{"id":9486,"date":"2018-02-23T09:00:03","date_gmt":"2018-02-23T14:00:03","guid":{"rendered":"https:\/\/blogs.mathworks.com\/pick\/?p=9486"},"modified":"2018-03-06T16:05:56","modified_gmt":"2018-03-06T21:05:56","slug":"contour-data","status":"publish","type":"post","link":"https:\/\/blogs.mathworks.com\/pick\/2018\/02\/23\/contour-data\/","title":{"rendered":"Contour Data"},"content":{"rendered":"
\n <\/p>\n

Sean<\/a>‘s pick this week is contourdata<\/tt><\/a> by Duane Hanselman<\/a>.\n <\/p>\n

<\/introduction><\/p>\n

Last week I was asked a simple question from a customer: “How do I export a contour plot to Google Earth?”<\/p>\n

I knew that this should be possible for either contour line plots or filled plots since the Mapping Toolbox<\/a> has functions for writing the needed plot primitives, i.e: lines (kmlwriteline<\/tt><\/a>), polygons (kmlwritepolygon<\/tt><\/a>), and points (kmlwritepoint<\/tt><\/a>).\n <\/p>\n

So how to do it? I knew about the contourc<\/tt><\/a> function but had never used it. In theory, this would give me the contour lines that I could then write to Google Earth with the kml* functions.\n <\/p>\n

For this example, I’ll use peaks, and plot them roughly over New England.<\/p>\n

z = peaks(50);\r\nlon = linspace(-73, -70, 50);\r\nlat = linspace(42, 45, 50);\r\nnlevels = 10;\r\nc = contourc(lon, lat, z, nlevels);<\/pre>\n
Okay, so what is c?<\/p>\n
whos('c'<\/span>)<\/pre>\n
  Name      Size             Bytes  Class     Attributes\r\n\r\n  c         2x817            13072  double              \r\n\r\n<\/pre>\n
Huh?<\/p>\n
To the documentation I go.  The doc for contourc<\/tt> pointed to the ContourMatrix<\/a> property of a contour plot.  The rows of the matrix are x and y preceded by the contour level and number of points.  Contourc very quickly became one of my not favorite functions.  Ughh.  I generally try to avoid structures and prefer tables but this is an ideal<\/i> use for an array of structures.  It has some meta information: level, number of points, and whether it’s a closed contour or not, and some data that could be various sizes so you can’t use a table.\n   <\/p>\n
Am I really going to have to write a while-loop to parse this thing?<\/p>\n
No!  Professor Hanselman has a function that does exactly<\/i> what I want.\n   <\/p>\n
cs = contourdata(c);\r\ndisp(cs)<\/pre>\n
  1×16 struct array with fields:\r\n    level\r\n    numel\r\n    xdata\r\n    ydata\r\n    isopen\r\n<\/pre>\n
Perfect.<\/p>\n
So to finish off the example what else did I have to do?<\/p>\n
kmlwrite<\/tt> would be the easiest way to write everything in one shot.  It accepts a geoshape<\/tt><\/a>.  I need to have the string literals “Lat”, “Lon”, “Latitude”<\/i> or “Longitude”<\/i> as fields of a struct to pass in.\n   <\/p>\n
[cs.Lat] = cs.ydata;\r\n[cs.Lon] = cs.xdata;\r\ncs = rmfield(cs, {'xdata'<\/span>, 'ydata'<\/span>});\r\ng = geoshape(cs);<\/pre>\n
Geoshapes can be written directly with kmlwrite<\/tt>.  However, I need to tell kmlwrite<\/tt> which color to use for each line.  The level value is stored as a feature property in the geoshape passed in from the struct.  We can get the corresponding color using the index into the unique levels which are sorted be default.\n   <\/p>\n
[~, ~, levidx] = unique(g.level);\r\ncmap = parula(nlevels);<\/pre>\n
Finally, write the kml file.  In order to guarantee that the levels can be seen, clamp them to the ground.<\/p>\n
kmlwrite('NewEnglandPeaks.kml'<\/span>, g, 'Color'<\/span>, cmap(levidx, :), 'AltitudeMode'<\/span>, 'clampToGround'<\/span>)<\/pre>\n
Warning: Omitting unsupported data\r\nclass: logical \r\n<\/pre>\n
 <\/p>\n
Comments<\/a><\/h3>\n
Give it a try and let us know what you think here<\/a> or leave a comment<\/a> for Prof. Hanselman.\n   <\/p>\n