def singleSet(temps, motorFreqs, numMeas=10, substance='Water', pauseTime=1, tempTime=120, motorTime=60, countTime=10.0, plotResults = True):
initialize(substance) #Initialize ports, files, and constants (see below)
for temp in temps:
stirFreq = 200.0 #Set stirring speed for bath
setBath(temp, stirFreq, minStableTime=tempTime) #Set temperature and wait for stability (see below)
for motorFreq in motorFreqs: #Cycle through motorFreqs
# before each measurement, we reset the chains by stirring them up, and then letting them reform
print 'Spinning rotor for ' + str(motorTime) + ' seconds.'
setMotorFreq(stirFreq, sleepTime=motorTime) # Prevent sedimentation
print 'Pausing rotor for ' + str(pauseTime) + ' seconds.'
setMotorFreq(0, sleepTime=pauseTime) # Pause, perhaps to wait for chains to form
breakBool = setMotorFreq(motorFreq, sleepTime=motorTime) #Set motor and checks if motorFreq is too high (high value may be changed in method setMotorFreq) (see below)
if breakBool: break #Break if motorFreq is above threshold
rotorFreqs = getData(numMeas, countTime=countTime) #Data retrieval (see below)
plt.savefig('Figs/'+time.strftime("%y-%m-%d-%H-%M-%S", time.localtime())+'-'+str(motorFreq)+'.png')
data = processData(temp, motorFreq, rotorFreqs) #Data processing (see below)
# calculate the std. error:
#se = numpy.std(rotorFreqs) / sqrt(numpy.size(rotorFreqs))
# Data recording: temp. - motorFreq. - avg. rotor Freq. - std. err.
writeToFile( data )
print 'Measurements at ' + str(temp) + ' degrees C completed.'
closeUp()
if plotResults and len(data) > 1:
kplt.plotData(os.getcwd(), Filename, writeFile=True, fit=False)
def singleSet(temps, motorFreqs, autoCount=False, countTime=10.0, numMeas=10, pauseTime=1, sampRate=2048, tempTime=120, motorTime=60, printDataBool=False, plotResults = True, substance='Water'):
initialize(substance) #Initialize ports, files, and constants (see below)
for temp in temps:
stirFreq = 400.0 #Set stirring speed for bath
setBath(temp, stirFreq, minStableTime=tempTime) #Set temperature and wait for stability (see below)
for motorFreq in motorFreqs: #Cycle through motorFreqs
print 'motorFreq is ' + str(motorFreq) + ' deg/sec.'
# 28.Feb.2014, Kaz: minimize sampRate to avoid data overflow for longer runs at slow shear:
rates = 2**np.array(range(4, 12))
minSampRate = (20.0 * motorFreq/3.6)
# rational is that you need at least 15 counts per tick, which I determined experimentally
# with 100 ticks per rotation, and 3.6 degrees per tick
# 15 counts/tick * (motorRate deg./sec. / 3.6 deg./tick) = minCountRate counts/second
sampRate = rates[np.abs(rates-minSampRate).argmin()]
if (sampRate-minSampRate) < 0 and sampRate != rates[-1]:
sampRate = rates[np.abs(rates-minSampRate).argmin()+1]
print 'sampRate is ' + str(sampRate) + ' samples/sec.'
# before each measurement, we reset the chains by stirring them up, and then letting them reform
print 'Spinning rotor for ' + str(motorTime) + ' seconds.'
setMotorFreq(stirFreq, sleepTime=motorTime) # Prevent sedimentation
print 'Pausing rotor for ' + str(pauseTime) + ' seconds.'
setMotorFreq(0, sleepTime=pauseTime) # Pause, perhaps to wait for chains to form
breakBool = setMotorFreq(motorFreq, sleepTime=motorTime) #Set motor and checks if motorFreq is too high (high value may be changed in method setMotorFreq) (see below)
if breakBool: break #Break if motorFreq is above threshold
# autoCount sets the count time to however long it takes for the motor to complete to full rotations
if autoCount == True:
cTime = np.ceil(720./motorFreq)
print 'Counting for ' + str(cTime) + ' seconds.'
