def _defineParams(self, form):
form.addSection(label='Input')
form.addParam('inputMicrographs',
params.PointerParam,
pointerClass='SetOfMicrographs',
label='Input micrographs',
important=True,
help='Select the input micrographs. '
'If using the *Optimize* mode, just a subset of '
'micrographs are used to compute the FOM maps. '
'If in *Compute* mode, all micrographs will be '
'auto-picked.')
form.addParam('ctfRelations',
params.RelationParam,
relationName=RELATION_CTF,
attributeName='getInputMicrographs',
label='CTF estimation',
help='Choose some CTF estimation related to the '
'input micrographs.')
# From Relion 3.+, references can be 2D or 3D
# need to add these parameters
refCondition = 'referencesType==%s' % REF_AVERAGES
ref3dCondition = 'referencesType==%s' % REF_VOLUME
form.addSection('References')
form.addParam('referencesType',
params.EnumParam,
choices=['2D', '3D'],
default=REF_AVERAGES,
display=params.EnumParam.DISPLAY_HLIST,
label='References',
help='The preferred way to autopick is '
'by providing 2D references images that were '
'obtained by 2D classification. \n'
'The Gaussian blob references may be useful to '
'kickstart a new data set.')
# In Relion 3 it is also possible to pass a volume as reference for
# autopicking
form.addParam(
'inputReferences',
params.PointerParam,
pointerClass='SetOfAverages',
condition=refCondition,
label='Input references',
important=True,
help='Input references (SetOfAverages) for auto-pick. \n\n'
'Note that the absolute greyscale needs to be correct, \n'
'so only use images with proper normalization. '
'From Relion 3.0 it is also possible to provide a '
'3D volume which projections will be used as '
'references.')
form.addParam('inputReferences3D',
params.PointerParam,
pointerClass='Volume',
condition=ref3dCondition,
label='Input references',
important=True,
help='Input volume from which 2D references will be '
'made by projection. Note that the absolute '
'greyscale needs to be correct, so only use '
'maps created by RELION itself from this data set.')
form.addParam('symmetryGroup',
params.StringParam,
default='c1',
condition=ref3dCondition,
label='Symmetry',
help="Symmetry point group of the 3D reference. "
"Only projections in the asymmetric part of the "
"sphere will be generated.")
form.addParam('angularSamplingDeg',
params.EnumParam,
default=0,
choices=ANGULAR_SAMPLING_LIST,
condition=ref3dCondition,
label='3D angular sampling (deg)',
help="There are only a few discrete angular samplings "
"possible because we use the HealPix library to "
"generate the sampling of the first two Euler "
"angles on the sphere. The samplings are approximate "
"numbers and vary slightly over the sphere.\n"
"For autopicking, 30 degrees is usually fine enough, "
"but for highly symmetrical objects one may need to "
"go finer to adequately sample the asymmetric part of "
"the sphere.")
form.addParam(
'particleDiameter',
params.IntParam,
default=-1,
label='Mask diameter (A)',
help='Diameter of the circular mask that will be applied '
'around the templates in Angstroms. When set to a '
'negative value, this value is estimated '
'automatically from the templates themselves.')
form.addParam('lowpassFilterRefs',
params.IntParam,
default=20,
label='Lowpass filter references (A)',
help='Lowpass filter that will be applied to the '
'references before template matching. \n'
'Do NOT use very high-resolution templates to '
'search your micrographs. \n'
'The signal will be too weak at high resolution '
'anyway, and you may find Einstein from noise...')
form.addParam('highpassFilterMics',
params.IntParam,
default=-1,
label='Highpass filter (A)',
help='Highpass filter that will be applied to the '
'micrographs. This may be useful to get rid of '
'background ramps due to uneven ice distributions. '
'Give a negative value to skip the highpass '
'filter. Useful values are often in the range '
'of 200-400 Angstroms.')
form.addParam(
'angularSampling',
params.IntParam,
default=5,
label='Angular sampling (deg)',
help='Angular sampling in degrees for exhaustive searches '
'of the in-plane rotations for all references.')
