profGenerate              package:xcms              R Documentation

_G_e_n_e_r_a_t_i_o_n _o_f _p_r_o_f_i_l_e _d_a_t_a

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

     Generates profile data in a given range from an indexed pair of
     vectors.

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

     profBin(x, y, num, xstart = min(x), xend = max(x), param = list())
     profBinM(x, y, zidx, num, xstart = min(x), xend = max(x), NAOK = FALSE, param = list())
     profBinLin(x, y, num, xstart = min(x), xend = max(x), param = list())
     profBinLinM(x, y, zidx, num, xstart = min(x), xend = max(x), NAOK = FALSE, param = list())
     profBinLinBase(x, y, num, xstart = min(x), xend = max(x), param = list())
     profBinLinBaseM(x, y, zidx, num, xstart = min(x), xend = max(x), NAOK = FALSE, param = list())
     profIntLin(x, y, num, xstart = min(x), xend = max(x), param = list())
     profIntLinM(x, y, zidx, num, xstart = min(x), xend = max(x), NAOK = FALSE, param = list())

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

       x: numeric vector of value positions

       y: numeric vector of values to bin

    zidx: starting position of each new segment

     num: number of equally spaced x bins

  xstart: starting x value

    xend: ending x value

    NAOK: allow NA values (faster)

   param: parameters for profile generation

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

     These functions take a vector of unequally spaced 'y' values and
     transform them into either a vector or matrix, depending on
     whether there is an index or not. Each point in the vector or
     matrix represents the data for the point centered at its
     corresponding 'x' value, plus or minus half the 'x' step size
     ('xend-xstart/(num-1)').

     The 'Bin' functions set each matrix or vector value to the maximal
     point that gets binned into it.

     The 'BinLin' functions do the same except that they linearly
     interpolate values into which nothing was binned.

     The 'BinLinBase' functions do the same except that they populate
     empty parts of spectra with a base value. They take to two
     parameters: 1) 'baselevel', the intensity level to fill in for
     empty parts of the spectra. It defaluts to half of the minimum
     intensity. 2) 'basespace', the m/z length after which the signal
     will drop to the base level. Linear interpolation will be used
     between consecuitive data points falling within '2*basespace' of
     eachother. It defaluts to 0.075.

     The 'IntLin' functions set each matrix or vector value to the
     integral of the linearly interpolated data from plus to minus half
     the step size.

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

     For 'prof*', a numeric vector of length 'num'.

     For 'prof*M', a matrix with dimensions 'num' by 'length(zidx)'.

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

     Colin A. Smith, csmith@scripps.edu

