More checks on refMeas. Renamed method refMeas to getRefMeas. Added removeRefMeas. Stabilized API?
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@ -372,7 +372,7 @@ class Measurement:
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if ext != DOTMEXT:
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newname = newname + DOTMEXT
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newname_full = str(pathlib.Path(self.folder) / newname )
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newname_full = str(pathlib.Path(self.folder) / newname)
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os.rename(self.fn, newname_full)
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def genNewUUID(self):
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@ -388,7 +388,7 @@ class Measurement:
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"""
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return self._UUID
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def refMeas(self, mtype: MeasurementType):
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def getRefMeas(self, mtype: MeasurementType):
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"""
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Return corresponding reference measurement, if configured and can be found. If the reference
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measurement is currently not open, it tries to open it by traversing other measurement
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@ -402,30 +402,66 @@ class Measurement:
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except KeyError:
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raise ValueError(f"No reference measurement configured for '{self.name}'")
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m = None
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# Try to find it in the dictionary of of open measurements
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if required_uuid in Measurement.uuid_s.keys():
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m = Measurement.uuid_s[required_uuid]
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logging.info(f'Returned reference measurement {m.name} from list of open measurements')
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return m
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# See if we can open it using its last stored file name
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# Not found in list of openend measurements. See if we can open it using its last stored file name we know of
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if m is None:
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try:
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m = Measurement(possible_name)
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if m.UUID == required_uuid:
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logging.info(f'Opened reference measurement {m.name} by name')
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return m
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except Exception as e:
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logging.error(f'Could not find reference measurement using file name: {possible_name}')
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# Last resort, see if we can find the measurement in the same folder
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# Last resort, see if we can find the right measurement in the same folder
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if m is None:
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try:
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m = Measurement.fromFolderWithUUID(required_uuid, self.folder, skip=[self.name])
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logging.info('Found reference measurement in folder with correct UUID. Updating name of reference measurement')
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# Update the measurement file name in the list, such that next time it
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# can be opened just by its name.
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self.setRefMeas(m)
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return m
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except:
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logging.error("Could not find the reference measurement. Is it deleted?")
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raise RuntimeError("Could not find reference measurement")
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# Well, we found it. Now make sure the reference measurement actually has the right type (User could have marked it as a NotSpecific for example in the mean time).
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if m is not None:
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if m.measurementType() != mtype:
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m.removeRefMeas(mtype)
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raise RuntimeError(f"Reference measurement for {self.name} is not a proper reference (anymore).")
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# Whow, we passed all security checks, here we go!
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return m
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else:
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# Nope, not there.
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raise RuntimeError(f"Could not find the reference measurement for '{self.name}'. Is it deleted?")
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def removeRefMeas(self, mtype: MeasurementType):
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"""
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Remove an existing reference measurement of specified type from this measurement. Silently ignores this
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action if no reference measurement of this type is configured.
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"""
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try:
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del self._refMeas[mtype]
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self.__storeReafMeas()
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except KeyError:
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pass
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def __storeReafMeas(self):
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"""
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Internal method that syncs the dictionary of reference methods with the backing HDF5 file
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"""
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with self.file("r+") as f:
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# Update attribute in file. Stored as a flat list of string tuples:
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# [(ref_value1, uuid_1, name_1), (ref_value2, uuid_2, name_2), ...]
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reflist = list((str(key.value), val1, val2) for key, (val1, val2) in self._refMeas.items())
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# print(reflist)
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f.attrs['refMeas'] = reflist
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def setRefMeas(self, m: Measurement):
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"""
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@ -438,12 +474,7 @@ class Measurement:
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raise ValueError('Measurement to be set as reference is not a reference measurement')
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self._refMeas[mtype] = (m.UUID, m.name)
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with self.file("r+") as f:
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# Update attribute in file. Stored as a flat list of string tuples:
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# [(ref_value1, uuid_1, name_1), (ref_value2, uuid_2, name_2), ...]
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reflist = list((str(key.value), val1, val2) for key, (val1, val2) in self._refMeas.items())
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# print(reflist)
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f.attrs['refMeas'] = reflist
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self.__storeReafMeas()
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@staticmethod
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def fromFolderWithUUID(uuid_str: str, folder: str='', skip=[]):
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@ -657,13 +688,13 @@ class Measurement:
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Nblock = block.shape[0]
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sum_ += np.sum(block, axis=0)
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N += Nblock
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meansquare += np.sum(block**2, axis=0) / self.N
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meansquare += np.sum(block ** 2, axis=0) / self.N
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avg = sum_ / N
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# In fact, this is not the complete RMS, as in includes the DC
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# If p = p_dc + p_osc, then rms(p_osc) = sqrt(ms(p)-ms(p_dc))
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if substract_average:
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meansquare -= avg**2
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meansquare -= avg ** 2
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rms = np.sqrt(meansquare)
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return rms
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@ -768,7 +799,7 @@ class Measurement:
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signal = self.data(channels)
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# Estimate noise power in block
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blocks = [signal[i * N : (i + 1) * N] for i in range(Nblocks)]
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blocks = [signal[i * N: (i + 1) * N] for i in range(Nblocks)]
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if noiseCorrection:
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# The difference between the measured signal in the previous block and
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@ -972,10 +1003,11 @@ class Measurement:
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raise ValueError(f"File {fn} does not exist.")
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if timestamp is None:
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timestamp = os.path.getmtime(fn)
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if mfn is None:
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mfn = os.path.splitext(fn)[0] + ".h5"
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mfn = os.path.splitext(fn)[0] + DOTMEXT
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else:
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mfn = os.path.splitext(mfn)[0] + ".h5"
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mfn = os.path.splitext(mfn)[0] + DOTMEXT
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dat = np.loadtxt(fn, skiprows=skiprows, delimiter=delimiter)
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if firstcoltime:
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