Plot a 3d graph with a slider to control number of points plotted

Question

I have data which is movement of an object in 3D space at regular time intervals. Data is as below:

Time  X   Y   Z
1     1   1   1
2     2   1   2
3     2   0   1
4     3   2   1
.....

(x,y,z) is the position of object at time t. I want to plot a 3D graph where it shows the complete movement of object in 3d space, but to have a slider or something of that sort where I can select a time range (say 500 to 750) and see the movement of the object in 3D space. So, here we have 4 dimensions: x,y,z are positions and time as 4th dimension and use a slider to control the plotting of points with in that time. [Example in Mathematica below gives a good idea about this]

To make it more clear. We first draw the complete movement of the object in 3D space from time 1 to N. Then, by controlling the slider, we draw the movement of same object between t1 to t2 time stamps. It is also important to display at what time the slider is at (as I have to make a note of some interested time stamps based on the movement).

I have Googled the same, but no example was close enough to get me what I want. All of those bind the slider to one of the axis variables (say x or y which might be time) but we have to bind it to 4th dimension, time. dygraphs was promising but I had similar issues as discussed above (also, didn't find any 3d support).

This one in Mathematica is interesting. But I don't have license for it. It just moves a point on the 3D path traced. This can solve my problem as well, but I should be able to know the time-stamp values when I pause it.

Solution in R is good for me because it does not have any licensing issues. Or in Matlab if it does not use any advanced visualization toolboxes. Or Python.

Thanks in Advance.

Answer 1

This is a raw example that can be customized as desired. It uses manipulate and plot3D

library(manipulate)
library(plot3D)

min_time <- 1
max_time <- 100
time_interval <- min_time:max_time

# Create data frame
DF <- data.frame(t = time_interval)

# Time parametric functions
X <- function(t) {
  return(2 * t)
}

Y <- function(t) {
  return(t ** 2)
}

Z <- function(t) {
  return(10 * cos(t / 100))
}
# Update data frame
DF$x <- sapply(DF$t, X)
DF$y <- sapply(DF$t, Y)
DF$z <- sapply(DF$t, Z)

# Use manipulate with RStudio
manipulate({
  lines3D(x = DF$x, y = DF$y, z = DF$z)
  scatter3D(
    x = DF$x[t],
    y = DF$y[t],
    z = DF$z[t],
    add = TRUE
  )
}, t = slider(min_time, max_time))