R: Plot CMA_per_episode and CMA_sliding

plot.CMA_per_episode {AdhereR}

R Documentation

Plot CMA_per_episode and CMA_sliding_window objects.

Description

Plots the event data and the estimated CMA per treatment episode and sliding window, respectively.

Usage

## S3 method for class 'CMA_per_episode'
plot(
  x,
  patients.to.plot = NULL,
  duration = NA,
  align.all.patients = FALSE,
  align.first.event.at.zero = FALSE,
  show.period = c("dates", "days")[2],
  period.in.days = 90,
  show.legend = TRUE,
  legend.x = "right",
  legend.y = "bottom",
  legend.bkg.opacity = 0.5,
  legend.cex = 0.75,
  legend.cex.title = 1,
  cex = 1,
  cex.axis = 0.75,
  cex.lab = 1,
  show.cma = TRUE,
  xlab = c(dates = "Date", days = "Days"),
  ylab = c(withoutCMA = "patient", withCMA = "patient (& CMA)"),
  title = c(aligned = "Event patterns (all patients aligned)", notaligned =
    "Event patterns"),
  col.cats = rainbow,
  unspecified.category.label = "drug",
  medication.groups.to.plot = NULL,
  medication.groups.separator.show = TRUE,
  medication.groups.separator.lty = "solid",
  medication.groups.separator.lwd = 2,
  medication.groups.separator.color = "blue",
  medication.groups.allother.label = "*",
  lty.event = "solid",
  lwd.event = 2,
  pch.start.event = 15,
  pch.end.event = 16,
  show.event.intervals = FALSE,
  show.overlapping.event.intervals = c("first", "last", "min gap", "max gap",
    "average")[1],
  plot.events.vertically.displaced = TRUE,
  print.dose = FALSE,
  cex.dose = 0.75,
  print.dose.outline.col = "white",
  print.dose.centered = FALSE,
  plot.dose = FALSE,
  lwd.event.max.dose = 8,
  plot.dose.lwd.across.medication.classes = FALSE,
  col.na = "lightgray",
  col.continuation = "black",
  lty.continuation = "dotted",
  lwd.continuation = 1,
  print.CMA = TRUE,
  CMA.cex = 0.5,
  plot.CMA = TRUE,
  plot.CMA.as.histogram = TRUE,
  plot.partial.CMAs.as = c("stacked", "overlapping", "timeseries")[1],
  plot.partial.CMAs.as.stacked.col.bars = "gray90",
  plot.partial.CMAs.as.stacked.col.border = "gray30",
  plot.partial.CMAs.as.stacked.col.text = "black",
  plot.partial.CMAs.as.timeseries.vspace = 7,
  plot.partial.CMAs.as.timeseries.start.from.zero = TRUE,
  plot.partial.CMAs.as.timeseries.col.dot = "darkblue",
  plot.partial.CMAs.as.timeseries.col.interval = "gray70",
  plot.partial.CMAs.as.timeseries.col.text = "firebrick",
  plot.partial.CMAs.as.timeseries.interval.type = c("none", "segments", "arrows",
    "lines", "rectangles")[2],
  plot.partial.CMAs.as.timeseries.lwd.interval = 1,
  plot.partial.CMAs.as.timeseries.alpha.interval = 0.25,
  plot.partial.CMAs.as.timeseries.show.0perc = TRUE,
  plot.partial.CMAs.as.timeseries.show.100perc = FALSE,
  plot.partial.CMAs.as.overlapping.alternate = TRUE,
  plot.partial.CMAs.as.overlapping.col.interval = "gray70",
  plot.partial.CMAs.as.overlapping.col.text = "firebrick",
  CMA.plot.ratio = 0.1,
  CMA.plot.col = "lightgreen",
  CMA.plot.border = "darkgreen",
  CMA.plot.bkg = "aquamarine",
  CMA.plot.text = CMA.plot.border,
  highlight.followup.window = TRUE,
  followup.window.col = "green",
  highlight.observation.window = TRUE,
  observation.window.col = "yellow",
  observation.window.opacity = 0.3,
  print.episode.or.sliding.window = FALSE,
  alternating.bands.cols = c("white", "gray95"),
  bw.plot = FALSE,
  rotate.text = -60,
  force.draw.text = FALSE,
  min.plot.size.in.characters.horiz = 0,
  min.plot.size.in.characters.vert = 0,
  max.patients.to.plot = 100,
  export.formats = NULL,
  export.formats.fileprefix = "AdhereR-plot",
  export.formats.height = NA,
  export.formats.width = NA,
  export.formats.save.svg.placeholder = TRUE,
  export.formats.svg.placeholder.type = c("jpg", "png", "webp")[2],
  export.formats.svg.placeholder.embed = FALSE,
  export.formats.html.template = NULL,
  export.formats.html.javascript = NULL,
  export.formats.html.css = NULL,
  export.formats.directory = NA,
  generate.R.plot = TRUE,
  do.not.draw.plot = FALSE,
  suppress.warnings = FALSE,
  ...
)

