Metadata-Version: 2.1
Name: pyssage
Version: 0.0.1
Summary: python version of some of the analyses from PASSaGE 2
Home-page: https://github.com/msrosenberg/pyssage
Author: Michael S. Rosenberg
Author-email: msrosenberg@vcu.edu
License: GPLv3
Description: # PySSaGE
        
        PySSaGE is a collection of python versions of analyses originally part of the *PASSaGE* (Rosenberg 2001) and [*PASSaGE* 
        2]((https://www.passagesoftware.net)) (Rosenberg and Anderson 2011) software packages for spatial analysis.
        
        A more throrough explanation of how to use the code is forthcoming.
        
        ## Analyses
        
        So far the following analyses have been implemented:
        
        ### Quadrat-Variance
        
        * TTLQV: Two-Term Local Quadrat Variance Analysis (Hill 1973)
        * 3TLQV: Three-Term Local Quadrat Variance Analysis (Hill 1973)
        * PQV: Paired Quadrat Variance Analysis
        * tQV: Triplet Quadrat Variance Analysis (Dale 1999)
        * 2NLV: Two-term New Local Variance Analysis (Galiano 1982)
        * 3NLV: Three-term New Local Variance Analysis (Galiano 1982)
        
        ### Distance Calculations
        * Euclidean distances/angles from 1, 2, and 3-dimensional points
        * Spherical distances/angles from latitudes and longitudes
        * Shortest-path/Geodesic distances  
        * Distances from arrays of data
          * Euclidean distances
          * Squared Euclidean distances
          * Manhattan distances
          * Canberra distances
          * Hamming distances
          * Jaccard distances
          * Cosine distances
          * Czekanowski distances
          * Correlation distances
          * Squared correlation distances
        * Distance class determination
        
        ### Connections/Links
        * Delaunay/Voronoi Tessellation (Delaunay 1928, 1934)
        * Minimum-spanning Tree
        * Relative Neighborhood Network
        * Gabriel Graph (Gabriel and Sokal 1969)
        * Least-diagonal Network (Fraser and van den Driessche 1972)
        * Range-based Connections
        * *k*-nearest Neighbors
        
        ### Correlograms
        * Correlograms (Cliff and Ord 1973, 1981; Sokal and Oden 1978)
          * Moran's *I* (Moran 1950)
          * Geary's *c* (Geary 1954)
        * Mantel Correlograms (Sokal *et al.* 1987)
        
        ### Anisotropy
        * Bearing Analysis (Falsetti and Sokal 1993)
        * Bearing Correlograms (Rosenberg 2000)
        * Windrose Correlograms (Oden and Sokal 1986)
        * Windrose Mantel Correlograms
        
        ### Miscellaneous
        * Mantel tests (Mantel 1967; Mantel and Valand 1970)
        
        
        ## References
        
        * Cliff, A.D., and J.K. Ord (1973) *Spatial Autocorrelation*. London: Pion.
        
        * Cliff, A.D., and J.K. Ord (1981) *Spatial Processes*. London: Pion.
        
        * Dale, M.R T. (1999) *Spatial Pattern Analysis in Plant Ecology.* Cambridge: Cambridge University Press.
        
        * Delaunay, B. (1928) Sur la sphÃ¨re vide. Pp. 695-700 in Proceedings of the International Mathematical Congress 
          held in Toronto, August 11-16. Toronto: University of Toronto Press.
        
        * Delaunay, B. (1934) Sur la sphÃ¨re vide. Bulletin de L'Academie des Sciences de L'URSS Classe des Sciences 
          MathÃ©matiques et Naturelles 7:793-800.
        
        * Falsetti, A.B., and R.R. Sokal (1993) Genetic structure of human populations in the British Isles. *Annals of 
          Human Biology* 20:215-229.
        
        * Fraser, A.R., and P. van den Driessche (1972) Triangles, density and pattern in point populations. Pp. 277-286 in 
          *Proceedings of the 3rd Conference of the Advisory Group of Forest Statisticians*. Jouy-en-Josas, France: 
          International Union for Research organization, Institut National de la Recherche Agronomique.
        
        * Gabriel, K.R., and R.R. Sokal (1969) A new statistical approach to geographic variation analysis. *Systematic 
          Zoology* 18:259-278.
        
        * Galiano, E.F. (1982) DÃ©tection et mesure de l'hÃ©tÃ©rogÃ©nÃ©itÃ© spatiale des espÃ¨ces dans les pÃ¢turages. *Acta 
          OEcologia / OEcologia Plantarum* 3:269-278.
        
        * Geary, R.C. (1954) The contiguity ratio and statistical mapping. *Incorporated Statistician* 5:115-145.
        
        * Moran, P.A.P. (1950) Notes on continuous stochastic phenomena. *Biometrika* 37:17-23.
        
        * Hill, M.O. (1973) The intensity of spatial pattern in plant communities. *Journal of Ecology* 61:225-235.
        
        * Mantel, N. (1967) The detection of disease clustering and a generalized regression approach. *Cancer Research* 
          27:209-220.
        
        * Mantel, N., and R.S. Valand (1970) A technique of nonparametric multivariate analysis. *Biometrics* 26:547-558.
        
        * Oden, N.L., and R.R. Sokal (1986) Directional autocorrelation: An extension of spatial correlograms to two 
          dimensions. *Systematic Zoology* 35:608-617.
        
        * Rosenberg, M.S. (2000) The bearing correlogram: A new method of analyzing directional spatial autocorrelation. 
          *Geographical Analysis* 32:267-278.
        
        * Rosenberg, M.S. (2001) *PASSAGE. Pattern Analysis, Spatial Statistics and Geographic Exegesis.* Version 1.
        
        * Rosenberg, M.S., and C.D. Anderson (2011) *PASSaGE. Pattern Analysis, Spatial Statistics and Geographic 
        Exegesis.* Version 2. *Methods in Ecology and Evolution* 2(3):229â€“232. 
        [DOI: 10.1111/j.2041-210x.2010.00081.x](https://dx.doi.org/10.1111/j.2041-210x.2010.00081.x)
        
        * Sokal, R.R., and N.L. Oden (1978) Spatial autocorrelation in biology 1. Methodology. *Biological Journal of the 
          Linnean Society* 10:199-228.
        
        * Sokal, R.R., N.L. Oden, and J.S.F. Barker (1987) Spatial structure in *Drosophila buzzatii* populations: Simple 
          and directional spatial autocorrelation. *American Naturalist* 129:122-142.
        
Platform: UNKNOWN
Requires-Python: >=3.6
Description-Content-Type: text/markdown
