data.frame in long format, computes and compares, for
sets of smoothing parameters, smooths of the response, possibly along with
growth rates calculated from the smooths.Takes an observed response and, for each individual, uses
byIndv4Times_SplinesGRs to smooth its values employing the smoothing
parameters specified by (i) spline.types, (ii) the tuning
parameters, being the degrees of freedom values in df or the
smoothing penalties in lambdas, and (iii) the
smoothing.methods. The values of these, and other, smoothing
arguments are set using the helper function
args4smoothing.
Provided get.rates is TRUE or includes raw and/or
smoothed and depending on the setting
of trait.types, the Absolute Growth Rates (AGR) and/or the
Relative Growth Rates (RGR) are calculated for each individual from the
unsmoothed, observed response and from the smooths of the
response, using either differences or first derivatives, as
specified by rates.method.
Generally, profile plots for the traits (a response, an AGR or an RGR)
specified in traits.types are produced if which.plots is
profiles; if which.plots specifies one or more deviations
plots, then those deviations plots will also be produced, these being
based on the unsmoothed data from which the smoothed data has been
subtracted. The layout of the plots is controlled via combinations of
one or more of the smoothing-parameter factors Type,
TunePar, TuneVal, Tuning (the combination
of TunePar and TuneVal) and Method, as well as
other factors associated with the data.
The factors that are to be used for the profile plots
are supplied via the argument profile.plot.args
using the helper function args4profile_plot and for the
and deviations boxplots using the helper function
args4devnboxes_plot. These helper functions set
plots.by, facet.x, and facet.y. For the plots of
the medians of the deviations, the factors are supplied via
the argument meddevn.plot.args using the helper function
args4meddevn_plot to set plots.by, facet.x,
facet.y and plots.group. Here, the basic principle is that
the number of levels combinations of the smoothing-parameter
factors included in the set of plots and
facets arguments to one of these helper functions must be the same
as those covered by the combinations of the values supplied to
spline.types, df, lambdas and smoothing.methods
and incorporated into the smooths.frame, such as is
returned by probeSmooths. This ensures that smooths
from different parameter sets are not pooled together in a single plot.
It is also possible to include factors that are not
smoothing-parameter factors in the plots amd
facets arguments.
The following profiles plots can be produced using
args4profile_plot: (i) separate plots of the
smoothed traits for each combination of the smoothing parameters
(include Type, Tuning and Method in plots.by);
(ii) as for (i), with the corresponding plot for the unsmoothed trait
preceeding the plots for the smoothed trait (also set include.raw to
alone); (iii) profiles plots that compare a smoothed trait for all
combinations of the values of the smoothing parameters, arranging the plots
side-by-side or one above the other (include Type, Tuning and
Method in facet.x and/or facet.y - to include the
unsmoothed trait set include.raw to one of facet.x or
facet.y; (iv) as for (iii), except that separate plots are
produced for each combination of the levels of the factors
in plot.by and each plot compares the smoothed traits for the
smoothing-parameter factors included in facet.x
and/or facet.y (set both plots.by and one or more of
facet.x and facet.y).
Deviation plots that can be produced are the absolute and relative deviations
boxplots and plots of medians deviations (see which.plots).
The handling of missing values is controlled via na.x.action and
na.y.action supplied to the helper function args4smoothing.
The probeSmooths arguments are grouped according to function in the following order:
Data description arguments: data, response, response.smoothed, individuals, times, keep.columns, trait.types, get.rates, rates.method, ntimes2span.
Smoothing arguments: smoothing.args (see args4smoothing).
General plot control: x.title, y.titles, facet.labeller, which.plots.
Profile plots (pf) features: profile.plot.args (see args4profile_plot)
Median-deviations (med) plots features: meddevn.plot.args (see args4meddevn_plot)
Deviations boxplots (box) features: devnboxes.plot.args (see args4devnboxes_plot)
probeSmooths(data, response = "PSA", response.smoothed = NULL,
individuals="Snapshot.ID.Tag", times = "DAP",
keep.columns = NULL,
get.rates = TRUE,
rates.method="differences", ntimes2span = NULL,
trait.types = c("response", "AGR", "RGR"),
smoothing.args =
args4smoothing(smoothing.methods = "direct",
spline.types = "NCSS",
df = NULL, lambdas = NULL),
x.title = NULL, y.titles = NULL,
which.plots = "profiles",
profile.plot.args =
args4profile_plot(plots.by = NULL,
facet.x = ".", facet.y = ".",
include.raw = "no"),
meddevn.plot.args =
args4meddevn_plot(plots.by = NULL, plots.group = NULL,
facet.x = ".", facet.y = ".",
propn.note = TRUE,
propn.types = c(0.1, 0.5, 0.75)),
devnboxes.plot.args =
args4devnboxes_plot(plots.by = NULL,
facet.x = ".", facet.y = ".",
which.plots = "none"),
...)A smooths.frame that contains the unsmoothed and smoothed data
in long format. That is, all the values for either an unsmoothed or a
smoothed trait are in a single column. The smooths for a trait for the
different combinatons of the smoothing parameters are placed in rows one
below the other. The columns that are included in the smooths.frame
are Type, TunePar, TuneVal, Tuning and Method,
as well as those specified by individuals, times, response, and
response.smoothed. and any included in the keep.columns, plots
and facet arguments.
