I am using library(network) and have the following edge list to generate a network.
Commands used:
library(network)
edgelist<-read.table("Filename")
net<-network(edgelist)
plot(net)
what I observe is isolated nodes in the network plot! Can anyone help in deciphering the reason?? I used the same edgelist with Cytoscape. It works perfect there. Why is it causing problem in R?
Following is the edgelist:
7 2
2 6
3 2
13 2
1 2
4 2
5 2
9 2
25 29
5 4
13 8
18 17
5 15
13 1
22 8
25 12
21 11
17 28
18 8
13 16
33 20
10 27
12 4
24 23
12 1
19 26
4 3
3 15
8 11
16 62
36 8
18 11
10 62
4 6
4 1
32 62
12 16
4 15
17 30
22 10
34 11
31 10
9 6
4 7
24 20
5 6
1 6
3 6
9 7
21 19
35 23
7 6
10 8
5 7
1 7
3 7
1 3
1 9
5 1
3 9
5 3
5 9
Found the reason! R network library requires node IDs to be in sequential order. One of the IDs was 62, while there was no node with an ID between 36 and 62. It ended up isolating those IDs as vertices..Once that problem was fixed, it worked well.
Related
I have an edgelist where I want to keep dyads that mutually selected each other (e.g., 1 -> 4 and 4 -> 1). However, in the final edgelist I only want to keep one row instead of both rows of the mutual dyads (e.g., only row 1 -> 4 not both rows 1 -> 4 and 4 -> 1). How do I achieve that?
Here is the dataset:
library(igraph)
ff <- as_data_frame(sample_gnm(10, 50, directed=TRUE))
ff
from to
1 1 10
2 1 3
3 1 4
4 1 5
5 1 6
6 1 7
7 1 8
8 2 1
9 2 3
10 2 8
11 2 9
12 3 1
13 3 2
14 3 10
15 3 4
16 3 5
17 3 6
18 3 8
19 3 9
20 4 3
21 4 10
22 5 1
23 5 2
24 5 3
25 5 4
26 6 2
27 6 3
28 6 4
29 6 5
30 7 3
31 7 5
32 7 6
33 7 10
34 7 8
35 8 1
36 8 2
37 8 4
38 8 5
39 8 10
40 9 1
41 9 2
42 9 3
43 9 4
44 9 5
45 9 7
46 10 1
47 10 3
48 10 4
49 10 8
50 10 9
cd <- which_mutual(g) #I know I can use `which_mutual` to identify the mutual dyads
ff[which(cd==1),] #but in the end this keeps both rows of the mutual dyads (e.g., 1 -> 4 and 4 -> 1)
from to
4 1 4
6 1 6
7 1 7
9 2 10
10 2 3
14 3 2
18 3 6
21 4 1
25 5 10
28 6 1
30 6 3
32 6 10
33 6 7
34 7 1
37 7 6
39 7 8
42 8 7
45 9 10
46 10 2
47 10 5
48 10 6
50 10 9
We may use duplicated to create a logical vector after sorting the elements by row
ff1 <- ff[which(cd==1),]
subset(ff1, !duplicated(cbind(pmin(from, to), pmax(from, to))))
could you guys help me?
I have a matrix like this. the first column and row are the IDs.
I need to sort it by column and row ID like this.
Thanks!
