plot3D_map {TSCS} | R Documentation |
Visualize Spatial(Cross-Section) Data of a Given Time Point - 3D Map
Description
plot_map
draws a three-dimensional spatial map. It is plotted based on the cross-section data
of a given time point, which is also often extracted from spatio-temporal data.
Usage
plot3D_map(newdata, xlab = NULL, ylab = NULL, zlab = NULL, title = NULL,
cex = 9, colorNA = "white")
Arguments
newdata |
data frame; should only contain the four variables in order: X coordinate, Y coordinate, Z coordinate and observation. This is the cross-section data or pure spatial data of a particular time point you have selected, with missing observations that you want to predict. (coordinates must be numeric) |
xlab |
a label for the x axis, defaults to the name of X coordinate. |
ylab |
a label for the y axis, defaults to the name of Y coordinate. |
zlab |
a label for the z axis, defaults to the name of Z coordinate. |
title |
a main title for the plot. |
cex |
numeric; size of plotting point for each spatial locations. (default: 9) |
colorNA |
colour for missing values/observations. (default: "white") |
Details
The resulting plot is interactive.
-
plot3D_map
is exclusive to 3D rectangular grid system. Similarly, if you want to fathom how this package handles 2D rectangular grid system, please refer toplot_map
.
See Also
plot_map
, plot3D_NA
, plot3D_dif
Examples
## Not run:
## TSCS spatial interpolation procedure:
basis <- tscsRegression3D(data = data, h1 = 3.75, h2 = 2.5, v = 5, alpha = 0.01);
basis$percentage
est <- tscsEstimate3D(matrix = basis$coef_matrix, newdata = newdata, h1 = 3.75, h2 = 2.5, v = 5);
str(est)
## comparison of estimates and true values:
plot_compare(est = est$estimate[,4], true = true)
index <- appraisal_index(est = est$estimate[,4], true = true);
index
## data visualization:
plot3D_dif(data = data[,1:3], h1 = 3.75, h2 = 2.5, v = 5)
plot3D_NA(newdata = newdata)
plot3D_map(newdata = newdata)
## End(Not run)