def main(self):
differentOutputFolder = True
# differentOutputFolder = False
# select nexus files
fileNames = gfh.requestFiles((("Nexus files", "*.nxs"), ),
"Select P61A file", "on")
pathName, _ = gfh.fileparts(fileNames[0])
# read all data from selected files
reader = P61ANexusReader()
data = pd.DataFrame(columns=reader.columns)
for f_name in fileNames:
data = pd.concat((data, reader.read(f_name)), ignore_index=True)
# select output folder if wanted
if differentOutputFolder:
outputPath = gfh.requestDirectory(
dialogTitle='Select output folder', folder=pathName)
else:
outputPath = pathName
# export data to spectrum files
for i in range(data.shape[0]):
curData = data.iloc[i]
header = [
'SCREEN_NAME=' + curData['ScreenName'],
'CHANNEL=' + str(curData['Channel']),
'DEADTIME=' + str(curData['DeadTime']),
'TREAL=' + str(curData['CountTime']),
'SPECTRTXT=' + str(len(curData['DataX']))
]
vals = np.transpose([curData['DataX'], curData['DataY']])
sfh.writeSpectrumFile(
outputPath + '/' +
gf.replace(curData['ScreenName'], '.nxs:', '_') + '.txt', vals,
header)
def getSpectrumFromFile(specFile="", dataDelim='\t', headerLines=5):
data = 0
heading = 0
if len(specFile) == 0:
specFile = fg.requestFiles((('Text file', '*.txt'),), 'Spektrumdatei auswaehlen', 'off')
if len(specFile) > 0:
#Read data from file
heading = fg.readLines(specFile, headerLines)
data = fg.dlmread(specFile, dataDelim, headerLines)
return data, heading
def accumSpectra(resFile='', files=None, method='sum', dataDelim='\t', headerLines=5):
# method: 'sum', 'mean', 'max', 'min'
results = None
header = []
if files is None:
files = fg.requestFiles((('Text file', '*.txt'),), 'Spektrumdateien auswaehlen', 'on')
if len(files) > 1:
for i in range(len(files)):
[data, heading] = getSpectrumFromFile(files[i], dataDelim, headerLines)
# initialize values if not existing
if results is None:
if method == 'min':
results = np.ones(data.shape) * 1e8
tlive = 1e6
treal = 1e6
else:
results = np.zeros(data.shape)
tlive = 0
treal = 0
results[:, 0] = data[:, 0]
# get current live and real time
if len(heading) > 2 and 'TLIVE' in heading[2]:
tliveCur = float(bf.replace(heading[2], 'TLIVE=', ''))
else:
tliveCur = tlive
if len(heading) > 3 and 'TREAL' in heading[3]:
trealCur = float(bf.replace(heading[3], 'TREAL=', ''))
else:
trealCur = treal
# update values
if method == 'sum' or method == 'mean':
results[:, 1] = results[:, 1] + data[:, 1]
tlive = tlive + tliveCur
treal = treal + trealCur
elif method == 'max':
results[:, 1] = np.max((results[:, 1], data[:, 1]), axis=0)
tlive = np.max((tlive, tliveCur))
treal = np.max((treal, trealCur))
elif method == 'min':
results[:, 1] = np.min((results[:, 1], data[:, 1]), axis=0)
tlive = np.min((tlive, tliveCur))
treal = np.min((treal, trealCur))
if method == 'mean':
results[:, 1] = results[:, 1] / len(files)
tlive = tlive / len(files)
treal = treal / len(files)
if headerLines > 0:
header = ['DATE=' + bf.datetimestr('%d-%m-%Y'), 'TIME=' + bf.datetimestr('%H:%M:%S'), 'TLIVE=' + str(tlive),
'TREAL=' + str(treal), heading[4]]
if len(resFile) > 0:
if headerLines > 0:
writeSpectrumFile(resFile, results, header[:(min(len(header), headerLines))])
else:
writeSpectrumFile(resFile, results)
return results, header, files
def loadFileP61A(fileP61A=""):
rawData = 0
if len(fileP61A) == 0:
fileP61A = fg.requestFiles((('Data file', '*.dat'),), 'Select P61A data file', 'off')