Two thoughts:
mat <- matrix(1:25, nr=5, dimnames=list(c('4',3,5,2,1), c('4',3,5,2,1)))
mat
# 4 3 5 2 1
# 4 1 6 11 16 21
# 3 2 7 12 17 22
# 5 3 8 13 18 23
# 2 4 9 14 19 24
# 1 5 10 15 20 25
If you want a strictly alphabetic ordering, then this will work:
mat[order(rownames(mat)),order(colnames(mat))]
# 1 2 3 4 5
# 1 25 20 10 5 15
# 2 24 19 9 4 14
# 3 22 17 7 2 12
# 4 21 16 6 1 11
# 5 23 18 8 3 13
This will not work well if the names are intended to be ordered numerically:
mat <- matrix(1:30, nr=3, dimnames=list(c('2',1,3), c('4',3,5,2,1,6,7,8,9,10)))
mat
# 4 3 5 2 1 6 7 8 9 10
# 2 1 4 7 10 13 16 19 22 25 28
# 1 2 5 8 11 14 17 20 23 26 29
# 3 3 6 9 12 15 18 21 24 27 30
mat[order(rownames(mat)),order(colnames(mat))]
# 1 10 2 3 4 5 6 7 8 9
# 1 14 29 11 5 2 8 17 20 23 26
# 2 13 28 10 4 1 7 16 19 22 25
# 3 15 30 12 6 3 9 18 21 24 27
(1, 10, 2, ...) For that, you need a slight modification:
mat[order(as.numeric(rownames(mat))),order(as.numeric(colnames(mat)))]
# 1 2 3 4 5 6 7 8 9 10
# 1 14 11 5 2 8 17 20 23 26 29
# 2 13 10 4 1 7 16 19 22 25 28
# 3 15 12 6 3 9 18 21 24 27 30
How do I generate a vector in the form
1 2 ... 19 20 19 ... 2 1
Is it possible using the c() function?
You can use seq as well as rev function for the desired purpose.
seq
> c(1:20, seq(19,1,-1))
[1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 19 18 17 16 15 14 13 12 11 10 9 8 7 6 5 4 3 2 1
As suggested by #jimbou,
> c(1:20, 19:1)
[1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 19 18 17 16 15 14 13 12 11 10 9 8 7 6 5 4 3 2 1
> c(1:20, rev(1:19))
[1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 19 18 17 16 15 14 13 12 11 10 9 8 7 6 5 4 3 2 1
I have a data frame consisting of the fluorescence read out of multiple cells tracked over time, for example:
Number=c(1,2,3,4,1,2,3,4,1,2,3,4,1,2,3,4)
Fluorescence=c(9,10,20,30,8,11,21,31,6,12,22,32,7,13,23,33)
df = data.frame(Number, Fluorescence)
Which gets:
Number Fluorescence
1 1 9
2 2 10
3 3 20
4 4 30
5 1 8
6 2 11
7 3 21
8 4 31
9 1 6
10 2 12
11 3 22
12 4 32
13 1 7
14 2 13
15 3 23
16 4 33
Number pertains to the cell number. What I want is to collate the fluorescence readout based on the cell number. The data.frame here has it counting 1-4, whereas really I want something like this:
Number Fluorescence
1 1 9
2 1 8
3 1 6
4 1 7
5 2 10
6 2 11
7 2 12
8 2 13
9 3 20
10 3 21
11 3 22
12 3 23
13 4 30
14 4 31
15 4 32
16 4 33
Or even more ideal would be having columns based on Number, then respective cell fluorescence:
1 2 3 4
1 9 10 20 30
2 8 11 21 31
3 6 12 22 32
4 7 13 23 33
I've used the which function to extract them one at a time:
Cell1=df[which(df[,1]==1),2]
But this would require me to write a line for each cell (of which there are hundreds).
Thank you for any help with this! Apologies that I'm still a bit of an R noob.
How about this:
library(tidyr);library(data.table)
number <- c(1,2,3,4,1,2,3,4,1,2,3,4,1,2,3,4)
fl <- c(9,10,20,30,8,11,21,31,6,12,22,32,7,13,23,33)
df <- data.table(number,fl)
df[, index:=1:.N, keyby=number]
df
number fl index
1: 1 9 1
2: 1 8 2
3: 1 6 3
4: 1 7 4
5: 2 10 1
6: 2 11 2
7: 2 12 3
8: 2 13 4
9: 3 20 1
10: 3 21 2
11: 3 22 3
12: 3 23 4
13: 4 30 1
14: 4 31 2
15: 4 32 3
16: 4 33 4
The index is added for the unique identifier in spread function from tidyr. Look this post for more information.
