Metadata-Version: 2.1
Name: hdstats
Version: 0.2.1
Summary: Multivariate / high-dimensional statistics and time series algorithms for spatial-temporal stacks
Home-page: http://github.com/daleroberts/hdstats
Author: Dale Roberts
Author-email: dale.o.roberts@gmail.com
License: BSD-3-Clause License
Description: # hdstats
        
        A library of multivariate, high-dimensional statistics, and time series algorithms for spatial-temporal stacks.
        
        ----
        
        ### Geometric median PCM
        
        Generation of geometric median pixel composite mosaics from a stack of data; see [example](https://github.com/daleroberts/hdstats/blob/master/docs/geomedian.ipynb).
        
        If you are using this algorithm in your research or products, please cite:
        
        *Roberts, D., Mueller, N., & McIntyre, A. (2017). High-dimensional pixel composites from earth observation time series. IEEE Transactions on Geoscience and Remote Sensing, 55(11), 6254-6264.*
        
        ### Geometric Median Absolute Deviation (MAD) PCM
        
        Accelerated generation of geometric median absolute deviation pixel composite mosaics from a stack of data; see [example](https://github.com/daleroberts/hdstats/blob/master/docs/mad.ipynb).
        
        If you are using this algorithm in your research or products, please cite:
        
        *Roberts, D., Dunn, B., & Mueller, N. (2018). Open data cube products using high-dimensional statistics of time series. In IGARSS 2018-2018 IEEE International Geoscience and Remote Sensing Symposium (pp. 8647-8650).*
        
        ### Feature generation for spatial-temporal time series stacks.
        
        see [example](https://github.com/daleroberts/hdstats/blob/master/docs/temporal.ipynb).
        
        ---
        
        ### Assumptions
        
        We assume that the data stack dimensions are ordered so that the spatial dimensions are first (*y*,*x*), followed by the spectral dimension of size *p*, finishing with the temporal dimension. Algorithms reduce in the last dimension (typically, the temporal dimension).
        
        ---
        
        ### Research and Development / Advanced Implementations
        
        All advanced implementations and cutting-edge research codes are now found in [github.com/daleroberts/hdstats-private](https://github.com/daleroberts/hdstats-private). These are only available to research collaborators.
        
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