweep.flac'):
+    if source[-4:] == ".wav" :
+        dest = source
+        print "already converted: " + dest
+        
+    else:
+        dest = source + '.wav'
+        decoder  = FileDecoder(source)
+        encoder  = WavEncoder(dest, overwrite=True)
+        (decoder | encoder).run()
+        print "decoded: " + dest
+    return dest
diff -r 000000000000 -r e34cf1b6fe09 pyspark/dml-analyser.cfg
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/pyspark/dml-analyser.cfg	Sat Feb 20 18:14:24 2016 +0100
@@ -0,0 +1,3 @@
+[Ontology]
+
+dmlclaOntology_URI = ontologies/dmlclaOntology.n3
diff -r 000000000000 -r e34cf1b6fe09 pyspark/dml-analyser.py
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/pyspark/dml-analyser.py	Sat Feb 20 18:14:24 2016 +0100
@@ -0,0 +1,188 @@
+# Part of DML (Digital Music Laboratory)
+#
+# This program is free software; you can redistribute it and/or
+# modify it under the terms of the GNU General Public License
+# as published by the Free Software Foundation; either version 2
+# of the License, or (at your option) any later version.
+# 
+# This program is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+# GNU General Public License for more details.
+# 
+# You should have received a copy of the GNU General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA  02110-1301  USA
+
+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+__author__="hargreavess"
+
+import ConfigParser
+import logging
+import os
+import time
+import shutil
+import argparse
+from os import walk
+import rdflib
+from rdflib import Graph
+from RDFClosure import DeductiveClosure, OWLRL_Semantics
+from transforms.tonicHistogram import find_cla_tonic_histogram, add_tonic_histogram_to_graph
+from transforms.tuningFrequencyStatistics import find_cla_tf_statistics, add_tf_statistics_to_graph
+from transforms.semitoneHistogram import find_cla_semitone_histogram, add_semitone_histogram_to_graph
+from transforms.tonicNormSemitoneHistogram import find_cla_tonic_norm_semitone_histogram, add_tonic_norm_semitone_histogram_to_graph
+
+input_rdf_graph = Graph()
+
+def main():
+
+    # get config
+    config = ConfigParser.ConfigParser()
+    config.read('dml-analyser.cfg')
+
+    # parse dmlcla ontolgy
+    input_rdf_graph.parse(config.get('Ontology', 'dmlclaOntology_URI'), format="n3")
+    DeductiveClosure(OWLRL_Semantics).expand(input_rdf_graph)
+
+    # parse input rdf
+    input_rdf_graph.parse(args.transforms, format="n3")
+    DeductiveClosure(OWLRL_Semantics).expand(input_rdf_graph)
+
+    # initialise output rdf graph
+    output_rdf_graph = Graph()
+
+    # Determine which transforms are to be applied, and
+    # the associated input files
+    transforms = find_transforms_in_n3(input_rdf_graph)
+
+    # Apply the transform(s) to each file and create 
+    # rdf results graph
+    output_rdf_graph = execute_transforms(transforms, output_rdf_graph)
+
+    # Write output rdf to stdout
+    print(output_rdf_graph.serialize(format='n3'))
+
+# Loop through all transforms, process the corresponding
+# input files appropriately and add the (RDF) result to output_rdf_graph
+def execute_transforms(transforms, output_rdf_graph):
+
+    transform_iter = transforms.iterkeys()
+    key_histogram = []
+
+    for (transform, transform_type) in transforms:
+
+        input_f_files = transforms.get((transform, transform_type))
+
+        # Add additional clauses to this if statement
+        # for each transform type
+        if transform_type == rdflib.term.URIRef(u'http://dml.org/dml/cla#CollectionLevelTonic'):
+
+            (tonic_histogram, sample_count) = find_cla_tonic_histogram(input_f_files)
+            output_rdf_graph = add_tonic_histogram_to_graph(tonic_histogram, output_rdf_graph, transform, sample_count, input_f_files)
+            
+        elif transform_type == rdflib.term.URIRef(u'http://dml.org/dml/cla#CollectionLevelTuningFrequencyStatistics'):
+
+            statistics, sample_count = find_cla_tf_statistics(input_f_files)
+            output_rdf_graph = add_tf_statistics_to_graph(statistics, output_rdf_graph, transform, sample_count, input_f_files)
+
+        elif transform_type == rdflib.term.URIRef(u'http://dml.org/dml/cla#CollectionLevelSemitone'):
+
+            (semitone_histogram, sample_count) = find_cla_semitone_histogram(input_f_files)
+            output_rdf_graph = add_semitone_histogram_to_graph(semitone_histogram, output_rdf_graph, transform, sample_count, input_f_files)
+
+        elif transform_type == rdflib.term.URIRef(u'http://dml.org/dml/cla#CollectionLevelTonicNormSemitone'):
+
+            (tonic_norm_semitone_histogram, sample_count) = find_cla_tonic_norm_semitone_histogram(input_f_files, input_rdf_graph)
+            output_rdf_graph = add_tonic_norm_semitone_histogram_to_graph(tonic_norm_semitone_histogram, output_rdf_graph, transform, sample_count, input_f_files, input_rdf_graph)
+
+    return output_rdf_graph
+
+# Find all transforms, and their associated input files,
+# from rdf_graph
+def find_transforms_in_n3(rdf_graph):
+
+    qres = rdf_graph.query(
+        """prefix dml:     <http://dml.org/dml/cla#>
+            SELECT ?transform ?dml_input ?transform_type
+            WHERE {
+                ?transform a dml:Transform .
+                ?transform dml:input ?dml_input .
+                ?transform dml:type ?transform_type .
+            }""")
+
+    transforms = dict()
+    
+    for row in qres:
+
+        transform_bnode = row.transform
+        dml_input = row.dml_input
+        transform_type = row.transform_type
+
+        if transforms.has_key((transform_bnode, transform_type)):
+
+            transform_key = transforms.get((transform_bnode, transform_type))
+            transform_key.append(dml_input)
+
+        else:
+
+            transforms[(transform_bnode, transform_type)] = [dml_input]
+
+    return transforms
+
+# Determine the mapping between feature file URIs and
+# their source audio file URIs
+def map_audio_to_feature_files():    
+
+    # Loop through audio files
+    lines = [line.strip() for line in args.audio_files]
+
+    for audio_file in lines:
+
+        print "sonic-annotator -T " + args.transforms + " --rdf-basedir " + args.basedir + " <" + audio_file + ">"
+
+    audio_to_feature_file_dict = dict()
+
+    for (dirpath, dirnames, filenames) in walk(args.basedir):
+        for file in filenames:
+
+            print "found file: " + file
+
+            if file.endswith(".n3"):
+
+                print "found n3 file: " + file
+
+                # open and parse n3 file
+                rdf_graph = Graph()
+                rdf_graph.parse(os.path.join(dirpath, file), format="n3")
+
+                # find subject in ?subject a mo:AudioFile
+                qres = rdf_graph.query(
+                    """SELECT ?audio_file
+                       WHERE {
+                          ?audio_file a mo:AudioFile .
+                       }""")
+
+                print len(qres)
+
+                for row in qres:
+
+                    print("audio file URI is %s" % row.audio_file.n3())
+                    print("feature file URI is %s" % os.path.join(os.getcwd(), dirpath, file))
+                    audio_to_feature_file_dict[row.audio_file.n3()] = os.path.join(os.getcwd(), dirpath, file)
+
+                # add full file URI, subject to dict
+
+    print audio_to_feature_file_dict
+
+if __name__ == "__main__":
+
+    parser = argparse.ArgumentParser()
+
+    parser.add_argument("-T", "--transforms", help="the URI of an n3 (RDF) file describing one or more transforms, and the files to which they should be applied")
+    parser.add_argument("-b", "--basedir", help="the URI of the base output directory")
+
+    args = parser.parse_args()
+
+    main()
+    
diff -r 000000000000 -r e34cf1b6fe09 pyspark/dml-cla.tar.gz
Binary file pyspark/dml-cla.tar.gz has changed
diff -r 000000000000 -r e34cf1b6fe09 pyspark/ilm/assetDB.py
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/pyspark/ilm/assetDB.py	Sat Feb 20 18:14:24 2016 +0100
@@ -0,0 +1,229 @@
+# Part of DML (Digital Music Laboratory)
+#
+# This program is free software; you can redistribute it and/or
+# modify it under the terms of the GNU General Public License
+# as published by the Free Software Foundation; either version 2
+# of the License, or (at your option) any later version.
+# 
+# This program is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+# GNU General Public License for more details.
+# 
+# You should have received a copy of the GNU General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA  02110-1301  USA
+
+#!/usr/bin/env python
+# encoding: utf-8
+"""
+assetDB.py
+
+Created by George Fazekas on 2012-01-16. Modifications by Mathieu Barthet in 2013-12,
+Steven Hargreaves 22/12/2014.
+Copyright (c) 2013 . All rights reserved.
+"""
+
+import sys,os,logging
+import sqlalchemy as sal
+from sqlalchemy.ext.declarative import declarative_base
+from sqlalchemy import Column, Integer, String, Sequence, Enum
+from sqlalchemy.orm import sessionmaker
+from sqlalchemy.dialects import mysql
+from hashlib import md5
+
+class assetDB(object):
+
+    asset_types = ['wav','mpeg/320kbps','mpeg/64kbps']
+    extensions = ['wav','mp3','mp3']
+    ext = dict(zip(asset_types,extensions))
+
+    def __init__(self, prefix, pref=list(), config=None):
+        self.log = logging.getLogger('spark_feat_extract')
+        self.log.info("ORM Version: %s",sal.__version__)
+        self.config = config
+        self.session = None
+        self.Assets = None
+        self.prefix = prefix
+        if pref :
+            self.asset_prefs = pref
+        else :
+            self.asset_prefs = assetDB.asset_types
+        # reporting errors:
+        self.found_different_asset_type = 0
+        self.errata_file = None
+        if config and hasattr(config,"db_errata_file") :
+            self.errata_file = config.db_errata_file
+
+
+    def connect(self,echo=False):
+        '''Connect to the MySQL database and create a session.'''
+        URL = "mysql://%s:%s@%s/%s" %(self.config.get('Commercial Asset Database', 'user'),self.config.get('Commercial Asset Database', 'passwd'),self.config.get('Commercial Asset Database', 'host'),self.config.get('Commercial Asset Database', 'name'))
+        self.log.info("Connecting to database server at: %s",URL.replace(self.config.get('Commercial Asset Database', 'passwd'),'*****'))
+        engine=sal.create_engine(URL, echo=echo)
+        Session = sessionmaker(bind=engine)
+        self.session = Session()
+        self.log.debug("MySQL session created successfully.")
+        return self
+
+    def close(self):
+        '''Close the database session'''
+        if self.session :
+            self.session.close()
+            self.log.info("Database closed.")
+        return self
+
+    def create_mapper(self):
+        '''Create an Object-Relational Mapper'''
+        Base = declarative_base()
+        class Assets(Base):
+            #change
+            #__tablename__ = 'assets'
+            __tablename__ = self.config.get('Commercial Asset Database', 'tablename')
+            # map all table columns to variables here, e.g.
+            # album_id = Column(Integer, primary_key=True)
+            # song_title = Column(String)
+            # genre_id = Column(Integer)
+        self.Assets = Assets
+        return self
+
+    def get_assets(self,start=0,limit=10,asset_type='audio/x-wav'):
+        '''Returns some assets from the database.
+        If the path given by the specified asset type does not exists, 
+        try to find the assets given the preference list provided in self.asset_prefs.
+        If no valid path can be found for an asset, log the error and yield None for the path.'''
+        # limit = start + limit # this changes the semantics of the SQL limit
+
+        # create the ORM mapper object if doesn't exist
+        if self.Assets == None :
+            self.create_mapper()
+
+        # generate an SQL query and for each asset in the results, yield a (validated) path name for the asset, or yield None if not found
+        for asset in self.session.query(self.Assets)[start:limit]:
+            path = self.generate_path(asset,asset_type)
+            if self.validate_path(path) and self.validate_size(path,asset_type):
+                yield path,asset
+            elif not self.asset_prefs :
+                self.log.error("Requested file for asset not found: %s. (Album ID: %i)",asset.song_title,asset.album_id)
+                yield None,asset
+            else :
+                #change
+                self.log.warning("Requested file for asset bad or not found: %s. (Album ID: %i)",asset.song_title,asset.album_id)
+                self.log.warning("Trying other asset types.")
+                path = self.find_preferred_asset_path(asset)
+                if path == None :
+                    yield None,asset
+                else :
+                    yield path,asset
+            # ensure each asset yields only once
+            pass
+        pass
+
+    def get_assets_by_genre(self,genre_id,start=0,limit=10,asset_type='audio/x-wav'):
+        '''Returns some assets of the given genre_id from the database.
+        If the path given by the specified asset type does not exists, 
+        try to find the assets given the preference list provided in self.asset_prefs.
+        If no valid path can be found for an asset, log the error and yield None for the path.'''
+        # limit = start + limit # this changes the semantics of the SQL limit
+
+        # create the ORM mapper object if doesn't exist
+        if self.Assets == None :
+            self.create_mapper()
+
+        # generate an SQL query and for each asset in the results, yield a (validated) path name for the asset, or yield None if not found
+        for asset in self.session.query(self.Assets).filter(self.Assets.genre_id == genre_id).all()[start:limit]:
+            path = self.generate_path(asset,asset_type)
+            if self.validate_path(path) and self.validate_size(path,asset_type):
+                yield path,asset
+            elif not self.asset_prefs :
+                self.log.error("Requested file for asset not found: %s. (Album ID: %i)",asset.song_title,asset.album_id)
+                yield None,asset
+            else :
+                #change
+                self.log.warning("Requested file for asset bad or not found: %s. (Album ID: %i)",asset.song_title,asset.album_id)
+                self.log.warning("Trying other asset types.")
+                path = self.find_preferred_asset_path(asset)
+                if path == None :
+                    yield None,asset
+                else :
+                    yield path,asset
+            # ensure each asset yields only once
+            pass
+        pass
+
+    def find_preferred_asset_path(self,asset):
+        '''Iteratively find a path name for each asset type in asset_prefs and return the first one available. 
+        Return None if not found and log this event for error management.'''
+        path = unicode()
+        for asset_type in self.asset_prefs :
+            path = self.generate_path(asset,asset_type)
+            if self.validate_path(path):
+                self.log.info("Asset found but type is different from requested: %s. (Album ID: %i) ",asset.song_title,asset.album_id)
+                self.append_db_errata(path,"Found different asset type for problem case. (%s)"%asset_type)
+                self.found_different_asset_type += 1
+                if self.validate_size(path,asset_type):
+                    return path
+                else :
+                    self.log.error("Requested file for asset is worng size, probably corrupt: %s. (Album ID: %i)",asset.song_title,asset.album_id)
+                    continue
+            else:
+                self.append_db_errata(path,"File not found.")
+        if len(path) == 0 :
+            self.log.warning("Asset not found for: %s. (Album ID: %i)",asset.song_title,asset.album_id)
+            return None
+
+    def generate_path(self,asset,asset_type):
+        '''Generate the path name given a asset database object and a requested asset type'''
+        path = '' # need to generate audio file path here
+        return path
+
+    def validate_path(self,path):
+        '''Validate the generated path name.'''
+        return os.path.isfile(path)
+
+    def validate_size(self,path,asset_type):
+        '''Check if the file size makes sense.'''
+        size = -1
+        try :
+            size = int(os.path.getsize(path))
+        except Exception, e:
+            self.append_db_errata(path,"Unable to determine file size.")
+            self.log.error("Unable to determine file size: %s." %path)
+            self.log.error("Exception %s."%str(e))
+            return False
+        if size == 0 :
+            self.append_db_errata(path,"File has zero size.")
+            self.log.error("File has zero size: %s."%path)
+            return False
+        if 'wav' in asset_type :
+            # rationale: with very small files some feature extractor plugins fail or output junk
+            if size > 209715200 or size < 209715 :
+                self.append_db_errata(path,"Rejected file size is: %f KB" %(size/1024.0))
+                return False
+        if 'mpeg' in asset_type :
+            # same assuming about 1:10 compression
+            if size > 41943040 or size < 65536 :
+                self.append_db_errata(path,"Rejected file size is: %f KB" %(size/1024.0))
+                return False
+        return True
+
+    def get_different_asset_no(self):
+        '''Return a count of the cases where the preferred asset type was not found'''
+        return self.found_different_asset_type
+
+    def reset_different_asset_no(self):
+        '''Reset the asset type was not found counter'''
+        self.found_different_asset_type = 0
+
+    def append_db_errata(self,filename,reason,metadata=""):
+        '''Append to a file collecting assets present in the DB but not found on disk.'''
+        if not self.errata_file : return False
+        try :
+            with open(self.errata_file,"a+") as ef:
+                if metadata :
+                    ef.write("%(filename)s,%(reason)s,%(metadata)s\n"%locals())
+                else:
+                    ef.write("%(filename)s,%(reason)s\n"%locals())
+        except:
+            self.log.error("Failed to append database errata.")
+
diff -r 000000000000 -r e34cf1b6fe09 pyspark/ilm/server.cfg
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/pyspark/ilm/server.cfg	Sat Feb 20 18:14:24 2016 +0100
@@ -0,0 +1,28 @@
+[Files]
+
+[Audio Files]
+audio-file-size-limit = 100
+audio-prefix = /media
+
+[Sonic Annotator]
+output-dir = /media/data
+vamp-transform-list = transform_list.txt
+
+[Commercial Asset Database]
+host = localhost
+user = ???
+passwd = ???
+name = ???
+tablename = ???
+
+[Queries]
+sql-start = 0
+sql-limit = 1000000
+genre-id = 16
+
+[Spark]
+num-cores = 20
+memory = 100g
+
+[Application]
+array-step-size = 1000
diff -r 000000000000 -r e34cf1b6fe09 pyspark/ilm/spark_feat_extract.py
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/pyspark/ilm/spark_feat_extract.py	Sat Feb 20 18:14:24 2016 +0100
@@ -0,0 +1,158 @@
+# Part of DML (Digital Music Laboratory)
+#
+# This program is free software; you can redistribute it and/or
+# modify it under the terms of the GNU General Public License
+# as published by the Free Software Foundation; either version 2
+# of the License, or (at your option) any later version.
+# 
+# This program is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+# GNU General Public License for more details.
