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3844827505
@ -274,7 +274,6 @@ class Measurement:
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self._qtys = [SIQtys.default() for i in range(self.nchannels)]
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logging.debug(f'Physical quantity data not available in measurement file. Assuming {SIQtys.default}')
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def setAttribute(self, atrname, value):
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"""
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Set an attribute in the measurement file, and keep a local copy in
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@ -632,8 +631,8 @@ class Measurement:
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return False
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def exportAsWave(self, fn=None, force=False, newsampwidth=None,
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normalize=True, **kwargs):
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def exportAsWave(self, fn=None, force=False, dtype=None,
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normalize=False, **kwargs):
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"""Export measurement file as wave. In case the measurement data is
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stored as floats, the values are scaled to the proper integer (PCM)
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data format.
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@ -645,9 +644,8 @@ class Measurement:
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force: If True, overwrites any existing files with the given name
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, otherwise a RuntimeError is raised.
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newsampwidth: sample width in bytes with which to export the data.
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This should only be given in case the measurement data is stored as
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floating point values, otherwise an error is thrown
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dtype: if not None, convert data to this data type.
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Options are 'int16', 'int32', 'float32'.
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normalize: If set: normalize the level to something sensible.
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"""
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@ -661,39 +659,49 @@ class Measurement:
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if os.path.exists(fn) and not force:
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raise RuntimeError(f'File already exists: {fn}')
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if not np.isclose(self.samplerate%1,0):
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raise RuntimeError(f'Sample rates should be approximately integer for exporting to Wave to work')
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# TODO: With VERY large measurment files, this is not possible! Is this
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# a theoretical case?
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# TODO: add sensitivity? Then use self.data() instead of self.rawData()
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data = self.rawData(**kwargs)
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if np.issubdtype(data.dtype, np.floating) and newsampwidth is None:
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raise ValueError('Newsampwidth parameter should be given for floating point raw data')
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if normalize:
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# Scale back to maximum of absolute value
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maxabs = np.max(np.abs(data))
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data = data / maxabs # "data /= maxabs" fails if dtpyes differ
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if newsampwidth is not None:
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# Convert to floats, then to new sample width
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if dtype==None:
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dtype = data.dtype # keep existing
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logging.debug(f"dtype not passed as arg; using dtype = {dtype}")
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# dtype conversion
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if dtype=='int16':
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newtype = np.int16
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newsampwidth = 2
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elif dtype=='int32':
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newtype = np.int32
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newsampwidth = 4
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elif dtype=='float32':
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newtype = np.float32
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elif dtype=='float64':
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newtype = np.float64
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else:
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logging.debug(f"cannot handle this dtype {dtype}")
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pass
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# Convert range to [-1, 1]
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# TODO: this is wrong for float data where full scale > 1
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sensone = np.ones_like(self.sensitivity)
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data = scaleBlockSens(data, sensone)
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if newsampwidth == 2:
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newtype = np.int16
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elif newsampwidth == 4:
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newtype = np.int32
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else:
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raise ValueError('Invalid sample width, should be 2 or 4')
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if dtype=='int16' or dtype=='int32':
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# Scale data to integer range and convert to integers
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scalefac = 2**(8*newsampwidth-1)-1
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# Scale data to integer range, and then convert to integers
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data = (data*scalefac).astype(newtype)
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wavfile.write(fn, int(self.samplerate), data)
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wavfile.write(fn, int(self.samplerate), data.astype(newtype))
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@staticmethod
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def fromtxt(fn,
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