fileP61A = fileP61A[0]
if len(fileP61A) > 0:
# read header data from file
heading, metaInfo = importFileHeader(fileP61A, '\t', True, (('Data file', '*.dat'),),
'Select P61A data file', 'off')
# the first column is text
rawData = fg.dlmread(fileP61A, '\t', 2, usedCols=range(1, len(heading)))
return rawData, heading, metaInfo
def getDecVals(decFile, hklVals=None):
decVals = 0
if decFile is None or len(decFile) == 0:
fileNames = fg.requestFiles((('Text file', '*.txt'),), 'Select DEC file', "off")
decFile = fileNames[0]
if decFile is not None:
# Convert data to matrix
data = fg.dlmread(decFile, '\t', 1)
if hklVals is not None:
#select relevant values
return dc.selectDecVals(data, hklVals)
else:
return data
def importFileHeader(importFile='', delim='\t', withMetaLine=False,
fileType=(('Data file', '*.txt'), ('Data file', '*.dat')), diagTitle='Select data file', multiSel='off'):
if len(importFile) == 0:
importFile = fg.requestFiles(fileType, diagTitle, multiSel)
importFile = importFile[0]
if len(importFile) > 0:
# read header from file
if withMetaLine:
heading = fg.readLines(importFile, 2)
# first line consists of comments or metadata
metaInfo = heading[0]
# second line contains header information
heading = bf.split(heading[1], delim)
else:
heading = fg.readLines(importFile, 1)
metaInfo = ''
heading = bf.split(heading[0], '\t')
return heading, metaInfo
def importNumericalDataWithHeader(importFile='', delim='\t', withMetaLine=False, skipCols=0,
fileType=(('Data file', '*.txt'), ('Data file', '*.dat')), diagTitle='Select data file', multiSel='off'):
data = dict()
header = 0
if len(importFile) == 0:
importFile = fg.requestFiles(fileType, diagTitle, multiSel)
importFile = importFile[0]
if len(importFile) > 0:
# read header data from file
heading, metaInfo = importFileHeader(importFile, delim, withMetaLine, fileType, diagTitle, multiSel)
# the first column is text
if withMetaLine:
skipRows = 2
else:
skipRows = 1
rawData = fg.dlmread(importFile, delim, skipRows, usedCols=range(skipCols, len(heading)))
# convert data to dictionary
data = bf.matrix2dict(rawData, heading[skipCols:])
return data, metaInfo
import numpy as np
import itertools
import basics.functions as bf
import filehandling.general as fg
import filehandling.specific as fs
# Fio file processing for ROI analysis
fileNames = fg.requestFiles((("Fio files", '*.fio'), ),
'Select motor positions files', 'on')
for i in range(len(fileNames)):
fioData = fs.read_fio(fileNames[i])
fg.dlmwrite(bf.replace(fileNames[i], '.fio', '_roi.txt'),
fioData.values,
head=bf.stringList2string(list(fioData.columns), '\t'),
format='%f')
# header for position files: om eta tth0 tth1 psi0 psi1 phi x y z petracurrent
header = [
'om', 'eta', 'tth0', 'tth1', 'psi0', 'psi1', 'phi', 'x', 'y', 'z',
'petraCur'
]
headLine = bf.stringList2string(header, '\t')
# Fio file processing for residual stress analysis and texture analysis
# phioffset = 45
phioffset = 0
fileNames = fg.requestFiles((("Fio files", '*.fio'), ),
'Select motor positions files', 'on')
for i in range(len(fileNames)):
scanData, fixData = fs.read_fio(fileNames[i])
energiesDet2 = conv.latticeDists2energies(dVals, 11.5)
energiesDet1 = conv.latticeDists2energies(dVals, 15)
for i in range(len(hklValsLab6)):
print('%d\t%.3f\t%.3f' %
(hklValsLab6[i], energiesDet2[i], energiesDet1[i]))
dc.calc3Gamma2(hklValsLab6)
