I'm using the text-mining tm library for R.
I'm running on R version 3.3.1
I have this code:
lda <- LDA(docterm,k = 3,method = 'Gibbs')
lda.topics <- as.matrix(topics(lda))
lda.terms <- as.matrix(terms(lda,5))
topic.terms <- c()
topic.terms[1] <- paste(c(lda.terms[,1],'\n'),collapse = '\n')
topic.terms[2] <- paste(c(lda.terms[,2],'\n'),collapse = '\n')
topic.terms[3] <- paste(c(lda.terms[,3],'\n'),collapse = '\n')
tw.df <- tw.df %>%
mutate(topico = topic.terms[lda.topics])
But every time I try to run it with source file.r
It throws me this:
Error in eval(expr, envir, enclos) : could not find function "LDA"
I don't get it, the tm package is installed.
Has anybody encountered this kind of behaviour before?
Any ideas on how to solve it?
Thanks in advance!
Try installing and using the package 'topicmodels'.
install.packages('topicmodels')
It should work.
Related
Can anyone figure out why I get the error below after running the following code?
library(haven)
library(survival)
library(dplyr)
library(readr)
library(glmmLasso)
par(mar=c(1,1,1,1))
library(discSurv)
HH<- as.data.frame(read_dta("https://www.stata.com/data/jwooldridge/eacsap/recid.dta") )
HHC <- contToDisc(dataShort = HH, timeColumn = "durat", intervalLimits = 20,equi = TRUE)
dtLong<-dataLong(dataShort = HHC, timeColumn = "timeDisc",
eventColumn = "cens",timeAsFactor = FALSE)
formula.1<-y~factor(black)+factor(alcohol)
family<-binomial(link = "logit")
lambda <- 20
penal.vec<-20
next.try<-TRUE
BIC_vec<-rep(Inf,length(lambda))
Deltama.glm2<-as.matrix(t(rep(0,3)))#coefficients + Intercept
Smooth.glm2<-as.matrix(t(rep(0,20)))
j<-1;test.step<-1;
glm2 <- glmmLasso(formula.1,
rnd = NULL,family = family, data = dtLong, lambda=lambda[j],final.re=T,switch.NR=F,
control = list(smooth=list(formula=~- 1+as.numeric(timeInt),nbasis=20,spline.degree=3,
diff.ord=2,penal=penal.vec[test.step],start=Smooth.glm2[j,]),
method.final="EM", print.iter=T,print.iter.final=T,
eps.final=1e-4,epsilon=1e-4,complexity="non.zero",
start=Deltama.glm2[j,]))
Iteration 41
Final Re-estimation Iteration 9Error in Z_aktuell * D : non-conformable arrays
when I change Deltama.glm2<-as.matrix(t(rep(0,3))) to Deltama.glm2<-as.matrix(t(rep(0,2)))
I get the error
Iteration 1Error in grad.lasso[b.is.0] <- score.beta[b.is.0] - lambda.b * sign(score.beta[b.is.0]) :
NAs are not allowed in subscripted assignments
I have tried to remove the starting values as suggested on glmmLasso error and warning without success
Switching from R version 4.2.2 to 3.6.0 solved the issue. Seems there is a compatibility issue between glmmlasso and the newer versions of R.
I want to use the function dm_draw() to visualize a dm object but when I ran the command I get the error message " Error: invalid version specification ‘0,2’". I've tried the code included in the vignette "Visualizing dm objects" (https://cran.r-project.org/web/packages/dm/vignettes/tech-dm-draw.html) and I get the same error message when I run the dm_draw() function.
library(dm)
library(dplyr)
flights_dm_w_many_keys <- dm_nycflights13(color = FALSE)
dm_draw(flights_dm_w_many_keys)
I'm using dm version 0.2.7 and DiagrammeR 1.0.8. R version 4.1.2
I'm looking for a solution to visualize a dm object, it can be also different from dm_draw().
I hope someone can help me to get that done. Sorry for my broken English and thanks for your time, any type of help is appreciated.
You can use this code:
library(dm)
library(dplyr)
library(DiagrammeR)
library(DiagrammeRsvg)
# Use this function
dm_draw_svg = function(dm,...) {
if (!requireNamespace("DiagrammeRsvg", quietly = TRUE)) {
stop(
"Package \"DiagrammeRsvg\" must be installed to use this function.",
call. = FALSE
)
}
dm::dm_draw(dm = dm, ...) %>%
DiagrammeRsvg::export_svg() %>%
htmltools::HTML() %>%
htmltools::html_print()
}
flights_dm_w_many_keys <- dm_nycflights13(color = FALSE)
# plot
dm_draw_svg(flights_dm_w_many_keys)
Output:
When trying to mimic some python code using R's reticulate package:
import_from_path("jwt_auth", "C:/Program Files/Python 3.5/Lib/site-packages/boxsdk/auth")
I get this error:
Error in py_module_import(module, convert = convert) :
SystemError: Parent module '' not loaded, cannot perform relative import
Detailed traceback:
File "C:\Program Files\Python 3.5\Lib\site-packages\boxsdk\auth\jwt_auth.py", line 13, in <module>
from .oauth2 import OAuth2
Is there a better way to load sub-modules in R like such:
from boxsdk import JWTAuth
I haven't seen any solid solution. In the package I do something like this. Interestingly the drill down of reportlab can be done with dot notation.
