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2008-Jul-06 06:13 UTC

[R] lattice question

I'm creating a lattice barchart based off a pretty complicated data 
structure. The barchart comes out quite nice ( thanks
to lattice ) but the problem is that the horizontal axis comes out all 
scrunched because the barchart doesn't know that the intervals
of Var.1  are really "associated" with the conditioning variable
Var.2.
Therefore,  all the intervals of Var.1 are put on the horizontal axis of 
each
plot whereas the horizontal axis for each plot should only contain the 
intervals ( Var.1 values ) that are on the same row as Var.2.

What I'm saying probably doesn't make that much sense but, if someone 
ran the code below, and looked at the structure of the data, I think it 
would become clearer. Basically, I need a way to tell lattice that 
subsets of Var.1 should be on each horizontal axis, not the whole of 
Var.1.

Thanks to anyone who could take the time to look at the code below.  I 
think I have to somehow use subscripts  or somehow reshape the dataset 
but I don't know the lattice package well enough to figure out the 
former or the latter.  I spent today trying but with no success. 
Thanks.

#DATA STRUCTURE CODE
 
#===============================================================================
pdata<-structure(list(Var.1 = structure(c(1L, 2L, 3L, 4L, 5L, 6L, 7L,
1L, 2L, 3L, 4L, 5L, 6L, 7L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 1L, 2L,
3L, 4L, 5L, 6L, 7L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 1L, 2L, 3L, 4L,
5L, 6L, 7L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 1L, 2L, 3L, 4L, 5L, 6L,
7L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 1L,
2L, 3L, 4L, 5L, 6L, 7L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L,
11L, 12L, 13L, 14L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 8L, 9L,
10L, 11L, 12L, 13L, 14L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 8L,
9L, 10L, 11L, 12L, 13L, 14L, 8L, 9L, 10L, 11L, 12L, 13L, 14L,
8L, 9L, 10L, 11L, 12L, 13L, 14L, 8L, 9L, 10L, 11L, 12L, 13L,
14L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 8L, 9L, 10L, 11L, 12L,
13L, 14L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 8L, 9L, 10L, 11L,
12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 15L, 16L, 17L,
18L, 19L, 20L, 21L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 15L, 16L,
17L, 18L, 19L, 20L, 21L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 15L,
16L, 17L, 18L, 19L, 20L, 21L, 15L, 16L, 17L, 18L, 19L, 20L, 21L,
15L, 16L, 17L, 18L, 19L, 20L, 21L, 15L, 16L, 17L, 18L, 19L, 20L,
21L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 15L, 16L, 17L, 18L, 19L,
20L, 21L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 24L, 25L,
26L, 27L, 28L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 22L, 23L, 24L,
25L, 26L, 27L, 28L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 22L, 23L,
24L, 25L, 26L, 27L, 28L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 22L,
23L, 24L, 25L, 26L, 27L, 28L, 22L, 23L, 24L, 25L, 26L, 27L, 28L,
22L, 23L, 24L, 25L, 26L, 27L, 28L, 22L, 23L, 24L, 25L, 26L, 27L,
28L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 22L, 23L, 24L, 25L, 26L,
27L, 28L), .Label = c("(-0.7,-0.157]", "(-0.157,-0.0798]", 
"(-0.0798,-0.0194]",
"(-0.0194,0.039]", "(0.039,0.102]",
"(0.102,0.184]", "(0.184,0.847]",
"(-0.656,-0.127]", "(-0.127,-0.0627]",
"(-0.0627,-0.0122]",
"(-0.0122,0.0344]",
"(0.0344,0.0858]", "(0.0858,0.151]",
"(0.151,0.767]", "(-0.56,-0.107]",
"(-0.107,-0.0511]", "(-0.0511,-0.0103]",
"(-0.0103,0.031]",
"(0.031,0.078]",
"(0.078,0.137]", "(0.137,0.702]",
"(-0.549,-0.104]", "(-0.104,-0.0489]",
"(-0.0489,-0.00959]", "(-0.00959,0.0296]",
"(0.0296,0.0764]",
"(0.0764,0.134]", "(0.134,0.679]"), class =
"factor"), Var.2 =
structure(c(1L,
1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
4L, 4L, 4L, 4L, 4L, 4L, 4L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L,
4L, 4L, 4L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
4L, 4L, 4L, 4L, 4L, 4L, 4L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L,
