On Wed, Sep 8, 2010 at 5:35 PM, Michael Gilbert wrote:
> On Wed, 8 Sep 2010 15:44:02 -0400, Michael Gilbert wrote:
>> On Wed, Sep 8, 2010 at 12:23 PM, Charles R Harris wrote:
>> >
>> >
>> > On Wed, Sep 8, 2010 at 9:46 AM, Michael Gilbert
>> > wrote:
>> >>
>> >> On Wed, 8 Sep 2010 09:43:56 -0600,
On Wed, 8 Sep 2010 15:44:02 -0400, Michael Gilbert wrote:
> On Wed, Sep 8, 2010 at 12:23 PM, Charles R Harris wrote:
> >
> >
> > On Wed, Sep 8, 2010 at 9:46 AM, Michael Gilbert
> > wrote:
> >>
> >> On Wed, 8 Sep 2010 09:43:56 -0600, Charles R Harris wrote:
> >> > On Wed, Sep 8, 2010 at 9:26 AM, Mi
On 8 September 2010 16:33, Robert Kern wrote:
> On Wed, Sep 8, 2010 at 15:10, Michael Gilbert
> wrote:
>> On Wed, 8 Sep 2010 15:04:17 -0500, Robert Kern wrote:
>>> On Wed, Sep 8, 2010 at 14:44, Michael Gilbert
>>> wrote:
>
>>> > Just wanted to say that numpy object arrays + decimal solved all of
On Wed, Sep 8, 2010 at 15:10, Michael Gilbert
wrote:
> On Wed, 8 Sep 2010 15:04:17 -0500, Robert Kern wrote:
>> On Wed, Sep 8, 2010 at 14:44, Michael Gilbert
>> wrote:
>> > Just wanted to say that numpy object arrays + decimal solved all of my
>> > problems, which were all caused by the disconne
Wow, this is great! Thanks for all the great questions.
Sebastian Walter gmail.com> writes:
> is it really the covariance matrix you want to invert? Or do you want
> to compute something like
> x^T C^{-1} x,
> where x is an array of size N and C an array of size (N,N)?
Yes, this is what I am c
On Wed, Sep 8, 2010 at 14:42, Chris Ball wrote:
> Robert Kern gmail.com> writes:
>
>>
>> On Tue, Sep 7, 2010 at 15:12, Friedrich Romstedt
>> gmail.com> wrote:
>> > Ah, no need to answer, I do this myself:
>> >
>> > Friedrich, would you please use numpy.inf and -numpy.inf.
>>
>> But if you have a
On Wed, 8 Sep 2010 22:20:30 +0200, Sandro Tosi wrote:
> On Wed, Sep 8, 2010 at 22:10, Michael Gilbert
> wrote:
> > Here is an example:
> >
> > >>> 0.3/3.0 - 0.1
> > -1.3877787807814457e-17
> >
> > >>> mpmath.mpf( '0.3' )/mpmath.mpf( '3.0' ) - mpmath.mpf( '0.1' )
> > mpf('-1.387778780781445
On Wed, Sep 8, 2010 at 22:10, Michael Gilbert
wrote:
> Here is an example:
>
> >>> 0.3/3.0 - 0.1
> -1.3877787807814457e-17
>
> >>> mpmath.mpf( '0.3' )/mpmath.mpf( '3.0' ) - mpmath.mpf( '0.1' )
> mpf('-1.3877787807814457e-17')
>
> >>> decimal.Decimal( '0.3' )/decimal.Decimal( '3.0' ) - de
On Wed, 8 Sep 2010 15:04:17 -0500, Robert Kern wrote:
> On Wed, Sep 8, 2010 at 14:44, Michael Gilbert
> wrote:
> > On Wed, Sep 8, 2010 at 12:23 PM, Charles R Harris wrote:
> >>
> >>
> >> On Wed, Sep 8, 2010 at 9:46 AM, Michael Gilbert
> >> wrote:
> >>>
> >>> On Wed, 8 Sep 2010 09:43:56 -0600, Cha
On Wed, Sep 8, 2010 at 14:44, Michael Gilbert
wrote:
> On Wed, Sep 8, 2010 at 12:23 PM, Charles R Harris wrote:
>>
>>
>> On Wed, Sep 8, 2010 at 9:46 AM, Michael Gilbert
>> wrote:
>>>
>>> On Wed, 8 Sep 2010 09:43:56 -0600, Charles R Harris wrote:
>>> > On Wed, Sep 8, 2010 at 9:26 AM, Michael Gilbe
8/09/10 @ 15:35 (-0400), thus spake Anne Archibald:
> 2010/9/8 Ernest Adrogué :
> > I have a sorted, flat array:
> >
> > In [139]: a =np.array([0,1,2,2,2,3])
> >
> > Basically, I want views of the areas where there
> > are repeated numbers (since the array is sorted, they
> > will be contiguous).
