MATLAB: Create a logical vector

logical_vectorneuroscience

Hi All,

I have a cell array, where each cell in the first row contains a double of various lengths. Each double corresponds to sample numbers where a spike occurs (from a neuron – variable called cluster_split). I also have created an array of 0's the length of signal I am interested in (variable called LFP). I would like to index across each double (i.e.: cluster_split{1,1}) and create a logical vector of 1's and 0's.

For example, if in cluster_split{1,1} there is a value equal to 2502 (corresponding to sample 2502 in the LFP vector), then Matlab would output a 1 to the LFP array. I would like to create a separate "LFP" file for every double in the cluster_split cell array.

Thanks in advance for the help!

Best Answer

Does this help?

LFP = false(1, 3000);
LFP(2500) = true;

If LFP is at millisecond resolution and a spike occurs at 2500 milliseconds, you'll see a 1 in position 2500. Since I used true/false the vector is logical.

Related Solutions

MATLAB: Resampling an unbalanced dataset

Throw out all but 700 items where churn = true??? Then you'd have 700 false ones and 700 true ones. If not, then tell us in more detail what "balance" means to you.

MATLAB: Does the cellfun fails

"...however if I try to apply the same command again as..."

You have failed to take into account that inbetween running these two commands you have changed the data. So while the first cell array only contained scalar numeric (which is a bad way to store numeric data), the second time you call cellfun the cell array now also contains char vectors (lots of 'false', to be precise). Of course when you compare 'false'==1 then the output will be a vector like this:

>> 'false'==1
ans =
     0     0     0     0     0

and that is clearly not a scalar value, so your cellfun usage will fail unless you use 'uni',false and some more complex processing, or wrap the first argument function in any or something similar. Your third example give this error message

Function 'subsindex' is not defined for values of class 'cell'

because when you use the option 'UniformOutput',false then cellfun outputs a cell array, which cannot be used for indexing. So your attempt to use the output as an index will fail.

Here is a simpler approach using a numeric array (which it should be anyway):

>> m = cell2mat(a);
>> id0 = m==0;
>> id1 = m==1;
>> a(id0) = {'false'};
>> a(id1) = {'true'};
>> a
a = 
    'false'    'true'     [    2]    [    3]    [    4]    [    5]    [    6]    [    7]    [    8]    [    9]    [   10]    [   11]
    'true'     'false'    'false'    'false'    'false'    'false'    'false'    'false'    'false'    'false'    'false'    'false'
    [    2]    'true'     'true'     'true'     'false'    'false'    'true'     'false'    'false'    'false'    'false'    'false'
    [    3]    'true'     'true'     'true'     'false'    'false'    'true'     'false'    'false'    'false'    'false'    'false'
    [    4]    'true'     'true'     'true'     'false'    'false'    'true'     'false'    'false'    'false'    'false'    'false'
    [    5]    'true'     'true'     'true'     'false'    'false'    'true'     'false'    'false'    'false'    'false'    'false'
    [    6]    'true'     'true'     'true'     'false'    'false'    'true'     'false'    'false'    'false'    'false'    'false'
    [    7]    'true'     'true'     'true'     'false'    'false'    'true'     'false'    'false'    'false'    'false'    'false'
    [    8]    'true'     'true'     'true'     'false'    'false'    'true'     'false'    'false'    'false'    'false'    'false'
    [    9]    'true'     'true'     'true'     'false'    'false'    'true'     'false'    'false'    'false'    'false'    'false'
    [   10]    'true'     'true'     'true'     'false'    'false'    'true'     'false'    'false'    'false'    'false'    'false'
    [   11]    'true'     'true'     'true'     'false'    'false'    'true'     'false'    'true'     'false'    'false'    'false'

Note that your row and column headers indicate that you should perhaps be using a table, or only storing the actual data (not the headers) in a simple numeric array. Then you could do this task very simply with some basic indexing:

>> c = {'false','true'};
>> b = c(1+m(2:end,2:end))
b = 
    'false'    'false'    'false'    'false'    'false'    'false'    'false'    'false'    'false'    'false'    'false'
    'true'     'true'     'true'     'false'    'false'    'true'     'false'    'false'    'false'    'false'    'false'
    'true'     'true'     'true'     'false'    'false'    'true'     'false'    'false'    'false'    'false'    'false'
    'true'     'true'     'true'     'false'    'false'    'true'     'false'    'false'    'false'    'false'    'false'
    'true'     'true'     'true'     'false'    'false'    'true'     'false'    'false'    'false'    'false'    'false'
    'true'     'true'     'true'     'false'    'false'    'true'     'false'    'false'    'false'    'false'    'false'
    'true'     'true'     'true'     'false'    'false'    'true'     'false'    'false'    'false'    'false'    'false'
    'true'     'true'     'true'     'false'    'false'    'true'     'false'    'false'    'false'    'false'    'false'
    'true'     'true'     'true'     'false'    'false'    'true'     'false'    'false'    'false'    'false'    'false'
    'true'     'true'     'true'     'false'    'false'    'true'     'false'    'false'    'false'    'false'    'false'
    'true'     'true'     'true'     'false'    'false'    'true'     'false'    'true'     'false'    'false'    'false'

Best Answer

Related Solutions

MATLAB: Resampling an unbalanced dataset

MATLAB: Does the cellfun fails

Related Question