[Numpy-discussion] feature tracking in numpy/scipy

Benjamin Root ben.root at ou.edu
Thu Mar 7 14:14:28 EST 2013

On Sat, Mar 2, 2013 at 5:32 PM, Scott Collis <scollis.acrf at gmail.com> wrote:

> Good afternoon list,
> I am looking at feature tracking in a 2D numpy array, along the lines of
> Dixon and Wiener 1993 (for tracking precipitating storms)
> Identifying features based on threshold is quite trivial using
> ndimage.label
> b_fld=np.zeros(mygrid.fields['rain_rate_A']['data'].shape)
> rr=10
> b_fld[mygrid.fields['rain_rate_A']['data'] > rr]=1.0
> labels, numobjects = ndimage.label(b_fld[0,0,:,:])
> (note mygrid.fields['rain_rate_A']['data'] is dimensions time,height, y, x)
> using the matplotlib contouring and fetching the vertices I can get a nice
> list of polygons of rain rate above a certain threshold… Now from here I
> can just go and implement the Dixon and Wiener methodology but I thought I
> would check here first to see if anyone know of a object/feature tracking
> algorithm in numpy/scipy or using numpy arrays (it just seems like
> something people would want to do!).. i.e. something that looks back and
> forward in time and identifies polygon movement and identifies objects with
> temporal persistence..
> Cheers!
> Scott
> Dixon, M., and G. Wiener, 1993: TITAN: Thunderstorm Identification,
> Tracking, Analysis, and Nowcasting—A Radar-based Methodology. *Journal of
> Atmospheric and Oceanic Technology*, *10*, 785–797,
> doi:10.1175/1520-0426(1993)010<0785:TTITAA>2.0.CO;2.
> http://journals.ametsoc.org/doi/abs/10.1175/1520-0426%281993%29010%3C0785%3ATTITAA%3E2.0.CO%3B2
Say hello to my PhD project: https://github.com/WeatherGod/ZigZag

In it, I have the centroid-tracking portion of the TITAN code, along with
SCIT, and hooks into MHT.  Several of the dependencies are also available
in my repositories.


P.S. - I have personally met Dr. Dixon on multiple occasions and he is a
great guy to work with.  Feel free to email him or myself with questions
about TITAN.
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