Robert Kern robert.kern at gmail.com writes:
On Thu, Jun 16, 2011 at 06:28, Christian K. ckkart at hoc.net wrote:
Hi,
I need to do fit a 3d surface to a point cloud. This sounds like a job for
3d
orthogonal distance regression. Does anybody know of an implementation?
As eat points
If I understand correctly, your error is that you convert only the second
column, because your converters dictionary contains a single key (1).
If you have it contain keys from 0 to 3 associated to the same function, it
should work.
-=- Olivier
2011/6/17 gary ruben gru...@bigpond.net.au
I'm
I didn't have time yesterday but the attached illustrates what I mean
about putting the shared data in a module (it should work with the
previous myutil).
I don't get a big speed up but at least it is faster using multiple
subprocesses:
Not threaded: 0.450406074524
Using 8 processes: 0.282383
Thanks Olivier,
Your suggestion gets me a little closer to what I want, but doesn't
quite work. Replacing the conversion with
c = lambda x:np.cast[np.complex64](complex(*eval(x)))
b = np.genfromtxt(a,converters={0:c, 1:c, 2:c,
3:c},dtype=None,delimiter=18,usecols=range(4))
produces
On 06/17/2011 08:22 AM, gary ruben wrote:
Thanks Olivier,
Your suggestion gets me a little closer to what I want, but doesn't
quite work. Replacing the conversion with
c = lambda x:np.cast[np.complex64](complex(*eval(x)))
b = np.genfromtxt(a,converters={0:c, 1:c, 2:c,
2011/6/17 Bruce Southey bsout...@gmail.com
On 06/17/2011 08:22 AM, gary ruben wrote:
Thanks Olivier,
Your suggestion gets me a little closer to what I want, but doesn't
quite work. Replacing the conversion with
c = lambda x:np.cast[np.complex64](complex(*eval(x)))
b =
On 06/17/2011 08:51 AM, Olivier Delalleau wrote:
2011/6/17 Bruce Southey bsout...@gmail.com mailto:bsout...@gmail.com
On 06/17/2011 08:22 AM, gary ruben wrote:
Thanks Olivier,
Your suggestion gets me a little closer to what I want, but doesn't
quite work. Replacing the
Thanks for the hints Olivier and Bruce. Based on them, the following
is a working solution, although I still have that itchy sense that genfromtxt
should be able to do it directly.
import numpy as np
from StringIO import StringIO
a = StringIO('''\
(-3.9700,-5.0400) (-1.1318,-2.5693)
On Thu, Jun 16, 2011 at 8:54 PM, Charles R Harris
charlesr.har...@gmail.com wrote:
On Wed, Jun 15, 2011 at 1:30 PM, Gökhan Sever gokhanse...@gmail.com wrote:
Hello,
The following snippet works fine for a regular string and prints out
the string without a problem.
python
Python 2.7
It does not appear that unwrap works properly for masked arrays. First, it
uses np.asarray() at the start of the function. However, that alone would
not fix the problem given the nature of how unwrap works (performing diff
operations). I tried a slightly modified version of unwrap, but I could
Hi all,
I'm wondering if there is a way to get the range of values a given dtype
can hold?
essentially, I'm looking for something like sys.maxint, for for whatever
numpy dtype I have n hand (and eps for floating point types).
I was hoping there would be something like
a_dtype.max_value
Le vendredi 17 juin 2011 à 10:38 -0700, Christopher Barker a écrit :
Hi all,
I'm wondering if there is a way to get the range of values a given dtype
can hold?
essentially, I'm looking for something like sys.maxint, for for whatever
numpy dtype I have n hand (and eps for floating point
On Thu, Jun 16, 2011 at 8:18 PM, Derek Homeier
de...@astro.physik.uni-goettingen.de wrote:
On 17.06.2011, at 2:02AM, Mark Wiebe wrote:
ok, that was a lengthy hunt, but it's in printing the string in
make_iso_8601_date:
tmplen = snprintf(substr, sublen, %04 NPY_INT64_FMT, dts-year);
On 06/17/2011 06:56 AM, Benjamin Root wrote:
It does not appear that unwrap works properly for masked arrays. First,
it uses np.asarray() at the start of the function. However, that alone
would not fix the problem given the nature of how unwrap works
(performing diff operations). I tried a
Fabrice Silva wrote:
I'm wondering if there is a way to get the range of values a given dtype
can hold?
http://docs.scipy.org/doc/numpy/reference/routines.dtype.html#data-type-information
yup, that does it, I hadn't found that, as I was expecting a more OO
way, i.e. as a method of the
On Fri, Jun 17, 2011 at 13:27, Christopher Barker chris.bar...@noaa.gov wrote:
Actually, I'm a bit confused about dtypes from an OO design perspective
anyway. I note that the dtypes seem to have all (most?) of the methods
of ndarrays (or placeholders, anyway), which I don't quite get.
No,
On 06/17/2011 12:38 PM, Christopher Barker wrote:
Hi all,
I'm wondering if there is a way to get the range of values a given dtype
can hold?
essentially, I'm looking for something like sys.maxint, for for whatever
numpy dtype I have n hand (and eps for floating point types).
