Given a 5 x 5 Grid comprising of tiles numbered from 1 to 25 and a set of 5 start-end point pairs.
For each pair,find a path from the start point to the end point.
The paths should meet the below conditions:
a) Only Horizontal and Vertical moves allowed.
b) No two paths should overlap.
c) Paths should cover the entire grid
Input consist of 5 lines.
Each line contains two space-separated integers,Starting and Ending point.
Output: Print 5 lines. Each line consisting of space-separated integers,the path for the corresponding start-end pair. Assume that such a path Always exists. In case of Multiple Solution,print any one of them.
Sample Input
1 22
4 17
5 18
9 13
20 23
Sample Output
1 6 11 16 21 22
4 3 2 7 12 17
5 10 15 14 19 18
9 8 13
20 25 24 23
i think there should be restriction or it lacks some more information about the input ( start point and endpoint)
because if we take following input then covering whole grid is not possible
1 22,
6 7,
11 12,
16 17,
8 9
Related
I need to find the the size of bin with maximum and minimum element. I am using histc function in MATLAB.
Here is what I am doing,
A=[1 2 3 11 22 3 4 55 6 7 2 33 44 5 22]
edges = [10 inf];
N = histc(A,edges)
it gives N=[6,0]; means there are 6 elements having values greater than 10. Now I want to count what is the maximum count in a bin for my condition.
here it should be 2 as there are two instances where we have two integers satisfying my condition 11 22 and 33 44
How to count it in MATLAB.
Here you go;
A=[1 2 3 11 22 3 4 55 6 7 2 33 44 5 22]
arr=diff([0 (find(~(A>10))) numel(A)+1]) -1;
arr(find(arr(1,:)==0))=[];
largest=max(arr); % longest sequence of occurences of numbers > 10
smallest=min(arr); % smallest sequence of occurences of numbers > 10
Cheers!!
i have extracted 23 sentences from a text file which are divided and shown in separate line each sentence is given a number in ascending order {1,2,3,...}, code i used for this is as follows:
sentences = regexp(F,'\S.*?[\.\!\?]','match')
char(sentences)
now i did some processing and got filtered answer which shows a subset of sentences as shown below:
result = 1 4 5 9 11 14 16 17
the code i used for result is as follows:
result = unique([OccursTogether{:}]);
display(result)
now what i want to do is to show the sentences that are not present in the result variable for example the result i need is as follows:
result2 = 2 3 6 7 8 10 12 13 15 18 19 20 21 22 23
remember sentences is [1*N] cell where as result is simple array saving integers.
The function you are looking for is setdiff:
%// Create an array containing the indices of all the sentences
AllSentences = 1:23;
%// Indices of sentences present
result = [1 4 5 9 11 14 16 17]
%// And not present
NotPresent = setdiff(AllSentences,result)
NotPresent =
Columns 1 through 13
2 3 6 7 8 10 12 13 15 18 19 20 21
Columns 14 through 15
22 23
I'm not sure to understand what is a cell array and what is not, but for cell arrays you can convert them to numeric arrays using cell2mat and apply the same methodology.
Eg:
AllSentences = {1:23};
NotPresent = setdiff(cell2mat(AllSentences),result)
I have the following example dataset which consists of the # of fish caught per check of a net. The nets are not checked at uniform intervals. The day of the check is denoted in julian days as well as the number of days the net had been fishing since last checked (or since it's deployment in the case of the first check)
http://textuploader.com/9ybp
Site_Number Check_Day_Julian Set_Duration_Days Fish_Caught
2 5 3 100
2 10 5 70
2 12 2 65
2 15 3 22
100 4 3 45
100 10 6 20
100 18 8 8
450 10 10 10
450 14 4 4
In any case, I would like to turn the raw data above into the following format:
http://textuploader.com/9y3t
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18
2 0 0 100 100 100 70 70 70 70 70 65 65 22 22 22 0 0 0
100 0 45 45 45 20 20 20 20 20 20 8 8 8 8 8 8 8 8
450 10 10 10 10 10 10 10 10 10 10 4 4 4 4 0 0 0 0
This is a matrix which assigns the # of fish caught during the period to EACH of the days that were within that period. The columns of the matrix are Julian days, the rows are site numbers.
I have tried to do this with some matrix functions but I have had much difficulty trying to populate all the fields that are within the time period, but I do not necessarily have a row of data for?
I had posted my small bit of code here, but upon reflection, my approach is quite archaic and a bit off point. Can anyone suggest a method to convert the data into the matrix provided? I've been scratching my head and googling all day but now I am stumped.
Cheers,
C
Two answers, the second one is faster but a bit low level.
