Generate and Apply Mask : Make a soft mask of the region to be excluded.

Usage in command line

    sp_signalsubtract.py sp_mask --map2mask=map_to_make_mask_from --fullmap=full_map --outdir=output_subtraction_directory --mapthresh=threshold --verbosity=verbosity_level

sp_signalsubtract comprises the steps needed to subtract masked regions from a map in order to focus on the remaining features from that map. There are six steps for this process (five within SPHIRE):

1. Average and low-pass filter a map for segmentation

2. Locate regions to be subtracted

3. Mask a soft mask of the region to be excluded :

sp_signalsubtract.py sp_mask --map2mask=map_to_make_mask_from --outdir=output_subtraction_directory --fullmap=full_map --mapthresh=threshold

The map to make a mask from (–map2mask) corresponds to the region that you want to subtract.

!!!IMPORTANT!!! The full map which is to be multiplied by the mask (–fullmap) must NOT have been postprocessed (e.g., sharpened). Otherwise, re-projections will not be optimally comparable to the experimental images.

Grouped segments

Final mask

4. Compute re-projections of map to be subtracted, and subtract them from the original images

5. Compute reconstruction of density remaining after signal-subtraction

6. Center map of the remaining density

--map2mask

Map from which a mask will be generated. (default required string)

--fullmap

Map which will be multiplied by the mask. (default None)

--outdir

Directory where outputs will be written. (default required string)

--mapthresh

Full map will be initially binarized at this threshold. (default None)

--verbosity

Verbosity level

: Controls how much information will be written to the screen. (default 2)

mask_final.hdf

Final mask

vol_masked.hdf

Diagnostic masked input map

ctf_params.txt

CTF parameter file

Tapu Shaikh

Category 1:: APPLICATIONS

sphire/bin/sp_signalsubtract.py

Beta:: Under evaluation and testing. Please let us know if there are any bugs.