def getBonlyOutputFromLog(self, _strBestLog):
listLog = _strBestLog.split("\n")
indexLine = 0
xsDataResultBest = XSDataResultBest()
xsDataBestCollectionPlan = XSDataBestCollectionPlan()
xsDataCrystalScale = XSDataCrystalScale()
#
while not "Relative scale" in listLog[indexLine]:
indexLine += 1
xsDataCrystalScale.scale = XSDataDouble(listLog[indexLine].split()[-1])
#
while not "Overall B-factor" in listLog[indexLine]:
indexLine += 1
xsDataCrystalScale.bFactor = XSDataDouble(listLog[indexLine].split()[-2])
xsDataBestCollectionPlan.crystalScale = xsDataCrystalScale
xsDataResultBest.addCollectionPlan(xsDataBestCollectionPlan)
return xsDataResultBest
def getBonlyOutputFromLog(self, _strBestLog):
listLog = _strBestLog.split("\n")
indexLine = 0
xsDataResultBest = XSDataResultBest()
xsDataBestCollectionPlan = XSDataBestCollectionPlan()
xsDataCrystalScale = XSDataCrystalScale()
#
while not "Relative scale" in listLog[indexLine]:
indexLine += 1
xsDataCrystalScale.scale = XSDataDouble(listLog[indexLine].split()[-1])
#
while not "Overall B-factor" in listLog[indexLine]:
indexLine += 1
xsDataCrystalScale.bFactor = XSDataDouble(
listLog[indexLine].split()[-2])
xsDataBestCollectionPlan.crystalScale = xsDataCrystalScale
xsDataResultBest.addCollectionPlan(xsDataBestCollectionPlan)
return xsDataResultBest
def getDataCollectionOutputDataFromLog(self, _strBestLog):
xsDataResultBest = XSDataResultBest()
# loop through the lines of the log file
isScanningWedge = False
indexLine = 0
listLog = _strBestLog.split("\n")
iCollectionPlanNumber = 1
while indexLine < len(listLog):
if "Plan of data collection for radiation damage characterisation" in listLog[indexLine]:
xsDataBestCollectionPlan = XSDataBestCollectionPlan()
xsDataBestStrategySummary = XSDataBestStrategySummary()
indexLine += 2
regEx = re.compile(""" Resolution limit =\s*(\d+\.\d+) Angstrom\s*Distance =\s*(\d+\.\d+)mm""")
matchObj = regEx.search(listLog[indexLine])
if matchObj == None:
raise BaseException("Cannot parse best log file!")
resultMatch = matchObj.groups()
resultion = float(resultMatch[0])
distance = float(resultMatch[1])
xsDataBestStrategySummary.resolution = XSDataDouble(resultion)
xsDataBestStrategySummary.distance = XSDataLength(distance)
xsDataBestCollectionPlan.strategySummary = xsDataBestStrategySummary
# Burn strategy
indexLine += 7
collectionRunNumber = 1
while not listLog[indexLine].startswith("-------------------------------"):
listLine = listLog[indexLine].split()
if listLine[0].startswith("exposure") or listLine[0].startswith("burn"):
xsDataBestCollectionRun = XSDataBestCollectionRun()
xsDataBestCollectionRun.collectionRunNumber = XSDataInteger(collectionRunNumber)
xsDataBestCollectionRun.action = XSDataString(listLine[0])
xsDataBestCollectionRun.phiStart = XSDataAngle(listLine[1])
xsDataBestCollectionRun.phiWidth = XSDataAngle(listLine[2])
xsDataBestCollectionRun.exposureTime = XSDataTime(listLine[3])
xsDataBestCollectionRun.numberOfImages = XSDataInteger(listLine[4].split("|")[0])
xsDataBestCollectionRun.transmission = XSDataDouble(listLine[5])
xsDataBestCollectionPlan.addCollectionRun(xsDataBestCollectionRun)
collectionRunNumber += 1
indexLine += 1
xsDataBestCollectionPlan.collectionPlanNumber = XSDataInteger(iCollectionPlanNumber)
xsDataResultBest.addCollectionPlan(xsDataBestCollectionPlan)
if "Main Wedge" in listLog[indexLine] or "Low resolution Wedge" in listLog[indexLine] \
or "Strategy for SAD data collection" in listLog[indexLine]:
isScanningWedge = True
xsDataBestCollectionPlan = XSDataBestCollectionPlan()
