[Numpy-discussion] ANN: SfePy 2013.4
I am pleased to announce release 2013.4 of SfePy. Description --- SfePy (simple finite elements in Python) is a software for solving systems of coupled partial differential equations by the finite element method. The code is based on NumPy and SciPy packages. It is distributed under the new BSD license. Home page: http://sfepy.org Mailing list: http://groups.google.com/group/sfepy-devel Git (source) repository, issue tracker, wiki: http://github.com/sfepy Highlights of this release -- - simplified quadrature definition - equation sequence solver - initial support for 'plate' integration/connectivity type - script for visualization of quadrature points and weights For full release notes see http://docs.sfepy.org/doc/release_notes.html#id1 (rather long and technical). Best regards, Robert Cimrman and Contributors (*) (*) Contributors to this release (alphabetical order): Vladimír Lukeš, Jaroslav Vondřejc ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
[Numpy-discussion] (no subject)
Hi, I'm sorry if I missed something obvious - but is there a vectorized way to look for None in an array? In [3]: a = np.array([1, 1]) In [4]: a == object() Out[4]: array([False, False], dtype=bool) In [6]: a == None Out[6]: False (same for object arrays), Thanks a lot, Matthew ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] Silencing NumPy output
I didn't forgot this, but I got side tracked. Here is the Theano code I would like to try to use to replace os.system: https://github.com/Theano/Theano/blob/master/theano/misc/windows.py But I won't be able to try this before next week. Fred On Fri, Nov 15, 2013 at 5:49 PM, David Cournapeau courn...@gmail.com wrote: On Fri, Nov 15, 2013 at 7:41 PM, Robert Kern robert.k...@gmail.com wrote: On Fri, Nov 15, 2013 at 7:28 PM, David Cournapeau courn...@gmail.com wrote: On Fri, Nov 15, 2013 at 6:21 PM, Charles R Harris charlesr.har...@gmail.com wrote: Sure, give it a shot. Looks like subprocess.Popen was intended to replace os.system in any case. Except that output is not 'real time' with straight Popen, and doing so reliably on every platform (cough - windows - cough) is not completely trivial. You also have to handle buffered output, etc... That code is very fragile, so this would be quite a lot of testing to change, and I am not sure it worths it. It doesn't have to be real time. Just use .communicate() and print out the stdout and stderr to their appropriate streams after the subprocess finishes. Indeed, it does not have to be, but that's useful for debugging compilation issues (not so much for numpy itself, but for some packages which have files that takes a very long time to build, like scipy.sparsetools or bottleneck). That's a minor point compared to the potential issues when building on windows, though. David ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] (no subject)
On Fri, Nov 22, 2013 at 4:23 PM, Matthew Brett matthew.br...@gmail.comwrote: Hi, I'm sorry if I missed something obvious - but is there a vectorized way to look for None in an array? In [3]: a = np.array([1, 1]) In [4]: a == object() Out[4]: array([False, False], dtype=bool) In [6]: a == None Out[6]: False (same for object arrays), Looks like using a scalar array that holds the value None will work: In [8]: a Out[8]: array([[1, 2], 'foo', None], dtype=object) In [9]: a == np.array(None) Out[9]: array([False, False, True], dtype=bool) Warren Thanks a lot, Matthew ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] (no subject)
On Fri, Nov 22, 2013 at 9:23 PM, Matthew Brett matthew.br...@gmail.com wrote: Hi, I'm sorry if I missed something obvious - but is there a vectorized way to look for None in an array? In [3]: a = np.array([1, 1]) In [4]: a == object() Out[4]: array([False, False], dtype=bool) In [6]: a == None Out[6]: False [~] |1 x = np.array([1, None, 2], dtype=object) [~] |2 np.equal(x, None) array([False, True, False], dtype=bool) -- Robert Kern ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
[Numpy-discussion] numpy.i and INPLACE_ARRAY1[ANY]
Hey,
I am trying to improve the Lilv http://drobilla.net/software/lilv/ Python
bindings to include numpy.i to allow for creation and verification of audio
test buffers using NumPy.
