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Luigi Marongiu

2020-Oct-27 12:33 UTC

[R] R for-loop to add layer to lattice plot

Hello,
I am using e1071 to run support vector machine. I would like to plot
the data with lattice and specifically show the hyperplanes created by
the system.
I can store the hyperplane as a contour in an object, and I can plot
one object at a time. Since there will be thousands of elements to
plot, I can't manually add them one by one to the plot, so I tried to
loop into them, but only the last is added.
Here it the working example for more clarity:

```
library(e1071)
library(lattice)
library(latticeExtra)

make.grid <- function(x, n = 1000) {
  grange = apply(x, 2, range)
  x1 = seq(from = grange[1,1], to = grange[2,1], length = n)
  x2 = seq(from = grange[1,2], to = grange[2,2], length = n)
  expand.grid(X1 = x1, X2 = x2)
}

plot_list <- list()
for (i in 1:10) {
  x1 = rnorm(100, mean = 0.2, sd = 0.15)
  y1 = rnorm(100, mean = 0.7, sd = 0.15)
  y2 = rnorm(100, mean = 0.2, sd = 0.15)
  x2 = rnorm(100, mean = 0.75, sd = 0.15)
  df = data.frame(x = c(x1,x2), y=c(y1,y2),
                  z=c(rep(0, length(x1)), rep(1, length(x2))))
  df$z = factor(c(rep(0, length(x1)), rep(1, length(x2))))
  df[, "train"] <- ifelse(runif(nrow(df)) < 0.8, 1, 0)
  trainset <- df[df$train == 1, ]
  testset <- df[df$train == 0, ]
  trainColNum <- grep("train", names(df))
  trainset <- trainset[, -trainColNum]
  testset <- testset[, -trainColNum]
  svm_model <- svm(z ~ .,
                  data = trainset,
                  type = "C-classification",
                  kernel = "linear",
                  scale = FALSE)
  # generate contour
  xmat = make.grid(matrix(c(testset$x, testset$y),
                          ncol = 2, byrow=FALSE))
  xgrid = as.data.frame(xmat)
  names(xgrid) = c("x", "y")
  z = predict(svm_model, xgrid)
  xyz_dat = as.data.frame(cbind(xgrid, z))
  plot_list[[i]] = contourplot(z ~ y+x, data=xyz_dat, pretty = TRUE,
                               xlim=c(-1,50), ylim=c(-0.001, 0.05),
                               labels = FALSE, col = "blue", lwd =
0.5)

}
# the contour is stored in the object plot_list
str(plot_list) # confirm that there is data here

# I can add one element at the time to lattice's xyplot and store it
in an object P
P = xyplot(y ~ x, group = z, data = df,
           pch = 16, cex = 1.5, alpha = 0.25) + as.layer(plot_list[[1]]) +
  as.layer(plot_list[[2]])
plot(P)  # this demonstrates that the lines are not the same

# but if I add the elements via loop, it does not work
for (i in 1:length(plot_list)) {
  print(i)
  P = xyplot(y ~ x, group = z, data = df,
             pch = 16, cex = 1.5, alpha = 0.25) + as.layer(plot_list[[i]])
}
plot(P)
```

Am I missing something?
Thank you

Mark Leeds

2020-Oct-27 14:47 UTC

head link

[R] R for-loop to add layer to lattice plot

Hi: I think you're writing over the plots so only the last one exists.
Maybe try P = P + whatever but
I'm not sure if that's allowed with plots.



