gpoints-methods           package:flowViz           R Documentation

_A_d_d_i_n_g _p_o_i_n_t_s _w_i_t_h_i_n _a _g_a_t_e _t_o _a _p_l_o_t

_D_e_s_c_r_i_p_t_i_o_n:

     These methods extend the basic graphics 'points' methods for
     drawing of points contained within a 'filter'. They allow for
     multiple dispatch, since not all 'filter' types need to be
     evaluated for plotting, but this decision should be made
     internally. In any case, we need the raw data in the form of a
     'flowFrame'.

_D_e_t_a_i_l_s:

     When plotting code{flowFrame}s using the 'plot' method provided by
     'flowViz', the plotted parameters are recorded, which makes it
     possible to correctly overlay the points within 'filter's assuming
     that they are defined for the repective parameters. Warnings and
     error will be cast for the cases where the parameters are
     non-distinct or ambigious.

_M_e_t_h_o_d_s:



     _x = "_f_i_l_t_e_r", _d_a_t_a = "_f_l_o_w_F_r_a_m_e", _c_h_a_n_n_e_l_s = "_m_i_s_s_i_n_g" General
          method for all objects inheriting from 'filter'. This is used
          as the default when no more explicit method is found. It
          tries to find the plotted parameters from the internal
          'flowViz.state' environment. This only works if the flow data
          has been plotted using the 'plot' methods provided by this
          'flowViz' package. 

     _x = "_f_i_l_t_e_r", _d_a_t_a = "_m_i_s_s_i_n_g", _c_h_a_n_n_e_l_s = "_A_N_Y" This gives a
          useful error message when we don't get what we need. 

     _x = "_f_i_l_t_e_r_R_e_s_u_l_t", _d_a_t_a = "_f_l_o_w_F_r_a_m_e", _c_h_a_n_n_e_l_s = "_c_h_a_r_a_c_t_e_r" We
          can get all the information about a 'filter' from its
          'filterResult' without the need to re-evaluate.

     _x = "_c_u_r_v_1_F_i_l_t_e_r", _d_a_t_a = "_A_N_Y" We either need a 'filterResult' or
          the raw data as a 'flowFrame' for 'curv1Filter's. 

     _x = "_c_u_r_v_1_F_i_l_t_e_r", _d_a_t_a = "_f_l_o_w_F_r_a_m_e" see above 

     _x = "_c_u_r_v_1_F_i_l_t_e_r", _d_a_t_a = "_m_i_s_s_i_n_g" see above 

     _x = "_c_u_r_v_1_F_i_l_t_e_r", _d_a_t_a = "_m_u_l_t_i_p_l_e_F_i_l_t_e_r_R_e_s_u_l_t" see above 

     _x = "_c_u_r_v_2_F_i_l_t_e_r", _d_a_t_a = "_A_N_Y" We either need a 'filterResult' or
          the raw data as a 'flowFrame' for 'curv2Filter's.

     _x = "_c_u_r_v_1_F_i_l_t_e_r", _d_a_t_a = "_f_l_o_w_F_r_a_m_e", _c_h_a_n_n_e_l_s = "_c_h_a_r_a_c_t_e_r" We
          evaluate the 'filter' on the 'flowFrame' and plot the subset
          of selected points. By default, every subpopulation (if there
          are any) is colored differently.

     _x = "_c_u_r_v_2_F_i_l_t_e_r", _d_a_t_a = "_f_l_o_w_F_r_a_m_e", _c_h_a_n_n_e_l_s = "_c_h_a_r_a_c_t_e_r" see
          above 

     _x = "_k_m_e_a_n_s_F_i_l_t_e_r", _d_a_t_a = "_f_l_o_w_F_r_a_m_e", _c_h_a_n_n_e_l_s = "_c_h_a_r_a_c_t_e_r" see
          above 

     _x = "_n_o_r_m_2_F_i_l_t_e_r", _d_a_t_a = "_f_l_o_w_F_r_a_m_e", _c_h_a_n_n_e_l_s = "_c_h_a_r_a_c_t_e_r" see
          above 

     _x = "_p_o_l_y_g_o_n_G_a_t_e", _d_a_t_a = "_f_l_o_w_F_r_a_m_e", _c_h_a_n_n_e_l_s = "_c_h_a_r_a_c_t_e_r" see
          above 

     _x = "_q_u_a_d_G_a_t_e", _d_a_t_a = "_f_l_o_w_F_r_a_m_e", _c_h_a_n_n_e_l_s = "_c_h_a_r_a_c_t_e_r" see
          above 

     _x = "_r_e_c_t_a_n_g_l_e_G_a_t_e", _d_a_t_a = "_f_l_o_w_F_r_a_m_e", _c_h_a_n_n_e_l_s = "_c_h_a_r_a_c_t_e_r" 
          see above 


_A_u_t_h_o_r(_s):

     F. Hahne

_S_e_e _A_l_s_o:

     'filter', 'flowFrame', 'glines', 'gpolygon'