+# 
+# You should have received a copy of the GNU General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA  02110-1301  USA
+
+#!/usr/local/spark-1.0.0-bin-hadoop2/bin/spark-submit
+# -*- coding: utf-8 -*-
+__author__="hargreavess"
+
+from assetDB import assetDB
+from pyspark import SparkConf, SparkContext
+import ConfigParser
+import logging
+from transform import *
+import os
+import time
+import shutil
+
+def main():
+    start_complete = time.time();
+
+    # get config
+    config = ConfigParser.ConfigParser()
+    config.read('server.cfg')
+
+    #vamp_transform = [config.get('Sonic Annotator', 'vamp-transform')]
+    vamp_transform_list = config.get('Sonic Annotator', 'vamp-transform-list')
+    genre_id = config.getint('Queries', 'genre-id')
+
+    output_dir = config.get('Sonic Annotator', 'output-dir')
+    ltime = time.localtime()
+    output_dir = output_dir + '_' + str(ltime.tm_mday) + '_' + str(ltime.tm_mon) + '_' + str(ltime.tm_year)
+    output_dir = output_dir + '_' + str(ltime.tm_hour) + str(ltime.tm_min) + '_' + str(ltime.tm_sec)
+    output_dir = output_dir + '_genre_id_' + str(genre_id)
+    # create output directory, if it doesn't exist
+    if not os.access(output_dir, os.F_OK):
+        os.makedirs(output_dir)
+
+    # copy vamp_transform_list file to output directory
+    shutil.copy(vamp_transform_list, output_dir)
+        
+    # create logger
+    #logger = logging.getLogger('spark_feat_extract')
+    logger = logging.getLogger('spark_feat_extract')
+    logger.setLevel(logging.DEBUG)
+
+    # create file handler and set level to debug
+    fh = logging.FileHandler(output_dir + "/ilm.assets.spark.features.log")
+    fh.setLevel(logging.DEBUG)
+
+    # create formatter
+    formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s')
+
+    # add formatter to fh
+    fh.setFormatter(formatter)
+
+    # add fh to logger
+    logger.addHandler(fh)
+
+    logger.info('starting new spark_feat_extract job')
+    logger.info("using vamp transform list: " + vamp_transform_list)
+    logger.info('audio-file-size-limit: ' + config.get('Audio Files', 'audio-file-size-limit'))
+    logger.info("audio-prefix: " + config.get('Audio Files', 'audio-prefix'))
+    logger.info('num-cores: ' + config.get('Spark', 'num-cores'))
+    logger.info("spark memory: " + config.get('Spark', 'memory'))
+    logger.info("genre_id: " + str(genre_id))
+
+    # create a spark context
+    conf = (SparkConf()
+            .setMaster("local[" + config.get('Spark', 'num-cores') + "]")
+            .setAppName("spark feature extractor")
+            .set("spark.executor.memory", "" + config.get('Spark', 'memory') + ""))
+    sc = SparkContext(conf = conf)
+
+    SQL_start = config.getint('Queries', 'sql-start')
+    SQL_limit = config.getint('Queries', 'sql-limit')
+    local_SQL_start = SQL_start
+    logger.info('SQL_start = %i', SQL_start)
+    logger.info('SQL_limit = %i', SQL_limit)
+
+    array_step_size = config.getint('Application', 'array-step-size')
+    logger.info('array-step-size = %i', array_step_size)
+    local_SQL_limit = min(SQL_limit, array_step_size)
+
+    while local_SQL_limit <= SQL_limit:
+
+        # query db for assets (song tracks)
+        db = assetDB(prefix=config.get('Audio Files', 'audio-prefix'),config=config)
+        db.connect()
+
+        data = []
+        logger.info('local_start = %i', local_SQL_start)
+        logger.info('local_SQL_limit = %i', local_SQL_limit)
+
+        for path, asset in db.get_assets_by_genre(genre_id, local_SQL_start, local_SQL_limit):
+            if path == None:
+                logger.warning("Asset not found for: %s. (Album ID: %i Track No: %i)",asset.song_title,asset.album_id,asset.track_no)
+            else:
+                data.append(path)
+
+        db.close
+
+        # If the db query returned no results, stop here
+        if len(data) == 0:
+            break
+
+        batch_output_dir = output_dir + '/batch' + str(local_SQL_start) + '-' + str(local_SQL_limit)
+        os.makedirs(batch_output_dir)
+        logger.info('created results directory ' + batch_output_dir)
+
+        logger.info("calling sc.parallelize(data)...")
+        start = time.time();
+
+        # define distributed dataset
+        distData = sc.parallelize(data)
+        end = time.time();
+        logger.info("finished in " + (str)(end - start))
+
+        logger.info("calling distData.map...")
+        start = time.time();
+
+        # define map 
+        m1 = distData.map(lambda x: transform(audio_file=x,
+            vamp_transform_list=vamp_transform_list,
+            output_dir=batch_output_dir))
+        end = time.time();
+        logger.info("finished in " + (str)(end - start))
+
+        logger.info("calling m1.collect()...")
+        start = time.time();
+
+        # collect results
+        theResult = m1.collect()
+
+        end = time.time();
+
+        logger.info("finished in " + (str)(end - start))
+
+        local_SQL_start += array_step_size
+        local_SQL_limit += min(SQL_limit, array_step_size)
+
+    print "finished all in " + (str)(end - start_complete)
+    logger.info("finished all in " + (str)(end - start_complete))
+
+if __name__ == "__main__":
+    main()
+    
diff -r 000000000000 -r e34cf1b6fe09 pyspark/ilm/transform.py
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/pyspark/ilm/transform.py	Sat Feb 20 18:14:24 2016 +0100
@@ -0,0 +1,45 @@
+# Part of DML (Digital Music Laboratory)
+#
+# This program is free software; you can redistribute it and/or
+# modify it under the terms of the GNU General Public License
+# as published by the Free Software Foundation; either version 2
+# of the License, or (at your option) any later version.
+# 
+# This program is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+# GNU General Public License for more details.
+# 
+# You should have received a copy of the GNU General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA  02110-1301  USA
+
+#!/usr/bin/python
+# -*- coding: utf-8 -*-
+__author__="hargreavess"
+__date__ ="$29-Sep-2014 15:31:01$"
+
+import subprocess
+import time
+import random
+from os import walk
+
+def transform(audio_file, vamp_transform_list, output_dir):
+    print "transforming " + audio_file
+
+    command = ['sonic-annotator']
+    command.extend(['-T', vamp_transform_list,
+        audio_file, '-w', 'rdf', '--rdf-force', '--rdf-basedir', output_dir, '--rdf-many-files',
+        '-w', 'csv', '--csv-force', '--csv-basedir', output_dir])
+
+    print "calling subprocess.subprocess.Popen..."
+    start = time.time()
+    p = subprocess.Popen(
+        command, stdout=subprocess.PIPE, stderr=subprocess.STDOUT)
+    p.wait()
+
+    end = time.time()
+    print "finished in " + (str)(end-start)
+
+    return True
+
diff -r 000000000000 -r e34cf1b6fe09 pyspark/ilm/transform_list.txt
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/pyspark/ilm/transform_list.txt	Sat Feb 20 18:14:24 2016 +0100
@@ -0,0 +1,7 @@
+/home/dmluser/vamp_plugins/beatroot_standard.n3
+/home/dmluser/vamp_plugins/tempotracker_tempo_standard.n3
+/home/dmluser/vamp_plugins/tempotracker_beats_standard.n3
+/home/dmluser/vamp_plugins/qm_vamp_key_standard.n3
+/home/dmluser/vamp_plugins/qm_vamp_key_standard_tonic.n3
+/home/dmluser/vamp_plugins/qm-segmentation_standard.n3
+/home/dmluser/vamp_plugins/qm-chromagram_standard.n3
diff -r 000000000000 -r e34cf1b6fe09 pyspark/n3Parser.py
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/pyspark/n3Parser.py	Sat Feb 20 18:14:24 2016 +0100
@@ -0,0 +1,74 @@
+# Part of DML (Digital Music Laboratory)
+#
+# This program is free software; you can redistribute it and/or
+# modify it under the terms of the GNU General Public License
+# as published by the Free Software Foundation; either version 2
+# of the License, or (at your option) any later version.
+# 
+# This program is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+# GNU General Public License for more details.
+# 
+# You should have received a copy of the GNU General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA  02110-1301  USA
+
+from rdflib import Graph
+from rdflib.plugins.parsers.notation3 import BadSyntax
+import warnings
+import codecs
+import platform
+
+# Load and parse an n3 file
+def get_rdf_graph_from_n3(n3_file_uri):
+
+    graph = Graph()
+
+    try:
+        graph.parse(n3_file_uri, format="n3")
+    except UnicodeDecodeError:
+        
+        n3_file_str = uri2path(n3_file_uri)
+        n3_file_iso = codecs.open(n3_file_str, 'r', "iso-8859-1")
+
+        # check if n3 is valid and parse
+        # repair if necessary
+        graph = parse_potentially_corrupt_n3(n3_file_iso.read())
+
+    except (AssertionError, BadSyntax):
+
+        n3_file_str = uri2path(n3_file_uri)
+        n3_file = open(n3_file_str, 'r')
+        graph = parse_potentially_corrupt_n3(n3_file.read())
+
+    return graph
+
+# can parse truncated n3
+def parse_potentially_corrupt_n3(content):
+    feature_graph = Graph()
+    # test if file is complete. 
+    # if not, delete the last corrupted entry
+    if not '.' in content[-4:]:
+        warnings.warn("Incomplete rdf file, ignoring last entry")
+        # we find the last correct event
+        lastentry = content.rfind(':event')
+        feature_graph.parse(data=content[:lastentry], format="n3")
+    else:
+        feature_graph.parse(data=content, format="n3")
+
+    return feature_graph
+
+# returns filepath from url
+def uri2path(n3_file_uri):
+    
+    n3_file_uri_str = n3_file_uri.__str__()
+    
+    # Assume that n3_file_uri_str starts with 'file://' - we need to remove that
+    if 'Win' in platform.system():
+        FILE_URI_START_INDEX = 8
+    else:
+        FILE_URI_START_INDEX = 7
+            
+    n3_file_str = n3_file_uri_str[FILE_URI_START_INDEX:len(n3_file_uri_str)]
+    return n3_file_str
\ No newline at end of file
diff -r 000000000000 -r e34cf1b6fe09 pyspark/ontologies/dmlclaOntology.n3
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/pyspark/ontologies/dmlclaOntology.n3	Sat Feb 20 18:14:24 2016 +0100
@@ -0,0 +1,205 @@
+@prefix rdfs:           <http://www.w3.org/2000/01/rdf-schema#> .
+@prefix owl:            <http://www.w3.org/2002/07/owl#> .
+@prefix xsd:            <http://www.w3.org/2001/XMLSchema#> .
+@prefix rdf:            <http://www.w3.org/1999/02/22-rdf-syntax-ns#> .
+@prefix dml:            <http://dml.org/dml/cla#> .
+@prefix vamp:           <http://purl.org/ontology/vamp/> .
+@prefix dc:             <http://purl.org/dc/elements/1.1/> .
+@prefix qmplugbase:     <http://vamp-plugins.org/rdf/plugins/qm-vamp-plugins#> .
+@prefix silvetplugbase: <http://vamp-plugins.org/rdf/plugins/silvet#> .
+
+# This file defines an ontology, which also imports the vamp plugin ontology
+<dmlclaOntology.n3> a owl:Ontology;
+    owl:imports <http://vamp-plugins.org/rdf/plugins/qm-vamp-plugins> .
+
+# Our highest level class is a dml:Transform
+dml:Transform a owl:Class .
+dml:CollectionLevelAnalysis rdfs:subClassOf dml:Transform .
+
+dml:type rdfs:subPropertyOf rdf:type .
+
+vamp:Transform rdfs:subClassOf dml:Transform .
+
+dml:input a owl:ObjectProperty .
+dml:output a owl:ObjectProperty .
+
+# A CollectionLevelTonic is a CollectionLevelAnalysis,
+# it requires at least one input, and these inputs
+# will all be outputs from the qm keydetector vamp plugin.
+dml:CollectionLevelTonic rdfs:subClassOf dml:CollectionLevelAnalysis ;
+    owl:equivalentClass [ a owl:Restriction ;
+    					  owl:onProperty dml:collectionLevelTonicInput ;
+    					  owl:minCardinality 1] ;
+    owl:equivalentClass [ a owl:Restriction ;
+    					  owl:onProperty dml:collectionLevelTonicOutput ;
+    					  owl:cardinality 1] .
+    					  
+dml:collectionLevelTonicInput rdfs:subPropertyOf dml:input ;
+	rdfs:range qmplugbase:qm-keydetector_output_tonic .
+
+dml:collectionLevelTonicOutput rdfs:subPropertyOf dml:output ;
+	rdfs:range dml:TonicHistogram .
+
+# A (Tonic) Key Histogram is defined as:
+dml:TonicHistogram a vamp:DenseOutput ;
+    vamp:identifier       "tonichistogram" ;
+    dc:title              "Tonic Histogram" ;
+    dc:description        "Histogram of estimated tonic (from C major = 1 to B major = 12)."  ;
+    vamp:fixed_bin_count  "true" ;
+    vamp:unit             "" ;
+    vamp:bin_count        12 ;
+    vamp:bin_names        ( "C" "C#" "D" "D#" "E" "F" "F#" "G" "G#" "A" "A#" "B");
+    owl:intersectionOf (
+			[ a owl:Restriction;
+			  owl:onProperty dml:sample_count ;
+			  owl:cardinality 1]
+			[ a owl:Restriction;
+			  owl:onProperty dml:bin ;
+			  owl:cardinality 12] ) .
+
+dml:bin a owl:ObjectProperty ;
+	rdfs:range dml:Bin .
+	
+dml:Bin a owl:Class;
+		owl:intersectionOf (
+			[ a owl:Restriction;
+			  owl:onProperty dml:bin_number ;
+			  owl:cardinality 1]
+			[ a owl:Restriction;
+			  owl:onProperty dml:bin_value ;
+			  owl:cardinality 1]
+			[ a owl:Restriction;
+			  owl:onProperty dml:bin_name ;
+			  owl:minCardinality 0]
+			   ) .
+
+dml:bin_number a owl:DatatypeProperty ;
+	rdfs:range xsd:integer .
+
+dml:bin_value a owl:DatatypeProperty .
+
+dml:bin_name a owl:DatatypeProperty ;
+	rdfs:range xsd:string .
+
+dml:sample_count a owl:DatatypeProperty ;
+	rdfs:range xsd:integer .
+
+# A Key Histogram is defined as:
+dml:KeyHistogram a vamp:DenseOutput ;
+    vamp:identifier       "keyhistogram" ;
+    dc:title              "Key Histogram" ;
+    dc:description        "Histogram of estimated key (from C major = 1 to B major = 12 and C minor = 13 to B minor = 24)."  ;
+    vamp:fixed_bin_count  "true" ;
+    vamp:unit             "" ;
+    vamp:bin_count        24 ;
+    vamp:bin_names        ( "Cmaj" "C#maj" "Dmaj" "D#maj" "Emaj" "Fmaj" "F#maj" "Gmaj" "G#maj" "Amaj" "A#maj" "Bmaj" "Cmin" "C#min" "Dmin" "D#min" "Emin" "Fmin" "F#min" "Gmin" "G#min" "Amin" "A#min" "Bmin");
+    dml:sample_count [ a xsd:integer] ;
+    owl:equivalentClass [ a owl:Restriction ;
+    					  owl:onProperty dml:bin ;
+    					  owl:cardinality 24] .
+
+
+
+# A CollectionLevelTuningFrequencyStatistics is a CollectionLevelAnalysis,
+# it requires at least one input, and these inputs
+# will all be outputs from the silvet transcription plugin.
+dml:CollectionLevelTuningFrequencyStatistics rdfs:subClassOf dml:CollectionLevelAnalysis ;
+    owl:equivalentClass [ a owl:Restriction ;
+    					  owl:onProperty dml:collectionLevelTuningFrequencyStatisticsInput ;
+    					  owl:minCardinality 1] ;
+    owl:equivalentClass [ a owl:Restriction ;
+    					  owl:onProperty dml:collectionLevelTuningFrequencyStatisticsOutput ;
+    					  owl:cardinality 1] .
+
+dml:collectionLevelTuningFrequencyStatisticsInput rdfs:subPropertyOf dml:input ;
+	rdfs:range silvetplugbase:silvet_output_notes .
+
+dml:collectionLevelTuningFrequencyStatisticsOutput rdfs:subPropertyOf dml:output ;
+	rdfs:range dml:TuningFrequencyStatistics .
+
+# TuningFrequencyStatistics is defined as:
+dml:TuningFrequencyStatistics a vamp:DenseOutput ;
+    vamp:identifier       "tuningfrequencystatistics" ;
+    dc:title              "Tuning Frequency Statistics" ;
+    dc:description        "Statistics of Estimated Tuning Frequency including mean, standard deviation and histogram" ;
+    owl:intersectionOf (
+			[ a owl:Restriction;
+			  owl:onProperty dml:mean ;
+			  owl:cardinality 1]
+			[ a owl:Restriction;
+			  owl:onProperty dml:std_dev ;
+			  owl:cardinality 1] 
+                        [ a owl:Restriction;
+			  owl:onProperty dml:bin ;
+			  owl:cardinality 100]) .
+
+dml:mean a owl:DatatypeProperty ;
+	rdfs:range xsd:float .
+
+dml:std_dev a owl:DatatypeProperty ;
+	rdfs:range xsd:float .
+	
+# A CollectionLevelSemitone is a CollectionLevelAnalysis,
+# it requires at least one input, and these inputs
+# will all be outputs from the http://vamp-plugins.org/rdf/plugins/silvet#silvet plugin.
+dml:CollectionLevelSemitone rdfs:subClassOf dml:CollectionLevelAnalysis ;
+    owl:intersectionOf (
+    	[ a owl:Restriction ;
+			owl:onProperty dml:collectionLevelSemitoneInput ;
+			owl:minCardinality 1]
+		[ a owl:Restriction ;
+			owl:onProperty dml:collectionLevelSemitoneOutput ;
+			owl:cardinality 1] ) .
+    					  
+dml:collectionLevelSemitoneInput rdfs:subPropertyOf dml:input ;
+	rdfs:range silvetplugbase:silvet_output_notes .
+
+dml:collectionLevelSemitoneOutput rdfs:subPropertyOf dml:output ;
+	rdfs:range dml:SemitoneHistogram .
+
+# A Semitone Histogram is defined as:
+dml:SemitoneHistogram a vamp:DenseOutput ;
+    vamp:identifier       "semitonehistogram" ;
+    dc:title              "Semitone Histogram" ;
+    dc:description        "Histogram of estimated semitones"  ;
+    vamp:fixed_bin_count  "false" ;
+    vamp:unit             "" ;
+    owl:intersectionOf (
+			[ a owl:Restriction;
+			  owl:onProperty dml:sample_count ;
+			  owl:cardinality 1]
+			[ a owl:Restriction;
+			  owl:onProperty dml:bin ;
+			  owl:minCardinality 1] ) .
