I was using the following command:
T = textscan(fid, format_spec, 'HeaderLines', 0);
Evaluating T seemed to show that the file was being read correctly, with the correct number of colums matching my CSV.
>> T
T =
Columns 1 through 4
{1x1 cell} [11] [0x1 double] [0x1 double]
Columns 5 through 7
[0x1 double] [0x1 double] [0x1 double]
Columns 8 through 10
[0x1 double] [0x1 double] [0x1 double]
The problem was that I was reading a CSV file, and the default setting for textscan uses another option for the delimiter. By leaving this field unspecified, the function was not able to handle the file correctly. I changed the line to the following:
T = textscan(fid, format_spec, 'Delimiter', ',', 'HeaderLines', 0);
This now read in the entire file correctly, revealing all of the rows were read in as expected:
>> T
T =
Columns 1 through 2
{81231x1 cell} [81231x1 double]
Columns 3 through 4
[81231x1 double] [81231x1 double]
Columns 5 through 6
[81231x1 double] [81231x1 double]
Columns 7 through 8
[81231x1 double] [81231x1 double]
Columns 9 through 10
[81231x1 double] [81231x1 double]
Note that the data was read into "cells", which means that it must be handled slightly differently. In this case, if I evaluate T(1), this doesn't give all of the data from column one, I just get the following:
>> T(1)
ans =
{81231x1 cell}
Instead, I have to use the following command:
>> T{1}
ans =
'2016-02-05_19-09-50' '2016-02-05_19-10-38' '2016-02-05_19-21-43' '2016-02-05_19-22-31' '2016-02-05_19-23-19' '2016-02-05_19-24-08' '2016-02-05_19-26-11' '2016-02-05_19-26-59' '2016-02-05_19-27-47' '2016-02-05_19-28-36'
Note the curly braces around the number after T. It is also possible to only return a subset of the data by specifying the indices after the curly braces, as follows:
>> T{1}(1:3)
ans =
'2016-02-05_19-09-50' '2016-02-05_19-10-38' '2016-02-05_19-21-43'
Finally, we can get the data into a format we are more used to by using the cell2mat() function.
dates=cell2mat(T{1})
This concerts the data into a matrix. In my case I have read in strings, and so the matrix is a 2d array. Now to view the first three dates, I can use the following command:
>> dates(1:3,:)
ans =
2016-02-05_19-09-502016-02-05_19-10-382016-02-05_19-21-43
And from here the data can be treated as normal.
