ma, 2010-01-11 kello 16:11 -0800, Christopher Barker kirjoitti:
[clip]
If no conversion is performed, zero is returned and the value of nptr
is stored in the location referenced by endptr.
off do do some more testing, but I guess that means that those pointers
need to be checked after the
Hi,
I'm trying to build a differential equation integrator and later a stochastic
differential equation integrator.
I'm having trouble getting f2py to work where the callback itself receives an
array from the Fortran routine does some work on it and then passes an array
back.
For the
Hi,
The problem is that f2py does not support callbacks that
return arrays. There is easy workaround to that: provide
returnable arrays as arguments to callback functions.
Using your example:
SUBROUTINE CallbackTest(dv,v0,Vout,N)
IMPLICIT NONE
!F2PY intent( hide ):: N
INTEGER:: N, ic
filter(lambda x: x.startswith('eig'),dir(np.linalg))
['eig', 'eigh', 'eigvals', 'eigvalsh']
import scipy.linalg as spla
filter(lambda x: x.startswith('eig'),dir(spla))
['eig', 'eig_banded', 'eigh', 'eigvals', 'eigvals_banded', 'eigvalsh']
hth,
Alan Isaac
On 1/12/2010 1:35 AM, Jankins wrote:
from scipy.sparse.linalg.eigen import eigen
Traceback (most recent call last):
File stdin, line 1, inmodule
ImportError: cannot import name eigen
Look at David's example:
from scipy.sparse.linalg import eigen
hth,
Alan Isaac
import scipy.sparse.linalg as linalg
dir(linalg)
['LinearOperator', 'Tester', '__all__', '__builtins__', '__doc__',
'__file__', '
__name__', '__package__', '__path__', 'aslinearoperator', 'bench',
'bicg', 'bicg
stab', 'cg', 'cgs', 'dsolve', 'eigen', 'factorized', 'gmres',
'interface', 'isol
On Tue, Jan 12, 2010 at 4:11 PM, Jankins andyjian430...@gmail.com wrote:
Hi
On my Ubuntu, I would reach the arpack wrapper as follows:
from scipy.sparse.linalg.eigen.arpack import eigen
However, I'd guess that you deal with a symmetric matrix (Laplacian or
adjacency matrix), so the symmetric
We have noticed the MaskedArray implementation in numpy-1.4.0 breaks
some of our code. For instance we see the following:
in 1.3.0:
a = numpy.ma.MaskedArray([[1,2,3],[4,5,6]])
numpy.ma.sum(a, 1)
masked_array(data = [ 6 15],
mask = False,
fill_value = 99)
in 1.4.0
a =
Thanks so so much.
Finally, it works.
import scipy.sparse.linalg.eigen.arpack as arpack
dir(arpack)
['__builtins__', '__doc__', '__file__', '__name__', '__package__',
'__path__', '
_arpack', 'arpack', 'aslinearoperator', 'eigen', 'eigen_symmetric',
'np', 'speig
s', 'warnings']
But I
On 11/01/2010 18:10, josef.p...@gmail.com wrote:
For this problem, it's supposed to be only those packages that have or
import cython generated code.
Right; is this a known bug, is there a known fix for mac dmgs ?
(Whisper, how'd it get past testing ?)
scipy/stats/__init__.py has an apparent
On Tue, Jan 12, 2010 at 10:33, denis denis-bz...@t-online.de wrote:
On 11/01/2010 18:10, josef.p...@gmail.com wrote:
For this problem, it's supposed to be only those packages that have or
import cython generated code.
Right; is this a known bug, is there a known fix for mac dmgs ?
On Tue, Jan 12, 2010 at 11:33 AM, denis denis-bz...@t-online.de wrote:
On 11/01/2010 18:10, josef.p...@gmail.com wrote:
For this problem, it's supposed to be only those packages that have or
import cython generated code.
Right; is this a known bug, is there a known fix for mac dmgs ?
On Jan 12, 2010, at 10:52 AM, stephen.pas...@stfc.ac.uk
stephen.pas...@stfc.ac.uk wrote:
We have noticed the MaskedArray implementation in numpy-1.4.0 breaks
some of our code. For instance we see the following:
My, that's embarrassing. Sorry for the inconvenience.
in 1.3.0:
a =
Hello,
I have a question about the augmented assignment statements *=, +=, etc.
Apparently, the casting of types is not working correctly. Is this
known resp. intended behavior of numpy?
(I'm using numpy.__version__ = '1.4.0.dev7039' on this machine but I
remember a recent checkout of numpy
On Tue, Jan 12, 2010 at 12:05, Sebastian Walter
sebastian.wal...@gmail.com wrote:
Hello,
I have a question about the augmented assignment statements *=, +=, etc.