# define settings and import the data files
# plotResMwl = False
# plotResUvp = False
plotResMwl = True
plotResUvp = True
showErr = True
# showErr = False
checkUvpVals = True
fileNames = fg.requestFiles((("Data files", "*.dat"), ),
"Select P61A data file", "on")
# import all data
allData = dict()
allMetaInfo = dict()
for fileName in fileNames:
data, metaInfo = fs.loadFileP61A2(fileName)
allData[fileName] = data
allMetaInfo[fileName] = metaInfo
# combine all data for one analysis
combinedData = allData[fileNames[0]]
keyList = bf.getKeyList(combinedData)
for fileName in fileNames[1:]:
for key in keyList:
combinedData[key] = np.concatenate(
(combinedData[key], allData[fileName][key]))
# prepare data for multi wavelength and universal plot analysis
def createPeakMeasurementFile(settings, fileNamesAxes=None, fileNamesPeaks=None, resFile=None):
# header of new file
fileHead = ['LNr', 'dVal[nm]', 'dVar[nm]', 'Iint', 'Integralb', 'tth', 'phiP', 'psiP', 'etaP',
'Ringstr', 'RT', 'DT', 'xdiff', 'ydiff', 'zdiff', 'motor1', 'motor2', 'motor3',
'temp1', 'temp2', 'wavelength', 'deltatime']
# select files
if fileNamesAxes is None or len(fileNamesAxes) == 0:
multiSel = 'on'
fileNamesAxes = fg.requestFiles((('Text file', '*.txt'),), 'Achspositionsdateien auswaehlen', multiSel)
if fileNamesPeaks is None or len(fileNamesPeaks) == 0:
fileNamesPeaks = fg.requestFiles((('Text file', '*.txt'),), 'Auswertedateien auswaehlen', "on")
if fileNamesAxes is not None and len(fileNamesAxes) != 0:
if resFile is None or len(resFile) == 0:
# specify name of result file
if len(fileNamesAxes) == 1 and fileNamesAxes[0].find('_positions.txt') > 0:
resFile = bf.replace(fileNamesAxes[0], '_positions.txt', '_finalData.txt')
elif len(fileNamesAxes) == 1 and fileNamesAxes[0].find('_pos.txt') > 0:
resFile = bf.replace(fileNamesAxes[0], '_pos.txt', '_finalData.txt')
elif len(fileNamesAxes) == 1:
resFile = bf.replace(fileNamesAxes[0], '.txt', '_finalData.txt')
else:
pathName, file = fg.fileparts(fileNamesAxes[0])
resFile = pathName + '/finalData.txt'
if settings['type'] == 'P61_0':
resFile = resFile.replace('.txt', '0.txt')
elif settings['type'] == 'H4_1' or settings['type'] == 'P61_1':
resFile = resFile.replace('.txt', '1.txt')
elif settings['type'] == 'H4_2':
resFile = resFile.replace('.txt', '2.txt')
axesFiles = len(fileNamesAxes)
peakFiles = len(fileNamesPeaks)
# read data from axes files
dataAxes = []
for i in range(axesFiles):
dataAxes.append(fg.dlmread(fileNamesAxes[i], '\t', 1))
dataAxes = np.array(dataAxes)
# read data from peak files
dataPeaks = []
for i in range(peakFiles):
dataPeaks.append(fg.dlmread(fileNamesPeaks[i], '\t', 1))
dataPeaks = np.array(dataPeaks)
if len(bf.size(dataPeaks[0])) == 1:
peakCount = bf.min(bf.size(dataPeaks[0], 0), bf.size(dataPeaks[0], 1))[0] # peakFiles
else:
peakCount = bf.size(dataPeaks[0], 0)
peaks = np.setdiff1d(range(0, peakCount), settings['unused'] - 1) # function needs zero based unused values
# create new data set
lineCount = peakFiles * len(peaks)
data = np.zeros((lineCount, 22))
curAxesFile = 0
curAxesLine = 0
peakNum = 1
for i in peaks:
for j in range(peakFiles):
curLine = (peakNum - 1) * peakFiles + j
data[curLine, 0] = peakNum # peak number
# angle dispersive data measured at own laboratory devices (roh, xrdml and uxd file format)
if settings['type'] == 'AD':
if len(bf.size(dataPeaks)) < 3:
data[curLine, 5] = dataPeaks[j, 4] # ttheta
else:
data[curLine, 5] = dataPeaks[j][i, 4] # ttheta
