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@@ -54,6 +54,12 b' class Audio(DisplayObject):' | |||
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54 | 54 | autoplay : bool |
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55 | 55 | Set to True if the audio should immediately start playing. |
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56 | 56 | Default is `False`. |
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57 | normalize : bool | |
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58 | Whether audio should be normalized (rescaled) to the maximum possible | |
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59 | range. Default is `True`. When set to `False`, `data` must be between | |
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60 | -1 and 1 (inclusive), otherwise an error is raised. | |
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61 | Applies only when `data` is a list or array of samples; other types of | |
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62 | audio are never normalized. | |
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57 | 63 | |
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58 | 64 | Examples |
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59 | 65 | -------- |
@@ -83,7 +89,7 b' class Audio(DisplayObject):' | |||
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83 | 89 | """ |
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84 | 90 | _read_flags = 'rb' |
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85 | 91 | |
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86 | def __init__(self, data=None, filename=None, url=None, embed=None, rate=None, autoplay=False): | |
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92 | def __init__(self, data=None, filename=None, url=None, embed=None, rate=None, autoplay=False, normalize=True): | |
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87 | 93 | if filename is None and url is None and data is None: |
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88 | 94 | raise ValueError("No audio data found. Expecting filename, url, or data.") |
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89 | 95 | if embed is False and url is None: |
@@ -99,7 +105,7 b' class Audio(DisplayObject):' | |||
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99 | 105 | if self.data is not None and not isinstance(self.data, bytes): |
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100 | 106 | if rate is None: |
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101 | 107 | raise ValueError("rate must be specified when data is a numpy array or list of audio samples.") |
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102 | self.data = Audio._make_wav(data, rate) | |
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108 | self.data = Audio._make_wav(data, rate, normalize) | |
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103 | 109 | |
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104 | 110 | def reload(self): |
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105 | 111 | """Reload the raw data from file or URL.""" |
@@ -115,16 +121,16 b' class Audio(DisplayObject):' | |||
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115 | 121 | self.mimetype = "audio/wav" |
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116 | 122 | |
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117 | 123 | @staticmethod |
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118 | def _make_wav(data, rate): | |
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124 | def _make_wav(data, rate, normalize): | |
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119 | 125 | """ Transform a numpy array to a PCM bytestring """ |
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120 | 126 | import struct |
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121 | 127 | from io import BytesIO |
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122 | 128 | import wave |
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123 | 129 | |
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124 | 130 | try: |
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125 | scaled, nchan = Audio._validate_and_normalize_with_numpy(data) | |
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131 | scaled, nchan = Audio._validate_and_normalize_with_numpy(data, normalize) | |
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126 | 132 | except ImportError: |
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127 | scaled, nchan = Audio._validate_and_normalize_without_numpy(data) | |
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133 | scaled, nchan = Audio._validate_and_normalize_without_numpy(data, normalize) | |
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128 | 134 | |
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129 | 135 | fp = BytesIO() |
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130 | 136 | waveobj = wave.open(fp,mode='wb') |
@@ -139,7 +145,7 b' class Audio(DisplayObject):' | |||
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139 | 145 | return val |
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140 | 146 | |
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141 | 147 | @staticmethod |
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142 | def _validate_and_normalize_with_numpy(data): | |
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148 | def _validate_and_normalize_with_numpy(data, normalize): | |
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143 | 149 | import numpy as np |
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144 | 150 | |
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145 | 151 | data = np.array(data, dtype=float) |
@@ -154,21 +160,32 b' class Audio(DisplayObject):' | |||
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154 | 160 | data = data.T.ravel() |
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155 | 161 | else: |
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156 | 162 | raise ValueError('Array audio input must be a 1D or 2D array') |
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157 | scaled = np.int16(data/np.max(np.abs(data))*32767).tolist() | |
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163 | ||
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164 | max_abs_value = np.max(np.abs(data)) | |
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165 | normalization_factor = Audio._get_normalization_factor(max_abs_value, normalize) | |
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166 | scaled = np.int16(data / normalization_factor * 32767).tolist() | |
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158 | 167 | return scaled, nchan |
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159 | 168 | |
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169 | ||
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160 | 170 | @staticmethod |
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161 | def _validate_and_normalize_without_numpy(data): | |
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171 | def _validate_and_normalize_without_numpy(data, normalize): | |
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162 | 172 | try: |
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163 | maxabsvalue = float(max([abs(x) for x in data])) | |
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173 | max_abs_value = float(max([abs(x) for x in data])) | |
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164 | 174 | except TypeError: |
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165 | 175 | raise TypeError('Only lists of mono audio are ' |
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166 | 176 | 'supported if numpy is not installed') |
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167 | 177 | |
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168 | scaled = [int(x/maxabsvalue*32767) for x in data] | |
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178 | normalization_factor = Audio._get_normalization_factor(max_abs_value, normalize) | |
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179 | scaled = [int(x / normalization_factor * 32767) for x in data] | |
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169 | 180 | nchan = 1 |
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170 | 181 | return scaled, nchan |
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171 | 182 | |
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183 | @staticmethod | |
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184 | def _get_normalization_factor(max_abs_value, normalize): | |
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185 | if not normalize and max_abs_value > 1: | |
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186 | raise ValueError('Audio data must be between -1 and 1 when normalize=False.') | |
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187 | return max_abs_value if normalize else 1 | |
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188 | ||
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172 | 189 | def _data_and_metadata(self): |
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173 | 190 | """shortcut for returning metadata with url information, if defined""" |
