def _relionTomoStar2Subtomograms(prot, outputSubTomogramsSet, tomoTable, invert):
ih = ImageHandler()
samplingRate = outputSubTomogramsSet.getSamplingRate()
for row, inSubtomo in zip(tomoTable, prot.inputSubtomos.get()):
subtomo = SubTomogram()
coordinate3d = Coordinate3D()
transform = Transform()
origin = Transform()
volname = row.get(TOMO_NAME, FILE_NOT_FOUND)
subtomoFn = row.get(SUBTOMO_NAME, FILE_NOT_FOUND)
subtomo.setVolName(managePath4Sqlite(volname))
subtomo.setTransform(transform)
subtomo.setAcquisition(TomoAcquisition())
subtomo.setClassId(row.get('rlnClassNumber', 0))
subtomo.setSamplingRate(samplingRate)
subtomo.setCoordinate3D(coordinate3d) # Needed to get later the tomogram pointer via getCoordinate3D()
x = row.get(COORD_X, 0)
y = row.get(COORD_Y, 0)
z = row.get(COORD_Z, 0)
tiltPrior = row.get(TILT_PRIOR, 0)
psiPrior = row.get(PSI_PRIOR, 0)
# ctf3d = row.get(CTF_MISSING_WEDGE, FILE_NOT_FOUND)
coordinate3d = subtomo.getCoordinate3D()
coordinate3d.setX(float(x), BOTTOM_LEFT_CORNER)
coordinate3d.setY(float(y), BOTTOM_LEFT_CORNER)
coordinate3d.setZ(float(z), BOTTOM_LEFT_CORNER)
coordinate3d._3dcftMrcFile = inSubtomo.getCoordinate3D()._3dcftMrcFile # Used for the ctf3d in Relion 3.0 (tomo)
M = _getTransformMatrix(row, invert)
transform.setMatrix(M)
subtomo.setCoordinate3D(coordinate3d)
subtomo._tiltPriorAngle = Float(tiltPrior)
subtomo._psiPriorAngle = Float(psiPrior)
# Set the origin and the dimensions of the current subtomogram
x, y, z, n = ih.getDimensions(subtomoFn)
zDim, _ = manageIhDims(subtomoFn, z, n)
origin.setShifts(x / -2. * samplingRate, y / -2. * samplingRate, zDim / -2. * samplingRate)
subtomo.setOrigin(origin)
subtomo.setFileName(managePath4Sqlite(subtomoFn))
# if subtomo is in a vesicle
if 'tid_' in subtomoFn:
vesicleId = subtomoFn.split('tid_')[1]
vesicleId = vesicleId[0]
scoor = subtomo.getCoordinate3D()
scoor.setGroupId(vesicleId)
subtomo.setCoordinate3D(scoor)
# Add current subtomogram to the output set
outputSubTomogramsSet.append(subtomo)
def rowToAlignment(alignmentList, alignType):
"""
is2D == True-> matrix is 2D (2D images alignment)
otherwise matrix is 3D (3D volume alignment or projection)
invTransform == True -> for xmipp implies projection
"""
# use all angles in 2D since we might have mirrors
# is2D = alignType == em.ALIGN_2D
inverseTransform = alignType == emcts.ALIGN_PROJ
alignment = Transform()
angles = numpy.zeros(3)
shifts = numpy.zeros(3)
shifts[0] = alignmentList[3]
shifts[1] = alignmentList[4]
shifts[2] = 0
angles[0] = alignmentList[0]
angles[1] = alignmentList[1]
angles[2] = alignmentList[2]
matrix = matrixFromGeometry(shifts, angles, inverseTransform)
alignment.setMatrix(matrix)
return alignment
def createPhantomsStep(self):
mwfilter = self.mwfilter.get()
rotmin = self.rotmin.get()
rotmax = self.rotmax.get()
tiltmin = self.tiltmin.get()
tiltmax = self.tiltmax.get()
psimin = self.psimin.get()
psimax = self.psimax.get()
fnVol = self._getExtraPath("phantom000.vol")
if self.option.get() == 0:
inputVol = self.inputVolume.get()
