I don't understand the input f expected by play3d and movie3d in the rgl package.
library(rgl)
nobs<-10
x<-runif(nobs)
y<-runif(nobs)
z<-runif(nobs)
n<-rep(1:nobs)
df<-as.data.frame(cbind(x,y,z,n))
listofobs<-split(df,n)
plot3d(df[,1],df[,2],df[,3], type = "n", radius = .2 )
myplotfunction<-function(x) {
rgl.spheres(x=x$x,y=x$y,z=x$z, type="s", r=0.025)
}
When executing the 2 lines below, the animation does play but both lines (play3d() and movie3d()) trigger the error displayed below:
play3d(f=lapply(listofobs,myplotfunction), fps=1 )
movie3d(f=lapply(listofobs,myplotfunction), fps=1 , duration=20)
I am hoping someone can correct my code and help me understand the f input to play3d and movie3d.
Question 1: Why is the play3d line above correct enough that the animation does display correctly?
Question 2: Why is the play3d line above incorrect enough that it triggers the error?
Question 3: What is wrong with the movie3d line that it does not produce a video output?
As the docs say, f is "A function returning a list that may be passed to par3d". It's not a list, which is what your usage passes.
To answer the questions:
R evaluates the lapply call which does the animation, then play3d looks at the result and dies because it's not a function.
f needs to be a function, as described in the help page.
It dies when it looks at f, because it's not a function.
This looks like it will do what you want:
library(rgl)
nobs<-10
x<-runif(nobs)
y<-runif(nobs)
z<-runif(nobs)
df<-data.frame(x,y,z)
plot3d(df, type = "n" )
id <- NA
myplotfunction<-function(time) {
index <- round(time)
# For a 3x faster display, use index <- round(3*time)
# To cycle through the points several times, use
# index <- round(3*time) %% nobs + 1
if (!is.na(id))
pop3d(id = id) # Delete previous item
id <<- spheres3d(df[index,], r=0.025)
list()
}
play3d(myplotfunction, startTime = 1, duration = nobs - 1)
movie3d(myplotfunction, startTime = 1, duration = nobs - 1, fps = 1)
This will leave a GIF in file.path(tempdir(), "movie.gif").
Some other notes:
don't call rgl.spheres. It will cause you immense pain later. Use spheres3d, or never call any *3d function, and never upgrade rgl: you're living in the past using the rgl.* functions. The *3d functions and the rgl.* functions don't play nicely together.
to construct a dataframe, just use the data.frame() function, don't convert
a matrix.
you don't need all those contortions to extract points from the dataframe.
Most rgl functions can handle a dataframe with x, y, and z columns.
You might notice the plot3d frame move a little: spheres are bigger than points, so it will adjust to accommodate them. You could use xlim, ylim and zlim to set the original frame a little bigger if you don't like this.
Related
I'm relatively new to Z3 and experimenting with it in python. I've coded a program which returns the order in which different actions is performed, represented with a number. Z3 returns an integer representing the second the action starts.
Now I want to look at the model and see if there is an instance of time where nothing happens. To do this I made a list with only 0's and I want to change the index at the times where each action is being executed, to 1. For instance, if an action start at the 5th second and takes 8 seconds to be executed, the index 5 to 12 would be set to 1. Doing this with all the actions and then look for 0's in the list would hopefully give me the instances where nothing happens.
The problem is: I would like to write something like this for coding the problem
list_for_check = [0]*total_time
m = s.model()
for action in actions:
for index in range(m.evaluate(action.number) , m.evaluate(action.number) + action.time_it_takes):
list_for_check[index] = 1
But I get the error:
'IntNumRef' object cannot be interpreted as an integer
I've understood that Z3 isn't returning normal ints or bools in their models, but writing
if m.evaluate(action.boolean):
works, so I'm assuming the if is overwritten in a way, but this doesn't seem to be the case with range. So my question is: Is there a way to use range with Z3 ints? Or is there another way to do this?
The problem might also be that action.time_it_takes is an integer and adding a Z3int with a "normal" int doesn't work. (Done in the second part of the range).
I've also tried using int(m.evaluate(action.number)), but it doesn't work.
