<input file> | Input file, usually a cls*img file |
<iterations> | Number of iterative loops |
[ref1] | Indicates that the first image in the file is a reference |
[ign1] | Indicates that the first image is a dummy which should be ignored |
[finalref] | Once the average has been generated, a final alignment to the reference is performed |
[saveali] | Saves the individual aligned images in a separate file |
[savecen] | Save the translationally (but not rotationally) aligned images |
[savesteps] | Save the class average after each iterative step to monitor convergence |
[badfile] | Save all excluded images in 'bad' files. |
[stat] | Writes individual image statistics to 'class.stat' |
[saverefs] | Write the reference image as well as the class average to the output file |
[mask=<rad>] | Circular mask radius for the class average |
[refmask] | This will use a mask generated from the reference image. Assumes the 3D model has been sensibly masked. |
[maxshift=<rad>] | Maximum translation allowed in alignment. If not specified, implied value from mask is used. |
[keep=<sigmamult>] | The threshold value for keeping images. Standard deviation multiplier |
[locfromfile] | Determine the output file image position from the input filename. |
[median] | When CTF correction is NOT used, this produces better statistics. |
[ctfc=<res>] | Enables CTF correction, thru resolution <res> in angstroms. |
[ctfcw=<SF file>] | Enables CTF correction, with Wiener filtration, requires s vs inten struct. factor file. |
[ctfcw] | Enables CTF correction, with Wiener filtration, SNR is estimated from the data (DOESN'T WORK) |
[fixac=<0 to 1>] | This allows you to set the %AC value in the image headers to a fixed value. Note that this will NOT compensate defocus for change in %AC. |
[imask=<rad>] | Inside mask radius. |
[sigfilt] | Filters the class averages so only intense values are used in alignment |
[even|odd] | Only use the even or odd images in the input file |
[sigmaimg] | Generate a standard deviation image |
[even/odd] | Processes only the even or odd numbered images in the file (used by ttest) |
[logit=<label>] | This specifies a label to use in the particle.log file. This records particle number classification throughout a refinement. |
[refine] | This enables 1/2 pixel accuracy in alignment, it is slow, and rarely worthwhile. |
[usefilt] | This will use a filtered dataset for alignment, but uses the real data for averaging. |
[slow] | This will do alignment via exhaustive search. It is VERY slow. |
classalign2 cls000.hed 8 ref1 finalref saverefs mask=32 keep=.8 locfromfile ctfc=15
This is one of the most important programs in EMAN. It is responsible for taking a set of particles within a single class, that is, they are supposed to be in the same orientation, and performing a mutual alignement to generate a class-average. This program is largely responsible for the model independance of EMAN, ie - why EMAN can converge in so few iterations. This program is also where CTF amplitude correction occurs.
There are quite a few options for this program. It is typically called from classalignall, which has almost identical options. The few options that are present here, but not in classalignall, are intended for occasional use when checking robustness of the proceedures.
There are 3 manditory options which are specified in all cases. First, is the . This file contains the images which are to be used to generate a class average. Optionally, the first image in this file may be a reference image with assigned euler angles. The reference will be used only during the first iteration of the alignment process, so the final class average is nearly independent of this reference. It also provides a final rotational orientation for the class average.
The number of iterations (with no prefixed text) and the
'keep= When the program runs, it displays some useful information on the
screen. First you will see 1 or more rows of '.'s appear. Each '.'
represents an image being aligned. If a '*' appears instead of a '.',
that means that particular image was below the threshold and discarded.
Note that '*' images are only excluded from the average during a
particular cycle. They may be included again in later cycles if the
class average 'wanders' in their direction.
If your input file contains a reference image (which the other images
are expected to look at least vaguely similar to), then 'ref1' should be
specified. Usually 'finalref' is also specified. Normally the initial
reference is used only during the first iteration, however, during
several iterations the orientation of the class average in the plane
can drift. 'finalref' insures that the final class average is oriented
as closely as possible to the orientation of the initial reference. It
does not change the appearance of the class average, only its orientation.
'saverefs' is also usually specified with 'ref1'. This causes the
reference images to be saved along with the class averages in the output
file. This is used to compare each reference with the corresponding class
average. When the refinement cycle begins to converge, the reference
images should be nearly identical to the class averages, although the
class averages will always be noisier.
'saveali', 'savesteps', 'badfile' and 'stat' are all used primarily when
something seems to be going wrong. They cause various output files to be
generated, which can then be used to see exactly what's happening. They
are rarely used in a normal refinement cycle.
The default output image from classalign2 is a class average. This means,
each pixel is equal to the average of that pixel's value in each of the
aligned images. However, very often the median value will have better
properties than the mean value (less affected by outliers). Median
images can be generated instead of averages by specifying the 'median'
option. Note that this option is incompatible with CTF correction (see
'ctfc' below).
Usually, classalign2 will simply append each output class average to the
end of 'classes.hed'. However, if the program is being run in parallel,
it is usually desirable to preserve the ordering of the images in the
output file. 'locfromfile' will cause the output images to be put in
specific 'slots' in the output file, overwriting any image already in that
location in the file. This is used by default when classalignall is run.
'sigfilt' is used when a refinement is failing to produce consistent
results in the early rounds of refinement. This applies a non-linear
noise reducing filter to the reference image to try to get better
initial alignment. It is generally only used when necessary, and then,
only for early refinement rounds. It should not be used when the final
few refinement iterations are performed.
'ctfc' and 'ctfcw' are provided to enable CTF correction when
generating class averages. For this to work properly all of the images
in the input file must be pretreated by the ctfit program, so the
phases are flipped and the CTF parameters are stored in the individual
image headers. See the documentation for that program
and the CTF correction primer
for a discussion of how CTF correction
is performed. ctfc is specified with a filter resolution for the final
image. Otherwise high resolution noise will dominate. eg - 'ctfc=12' will
apply a 12A filter to the final image. NOTE: This IS specified in Angstroms,
not pixels like most other filter options.
'ctfcw' is the preferred variant, but requires an x-ray scattering curve
or a simulated x-ray scattering curve. This curve MUST be used directly
with ctfit when the data is pretreated, or the class average will be
improperly filtered. This option applies a true Wiener filter to the
data based on the SNR (signal to noise ratio) estimated from the data
combined with the scattering curve. eg- 'ctfcw=groel.sm' would ctf-correct
the data with an applied wiener filter. groel.sm would be the 2-column
data file defining the x-ray scattering curve.
EMAN Manual page, generated Tue Oct 8 21:38:47 2002