I created this random time series:
MM=1584
Z0<-rnorm(MM,8,1.0)#;ts.plot(Z0)
s_1=1.50; p_1=121; p_2=240
s_2=1.25; p_3=361; p_4=480
s_3=1.10; p_5=601; p_6=720
s_4=1.50; p_7=960; p_8=1020
s_5=1.25; p_9=1140; p_10=1320
s_6=1.50; p_11=1369; p_12=1440
a=(Z0[1:p_1-1])
b=(s_1+Z0[p_1:p_2])
c=(Z0[(p_2+1):(p_3-1)])
d=(s_2+Z0[p_3:p_4])
e=(Z0[(p_4+1):(p_5-1)])
f=(s_2+Z0[p_5:p_6])
g=(Z0[(p_6+1):(p_7-1)])
h=(s_3+Z0[p_7:p_8])
i=(Z0[(p_8+1):(p_9-1)])
l=(s_4+Z0[p_9:p_10])
m=(Z0[(p_10+1):(p_11-1)])
n=(s_5+Z0[p_11:p_12])
o=Z0[(p_12+1):MM]
Z=c(a,b,c,d,e,f,g,h,i,l,m,n,o);ts.plot(Z)
abline(v=p_1,col="red");abline(v=p_2,col="red");abline(v=p_3,col="red")
abline(v=p_4,col="red");abline(v=p_5,col="red");abline(v=p_6,col="red")
abline(v=p_7,col="red");abline(v=p_8,col="red");abline(v=p_9,col="red")
abline(v=p_10,col="red");abline(v=p_11,col="red");abline(v=p_12,col="red")
Zm=as.data.frame(Z)
write.csv2(Zm, file="C:/Users/Luca/Dekstop/Zm/Zm1.csv")
I would like to repeat these commands to create 100 series and to save these with write.cs2(...Zm"...".csv).
I don't want to change the file names and repeat the commands all manually.
I searched something useful in other questions but I didn't find it.
The loop has to change only the name of data frame (Zm) and the file names, for each loop.
I'm looking to repeat 100 times the creation of Z0 (Z01, Z02, Z03 ... Z0100) , then Z (Z1, Z2, ... Z100) so Zm (Zm1, Zm2, Zm3... Zm100) and save them in the folder with new file names (folder/Zm1, Zm2, Zm3 etc...) all in 1 command with a loop.
I'm not sure why you want to change the name of the data frames, but dynamically changing the name of the file is straightforward.
for (i in 1:100) { ... write.csv2(Zm, file=paste("C:/Users/Luca/Dekstop/Zm/Zm", i, ".csv", sep = "")) }
If you want to keep the created data frames, why not just simply use a list?
Related
I've first figured out how to read and name multiple H5 files from my directory, but I'm running into actually being able to graph with them. My problem is multiple - with this type of file, I do not know how to make the columns have the same number of rows and I do not know how to call on specific files.
My initial setup is as followed
library("rhdf5")
library("ggplot2")
library("fs")
library("tidyverse")
wd <- "D:/Data/1282-1329/"
setwd(wd)
testh5 <- H5Fopen("1282.h5")
H5Fclose(testh5)
y <- h5read(file = "1282.h5",
name = "/Signal")
x <- h5read(file = "1282.h5",
name = "/Scan")
The / refers to the H5 files 'Group' and the Signal or Scan refers to the 'Name', thus "/Signal" creates a numerical list with a length of 48 (number of files within 1282-1329). I make multiple lists from each of these by doing
file_paths <- fs::dir_ls("D:/Data/1282-1329/H5")
file_paths
file_Scan <- list()
for (i in seq_along(file_paths)) {
file_Scan[[i]] <- h5read(
file = file_paths[[i]],
name = "/Scan"
)
}
file_Signal <- list()
for (i in seq_along(file_paths)) {
file_Signal[[i]] <- h5read(
file = file_paths[[i]],
name = "/Signal"
)
}
file_Scan <- setNames(file_Scan, file_paths)
file_Signal <- setNames(file_Signal, file_paths)
Thus str(file_Signal) gives me something like..
List of 48
$ D:/Data/1282-1329/H5/1282.h5: num [1:8044(1d)] 11569527 11576106 10848312 11007212 11074822 ...
$ D:/Data/1282-1329/H5/1283.h5: num [1:8045(1d)] 9746633 9886735 10000637 9617273 ...