data[curLine, 6] = dataAxes[curAxesFile][curAxesLine, 2] # phi
data[curLine, 7] = dataAxes[curAxesFile][curAxesLine, 1] # psi
data[curLine, 8] = 90 # eta
data[curLine, 9] = 45 # current
data[curLine, 10] = dataAxes[curAxesFile][curAxesLine, 7] # real time
data[curLine, 12] = dataAxes[curAxesFile][curAxesLine, 3] # x axis
data[curLine, 13] = dataAxes[curAxesFile][curAxesLine, 4] # y axis
data[curLine, 14] = dataAxes[curAxesFile][curAxesLine, 5] # z axis
data[curLine, 20] = settings['pars'] # wavelength
data[curLine, 1] = conv.angles2latticeDists(data[curLine, 5], data[curLine, 20]) # peak value
if len(bf.size(dataPeaks)) < 3:
data[curLine, 2] = data[curLine, 1] - conv.angles2latticeDists(data[curLine, 5] +
dataPeaks[j, 7], data[curLine, 20]) # peak deviation
data[curLine, 3] = dataPeaks[j, 5] # peak intensity
data[curLine, 4] = (2 * np.pi) ** 0.5 * dataPeaks[j, 3] # peak IB [°]
else:
data[curLine, 2] = data[curLine, 1] - conv.angles2latticeDists(data[curLine, 5] +
dataPeaks[j][i, 7], data[curLine, 20]) # peak deviation
data[curLine, 3] = dataPeaks[j][i, 5] # peak intensity
data[curLine, 4] = (2 * np.pi)**0.5 * dataPeaks[j][i, 3] # peak IB [°]
# Seifert measurement data
elif len(settings['type']) > 6 and settings['type'][0:6] == 'Seifert':
data[curLine, 5] = dataPeaks[j][i, 4] # ttheta
data[curLine, 6] = dataAxes[curAxesFile][curAxesLine, 4] # phi
if data[curLine, 6] != 0 or data[curLine, 6] != 90 or data[curLine, 6] != 180 or data[curLine, 6] != 270:
data[curLine, 6] = 0
data[curLine, 7] = dataAxes[curAxesFile][curAxesLine, 3] # psi
if settings['type'] == 'SeifertM': # omega measurement
data[curLine, 8] = 0 # eta
else:
data[curLine, 8] = 90 # eta
data[curLine, 9] = 45 # current
data[curLine, 10] = dataAxes[curAxesFile][curAxesLine, 14] # real time
data[curLine, 12] = dataAxes[curAxesFile][curAxesLine, 5] # x axis
data[curLine, 13] = dataAxes[curAxesFile][curAxesLine, 6] # y axis
data[curLine, 14] = dataAxes[curAxesFile][curAxesLine, 7] # z axis
data[curLine, 20] = settings['pars'] # wavelength
data[curLine, 1] = conv.angles2latticeDists(data[curLine, 5], data[curLine, 20]) # peak value
data[curLine, 2] = data[curLine, 1] - conv.angles2latticeDists(data[curLine, 5] +
dataPeaks[j][i, 7], data[curLine, 20]) # peak deviation
data[curLine, 3] = dataPeaks[j][i, 5] # peak intensity
data[curLine, 4] = (2 * np.pi) ** 0.5 * dataPeaks[j][i, 3] # peak IB [°]
elif settings['type'] == 'ED' or settings['type'][0:2] == 'H4' or settings['type'][0:3] == 'P61':
if settings['type'][0:2] == 'H4':
data[curLine, 5] = settings['tth']
data[curLine, 6] = dataAxes[curAxesFile][curAxesLine, 5] # phi
data[curLine, 7] = dataAxes[curAxesFile][curAxesLine, 4] # psi
data[curLine, 8] = 90 # eta
data[curLine, 9] = 45 # current
# real time
# dead time
data[curLine, 12] = dataAxes[curAxesFile][curAxesLine, 6] # x axis
data[curLine, 13] = dataAxes[curAxesFile][curAxesLine, 7] # y axis
data[curLine, 14] = dataAxes[curAxesFile][curAxesLine, 8] # z axis
elif settings['type'][0:3] == 'P61':
if settings['type'] == 'P61_0':
data[curLine, 5] = dataAxes[curAxesFile][curAxesLine, 2] # ttheta
data[curLine, 7] = dataAxes[curAxesFile][curAxesLine, 4] # psi
elif settings['type'] == 'P61_1':
data[curLine, 5] = dataAxes[curAxesFile][curAxesLine, 3] # ttheta
data[curLine, 7] = dataAxes[curAxesFile][curAxesLine, 5] # psi
data[curLine, 6] = dataAxes[curAxesFile][curAxesLine, 6] # phi
