Merge branch 'develop' into channel_metadata
This commit is contained in:
commit
3e2e8c8953
@ -71,7 +71,7 @@ if(CMAKE_SYSTEM_NAME STREQUAL "Windows")
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link_directories(C:\\mingw\\lib)
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link_directories(C:\\mingw\\bin)
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link_directories(..\\rtaudio)
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link_directories(C:\\Users\\librewin7\\Miniconda3)
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link_directories(C:\\Users\\User\\Miniconda3)
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else()
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set(win32 false)
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set(CMAKE_C_FLAGS "${CMAKE_C_FLAGS} -fPIC -std=c11 \
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@ -3,7 +3,7 @@
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"""
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Description: Read data from image stream and record sound at the same time
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"""
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import cv2 as cv
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#import cv2 as cv
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from .lasp_atomic import Atomic
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from threading import Thread, Condition, Lock
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import numpy as np
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@ -73,7 +73,7 @@ class AvStream:
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rtaudio_inputparams = None
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rtaudio_outputparams = None
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self.nframes_per_block = 512
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self.nframes_per_block = 1024
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if self.duplex_mode or avtype == AvType.audio_output:
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rtaudio_outputparams = {'deviceid': device.index,
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@ -489,6 +489,8 @@ class Measurement:
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firstcoltime: If true, the first column is the treated as the
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sample time.
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"""
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if os.path.splitext(mfn)[1] != '.h5':
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mfn += '.h5'
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if os.path.exists(mfn):
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raise ValueError(f'File {mfn} already exist.')
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if timestamp is None:
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@ -497,6 +499,13 @@ class Measurement:
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if data.ndim != 2:
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data = data[:, np.newaxis]
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try:
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len(sensitivity)
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except:
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raise ValueError('Sensitivity should be given as array-like data type')
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sensitivity = np.asarray(sensitivity)
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nchannels = data.shape[1]
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if nchannels != sensitivity.shape[0]:
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raise ValueError(
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@ -514,3 +523,45 @@ class Measurement:
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compression='gzip')
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ad[0] = data
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return Measurement(mfn)
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@staticmethod
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def fromWaveFile(fn, newfn=None, force=False, timestamp=None):
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"""Convert a measurement file to a wave file, and return the
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measurement handle."""
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if timestamp is None:
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timestamp = int(time.time())
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base_fn = os.path.splitext(fn)[0]
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if newfn is None:
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newfn = base_fn + '.h5'
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if os.path.exists(newfn) and not force:
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raise RuntimeError(f'Measurement file name {newfn} already exists in path, set "force" to true to overwrite')
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with wave.open(fn, 'r') as wf:
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nchannels = wf.getnchannels()
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samplerate = wf.getframerate()
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sensitivity = np.ones(nchannels)
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sampwidth = wf.getsampwidth()
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nframes = wf.getnframes()
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if sampwidth == 2:
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dtype = np.int16
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elif sampwidth == 1:
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dtype = np.int8
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elif sampwidth == 4:
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dtype = np.int32
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with h5.File(newfn, 'w') as hf:
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hf.attrs['samplerate'] = samplerate
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hf.attrs['nchannels'] = nchannels
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hf.attrs['time'] = timestamp
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hf.attrs['blocksize'] = 1
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hf.attrs['sensitivity'] = sensitivity
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data = np.frombuffer(
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wf.readframes(nframes), dtype=dtype).reshape(nframes, nchannels)
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ad = hf.create_dataset('audio', (1, data.shape[0], data.shape[1]),
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dtype=dtype,
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maxshape=(1, data.shape[0], data.shape[1]),
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compression='gzip')
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ad[0] = data
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return Measurement(newfn)
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