Re: [Numpy-discussion] Math Inspector Beta

[Mansour Moufid]

Very cool!

But the Mac disk image (mathinspector_0.9.1.dmg) isn't opening ("corrupt
image").

It's 145279488 bytes and the shasum ends with f1ed9231.
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Re: [Numpy-discussion] Unreliable crash when converting using numpy.asarray via C buffer interface

[Mansour Moufid]

On Tue, Jan 26, 2021 at 3:50 AM Friedrich Romstedt
 wrote:
>
> Hi,
>
> This is with Python 3.8.2 64-bit and numpy 1.19.2 on Windows 10.  I'd
> like to be able to convert some C++ extension type to a numpy array by
> using ``numpy.asarray``.  The extension type implements the Python
> buffer interface to support this.
>
> The extension type, called "Image" here, holds some chunk of
> ``double``, C order, contiguous, 2 dimensions.  It "owns" the buffer;
> the buffer is not shared with other objects.  The following Python
> code crashes::
>
> image = <... Image production ...>
> ar = numpy.asarray(image)
>
> However, when I say::
>
> image = <... Image production ...>
> print("---")
> ar = numpy.asarray(image)
>
> the entire program is executing properly with correct data in the
> numpy ndarray produced using the buffer interface.

Maybe a dereference bug.

Try setting pointers to NULL after freeing, something like this:

delete[] view->shape;
view->shape = NULL;
delete[] view->strides;
view->strides = NULL;

...

delete[] self->data;
self->data = NULL;
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Re: [Numpy-discussion] Unreliable crash when converting using numpy.asarray via C buffer interface

[Mansour Moufid]

On Mon, Feb 15, 2021 at 7:35 PM Mansour Moufid  wrote:
>
> On Tue, Jan 26, 2021 at 3:50 AM Friedrich Romstedt
>  wrote:
> >
> > Hi,
> >
> > This is with Python 3.8.2 64-bit and numpy 1.19.2 on Windows 10.  I'd
> > like to be able to convert some C++ extension type to a numpy array by
> > using ``numpy.asarray``.  The extension type implements the Python
> > buffer interface to support this.
> >
> > The extension type, called "Image" here, holds some chunk of
> > ``double``, C order, contiguous, 2 dimensions.  It "owns" the buffer;
> > the buffer is not shared with other objects.  The following Python
> > code crashes::
> >
> > image = <... Image production ...>
> > ar = numpy.asarray(image)
> >
> > However, when I say::
> >
> > image = <... Image production ...>
> > print("---")
> > ar = numpy.asarray(image)
> >
> > the entire program is executing properly with correct data in the
> > numpy ndarray produced using the buffer interface.
>
> Maybe a dereference bug.
>
> Try setting pointers to NULL after freeing, something like this:
>
> delete[] view->shape;
> view->shape = NULL;
> delete[] view->strides;
> view->strides = NULL;
>
> ...
>
> delete[] self->data;
> self->data = NULL;

Sorry for two messages in a row, I just noticed:

I don't see the type's tp_free member defined?

You can set it to PyObject_Free in Init_ImageType:

ImageType.tp_free = PyObject_Free;

See here: https://docs.python.org/3/c-api/typeobj.html#c.PyTypeObject.tp_free
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[Numpy-discussion] Re: dtype=(bool) vs dtype=bool

[Mansour Moufid]

On Tue, Oct 19, 2021 at 9:43 AM  wrote:
>
> See the following testing in IPython shell:
>
> In [6]: import numpy as np
>
> In [7]: a = np.array([1], dtype=(bool))
>
> In [8]: b = np.array([1], dtype=bool)
>
> In [9]: a
> Out[9]: array([ True])
>
> In [10]: b
> Out[10]: array([ True])
>
> It seems that dtype=(bool) and dtype=bool are both correct usages. If so, 
> which is preferable?

For a one-element tuple, add a comma:

>>> bool

>>> (bool)

>>> (bool,)
(,)
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