data[curLine, 8] = 90 # eta
data[curLine, 9] = dataAxes[curAxesFile][curAxesLine, 10] # petracurrent
# real time
# dead time
data[curLine, 12] = dataAxes[curAxesFile][curAxesLine, 7] # x
data[curLine, 13] = dataAxes[curAxesFile][curAxesLine, 8] # y
data[curLine, 14] = dataAxes[curAxesFile][curAxesLine, 9] # z
elif settings['type'] == 'ED':
data[curLine, 5] = dataAxes[curAxesFile][curAxesLine, 1] + dataAxes[curAxesFile][curAxesLine, 2] # ttheta
data[curLine, 6] = dataAxes[curAxesFile][curAxesLine, 4] # phi
data[curLine, 7] = dataAxes[curAxesFile][curAxesLine, 3] # psi
data[curLine, 8] = 90 # eta
data[curLine, 9] = 45 # current
data[curLine, 10] = dataAxes[curAxesFile][curAxesLine, 14] # real time
# dead time
data[curLine, 12] = dataAxes[curAxesFile][curAxesLine, 5] # x axis
data[curLine, 13] = dataAxes[curAxesFile][curAxesLine, 6] # y axis
data[curLine, 14] = dataAxes[curAxesFile][curAxesLine, 7] # z axis
if len(settings['pars']) == 0:
data[curLine, 1] = conv.energies2latticeDists(dataPeaks[j][i, 4], data[curLine, 5]) # peak value
data[curLine, 2] = data[curLine, 1] - conv.energies2latticeDists(dataPeaks[j][i, 4] +
dataPeaks[j][i, 7] / dataPeaks[j][i, 2], data[curLine, 5]) # peak deviation
data[curLine, 4] = (2 * np.pi) ** 0.5 * dataPeaks[j][i, 3] # peak IB [keV]
else:
data[curLine, 1] = conv.energies2latticeDists(conv.channels2energies(dataPeaks[j][i, 4],
settings['pars']), data[curLine, 5]) # peak value
data[curLine, 2] = data[curLine, 1] - conv.energies2latticeDists(conv.channels2energies(dataPeaks[j][i, 4]
+ dataPeaks[j][i, 7] / dataPeaks[j][i, 2], settings['pars']), data[curLine, 5]) # peak deviation
data[curLine, 4] = (2 * np.pi) ** 0.5 * dataPeaks[j][i, 3] # peak IB [keV]
data[curLine, 3] = dataPeaks[j][i, 5] # peak intensity
if settings['type'][0:2] == 'P61':
data[curLine, 2] = 1 / data[curLine, 3] # error weight as intensity
# ED data in general
elif settings['type'] == 'ED':
data[curLine, 5] = dataAxes[curAxesFile][curAxesLine, 1] + dataAxes[curAxesFile][curAxesLine, 1] # ttheta
data[curLine, 6] = dataAxes[curAxesFile][curAxesLine, 4] # phi
data[curLine, 7] = dataAxes[curAxesFile][curAxesLine, 3] # psi
data[curLine, 8] = 90 # eta
data[curLine, 9] = 45 # current
data[curLine, 10] = dataAxes[curAxesFile][curAxesLine, 14] # real time
# dead time
data[curLine, 12] = dataAxes[curAxesFile][curAxesLine, 5] # x axis
data[curLine, 13] = dataAxes[curAxesFile][curAxesLine, 6] # y axis
data[curLine, 14] = dataAxes[curAxesFile][curAxesLine, 7] # z axis
if settings['pars'] is None:
data[curLine, 1] = conv.energies2latticeDists(dataPeaks[j][i, 4], data[curLine, 5]) # peak value
data[curLine, 2] = data[curLine, 1] - conv.energies2latticeDists(dataPeaks[j][i, 4] +
dataPeaks[j][i, 7], data[curLine, 5]) # peak deviation
data[curLine, 4] = (2 * np.pi)**0.5 * dataPeaks[j][i, 3] # peak IB [keV]
else:
data[curLine, 1] = conv.energies2latticeDists(conv.channels2energies(dataPeaks[j][i, 4], settings['pars']),
data[curLine, 5]) # peak value
data[curLine, 2] = dataPeaks[j][i, 4] - conv.energies2latticeDists(conv.channels2energies(dataPeaks[j][i, 4] +
dataPeaks[j][i, 7], settings['pars']), data[curLine, 5]) # peak deviation
data[curLine, 4] = (2 * np.pi)**0.5 * dataPeaks[j][i, 3] # peak IB [keV]
data[curLine, 3] = dataPeaks[j][i, 5] # peak intensity
# EDDI files
elif settings['type'] == 'EDDI':
