comparison pyspark/transforms/tonicHistogram.py @ 0:e34cf1b6fe09 tip

commit

+# 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)