I am just trying to get *something* working at the moment so I am tring to
wrap a test function.
static inline void
lilv_test(float* data_location){}
and I have in lilv.i:
%apply (float* INPLACE_ARRAY1) {(float* data_location)};
This doesn’t produce any warnings or anything but when I try and use it
from Python I get:
TypeError: in method 'lilv_test', argument 1 of type 'float *'
What does work is if I have:
lilv_test(float* data_location, int n){}
and
%apply (float* INPLACE_ARRAY1, int DIM1) {(float* data_location, int n)};
but this doesn’t fit very well with the functions I eventually want to
wrap, as they don’t have a dimension argument.
Is it not possible to use INPLACE_ARRAY1 without a dimension?
Thanks for any help,
Kaspar
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Re: [Numpy-discussion] [EXTERNAL] numpy.i and INPLACE_ARRAY1[ANY]
Kaspar,
Yes, in order for numpy.i typemaps to work, you need to provide dimensions.
How is lilv_test(float*) supposed to know how large the float array is? Is it
actually a method where the class knows the size? In cases where dimensions
are not passed through the argument list, you have two options:
1. Write a proxy function that does have dimension arguments and calls the
original function, and then wrap that instead of the original function.
2. Use the functions and macros in numpy.i to write new typemaps that work
for your case.
-Bill
On Nov 22, 2013, at 3:30 PM, Kaspar Emanuel wrote:
Hey,
I am trying to improve the Lilv Python bindings to include numpy.i to allow
for creation and verification of audio test buffers using NumPy.
I am just trying to get something working at the moment so I am tring to wrap
a test function.
static inline void
lilv_test(float* data_location){}
and I have in lilv.i:
%apply (float* INPLACE_ARRAY1) {(float* data_location)};
This doesn’t produce any warnings or anything but when I try and use it from
Python I get:
TypeError: in method 'lilv_test', argument 1 of type 'float *'
What does work is if I have:
lilv_test(float* data_location, int n){}
and
%apply (float* INPLACE_ARRAY1, int DIM1) {(float* data_location, int n)};
but this doesn’t fit very well with the functions I eventually want to wrap,
as they don’t have a dimension argument.
Is it not possible to use INPLACE_ARRAY1 without a dimension?
Thanks for any help,
Kaspar
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** P.O. Box 5800 Fax: (505)284-0154 **
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Re: [Numpy-discussion] [EXTERNAL] numpy.i and INPLACE_ARRAY1[ANY]
Hi Bill,
thanks for your response. So the function I am actually trying to wrap is:
static inline void
lilv_instance_connect_port(LilvInstance* instance,
uint32_t port_index,
void* data_location)
It just passes on the pointer to the data_location (the audio buffer) and
then you call lilv_instance_run(int nframes) where nframes could be the
dimension of your buffer, or possibly less if you really want.
So following your recommendations I tried to make a wrapper function:
lilv_instance_pyconnect(LilvInstance* instance,
uint32_t port_index,
float* data_location, int unused)
and then a typemap following what is in numpy.i :
%typecheck(SWIG_TYPECHECK_DOUBLE_ARRAY,
fragment=NumPy_Macros)
(UNUSED1* UNUSED2, UNUSED3 UNUSED4, DATA_TYPE* INPLACE_ARRAY1, DIM_TYPE DIM1)
{
$1 = is_array($input) PyArray_EquivTypenums(array_type($input),
DATA_TYPECODE);
}
%typemap(in,
fragment=NumPy_Fragments)
(UNUSED1* UNUSED2, UNUSED3 UNUSED4, DATA_TYPE* INPLACE_ARRAY1, DIM_TYPE DIM1)
(PyArrayObject* array=NULL, int i=1)
{
array = obj_to_array_no_conversion($input, DATA_TYPECODE);
if (!array || !require_dimensions(array,1) || !require_contiguous(array)
|| !require_native(array)) SWIG_fail;
$1 = (DATA_TYPE*) array_data(array);
$2 = 1;
for (i=0; i array_numdims(array); ++i) $2 *= array_size(array,i);
}
which I tried to apply with:
%apply (LilvInstance* instance, uint32_t port_index, float*
INPLACE_ARRAY1, int DIM1) {(LilvInstance* instance, uint32_t
port_index, float* data_location, int unused)}
But it doesn’t seem to do anything an I just get a TypeError.