xsDataBestStrategySummary = XSDataBestStrategySummary()
if "Main Wedge" in listLog[indexLine]:
indexLine += 2
# ResolutionReasoning
xsDataBestStrategySummary.resolutionReasoning = XSDataString(listLog[indexLine].strip())
elif "Strategy for SAD data collection" in listLog[indexLine]:
indexLine += 2
xsDataBestStrategySummary.resolutionReasoning = XSDataString(listLog[indexLine].strip())
else:
xsDataBestStrategySummary.resolutionReasoning = XSDataString("Low-resolution pass, no overloads and full completeness")
# Resolution, transmission, distance
indexLine += 1
while not "Resolution limit" in listLog[indexLine]:
indexLine += 1
regEx = re.compile(""" Resolution limit =\s*(\d+\.\d+) Angstrom Transmission =\s*(\d+\.\d+)% Distance =\s*(\d+\.\d+)mm""")
matchObj = regEx.search(listLog[indexLine])
if matchObj == None:
raise BaseException("Cannot parse best log file!")
resultMatch = matchObj.groups()
resultion = float(resultMatch[0])
transmission = float(resultMatch[1])
distance = float(resultMatch[2])
xsDataBestStrategySummary.resolution = XSDataDouble(resultion)
xsDataBestStrategySummary.transmission = XSDataDouble(transmission)
xsDataBestStrategySummary.distance = XSDataLength(distance)
# Resolution, transmission, distance
indexLine += 8
while not listLog[indexLine].startswith("-------------------------------"):
listLine = listLog[indexLine].split()
xsDataBestCollectionRun = XSDataBestCollectionRun()
xsDataBestCollectionRun.collectionRunNumber = XSDataInteger(listLine[0])
xsDataBestCollectionRun.phiStart = XSDataAngle(listLine[1])
xsDataBestCollectionRun.phiWidth = XSDataAngle(listLine[2])
xsDataBestCollectionRun.exposureTime = XSDataTime(listLine[3])
xsDataBestCollectionRun.numberOfImages = XSDataInteger(listLine[4].split("|")[0])
xsDataBestCollectionRun.overlaps = XSDataString(listLine[5])
xsDataBestCollectionPlan.addCollectionRun(xsDataBestCollectionRun)
indexLine += 1
#
xsDataBestStrategySummary.completeness = XSDataDouble(listLine[11])
#
while not "Redundancy" in listLog[indexLine]:
indexLine += 1
xsDataBestStrategySummary.redundancy = XSDataDouble(listLog[indexLine].split()[-1])
#
while not "I/Sigma (outer shell)" in listLog[indexLine]:
indexLine += 1
xsDataBestStrategySummary.iSigma = XSDataDouble(listLog[indexLine].split()[6].replace(")", ""))
#
while not "Total Exposure time" in listLog[indexLine]:
indexLine += 1
xsDataBestStrategySummary.totalExposureTime = XSDataTime(listLog[indexLine].split()[4])
#
while not "Total Data Collection time" in listLog[indexLine]:
indexLine += 1
xsDataBestStrategySummary.totalDataCollectionTime = XSDataTime(listLog[indexLine].split()[5])
#
while not "Wedge Data Collection Statistics according to the Strategy" in listLog[indexLine]:
indexLine += 1
(xsDataBestStatisticalPrediction, indexLine) = self.getXSDataBestStatisticalPrediction(listLog, indexLine)
xsDataBestCollectionPlan.strategySummary = xsDataBestStrategySummary
xsDataBestCollectionPlan.statisticalPrediction = xsDataBestStatisticalPrediction
xsDataBestCollectionPlan.collectionPlanNumber = XSDataInteger(iCollectionPlanNumber)
iCollectionPlanNumber += 1
xsDataResultBest.addCollectionPlan(xsDataBestCollectionPlan)
if "Additional information" in listLog[indexLine]:
#
while not "Relative scale" in listLog[indexLine]:
indexLine += 1
scale = float(listLog[indexLine].split()[-1])
#
while not "Overall B-factor" in listLog[indexLine]:
indexLine += 1
#
bFactor = float(listLog[indexLine].split()[-2])
while not "Estimated limit of resolution" in listLog[indexLine]:
indexLine += 1