rotorFreqs = getData(numMeas, countTime=cTime, sampRate=sampRate, printDataBool=printDataBool) #Data retrieval (see below)
else:
rotorFreqs = getData(numMeas, countTime=countTime, sampRate=sampRate, printDataBool=printDataBool) #Data retrieval (see below)
plt.savefig('Figs/'+time.strftime("%y-%m-%d-%H-%M-%S", time.localtime())+'-'+str(motorFreq)+'.png')
data = processData(temp, motorFreq, rotorFreqs) #Data processing (see below)
# calculate the std. error:
#se = numpy.std(rotorFreqs) / sqrt(numpy.size(rotorFreqs))
# Data recording: temp. - motorFreq. - avg. rotor Freq. - std. err. - sampRate - duration
writeToFile( data )
print 'Measurements at ' + str(temp) + ' degrees C completed.'
closeUp()
if plotResults and len(data) > 1:
kplt.plotData(os.getcwd(), Filename, writeFile=True, fit=False)
def singleSet(temps,
motorFreqs,
autoCount=False,
countTime=10.0,
numMeas=10,
pauseTime=1,
sampRate=2048,
tempTime=120,
motorTime=60,
printDataBool=False,
plotResults=True,
substance='Water'):
initialize(substance) #Initialize ports, files, and constants (see below)
for temp in temps:
stirFreq = 400.0 #Set stirring speed for bath
setBath(temp, stirFreq, minStableTime=tempTime
) #Set temperature and wait for stability (see below)
for motorFreq in motorFreqs: #Cycle through motorFreqs
print 'motorFreq is ' + str(motorFreq) + ' deg/sec.'
# 28.Feb.2014, Kaz: minimize sampRate to avoid data overflow for longer runs at slow shear:
rates = 2**np.array(range(4, 12))
minSampRate = (20.0 * motorFreq / 3.6)
# rational is that you need at least 15 counts per tick, which I determined experimentally
# with 100 ticks per rotation, and 3.6 degrees per tick
# 15 counts/tick * (motorRate deg./sec. / 3.6 deg./tick) = minCountRate counts/second
sampRate = rates[np.abs(rates - minSampRate).argmin()]
if (sampRate - minSampRate) < 0 and sampRate != rates[-1]:
sampRate = rates[np.abs(rates - minSampRate).argmin() + 1]
print 'sampRate is ' + str(sampRate) + ' samples/sec.'
# before each measurement, we reset the chains by stirring them up, and then letting them reform
print 'Spinning rotor for ' + str(motorTime) + ' seconds.'
setMotorFreq(stirFreq,
sleepTime=motorTime) # Prevent sedimentation
print 'Pausing rotor for ' + str(pauseTime) + ' seconds.'
setMotorFreq(0, sleepTime=pauseTime
) # Pause, perhaps to wait for chains to form
breakBool = setMotorFreq(
motorFreq, sleepTime=motorTime
) #Set motor and checks if motorFreq is too high (high value may be changed in method setMotorFreq) (see below)
if breakBool: break #Break if motorFreq is above threshold
# autoCount sets the count time to however long it takes for the motor to complete to full rotations
if autoCount == True:
cTime = np.ceil(720. / motorFreq)
print 'Counting for ' + str(cTime) + ' seconds.'
rotorFreqs = getData(
numMeas,
countTime=cTime,
sampRate=sampRate,
printDataBool=printDataBool) #Data retrieval (see below)
else:
rotorFreqs = getData(
numMeas,
countTime=countTime,
sampRate=sampRate,
printDataBool=printDataBool) #Data retrieval (see below)
plt.savefig('Figs/' +
time.strftime("%y-%m-%d-%H-%M-%S", time.localtime()) +
'-' + str(motorFreq) + '.png')
data = processData(temp, motorFreq,
rotorFreqs) #Data processing (see below)
# calculate the std. error:
#se = numpy.std(rotorFreqs) / sqrt(numpy.size(rotorFreqs))
# Data recording: temp. - motorFreq. - avg. rotor Freq. - std. err. - sampRate - duration
writeToFile(data)
print 'Measurements at ' + str(temp) + ' degrees C completed.'
closeUp()
if plotResults and len(data) > 1:
kplt.plotData(os.getcwd(), Filename, writeFile=True, fit=False)
