On Monday 05 May 2008 15:35:35 Eric Firing wrote:
> What I meant was that I don't see that such a ravelled version of a
> matrix would be likely to make sense in a linear algebra context, so
> leaving it as a matrix is likely to cause confusion rather than
> convenience. Still, it would be consist
Pierre GM wrote:
> On Monday 05 May 2008 15:10:56 Eric Firing wrote:
>> Pierre GM wrote:
>>> * An alternative would be to force the output of MaskedArray.compressed()
>>> to type(MaskedArray._baseclass), where the _baseclass attribute is the
>>> class of the underlying array: usually it's only ndar
On Monday 05 May 2008 15:10:56 Eric Firing wrote:
> Pierre GM wrote:
> > * An alternative would be to force the output of MaskedArray.compressed()
> > to type(MaskedArray._baseclass), where the _baseclass attribute is the
> > class of the underlying array: usually it's only ndarray, but it can be
>
Pierre GM wrote:
> On Monday 05 May 2008 13:19:40 Russell E. Owen wrote:
>> The object returned by maskedArray.compressed() appears to be a normal
>> numpy array (based on repr output), but in reality it has some
>> surprising differences:
>
> Russell:
>
> * I assume you're not using the latest v
On Monday 05 May 2008 13:19:40 Russell E. Owen wrote:
> The object returned by maskedArray.compressed() appears to be a normal
> numpy array (based on repr output), but in reality it has some
> surprising differences:
Russell:
* I assume you're not using the latest version of numpy, are you ? If
Robert Kern wrote:
> I don't know the reason why it's not an ndarray, but you don't have to
> copy the data again to get one:
>
> c = ma.compressed().view(numpy.ndarray)
would:
c - numpy.asarray(ma.compressed())
work too?
-CHB
--
Christopher Barker, Ph.D.
Oceanographer
Emergency Respons
On Mon, May 5, 2008 at 12:19 PM, Russell E. Owen <[EMAIL PROTECTED]> wrote:
> The object returned by maskedArray.compressed() appears to be a normal
> numpy array (based on repr output), but in reality it has some
> surprising differences:
>
> import numpy
> a = numpy.arange(10, dtype=int)
> b
The object returned by maskedArray.compressed() appears to be a normal
numpy array (based on repr output), but in reality it has some
surprising differences:
import numpy
a = numpy.arange(10, dtype=int)
b = numpy.zeros(10)
b[1] = 1
b[3] = 1
ma = numpy.core.ma.array(a, mask=b, dtype=float)
print