Hi,
It seems that the files did not make it through the mailer. Perhaps it didn't
like my extensions. I have now attached the files as .txt's as well as copied
in the contents of each file:
list(list(structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L), .Label = c("0", "1",
"2"), class = "factor"), structure(c(3L, 1L, 3L, 3L, 3L, 3L,
3L, 3L, 3L, 1L, 3L, 3L, 3L, 1L, 3L, 3L, 3L, 1L, 3L, 1L, 1L, 1L,
1L, 1L, 1L, 3L, 1L, 1L, 1L, 3L, 3L, 1L, 3L, 1L, 3L, 3L, 3L, 3L,
1L, 3L, 3L, 3L, 1L, 3L, 1L, 1L, 1L, 1L, 3L, 1L, 1L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 1L, 3L, 3L, 3L, 1L, 3L, 3L, 3L, 1L, 1L, 3L, 3L,
3L, 3L, 3L, 3L, 3L, 1L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 1L, 3L, 1L,
3L, 1L, 3L, 3L, 1L, 3L, 3L, 1L, 3L, 3L, 1L, 3L, 3L, 1L), .Label = c("0",
"1", "2"), class = "factor"), structure(c(3L, 2L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 1L, 3L, 3L, 3L, 1L, 3L, 3L, 3L, 2L, 3L, 1L, 2L,
2L, 1L, 1L, 1L, 3L, 1L, 1L, 1L, 3L, 3L, 1L, 3L, 2L, 3L, 3L, 3L,
3L, 2L, 3L, 3L, 3L, 1L, 3L, 2L, 1L, 1L, 1L, 3L, 2L, 1L, 3L, 3L,
3L, 3L, 3L, 3L, 3L, 2L, 3L, 3L, 3L, 2L, 3L, 3L, 3L, 2L, 1L, 3L,
3L, 3L, 3L, 3L, 3L, 3L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 1L, 3L,
1L, 3L, 2L, 3L, 3L, 1L, 3L, 3L, 1L, 3L, 3L, 2L, 3L, 3L, 2L), .Label = c("0",
"1", "2"), class = "factor"), structure(c(3L, 2L, 3L, 3L, 3L,
3L, 1L, 3L, 3L, 1L, 1L, 3L, 3L, 1L, 1L, 3L, 3L, 2L, 3L, 1L, 2L,
2L, 1L, 1L, 1L, 3L, 1L, 1L, 1L, 3L, 3L, 1L, 1L, 2L, 1L, 1L, 3L,
1L, 2L, 1L, 3L, 1L, 1L, 3L, 2L, 1L, 1L, 1L, 3L, 2L, 1L, 3L, 3L,
3L, 3L, 1L, 3L, 1L, 2L, 1L, 3L, 1L, 2L, 1L, 1L, 1L, 2L, 1L, 1L,
3L, 3L, 3L, 3L, 3L, 3L, 2L, 1L, 3L, 1L, 3L, 1L, 1L, 1L, 1L, 3L,
1L, 3L, 2L, 3L, 3L, 1L, 3L, 1L, 1L, 1L, 1L, 2L, 3L, 3L, 2L), .Label = c("0",
"1", "2"), class = "factor")), list(structure(c(2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L
), .Label = c("0", "1", "2"), class = "factor"), structure(c(2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 1L, 2L, 2L, 2L,
1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 2L, 2L, 1L, 2L,
2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 1L, 2L, 1L, 1L, 1L, 1L, 2L,
1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 1L, 2L, 2L,
2L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 2L, 1L, 2L, 2L, 1L, 2L, 2L, 1L,
2L, 2L, 2L), .Label = c("0", "1", "2"), class = "factor"), structure(c(1L,
2L, 1L, 2L, 1L, 2L, 1L, 1L, 2L, 1L, 1L, 2L, 1L, 1L, 1L, 2L, 1L,
