def generateWidesweepFreqList(FPGAparams,
outputFN='rfFreqs.txt',
resAtten=65,
alias_BW=1600.E6,
lo_hole=512.E3,
tone_BW=512.0E3,
minNominalFreqSpacing=800.0E3):
"""
Creates a frequency list for a widesweep centered around 0Hz.
INPUTS:
FPGAparams: filename to fpga parameter file
outputFN: name of output file
resAtten: resonator attenuation (65 is good for MEC)
alias_BW: bandwidth of antialiasing filter. (a little less than 2GHz). Will be clipped to the DAC bandwidth in the fpga file
lo_hole: freq hole around LO that we should avoid
tone_BW: bandwidth around tone to avoid crosstalk in FFT/DDS
minNominalFreqSpacing: The number of tones should be <= alias_BW/minNominalFreqSpacing. Will be clipped to the number of channels supported by the firmware.
"""
try:
params = readDict()
params.readFromFile(FPGAparams)
except TypeError:
params = paramFile
max_BW = int(params['dacSampleRate'])
alias_BW = min(alias_BW, max_BW)
freqResolution = params['dacSampleRate'] / (params['nDacSamplesPerCycle'] *
params['nLutRowsToUse'])
minNominalFreqSpacing = max(tone_BW + 100. * freqResolution,
minNominalFreqSpacing)
nChannels = params['nChannels']
avgSpacing = (alias_BW - tone_BW) / nChannels
if avgSpacing < (minNominalFreqSpacing):
avgSpacing = minNominalFreqSpacing
nChannels = int((alias_BW - tone_BW) / avgSpacing)
if nChannels <= 1:
nChannels = 1
avgSpacing = 0.
lo = 0.
freqs_low = makeRandomFreqSideband(
0. - alias_BW / 2. + freqResolution / 2.,
-lo_hole / 2. - freqResolution / 2., np.ceil(nChannels / 2.), tone_BW,
freqResolution)
freqs_high = makeRandomFreqSideband(lo_hole / 2. + freqResolution / 2.,
alias_BW / 2. - freqResolution / 2.,
np.floor(nChannels / 2.), tone_BW,
freqResolution)
freqs = np.append(freqs_low, freqs_high)
resIDs = np.asarray(range(len(freqs)))
attens = np.asarray([np.rint(resAtten * 4.) / 4.] * len(freqs))
data = np.asarray([resIDs, freqs, attens]).T
np.savetxt(outputFN, data, fmt="%4i %10.1f %4i")
self.curAxis='x'
print('Done.')
print(
'If you want to re-select kx, click first bright spot to the right of center (red dot), otherwise close the plot')
if __name__=='__main__':
if len(sys.argv)<2:
print('Usage: "python alignGrid.py <configFile>", where <configFile> is in MKID_DATA_DIR')
exit(1)
cfgFn=sys.argv[1]
if not os.path.isfile(cfgFn):
mdd = os.environ['MKID_DATA_DIR']
cfgFn = os.path.join(mdd, cfgFn)
paramDict = readDict()
paramDict.read_from_file(cfgFn)
aligner = BMAligner(paramDict['masterPositionList'], paramDict['nXPix'], paramDict['nYPix'], paramDict['instrument'], paramDict['flip'])
aligner.makeRawImage()
#aligner.fftRawImage()
aligner.loadFFT()
aligner.findKvecsManual()
aligner.findAngleAndScale()
aligner.rotateAndScaleCoords()
aligner.findOffset(50000)
aligner.plotCoords()
aligner.saveRawMap(paramDict['outputFilename'])
if paramDict['masterDoublesList'] is not None:
aligner.makeDoublesRawMap(paramDict['masterDoublesList'], paramDict['outputDoubleName'])
if __name__ == '__main__':
parser = argparse.ArgumentParser(description='ML Inference Script')
parser.add_argument('mlConfig',
nargs=1,
help='Machine learning model config file')
parser.add_argument('inferenceData',
nargs=1,
help='HDF5 file containing powersweep data')
parser.add_argument('-o',
'--output-dir',
nargs=1,
default=[None],
help='Directory to save output file')
parser.add_argument('-s',
'--add-scores',
action='store_true',
help='Adds a score column to the output file')
args = parser.parse_args()
mlDict = readDict()
mlDict.readFromFile(args.mlConfig[0])
h5FileName = args.inferenceData[0]
if not os.path.isfile(h5FileName):
h5FileName = os.path.join(os.environ['MKID_DATA_DIR'], h5FileName)
outputDir = args.output_dir[0]
findPowers(mlDict, h5FileName, outputDir, args.add_scores)
def loadClickthroughFile(fn):
'''
Loads clickthrough results from WideAna output file. Returns list of
ResIDs, peak locations, and frequencies (in GHz)
'''
if not os.path.isfile(fn):
fn = os.path.join(mdd, fn)
resIDs, locs, freqs = np.loadtxt(fn, unpack=True)
return resIDs, locs, freqs
if __name__ == '__main__':
if len(sys.argv) < 3:
print 'Usage: python findLOsAndMakeFreqFiles.py <setupcfgfile> <templarcfgfile>'
setupDict = readDict()
try:
setupDict.readFromFile(sys.argv[1])
try:
mdd = setupDict['MKID_DATA_DIR']
except KeyError:
mdd = os.environ['MKID_DATA_DIR']
except IOError:
mdd = os.environ['MKID_DATA_DIR']
setupDict.readFromFile(os.path.join(mdd, sys.argv[1]))
#print setupDict
templarCfgFile = sys.argv[2]
freqFiles = []
los = []
flNums = []
freqBandFlags = []
log.info('N good pixels: ' + str(np.sum(self.beamMap.flags.astype(int)==beamMapFlags['good'])))
log.info('N doubles: ' + str(np.sum(self.beamMap.flags.astype(int)==beamMapFlags['double'])))
log.info('N failed pixels (read out but not beammapped): ' + str(np.sum((self.beamMap.flags.astype(int)!=beamMapFlags['good']) & (self.beamMap.flags.astype(int)!=beamMapFlags['double']) & (self.beamMap.flags.astype(int)!=beamMapFlags['noDacTone']))))
np.savetxt(path, np.transpose([self.beamMap.resIDs.astype(int), self.beamMap.flags.astype(int), self.placedXs.astype(int), self.placedYs.astype(int)]), fmt='%4i %4i %4i %4i')
if __name__=='__main__':
parser = argparse.ArgumentParser(description='argument parser')
parser.add_argument('cfgFile', nargs=1, type=str, default='/mnt/data0/MEC/20181218/clean.cfg', help='Configuration file')
#default config file location
args = parser.parse_args()
configFileName = args.cfgFile[0]
resolutionType = args
log.setLevel(logging.INFO)
configData = readDict()
configData.read_from_file(configFileName)
beammapDirectory = configData['beammapDirectory']
finalBMFile = configData['finalBMFile']
rawBMFile = configData['rawBMFile']
useFreqs = configData['useFreqs']
psFiles = configData['powersweeps']
designFile = configData['designMapFile']
numRows = configData['numRows']
numCols = configData['numCols']
flipParam = configData['flip']
inst = configData['instrument']
rawBeamMap = Beammap(rawBMFile, (146, 140), 'MEC')
if useFreqs:
rawBeamMap.loadFrequencies(psFiles)