plot_lattice | R Documentation |
Plots a set of projections of the full-dimensional input space.
plot_lattice(
ems,
targets,
ppd = 20,
cb = FALSE,
cutoff = 3,
maxpoints = 50000,
imp_breaks = NULL,
contour = TRUE,
ranges = NULL,
raster_imp = FALSE,
plot_vars = NULL,
fixed_vars = NULL
)
ems |
The |
targets |
The corresponding target values. |
ppd |
The number of points to sample per dimension. |
cb |
Whether or not a colourblind-friendly plot should be produced. |
cutoff |
The cutoff value for non-implausible points. |
maxpoints |
The limit on the number of points to be evaluated. |
imp_breaks |
If plotting nth maximum implausibility, defines the levels at which to draw contours. |
contour |
Logical determining whether to plot implausibility contours or not. |
ranges |
Parameter ranges. If not supplied, defaults to emulator ranges. |
raster_imp |
Should the implausibility plots be rasterised? |
plot_vars |
If provided, indicates which subset of parameters to plot. |
fixed_vars |
If provided, indicates the fixed value of the plot-excluded parameters. |
The plots are:
One dimensional optical depth plots (diagonal);
Two dimensional optical depth plots (lower triangle);
Two dimensional minimum implausibility plots (upper triangle).
The optical depth is calculated as follows. A set of points is constructed across the full d-dimensional parameter space, and implausibility is calculated at each point. The points are collected into groups based on their placement in a projection to a one- or two-dimensional slice of the parameter space. For each group, the proportion of non-implausible points is calculated, and this value in [0,1] is plotted. The minimum implausibility plots are similar, but with minimum implausibility calculated rather than proportion of non-implausible points.
The maxpoints
argument is used as a cutoff for if a regular ppd grid would
result in a very large number of points. If this is the case, then maxpoints
points
are sampled uniformly from the region instead of regularly spacing them.
If only a subset of parameters are relevant, then the plot_vars
and fixed_vars
can be used to specify the subset. If plot_vars
is provided, corresponding to a list
of parameter names, then those parameters not included are fixed to their mid-range values;
if fixed_vars is provided as a named list, then the parameters not included are fixed
to the corresponding specified values.
A ggplot object
Bower, Goldstein & Vernon (2010) <doi:10.1214/10-BA524>
Other visualisation tools:
behaviour_plot()
,
diagnostic_wrap()
,
effect_strength()
,
emulator_plot()
,
hit_by_wave()
,
output_plot()
,
plot_actives()
,
plot_wrap()
,
simulator_plot()
,
space_removed()
,
validation_pairs()
,
wave_dependencies()
,
wave_points()
,
wave_values()
# Excessive runtime
plot_lattice(SIREmulators$ems, SIREmulators$targets, ppd = 10)
plot_lattice(SIREmulators$ems$nS, SIREmulators$targets)
plot_lattice(SIREmulators$ems, SIREmulators$targets, plot_vars = c('aSI', 'aIR'))
plot_lattice(SIREmulators$ems, SIREmulators$targets, fixed_vars = list(aSR = 0.03))
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