Provided by: gmt-common_5.4.5+dfsg-1_all bug


       dimfilter - Directional filtering of 2-D gridded files in the space (or time) domain


       dimfilter  -Ddistance_flag
        -Nxsectors [  -Qcols ] [  -Iincrement ] [  -Rregion ] [  -T ] [  -V[level] ] [ -fflags ]

       Note: No space is allowed between the option flag and the associated arguments.


       dimfilter  will  filter  a  .nc  file  in the space (or time) domain by dividing the given
       filter circle into  n_sectors,  applying  one  of  the  selected  primary  convolution  or
       non-convolution  filters  to  each sector, and choosing the final outcome according to the
       selected secondary filter. It computes distances using Cartesian or Spherical  geometries.
       The  output .nc file can optionally be generated as a subregion of the input and/or with a
       new -Increment. In this way, one may have "extra space" in the input data  so  that  there
       will  be  no  edge effects for the output grid. If the filter is low-pass, then the output
       may be less frequently sampled than the input. -Q is for the error analysis mode and  only
       requires  the  total  number  of  columns  in  the input file, which contains the filtered
       depths. Finally, one should know that dimfilter will not produce a smooth output as  other
       spatial  filters do because it returns a minimum median out of N medians of N sectors. The
       output can be rough unless the input data is noise-free.  Thus,  an  additional  filtering
       (e.g., Gaussian via grdfilter) of the DiM-filtered data is generally recommended.

              The data grid to be filtered.

              Distance flag tells how grid (x,y) relates to filter width, as follows:

              flag  =  0:  grid  (x,y)  same units as width, Cartesian distances.  flag = 1: grid
              (x,y) in degrees, width in kilometers, Cartesian distances.  flag = 2:  grid  (x,y)
              in degrees, width in km, dx scaled by cos(middle y), Cartesian distances.

              The  above options are fastest because they allow weight matrix to be computed only
              once. The next three options are slower because they  recompute  weights  for  each

              flag  =  3:  grid  (x,y) in degrees, width in km, dx scaled by cosine(y), Cartesian
              distance calculation.

              flag = 4: grid (x,y) in degrees, width in km, Spherical distance calculation.

              Sets the primary filter type. Choose among convolution and non-convolution filters.
              Append the filter code x followed by the full diameter width. Available convolution
              filters are:

              (b) Boxcar: All weights are equal.

              (c) Cosine Arch: Weights follow a cosine arch curve.

              (g) Gaussian: Weights are given by the Gaussian function.

              Non-convolution filters are:

              (m) Median: Returns median value.

              (p) Maximum likelihood probability (a mode estimator): Return modal value. If  more
              than  one  mode is found we return their average value. Append - or + to the filter
              width if you rather want to return the smallest or largest of the modal values.

              Sets the secondary filter type x and the number of bow-tie sectors.   sectors  must
              be integer and larger than 0. When sectors is set to 1, the secondary filter is not
              effective. Available secondary filters are:

              (l) Lower: Return the minimum of all filtered values.

              (u) Upper: Return the maximum of all filtered values.

              (a) Average: Return the mean of all filtered values.

              (m) Median: Return the median of all filtered values.

              (p) Mode: Return the mode of all filtered values.
     is the output of the filter.


       -I     x_inc [and optionally y_inc] is the output Increment. Append m to indicate minutes,
              or  c to indicate seconds. If the new x_inc, y_inc are NOT integer multiples of the
              old ones (in the input data), filtering will be considerably slower. [Default: Same
              as input.]

       -R     west,  east,  south,  and  north defines the Region of the output points. [Default:
              Same as input.]

       -T     Toggle the node registration for the output grid so as to become  the  opposite  of
              the input grid [Default gives the same registration as the input grid].

       -Qcols cols  is  the total number of columns in the input text table file.  For this mode,
              it expects to read depths consisted of several columns. Each  column  represents  a
              filtered grid with a filter width, which can be obtained by grd2xyz -Z. The outcome
              will be median, MAD, and mean. So, the column with the medians is used to  generate
              the  regional  component  and the column with the MADs is used to conduct the error

       -V[level] (more ...)
              Select verbosity level [c].