rankingResolution = float(listLog[indexLine].split()[5])
for collectionPlan in xsDataResultBest.collectionPlan:
xsDataCrystalScale = XSDataCrystalScale()
xsDataCrystalScale.scale = XSDataDouble(scale)
xsDataCrystalScale.bFactor = XSDataDouble(bFactor)
collectionPlan.crystalScale = xsDataCrystalScale
collectionPlan.strategySummary.rankingResolution = XSDataDouble(rankingResolution)
indexLine += 1
return xsDataResultBest
def getDataCollectionOutputDataFromLog(self, _strBestLog):
xsDataResultBest = XSDataResultBest()
# loop through the lines of the log file
isScanningWedge = False
indexLine = 0
listLog = _strBestLog.split("\n")
iCollectionPlanNumber = 1
while indexLine < len(listLog):
if "Plan of data collection for radiation damage characterisation" in listLog[
indexLine]:
xsDataBestCollectionPlan = XSDataBestCollectionPlan()
xsDataBestStrategySummary = XSDataBestStrategySummary()
indexLine += 2
regEx = re.compile(
""" Resolution limit =\s*(\d+\.\d+) Angstrom\s*Distance =\s*(\d+\.\d+)mm"""
)
matchObj = regEx.search(listLog[indexLine])
if matchObj == None:
raise BaseException("Cannot parse best log file!")
resultMatch = matchObj.groups()
resultion = float(resultMatch[0])
distance = float(resultMatch[1])
xsDataBestStrategySummary.resolution = XSDataDouble(resultion)
xsDataBestStrategySummary.distance = XSDataLength(distance)
xsDataBestCollectionPlan.strategySummary = xsDataBestStrategySummary
# Burn strategy
indexLine += 7
collectionRunNumber = 1
while not listLog[indexLine].startswith(
"-------------------------------"):
listLine = listLog[indexLine].split()
if listLine[0].startswith(
"exposure") or listLine[0].startswith("burn"):
xsDataBestCollectionRun = XSDataBestCollectionRun()
xsDataBestCollectionRun.collectionRunNumber = XSDataInteger(
collectionRunNumber)
xsDataBestCollectionRun.action = XSDataString(
listLine[0])
xsDataBestCollectionRun.phiStart = XSDataAngle(
listLine[1])
xsDataBestCollectionRun.phiWidth = XSDataAngle(
listLine[2])
xsDataBestCollectionRun.exposureTime = XSDataTime(
listLine[3])
xsDataBestCollectionRun.numberOfImages = XSDataInteger(
listLine[4].split("|")[0])
xsDataBestCollectionRun.transmission = XSDataDouble(
listLine[5])
xsDataBestCollectionPlan.addCollectionRun(
xsDataBestCollectionRun)
collectionRunNumber += 1
indexLine += 1
xsDataBestCollectionPlan.collectionPlanNumber = XSDataInteger(
iCollectionPlanNumber)
xsDataResultBest.addCollectionPlan(xsDataBestCollectionPlan)
if "Main Wedge" in listLog[indexLine] or "Low resolution Wedge" in listLog[indexLine] \
or "Strategy for SAD data collection" in listLog[indexLine]:
isScanningWedge = True
xsDataBestCollectionPlan = XSDataBestCollectionPlan()
xsDataBestStrategySummary = XSDataBestStrategySummary()
if "Main Wedge" in listLog[indexLine]:
indexLine += 2
# ResolutionReasoning
xsDataBestStrategySummary.resolutionReasoning = XSDataString(
listLog[indexLine].strip())
elif "Strategy for SAD data collection" in listLog[indexLine]:
indexLine += 2
xsDataBestStrategySummary.resolutionReasoning = XSDataString(
listLog[indexLine].strip())
else:
xsDataBestStrategySummary.resolutionReasoning = XSDataString(
"Low-resolution pass, no overloads and full completeness"
)
# Resolution, transmission, distance
indexLine += 1
while not "Resolution limit" in listLog[indexLine]:
indexLine += 1
regEx = re.compile(
""" Resolution limit =\s*(\d+\.\d+) Angstrom Transmission =\s*(\d+\.\d+)% Distance =\s*(\d+\.\d+)mm"""
)
matchObj = regEx.search(listLog[indexLine])
if matchObj == None:
raise BaseException("Cannot parse best log file!")