1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
2L, 1L, 2L), .Label = c("0", "1", "2"), class = "factor")), list(
structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L), .Label = c("0",
"1", "2"), class = "factor"), structure(c(3L, 2L, 3L, 2L,
3L, 3L, 3L, 3L, 2L, 2L, 3L, 3L, 3L, 2L, 3L, 3L, 3L, 2L, 3L,
2L, 2L, 2L, 2L, 2L, 2L, 3L, 2L, 2L, 2L, 3L, 3L, 2L, 3L, 2L,
3L, 3L, 3L, 3L, 2L, 3L, 3L, 3L, 2L, 3L, 2L, 2L, 2L, 2L, 3L,
2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 2L, 3L, 3L, 3L, 2L, 3L,
3L, 3L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 2L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 2L, 2L, 2L, 3L, 2L, 3L, 3L, 2L, 3L, 3L, 2L,
3L, 3L, 2L, 3L, 3L, 2L), .Label = c("0", "1", "2"), class = "factor"),
structure(c(3L, 2L, 3L, 2L, 3L, 3L, 1L, 3L, 2L, 2L, 1L, 3L,
3L, 2L, 1L, 3L, 3L, 2L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L,
2L, 2L, 3L, 3L, 2L, 1L, 2L, 1L, 1L, 3L, 1L, 2L, 1L, 3L, 1L,
2L, 3L, 2L, 2L, 2L, 2L, 3L, 2L, 2L, 3L, 3L, 3L, 3L, 1L, 3L,
1L, 2L, 1L, 3L, 1L, 2L, 1L, 1L, 1L, 2L, 2L, 1L, 3L, 3L, 3L,
3L, 3L, 3L, 2L, 1L, 3L, 1L, 3L, 1L, 1L, 1L, 2L, 2L, 2L, 3L,
2L, 3L, 3L, 2L, 3L, 1L, 2L, 1L, 1L, 2L, 3L, 3L, 2L), .Label = c("0",
"1", "2"), class = "factor"), structure(c(3L, 1L, 3L, 1L,
3L, 3L, 1L, 3L, 1L, 1L, 1L, 3L, 3L, 2L, 1L, 3L, 3L, 1L, 3L,
1L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 3L, 3L, 1L, 1L, 2L,
1L, 1L, 3L, 1L, 2L, 1L, 3L, 1L, 1L, 3L, 1L, 2L, 2L, 1L, 3L,
2L, 1L, 3L, 3L, 3L, 3L, 1L, 3L, 1L, 1L, 1L, 3L, 1L, 1L, 1L,
1L, 1L, 1L, 2L, 1L, 3L, 3L, 3L, 3L, 3L, 3L, 1L, 1L, 3L, 1L,
3L, 1L, 1L, 1L, 2L, 1L, 1L, 3L, 1L, 3L, 3L, 1L, 3L, 1L, 1L,
1L, 1L, 1L, 3L, 3L, 2L), .Label = c("0", "1", "2"), class = "factor")))
list(4L, 3L, 4L)
MaxGrowth.txt:
list(4L, 3L, 4L)
AllPredictedValues.txt
list(list(structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L), .Label = c("0", "1",
"2"), class = "factor"), structure(c(3L, 1L, 3L, 3L, 3L, 3L,
3L, 3L, 3L, 1L, 3L, 3L, 3L, 1L, 3L, 3L, 3L, 1L, 3L, 1L, 1L, 1L,
1L, 1L, 1L, 3L, 1L, 1L, 1L, 3L, 3L, 1L, 3L, 1L, 3L, 3L, 3L, 3L,
1L, 3L, 3L, 3L, 1L, 3L, 1L, 1L, 1L, 1L, 3L, 1L, 1L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 1L, 3L, 3L, 3L, 1L, 3L, 3L, 3L, 1L, 1L, 3L, 3L,
3L, 3L, 3L, 3L, 3L, 1L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 1L, 3L, 1L,
3L, 1L, 3L, 3L, 1L, 3L, 3L, 1L, 3L, 3L, 1L, 3L, 3L, 1L), .Label = c("0",