       -f[i|o]colinfo (more ...)
              Specify data types of input and/or output columns.

       -^ or just -
              Print a short message about the syntax of the command, then exits (NOTE: on Windows
              just use -).

       -+ or just +
              Print  an  extensive  usage  (help)  message,  including  the  explanation  of  any
              module-specific option (but not the GMT common options), then exits.

       -? or no arguments
              Print a complete usage (help) message, including the explanation  of  all  options,
              then exits.


       By  default  GMT  writes  out grid as single precision floats in a COARDS-complaint netCDF
       file format. However, GMT is able to produce grid files in many other commonly  used  grid
       file formats and also facilitates so called "packing" of grids, writing out floating point
       data as 1- or 2-byte integers. (more ...)


       When the output grid  type  is  netCDF,  the  coordinates  will  be  labeled  "longitude",
       "latitude", or "time" based on the attributes of the input data or grid (if any) or on the
       -f or -R options. For example, both  -f0x  -f1t  and  -R90w/90e/0t/3t  will  result  in  a
       longitude/time grid. When the x, y, or z coordinate is time, it will be stored in the grid
       as relative time since epoch as specified by TIME_UNIT and TIME_EPOCH in the gmt.conf file
       or on the command line. In addition, the unit attribute of the time variable will indicate
       both this unit and epoch.


       Suppose that is a file of 5 minute bathymetry from 140E to 260E and
       0N  to  50N,  and you want to find the medians of values within a 300km radius (600km full
       width) of the output points, which you choose to be from 150E to 250E and 10N to 40N,  and
       you  want  the output values every 0.5 degree. To prevent the medians from being biased by
       the sloping plane, you want to divide the filter circle into 6 sectors and to  choose  the
       lowest value among 6 medians. Using spherical distance calculations, you need:

              gmt dimfilter -Fm600 -D4 \
                  -Nl6 -R150/250/10/40 -I0.5 -V

       Suppose  that  is a file of 0.5 minute bathymetry from 32W to 15W and 8N to
       25N, and you want to remove small-length-scale features in order to define a swell  in  an
       area extending from 27.5W to 20.5W and 12.5N to 19.5N, and you want the output value every
       2 minute. Using cartesian distance calculations, you need:

              gmt dimfilter -Fm220 -Nl8 -D2 -R-27.5/-20.5/12.5/19.5 -I2m -V
              gmt grdfilter -Fg50 -D2 -V

       Suppose that you found a range of filter widths for a given area,  and  you  filtered  the
       given  bathymetric  data  using  the range of filter widths (e.g.,, and you want to define a regional trend using the range of  filter  widths,  and
       you want to obtain median absolute deviation (MAD) estimates at each data point. Then, you
       will need to do:

              gmt grd2xyz -Z > f100.d
              gmt grd2xyz -Z > f110.d
              gmt grd2xyz -Z > f120.d
              gmt grd2xyz -Z > f130.d
              paste f100.d f110.d f120.d f130.d > depths.d
              gmt dimfilter depths.d -Q4 > output.z


       When working with geographic (lat, lon) grids,  all  three  convolution  filters  (boxcar,
       cosine arch, and gaussian) will properly normalize the filter weights for the variation in
       gridbox size with latitude, and  correctly  determine  which  nodes  are  needed  for  the
       convolution  when  the  filter  "circle" crosses a periodic (0-360) boundary or contains a
       geographic pole. However, the spatial filters, such as median and mode filters, do not use
       weights  and  thus should only be used on Cartesian grids (or at very low latitudes) only.
       If you want to apply such spatial filters you should project your data  to  an  equal-area
       projection and run dimfilter on the resulting Cartesian grid.


       The  is a skeleton shell script that can be used to set up a complete DiM
       analysis, including the MAD analysis.


       Kim, S.-S., and Wessel, P. (2008),  Directional  Median  Filtering  for  Regional-Residual
       Separation     of     Bathymetry,     Geochem.     Geophys.     Geosyst.,    9,    Q03005,


       gmt, grdfilter


       2019, P. Wessel, W. H. F. Smith, R. Scharroo, J. Luis, and F. Wobbe