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Data compression is an essential part of information theory. It is used to reduce the data size for more efficiency

storage and transmission. One of the basic compression methods is Huffman coding, which uses frequency

character occurrences to create an optimal binary tree.

In this assignment, we will explore compression using Huffman coding. The following files are attached:

$$ huffman.py $-$ Python code for encoding and decoding Huffman code

$$ huffman$\_$tree.txt $-$ coding tree with which the other two files were compressed

$$ compressed$1.$txt $-$ the first compressed file $($string zero and one$)$

$$ compressed$2.$txt $-$ second compressed file $($string zero and one$)$

For attachments, it is important to mention that the full alphabet consists of $32$ characters $(5$ bits$)$: ABCDEFGHIJKLMNOPQRSTUVWXYZ$,.!?$:

$($the symbol $$ is a space$).$ The bit length of such inputs is five times the length of the strings themselves.

Your task is to analyze the following statements.

The last two statements carry $3$ unit points each if answered correctly, or $-3$ for incorrect

answered, and there is also a logical check.

Claims

$1.\backslash$geoquad Data redundancy can be reduced by compression.

$2.\backslash$geoquad The compression ratio is the ratio of the size of the compressed data to the size of the original data.

$3.\backslash$geoquad Entropy represents the average amount of information in a data set.

$4.\backslash$geoquad Huffman code is an absolutely optimal coding of any data.

$5.\backslash$geoquad Huffman decoding can decode any data regardless of whether it has a corresponding code.

$6.\backslash$geoquad The code generated by Huffman coding is unique for each character.

$7.\backslash$geoquad Each leaf in the Huffman tree represents one character from the input data.

$8.\backslash$geoquad Huffman coding is a lossy compression method.

$9.\backslash$geoquad Lossy compression can be used for text data where accuracy is important.

$10.\backslash$geoquad The compressed$1.$txt file is optimally compressed with the Huffman code $(\backslash$pm $3$ points$).$

$11.\backslash$geoquad The compressed$2.$txt file became larger than the input text $(\backslash$pm $3$ points$)$ due to compression.

$1$