On Tue, Oct 27, 2020 at 8:34 AM Luigi Marongiu <marongiu.luigi at
gmail.com>
wrote:
> Hello,
> I am using e1071 to run support vector machine. I would like to plot
> the data with lattice and specifically show the hyperplanes created by
> the system.
> I can store the hyperplane as a contour in an object, and I can plot
> one object at a time. Since there will be thousands of elements to
> plot, I can't manually add them one by one to the plot, so I tried to
> loop into them, but only the last is added.
> Here it the working example for more clarity:
>
> ```
> library(e1071)
> library(lattice)
> library(latticeExtra)
>
> make.grid <- function(x, n = 1000) {
>   grange = apply(x, 2, range)
>   x1 = seq(from = grange[1,1], to = grange[2,1], length = n)
>   x2 = seq(from = grange[1,2], to = grange[2,2], length = n)
>   expand.grid(X1 = x1, X2 = x2)
> }
>
> plot_list <- list()
> for (i in 1:10) {
>   x1 = rnorm(100, mean = 0.2, sd = 0.15)
>   y1 = rnorm(100, mean = 0.7, sd = 0.15)
>   y2 = rnorm(100, mean = 0.2, sd = 0.15)
>   x2 = rnorm(100, mean = 0.75, sd = 0.15)
>   df = data.frame(x = c(x1,x2), y=c(y1,y2),
>                   z=c(rep(0, length(x1)), rep(1, length(x2))))
>   df$z = factor(c(rep(0, length(x1)), rep(1, length(x2))))
>   df[, "train"] <- ifelse(runif(nrow(df)) < 0.8, 1, 0)
>   trainset <- df[df$train == 1, ]
>   testset <- df[df$train == 0, ]
>   trainColNum <- grep("train", names(df))
>   trainset <- trainset[, -trainColNum]
>   testset <- testset[, -trainColNum]
>   svm_model <- svm(z ~ .,
>                   data = trainset,
>                   type = "C-classification",
>                   kernel = "linear",
>                   scale = FALSE)
>   # generate contour
>   xmat = make.grid(matrix(c(testset$x, testset$y),
>                           ncol = 2, byrow=FALSE))
>   xgrid = as.data.frame(xmat)
>   names(xgrid) = c("x", "y")
>   z = predict(svm_model, xgrid)
>   xyz_dat = as.data.frame(cbind(xgrid, z))
>   plot_list[[i]] = contourplot(z ~ y+x, data=xyz_dat, pretty = TRUE,
>                                xlim=c(-1,50), ylim=c(-0.001, 0.05),
>                                labels = FALSE, col = "blue", lwd
= 0.5)
>
> }
> # the contour is stored in the object plot_list
> str(plot_list) # confirm that there is data here
>
> # I can add one element at the time to lattice's xyplot and store it
> in an object P
> P = xyplot(y ~ x, group = z, data = df,
>            pch = 16, cex = 1.5, alpha = 0.25) + as.layer(plot_list[[1]]) +
>   as.layer(plot_list[[2]])
> plot(P)  # this demonstrates that the lines are not the same
>
> # but if I add the elements via loop, it does not work
> for (i in 1:length(plot_list)) {
>   print(i)
>   P = xyplot(y ~ x, group = z, data = df,
>              pch = 16, cex = 1.5, alpha = 0.25) + as.layer(plot_list[[i]])
> }
> plot(P)
> ```
>
> Am I missing something?
> Thank you
>
> ______________________________________________
> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>
	[[alternative HTML version deleted]]

Deepayan Sarkar

2020-Oct-28 05:59 UTC

head link

[R] R for-loop to add layer to lattice plot

On Tue, Oct 27, 2020 at 6:04 PM Luigi Marongiu <marongiu.luigi at
gmail.com> wrote:>
> Hello,
> I am using e1071 to run support vector machine. I would like to plot
> the data with lattice and specifically show the hyperplanes created by
> the system.
> I can store the hyperplane as a contour in an object, and I can plot
> one object at a time. Since there will be thousands of elements to
> plot, I can't manually add them one by one to the plot, so I tried to
> loop into them, but only the last is added.
> Here it the working example for more clarity:
>
> ```
> library(e1071)
> library(lattice)
> library(latticeExtra)
>
> make.grid <- function(x, n = 1000) {
>   grange = apply(x, 2, range)
>   x1 = seq(from = grange[1,1], to = grange[2,1], length = n)
>   x2 = seq(from = grange[1,2], to = grange[2,2], length = n)
>   expand.grid(X1 = x1, X2 = x2)
> }
>
> plot_list <- list()
> for (i in 1:10) {
>   x1 = rnorm(100, mean = 0.2, sd = 0.15)
>   y1 = rnorm(100, mean = 0.7, sd = 0.15)
>   y2 = rnorm(100, mean = 0.2, sd = 0.15)
>   x2 = rnorm(100, mean = 0.75, sd = 0.15)
>   df = data.frame(x = c(x1,x2), y=c(y1,y2),
>                   z=c(rep(0, length(x1)), rep(1, length(x2))))
>   df$z = factor(c(rep(0, length(x1)), rep(1, length(x2))))
>   df[, "train"] <- ifelse(runif(nrow(df)) < 0.8, 1, 0)
>   trainset <- df[df$train == 1, ]
>   testset <- df[df$train == 0, ]
>   trainColNum <- grep("train", names(df))
>   trainset <- trainset[, -trainColNum]
>   testset <- testset[, -trainColNum]
>   svm_model <- svm(z ~ .,
>                   data = trainset,
>                   type = "C-classification",
>                   kernel = "linear",
>                   scale = FALSE)
>   # generate contour
>   xmat = make.grid(matrix(c(testset$x, testset$y),
>                           ncol = 2, byrow=FALSE))
>   xgrid = as.data.frame(xmat)
>   names(xgrid) = c("x", "y")
>   z = predict(svm_model, xgrid)
>   xyz_dat = as.data.frame(cbind(xgrid, z))
>   plot_list[[i]] = contourplot(z ~ y+x, data=xyz_dat, pretty = TRUE,
>                                xlim=c(-1,50), ylim=c(-0.001, 0.05),
>                                labels = FALSE, col = "blue", lwd
= 0.5)
>
> }
> # the contour is stored in the object plot_list
> str(plot_list) # confirm that there is data here
>
> # I can add one element at the time to lattice's xyplot and store it
> in an object P
> P = xyplot(y ~ x, group = z, data = df,
>            pch = 16, cex = 1.5, alpha = 0.25) + as.layer(plot_list[[1]]) +
>   as.layer(plot_list[[2]])
> plot(P)  # this demonstrates that the lines are not the same
>
> # but if I add the elements via loop, it does not work
> for (i in 1:length(plot_list)) {
>   print(i)
>   P = xyplot(y ~ x, group = z, data = df,
>              pch = 16, cex = 1.5, alpha = 0.25) + as.layer(plot_list[[i]])
> }
> plot(P)
> ```
>
> Am I missing something?
Yes, as Mark says, you need to change the last part to something like

P = xyplot(y ~ x, group = z, data = df, pch = 16, cex = 1.5, alpha = 0.25)
for (i in 1:length(plot_list)) {
  print(i)
  P = P + as.layer(plot_list[[i]])
}
plot(P)

-Deepayan
> Thank you
>
> ______________________________________________
> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.

