new plot function with pipes

[jazznbass]

Our plot function is becoming more and more bloated. I have redesigned a new approach which embraces a pipe structure and more straight forward functional programming (similar to ggplot). While keeping the previous plot function intact, i like to add it to v0.54 and gradually shift it to be the main approach. Here is an example of what it looks like:

scplot(exampleABAB) %>% 
  add_line("trendA", col = "red") %>%
  add_line("maxA", col = "lightblue") %>%
  add_marks(outlier(exampleABAB), col = "brown", cex = 2) %>%
  set_xaxis(increase = 4, label = "Weeks") %>%
  set_yaxis(lim = c(0, 50), label = "Points") %>%
  add_title("Points as a function of weeks") %>%
  set_case_names("MY", "FUNNY", "VALENTINE") %>%
  set_phase_names("Baseline", "Intervention", "Fall-Back", "Intervention") %>%
  add_style("grid2") %>%
  add_style("tiny") %>%
  add_style(fill.bg = "grey96")

beside the clear coding here are some more advantages:

• putting the steps (drawing marks, lines, adding styles) into separate functions helps to implement future features much more easily
• For the user, documentation is easier to find because each step can get its own help page
• The return value is an object (class scdf_plot). The plot itself is generated, when the object is printed. This makes it easier to implement export functions for pdf, png etc.

Here is what the code for the above plot would look like with the current function:

plot(exampleABAB, 
     style = list(style = c("grid2", "tiny"), fill.bg = "grey96"),
     lines = list(list("trendA", col = "red"), list("maxA", col = "lightblue")),
     marks = list(positions = outlier(exampleABAB)$dropped.mt, col = "brown", cex = 2),
     xinc = 4, xlab = "Weeks",
     ylim = c(0,50), ylab = "Points",
     main = "Points as a function of weeks",
     case.names = c("MY", "FUNNY", "VALENTINE"),
     phase.names = c("Baseline", "Intervention", "Fall-Back", "Intervention") 
)

@researchtool What do you think?

[researchtool]

Oh I love that! I have a few ideas for plot.scdf() too. That would harmonize with the new approach.

[jazznbass]

I've been adding some more functions and extended the customisability. Here is a current example (a bit extensive to show the possibilities). Any suggestions are welcome :-)

scplot(exampleABAB) %>% 
  add_line("trendA", col = "red") %>%
  add_line("maxA", col = "lightblue") %>%
  add_marks(case = 1, positions = 14, col = "red", cex = 3, pch = 4) %>%
  add_marks(case = 2, positions = c(17, 20), col = "red", cex = 3, pch = 4) %>%
  add_marks(positions = outlier(exampleABAB), col = "brown", cex = 2) %>%
  set_xaxis(increase = 4, label = "Weeks", cex = 0.7, col = "brown") %>%
  set_yaxis(lim = c(0, 50), label = "Points", col = "sienna3", cex = 1, orientation = 0) %>%
  add_title("Points by week", col = "salmon3", cex = 1.5, font = 3) %>%
  set_phasenames("Baseline", "Intervention", "Fall-Back", "Intervention",  cex = 1, col = "darkgreen") %>%
  set_style("grid2") %>%
  set_style("tiny") %>%
  set_style(fill.bg = "grey96") %>%
  add_text(case = 1, 5, 35, "Wow!!", col = "red") %>%
  add_arrow(case = 1, 5, 30, 5, 22, col = "blue") %>%
  set_casenames("MY", "FUNNY", "VALENTINE", col = "darkblue", cex = 0.6)

[jazznbass]

Meanwhile I started a new package scplot which is intended to be included into scan in a later Version. scplot generated ggplot2 output and thus is extremely versatile