Views-utils             package:IRanges             R Documentation

_U_t_i_l_i_t_y _f_u_n_c_t_i_o_n_s _a_n_d _n_u_m_e_r_i_c _s_u_m_m_a_r_y _o_f _V_i_e_w_s _o_f _n_u_m_e_r_i_c_s

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

     The 'slice' function creates a Views object that contains the
     indices where the data are within the specified bounds.

     The 'viewMins', 'viewMaxs', 'viewSums' functions calculate the
     minimums, maximums, and sums on views respectively.

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

       slice(x, lower=-Inf, upper=Inf, ...)

       viewMins(x, na.rm=FALSE)
       viewMaxs(x, na.rm=FALSE)
       viewSums(x, na.rm=FALSE)

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

       x: An XRleInteger, XInteger object or an integer vector for
          'slice'.

          An XRleIntegerViews, XIntegerViews object for 'viewMins',
          'viewMaxs' and 'viewSums'. 

lower, upper: The lower and upper bounds for the slice. 

   na.rm: Logical indicating whether or not to include missing values
          in the results. 

     ...: Additional arguments to be passed to or from methods. 

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

     The 'slice' function creates views on XRleInteger or XInteger
     objects where the data are within the specified bounds. This is
     useful for finding areas of absolute maxima (peaks), absolute
     minima (troughs), or fluxuations within a specified limits.

     The 'viewMins', 'viewMaxs', and 'viewSums' functions provide
     efficient methods for calculating the specified numeric summary by
     performing the looping in compiled code.

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

     An XRleIntegerViews or XIntegerViews object for 'slice'.

     An integer vector of 'length(x)' containing the numeric summaries
     for the views.

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

     P. Aboyoun

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

     XRleIntegerViews-class, XIntegerViews-class

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

       ## Views derived from vector
       vec <- as.integer(c(19, 5, 0, 8, 5))
       slice(vec, lower=5, upper=8)

       set.seed(0)
       vec <- sample(24)
       vecViews <- slice(vec, lower=4, upper=16)
       vecViews
       viewMins(vecViews)
       viewMaxs(vecViews)
       viewSums(vecViews)

       ## Views derived from coverage
       x <- IRanges(start=c(1L, 9L, 4L, 1L, 5L, 10L),
                    width=c(5L, 6L, 3L, 4L, 3L,  3L))
       coverage(x, start=1, end=15)

