def smallDataTest():
breakPrint()
generalPrint("testsSpectralCalc", "Running test function: smallDataTest")
# read in data
reader = DataReaderATS(atsPath)
startTime1 = "2016-02-21 03:00:00"
stopTime1 = "2016-02-21 03:30:00"
timeData = reader.getPhysicalData(startTime1, stopTime1)
timeData.printInfo()
# now let's try the calibrator
cal = Calibrator(calPath)
cal.printInfo()
sensors = reader.getSensors(timeData.chans)
serials = reader.getSerials(timeData.chans)
choppers = reader.getChoppers(timeData.chans)
timeData = cal.calibrate(timeData, sensors, serials, choppers)
timeData.printInfo()
specCal = SpectrumCalculator(timeData.sampleFreq, timeData.numSamples)
specData = specCal.calcFourierCoeff(timeData)
specData.printInfo()
fig = plt.figure(figsize=(10, 10))
specData.view(fig=fig, label="Raw spectral data")
# now let's try and process something
sproc = SignalProcessor()
timeData2 = reader.getPhysicalData(startTime1, stopTime1)
timeData2 = cal.calibrate(timeData2, sensors, serials, choppers)
timeData2 = sproc.notchFilter(timeData2, 50.0)
timeData2 = sproc.notchFilter(timeData2, 16.6667)
specData2 = specCal.calcFourierCoeff(timeData2)
specData2.printInfo()
specData2.view(fig=fig, label="Notch filtered")
# set plot properties
fig.tight_layout(rect=[0, 0.02, 1, 0.96])
addLegends(fig)
plt.show()
def testRemoveNans():
breakPrint()
generalPrint("testsSignalProcess", "Running test function: testRemoveNans")
# read in data
spamReader = DataReaderSPAM(spamPath)
spamReader.printInfo()
# now get some data
startTime = "2016-02-07 02:30:00"
stopTime = "2016-02-07 02:35:00"
timeData = spamReader.getPhysicalData(startTime, stopTime)
timeData.printInfo()
numSamples = timeData.numSamples
# let's set some samples to zero
sampleStart = int(0.3 * numSamples)
sampleStop = int(0.4 * numSamples)
for c in timeData.chans:
timeData.data[c][sampleStart:sampleStop] = np.nan
# now plot
timeDataProcessed = copy.deepcopy(timeData)
timeDataProcessed.data = removeNans(timeDataProcessed.data)
fig = plt.figure(figsize=(20, 10))
timeData.view(sampleStop=timeData.numSamples, fig=fig, label="With nans")
timeDataProcessed.view(sampleStop=timeData.numSamples,
fig=fig,
label="Without nans")
fig.tight_layout(rect=[0, 0.02, 1, 0.96])
addLegends(fig)
plt.show()
def plotTest():
breakPrint()
generalPrint("testsSignalProcess", "Running test function: plotTest")
# read in data
atsReader = DataReaderATS(atsPath)
# now get some data
startTime1 = "2016-02-21 03:00:00"
stopTime1 = "2016-02-21 03:05:00"
timeData1 = atsReader.getPhysicalData(startTime1, stopTime1)
timeData1.printInfo()
# get a second set of data
startTime2 = "2016-02-21 03:03:00"
stopTime2 = "2016-02-21 03:05:00"
timeData2 = atsReader.getPhysicalData(startTime2, stopTime2)
timeData2.printInfo()
# now plot
fig = plt.figure(figsize=(20, 10))
timeData1.view(sampleStop=timeData1.numSamples - 1,
fig=fig,
xlim=[timeData1.startTime, timeData2.stopTime])
timeData2.view(sampleStop=timeData2.numSamples - 1,
fig=fig,
xlim=[timeData1.startTime, timeData2.stopTime])
fig.tight_layout(rect=[0, 0.02, 1, 0.96])
addLegends(fig)
plt.show()
def testResample():
breakPrint()
generalPrint("testsSignalProcess", "Running test function: testResample")
# read in data
spamReader = DataReaderSPAM(spamPath)
# now get some data
startTime = "2016-02-07 02:00:00"
stopTime = "2016-02-07 03:00:00"
# let's get some unscaled data
timeData = spamReader.getUnscaledData(startTime, stopTime)
timeData.printInfo()
timeDataSave = copy.deepcopy(timeData)
timeData.printInfo()
# now do some signal processing
sproc = SignalProcessor()
timeData = sproc.resample(timeData, 50)
timeData.printInfo()
# now let's plot and see what happens
fig = plt.figure(figsize=(20, 10))
x = timeData.getDateArray()
xlim = [timeDataSave.startTime, x[4000]]
