Seeking faster objective mapping of noisy, irregularly spaced data

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If you have noisy data sampled at irregular x,y locations, you can use objective mapping to make a smooth map of the results. I have used Kirill Pankratov's nice implementation objmap (described here, code here) for many years. I like it better than griddata because you choose the x- and y-scales over which datapoints "influence" the final map, and the amount of error to allow at your measurement locations. Now I have a new application that requires making many such maps, and speed is an issue. I wanted to check if there is a more recent Matlab implementation that runs faster or another fast mapping technique meant for noisy sparse data. I tried using the Matlab profiler on the objmap function but there were no obvious bottlenecks. [I found barnesn on the File Exchange which works fine, but it seems to be slower than objmap.] Thanks for any ideas.

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