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1#!/usr/bin/env python3
2#
3#   Copyright 2017 - The Android Open Source Project
4#
5#   Licensed under the Apache License, Version 2.0 (the "License");
6#   you may not use this file except in compliance with the License.
7#   You may obtain a copy of the License at
8#
9#       http://www.apache.org/licenses/LICENSE-2.0
10#
11#   Unless required by applicable law or agreed to in writing, software
12#   distributed under the License is distributed on an "AS IS" BASIS,
13#   WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
14#   See the License for the specific language governing permissions and
15#   limitations under the License.
16"""This module provides abstraction of audio data."""
17
18import contextlib
19import copy
20import numpy
21import struct
22from io import StringIO
23"""The dict containing information on how to parse sample from raw data.
24
25Keys: The sample format as in aplay command.
26Values: A dict containing:
27    message: Human-readable sample format.
28    dtype_str: Data type used in numpy dtype.  Check
29               https://docs.scipy.org/doc/numpy/reference/arrays.dtypes.html
30               for supported data type.
31    size_bytes: Number of bytes for one sample.
32"""
33SAMPLE_FORMATS = dict(
34    S32_LE=dict(
35        message='Signed 32-bit integer, little-endian',
36        dtype_str='<i',
37        size_bytes=4),
38    S16_LE=dict(
39        message='Signed 16-bit integer, little-endian',
40        dtype_str='<i',
41        size_bytes=2))
42
43
44def get_maximum_value_from_sample_format(sample_format):
45    """Gets the maximum value from sample format.
46
47    Args:
48        sample_format: A key in SAMPLE_FORMAT.
49
50    Returns:The maximum value the sample can hold + 1.
51
52    """
53    size_bits = SAMPLE_FORMATS[sample_format]['size_bytes'] * 8
54    return 1 << (size_bits - 1)
55
56
57class AudioRawDataError(Exception):
58    """Error in AudioRawData."""
59    pass
60
61
62class AudioRawData(object):
63    """The abstraction of audio raw data.
64
65    @property channel: The number of channels.
66    @property channel_data: A list of lists containing samples in each channel.
67                            E.g., The third sample in the second channel is
68                            channel_data[1][2].
69    @property sample_format: The sample format which should be one of the keys
70                             in audio_data.SAMPLE_FORMATS.
71    """
72
73    def __init__(self, binary, channel, sample_format):
74        """Initializes an AudioRawData.
75
76        Args:
77            binary: A string containing binary data. If binary is not None,
78                       The samples in binary will be parsed and be filled into
79                       channel_data.
80            channel: The number of channels.
81            sample_format: One of the keys in audio_data.SAMPLE_FORMATS.
82        """
83        self.channel = channel
84        self.channel_data = [[] for _ in range(self.channel)]
85        self.sample_format = sample_format
86        if binary:
87            self.read_binary(binary)
88
89    def read_binary(self, binary):
90        """Reads samples from binary and fills channel_data.
91
92        Reads samples of fixed width from binary string into a numpy array
93        and shapes them into each channel.
94
95        Args:
96            binary: A string containing binary data.
97        """
98        sample_format_dict = SAMPLE_FORMATS[self.sample_format]
99
100        # The data type used in numpy fromstring function. For example,
101        # <i4 for 32-bit signed int.
102        np_dtype = '%s%d' % (sample_format_dict['dtype_str'],
103                             sample_format_dict['size_bytes'])
104
105        # Reads data from a string into 1-D array.
106        np_array = numpy.fromstring(binary, dtype=np_dtype)
107
108        n_frames = len(np_array) / self.channel
109        # Reshape np_array into an array of shape (n_frames, channel).
110        np_array = np_array.reshape(int(n_frames), self.channel)
111        # Transpose np_arrya so it becomes of shape (channel, n_frames).
112        self.channel_data = np_array.transpose()
113