You might have noticed I am a little bit out of my depth…
Ta,
Kaspar
On 22 November 2013 22:40, Bill Spotz wfsp...@sandia.gov wrote:
Kaspar,
Yes, in order for numpy.i typemaps to work, you need to provide
dimensions. How is lilv_test(float*) supposed to know how large the float
array is? Is it actually a method where the class knows the size? In
cases where dimensions are not passed through the argument list, you have
two options:
1. Write a proxy function that does have dimension arguments and calls
the original function, and then wrap that instead of the original function.
2. Use the functions and macros in numpy.i to write new typemaps that
work for your case.
-Bill
On Nov 22, 2013, at 3:30 PM, Kaspar Emanuel wrote:
Hey,
I am trying to improve the Lilv Python bindings to include numpy.i to
allow for creation and verification of audio test buffers using NumPy.
I am just trying to get something working at the moment so I am tring to
wrap a test function.
static inline void
lilv_test(float* data_location){}
and I have in lilv.i:
%apply (float* INPLACE_ARRAY1) {(float* data_location)};
This doesn’t produce any warnings or anything but when I try and use it
from Python I get:
TypeError: in method 'lilv_test', argument 1 of type 'float *'
What does work is if I have:
lilv_test(float* data_location, int n){}
and
%apply (float* INPLACE_ARRAY1, int DIM1) {(float* data_location, int n)};
but this doesn’t fit very well with the functions I eventually want to
wrap, as they don’t have a dimension argument.
Is it not possible to use INPLACE_ARRAY1 without a dimension?
Thanks for any help,
Kaspar
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** Sandia National Laboratories Voice: (505)845-0170 **
** P.O. Box 5800 Fax: (505)284-0154 **
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Re: [Numpy-discussion] [EXTERNAL] numpy.i and INPLACE_ARRAY1[ANY]
I think you are getting close. Application of the typemap simply requires
%apply (float* INPLACE_ARRAY1, int DIM1) {(float* data_location, int
unused)}
rather than the entire argument list.
Be sure you understand the use case. The (data_location, unused) pair is going
to be provided by a numpy array and its length. You might want to do a check
to make sure variable unused has the correct value before you pass the numpy
array data on to your function.
Typemaps are generally non-intuitive. But once you understand all the rules,
they start to make sense.
-Bill
On Nov 22, 2013, at 4:05 PM, Kaspar Emanuel wrote:
Hi Bill,
thanks for your response. So the function I am actually trying to wrap is:
static inline void
lilv_instance_connect_port(LilvInstance* instance,
uint32_t port_index,
void* data_location)
It just passes on the pointer to the data_location (the audio buffer) and
then you call lilv_instance_run(int nframes) where nframes could be the
dimension of your buffer, or possibly less if you really want.
So following your recommendations I tried to make a wrapper function:
lilv_instance_pyconnect(LilvInstance* instance,
uint32_t port_index,
float* data_location, int unused)
and then a typemap following what is in numpy.i :
%typecheck(SWIG_TYPECHECK_DOUBLE_ARRAY,
fragment=NumPy_Macros)
(UNUSED1* UNUSED2, UNUSED3 UNUSED4, DATA_TYPE* INPLACE_ARRAY1, DIM_TYPE
DIM1)
{
$1 = is_array($input) PyArray_EquivTypenums(array_type($input),
DATA_TYPECODE);
}
%typemap(in,
fragment=NumPy_Fragments)
(UNUSED1* UNUSED2, UNUSED3 UNUSED4, DATA_TYPE* INPLACE_ARRAY1, DIM_TYPE
DIM1)
(PyArrayObject* array=NULL, int i=1)
{
array = obj_to_array_no_conversion($input, DATA_TYPECODE);
if (!array || !require_dimensions(array,1) || !require_contiguous(array)
|| !require_native(array)) SWIG_fail;
$1 = (DATA_TYPE*) array_data(array);
$2 = 1;
for (i=0; i array_numdims(array); ++i) $2 *= array_size(array,i);
}
which I tried to apply with:
%apply (LilvInstance* instance, uint32_t port_index, float* INPLACE_ARRAY1,
int DIM1) {(LilvInstance* instance, uint32_t port_index, float*
data_location, int unused)}
But it doesn’t seem to do anything an I just get a TypeError.