## S3 method for class 'CMA_sliding_window'
plot(
  x,
  patients.to.plot = NULL,
  duration = NA,
  align.all.patients = FALSE,
  align.first.event.at.zero = FALSE,
  show.period = c("dates", "days")[2],
  period.in.days = 90,
  show.legend = TRUE,
  legend.x = "right",
  legend.y = "bottom",
  legend.bkg.opacity = 0.5,
  legend.cex = 0.75,
  legend.cex.title = 1,
  cex = 1,
  cex.axis = 0.75,
  cex.lab = 1,
  show.cma = TRUE,
  xlab = c(dates = "Date", days = "Days"),
  ylab = c(withoutCMA = "patient", withCMA = "patient (& CMA)"),
  title = c(aligned = "Event patterns (all patients aligned)", notaligned =
    "Event patterns"),
  col.cats = rainbow,
  unspecified.category.label = "drug",
  medication.groups.to.plot = NULL,
  medication.groups.separator.show = TRUE,
  medication.groups.separator.lty = "solid",
  medication.groups.separator.lwd = 2,
  medication.groups.separator.color = "blue",
  medication.groups.allother.label = "*",
  lty.event = "solid",
  lwd.event = 2,
  pch.start.event = 15,
  pch.end.event = 16,
  show.event.intervals = FALSE,
  show.overlapping.event.intervals = c("first", "last", "min gap", "max gap",
    "average")[1],
  plot.events.vertically.displaced = TRUE,
  print.dose = FALSE,
  cex.dose = 0.75,
  print.dose.outline.col = "white",
  print.dose.centered = FALSE,
  plot.dose = FALSE,
  lwd.event.max.dose = 8,
  plot.dose.lwd.across.medication.classes = FALSE,
  col.na = "lightgray",
  col.continuation = "black",
  lty.continuation = "dotted",
  lwd.continuation = 1,
  print.CMA = TRUE,
  CMA.cex = 0.5,
  plot.CMA = TRUE,
  plot.CMA.as.histogram = TRUE,
  plot.partial.CMAs.as = c("stacked", "overlapping", "timeseries")[1],
  plot.partial.CMAs.as.stacked.col.bars = "gray90",
  plot.partial.CMAs.as.stacked.col.border = "gray30",
  plot.partial.CMAs.as.stacked.col.text = "black",
  plot.partial.CMAs.as.timeseries.vspace = 7,
  plot.partial.CMAs.as.timeseries.start.from.zero = TRUE,
  plot.partial.CMAs.as.timeseries.col.dot = "darkblue",
  plot.partial.CMAs.as.timeseries.col.interval = "gray70",
  plot.partial.CMAs.as.timeseries.col.text = "firebrick",
  plot.partial.CMAs.as.timeseries.interval.type = c("none", "segments", "arrows",
    "lines", "rectangles")[2],
  plot.partial.CMAs.as.timeseries.lwd.interval = 1,
  plot.partial.CMAs.as.timeseries.alpha.interval = 0.25,
  plot.partial.CMAs.as.timeseries.show.0perc = TRUE,
  plot.partial.CMAs.as.timeseries.show.100perc = FALSE,
  plot.partial.CMAs.as.overlapping.alternate = TRUE,
  plot.partial.CMAs.as.overlapping.col.interval = "gray70",
  plot.partial.CMAs.as.overlapping.col.text = "firebrick",
  CMA.plot.ratio = 0.1,
  CMA.plot.col = "lightgreen",
  CMA.plot.border = "darkgreen",
  CMA.plot.bkg = "aquamarine",
  CMA.plot.text = CMA.plot.border,
  highlight.followup.window = TRUE,
  followup.window.col = "green",
  highlight.observation.window = TRUE,
  observation.window.col = "yellow",
  observation.window.opacity = 0.3,
  print.episode.or.sliding.window = FALSE,
  alternating.bands.cols = c("white", "gray95"),
  bw.plot = FALSE,
  rotate.text = -60,
  force.draw.text = FALSE,
  min.plot.size.in.characters.horiz = 0,
  min.plot.size.in.characters.vert = 0,
  max.patients.to.plot = 100,
  export.formats = NULL,
  export.formats.fileprefix = "AdhereR-plot",
  export.formats.height = NA,
  export.formats.width = NA,
  export.formats.save.svg.placeholder = TRUE,
  export.formats.svg.placeholder.type = c("jpg", "png", "webp")[2],
  export.formats.svg.placeholder.embed = FALSE,
  export.formats.html.template = NULL,
  export.formats.html.javascript = NULL,
  export.formats.html.css = NULL,
  export.formats.directory = NA,
  generate.R.plot = TRUE,
  do.not.draw.plot = FALSE,
  suppress.warnings = FALSE,
  ...
)