"1", "2"), class = "factor"), structure(c(3L, 2L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 1L, 3L, 3L, 3L, 1L, 3L, 3L, 3L, 2L, 3L, 1L, 2L,
2L, 1L, 1L, 1L, 3L, 1L, 1L, 1L, 3L, 3L, 1L, 3L, 2L, 3L, 3L, 3L,
3L, 2L, 3L, 3L, 3L, 1L, 3L, 2L, 1L, 1L, 1L, 3L, 2L, 1L, 3L, 3L,
3L, 3L, 3L, 3L, 3L, 2L, 3L, 3L, 3L, 2L, 3L, 3L, 3L, 2L, 1L, 3L,
3L, 3L, 3L, 3L, 3L, 3L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 1L, 3L,
1L, 3L, 2L, 3L, 3L, 1L, 3L, 3L, 1L, 3L, 3L, 2L, 3L, 3L, 2L), .Label = c("0",
"1", "2"), class = "factor"), structure(c(3L, 2L, 3L, 3L, 3L,
3L, 1L, 3L, 3L, 1L, 1L, 3L, 3L, 1L, 1L, 3L, 3L, 2L, 3L, 1L, 2L,
2L, 1L, 1L, 1L, 3L, 1L, 1L, 1L, 3L, 3L, 1L, 1L, 2L, 1L, 1L, 3L,
1L, 2L, 1L, 3L, 1L, 1L, 3L, 2L, 1L, 1L, 1L, 3L, 2L, 1L, 3L, 3L,
3L, 3L, 1L, 3L, 1L, 2L, 1L, 3L, 1L, 2L, 1L, 1L, 1L, 2L, 1L, 1L,
3L, 3L, 3L, 3L, 3L, 3L, 2L, 1L, 3L, 1L, 3L, 1L, 1L, 1L, 1L, 3L,
1L, 3L, 2L, 3L, 3L, 1L, 3L, 1L, 1L, 1L, 1L, 2L, 3L, 3L, 2L), .Label = c("0",
"1", "2"), class = "factor")), list(structure(c(2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L
), .Label = c("0", "1", "2"), class = "factor"), structure(c(2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 1L, 2L, 2L, 2L,
1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 2L, 2L, 1L, 2L,
2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 1L, 2L, 1L, 1L, 1L, 1L, 2L,
1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 1L, 2L, 2L,
2L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 2L, 1L, 2L, 2L, 1L, 2L, 2L, 1L,
2L, 2L, 2L), .Label = c("0", "1", "2"), class = "factor"), structure(c(1L,
2L, 1L, 2L, 1L, 2L, 1L, 1L, 2L, 1L, 1L, 2L, 1L, 1L, 1L, 2L, 1L,
1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
2L, 1L, 2L), .Label = c("0", "1", "2"), class = "factor")), list(
structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L), .Label = c("0",
"1", "2"), class = "factor"), structure(c(3L, 2L, 3L, 2L,
3L, 3L, 3L, 3L, 2L, 2L, 3L, 3L, 3L, 2L, 3L, 3L, 3L, 2L, 3L,
2L, 2L, 2L, 2L, 2L, 2L, 3L, 2L, 2L, 2L, 3L, 3L, 2L, 3L, 2L,
3L, 3L, 3L, 3L, 2L, 3L, 3L, 3L, 2L, 3L, 2L, 2L, 2L, 2L, 3L,
2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 2L, 3L, 3L, 3L, 2L, 3L,
3L, 3L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 2L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 2L, 2L, 2L, 3L, 2L, 3L, 3L, 2L, 3L, 3L, 2L,
3L, 3L, 2L, 3L, 3L, 2L), .Label = c("0", "1", "2"), class = "factor"),