+
+# A CollectionLevelTonicNormSemitone is a CollectionLevelAnalysis,
+# it requires at least one input, and these inputs
+# will all be pairs of outputs from the http://vamp-plugins.org/rdf/plugins/silvet#silvet
+# and qmplugbase:qm-keydetector_output_tonic plugins.
+dml:CollectionLevelTonicNormSemitone rdfs:subClassOf dml:CollectionLevelAnalysis ;
+    owl:intersectionOf (
+    	[ a owl:Restriction ;
+			owl:onProperty dml:collectionLevelTonicNormSemitoneInput ;
+			owl:minCardinality 1]
+		[ a owl:Restriction ;
+			owl:onProperty dml:collectionLevelTonicNormSemitoneOutput ;
+			owl:cardinality 1] ) .
+
+dml:collectionLevelTonicNormSemitoneInput rdfs:subPropertyOf dml:input ;
+	rdfs:range dml:InputSet .
+
+dml:InputSet a owl:Class;
+		owl:intersectionOf (
+			[ a owl:Restriction;
+			  owl:onProperty dml:silvetInputSetItem ;
+			  owl:cardinality 1]
+			[ a owl:Restriction;
+			  owl:onProperty dml:tonicInputSetItem ;
+			  owl:cardinality 1] ) .
+
+dml:silvetInputSetItem rdfs:range silvetplugbase:silvet_output_notes .
+
+dml:tonicInputSetItem rdfs:range qmplugbase:qm-keydetector_output_tonic .
+
+dml:collectionLevelTonicNormSemitoneOutput rdfs:subPropertyOf dml:output ;
+	rdfs:range dml:SemitoneHistogram .
diff -r 000000000000 -r e34cf1b6fe09 pyspark/sonic-annotator-notimeside/sonic_annotator_vamp.py
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/pyspark/sonic-annotator-notimeside/sonic_annotator_vamp.py	Sat Feb 20 18:14:24 2016 +0100
@@ -0,0 +1,121 @@
+# Part of DML (Digital Music Laboratory)
+#
+# This program is free software; you can redistribute it and/or
+# modify it under the terms of the GNU General Public License
+# as published by the Free Software Foundation; either version 2
+# of the License, or (at your option) any later version.
+# 
+# This program is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+# GNU General Public License for more details.
+# 
+# You should have received a copy of the GNU General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA  02110-1301  USA
+
+#!/usr/bin/python
+# -*- coding: utf-8 -*-
+"""
+Created on Fri Oct 11 13:22:37 2013
+
+@author: thomas
+"""
+
+from __future__ import division
+
+import sys
+import shutil
+import os
+import errno
+import subprocess
+import time 
+import random
+import hashlib
+
+# uses a separate console process to achieve the file conversion
+def vamp_host_process(argslist):
+    #"""Call sonic annotator"""
+
+    vamp_host = 'sonic-annotator'
+    command = [vamp_host]
+    command.extend(argslist)
+
+    # which sa version?
+    #p = subprocess.Popen([vamp_host, '-v'], stdout=subprocess.PIPE, stderr=subprocess.STDOUT)
+    #print(p.stdout.read())
+
+
+    #stdout = subprocess.check_output(command, stderr=subprocess.STDOUT)
+    time.sleep(random.random()*1.0)
+    p = subprocess.Popen(command, stdout=subprocess.PIPE, stderr=subprocess.STDOUT)
+    text = p.stdout.read()
+    retcode = p.wait()
+    if (retcode==0):
+        print "Finished."
+        return 1
+    else:
+        print "Error " + text
+        return 0
+    
+    #time.sleep(random.random()*1.0)
+    #print command
+    #subprocess.call(command,shell=True)
+    return 1
+
+
+# processes the given file using a vamp plugin and sonic annotator
+# @param string wav_file file to be processed
+def transform(wav_file = 'sweep.mp3',
+              transform_file = 'bbc_speechmusic.n3'):
+
+    # get transform hash
+    BLOCKSIZE = 65536
+    hasher = hashlib.sha1()
+    with open(transform_file, 'rb') as afile:
+        buf = afile.read(BLOCKSIZE)
+        while len(buf) > 0:
+            hasher.update(buf)
+            buf = afile.read(BLOCKSIZE)
+    tpath = os.path.split(transform_file)
+    
+    # prepare output directory:
+    # get audio file subpath
+    # create directory _Features for output if doesnt exist
+    spath = os.path.split(wav_file)
+    hash = str(hasher.hexdigest())
+    featpath = spath[0] + '/_Analysis/' + tpath[1] + "_" + hash[:5]
+    
+    #if not os.path.exists(featpath):
+    #    os.makedirs(featpath)
+    print 'Creating directory' + featpath
+    try:
+        os.makedirs(featpath)
+    except OSError as exception:
+        if exception.errno!= errno.EEXIST:
+            raise   
+    
+    # copy transform file into directory
+    shutil.copy(transform_file, featpath + '/' +  tpath[1][:-3] + '_' + hash[:5] + '.n3')
+
+    #./sonic-annotator -t silvet_settings.n3 input.wav -w csv
+    # prepare arguments
+    args = ['-t', transform_file, wav_file, '-w', 'csv', '-w', 'rdf',
+            '--rdf-basedir',featpath,'--csv-basedir',featpath, '--rdf-many-files', '--rdf-append']
+    #args = ['-t', transform_file, wav_file, '-w', 'csv', '--csv-force','--csv-basedir',featpath]
+
+
+    print "Analysing " + wav_file
+    
+    result = vamp_host_process(args)
+    # execute vamp host
+    return [wav_file, result]
+
+
+# entry function only for testing
+if __name__ == "__main__":
+    if len(sys.argv) >= 2:
+        transform(sys.argv[1])
+    else:
+        transform()
+
diff -r 000000000000 -r e34cf1b6fe09 pyspark/sonic-annotator-notimeside/test_sonic_annotator_notimeside.py
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/pyspark/sonic-annotator-notimeside/test_sonic_annotator_notimeside.py	Sat Feb 20 18:14:24 2016 +0100
@@ -0,0 +1,76 @@
+# Part of DML (Digital Music Laboratory)
+#
+# This program is free software; you can redistribute it and/or
+# modify it under the terms of the GNU General Public License
+# as published by the Free Software Foundation; either version 2
+# of the License, or (at your option) any later version.
+# 
+# This program is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+# GNU General Public License for more details.
+# 
+# You should have received a copy of the GNU General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA  02110-1301  USA
+
+#!/usr/local/spark-1.0.0-bin-hadoop2/bin/spark-submit
+# -*- coding: utf-8 -*-
+__author__="wolffd"
+__date__ ="$11-Jul-2014 15:31:01$"
+
+from pyspark import SparkConf, SparkContext
+import sys
+import os
+from sonic_annotator_vamp import *
+
+# this is the main routine to be submmitted as a spark job
+#
+#
+# Running python applications through ./bin/pyspark is deprecated as of Spark 1.0.
+# Use ./bin/spark-submit <python file> --py-files sonic_annotator_vamp.py
+# you can also provide a zip of all necessary python files
+#
+# @param string audiopath root of the folder structure to be traversed
+# @param string transform_file path to the .n3 turtle file describing the transform
+#def main(audiopath = '/home/wolffd/Documents/python/dml/TimeSide/tests/samples/',
+#         transform_file = '/home/wolffd/Documents/python/dml/pyspark/sonic-annotator-notimeside/silvet_settings.n3',
+#         masterip = '10.2.165.101'):
+def main(audiopath = '/CHARM-Collection',
+         transform_file = 'bbc_speechmusic.n3',
+         masterip = '0.0.0.0'):
+    print "PySpark Telemeta and Vamp Test"
+
+    # configure spark, cave: local profile uses just 1 core
+    conf = (SparkConf()
+            #.setMaster("local")
+            .setMaster("spark://" + masterip + ":7077")
+            .setAppName("Sonic Annotating")
+            .set("spark.executor.memory", "40g")
+            .set("spark.cores.max", "35"));
+    sc = SparkContext(conf = conf)
+    
+    # here traverse the file structure
+    data = []
+    for (dirpath, dirnames, filenames) in os.walk(audiopath):
+        for file in filenames:
+            if file.endswith(".wav") or file.endswith(".mp3") or file.endswith(".flac"):
+                data.append(os.path.join(dirpath, file))
+    njobs = len(data)
+    donejobs = sc.accumulator(0)
+    print "Total: " + str(njobs) + " files"
+
+    # define distributed dataset
+    distData = sc.parallelize(data)
+    
+    # define map 
+    m1 = distData.map(lambda x: transform(wav_file=x,transform_file=transform_file))
+
+    # reduce (just do the maps ;) )
+    result = m1.collect()
+
+if __name__ == "__main__":
+    if len(sys.argv) >= 3:
+        main(sys.argv[1],sys.argv[2])
+    else:
+        main()
diff -r 000000000000 -r e34cf1b6fe09 pyspark/test_timeside_vamp_spark.py
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/pyspark/test_timeside_vamp_spark.py	Sat Feb 20 18:14:24 2016 +0100
@@ -0,0 +1,59 @@
+# Part of DML (Digital Music Laboratory)
+#
+# This program is free software; you can redistribute it and/or
+# modify it under the terms of the GNU General Public License
+# as published by the Free Software Foundation; either version 2
+# of the License, or (at your option) any later version.
+# 
+# This program is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+# GNU General Public License for more details.
+# 
+# You should have received a copy of the GNU General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA  02110-1301  USA
+
+#!/usr/local/spark-1.0.0-bin-hadoop2/bin/spark-submit
+# -*- coding: utf-8 -*-
+__author__="wolffd"
+__date__ ="$11-Jul-2014 15:31:01$"
+
+from pyspark import SparkConf, SparkContext
+# @todo: timeside has to be packed for multi-pc usage
+from timeside_vamp import *
+from os import walk
+
+# Running python applications through ./bin/pyspark is deprecated as of Spark 1.0.
+# Use ./bin/spark-submit <python file>
+
+
+def main():
+    print "PySpark Telemeta and Vamp Test"
+    conf = (SparkConf()
+            .setMaster("local")
+            .setAppName("My app")
+            .set("spark.executor.memory", "1g"))
+    sc = SparkContext(conf = conf)
+    
+    # here come the wav file names
+    
+    mypath = '../../TimeSide/tests/samples/'
+    data = []
+    for (dirpath, dirnames, filenames) in walk(mypath):
+        for file in filenames:
+            if file.endswith(".wav"):
+                data.append(os.path.join(dirpath, file))
+    
+    # define distributed dataset
+    distData = sc.parallelize(data)
+    
+    # define map 
+    m1 = distData.map(lambda x: transform(wav_file=x))
+   
+    #process 2
+    m1.take(2)
+
+if __name__ == "__main__":
+    main()
+    
\ No newline at end of file
diff -r 000000000000 -r e34cf1b6fe09 pyspark/test_timeside_vamp_spark_charm.py
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/pyspark/test_timeside_vamp_spark_charm.py	Sat Feb 20 18:14:24 2016 +0100
@@ -0,0 +1,101 @@
+# Part of DML (Digital Music Laboratory)
+#
+# This program is free software; you can redistribute it and/or
+# modify it under the terms of the GNU General Public License
+# as published by the Free Software Foundation; either version 2
+# of the License, or (at your option) any later version.
+# 
+# This program is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+# GNU General Public License for more details.
+# 
+# You should have received a copy of the GNU General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA  02110-1301  USA
+
+#!/usr/local/spark-1.0.0-bin-hadoop2/bin/spark-submit
+# -*- coding: utf-8 -*-
+__author__="wolffd"
+__date__ ="$11-Jul-2014 15:31:01$"
+
+# How to run this?
+
+# to start hdfs:  /usr/local/hadoop/sbin/start-dfs.sh
+
+# Running python applications through ./bin/pyspark is deprecated as of Spark 1.0.
+# Use ./bin/spark-submit
+# spark-submit test_timeside_vamp_spark_charm.py --py-files vamp_plugin_dml.py,timeside_vamp.py,decode_to_wav.py
+
+#import pydoop.hdfs as hdfs
+from pyspark import SparkConf, SparkContext
+# @todo: timeside has to be packed for multi-pc usage
+import os.path
+import os
+import sys
+from os import walk
+# NOTE: this is only for debugging purposes, we can 
+# now use a regular timeside installation, e.g. installed by 
+sys.path.append(os.getcwd() + '/../TimeSide/')
+
+# mappers
+from timeside_vamp import *
+from decode_to_wav import *
+
+def main():
+    print "PySpark Telemeta and Vamp Test on CHARM"
+    
+    # configure the Spark Setup
+    conf = (SparkConf()
+            .setMaster("spark://0.0.0.0:7077") 
+            #.setMaster("local")
+            .setAppName("CharmVamp")
+            .set("spark.executor.memory", "1g"))
+    sc = SparkContext(conf = conf)
+
+    # SMB Share
+    # mount.cifs //10.2.165.194/mirg /home/wolffd/wansteadshare -o username=dml,password=xxx,domain=ENTERPRISE")
+
+
+    # uses local paths
+    # get list of obkects to process
+    mypath = '/samples/'
+    data = []
+    for (dirpath, dirnames, filenames) in walk(mypath):
+        for file in filenames:
+            if  file.endswith(".wav") or file.endswith(".flac"): 
+                data.append(os.path.join(dirpath, file))
+
+    data = data[0:2]
+    # HDFS
+    # note: for HDFS we need wrappers for VAMP and gstreamer :/
+    # copy to hdfs (put in different file before)
+    #hdfs.mkdir("test")
+    #hdfs.chmod("test","o+rw")
+    ##this copies the test wavs to hdfs
+    #hdfs.put("samples/","test/")
+    # get hdfs paths
+#    data = []
+#    filenames = hdfs.ls("hdfs://0.0.0.0:9000/user/hduser/test/samples")
+#    print filenames 
+#    for file in filenames:
+#        if file[-4:]== ".wav" or file[-4:]==".flac":
+#            data.append(file)
+#    
+    # define distributed dataset
+    # todo: can we do this with the wav data itself?
+    distData = sc.parallelize(data)
+  
+    # define map that decodes to wav
+    m0 = distData.map(lambda x: decode_to_wav(source=x))
+    
+    # define map that applies the vamp plugin
+    m1 = m0.map(lambda x: transform(wav_file=x)).collect()
+    print m1
+    return m1
+    #process 2
+    #m1.take(2)
+
+if __name__ == "__main__":
+    main()
+    
diff -r 000000000000 -r e34cf1b6fe09 pyspark/test_transform_n3s/keyhisto_cla_trans.n3
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/pyspark/test_transform_n3s/keyhisto_cla_trans.n3	Sat Feb 20 18:14:24 2016 +0100
@@ -0,0 +1,60 @@
+@prefix rdfs:    <http://www.w3.org/2000/01/rdf-schema#> .
+@prefix owl:     <http://www.w3.org/2002/07/owl#> .
+@prefix xsd:     <http://www.w3.org/2001/XMLSchema#> .
+@prefix rdf:     <http://www.w3.org/1999/02/22-rdf-syntax-ns#> .
+@prefix dml:     <http://example.org/dml#> .
+@prefix vamp:    <http://purl.org/ontology/vamp/> .
+@prefix dc:      <http://purl.org/dc/elements/1.1/> .
+
+# This file defines an ontology, which also inports the vamp plugin ontology
+<dmlclaOntology.n3> a owl:Ontology;
+    owl:imports <http://vamp-plugins.org/rdf/plugins/qm-vamp-plugins> .
+
+# Our highest level class is a CollectionLevelAnalysis
+dml:Transform a owl:Class .
+dml:CollectionLevelAnalysis rdfs:subClassOf dml:Transform .
+
+dml:type rdfs:subPropertyOf rdf:type .
+
+vamp:Transform rdfs:subClassOf dml:Transform .
+
+# A CollectionLevelKeyTonic is a CollectionLevelAnalysis,
+# it requires at least one input, and these inputs
+# will all be outputs from the qm keydetector vamp plugin.
+# Its output is an Average Tonic Key.
+dml:CollectionLevelKeyTonic rdfs:subClassOf dml:CollectionLevelAnalysis ;
+    dml:input [ a <http://vamp-plugins.org/rdf/plugins/qm-vamp-plugins#qm-keydetector_output_tonic>] ;
+    dml:output [ a dml:KeyTonicHistogram] .
+
+dml:CollectionLevelKey rdfs:subClassOf dml:CollectionLevelAnalysis ;
+    dml:input [ a <http://vamp-plugins.org/rdf/plugins/qm-vamp-plugins#qm-keydetector_output_key>] ;
+    dml:output [ a dml:KeyHistogram] .
+
+# specify domain and range of dml:input here:   
+#dml:input <http://vamp-plugins.org/rdf/plugins/qm-vamp-plugins#qm-keydetector_output_tonic> ;    
+
+# An Average Key is defined as:
+dml:AverageKeyTonic a vamp:SparseOutput ;
+    dml:identifier "average tonic key" ;
+    dc:title "Average Key Tonic" ;
+    dc:description "Average estimated tonic key (from C major = 1 to B major = 12)"  ;
+    vamp:unit "" ;
+    dml:sample_count [ a xsd:integer] ;
+    dml:result [ a owl:DatatypeProperty] .
+
+# A (Tonic) Key Histogram is defined as:
+dml:KeyTonicHistogram a vamp:DenseOutput ;
+    vamp:identifier       "keytonichistogram" ;
+    dc:title              "Key Tonic Histogram" ;
+    dc:description        "Histogram of estimated tonic key (from C major = 1 to B major = 12)."  ;
+    vamp:fixed_bin_count  "true" ;
+    vamp:unit             "" ;
+    vamp:bin_count        12 ;
+    vamp:bin_names        ( "C" "C#" "D" "D#" "E" "F" "F#" "G" "G#" "A" "A#" "B");
+    dml:sample_count [ a xsd:integer] ;
+    dml:result [ a owl:DatatypeProperty] .
+    
+# Some example data
+_:cl_key_tonic dml:type dml:CollectionLevelKeyTonic ;
+    dml:input <file:///mnt/audio/Beethoven/_Analysis/qm_vamp_key_standard_tonic.n3_3cb2d/020A-H01915XXXXXX-0100A0_vamp_qm-vamp-plugins_qm-keydetector_key.n3> ;
+    dml:input <file:///mnt/audio/Beethoven/_Analysis/qm_vamp_key_standard_tonic.n3_3cb2d/020A-H01916XXXXXX-0100A0_vamp_qm-vamp-plugins_qm-keydetector_key.n3> .
diff -r 000000000000 -r e34cf1b6fe09 pyspark/test_transform_n3s/tuningstats_cla_trans.n3
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/pyspark/test_transform_n3s/tuningstats_cla_trans.n3	Sat Feb 20 18:14:24 2016 +0100
@@ -0,0 +1,133 @@
+@prefix rdfs:    <http://www.w3.org/2000/01/rdf-schema#> .
