colacor - Cross-Correlation Calculation and Refinement of Manual Docking
colores - FFT Accelerated 6D Exhaustive Search
eul2pdb - Graphical Representation of Euler Angles
map2map - Format Conversion
pdb2sax - Create a Simulated SAXS Bead Model from a PDB
pdb2vol - Create a Volumetric Map from a PDB
pdbsymm- Symmetry Builder
qdock - Rigid-Body Docking of High- and Low-Resolution Data
qpdb - Vector Quantization of a PDB
qrange - Automatic Vector Quantization and Rigid-Body Docking
qvol - Vector Quantization of Volumetric Map
vol2pdb - Create a PDB from a Volumetric Map
volcube - Creating Isocontour Surfaces
voldiff - Discrepancy / Difference Mapping
voledit - Inspecting 2D Cross Sections of Density Values
volhist - Inspecting and Shifting the Voxel Histogram
volvoxl - Grid Interpolation
Header File and Library Routines

Purpose:

Basic usage (at shell prompt):
 

The basic input parameters are:

<Situs density map> Low resolution map in Situs format.  To convert your EM map to Situs format use the map2map utility.

<PDB structure> Atomic structure in PDB format.

-res <value> Estimated resolution of the density map in Å.  [default -res 15.0]

-cutoff  <value> Density map threshold value. All density levels below this value are set to zero. You can use volhist to rescale the density levels or to shift the background peak in the voxel histogram to the origin.  [default -cutoff 0.0]

-corr   <number>  Two options are implemented:

Input at program prompt:
None.

Purpose:

Basic usage (at shell prompt):
 

The basic input parameters are:

<Situs density map> Low resolution map in Situs format.  To convert your EM map to Situs format use the map2map utility.

<PDB structure> Atomic structure in PDB format.

-nprocs <number> This option sets the number of processors used for the on-lattice 6D search and the off-lattice Powell optimization. Colores supports systems with multiple, dual-core and/or hyperthreaded processors. For example, on a dual processor Intel Xeon machine with Hyperthreading, '-nprocs 4' produces the shortest runtimes (two processors times two threads). The same holds for a dual-core Pentium4 with Hyperthreading. On the other hand, '-nprocs 2' is the optimal value for a dual processor AMD Opteron system. Note that on some architectures the threads may not show in the UNIX "top" window, if in doubt do your own time comparison. [default -nprocs 1]

-res <value> Estimated resolution of your density map in Å.  [default -res 15.0]

-cutoff  <value> Density map cutoff value. All density levels below this value are set to zero. You can use volhist to rescale the density levels or to shift the background peak in the voxel histogram to the origin.  [default -cutoff 0.0]

-deg  <value> Angular sampling of the rotational search space in degrees. For typical electron microscopy maps the angular step size should be between 6-20°.  [default -deg 15.0]

-corr   <number>  This option controls the fitting criterion.
Two options are implemented: 

-corr 0 Standard linear cross-correlation.  The scalar product between the density maps of the low resolution map and the low-pass filtered atomic structure. For resolutions > 10Å this criterion is less discriminative. Note that this needs to be turned on explicitely.

-corr 1 [default] A Laplacian filter is applied by default to maximize the fitting contrast. This is the recommended docking criterion for low resolution docking (up to 25Å resolution). To provide for a more robust algorithm when dealing with cropped or thresholded experimental data we implemented a mask that filters out hard artificial surfaces.  Due to the masking and filtering expect overall smaller correlation values compared to -corr 0.

-ani <value>   Defines the resolution anisotropy factor (z direction vs. x,y plane)  [default: -ani 1.0]. Allows one to set a different resolution in the z direction vs. the x,y plane. E.g. "-ani 1.5 -res 20" specifies a 30 A resolution in the z direction, and a 20 A resolution in x,y. This is useful for researchers dealing with membrane protein or tomography reconstructions that have a reduced resolution in the z direction.

