def _convertInputStep(self):
self.info("Relion version:")
self.runJob("relion_run_motioncorr --version", "", numberOfMpi=1)
self.info("Detected version from config: %s" %
relion.Plugin.getActiveVersion())
ProtAlignMovies._convertInputStep(self)
def _convertInputStep(self):
self.info("Relion version:")
self.runJob("relion_convert_to_tiff --version", "", numberOfMpi=1)
self.info("Detected version from config: %s" %
relion.Plugin.getActiveVersion())
# Create a local link to the input gain file if necessary
inputGain = self.getInputGain()
if inputGain:
tmpGain = self._getTmpPath('gain_estimate.bin')
pwutils.createLink(inputGain, tmpGain)
pwutils.createLink(inputGain.replace('.bin', '_reliablity.bin'),
tmpGain.replace('.bin', '_reliablity.bin'))
ProtAlignMovies._convertInputStep(self)
def _updateOutputSet(self,
outputName,
outputSet,
state=pwobj.Set.STREAM_OPEN):
""" Redefine this method to update optics info. """
if outputName not in self.updatedSets:
og = OpticsGroups.fromImages(outputSet)
og.updateAll(rlnMicrographOriginalPixelSize=self.inputMovies.get().
getSamplingRate())
og.toImages(outputSet)
self.updatedSets.append(outputName)
ProtAlignMovies._updateOutputSet(self,
outputName,
outputSet,
state=state)
def _validate(self):
# Check base validation before the specific ones for Motioncor
errors = ProtAlignMovies._validate(self)
if not relion.Plugin.getActiveVersion():
errors.append("Could not detect the current Relion version. \n"
"RELION_HOME='%s'" % relion.Plugin.getHome())
return errors
def _updateOutputSet(self,
outputName,
outputSet,
state=pwobj.Set.STREAM_OPEN):
""" Redefine this method to set EER attrs. """
first = getattr(self, '_firstUpdate', True)
if first and outputName == 'outputMovies':
og = OpticsGroups.fromImages(outputSet)
if self.isEER:
og.updateAll(rlnEERGrouping=self.eerGroup.get(),
rlnEERUpsampling=self.eerSampling.get() + 1)
og.updateAll(rlnMicrographStartFrame=self.alignFrame0.get())
og.toImages(outputSet)
ProtAlignMovies._updateOutputSet(self,
outputName,
outputSet,
state=state)
self._firstUpdate = False
def _convertInputStep(self):
inputMovies = self.getInputMovies()
# parse EER gain file before its conversion to mrc
if self.isEER and inputMovies.getGain():
defects = parseEERDefects(inputMovies.getGain())
if defects:
with open(self._getExtraPath("defects_eer.txt"), "w") as f:
for d in defects:
f.write(" ".join(str(i) for i in d) + "\n")
ProtAlignMovies._convertInputStep(self)
if self.isEER:
# write FmIntFile
_, numbOfFrames, _ = inputMovies.getFramesRange()
if self.doApplyDoseFilter:
_, dose = self._getCorrectedDose(inputMovies)
else:
dose = 0.0
with open(self._getExtraPath("FmIntFile.txt"), "w") as f:
f.write("%d %d %f" % (numbOfFrames, self.eerGroup.get(), dose))
def _validate(self):
# Check base validation before the specific ones for Motioncor
errors = ProtAlignMovies._validate(self)
if not relion.Plugin.getActiveVersion():
errors.append("Could not detect the current Relion version. \n"
"RELION_HOME='%s'" % relion.Plugin.getHome())
acq = self.inputMovies.get().getAcquisition()
if self.doDW:
dose = acq.getDosePerFrame()
if dose is None or dose < 0.001:
errors.append(
"Input movies do not contain the dose per frame, "
"dose-weighting can not be performed. ")
return errors
def _createOutputMovie(self, movie):
""" Overwrite this function to store the Relion's specific
Motion model coefficients.
"""
m = ProtAlignMovies._createOutputMovie(self, movie)
# Load local motion values only if the patches are more than one
if self.patchX.get() > 2 and self.patchY.get() > 2:
try:
table = md.Table(fileName=self._getMovieExtraFn(
movie, '.star'),
tableName='local_motion_model')
coeffs = [row.rlnMotionModelCoeff for row in table]
except:
print("Failed to parse local motion from: %s" %
os.path.abspath(self._getMovieExtraFn(movie, '.star')))
coeffs = [] # Failed to parse the local motion
m._rlnMotionModelCoeff = pwobj.String(json.dumps(coeffs))
return m
def _validate(self):
if self.autoControlPoints.get():
self._setControlPoints() # make sure we work with proper values
# check execution issues
errors = ProtAlignMovies._validate(self)
errors.extend(self._validateBinary())
errors.extend(self._validateParallelProcessing())
if errors:
return errors
# check settings issues
if self.doLocalAlignment.get() and not self.useGpu.get():
errors.append("GPU is needed to do local alignment.")
if (self.controlPointX < 3):
errors.append("You have to use at least 3 control points in X dim")
if (self.controlPointY < 3):
errors.append("You have to use at least 3 control points in Y dim")
if (self.controlPointT < 3):
errors.append("You have to use at least 3 control points in T dim")
return errors
def _validate(self):
# Check base validation before the specific ones
errors = ProtAlignMovies._validate(self)
if self.doApplyDoseFilter and self.inputMovies.get():
inputMovies = self.inputMovies.get()
doseFrame = inputMovies.getAcquisition().getDosePerFrame()
if doseFrame == 0.0 or doseFrame is None:
errors.append('Dose per frame for input movies is 0 or not '
'set. You cannot apply dose filter.')
