FITCIRCLE(1gmt) | GMT | FITCIRCLE(1gmt) |
fitcircle - find mean position and pole of best-fit great [or small] circle to points on a sphere.
fitcircle [ table ] -Lnorm [ -Fflags ] [ -S[lat] ] [ -V[level] ] [ -bibinary ] [ -dinodata ] [ -eregexp ] [ -fflags ] [ -ggaps ] [ -hheaders ] [ -iflags ] [ -oflags ] [ -:[i|o] ]
Note: No space is allowed between the option flag and the associated arguments.
fitcircle reads lon,lat [or lat,lon] values from the first two columns on standard input [or table]. These are converted to Cartesian three-vectors on the unit sphere. Then two locations are found: the mean of the input positions, and the pole to the great circle which best fits the input positions. The user may choose one or both of two possible solutions to this problem. The first is called -L1 and the second is called -L2. When the data are closely grouped along a great circle both solutions are similar. If the data have large dispersion, the pole to the great circle will be less well determined than the mean. Compare both solutions as a qualitative check.
The -L1 solution is so called because it approximates the minimization of the sum of absolute values of cosines of angular distances. This solution finds the mean position as the Fisher average of the data, and the pole position as the Fisher average of the cross-products between the mean and the data. Averaging cross-products gives weight to points in proportion to their distance from the mean, analogous to the "leverage" of distant points in linear regression in the plane.
The -L2 solution is so called because it approximates the minimization of the sum of squares of cosines of angular distances. It creates a 3 by 3 matrix of sums of squares of components of the data vectors. The eigenvectors of this matrix give the mean and pole locations. This method may be more subject to roundoff errors when there are thousands of data. The pole is given by the eigenvector corresponding to the smallest eigenvalue; it is the least-well represented factor in the data and is not easily estimated by either method.
The ASCII output formats of numerical data are controlled by parameters in your gmt.conf file. Longitude and latitude are formatted according to FORMAT_GEO_OUT, absolute time is under the control of FORMAT_DATE_OUT and FORMAT_CLOCK_OUT, whereas general floating point values are formatted according to FORMAT_FLOAT_OUT. Be aware that the format in effect can lead to loss of precision in ASCII output, which can lead to various problems downstream. If you find the output is not written with enough precision, consider switching to binary output (-bo if available) or specify more decimals using the FORMAT_FLOAT_OUT setting.
Suppose you have lon,lat,grav data along a twisty ship track in the file ship.xyg. You want to project this data onto a great circle and resample it in distance, in order to filter it or check its spectrum. Do the following:
gmt fitcircle ship.xyg -L2 gmt project ship.xyg -Cox/oy -Tpx/py -S -Fpz | sample1d -S-100 -I1 > output.pg
Here, ox/oy is the lon/lat of the mean from fitcircle, and px/py is the lon/lat of the pole. The file output.pg has distance, gravity data sampled every 1 km along the great circle which best fits ship.xyg
If you have lon, lat points in the file data.txt and wish to return the northern hemisphere great circle pole location using the L2 norm, try
gmt fitcircle data.txt -L2 -Fn > pole.txt
gmt, gmtvector, project, mapproject, sample1d
2019, P. Wessel, W. H. F. Smith, R. Scharroo, J. Luis, and F. Wobbe
May 21, 2019 | 5.4.5 |