+@prefix owl:     <http://www.w3.org/2002/07/owl#> .
+@prefix xsd:     <http://www.w3.org/2001/XMLSchema#> .
+@prefix rdf:     <http://www.w3.org/1999/02/22-rdf-syntax-ns#> .
+@prefix dml:     <http://dml.org/dml/cla#> .
+@prefix vamp:    <http://purl.org/ontology/vamp/> .
+@prefix dc:      <http://purl.org/dc/elements/1.1/> .
+
+# This file defines an ontology, which also imports the vamp plugin ontology
+<dmlclaOntology.n3> a owl:Ontology;
+    owl:imports <http://vamp-plugins.org/rdf/plugins/qm-vamp-plugins> .
+
+# Our highest level class is a dml:Transform
+dml:Transform a owl:Class .
+dml:CollectionLevelAnalysis rdfs:subClassOf dml:Transform .
+
+dml:type rdfs:subPropertyOf rdf:type .
+
+vamp:Transform rdfs:subClassOf dml:Transform .
+
+dml:input a owl:ObjectProperty .
+dml:output a owl:ObjectProperty .
+
+# A CollectionLevelKeyTonic is a CollectionLevelAnalysis,
+# it requires at least one input, and these inputs
+# will all be outputs from the qm keydetector vamp plugin.
+dml:CollectionLevelKeyTonic rdfs:subClassOf dml:CollectionLevelAnalysis ;
+    owl:equivalentClass [ a owl:restriction ;
+    					  owl:onProperty dml:collectionLevelKeyTonicInput ;
+    					  owl:minCardinality 1] ;
+    owl:equivalentClass [ a owl:restriction ;
+    					  owl:onProperty dml:collectionLevelKeyTonicOutput ;
+    					  owl:cardinality 1] .
+    					  
+dml:collectionLevelKeyTonicInput rdfs:subPropertyOf dml:input ;
+	rdfs:range <http://vamp-plugins.org/rdf/plugins/qm-vamp-plugins#qm-keydetector_output_tonic> .
+
+dml:collectionLevelKeyTonicOutput rdfs:subPropertyOf dml:output ;
+	rdfs:range dml:KeyTonicHistogram .
+
+# A (Tonic) Key Histogram is defined as:
+dml:KeyTonicHistogram a vamp:DenseOutput ;
+    vamp:identifier       "keytonichistogram" ;
+    dc:title              "Key Tonic Histogram" ;
+    dc:description        "Histogram of estimated tonic key (from C major = 1 to B major = 12)."  ;
+    vamp:fixed_bin_count  "true" ;
+    vamp:unit             "" ;
+    vamp:bin_count        12 ;
+    vamp:bin_names        ( "C" "C#" "D" "D#" "E" "F" "F#" "G" "G#" "A" "A#" "B");
+    owl:intersectionOf (
+			[ a owl:Restriction;
+			  owl:onProperty dml:sample_count ;
+			  owl:cardinality 1]
+			[ a owl:Restriction;
+			  owl:onProperty dml:bin ;
+			  owl:cardinality 12] ) .
+
+dml:bin a owl:ObjectProperty ;
+	rdfs:range dml:Bin .
+	
+dml:Bin a owl:Class;
+		owl:intersectionOf (
+			[ a owl:Restriction;
+			  owl:onProperty dml:bin_number ;
+			  owl:cardinality 1]
+			[ a owl:Restriction;
+			  owl:onProperty dml:bin_value ;
+			  owl:cardinality 1] ) .
+
+dml:bin_number a owl:DatatypeProperty ;
+	rdfs:range xsd:integer .
+
+dml:bin_value a owl:DatatypeProperty .
+
+dml:sample_count a owl:DatatypeProperty ;
+	rdfs:range xsd:integer .
+
+# A Key Histogram is defined as:
+dml:KeyTonicHistogram a vamp:DenseOutput ;
+    vamp:identifier       "keyhistogram" ;
+    dc:title              "Key Histogram" ;
+    dc:description        "Histogram of estimated key (from C major = 1 to B major = 12 and C minor = 13 to B minor = 24)."  ;
+    vamp:fixed_bin_count  "true" ;
+    vamp:unit             "" ;
+    vamp:bin_count        24 ;
+    vamp:bin_names        ( "Cmaj" "C#maj" "Dmaj" "D#maj" "Emaj" "Fmaj" "F#maj" "Gmaj" "G#maj" "Amaj" "A#maj" "Bmaj" "Cmin" "C#min" "Dmin" "D#min" "Emin" "Fmin" "F#min" "Gmin" "G#min" "Amin" "A#min" "Bmin");
+    dml:sample_count [ a xsd:integer] ;
+    owl:equivalentClass [ a owl:restriction ;
+    					  owl:onProperty dml:bin ;
+    					  owl:cardinality 24] .
+
+
+
+# A CollectionLevelTuningFrequencyStatistics is a CollectionLevelAnalysis,
+# it requires at least one input, and these inputs
+# will all be outputs from the silvet transcription plugin.
+dml:CollectionLevelTuningFrequencyStatistics rdfs:subClassOf dml:CollectionLevelAnalysis ;
+    owl:equivalentClass [ a owl:restriction ;
+    					  owl:onProperty dml:collectionLevelTuningFrequencyStatisticsInput ;
+    					  owl:minCardinality 1] ;
+    owl:equivalentClass [ a owl:restriction ;
+    					  owl:onProperty dml:collectionLevelTuningFrequencyStatisticsOutput ;
+    					  owl:cardinality 1] .
+
+dml:collectionLevelTuningFrequencyStatisticsInput rdfs:subPropertyOf dml:input ;
+	rdfs:range <http://vamp-plugins.org/rdf/plugins/silvet#silvet_output_notes> .
+
+dml:collectionLevelTuningFrequencyStatisticsOutput rdfs:subPropertyOf dml:output ;
+	rdfs:range dml:TuningFrequencyStatistics .
+
+# TuningFrequencyStatistics is defined as:
+dml:TuningFrequencyStatistics a vamp:DenseOutput ;
+    vamp:identifier       "tuningfrequencystatistics" ;
+    dc:title              "Tuning Frequency Statistics" ;
+    dc:description        "Statistics of Estimated Tuning Frequency" ;
+    owl:intersectionOf (
+			[ a owl:Restriction;
+			  owl:onProperty dml:mean ;
+			  owl:cardinality 1]
+			[ a owl:Restriction;
+			  owl:onProperty dml:std_dev ;
+			  owl:cardinality 1] ) .
+
+dml:mean a owl:DatatypeProperty ;
+	rdfs:range xsd:float .
+
+dml:std_dev a owl:DatatypeProperty ;
+	rdfs:range xsd:float .
+
+# Some example data
+_:cl_tuning_statistics dml:type dml:CollectionLevelTuningFrequencyStatistics ;
+    dml:input <file:///mnt/audio/Bruckner/_Analysis/silvet_settings_slow_nonfinetune_allinstruments.n3_1db32/020A-H03614XXXXXX-0104A0_vamp_silvet_silvet_notes.n3> ;
+    dml:input <file:///mnt/audio/Bruckner/_Analysis/silvet_settings_slow_nonfinetune_allinstruments.n3_1db32/020A-H03799XXXXXX-0103A0_vamp_silvet_silvet_notes.n3> .
diff -r 000000000000 -r e34cf1b6fe09 pyspark/test_transform_n3s/tuningstats_cla_trans_win.n3
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/pyspark/test_transform_n3s/tuningstats_cla_trans_win.n3	Sat Feb 20 18:14:24 2016 +0100
@@ -0,0 +1,139 @@
+@prefix rdfs:    <http://www.w3.org/2000/01/rdf-schema#> .
+@prefix owl:     <http://www.w3.org/2002/07/owl#> .
+@prefix xsd:     <http://www.w3.org/2001/XMLSchema#> .
+@prefix rdf:     <http://www.w3.org/1999/02/22-rdf-syntax-ns#> .
+@prefix dml:     <http://dml.org/dml/cla#> .
+@prefix vamp:    <http://purl.org/ontology/vamp/> .
+@prefix dc:      <http://purl.org/dc/elements/1.1/> .
+
+# This file defines an ontology, which also imports the vamp plugin ontology
+<dmlclaOntology.n3> a owl:Ontology;
+    owl:imports <http://vamp-plugins.org/rdf/plugins/qm-vamp-plugins> .
+
+# Our highest level class is a dml:Transform
+dml:Transform a owl:Class .
+dml:CollectionLevelAnalysis rdfs:subClassOf dml:Transform .
+
+dml:type rdfs:subPropertyOf rdf:type .
+
+vamp:Transform rdfs:subClassOf dml:Transform .
+
+dml:input a owl:ObjectProperty .
+dml:output a owl:ObjectProperty .
+
+# A CollectionLevelKeyTonic is a CollectionLevelAnalysis,
+# it requires at least one input, and these inputs
+# will all be outputs from the qm keydetector vamp plugin.
+dml:CollectionLevelKeyTonic rdfs:subClassOf dml:CollectionLevelAnalysis ;
+    owl:equivalentClass [ a owl:restriction ;
+    					  owl:onProperty dml:collectionLevelKeyTonicInput ;
+    					  owl:minCardinality 1] ;
+    owl:equivalentClass [ a owl:restriction ;
+    					  owl:onProperty dml:collectionLevelKeyTonicOutput ;
+    					  owl:cardinality 1] .
+    					  
+dml:collectionLevelKeyTonicInput rdfs:subPropertyOf dml:input ;
+	rdfs:range <http://vamp-plugins.org/rdf/plugins/qm-vamp-plugins#qm-keydetector_output_tonic> .
+
+dml:collectionLevelKeyTonicOutput rdfs:subPropertyOf dml:output ;
+	rdfs:range dml:KeyTonicHistogram .
+
+# A (Tonic) Key Histogram is defined as:
+dml:KeyTonicHistogram a vamp:DenseOutput ;
+    vamp:identifier       "keytonichistogram" ;
+    dc:title              "Key Tonic Histogram" ;
+    dc:description        "Histogram of estimated tonic key (from C major = 1 to B major = 12)."  ;
+    vamp:fixed_bin_count  "true" ;
+    vamp:unit             "" ;
+    vamp:bin_count        12 ;
+    vamp:bin_names        ( "C" "C#" "D" "D#" "E" "F" "F#" "G" "G#" "A" "A#" "B");
+    owl:intersectionOf (
+			[ a owl:Restriction;
+			  owl:onProperty dml:sample_count ;
+			  owl:cardinality 1]
+			[ a owl:Restriction;
+			  owl:onProperty dml:bin ;
+			  owl:cardinality 12] ) .
+
+dml:bin a owl:ObjectProperty ;
+	rdfs:range dml:Bin .
+	
+dml:Bin a owl:Class;
+		owl:intersectionOf (
+			[ a owl:Restriction;
+			  owl:onProperty dml:bin_number ;
+			  owl:cardinality 1]
+			[ a owl:Restriction;
+			  owl:onProperty dml:bin_value ;
+			  owl:cardinality 1] ) .
+
+dml:bin_number a owl:DatatypeProperty ;
+	rdfs:range xsd:integer .
+
+dml:bin_value a owl:DatatypeProperty .
+
+dml:sample_count a owl:DatatypeProperty ;
+	rdfs:range xsd:integer .
+
+# A Key Histogram is defined as:
+dml:KeyTonicHistogram a vamp:DenseOutput ;
+    vamp:identifier       "keyhistogram" ;
+    dc:title              "Key Histogram" ;
+    dc:description        "Histogram of estimated key (from C major = 1 to B major = 12 and C minor = 13 to B minor = 24)."  ;
+    vamp:fixed_bin_count  "true" ;
+    vamp:unit             "" ;
+    vamp:bin_count        24 ;
+    vamp:bin_names        ( "Cmaj" "C#maj" "Dmaj" "D#maj" "Emaj" "Fmaj" "F#maj" "Gmaj" "G#maj" "Amaj" "A#maj" "Bmaj" "Cmin" "C#min" "Dmin" "D#min" "Emin" "Fmin" "F#min" "Gmin" "G#min" "Amin" "A#min" "Bmin");
+    dml:sample_count [ a xsd:integer] ;
+    owl:equivalentClass [ a owl:restriction ;
+                            owl:onProperty dml:bin ;
+                            owl:cardinality 24] .
+
+
+
+# A CollectionLevelTuningFrequencyStatistics is a CollectionLevelAnalysis,
+# it requires at least one input, and these inputs
+# will all be outputs from the silvet transcription plugin.
+dml:CollectionLevelTuningFrequencyStatistics rdfs:subClassOf dml:CollectionLevelAnalysis ;
+    owl:equivalentClass [ a owl:restriction ;
+    					  owl:onProperty dml:collectionLevelTuningFrequencyStatisticsInput ;
+    					  owl:minCardinality 1] ;
+    owl:equivalentClass [ a owl:restriction ;
+    					  owl:onProperty dml:collectionLevelTuningFrequencyStatisticsOutput ;
+    					  owl:cardinality 1] .
+
+dml:collectionLevelTuningFrequencyStatisticsInput rdfs:subPropertyOf dml:input ;
+	rdfs:range <http://vamp-plugins.org/rdf/plugins/silvet#silvet_output_notes> .
+
+dml:collectionLevelTuningFrequencyStatisticsOutput rdfs:subPropertyOf dml:output ;
+	rdfs:range dml:TuningFrequencyStatistics .
+
+# TuningFrequencyStatistics is defined as:
+dml:TuningFrequencyStatistics a vamp:DenseOutput ;
+    vamp:identifier       "tuningfrequencystatistics" ;
+    dc:title              "Tuning Frequency Statistics" ;
+    dc:description        "Statistics of Estimated Tuning Frequency including mean, standard deviation and histogram" ;
+    owl:intersectionOf (
+			[ a owl:Restriction;
+			  owl:onProperty dml:mean ;
+			  owl:cardinality 1]
+			[ a owl:Restriction;
+			  owl:onProperty dml:std_dev ;
+			  owl:cardinality 1] 
+                        [ a owl:Restriction;
+			  owl:onProperty dml:bin ;
+			  owl:cardinality 100]) .
+
+dml:mean a owl:DatatypeProperty ;
+	rdfs:range xsd:float .
+
+dml:std_dev a owl:DatatypeProperty ;
+	rdfs:range xsd:float .
+
+# Some example data
+_:cl_tuning_statistics dml:type dml:CollectionLevelTuningFrequencyStatistics ;
+#    dml:input <file:///mnt/audio/Bruckner/_Analysis/silvet_settings_slow_nonfinetune_allinstruments.n3_1db32/020A-H03614XXXXXX-0104A0_vamp_silvet_silvet_notes.n3> ;
+#    dml:input <file:///mnt/audio/Bruckner/_Analysis/silvet_settings_slow_nonfinetune_allinstruments.n3_1db32/020A-H03799XXXXXX-0103A0_vamp_silvet_silvet_notes.n3> ;
+  dml:input <file:///D:/mirg/Pitch_Analysis/026A-1CL0001773XX-0100A0_vamp_silvet_silvet_notes.csv> ;
+# dml:input <file:///D:/mirg/Pitch_Analysis/026A-1CL0002164XX-0100A0_vamp_silvet_silvet_notes.n3> ;
+    dml:input <file:///D:/mirg/Pitch_Analysis/026A-1CL0001773XX-0100A0_vamp_silvet_silvet_notes.n3> .
\ No newline at end of file
diff -r 000000000000 -r e34cf1b6fe09 pyspark/timeside_vamp.py
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/pyspark/timeside_vamp.py	Sat Feb 20 18:14:24 2016 +0100
@@ -0,0 +1,91 @@
+# Part of DML (Digital Music Laboratory)
+#
+# This program is free software; you can redistribute it and/or
+# modify it under the terms of the GNU General Public License
+# as published by the Free Software Foundation; either version 2
+# of the License, or (at your option) any later version.
+# 
+# This program is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+# GNU General Public License for more details.
+# 
+# You should have received a copy of the GNU General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA  02110-1301  USA
+
+#!/usr/bin/python
+# -*- coding: utf-8 -*-
+"""
+Created on Fri Oct 11 13:22:37 2013
+
+@author: thomas
+"""
+
+from __future__ import division
+
+import matplotlib.pyplot as plt
+import numpy as np
+import sys
+import os
+
+# NOTE: this is only for debugging purposes, we can 
+# now use a regular timeside and sonic annotator installation,
+#sudo ln -s ../../sonic_annotator/sonic-annotator-0.7-linux-amd64/sonic-annotator /usr/sbin/
+#sys.path.append(os.getcwd() + '../../sonic_annotator/sonic-annotator-0.7-linux-amd64/')
+
+import timeside
+from timeside.analyzer.core import AnalyzerResult, AnalyzerResultContainer
+from timeside import __version__
+from vamp_plugin_dml import *
+
+def transform(wav_file = 'sweep.wav'):
+
+
+    # normal
+    d = timeside.decoder.file.FileDecoder(wav_file)
+    
+    # Get available Vamp plugins list
+    from timeside.analyzer.vamp_plugin import VampSimpleHost
+    plugins_list = VampSimpleHostDML.get_plugins_list()
+
+    # Display avalaible plugins
+    print 'index \t soname \t \t identifier \t output '
+    print '------ \t \t ---------- \t ------ '
+    for index, line in zip(xrange(len(plugins_list)),plugins_list):
+        print '%d : %s \t %s \t %s' % (index,line[0],line[1],line[2])
+
+    # Let's choose #7
+    my_plugin = plugins_list[0]#11
+    print my_plugin
+
+    #
+    # Vamp plugin Analyzer
+    #vamp = timeside.analyzer.vamp_plugin.VampSimpleHostDML([my_plugin])
+    vamp = VampSimpleHostDML([my_plugin])
+    #vamp = timeside.analyzer.VampSimpleHostDML()
+    
+    myPipe = (d | vamp ).run()
+
+    # Get the vamp plugin result and plot it
+    for key in vamp.results.keys():
+        print vamp.results[key].data
+        res_vamp = vamp.results[key]
+        
+        
+    # test storage as HDF5
+    #vamp.results.to_hdf5(wav_file + '.h5')
+    #res_hdf5 = vamp.results.from_hdf5(wav_file + '.h5')
+    #print '%15s' % 'from hdf5:',
+    #print res_hdf5
+        
+    return res_vamp
+
+    # res_vamp = vamp.results['vamp_simple_host.percussiononsets.detectionfunction']
+
+if __name__ == "__main__":
+    if len(sys.argv) >= 2:
+        transform(sys.argv[1])
+    else:
+        transform()
+        
\ No newline at end of file
diff -r 000000000000 -r e34cf1b6fe09 pyspark/transforms/semitoneHistogram.py
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/pyspark/transforms/semitoneHistogram.py	Sat Feb 20 18:14:24 2016 +0100
@@ -0,0 +1,148 @@
+# Part of DML (Digital Music Laboratory)
+#
+# This program is free software; you can redistribute it and/or
+# modify it under the terms of the GNU General Public License
+# as published by the Free Software Foundation; either version 2
+# of the License, or (at your option) any later version.
