Python-based Hierarchical ENvironment for Integrated Xtallography
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Calculating a simple NCS averaged map

List of all ncs_average keywords

If you already have map coefficients in an MTZ file and have identified your NCS with phenix.find_ncs and just want to calculate the average density in all your NCS copies, you can use phenix.ncs_average. In most cases this can be run automatically by passing the name of the MTZ file and the ncs_spec file with NCS information.

The output of phenix.ncs_average is a CCP4-style map file.

These simple NCS averaged maps can be accurate maps for cases with high NCS symmetry and they are useful for evaluating what an NCS density modified map should be expected to look like.

List of all ncs_average keywords

Legend: black bold - scope names
        black - parameter names
        red - parameter values
        blue - parameter help
        blue bold - scope help
        Parameter values:
          * means selected parameter (where multiple choices are available)
          False is No
          True is Yes
          None means not provided, not predefined, or left up to the program
          "%3d" is a Python style formatting descriptor
      mtz_in= None Input MTZ file with map coefficients
      map_coeff_labels= None If map coefficients cannot be identified
                        automatically from your MTZ file, you can specify the
                        label or labels for them. (Please separate labels with
                        blank space, MTZ columns grouped together separated by
                        commas with no blanks.) You can specify:
                        map_coeff_labels (e.g., FWT,PHIFWT) amplitudes and
                        phases (e.g., FP,SIGFP PHIB) or amplitudes, phases,
                        weights (e.g., FP,SIGFP PHIB FOM)
      map_file= None Optional input CCP4-style map file. No mtz_in is needed
                if a map file is supplied
      ncs_in= None File with NCS operators to be applied to ncs_in This can be
              a .ncs_spec file from find_ncs, simple_ncs_from_pdb or
              find_ncs_from_density It can also be NCS formatted for resolve,
              including rotations, translations, and centers
      ccp4_map_out= ncs_average.ccp4 Output CCP4-style map file with
                    NCS-averaged density
      log= ncs_average.log Output log file
      params_out= ncs_average_params.eff Parameters file to rerun ncs averaging
      temp_dir= "temp_dir" Optional temporary work directory
      output_dir= "" Output directory where files are to be written
      high_resolution= None high-resolution limit for map calculation
      solvent_content= 0.5 solvent fraction
      wang_radius= 5 Smoothing radius for identification of solvent boundary
      high_resolution_scale= 0.95 Resolution of output map coeffs will be
                             high_resolution_scale* resolution of input map
                             coeffs if high_resolution is None
      verbose= False Verbose output
      raise_sorry= False Raise sorry if problems
      debug= False Debugging output
      dry_run= False Just read in and check parameter names
      coarse_grid= False Use coarse grid (saves on memory)
      resolve_command_list= None You can supply any resolve command here NOTE:
                            for command-line usage you need to enclose the
                            whole set of commands in double quotes (")
                            and each individual command in single quotes (')
                            like this: resolve_command_list="'no_build'
                            'b_overall 23' "