Luigi Marongiu

2020-Oct-28 09:09 UTC

head link

[R] R for-loop to add layer to lattice plot

Awesome, thanks!

On Wed, Oct 28, 2020 at 7:00 AM Deepayan Sarkar
<deepayan.sarkar at gmail.com> wrote:>
> On Tue, Oct 27, 2020 at 6:04 PM Luigi Marongiu <marongiu.luigi at
gmail.com> wrote:
> >
> > Hello,
> > I am using e1071 to run support vector machine. I would like to plot
> > the data with lattice and specifically show the hyperplanes created by
> > the system.
> > I can store the hyperplane as a contour in an object, and I can plot
> > one object at a time. Since there will be thousands of elements to
> > plot, I can't manually add them one by one to the plot, so I tried
to
> > loop into them, but only the last is added.
> > Here it the working example for more clarity:
> >
> > ```
> > library(e1071)
> > library(lattice)
> > library(latticeExtra)
> >
> > make.grid <- function(x, n = 1000) {
> >   grange = apply(x, 2, range)
> >   x1 = seq(from = grange[1,1], to = grange[2,1], length = n)
> >   x2 = seq(from = grange[1,2], to = grange[2,2], length = n)
> >   expand.grid(X1 = x1, X2 = x2)
> > }
> >
> > plot_list <- list()
> > for (i in 1:10) {
> >   x1 = rnorm(100, mean = 0.2, sd = 0.15)
> >   y1 = rnorm(100, mean = 0.7, sd = 0.15)
> >   y2 = rnorm(100, mean = 0.2, sd = 0.15)
> >   x2 = rnorm(100, mean = 0.75, sd = 0.15)
> >   df = data.frame(x = c(x1,x2), y=c(y1,y2),
> >                   z=c(rep(0, length(x1)), rep(1, length(x2))))
> >   df$z = factor(c(rep(0, length(x1)), rep(1, length(x2))))
> >   df[, "train"] <- ifelse(runif(nrow(df)) < 0.8, 1, 0)
> >   trainset <- df[df$train == 1, ]
> >   testset <- df[df$train == 0, ]
> >   trainColNum <- grep("train", names(df))
> >   trainset <- trainset[, -trainColNum]
> >   testset <- testset[, -trainColNum]
> >   svm_model <- svm(z ~ .,
> >                   data = trainset,
> >                   type = "C-classification",
> >                   kernel = "linear",
> >                   scale = FALSE)
> >   # generate contour
> >   xmat = make.grid(matrix(c(testset$x, testset$y),
> >                           ncol = 2, byrow=FALSE))
> >   xgrid = as.data.frame(xmat)
> >   names(xgrid) = c("x", "y")
> >   z = predict(svm_model, xgrid)
> >   xyz_dat = as.data.frame(cbind(xgrid, z))
> >   plot_list[[i]] = contourplot(z ~ y+x, data=xyz_dat, pretty = TRUE,
> >                                xlim=c(-1,50), ylim=c(-0.001, 0.05),
> >                                labels = FALSE, col = "blue",
lwd = 0.5)
> >
> > }
> > # the contour is stored in the object plot_list
> > str(plot_list) # confirm that there is data here
> >
> > # I can add one element at the time to lattice's xyplot and store
it
> > in an object P
> > P = xyplot(y ~ x, group = z, data = df,
> >            pch = 16, cex = 1.5, alpha = 0.25) +
as.layer(plot_list[[1]]) +
> >   as.layer(plot_list[[2]])
> > plot(P)  # this demonstrates that the lines are not the same
> >
> > # but if I add the elements via loop, it does not work
> > for (i in 1:length(plot_list)) {
> >   print(i)
> >   P = xyplot(y ~ x, group = z, data = df,
> >              pch = 16, cex = 1.5, alpha = 0.25) +
as.layer(plot_list[[i]])
> > }
> > plot(P)
> > ```
> >
> > Am I missing something?
>
> Yes, as Mark says, you need to change the last part to something like
>
> P = xyplot(y ~ x, group = z, data = df, pch = 16, cex = 1.5, alpha = 0.25)
> for (i in 1:length(plot_list)) {
>   print(i)
>   P = P + as.layer(plot_list[[i]])
> }
> plot(P)
>
> -Deepayan
>
> > Thank you
> >
> > ______________________________________________
> > R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
> > https://stat.ethz.ch/mailman/listinfo/r-help
> > PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
> > and provide commented, minimal, self-contained, reproducible code.


-- 
Best regards,
Luigi

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