I have a set of documents containing pre-processed texts from html pages. They are already given to me. I want to extract only the words from it. I do not want any numbers or common words or any single letters to be extracted. The first problem I am facing is this.
Suppose I have a cell array :
{'!' '!!' '!!!!)' '!!!!thanks' '!!dogsbreath' '!)' '!--[endif]--' '!--[if'}
I want to make the cell array having only the words - like this.
{'!!!!thanks' '!!dogsbreath' '!--[endif]--' '!--[if'}
And then convert this to this cell array
{'thanks' 'dogsbreath' 'endif' 'if'}
Is there any way to do this ?
Updated Requirement : Thanks to all of your answers. However I am facing a problem ! Let me illustrate this (Please note that the cell values are extracted text from HTML documents and hence may contain non ASCII values) -
{'!/bin/bash' '![endif]' '!take-a-long' '!–photo'}
This gives me the answer
{'bin' 'bash' 'endif' 'take' 'a' 'long' 'â' 'photo' }
My Questions:
Why is bin/bash and take-a-long being separated into three cells ? Its not a problem for me but still why? Can this be avoided. I mean all words coming from a single cell being combined into one.
Notice that in '!–photo' there exists an non-ascii character â which esentially means a. Can a step be incorporated such that this transformation is automatic?
I noticed that the text "it? __________ About the Author:" gives me "__________" as a word. Why is this so ?
Also the text "2. areoplane 3. cactus 4. a_rinny_boo... 5. trumpet 6. window 7. curtain ... 173. gypsy_wagon..." returns a word as 'areoplane' 'cactus' 'a_rinny_boo' 'trumpet' 'window' 'curtain' 'gypsy_wagon'. I want the words 'a_rinny_boo' and ''gypsy_wagon to be 'a' 'rinny' 'boo' 'gypsy' 'wagon'. Can this be done ?
Update 1 Following all the suggestions I have written down a function which does most of the things except the above two newly asked questions.
function [Text_Data] = raw_txt_gn(filename)
% This function will convert the text documnets into raw text
% It will remove all commas empty cells and other special characters
% It will also convert all the words of the text documents into lowercase
T = textread(filename, '%s');
% find all the important indices
ind1=find(ismember(T,':WebpageTitle:'));
T1 = T(ind1+1:end,1);
% Remove things which are not basically words
not_words = {'##','-',':ImageSurroundingText:',':WebpageDescription:',':WebpageKeywords:',' '};
T2 = []; count = 1;
for j=1:length(T1)
x = T1{j};
ind=find(ismember(not_words,x), 1);
if isempty(ind)
B = regexp(x, '\w*', 'match');
B(cellfun('isempty', B)) = []; % Clean out empty cells
B = [B{:}]; % Flatten cell array
% convert the string into lowecase
% so that while generating the features the case sensitivity is
% handled well
x = lower(B);
T2{count,1} = x;
count = count+1;
end
end
T2 = T2(~cellfun('isempty',T2));
% Getting the common words in the english language
% found from Wikipedia
not_words2 = {'the','be','to','of','and','a','in','that','have','i'};
not_words2 = [not_words2, 'it' 'for' 'not' 'on' 'with' 'he' 'as' 'you' 'do' 'at'];
not_words2 = [not_words2, 'this' 'but' 'his' 'by' 'from' 'they' 'we' 'say' 'her' 'she'];
not_words2 = [not_words2, 'or' 'an' 'will' 'my' 'one' 'all' 'would' 'there' 'their' 'what'];
not_words2 = [not_words2, 'so' 'up' 'out' 'if' 'about' 'who' 'get' 'which' 'go' 'me'];
not_words2 = [not_words2, 'when' 'make' 'can' 'like' 'time' 'no' 'just' 'him' 'know' 'take'];
not_words2 = [not_words2, 'people' 'into' 'year' 'your' 'good' 'some' 'could' 'them' 'see' 'other'];
not_words2 = [not_words2, 'than' 'then' 'now' 'look' 'only' 'come' 'its' 'over' 'think' 'also'];
not_words2 = [not_words2, 'back' 'after' 'use' 'two' 'how' 'our' 'work' 'first' 'well' 'way'];
not_words2 = [not_words2, 'even' 'new' 'want' 'because' 'any' 'these' 'give' 'day' 'most' 'us'];
for j=1:length(T2)
x = T2{j};
% if a particular cell contains only numbers then make it empty
if sum(isstrprop(x, 'digit'))~=0
T2{j} = [];
end
% also remove single character cells
if length(x)==1
T2{j} = [];
end
% also remove the most common words from the dictionary
% the common words are taken from the english dicitonary (source
% wikipedia)
ind=find(ismember(not_words2,x), 1);
if isempty(ind)==0
T2{j} = [];
end
end
Text_Data = T2(~cellfun('isempty',T2));
Update 2
I found this code in here which tells me how to check for non-ascii characters. Incorporating this code snippet in Matlab as
% remove the non-ascii characters
if all(x < 128)
else
T2{j} = [];
end
and then removing the empty cells it seems my second requirement is fulfilled though the text containing a part of non-ascii characters completely disappears.