fnInVol = inputVol.getLocation()[1]
dim = inputVol.getDim()
if mwfilter:
mwangle = self.mwangle.get()
self.runJob(
"xmipp_transform_filter",
" --fourier wedge -%d %d 0 0 0 -i %s -o %s" %
(mwangle, mwangle, fnInVol, fnVol))
else:
self.runJob("xmipp_image_convert",
" -i %s -o %s" % (fnInVol, fnVol))
else:
desc = self.create.get()
fnDescr = self._getExtraPath("phantom.descr")
fhDescr = open(fnDescr, 'w')
fhDescr.write(desc)
fhDescr.close()
dim = [desc.split()[0], desc.split()[1], desc.split()[2]]
self.runJob("xmipp_phantom_create",
" -i %s -o %s" % (fnDescr, fnVol))
if mwfilter:
mwangle = self.mwangle.get()
self.runJob(
"xmipp_transform_filter",
" --fourier wedge -%d %d 0 0 0 -i %s -o %s" %
(mwangle, mwangle, fnVol, fnVol))
self.outputSet = self._createSetOfSubTomograms(
self._getOutputSuffix(SetOfSubTomograms))
self.outputSet.setDim(dim)
self.outputSet.setSamplingRate(self.sampling.get())
coordsBool = self.coords.get()
if coordsBool:
tomos = self.tomos.get()
tomo = tomos.getFirstItem()
tomoDim = tomo.getDim()
self.coords = self._createSetOfCoordinates3D(tomos)
subtomobase = SubTomogram()
acq = TomoAcquisition()
subtomobase.setAcquisition(acq)
subtomobase.setLocation(fnVol)
subtomobase.setSamplingRate(self.sampling.get())
transformBase = Transform()
transformBase.setMatrix(np.identity(4))
subtomobase.setTransform(transformBase)
if coordsBool:
coor = Coordinate3D()
coor.setVolume(tomo)
coor.setX(np.random.randint(0, tomoDim[0]),
const.BOTTOM_LEFT_CORNER)
coor.setY(np.random.randint(0, tomoDim[1]),
const.BOTTOM_LEFT_CORNER)
coor.setZ(np.random.randint(0, tomoDim[2]),
const.BOTTOM_LEFT_CORNER)
subtomobase.setCoordinate3D(coor)
subtomobase.setVolName(tomo.getFileName())
self.coords.append(coor)
self.coords.setBoxSize(subtomobase.getDim()[0])
self.outputSet.append(subtomobase)
for i in range(int(self.nsubtomos.get()) - 1):
fnPhantomi = self._getExtraPath("phantom%03d.vol" % int(i + 1))
rot = np.random.randint(rotmin, rotmax)
tilt = np.random.randint(tiltmin, tiltmax)
psi = np.random.randint(psimin, psimax)
self.runJob(
"xmipp_transform_geometry",
" -i %s -o %s --rotate_volume euler %d %d %d " %
(fnVol, fnPhantomi, rot, tilt, psi))
if mwfilter:
self.runJob(
"xmipp_transform_filter",
" --fourier wedge -%d %d 0 0 0 -i %s -o %s" %
(mwangle, mwangle, fnPhantomi, fnPhantomi))
subtomo = SubTomogram()
subtomo.setAcquisition(acq)
subtomo.setLocation(fnPhantomi)
subtomo.setSamplingRate(self.sampling.get())
A = euler_matrix(np.deg2rad(psi), np.deg2rad(tilt),
np.deg2rad(rot), 'szyz')
transform = Transform()
transform.setMatrix(A)
subtomo.setTransform(transform)
if coordsBool:
coor = Coordinate3D()
coor.setVolume(tomo)
coor.setX(np.random.randint(0, tomoDim[0]),
const.BOTTOM_LEFT_CORNER)
coor.setY(np.random.randint(0, tomoDim[1]),
const.BOTTOM_LEFT_CORNER)
coor.setZ(np.random.randint(0, tomoDim[2]),
const.BOTTOM_LEFT_CORNER)
subtomo.setCoordinate3D(coor)
subtomo.setVolName(tomo.getFileName())
self.coords.append(coor)
self.outputSet.append(subtomo)
if coordsBool:
self.outputSet.setCoordinates3D(self.coords)