-erang <value value value value value value>   Defines the rotational space limits according to the range of the Euler angles (psi, theta, phi). By default the entire rotational space is considered    [default: -erang 0 360 0 180 0 360]. Note that the Euler angle range is not limited to these standard intervals, so you can specify also negative values (within certain limits), but in any event any colores output angles are remapped to the standard intervals. For example, if you want to perform a fine search of 2° angular sampling in only one of the Euler angles, these are the options:

-euler <number>  There are three ways to generate an exhaustive list of Euler angles that covers (nearly) uniformly the rotational space for a given angular sampling (option -deg).  The proportional method yields very even results and also performs well for smaller intervals specified via '-erang'. The pole sparsing method is widely used but yields slightly less uniform distributions. The spiral method also produces a less uniform distribution, but for medium to low resolution docking it is quite reasonable. The Euler angles are saved to a file col_eulers.dat, and you can edit this file and reload it using the -euler 3 option. This way, you can also load any manually generated Euler angle files. 

-peak <number> This option sets the peak search algorithm. By default, an advanced filtering-based approach is used. The older, sorting-based algorithm is available as an option.

-explor <number> Controls the number of the best fits found in the 6D on-lattice search to be subsequently refined by Powell optimization.  By default an off-lattice optimization is applied to the first 10 best on-lattice docking results. [default -explor 10]

-sizef <value> To avoid that the atomic structure is placed outside the target map during rotation the low resolution map is enlarged by a margin of width sizef times the maximum radius of the atomic structure.  Ideally, sizef should be set to 1.0 but in practice a value as low as 0.2 seems to work fine and saves compute time [default -sizef 0.2]

-nopowell This flag skips the Powell optimization and only the on-lattice search is performed. By default the Powell optimization is turned on.

-pwti <value number> Powell tolerance and max number of iterations of the Powell algorithm. This two parameters control the convergence of the optimization. By default, the tolerance is set to 1e-6 and the max iterations are limited to 25.

-pwdr <value value> Initial gradient of the translational and rotational search in the Powell optimization. By default the initial rotational gradient is set to 25% of the angular sampling (but not larger than 10°), and the translational initial gradient is set to 25% of the voxel spacing. To use the default value only for the rotational or only for the translational gradient, choose a negative number for the parameter that must be left at default, and your chosen value for the other.

-pwcorr <number> This option sets the Powell correlation algorithm. By default, the fastest algorithm which reproduces the standard cross correlation coefficient to within the Powell tolerance is determined at runtime.

-nopeaksharp This flag skips the peak sharpness estimation procedure in order to save processing time. By default, the peak sharpness estimation is turned on.

None.

Output:

Here is a brief description of the output files (see also the file headers);

col_best*.pdb The atomic coordinates in PDB format of the best fits found in the search. The total number of best fits saved is controlled by the option -explor, but only non-degenerate fits are returned, so the number may be smaller than specified by the -explor option. The PDB header contains information about the docking (sampling, fit criteria used, correlation values, position and orientation etc.). It also includes a table containing the angular variability of the correlation about the fit.

col_rotate.log This file contains the best translational fit (on-lattice) found for each rotation. The first 3 columns are the Euler angles (in degrees), the next 3 columns are the translational coordinates that gave the highest correlation value, followed by the correlation value (not normalized).

col_powell.log This file contains information about the Powell off-lattice search performed for the best fits from 6D lattice search.  As before, rotational and translational coordinates correspond to the first 6 columns , but note that the Euler angles are in radian units.

col_trans.sit  The on-lattice translation function in Situs format. Since the translational search space corresponds to the input map lattice , we can generate a map in which density values are the correlation values normalized by the maximum. This is a Situs format map, so you can use VMD to display it or use map2map to convert to other formats.

col_trans.log  Same as col_trans.sit, but instead of a map, the translational correlation values are stored in a regular file. Each row that corresponds to a lattice coordinate (columns 4,5,6) shows the corresponding Euler angles (columns 1,2,3) in degrees that exhibit the highest correlation value (column 7). 

