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IQcorr.py
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IQcorr.py
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'''
This file containts the procedures for cross correlations using 2 Aeroflex
Digitizers, a signal source and
31/03/2016
- B
'''
import numpy as np
from time import sleep # , time
from DataStorer import DataStoreSP, DataStore2Vec, DataStore11Vec
from nirack import nit # load PXI trigger
from covfunc import getCovMatrix # Function to calculate Covarianve Matrixes
import gc # Garbage memory collection
import os
class Process():
''' acesses the trigger, handles the data storage, saves the data,
acesses the procedure to calculate covariance Matrixes
'''
def __init__(self, D1, D2, pflux, sgen,
lags=20, BW=1e6, lsamples=1e4, corrAvg=1, doHist2d=False):
'''
D1, D2, pgen, pstar
D1,2: Digitizer 1,2 object
pgen: Flux Pump (Anritzu pulsed mode)
sgen: Signal Generator
pstar: Trigger source (PXI-Star)
'''
# Make some object references
self.D1 = D1
self.D2 = D2
self.D1w = self.D1.digitizer
self.D2w = self.D2.digitizer
self.sgen = sgen
self.pflux = pflux
self.pstar = nit()
self.corrAvg = corrAvg
self.lags = lags
self.BW = BW
self.lsamples = lsamples
self.pstar.send_many_triggers(10)
self._takeBG = True
self.num = 0 # number of missed triggers in a row
self.doHist2d = doHist2d
# Define the different measurement types here:
self.driveON = meastype(D1, D2, lags, 'ON', self.corrAvg) # Pump drive ON
self.driveOFF = meastype(D1, D2, lags, 'OFF', self.corrAvg) # Pump drive off
# self.driveOFFf1 = meastype(D1, D2, lags, 'f1') # Pump drive off & Probe Signal f1
# self.driveOFFf2 = meastype(D1, D2, lags, 'f2') # Pump drive off & Probe Signal f2
if doHist2d:
# hdf5 format is desired, files would become too large to address in 32bit
pass
# X = 100 # (Typical Bin size)
# Y = 100
# self.hist = np.memmap('histograms.dat', dtype=np.float32, mode='w+',
# shape=(6, X, Y, dim_3.pt, dim_2.pt, dim_1.pt))
def setup_D1D2(self):
'''
Trigger on PXI-Star
Enable pipelining
'''
# self.D1w.trigger_source_set(8)
# self.D2w.trigger_source_set(8)
# self.D1w.set_piplining(1)
# self.D2w.set_piplining(1)
def init_trigger_wcheck(self, Refcheck=True, Trigcheck=False):
if Refcheck is True:
ref1 = bool(self.D1w.ref_is_locked())
ref2 = bool(self.D2w.ref_is_locked())
if (ref1 and ref2):
self.init_trigger()
if Trigcheck:
sleep(0.017)
self.confirm_Trigger(Refcheck, Trigcheck)
else:
print ref1, ref2
print 'No reference lock! waiting..'
sleep(0.2)
self.init_trigger_wcheck(Refcheck, Trigcheck)
def confirm_Trigger(self, Refcheck, Trigcheck):
det1 = self.D1.digitizer.get_trigger_detected()
det2 = self.D2.digitizer.get_trigger_detected()
if det1 is False:
self.num += 1
sleep(0.1)
self.init_trigger_wcheck(Refcheck, Trigcheck)
if self.num > 3:
raise Exception('Trigger1 Not Detected 3x')
if det2 is False:
self.num += 1
sleep(0.1)
self.init_trigger_wcheck(Refcheck, Trigcheck)
if self.num > 3:
raise Exception('Trigger2 Not Detected 3x')
self.num = 0
def init_trigger(self):
self.D1.init_trigger_buff()
self.D2.init_trigger_buff()
sleep(0.022)
self.pstar.send_software_trigger()
def create_datastore_objs(self, folder, filen_0, dim_1, dim_2, dim_3):
self.driveON.create_objs(folder, filen_0, dim_1, dim_2, dim_3)
if self._takeBG:
self.driveOFF.create_objs(folder, filen_0, dim_1, dim_2, dim_3)
def data_save(self):
self.driveON.data_save()
if self._takeBG:
self.driveOFF.data_save()
def data_record(self, kk, jj, ii):
self.driveON.data_record(kk, jj, ii)
if self._takeBG:
self.driveOFF.data_record(kk, jj, ii)
def data_variables(self):
self.driveON.data_variables()
if self._takeBG:
self.driveOFF.data_variables()
def download_data(self, cz):
'''This downloads data from D1 and D2,
once downloaded, data acquisition can continue.