So my first problem here is [1:8044(1d)] and [1:8045(1d)] - they're one row off. But I'm unable to add in NAs or make the lengths the same as I would a normal list. Is it because I'm thinking about this wrong? I feel like the solution is simple.
My ultimate goal will be to create multiple single plots for each of these files in the directory using something like
for (i in seq_along(file_paths)) {
plots[[i]] = ggplot(file_paths, aes(x=file_Signal, y=file_Scan))+
geom_point(size=1)
}
Then use these to create a rolling gif of the files with Even numbers (1282, 1284, 1286, etc) and Odd numbers (1283, 1285, 1287, etc.)
Thank you for any help or resources to might have to offer.
Trying to extract two attributes from the XML file extract (from a large XML file) namely 'nmRegime' and 'CalendarSystemT' (this is the date). Once extract those two records need to be saved as two columns in a data frame in R along with the filename.
There are several 'event' nodes within one given XML file and there are nearly 100 individual XML files.
<Event tEV="FirA" clearEV="false" onEV="true" dateOriginEV="Calendar" nYrsFromStEV="" nDaysFromStEV="" tFaqEV="Blank" tAaqEV="Blank" aqStYrEV="0" aqEnYrEV="0" nmEV="Fire_Cool" categoryEV="CatUndef" tEvent="Doc" idSP="105" nmRegime="Wheat, Tilled, stubble cool burn" regimeInstance="1">
<notesEV></notesEV>
<dateEV CalendarSystemT="FixedLength">19710331</dateEV>
<FirA fracAfctFirA="0.6" fracGbfrToAtmsFirA="0.98" fracStlkToAtmsFirA="0.98" fracLeafToAtmsFirA="0.98" fracGbfrToGlitFirA="0.02" fracStlkToSlitFirA="0.02" fracLeafToLlitFirA="0.02" fracCortToCodrFirA="1.0" fracFirtToFidrFirA="1.0" fracDGlitToAtmsFirA="0.931" fracRGlitToAtmsFirA="0.931" fracDSlitToAtmsFirA="0.931" fracRSlitToAtmsFirA="0.931" fracDLlitToAtmsFirA="0.931" fracRLlitToAtmsFirA="0.931" fracDCodrToAtmsFirA="0.0" fracRCodrToAtmsFirA="0.0" fracDFidrToAtmsFirA="0.0" fracRFidrToAtmsFirA="0.0" fracDGlitToInrtFirA="0.019" fracRGlitToInrtFirA="0.019" fracDSlitToInrtFirA="0.019" fracRSlitToInrtFirA="0.019" fracDLlitToInrtFirA="0.019" fracRLlitToInrtFirA="0.019" fracDCodrToInrtFirA="0.0" fracRCodrToInrtFirA="0.0" fracDFidrToInrtFirA="0.0" fracRFidrToInrtFirA="0.0" fracSopmToAtmsFirA="" fracLrpmToAtmsFirA="" fracMrpmToAtmsFirA="" fracSommToAtmsFirA="" fracLrmmToAtmsFirA="" fracMrmmToAtmsFirA="" fracMicrToAtmsFirA="" fracSopmToInrtFirA="" fracLrpmToInrtFirA="" fracMrpmToInrtFirA="" fracSommToInrtFirA="" fracLrmmToInrtFirA="" fracMrmmToInrtFirA="" fracMicrToInrtFirA="" fracMnamNToAtmsFirA="" fracSAmmNToAtmsFirA="" fracSNtrNToAtmsFirA="" fracDAmmNToAtmsFirA="" fracDNtrNToAtmsFirA="" fixFirA="" phaFirA="" />
</Event>
Had some success in extracting 'nmRegime' but no success with 'CalendarSystemT'. Used below code for data extraction.
The second question, is there a way to loop the list of XML files and do this operation?
# get records
library(xml2)
recs <- xml_find_all(xml, "//Event")
#extract the names
labs <- trimws(xml_attr(recs, "nmRegime"))
names <- labs[!is.na(labs)]
# Extract the date
recs_t <- xml_find_all(xml, "//Event/dateEV")
time <- trimws(xml_attr(recs_t, "CalendarSystemT"))
The calendar time value is not an attribute but is stored as the node's element and is accessed directly.