form.addParam('refsHaveInvertedContrast',
params.BooleanParam,
default=True,
label='References have inverted contrast?',
help='Set to Yes to indicate that the reference have '
'inverted contrast with respect to the particles '
'in the micrographs.')
form.addParam('refsCtfCorrected',
params.BooleanParam,
default=True,
label='Are References CTF corrected?',
help='Set to Yes if the references were created with '
'CTF-correction inside RELION.\n'
'If set to Yes, the input micrographs should contain '
'the CTF information.')
form.addParam(
'ignoreCTFUntilFirstPeak',
params.BooleanParam,
default=False,
label='Ignore CTFs until first peak?',
help='Set this to Yes, only if this option was also used '
'to generate the references.')
form.addSection('Autopicking')
group = form.addGroup('Autopick')
group.addParam('pickingThreshold',
params.FloatParam,
default=0.25,
label='Picking threshold:',
help='Use lower thresholds to pick more particles '
'(and more junk probably)')
group.addParam('interParticleDistance',
params.IntParam,
default=-1,
label='Minimum inter-particle distance (A):',
help='Particles closer together than this distance \n'
'will be consider to be a single cluster. \n'
'From each cluster, only one particle will be '
'picked.')
group.addParam(
'maxStddevNoise',
params.FloatParam,
default=1.1,
label='Maximum stddev noise:',
help='This is useful to prevent picking in carbon areas, '
'or areas with big contamination features. Peaks in '
'areas where the background standard deviation in '
'the normalized micrographs is higher than this '
'value will be ignored. Useful values are probably '
'in the range 1.0 to 1.2. Set to -1 to switch off '
'the feature to eliminate peaks due to high '
'background standard deviations.')
group.addParam(
'minAvgNoise',
params.FloatParam,
default=-999,
label='Minimum avg noise:',
help='This is useful to prevent picking in carbon areas,'
' or areas with big contamination features. Peaks '
'in areas where the background standard deviation '
'in the normalized micrographs is higher than this'
' value will be ignored. Useful values are '
'probably in the range -0.5 to 0. Set to -999 to '
'switch off the feature to eliminate peaks due to '
'low average background densities.')
group = form.addGroup('Computing')
group.addParam('shrinkFactor',
params.FloatParam,
default=0,
validators=[
params.Range(0, 1, "value should be "
"between 0 and 1. ")
],
label='Shrink factor',
help='This is useful to speed up the calculations, '
'and to make them less memory-intensive. The '
'micrographs will be downscaled (shrunk) to '
'calculate the cross-correlations, and peak '
'searching will be done in the downscaled FOM '
'maps. When set to 0, the micrographs will de '
'downscaled to the lowpass filter of the '
'references, a value between 0 and 1 will '
'downscale the micrographs by that factor. '
'Note that the results will not be exactly '
'the same when you shrink micrographs!')
group.addParam('doGpu',
params.BooleanParam,
default=True,
label='Use GPU acceleration?',
help='If set to Yes, the job will try to use GPU '
'acceleration.')
group.addParam('gpusToUse',
params.StringParam,
default='',
label='Which GPUs to use:',
condition='doGpu',
help='This argument is not necessary. If left empty, '
'the job itself will try to allocate available GPU '
'resources. You can override the default '
'allocation by providing a list of which GPUs '
'(0,1,2,3, etc) to use. MPI-processes are '
'separated by ":", threads by ",". '
'For example: "0,0:1,1:0,0:1,1"')
form.addParam(
'extraParams',
params.StringParam,
default='',
label='Additional arguments:',
help='In this box command-line arguments may be provided '
'that are not generated by the GUI. This may be '
'useful for testing developmental options and/or '
'expert use of the program. \n'
'The command "relion_autopick" will print a list '
'of possible options.')
