run-length-encoding

问题 I am trying to learn about run length encoding and I found this challenge online that I cant do. It requires you to write a compression function called compression(strg) that takes a binary string strg of length 64 as input and returns another binary string as output. The output binary string should be a run-length encoding of the input string. compression('1010101001010101101010100101010110101010010101011010101001010101') '1010101001010101*4' Here is what I have, but this does NOT find the

问题 Currently I am learning python and I'd like to get a little bit more into Data Compression. So I decided to try to code Run-Length Encoding(RLE). From what I've read it can be useful when you try to compress pictures. I would like to know what would be the easiest image-file-type for a beginner? How can I read out pixel RGB values or similar from a picture with python? 回答1: As for the second part of your question: I would highly recommend OpenCV. It is very power for image processing and

问题 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

问题 I am having some issues that I am hoping you will be able to clarify. I have self taught myself a video encoding process similar to Mpeg2. The process is as follows: Split an RGBA image into 4 separate channel data memory blocks. so an array of all R values, a separate array of G values etc. take the array and grab a block of 8x8 pixel data, to transform it using the Discrete Cosine Transform (DCT). Quantize this 8x8 block using a pre-calculated quantization matrix. Zigzag encode the output

问题 I've got a following data frame in Python: df = pd.DataFrame.from_dict({'measurement_id': np.repeat([1, 2], [6, 6]), 'min': np.concatenate([np.repeat([1, 2, 3], [2, 2, 2]), np.repeat([1, 2, 3], [2, 2, 2])]), 'obj': list('AB' * 6), 'var': [1, 2, 1, 2, 2, 1, 2, 1, 2, 1, 1, 1]}) First, within each group defined by object , I'd like to assign id to unique run of measurement_id and var columns. If any value of those columns changes, it starts new run that should be assigned with new id. So the df[

问题 The classical RLE algorithm compresses data by using numbers to represent how many times the character following a number appears in the text at that position. For example: AAABBAAABBCECE => 3A2B3A2B1C1E1C1E However, in the above example, that method results in even more space being used by the compressed text. A better idea would be to use numbers to represent how many times the substring following a number appears in the given text. For example: AAABBAAABBCECE => 2AAABB2CE ("AAABB" twice,

问题 I updated my question because I need one more column to my output tible. I have the following tibble: library(tibble) my_tbl <- tribble( ~year, ~event_id, ~winner_id, 2011, "A", 4322, 2012, "A", 4322, 2013, "A", 4322, 2014, "A", 5478, 2015, "A", 4322, 2011, "B", 4322, 2012, "B", 7893, 2013, "B", 7893, 2014, "B", 2365, 2015, "B", 3407, 2011, "C", 5556, 2012, "C", 5556, 2013, "C", 1238, 2014, "C", 2391, 2015, "C", 2391, 2011, "D", 4219, 2012, "D", 7623, 2013, "D", 8003, 2014, "D", 2851, 2015,

问题 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. 回答1: 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) 回答2: Create a grouping variable using diff and use it in ave to calculate

问题 In R, I want to summarize my data after grouping it based on the runs of a variable x (aka each group of the data corresponds to a subset of the data where consecutive x values are the same). For instance, consider the following data frame, where I want to compute the average y value within each run of x : (dat <- data.frame(x=c(1, 1, 1, 2, 2, 1, 2), y=1:7)) # x y # 1 1 1 # 2 1 2 # 3 1 3 # 4 2 4 # 5 2 5 # 6 1 6 # 7 2 7 In this example, the x variable has runs of length 3, then 2, then 1, and

问题 This is a follow up question to the one I posted here: How to find the longest duplicate sequence in a tibble column? As the output, I need one more column (years): library(tibble) library(purrr) my_tbl <- tribble( ~year, ~event_id, ~winner_id, 2011, "A", 4322, 2012, "A", 4322, 2013, "A", 4322, 2014, "A", 5478, 2015, "A", 4322, 2011, "B", 4322, 2012, "B", 7893, 2013, "B", 7893, 2014, "B", 2365, 2015, "B", 3407, 2011, "C", 5556, 2012, "C", 5556, 2013, "C", 1238, 2014, "C", 2391, 2015, "C",