dichromat             package:dichromat             R Documentation

_R_e_m_o_v_e _r_e_d-_g_r_e_e_n _d_i_s_t_i_n_c_t_i_o_n_s _f_r_o_m _c_o_l_o_u_r_s

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

     Collapses red-green color distinctions to approximate the effect
     of the two common forms of red-green colour blindness, protanopia
     and deuteranopia.

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

     dichromat(colours, type = c("deutan", "protan"))

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

 colours: A vector of R colors, either color names or color hex strings

    type: Type of color-blindness to simulate

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

     Someone with the specified form of red-green colour blindness will
     find that the transformation has little effect on the appearance
     of colours.  Colours that are indistinguishable after
     transformation were likely indistinguishable to them before
     transformation.  About 10% of men (and almost no women) have
     red-green colour blindness.

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

     A vector of R colors

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

     Thomas Lumley

_R_e_f_e_r_e_n_c_e_s:

     F. Vinot, H. Brettel and J. D. Mollon (1999) Digital video
     colourmaps for checking the legibility of displays by dichromats.
     Color Research and Application 24, 243-252.

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

     ## from example(pie)
      par(mfrow=c(2,2))
      pie.sales <- c(0.12, 0.3, 0.26, 0.16, 0.04, 0.12)
      names(pie.sales) <- c("Blueberry", "Cherry",
              "Apple", "Boston Cream", "Other", "Vanilla Cream")
      pie(pie.sales) # default colours
      pie(pie.sales,
            col = c("purple", "violetred1", "green3", "cornsilk", "cyan", "white"))
      pie(pie.sales,col=dichromat( c("white", "lightblue", "mistyrose", "lightcyan", 
                     "lavender", "cornsilk"))) # default colours
      pie(pie.sales,
            col =dichromat(c("purple", "violetred1", "green3", "cornsilk", "cyan", "white")))

     ## standard color schemes
     pie(rep(1,10),col=heat.colors(10))
     pie(rep(1,10),col=dichromat(heat.colors(10)))
     pie(rep(1,8),col=palette())
     pie(rep(1,8),col=dichromat(palette()))

     pie(rep(1,15),col=topo.colors(15))
     pie(rep(1,15),col=dichromat(topo.colors(15)))
     pie(rep(1,15),col=terrain.colors(15))
     pie(rep(1,15),col=dichromat(terrain.colors(15)))

     pie(rep(1,15),col=cm.colors(15))
     pie(rep(1,15),col=dichromat(cm.colors(15)))
     bluescale<-colorRampPalette(c("#FFFFCC","#C7E9B4","#7FCDBB","#40B6C4","#2C7FB8" ,"#253494"))
     pie(rep(1,15),col=bluescale(15))
     pie(rep(1,15),col=dichromat(bluescale(15)))

     par(mfrow=c(2,3))
     x<-matrix(rnorm(10*10),10)
     redgreen<-colorRampPalette(c("red","green3"))
     image(1:10,1:10,x, col=bluescale(10),
     main="blue-yellow scale")
     image(1:10,1:10,x, col=dichromat(bluescale(10)), main="deutan")
     image(1:10,1:10,x,col=dichromat(bluescale(10),"protan"), main="protan")

     image(1:10,1:10,x, col=redgreen(10),
     main="red-green scale")
     image(1:10,1:10,x, col=dichromat(redgreen(10)), main="deutan")
     image(1:10,1:10,x, col=dichromat(redgreen(10),"protan"), main="protan")