structure(c(3L, 2L, 3L, 2L, 3L, 3L, 1L, 3L, 2L, 2L, 1L, 3L,
3L, 2L, 1L, 3L, 3L, 2L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L,
2L, 2L, 3L, 3L, 2L, 1L, 2L, 1L, 1L, 3L, 1L, 2L, 1L, 3L, 1L,
2L, 3L, 2L, 2L, 2L, 2L, 3L, 2L, 2L, 3L, 3L, 3L, 3L, 1L, 3L,
1L, 2L, 1L, 3L, 1L, 2L, 1L, 1L, 1L, 2L, 2L, 1L, 3L, 3L, 3L,
3L, 3L, 3L, 2L, 1L, 3L, 1L, 3L, 1L, 1L, 1L, 2L, 2L, 2L, 3L,
2L, 3L, 3L, 2L, 3L, 1L, 2L, 1L, 1L, 2L, 3L, 3L, 2L), .Label = c("0",
"1", "2"), class = "factor"), structure(c(3L, 1L, 3L, 1L,
3L, 3L, 1L, 3L, 1L, 1L, 1L, 3L, 3L, 2L, 1L, 3L, 3L, 1L, 3L,
1L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 3L, 3L, 1L, 1L, 2L,
1L, 1L, 3L, 1L, 2L, 1L, 3L, 1L, 1L, 3L, 1L, 2L, 2L, 1L, 3L,
2L, 1L, 3L, 3L, 3L, 3L, 1L, 3L, 1L, 1L, 1L, 3L, 1L, 1L, 1L,
1L, 1L, 1L, 2L, 1L, 3L, 3L, 3L, 3L, 3L, 3L, 1L, 1L, 3L, 1L,
3L, 1L, 1L, 1L, 2L, 1L, 1L, 3L, 1L, 3L, 3L, 1L, 3L, 1L, 1L,
1L, 1L, 1L, 3L, 3L, 2L), .Label = c("0", "1", "2"), class = "factor")))
On Oct 18, 2010, at 4:09 PM, jim holtman wrote:
> files did not make it through the mailer. How did you attach them?
> try outputting the data using 'dput' and then attaching a '.txt' file,
> or just pasting them in the email.
>
> On Mon, Oct 18, 2010 at 2:40 PM, Gregory Ryslik <rsa...@comcast.net> wrote:
>> Hi Everyone,
>>
>> This is closer to what I need but this returns me a matrix where each
>> element is a factor. Instead I would want a list of lists. The first entry
>> of the list should equal the first column of the matrix that mapply makes,
>> the second entry to the second column etc...
>>
>> I've attached the two files that have all.predicted.values and max.growth
>> from dput to make for easy testing. Thanks again!
>>
>> Kind regards,
>> Greg
>>
>> On Oct 18, 2010, at 1:33 PM, Erich Neuwirth wrote:
>>
>>> You probably need mapply since you have 2 list of arguments which you want
>>> to use "in sync"
>>>
>>> mapply(function(x1,x2)x1[[x2]],all.predicted.values,max.growth)
>>>
>>> might be what you want.
>>>
>>>
>>>
>>> On Oct 18, 2010, at 5:17 PM, Gregory Ryslik wrote:
>>>
>>>> Unfortunately, that gives me null everywhere. Here's the data I have for
>>>> all.predicted.values and max.growth. Perhaps this will help. Thus I want
>>>> all.predicted.values[[1]][[4]] then all.predicted.values[[2]][3]] and then
>>>> all.predicted.values[[3]][[4]].
>>>>
>>>> I've attached what your statement outputs at the end.
>>>>
>>>> Thanks again!
