Although you could, probably, do this in pure Julia, is there a reason to
not write a small preprocessing script using sed (or your OS’s equivalent)
to create altered *copies* of the data before reading it? If HDD space is
an issue, you could do this one file at a time using Julia’s run method,
i.e. something like
dfile = "your-data-file.dat"
run(`copy_and_replace.sh $dfile`)
data = readdlm("$dfile.copy")
run(`rm $dfile.copy`)
where the shell script copy_and_replace.sh copies the raw data (with file
name given in the first argument) into a new file with the string “.copy”
appended to the name, and then replaces all occurences of D with E (or e,
or whatever you need) using sed.
// T
On Friday, July 18, 2014 12:51:32 PM UTC+2, Andrei Berceanu wrote:
I would prefer to keep my original files intact.
> In Python I can do
>
>
>
>
>
>
>
>
> *import stringimport numpy as nprule = string.maketrans('D', 'E')data =
> np.loadtxt(fname, usecols=(2,3),\ converters = {2: lambda
> val: float(val.translate(rule)),\ 3: lambda
> val: float(val.translate(rule))})*
> By the way, is there a Julia equivalent to numpy's *loadtxt*? Because the
> files are in 3-column format with multiple spaces separating the 3 entries
> on each line and eol chars to separate the lines.
>
> On Friday, July 18, 2014 12:33:23 PM UTC+2, Ivar Nesje wrote:
>>
>> If you have a reasonable editor, you should be able to open all your
>> files and issue a global search and replace operation that changes D to E.
>> If you have many files you can use sed to automate the process.
>>
>> kl. 11:41:12 UTC+2 fredag 18. juli 2014 skrev Andrei Berceanu følgende:
>>>
>>> Hi all,
>>>
>>> I have a lot of datafiles containing numbers in Fortran's double
>>> precision notation (http://math.hawaii.edu/wordpress/fortran-3/#double),
>>> i.e. 1.23D-3, instead of the usual E scientific notation.
>>> Is there a simple way to import the data as Float64?
>>>
>>> Tnx!
>>> Andrei
>>>
>>
