grdtrend(1gmt) [debian man page]
GRDTREND(l) GRDTREND(l) NAME
grdtrend - Fit and/or remove a polynomial trend in a grd file SYNOPSIS
grdtrend grdfile -Nn_model[r] [ -Ddiff.grd ] [ -Ttrend.grd ] [ -V ] [ -Wweight.grd ] DESCRIPTION
grdtrend reads a 2-D gridded file and fits a low-order polynomial trend to these data by [optionally weighted] least-squares. The trend surface is defined by: m1 + m2*x + m3*y + m4*x*y + m5*x*x + m6*y*y + m7*x*x*x + m8*x*x*y + m9*x*y*y + m10*y*y*y. The user must specify -Nn_model, the number of model parameters to use; thus, -N4 fits a bilinear trend, -N6 a quadratic surface, and so on. Optionally, append r to the -N option to perform a robust fit. In this case, the program will iteratively reweight the data based on a robust scale estimate, in order to converge to a solution insensitive to outliers. This may be handy when separating a "regional" field from a "residual" which should have non-zero mean, such as a local mountain on a regional surface. If data file has values set to NaN, these will be ignored during fitting; if output files are written, these will also have NaN in the same locations. No space between the option flag and the associated arguments. grdfile The name of a 2-D binary grd file. -N [r]n_model sets the number of model parameters to fit. Prepend r for robust fit. OPTIONS
No space between the option flag and the associated arguments. -D Write the difference (input data - trend) to the file diff.grd. -T Write the fitted trend to the file trend.grd. -V Selects verbose mode, which will send progress reports to stderr [Default runs "silently"]. -W If weight.grd exists, it will be read and used to solve a weighted least-squares problem. [Default: Ordinary least-squares fit.] If the robust option has been selected, the weights used in the robust fit will be written to weight.grd. REMARKS
The domain of x and y will be shifted and scaled to [-1, 1] and the basis functions are built from Legendre polynomials. These have a numerical advantage in the form of the matrix which must be inverted and allow more accurate solutions. NOTE: The model parameters listed with -V are Legendre polynomial coefficients; they are not numerically equivalent to the m#s in the equation described above. The descrip- tion above is to allow the user to match -N with the order of the polynomial surface. EXAMPLES
To remove a planar trend from hawaii_topo.grd and write result in hawaii_residual.grd, try grdtrend hawaii_topo.grd -N3 -Dhawaii_residual.grd To do a robust fit of a bicubic surface to hawaii_topo.grd, writing the result in hawaii_trend.grd and the weights used in hawaii_weight.grd, and reporting the progress, try grdtrend hawaii_topo.grd -Nr10 -Thawaii_trend.grd -Whawaii_weight.grd -V SEE ALSO
gmt(1gmt), grdfft(1gmt), grdfilter(1gmt) 1 Jan 2004 GRDTREND(l)
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GRDFILTER(l) GRDFILTER(l) NAME
grdfilter - Filter a .grd file in the Time domain SYNOPSIS
grdfilter input_file.grd -Dflag -F<type><width> -Goutput_file.grd [ -Ix_inc[m|c][/y_inc[m|c]] ] [ -Rwest/east/south/north[r] ] [ -T ] [ -V ] DESCRIPTION
grdfilter will filter a .grd file in the time domain using a boxcar, cosine arch, gaussian, median, or mode filter and computing distances using Cartesian or Spherical geometries. The output .grd file can optionally be generated as a sub-Region of the input and/or with a new -Increment. In this way, one may have "extra space" in the input data so that the edges will not be used and the output can be within one- half- width of the input edges. If the filter is low-pass, then the output may be less frequently sampled than the input. input_file.grd The file of points to be filtered. -D 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 two options are slower because they recompute weights for each East-West scan line. 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. -F Choose one only of bcgmp for (b)oxcar, (c)osine Arch, (g)aussian, (m)edian, or maximum likelihood (p)robability (a mode estimator) filter and specify full width. -G output_file.grd is the output of the filter. OPTIONS
-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]. -V Selects verbose mode, which will send progress reports to stderr [Default runs "silently"]. EXAMPLES
Suppose that north_pacific_dbdb5.grd 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. Using spherical distance calculations, you need: grdfilter north_pacific_dbdb5.grd -Gfiltered_pacific.grd -Fm600 -D4 -R150/250/10/40 -I0.5 -V SEE ALSO
gmt(1gmt), grdfft(1gmt) 1 Jan 2004 GRDFILTER(l)