Arguments

`x`	A `CMA0` or derived object, representing the CMA to plot
`patients.to.plot`	A vector of strings containing the list of patient IDs to plot (a subset of those in the `cma` object), or `NULL` for all
`duration`	A number, the total duration (in days) of the whole period to plot; in `NA` it is automatically determined from the event data such that the whole dataset fits.
`align.all.patients`	Logical, should all patients be aligned (i.e., the actual dates are discarded and all plots are relative to the earliest date)?
`align.first.event.at.zero`	Logical, should the first event be placed at the origin of the time axis (at 0)?
`show.period`	A string, if "dates" show the actual dates at the regular grid intervals, while for "days" (the default) shows the days since the beginning; if `align.all.patients == TRUE`, `show.period` is taken as "days".
`period.in.days`	The number of days at which the regular grid is drawn (or 0 for no grid).
`show.legend`	Logical, should the legend be drawn?
`legend.x`	The position of the legend on the x axis; can be "left", "right" (default), or a numeric value.
`legend.y`	The position of the legend on the y axis; can be "bottom" (default), "top", or a numeric value.
`legend.bkg.opacity`	A number between 0.0 and 1.0 specifying the opacity of the legend background.
`legend.cex`, `legend.cex.title`	The legend and legend title font sizes.
`cex`, `cex.axis`, `cex.lab`	numeric values specifying the cex of the various types of text.
`show.cma`	Logical, should the CMA type be shown in the title?
`xlab`	Named vector of x-axis labels to show for the two types of periods ("days" and "dates"), or a single value for both, or `NULL` for nothing.
`ylab`	Named vector of y-axis labels to show without and with CMA estimates, or a single value for both, or `NULL` for nonthing.
`title`	Named vector of titles to show for and without alignment, or a single value for both, or `NULL` for nonthing.
`col.cats`	A color or a function that specifies the single colour or the colour palette used to plot the different medication; by default `rainbow`, but we recommend, whenever possible, a colorblind-friendly palette such as `viridis` or `colorblind_pal`.
`unspecified.category.label`	A string giving the name of the unspecified (generic) medication category.
`medication.groups.to.plot`	the names of the medication groups to plot or `NULL` (the default) for all.
`medication.groups.separator.show`	a boolean, if `TRUE` (the default) visually mark the medication groups the belong to the same patient, using horizontal lines and alternating vertical lines.
`medication.groups.separator.lty`, `medication.groups.separator.lwd`, `medication.groups.separator.color`	graphical parameters (line type, line width and colour describing the visual marking og medication groups as beloning to the same patient.
`medication.groups.allother.label`	a string giving the label to use for the implicit `__ALL_OTHERS__` medication group (defaults to "*").
`lty.event`, `lwd.event`, `pch.start.event`, `pch.end.event`	The style of the event (line style, width, and start and end symbols).
`show.event.intervals`	Logical, should the actual event intervals be shown? As per-episode and sliding windows might have overlapping intervals, it is better not to show them by default (`FALSE`).
`show.overlapping.event.intervals`	specifies how to plot the event intervals that appear in multiple sliding windows or episodes. We can plot how thye look in the first sliding window or episode (the default), how they appear in the last, pick the one that minimizes the gap (min gap) or maximizes it (max gap), or compute their average across all sliding windows or episodes containing them.
