When I try to generate the exams' solution with the exams2nops(...template="solution"...) I get the following error message:
Error in exams2pdf(file, n = n, nsamp = nsamp, dir = dir, name = name, :
formal argument "template" matched by multiple actual arguments
How can I produce an exams' solution with the exams2nops?
You cannot do that in one go, you need two runs after setting the same seed, e.g.,
set.seed(1)
exams2nops(my_exam)
set.seed(1)
exams2pdf(my_exam, template = "my_solution.tex")
You can use the solution.tex provided within the package as a starting point for my_solution.tex. But you may want to translate it to your natural language, use the name of your university, possibly insert a logo, add your actual exam name, possibly some into text etc. In exams2pdf() you need to add these things in the template LaTeX file directly.
won't the template="solution" not work in the exams2pdf? Also, can we do something like:
usepackage = "pdfpages", intro = intro2,... ?
Related
I am currently using Snakemake for a bioinformatics project. Given a human reference genome (hg19) and a bam file, I want to be able to specify that there will be multiple output files with the same name but different extensions. Here is my code
rule gridss_preprocess:
input:
ref=config['ref'],
bam=config['bamdir'] + "{sample}.dedup.downsampled.bam",
bai=config['bamdir'] + "{sample}.dedup.downsampled.bam.bai"
output:
expand(config['bamdir'] + "{sample}.dedup.downsampled.bam{ext}", ext = config['workreq'], sample = "{sample}")
Currently config['workreq'] is a list of extensions that start with "."
For example, I want to be able to use expand to indicate the following files
S1.dedup.downsampled.bam.cigar_metrics
S1.dedup.downsampled.bam.computesamtags.changes.tsv
S1.dedup.downsampled.bam.coverage.blacklist.bed
S1.dedup.downsampled.bam.idsv_metrics
I want to be able to do this for multiple sample files, S_. Currently I am not getting an error when I try to do a dry run. However, I am not sure if this will run properly.
Am I doing this right?
expand() defines a list of files. If you're using two parameters, the cartesian product will be used. Thus, your rule will define as output ALL files with your extension list for ALL samples. Since you define a wildcard in your input, I think that what you want is all files with your extension for ONE sample. And this rule will be executed as many times as the number of samples.
You're mixing up wildcards and placeholders for the expand() function. You can define a wildcard inside an expand() by doubling the brackets:
rule all:
input: expand(config['bamdir'] + "{sample}.dedup.downsampled.bam{ext}", ext = config['workreq'], sample=SAMPLELIST)
rule gridss_preprocess:
input:
ref=config['ref'],
bam=config['bamdir'] + "{sample}.dedup.downsampled.bam",
bai=config['bamdir'] + "{sample}.dedup.downsampled.bam.bai"
output:
expand(config['bamdir'] + "{{sample}}.dedup.downsampled.bam{ext}", ext = config['workreq'])
This expand function will expand in list
{sample}.dedup.downsampled.bam.cigar_metrics
{sample}.dedup.downsampled.bam.computesamtags.changes.tsv
{sample}.dedup.downsampled.bam.coverage.blacklist.bed
{sample}.dedup.downsampled.bam.idsv_metrics
and thus define the wildcard sample to match the files in the input.
For a project I am creating different layers which should all be written into one geopackage.
I am using QGIS 3.16.1 and the Python console inside QGIS which runs on Python 3.7
I tried many things but cannot figure out how to do this. This is what I used so far.
vl = QgsVectorLayer("Point", "points1", "memory")
vl2 = QgsVectorLayer("Point", "points2", "memory")
pr = vl.dataProvider()
pr.addAttributes([QgsField("DayID", QVariant.Int), QgsField("distance", QVariant.Double)])
vl.updateFields()
f = QgsFeature()
for x in range(len(tag_temp)):
f.setGeometry(QgsGeometry.fromPointXY(QgsPointXY(lon[x],lat[x])))
f.setAttributes([dayID[x], distance[x]])
pr.addFeature(f)
vl.updateExtents()
# I'll do the same for vl2 but with other data
uri ="D:/Documents/QGIS/test.gpkg"
options = QgsVectorFileWriter.SaveVectorOptions()
context = QgsProject.instance().transformContext()
QgsVectorFileWriter.writeAsVectorFormatV2(vl1,uri,context,options)
QgsVectorFileWriter.writeAsVectorFormatV2(vl2,uri,context,options)
Problem is that the in the 'test.gpkg' a layer is created called 'test' and not 'points1' or 'points2'.
And the second QgsVectorFileWriter.writeAsVectorFormatV2() also overwrites the output of the first one instead of appending the layer into the existing geopackage.
I also tried to create single .geopackages and then use 'Package Layers' processing tool (processing.run("native:package") to merge all layers into one geopackage, but then the attributes types are all converted into strings unfortunately.
Any help is much appreciated. Many thanks in advance.
You need to change the SaveVectorOptions, in particular the mode of actionOnExistingFile after creating the gpkg file :
options = QgsVectorFileWriter.SaveVectorOptions()
#options.driverName = "GPKG"
options.layerName = v1.name()
QgsVectorFileWriter.writeAsVectorFormatV2(v1,uri,context,options)
#switch mode to append layer instead of overwriting the file
options.actionOnExistingFile = QgsVectorFileWriter.CreateOrOverwriteLayer
options.layerName = v2.name()
QgsVectorFileWriter.writeAsVectorFormatV2(v2,uri,context,options)
The documentation is here : SaveVectorOptions
I also tried to create single .geopackages and then use 'Package Layers' processing tool (processing.run("native:package") to merge all layers into one geopackage, but then the attributes types are all converted into strings unfortunately.
