Christopher Barker wrote:

Hi folks,

Someone on the wxPython list posted a nifty recarray example that I don't quite understand. The idea is to have an array for an RGBA image:

rgbarec = numpy.dtype({'r':(numpy.uint8,0), 'g':(numpy.uint8,1), 'b':(numpy.uint8,2), 'a':(numpy.uint8,3)})

A = numpy.zeros(shape, dtype=(numpy.uint32, rgbarec) )

what I don't understand is having BOTH numpy.uint32 and rgbrec as the dtype. How does that work?

Basically, the rgbarec defines the fields, but the "base-type" for the numpy array is numpy.uint32 (rather than VOID which is the default data-type for arrays with fields defined). This is why it prints the way it does. I'm not sure what the real value is doing it that way as opposed to just having two views on the data: one as a uint32 and another as a "normal" recarray with a VOID data-type underlying it) like you suggest at the end. I think it's really just the "architecture" showing through to the user layer. -Travis

Stéfan van der Walt wrote:

That's the way, or just rgba_image.view(numpy.int32).

ah -- interestingly, I tried: rgba_image.view(dtype=numpy.int32) and got: Traceback (most recent call last): File "<stdin>", line 1, in <module> TypeError: view() takes no keyword arguments Since it is optional, shouldn't it be keyword argument? -Chris -- Christopher Barker, Ph.D. Oceanographer Emergency Response Division NOAA/NOS/OR&R (206) 526-6959 voice 7600 Sand Point Way NE (206) 526-6329 fax Seattle, WA 98115 (206) 526-6317 main reception Chris.Barker@noaa.gov

Stéfan van der Walt wrote:

2008/4/30 Christopher Barker :

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Stéfan van der Walt wrote:

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That's the way, or just rgba_image.view(numpy.int32).

ah -- interestingly, I tried:

rgba_image.view(dtype=numpy.int32)

and got:

Traceback (most recent call last): File "<stdin>", line 1, in <module> TypeError: view() takes no keyword arguments

Since it is optional, shouldn't it be keyword argument?

Thanks, fixed in r5115.

This was too hasty. I had considered this before. The problem with this is that the object can be either a type object or a data-type object. You can use view to both re-cast a numpy array as another subtype or as another data-type. So, please revert the change until a better solution is posted. -Travis

2008/5/1 Travis E. Oliphant :

Stéfan van der Walt wrote:

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2008/4/30 Christopher Barker :

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Stéfan van der Walt wrote:

...

That's the way, or just rgba_image.view(numpy.int32).

ah -- interestingly, I tried:

rgba_image.view(dtype=numpy.int32)

and got:

Traceback (most recent call last): File "<stdin>", line 1, in <module> TypeError: view() takes no keyword arguments

Since it is optional, shouldn't it be keyword argument?

Thanks, fixed in r5115.

This was too hasty. I had considered this before.

The problem with this is that the object can be either a type object or a data-type object. You can use view to both re-cast a numpy array as another subtype or as another data-type.

So, please revert the change until a better solution is posted.

If we're going to support keyword arguments, shouldn't those two options be *different* keywords (dtype and ndarray_subclass, say)? Then a single non-keyword argument tells numpy to guess which one you wanted... Anne

Stéfan van der Walt wrote:

2008/5/1 Travis E. Oliphant :

...

Stéfan van der Walt wrote:

...

2008/4/30 Christopher Barker :

...

Stéfan van der Walt wrote:

...

That's the way, or just rgba_image.view(numpy.int32).

ah -- interestingly, I tried:

rgba_image.view(dtype=numpy.int32)

and got:

Traceback (most recent call last): File "<stdin>", line 1, in <module> TypeError: view() takes no keyword arguments

Since it is optional, shouldn't it be keyword argument?

Thanks, fixed in r5115.

This was too hasty. I had considered this before.

The problem with this is that the object can be either a type object or a data-type object. You can use view to both re-cast a numpy array as another subtype or as another data-type.

So, please revert the change until a better solution is posted.

OK, I see your point. I'm working on a patch that does the following:

def view(type_or_dtype=None, dtype=None, type=None): if type_or_dtype: if dtype: raise ValueError("Cannot specify dtype twice") if type: raise ValueError("Cannot specify type twice")

if isinstance(type_or_dtype,py_type): type = type_or_dtype

if isinstance(type_or_dtype,numpy_dtype): dtype = type_or_dtype

return x.view(type=type).view(dtype=dtype)

Would that be a satisfying solution? I'll be back around 21:00 SAST to attend to the matter.

Yes, I think that would work. You need to do some checking for type=None and dtype=None as well, though. That way, the first argument would continue to work as now but be labeled correctly, but it would also support dtype= and type= keywords. -Travis

2008/5/1 Travis E. Oliphant :

...

OK, I see your point. I'm working on a patch that does the following:

def view(type_or_dtype=None, dtype=None, type=None): if type_or_dtype: if dtype: raise ValueError("Cannot specify dtype twice") if type: raise ValueError("Cannot specify type twice")

if isinstance(type_or_dtype,py_type): type = type_or_dtype

if isinstance(type_or_dtype,numpy_dtype): dtype = type_or_dtype

return x.view(type=type).view(dtype=dtype)

Would that be a satisfying solution? I'll be back around 21:00 SAST to attend to the matter.

Yes, I think that would work. You need to do some checking for type=None and dtype=None as well, though.

That way, the first argument would continue to work as now but be labeled correctly, but it would also support dtype= and type= keywords.

Please review http://projects.scipy.org/scipy/numpy/changeset/5117. Thanks Stéfan

On Thu, 01 May 2008, Christopher Barker apparently wrote:

Maybe we should have a Wiki page for "stuff we'd like to change, but won't until major API breakage is otherwise occurring"

Perhaps URL:http://www.scipy.org/ProposedEnhancements would suffice? Cheers, Alan

2008/5/1 Travis E. Oliphant :

Stéfan van der Walt wrote:

...

2008/5/1 Travis E. Oliphant :

...

...

OK, I see your point. I'm working on a patch that does the following:

def view(type_or_dtype=None, dtype=None, type=None): if type_or_dtype: if dtype: raise ValueError("Cannot specify dtype twice") if type: raise ValueError("Cannot specify type twice")

if isinstance(type_or_dtype,py_type): type = type_or_dtype

if isinstance(type_or_dtype,numpy_dtype): dtype = type_or_dtype

return x.view(type=type).view(dtype=dtype)

Would that be a satisfying solution? I'll be back around 21:00 SAST to attend to the matter.

Yes, I think that would work. You need to do some checking for type=None and dtype=None as well, though.

That way, the first argument would continue to work as now but be labeled correctly, but it would also support dtype= and type= keywords.

Please review http://projects.scipy.org/scipy/numpy/changeset/5117.

Check out

http://projects.scipy.org/scipy/numpy/changeset/5119

I think that's fine. It doesn't support weird combinations like x.view(np.matrix,dtype=np.int32) but people probably shouldn't do that anyway. Cheers Stéfan