Solution #1:
library(IRanges)
with(d, {
ir <- IRanges(end=Check_Day_Julian, width=Set_Duration_Days)
cov <- coverage(split(ir, Site_Number),
weight=split(Fish_Caught, Site_Number),
width=max(end(ir)))
do.call(rbind, lapply(cov, as.vector))
})
Solution #2:
with(d, {
ir <- IRanges(end=Check_Day_Julian, width=Set_Duration_Days)
site <- factor(Site_Number, unique(Site_Number))
m <- matrix(0, length(levels(site)), max(end(ir)))
ind <- cbind(rep(site, width(ir)), as.integer(ir))
m[ind] <- rep(Fish_Caught, width(ir))
m
})
I don't see a super obvious matrix transformation here. This is all i've got assuming the raw data is in a data.frame called dd
dd$Site_Number<-factor(dd$Site_Number)
mm<-matrix(0, nrow=nlevels(dd$Site_Number), ncol=18)
for(i in 1:nrow(dd)) {
mm[as.numeric(dd[i,1]), (dd[i,2]-dd[i,3]):dd[i,2] ] <- dd[i,4]
}
mm
This question already has answers here:
How to access the last value in a vector?
(12 answers)
Closed 10 years ago.
This may be redundant but I could not find a similar question on SO.
Is there a shortcut to getting the last n elements/entries in a vector or array without using the length of the vector in the calculation?
foo <- 1:23
> foo
[1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
Let say one wants the last 7 entities, I want to avoid this cumbersome syntax:
> foo[(length(foo)-6):length(foo)]
[1] 17 18 19 20 21 22 23
Python has foo[-7:]. Is there something similar in R? Thanks!
You want the tail function
foo <- 1:23
tail(foo, 5)
#[1] 19 20 21 22 23
tail(foo, 7)
#[1] 17 18 19 20 21 22 23
x <- 1:3
# If you ask for more than is currently in the vector it just
# returns the vector itself.
tail(x, 5)
#[1] 1 2 3
Along with head there are easy ways to grab everything except the last/first n elements of a vector as well.
x <- 1:10
# Grab everything except the first element
tail(x, -1)
#[1] 2 3 4 5 6 7 8 9 10
# Grab everything except the last element
head(x, -1)
#[1] 1 2 3 4 5 6 7 8 9
Not a good idea when you have the awesome tail function but here's an alternative:
n <- 3
rev(rev(foo)[1:n])
I'm preparing myself for the down votes.
So I have to decrypt a .txt file that is crypted with XOR code and with a repeated password that is unknown, and the goal is to discover the message.
Here are the things that I already know because of the professor:
First I need to find the length of the unknown password
The message has been altered and it doesn't have spaces (this may add a bit more difficulty because the space character has the highest frequency in a message)
Any ideas on how to solve this?
thx in advanced :)
First you need to find out the length of the password. You do this by assessing the Index of Coincidence or Kappa-test. XOR the ciphertext with itself shifted 1 step and count the number of characters that are the same (value 0). You get the Kappa value by dividing the result with the total number of characters minus 1. Shift one more time and again calculate the Kappa value. Shift the ciphertext as many times as needed until you discover the password length. If the length is 4 you should see something similar to this:
Offset Hits
-------------------------
1 2.68695%
2 2.36399%
3 3.79009%
4 6.74012%
5 3.6953%
6 1.81582%
7 3.82744%
8 6.03504%
9 3.60273%
10 1.98052%
11 3.83241%
12 6.5627%
As you see the Kappa value is significantly higher on multiples of 4 (4, 8 and 12) than the others. This suggests that the length of the password is 4.
Now that you have the password length you should again XOR the cipher text with itself but now you shift by multiples of the length. Why? Since the ciphertext looks like this:
THISISTHEPLAINTEXT <- Plaintext
PASSPASSPASSPASSPA <- Password
------------------
EJKELDOSOSKDOWQLAG <- Ciphertext
When two values which are the same are XOR:ed the result is 0:
EJKELDOSOSKDOWQLAG <- Ciphertext
EJKELDOSOSKDOWQLAG <- Ciphertext shifted 4.
Is in reality:
THISISTHEPLAINTEXT <- Plaintext
PASSPASSPASSPASSPA <- Password
THISISTHEPLAINTEXT <- Plaintext
PASSPASSPASSPASSPA <- Password
Which is:
THISISTHEPLAINTEXT <- Plaintext
THISISTHEPLAINTEXT <- Plaintext
As you see the password "disappears" and the plaintext is XOR:ed with itself.
So what can we do now then? You wrote that the spaces are removed. This makes it a bit harder to get the plaintext or password. But not at all impossible.
