It looks like some of the problem I was seeing has to do with reading in
hdf5 files from matlab that contain strings for column types. when they
are read in using h5py the type is reported as 'O' which is object. The
problem is I can't reproduce the problem in small script because I can't
get hdf
I was able to fix my problem. One of the types in the recarray was of type
object when it should have been S27. Type object was the result of reading
in a matlab generated hdf5 file which had a string for one of the matrix
columns. I converted this column manually to a S27.
I am reverting my cod
Will do. I'm working on my side to get a solution that works. It seems
that when i use append_field i dont get a recarray back and when i call
asrecarray=True, i get an error. once i fix this. i will replicate the
error and post to github.
On Thu, May 11, 2017 at 5:07 PM, Eric Wieser
wrote:
>
Even if you solve your own problem, please do - a SystemError is 100% a
mistake in numpy, and should never be raised from python code, even if you
call a numpy function with the wrong inputs.
Eric
On Thu, 11 May 2017 at 19:35 Isaac Gerg wrote:
> Sure.
>
> On Thu, May 11, 2017 at 2:31 PM, Eric W
On 11 May 2017, at 8:52 pm, Isaac Gerg wrote:
>
> Looking at the code, i think merge and stack take in ndarrays, not recarrays
> is that correct?
It should accept either; however if your a and b are two recarrays with all
uniquely named columns
to get the 10-column recarray in your original exa
Looking at the code, i think merge and stack take in ndarrays, not recarrays
is that correct?
On Thu, May 11, 2017 at 2:34 PM, Isaac Gerg wrote:
> Sure.
>
> On Thu, May 11, 2017 at 2:31 PM, Eric Wieser
> wrote:
>
>> If that's the case, can you file an issue on github along with a minimal
>> exa
Sure.
On Thu, May 11, 2017 at 2:31 PM, Eric Wieser
wrote:
> If that's the case, can you file an issue on github along with a minimal
> example that produces the error, and the full stack trace?
>
> On Thu, 11 May 2017 at 19:29 Isaac Gerg wrote:
>
>> newtable = np.lib.recfunctions.merge_arrays([
If that's the case, can you file an issue on github along with a minimal
example that produces the error, and the full stack trace?
On Thu, 11 May 2017 at 19:29 Isaac Gerg wrote:
> newtable = np.lib.recfunctions.merge_arrays([a, b], asrecarray=True)
>
> yeilds:
>
> builtins.SystemError: ..\Objec
newtable = np.lib.recfunctions.merge_arrays([a, b], asrecarray=True)
yeilds:
builtins.SystemError: ..\Objects\dictobject.c:2054: bad argument to
internal function
On Thu, May 11, 2017 at 2:02 PM, Benjamin Root wrote:
> Check in numpy.recfunctions. I know there is merge_arrays() and
> stack_arr
Check in numpy.recfunctions. I know there is merge_arrays() and
stack_arrays(). I forget which one does what.
Cheers!
Ben Root
On Thu, May 11, 2017 at 1:51 PM, Isaac Gerg wrote:
> I'd prefer to stay in numpy land if possible.
>
> On Thu, May 11, 2017 at 1:17 PM, Isaac Xin Pei wrote:
>
>> Chec
I'd prefer to stay in numpy land if possible.
On Thu, May 11, 2017 at 1:17 PM, Isaac Xin Pei wrote:
> Check Pandas pd.concate ?
> On Thu, May 11, 2017 at 12:45 PM Isaac Gerg
> wrote:
>
>> I have 2 arrays, a and b which are rec arrays of length 10. Each array
>> has 5 columns.
>>
>> I would lik
Check Pandas pd.concate ?
On Thu, May 11, 2017 at 12:45 PM Isaac Gerg wrote:
> I have 2 arrays, a and b which are rec arrays of length 10. Each array
> has 5 columns.
>
> I would like to combine all the columns into a single recarray with 10
> columns and length 10.
>
> Thanks,
> Isaac
> ___
I have 2 arrays, a and b which are rec arrays of length 10. Each array has
5 columns.
I would like to combine all the columns into a single recarray with 10
columns and length 10.
Thanks,
Isaac
___
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