4L, 4L, 4L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
4L, 4L, 4L, 4L, 4L, 4L, 4L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L,
4L, 4L, 4L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L), .Label = 
c("VNR",
"NR", "PR", "VPR"), class = "factor"),
Var.3 = 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, 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, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 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, 3L, 3L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 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, 3L,
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 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, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L), .Label = 
c("Negative",
"Neutral", "Positive"), class = "factor"), value =
c(153L, 157L,
151L, 152L, 129L, 129L, 89L, 134L, 129L, 126L, 125L, 106L, 108L,
120L, 148L, 109L, 128L, 123L, 132L, 111L, 142L, 139L, 146L, 156L,
153L, 167L, 123L, 161L, 177L, 178L, 163L, 175L, 140L, 141L, 143L,
217L, 206L, 185L, 192L, 203L, 196L, 190L, 195L, 192L, 217L, 210L,
181L, 197L, 222L, 123L, 168L, 156L, 169L, 178L, 178L, 149L, 181L,
175L, 177L, 168L, 153L, 179L, 139L, 156L, 142L, 115L, 135L, 143L,
164L, 158L, 111L, 119L, 131L, 120L, 160L, 141L, 161L, 123L, 135L,
152L, 135L, 164L, 191L, 183L, 81L, 94L, 74L, 90L, 77L, 62L, 57L,
74L, 71L, 71L, 77L, 72L, 63L, 77L, 83L, 63L, 68L, 83L, 71L, 81L,
73L, 70L, 81L, 91L, 91L, 78L, 93L, 75L, 71L, 64L, 62L, 51L, 56L,
47L, 51L, 93L, 66L, 74L, 67L, 70L, 66L, 71L, 60L, 71L, 79L, 73L,
96L, 81L, 89L, 54L, 63L, 52L, 48L, 48L, 57L, 69L, 101L, 109L,
89L, 74L, 96L, 97L, 96L, 92L, 84L, 88L, 82L, 76L, 78L, 88L, 76L,
69L, 83L, 84L, 79L, 76L, 62L, 58L, 79L, 83L, 94L, 95L, 113L,
107L, 53L, 45L, 34L, 39L, 42L, 38L, 34L, 41L, 28L, 30L, 36L,
48L, 35L, 28L, 31L, 29L, 45L, 45L, 45L, 48L, 39L, 52L, 43L, 41L,
42L, 44L, 38L, 44L, 24L, 26L, 22L, 12L, 13L, 17L, 20L, 28L, 28L,
32L, 25L, 25L, 35L, 28L, 24L, 24L, 34L, 19L, 28L, 30L, 28L, 17L,
18L, 20L, 15L, 17L, 21L, 18L, 54L, 48L, 43L, 46L, 39L, 47L, 52L,
38L, 51L, 35L, 57L, 50L, 43L, 29L, 26L, 38L, 44L, 51L, 39L, 31L,
52L, 40L, 50L, 49L, 41L, 38L, 45L, 57L, 46L, 21L, 32L, 19L, 26L,
27L, 33L, 23L, 27L, 20L, 26L, 35L, 21L, 19L, 24L, 21L, 42L, 37L,
23L, 30L, 20L, 29L, 30L, 25L, 37L, 26L, 27L, 35L, 13L, 12L, 6L,
8L, 12L, 10L, 11L, 17L, 20L, 17L, 16L, 23L, 19L, 13L, 15L, 14L,
21L, 15L, 18L, 19L, 13L, 13L, 17L, 6L, 13L, 7L, 10L, 16L, 33L,
28L, 34L, 29L, 28L, 26L, 44L, 23L, 39L, 34L, 23L, 26L, 33L, 26L,
18L, 32L, 20L, 36L, 32L, 32L, 18L, 31L, 25L, 28L, 27L, 29L, 31L,
38L), cap = c(15193749250, 15193749250, 15193749250, 15193749250,
15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
15193749250, 15193749250), group = 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,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 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 = "ZMH.NYSE", 
class = "factor"),
     wt = 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, 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, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
     3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
     3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
     3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
     3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
     3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
     3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
     4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
     4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
     4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
     4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
     4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L), .Label = c("5.5.5",
     "10.10.10", "20.20.20", "30.30.30"), class =
"factor")), .Names =
c("Var.1",
"Var.2", "Var.3", "value", "cap",
"group", "wt"), row.names = c(NA,
336L), class = "data.frame")

print(str(pdata))
print(pdata)