Also note that if an Event Node is missing a "dateEV" then there will be problems aligning the "labs" with the "time". It is better to extract the time value from each parent node instead of the entire document.
library(xml2)
library(dplyr)
xml<- read_xml('<Event tEV="FirA" clearEV="false" onEV="true" dateOriginEV="Calendar" nYrsFromStEV="" nDaysFromStEV="" tFaqEV="Blank" tAaqEV="Blank" aqStYrEV="0" aqEnYrEV="0" nmEV="Fire_Cool" categoryEV="CatUndef" tEvent="Doc" idSP="105" nmRegime="Wheat, Tilled, stubble cool burn" regimeInstance="1">
<notesEV></notesEV>
<dateEV CalendarSystemT="FixedLength">19710331</dateEV>
<FirA fracAfctFirA="0.6" fracGbfrToAtmsFirA="0.98" fracStlkToAtmsFirA="0.98" fracLeafToAtmsFirA="0.98" fracGbfrToGlitFirA="0.02" fracStlkToSlitFirA="0.02" fracLeafToLlitFirA="0.02" fracCortToCodrFirA="1.0" fracFirtToFidrFirA="1.0" fracDGlitToAtmsFirA="0.931" fracRGlitToAtmsFirA="0.931" fracDSlitToAtmsFirA="0.931" fracRSlitToAtmsFirA="0.931" fracDLlitToAtmsFirA="0.931" fracRLlitToAtmsFirA="0.931" fracDCodrToAtmsFirA="0.0" fracRCodrToAtmsFirA="0.0" fracDFidrToAtmsFirA="0.0" fracRFidrToAtmsFirA="0.0" fracDGlitToInrtFirA="0.019" fracRGlitToInrtFirA="0.019" fracDSlitToInrtFirA="0.019" fracRSlitToInrtFirA="0.019" fracDLlitToInrtFirA="0.019" fracRLlitToInrtFirA="0.019" fracDCodrToInrtFirA="0.0" fracRCodrToInrtFirA="0.0" fracDFidrToInrtFirA="0.0" fracRFidrToInrtFirA="0.0" fracSopmToAtmsFirA="" fracLrpmToAtmsFirA="" fracMrpmToAtmsFirA="" fracSommToAtmsFirA="" fracLrmmToAtmsFirA="" fracMrmmToAtmsFirA="" fracMicrToAtmsFirA="" fracSopmToInrtFirA="" fracLrpmToInrtFirA="" fracMrpmToInrtFirA="" fracSommToInrtFirA="" fracLrmmToInrtFirA="" fracMrmmToInrtFirA="" fracMicrToInrtFirA="" fracMnamNToAtmsFirA="" fracSAmmNToAtmsFirA="" fracSNtrNToAtmsFirA="" fracDAmmNToAtmsFirA="" fracDNtrNToAtmsFirA="" fixFirA="" phaFirA="" />
</Event>')
recs <- xml_find_all(xml, "//Event")
#extract the names
labs <- trimws(xml_attr(recs, "nmRegime")) names <- labs[!is.na(labs)]
# Extract the date
time <- xml_find_first(recs, ".//dateEV") %>% xml_text() %>% trimws()
To answer your second question, yes you could can wrap the above script into a function and then use lapply to loop through your entire list of files.
See this question and answer for details: R XML - combining parent and child nodes(w same name) into data frame
I am trying to find Cronbach's Alpha for survey data containing a series of multi-item measures. Rather than have to manually write out every single multi-item measure, it looks like something a loop should be able to manage far more effectively, but it needs to change only part of the column name, according to the question number.
The basic idea as it currently sits in my head would be...
for (N in 4:22) {
ytqN <- data.frame(YT_Data$QNa, YT_Data$QNb, YT_Data$QNc)
alpha(ytqN)
}
The loop would then create new data frames for each multi item measure and run Cronbach's Alpha as it goes.
