Computes Singular Value Decomposition of D-Matrix and projects data on right Singular Vectors.
subtom_eigenvolumes_wmd(
'all_motl_fn_prefix', all_motl_fn_prefix ('combinedmotl/allmotl'),
'ptcl_fn_prefix', ptcl_fn_prefix ('subtomograms/subtomo'),
'dmatrix_fn_prefix', dmatrix_fn_prefix ('class/dmatrix_wmd'),
'eig_val_fn_prefix', eig_val_fn_prefix ('class/eigval_wmd'),
'eig_vol_fn_prefix', eig_vol_fn_prefix ('class/eigvol_wmd'),
'variance_fn_prefix', variance_fn_prefix ('class/variance_wmd'),
'mask_fn', mask_fn ('none'),
'iteration', iteration (1),
'num_svs', num_svs (40),
'svds_iterations', svds_iterations ('default'),
'svds_tolerance', svds_tolerance ('default'))
Calculates num_svs
weighted projections of wedge-masked differences onto the
same number of determined Right-Singular Vectors, by means of the Singular Value
Decomposition of a previously calculated D-matrix, named as given by
dmatrix_fn_prefix
and iteration
to produce Eigenvolumes which can then
be used to determine which vectors can best influence classification. The
Eigenvolumes are also masked by the file specified by mask_fn
. The output
weighted Eigenvolume will be written out as specified by eig_vol_fn_prefix
,
iteration
and #, where the # is the particular Eigenvolume being written
out. The calculated Eigenvalues which correspond to the square of the singular
vectors are also written oun as given by eig_val_fn_prefix
and
iteration
, and the variance map of the data is written out as determined by
variance_fn_prefix
and iteration
. Two options svds_iterations
and
svds_tolerance
are also available to tune how svds is run. If the string
'default' is given for either the default values in svds will be used.
subtom_eigenvolumes_wmd(...
'all_motl_fn_prefix', 'combinedmotl/allmotl', ...
'ptcl_fn_prefix', 'subtomograms/subtomo', ...
'dmatrix_fn_prefix', 'class/dmatrix', ...
'eig_val_fn_prefix', 'class/eigval', ...
'eig_vol_fn_prefix', 'class/eigvol', ...
'variance_fn_prefix', 'class/variance', ...
'mask_fn', 'class/class_mask.em', ...
'iteration', 1, ...
'num_svs', 40, ...
'svds_iterations', 'default', ...
'svds_tolerance', 'default')