At the same time D1 and D2 data can be processed
'''
self.D1.get_Levelcorr() # update level correction value
self.D2.get_Levelcorr()
self.D1.downl_data_buff()
self.D2.downl_data_buff()
if (self.D1.ADCFAIL or self.D2.ADCFAIL):
print 'Remeasure --'
self.init_trigger()
self.D1.ADCFAIL = False
self.D2.ADCFAIL = False
self.download_data(cz)
elif (bool(self.D1.ADCoverflow) or bool(self.D1.ADCoverflow)):
self.nnnnn += 1
print 'remeasure this: '+str(self.nnnnn)
if self.nnnnn > 7:
raise Exception('Continuous ADC-overflow')
self.init_trigger()
self.download_data(cz)
def process_data(self):
self.D1.process_data() # process data, while measurement is running
self.D2.process_data()
def avg_corr(self):
'''init_trigger() should have run once before. This is the averaging,
processing and measurement main loop '''
for cz in range(int(self.corrAvg)):
# Download ON data
self.nnnnn = 0
self.download_data(cz)
# Initiate OFF data aquisition
if self._takeBG:
self.pflux.output(0)
# print 'output off'
sleep(0.1)
self.init_trigger() # Initiate next measurement set
# Process digitizer ON data
self.process_data()
self.driveON.add_avg() # store ON data
# Download OFF data
if self._takeBG:
self.download_data(cz) # Download data from digitizer
#After download Drive can be switched ON again
self.pflux.output(1)
# print 'output on'
sleep(0.1)
# Initiate trigger for next average
if (cz+1) < int(self.corrAvg):
self.init_trigger()
# self.init_trigger_wcheck(True, True) # Refcheck (Y), Trigcheck (N)
# Process OFF data
if self._takeBG:
self.process_data() # Processing digitizer data
self.driveOFF.add_avg() # store OFF data
def full_aqc(self, kk, jj, ii):
''' This it the function to run
1. clears variables
2. triggers and averages correlation
3. calulates correlations
4. record data to memory
still needs data_save to be run to save the data file in the end.
'''
self.data_variables() # 1 clears temp data
# self.init_trigger() # 2
# self.init_trigger_wcheck(True, False) # Refcheck (Y), Trigcheck (N)
self.D1.checkADCOverload()
self.D2.checkADCOverload()
self.avg_corr() # 3
self.data_record(kk, jj, ii) # 4
if self.doHist2d:
self.make_densityM(kk, jj, ii)
def make_densityM(self, kk, jj, ii):
''' This creates a figure of the histogram at one specific point'''
I1 = self.D1.scaledI
Q1 = self.D1.scaledQ
I2 = self.D2.scaledI
Q2 = self.D2.scaledQ
histI1Q1, xl, yl = np.histogram2d(I1, Q1)
histI2Q2, xl, yl = np.histogram2d(I2, Q2)
histI1I2, xl, yl = np.histogram2d(I1, I2)
histQ1Q2, xl, yl = np.histogram2d(Q1, Q2)
histI1Q2, xl, yl = np.histogram2d(I1, Q2)
histQ1I2, xl, yl = np.histogram2d(Q1, I2)
class meastype(object):
''' This class contains the different types of measurements done:
one where the Drive is switched off, one, where its on,
one where a Probe signal is present at f1 one at f2... '''
def __init__(self, D1, D2, lags, name, corrAvg):
gc.collect()
self.D1 = D1
self.D2 = D2
self.lags = lags
self.name = name
self.corrAvg = corrAvg
self.data_variables()