Can my final requirements be completed ? Most of them concerns the character '_' and '-'.
A regexp approach to go directly to the final step:
A = {'!' '!!' '!!!!)' '!!!!thanks' '!!dogsbreath' '!)' '!--[endif]--' '!--[if'};
B = regexp(A, '\w*', 'match');
B(cellfun('isempty', B)) = []; % Clean out empty cells
B = [B{:}]; % Flatten cell array
Which matches any alphabetic, numeric, or underscore character. For the sample case we get a 1x4 cell array:
B =
'thanks' 'dogsbreath' 'endif' 'if'
Edit:
Why is bin/bash and take-a-long being separated into three cells ? Its not a problem for me but still why? Can this be avoided. I mean all words coming from a single cell being combined into one.
Because I'm flattening the cell arrays to remove nested cells. If you remove B = [B{:}]; each cell will have a nested cell inside containing all of the matches for the input cell array. You can combine these however you want after.
Notice that in '!–photo' there exists an non-ascii character â which esentially means a. Can a step be incorporated such that this transformation is automatic?
Yes, you'll have to make it based on the character codes.
I noticed that the text "it? __________ About the Author:" gives me "__________" as a word. Why is this so ?
As I said, the regex matches alphabetic, numeric, or underscore characters. You can change your filter to exclude _, which will also address the fourth bullet point: B = regexp(A, '[a-zA-Z0-9]*', 'match'); This will match a-z, A-Z, and 0-9 only. This will also exclude the non-ASCII characters, which it seems like the \w* flag matches.
I think #excaza's solution would be the go-to approach, but here's an alternative one with isstrprop using its optional input argument 'alpha' to look for alphabets -
A(cellfun(#(x) any(isstrprop(x, 'alpha')), A))
Sample run -
>> A
A =
'!' '!!' '!!!!)' '!!!!thanks' '!!dogsbreath' '!)' '!--[endif]--' '!--[if'
>> A(cellfun(#(x) any(isstrprop(x, 'alpha')), A))
ans =
'!!!!thanks' '!!dogsbreath' '!--[endif]--' '!--[if'
To get to the final destination, you can tweak this approach a bit, like so -
B = cellfun(#(x) x(isstrprop(x, 'alpha')), A,'Uni',0);
out = B(~cellfun('isempty',B))
Sample run -
A =
'!' '!!' '!!!!)' '!!!!thanks' '!!dogsbreath' '!)' '!--[endif]--' '!--[if'
out =
'thanks' 'dogsbreath' 'endif' 'if'
Related
How can I go about doing this? So far I've opened the file like this
fileID = fopen('hamlet.txt'.'r');
[A,count] = fscanf(fileID, '%s');
fclose(fileID);
Getting spaces from the file
First, if you want to capture spaces, you'll need to change your format specifier. %s reads only non-whitespace characters.
>> fileID = fopen('space.txt','r');
>> A = fscanf(fileID, '%s');
>> fclose(fileID);
>> A
A = Thistexthasspacesinit.
Instead, we can use %c:
>> fileID = fopen('space.txt','r');
>> A = fscanf(fileID, '%c');
>> fclose(fileID);
>> A
A = This text has spaces in it.
Mapping between characters and values (array indices)
We could create a character array that contains all of the target characters to look for:
search_chars = ['A':'Z', 'a':'z', ',', '.', ' '];
That would work, but to map the character to a position in the array you'd have to do something like:
>> char_pos = find(search_chars == 'q')
char_pos = 43
You could also use containters.Map, but that seems like overkill.
