plot.mat                 package:sma                 R Documentation

_R_e_d _a_n_d _G_r_e_e_n _C_o_l_o_r _I_m_a_g_e _o_f _D_a_t_a _M_a_t_r_i_x

_D_e_s_c_r_i_p_t_i_o_n:

     This function produces a red and green color image of a data
     matrix using an RGB color specification. Larger entries are
     represented with reds of increasing intensity, and smaller entries
     are represented with greens of increasing intensity.

_U_s_a_g_e:

     plot.mat(x, nrgcols=50, rlabels=FALSE, clabels=FALSE, rcols=1, ccols=1, title="",...)

_A_r_g_u_m_e_n_t_s:

       x: a matrix of numbers.

 nrgcols: the number of colors (>= 1) to be used in the red and green
          palette.

 rlabels: vector of character strings to be placed at the row
          tickpoints, labels for the rows of 'X'.

 clabels: vector of character strings to be placed at the column
          tickpoints, labels for the columns of 'X'.

   rcols: colors to be used for the labels of the rows of 'X'. 'rcols'
          can have either length 1, in which case all the labels are
          displayed using the same color, or the same length as
          'rlabels', in which case a color is specified for the label
          of each row of 'X'.

   ccols: colors to be used for the labels of the columns of 'X'.
          'ccols' can have either length 1, in which case all the
          labels are displayed using the same color, or the same length
          as 'clabels', in which case a color is specified for the
          label of each column of 'X'.

   title: character string, overall title for the plot.

     ...: graphical parameters may also be supplied as arguments  to
          the function (see 'par').  E.g. 'zlim=c(-3,3)'

_A_u_t_h_o_r(_s):

     Sandrine Dudoit, sandrine@stat.berkeley.edu

_S_e_e _A_l_s_o:

     'plot.cor', 'rgcolors.func', 'cor.na', 'cor', 'image', 'rgb'.

_E_x_a_m_p_l_e_s:

     data(MouseArray)
     ##mouse.setup <- init.grid()
     ##mouse.data <- init.data() ## see \emph{init.data}
     mouse.lratio <- stat.ma(mouse.data, mouse.setup)

     ## Looking at log ratios of mouse1
     plot.mat(spatial.func(mouse.lratio$M[,1], mouse.setup))

