def initializeRefinementUploadVariables(self):
''' untars results, reads required parameters, establishes necessary objects for upload script '''
apDisplay.printColor(
"uploading refinement results for %s reconstruction routine" %
(self.package), "cyan")
### establish directories and make an appion results directory
self.basepath = os.path.abspath(self.params['rundir'])
self.resultspath = os.path.abspath(
os.path.join(self.params['rundir'],
str(self.package) + "_results"))
if not os.path.isdir(self.resultspath):
os.mkdir(self.resultspath)
self.reconpath = os.path.abspath(
os.path.join(self.params['rundir'],
self.runparams['reconstruction_working_dir']))
### get all stack parameters, map particles in reconstruction to particles in stack, get all model data
self.stackdata = apStack.getOnlyStackData(self.runparams['stackid'])
self.stackmapping = apRecon.partnum2defid(self.runparams['stackid'])
self.modeldata = []
if len(self.runparams['modelid'].split(",")) > 1:
models = self.runparams['modelid'].split(",")
for i in range(len(models)):
self.modeldata.append(
appiondata.ApInitialModelData.direct_query(int(models[i])))
else:
self.modeldata.append(
appiondata.ApInitialModelData.direct_query(
self.runparams['modelid']))
return
def start(self):
"""
this is the main component of the script
where all the processing is done
"""
### initialize some variables
self.runq = None
self.apix = apStack.getStackPixelSizeFromStackId(self.params['stackid'])
apDisplay.printMsg("Pixel size: %.5f"%(self.apix))
self.boxsize = apStack.getStackBoxsize(self.params['stackid'])
apDisplay.printMsg("Box size: %d"%(self.boxsize))
self.checkResults()
self.stackmapping = apRecon.partnum2defid(self.params['stackid'])
self.numiter = self.getNumberOfIterations()
for i in range(self.numiter):
iternum = i+1
apDisplay.printColor("\nUploading iteration %d of %d\n"%(iternum, self.numiter), "green")
self.uploadIteration(iternum)
reconrunid = apRecon.getReconRunIdFromNamePath(self.params['runname'], self.params['rundir'])
if reconrunid:
apDisplay.printMsg("calculating euler jumpers for recon="+str(reconrunid))
eulerjump = apEulerJump.ApEulerJump()
eulerjump.calculateEulerJumpsForEntireRecon(reconrunid, self.params['stackid'])
apRecon.setGoodBadParticlesFromReconId(reconrunid)
else:
apDisplay.printWarning("Could not find recon run id")
def initializeRefinementUploadVariables(self):
""" untars results, reads required parameters, establishes necessary objects for upload script """
apDisplay.printColor("uploading refinement results for %s reconstruction routine" % (self.package), "cyan")
### establish directories and make an appion results directory
self.basepath = os.path.abspath(self.params["rundir"])
self.resultspath = os.path.abspath(os.path.join(self.params["rundir"], str(self.package) + "_results"))
if not os.path.isdir(self.resultspath):
os.mkdir(self.resultspath)
self.reconpath = os.path.abspath(
os.path.join(self.params["rundir"], self.runparams["reconstruction_working_dir"])
)
### get all stack parameters, map particles in reconstruction to particles in stack, get all model data
self.stackdata = apStack.getOnlyStackData(self.runparams["stackid"])
self.stackmapping = apRecon.partnum2defid(self.runparams["stackid"])
self.modeldata = []
if len(self.runparams["modelid"].split(",")) > 1:
models = self.runparams["modelid"].split(",")
for i in range(len(models)):
self.modeldata.append(appiondata.ApInitialModelData.direct_query(int(models[i])))
else:
self.modeldata.append(appiondata.ApInitialModelData.direct_query(self.runparams["modelid"]))
return
def start(self):
"""
this is the main component of the script
where all the processing is done
"""
### initialize some variables
self.runq = None
self.apix = apStack.getStackPixelSizeFromStackId(self.params['stackid'])
apDisplay.printMsg("Pixel size: %.5f"%(self.apix))
self.boxsize = apStack.getStackBoxsize(self.params['stackid'])
apDisplay.printMsg("Box size: %d"%(self.boxsize))
self.checkResults()
self.stackmapping = apRecon.partnum2defid(self.params['stackid'])
self.numiter = self.getNumberOfIterations()
for i in range(self.numiter):
iternum = i+1
apDisplay.printColor("\nUploading iteration %d of %d\n"%(iternum, self.numiter), "green")
self.uploadIteration(iternum)
reconrunid = apRecon.getReconRunIdFromNamePath(self.params['runname'], self.params['rundir'])
if reconrunid:
apDisplay.printMsg("calculating euler jumpers for recon="+str(reconrunid))
eulerjump = apEulerJump.ApEulerJump()
eulerjump.calculateEulerJumpsForEntireRecon(reconrunid, self.params['stackid'])
apRecon.setGoodBadParticlesFromReconId(reconrunid)
else:
apDisplay.printWarning("Could not find recon run id")
def start(self):
if self.params['rundir'] is None or not os.path.isdir(
self.params['rundir']):
apDisplay.printError("upload directory does not exist: " +
str(self.params['rundir']))
