[Numpy-discussion] Problems creating numpy.array with a dtype

[Vincent Davis]

>
> the tuple (row) is one element of the structured array. It's possible
> to have an n-dimensional structured array where each element is a
> tuple.


Also just was looking at this and while you can't do this
anarray = np.array([1,2,3], dtype = [('num', int)])
you can
anarray = np.array([(1,),(2,),(3,)], dtype = [('num', int)])

Vincent


On Sat, May 15, 2010 at 7:37 AM, <josef.pktd at gmail.com> wrote:

> On Sat, May 15, 2010 at 9:27 AM, Jimmie Houchin <jlhouchin at gmail.com>
> wrote:
> > On 5/15/2010 6:30 AM, josef.pktd at gmail.com wrote:
> >> On Sat, May 15, 2010 at 12:24 AM, Jimmie Houchin<jlhouchin at gmail.com>
>  wrote:
> >>> def getArray(instrument, weekString=None):
> >>>      ...
> >>>      cur.execute(sql)
> >>>      weekData = cur.fetchall()
> >>>      wdata = []
> >>>      lst = []
> >>>      dtminute, dttypes = createDType()
> >>>      for i in dttypes:
> >>>          if i[1] == 'f8': lst.append(0.0)
> >>>          elif i[1] == 'i1': lst.append(0)
> >>>          else: lst.append('')
> >>>      for m in weekData:
> >>>          data = list(m)+lst[9:]
> >>>          wdata.append(data)
> >>
> >> I think "data" here should be a tuple, i.e. tuple(data)
> >> structured arrays expect tuples for each element/row
> >>
> >> If this is not it, then you could provide a mini example of wdata with
> >> just a few rows.
> >>
> >>>      return np.array(wdata,dtype=dtminute)
> >>>
> >>> The createDType() function works fine. The getArray() function fails
> with:
> >>> ValueError: Setting void-array with object members using buffer.
> >>
> >> cryptic exceptions messages in array construction usually means there
> >> is some structure in the argument data that numpy doesn't understand,
> >> I usually work with trial and error for a specific example
> >>
> >> Josef
> >
> > Hello Josef,
> >
> > Wrapping data,   tuple(list(m)+lst[9:])
> > works.
> >
> > Thanks.
> >
> > For some reason I was under the impression that numpy accepted either
> > lists or tuples as long as the shape of the structure, and the data
> > types was the same as the dtype array structure that it is filling.
> > Is there a particular reason this is not so?
>
> the tuple (row) is one element of the structured array. It's possible
> to have an n-dimensional structured array where each element is a
> tuple.
>
> So, I guess, numpy needs the distinction between list and tuples to
> know what is an element.
> That's from hitting at this very often, I never looked at the numpy
> internals for this.
>
> Josef
>
> >
> > Again, thanks. I can now get rid of my moderately less elegant, but
> > working second version.
> >
> > Jimmie
> >
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> >
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  *Vincent Davis
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