@@ -16,7 +16,6 @@ From a programming point of view, the first objectives of this project are to le
-[_Q3.2._](#q32-toc)
-[_Q4. Compression with Huffman_](#q4-compression-with-huffman-toc)
-[_Upload your work_](#compress-the-files-and-upload-them-to-the-lms-toc)
-[_Fill the quizz on the LMS_](#fill-the-quizz-on-the-lms-toc)
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@@ -156,20 +155,11 @@ Basically speaking, the maximum level of compression that can be obtained with t
$$\frac{7\times \textrm{number of characters in the initial text file}}{\textrm{number of characters in the compressed file}}$$
4. How to improve the level of compression ? The occurrence frequencies of each character only capture the redundancy of the characters, but not the one between consecutive characters... So, you can do the same exercice by analyzing the occurence frequencies of all 2-letter (or more) words. This should allow you to capture more redundancy of the text and then to improve the compression ratio.
## Compress the files and [upload them to the LMS](https://lms.isae.fr/mod/assign/view.php?id=107859) [[toc](#table-of-content)]
- [ ] `src/occurrence_frequencies.py`
- [ ] `src/enhanced_occurrence_frequencies.py`
- [ ] `src/text_length.py`
- [ ] `src/data_compression.py`
To compress several files into one archive, select all the files, then, right-click and choose compress in the menu. Choose the `.zip` extension for the new archive.
alternately, you can use one of the following commands from a shell:
## Compress the files and upload them to the LMS [[toc](#table-of-content)]
