diff dml-cla/python/semitone_hist.py @ 0:718306e29690 tip

commiting public release
author Daniel Wolff
date Tue, 09 Feb 2016 21:05:06 +0100
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--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/dml-cla/python/semitone_hist.py	Tue Feb 09 21:05:06 2016 +0100
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+# Part of DML (Digital Music Laboratory)
+# Copyright 2014-2015 Steven Hargreaves; Samer Abdallah, University of London
+ 
+# 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, abdallahs"
+
+import sys
+from csvutils import *
+from pitchutils import *
+from aggregate import *
+from rdflib   import RDF, RDFS
+from rdfutils import parse_xsd_duration, event_ns, tl_ns, af_ns
+from n3Parser import get_rdf_graph_from_n3
+
+# map from pitch names to pitch class numbers in 0..11
+pitch_map = { pitch_name(i,oct):i for oct in range(0,9) for i in range(0,12) }
+
+# data conversions to a list of (pitch_name:string,duration:float) pairs representation
+
+def transcription_from_csv(filename):
+    # we assume format time, duration, pitch, velocity, note_name 
+    return csv_map_rows(filename,5,lambda row:(row[4],float(row[1])))
+
+def transcription_from_n3(filename):
+    graph=get_rdf_graph_from_n3(filename)
+    notes = [ ( graph.value(ev, RDFS.label),
+                parse_xsd_duration(graph.value(graph.value(ev,event_ns.time), tl_ns.duration)) )
+              for ev in subject((RDF.type, af_ns.Note)) ]
+
+def notes_histogram(notes):
+    hist = 12*[0]
+    for note in notes: hist[pitch_map[note[0]]] += note[1]
+    return hist
+
+# Compute aggregate pitch histogram from a list of input transcriptions.
+def aggregate(transcriptions):
+    parser_table = { 'n3':transcription_from_n3, 
+                     'csv':transcription_from_csv }
+
+    hist = 12*[0] # will be aggragate histogram
+    def accum(f):
+        h = notes_histogram(decode_tagged(parser_table,f))
+        total = sum(h)
+        for x in range(0, 12): hist[x] += h[x]/total
+    stats=for_each(transcriptions,accum)
+    return { 'result': discrete_hist(pitch_class_names,hist), 'stats':stats }