if self.doComputeMicThumbnail or self.doComputePSD:
try:
from pwem import Domain
eman2 = Domain.importFromPlugin('eman2', doRaise=True)
except:
errors.append(
"EMAN2 plugin not found!\nComputing thumbnails "
"or PSD requires EMAN2 plugin and binaries installed.")
return errors
def __init__(self, **args):
ProtAlignMovies.__init__(self, **args)
self.stepsExecutionMode = STEPS_PARALLEL
def _getFrameRange(self, n, prefix):
# Reimplement this method to ignore prefix (called from base class)
# and always use 'sum' as prefix
return ProtAlignMovies._getFrameRange(self, n, 'sum')
def __init__(self, **kwargs):
ProtAlignMovies.__init__(self, **kwargs)
self.stepsExecutionMode = STEPS_SERIAL
self.updatedSets = []
def _defineAlignmentParams(self, form):
ProtAlignMovies._defineAlignmentParams(self, form)
form.addParam('splineOrder',
params.EnumParam,
condition="doSaveAveMic or doSaveMovie",
default=self.INTERP_CUBIC,
choices=['linear', 'cubic'],
expertLevel=cons.LEVEL_ADVANCED,
label='Interpolation',
help="linear (faster but lower quality), "
"cubic (slower but more accurate).")
form.addHidden(
params.USE_GPU,
params.BooleanParam,
default=True,
label="Use GPU for execution",
help="This protocol has both CPU and GPU implementation.\
Select the one you want to use.")
form.addHidden(params.GPU_LIST,
params.StringParam,
default='0',
expertLevel=cons.LEVEL_ADVANCED,
label="Choose GPU IDs",
help="Add a list of GPU devices that can be used")
form.addParam(
'maxResForCorrelation',
params.FloatParam,
default=30,
label='Maximal resolution (A)',
help=
"Maximal resolution in A that will be preserved during correlation."
)
form.addParam('doComputePSD',
params.BooleanParam,
default=True,
label="Compute PSD (before/after)?",
help="If Yes, the protocol will compute for each movie "
"the PSD of the average micrograph (without CC "
"alignement) and after that, to compare each PSDs")
form.addParam('maxShift',
params.IntParam,
default=30,
expertLevel=cons.LEVEL_ADVANCED,
label="Maximum shift (pixels)",
help='Maximum allowed distance (in pixels) that each '
'frame can be shifted with respect to the next.')
form.addParam('outsideMode',
params.EnumParam,
choices=['Wrapping', 'Average', 'Value'],
default=self.OUTSIDE_WRAP,
expertLevel=cons.LEVEL_ADVANCED,
label="How to fill borders",
help='How to fill the borders when shifting the frames')
# this must stay together with the outside mode
form.addParam('outsideValue',
params.FloatParam,
default=0.0,
expertLevel=cons.LEVEL_ADVANCED,
condition="outsideMode==2",
label='Fill value',
help="Fixed value for filling borders")
#Local alignment params
group = form.addGroup('Local alignment')
group.addParam(
'doLocalAlignment',
params.BooleanParam,
default=True,
label="Compute local alignment?",
help=
"If Yes, the protocol will try to determine local shifts, similarly to MotionCor2."
)
group.addParam(
'autoControlPoints',
params.BooleanParam,
default=True,
label="Auto control points",
expertLevel=cons.LEVEL_ADVANCED,
condition='doLocalAlignment',
help=
"If on, protocol will automatically determine necessary number of control points."
)
line = group.addLine('Number of control points',
expertLevel=cons.LEVEL_ADVANCED,
help='Number of control points use for BSpline.',
condition='not autoControlPoints')
line.addParam('controlPointX', params.IntParam, default=6, label='X')
line.addParam('controlPointY', params.IntParam, default=6, label='Y')
line.addParam('controlPointT', params.IntParam, default=5, label='t')
group.addParam('minLocalRes',
params.FloatParam,
default=500,
expertLevel=cons.LEVEL_ADVANCED,
label='Min size of the patch (A)',
help="How many A should contain each patch?")
group.addParam(
'skipAutotuning',
params.BooleanParam,
default=False,
expertLevel=cons.LEVEL_ADVANCED,
label='Skip autotuning',
help=
"We try to faster settings of for the FFT library. This takes some time, "
"but consecutive executions will be faster and use less memory."
"Set to True (autotuning will be turned off) if you process just few movies"
)
group.addParam(
'groupNFrames',
params.IntParam,
default=3,
expertLevel=cons.LEVEL_ADVANCED,
label='Group N frames',
help=
'Group every specified number of frames by adding them together. \
The alignment is then performed on the summed frames.',
condition='doLocalAlignment')
form.addSection(label="Gain orientation")
form.addParam('gainRot',
params.EnumParam,
choices=[
'no rotation', '90 degrees', '180 degrees',
'270 degrees'
],
label="Rotate gain reference:",
default=self.NO_ROTATION,
display=params.EnumParam.DISPLAY_COMBO,
help="Rotate gain reference counter-clockwise.")
form.addParam(
'gainFlip',
params.EnumParam,
choices=['no flip', 'upside down', 'left right'],
label="Flip gain reference:",
default=self.NO_FLIP,
display=params.EnumParam.DISPLAY_COMBO,
help="Flip gain reference after rotation. "
"For tiff movies, gain is automatically upside-down flipped")
form.addParallelSection(threads=1, mpi=1)
def _createOutputMovie(self, movie):
alignedMovie = ProtAlignMovies._createOutputMovie(self, movie)
self._setAlignmentInfo(movie, alignedMovie)
return alignedMovie
def __init__(self, **kwargs):
ProtAlignMovies.__init__(self, **kwargs)
self.stepsExecutionMode = STEPS_PARALLEL
self.isEER = False