Logic                  package:base                  R Documentation

_L_o_g_i_c_a_l _O_p_e_r_a_t_o_r_s

_D_e_s_c_r_i_p_t_i_o_n:

     These operators act on logical vectors.

_U_s_a_g_e:

     ! x
     x & y
     x && y
     x | y
     x || y
     xor(x, y)
     isTRUE(x)

_A_r_g_u_m_e_n_t_s:

    x, y: logical vectors, or objects which can be coerced to such or
          for which methods have been written.

_D_e_t_a_i_l_s:

     '!' indicates logical negation (NOT).

     '&' and '&&' indicate logical AND and '|' and '||' indicate
     logical OR.  The shorter form performs elementwise comparisons in
     much the same way as arithmetic operators.  The longer form
     evaluates left to right examining only the first element of each
     vector.  Evaluation proceeds only until the result is determined. 
     The longer form is appropriate for programming control-flow and
     typically preferred in 'if' clauses.

     'xor' indicates elementwise exclusive OR.

     'isTRUE(x)' is an abbreviation of 'identical(TRUE,x)'.

     Numeric and complex vectors will be coerced to logical values,
     with zero being false and all non-zero values being true.  Raw
     vectors are handled without any coercion for '!', '&' and '|',
     with these operators being applied bitwise (so '!' is the
     1-complement).

     The operators '!', '&' and '|' are generic functions: methods can
     be written for them individually or via the 'Ops') group generic
     function.

     'NA' is a valid logical object.  Where a component of 'x' or 'y'
     is 'NA', the result will be 'NA' if the outcome is ambiguous.  In
     other words 'NA & TRUE' evaluates to 'NA', but 'NA & FALSE'
     evaluates to 'FALSE'.  See the examples below.

_R_e_f_e_r_e_n_c_e_s:

     Becker, R. A., Chambers, J. M. and Wilks, A. R. (1988) _The New S
     Language_. Wadsworth & Brooks/Cole.

_S_e_e _A_l_s_o:

     'TRUE' or 'logical'.

     'any' and 'all' for OR and AND on many scalar arguments.

     'Syntax' for operator precedence.

_E_x_a_m_p_l_e_s:

     y <- 1 + (x <- rpois(50, lambda=1.5) / 4 - 1)
     x[(x > 0) & (x < 1)]    # all x values between 0 and 1
     if (any(x == 0) || any(y == 0)) "zero encountered"

     ## construct truth tables :

     x <- c(NA, FALSE, TRUE)
     names(x) <- as.character(x)
     outer(x, x, "&")## AND table
     outer(x, x, "|")## OR  table