You might have noticed I am a little bit out of my depth…
Ta,
Kaspar
On 22 November 2013 22:40, Bill Spotz wfsp...@sandia.gov wrote:
Kaspar,
Yes, in order for numpy.i typemaps to work, you need to provide dimensions.
How is lilv_test(float*) supposed to know how large the float array is? Is
it actually a method where the class knows the size? In cases where
dimensions are not passed through the argument list, you have two options:
1. Write a proxy function that does have dimension arguments and calls the
original function, and then wrap that instead of the original function.
2. Use the functions and macros in numpy.i to write new typemaps that work
for your case.
-Bill
On Nov 22, 2013, at 3:30 PM, Kaspar Emanuel wrote:
Hey,
I am trying to improve the Lilv Python bindings to include numpy.i to allow
for creation and verification of audio test buffers using NumPy.
I am just trying to get something working at the moment so I am tring to
wrap a test function.
static inline void
lilv_test(float* data_location){}
and I have in lilv.i:
%apply (float* INPLACE_ARRAY1) {(float* data_location)};
This doesn’t produce any warnings or anything but when I try and use it
from Python I get:
TypeError: in method 'lilv_test', argument 1 of type 'float *'
What does work is if I have:
lilv_test(float* data_location, int n){}
and
%apply (float* INPLACE_ARRAY1, int DIM1) {(float* data_location, int n)};
but this doesn’t fit very well with the functions I eventually want to
wrap, as they don’t have a dimension argument.
Is it not possible to use INPLACE_ARRAY1 without a dimension?
Thanks for any help,
Kaspar
___
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** Bill Spotz **
** Sandia National Laboratories Voice: (505)845-0170 **
** P.O. Box 5800 Fax: (505)284-0154 **
** Albuquerque, NM 87185-0370Email: wfsp...@sandia.gov **
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** Bill Spotz
Re: [Numpy-discussion] [EXTERNAL] numpy.i and INPLACE_ARRAY1[ANY]
Cool! That seems to have worked. Many thanks. So I didn't need my own
typemap for this at all as it will already ignore the rest of the
arguments?
What I still don't understand is that there seems to be a typemap for
INPLACE_ARRAY1[ANY] without any DIM1. How come I can't apply that?
Be sure you understand the use case. The (data_location, unused)
pair is going to be provided by a numpy array and its length. You
might want to do a check to make sure variable unused has the
correct value before you pass the numpy array data on to your
function.
The only point where the check could be made would be in the run
function which should not be run with a value longer than the array
length.
On 22 November 2013 23:19, Bill Spotz wfsp...@sandia.gov wrote:
I think you are getting close. Application of the typemap simply requires
%apply (float* INPLACE_ARRAY1, int DIM1) {(float* data_location, int
unused)}
rather than the entire argument list.
Be sure you understand the use case. The (data_location, unused) pair is
going to be provided by a numpy array and its length. You might want to do a
check to make sure variable unused has the correct value before you pass
the numpy array data on to your function.
Typemaps are generally non-intuitive. But once you understand all the rules,
they start to make sense.
-Bill
On Nov 22, 2013, at 4:05 PM, Kaspar Emanuel wrote:
Hi Bill,
thanks for your response. So the function I am actually trying to wrap is:
static inline void
lilv_instance_connect_port(LilvInstance* instance,
uint32_t port_index,
void* data_location)
It just passes on the pointer to the data_location (the audio buffer) and
then you call lilv_instance_run(int nframes) where nframes could be the
dimension of your buffer, or possibly less if you really want.
So following your recommendations I tried to make a wrapper function:
lilv_instance_pyconnect(LilvInstance* instance,
uint32_t port_index,
float* data_location, int unused)
and then a typemap following what is in numpy.i :
%typecheck(SWIG_TYPECHECK_DOUBLE_ARRAY,
fragment=NumPy_Macros)
(UNUSED1* UNUSED2, UNUSED3 UNUSED4, DATA_TYPE* INPLACE_ARRAY1, DIM_TYPE
DIM1)
{
$1 = is_array($input) PyArray_EquivTypenums(array_type($input),
DATA_TYPECODE);
}
%typemap(in,
fragment=NumPy_Fragments)
(UNUSED1* UNUSED2, UNUSED3 UNUSED4, DATA_TYPE* INPLACE_ARRAY1, DIM_TYPE
DIM1)
(PyArrayObject* array=NULL, int i=1)
{
array = obj_to_array_no_conversion($input, DATA_TYPECODE);
if (!array || !require_dimensions(array,1) || !require_contiguous(array)
|| !require_native(array)) SWIG_fail;
$1 = (DATA_TYPE*) array_data(array);
$2 = 1;
for (i=0; i array_numdims(array); ++i) $2 *= array_size(array,i);
}
which I tried to apply with:
%apply (LilvInstance* instance, uint32_t port_index, float* INPLACE_ARRAY1,
int DIM1) {(LilvInstance* instance, uint32_t port_index, float*
data_location, int unused)}
But it doesn’t seem to do anything an I just get a TypeError.