+# 
+# This program is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+# GNU General Public License for more details.
+# 
+# You should have received a copy of the GNU General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA  02110-1301  USA
+
+# -*- coding: utf-8 -*-
+__author__="hargreavess"
+
+from rdflib import Namespace, BNode, RDF, Literal
+from n3Parser import get_rdf_graph_from_n3
+from csvParser import get_dict_from_csv
+
+dml_ns = Namespace("http://dml.org/dml/cla#")
+semitone_labels = ("C", "C#", "D", "D#", "E", "F", "F#", "G", "G#", "A", "A#", "B")
+semitone_label_codes = dict()
+for octave in range(0, 11):
+
+    semitone_idx = 1
+
+    for semitone_label in semitone_labels:
+
+        semitone_label_with_octave = semitone_label + str(octave)
+        semitone_label_codes[semitone_label_with_octave] = semitone_idx
+        semitone_idx += 1
+
+
+# normalisation per clip ?
+perfilenorm = 1
+
+# Add triples representing a 'pitch histogram' result to
+# an RDF graph
+def add_semitone_histogram_to_graph(semitone_histogram, output_rdf_graph, transform, sample_count, input_f_files):
+    
+    output_bnode = BNode()
+    output_rdf_graph.add((transform, dml_ns.output, output_bnode))
+    for input_f_file in input_f_files:
+        output_rdf_graph.add((transform, dml_ns.input, input_f_file))
+    output_rdf_graph.add((output_bnode, RDF.type, dml_ns.SemitoneHistogram))
+    output_rdf_graph.add((output_bnode, dml_ns.sample_count, Literal(sample_count)))
+
+    for semitone in semitone_histogram:
+
+        bin_bnode = BNode()
+        output_rdf_graph.add((output_bnode, dml_ns.bin, bin_bnode))
+        output_rdf_graph.add((bin_bnode, dml_ns.bin_number, Literal(semitone)))
+        output_rdf_graph.add((bin_bnode, dml_ns.bin_value, Literal(semitone_histogram.get(semitone))))
+        output_rdf_graph.add((bin_bnode, dml_ns.bin_name, Literal(semitone_labels[semitone - 1])))
+
+    return output_rdf_graph
+
+# Parse an input_f_file n3 file, and generate
+# a semitone histogram
+def find_semitone_histogram(input_f_file, perfilenorm):
+    
+    piece_semitone_hist = dict()
+
+    for x in range(1, 13):
+
+        piece_semitone_hist[x] = 0
+
+    piece_duration = 0
+
+    if input_f_file.endswith('.csv'):
+
+        csv_dict = get_dict_from_csv(input_f_file, columtype = ['time','duration','pitch','velocity','label'])
+        
+        for row in csv_dict:
+            
+            duration = float(row['duration'])
+            piece_semitone_hist[semitone_label_codes[row['label']]] += duration
+            piece_duration += duration
+
+    else:
+
+        f_file_graph = get_rdf_graph_from_n3(input_f_file)
+    
+        qres = f_file_graph.query(
+        """prefix dml:     <http://dml.org/dml/cla#>
+           prefix tl:      <http://purl.org/NET/c4dm/timeline.owl#>
+           prefix af:      <http://purl.org/ontology/af/>
+            SELECT ?event ?pitch ?duration
+            WHERE {
+                ?event a af:Note .
+                ?event event:time ?event_time .
+                ?event_time tl:duration ?duration .
+                ?event rdfs:label ?pitch .
+            }""")
+
+        for row in qres:
+            
+            # parse xsd:duration type
+            tl_duration_str_len = len(row.duration)
+            tl_duration = float(row.duration[2:tl_duration_str_len-1])
+    
+            piece_semitone_hist[semitone_label_codes[row.pitch.__str__()]] += tl_duration
+            piece_duration += tl_duration
+
+    # normalise if necessary
+    if perfilenorm:
+
+        for x in range(1, 13):
+
+            piece_semitone_hist[x] /= piece_duration
+
+    return piece_semitone_hist
+
+# Parse the input_f_files n3 files, and generate
+# a collection-level semitone histogram
+def find_cla_semitone_histogram(input_f_files):
+
+    num_f_files = len(input_f_files)
+    semitone_hist = dict()
+    
+    for x in range(1, 13):
+
+        semitone_hist[x] = 0
+
+    for input_f_file in input_f_files:
+
+        piece_semitone_hist = find_semitone_histogram(input_f_file, perfilenorm)
+
+        for x in range(1, 13):
+
+            semitone_hist[x] += piece_semitone_hist[x]
+
+    # normalise the collection histogram by duration
+    hist_total = 0
+
+    for semitone_bin in semitone_hist:
+
+        hist_total += semitone_hist[semitone_bin]
+        
+    for semitone_bin in semitone_hist:
+
+        semitone_hist[semitone_bin] /= hist_total
+    
+    return (semitone_hist, num_f_files)
diff -r 000000000000 -r e34cf1b6fe09 pyspark/transforms/tonicHistogram.py
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/pyspark/transforms/tonicHistogram.py	Sat Feb 20 18:14:24 2016 +0100
@@ -0,0 +1,156 @@
+# Part of DML (Digital Music Laboratory)
+#
+# This program is free software; you can redistribute it and/or
+# modify it under the terms of the GNU General Public License
+# as published by the Free Software Foundation; either version 2
+# of the License, or (at your option) any later version.
+# 
+# This program is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+# GNU General Public License for more details.
+# 
+# You should have received a copy of the GNU General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA  02110-1301  USA
+
+# -*- coding: utf-8 -*-
+__author__="hargreavess"
+
+from rdflib import Graph, Namespace, BNode, RDF, Literal
+from n3Parser import get_rdf_graph_from_n3
+from csvParser import get_dict_from_csv, get_array_from_csv
+
+dml_ns = Namespace("http://dml.org/dml/cla#")
+
+# Add triples representing a 'tonic histogram' result to
+# an RDF graph
+def add_tonic_histogram_to_graph(tonic_histogram, output_rdf_graph, transform, sample_count, input_f_files):
+
+    output_bnode = BNode()
+    output_rdf_graph.add((transform, dml_ns.output, output_bnode))
+    for input_f_file in input_f_files:
+        output_rdf_graph.add((transform, dml_ns.input, input_f_file))
+    output_rdf_graph.add((output_bnode, RDF.type, dml_ns.TonicHistogram))
+    output_rdf_graph.add((output_bnode, dml_ns.sample_count, Literal(sample_count)))
+
+    for tonic in tonic_histogram:
+
+        bin_bnode = BNode()
+        output_rdf_graph.add((output_bnode, dml_ns.bin, bin_bnode))
+        output_rdf_graph.add((bin_bnode, dml_ns.bin_number, Literal(tonic)))
+        output_rdf_graph.add((bin_bnode, dml_ns.bin_value, Literal(tonic_histogram.get(tonic))))
+
+    return output_rdf_graph
+
+# Parse the input_f_files n3 files, and generate
+# a tonic histogram
+def find_cla_tonic_histogram(input_f_files):
+
+    num_f_files = len(input_f_files)
+    tonic_hist = dict()
+
+    for x in range(1,13):
+
+        tonic_hist[x] = 0
+
+    for input_f_file in input_f_files:
+
+#        tonic = find_last_key_in_piece(input_f_file)
+        tonic = find_most_common_key_in_piece(input_f_file)
+        tonic_hist[tonic] = tonic_hist.get(tonic) + 1
+
+    return (tonic_hist, num_f_files)
+
+def find_most_common_key_in_piece(input_f_file):
+    
+    tonic_hist = find_tonic_histogram(input_f_file)
+    duration_of_tonic = max(tonic_hist.values())
+    result = -1
+
+    for tonic in tonic_hist:
+        
+        if tonic_hist[tonic] == duration_of_tonic:
+            result = tonic
+    
+    return result
+
+# Parse the input_f_files n3 file, and generate
+# a tonic histogram
+def find_tonic_histogram(input_f_file):
+
+    tonic_hist = dict()
+
+    for x in range(1,13):
+
+        tonic_hist[x] = 0
+
+    if input_f_file.endswith('.csv'):
+
+        # ['time','keynr','label']
+        csv_array = get_array_from_csv(input_f_file)
+
+        for idx in range(1, len(csv_array)):
+
+            tonic_duration = csv_array[idx][0] - csv_array[idx - 1][0]
+            tonic = int(csv_array[idx - 1][1])
+            tonic_hist[tonic] = tonic_hist.get(tonic) + tonic_duration
+    
+    else:
+
+        # TODO - n3 version of tonic histogram
+        # for now use last key in piece
+        tonic = find_last_key_in_piece(input_f_file)
+        tonic_hist[tonic] = tonic_hist.get(tonic) + 1
+
+    return (tonic_hist)
+
+# Determine the last (temporally) key in the
+# input_f_file n3 file
+def find_last_key_in_piece(input_f_file):
+
+    max_time = 0
+    last_key = 0
+
+    if input_f_file.endswith('.csv'):
+
+        csv_dict = get_dict_from_csv(input_f_file, columtype = ['time','keynr','label'])
+
+        for row in csv_dict:
+            
+            tl_time = float(row['time'])
+            
+            if tl_time > max_time:
+                
+                max_time = tl_time
+                last_key = row['keynr']
+    
+    
+    else:
+
+        key_feature_graph = get_rdf_graph_from_n3(input_f_file)
+    
+        qres = key_feature_graph.query(
+            """prefix dml:     <http://dml.org/dml/cla#>
+               prefix event: <http://purl.org/NET/c4dm/event.owl#>
+               prefix tl: <http://purl.org/NET/c4dm/timeline.owl#>
+               prefix af: <http://purl.org/ontology/af/>
+                SELECT ?event ?key ?tl_time
+                WHERE {
+                    ?event event:time ?event_time .
+                    ?event_time tl:at ?tl_time .
+                    ?event af:feature ?key .
+                }""")
+    
+        for row in qres:
+    
+            tl_time_str_len = len(row.tl_time)
+            tl_time = float(row.tl_time[2:tl_time_str_len-1])
+    
+            if tl_time > max_time:
+    
+                max_time = tl_time
+                last_key = row.key
+
+
+    return int(last_key)
diff -r 000000000000 -r e34cf1b6fe09 pyspark/transforms/tonicNormSemitoneHistogram.py
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/pyspark/transforms/tonicNormSemitoneHistogram.py	Sat Feb 20 18:14:24 2016 +0100
@@ -0,0 +1,126 @@
+# Part of DML (Digital Music Laboratory)
+#
+# This program is free software; you can redistribute it and/or
+# modify it under the terms of the GNU General Public License
+# as published by the Free Software Foundation; either version 2
+# of the License, or (at your option) any later version.
+# 
+# This program is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+# GNU General Public License for more details.
+# 
+# You should have received a copy of the GNU General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA  02110-1301  USA
+
+# -*- coding: utf-8 -*-
+__author__="hargreavess"
+
+import rdflib
+from rdflib import Namespace, BNode, RDF, Literal
+from n3Parser import get_rdf_graph_from_n3
+from semitoneHistogram import find_semitone_histogram, semitone_labels
+from tonicHistogram import find_last_key_in_piece, find_most_common_key_in_piece
+
+dml_ns = Namespace("http://dml.org/dml/cla#")
+perfilenorm = 1
+
+# normalisation per clip ?
+perfilenorm = 1
+
+# Add triples representing a "pitch histogram" result to
+# an RDF graph
+def add_tonic_norm_semitone_histogram_to_graph(semitone_histogram, output_rdf_graph, transform, sample_count, input_f_files, input_rdf_graph):
+    
+    query = rdflib.plugins.sparql.prepareQuery(
+            """SELECT ?silvet_input ?tonic_input
+                WHERE {
+                    ?tonicNormSemitoneInput dml:silvetInputSetItem ?silvet_input .
+                    ?tonicNormSemitoneInput dml:tonicInputSetItem ?tonic_input .
+                }""", initNs = { "dml": dml_ns })
+
+    output_bnode = BNode()
+    output_rdf_graph.add((transform, dml_ns.output, output_bnode))
+    
+    for transform_input in input_f_files:
+
+        output_rdf_graph.add((transform, dml_ns.input, transform_input))
+        qres = input_rdf_graph.query(query, initBindings={'tonicNormSemitoneInput': transform_input})
+
+        for row in qres:
+
+            output_rdf_graph.add((transform_input, dml_ns.silvetInputSetItem, row.silvet_input))
+            output_rdf_graph.add((transform_input, dml_ns.tonicInputSetItem, row.tonic_input))
+
+    output_rdf_graph.add((output_bnode, RDF.type, dml_ns.SemitoneHistogram))
+    output_rdf_graph.add((output_bnode, dml_ns.sample_count, Literal(sample_count)))
+
+    for semitone in semitone_histogram:
+
+        bin_bnode = BNode()
+        output_rdf_graph.add((output_bnode, dml_ns.bin, bin_bnode))
+        output_rdf_graph.add((bin_bnode, dml_ns.bin_number, Literal(semitone)))
+        output_rdf_graph.add((bin_bnode, dml_ns.bin_value, Literal(semitone_histogram.get(semitone))))
+        output_rdf_graph.add((bin_bnode, dml_ns.bin_name, Literal(semitone_labels[semitone - 1])))
+
+    return output_rdf_graph
+
+# Parse the transform_inputs (sets of n3 files), and generate
+# a tonic-normalised semitone histogram
+def find_cla_tonic_norm_semitone_histogram(transform_inputs, input_rdf_graph):
+
+    sample_count = len(transform_inputs)
+    semitone_hist = dict()
+
+    for x in range(1, 13):
+
+        semitone_hist[x] = 0
+    
+    query = rdflib.plugins.sparql.prepareQuery(
+    """SELECT ?silvet_input ?tonic_input
+        WHERE {
+            ?tonicNormSemitoneInput dml:silvetInputSetItem ?silvet_input .
+            ?tonicNormSemitoneInput dml:tonicInputSetItem ?tonic_input .
+        }""", initNs = { "dml": dml_ns })
+
+    for transform_input in transform_inputs:
+
+        qres = input_rdf_graph.query(query, initBindings={'tonicNormSemitoneInput': transform_input})
+
+        piece_semitone_hist = []
+
+        for row in qres:
+
+            piece_semitone_hist = find_semitone_histogram(row.silvet_input, perfilenorm)
+#            piece_tonic = find_last_key_in_piece(row.tonic_input)
+            piece_tonic = find_most_common_key_in_piece(row.tonic_input)
+            piece_semitone_hist = normalise_semitone_hist_by_tonic(piece_semitone_hist, piece_tonic)
+
+        for x in range(1, 13):
+
+            semitone_hist[x] += piece_semitone_hist[x]
+
+    # normalise the collection histogram by duration
+    hist_total = 0
+
+    for semitone_bin in semitone_hist:
+
+        hist_total += semitone_hist[semitone_bin]
+        
+    for semitone_bin in semitone_hist:
+
+        semitone_hist[semitone_bin] /= hist_total
+    
+    return (semitone_hist, sample_count)
+
+def normalise_semitone_hist_by_tonic(piece_semitone_hist, piece_tonic):
+        
+    tonic_norm_semitone_hist = dict()
+    
+    for semitone_bin in piece_semitone_hist:
+
+        shifted_bin = ((semitone_bin - piece_tonic) % 12) + 1
+        tonic_norm_semitone_hist[shifted_bin] = piece_semitone_hist[semitone_bin]
+        
+    return tonic_norm_semitone_hist
diff -r 000000000000 -r e34cf1b6fe09 pyspark/transforms/tuningFrequencyStatistics.py
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/pyspark/transforms/tuningFrequencyStatistics.py	Sat Feb 20 18:14:24 2016 +0100
@@ -0,0 +1,280 @@
+# Part of DML (Digital Music Laboratory)
+#
+# This program is free software; you can redistribute it and/or
+# modify it under the terms of the GNU General Public License
+# as published by the Free Software Foundation; either version 2
+# of the License, or (at your option) any later version.
+# 
+# This program is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+# GNU General Public License for more details.
+# 
+# You should have received a copy of the GNU General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA  02110-1301  USA
+
+# -*- coding: utf-8 -*-
+__author__="Daniel Wolff, hargreaves"
+
+# this script derives standard statistics for tuning frequency, 
+# in particular:
+# average
+# standard deviation
+
+from rdflib import Graph, Namespace, BNode, RDF, Literal
+import codecs
+import warnings
+import numpy
+import csv
+from n3Parser import get_rdf_graph_from_n3, uri2path
+# from csvParser import get_dict_from_csv, get_array_from_csv
+
+# statistics per clip ?