Notes:

Purpose:

Usage (at shell prompt):
 

Input at program prompt:

None.

Pseudo-atomic structure in PDB-format. Each triplet of Euler angles in the input file is represented as a point on a 10 A radius sphere. The phi Euler angle (rotation in the projection plane) is encoded in the B-factor column of the PDB file (in radians units), whereas theta and psi correspond to longitude and latitude on the sphere.

Former names: convert, conformat

Purpose:

Volumetric density data is converted to a Situs-specific format on a cubic lattice. This allows Situs programs to keep track of coordinate systems and it makes the core Situs programs independent of the ever changing map format standards. 

Usage (at shell prompt):
 

Interactive input at program prompt (for automation see below):

• Input file format.
• Number of x, y, and z increments (columns, rows, and sections).
• Voxel size (grid spacing).
• Order of x, y, and z increments in the input file.

Notes and Known Bugs:

• You can automate this program by "overloading" the standard input if you put expected values in a script!
• You should always check out the free conversion programs MAPMAN, part of Gerard Kleywegt's RAVE package, and especially Image Science 's em2em program.

• The MRC and CCP4 map formats are not fully supported as many flavors are available. If you encounter problems, we recommend that you use the above third party conversion tools. It is generally safe to use the SPIDER format which is fully supported by map2map, so if in doubt convert to SPIDER first. Known problems: Some users have reported a mixup of axes / scrambling of densities with some particular maps. Very old CCP4 maps may correspond to the format currently denoted "MRC", whereas future MRC maps may correspond to the current "CCP4" format. For a history and future plans of this development read Stephen Fuller's page at EMBL.
  
• Avoid round-trip conversions "EM map format" -> Situs -> "EM map format", because information about the unit cell extent beyond that of the actual range of data is lost. Also, Situs lattices are cubic, so any skewed unit cell parameters (alpha, beta, gamma, etc) of the original map are not saved.

Purpose:

Usage (at shell prompt):
 

Interactive input at program prompt (also suitable for automation):

• Choice of atom mass-weighting and B-factor cutoff level. Atoms with B-factors above the cutoff level will be ignored. You can automate this program by "overloading" the standard input if you put expected values in a script!

PDB file that contains the centers of the simulated beads with the radii in the occupancy column. This file can then be either inspected with a visualization program (for example VMD), or processed into a bead volume map using pdb2vol.

Purpose:

Usage (at shell prompt):
 

Interactive input at program prompt (also suitable for automation):

• If water, hydrogen,codebook vector atoms are present, choice of ignoring them.
• Choice of atom mass-weighting and B-factor cutoff level. Atoms with B-factors above the cutoff level will be ignored.
• Desired voxel spacing for output map.
• Kernel width, defined by either the kernel half-max radius r-half (enter positive value) or by the target resolution of the output map (enter value of resolution as negative number). The standard deviation (sigma) of the kernel is assumed to be half the target resolution.
• Type of smoothing kernel:
• Gaussian, exp(-1.5 r^2 / sigma^2)
• Triangular, max(0, 1 - 0.5 |r| / r-half)
• Semi-Epanechnikov, max(0, 1 - 0.5 |r|^1.5 / r-half^1.5)
• Epanechnikov, max(0, 1 - 0.5 r^2 / r-half^2)
• Hard Sphere,  max(0, 1 - 0.5 r^60 / r-half^60)
• Choice of correction for lattice smoothing (subtract the lattice projection mean-square deviation from the kernel variance).
• The kernel amplitude at the kernel origin (r=0).
• You can automate this program by "overloading" the standard input if you put expected values in a script!

Density file in Situs format. The new grid follows the coordinate system origin convention of the atomic structure and forms the smallest possible box that fully encloses the structure convoluted by the kernel.

