问题
Hello I have a cell array of char (separated by underscore) that I would like to convert to double.
I do it in a for
loop, but since the dimensions are very big, it takes a lot of time.
I would like to use cellfun
, but I don't know how to pass the delimiter.
Can you help me?
listofwords = {'02_04_04_52';'02_24_34_02'};
for i = 1 : size(listofwords,1)
listofwords_double(i,:) = str2double(strsplit(listofwords{i},'_'))./1000;
end
listofwords_double2= cellfun(@strsplit , listofwords);
Benchmark
As requested by Divakar
>> benchmark1
Speedup with EVAL over NO-LOOP-SSCANF = -46.3398%
>> benchmark1
Speedup with EVAL over NO-LOOP-SSCANF = -46.4068%
>> benchmark1
Speedup with EVAL over NO-LOOP-SSCANF = -47.1129%
>> benchmark1
Speedup with EVAL over NO-LOOP-SSCANF = -46.2882%
>> benchmark1
Speedup with EVAL over NO-LOOP-SSCANF = -46.2325%
>> benchmark1
Speedup with EVAL over NO-LOOP-SSCANF = -46.0161%
>> benchmark1
Speedup with EVAL over NO-LOOP-SSCANF = -46.9728%
>> benchmark1
Speedup with EVAL over NO-LOOP-SSCANF = -46.4267%
>> benchmark1
Speedup with EVAL over NO-LOOP-SSCANF = -46.2867%
>> benchmark1
Speedup with EVAL over NO-LOOP-SSCANF = -46.3031%
回答1:
You can use anonymous function like this -
listofwords_double2= cellfun(@(x) strsplit(x,'_') , listofwords,'uni',0)
Another approach with regexp
and a one-liner -
cell2mat(cellfun(@(x) str2double(regexp(x,'_','Split'))./1000 , listofwords,'uni',0))
Performance oriented solutions
Approach #1
N = 4; %// Edit this to 10 in your actual case
cat_cell = strcat(listofwords,'_');
one_str = [cat_cell{:}];
one_str(end)=[];
sep_cells = regexp(one_str,'_','Split');
out = reshape(str2double(sep_cells),N,[]).'./1000; %//'# desired output
Approach #2
Benchmarking the above solution suggests strcat
could prove to be the bottleneck. To get rid of that you can use a cumsum
based approach for that part. This is listed next -
N = 4; %// Edit this to 10 in your actual case
lens = cellfun(@numel,listofwords);
tlens = sum(lens);
idx = zeros(1,tlens); %// Edit this to "idx(1,tlens)=0;" for more performance
idx(cumsum(lens(1:end-1))+1)=1;
idx2 = (1:tlens) + cumsum(idx);
one_str(1:max(idx2))='_';
one_str(idx2) = [listofwords{:}];
sep_cells = regexp(one_str,'_','Split');
out = reshape(str2double(sep_cells),N,[]).'./1000; %//'# desired output
Approach #3
Now, this one uses sscanf
and appears to be really fast. Here's the code -
N = 4; %// Edit this to 10 in your actual case
lens = cellfun(@numel,listofwords);
tlens = sum(lens);
idx(1,tlens)=0;
idx(cumsum(lens(1:end-1))+1)=1;
idx2 = (1:tlens) + cumsum(idx);
one_str(1:max(idx2)+1)='_';
one_str(idx2) = [listofwords{:}];
delim = repmat('%d_',1,N*numel(lens));
out = reshape(sscanf(one_str, delim),N,[])'./1000; %//'# desired output
Benchmarking
As requested by @CST-Link, here's the benchmark comparing his "Kraken" eval
against approach #3
. The benchmarking code would look something like this -
clear all
listofwords = repmat({'02_04_04_52_23_14_54_672_0'},100000,1);
for k = 1:50000
tic(); elapsed = toc(); %// Warm up tic/toc
end
tic
N = 9; %// Edit this to 10 in your actual case
lens = cellfun(@numel,listofwords);
tlens = sum(lens);
idx(1,tlens)=0;
idx(cumsum(lens(1:end-1))+1)=1;
idx2 = (1:tlens) + cumsum(idx);
one_str(1:max(idx2)+1)='_';
one_str(idx2) = [listofwords{:}];
delim = repmat('%d_',1,N*numel(lens));
out = reshape(sscanf(one_str, delim),N,[])'./1000; %//'# desired output
time1 = toc;
clear out delim one_str idx2 idx tlens lens N
tic
n_numbers = 1+sum(listofwords{1}=='_');
n_words = numel(listofwords);
listofwords_double = zeros(n_numbers, n_words);
for i = 1:numel(listofwords)
temp = ['[', listofwords{i}, ']'];
temp(temp=='_') = ';';
listofwords_double(:,i) = eval(temp);
end;
listofwords_double = (listofwords_double / 1000).';
time2 = toc;
speedup = ((time1-time2)/time2)*100;
disp(['Speedup with EVAL over NO-LOOP-SSCANF = ' num2str(speedup) '%'])
And here are the benchmark results when the code is run for a few number of times -
>> benchmark1
Speedup with EVAL over NO-LOOP-SSCANF = 0.30609%
>> benchmark1
Speedup with EVAL over NO-LOOP-SSCANF = 0.012241%
>> benchmark1
Speedup with EVAL over NO-LOOP-SSCANF = -2.3146%
>> benchmark1
Speedup with EVAL over NO-LOOP-SSCANF = 0.33678%
>> benchmark1
Speedup with EVAL over NO-LOOP-SSCANF = -1.8189%
>> benchmark1
Speedup with EVAL over NO-LOOP-SSCANF = -0.12254%
Looking at the results and observing some negative speedups (indicating sscanf
to be better in those cases) among some positive speedups, my opinion would be to stick with sscanf
.
回答2:
A solution could be:
listofwords_double2 = cellfun(@(x) str2double(strsplit(x, '_'))./ 1000, listofwords);
Just a side note: my version of Matlab does not have strsplit
, so I cannot test it.
来源:https://stackoverflow.com/questions/26487246/passing-argument-to-cellfun-matlab