### create temp directory for extracting data
self.params['tmpdir'] = os.path.join(self.params['rundir'], "temp")
apParam.createDirectory(self.params['tmpdir'], warning=True)
### make sure that the stack & model IDs exist in database
emanJobFile = self.findEmanJobFile()
self.params['stack'] = apStack.getOnlyStackData(self.params['stackid'])
self.stackmapping = apRecon.partnum2defid(self.params['stackid'])
self.params['model'] = appiondata.ApInitialModelData.direct_query(
self.params['modelid'])
self.params['boxsize'] = apStack.getStackBoxsize(
self.params['stackid'])
### parse out the refinement parameters from the log file
self.parseLogFile()
### parse out the message passing subclassification parameters from the job/log file
if self.params['package'] == 'EMAN/MsgP':
self.parseMsgPassingParams()
### convert class average files from old to new format
self.convertClassAvgFiles()
### get a list of the files in the directory
self.listFiles()
### create a refinementRun entry in the database
self.insertRefinementRun()
if self.params['euleronly'] is False:
### insert the Iteration info
for iteration in self.iterationdatas:
### if only uploading one iteration, skip to that one
if self.params['oneiter'] and int(
iteration['num']) != self.params['oneiter']:
continue
### if beginning at later iteration, skip to that one
if self.params['startiter'] and int(
iteration['num']) < self.params['startiter']:
continue
### if beginning at later iteration, skip to that one
if self.params['enditer'] and int(
iteration['num']) > self.params['enditer']:
continue
apDisplay.printColor(
"\nUploading iteration " + str(iteration['num']) + " of " +
str(len(self.iterationdatas)) + "\n", "green")
for i in range(75):
sys.stderr.write("#")
sys.stderr.write("\n")
self.insertIteration(iteration)
### calculate euler jumps
if self.params['commit'] is True:
reconrunid = self.params['refineRun'].dbid
stackid = self.params['stack'].dbid
if self.params['oneiter'] is None and len(self.iterationdatas) > 1:
apDisplay.printMsg("calculating euler jumpers for recon=" +
str(reconrunid))
eulerjump = apEulerJump.ApEulerJump()
eulerjump.calculateEulerJumpsForEntireRecon(
reconrunid, stackid)
### coran keep plot
if self.params['package'] == 'EMAN/SpiCoran':
apCoranPlot.makeCoranKeepPlot(reconrunid)
apRecon.setGoodBadParticlesFromReconId(reconrunid)
def start(self):
if self.params['rundir'] is None or not os.path.isdir(self.params['rundir']):
apDisplay.printError("upload directory does not exist: "+str(self.params['rundir']))
### create temp directory for extracting data
self.params['tmpdir'] = os.path.join(self.params['rundir'], "temp")
apParam.createDirectory(self.params['tmpdir'], warning=True)
### make sure that the stack & model IDs exist in database
emanJobFile = self.findEmanJobFile()
self.params['stack'] = apStack.getOnlyStackData(self.params['stackid'])
self.stackmapping = apRecon.partnum2defid(self.params['stackid'])
self.params['model'] = appiondata.ApInitialModelData.direct_query(self.params['modelid'])
self.params['boxsize'] = apStack.getStackBoxsize(self.params['stackid'])
### parse out the refinement parameters from the log file
self.parseLogFile()
### parse out the message passing subclassification parameters from the job/log file
if self.params['package'] == 'EMAN/MsgP':
self.parseMsgPassingParams()
### convert class average files from old to new format
self.convertClassAvgFiles()
### get a list of the files in the directory
self.listFiles()
### create a refinementRun entry in the database
self.insertRefinementRun()
if self.params['euleronly'] is False:
### insert the Iteration info
for iteration in self.iterationdatas:
### if only uploading one iteration, skip to that one
if self.params['oneiter'] and int(iteration['num']) != self.params['oneiter']:
continue
### if beginning at later iteration, skip to that one
if self.params['startiter'] and int(iteration['num']) < self.params['startiter']:
continue
### if beginning at later iteration, skip to that one
if self.params['enditer'] and int(iteration['num']) > self.params['enditer']:
continue
apDisplay.printColor("\nUploading iteration "+str(iteration['num'])+" of "
+str(len(self.iterationdatas))+"\n", "green")
for i in range(75):
sys.stderr.write("#")
sys.stderr.write("\n")
self.insertIteration(iteration)
### calculate euler jumps
if self.params['commit'] is True:
reconrunid = self.params['refineRun'].dbid
stackid = self.params['stack'].dbid
if self.params['oneiter'] is None and len(self.iterationdatas) > 1:
apDisplay.printMsg("calculating euler jumpers for recon="+str(reconrunid))
eulerjump = apEulerJump.ApEulerJump()
eulerjump.calculateEulerJumpsForEntireRecon(reconrunid, stackid)
### coran keep plot
if self.params['package']=='EMAN/SpiCoran':
apCoranPlot.makeCoranKeepPlot(reconrunid)
apRecon.setGoodBadParticlesFromReconId(reconrunid)