Purpose:

Usage (at shell prompt):
 

Interactive input at program prompt (also suitable for automation):

Depending on symmetry type:

• Helical rise per subunit (in z-direction).
• Angular twist per subunit (sign determines handedness).
• Desired number of subunits to be placed before file1 structure.
• Desired number of subunits to be placed after file1 structure.
• Order of the principal symmetry axis.
• [If file2 is unspecified: x- and y-position of helical axis (offset from file1 coordinate system origin).]
• z-position of secondary symmetry axes (for D symmetry - offset from file1 coordinate system origin).
• You can automate this program by "overloading" the standard input if you put expected values in a script!
  

Symmetry PDB file containing multiple copies of input PDB file.

Note:

file2 input maps that don't have square (x,y) cross-sections or whose helical axis is not in the geometric center of the square cross-sections must first be crop-edited with voledit.

Purpose:

Specialized tool to dock a high-resolution structure to low-resolution data using a fixed number of codebook vectors . Much of the functionality of qdock has been superseded by the combined vector quantization / docking utility qrange and by the cross-correlation based colores. qdock remains part of the distribution to support correlation-coefficient based docking. It is assumed that the user has already determined a suitable number k of codebook vectors with qrange and has created the vector files with qpdb and qvol .

Similar to qrange, qdock carries out an exhaustive search of the k! = k*(k-1)* ...*2 permutations of corresponding codebook vectors and returns a list of best least-squares fits. The limitation of qdock is that the docking can be carried out only for a fixed number k of vectors. The advantage of qdock is that the results can be ranked (if desired) by the correlation coefficient that measures the overlap of the high- and low-resolution data. A lower rms deviation (rmsd) of the least-squares fit typically corresponds to a higher correlation coefficient. However, the coefficients typically lie within a very narrow numeric range and care must be taken because fits based on the correlation coefficient alone are often ambiguous.

Usage (at shell prompt):
 

Interactive input at program prompt (also suitable for automation):

• Choice of volumetric map coordinate system. 
• Ranking by vector rmsd or by correlation coefficient (carbon alpha or full atom). 
• Selection of a docked high-resolution structure from a list. 
• Filename for the selected output structure. 
• If desired, select and export additional results from the list.
  
• You can automate this program by "overloading" the standard input if you put expected values in a script!

• (Program level:) Possible pairs of corresponding codebook vectors. The (default: 20) best least-squares fits are ranked by their rmsd (in Angstrom), or by their correlation coefficient. Permutations indicate the order of qpdb vectors fitted to qvol vectors. See the Situs manuscripts for more information. Also, the positional and orientational accuracy of the fitting is given, calculated based on the statistical vector variability.

• (Shell level:) The superposition of the selected corresponding codebook vectors defines a rigid-body transformation which superimposes high- and low-resolution data sets. After transformation, the docked high-resolution structure is written to a file in PDB format. The file3 codebook vectors are sorted and transformed in concert with the structure; they are appended, together with the file1 vectors, to the output PDB file.

Purpose:

Specialized tool to perform a vector quantization of atomic resolution data. qpdb supports the correlation-coefficient based docking with qdock, and also flexible docking. To enable skeleton-based flexible docking with qvol, qpdb includes options to learn vector distances and to export the Voronoi cells generated by the vectors. 

Usage:

Usage (at shell prompt):
 

Interactive input at program prompt (also suitable for automation):

• If water, hydrogen,codebook vector atoms are present, choice of ignoring them.
• B-factor cutoff level. Atoms with B-factors above this level will be ignored.
• Number of codebook vectors.
• Choice of computing the vector connectivities (neighborhood relationships) with the Competitive Hebb Rule (Wriggers et al., 1998) and writing them to a file.
• Choice of computing the Voronoi cells and writing them to a file.
• You can automate this program by "overloading" the standard input if you put expected values in a script!

• (Program level:) The sphericity, a measure between 0 and 1 that characterizes how spherical the shape of the structure (file1) is. After the vector quantization the program prints the average rms variability of the codebook vectors in Angstrom. Also given in Angstrom is the radius of gyration of the vectors. 