`plot.events.vertically.displaced`	Should consecutive events be plotted on separate rows (i.e., separated vertically, the default) or on the same row?
`print.dose`, `cex.dose`, `print.dose.outline.col`, `print.dose.centered`	Print daily dose as a number and, if so, how (color, size, position...).
`plot.dose`, `lwd.event.max.dose`, `plot.dose.lwd.across.medication.classes`	Show dose through the width of the event lines and, if so, what the maximum width should be, and should this maximum be by medication class or overall.
`col.na`	The colour used for missing event data.
`col.continuation`, `lty.continuation`, `lwd.continuation`	The color, style and width of the contuniation lines connecting consecutive events.
`print.CMA`	Logical, should the CMA values be printed?
`CMA.cex`	... and, if printed, what cex (numeric) to use?
`plot.CMA`	Logical, should the distribution of the CMA values across episodes/sliding windows be plotted? If `TRUE` (the default), the distribution is shown on the left-hand side of the plot, otherwise it is not.
`plot.CMA.as.histogram`	Logical, should the CMA plot be a histogram or a (truncated) density plot? Please note that it is TRUE by deafult for CMA_per_episode and FALSE for CMA_sliding_window, because usually there are more sliding windows than episodes. Also, the density estimate cannot be estimated for less than three different values.
`plot.partial.CMAs.as`	Should the partial CMAs be plotted? Possible values are "stacked", "overlapping" or "timeseries", or `NULL` for no partial CMA plots. Please note that `plot.CMA` and `plot.partial.CMAs.as` are independent of each other.
`plot.partial.CMAs.as.stacked.col.bars`, `plot.partial.CMAs.as.stacked.col.border`, `plot.partial.CMAs.as.stacked.col.text`	If plotting the partial CMAs as stacked bars, define their graphical attributes.
`plot.partial.CMAs.as.timeseries.vspace`, `plot.partial.CMAs.as.timeseries.start.from.zero`, `plot.partial.CMAs.as.timeseries.col.dot`, `plot.partial.CMAs.as.timeseries.col.interval`, `plot.partial.CMAs.as.timeseries.col.text`, `plot.partial.CMAs.as.timeseries.interval.type`, `plot.partial.CMAs.as.timeseries.lwd.interval`, `plot.partial.CMAs.as.timeseries.alpha.interval`, `plot.partial.CMAs.as.timeseries.show.0perc`, `plot.partial.CMAs.as.timeseries.show.100perc`	If plotting the partial CMAs as imeseries, these are their graphical attributes.
`plot.partial.CMAs.as.overlapping.alternate`, `plot.partial.CMAs.as.overlapping.col.interval`, `plot.partial.CMAs.as.overlapping.col.text`	If plotting the partial CMAs as overlapping segments, these are their graphical attributes.
`CMA.plot.ratio`	A number, the proportion of the total horizontal plot space to be allocated to the CMA plot.
`CMA.plot.col`, `CMA.plot.border`, `CMA.plot.bkg`, `CMA.plot.text`	Strings giving the colours of the various components of the CMA plot.
`highlight.followup.window`	Logical, should the follow-up window be plotted?
`followup.window.col`	The follow-up window colour.
`highlight.observation.window`	Logical, should the observation window be plotted?
`observation.window.col`, `observation.window.opacity`	Attributes of the observation window (colour, transparency).
`print.episode.or.sliding.window`	Logical, should we show which events belong to which episode or sliding window? To work, the CMA must have been constructed with `return.mapping.events.episodes` or `return.mapping.events.sliding.window` set to `TRUE`, respectively.
