grdtrend − Fit and/or remove a polynomial trend in a grid file
grdtrend grdfile −Nn_model[r] [ −Ddiff.grd ] [ −Ttrend.grd ] [ −V ] [ −Wweight.grd ]
grdtrend reads a 2-D grid 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 grid file.
−N |
[r]n_model sets the number of model parameters to fit. Append r for robust fit. |
No space between the option flag and the associated arguments.
−D |
Write the difference (input data - trend) to the file diff.grd. |
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−T |
Write the fitted trend to the file trend.grd. |
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−V |
Selects verbose mode, which will send progress reports to stderr [Default runs "silently"]. |
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−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. |
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 description above is to allow the user to match −N with the order of the polynomial surface. See grdmath if you need to evaluate the trend using the reported coefficients.
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 2- or 4-byte integers. To specify the precision, scale and offset, the user should add the suffix =id[/scale/offset[/nan]], where id is a two-letter identifier of the grid type and precision, and scale and offset are optional scale factor and offset to be applied to all grid values, and nan is the value used to indicate missing data. When reading grids, the format is generally automatically recognized. If not, the same suffix can be added to input grid file names. See grdreformat(1) and Section 4.17 of the GMT Technical Reference and Cookbook for more information.
When reading a netCDF file that contains multiple grids, GMT will read, by default, the first 2-dimensional grid that can find in that file. To coax GMT into reading another multi-dimensional variable in the grid file, append ?varname to the file name, where varname is the name of the variable. Note that you may need to escape the special meaning of ? in your shell program by putting a backslash in front of it, or by placing the filename and suffix between quotes or double quotes. The ?varname suffix can also be used for output grids to specify a variable name different from the default: "z". See grdreformat(1) and Section 4.18 of the GMT Technical Reference and Cookbook for more information, particularly on how to read splices of 3-, 4-, or 5-dimensional grids.
To remove a planar trend from hawaii_topo.grd and write result in hawaii_residual.grd:
grdtrend hawaii_topo.grd −N 3 −D hawaii_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:
grdtrend hawaii_topo.grd −N 10r −T hawaii_trend.grd −W hawaii_weight.grd −V
GMT(1), grdfft(1), grdfilter(1)