Thanks in advance :)
When you call evaluate it returns an IntNumRef, which is an internal z3 representation of an integer number inside z3. You need to call as_long() method of it to convert it to a Python number. Here's an example:
from z3 import *
s = Solver()
a = Int('a')
s.add(a > 4);
s.add(a < 7);
if s.check() == sat:
m = s.model()
print("a is %s" % m.evaluate(a))
print("Iterating from a to a+5:")
av = m.evaluate(a).as_long()
for index in range(av, av + 5):
print(index)
When I run this, I get:
a is 5
Iterating from a to a+5:
5
6
7
8
9
which is exactly what you're trying to achieve.
The method as_long() is defined here. Note that there are similar conversion functions from bit-vectors and rationals as well. You can search the z3py api using the interface at: https://z3prover.github.io/api/html/namespacez3py.html
I wrote a function that acts on each combination of columns in an input matrix. It uses multiple for loops and is very slow, so I am trying to parallelize it to use the maximum number of threads on my computer.
I am having difficulty finding the correct syntax to set this up. I'm using the Parallel package in octave, and have tried several ways to set up the calls. Here are two of them, in a simplified form, as well as a non-parallel version that I believe works:
function A = parallelExample(M)
pkg load parallel;
# Get total count of columns
ct = columns(M);
# Generate column pairs
I = nchoosek([1:ct],2);
ops = rows(I);
slice = ones(1, ops);
Ic = mat2cell(I, slice, 2);
## # Non-parallel
## A = zeros(1, ops);
## for i = 1:ops
## A(i) = cmbtest(Ic{i}, M);
## endfor
# Parallelized call v1
A = parcellfun(nproc, #cmbtest, Ic, {M});
## # Parallelized call v2
## afun = #(x) cmbtest(x, M);
## A = parcellfun(nproc, afun, Ic);
endfunction
# function to apply
function P = cmbtest(indices, matrix)
colset = matrix(:,indices);
product = colset(:,1) .* colset(:,2);
P = sum(product);
endfunction
For both of these examples I generate every combination of two columns and convert those pairs into a cell array that the parcellfun function should split up. In the first, I attempt to convert the input matrix M into a 1x1 cell array so it goes to each parallel instance in the same form. I get the error 'C must be a cell array' but this must be internal to the parcellfun function. In the second, I attempt to define an anonymous function that includes the matrix. The error I get here specifies that 'cmbtest' is undefined.
(Naturally, the actual function I'm trying to apply is far more complex than cmbtest here)
Other things I have tried:
Put M into a global variable so it doesn't need to be passed. Seemed to be impossible to put a global variable in a function file, though I may just be having syntax issues.
Make cmbtest a nested function so it can access M (parcellfun doesn't support that)
I'm out of ideas at this point and could use help figuring out how to get this to work.
Converting my comments above to an answer.
When performing parallel operations, it is useful to think of each parallel worker that will result as separate and independent octave instances, which need to have appropriate access to all functions and variables they will require in order to do their independent work.
Therefore, do not rely on subfunctions when calling parcellfun from a main function, since this might lead to errors if the worker is unable to access the subfunction directly under the hood.
In this case, separating the subfunction into its own file fixed the problem.
I have 4 subfolder that contains 5 rasters with continuous values. So a build a loop with "for" function to :
list these raster files
stack these files per folder , i.e 4 rasterstacks objects (that contains 5 rasters)
I apllied a treshold to transform the the continuous raster in binary raster
Finally I wrote the binary raster using wirte.raster function.
My issue is in a step 4. Eventhough I use the argument "byLayer = T" in writeRaster function
the rasters saved were a rasterstack with the 5 binary rasters. And i want write it per raster, per file, per band
I really grateful if anyone give me any insights
setwd("Vole_raw_mean_Present/")
sub <- list.dirs(full.names=FALSE, recursive=FALSE)
for(j in 1:length(sub)) {
print(sub[j])
h <- list.files(path=sub[j], recursive=TRUE, full.names=TRUE, pattern='.tif')
print(h)
stack_present <- stack(h)
print(stack_present)
binary_0.2 <- stack_present >=0.2
writeRaster(binary_0.2, filename=paste0(sub[j], bylayer = T, suffix = "_bin.tif"), overwrite=TRUE)
}
This is wrong because the argument "bylayer" is lost as it becomes part of the filename)
writeRaster(binary_0.2, filename=paste0(sub[j], bylayer = T, suffix = "_bin.tif"), overwrite=TRUE)
It should be something like this (and it helps to do it in two steps)
f <- paste0(sub[j], "bin.tif")
writeRaster(binary_0.2, filename=f, bylayer=TRUE, overwrite=TRUE)
Illustrated here
library(raster)
b <- brick(system.file("external/rlogo.grd", package="raster"))
dir.create("test")
setwd("test")
writeRaster(b, filename="abc.tif", bylayer=T)
list.files()
#[1] "abc_1.tif" "abc_2.tif" "abc_3.tif"
writeRaster(b, filename="bin.tif", bylayer=T, suffix = paste0("f", 1:3))
list.files(pattern="bin")
#[1] "bin_f1.tif" "bin_f2.tif" "bin_f3.tif"
Alternatively, you can loop over the files within each folder
I am trying to apply a function over each row of a DataFrame as the code shows.