resultMatch = matchObj.groups()
resultion = float(resultMatch[0])
transmission = float(resultMatch[1])
distance = float(resultMatch[2])
xsDataBestStrategySummary.resolution = XSDataDouble(resultion)
xsDataBestStrategySummary.transmission = XSDataDouble(
transmission)
xsDataBestStrategySummary.distance = XSDataLength(distance)
# Resolution, transmission, distance
indexLine += 8
while not listLog[indexLine].startswith(
"-------------------------------"):
listLine = listLog[indexLine].split()
xsDataBestCollectionRun = XSDataBestCollectionRun()
xsDataBestCollectionRun.collectionRunNumber = XSDataInteger(
listLine[0])
xsDataBestCollectionRun.phiStart = XSDataAngle(listLine[1])
xsDataBestCollectionRun.phiWidth = XSDataAngle(listLine[2])
xsDataBestCollectionRun.exposureTime = XSDataTime(
listLine[3])
xsDataBestCollectionRun.numberOfImages = XSDataInteger(
listLine[4].split("|")[0])
xsDataBestCollectionRun.overlaps = XSDataString(
listLine[5])
xsDataBestCollectionPlan.addCollectionRun(
xsDataBestCollectionRun)
indexLine += 1
#
xsDataBestStrategySummary.completeness = XSDataDouble(
listLine[11])
#
while not "Redundancy" in listLog[indexLine]:
indexLine += 1
xsDataBestStrategySummary.redundancy = XSDataDouble(
listLog[indexLine].split()[-1])
#
while not "I/Sigma (outer shell)" in listLog[indexLine]:
indexLine += 1
xsDataBestStrategySummary.iSigma = XSDataDouble(
listLog[indexLine].split()[6].replace(")", ""))
#
while not "Total Exposure time" in listLog[indexLine]:
indexLine += 1
xsDataBestStrategySummary.totalExposureTime = XSDataTime(
listLog[indexLine].split()[4])
#
while not "Total Data Collection time" in listLog[indexLine]:
indexLine += 1
xsDataBestStrategySummary.totalDataCollectionTime = XSDataTime(
listLog[indexLine].split()[5])
#
while not "Wedge Data Collection Statistics according to the Strategy" in listLog[
indexLine]:
indexLine += 1
(xsDataBestStatisticalPrediction,
indexLine) = self.getXSDataBestStatisticalPrediction(
listLog, indexLine)
xsDataBestCollectionPlan.strategySummary = xsDataBestStrategySummary
xsDataBestCollectionPlan.statisticalPrediction = xsDataBestStatisticalPrediction
xsDataBestCollectionPlan.collectionPlanNumber = XSDataInteger(
iCollectionPlanNumber)
iCollectionPlanNumber += 1
xsDataResultBest.addCollectionPlan(xsDataBestCollectionPlan)
if "Additional information" in listLog[indexLine]:
#
while not "Relative scale" in listLog[indexLine]:
indexLine += 1
scale = float(listLog[indexLine].split()[-1])
#
while not "Overall B-factor" in listLog[indexLine]:
indexLine += 1
#
bFactor = float(listLog[indexLine].split()[-2])
while not "Estimated limit of resolution" in listLog[indexLine]:
indexLine += 1
rankingResolution = float(listLog[indexLine].split()[5])
for collectionPlan in xsDataResultBest.collectionPlan:
xsDataCrystalScale = XSDataCrystalScale()
xsDataCrystalScale.scale = XSDataDouble(scale)
xsDataCrystalScale.bFactor = XSDataDouble(bFactor)
collectionPlan.crystalScale = xsDataCrystalScale
collectionPlan.strategySummary.rankingResolution = XSDataDouble(
rankingResolution)
indexLine += 1
return xsDataResultBest