• (Shell level:) Codebook vectors in PDB-formatted output file. The vector rms variabilities, representing the precision of the codebook vectors, are written to the occupancy fields of the PDB-style atom entries. The effective radii of the Voronoi cells are written to the B-factor fields of the PDB-style atom entries. (Optional) Vector connectivities can be written to a PSF file or a distance constraints file. Constraint file entries are triples of free-format values in the order <index1> <index2> <distance in Angstrom>, where the indices correspond to the order of vectors in file2, counting from 1. (Optional) The Voronoi cells can be written to a PDB file consisting of the file1 atom entries where the index of each corresponding vector is written to the B-factor field of the output file.

Purpose:

This program automatically superimposes atomic structures with corresponding low-resolution density. Practically all density must be accounted for by the atomic structure for this to work. If in doubt use colores. You've been warned!

qrange consolidates the functions of the older vector quantization routines qvol and qpdb and of the rigid-body docking routine qdock into a single program to enable a more user-friendly fitting. The major conceptual innovation of  qrange and related programs is the discretization of the configurational search space by vector quantization . This discretization yields a list of best-scoring superpositions of the codebook vectors that represent the structural data sets. The search is computationally very efficient and can be carried out on a standard workstation within seconds.

The global optimum of vector positions is difficult to find. In qrange a small number of TRN calculations (8 by default) are repeated with different random number seeds. The averaged codebook vectors and their statistical variability are then saved. In general, a low vector variability indicates good convergence and reliable vector positions. The variability depends on the shape of the 3D input density distribution and on the number of vectors. Therefore, it is a good selection criterion for finding an optimal number k of codebook vectors.

To optimally represent the input density distribution, qrange employs a multi-resolution approach and computes vectors for a range of k (3 <= k <= 9 by default). Note that for globular shapes a small number of vectors (3-4) is usually sufficient to encode the shape unambiguously. A maximum number of k=9 vectors ( = 27 degrees of freedom) provides sufficient leeway to encode even the most complex shapes.

Usage:

Usage (at shell prompt):
 

Interactive input at program prompt (also suitable for automation):

• Choice of utilities to inspect the density distribution (e.g. voxel histogram).
• Threshold (cutoff) density value.
• Choice of volumetric map coordinate system.
• If water molecules are present, choice of ignoring them.
• B-factor cutoff level. Atoms with B-factors above this level will be ignored.
• Selection of the vector number k from a list.
• Selection of a docked high-resolution structure from a list.
• Filename for the selected output structure.
• If desired, select and export additional results from the lists.
• You can automate this program by "overloading" the standard input if you put expected values in a script!

• (Program level:) The sphericity, a measure between 0 and 1 that characterizes how spherical the shape of the structure (file2) is. After the multiple vector quantizations the program prints the selection criteria (vector variability and vector rmsd) as a function of k. Also shown are the possible pairings of corresponding codebook vectors. The best least-squares fits are ranked by their vector rmsd (in Angstrom). Also, the correlation coefficient is given. Permutations indicate the internal order of vectors. Finally, the positional and orientational accuracy of the selected fit is given, as computed from the statistical vector variability.

• (Shell level:) The superposition of the selected corresponding codebook vectors defines a rigid-body transformation which superimposes high- and low-resolution data sets. After transformation, the docked high-resolution structure is written to a file in PDB format. The codebook vectors are appended to this output file. QVOL atoms represent the low-resolution vectors and QPDB atoms represent the high resolution vectors. The vector rms variabilities, representing the precision of the codebook vectors, are written to the occupancy fields of the PDB-style atom entries. 

• qrange employs an efficient atom mass-weighting scheme using "equally weighted input vectors".

• The user has the choice to change the origin of the map coordinate system. This option might be helpful if a graphics program has a different convention for defining the map coordinate system than map2map .

• The program also allows to ignore flexible or poorly defined atoms with high crystallographic B-factors. This option should only be chosen if there is an indication that parts of the protein are not visible in the low-resolution data due to disorder.