You might have noticed I am a little bit out of my depth…
Ta,
Kaspar
On 22 November 2013 22:40, Bill Spotz wfsp...@sandia.gov wrote:
Kaspar,
Yes, in order for numpy.i typemaps to work, you need to provide dimensions.
How is lilv_test(float*) supposed to know how large the float array is? Is
it actually a method where the class knows the size? In cases where
dimensions are not passed through the argument list, you have two options:
1. Write a proxy function that does have dimension arguments and calls the
original function, and then wrap that instead of the original function.
2. Use the functions and macros in numpy.i to write new typemaps that work
for your case.
-Bill
On Nov 22, 2013, at 3:30 PM, Kaspar Emanuel wrote:
Hey,
I am trying to improve the Lilv Python bindings to include numpy.i to
allow for creation and verification of audio test buffers using NumPy.
I am just trying to get something working at the moment so I am tring to
wrap a test function.
static inline void
lilv_test(float* data_location){}
and I have in lilv.i:
%apply (float* INPLACE_ARRAY1) {(float* data_location)};
This doesn’t produce any warnings or anything but when I try and use it
from Python I get:
TypeError: in method 'lilv_test', argument 1 of type 'float *'
What does work is if I have:
lilv_test(float* data_location, int n){}
and
%apply (float* INPLACE_ARRAY1, int DIM1) {(float* data_location, int n)};
but this doesn’t fit very well with the functions I eventually want to
wrap, as they don’t have a dimension argument.
Is it not possible to use INPLACE_ARRAY1 without a dimension?
Thanks for any help,
Kaspar
Re: [Numpy-discussion] [EXTERNAL] numpy.i and INPLACE_ARRAY1[ANY]
Yes, typemaps are checked against individual arguments or contiguous groups of
arguments, not necessarily the entire argument list.
I believe the argument would have to be float data_location[], signifying a
null-terminated array, rather than float*, for the INPLACE_ARRAY1[ANY] to work.
On Nov 22, 2013, at 4:32 PM, Kaspar Emanuel wrote:
Cool! That seems to have worked. Many thanks. So I didn't need my own
typemap for this at all as it will already ignore the rest of the
arguments?
What I still don't understand is that there seems to be a typemap for
INPLACE_ARRAY1[ANY] without any DIM1. How come I can't apply that?
Be sure you understand the use case. The (data_location, unused)
pair is going to be provided by a numpy array and its length. You
might want to do a check to make sure variable unused has the
correct value before you pass the numpy array data on to your
function.
The only point where the check could be made would be in the run
function which should not be run with a value longer than the array
length.
On 22 November 2013 23:19, Bill Spotz wfsp...@sandia.gov wrote:
I think you are getting close. Application of the typemap simply requires
%apply (float* INPLACE_ARRAY1, int DIM1) {(float* data_location, int
unused)}
rather than the entire argument list.
Be sure you understand the use case. The (data_location, unused) pair is
going to be provided by a numpy array and its length. You might want to do
a check to make sure variable unused has the correct value before you pass
the numpy array data on to your function.
Typemaps are generally non-intuitive. But once you understand all the
rules, they start to make sense.
-Bill
On Nov 22, 2013, at 4:05 PM, Kaspar Emanuel wrote:
Hi Bill,
thanks for your response. So the function I am actually trying to wrap is:
static inline void
lilv_instance_connect_port(LilvInstance* instance,
uint32_t port_index,
void* data_location)
It just passes on the pointer to the data_location (the audio buffer) and
then you call lilv_instance_run(int nframes) where nframes could be the
dimension of your buffer, or possibly less if you really want.