`alternating.bands.cols`	The colors of the alternating vertical bands distinguishing the patients; can be `NULL` = don't draw the bandes; or a vector of colors.
`bw.plot`	Logical, should the plot use grayscale only (i.e., the `gray.colors` function)?
`rotate.text`	Numeric, the angle by which certain text elements (e.g., axis labels) should be rotated.
`force.draw.text`	Logical, if `TRUE`, always draw text even if too big or too small
`min.plot.size.in.characters.horiz`, `min.plot.size.in.characters.vert`	Numeric, the minimum size of the plotting surface in characters; horizontally (min.plot.size.in.characters.horiz) refers to the the whole duration of the events to plot; vertically (min.plot.size.in.characters.vert) refers to a single event. If the plotting is too small, possible solutions might be: if within `RStudio`, try to enlarge the "Plots" panel, or (also valid outside `RStudio` but not if using `RStudio server` start a new plotting device (e.g., using `X11()`, `quartz()` or `windows()`, depending on OS) or (works always) save to an image (e.g., `jpeg(...); ...; dev.off()`) and display it in a viewer.
`max.patients.to.plot`	Numeric, the maximum patients to attempt to plot.
`export.formats`	a string giving the formats to export the figure to (by default `NULL`, meaning no exporting); can be any combination of "svg" (just an `SVG` file), "html" (`SVG` + `HTML` + `CSS` + `JavaScript`, all embedded within one `HTML` document), "jpg", "png", "webp", "ps" or "pdf".
`export.formats.fileprefix`	a string giving the file name prefix for the exported formats (defaults to "AdhereR-plot").
`export.formats.height`, `export.formats.width`	numbers giving the desired dimensions (in pixels) for the exported figure (defaults to sane values if `NA`).
`export.formats.save.svg.placeholder`	a logical, if TRUE, save an image placeholder of type given by `export.formats.svg.placeholder.type` for the `SVG` image.
`export.formats.svg.placeholder.type`	a string, giving the type of placeholder for the `SVG` image to save; can be "jpg", "png" (the default) or "webp".
`export.formats.svg.placeholder.embed`	a logical, if `TRUE`, embed the placeholder image in the HTML document (if any) using `base64` encoding, otherwise (the default) leave it as an external image file (works only when an `HTML` document is exported and only for `JPEG` or `PNG` images.
`export.formats.html.template`, `export.formats.html.javascript`, `export.formats.html.css`	character strings or `NULL` (the default) giving the path to the `HTML`, `JavaScript` and `CSS` templates, respectively, to be used when generating the HTML+CSS semi-interactive plots; when `NULL`, the default ones included with the package will be used. If you decide to define new templates please use the default ones for inspiration and note that future version are not guaranteed to be backwards compatible!
`export.formats.directory`	a string; if exporting, which directory to export to; if `NA` (the default), creates the files in a temporary directory.
`generate.R.plot`	a logical, if `TRUE` (the default), generate the standard (base `R`) plot for plotting within `R`.
`do.not.draw.plot`	a logical, if `TRUE` (not the default), does not draw the plot itself, but only the legend (if `show.legend` is `TRUE`) at coordinates (0,0) irrespective of the given legend coordinates. This is intended to allow (together with the `get.legend.plotting.area()` function) the separate plotting of the legend.
`suppress.warnings`	Logical, if `TRUE` don't show any warnings.
`...`	other parameters (to be passed to the estimation and plotting of the simple CMA)

