Calculates and plots the median of the deviations of the supplied smoothed values from the
supplied observed values for traits and combinations of different smoothing methods and
smoothing degrees of freedom, possibly for subsets of factor
combinations.
The requisite values can be generated using probeSmoothing
with which.plots
set to none
. The results of smoothing methods applied externally to
growthPheno
can be included via the extra.smooths
argument. Envelopes of the
median value of a trait for each factor
combination can be added.
Note: this function is soft deprecated and may be removed in
future versions.
Use plotSmoothsMedianDevns
.
plotMedianDeviations(data, response, response.smoothed,
x = NULL, xname="xDays",
individuals = "Snapshot.ID.Tag",
x.title = NULL, y.titles = NULL,
facet.x = "Treatment.1", facet.y = "Smarthouse",
labeller = NULL,
trait.types = c("response", "AGR", "RGR"),
propn.types = c(0.1, 0.5, 0.75), propn.note = TRUE,
alpha.med.devn = 0.5,
smoothing.methods = "direct", df, extra.smooths = NULL,
ggplotFuncsMedDevn = NULL, printPlot = TRUE, ...)
A list
that consists of two components: (i) a componenent named
plots
that stores a list
of the median deviations plots,
one for each trait.types
; (ii) a component named med.dev.dat
that stores the
data.frame
containing the median deviations that have been plotted.
Each plot in the plots
list
is in an object of class
"ggplot
", which can be plotted using print
.
A data.frame
containing the observed and smoothed values
from which the deviations are to be computed. There should be a column
of smoothed values for each combination of smoothing.methods
,
df
and the types specified by trait.types
. In addition,
there should be a column of values for each element of
extra.smooths
in combination with the elements of
trait.types
. Also, there should be a column of observed values
for each of the types specified by trait.types
. The naming of the
columns for smoothed traits should follow the convention that a name is
made up, in the order sepcified, of (i) a response.smoothed
,
(ii) the trait.type
if not just a response
trait type, a
smoothing.method
or an extra.smooths
and,
(iii) if a smoothing.method
, a df.
Each component should be separated by a period (.).
A character
specifying the response variable for which the
observed values are supplied. Depending on the setting of
trait.types
, the observed values of related trait.types
may also need to be be supplied.
A character
specifying the name of the column
containing the values of the smoothed response variable, corresponding
to response
and obtained for the combinations of
smoothing.methods
and df
, usually using smoothing splines.
If response.smoothed
is NULL
, then
response.smoothed
is set to the response
to which
.smooth
is added.
Depending on the setting of trait.types
, the smoothed
values of related trait.types
may also need to be be supplied.
A character
giving the variable to be plotted on the
x-axis; it may incorporate an expression. If x
is NULL
then
xname
is used.
A character
giving the name of the
numeric
that contains the values from which
x
is derived, it being that x
may incorporate an
expression.
A character
giving the name of the
factor
that defines the subsets of the data
for which each subset corresponds to the response
values for
an individual (e.g. plant, pot, cart, plot or unit).
A character
giving the title for the x-axis.
If NULL
then set to xname
.
A character
giving the titles for the y-axis,
one for each trait specified by trait.types
.
If NULL
then set to the traits derived for response
from trait.types
.
A data.frame
giving the variable to be used to
form subsets to be plotted in separate columns of plots.
Use "."
if a split into columns is not wanted. For
which.plots
set to methodcompare
or dfcompare
facet.x
is ignored.
A data.frame
giving the variable to be used to
form subsets to be plotted in separate rows of plots.
Use "."
if a split into columns is not wanted.
A ggplot
function
for labelling the
facets of a plot produced using the ggplot
function.
For more information see ggplot
.
A character
giving the traits types that are to be
plotted. While AGR
and RGR
are commonly used, the names
can be arbitrary, except that response
is a special case that
indicates that the original response is to be plotted.
A numeric
giving the proportion of the medians
values of each of the trait.types
that are to be plotted
in the median deviations plots. If set to NULL
, the plots of
the proprotions are omitted.
A logical
indicating whether a note giving the
proportion of the median values plotted in the compare.medians
plots.
A numeric
specifying the degrees of
transparency to be used in plotting a median deviations plot.
It is a ratio in which the denominator specifies the number of
points (or lines) that must be overplotted to give a solid cover.
A character
giving the smoothing method used in
producing the response.smoothed
and which is to be used in labelling
the plot.
A numeric
specifying the smoothing degrees of freedom used in
producing the response.smoothed
and which is to be used in labelling
the plot.
A character
specifying one or more
smoothing.method
labels that have been used in naming of columns of
smooths of the response
obtained by methods other than the smoothing
spline methods provided by growthPheno
. Depending on the setting of
trait.types
, the smoothed values of related trait types must also be
supplied, with names constructed according to the convention described under
data
.
A list
, each element of which contains the
results of evaluating a ggplot
function.
It is created by calling the list
function with
a ggplot
function call for each element.
These functions are applied in creating the ggplot
object.
A logical
indicating whether or not to print any
plots.
allows passing of arguments to plotLongitudinal
.
Chris Brien
plotDeviationsBoxes
, probeSmoothing
, ggplot
.
data(exampleData)
vline <- list(ggplot2::geom_vline(xintercept=29, linetype="longdash", size=1),
ggplot2::scale_x_continuous(breaks=seq(28, 42, by=2)))
traits <- probeSmoothing(data = longi.dat, xname = "xDAP", times.factor = "DAP",
response = "PSA", response.smoothed = "sPSA",
df = c(4:7),
facet.x = ".", facet.y = ".",
which.plots = "none",
propn.types = NULL)
med <- plotMedianDeviations(data = traits,
response = "PSA", response.smoothed = "sPSA",
x="xDAP", xname = "xDAP",
df = c(4,7), x.title = "DAP",
facet.x = ".", facet.y = ".",
trait.types = "response", propn.types = 0.05,
ggplotFuncsMedDevn = vline)
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