This doesn't work though. :(
ytq4 <- data.frame(YT_Data$Q4a, YT_Data$Q4b, YT_Data$Q4c)
alpha(ytq4)
ytq5 <- data.frame(YT_Data$Q5a, YT_Data$Q5b, YT_Data$Q5c)
alpha(ytq5)
ytq6 <- data.frame(YT_Data$Q6a, YT_Data$Q6b, YT_Data$Q6c)
alpha(ytq6)
ytq7 <- data.frame(YT_Data$Q7a, YT_Data$Q7b, YT_Data$Q7c)
alpha(ytq7)
ytq8 <- data.frame(YT_Data$Q8a, YT_Data$Q8b, YT_Data$Q8c)
alpha(ytq8)
ytq9 <- data.frame(YT_Data$Q9a, YT_Data$Q9b, YT_Data$Q9c)
alpha(ytq9)
ytq10 <- data.frame(YT_Data$Q10a, YT_Data$Q10b, YT_Data$Q10c)
alpha(ytq10)
ytq11 <- data.frame(YT_Data$Q11a, YT_Data$Q11b, YT_Data$Q11c)
alpha(ytq11)
ytq12 <- data.frame(YT_Data$Q12a, YT_Data$Q12b, YT_Data$Q12c)
alpha(ytq12)
ytq13 <- data.frame(YT_Data$Q13a, YT_Data$Q13b, YT_Data$Q13c)
alpha(ytq13)
ytq14 <- data.frame(YT_Data$Q14a, YT_Data$Q14b, YT_Data$Q14c)
alpha(ytq14)
ytq15 <- data.frame(YT_Data$Q15a, YT_Data$Q15b, YT_Data$Q15c)
alpha(ytq15)
ytq16 <- data.frame(YT_Data$Q16a, YT_Data$Q16b, YT_Data$Q16c)
alpha(ytq16)
ytq17 <- data.frame(YT_Data$Q17a, YT_Data$Q17b, YT_Data$Q17c)
alpha(ytq17)
ytq18 <- data.frame(YT_Data$Q18a, YT_Data$Q18b, YT_Data$Q18c)
alpha(ytq18)
ytq19 <- data.frame(8 - YT_Data$Q19a, YT_Data$Q19b, YT_Data$Q19c)
# Reverse code Q19a
alpha(ytq19)
ytq20 <- data.frame(YT_Data$Q20a, YT_Data$Q20b, YT_Data$Q20c)
alpha(ytq20)
ytq21 <- data.frame(YT_Data$Q21a, YT_Data$Q21b, YT_Data$Q21c)
alpha(ytq21)
ytq22 <- data.frame(YT_Data$Q22a, YT_Data$Q22b, YT_Data$Q22c)
alpha(ytq22)
The desired results would be a single output containing all the Cronbach's Alphas for the multi item measures for questions 4-22 in the data set I am currently working on executed via a single piece of code, rather than have to go question by question.
It's easier to help if you include your data, but I guess this should work:
alpha_list = list()
for(N in 4:22){
ytq = data.frame(YT_Data[paste0("Q",N,"a")],
YT_Data[paste0("Q",N,"b")],
YT_Data[paste0("Q",N,"c")])
alpha_list[[N]] = alpha(ytq)
}
We are using paste0() to create the column names while looping on N. alpha_list will be a list with the results given by alpha()
Is there a way to document variables in R with their date of creation/modification?
Because I have .RData files that I used fluency, but sometimes need update the values based in how old is it.
Try file.info():
To get the last modified time:
file.info('path/to/file.Rdata')$mtime
If you want to know when individual variables within your .RData object were last defined by R the only thing I know to do would be to manually add that metadata in something like this:
a = 3
attr(a, 'time_defined') = Sys.time()
b = 4
attr(b, 'time_defined') = Sys.time()
save(a, b, file = 'my_data.RData')
# ... later on ...
load('my_data.RData')
if(difftime(attr(a, 'time_defined'), Sys.time(), units = 'days') > 10) # do the following if more than 10 days old
I need to import a list of 36 csv files, but after running the code I get only 26 of them. Probably, 10 files have format problems. Is there a way in R to detect the 10 files that cannot be imported?
If you the file names in a list, you can use the following code:
all <- c("16048.txt", "16062.txt", "16066.txt", "16093.txt", "16095.txt", "16122.txt", "16241.txt", "16360.txt", "16380.txt", "16389.txt", "16510.txt", "16511.txt", "16701.txt", "16729.txt", "16735.txt", "16737.txt", "16761.txt", "16816.txt", "16867.txt", "16876.txt", "16880.txt", "16883.txt", "16884.txt", "16885.txt", "16893.txt", "16904.txt", "16906.txt", "16908.txt", "16929.txt", "16931.txt", "16938.txt", "16943.txt", "16959.txt", "16967.txt", "16968.txt", "16969.txt")
imp <- c("16761.txt", "16959.txt", "16884.txt", "16093.txt", "16883.txt", "16122.txt", "16906.txt", "16737.txt", "16968.txt", "16095.txt", "16062.txt", "16816.txt", "16360.txt", "16893.txt", "16885.txt", "16938.txt", "16048.txt", "16931.txt", "16876.txt", "16511.txt", "16969.txt", "16241.txt", "16967.txt", "16701.txt", "16380.txt", "16510.txt")
Where all is the list of filenames you need and imp is the imperfect result you got. You can get a list of the missing files with:
missing <- all[!all %in% imp]