self._defineStreamingParams(form)
form.addParallelSection(threads=0, mpi=4)
def _defineParams(self, form):
form.addSection(label='Input')
form.addParam('inputMicrographs',
params.PointerParam,
pointerClass='SetOfMicrographs',
label='Input micrographs',
important=True,
help='Select the input micrographs. '
'If using the *Optimize* mode, just a subset of '
'micrographs are used to compute the FOM maps. '
'If in *Compute* mode, all micrographs will be '
'auto-picked.')
form.addParam('ctfRelations',
params.RelationParam,
relationName=RELATION_CTF,
attributeName='getInputMicrographs',
label='CTF estimation',
help='Choose some CTF estimation related to the '
'input micrographs.')
form.addParam('runType',
params.EnumParam,
default=RUN_OPTIMIZE,
choices=['Optimize params', 'Pick all micrographs'],
display=params.EnumParam.DISPLAY_LIST,
label='Run type: ',
help='Usually, first you should use the *Optimize* mode '
'to compute the FOM maps for a few micrographs and '
'use them to tune the picking parameters using the '
'wizard. After that you can run the job in *Compute*'
' mode and auto-pick all the micrographs. ')
group = form.addGroup('Micrographs for optimization',
condition='runType==%d' % RUN_OPTIMIZE)
group.addParam('micrographsSelection',
params.EnumParam,
default=MICS_AUTO,
choices=['automatic selection', 'input subset'],
display=params.EnumParam.DISPLAY_HLIST,
label='Choose micrographs by',
help='If you choose "automatic selection", you only '
'need to provide the number of microgrphs to use '
'and that number will be selected to cover the '
'defocus range. ')
group.addParam('micrographsNumber',
params.IntParam,
default='10',
condition='micrographsSelection==%d' % MICS_AUTO,
label='Micrographs for optimization:',
help='Select the number of micrographs that you want'
'to be used for the parameters optimization. ')
group.addParam('micrographsSubset',
params.PointerParam,
condition='micrographsSelection==%d' % MICS_SUBSET,
pointerClass='SetOfMicrographs',
label='Subset of micrographs',
help='Choose as input a subset of micrographs that '
'you have previously selected. '
'(Probably covering the defocus range).')
# From Relion 2.+, it can be picked with gaussian blobs, so we
# need to add these parameters
refCondition = 'referencesType==%s' % REF_AVERAGES
group = form.addGroup('References')
group.addParam('referencesType',
params.EnumParam,
choices=['References', 'Gaussian blobs'],
default=REF_AVERAGES,
display=params.EnumParam.DISPLAY_HLIST,
label='References type',
help='You may select "Gaussian blobs" to be used as '
'references. The preferred way to autopick is '
'by providing 2D references images that were '
'obtained by 2D classification. \n'
'The Gaussian blob references may be useful to '
'kickstart a new data set.')
group.addParam('gaussianPeak',
params.FloatParam,
default=0.1,
condition='referencesType==%s' % REF_BLOBS,
label='Gaussian peak value',
help='The peak value of the Gaussian blob. '
'Weaker data will need lower values.')
pointerClassStr = 'SetOfAverages'
# In Relion 3 it is also possible to pass a volume as reference for
# autopicking
if isVersion3():
pointerClassStr += ",Volume"
group.addParam(
'inputReferences',
params.PointerParam,
pointerClass='SetOfAverages',
condition=refCondition,
label='Input references',
important=True,
help='Input references (SetOfAverages) for auto-pick. \n\n'
'Note that the absolute greyscale needs to be correct, \n'
'so only use images with proper normalization. '
'From Relion 3.0 it is also possible to provide a '
'3D volume which projections will be used as '
'references.')
group.addParam(
'particleDiameter',
params.IntParam,
default=-1,
label='Mask diameter (A)',
help='Diameter of the circular mask that will be applied '
'around the templates in Angstroms. When set to a '
'negative value, this value is estimated '
'automatically from the templates themselves.')
