Hi,
> i am trying to invert matrices like this:
> [[ 0.01643777 -0.13539939 0.11946689]
> [ 0.12479926 0.01210898 -0.09217618]
> [-0.13050087 0.07575163 0.01144993]]
>
> in perl using Math::MatrixReal;
> and in various online calculators i get
> [ 2.472715991745 3.680743681735 -3.831392002
The svs are
1.1695e-01, 1.1682e-01, 6.84719250e-10
so if you try
>>> np.linalg.pinv(a,1e-5)
array([[ 0.41097834, 3.12024106, -3.26279309],
[-3.38526587, 0.30274957, 1.89394811],
[ 2.98692033, -2.30459609, 0.28627222]])
you at least get an answer that's not near-ran
The matrix in singular, so you can not expect a stable inverse.
Nadav.
From: numpy-discussion-boun...@scipy.org [numpy-discussion-boun...@scipy.org]
On Behalf Of jp d [yo...@yahoo.com]
Sent: 11 August 2011 03:50
To: numpy-discussion@scipy.org
Subject: [Numpy-d
On 8/10/2011 8:50 PM, jp d wrote:
> i am trying to invert matrices like this:
> [[ 0.01643777 -0.13539939 0.11946689]
> [ 0.12479926 0.01210898 -0.09217618]
> [-0.13050087 0.07575163 0.01144993]]
> in perl using Math::MatrixReal;
> and in various online calculators i get
> [ 2.47271599174
hi,
i am trying to invert matrices like this:
[[ 0.01643777 -0.13539939 0.11946689]
[ 0.12479926 0.01210898 -0.09217618]
[-0.13050087 0.07575163 0.01144993]]
in perl using Math::MatrixReal;
and in various online calculators i get
[ 2.472715991745 3.680743681735 -3.831392002314 ]
[ -4.67
Hi,
On Wed, Aug 10, 2011 at 5:03 PM, wrote:
> On Wed, Aug 10, 2011 at 6:17 PM, Matthew Brett
> wrote:
>> Hi,
>>
>> On Wed, Aug 10, 2011 at 12:38 PM, Skipper Seabold
>> wrote:
>>> On Wed, Aug 10, 2011 at 3:28 PM, Matthew Brett
>>> wrote:
Hi,
I think this one might be for Paul
On Wed, Aug 10, 2011 at 6:17 PM, Matthew Brett wrote:
> Hi,
>
> On Wed, Aug 10, 2011 at 12:38 PM, Skipper Seabold wrote:
>> On Wed, Aug 10, 2011 at 3:28 PM, Matthew Brett
>> wrote:
>>> Hi,
>>>
>>> I think this one might be for Pauli.
>>>
>>> I've run into an odd problem that seems to be an inte
Hi,
On Wed, Aug 10, 2011 at 12:38 PM, Skipper Seabold wrote:
> On Wed, Aug 10, 2011 at 3:28 PM, Matthew Brett
> wrote:
>> Hi,
>>
>> I think this one might be for Pauli.
>>
>> I've run into an odd problem that seems to be an interaction of
>> numpydoc and autosummary and large classes.
>>
>> In
Came across this today when trying to determine what was wrong with my code:
import numpy as np
matched_to = np.array([-1] * 5)
in_ellipse = np.array([False, True, True, True, False])
match = np.array([False, True, True])
matched_to[in_ellipse][match] = 3
I would expect matched_to to now be "arra
On 10. aug. 2011, at 21.03, Gael Varoquaux wrote:
> On Wed, Aug 10, 2011 at 04:01:37PM -0400, Anne Archibald wrote:
>> A 1 Gb text file is a miserable object anyway, so it might be desirable
>> to convert to (say) HDF5 and then throw away the text file.
>
> +1
>
> G
+1 and a very warm recomme
On 10 Aug 2011, at 22:03, Gael Varoquaux wrote:
> On Wed, Aug 10, 2011 at 04:01:37PM -0400, Anne Archibald wrote:
>> A 1 Gb text file is a miserable object anyway, so it might be desirable
>> to convert to (say) HDF5 and then throw away the text file.
>
> +1
There might be concerns about ensurin
On Wed, Aug 10, 2011 at 04:01:37PM -0400, Anne Archibald wrote:
> A 1 Gb text file is a miserable object anyway, so it might be desirable
> to convert to (say) HDF5 and then throw away the text file.
+1
G
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There was also some work on a semi-mutable array type that allowed
appending along one axis, then 'freezing' to yield a normal numpy
array (unfortunately I'm not sure how to find it in the mailing list
archives). One could write such a setup by hand, using mmap() or
realloc(), but I'd be inclined t
On 10 Aug 2011, at 19:22, Russell E. Owen wrote:
> A coworker is trying to load a 1Gb text data file into a numpy array
> using numpy.loadtxt, but he says it is using up all of his machine's 6Gb
> of RAM. Is there a more efficient way to read such text data files?
The npyio routines (loadtxt as
On Wed, Aug 10, 2011 at 3:28 PM, Matthew Brett wrote:
> Hi,
>
> I think this one might be for Pauli.
>
> I've run into an odd problem that seems to be an interaction of
> numpydoc and autosummary and large classes.
>
> In summary, large classes and numpydoc lead to large tables of class
> methods,
Hi,
I think this one might be for Pauli.
I've run into an odd problem that seems to be an interaction of
numpydoc and autosummary and large classes.
In summary, large classes and numpydoc lead to large tables of class
methods, and there seems to be an error in the creation of the large
tables in
A coworker is trying to load a 1Gb text data file into a numpy array
using numpy.loadtxt, but he says it is using up all of his machine's 6Gb
of RAM. Is there a more efficient way to read such text data files?
-- Russell
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Works fine with the [...]s.
Thanks very much.
--George
On 10 August 2011 17:15, Mark Wiebe wrote:
> On Wed, Aug 10, 2011 at 3:45 AM, George Nurser wrote:
>>
>> Hi,
>> I'm running numpy 1.6.1rc2 + python 2.7.1 64-bit from python.org on OSX
>> 10.6.8.
>>
>> I have a f2py'd fortran routine that in
On 10 August 2011 04:01, Pauli Virtanen wrote:
> Mon, 08 Aug 2011 11:27:14 -0400, Angus McMorland wrote:
>> I've just upgraded to the latest numpy from git along with upgrading
>> Ubuntu to natty. Now some of my code, which relies on ctypes-wrapping of
>> data structures from a messaging system, f
On Wed, Aug 10, 2011 at 3:45 AM, George Nurser wrote:
> Hi,
> I'm running numpy 1.6.1rc2 + python 2.7.1 64-bit from python.org on OSX
> 10.6.8.
>
> I have a f2py'd fortran routine that inputs and outputs fortran real*8
> scalars, and I normally call it like
>
> tu,tv,E,El,IF,HF,HFI = LW.rotate2u(
Hi,
I'm running numpy 1.6.1rc2 + python 2.7.1 64-bit from python.org on OSX 10.6.8.
I have a f2py'd fortran routine that inputs and outputs fortran real*8
scalars, and I normally call it like
tu,tv,E,El,IF,HF,HFI = LW.rotate2u(u,v,NN,ff,0)
I now want to call it over 2D arrays UT,VT,N,f
Using st
Mon, 08 Aug 2011 11:27:14 -0400, Angus McMorland wrote:
> I've just upgraded to the latest numpy from git along with upgrading
> Ubuntu to natty. Now some of my code, which relies on ctypes-wrapping of
> data structures from a messaging system, fails with the error message:
>
> "RuntimeWarning: It
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