Hello, First of all, I want to introduce myself. I am Víctor González and I'll be working with Jorge Arévalo in the AniMove plugin for python. We are part of geomati.co and we are very excited for this first collaboration with the Faunalia and QGIS community.
We already started analyzing the task and we have some questions. First, we are going to made a fork of the current animove plugin repository [1] and when we finish we'll do a pull request. Is that ok with you? Anyone has a better idea? Regarding the kernel analysis algorithm, we found that the gaussian_kde class in scipy [2] has a set_bandwidth method in order to set the bandwidth of the method as a simple scalar. But this is only available from 0.11.0 version. Which version of scipy we assume will be installed in the distribution? Also, that gaussian_kde class allows 'scotts' and 'silverman' method to calculate the bandwidth, but no LSCV or is available. The only way to have it working is to set the bw_method as a callable and implement the LSCV bandwidth ourselves. The problem is that we are not experts in statistics and we don't know how to implement it. We searched for the formula but it's quite hard to understand and implement at first. Do you know of any python implementation? Finally, the kernel analysis is supposed to create several probability rasters (one for each animal), right? The problem is that we don't know the number of outputs beforehand, so we cannot specify them in the SEXTANTE algorithm. A solution is to create the rasters in a folder (specified by the user) and then add it to QGIS by hand. Is that ok? Thanks in advance, Víctor. ----- [1] https://github.com/volterra79/sextante_animove [2] http://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.gaussian_kde.html
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