Re: [Numpy-discussion] Non-writeable default for numpy.ndarray

2006-10-01 Thread Francesc Altet
El dv 29 de 09 del 2006 a les 16:27 -0600, en/na Travis Oliphant va escriure: > Francesc Altet wrote: > > >I see. Thanks for the explanation. > > > > > You deserve the thanks for the great testing of less-traveled corners of > NumPy. It's exactly the kind of thing needed to get NumPy ready fo

Re: [Numpy-discussion] Non-writeable default for numpy.ndarray

2006-09-29 Thread Travis Oliphant
Francesc Altet wrote: >I see. Thanks for the explanation. > > You deserve the thanks for the great testing of less-traveled corners of NumPy. It's exactly the kind of thing needed to get NumPy ready for release. -Travis ---

Re: [Numpy-discussion] Non-writeable default for numpy.ndarray

2006-09-29 Thread Tim Hochberg
Travis Oliphant wrote: > Tim Hochberg wrote: > >> Francesc Altet wrote: >> >> It's not that the it's being built from ndarray, it's that the buffer >> that you are passing it is read only. >> > This is correct. > >> In fact, I'd argue that allowing >> the writeable flag to be set t

Re: [Numpy-discussion] Non-writeable default for numpy.ndarray

2006-09-29 Thread Travis Oliphant
Tim Hochberg wrote: > Francesc Altet wrote: > > It's not that the it's being built from ndarray, it's that the buffer > that you are passing it is read only. This is correct. > In fact, I'd argue that allowing > the writeable flag to be set to True in this case is actually a bug. > It's a

Re: [Numpy-discussion] Non-writeable default for numpy.ndarray

2006-09-29 Thread Francesc Altet
A Divendres 29 Setembre 2006 18:12, Tim Hochberg va escriure: > It's not that the it's being built from ndarray, it's that the buffer > that you are passing it is read only. In fact, I'd argue that allowing > the writeable flag to be set to True in this case is actually a bug. > > Consider this sli

Re: [Numpy-discussion] Non-writeable default for numpy.ndarray

2006-09-29 Thread Tim Hochberg
Francesc Altet wrote: > Hello, > > Is the next a bug a feature? > > In [102]: f4=numpy.ndarray(buffer="a\x00b"*4, dtype="f4", shape=3) > > In [103]: f4 > Out[103]: array([ 2.60561966e+20, 8.94319890e-39, 5.92050103e+20], > dtype=float32) > > In [104]: f4[2] = 2 > -