timeDataSave.view(sampleStop=20000, fig=fig, xlim=xlim, label="Raw data")
timeData.view(sampleStop=4000, fig=fig, xlim=xlim, label="Resampled data")
fig.tight_layout(rect=[0, 0.02, 1, 0.96])
addLegends(fig)
plt.show()
def hpFilterTest():
breakPrint()
generalPrint("testsSignalProcess", "Running test function: hpFilterTest")
# read in data
atsReader = DataReaderATS(atsPath)
# now get some data
startTime = "2016-02-21 03:00:00"
stopTime = "2016-02-21 04:00:00"
timeData = atsReader.getPhysicalData(startTime, stopTime)
timeDataSave = copy.deepcopy(timeData)
timeData.printInfo()
# now do some signal processing
sproc = SignalProcessor()
timeData = sproc.highPass(timeData, 24)
timeData.printInfo()
# now let's plot and see what happens
fig = plt.figure(figsize=(20, 10))
timeDataSave.view(fig=fig, label="Raw data")
timeData.view(fig=fig, label="High pass filtered")
fig.tight_layout(rect=[0, 0.02, 1, 0.96])
addLegends(fig)
plt.show()
def testCompareSpectra():
breakPrint()
generalPrint("testsWindowDecimate",
"Running test function: testCompareSpectra")
# read in no notch
specReader = SpectrumReader(specPath)
specReader.openBinaryForReading("spectra", 0)
numWindows = specReader.getNumWindows()
specReader.printInfo()
win = int(numWindows / 2)
fig = plt.figure(figsize=(14, 10))
specData = specReader.readBinaryWindowLocal(win)
specData.printInfo()
specData.view(fig=fig, label="No notch")
# now the notched version
specReader = SpectrumReader(specPathNotch)
specReader.openBinaryForReading("spectra", 0)
specDataNotch = specReader.readBinaryWindowLocal(win)
specDataNotch.printInfo()
specDataNotch.view(fig=fig, label="Notched")
# plot
fig.tight_layout(rect=[0, 0.02, 1, 0.96])
addLegends(fig)
plt.show()
def testFillGap():
breakPrint()
generalPrint("testsSignalProcess", "Running test function: testFillGap")
# read in data
atsReader = DataReaderATS(atsPath)
# now get some data
startTime1 = "2016-02-21 03:00:00"
stopTime1 = "2016-02-21 03:08:00"
timeData1 = atsReader.getPhysicalData(startTime1, stopTime1)
# more data
startTime2 = "2016-02-21 03:10:00"
stopTime2 = "2016-02-21 03:15:00"
timeData2 = atsReader.getPhysicalData(startTime2, stopTime2)
# now do some signal processing
sproc = SignalProcessor()
timeData = sproc.fillGap(timeData1, timeData2)
timeData.printInfo()
# now let's plot and see what happens
fig = plt.figure(figsize=(20, 10))
x = timeData.getDateArray()
xlim = [timeData1.startTime, timeData2.stopTime]
timeData.view(sampleStop=timeData.numSamples - 1,
fig=fig,
xlim=xlim,
label="Gap filled")
timeData1.view(sampleStop=timeData1.numSamples - 1,
fig=fig,
xlim=xlim,
label="Section1")
timeData2.view(sampleStop=timeData2.numSamples - 1,
fig=fig,
xlim=xlim,
label="Section2")
fig.tight_layout(rect=[0, 0.02, 1, 0.96])
addLegends(fig)
plt.show()
# now test with spam data
spamReader = DataReaderSPAM(spamPath)
# now get some data
startTime1 = "2016-02-07 02:00:00"
stopTime1 = "2016-02-07 02:08:00"
timeData1 = spamReader.getPhysicalData(startTime1, stopTime1)
# more data
startTime2 = "2016-02-07 02:10:00"
stopTime2 = "2016-02-07 02:15:00"
timeData2 = spamReader.getPhysicalData(startTime2, stopTime2)
# now do some signal processing
sproc = SignalProcessor()
timeData = sproc.fillGap(timeData1, timeData2)
timeData.printInfo()
# now let's plot and see what happens
fig = plt.figure(figsize=(20, 10))
x = timeData.getDateArray()
xlim = [timeData1.startTime, timeData2.stopTime]
timeData.view(sampleStop=timeData.numSamples - 1,
fig=fig,
xlim=xlim,
label="Gap filled")
timeData1.view(sampleStop=timeData1.numSamples - 1,
fig=fig,
xlim=xlim,
label="Section1")
timeData2.view(sampleStop=timeData2.numSamples - 1,
fig=fig,
xlim=xlim,
label="Section2")
fig.tight_layout(rect=[0, 0.02, 1, 0.96])
addLegends(fig)
plt.show()