form.addSection('References')
form.addParam('lowpassFilterRefs',
params.IntParam,
default=20,
condition=refCondition,
label='Lowpass filter references (A)',
help='Lowpass filter that will be applied to the '
'references before template matching. \n'
'Do NOT use very high-resolution templates to '
'search your micrographs. \n'
'The signal will be too weak at high resolution '
'anyway, and you may find Einstein from noise...')
form.addParam('highpassFilterMics',
params.IntParam,
default=-1,
label='Highpass filter (A)',
help='Highpass filter that will be applied to the '
'micrographs. This may be useful to get rid of '
'background ramps due to uneven ice distributions. '
'Give a negative value to skip the highpass '
'filter. Useful values are often in the range '
'of 200-400 Angstroms.')
form.addParam(
'angularSampling',
params.IntParam,
default=5,
label='Angular sampling (deg)',
help='Angular sampling in degrees for exhaustive searches '
'of the in-plane rotations for all references.')
form.addParam('refsHaveInvertedContrast',
params.BooleanParam,
default=True,
label='References have inverted contrast?',
help='Set to Yes to indicate that the reference have '
'inverted contrast with respect to the particles '
'in the micrographs.')
form.addParam('refsCtfCorrected',
params.BooleanParam,
default=True,
condition=refCondition,
label='Are References CTF corrected?',
help='Set to Yes if the references were created with '
'CTF-correction inside RELION.\n'
'If set to Yes, the input micrographs should contain '
'the CTF information.')
form.addParam(
'ignoreCTFUntilFirstPeak',
params.BooleanParam,
condition=refCondition,
default=False,
expertLevel=params.LEVEL_ADVANCED,
label='Ignore CTFs until first peak?',
help='Set this to Yes, only if this option was also used '
'to generate the references.')
form.addSection('Autopicking')
group = form.addGroup('Autopick')
group.addParam('pickingThreshold',
params.FloatParam,
default=0.25,
label='Picking threshold:',
help='Use lower thresholds to pick more particles '
'(and more junk probably)')
group.addParam('interParticleDistance',
params.IntParam,
default=-1,
label='Minimum inter-particle distance (A):',
help='Particles closer together than this distance \n'
'will be consider to be a single cluster. \n'
'From each cluster, only one particle will be '
'picked.')
group.addParam(
'maxStddevNoise',
params.FloatParam,
default=1.1,
label='Maximum stddev noise:',
help='This is useful to prevent picking in carbon areas, '
'or areas with big contamination features. Peaks in '
'areas where the background standard deviation in '
'the normalized micrographs is higher than this '
'value will be ignored. Useful values are probably '
'in the range 1.0 to 1.2. Set to -1 to switch off '
'the feature to eliminate peaks due to high '
'background standard deviations.')
group = form.addGroup('Computing')
group.addParam('shrinkFactor',
params.FloatParam,
default=0,
validators=[
params.Range(0, 1, "value should be "
"between 0 and 1. ")
],
label='Shrink factor',
help='This is useful to speed up the calculations, '
'and to make them less memory-intensive. The '
'micrographs will be downscaled (shrunk) to '
'calculate the cross-correlations, and peak '
'searching will be done in the downscaled FOM '
'maps. When set to 0, the micrographs will de '
'downscaled to the lowpass filter of the '
'references, a value between 0 and 1 will '
'downscale the micrographs by that factor. '
'Note that the results will not be exactly '
'the same when you shrink micrographs!')
group.addParam('doGpu',
params.BooleanParam,
default=True,
label='Use GPU acceleration?',
help='If set to Yes, the job will try to use GPU '
'acceleration.')
group.addParam('gpusToUse',
params.StringParam,
default='',
label='Which GPUs to use:',
condition='doGpu',
help='This argument is not necessary. If left empty, '
'the job itself will try to allocate available GPU '
'resources. You can override the default '
'allocation by providing a list of which GPUs '
'(0,1,2,3, etc) to use. MPI-processes are '
'separated by ":", threads by ",". '
'For example: "0,0:1,1:0,0:1,1"')
form.addParam(
'extraParams',
params.StringParam,
default='',
label='Additional arguments:',
help='In this box command-line arguments may be provided '
'that are not generated by the GUI. This may be '
'useful for testing developmental options and/or '
'expert use of the program. \n'
'The command "relion_autopick" will print a list '
'of possible options.')