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174 | 191 | md = {} |
@@ -19,7 +19,10 b' try:' | |||
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19 | 19 | import pathlib |
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20 | 20 | except ImportError: |
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21 | 21 | pass |
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22 | from unittest import mock | |
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22 | from unittest import TestCase, mock | |
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23 | import struct | |
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24 | import wave | |
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25 | from io import BytesIO | |
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23 | 26 | |
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24 | 27 | # Third-party imports |
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25 | 28 | import nose.tools as nt |
@@ -184,25 +187,66 b' def test_audio_from_file():' | |||
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184 | 187 | path = pjoin(dirname(__file__), 'test.wav') |
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185 | 188 | display.Audio(filename=path) |
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186 | 189 | |
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187 | def test_audio_from_numpy_array(): | |
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188 | display.Audio(get_test_tone(), rate=44100) | |
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190 | class TestAudioDataWithNumpy(TestCase): | |
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191 | def test_audio_from_numpy_array(self): | |
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192 | test_tone = get_test_tone() | |
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193 | audio = display.Audio(test_tone, rate=44100) | |
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194 | nt.assert_equal(len(read_wav(audio.data)), len(test_tone)) | |
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189 | 195 | |
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190 |
def test_audio_from_list |
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191 | # Simulate numpy not installed. | |
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192 | with mock.patch('numpy.array', side_effect=ImportError): | |
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193 | display.Audio(list(get_test_tone()), rate=44100) | |
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196 | def test_audio_from_list(self): | |
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197 | test_tone = get_test_tone() | |
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198 | audio = display.Audio(list(test_tone), rate=44100) | |
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199 | nt.assert_equal(len(read_wav(audio.data)), len(test_tone)) | |
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194 | 200 | |
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195 |
def test_audio_from_ |
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196 | # Simulate numpy not installed. | |
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197 | with mock.patch('numpy.array', side_effect=ImportError): | |
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198 | stereo_signal = [list(get_test_tone())] * 2 | |
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199 | nt.assert_raises(TypeError, lambda: display.Audio(stereo_signal, rate=44100)) | |
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200 | ||
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201 | def test_audio_from_numpy_array_without_rate_raises(): | |
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201 | def test_audio_from_numpy_array_without_rate_raises(self): | |
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202 | 202 | nt.assert_raises(ValueError, display.Audio, get_test_tone()) |
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203 | 203 | |
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204 | def get_test_tone(): | |
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205 | return numpy.sin(2 * numpy.pi * 440 * numpy.linspace(0, 1, 44100)) | |
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204 | def test_audio_data_normalization(self): | |
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205 | expected_max_value = numpy.iinfo(numpy.int16).max | |
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206 | for scale in [1, 0.5, 2]: | |
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207 | audio = display.Audio(get_test_tone(scale), rate=44100) | |
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208 | actual_max_value = numpy.max(numpy.abs(read_wav(audio.data))) | |
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209 | nt.assert_equal(actual_max_value, expected_max_value) | |
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210 | ||
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211 | def test_audio_data_without_normalization(self): | |
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212 | max_int16 = numpy.iinfo(numpy.int16).max | |
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213 | for scale in [1, 0.5, 0.2]: | |
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214 | test_tone = get_test_tone(scale) | |
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215 | test_tone_max_abs = numpy.max(numpy.abs(test_tone)) | |
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216 | expected_max_value = int(max_int16 * test_tone_max_abs) | |
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217 | audio = display.Audio(test_tone, rate=44100, normalize=False) | |
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218 | actual_max_value = numpy.max(numpy.abs(read_wav(audio.data))) | |
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219 | nt.assert_equal(actual_max_value, expected_max_value) | |
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220 | ||
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221 | def test_audio_data_without_normalization_raises_for_invalid_data(self): | |
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222 | nt.assert_raises( | |
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223 | ValueError, | |
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224 | lambda: display.Audio([1.001], rate=44100, normalize=False)) | |
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225 | nt.assert_raises( | |
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226 | ValueError, | |
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227 | lambda: display.Audio([-1.001], rate=44100, normalize=False)) | |
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228 | ||
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229 | def simulate_numpy_not_installed(): | |
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230 | return mock.patch('numpy.array', mock.MagicMock(side_effect=ImportError)) | |
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231 | ||
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232 | @simulate_numpy_not_installed() | |
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233 | class TestAudioDataWithoutNumpy(TestAudioDataWithNumpy): | |
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234 | # All tests from `TestAudioDataWithNumpy` are inherited. | |
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235 | ||
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236 | def test_audio_raises_for_nested_list(self): | |
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237 | stereo_signal = [list(get_test_tone())] * 2 | |
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238 | nt.assert_raises( | |
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239 | TypeError, | |
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240 | lambda: display.Audio(stereo_signal, rate=44100)) | |
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241 | ||
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242 | def get_test_tone(scale=1): | |
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243 | return numpy.sin(2 * numpy.pi * 440 * numpy.linspace(0, 1, 44100)) * scale | |
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244 | ||
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245 | def read_wav(data): | |
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246 | with wave.open(BytesIO(data)) as wave_file: | |
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247 | wave_data = wave_file.readframes(wave_file.getnframes()) | |
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248 | num_samples = wave_file.getnframes() * wave_file.getnchannels() | |
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249 | return struct.unpack('<%sh' % num_samples, wave_data) | |
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206 | 250 | |
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207 | 251 | def test_code_from_file(): |
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208 | 252 | c = display.Code(filename=__file__) |
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