# PLOTTING CODE
 
#===============================================================================
pdata$value[!is.finite(pdata$value)] <- 0

print(barchart(value ~ Var.1|Var.2*wt, group=Var.3, 
data=pdata,stack=TRUE,
             layout=c(4,4),
             scales=list(x=list(rot=90),y=list(relation="free")),
             auto.key=list(columns=3)))

Felix Andrews

2008-Jul-06 09:16 UTC

head link

[R] lattice question

I think you want
scales = list(x = list(relation="free"))


On Sun, Jul 6, 2008 at 4:13 PM,  <markleeds at verizon.net>
wrote:> I'm creating a lattice barchart based off a pretty complicated data
> structure. The barchart comes out quite nice ( thanks
> to lattice ) but the problem is that the horizontal axis comes out all
> scrunched because the barchart doesn't know that the intervals
> of Var.1  are really "associated" with the conditioning variable
Var.2.
> Therefore,  all the intervals of Var.1 are put on the horizontal axis of
> each
> plot whereas the horizontal axis for each plot should only contain the
> intervals ( Var.1 values ) that are on the same row as Var.2.
>
> What I'm saying probably doesn't make that much sense but, if
someone ran
> the code below, and looked at the structure of the data, I think it would
> become clearer. Basically, I need a way to tell lattice that subsets of
> Var.1 should be on each horizontal axis, not the whole of Var.1.
>
> Thanks to anyone who could take the time to look at the code below.  I
think
> I have to somehow use subscripts  or somehow reshape the dataset but I
don't
> know the lattice package well enough to figure out the former or the
latter.
>  I spent today trying but with no success. Thanks.
>
> #DATA STRUCTURE CODE
>
>
#===============================================================================>
> pdata<-structure(list(Var.1 = structure(c(1L, 2L, 3L, 4L, 5L, 6L, 7L,
> 1L, 2L, 3L, 4L, 5L, 6L, 7L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 1L, 2L,
> 3L, 4L, 5L, 6L, 7L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 1L, 2L, 3L, 4L,
> 5L, 6L, 7L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 1L, 2L, 3L, 4L, 5L, 6L,
> 7L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 1L,
> 2L, 3L, 4L, 5L, 6L, 7L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L,
> 11L, 12L, 13L, 14L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 8L, 9L,
> 10L, 11L, 12L, 13L, 14L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 8L,
> 9L, 10L, 11L, 12L, 13L, 14L, 8L, 9L, 10L, 11L, 12L, 13L, 14L,
> 8L, 9L, 10L, 11L, 12L, 13L, 14L, 8L, 9L, 10L, 11L, 12L, 13L,
> 14L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 8L, 9L, 10L, 11L, 12L,
> 13L, 14L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 8L, 9L, 10L, 11L,
> 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 15L, 16L, 17L,
> 18L, 19L, 20L, 21L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 15L, 16L,
> 17L, 18L, 19L, 20L, 21L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 15L,
> 16L, 17L, 18L, 19L, 20L, 21L, 15L, 16L, 17L, 18L, 19L, 20L, 21L,
> 15L, 16L, 17L, 18L, 19L, 20L, 21L, 15L, 16L, 17L, 18L, 19L, 20L,
> 21L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 15L, 16L, 17L, 18L, 19L,
> 20L, 21L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 24L, 25L,
> 26L, 27L, 28L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 22L, 23L, 24L,
> 25L, 26L, 27L, 28L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 22L, 23L,
> 24L, 25L, 26L, 27L, 28L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 22L,
> 23L, 24L, 25L, 26L, 27L, 28L, 22L, 23L, 24L, 25L, 26L, 27L, 28L,
> 22L, 23L, 24L, 25L, 26L, 27L, 28L, 22L, 23L, 24L, 25L, 26L, 27L,
> 28L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 22L, 23L, 24L, 25L, 26L,
> 27L, 28L), .Label = c("(-0.7,-0.157]",
"(-0.157,-0.0798]",
> "(-0.0798,-0.0194]",
> "(-0.0194,0.039]", "(0.039,0.102]",
"(0.102,0.184]", "(0.184,0.847]",
> "(-0.656,-0.127]", "(-0.127,-0.0627]",
"(-0.0627,-0.0122]",
> "(-0.0122,0.0344]",
> "(0.0344,0.0858]", "(0.0858,0.151]",
"(0.151,0.767]", "(-0.56,-0.107]",
> "(-0.107,-0.0511]", "(-0.0511,-0.0103]",
"(-0.0103,0.031]", "(0.031,0.078]",
> "(0.078,0.137]", "(0.137,0.702]",
"(-0.549,-0.104]", "(-0.104,-0.0489]",
> "(-0.0489,-0.00959]", "(-0.00959,0.0296]",
"(0.0296,0.0764]",
> "(0.0764,0.134]", "(0.134,0.679]"), class =
"factor"), Var.2 > structure(c(1L,
> 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L,
> 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 1L, 1L, 1L, 1L, 1L,
> 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
> 4L, 4L, 4L, 4L, 4L, 4L, 4L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L,
> 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L,
> 4L, 4L, 4L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L,
> 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 1L,
> 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L,
> 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 1L, 1L, 1L, 1L, 1L,
> 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
> 4L, 4L, 4L, 4L, 4L, 4L, 4L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L,
> 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L,