The following table shows the ciphertext values for all english characters:
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z
A 0
B 3 0
C 2 1 0
D 5 6 7 0
E 4 7 6 1 0
F 7 4 5 2 3 0
G 6 5 4 3 2 1 0
H 9 10 11 12 13 14 15 0
I 8 11 10 13 12 15 14 1 0
J 11 8 9 14 15 12 13 2 3 0
K 10 9 8 15 14 13 12 3 2 1 0
L 13 14 15 8 9 10 11 4 5 6 7 0
M 12 15 14 9 8 11 10 5 4 7 6 1 0
N 15 12 13 10 11 8 9 6 7 4 5 2 3 0
O 14 13 12 11 10 9 8 7 6 5 4 3 2 1 0
P 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 0
Q 16 19 18 21 20 23 22 25 24 27 26 29 28 31 30 1 0
R 19 16 17 22 23 20 21 26 27 24 25 30 31 28 29 2 3 0
S 18 17 16 23 22 21 20 27 26 25 24 31 30 29 28 3 2 1 0
T 21 22 23 16 17 18 19 28 29 30 31 24 25 26 27 4 5 6 7 0
U 20 23 22 17 16 19 18 29 28 31 30 25 24 27 26 5 4 7 6 1 0
V 23 20 21 18 19 16 17 30 31 28 29 26 27 24 25 6 7 4 5 2 3 0
W 22 21 20 19 18 17 16 31 30 29 28 27 26 25 24 7 6 5 4 3 2 1 0
X 25 26 27 28 29 30 31 16 17 18 19 20 21 22 23 8 9 10 11 12 13 14 15 0
Y 24 27 26 29 28 31 30 17 16 19 18 21 20 23 22 9 8 11 10 13 12 15 14 1 0
Z 27 24 25 30 31 28 29 18 19 16 17 22 23 20 21 10 11 8 9 14 15 12 13 2 3 0
What does this mean then? If an A and a B is XOR:ed then the resulting value is 3. E and P will result in 21. Etc. OK but how will this help you?
Remember that the plaintext is XOR:ed with itself shifted by multiples of the password length. For each value you can check the above table and determine what combinations that position could have. Lets say the value is 25 then the two characters that resulted in the value 25 could be one of the following combinations:(I-P), (H-Q), (K-R), (J-S), (M-T), (L-U), (O-V), (N-W), (A-X) or (C-Z). But which one? Now you do more shifts and look up the corresponding values in the table again for each position. Next time the value might be 7 and since you already have a list of possible character combinations you only check against them. At the next two shifts the values are 3 and 1. Now you can determine that the character is W since that is the only common character in each shift, (N-W), (P-W), (T-W), (V-W). You can do this for most positions.
You will not get all the plaintext but you will get enough characters to discover the password. Take the known characters and XOR them in the correct position in the ciphertext. This will yield the password. The number of known characters you need atleast is the number of characters in the password if they are at the "correct" positions in regards to the password.
Good luck!
you should look at cracking a vigenere chiffre, especially at auto-correlation. The latter will help you finding out the length of the password and the rest is usually just bruteforcing on the normal distribution of letters (where the most common one is the letter e in the english language).
Although spaces are the most common characters and make decryptions like this easy, the other character also have different frequencies. For example, see this Wikipedia article. If you've got enough encrypted text and the password length isn't too large, it might just be enough to find out the most common bytes in the encrypted text. They will most likely be the encrypted versions of e that has the highest frequency in english texts.
This alone won't give you the decrypted text, but it's very likely you can find out the password length and (part of) the password itself with it. For example, let's assume the most frequent encrypted bytes are
w x m z y
with almost the same frequency and there's a significant drop in frequency after the last one. This will tell you two things:
The password length most likely is 5, because statistically, all encrypted e will be equally likely. EDIT: OK, this isn't correct, it will be 5 or above because the password can contain the same character multiple times.
The password will be some permutation of (w x m z y XOR e e e e e) - you can use the byte offsets modulo the password length to get the correct permutation.
EDIT: The same character occuring in the password multiple times makes things a bit harder, but you'll most likely be able to identify those because as I said, encrypted versions of e will cluster around frequency f - now if the character occurs n times, it will have a frequency near n*f.
The most common three letter trigram in English (assuming the language is probably English) is "the". Place "the" at all possible points on your cyphertext to derive a possible 3 characters of the key. Try each possible key fragment at all other possible positions on the cyphertext and see what you get. For example, "qzg" is unlikely to be correct, but "fen" could be. Look at the spacing between possible positions to derive the key length. With a key length and a key fragment you can place a lot more of the key.
As Lars said, look at ways of decrypting Vigenère, which is effectively what you have here.