subtom_parallel_eigencoeffs_pca
Computes particle Eigencoefficients
subtom_parallel_eigencoeffs_pca(
'all_motl_fn_prefix', all_motl_fn_prefix ('combinedmotl/allmotl'),
'ptcl_fn_prefix', ptcl_fn_prefix ('subtomograms/subtomo'),
'eig_coeff_fn_prefix', eig_coeff_fn_prefix ('class/eigcoeff_pca'),
'eig_val_fn_prefix', eig_val_fn_prefix ('class/eigval_pca'),
'eig_vol_fn_prefix', eig_vol_fn_prefix ('class/eigvol_pca'),
'weight_fn_prefix', weight_fn_prefix ('otherinputs/ampspec'),
'mask_fn', mask_fn ('none'),
'high_pass_fp', high_pass_fp (0),
'high_pass_sigma', high_pass_sigma (0),
'low_pass_fp', low_pass_fp (0),
'low_pass_sigma', low_pass_sigma (0),
'nfold', nfold (1),
'apply_weight', apply_weight (0),
'tomo_row', tomo_row (7),
'iteration', iteration (1),
'prealigned', prealigned (0),
'num_coeff_batch', num_coeff_batch (1),
'process_idx', process_idx (1))
Takes a batch subset of particles described by all_motl_fn_prefix with
filenames given by ptcl_fn_prefix, band-pass filters them as described by
high_pass_fp, high_pass_sigma, low_pass_fp, and low_pass_sigma,
optionally applies C-symmetry specified by nfold, and projects them onto by
default the Eigenvolumes specified by eig_vol_fn_prefix. This determines a
set of coefficients describing a low-rank approximation of the data. A subset of
this coefficient matrix is written out based on eig_coeff_fn_prefix and
process_idx, with there being num_coeff_batch batches in total.
If apply_weight is set to 1 the Eigenvolumes will be reweighted using the
correct weight of each particle as described by weight_fn_prefix and
tomo_row, then each particle will be read and projected in a loop. If
prealigned is set to 1, then it is understood that the particles have been
prealigned beforehand and the alignment of the particles can be skipped to save
time. mask_fn describes the mask used throughout classification and ‘none’
describes a default spherical mask.
Example
subtom_parallel_eigencoeffs_pca(
'all_motl_fn_prefix', 'combinedmotl/allmotl', ...
'ptcl_fn_prefix', 'subtomograms/subtomo_ali', ...
'eig_coeff_fn_prefix', 'class/eigcoeff', ...
'eig_val_fn_prefix', 'class/eigval', ...
'eig_vol_fn_prefix', 'class/eigvol', ...
'weight_fn_prefix', 'otherinputs/ampspec', ...
'mask_fn', 'otherinputs/classification_mask.em', ...
'high_pass_fp', 1, ...
'high_pass_sigma', 2, ...
'low_pass_fp', 15, ...
'low_pass_sigma', 3, ...
'nfold', 1, ...
'apply_weight', 1, ...
'tomo_row', 7, ...
'iteration', 1, ...
'prealigned', 1, ...
'num_coeff_batch', 100, ...
'process_idx', 1)