form.addSection('Helix')
form.addParam('fomLabel',
params.LabelParam,
important=True,
label='Helix processing is not implemented still.')
self._defineStreamingParams(form)
form.addParallelSection(threads=0, mpi=4)
def defineProcessParams(cls, form):
form.addParam('windowSize',
params.IntParam,
default=1024,
label='Box size (px)',
condition='not recalculate',
help='Boxsize in pixels to be used for FFT, 512 or '
'1024 highly recommended')
group = form.addGroup('Search limits')
line = group.addLine('Resolution (A)',
condition='not recalculate',
help='The CTF model will be fit to regions '
'of the amplitude spectrum corresponding '
'to this range of resolution.')
line.addParam('lowRes', params.FloatParam, default=50., label='Min')
line.addParam('highRes', params.FloatParam, default=4., label='Max')
line = group.addLine('Defocus search range (A)',
condition='not recalculate',
help='Select _minimum_ and _maximum_ values for '
'defocus search range (in A). Underfocus'
' is represented by a positive number.')
line.addParam('minDefocus',
params.FloatParam,
default=5000.,
label='Min')
line.addParam('maxDefocus',
params.FloatParam,
default=90000.,
label='Max')
group.addParam('stepDefocus',
params.FloatParam,
default=500.,
label='Defocus step (A)',
help='Step size for the defocus search.')
form.addParam('astigmatism',
params.FloatParam,
default=1000.0,
label='Expected (tolerated) astigmatism',
help='Estimated astigmatism in Angstroms',
expertLevel=params.LEVEL_ADVANCED)
form.addParam('plotResRing',
params.BooleanParam,
default=True,
label='Plot a resolution ring on a PSD file',
help='Whether to plot an estimated resolution ring '
'on the power spectrum',
expertLevel=params.LEVEL_ADVANCED)
form.addHidden(params.GPU_LIST,
params.StringParam,
default='0',
expertLevel=params.LEVEL_ADVANCED,
label="Choose GPU IDs",
help="GPU may have several cores. Set it to zero"
" if you do not know what we are talking about."
" First core index is 0, second 1 and so on."
" You can use multiple GPUs - in that case"
" set to i.e. *0 1 2*.")
form.addSection(label='Advanced')
group = form.addGroup('EPA')
group.addParam('doEPA',
params.BooleanParam,
default=True,
label="Do EPA",
help='Do Equiphase average used for output CTF file. '
'Only for nice output, will NOT be used for CTF '
'determination.')
group.addParam('EPAsmp',
params.IntParam,
default=4,
condition='doEPA',
expertLevel=params.LEVEL_ADVANCED,
label="Over-sampling factor for EPA")
group.addParam('doBasicRotave',
params.BooleanParam,
default=False,
condition='doEPA',
expertLevel=params.LEVEL_ADVANCED,
label="Do rotational average",
help='Do rotational average used for output CTF file. '
'Only for nice output, will NOT be used for CTF '
'determination.')
group.addParam('overlap',
params.FloatParam,
default=0.5,
condition='doEPA',
expertLevel=params.LEVEL_ADVANCED,
label="Overlap factor",
help='Overlapping factor for grid boxes sampling, '
'for windowsize=512, 0.5 means 256 pixels overlapping.')
group.addParam('convsize',
params.IntParam,
default=85,
condition='doEPA',
expertLevel=params.LEVEL_ADVANCED,
label="Boxsize for smoothing",
help='Boxsize to be used for smoothing, '
'suggested 1/5 ~ 1/20 of window size in pixel, '
'e.g. 99 for 512 window')
if cls.isVersion118():
group.addParam('smoothResL',
params.IntParam,
default=1000,
expertLevel=params.LEVEL_ADVANCED,
condition='doEPA',
label='Resolution for smoothing',
help='Provide a reasonable resolution for low '
'frequency background smoothing; 20 '
'angstrom suggested, 10-50 is proper range')
form.addParam('bfactor',
params.IntParam,
default=150,
label="B-factor",
help='B-factors used to decrease high resolution '
'amplitude, A^2; suggested range 50~300 except '
'using REBS method (see the paper for the details).')
