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<HTML>
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<TITLE>grdtrend</TITLE>
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<H1>grdtrend</H1>
<HR>
<PRE>
<!-- Manpage converted by man2html 3.0.1 -->
grdtrend - Fit and/or remove a polynomial trend in a grd
file
</PRE>
<H2>SYNOPSIS</H2><PRE>
<B>grdtrend</B> <I>grdfile</I> <B>-N</B><I>n</I><B>_</B><I>model</I>[<B>r</B>] [ <B>-D</B><I>diff.grd</I> ] [ <B>-T</B><I>trend.grd</I>
] [ <B>-V</B> ] [ <B>-W</B><I>weight.grd</I> ]
</PRE>
<H2>DESCRIPTION</H2><PRE>
<B>grdtrend</B> 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 <B>-N</B><I>n</I><B>_</B><I>model</I>, the number of model
parameters to use; thus, <B>-N</B><I>4</I> fits a bilinear trend, <B>-N</B><I>6</I> a
quadratic <A HREF="surface.html">surface</A>, and so on. Optionally, append <B>r</B> to the
<B>-N</B> option to perform a robust fit. In this case, the pro
gram will iteratively reweight the data based on a robust
scale estimate, in order to converge to a solution insen
sitive 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 argu
ments.
<I>grdfile</I>
The name of a 2-D binary grd file.
<B>-N</B> <I>n</I><B>_</B><I>model</I>[<B>r</B>] sets the number of model parameters to
fit. Append <B>r</B> for robust fit.
</PRE>
<H2>OPTIONS</H2><PRE>
No space between the option flag and the associated argu
ments.
<B>-D</B> Write the difference (input data - trend) to the
file <I>diff.grd</I>.
<B>-T</B> Write the fitted trend to the file <I>trend.grd</I>.
<B>-V</B> Selects verbose mode, which will send progress
reports to stderr [Default runs "silently"].
<B>-W</B> If <I>weight.grd</I> exists, it will be read and used to
solve a weighted least-squares problem. [Default:
fit will be written to <I>weight.grd</I>.
</PRE>
<H2>REMARKS</H2><PRE>
The domain of x and y will be shifted and scaled to [-1,
1] and the basis functions are built from Legendre polyno
mials. 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 <B>-V</B> 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 <B>-N</B> with
the order of the polynomial surface.
</PRE>
<H2>EXAMPLES</H2><PRE>
To remove a planar trend from hawaii_topo.grd and write
result in hawaii_residual.grd, try
<B>grdtrend</B> hawaii_topo.grd <B>-N</B>3 <B>-D</B>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, try
<B>grdtrend</B> hawaii_topo.grd <B>-N</B>10<B>r</B> <B>-T</B>hawaii_trend.grd
<B>-W</B>hawaii_weight.grd <B>-V</B>
</PRE>
<H2>SEE ALSO</H2><PRE>
<I>gmt</I>(l), <I><A HREF="grdfft.html">grdfft</A></I>(l), <I><A HREF="grdfilter.html">grdfilter</A></I>(l)
</PRE>
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