def data_variables(self):
''' create empty variables to store average values '''
self.D1Ma = np.float(0.0)
self.D1Pha = np.float(0.0)
self.D1vMa = np.float(0.0)
self.D1vPha = np.float(0.0)
self.D2vMa = np.float(0.0)
self.D2vPha = np.float(0.0)
self.D2Ma = np.float(0.0)
self.D2Pha = np.float(0.0)
self.covAvgMat = np.zeros([12, self.lags * 2 - 1]) # For one particular ii, jj, kk
self.D1aPow = np.float(0.0)
self.D2aPow = np.float(0.0)
def add_avg(self):
self.D1Ma += self.D1.AvgMag
self.D1Pha += self.D1.AvgPhase
self.D1vMa += self.D1.vAvgMag
self.D1vPha += self.D1.vAvgPh
self.D1aPow += self.D1.vAvgPow
# Digitizer 2 Values
self.D2Ma += self.D2.AvgMag
self.D2Pha += self.D2.AvgPhase
self.D2vMa += self.D2.vAvgMag
self.D2vPha += self.D2.vAvgPh
self.D2aPow += self.D2.vAvgPow
self.covAvgMat += getCovMatrix(self.D1.scaledI, self.D1.scaledQ,
self.D2.scaledI, self.D2.scaledQ,
self.lags)
def create_objs(self, folder, filen_0, dim_1, dim_2, dim_3):
''' Prepare Digitizer data files '''
folder = folder+filen_0+self.name+'\\'
if not os.path.exists(folder):
os.makedirs(folder)
self.DSP_PD1 = DataStoreSP(folder, filen_0, dim_1, dim_2, dim_3, 'D1Pow', cname='Watts')
self.DSP_PD2 = DataStoreSP(folder, filen_0, dim_1, dim_2, dim_3, 'D2Pow', cname='Watts')
self.DSP_LD1 = DataStoreSP(folder, filen_0, dim_1, dim_2, dim_3, 'D1LevCorr', cname='LvLCorr')
self.DSP_LD2 = DataStoreSP(folder, filen_0, dim_1, dim_2, dim_3, 'D2LevCorr', cname='LvLCorr')
self.DS2vD1 = DataStore2Vec(folder, filen_0, dim_1, dim_2, dim_3, 'D1vAvg')
self.DS2vD2 = DataStore2Vec(folder, filen_0, dim_1, dim_2, dim_3, 'D2vAvg')
self.DS2mD1 = DataStore2Vec(folder, filen_0, dim_1, dim_2, dim_3, 'D1mAvg')
self.DS2mD2 = DataStore2Vec(folder, filen_0, dim_1, dim_2, dim_3, 'D2mAvg')
self.DS11 = DataStore11Vec(folder, filen_0, dim_1, dim_2, self.D1, 'CovMat')
# Cov Matrix D1 has dim_3 info
def data_record(self, kk, jj, ii):
'''This loads the new information into the matices'''
corrAvg = np.float(self.corrAvg)
self.DS11.record_data(self.covAvgMat / corrAvg, kk, jj, ii)
self.DSP_PD1.record_data((self.D1aPow / corrAvg), kk, jj, ii)
self.DSP_PD2.record_data((self.D2aPow / corrAvg), kk, jj, ii)
self.DSP_LD1.record_data(self.D1.levelcorr, kk, jj, ii)
self.DSP_LD2.record_data(self.D2.levelcorr, kk, jj, ii)
self.DS2mD2.record_data(self.D2Ma / corrAvg, self.D2Pha / corrAvg, kk, jj, ii)
self.DS2mD1.record_data(self.D1Ma / corrAvg, self.D1Pha / corrAvg, kk, jj, ii)
self.DS2vD1.record_data(self.D1vMa / corrAvg, self.D1vPha / corrAvg, kk, jj, ii)
self.DS2vD2.record_data(self.D2vMa / corrAvg, self.D2vPha / corrAvg, kk, jj, ii)
def data_save(self):
'''save the data in question, at the moment these functions rewrite the matrix eachtime,
instead of just appending to it.'''
self.DS11.save_data()
self.DSP_PD1.save_data()
self.DSP_PD2.save_data()
self.DSP_LD1.save_data()
self.DSP_LD2.save_data()
self.DS2mD2.save_data()
self.DS2mD1.save_data()
self.DS2vD1.save_data()
self.DS2vD2.save_data()