group = form.addGroup('High-res refinement')
group.addParam('doHighRes',
params.BooleanParam,
default=False,
label="Do high-resolution refinement",
help='Whether to do High-resolution refinement or not, '
'very useful for selecting high quality micrographs. '
'Especially useful when your data has strong '
'low-resolution bias')
group.addParam(
'HighResL',
params.FloatParam,
default=15.0,
condition='doHighRes',
label="Lowest resolution",
help='Lowest resolution to be used for High-resolution '
'refinement, in Angstroms')
group.addParam(
'HighResH',
params.FloatParam,
default=4.0,
condition='doHighRes',
label="Highest resolution",
help='Highest resolution to be used for High-resolution '
'refinement, in Angstroms')
group.addParam('HighResBf',
params.IntParam,
default=50,
condition='doHighRes',
label="B-factor",
help='B-factor to be used for High-resolution '
'refinement, in Angstroms')
form.addParam('doValidate',
params.BooleanParam,
default=False,
expertLevel=params.LEVEL_ADVANCED,
label="Do validation",
help='Whether to validate the CTF determination.')
form.addSection(label='Phase shift')
form.addParam('doPhShEst',
params.BooleanParam,
default=False,
label="Estimate phase shift?",
help='For micrographs collected with phase-plate. '
'It is suggested to import such micrographs with '
'amplitude contrast = 0. Also, using smaller '
'_lowest resolution_ (e.g. 15A) and smaller '
'_boxsize for smoothing_ (e.g. 50 for 1024 '
'window size) might be better.')
line = form.addLine('Phase shift range range (deg)',
condition='doPhShEst',
help='Select _lowest_ and _highest_ phase shift '
'(in degrees).')
line.addParam('phaseShiftL',
params.FloatParam,
default=0.0,
condition='doPhShEst',
label="Min")
line.addParam('phaseShiftH',
params.FloatParam,
default=180.0,
condition='doPhShEst',
label="Max")
form.addParam('phaseShiftS',
params.FloatParam,
default=10.0,
condition='doPhShEst',
label="Step",
help='Phase shift search step. Do not worry about '
'the accuracy; this is just the search step, '
'Gctf will refine the phase shift anyway.')
form.addParam('phaseShiftT',
params.EnumParam,
default=CCC,
condition='doPhShEst',
label='Target',
choices=['CCC', 'Resolution limit'],
display=params.EnumParam.DISPLAY_HLIST,
help='Phase shift target in the search: CCC or '
'resolution limit. Second option might generate '
'more accurate estimation if results are '
'essentially correct, but it tends to overfit high '
'resolution noise and might have the potential '
'possibility to generate completely wrong results. '
'The accuracy of CCC method might not be as '
'good, but it is more stable in general cases.')
if cls.isVersion118():
form.addParam('coSearchRefine',
params.BooleanParam,
default=False,
condition='doPhShEst',
label='Search and refine simultaneously?',
help='Specify this option to do refinement during '
'phase shift search. Default approach is to do '
'refinement after search.')
form.addParam(
'refine2DT',
params.IntParam,
validators=[
params.Range(1, 3, "value should be "
"1, 2 or 3. ")
],
default=1,
condition='doPhShEst',
label='Refinement type',
help='Refinement type: 1, 2, 3 allowed.\n NOTE: '
'This parameter is different from Target and is'
'optional for different types of refinement algorithm, '
'in general cases they work similar. In challenging '
'case, they might converge to different results, '
'try to see which works best in your case. '
'My suggestion is running as default first, and '
'then try new refinement on the micrographs '
'which failed.')
form.addParallelSection(threads=1, mpi=1)