• Often there is no one-to-one correspondence between low-resolution data and what one would consider the physical density of the structure, so users may need to experiment with the volumetric and B-factor threshold values until the results are satisfying. To help estimate appropriate threshold values for single molecules, qvol and qpdb print the radius of gyration of the codebook vectors, a measure of vector compactness. At the proper threshold densities the radius of gyration returned by qvol   should be approximately equal to that of qpdb .

Purpose:

Specialized tool to perform a vector quantization of low-resolution, single molecule data. For rigid-body docking, much of the functionality of qvol has been superseded by the combined vector quantization / docking utility qrange . qvol remains part of the distribution to support the correlation-coefficient based docking with qdock, and to support flexible docking. In the absence of existing vector positions, qvol carries out a global search using the TRN algorithm. If start vectors are already known, the LBG local search algorithm is used instead of TRN. LBG allows to add distance constraints to the vector refinement that are useful for flexible docking.

The global optimum of vector positions is difficult to find. With TRN, a small number of calculations (8 by default) are repeated with different random number seeds. The averaged codebook vectors and their statistical variability are then written to the output file. With LBG, no statistical clustering is performed. In this case it is important to specify reliable initial positions from a prior qvol run. 

Usage:

In a practical application of qvol, one should extract from the volumetric data a region of interest corresponding to a single molecule using e.g. voledit. Next, the user must determine a suitable number of codebook vectors. Only densities above a user-defined threshold value are considered by qvol to eliminate background noise in the low-resolution data. Depending on the noise, this threshold value should be at 50-80% of the level that is typically considered the "molecular surface" of the biopolymer in the low-resolution data. 

Usage (at shell prompt):
 

Interactive input at program prompt (also suitable for automation):

• Choice of utilities to inspect the density distribution (e.g. voxel histogram).
• Threshold (cutoff) density value.
• Number of codebook vectors.
• (If file2 is specified): Choice of entering distance constraints manually or from a file. There are two constraint file options. Constraint file entries generated e.g. with qpdb are triples of free-format values in the order <index1> <index2> <distance in Angstrom>, where the indices correspond to the order of vectors in file2, counting from 1. It is also possible to read the connectivities from a PSF file in which case the missing distances are computed from file2.
  
• Choice of computing the vector connectivities (neighborhood relationships) with the Competitive Hebb Rule (Wriggers et al., 1998) and writing them to a file.
• You can automate this program by "overloading" the standard input if you put expected values in a script!

• (Program level:) Statistical analysis of the vectors and their radius of gyration, i.e. the radial rms deviation from the vector center of mass. 

• (Shell level): Codebook vectors in a PDB-formatted output file. The vector rms variabilities, representing the precision of the codebook vectors, are written to the occupancy fields of the PDB-style atom entries. (Optional) Vector connectivities can be written to a PSF file or a distance constraints file.

• Vector connectivities in PSF format can be visualized and edited as bond connections (together with the atom-style PDB entries of file2 and file3) using the molecular graphics program VMD. Simply overload the PSF file into the PDB file in the VMD 'Molecule' menu. Then under the 'Mouse' menu select 'Add/Remove Bonds'. The edited connectivity can then be saved later into a PSF file from the VMD command console (assuming your molecule is 'top'):

set sel [atomselect top all] $sel writepsf my.psf

• If there are cluster size deviations from the expected value (default: 8) when using the TRN algorithm, refine the found vector positions by passing them to qvol as input file of a second, LBG run.

• Distance constraints do not determine the chirality (handedness) of vector connections. If you encounter mirror images or otherwise flipped connections after running qvol compared to connections determined with qpdb, you need to experiment with the indexing of your constraints. The LBG method combined with the SHAKE constraint algorithm is relatively insensitive to the position of start vectors.

Purpose:

Usage (at shell prompt):
 

Input at program prompt:

None.

Output:

PDB format file with densities written to occupancy field (if rescaling necessary the conversion factor is given by the program).