Details

The x-axis represents time (either in days since the earliest date or as actual dates), with consecutive events represented as ascending on the y-axis.

Each event is represented as a segment with style lty.event and line width lwd.event starting with a pch.start.event and ending with a pch.end.event character, coloured with a unique color as given by col.cats, extending from its start date until its end date. Consecutive events are thus represented on consecutive levels of the y-axis and are connected by a "continuation" line with col.continuation colour, lty.continuation style and lwd.continuation width; these continuation lines are purely visual guides helping to perceive the sequence of events, and carry no information about the avilability of medicine in this interval.

Above these, the treatment episodes or the sliding windows are represented in a stacked manner from the earlieast (left, bottom of the stack) to the latest (right, top of the stack), each showing the CMA as percent fill (capped at 100% even if CMA values may be higher) and also as text.

The follow-up and the observation windows are plotted as empty an rectangle and as shaded rectangle, respectively (for some CMAs the observation window might be adjusted in which case the adjustment may also be plotted using a different shading).

The kernel density ("smoothed histogram") of the CMA estimates across treatment episodes/sliding windows (if more than 2) can be visually represented as well in the left side of the figure (NB, their horizontal scales may be different across patients).

When several patients are displayed on the same plot, they are organized vertically, and alternating bands (white and gray) help distinguish consecutive patients. Implicitely, all patients contained in the cma object will be plotted, but the patients.to.plot parameter allows the selection of a subset of patients.

Finally, the y-axis shows the patient ID and possibly the CMA estimate as well.

Any not explicitely defined arguments are passed to the simple CMA estimation and plotting function; therefore, for more info about possible estimation parameters plese see the help for the appropriate simple CMA, and for possible aesthetic tweaks, please see the help for their plotting.

Examples

## Not run: 
cmaW <- CMA_sliding_window(CMA=CMA1,
                        data=med.events,
                        ID.colname="PATIENT_ID",
                        event.date.colname="DATE",
                        event.duration.colname="DURATION",
                        event.daily.dose.colname="PERDAY",
                        medication.class.colname="CATEGORY",
                        carry.only.for.same.medication=FALSE,
                        consider.dosage.change=FALSE,
                        followup.window.start=0,
                        observation.window.start=0,
                        observation.window.duration=365,
                        sliding.window.start=0,
                        sliding.window.start.unit="days",
                        sliding.window.duration=90,
                        sliding.window.duration.unit="days",
                        sliding.window.step.duration=7,
                        sliding.window.step.unit="days",
                        sliding.window.no.steps=NA,
                        date.format="%m/%d/%Y"
                       );
plot(cmaW, patients.to.plot=c("1","2"));
cmaE <- CMA_per_episode(CMA=CMA1,
                        data=med.events,
                        ID.colname="PATIENT_ID",
                        event.date.colname="DATE",
                        event.duration.colname="DURATION",
                        event.daily.dose.colname="PERDAY",
                        medication.class.colname="CATEGORY",
                        carry.only.for.same.medication=FALSE,
                        consider.dosage.change=FALSE,
                        followup.window.start=0,
                        observation.window.start=0,
                        observation.window.duration=365,
                        date.format="%m/%d/%Y"
                       );
plot(cmaE, patients.to.plot=c("1","2"));
## End(Not run)