So following your recommendations I tried to make a wrapper function:
lilv_instance_pyconnect(LilvInstance* instance,
uint32_t port_index,
float* data_location, int unused)
and then a typemap following what is in numpy.i :
%typecheck(SWIG_TYPECHECK_DOUBLE_ARRAY,
fragment=NumPy_Macros)
(UNUSED1* UNUSED2, UNUSED3 UNUSED4, DATA_TYPE* INPLACE_ARRAY1, DIM_TYPE
DIM1)
{
$1 = is_array($input) PyArray_EquivTypenums(array_type($input),
DATA_TYPECODE);
}
%typemap(in,
fragment=NumPy_Fragments)
(UNUSED1* UNUSED2, UNUSED3 UNUSED4, DATA_TYPE* INPLACE_ARRAY1, DIM_TYPE
DIM1)
(PyArrayObject* array=NULL, int i=1)
{
array = obj_to_array_no_conversion($input, DATA_TYPECODE);
if (!array || !require_dimensions(array,1) || !require_contiguous(array)
|| !require_native(array)) SWIG_fail;
$1 = (DATA_TYPE*) array_data(array);
$2 = 1;
for (i=0; i array_numdims(array); ++i) $2 *= array_size(array,i);
}
which I tried to apply with:
%apply (LilvInstance* instance, uint32_t port_index, float* INPLACE_ARRAY1,
int DIM1) {(LilvInstance* instance, uint32_t port_index, float*
data_location, int unused)}
But it doesn’t seem to do anything an I just get a TypeError.
You might have noticed I am a little bit out of my depth…
Ta,
Kaspar
On 22 November 2013 22:40, Bill Spotz wfsp...@sandia.gov wrote:
Kaspar,
Yes, in order for numpy.i typemaps to work, you need to provide dimensions.
How is lilv_test(float*) supposed to know how large the float array is?
Is it actually a method where the class knows the size? In cases where
dimensions are not passed through the argument list, you have two options:
1. Write a proxy function that does have dimension arguments and calls the
original function, and then wrap that instead of the original function.
2. Use the functions and macros in numpy.i to write new typemaps that work
for your case.
-Bill
On Nov 22, 2013, at 3:30 PM, Kaspar Emanuel wrote:
Hey,
I am trying to improve the Lilv Python bindings to include numpy.i to
allow for creation and verification of audio test buffers using NumPy.
I am just trying to get something working at the moment so I am tring to
wrap a test function.
static inline void
lilv_test(float* data_location){}
and I have in lilv.i:
%apply (float* INPLACE_ARRAY1) {(float* data_location)};
This doesn’t produce any warnings or anything but when I try and use it
from Python I get:
TypeError: in method 'lilv_test', argument 1 of type 'float *'
What does work is if I have:
lilv_test(float*
Re: [Numpy-discussion] [EXTERNAL] numpy.i and INPLACE_ARRAY1[ANY]
OK yeah, I tested with float data_location[] but then it expects and
array of length 0, (shape [0] it says). With float data_location[64] I
can use 64 size array but this isn't very useful in this instance. I
will try and make a typemap for just (float* INPLACE_ARRAY) without a
DIM1 as that's probably the cleanest.
When I was playing with the typemaps before I put %typecheck and
%typemap in lilv.i just under %include numpy.i (as in attached) but
I don't think they were actually noticed till I put them in numpy.i
itself. Where is the appropriate place to extend these?
On 22 November 2013 23:44, Bill Spotz wfsp...@sandia.gov wrote:
Yes, typemaps are checked against individual arguments or contiguous groups
of arguments, not necessarily the entire argument list.
I believe the argument would have to be float data_location[], signifying a
null-terminated array, rather than float*, for the INPLACE_ARRAY1[ANY] to
work.
On Nov 22, 2013, at 4:32 PM, Kaspar Emanuel wrote:
Cool! That seems to have worked. Many thanks. So I didn't need my own
typemap for this at all as it will already ignore the rest of the
arguments?
What I still don't understand is that there seems to be a typemap for
INPLACE_ARRAY1[ANY] without any DIM1. How come I can't apply that?