data[curLine, 5] = dataAxes[curAxesFile][curAxesLine, 1] # ttheta
data[curLine, 6] = dataAxes[curAxesFile][curAxesLine, 2] # phi
data[curLine, 7] = dataAxes[curAxesFile][curAxesLine, 3] # psi
data[curLine, 8] = dataAxes[curAxesFile][curAxesLine, 4] # eta
data[curLine, 9] = dataAxes[curAxesFile][curAxesLine, 5] # current
data[curLine, 10] = dataAxes[curAxesFile][curAxesLine, 6] # real time
data[curLine, 11] = dataAxes[curAxesFile][curAxesLine, 7] # dead time
data[curLine, 12] = dataAxes[curAxesFile][curAxesLine, 8] # x axis
data[curLine, 13] = dataAxes[curAxesFile][curAxesLine, 9] # y axis
data[curLine, 14] = dataAxes[curAxesFile][curAxesLine, 10] # z axis
data[curLine, 15] = dataAxes[curAxesFile][curAxesLine, 11] # motor 1
data[curLine, 16] = dataAxes[curAxesFile][curAxesLine, 12] # motor 2
data[curLine, 17] = dataAxes[curAxesFile][curAxesLine, 13] # motor 3
data[curLine, 19] = dataAxes[curAxesFile][curAxesLine, 14] # temp 1
data[curLine, 19] = dataAxes[curAxesFile][curAxesLine, 15] # temp 2
data[curLine, 20] = dataAxes[curAxesFile][curAxesLine, 16] # heatrate
if settings['pars'] is None:
data[curLine, 1] = conv.energies2latticeDists(dataPeaks[j][i, 4], data[curLine, 5]) # peak value
data[curLine, 2] = data[curLine,1] - conv.energies2latticeDists(dataPeaks[j][i, 4] +
dataPeaks[j][i, 7], data[curLine, 5]) # peak deviation
data[curLine, 4] = (2 * np.pi)**0.5 * dataPeaks[j][i, 3] # peak IB [keV]
else:
data[curLine, 1] = conv.energies2latticeDists(conv.channels2energies(dataPeaks[j][i, 4], settings['pars']),
data[curLine, 5]) # peak value
data[curLine, 2] = data[curLine, 1] - conv.energies2latticeDists(conv.channels2energies(dataPeaks[j][i, 4]
+ dataPeaks[j][i, 7], settings['pars']), data[curLine, 5]) # peak deviation
data[curLine, 4] = conv.channels2energies((2 * np.pi)**0.5 * dataPeaks[j][i, 3], settings['pars']) # peak IB [keV]
data[curLine, 3] = dataPeaks[j][i, 5] # peak intensity
# go to next measurement
curAxesLine = curAxesLine + 1
if bf.size(dataAxes[curAxesFile], 0) <= curAxesLine:
curAxesFile = curAxesFile + 1
if axesFiles <= curAxesFile:
curAxesFile = 0
curAxesLine = 0
peakNum = peakNum + 1
# write new file
fid = open(resFile, 'w')
for i in range(len(fileHead)):
fid.write(('%s\t' % fileHead[i]))
fg.writeLine(fid, '')
formatStr = '%.0f\t%.8f\t%.8f\t%.2f\t%.6f\t%.4f\t%.4f\t%.4f\t%.4f\t%.1f\t%.1f\t%.2f\t%.3f\t%.3f\t'\
+ '%.5f\t%.3f\t%.3f\t%.3f\t%.2f\t%.2f\t%.8f\t%.0f'
for j in range(lineCount):
fg.writeDataLine(fid, formatStr, data[j, :])
fid.close()
return data, resFile
import numpy as np
import basics.functions as bf
import diffraction.calculations as dc
import filehandling.general as fg
import filehandling.specific as fs
import plotting.specific as ps
# define settings and import the data files
# plotResMwl = False
plotResMwl = True
showErr = True
# showErr = False
fileNames = fg.requestFiles((("Data files", "*.dat"), ),
"Select P61A data file", "on")
# import all data
allData = dict()
allMetaInfo = dict()
for fileName in fileNames:
data, metaInfo = fs.loadFileP61A2(fileName)
allData[fileName] = data
allMetaInfo[fileName] = metaInfo
# combine all data for one analysis
combinedData = allData[fileNames[0]]
keyList = bf.getKeyList(combinedData)
for fileName in fileNames[1:]:
for key in keyList:
combinedData[key] = np.concatenate(
(combinedData[key], allData[fileName][key]))
# prepare data for multi wavelength and universal plot analysis
a0Val = 0.289
