Mercurial > hg > dml-open-cliopatria
comparison dml-cla/python/tonic_norm_semitone_hist.py @ 0:718306e29690 tip
commiting public release
author | Daniel Wolff |
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date | Tue, 09 Feb 2016 21:05:06 +0100 |
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-1:000000000000 | 0:718306e29690 |
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1 # Part of DML (Digital Music Laboratory) | |
2 # Copyright 2014-2015 Steven Hargreaves; Samer Abdallah, University of London | |
3 | |
4 # This program is free software; you can redistribute it and/or | |
5 # modify it under the terms of the GNU General Public License | |
6 # as published by the Free Software Foundation; either version 2 | |
7 # of the License, or (at your option) any later version. | |
8 # | |
9 # This program is distributed in the hope that it will be useful, | |
10 # but WITHOUT ANY WARRANTY; without even the implied warranty of | |
11 # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the | |
12 # GNU General Public License for more details. | |
13 # | |
14 # You should have received a copy of the GNU General Public | |
15 # License along with this library; if not, write to the Free Software | |
16 # Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA | |
17 | |
18 # -*- coding: utf-8 -*- | |
19 __author__="hargreavess, abdallahs, wolffd" | |
20 | |
21 import sys | |
22 from csvutils import * | |
23 from pitchutils import * | |
24 from aggregate import * | |
25 from rdflib import RDF, RDFS | |
26 from rdfutils import parse_xsd_duration, event_ns, tl_ns, af_ns | |
27 from n3Parser import get_rdf_graph_from_n3 | |
28 from semitone_hist import notes_histogram, transcription_from_csv, transcription_from_n3 | |
29 from key_tonic_hist import tonic_from_n3, tonic_from_csv | |
30 | |
31 # Compute aggregate pitch histogram from a list of input transcriptions. | |
32 def aggregate(transcriptions_tonics,opts): | |
33 parser_table = { 'n3':transcription_from_n3, | |
34 'csv':transcription_from_csv } | |
35 | |
36 hist = 12*[0] # will be aggragate histogram | |
37 def add_no_norm(h): | |
38 for x in range(0, 12): hist[x] += h[x] | |
39 | |
40 def add_norm(h): | |
41 total=sum(h) | |
42 for x in range(0, 12): hist[x] += h[x]/total | |
43 | |
44 if opts['normalisation']=='piece': add_to_hist=add_norm | |
45 else: add_to_hist=add_no_norm | |
46 | |
47 def accum(f): | |
48 # subtract 1 from tonic because tonic_from_csv uses range 1 to 12 whilst this script uses 0 to 11 | |
49 add_to_hist( rotate_left( notes_histogram(decode_tagged(parser_table,f['transcription'])), | |
50 argmax(find_tonic_histogram(f['tonic']['value'],f['duration'])))) | |
51 | |
52 # do_stuff | |
53 stats=for_each(transcriptions_tonics,accum) | |
54 return { 'result': discrete_hist([str(i) for i in range(1,13)],hist), 'stats':stats } | |
55 | |
56 def rotate_left(x,n): return x[n:]+x[:n] | |
57 | |
58 def argmax(x): return max(range(0,len(x)),key=x.__getitem__) | |
59 | |
60 # Parse the qm-keydetector_tonic csv file, and generate | |
61 # a tonic histogram | |
62 def find_tonic_histogram(input_f_file,duration): | |
63 tonic_hist = 12*[0] | |
64 # ['time','keynr','label'] -> [time:float, keynr:in(range(0,12))] | |
65 data = csv_map_columns(input_f_file,3,[lambda r:float(r[0]), lambda r:int(r[1])-1]) | |
66 | |
67 # build duration weighted histogram | |
68 for idx in range(1,len(data[0]) ): | |
69 tonic_hist[data[1][idx-1]] += data[0][idx] - data[0][idx-1] | |
70 | |
71 # add last tonic if duration is given | |
72 if duration>0: | |
73 tonic_hist[data[1][-1]] += duration - data[0][-1] | |
74 | |
75 return tonic_hist | |
76 |