forked from platypush/platypush
Removed/commented references to numpy.typing
.
That module isn't available yet on the numpy version installed on Debian `oldstable`.
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parent
193314fcd0
commit
23e53f13f0
7 changed files with 17 additions and 29 deletions
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@ -2,7 +2,6 @@ from abc import ABC, abstractmethod
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from typing import Optional, Tuple
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import numpy as np
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from numpy.typing import NDArray
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from ._parser import SoundParser
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@ -31,7 +30,7 @@ class SoundBase(SoundParser, ABC):
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t_start: float = 0,
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t_end: float = 0,
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**_,
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) -> NDArray[np.floating]:
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): # -> NDArray[np.floating]:
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"""
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Get the wave binary data associated to this sound
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@ -50,7 +49,7 @@ class SoundBase(SoundParser, ABC):
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t_end: float = 0.0,
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freq_range: Optional[Tuple[float, float]] = None,
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freq_buckets: Optional[int] = None,
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) -> NDArray[np.floating]:
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): # -> NDArray[np.floating]:
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"""
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Get the real part of the Fourier transform associated to a time-bounded
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sample of this sound.
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@ -4,9 +4,6 @@ from threading import Thread
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from time import time
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from typing import Any, Callable, Optional
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import numpy as np
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from numpy.typing import NDArray
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from ._mix import Mix
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@ -20,7 +17,7 @@ class AudioGenerator(Thread):
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def __init__(
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self,
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*args,
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audio_queue: Queue[NDArray[np.number]],
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audio_queue: Queue, # Queue[NDArray[np.number]],
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mix: Mix,
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blocksize: int,
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sample_rate: int,
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@ -3,7 +3,6 @@ import logging
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from typing import List, Tuple, Union
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import numpy as np
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from numpy.typing import DTypeLike, NDArray
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from ...._utils import convert_nd_array
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from ._base import SoundBase
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@ -16,7 +15,7 @@ class Mix(SoundBase):
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through an audio stream to an audio device
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"""
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def __init__(self, *sounds, channels: int, dtype: DTypeLike, **kwargs):
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def __init__(self, *sounds, channels: int, dtype, **kwargs):
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super().__init__(**kwargs)
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self._sounds: List[Sound] = []
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self.logger = logging.getLogger(__name__)
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@ -64,7 +63,7 @@ class Mix(SoundBase):
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normalize_range: Tuple[float, float] = (-1.0, 1.0),
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on_clip: str = 'scale',
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**_,
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) -> NDArray[np.number]:
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): # -> NDArray[np.number]:
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wave = None
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for sound in self._sounds:
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@ -4,9 +4,6 @@ from typing import Callable, Optional
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import sounddevice as sd
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import numpy as np
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from numpy.typing import NDArray
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# pylint: disable=too-few-public-methods
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class AudioOutputCallback:
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@ -18,7 +15,7 @@ class AudioOutputCallback:
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def __init__(
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self,
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*args,
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audio_queue: Queue[NDArray[np.number]],
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audio_queue: Queue, # Queue[NDArray[np.number]],
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channels: int,
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blocksize: int,
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should_stop: Callable[[], bool] = lambda: False,
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@ -50,7 +47,8 @@ class AudioOutputCallback:
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assert not status.output_underflow, 'Output underflow: increase blocksize?'
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assert not status, f'Audio callback failed: {status}'
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def _audio_callback(self, outdata: NDArray[np.number], frames: int, status):
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# outdata: NDArray[np.number]
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def _audio_callback(self, outdata, frames: int, status):
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if self._is_paused():
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return
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@ -72,7 +70,8 @@ class AudioOutputCallback:
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outdata[:audio_length] = data[:audio_length]
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# _ = time
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def __call__(self, outdata: NDArray[np.number], frames: int, _, status):
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# outdata: NDArray[np.number]
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def __call__(self, outdata, frames: int, _, status):
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try:
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self._audio_callback(outdata, frames, status)
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except AssertionError as e:
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@ -3,9 +3,7 @@ from queue import Queue
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from threading import Event
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from typing import Any, Generator, Iterable, Optional, Type
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import numpy as np
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import sounddevice as sd
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from numpy.typing import DTypeLike, NDArray
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from ...._model import AudioState
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from ..._player import AudioPlayer
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@ -26,7 +24,7 @@ class AudioSynthPlayer(AudioPlayer):
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*args,
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volume: float,
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channels: int,
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dtype: DTypeLike,
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dtype, # : DTypeLike,
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sounds: Optional[Iterable[Sound]] = None,
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**kwargs
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):
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@ -36,7 +34,7 @@ class AudioSynthPlayer(AudioPlayer):
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super().__init__(*args, volume=volume, channels=channels, dtype=dtype, **kwargs)
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self._generator_stopped = Event()
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self._completed_callback_event = Event()
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self._audio_queue: Queue[NDArray[np.number]] = Queue(
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self._audio_queue = Queue( # Queue[NDArray[np.number]]
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maxsize=self.queue_size or 0
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)
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@ -1,9 +1,8 @@
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from enum import Enum
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import json
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from typing import Final, Optional, Tuple, Union
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from typing import Final, Optional, Union
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import numpy as np
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from numpy.typing import NDArray
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from ._base import SoundBase
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@ -103,7 +102,7 @@ class Sound(SoundBase):
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def _get_audio_pad(
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self, sample_rate: float, t_start: float, t_end: float
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) -> Tuple[NDArray[np.floating], NDArray[np.floating]]:
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): # -> Tuple[NDArray[np.floating], NDArray[np.floating]]:
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"""
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Return the left and right audio pads for a given audio length as a
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``(left, right)`` tuple of numpy zero-filled arrays.
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@ -120,7 +119,7 @@ class Sound(SoundBase):
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)
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)
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def _generate_wave(self, x: NDArray[np.floating]):
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def _generate_wave(self, x):
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"""
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Generate a raw audio wave as a numpy array of floating between -1 and 1
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given ``x`` as a set of timestamp samples.
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@ -149,7 +148,7 @@ class Sound(SoundBase):
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t_start: float = 0,
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t_end: float = 0,
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**_,
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) -> NDArray[np.floating]:
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): # -> NDArray[np.floating]:
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"""
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Get the wave binary data associated to this sound
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@ -1,10 +1,7 @@
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import numpy as np
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from numpy.typing import DTypeLike, NDArray
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def convert_nd_array( # pylint: disable=too-many-return-statements
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wave: NDArray[np.floating], dtype: DTypeLike
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) -> NDArray[np.number]:
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def convert_nd_array(wave, dtype): # pylint: disable=too-many-return-statements
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"""
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Given a wave as a series of floating point numbers, convert them to the
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appropriate data type.
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