This is definitively the recommended way, please consider reporting the bug
I am trying to build the inline segment to filter the pages (ex. to separate the pages for blogs and games) using the function BuildClassificationValueSegment() to get the data from Adobe Analytics API,
I have tried some thing like
report.data.visits <- QueueTrended(reportsuite.id,date.from,date.to,metrics,elements,
segment.inline = BuildClassificationValueSegment("evar2","blog","OR")).
Got error like :
Error in ApiRequest(body = report.description, func.name = "Report.Validate") :
ERROR: segment_invalid - Segment "evar2" not valid for this company
In addition: Warning message:
In if (segment.inline != "") { :
the condition has length > 1 and only the first element will be used
Please help on the same.Thanks in advance...
I recommend you to declare the InlineSegment in advance and store it in a variable. Then pass it to the QueueTrended function.
I've been using the following syntax to generate an inline segment:
InlineSegment <- list(container=list(type=unbox("hits"),
rules=data.frame(
name=c("Page Name(eVar48)"),
element=c("evar48"),
operator=c("equals"),
value=c(as.character("value1","value2"))
))
You can change the name and element arguments in order to personalize the query.
The next step is to pass the InlineSegment to the QueueRanked function:
Report <- as.data.frame(QueueRanked("reportsuite",
date.from = dateStart,
date.to = dateEnd,
metrics = c("pageviews"),
elements = c("element"),
segment.inline = InlineSegment,
max.attempts=500))
I borrowed that syntax from this thread some time ago: https://github.com/randyzwitch/RSiteCatalyst/issues/129
Please note that there might be easier ways to obtain this kind of report without using InlineSegmentation. Maybe you can use the selected argument from the QueueRanked function in order to narrow down the scope of the report.
Also, I'm purposefully avoiding the BuildClassificationValueSegment function as I found it a bit difficult to understand.
Hope this workaround helps...
I am trying to pass a variable to install.package,library, ls and ?
Passing a variable to install.package works fine, but I get an error for the others.
name1 <- as.character("dplyr")
install.packages(name1)
library(name1)
ls(name1)
?name1
I would be greatfull for your help.
One of the three issues, library(name1), can be resolved with the option character.only = TRUE:
library(name1, character.only = TRUE)
To list all the objects in the library with the name stored in name1, try
ls(paste0("package:",name1))
or
ls(getNamespace(name1))
(see here for a discussion on the difference between these two commands, including further options to show hidden objects).
Concerning the third point, ?, I have no solution to offer other than using help(name1) instead, as suggested also by #PierreLafortune.
How can I find how did I first declare a certain variable when I am a few hundred
lines down from where I first declared it. For example, I have declared the following:
a <- c(vectorA,vectorB,vectorC)
and now I want to see how I declared it. How can I do that?
Thanks.
You could try using the history command:
history(pattern = "a <-")
to try to find lines in your history where you assigned something to the variable a. I think this matches exactly, though, so you may have to watch out for spaces.
Indeed, if you type history at the command line, it doesn't appear to be doing anything fancier than saving the current history in a tempfile, loading it back in using readLines and then searching it using grep. It ought to be fairly simple to modify that function to include more functionality...for example, this modification will cause it to return the matching lines so you can store it in a variable:
myHistory <- function (max.show = 25, reverse = FALSE, pattern, ...)
{
file1 <- tempfile("Rrawhist")
savehistory(file1)
rawhist <- readLines(file1)
unlink(file1)
if (!missing(pattern))
rawhist <- unique(grep(pattern, rawhist, value = TRUE,
...))
nlines <- length(rawhist)
if (nlines) {
inds <- max(1, nlines - max.show):nlines
if (reverse)
inds <- rev(inds)
}
else inds <- integer()
#file2 <- tempfile("hist")
#writeLines(rawhist[inds], file2)
#file.show(file2, title = "R History", delete.file = TRUE)
rawhist[inds]
}
I will assume you're using the default R console. If you're on Windows, you can File -> Save history and open the file in your fav text browser, or you can use function savehistory() (see help(savehistory)).
What you need to do is get a (good) IDE, or at least a decent text editor. You will benevit from code folding, syntax coloring and much more. There's a plethora of choices, from Tinn-R, VIM, ESS, Eclipse+StatET, RStudio or RevolutionR among others.
You can run grep 'a<-' .Rhistory from terminal (assuming that you've cdd to your working directory). ESS has several very useful history-searching functions, like (comint-history-isearch-backward-regexp) - binded to M-r by default.
For further info, consult ESS manual: http://ess.r-project.org/Manual/ess.html
When you define a function, R stores the source code of the function (preserving formatting and comments) in an attribute named "source". When you type the name of the function, you will get this content printed.
But it doesn't do this with variables. You can deparse a variable, which generates an expression that will produce the variable's value but this doesn't need to be the original expression. For example when you have b <- c(17, 5, 21), deparse(b) will produce the string "c(17, 5, 21)".
In your example, however, the result wouldn't be "c(vectorA,vectorB,vectorC)", it would be an expression that produces the combined result of your three vectors.