Can run from external directory. Outputs CSV. Works with TextGrids.

helpers/utilities.py

@@ -0,0 +1,171 @@
+# Copyright (c) 2014 Joseph Keshet, Morgan Sonderegger, Thea Knowles
+#
+# This file is part of Autovot, a package for automatic extraction of
+# voice onset time (VOT) from audio files.
+#
+# Autovot is free software: you can redistribute it and/or modify it
+# under the terms of the GNU Lesser General Public License as
+# published by the Free Software Foundation, either version 3 of the
+# License, or (at your option) any later version.
+#
+# Autovot 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
+# Lesser General Public License for more details.
+#
+# You should have received a copy of the GNU Lesser General Public
+# License along with Autovot.  If not, see
+# <http://www.gnu.org/licenses/>.
+#
+
+import subprocess
+import random
+import logging
+import wave
+import tempfile
+import os
+
+
+def csv_append_row(tmp_preds, preds_filename, with_headers=True):
+
+    if with_headers:
+        skip_header = True
+
+    all_lines = list()
+
+    # check if the CSV file exists
+    if os.path.isfile(preds_filename):
+        # read it lines
+        for line in open(preds_filename, 'r'):
+            all_lines.append(line)
+    else:
+        # if the file does not exist it does not have headers and they should be copied
+        skip_header = False
+
+    # check if there is a header
+    for line in open(tmp_preds, 'r'):
+        if skip_header:
+            skip_header = False
+        else:
+            all_lines.append(line)
+    # now dump everything back
+    with open(preds_filename, 'w') as f:
+        for line in all_lines:
+            f.write(line)
+
+
+
+def generate_tmp_filename():
+    return tempfile._get_default_tempdir() + "/" + next(tempfile._get_candidate_names()) + ".txt"
+
+
+def logging_defaults(logging_level="INFO"):
+    logging.basicConfig(level=logging_level, format='%(asctime)s.%(msecs)d [%(filename)s] %(levelname)s: %(message)s',
+                        datefmt='%H:%M:%S')
+
+def num_lines(filename):
+    lines = 0
+    for _ in open(filename, 'rU'):
+        lines += 1
+    return lines
+
+
+def easy_call(command):
+    try:
+        logging.debug(command)
+        return_code = subprocess.call(command, shell=True)
+        if return_code == 127 or return_code < 0:
+            logging.debug('Return code: %d' % return_code)
+            exit(-1)
+    except Exception as exception:
+        logging.error('Could not execute the following:')
+        logging.error(command)
+        logging.error('%s - %s' % (type(exception), exception.args))
+        exit(-1)
+
+
+def random_shuffle_data(in_features_filename, in_labels_filename, out_features_filename, out_labels_filename):
+
+    # open files
+    in_features = open(in_features_filename, 'rU')
+    in_labels = open(in_labels_filename, 'rU')
+
+    # read infra text header
+    header = in_labels.readline()
+    dims = header.split()
+
+    # read file lines
+    lines = list()
+    for x, y in zip(in_features, in_labels):
+        lines.append((x, y))
+    if len(lines) != int(dims[0]):
+        logging.error("Either the feature file and the label file are not the same length of label file missing a "
+                      "header")
+        exit(-1)
+
+    # close files
+    in_features.close()
+    in_labels.close()
+
+    # random shuffle the instances
+    random.shuffle(lines)
+
+    # write back the result
+    out_features = open(out_features_filename, 'w')
+    out_labels = open(out_labels_filename, 'w')
+
+    # write labels header
+    header = "%s %s\n" % (dims[0], dims[1])
+    out_labels.write(header)
+
+    # write data
+    for x, y in lines:
+        out_features.write(x)
+        out_labels.write(y)
+
+    # close files
+    out_features.close()
+    out_labels.close()
+
+    return len(lines)
+
+
+def extract_lines(input_filename, output_filename, lines_range, has_header=False):
+
+    if lines_range[0] >= lines_range[1]:
+        logging.error("Range should be causal.")
+        exit(-1)
+    input_file = open(input_filename, 'rU')
+    output_file = open(output_filename, 'w')
+    if has_header:
+        header = input_file.readline().strip().split()
+        new_header = "%d 2\n" % (lines_range[1]-lines_range[0]+1)
+        output_file.write(new_header)
+    for line_num, line in enumerate(input_file):
+        if lines_range[0] <= line_num <= lines_range[1]:
+            output_file.write(line)
+    input_file.close()
+    output_file.close()
+
+
+def is_textgrid(filename):
+    try:
+        file = open(filename, 'rU')
+        first_line = file.readline()
+    except:
+        return False
+    if "ooTextFile" in first_line:
+        return True
+    return False
+
+
+def is_valid_wav(filename):
+    # check the sampling rate and number bits of the WAV
+    try:
+        wav_file = wave.Wave_read(filename)
+    except:
+        return False
+    if wav_file.getframerate() != 16000 or wav_file.getsampwidth() != 2 or wav_file.getnchannels() != 1 \
+        or wav_file.getcomptype() != 'NONE':
+        return False
+    return True