>>>>
>>>> Browse[2]> max.growth
>>>> [[1]]
>>>> [1] 4
>>>>
>>>> [[2]]
>>>> [1] 3
>>>>
>>>> [[3]]
>>>> [1] 4
>>>>
>>>> Browse[2]> all.predicted.values
>>>> [[1]]
>>>> [[1]][[1]]
>>>> [1] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
>>>> 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
>>>> [55] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
>>>> 0 0 0 0 0 0 0 0 0 0 0
>>>> Levels: 0 1 2
>>>>
>>>> [[1]][[2]]
>>>> [1] 2 2 2 0 2 0 2 2 2 2 2 2 2 2 0 2 2 2 2 2 2 2 2 2 2 0 0 2 2 2 2 0 0 0 2
>>>> 2 0 0 2 2 0 2 2 2 2 2 0 2 2 2 0 2 2 0
>>>> [55] 0 0 2 0 2 0 0 0 0 2 2 2 2 0 2 2 2 0 2 2 0 0 2 2 2 2 2 2 2 0 0 0 2 0 2
>>>> 2 2 2 0 2 2 2 0 2 0 0
>>>> Levels: 0 1 2
>>>>
>>>> [[1]][[3]]
>>>> [1] 0 0 0 0 2 0 0 0 0 0 0 0 0 2 0 0 0 0 0 2 0 2 2 2 0 0 0 2 0 0 2 0 0 0 0
>>>> 0 0 0 2 0 0 0 0 0 2 2 0 0 0 2 0 0 0 0
>>>> [55] 0 0 2 0 2 0 0 0 0 2 2 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
>>>> 2 2 0 0 0 0 0 0 2 0 0
>>>> Levels: 0 1 2
>>>>
>>>> [[1]][[4]]
>>>> [1] 0 0 0 0 2 0 0 0 0 0 0 0 0 2 0 0 0 0 0 2 0 2 2 2 0 0 0 2 0 0 2 0 0 0 0
>>>> 0 0 0 2 0 0 0 0 0 2 2 0 0 0 2 0 0 0 0
>>>> [55] 0 0 2 0 2 0 0 0 0 2 2 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
>>>> 2 2 0 0 0 0 0 0 2 0 0
>>>> Levels: 0 1 2
>>>>
>>>>
>>>> [[2]]
>>>> [[2]][[1]]
>>>> [1] 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
>>>> 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
>>>> [55] 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
>>>> 2 2 2 2 2 2 2 2 2 2 2
>>>> Levels: 0 1 2
>>>>
>>>> [[2]][[2]]
>>>> [1] 2 2 2 2 1 2 2 2 2 2 1 2 2 2 2 1 2 1 2 2 2 2 2 2 2 2 2 2 1 2 2 2 2 2 1
>>>> 2 2 2 1 2 2 1 1 2 2 2 2 2 2 2 2 1 2 2
>>>> [55] 2 2 2 2 1 2 2 2 2 1 2 2 1 1 1 2 2 2 1 2 1 2 1 2 1 2 2 2 1 1 2 2 1 2 2
>>>> 1 1 2 1 1 1 2 2 1 2 2
>>>> Levels: 0 1 2
>>>>
>>>> [[2]][[3]]
>>>> [1] 2 2 2 0 1 2 2 2 2 2 1 2 2 2 0 1 2 1 2 2 2 2 2 2 2 0 0 2 1 2 2 2 0 0 1
>>>> 2 0 0 1 2 0 1 1 2 2 2 0 2 2 2 0 1 2 2
>>>> [55] 0 2 2 2 1 0 0 0 0 1 2 2 1 1 1 2 2 0 1 2 1 0 1 2 1 2 2 2 1 1 2 2 1 2 2
>>>> 1 1 2 1 1 1 2 2 1 0 2
>>>> Levels: 0 1 2
>>>>
>>>>
>>>> [[3]]
>>>> [[3]][[1]]
>>>> [1] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
>>>> 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
>>>> [55] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
>>>> 0 0 0 0 0 0 0 0 0 0 0
>>>> Levels: 0 1 2
>>>>
>>>> [[3]][[2]]
>>>> [1] 2 2 2 0 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 0 0 2 2 2 2 2 0 0 2
>>>> 2 2 0 2 2 0 2 2 2 2 2 0 2 2 2 0 2 2 2
>>>> [55] 0 2 2 2 2 2 0 0 2 2 2 2 2 2 2 2 2 0 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
>>>> 2 2 2 2 2 2 2 2 2 2 2
>>>> Levels: 0 1 2
>>>>
>>>> [[3]][[3]]
>>>> [1] 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 1 1 1 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1
>>>> 0 0 0 1 0 0 1 1 0 0 0 0 0 0 0 0 1 0 0
>>>> [55] 0 0 0 0 1 0 0 0 0 1 0 0 1 1 1 0 0 0 1 0 1 1 1 0 1 0 0 0 1 1 0 0 1 0 0
>>>> 1 1 0 1 1 1 0 0 1 1 0
>>>> Levels: 0 1 2
>>>>
>>>> [[3]][[4]]
>>>> [1] 2 2 2 0 1 0 2 2 0 2 1 2 2 0 0 1 1 1 1 0 2 0 0 0 2 0 0 0 1 2 0 0 0 0 1
