2010/6/5, Hamish <hamis...@yahoo.com>: > Hanlie wrote: >> >> At this point, g.region reports 1146474 cells in the region, while I >> >> have 1146370 lines of coordinates in my file. > ... >> > So it looks like there are about 100 coordinates missing from the ASCII >> > ASCII file. > > 0.01% .. > >> Maybe "holes" in the data? > > perhaps this: https://trac.osgeo.org/grass/ticket/123 > ??
I don't think it's this bug because this bug discards only one line of data. I don't get any data in because the number of coordinate pairs in the file is less than the number of cells in the defined region. > > >> I was thinking perhaps importing the points as vectors, converting >> them to raster and then doing a nearest neighbour or IDW interpolation >> to fill the gaps. At least then I'll be able to see where the gaps are >> and limit the interpolated pixels using a mask? > > No need to do anything different to find the missing pixels. Inspecting > the output of r.univar with r.in.xyz's method=n maps can be very useful > for troubleshooting. > > > from the help page: > > Gridded data > If data is known to be on a regular grid r.in.xyz can > reconstruct the map perfectly as long as some care is > taken to set up the region correctly and that the > data's native map projection is used. A typical method > would involve determining the grid resolution either by > examining the data's associated documentation or by > studying the text file. Next scan the data with > r.in.xyz's -s (or -g) flag to find the input data's > bounds. GRASS uses the cell-center raster convention > where data points fall within the center of a cell, as > opposed to the grid-node convention. Therefore you will > need to grow the region out by half a cell in all > directions beyond what the scan found in the file. > After the region bounds and resolution are set cor- > rectly with g.region, run r.in.xyz using the n method > and verify that n=1 at all places. r.univar can help. > Once you are confident that the region exactly matches > the data proceed to run r.in.xyz using one of the mean, > min, max, or median methods. With n=1 throughout, the > result should be identical regardless of which of those > methods are used. > > > with the "n" map you might use r.mapcalc to extract the NULL cells > as some value, then r.out.xyz or r.to.vect on th extracts to highlight > where they are. Or maybe you get lucky with r.colors with "nv" set to > bright magenta on the original data. Thanks, I'll try this to find where the holes in the data are. > > > > Hamish > > > > > _______________________________________________ grass-user mailing list grass-user@lists.osgeo.org http://lists.osgeo.org/mailman/listinfo/grass-user