Week6-LanguageDet

#sol. python

import numpy as np
import pandas as pd

def computeLanguageError(freq):
    # Computes the squared error between the letter frequencies given
    # as input and the letter frequencies of 15 languages stored in the
    # file letter_frequencies.csv

    # Open the file letter_frequencies.
    data = pd.read_csv("letter_frequencies.csv")

    # Extract a matrix containing the letter frequencies for the 15
    # languages and transpose it to yield a size 15 x 26 matrix
    languageFrequencies = np.array(data.iloc[0:26, 1:16]).T

    # Compute the squared errors. Subtracting a vector from a matrix will
    # "recycle" the vector, so it is subtracted from each row.
    E = np.sum((languageFrequencies - freq)**2, axis=1)
    return E





#sol. matlab


function E = computeLanguageError(freq)
% Computes the squared error between the letter frequencies given
% as input and the letter frequencies of 15 languages stored in the
% file letter_frequencies.csv

% Open the file letter_frequencies.
data = readtable('letter_frequencies.csv');

% Extract a 26 x 15 matrix containing the letter frequencies for
% the 15 languages
languageFrequencies = data{1:26, 2:16};

% Create a 26 x 15 matrix where each column is the letter
% frequencies in the text
textFrequencies = repmat(freq(:), 1, 15);

% Compute the squared errors
E = sum((languageFrequencies - textFrequencies).^2);



#sol. R

computeLanguageError <- function(freq) {
    # Computes the squared error between the letter frequencies given
    # as input and the letter frequencies of 15 languages stored in the
    # file letter_frequencies.csv

    # Open the file letter_frequencies.
    data = read.csv("letter_frequencies.csv")

    # Extract a 26 x 15 matrix containing the letter frequencies for
    # the 15 languages
    languageFrequencies = data[1:26, 2:16]

    # Compute the squared errors. Subtracting a vector from a matrix will
    # "recycle" the vector, so it is subtracted from each column.
    E = apply((languageFrequencies - freq)^2, 2, sum)
    return(E)
}