>>>> 2 0 0 1 2 0 1 1 2 0 0 0 2 2 0 0 1 2 0
>>>> [55] 0 0 0 0 1 0 0 0 0 1 0 2 1 1 1 2 0 0 1 2 1 1 1 2 1 2 2 2 1 1 0 0 1 0 2
>>>> 1 1 2 1 1 1 2 0 1 1 0
>>>> Levels: 0 1 2
>>>>
>>>>
>>>> Browse[2]>
>>>> predicted.values.for.max.growth<-diag(sapply(all.predicted.values,'[[','max.growth'))
>>>> Browse[2]> predicted.values.for.max.growth
>>>> [[1]]
>>>> NULL
>>>>
>>>> [[2]]
>>>> [1] 0
>>>>
>>>> [[3]]
>>>> [1] 0
>>>>
>>>> [[4]]
>>>> [1] 0
>>>>
>>>> [[5]]
>>>> NULL
>>>>
>>>> [[6]]
>>>> [1] 0
>>>>
>>>> [[7]]
>>>> [1] 0
>>>>
>>>> [[8]]
>>>> [1] 0
>>>>
>>>> [[9]]
>>>> NULL
>>>>
>>>>
>>>>
>>>> On Oct 18, 2010, at 11:08 AM, Henrique Dallazuanna wrote:
>>>>
>>>>> Try this:
>>>>>
>>>>> diag(sapply(all.predicted.values, '[[', 'max.growth'))
>>>>>
>>>>>
>>>>> On Mon, Oct 18, 2010 at 12:59 PM, Gregory Ryslik <rsa...@comcast.net>
>>>>> wrote:
>>>>> Hi,
>>>>>
>>>>> I have a list of n items and the ith element has m_i elements within it.
>>>>>
>>>>> I want to do something like:
>>>>>
>>>>> predicted.values<- lapply(all.predicted.values,'[[',max.growth[[i]])
>>>>>
>>>>> Where max.growth[[i]] is the element I want to extract from each of the
>>>>> ith predicted elements. Thus, for example, I want to extract the
>>>>> max.growth[[1]] element from all.predicted.values[[1]] (which is itself
>>>>> a list). Then I want to extract max.growth[[2]] element from
>>>>> all.predicted.values[[2]].
>>>>>
>>>>> I realize I can do this with a for loop but then if I can do this as one
>>>>> line that would be preferable.
>>>>>
>>>>> Thanks!
>>>>>
>>>>> Greg
>>>>> [[alternative HTML version deleted]]
>>>>>
>>>>> ______________________________________________
>>>>> R-help@r-project.org mailing list
>>>>> https://stat.ethz.ch/mailman/listinfo/r-help
>>>>> PLEASE do read the posting guide
>>>>> http://www.R-project.org/posting-guide.html
>>>>> and provide commented, minimal, self-contained, reproducible code.
>>>>>
>>>>>
>>>>>
>>>>> --
>>>>> Henrique Dallazuanna
>>>>> Curitiba-Paraná-Brasil
>>>>> 25° 25' 40" S 49° 16' 22" O
>>>>
>>>>
>>>> [[alternative HTML version deleted]]
>>>>
>>>> ______________________________________________
>>>> R-help@r-project.org mailing list
>>>> https://stat.ethz.ch/mailman/listinfo/r-help
>>>> PLEASE do read the posting guide
>>>> http://www.R-project.org/posting-guide.html
>>>> and provide commented, minimal, self-contained, reproducible code.
>>>
>>> --
>>> Erich Neuwirth
>>> Didactic Center for Computer Science and Institute for Scientific Computing
>>> University of Vienna
>>>
>>>
>>>
>>>
>>
>> ______________________________________________
>> R-help@r-project.org mailing list
>> https://stat.ethz.ch/mailman/listinfo/r-help
>> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
>> and provide commented, minimal, self-contained, reproducible code.
>>
>
>
>
> --
> Jim Holtman
> Cincinnati, OH
> +1 513 646 9390
>
> What is the problem that you are trying to solve?
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