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extract_allfeatures.m
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extract_allfeatures.m
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%% Import data from text file.
% Script for importing data from the following text file:
%
% /Users/paolosassi/Documents/MATLAB/Computational Intelligence/Assignment 1/auto-mpg.data
%
% To extend the code to different selected data or a different text file,
% generate a function instead of a script.
% Auto-generated by MATLAB on 2016/10/28 16:36:41
%% Initialize variables.
filename = 'auto-mpg.data';
delimiter = {'\t',' '};
%% Read columns of data as text:
% For more information, see the TEXTSCAN documentation.
formatSpec = '%*q%q%q%q%q%q%q%q%[^\n\r]';
%% Open the text file.
fileID = fopen(filename,'r');
%% Read columns of data according to the format.
% This call is based on the structure of the file used to generate this
% code. If an error occurs for a different file, try regenerating the code
% from the Import Tool.
dataArray = textscan(fileID, formatSpec, 'Delimiter', delimiter, 'MultipleDelimsAsOne', true, 'ReturnOnError', false);
%% Close the text file.
fclose(fileID);
%% Convert the contents of columns containing numeric text to numbers.
% Replace non-numeric text with NaN.
raw = repmat({''},length(dataArray{1}),length(dataArray)-1);
for col=1:length(dataArray)-1
raw(1:length(dataArray{col}),col) = dataArray{col};
end
numericData = NaN(size(dataArray{1},1),size(dataArray,2));
for col=[1,2,3,4,5,6,7]
% Converts text in the input cell array to numbers. Replaced non-numeric
% text with NaN.
rawData = dataArray{col};
for row=1:size(rawData, 1);
% Create a regular expression to detect and remove non-numeric prefixes and
% suffixes.
regexstr = '(?<prefix>.*?)(?<numbers>([-]*(\d+[\,]*)+[\.]{0,1}\d*[eEdD]{0,1}[-+]*\d*[i]{0,1})|([-]*(\d+[\,]*)*[\.]{1,1}\d+[eEdD]{0,1}[-+]*\d*[i]{0,1}))(?<suffix>.*)';
try
result = regexp(rawData{row}, regexstr, 'names');
numbers = result.numbers;
% Detected commas in non-thousand locations.
invalidThousandsSeparator = false;
if any(numbers==',');
thousandsRegExp = '^\d+?(\,\d{3})*\.{0,1}\d*$';
if isempty(regexp(numbers, thousandsRegExp, 'once'));
numbers = NaN;
invalidThousandsSeparator = true;
end
end
% Convert numeric text to numbers.
if ~invalidThousandsSeparator;
numbers = textscan(strrep(numbers, ',', ''), '%f');
numericData(row, col) = numbers{1};
raw{row, col} = numbers{1};
end
catch me
end
end
end
%% Replace non-numeric cells with NaN
R = cellfun(@(x) ~isnumeric(x) && ~islogical(x),raw); % Find non-numeric cells
raw(R) = {NaN}; % Replace non-numeric cells
%% Create output variable
features = cell2mat(raw);
%% Clear temporary variables
clearvars filename delimiter formatSpec fileID dataArray ans raw col numericData rawData row regexstr result numbers invalidThousandsSeparator thousandsRegExp me R;