Purpose:

Usage (at shell prompt):
 

Interactive input at program prompt (also suitable for automation):

• New voxel size for rendering (the input grid is automatically interpolated).
• Isocontour surface density level.
• Rendering style: lines (wireframe), triangles (solid, flat shades), or trinorm (solid, smooth shades).
• You can automate this program by "overloading" the standard input if you put expected values in a script!

• (Program level:) Diagnostic messages and classification of the "marching cube" intersection patterns according to Heiden et al., J. Comp. Chem. 14 (1993), 246-250.

• (Shell level:) VMD script file with graphics primitives. The primitives can be sourced from the VMD text console (cf. VMD user guide ). File parameters are written to a header. Example: The following sequence of commands in the VMD text console will first list all files in the current directory and then render the graphics primitives of file "trinorm.vmd" in red", and those of file "wireframe.vmd" in green:

Known Bugs:

Former name: subtract

Purpose:

Usage (at shell prompt):
 

Input at program prompt:

None.

Output:

Density file in Situs format. The new density values are computed by subtracting the corresponding values of input grid 2 (which is resampled by trilinear interpolation, if necessary) from those of input grid 1. The output grid inherits the parameters from grid 1.

Purpose:

Interactive input at program prompt (also suitable for automation):

• Type of cross section, (x,y), (y,z), or (z,x).
• Threshold (cutoff) value for the rendering of the density.
• z, x, or y position of the cross section plane (grid units).
• Polygon clipping parameters and vertices (options).
• Cropping parameters in voxel units (options).
• Zero padding in voxel units (options).
• Segmentation parameters to extract a targeted contiguous volume. Originating from the vicinity of a given start voxel, voledit finds recursively the maximum contiguous volume formed by neighboring voxels that exceed a given threshold density level. An additional layer is added for aesthetic reasons to facilitate isocontouring near the cutoff level. Although the extracted grid contains some voxels (in the contour layer) with densities below the cutoff, all voxels with density values above the cutoff are guaranteed to be part of the found contiguous volume. Voxels outside the contour layer are assigned a density value of 0.
• File name for 2D slice or 3D volume output file (options).
• You can automate this program by "overloading" the standard input if you put expected values in a script!

(Shell window:) Cross section of the input map in Situs format. Note that pairs of voxels neighboring in the vertical direction are represented by a single character:

This program requires the use of a fixed-width font in the shell window.

Purpose:

Usage (at shell prompt):
 

Interactive input at program prompt (if file2 specified):

• Offset density value (will be added to all voxels). 
• Scaling factor.
• You can automate this program by "overloading" the standard input if you put expected values in a script!

• (Program level:) Voxel histogram and fractional volume of volumetric data echoed to the screen. The histogram bars are normalized by the second highest density peak.

• (Shell level:) Density file in Situs format (if specified). The new density values are computed by adding the offset value and by multiplying the scaling factor entered at the program prompt. The new grid inherits all size and position parameters of the old grid.

Purpose:

Usage (at shell prompt):
 

Interactive input at program prompt (also suitable for automation):

The desired new voxel size (grid spacing). You can automate this program by "overloading" the standard input if you put expected values in a script!

Output:

Density file in Situs format. The new grid inherits the coordinate system origin and forms the largest possible box that is fully enclosed by the old grid.

The suite of programs is supported by a header file (situs.h) containing user-defined parameters and by auxiliary library programs. The library programs and their respective header files handle input and output of atomic coordinates in PDB format (lib_pio.c), input and output of volumetric data (lib_vio.c), input of data at the prompt (lib_std.c), Eigenvector computation for real symmetric 3x3 matrices (lib_jac.c), Euler angle generation (lib_eul.c), random number generation (lib_rnd.c), array management (lib_vec.c), Powell optimization (lib_pow.c), map manipulation (lib_vwk.c), PDB manipulation (lib_pwk.c), symmetric multiprocessing (lib_smp.c), and timing (lib_tim.c).