+perfilestats = 1
+
+# dml namespace
+dml_ns = Namespace("http://dml.org/dml/cla#")
+
+# Add triples representing a 'key histogram' result to
+# an RDF graph
+def add_tf_statistics_to_graph(statistics, output_rdf_graph, transform, sample_count, input_f_files):
+    
+    # add base
+    output_bnode = BNode()
+    output_rdf_graph.add((transform, dml_ns.output, output_bnode))
+    for input_f_file in input_f_files:
+        output_rdf_graph.add((transform, dml_ns.input, input_f_file))
+    output_rdf_graph.add((output_bnode, RDF.type, dml_ns.TuningFrequencyStatistics))
+    output_rdf_graph.add((output_bnode, dml_ns.sample_count, Literal(sample_count)))
+
+    # add mean and std
+    output_rdf_graph.add((output_bnode, dml_ns.mean, Literal(statistics["mean"])))
+    output_rdf_graph.add((output_bnode, dml_ns.std_dev, Literal(statistics["std-dev"])))
+    
+    # add histogram
+    for i in range(0,len(statistics["histogram"]["count"])):
+
+        bin_bnode = BNode()
+        output_rdf_graph.add((output_bnode, dml_ns.bin, bin_bnode))
+        output_rdf_graph.add((bin_bnode, dml_ns.bin_number, Literal(i+1)))
+        output_rdf_graph.add((bin_bnode, dml_ns.bin_value, Literal(statistics["histogram"]["count"][i])))
+        output_rdf_graph.add((bin_bnode, dml_ns.bin_name, Literal(statistics["histogram"]["index"][i])))
+
+    return output_rdf_graph
+
+# Parse the input_f_files n3 files, and generate
+# a key histogram
+def find_cla_tf_statistics(input_f_files):
+
+
+    sample_count = len(input_f_files)
+    
+    all_data = []
+    perfile_freq = []
+    perfile_hist = []
+    hist_index =[]
+    for input_f_file in input_f_files:
+
+        # get all data from feature file
+        data = file_to_table(input_f_file)
+
+        # filter those rows which have an A
+        # returns duration, frequency
+        data = filter_norm_A(data)
+        
+        if perfilestats:
+            # get frequency and duration columns
+            freq = string2numpy(data,2)
+            dur = string2numpy(data,1)
+            # get mean values per clip now,
+            # then statistics over clips later
+            avg, std = numstats(freq, weights = dur)
+            hist = histogram(freq, nbins = 100, lb=390, ub=490, weights = dur)
+            
+            # remember statistics
+            perfile_freq.append(avg) 
+            perfile_hist.append(hist["count"])
+            
+            # remember histogram index
+            if len(hist_index) == 0:
+                hist_index = hist["index"]
+            
+        else:
+            # this version just adds everything per collection,
+            # recordings are not treated as seperate entities
+            all_data.extend(data)
+            
+
+    if perfilestats:
+        avg, std = histostats(numpy.array(perfile_freq,dtype=float))
+        hist_avg, hist_std = histostats(numpy.array(perfile_hist,dtype=float))
+    
+    else:
+        # get frequency and duration columns
+        freq = string2numpy(all_data,2)
+        dur = string2numpy(all_data,1)
+
+        # get basic statistics
+        avg, std = numstats(freq, weights = dur)
+
+        # get histogram weighted by duration
+        hist = histogram(freq, nbins = 100, lb=390, ub=490, weights = dur)
+        
+    return {"mean": avg, "std-dev": std, "histogram": hist}, sample_count#(key_hist, num_f_files)
+
+# convert one column, specified by datapos, to numpy
+def string2numpy(data,datapos):
+    
+    edata = []
+    for row in data:
+        edata.append(row[datapos])
+        
+    colu = numpy.array(edata,dtype=float)
+    return colu
+
+#calculates the histogram
+# nbins: number of bins
+# lb: lower bound
+# ub: upper bound
+def histogram(colu, nbins = 100, lb=-1, ub=-1, weights = []):
+    
+    # lower bounds defined?
+    if lb == -1 or ub == -1:
+        lb = colu.min()
+        ub = colu.max()
+        
+    # get histogram
+    count,index = numpy.histogram(colu,bins=nbins,range = [lb, ub],weights = weights)
+    count = count.tolist()
+    index = index.tolist()
+    
+    # normalise for clip
+    count = count / numpy.max(count)
+    
+    # return histogram
+    return {"count":count, "index":index}
+
+
+# calculates unweighted statistics for the histograms
+def histostats(counts):
+    avg = numpy.average(counts, axis = 0).tolist()
+
+    #weighted standard deviation
+    std = numpy.std(counts, axis =0)
+
+    #med = numpy.median(colu, weights = weights).tolist()
+    # could use https://pypi.python.org/pypi/wquantiles for weighted median
+
+    return (avg,std)
+    
+#calculates weighted statistics for  numerical input
+def numstats(colu, weights = []):
+    
+    # we want to always use the last dimension
+    # get average
+    avg = numpy.average(colu, axis = 0 ,weights = weights)
+
+    #weighted standard deviation
+    std = numpy.sqrt(numpy.average((colu-avg)**2, axis = 0, weights=weights))
+    #std = numpy.std(colu, weights = weights).tolist()
+    
+    #med = numpy.median(colu, weights = weights).tolist()
+    # could use https://pypi.python.org/pypi/wquantiles for weighted median
+
+    return (avg,std)
+
+
+# only returns data columns which refer to the note A
+# the frequencies are folded up / down to A4
+# returns time, duration, frequency
+def filter_norm_A(data):
+    Adata = []
+    for row in data:
+        # we assume format time , duration , pitch, ingeger_pitch, label 
+        if 'A3' in row[4]:
+            Adata.append(row[:2] + [2*row[2]])
+        elif 'A4' in row[4]:
+            Adata.append(row[:3])
+        elif 'A5' in row[4]:
+            Adata.append(row[:2] + [0.5*row[2]])
+            
+    return Adata
+    
+    
+# Read named features into table of format
+# time, feature[0], feature[1} ...
+def file_to_table(input_f_file):
+    if input_f_file.endswith('.n3'):
+        data = n3_to_table(input_f_file)
+    elif input_f_file.endswith('.csv'):    
+        data = csv_to_table(input_f_file)
+        #data = get_array_from_csv(input_f_file)
+        #data = get_dict_from_csv(input_f_file,columtype = ['time','duration','pitch','velocity','label'])
+    return data
+
+
+# Read named features into table of format
+# time, feature[0], feature[1} ...
+def n3_to_table(input_f_file):
+
+    # read feature file
+    feature_graph = get_rdf_graph_from_n3(input_f_file)
+
+    # we construct a generic search string that gets all 
+    # necessary features 
+
+    q = """prefix dml:     <http://dml.org/dml/cla#>
+            SELECT ?event ?tl_time ?tl_duration ?feature ?label
+            WHERE {
+                ?event event:time ?event_time .
+                ?event_time tl:beginsAt ?tl_time .
+                ?event_time tl:duration ?tl_duration .
+                ?event rdfs:label ?label .
+                ?event af:feature ?feature .
+            }"""       
+    
+    # query parsed file
+    qres = feature_graph.query(q)
+    data = []
+    for row in qres:
+        # parse time
+        tl_time_str_len = len(row.tl_time)
+        tl_time = float(row.tl_time[2:tl_time_str_len-1])
+        
+        # parse duration
+        tl_dur_str_len = len(row.tl_duration)
+        tl_duration = row.tl_duration[2:tl_dur_str_len-1]
+        # parse feature
+        data.append([tl_time, tl_duration] + [float(i) for i in row.feature.split(' ') ] + [row.label])
+        
+    #data = numpy.array(data, dtype=float)
+    # print data
+    # we assume format time , duration , pitch, velocity, label 
+    return data #int(last_key)
+
+# todo: do the same conversion for csv, should allow to use the same script with csv
+def csv_to_table(input_f_file):
+    
+    
+    output = []
+    badcount = 0
+    
+    # keep track of column names
+    ncols = 0
+    with open(uri2path(input_f_file), 'rb') as csvfile:
+        contents = csv.reader(csvfile, delimiter=',', quotechar='"')
+        for row in contents:
+            if ncols == 0:
+                ncols = len(row)
+                
+	    if len(row) >= ncols:
+                # we assume format time , duration , pitch, velocity, label 
+	        output.append([float(row[0]), float(row[1]),  float(row[2])] + row[3:])
+            else: 
+                badcount += 1
+                
+    if badcount > 0:
+        warnings.warn("Incomplete csv file, ignoring " + str(badcount) + " entries")
+            
+    return output
\ No newline at end of file
diff -r 000000000000 -r e34cf1b6fe09 pyspark/vamp_plugin_dml.py
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/pyspark/vamp_plugin_dml.py	Sat Feb 20 18:14:24 2016 +0100
@@ -0,0 +1,189 @@
+# -*- coding: utf-8 -*-
+#
+# Copyright (c) 2013 Paul Brossier <piem@piem.org>
+
+# This file is part of TimeSide.
+
+# TimeSide is free software: you can redistribute it and/or modify
+# it under the terms of the GNU General Public License as published by
+# the Free Software Foundation, either version 2 of the License, or
+# (at your option) any later version.
+
+# TimeSide is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+# GNU General Public License for more details.
+
+# You should have received a copy of the GNU General Public License
+# along with TimeSide.  If not, see <http://www.gnu.org/licenses/>.
+
+# Author: Paul Brossier <piem@piem.org>
+
+from timeside.core import implements, interfacedoc
+from timeside.analyzer.core import Analyzer
+from timeside.api import IAnalyzer
+import re
+import subprocess
+import numpy as np
+
+
+def simple_host_process(argslist):
+    """Call vamp-simple-host"""
+
+    vamp_host = 'vamp-simple-host'
+    command = [vamp_host]
+    command.extend(argslist)
+    # try ?
+    stdout = subprocess.check_output(
+        command, stderr=subprocess.STDOUT).splitlines()
+
+    return stdout
+
+
+# Raise an exception if Vamp Host is missing
+from timeside.exceptions import VampImportError
+try:
+    simple_host_process(['-v'])
+    WITH_VAMP = True
+except OSError:
+    WITH_VAMP = False
+    raise VampImportError
+
+
+class VampSimpleHostDML(Analyzer):
+
+    """Vamp plugins library interface analyzer"""
+
+    implements(IAnalyzer)
+
+    def __init__(self, plugin_list=None):
+        super(VampSimpleHostDML, self).__init__()
+        if plugin_list is None:
+            plugin_list = self.get_plugins_list()
+            #plugin_list = [['vamp-example-plugins', 'percussiononsets', 'detectionfunction']]
+
+        self.plugin_list = plugin_list
+
+    @interfacedoc
+    def setup(self, channels=None, samplerate=None,
+              blocksize=None, totalframes=None):
+        super(VampSimpleHostDML, self).setup(
+            channels, samplerate, blocksize, totalframes)
+
+    @staticmethod
+    @interfacedoc
+    def id():
+        return "vamp_simple_host_dml"
+
+    @staticmethod
+    @interfacedoc
+    def name():
+        return "Vamp Plugins Host for DML"
+
+    @staticmethod
+    @interfacedoc
+    def unit():
+        return ""
+
+    def process(self, frames, eod=False):
+        pass
+        return frames, eod
+
+    def post_process(self):
+        #plugin = 'vamp-example-plugins:amplitudefollower:amplitude'
+
+        wavfile = self.mediainfo()['uri'].split('file://')[-1]
+
+        for plugin_line in self.plugin_list:
+
+            plugin = ':'.join(plugin_line)
+            (time, duration, value) = self.vamp_plugin(plugin, wavfile)
+            if value is None:
+                return
+
+            if duration is not None:
+                plugin_res = self.new_result(
+                    data_mode='value', time_mode='segment')
+                plugin_res.data_object.duration = duration
+            else:
+                plugin_res = self.new_result(
+                    data_mode='value', time_mode='event')
+
+            plugin_res.data_object.time = time
+            plugin_res.data_object.value = value
+
+# Fix strat, duration issues if audio is a segment
+#            if self.mediainfo()['is_segment']:
+#                start_index = np.floor(self.mediainfo()['start'] *
+#                                       self.result_samplerate /
+#                                       self.result_stepsize)
+#
+#                stop_index = np.ceil((self.mediainfo()['start'] +
+#                                      self.mediainfo()['duration']) *
+#                                     self.result_samplerate /
+#                                     self.result_stepsize)
+#
+#                fixed_start = (start_index * self.result_stepsize /
+#                               self.result_samplerate)
+#                fixed_duration = ((stop_index - start_index) * self.result_stepsize /
+#                                  self.result_samplerate)
+#
+#                plugin_res.audio_metadata.start = fixed_start
+#                plugin_res.audio_metadata.duration = fixed_duration
+#
+#                value = value[start_index:stop_index + 1]
+            plugin_res.id_metadata.id += '.' + '.'.join(plugin_line[1:])
+            plugin_res.id_metadata.name += ' ' + \
+                ' '.join(plugin_line[1:])
+
+            self.process_pipe.results.add(plugin_res)
+
+    @staticmethod
+    def vamp_plugin(plugin, wavfile):
+
+        args = [plugin, wavfile]
+
+        stdout = simple_host_process(args)  # run vamp-simple-host
+
+        stderr = stdout[0:8]  # stderr containing file and process information
+        res = stdout[8:]  # stdout containg the feature data
+
+        if len(res) == 0:
+            return ([], [], [])
+
+        # Parse stderr to get blocksize and stepsize
+        blocksize_info = stderr[4]
+
+        import re
+        # Match agianst pattern 'Using block size = %d, step size = %d'
+        m = re.match(
+            'Using block size = (\d+), step size = (\d+)', blocksize_info)
+
+        blocksize = int(m.groups()[0])
+        stepsize = int(m.groups()[1])
+        # Get the results
+
+        # how are types defined in this? what types can timeside use?
+        # value = np.asfarray([line.split(': ')[1] for line in res if (len(line.split(': ')) > 1)])
+        value = [line.split(': ')[1] for line in res if (len(line.split(': ')) > 1)]
+        value = [re.sub("[^0-9\.\s]","",x) for x in value]
+        value = np.asfarray([[x.split(' ')[0] for x in value], [x.split(' ')[1] for x in value]]) # only get the first thing in the string
+        time = np.asfarray([r.split(':')[0].split(',')[0] for r in res])
+
+        time_len = len(res[0].split(':')[0].split(','))
+        if time_len == 1:
+            # event
+            duration = None
+        elif time_len == 2:
+            # segment
+            duration = np.asfarray(
+                [r.split(':')[0].split(',')[1] for r in res])
+
+        return (time, duration, value)
+
+    @staticmethod
+    def get_plugins_list():
+        arg = ['--list-outputs']
+        stdout = simple_host_process(arg)
+
+        return [line.split(':')[1:] for line in stdout]
diff -r 000000000000 -r e34cf1b6fe09 sonic_annotator/vamp_plugins/bbc_speechmusic.n3
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/sonic_annotator/vamp_plugins/bbc_speechmusic.n3	Sat Feb 20 18:14:24 2016 +0100
@@ -0,0 +1,29 @@
+@prefix xsd:      <http://www.w3.org/2001/XMLSchema#> .
+@prefix vamp:     <http://purl.org/ontology/vamp/> .
+@prefix :         <#> .
+
+:transform a vamp:Transform ;
+    vamp:plugin <http://vamp-plugins.org/rdf/plugins/bbc-vamp-plugins#bbc-speechmusic-segmenter> ;
+    vamp:step_size "1024"^^xsd:int ; 
+    vamp:block_size "1024"^^xsd:int ; 
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "change_threshold" ] ;
+        vamp:value "0.0781"^^xsd:float ;
+    ] ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "decision_threshold" ] ;
+        vamp:value "0.2734"^^xsd:float ;
+    ] ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "margin" ] ;
+        vamp:value "14"^^xsd:float ;
+    ] ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "min_music_length" ] ;
+        vamp:value "0"^^xsd:float ;
+    ] ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "resolution" ] ;
+        vamp:value "256"^^xsd:float ;
+    ] ;
+    vamp:output <http://vamp-plugins.org/rdf/plugins/bbc-vamp-plugins#bbc-speechmusic-segmenter_output_segmentation> .
diff -r 000000000000 -r e34cf1b6fe09 sonic_annotator/vamp_plugins/beatroot_standard.n3
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/sonic_annotator/vamp_plugins/beatroot_standard.n3	Sat Feb 20 18:14:24 2016 +0100
@@ -0,0 +1,26 @@
+@prefix xsd:      <http://www.w3.org/2001/XMLSchema#> .
+@prefix vamp:     <http://purl.org/ontology/vamp/> .
+@prefix :         <#> .
+
+:transform a vamp:Transform ;
+    vamp:plugin <http://vamp-plugins.org/rdf/plugins/beatroot-vamp#beatroot> ;
+    vamp:step_size "441"^^xsd:int ; 
+    vamp:block_size "2048"^^xsd:int ; 
+    vamp:plugin_version """1""" ; 
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "expiryTime" ] ;
+        vamp:value "10"^^xsd:float ;
+    ] ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "maxChange" ] ;
+        vamp:value "0.2"^^xsd:float ;
+    ] ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "postMarginFactor" ] ;
+        vamp:value "0.3"^^xsd:float ;
+    ] ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "preMarginFactor" ] ;
+        vamp:value "0.15"^^xsd:float ;
+    ] ;
+    vamp:output <http://vamp-plugins.org/rdf/plugins/beatroot-vamp#beatroot_output_beats> .
diff -r 000000000000 -r e34cf1b6fe09 sonic_annotator/vamp_plugins/chordino_chordnotes.n3
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/sonic_annotator/vamp_plugins/chordino_chordnotes.n3	Sat Feb 20 18:14:24 2016 +0100
@@ -0,0 +1,37 @@
+@prefix xsd:      <http://www.w3.org/2001/XMLSchema#> .
+@prefix vamp:     <http://purl.org/ontology/vamp/> .
+@prefix :         <#> .
+
+:transform a vamp:Transform ;
+    vamp:plugin <http://vamp-plugins.org/rdf/plugins/nnls-chroma#chordino> ;
+    vamp:step_size "2048"^^xsd:int ; 
+    vamp:block_size "16384"^^xsd:int ; 
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "boostn" ] ;
+        vamp:value "0.1"^^xsd:float ;
+    ] ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "rollon" ] ;
+        vamp:value "0"^^xsd:float ;
+    ] ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "s" ] ;
+        vamp:value "0.7"^^xsd:float ;
+    ] ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "tuningmode" ] ;
+        vamp:value "0"^^xsd:float ;
+    ] ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "useHMM" ] ;
+        vamp:value "1"^^xsd:float ;
+    ] ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "useNNLS" ] ;
+        vamp:value "1"^^xsd:float ;
+    ] ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "whitening" ] ;
+        vamp:value "1"^^xsd:float ;
+    ] ;
+    vamp:output <http://vamp-plugins.org/rdf/plugins/nnls-chroma#chordino_output_chordnotes> .
diff -r 000000000000 -r e34cf1b6fe09 sonic_annotator/vamp_plugins/chordino_simple.n3
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/sonic_annotator/vamp_plugins/chordino_simple.n3	Sat Feb 20 18:14:24 2016 +0100
@@ -0,0 +1,37 @@
+@prefix xsd:      <http://www.w3.org/2001/XMLSchema#> .
+@prefix vamp:     <http://purl.org/ontology/vamp/> .
+@prefix :         <#> .