# this is needed in case we use python in the R code rather than source_python
fitz <- NULL
pdfr <- NULL
pdfw <- NULL
repl <- NULL
.onLoad <- function(libname, pkgname) {
# this will fail in package check
reticulate::use_condaenv(condaenv = "myenv", required = TRUE)
fitz <<- reticulate::import("fitz", delay_load = TRUE)
pdfr_0 <- reticulate::import("PyPDF2", delay_load = TRUE)
pdfr <<- pdfr_0$PdfFileReader
pdfw <<- pdfr_0$PdfFileWriter
repl <- reticulate::import("reportlab.pdfgen.canvas", delay_load = TRUE)
}
I am new to R. I have to use POSTagger in my code. I am using openNLP with R. While trying following sample code (in Sample.R file):
library("NLP")
library("openNLP")
s <- paste(c("Pierre Vinken, 61 years old, will join the board as a ",
"nonexecutive director Nov. 29.\n",
"Mr. Vinken is chairman of Elsevier N.V., ",
"the Dutch publishing group."),
collapse = "")
s <- as.String(s)
sent_token_annotator <- Maxent_Sent_Token_Annotator()
a1 <- annotate(s, sent_token_annotator)
s[a1]
And running this code from R Console (Using source("Sample.R"))
I am getting following error:
Error in as.data.frame.default(x[[i]], optional = TRUE) :
cannot coerce class "c("Simple_POS_Tag_Annotator", "Annotator")" to a data.frame
Following is the output of traceback() command :
14: stop(gettextf("cannot coerce class \"%s\" to a data.frame", deparse(class(x))),
domain = NA)
13: as.data.frame.default(x[[i]], optional = TRUE)
12: as.data.frame(x[[i]], optional = TRUE)
11: data.frame(x = function (s, a = Annotation())
{
s <- as.String(s)
y <- f(s)
n <- length(y)
id <- .seq_id(next_id(a$id), n)
type <- rep.int("sentence", n)
if (is.Annotation(y)) {
y$id <- id
y$type <- type
}
else if (is.Span(y)) {
y <- as.Annotation(y, id = id, type = type)
}
else stop("Invalid result from underlying sentence tokenizer.")
if (length(i <- which(a$type == "paragraph"))) {
a <- a[i]
a$features <- lapply(annotations_in_spans(y, a), function(e) list(constituents = e$id))
y <- c(y, a)
}
y
}, check.names = FALSE, stringsAsFactors = FALSE)
10: eval(expr, envir, enclos)
9: eval(as.call(c(expression(data.frame), x, check.names = !optional,
stringsAsFactors = stringsAsFactors)))
8: as.data.frame.list(x[[i]], optional = TRUE, stringsAsFactors = stringsAsFactors)
7: as.data.frame(x[[i]], optional = TRUE, stringsAsFactors = stringsAsFactors)
6: data.frame(position)
5: annotate(s, sent_token_annotator) at sample.R#11
4: eval(expr, envir, enclos)
3: eval(ei, envir)
2: withVisible(eval(ei, envir))
1: source("sample.R")
What can be possibly wrong? I am using Rx64 3.1.1 on Windows 7. Any help will be much appreciated. Thanks in advance.
I have the same problem and i fixed it by removing/detach the ggplot2 package. There is a function called Annotate in ggplot2 and it is the same name in both packages. I suggest you make sure that it is looking at the correct function in the library... in my case it was looking at the Annotate function of ggplot2 and not the NLP package.
I don't have an exact answer but suffered the same error using NLP, openNLP, tm, qdap. I worked backward restarting R and loading (library) one package, running code, then loading another package and running code, until I ran across the "cannot coerce to a dataframe" error. I found, in my case that qdap interferes with the openNLP annotate() function call -- which is actually using an NLP wrapper.
openNLP version 0.2-3 imports NLP (≥ 0.1-2), openNLPdata (≥ 1.5.3-1), and rJava (≥ 0.6-3). Because you loaded NLP explicitly, it may be a case of two instances of NLP running in memory interfering with each other. Try just loading openNLP and running your code
Multiple packages have same name. If you specifically tell R which package to use it will probably resolve the issue. For example, instead of Arrange(...), try using openNLP::Arrange(...)
I am trying to vectorize this call to source_url, in order to load some functions from GitHub:
library(devtools)
# Find ggnet functions.
fun = c("ggnet.R", "functions.R")
fun = paste0("https://raw.github.com/briatte/ggnet/master/", fun)
# Load ggnet functions.
source_url(fun[1], prompt = FALSE)
source_url(fun[2], prompt = FALSE)
The last two lines should be able to work in a lapply call, but for some reason, this won't work from knitr: to have this code work when I process a Rmd document to HTML, I have to call source_url twice.
The same error shows up with source_url from devtools and with the one from downloader: somehwere in my code, an object of type closure is not subsettable.
I suspect that this has something to do with SHA; any explanation would be most welcome.
It has nothing to do with knitr or devtools or vectorization. It is just an error in your(?) code, and it is fairly easy to find it out using traceback().
> library(devtools)
> # Find ggnet functions.
> fun = c("ggnet.R", "functions.R")
> fun = paste0("https://raw.github.com/briatte/ggnet/master/", fun)
> # Load ggnet functions.
> source_url(fun[1], prompt = FALSE)
SHA-1 hash of file is 2c731cbdf4a670170fb5298f7870c93677e95c7b
> source_url(fun[2], prompt = FALSE)
SHA-1 hash of file is d7d466413f9ddddc1d71982dada34e291454efcb
Error in df$Source : object of type 'closure' is not subsettable
> traceback()
7: which(df$Source == x) at file34af6f0b0be5#14
6: who.is.followed.by(df, "JacquesBompard") at file34af6f0b0be5#19
5: eval(expr, envir, enclos)
4: eval(ei, envir)
3: withVisible(eval(ei, envir))
2: source(temp_file, ...)
1: source_url(fun[2], prompt = FALSE)
You used df in the code, and df is a function in the stats package (density of the F distribution). I know you probably mean a data frame, but you did not declare that in the code.