> 4L, 4L, 4L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L,
> 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 1L,
> 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L,
> 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 1L, 1L, 1L, 1L, 1L,
> 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
> 4L, 4L, 4L, 4L, 4L, 4L, 4L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L,
> 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L,
> 4L, 4L, 4L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L,
> 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L), .Label >
c("VNR",
> "NR", "PR", "VPR"), class =
"factor"), Var.3 = 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, 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, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
> 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
> 3L, 3L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 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, 3L, 3L, 3L, 3L, 3L,
> 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
> 3L, 3L, 3L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
> 1L, 1L, 1L, 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, 3L,
> 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
> 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 1L, 1L,
> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 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, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
> 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L), .Label >
c("Negative",
> "Neutral", "Positive"), class = "factor"),
value = c(153L, 157L,
> 151L, 152L, 129L, 129L, 89L, 134L, 129L, 126L, 125L, 106L, 108L,
> 120L, 148L, 109L, 128L, 123L, 132L, 111L, 142L, 139L, 146L, 156L,
> 153L, 167L, 123L, 161L, 177L, 178L, 163L, 175L, 140L, 141L, 143L,
> 217L, 206L, 185L, 192L, 203L, 196L, 190L, 195L, 192L, 217L, 210L,
> 181L, 197L, 222L, 123L, 168L, 156L, 169L, 178L, 178L, 149L, 181L,
> 175L, 177L, 168L, 153L, 179L, 139L, 156L, 142L, 115L, 135L, 143L,
> 164L, 158L, 111L, 119L, 131L, 120L, 160L, 141L, 161L, 123L, 135L,
> 152L, 135L, 164L, 191L, 183L, 81L, 94L, 74L, 90L, 77L, 62L, 57L,
> 74L, 71L, 71L, 77L, 72L, 63L, 77L, 83L, 63L, 68L, 83L, 71L, 81L,
> 73L, 70L, 81L, 91L, 91L, 78L, 93L, 75L, 71L, 64L, 62L, 51L, 56L,
> 47L, 51L, 93L, 66L, 74L, 67L, 70L, 66L, 71L, 60L, 71L, 79L, 73L,
> 96L, 81L, 89L, 54L, 63L, 52L, 48L, 48L, 57L, 69L, 101L, 109L,
> 89L, 74L, 96L, 97L, 96L, 92L, 84L, 88L, 82L, 76L, 78L, 88L, 76L,
> 69L, 83L, 84L, 79L, 76L, 62L, 58L, 79L, 83L, 94L, 95L, 113L,
> 107L, 53L, 45L, 34L, 39L, 42L, 38L, 34L, 41L, 28L, 30L, 36L,
> 48L, 35L, 28L, 31L, 29L, 45L, 45L, 45L, 48L, 39L, 52L, 43L, 41L,
> 42L, 44L, 38L, 44L, 24L, 26L, 22L, 12L, 13L, 17L, 20L, 28L, 28L,
> 32L, 25L, 25L, 35L, 28L, 24L, 24L, 34L, 19L, 28L, 30L, 28L, 17L,
> 18L, 20L, 15L, 17L, 21L, 18L, 54L, 48L, 43L, 46L, 39L, 47L, 52L,
> 38L, 51L, 35L, 57L, 50L, 43L, 29L, 26L, 38L, 44L, 51L, 39L, 31L,
> 52L, 40L, 50L, 49L, 41L, 38L, 45L, 57L, 46L, 21L, 32L, 19L, 26L,
> 27L, 33L, 23L, 27L, 20L, 26L, 35L, 21L, 19L, 24L, 21L, 42L, 37L,
> 23L, 30L, 20L, 29L, 30L, 25L, 37L, 26L, 27L, 35L, 13L, 12L, 6L,
> 8L, 12L, 10L, 11L, 17L, 20L, 17L, 16L, 23L, 19L, 13L, 15L, 14L,
> 21L, 15L, 18L, 19L, 13L, 13L, 17L, 6L, 13L, 7L, 10L, 16L, 33L,
> 28L, 34L, 29L, 28L, 26L, 44L, 23L, 39L, 34L, 23L, 26L, 33L, 26L,
> 18L, 32L, 20L, 36L, 32L, 32L, 18L, 31L, 25L, 28L, 27L, 29L, 31L,
> 38L), cap = c(15193749250, 15193749250, 15193749250, 15193749250,
> 15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
> 15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
> 15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
> 15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
> 15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
> 15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
> 15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
> 15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
> 15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
> 15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
> 15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
> 15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
> 15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
> 15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
> 15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
> 15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
> 15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
> 15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
> 15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
> 15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
> 15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
> 15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
> 15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
> 15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
> 15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
> 15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
> 15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
