curve                package:graphics                R Documentation

_D_r_a_w _F_u_n_c_t_i_o_n _P_l_o_t_s

_D_e_s_c_r_i_p_t_i_o_n:

     Draws a curve corresponding to the given function or, for
     'curve()' also an expression (in 'x') over the interval
     '[from,to]'.

_U_s_a_g_e:

     curve(expr, from = NULL, to = NULL, n = 101, add = FALSE,
           type = "l", ylab = NULL, log = NULL, xlim = NULL, ...)

     ## S3 method for class 'function':
     plot(x, y = 0, to = 1, from = y, xlim = NULL, ...)

_A_r_g_u_m_e_n_t_s:

    expr: an expression written as a function of 'x', or alternatively
          the name of a function which will be plotted.

       x: a 'vectorizing' numeric R function.

 from,to: the range over which the function will be plotted.

       n: integer; the number of x values at which to evaluate.

     add: logical; if 'TRUE' add to already existing plot.

    xlim: numeric of length 2; if specified, it serves as default for
          'c(from, to)'.

    type: plot type: see 'plot.default'.

       y: alias for 'from' for compatibility with 'plot()'

ylab, log, ...: labels and graphical parameters can also be specified
          as arguments. 'plot.function' passes all these to 'curve'.

_D_e_t_a_i_l_s:

     The evaluation of 'expr' is at 'n' points equally spaced over the
     range '[from, to]', possibly adapted to log scale.  The points
     determined in this way are then joined with straight lines. 'x(t)'
     or 'expr' (with 'x' inside) must return a numeric of the same
     length as the argument 't' or 'x'.

     For 'curve()', if either of 'from' or 'to' is 'NULL', it defaults
     to the corresponding element of 'xlim', and 'xlim' defaults to the
     x-limits of the current plot. For 'plot(<function>, ..)', the
     defaults for (from,to) are (0,1).

     'log' is taken from the current plot only when 'add' is true, and
     otherwise defaults to '""' indicating linear scales on both axes.

     This used to be a quick hack which now seems to serve a useful
     purpose, but can give bad results for functions which are not
     smooth.

     For expensive-to-compute 'expr'essions, you should use smarter
     tools.

_S_e_e _A_l_s_o:

     'splinefun' for spline interpolation, 'lines'.

_E_x_a_m_p_l_e_s:

     plot(qnorm)
     plot(qlogis, main = "The Inverse Logit : qlogis()")
     abline(h=0, v=0:2/2, lty=3, col="gray")

     curve(sin, -2*pi, 2*pi)
     curve(tan, main = "curve(tan)  --> same x-scale as previous plot")

     op <- par(mfrow=c(2,2))
     curve(x^3-3*x, -2, 2)
     curve(x^2-2, add = TRUE, col = "violet")

     ## simple and sophisticated, quite similar:
     plot(cos, -pi,  3*pi)
     plot(cos, xlim = c(-pi,3*pi), n = 1001, col = "blue", add=TRUE)

     chippy <- function(x) sin(cos(x)*exp(-x/2))
     curve(chippy, -8, 7, n=2001)
     plot (chippy, -8, -5)

     for(ll in c("","x","y","xy"))
        curve(log(1+x), 1,100, log=ll, sub=paste("log= '",ll,"'",sep=""))
     par(op)