Instead, let's use the ASCII value of each character. For convenience, we'll use only values 1:126 (0 is NUL, and 127 is DEL. We should never encounter either of those.) Converting from characters to their ASCII code is easy:
>> c = 'q'
c = s
>> a = uint8(c) % MATLAB actually does this using double(). Seems wasteful to me.
a = 115
>> c2 = char(a)
c2 = s
Note that by doing this, you're counting characters that are not in your desired list like ! and *. If that's a problem, then use search_chars and figure out how you want to map from characters to indices.
Looping solution
The most intuitive way to count each character is a loop. For each character in A, find its ASCII code and increment the counter array at that index.
char_count = zeros(1, 126);
for current_char = A
c = uint8(current_char);
char_count(c) = char_count(c) + 1;
end
Now you've got an array of counts for each character with ASCII codes from 1 to 126. To find out how many instances of 's' there are, we can just use its ASCII code as an index:
>> char_count(115)
ans = 4
We can even use the character itself as an index:
>> char_count('s')
ans = 4
Vectorized solution
As you can see with that last example, MATLAB's weak typing makes characters and their ASCII codes pretty much equivalent. In fact:
>> 's' == 115
ans = 1
That means that we can use implicit broadcasting and == to create a logical 2D array where L(c,a) == 1 if character c in our string A has an ASCII code of a. Then we can get the count for each ASCII code by summing along the columns.
L = (A.' == [1:126]);
char_count = sum(L, 1);
A one-liner
Just for fun, I'll show one more way to do this: histcounts. This is meant to put values into bins, but as we said before, characters can be treated like values.
char_count = histcounts(uint8(A), 1:126);
There are dozens of other possibilities, for instance you could use the search_chars array and ismember(), but this should be a good starting point.
With [A,count] = fscanf(fileID, '%s'); you'll only count all string letters, doesn't matter which one. You can use regexp here which search for each letter you specify and will put it in a cell array. It consists of fields which contains the indices of your occuring letters. In the end you only sum the number of indices and you have the count for each letter:
fileID = fopen('hamlet.txt'.'r');
A = fscanf(fileID, '%s');
indexCellArray = regexp(A,{'A','B','C','D',... %I'm too lazy to add the other letters now^^
'a','b','c','d',...
','.' '};
letterCount = cellfun(#(x) numel(x),indexCellArray);
fclose(fileID);
Maybe you put the cell array in a struct where you can give fieldnames for the letters, otherwise you might loose track which count belongs to which number.
Maybe there's much easier solution, cause this one is kind of exhausting to put all the letters in the regexp but it works.
I would like to make the following code simpler.
files=dir('~/some*.txt');
numFiles=length(files);
for i = 1:numFiles
name=files(i).name;
name=strsplit(name,'.');
name=name{1};
name=strsplit(name, '_');
name=name(2);
name = str2num(name{1});
disp(name);
end
I am a begginer in Matlab, in general I would love something like:
name = str2num(strsplit(strsplit(files(i).name,'.')(1),'_')(2));
but matlab does not like this.
Another issue of the approach above is that matlab keeps giving cell type even for something like name(2) but this may be just the problem with my syntax.
Example file names:
3000_0_100ms.txt
3000_0_5s.txt
3000_110_5s.txt
...
Let's say I want to select all files ending in '5s' then I need to split them (after removing the extension) by '_' and return the second part, in the case of the three filenames above, that would be 0, 0, 110.
But I am in general curious how to do this simple operation in matlab without the complicated code that I have above.
Because your filenames follow a specific pattern, they're a prime candidate for a regular expression. While regular expressions can be confusing to learn at the outset they are very powerful tools.
Consider the following example, which pulls out all numbers that have both leading and trailing underscores:
filenames = {'3000_0_100ms.txt', '3000_0_5s.txt', '3000_110_5s.txt'};
strs = regexp(filenames, '(?<=\_)(\d+)(?=\_)', 'match');
strs = [strs{:}]; % Denest one layer of cells
nums = str2double(strs);
Which returns:
nums =
0 0 110
Being used here are what's called lookbehind (?<=...) and lookahead (?=...) operators. As their names suggest, they look in their respective directions related to the expression they're part of, (\d+) in our case, which looks for one or more digits. Though this approach requires more steps than the simple '\_(\d+)\_' expression, the latter requires you either utilize MATLAB's 'tokens' regex operator, which adds another layer of cells and that annoys me, or use the 'match' operator and strip the underscores from the match prior to converting to a numeric value.