spread(df,number,fl)
index 1 2 3 4
1: 1 9 10 20 30
2: 2 8 11 21 31
3: 3 6 12 22 32
4: 4 7 13 23 33
I am new to R,I am trying to plot a cumulative frequency histogram(non-uniform bins) for a huge amount of data(few millions of positive numbers with a minimum value "1" and maximum value varies from data to data like for instance 1*10^6 or 1*10^5).I used this simple code to generate a histogram with the data.
for example:-sample data
[89601] 10 2 2 4 3 12 3 25 25 2
[89611] 5 5 5 2 23 22 14 8 13 10
[89621] 13 19 157 2 3 2 4 2 3 33
[89631] 22 2 14 9 2 3 3 3 8 2
[89641] 8 3 2 127 8 2 18 2 4 2
[89651] 2 13 3 34 8 2 6 10 3 7
[89661] 3 9 7 3 36 9 5 2 10 15
[89671] 7 2 23 2 2 2 2 7 6 25
[89681] 3 3 2 6 37 49 28 11 3 35
[89691] 2 2 8 3 3 2 2 4 3 12
[89701] 3 5 2 7 3 2 15 6 3 14
[89711] 13 5 3 2 2 8 34 4 4 65
[89721] 5 9 12 2 11 2 2 79 9 13
[89731] 2 66 2 9 10 22 11 2 6 3
[89741] 12 2 11 5 4 4 2 4 3 4
[89751] 2 8 9 3 2 2 84 7 11 10
[89761] 8 30 16 3 63 2 2 24 13 2
[89771] 11 37 2 9 21 21 10 2 2 49
[89781] 3 3 8 5 2 19 9 6 5 4
[89791] 4 2 9 2 10 33 5 4 2 2
[89801] 4 2 2 4 9 3 11 2 5 142
[89811] 17 2 11 4 2 8 26 2 9 8
[89821] 10 2 4 2 5 2 20 7 145 11
[89831] 22 19 8 14 18 39 3 2 3 3
[89841] 2 11 10 3 2 3 3 5 6 12
[89851] 17 5 3 8 2 2 2 2 2 5
[89861] 4 2 13 3 2 2 2 2 3 2
[89871] 4 3 21 2 6 2 8 9 7 14
[89881] 2 582 3 15 11 3 20 16 9 8
[89891] 6 2 6 7 3 20 17 2 9 5
[89901] 5 11 2 12 7 2 46 2 144 9
[89911] 2 3 36 25 3 2 16 2 2 119
[89921] 5 5 10 6 2 2 6 84 13 2
[89931] 2 6 6 2 17 3 7 4 102 48
data <- read.table("sample.txt", header=FALSE)
data <- hist(data$V1, breaks=length(data$V1), xlim=c(0,4000000))
plot(data)
when I did this I could get a histogram with all the data(positive numbers)on x axis and counts on y-axis.Then again I changed the limit of the x only upto the area of interest
plot(data, xlim=c(0,200000))
Like before a histogram is plotted,but using "plot" I couldn't define the number of bins and hence the histogram is not clear(not like bars which I want to be) and informative.
As I am new to this forum,I have no idea how to upload images,so I couldn't provide with the histogram.
Any suggestions would be very helpful.
For plotting histogram you can use hist() function just this way:
hist(data$V1, xlim=c(0,200000), breaks=100)
The breaks parameter shows, how many bars will be plotted. But this number is related to all plot, not to xlim you specified. So, at first it will make a histogram with given number of breakes and after that it will cut the part of plot you need.
But there is another way to plot the bars:
data <- read.table("sample.txt", header=FALSE)
data.hist <- hist(data$V1, breaks=length(data$V1), xlim=c(0,4000000))
plot(data.hist$counts, type='h')
The hist function returns an object which represents histogram parameters.
I assume, you are interested in "counts" field.
You can plot this info in histogram-like way by defining type='h'.