subtom_eigenvolumes_wmd

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.

Example

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')

See Also