Approach 2:
filenames = {'3000_0_100ms.txt', '3000_0_5s.txt', '3000_110_5s.txt'};
strs = regexp(filenames, '\_(\d+)\_', 'tokens');
strs = [strs{:}]; % Denest one layer of cells
strs = [strs{:}]; % Denest another layer of cells
nums = str2double(strs);
Approach 3:
filenames = {'3000_0_100ms.txt', '3000_0_5s.txt', '3000_110_5s.txt'};
strs = regexp(filenames, '\_(\d+)\_', 'match');
strs = [strs{:}]; % Denest one layer of cells
strs = regexprep(strs, '\_', '');
nums = str2double(strs);
You can use regexp to do a regular expression matching and obtain the numbers in the second place directly. This is an explanation of the regular expression I am using.
>>names = regexp({files(:).name},'\d*_(\d*)_\d*m?s\.txt$','tokens')
>>names = [names{:}]; % Get names out of their cells
>>names = [names{:}]; % Break cells one more time
>> nums = str2double(names); % Convert to double to obtain numbers
I have file names stored as follows:
>> allFiles.name
ans =
k-120_knt-500_threshold-0.3_percent-34.57.csv
ans =
k-216_knt-22625_threshold-0.3_percent-33.33.csv
I wish to extract the 4 values from them and store in a cell.
data={};
for k =1:numel(allFiles)
data{k,1}=csvread(allFiles(k).name,1,0);
data{k,2}= %kvalue
data{k,3}= %kntvalue
data{k,4}=%threshold
data{k,5}=%percent
...
end
There's probably a regular expression that can be used to do this, but a simple piece of code would be
data={numel(allFiles),5};
for k =1:numel(allFiles)
data{k,1}=csvread(allFiles(k).name,1,0);
[~,name] = fileparts(allFiles(k).name);
dashIdx = strfind(name,'-'); % find location of dashes
usIdx = strfind(name,'_'); % find location of underscores
data{k,2}= str2double(name(dashIdx(1)+1:usIdx(1)-1)); %kvalue
data{k,3}= str2double(name(dashIdx(2)+1:usIdx(2)-1)); %kntvalue
data{k,4}= str2double(name(dashIdx(3)+1:usIdx(3)-1)); %threshold
data{k,5}= str2double(name(dashIdx(4)+1:end)); %percent
...
end
For efficiency, you might consider using a single matrix to store all the numeric data, and/or a structure (so that you can access the data by name rather than index).
You simply need to tokenize using strtok multiple times (there is more than 1 way to solve this). Someone has a handy matlab script somewhere on the web to tokenize strings into a cell array.
(1) Starting with:
filename = 'k-216_knt-22625_threshold-0.3_percent-33.33.csv'
Use strfind to prune out the extension
r = strfind(filename, '.csv')
filenameWithoutExtension = filename(1:r-1)
This leaves us with:
'k-216_knt-22625_threshold-0.3_percent-33.33'
(2) Then tokenize this:
'k-216_knt-22625_threshold-0.3_percent-33.33'
using '_' . You get the tokens:
'k-216'
'knt-22625'
'threshold-0.3'
'percent-33.33'
(3) Lastly, for each string, tokenize using using '-'. Each second string will be:
'216'
'22625'
'0.3'
'33.33'
And use str2num to convert.
Strategy: strsplit() + str2num().
