R/neuronlistfh.R
[.neuronlistfh
extracts either a sublist from a
neuronlistfh (converting it to a regular in memory list in the process)
or its attached data.frame.
# S3 method for neuronlistfh [(x, i, j, drop)
x | A neuronlistfh object |
---|---|
i, j | elements to extract or replace. Numeric, logical or character or,
for the [ get method, empty. See details and the help for
|
drop | logical. If |
A new in-memory neuronlist
or when using two subscripts, a
data.frame
- see examples.
Note that if i is a numeric or logical indexing vector, it will be converted internally to a vector of names by using the (sorted) names of the objects in x (i.e. names(x)[i])
neuronlistfh
, [.neuronlist
,
[.data.frame
, [<-.data.frame
,
Other neuronlistfh: neuronlistfh
,
read.neuronlistfh
,
remotesync
,
write.neuronlistfh
# make a test neuronlistfh backed by a temporary folder on disk tf=tempfile('kcs20fh') kcs20fh<-as.neuronlistfh(kcs20, dbdir=tf) # get first neurons as an in memory neuronlist class(kcs20fh[1:3])#> [1] "neuronlist" "list"# extract attached data.frame str(kcs20fh[,])#> 'data.frame': 20 obs. of 14 variables: #> $ gene_name: chr "FruMARCM-M001205_seg002" "GadMARCM-F000122_seg001" "GadMARCM-F000050_seg001" "GadMARCM-F000142_seg002" ... #> $ Name : chr "fru-M-500112" "Gad1-F-900005" "Gad1-F-100010" "Gad1-F-300043" ... #> $ idid : num 1024 10616 8399 10647 9758 ... #> $ soma_side: Factor w/ 3 levels "L","M","R": 1 1 3 1 1 3 3 3 3 3 ... #> $ flipped : logi FALSE FALSE TRUE FALSE FALSE TRUE ... #> $ Driver : chr "fru-Gal4" "Gad1-Gal4" "Gad1-Gal4" "Gad1-Gal4" ... #> $ Gender : chr "M" "F" "F" "F" ... #> $ X : num 361 368 383 350 388 ... #> $ Y : num 95 105.9 61.7 78.2 114.8 ... #> $ Z : num 84.1 94.7 97.3 96.7 87.8 ... #> $ exemplar : Factor w/ 96 levels "5HT1bMARCM-M000076_seg001",..: 60 78 76 79 41 45 59 82 6 63 ... #> $ cluster : int 9 70 57 71 64 44 16 61 52 12 ... #> $ idx : int 156 1519 1132 1535 1331 795 268 1265 898 190 ... #> $ type : Factor w/ 3 levels "ab","apbp","gamma": 3 3 1 2 1 1 1 2 2 1 ...# or part of the data.frame str(kcs20fh[1:2,1:3])#> 'data.frame': 2 obs. of 3 variables: #> $ gene_name: chr "FruMARCM-M001205_seg002" "GadMARCM-F000122_seg001" #> $ Name : chr "fru-M-500112" "Gad1-F-900005" #> $ idid : num 1024 10616# data.frame assignment (this one changes nothing) kcs20fh[1:2,'gene_name'] <- kcs20fh[1:2,'gene_name'] # clean up unlink(tf, recursive=TRUE)