If trait.types includes AGR or RGR, then the included growth
rate(s) of the response and response.smoothed must be present, unless
get.rates is TRUE or includes raw and/or smoothed. In this case,
the growth rates specified by trait.types will be calculated for the responses
nominated by get.rates and the differences between the times
used in calculating the rates will be computed and added. Then, the names of the
growth rates are formed from response and response.smoothed by
appending .AGR and .RGR as appropriate; the name of the column with
the times differences will be formed by appending .diffs to the
value of times. The external.smooths will also be included.
A smooths.frame has the attributes described in
smooths.frame.
Columns in the supplied data.frame that have not been used in
probeSmooths will not be included in the returned smooths.frame.
If they might be needed subsequently, such as when extra plots are produced, they
can be included in the smooths.frame by listing them in a
character vector for the keep.columns argument.
The smooths.frame is returned invisibly.
A data.frame containing the data or a smooths.frame
as is produced by probeSmooths. if data is not a
smooths.frame, then smoothing will be performed. If data
is a smooths.frame, then the plotting and selection of smooths
will be performed as specified by smoothing.args and which.plots.
A character specifying the response variable to be
supplied to smoothSpline and that is to be plotted
on the y-axis.
A character specifying the name of the column
containing the values of the smoothed response variable, corresponding
to response. If response.smoothed is NULL, then
response.smoothed is set to the response to which is added
the prefix s.
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 name of the column in
data containing the times at which the data was
collected, either as a numeric, factor, or
character. It will be used as the values of the predictor
variable to be supplied to smooth.spline and to be plotted
on the x-axis. If a factor or character,
the values should be numerics stored as characters.
A character vector giving the names of columns
from data that are to be included in the
smooths.frame that will be returned. Its main use is
when no plots are being produced by probeSmooths, but there
are columns in the supplied data.frame that are likely
to be needed for the plots and facets arguments when
producing plots subsequently.
A logical or a character specifying
which of the response and the response.smoothed are to
have growth rates (AGR and/or RGR) computed and stored. If set to
TRUE or c("raw", "smoothed"), growth rates will be
obtained for both. Setting to only one of raw or
smoothed, results in the growth rates for either the
response or the response.smoothed being computed.
If set to none or FALSE, no growth rates ar computed.
Which growth.rates are computed can be changed using the arguments
traits.types and the method used for computing them for the
response.smooth by rates.method. The growth rates for
the response can only be computed by differencing.
A character specifying the method to use in
calculating the growth rates for response.smoothed. The two
possibilities are "differences" and "derivatives".
A numeric giving the number of values in
times to span in calculating growth rates by differencing.
For ntimes2span set to NULL, if rates.method
is set to differences then ntimes2span is set to 2;
if rates.method is set to derivatives then
ntimes2span is set to 3.
Note that when get.rates is includes raw or is
TRUE, the growth rates for the unsmoothed response must be
calculated by differencing, even if the growth rates for the
smoothed response are computed using derivatives. When
differencing, each growth rate is calculated as the difference in
the values of one of the responses for pairs of times
values that are spanned by ntimes2span times values
divided by the difference between this pair of times values.
For ntimes2span set to 2, a growth rate is the
difference between consecutive pairs of values of one of the
responses divided by the difference between consecutive
pairs of times values.
A character giving the trait.types that
are to be plotted. If growth rates are included in trait.types,
then they will be computed for either the response and/or the
response.smoothed, depending on the setting of get.rates.
Any growth rates included in trait.types for the response
that are available in data, but have not been specified for
computation in get.rates, will be retained in the returned
smooths.frame.
If all, the response.smoothed, its AGR and
RGR, will be plotted. The response, and its AGR
and RGR, will be plotted as the plotting options require it.