data={};
for k =1:numel(allFiles)
data{k,1}=csvread(allFiles(k).name,1,0);
words = strsplit( allFiles(k).name(1:(end-4)), '_' );
data{k,2} = str2num(words{1}(2:end));
data{k,3} = str2num(words{2}(4:end));
data{k,4} = str2num(words{3}(10:end));
data{k,5} = str2num(words{4}(8:end));
end
eliminate punctuation
words split when meeting new line and space, then store in array
check the text file got error or not with the function of checkSpelling.m file
sum up the total number of error in that article
no suggestion is assumed to be no error, then return -1
sum of error>20, return 1
sum of error<=20, return -1
I would like to check spelling error of certain paragraph, I face the problem to get rid of the punctuation. It may have problem to the other reason, it return me the error as below:
My data2 file is :
checkSpelling.m
function suggestion = checkSpelling(word)
h = actxserver('word.application');
h.Document.Add;
correct = h.CheckSpelling(word);
if correct
suggestion = []; %return empty if spelled correctly
else
%If incorrect and there are suggestions, return them in a cell array
if h.GetSpellingSuggestions(word).count > 0
count = h.GetSpellingSuggestions(word).count;
for i = 1:count
suggestion{i} = h.GetSpellingSuggestions(word).Item(i).get('name');
end
else
%If incorrect but there are no suggestions, return this:
suggestion = 'no suggestion';
end
end
%Quit Word to release the server
h.Quit
f19.m
for i = 1:1
data2=fopen(strcat('DATA\PRE-PROCESS_DATA\F19\',int2str(i),'.txt'),'r')
CharData = fread(data2, '*char')'; %read text file and store data in CharData
fclose(data2);
word_punctuation=regexprep(CharData,'[`~!##$%^&*()-_=+[{]}\|;:\''<,>.?/','')
word_newLine = regexp(word_punctuation, '\n', 'split')
word = regexp(word_newLine, ' ', 'split')
[sizeData b] = size(word)
suggestion = cellfun(#checkSpelling, word, 'UniformOutput', 0)
A19(i)=sum(~cellfun(#isempty,suggestion))
feature19(A19(i)>=20)=1
feature19(A19(i)<20)=-1
end
Substitute your regexprep call to
word_punctuation=regexprep(CharData,'\W','\n');
Here \W finds all non-alphanumeric characters (inclulding spaces) that get substituted with the newline.
Then
word = regexp(word_punctuation, '\n', 'split');
As you can see you don't need to split by space (see above). But you can remove the empty cells:
word(cellfun(#isempty,word)) = [];
Everything worked for me. However I have to say that you checkSpelling function is very slow. At every call it has to create an ActiveX server object, add new document, and delete the object after check is done. Consider rewriting the function to accept cell array of strings.
UPDATE
The only problem I see is removing the quote ' character (I'm, don't, etc). You can temporary substitute them with underscore (yes, it's considered alphanumeric) or any sequence of unused characters. Or you can use list of all non-alphanumeric characters to be remove in square brackets instead of \W.
UPDATE 2
Another solution to the 1st UPDATE:
word_punctuation=regexprep(CharData,'[^A-Za-z0-9''_]','\n');
I have a cell array like:
>>text
'Sentence1'
'Sentence2'
'Sentence3'
Whenever I use
sprintf(fid,'%s\n',text)
I get an error saying:
'Function is not defined for 'cell' inputs.'
But if I put :
sprintf(fid,'%s\n',char(text))
It works but in the file appears all the sentences mixed all together like with no sense.
Can you recommend me what to do?
Whener I put text I get:
>>text
'Title '
'Author'
'comments '
{3x1} cell
That is why I can not use text{:}.
If you issue
sprintf('%s\n', text)
you are saying "print a string with a newline. The string is this cell array". That's not correct; a cell-array is not a string.
If you issue
sprintf('%s\n', char(text))
you are saying "print a string with a newline. The string is this cell array, which I convert to character array.". The thing is, that conversion results in a single character array, and sprintf will re-use the %s\n format only for multiple inputs. Moreover, it writes that single character array by column, meaning, all characters in the first column, concatenated horizontally with all characters from the second column, concatenated with all characters from the third column, etc.
Therefore, the approprate call to sprintf is something with multiple inputs:
sprintf(fid, '%s\n', text{:})
because the cell-expansion text{:} creates a comma-separated list from all entries in the cell-array, which is exactly what sprintf/fprintf expects.
EDIT As you indicate:, you have non-char entries in text. You have to check for that. If you want to pass only the strings into fprintf, use
fprintf(fid, '%s\n', text{ cellfun('isclass', text, 'char') })
if that {3x1 cell} is again a set of strings, so you want to write all strings recursively, then just use something like this:
function textWriter
text = {...
'Title'
'Author'
'comments'
{...
'Title2'
'Author2'
'comments2'
{...
'Title3'
'Author3'
'comments3'
}
}
}
text = cell2str(text);
fprintf(fid, '%s\n', text{:});
end
function out = cell2str(c)
out = {};
for ii = c(:)'
if iscell(ii{1})
S = cell2str(ii{1});
out(end+1:end+numel(S)) = S;
else
out{end+1} = ii{1};
end
end
end