> 15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
> 15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
> 15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
> 15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
> 15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
> 15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
> 15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
> 15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
> 15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
> 15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
> 15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
> 15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
> 15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
> 15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
> 15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
> 15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
> 15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
> 15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
> 15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
> 15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
> 15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
> 15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
> 15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
> 15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
> 15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
> 15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
> 15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
> 15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
> 15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
> 15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
> 15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
> 15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
> 15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
> 15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
> 15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
> 15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
> 15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
> 15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
> 15193749250, 15193749250, 15193749250, 15193749250, 15193749250,
> 15193749250, 15193749250), group = 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,
> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
> 1L, 1L, 1L, 1L, 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 =
"ZMH.NYSE", class
> = "factor"),
>    wt = 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, 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, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
>    3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
>    3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
>    3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
>    3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
>    3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
>    3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
>    4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
>    4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
>    4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
>    4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
>    4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L), .Label =
c("5.5.5",
>    "10.10.10", "20.20.20", "30.30.30"), class
= "factor")), .Names > c("Var.1",
> "Var.2", "Var.3", "value", "cap",
"group", "wt"), row.names = c(NA,
> 336L), class = "data.frame")
>
> print(str(pdata))
> print(pdata)
>
> # PLOTTING CODE
>
>
#===============================================================================>
> pdata$value[!is.finite(pdata$value)] <- 0
>
> print(barchart(value ~ Var.1|Var.2*wt, group=Var.3, data=pdata,stack=TRUE,
>            layout=c(4,4),
>            scales=list(x=list(rot=90),y=list(relation="free")),
>            auto.key=list(columns=3)))
>
> ______________________________________________
> R-help at 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.
>


-- 
Felix Andrews / ???
PhD candidate
Integrated Catchment Assessment and Management Centre
The Fenner School of Environment and Society
The Australian National University (Building 48A), ACT 0200
Beijing Bag, Locked Bag 40, Kingston ACT 2604
http://www.neurofractal.org/felix/
3358 543D AAC6 22C2 D336 80D9 360B 72DD 3E4C F5D8

Troels Ring

2008-Jul-29 15:29 UTC

head link

[R] lattice question

Dear friends - I have a plot of simulated data to compare to the 
observed and want the simulated to appear accumulated so that a darker 
grey corresponds to more lines of simulated data, but on top of that I 
want the measured values (Na) to be very visible. The code below meets 
only few of the desires. Hope someone will give me help to master the 
panel formation.
Best wishes
Troels

xyplot(Na+yrep[,1:100]~time|as.factor(ID),yrepbug,type=c("g","o"),
span=0.75,ylab="[Na]")

-- 

Troels Ring - -
Department of nephrology - - 
Aalborg Hospital 9100 Aalborg, Denmark - -
+45 99326629 - -
tring at gvdnet.dk

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