+
+:transform a vamp:Transform ;
+    vamp:plugin <http://vamp-plugins.org/rdf/plugins/nnls-chroma#chordino> ;
+    vamp:step_size "2048"^^xsd:int ; 
+    vamp:block_size "16384"^^xsd:int ; 
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "boostn" ] ;
+        vamp:value "0.1"^^xsd:float ;
+    ] ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "rollon" ] ;
+        vamp:value "0"^^xsd:float ;
+    ] ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "s" ] ;
+        vamp:value "0.7"^^xsd:float ;
+    ] ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "tuningmode" ] ;
+        vamp:value "0"^^xsd:float ;
+    ] ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "useHMM" ] ;
+        vamp:value "1"^^xsd:float ;
+    ] ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "useNNLS" ] ;
+        vamp:value "1"^^xsd:float ;
+    ] ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "whitening" ] ;
+        vamp:value "1"^^xsd:float ;
+    ] ;
+    vamp:output <http://vamp-plugins.org/rdf/plugins/nnls-chroma#chordino_output_simplechord> .
diff -r 000000000000 -r e34cf1b6fe09 sonic_annotator/vamp_plugins/marysas_beat_standard.n3
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/sonic_annotator/vamp_plugins/marysas_beat_standard.n3	Sat Feb 20 18:14:24 2016 +0100
@@ -0,0 +1,41 @@
+@prefix xsd:      <http://www.w3.org/2001/XMLSchema#> .
+@prefix vamp:     <http://purl.org/ontology/vamp/> .
+@prefix :         <#> .
+
+:transform_plugin a vamp:Plugin ;
+    vamp:identifier "marsyas_ibt" .
+
+:transform_library a vamp:PluginLibrary ;
+    vamp:identifier "mvamp-ibt" ;
+    vamp:available_plugin :transform_plugin .
+
+:transform a vamp:Transform ;
+    vamp:plugin :transform_plugin ;
+    vamp:step_size "512"^^xsd:int ; 
+    vamp:block_size "1024"^^xsd:int ; 
+    vamp:plugin_version """1""" ; 
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "indtime" ] ;
+        vamp:value "5"^^xsd:float ;
+    ] ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "induction" ] ;
+        vamp:value "0"^^xsd:float ;
+    ] ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "maxbpm" ] ;
+        vamp:value "250"^^xsd:float ;
+    ] ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "metrical_changes" ] ;
+        vamp:value "0"^^xsd:float ;
+    ] ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "minbpm" ] ;
+        vamp:value "50"^^xsd:float ;
+    ] ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "online" ] ;
+        vamp:value "0"^^xsd:float ;
+    ] ;
+    vamp:output [ vamp:identifier "beat_times" ] .
diff -r 000000000000 -r e34cf1b6fe09 sonic_annotator/vamp_plugins/melodia_standard.n3
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/sonic_annotator/vamp_plugins/melodia_standard.n3	Sat Feb 20 18:14:24 2016 +0100
@@ -0,0 +1,27 @@
+@prefix xsd:      <http://www.w3.org/2001/XMLSchema#> .
+@prefix vamp:     <http://purl.org/ontology/vamp/> .
+@prefix :         <#> .
+
+:transform a vamp:Transform ;
+    vamp:plugin <http://vamp-plugins.org/rdf/plugins/mtg-melodia#melodia> ;
+    vamp:step_size "128"^^xsd:int ; 
+    vamp:block_size "2048"^^xsd:int ; 
+    vamp:plugin_version """1""" ; 
+    vamp:program """Polyphonic""" ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "maxfqr" ] ;
+        vamp:value "1760"^^xsd:float ;
+    ] ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "minfqr" ] ;
+        vamp:value "55"^^xsd:float ;
+    ] ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "minpeaksalience" ] ;
+        vamp:value "0"^^xsd:float ;
+    ] ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "voicing" ] ;
+        vamp:value "0.2"^^xsd:float ;
+    ] ;
+    vamp:output <http://vamp-plugins.org/rdf/plugins/mtg-melodia#melodia_output_melody> .
diff -r 000000000000 -r e34cf1b6fe09 sonic_annotator/vamp_plugins/nnls-bothchroma_standard.n3
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/sonic_annotator/vamp_plugins/nnls-bothchroma_standard.n3	Sat Feb 20 18:14:24 2016 +0100
@@ -0,0 +1,34 @@
+@prefix xsd:      <http://www.w3.org/2001/XMLSchema#> .
+@prefix vamp:     <http://purl.org/ontology/vamp/> .
+@prefix :         <#> .
+
+:transform a vamp:Transform ;
+    vamp:plugin <http://vamp-plugins.org/rdf/plugins/nnls-chroma#nnls-chroma> ;
+    vamp:step_size "2048"^^xsd:int ; 
+    vamp:block_size "16384"^^xsd:int ; 
+    vamp:plugin_version """3""" ; 
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "chromanormalize" ] ;
+        vamp:value "0"^^xsd:float ;
+    ] ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "rollon" ] ;
+        vamp:value "0"^^xsd:float ;
+    ] ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "s" ] ;
+        vamp:value "0.7"^^xsd:float ;
+    ] ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "tuningmode" ] ;
+        vamp:value "0"^^xsd:float ;
+    ] ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "useNNLS" ] ;
+        vamp:value "1"^^xsd:float ;
+    ] ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "whitening" ] ;
+        vamp:value "1"^^xsd:float ;
+    ] ;
+    vamp:output <http://vamp-plugins.org/rdf/plugins/nnls-chroma#nnls-chroma_output_bothchroma> .
diff -r 000000000000 -r e34cf1b6fe09 sonic_annotator/vamp_plugins/nnls-logfreqspec_standard.n3
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/sonic_annotator/vamp_plugins/nnls-logfreqspec_standard.n3	Sat Feb 20 18:14:24 2016 +0100
@@ -0,0 +1,34 @@
+@prefix xsd:      <http://www.w3.org/2001/XMLSchema#> .
+@prefix vamp:     <http://purl.org/ontology/vamp/> .
+@prefix :         <#> .
+
+:transform a vamp:Transform ;
+    vamp:plugin <http://vamp-plugins.org/rdf/plugins/nnls-chroma#nnls-chroma> ;
+    vamp:step_size "2048"^^xsd:int ; 
+    vamp:block_size "16384"^^xsd:int ; 
+    vamp:plugin_version """3""" ; 
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "chromanormalize" ] ;
+        vamp:value "0"^^xsd:float ;
+    ] ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "rollon" ] ;
+        vamp:value "0"^^xsd:float ;
+    ] ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "s" ] ;
+        vamp:value "0.7"^^xsd:float ;
+    ] ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "tuningmode" ] ;
+        vamp:value "0"^^xsd:float ;
+    ] ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "useNNLS" ] ;
+        vamp:value "1"^^xsd:float ;
+    ] ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "whitening" ] ;
+        vamp:value "1"^^xsd:float ;
+    ] ;
+    vamp:output <http://vamp-plugins.org/rdf/plugins/nnls-chroma#nnls-chroma_output_logfreqspec> .
diff -r 000000000000 -r e34cf1b6fe09 sonic_annotator/vamp_plugins/powerspectrum_2048_1024.n3
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/sonic_annotator/vamp_plugins/powerspectrum_2048_1024.n3	Sat Feb 20 18:14:24 2016 +0100
@@ -0,0 +1,10 @@
+@prefix xsd:      <http://www.w3.org/2001/XMLSchema#> .
+@prefix vamp:     <http://purl.org/ontology/vamp/> .
+@prefix :         <#> .
+
+:transform a vamp:Transform ;
+    vamp:plugin <http://vamp-plugins.org/rdf/plugins/vamp-example-plugins#powerspectrum> ;
+    vamp:step_size "1024"^^xsd:int ; 
+    vamp:block_size "2048"^^xsd:int ; 
+    vamp:plugin_version """1""" ; 
+    vamp:output <http://vamp-plugins.org/rdf/plugins/vamp-example-plugins#powerspectrum_output_powerspectrum> .
diff -r 000000000000 -r e34cf1b6fe09 sonic_annotator/vamp_plugins/powerspectrum_2048_512.n3
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/sonic_annotator/vamp_plugins/powerspectrum_2048_512.n3	Sat Feb 20 18:14:24 2016 +0100
@@ -0,0 +1,10 @@
+@prefix xsd:      <http://www.w3.org/2001/XMLSchema#> .
+@prefix vamp:     <http://purl.org/ontology/vamp/> .
+@prefix :         <#> .
+
+:transform a vamp:Transform ;
+    vamp:plugin <http://vamp-plugins.org/rdf/plugins/vamp-example-plugins#powerspectrum> ;
+    vamp:step_size "512"^^xsd:int ; 
+    vamp:block_size "2048"^^xsd:int ; 
+    vamp:plugin_version """1""" ; 
+    vamp:output <http://vamp-plugins.org/rdf/plugins/vamp-example-plugins#powerspectrum_output_powerspectrum> .
diff -r 000000000000 -r e34cf1b6fe09 sonic_annotator/vamp_plugins/powerspectrum_4096_512.n3
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/sonic_annotator/vamp_plugins/powerspectrum_4096_512.n3	Sat Feb 20 18:14:24 2016 +0100
@@ -0,0 +1,10 @@
+@prefix xsd:      <http://www.w3.org/2001/XMLSchema#> .
+@prefix vamp:     <http://purl.org/ontology/vamp/> .
+@prefix :         <#> .
+
+:transform a vamp:Transform ;
+    vamp:plugin <http://vamp-plugins.org/rdf/plugins/vamp-example-plugins#powerspectrum> ;
+    vamp:step_size "512"^^xsd:int ; 
+    vamp:block_size "4096"^^xsd:int ; 
+    vamp:plugin_version """1""" ; 
+    vamp:output <http://vamp-plugins.org/rdf/plugins/vamp-example-plugins#powerspectrum_output_powerspectrum> .
diff -r 000000000000 -r e34cf1b6fe09 sonic_annotator/vamp_plugins/qm-barbeattracker_beatcounts.n3
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/sonic_annotator/vamp_plugins/qm-barbeattracker_beatcounts.n3	Sat Feb 20 18:14:24 2016 +0100
@@ -0,0 +1,14 @@
+@prefix xsd:      <http://www.w3.org/2001/XMLSchema#> .
+@prefix vamp:     <http://purl.org/ontology/vamp/> .
+@prefix :         <#> .
+
+:transform a vamp:Transform ;
+    vamp:plugin <http://vamp-plugins.org/rdf/plugins/qm-vamp-plugins#qm-barbeattracker> ;
+    vamp:step_size "512"^^xsd:int ; 
+    vamp:block_size "1024"^^xsd:int ; 
+    vamp:plugin_version """2""" ; 
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "bpb" ] ;
+        vamp:value "4"^^xsd:float ;
+    ] ;
+    vamp:output <http://vamp-plugins.org/rdf/plugins/qm-vamp-plugins#qm-barbeattracker_output_beatcounts> .
diff -r 000000000000 -r e34cf1b6fe09 sonic_annotator/vamp_plugins/qm-chromagram-means_standard.n3
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/sonic_annotator/vamp_plugins/qm-chromagram-means_standard.n3	Sat Feb 20 18:14:24 2016 +0100
@@ -0,0 +1,30 @@
+@prefix xsd:      <http://www.w3.org/2001/XMLSchema#> .
+@prefix vamp:     <http://purl.org/ontology/vamp/> .
+@prefix :         <#> .
+
+:transform a vamp:Transform ;
+    vamp:plugin <http://vamp-plugins.org/rdf/plugins/qm-vamp-plugins#qm-chromagram> ;
+    vamp:step_size "2048"^^xsd:int ; 
+    vamp:block_size "16384"^^xsd:int ; 
+    vamp:plugin_version """4""" ; 
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "bpo" ] ;
+        vamp:value "12"^^xsd:float ;
+    ] ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "maxpitch" ] ;
+        vamp:value "96"^^xsd:float ;
+    ] ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "minpitch" ] ;
+        vamp:value "36"^^xsd:float ;
+    ] ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "normalization" ] ;
+        vamp:value "0"^^xsd:float ;
+    ] ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "tuning" ] ;
+        vamp:value "440"^^xsd:float ;
+    ] ;
+    vamp:output <http://vamp-plugins.org/rdf/plugins/qm-vamp-plugins#qm-chromagram_output_chromameans> .
diff -r 000000000000 -r e34cf1b6fe09 sonic_annotator/vamp_plugins/qm-chromagram_standard.n3
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/sonic_annotator/vamp_plugins/qm-chromagram_standard.n3	Sat Feb 20 18:14:24 2016 +0100
@@ -0,0 +1,30 @@
+@prefix xsd:      <http://www.w3.org/2001/XMLSchema#> .
+@prefix vamp:     <http://purl.org/ontology/vamp/> .
+@prefix :         <#> .
+
+:transform a vamp:Transform ;
+    vamp:plugin <http://vamp-plugins.org/rdf/plugins/qm-vamp-plugins#qm-chromagram> ;
+    vamp:step_size "2048"^^xsd:int ; 
+    vamp:block_size "16384"^^xsd:int ; 
+    vamp:plugin_version """4""" ; 
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "bpo" ] ;
+        vamp:value "12"^^xsd:float ;
+    ] ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "maxpitch" ] ;
+        vamp:value "96"^^xsd:float ;
+    ] ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "minpitch" ] ;
+        vamp:value "36"^^xsd:float ;
+    ] ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "normalization" ] ;
+        vamp:value "0"^^xsd:float ;
+    ] ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "tuning" ] ;
+        vamp:value "440"^^xsd:float ;
+    ] ;
+    vamp:output <http://vamp-plugins.org/rdf/plugins/qm-vamp-plugins#qm-chromagram_output_chromagram> .
diff -r 000000000000 -r e34cf1b6fe09 sonic_annotator/vamp_plugins/qm-constantq_standard.n3
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/sonic_annotator/vamp_plugins/qm-constantq_standard.n3	Sat Feb 20 18:14:24 2016 +0100
@@ -0,0 +1,30 @@
+@prefix xsd:      <http://www.w3.org/2001/XMLSchema#> .
+@prefix vamp:     <http://purl.org/ontology/vamp/> .
+@prefix :         <#> .
+
+:transform a vamp:Transform ;
+    vamp:plugin <http://vamp-plugins.org/rdf/plugins/qm-vamp-plugins#qm-constantq> ;
+    vamp:step_size "2048"^^xsd:int ; 
+    vamp:block_size "16384"^^xsd:int ; 
+    vamp:plugin_version """3""" ; 
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "bpo" ] ;
+        vamp:value "12"^^xsd:float ;
+    ] ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "maxpitch" ] ;
+        vamp:value "84"^^xsd:float ;
+    ] ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "minpitch" ] ;
+        vamp:value "36"^^xsd:float ;
+    ] ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "normalized" ] ;
+        vamp:value "0"^^xsd:float ;
+    ] ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "tuning" ] ;
+        vamp:value "440"^^xsd:float ;
+    ] ;
+    vamp:output <http://vamp-plugins.org/rdf/plugins/qm-vamp-plugins#qm-constantq_output_constantq> .
diff -r 000000000000 -r e34cf1b6fe09 sonic_annotator/vamp_plugins/qm-mfcc-means_standard.n3
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/sonic_annotator/vamp_plugins/qm-mfcc-means_standard.n3	Sat Feb 20 18:14:24 2016 +0100
@@ -0,0 +1,22 @@
+@prefix xsd:      <http://www.w3.org/2001/XMLSchema#> .
+@prefix vamp:     <http://purl.org/ontology/vamp/> .
+@prefix :         <#> .
+
+:transform a vamp:Transform ;
+    vamp:plugin <http://vamp-plugins.org/rdf/plugins/qm-vamp-plugins#qm-mfcc> ;
+    vamp:step_size "1024"^^xsd:int ; 
+    vamp:block_size "2048"^^xsd:int ; 
+    vamp:plugin_version """1""" ; 
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "logpower" ] ;
+        vamp:value "1"^^xsd:float ;
+    ] ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "nceps" ] ;
+        vamp:value "20"^^xsd:float ;
+    ] ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "wantc0" ] ;
+        vamp:value "1"^^xsd:float ;
+    ] ;
+    vamp:output <http://vamp-plugins.org/rdf/plugins/qm-vamp-plugins#qm-mfcc_output_means> .
diff -r 000000000000 -r e34cf1b6fe09 sonic_annotator/vamp_plugins/qm-mfcc-standard.n3
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/sonic_annotator/vamp_plugins/qm-mfcc-standard.n3	Sat Feb 20 18:14:24 2016 +0100
@@ -0,0 +1,22 @@
+@prefix xsd:      <http://www.w3.org/2001/XMLSchema#> .
+@prefix vamp:     <http://purl.org/ontology/vamp/> .
+@prefix :         <#> .
+
+:transform a vamp:Transform ;
+    vamp:plugin <http://vamp-plugins.org/rdf/plugins/qm-vamp-plugins#qm-mfcc> ;
+    vamp:step_size "1024"^^xsd:int ; 
+    vamp:block_size "2048"^^xsd:int ; 
+    vamp:plugin_version """1""" ; 
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "logpower" ] ;
+        vamp:value "1"^^xsd:float ;
+    ] ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "nceps" ] ;
+        vamp:value "20"^^xsd:float ;
+    ] ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "wantc0" ] ;
+        vamp:value "1"^^xsd:float ;
+    ] ;
+    vamp:output <http://vamp-plugins.org/rdf/plugins/qm-vamp-plugins#qm-mfcc_output_coefficients> .
diff -r 000000000000 -r e34cf1b6fe09 sonic_annotator/vamp_plugins/qm-onsets-detectionfn_standard.n3
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/sonic_annotator/vamp_plugins/qm-onsets-detectionfn_standard.n3	Sat Feb 20 18:14:24 2016 +0100
@@ -0,0 +1,22 @@
+@prefix xsd:      <http://www.w3.org/2001/XMLSchema#> .
+@prefix vamp:     <http://purl.org/ontology/vamp/> .
+@prefix :         <#> .
+
+:transform a vamp:Transform ;
+    vamp:plugin <http://vamp-plugins.org/rdf/plugins/qm-vamp-plugins#qm-onsetdetector> ;
+    vamp:step_size "512"^^xsd:int ; 
+    vamp:block_size "1024"^^xsd:int ; 
+    vamp:plugin_version """3""" ; 
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "dftype" ] ;
+        vamp:value "3"^^xsd:float ;
+    ] ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "sensitivity" ] ;
+        vamp:value "50"^^xsd:float ;
+    ] ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "whiten" ] ;
+        vamp:value "0"^^xsd:float ;
+    ] ;
+    vamp:output <http://vamp-plugins.org/rdf/plugins/qm-vamp-plugins#qm-onsetdetector_output_detection_fn> .
diff -r 000000000000 -r e34cf1b6fe09 sonic_annotator/vamp_plugins/qm-onsets_standard.n3
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/sonic_annotator/vamp_plugins/qm-onsets_standard.n3	Sat Feb 20 18:14:24 2016 +0100
@@ -0,0 +1,22 @@
+@prefix xsd:      <http://www.w3.org/2001/XMLSchema#> .
+@prefix vamp:     <http://purl.org/ontology/vamp/> .
+@prefix :         <#> .
