How to calculate occurrence of 3 variables

Hello, I have a time series with 3 columns : Wave height (H), Peak period (T) and Direction (D). Usually I create bivariate frequency tables of H/T and H/D, but now I would like to compute the occurrence of H/T/D triplets for several classes in order to get a table like: H T D Occurrence 0.5 7.2 180 10% 1.2 8.2 220 7% and so on...

Thank you!

Answer 1

[Nihal]

The Scytale cipher is an ancient transposition cipher used by the Spartans. It involves wrapping a strip of parchment around a rod (scytale) of a certain diameter and writing the message along the rod. When unwrapped, the message becomes scrambled. To decrypt it, you need a rod of the same diameter.

To apply the Scytale method for image encryption and decryption in MATLAB, you can treat the image as a sequence of bytes and perform the transposition accordingly. Below is an example of how to implement this in MATLAB:

Encryption

1. Read the Image: Convert the image into a 1D array.
2. Determine the Key: The key is the number of columns (or the diameter of the rod).
3. Encrypt the Image: Rearrange the pixels according to the Scytale cipher.

Decryption

1. Read the Encrypted Image: Convert the encrypted image into a 1D array.
2. Determine the Key: Use the same key as for encryption.
3. Decrypt the Image: Rearrange the pixels back to their original order.

Here is the complete MATLAB code to perform image encryption and decryption using the Scytale method:

function scytale_image_encryption_decryption()

% Read the image

img = imread('your_image.png'); % Replace 'your_image.png' with your image file

[rows, cols, channels] = size(img);

total_pixels = rows * cols * channels;


% Convert the image to a 1D array

img_1d = img(:);


% Define the key (number of columns for the Scytale cipher)

key = 100; % Choose an appropriate key based on your image size


% Encrypt the image

encrypted_img_1d = scytale_encrypt(img_1d, key);


% Convert the encrypted 1D array back to an image

encrypted_img = reshape(encrypted_img_1d, [rows, cols, channels]);

imwrite(encrypted_img, 'encrypted_image.png'); % Save the encrypted image


% Decrypt the image

decrypted_img_1d = scytale_decrypt(encrypted_img_1d, key);


% Convert the decrypted 1D array back to an image

decrypted_img = reshape(decrypted_img_1d, [rows, cols, channels]);

imwrite(decrypted_img, 'decrypted_image.png'); % Save the decrypted image


% Display the original, encrypted, and decrypted images

figure;

subplot(1, 3, 1);

imshow(img);

title('Original Image');


subplot(1, 3, 2);

imshow(encrypted_img);

title('Encrypted Image');


subplot(1, 3, 3);

imshow(decrypted_img);

title('Decrypted Image');

end


function encrypted = scytale_encrypt(data, key)

% Calculate the number of rows needed

num_rows = ceil(length(data) / key);


% Pad the data if necessary

padded_length = num_rows * key;

padded_data = [data; zeros(padded_length - length(data), 1)];


% Reshape the data into a matrix

matrix = reshape(padded_data, [key, num_rows]);


% Transpose the matrix to perform the Scytale encryption

encrypted_matrix = matrix';


% Convert the encrypted matrix back to a 1D array

encrypted = encrypted_matrix(:);

end


function decrypted = scytale_decrypt(data, key)

% Calculate the number of rows needed

num_rows = ceil(length(data) / key);


% Reshape the encrypted data into a matrix

encrypted_matrix = reshape(data, [num_rows, key]);


% Transpose the matrix to perform the Scytale decryption

decrypted_matrix = encrypted_matrix';


% Convert the decrypted matrix back to a 1D array

decrypted = decrypted_matrix(:);


% Remove any padding zeros

decrypted = decrypted(1:find(decrypted, 1, 'last'));

end