Apparently, the casting of types is not working correctly. Is this
known resp. intended behavior of numpy?
Augmented assignment
I'm trying to use sphinx to build documentation for our project (CDAT)
that uses numpy. I'm running into an exception due to
numpy.numarray.numerictypes.SignedType not having an __init__ attribute,
which causes problems with numpydoc. I'm sure there must be a
workaround or I'm doing
On Tue, Jan 12, 2010 at 1:05 PM, Sebastian Walter
sebastian.wal...@gmail.com wrote:
Hello,
I have a question about the augmented assignment statements *=, +=, etc.
Apparently, the casting of types is not working correctly. Is this
known resp. intended behavior of numpy?
(I'm using
Pauli Virtanen wrote:
ma, 2010-01-11 kello 16:11 -0800, Christopher Barker kirjoitti:
[clip]
If no conversion is performed, zero is returned and the value of nptr
is stored in the location referenced by endptr.
off do do some more testing, but I guess that means that those pointers
need
On Tue, Jan 12, 2010 at 7:09 PM, Robert Kern robert.k...@gmail.com wrote:
On Tue, Jan 12, 2010 at 12:05, Sebastian Walter
sebastian.wal...@gmail.com wrote:
Hello,
I have a question about the augmented assignment statements *=, +=, etc.
Apparently, the casting of types is not working
ti, 2010-01-12 kello 12:51 -0500, Pierre GM kirjoitti:
[clip]
a = numpy.ma.MaskedArray([[1,2,3],[4,5,6]])
numpy.ma.sum(a, 1)
Traceback (most recent call last):
File stdin, line 1, in module
File
/usr/lib64/python2.5/site-packages/numpy-1.4.0-py2.5-linux-x86_64.egg/n
On Tue, Jan 12, 2010 at 12:31, Sebastian Walter
sebastian.wal...@gmail.com wrote:
On Tue, Jan 12, 2010 at 7:09 PM, Robert Kern robert.k...@gmail.com wrote:
On Tue, Jan 12, 2010 at 12:05, Sebastian Walter
sebastian.wal...@gmail.com wrote:
Hello,
I have a question about the augmented assignment
On Tue, Jan 12, 2010 at 11:32 AM, Pauli Virtanen p...@iki.fi wrote:
ti, 2010-01-12 kello 12:51 -0500, Pierre GM kirjoitti:
[clip]
a = numpy.ma.MaskedArray([[1,2,3],[4,5,6]])
numpy.ma.sum(a, 1)
Traceback (most recent call last):
File stdin, line 1, in module
File
On Tue, Jan 12, 2010 at 7:38 PM, Robert Kern robert.k...@gmail.com wrote:
On Tue, Jan 12, 2010 at 12:31, Sebastian Walter
sebastian.wal...@gmail.com wrote:
On Tue, Jan 12, 2010 at 7:09 PM, Robert Kern robert.k...@gmail.com wrote:
On Tue, Jan 12, 2010 at 12:05, Sebastian Walter
Sebastian Walter wrote:
However, this particular problem occurs when you try to automatically
differentiate an algorithm by using an Algorithmic Differentiation
(AD) tool.
E.g. given a function
x = numpy.ones(2)
def f(x):
a = numpy.ones(2)
a *= x
return numpy.sum(a)
I don't know
On Jan 12, 2010, at 1:52 PM, Charles R Harris wrote:
On Tue, Jan 12, 2010 at 11:32 AM, Pauli Virtanen p...@iki.fi wrote:
ti, 2010-01-12 kello 12:51 -0500, Pierre GM kirjoitti:
[clip]
a = numpy.ma.MaskedArray([[1,2,3],[4,5,6]])
numpy.ma.sum(a, 1)
Traceback (most recent call last):
I have a csv file like this:
Account, Symbol, Quantity, Price
One,SPY,5,119.00
One,SPY,3,120.00
One,SPY,-2,125.00
One,GE,...
One,GE,...
Two,SPY, ...
Three,GE, ...
...
The data is much larger, could be 10,000 records. I can load it
into a numpy array using
On Tue, Jan 12, 2010 at 3:33 PM, Marc Schwarzschild
m...@thebrookhavengroup.com wrote:
I have a csv file like this:
Account, Symbol, Quantity, Price
One,SPY,5,119.00
One,SPY,3,120.00
One,SPY,-2,125.00
One,GE,...
One,GE,...
Two,SPY, ...
Three,GE, ...
...
Christopher Barker wrote:
static int
@fn...@_fromstr(char *str, @type@ *ip, char **endptr, PyArray_Descr
*NPY_UNUSED(ignore))
{
double result;
result = NumPyOS_ascii_strtod(str, endptr);
*ip = (@type@) result;
return 0;
}
OK, I've done the diagnostics, but not all of
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