+
+:transform a vamp:Transform ;
+    vamp:plugin <http://vamp-plugins.org/rdf/plugins/qm-vamp-plugins#qm-onsetdetector> ;
+    vamp:step_size "512"^^xsd:int ; 
+    vamp:block_size "1024"^^xsd:int ; 
+    vamp:plugin_version """3""" ; 
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "dftype" ] ;
+        vamp:value "3"^^xsd:float ;
+    ] ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "sensitivity" ] ;
+        vamp:value "50"^^xsd:float ;
+    ] ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "whiten" ] ;
+        vamp:value "0"^^xsd:float ;
+    ] ;
+    vamp:output <http://vamp-plugins.org/rdf/plugins/qm-vamp-plugins#qm-onsetdetector_output_onsets> .
diff -r 000000000000 -r e34cf1b6fe09 sonic_annotator/vamp_plugins/qm-segmentation_standard.n3
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/sonic_annotator/vamp_plugins/qm-segmentation_standard.n3	Sat Feb 20 18:14:24 2016 +0100
@@ -0,0 +1,21 @@
+@prefix xsd:      <http://www.w3.org/2001/XMLSchema#> .
+@prefix vamp:     <http://purl.org/ontology/vamp/> .
+@prefix :         <#> .
+
+:transform a vamp:Transform ;
+    vamp:plugin <http://vamp-plugins.org/rdf/plugins/qm-vamp-plugins#qm-segmenter> ;
+    vamp:step_size "8820"^^xsd:int ; 
+    vamp:block_size "26460"^^xsd:int ; 
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "featureType" ] ;
+        vamp:value "1"^^xsd:float ;
+    ] ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "nSegmentTypes" ] ;
+        vamp:value "10"^^xsd:float ;
+    ] ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "neighbourhoodLimit" ] ;
+        vamp:value "4"^^xsd:float ;
+    ] ;
+    vamp:output <http://vamp-plugins.org/rdf/plugins/qm-vamp-plugins#qm-segmenter_output_segmentation> .
diff -r 000000000000 -r e34cf1b6fe09 sonic_annotator/vamp_plugins/qm_vamp_key_standard.n3
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/sonic_annotator/vamp_plugins/qm_vamp_key_standard.n3	Sat Feb 20 18:14:24 2016 +0100
@@ -0,0 +1,17 @@
+@prefix xsd:      <http://www.w3.org/2001/XMLSchema#> .
+@prefix vamp:     <http://purl.org/ontology/vamp/> .
+@prefix :         <#> .
+
+:transform a vamp:Transform ;
+    vamp:plugin <http://vamp-plugins.org/rdf/plugins/qm-vamp-plugins#qm-keydetector> ;
+    vamp:step_size "32768"^^xsd:int ; 
+    vamp:block_size "32768"^^xsd:int ; 
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "length" ] ;
+        vamp:value "10"^^xsd:float ;
+    ] ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "tuning" ] ;
+        vamp:value "440"^^xsd:float ;
+    ] ;
+    vamp:output <http://vamp-plugins.org/rdf/plugins/qm-vamp-plugins#qm-keydetector_output_key> .
diff -r 000000000000 -r e34cf1b6fe09 sonic_annotator/vamp_plugins/qm_vamp_key_standard_tonic.n3
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/sonic_annotator/vamp_plugins/qm_vamp_key_standard_tonic.n3	Sat Feb 20 18:14:24 2016 +0100
@@ -0,0 +1,17 @@
+@prefix xsd:      <http://www.w3.org/2001/XMLSchema#> .
+@prefix vamp:     <http://purl.org/ontology/vamp/> .
+@prefix :         <#> .
+
+:transform a vamp:Transform ;
+    vamp:plugin <http://vamp-plugins.org/rdf/plugins/qm-vamp-plugins#qm-keydetector> ;
+    vamp:step_size "32768"^^xsd:int ; 
+    vamp:block_size "32768"^^xsd:int ; 
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "length" ] ;
+        vamp:value "10"^^xsd:float ;
+    ] ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "tuning" ] ;
+        vamp:value "440"^^xsd:float ;
+    ] ;
+    vamp:output <http://vamp-plugins.org/rdf/plugins/qm-vamp-plugins#qm-keydetector_output_tonic> .
diff -r 000000000000 -r e34cf1b6fe09 sonic_annotator/vamp_plugins/silvet_settings_fast.n3
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/sonic_annotator/vamp_plugins/silvet_settings_fast.n3	Sat Feb 20 18:14:24 2016 +0100
@@ -0,0 +1,21 @@
+@prefix xsd:      <http://www.w3.org/2001/XMLSchema#> .
+@prefix vamp:     <http://purl.org/ontology/vamp/> .
+@prefix :         <#> .
+
+:transform a vamp:Transform ;
+    vamp:plugin <http://vamp-plugins.org/rdf/plugins/silvet#silvet> ;
+    vamp:step_size "1024"^^xsd:int ; 
+    vamp:block_size "1024"^^xsd:int ; 
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "finetune" ] ;
+        vamp:value "0"^^xsd:float ;
+    ] ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "instrument" ] ;
+        vamp:value "0"^^xsd:float ;
+    ] ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "mode" ] ;
+        vamp:value "0"^^xsd:float ;
+    ] ;
+    vamp:output <http://vamp-plugins.org/rdf/plugins/silvet#silvet_output_notes> .
diff -r 000000000000 -r e34cf1b6fe09 sonic_annotator/vamp_plugins/silvet_settings_fast_finetune.n3
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/sonic_annotator/vamp_plugins/silvet_settings_fast_finetune.n3	Sat Feb 20 18:14:24 2016 +0100
@@ -0,0 +1,21 @@
+@prefix xsd:      <http://www.w3.org/2001/XMLSchema#> .
+@prefix vamp:     <http://purl.org/ontology/vamp/> .
+@prefix :         <#> .
+
+:transform a vamp:Transform ;
+    vamp:plugin <http://vamp-plugins.org/rdf/plugins/silvet#silvet> ;
+    vamp:step_size "1024"^^xsd:int ; 
+    vamp:block_size "1024"^^xsd:int ; 
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "finetune" ] ;
+        vamp:value "0"^^xsd:float ;
+    ] ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "instrument" ] ;
+        vamp:value "0"^^xsd:float ;
+    ] ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "mode" ] ;
+        vamp:value "0"^^xsd:float ;
+    ] ;
+    vamp:output <http://vamp-plugins.org/rdf/plugins/silvet#silvet_output_notes> .
diff -r 000000000000 -r e34cf1b6fe09 sonic_annotator/vamp_plugins/silvet_settings_fast_finetune_allinstruments.n3
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/sonic_annotator/vamp_plugins/silvet_settings_fast_finetune_allinstruments.n3	Sat Feb 20 18:14:24 2016 +0100
@@ -0,0 +1,21 @@
+@prefix xsd:      <http://www.w3.org/2001/XMLSchema#> .
+@prefix vamp:     <http://purl.org/ontology/vamp/> .
+@prefix :         <#> .
+
+:transform a vamp:Transform ;
+    vamp:plugin <http://vamp-plugins.org/rdf/plugins/silvet#silvet> ;
+    vamp:step_size "1024"^^xsd:int ; 
+    vamp:block_size "1024"^^xsd:int ; 
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "finetune" ] ;
+        vamp:value "1"^^xsd:float ;
+    ] ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "instrument" ] ;
+        vamp:value "0"^^xsd:float ;
+    ] ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "mode" ] ;
+        vamp:value "0"^^xsd:float ;
+    ] ;
+    vamp:output <http://vamp-plugins.org/rdf/plugins/silvet#silvet_output_notes> .
diff -r 000000000000 -r e34cf1b6fe09 sonic_annotator/vamp_plugins/silvet_settings_fast_nonfinetune_allinstruments.n3
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/sonic_annotator/vamp_plugins/silvet_settings_fast_nonfinetune_allinstruments.n3	Sat Feb 20 18:14:24 2016 +0100
@@ -0,0 +1,21 @@
+@prefix xsd:      <http://www.w3.org/2001/XMLSchema#> .
+@prefix vamp:     <http://purl.org/ontology/vamp/> .
+@prefix :         <#> .
+
+:transform a vamp:Transform ;
+    vamp:plugin <http://vamp-plugins.org/rdf/plugins/silvet#silvet> ;
+    vamp:step_size "1024"^^xsd:int ; 
+    vamp:block_size "1024"^^xsd:int ; 
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "finetune" ] ;
+        vamp:value "0"^^xsd:float ;
+    ] ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "instrument" ] ;
+        vamp:value "0"^^xsd:float ;
+    ] ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "mode" ] ;
+        vamp:value "0"^^xsd:float ;
+    ] ;
+    vamp:output <http://vamp-plugins.org/rdf/plugins/silvet#silvet_output_notes> .
diff -r 000000000000 -r e34cf1b6fe09 sonic_annotator/vamp_plugins/silvet_settings_slow_finetune.n3
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/sonic_annotator/vamp_plugins/silvet_settings_slow_finetune.n3	Sat Feb 20 18:14:24 2016 +0100
@@ -0,0 +1,21 @@
+@prefix xsd:      <http://www.w3.org/2001/XMLSchema#> .
+@prefix vamp:     <http://purl.org/ontology/vamp/> .
+@prefix :         <#> .
+
+:transform a vamp:Transform ;
+    vamp:plugin <http://vamp-plugins.org/rdf/plugins/silvet#silvet> ;
+    vamp:step_size "1024"^^xsd:int ; 
+    vamp:block_size "1024"^^xsd:int ; 
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "finetune" ] ;
+        vamp:value "1"^^xsd:float ;
+    ] ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "instrument" ] ;
+        vamp:value "0"^^xsd:float ;
+    ] ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "mode" ] ;
+        vamp:value "1"^^xsd:float ;
+    ] ;
+    vamp:output <http://vamp-plugins.org/rdf/plugins/silvet#silvet_output_notes> .
diff -r 000000000000 -r e34cf1b6fe09 sonic_annotator/vamp_plugins/silvet_settings_slow_finetune_allinstruments.n3
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/sonic_annotator/vamp_plugins/silvet_settings_slow_finetune_allinstruments.n3	Sat Feb 20 18:14:24 2016 +0100
@@ -0,0 +1,21 @@
+@prefix xsd:      <http://www.w3.org/2001/XMLSchema#> .
+@prefix vamp:     <http://purl.org/ontology/vamp/> .
+@prefix :         <#> .
+
+:transform a vamp:Transform ;
+    vamp:plugin <http://vamp-plugins.org/rdf/plugins/silvet#silvet> ;
+    vamp:step_size "1024"^^xsd:int ; 
+    vamp:block_size "1024"^^xsd:int ; 
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "finetune" ] ;
+        vamp:value "1"^^xsd:float ;
+    ] ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "instrument" ] ;
+        vamp:value "0"^^xsd:float ;
+    ] ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "mode" ] ;
+        vamp:value "1"^^xsd:float ;
+    ] ;
+    vamp:output <http://vamp-plugins.org/rdf/plugins/silvet#silvet_output_notes> .
diff -r 000000000000 -r e34cf1b6fe09 sonic_annotator/vamp_plugins/silvet_settings_slow_finetune_piano.n3
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/sonic_annotator/vamp_plugins/silvet_settings_slow_finetune_piano.n3	Sat Feb 20 18:14:24 2016 +0100
@@ -0,0 +1,21 @@
+@prefix xsd:      <http://www.w3.org/2001/XMLSchema#> .
+@prefix vamp:     <http://purl.org/ontology/vamp/> .
+@prefix :         <#> .
+
+:transform a vamp:Transform ;
+    vamp:plugin <http://vamp-plugins.org/rdf/plugins/silvet#silvet> ;
+    vamp:step_size "1024"^^xsd:int ; 
+    vamp:block_size "1024"^^xsd:int ; 
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "finetune" ] ;
+        vamp:value "1"^^xsd:float ;
+    ] ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "instrument" ] ;
+        vamp:value "1"^^xsd:float ;
+    ] ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "mode" ] ;
+        vamp:value "1"^^xsd:float ;
+    ] ;
+    vamp:output <http://vamp-plugins.org/rdf/plugins/silvet#silvet_output_notes> .
diff -r 000000000000 -r e34cf1b6fe09 sonic_annotator/vamp_plugins/silvet_settings_slow_nonfinetune_allinstruments.n3
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/sonic_annotator/vamp_plugins/silvet_settings_slow_nonfinetune_allinstruments.n3	Sat Feb 20 18:14:24 2016 +0100
@@ -0,0 +1,21 @@
+@prefix xsd:      <http://www.w3.org/2001/XMLSchema#> .
+@prefix vamp:     <http://purl.org/ontology/vamp/> .
+@prefix :         <#> .
+
+:transform a vamp:Transform ;
+    vamp:plugin <http://vamp-plugins.org/rdf/plugins/silvet#silvet> ;
+    vamp:step_size "1024"^^xsd:int ; 
+    vamp:block_size "1024"^^xsd:int ; 
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "finetune" ] ;
+        vamp:value "0"^^xsd:float ;
+    ] ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "instrument" ] ;
+        vamp:value "0"^^xsd:float ;
+    ] ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "mode" ] ;
+        vamp:value "1"^^xsd:float ;
+    ] ;
+    vamp:output <http://vamp-plugins.org/rdf/plugins/silvet#silvet_output_notes> .
diff -r 000000000000 -r e34cf1b6fe09 sonic_annotator/vamp_plugins/silvet_settings_slow_nonfinetune_piano.n3
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/sonic_annotator/vamp_plugins/silvet_settings_slow_nonfinetune_piano.n3	Sat Feb 20 18:14:24 2016 +0100
@@ -0,0 +1,21 @@
+@prefix xsd:      <http://www.w3.org/2001/XMLSchema#> .
+@prefix vamp:     <http://purl.org/ontology/vamp/> .
+@prefix :         <#> .
+
+:transform a vamp:Transform ;
+    vamp:plugin <http://vamp-plugins.org/rdf/plugins/silvet#silvet> ;
+    vamp:step_size "1024"^^xsd:int ; 
+    vamp:block_size "1024"^^xsd:int ; 
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "finetune" ] ;
+        vamp:value "0"^^xsd:float ;
+    ] ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "instrument" ] ;
+        vamp:value "1"^^xsd:float ;
+    ] ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "mode" ] ;
+        vamp:value "1"^^xsd:float ;
+    ] ;
+    vamp:output <http://vamp-plugins.org/rdf/plugins/silvet#silvet_output_notes> .
diff -r 000000000000 -r e34cf1b6fe09 sonic_annotator/vamp_plugins/tempogram_standard.n3
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/sonic_annotator/vamp_plugins/tempogram_standard.n3	Sat Feb 20 18:14:24 2016 +0100
@@ -0,0 +1,46 @@
+@prefix xsd:      <http://www.w3.org/2001/XMLSchema#> .
+@prefix vamp:     <http://purl.org/ontology/vamp/> .
+@prefix :         <#> .
+
+:transform a vamp:Transform ;
+    vamp:plugin <http://vamp-plugins.org/rdf/plugins/tempogram#tempogram> ;
+    vamp:step_size "1024"^^xsd:int ; 
+    vamp:block_size "2048"^^xsd:int ; 
+    vamp:plugin_version """1""" ; 
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "C" ] ;
+        vamp:value "1000"^^xsd:float ;
+    ] ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "log2FftLength" ] ;
+        vamp:value "10"^^xsd:float ;
+    ] ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "log2HopSize" ] ;
+        vamp:value "6"^^xsd:float ;
+    ] ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "log2TN" ] ;
+        vamp:value "10"^^xsd:float ;
+    ] ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "maxBPM" ] ;
+        vamp:value "480"^^xsd:float ;
+    ] ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "minBPM" ] ;
+        vamp:value "30"^^xsd:float ;
+    ] ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "minDB" ] ;
+        vamp:value "-74"^^xsd:float ;
+    ] ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "octDiv" ] ;
+        vamp:value "30"^^xsd:float ;
+    ] ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "refBPM" ] ;
+        vamp:value "60"^^xsd:float ;
+    ] ;
+    vamp:output <http://vamp-plugins.org/rdf/plugins/tempogram#tempogram_output_cyclicTempogram> .
diff -r 000000000000 -r e34cf1b6fe09 sonic_annotator/vamp_plugins/tempotracker_beats_standard.n3
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/sonic_annotator/vamp_plugins/tempotracker_beats_standard.n3	Sat Feb 20 18:14:24 2016 +0100
@@ -0,0 +1,22 @@
+@prefix xsd:      <http://www.w3.org/2001/XMLSchema#> .
+@prefix vamp:     <http://purl.org/ontology/vamp/> .
+@prefix :         <#> .
+
+:transform a vamp:Transform ;
+    vamp:plugin <http://vamp-plugins.org/rdf/plugins/qm-vamp-plugins#qm-tempotracker> ;
+    vamp:step_size "512"^^xsd:int ; 
+    vamp:block_size "1024"^^xsd:int ; 
+    vamp:plugin_version """5""" ; 
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "dftype" ] ;
+        vamp:value "3"^^xsd:float ;
+    ] ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "method" ] ;
+        vamp:value "1"^^xsd:float ;
+    ] ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "whiten" ] ;
+        vamp:value "0"^^xsd:float ;
+    ] ;
+    vamp:output <http://vamp-plugins.org/rdf/plugins/qm-vamp-plugins#qm-tempotracker_output_beats> .
diff -r 000000000000 -r e34cf1b6fe09 sonic_annotator/vamp_plugins/tempotracker_tempo_standard.n3
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/sonic_annotator/vamp_plugins/tempotracker_tempo_standard.n3	Sat Feb 20 18:14:24 2016 +0100
@@ -0,0 +1,22 @@
+@prefix xsd:      <http://www.w3.org/2001/XMLSchema#> .
+@prefix vamp:     <http://purl.org/ontology/vamp/> .
+@prefix :         <#> .
+
+:transform a vamp:Transform ;
+    vamp:plugin <http://vamp-plugins.org/rdf/plugins/qm-vamp-plugins#qm-tempotracker> ;
+    vamp:step_size "512"^^xsd:int ; 
+    vamp:block_size "1024"^^xsd:int ; 
+    vamp:plugin_version """5""" ; 
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "dftype" ] ;
+        vamp:value "3"^^xsd:float ;
+    ] ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "method" ] ;
+        vamp:value "1"^^xsd:float ;
+    ] ;
+    vamp:parameter_binding [
+        vamp:parameter [ vamp:identifier "whiten" ] ;
+        vamp:value "0"^^xsd:float ;
+    ] ;
+    vamp:output <http://vamp-plugins.org/rdf/plugins/qm-vamp-plugins#qm-tempotracker_output_tempo> .