Be sure you understand the use case. The (data_location, unused)
pair is going to be provided by a numpy array and its length. You
might want to do a check to make sure variable unused has the
correct value before you pass the numpy array data on to your
function.
The only point where the check could be made would be in the run
function which should not be run with a value longer than the array
length.
On 22 November 2013 23:19, Bill Spotz wfsp...@sandia.gov wrote:
I think you are getting close. Application of the typemap simply requires
%apply (float* INPLACE_ARRAY1, int DIM1) {(float* data_location, int
unused)}
rather than the entire argument list.
Be sure you understand the use case. The (data_location, unused) pair is
going to be provided by a numpy array and its length. You might want to do
a check to make sure variable unused has the correct value before you
pass the numpy array data on to your function.
Typemaps are generally non-intuitive. But once you understand all the
rules, they start to make sense.
-Bill
On Nov 22, 2013, at 4:05 PM, Kaspar Emanuel wrote:
Hi Bill,
thanks for your response. So the function I am actually trying to wrap is:
static inline void
lilv_instance_connect_port(LilvInstance* instance,
uint32_t port_index,
void* data_location)
It just passes on the pointer to the data_location (the audio buffer) and
then you call lilv_instance_run(int nframes) where nframes could be the
dimension of your buffer, or possibly less if you really want.
So following your recommendations I tried to make a wrapper function:
lilv_instance_pyconnect(LilvInstance* instance,
uint32_t port_index,
float* data_location, int unused)
and then a typemap following what is in numpy.i :
%typecheck(SWIG_TYPECHECK_DOUBLE_ARRAY,
fragment=NumPy_Macros)
(UNUSED1* UNUSED2, UNUSED3 UNUSED4, DATA_TYPE* INPLACE_ARRAY1, DIM_TYPE
DIM1)
{
$1 = is_array($input) PyArray_EquivTypenums(array_type($input),
DATA_TYPECODE);
}
%typemap(in,
fragment=NumPy_Fragments)
(UNUSED1* UNUSED2, UNUSED3 UNUSED4, DATA_TYPE* INPLACE_ARRAY1, DIM_TYPE
DIM1)
(PyArrayObject* array=NULL, int i=1)
{
array = obj_to_array_no_conversion($input, DATA_TYPECODE);
if (!array || !require_dimensions(array,1) || !require_contiguous(array)
|| !require_native(array)) SWIG_fail;
$1 = (DATA_TYPE*) array_data(array);
$2 = 1;
for (i=0; i array_numdims(array); ++i) $2 *= array_size(array,i);
}
which I tried to apply with:
%apply (LilvInstance* instance, uint32_t port_index, float*
INPLACE_ARRAY1, int DIM1) {(LilvInstance* instance, uint32_t port_index,
float* data_location, int unused)}
But it doesn’t seem to do anything an I just get a TypeError.
You might have noticed I am a little bit out of my depth…
Ta,
Kaspar
On 22 November 2013 22:40, Bill Spotz wfsp...@sandia.gov wrote:
Kaspar,
Yes, in order for numpy.i typemaps to work, you need to provide
dimensions. How is lilv_test(float*) supposed to know how large the float
array is? Is it actually a method where the class knows the size? In
cases where dimensions are not passed through the argument list, you have
two options:
1. Write a proxy function that does have dimension arguments and calls
the original function, and then wrap that instead of the original function.
2. Use the functions and macros in numpy.i to write new typemaps that
work for your case.
-Bill
On Nov 22, 2013, at 3:30 PM, Kaspar Emanuel
Re: [Numpy-discussion] [EXTERNAL] numpy.i and INPLACE_ARRAY1[ANY]
Here is the typemap for anyone with a similar problem:
/* Typemap suite for (DATA_TYPE* INPLACE_ARRAY1)
*/
%typecheck(SWIG_TYPECHECK_DOUBLE_ARRAY,
fragment=NumPy_Macros)
(DATA_TYPE* INPLACE_ARRAY1)
{
$1 = is_array($input) PyArray_EquivTypenums(array_type($input),
DATA_TYPECODE);
}
%typemap(in,
fragment=NumPy_Fragments)
(DATA_TYPE* INPLACE_ARRAY1)
(PyArrayObject* array=NULL)
{
array = obj_to_array_no_conversion($input, DATA_TYPECODE);
if (!array || !require_dimensions(array,1) || !require_contiguous(array)
|| !require_native(array)) SWIG_fail;
$1 = (DATA_TYPE*) array_data(array);
}
It seems I have to put it in numpy.i for it to be used.