using RDatasets
iris = dataset("datasets", "iris")
function mean_n_var(x)
mean1=mean([x[1], x[2], x[3], x[4]])
var1=var([x[1], x[2], x[3], x[4]])
rst=[mean1, var1]
return rst
end
mean_n_var([2,4,5,6])
for row in eachrow(iris[1:4])
println(mean_n_var(convert(Array, row)))
end
However, instead of printing results, I'd like to save them in an array or another DataFrame.
Thanks in advance.
I thought it is worth to mention some more options available over what was already mentioned.
I assume you want a Matrix or a DataFrame. There are several possible approaches.
First is the most direct to get a Matrix:
mean_n_var(a) = [mean(a), var(a)]
hcat((mean_n_var(Array(x)) for x in eachrow(iris[1:4]))...) # rows
vcat((mean_n_var(Array(x)).' for x in eachrow(iris[1:4]))...) # cols
another possible approach is vectorized, e.g.:
mat_iris = Matrix(iris[1:4])
mat = hcat(mean(mat_iris, 2), var(mat_iris, 2))
df = DataFrame([vec(f(mat_iris, 2)) for f in [mean,var]], [:mean, :var])
DataFrame(mat) # this constructor also accepts variable names on master but is not released yet
In Stata, after a regression I know it is possible to call the elements of stored results by name. For example, if I want to manipulate the coefficient on the variable precip, I just type _b[precip]. My question is how do I do the same after the tabstat command? For example, say I want to multiply the coefficient on precip by the sample mean of precip:
reg --variables in regression--
tabstat --variables in regression--
mat X=r(StatTotal)
mat Y=_b[precip]*X[1,precip]
Ah, if only it were that simple. But alas, in the last line X[1, precip] is invalid syntax. Oddly, Stata does recognize display X[1, precip]. And Stata would know what I'm trying to do if instead of precip I used the column number where precip appears in the X vector. If I were just doing this operation once, no problem. But I need to do this operation several times (for several different model specifications) and for several variables which change position in the vector from one model to the next, so I cannot just use the column number.
I am not yet sure I understand exactly what you want to do, but here's my attempt to reproduce what you are doing:
sysuse auto, clear
regress price mpg foreign weight
tabstat mpg foreign weight, save
matrix X = r(StatTotal)
matrix Y = _b[mpg]*X[1, colnumb(X, "mpg") ]
If you need to put this into a cycle, that's doable, too:
matrix bb = e(b)
local explvar : colnames bb
foreach x in `explvar' {
if "`x'" != "_cons" {
matrix Y_`x' = _b[`x'] * X[1, colnumb(X, "`x'")]
}
else {
matrix Y_`x' = _b[`x']
}
}
You'd probably want to put this into a program that you will call after each regression model estimation call, e.g.:
program define reg2mat , prefix( name )
if "`e(cmd)'" != "regress" {
// this will intentionally produce an error
regress
}
tempname bb
matrix `bb' = e(b)
local explvar : colnames `bb'
foreach x in `explvar' {
if "`x'" != "_cons" {
matrix `prefix'_`x' = _b[`x'] * X[1, colnumb(X, "`x'")]
}
else {
matrix `prefix'_`x' = _b[`x']
}
}
end // of reg2mat
At many levels, it is not ideal, as it manipulates with the (global) matrices in Stata memory; most of the time, it is a bad idea, as the programs should only manipulate with objects local to them.
I suspect that what you want to do is addressed, in one way or another, by either omnipowerful margins command, or by an appropriate predict, or by matrix score (which is the low level version of predict). Attributing the effects to a variable only makes sense when your regressors are orthogonal, which only happens in carefully designed and conducted experiments.