ordiplot                package:vegan                R Documentation

_A_l_t_e_r_n_a_t_i_v_e _p_l_o_t _a_n_d _i_d_e_n_t_i_f_y _F_u_n_c_t_i_o_n_s _f_o_r _O_r_d_i_n_a_t_i_o_n

_D_e_s_c_r_i_p_t_i_o_n:

     Ordination plot function especially for congested plots. Function
     'ordiplot' always plots only unlabelled points, but
     'identify.ordiplot' can be used to add labels to selected site,
     species or constraint points.  Function 'identify.ordiplot' can be
     used to identify points from 'plot.cca', 'plot.decorana',
     'plot.procrustes' and 'plot.rad' as well.

_U_s_a_g_e:

     ordiplot(ord, choices = c(1, 2), type="points", ...)
     ## S3 method for class 'ordiplot':
     identify(x, what, ...)
     ## S3 method for class 'ordiplot':
     points(x, what, ...)
     ## S3 method for class 'ordiplot':
     text(x, what, ...)

_A_r_g_u_m_e_n_t_s:

     ord: A result from an ordination.

 choices: Axes shown. 

    type: The type of graph which may be '"points"', '"text"' or
          '"none"' for any ordination method, or any of the
          alternatives in 'plot.cca' or 'plot.decorana' in 'cca', 'rda'
          or 'decorana' graphs.

     ...: Other graphical parameters. 

       x: A result object from 'ordiplot'.

    what: Items identified in the ordination plot. The types depend on
          the kind of plot used. Most methods know 'sites' and
          'species', functions 'cca' and 'rda' know in addition 
          'constraints' (for `LC' scores), 'centroids' and 'biplot',
          and 'plot.procrustes' ordination plot has 'heads' and
          'points'.

_D_e_t_a_i_l_s:

     Function 'ordiplot' draws an ordination diagram using black
     circles for sites and red crosses for species.  It returns
     invisibly an object of class 'ordiplot' which can be used by
     'identify.ordiplot' to label selected sites or species, or
     constraints in 'cca' and 'rda'.

     The function can handle output from several alternative ordination
     methods. For 'cca', 'rda' and 'decorana' it uses their 'plot'
     method with option 'type = "points"'. In addition, the 'plot'
     functions of these methods return invisibly an 'ordiplot' object
     which can be used by 'identify.ordiplot' to label points. For
     other ordinations it relies on 'scores' to extract the scores.

     For full user control of plots, it is best to call 'ordiplot' with
     'type = "none"' and save the result, and then add sites and
     species using 'points.ordiplot' or 'text.ordiplot' which both pass
     all their arguments to the corresponding default graphical
     functions.

_V_a_l_u_e:

     Function 'ordiplot' returns invisibly an object of class
     'ordiplot' with items 'sites', 'species' and 'constraints' (if
     these are available in the ordination object). Function
     'identify.ordiplot' uses this object to label the point.

_N_o_t_e:

     The purpose of these functions is to provide similar functionality
     as the 'plot', 'plotid' and 'specid' methods in library 'labdsv'.
     The functions are somewhat limited in parametrization, but you can
     call directly the standard 'identify' and 'plot' functions for a
     better user control.

_A_u_t_h_o_r(_s):

     Jari Oksanen

_S_e_e _A_l_s_o:

     'identify' for basic operations, 'plot.cca', 'plot.decorana',
     'plot.procrustes' which also produce objects for
     'identify.ordiplot' and 'scores' for extracting scores from
     non-'vegan' ordinations.

_E_x_a_m_p_l_e_s:

     # Draw a cute NMDS plot
     data(dune)
     dune.dis <- vegdist(wisconsin(dune))
     library(MASS)
     dune.mds <- isoMDS(dune.dis)
     dune.mds <- postMDS(dune.mds, dune.dis)
     # Dirty trick: Save species weighted averages in cproj which we
     # know in ordiplot... (you should ask me to improve the function)
     dune.mds$cproj <- wascores(dune.mds$points, dune, expand = TRUE)
     fig <- ordiplot(dune.mds, type = "none")
     points(fig, "sites", pch=21, col="red", bg="yellow")
     text(fig, "species", col="blue", cex=0.9)
     # A quick plot of the previous.
     # identify is not run automatically because it needs user interaction:
     ## Not run: fig <- ordiplot(dune.mds)
     ## Not run: identify(fig, "spec")