On 22 November 2013 23:56, Kaspar Emanuel kaspar.eman...@gmail.com wrote:
OK yeah, I tested with float data_location[] but then it expects and
array of length 0, (shape [0] it says). With float data_location[64] I
can use 64 size array but this isn't very useful in this instance. I
will try and make a typemap for just (float* INPLACE_ARRAY) without a
DIM1 as that's probably the cleanest.
When I was playing with the typemaps before I put %typecheck and
%typemap in lilv.i just under %include numpy.i (as in attached) but
I don't think they were actually noticed till I put them in numpy.i
itself. Where is the appropriate place to extend these?
On 22 November 2013 23:44, Bill Spotz wfsp...@sandia.gov wrote:
Yes, typemaps are checked against individual arguments or contiguous
groups of arguments, not necessarily the entire argument list.
I believe the argument would have to be float data_location[],
signifying a null-terminated array, rather than float*, for the
INPLACE_ARRAY1[ANY] to work.
On Nov 22, 2013, at 4:32 PM, Kaspar Emanuel wrote:
Cool! That seems to have worked. Many thanks. So I didn't need my own
typemap for this at all as it will already ignore the rest of the
arguments?
What I still don't understand is that there seems to be a typemap for
INPLACE_ARRAY1[ANY] without any DIM1. How come I can't apply that?
Be sure you understand the use case. The (data_location, unused)
pair is going to be provided by a numpy array and its length. You
might want to do a check to make sure variable unused has the
correct value before you pass the numpy array data on to your
function.
The only point where the check could be made would be in the run
function which should not be run with a value longer than the array
length.
On 22 November 2013 23:19, Bill Spotz wfsp...@sandia.gov wrote:
I think you are getting close. Application of the typemap simply
requires
%apply (float* INPLACE_ARRAY1, int DIM1) {(float* data_location,
int unused)}
rather than the entire argument list.
Be sure you understand the use case. The (data_location, unused) pair
is going to be provided by a numpy array and its length. You might want to
do a check to make sure variable unused has the correct value before you
pass the numpy array data on to your function.
Typemaps are generally non-intuitive. But once you understand all the
rules, they start to make sense.
-Bill
On Nov 22, 2013, at 4:05 PM, Kaspar Emanuel wrote:
Hi Bill,
thanks for your response. So the function I am actually trying to
wrap is:
static inline void
lilv_instance_connect_port(LilvInstance* instance,
uint32_t port_index,
void* data_location)
It just passes on the pointer to the data_location (the audio buffer)
and then you call lilv_instance_run(int nframes) where nframes could be the
dimension of your buffer, or possibly less if you really want.
So following your recommendations I tried to make a wrapper function:
lilv_instance_pyconnect(LilvInstance* instance,
uint32_t port_index,
float* data_location, int unused)
and then a typemap following what is in numpy.i :
%typecheck(SWIG_TYPECHECK_DOUBLE_ARRAY,
fragment=NumPy_Macros)
(UNUSED1* UNUSED2, UNUSED3 UNUSED4, DATA_TYPE* INPLACE_ARRAY1,
DIM_TYPE DIM1)
{
$1 = is_array($input) PyArray_EquivTypenums(array_type($input),
DATA_TYPECODE);
}
%typemap(in,
fragment=NumPy_Fragments)
(UNUSED1* UNUSED2, UNUSED3 UNUSED4, DATA_TYPE* INPLACE_ARRAY1,
DIM_TYPE DIM1)
(PyArrayObject* array=NULL, int i=1)
{
array = obj_to_array_no_conversion($input, DATA_TYPECODE);
if (!array || !require_dimensions(array,1) ||
!require_contiguous(array)
|| !require_native(array)) SWIG_fail;
$1 = (DATA_TYPE*) array_data(array);
$2 = 1;
for (i=0; i array_numdims(array); ++i) $2 *= array_size(array,i);
}
which I tried to apply with:
%apply (LilvInstance* instance, uint32_t port_index, float*
INPLACE_ARRAY1, int DIM1)
