annotate dml-cla/python/key_tonic_hist.py @ 0:718306e29690 tip

commiting public release
author Daniel Wolff
date Tue, 09 Feb 2016 21:05:06 +0100
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Daniel@0 1 # Part of DML (Digital Music Laboratory)
Daniel@0 2 # Copyright 2014-2015 Samer Abdallah, University College London
Daniel@0 3
Daniel@0 4 # This program is free software; you can redistribute it and/or
Daniel@0 5 # modify it under the terms of the GNU General Public License
Daniel@0 6 # as published by the Free Software Foundation; either version 2
Daniel@0 7 # of the License, or (at your option) any later version.
Daniel@0 8 #
Daniel@0 9 # This program is distributed in the hope that it will be useful,
Daniel@0 10 # but WITHOUT ANY WARRANTY; without even the implied warranty of
Daniel@0 11 # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
Daniel@0 12 # GNU General Public License for more details.
Daniel@0 13 #
Daniel@0 14 # You should have received a copy of the GNU General Public
Daniel@0 15 # License along with this library; if not, write to the Free Software
Daniel@0 16 # Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
Daniel@0 17
Daniel@0 18 # -*- coding: utf-8 -*-
Daniel@0 19 __author__="samer"
Daniel@0 20
Daniel@0 21 from rdfutils import *
Daniel@0 22 from n3Parser import *
Daniel@0 23 from pitchutils import *
Daniel@0 24 from aggregate import *
Daniel@0 25 from csvutils import csv_map_rows
Daniel@0 26 from warnings import warn
Daniel@0 27
Daniel@0 28 def tonic_from_n3(filename):
Daniel@0 29 graph=get_rdf_graph_from_n3(filename)
Daniel@0 30 max_time = 0
Daniel@0 31 tonic = None
Daniel@0 32 for ev, time in graph.subjects_objects(ev_ns.time):
Daniel@0 33 t = parse_xsd_duration(graph.value(time,tl_ns.at))
Daniel@0 34 if t>max_time: tonic = graph.value(ev,af_ns.feature)
Daniel@0 35 return tonic-1
Daniel@0 36
Daniel@0 37 def tonic_from_csv(filename):
Daniel@0 38 # format: time, pitch_class_number, pitch_class_name
Daniel@0 39 return int(csv_map_rows(filename,3,lambda row:row[1])[-1])-1
Daniel@0 40
Daniel@0 41
Daniel@0 42 def aggregate(inputs):
Daniel@0 43 parser_table = { 'n3':tonic_from_n3,
Daniel@0 44 'csv':tonic_from_csv }
Daniel@0 45 hist = 12*[0]
Daniel@0 46 def accum(f): hist[decode_tagged(parser_table,f)] += 1
Daniel@0 47 stats=for_each(inputs,accum)
Daniel@0 48 return { 'result': discrete_hist(pitch_class_names,hist), 'stats':stats }