I was hoping
Robert Kern wrote:
On Fri, Jun 17, 2011 at 13:27, Christopher Barker chris.bar...@noaa.gov
wrote:
Actually, I'm a bit confused about dtypes from an OO design perspective
anyway. I note that the dtypes seem to have all (most?) of the methods
of ndarrays (or placeholders, anyway), which I
On Fri, Jun 17, 2011 at 1:26 PM, Eric Firing efir...@hawaii.edu wrote:
On 06/17/2011 06:56 AM, Benjamin Root wrote:
It does not appear that unwrap works properly for masked arrays. First,
it uses np.asarray() at the start of the function. However, that alone
would not fix the problem
On 17.06.2011, at 8:05PM, Mark Wiebe wrote:
On Thu, Jun 16, 2011 at 8:18 PM, Derek Homeier
de...@astro.physik.uni-goettingen.de wrote:
On 17.06.2011, at 2:02AM, Mark Wiebe wrote:
ok, that was a lengthy hunt, but it's in printing the string in
make_iso_8601_date:
tmplen =
Using the master branch, I was running the scipy tests when a crash
occurred. I believe the crash originates within numpy. The tests for numpy
do pass on my machine (F15, x86_64, python 2.7). Below is the backtrace:
*** glibc detected *** python: double free or corruption (!prev):
On Fri, Jun 17, 2011 at 15:03, Benjamin Root ben.r...@ou.edu wrote:
Using the master branch, I was running the scipy tests when a crash
occurred. I believe the crash originates within numpy. The tests for numpy
do pass on my machine (F15, x86_64, python 2.7). Below is the backtrace:
Please
On Fri, Jun 17, 2011 at 15:18, Benjamin Root ben.r...@ou.edu wrote:
On Fri, Jun 17, 2011 at 3:07 PM, Robert Kern robert.k...@gmail.com wrote:
On Fri, Jun 17, 2011 at 15:03, Benjamin Root ben.r...@ou.edu wrote:
Using the master branch, I was running the scipy tests when a crash
occurred. I
On Fri, 17 Jun 2011 15:39:21 -0500, Robert Kern wrote:
[clip]
File
/home/bvr/Programs/scipy/scipy/sparse/linalg/eigen/arpack/tests/test_arpack.py,
line 378 in test_ticket_1459_arpack_crash
Well, if it's testing that it crashes, test passed!
Here is the referenced ticket and the relevant
Hi Gary,
On 17.06.2011, at 5:39PM, gary ruben wrote:
Thanks for the hints Olivier and Bruce. Based on them, the following
is a working solution, although I still have that itchy sense that genfromtxt
should be able to do it directly.
import numpy as np
from StringIO import StringIO
a =
On Mon, Jun 13, 2011 at 8:53 PM, Russell E. Owen ro...@uw.edu wrote:
In article banlktikodians0ujrdkpudffo8agpnx...@mail.gmail.com,
Ralf Gommers ralf.gomm...@googlemail.com wrote:
On Thu, Jun 9, 2011 at 11:46 PM, Russell E. Owen ro...@uw.edu wrote:
What would it take to automatically
2011/6/17 Derek Homeier de...@astro.physik.uni-goettingen.de
Hi Gary,
On 17.06.2011, at 5:39PM, gary ruben wrote:
Thanks for the hints Olivier and Bruce. Based on them, the following
is a working solution, although I still have that itchy sense that
genfromtxt
should be able to do it
On Fri, Jun 17, 2011 at 2:46 PM, Derek Homeier
de...@astro.physik.uni-goettingen.de wrote:
On 17.06.2011, at 8:05PM, Mark Wiebe wrote:
On Thu, Jun 16, 2011 at 8:18 PM, Derek Homeier
de...@astro.physik.uni-goettingen.de wrote:
On 17.06.2011, at 2:02AM, Mark Wiebe wrote:
ok, that was
On Fri, Jun 17, 2011 at 3:48 PM, Pauli Virtanen p...@iki.fi wrote:
On Fri, 17 Jun 2011 15:39:21 -0500, Robert Kern wrote:
[clip]
File
/home/bvr/Programs/scipy/scipy/sparse/linalg/eigen/arpack/tests/test_arpack.py,
line 378 in test_ticket_1459_arpack_crash
Well, if it's testing that
On 17.06.2011, at 11:01PM, Olivier Delalleau wrote:
You were just overdoing it by already creating an array with the converter,
this apparently caused genfromtxt to create a structured array from the
input (which could be converted back to an ndarray, but that can prove
tricky as well) -
Thanks guys - I'm happy with the solution for now. FYI, Derek's
suggestion doesn't work in numpy 1.5.1 either.
For any developers following this thread, I think this might be a nice
use case for genfromtxt to handle in future.
As a corollary of this problem, I wonder whether there's a
For the hardcoded part, you can easily read the first line of your file and
split it with the same delimiter to know the number of columns.
It's sure it'd be best to be able to be able to skip this part, but you
don't need to hardcode this number into your code at least.
Something like:
n_cols =
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