A list that is most easily generated
using args4smoothing, it documenting the
options available for smoothing the data. It gives the settings of
smoothing.methods, spline.types, df, lambdas,
smoothing.segments, npspline.segments, na.x.action,
na.y.action, external.smooths, and correctBoundaries,
to be used in smoothing the response or in selecting a subset
of the smooths in data, depending on whether data is a
data.frame or a smooths.frame, respectively.
Set smoothing.args to NULL if data is a
smooths.frame and only plotting or extraction of a chosen
smooth is required.
Title for the x-axis, used for all plots. If NULL then set to
times.
A character giving the titles for the y-axis,
one for each trait specified by trait.types and used for all plots.
If NULL then set to the traits derived for response
from trait.types.
A logical indicating which plots are to be produced.
The options are either none or some combination of profiles,
absolute.boxplots, relative.boxplots and
medians.deviations. The various profiles plots that can be
poduced are described in the introduction to this function.
Boxplots of the absolute deviations are specified by
absolute.boxplots, the absolute deviations being the values of a
trait minus their smoothed values (observed - smoothed). Boxplots of the
relative deviations are specified by relative.boxplots, the
relative deviations being the absolute deviations divided by the smoothed
values of the trait.
The option medians.deviations results
in a plot that compares the medians of the absolute deviations over the
values of times for each combination of the smoothing-parameter values.
The arguments to probeSmooths that apply to medians.deviations
plots have the suffix med.
A named list that is most easily
generated using args4profile_plot, it documenting the
options available for varying profile plots and boxplots. Note
that if args4profile_plot is to be called to change
from the default settings given in the default probeSmooths call
and some of those settings are to be retained, then the arguments
whose settings are to be retained must also be included in the call
to args4profile_plot; be aware that if you call
args4profile_plot, then the defaults for this call are
those for args4profile_plot, NOT the call to
args4profile_plot shown as the default for
probeSmooths.
A named list that is most easily
generated using args4meddevn_plot, it documenting the
options available for varying median deviations plots. Note
that if args4meddevn_plot is to be called to change
from the default settings given in the default probeSmooths call
and some of those settings are to be retained, then the arguments
whose settings are to be retained must also be included in the call
to args4meddevn_plot; be aware that if you call
args4meddevn_plot, then the defaults for this call are
those for args4meddevn_plot, NOT the call to
args4meddevn_plot shown as the default for
probeSmooths.
A named list that is most easily
generated using args4devnboxes_plot, it documenting the
options available for varying the boxplots. Note
that if args4devnboxes_plot is to be called to change
from the default settings given in the default probeSmooths
call and some of those settings are to be retained, then the arguments
whose settings are to be retained must also be included in the call
to args4devnboxes_plot; be aware that if you call
args4devnboxes_plot, then the defaults for this call
are those for args4devnboxes_plot, NOT the call
to args4devnboxes_plot shown as the default for
probeSmooths.
allows passing of arguments to plotProfiles.
Chris Brien
args4smoothing, , args4meddevn_plot, args4profile_plot,
traitSmooth,
smoothSpline, byIndv4Times_SplinesGRs, byIndv4Times_GRsDiff,
smooth.spline, psNormal, plotSmoothsComparison,
plotSmoothsMedianDevns, ggplot.
data(exampleData)
longi.dat <- longi.dat[1:140,] #reduce to a smaller data set
vline <- list(ggplot2::geom_vline(xintercept=29, linetype="longdash", linewidth=1))
yfacets <- c("Smarthouse", "Treatment.1")
probeSmooths(data = longi.dat,
response = "PSA", response.smoothed = "sPSA",
individuals = "Snapshot.ID.Tag",times = "DAP",
smoothing.args =
args4smoothing(df = c(4,7),
lambda = list(PS = c(0.316,10))),
profile.plot.args =
args4profile_plot(plots.by = NULL,
facet.x = "Tuning",
facet.y = c("Smarthouse", "Treatment.1"),
include.raw = "no",
alpha = 0.4,
colour.column = "Method",
colour.values = c("orange", "olivedrab"),
ggplotFuncs = vline))
#An example that supplies three smoothing schemes to be compared
data(tomato.dat)
probeSmooths(data = tomato.dat,
response = "PSA", response.smoothed = "sPSA",
times = "DAP",
smoothing.args =
args4smoothing(spline.types = c( "N", "NCS", "P"),
df = c( 4, 6, NA),
lambdas = c( NA, NA, 1),
smoothing.methods = c("dir", "log", "log"),
combinations = "parallel"),
which.plots = "medians.deviations",
meddevn.plot.args =
args4meddevn_plot(plots.by = NULL,
plots.group = c("Type", "Tuning", "Method"),
facet.x = ".", facet.y = ".",
propn.note = FALSE, propn.types = NULL))
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