run-length-encoding

I want to compress a series of characters. For example if i type Input : FFFFFBBBBBBBCCBBBAABBGGGGGSSS (27 x 8 bits = 216 bits) Output: F5B7C2B3A2B2G5S3 (14 x 8 bits = 112bits) So far this is what i have, i can count the number of Characters in the Array. But the most important task is to count them in the same sequence. I can't seem to figure that out :( Ive stared doing C just a few weeks back, i have knowledge on Array, pointers, ASCII value but in any case can't seem to count these characters in a sequence. Ive try a bit of everything. This approach is no good but it the closest i came to

Is there a vectorised way to do the following? (shown by an example): input_lengths = [ 1 1 1 4 3 2 1 ] result = [ 1 2 3 4 4 4 4 5 5 5 6 6 7 ] I have spaced out the input_lengths so it is easy to understand how the result is obtained The resultant vector is of length: sum(lengths) . I currently calculate result using the following loop: result = ones(1, sum(input_lengths )); counter = 1; for i = 1:length(input_lengths) start_index = counter; end_index = counter + input_lengths (i) - 1; result(start_index:end_index) = i; counter = end_index + 1; end EDIT: I can also do this using arrayfun

The problem is to: Write a function (encode L) that takes a list of atoms L and run-length encodes the list such that the output is a list of pairs of the form (value length) where the first element is a value and the second is the number of times that value occurs in the list being encoded. For example: (encode '(1 1 2 4 4 8 8 8)) ---> '((1 2) (2 1) (4 2) (8 3)) This is the code I have so far: (define (encode lst) (cond ((null? lst) '()) (else ((append (list (car lst) (count lst 1)) (encode (cdr lst))))))) (define (count lst n) (cond ((null? lst) n) ((equal? (car lst) (car (cdr lst))) (count

I didn't find a solution for this common grouping problem in R: This is my original dataset ID State 1 A 2 A 3 B 4 B 5 B 6 A 7 A 8 A 9 C 10 C This should be my grouped resulting dataset State min(ID) max(ID) A 1 2 B 3 5 A 6 8 C 9 10 So the idea is to sort the dataset first by the ID column (or a timestamp column). Then all connected states with no gaps should be grouped together and the min and max ID value should be returned. It's related to the rle method, but this doesn't allow the calculation of min, max values for the groups. Any ideas? You could try: library(dplyr) df %>% mutate(rleid =

I want to summarize rather than compress in a similar manner to run length encoding but in a nested sense. For instance, I want : ABCBCABCBCDEEF to become: (2A(2BC))D(2E)F I am not concerned that an option is picked between two identical possible nestings E.g. ABBABBABBABA could be (3ABB)ABA or A(3BBA)BA which are of the same compressed length, despite having different structures. However I do want the choice to be MOST greedy. For instance: ABCDABCDCDCDCD would pick (2ABCD)(3CD) - of length six in original symbols which is less than ABCDAB(4CD) which is length 8 in original symbols. In terms

If I have a vector like "a": 0 0 1 1 1 0 0 0 0 1 1 0 0 0 How can I generate a vector of the same length containing the count of consecutive elements, like so: "b": 2 2 3 3 3 4 4 4 4 2 2 3 3 3 I tried rle, but I did not manage to stretch it out this way. Another option using rle and rep with(rle(a), rep(lengths, times = lengths)) # [1] 2 2 3 3 3 4 4 4 4 2 2 3 3 3 data a <- c(0, 0, 1, 1, 1, 0, 0, 0, 0, 1, 1, 0, 0, 0) Create a grouping variable using diff and use it in ave to calculate length of each group. ave(x, cumsum(c(0, diff(x) != 0)), FUN = length) # [1] 2 2 3 3 3 4 4 4 4 2 2 3 3 3 You can