On Wed, Sep 8, 2010 at 12:23 PM, Charles R Harris wrote:
>
>
> On Wed, Sep 8, 2010 at 9:46 AM, Michael Gilbert
> wrote:
>>
>> On Wed, 8 Sep 2010 09:43:56 -0600, Charles R Harris wrote:
>> > On Wed, Sep 8, 2010 at 9:26 AM, Michael Gilbert
>> > > > > wrote:
>> >
>> > > Hi,
>> > >
>> > > Are there an
Robert Kern gmail.com> writes:
>
> On Tue, Sep 7, 2010 at 15:12, Friedrich Romstedt
> gmail.com> wrote:
> > Ah, no need to answer, I do this myself:
> >
> > Friedrich, would you please use numpy.inf and -numpy.inf.
>
> But if you have an integer array, you will run into the same problem.
> The
2010/9/8 Ernest Adrogué :
> Hello,
>
> I have a sorted, flat array:
>
> In [139]: a =np.array([0,1,2,2,2,3])
>
> Basically, I want views of the areas where there
> are repeated numbers (since the array is sorted, they
> will be contiguous).
>
> But, of course, to find the numbers that are repeated
2010/9/8 Ernest Adrogué :
> I have a sorted, flat array:
>
> In [139]: a =np.array([0,1,2,2,2,3])
>
> Basically, I want views of the areas where there
> are repeated numbers (since the array is sorted, they
> will be contiguous).
>
> But, of course, to find the numbers that are repeated
> I have to
Hello,
I have a sorted, flat array:
In [139]: a =np.array([0,1,2,2,2,3])
Basically, I want views of the areas where there
are repeated numbers (since the array is sorted, they
will be contiguous).
But, of course, to find the numbers that are repeated
I have to use comparison operations that ret
On Wed, Sep 8, 2010 at 9:46 AM, Michael Gilbert wrote:
> On Wed, 8 Sep 2010 09:43:56 -0600, Charles R Harris wrote:
> > On Wed, Sep 8, 2010 at 9:26 AM, Michael Gilbert <
> michael.s.gilb...@gmail.com
> > > wrote:
> >
> > > Hi,
> > >
> > > Are there any plans to add support for decimal floating po
On Thu, Sep 9, 2010 at 12:43 AM, Charles R Harris
wrote:
>
>
> On Wed, Sep 8, 2010 at 9:26 AM, Michael Gilbert
> wrote:
>>
>> Hi,
>>
>> Are there any plans to add support for decimal floating point
>> arithmetic, as defined in the 2008 revision of the IEEE 754 standard
>> [0], in numpy?
>>
>
> No
On Wed, 8 Sep 2010 09:43:56 -0600, Charles R Harris wrote:
> On Wed, Sep 8, 2010 at 9:26 AM, Michael Gilbert > wrote:
>
> > Hi,
> >
> > Are there any plans to add support for decimal floating point
> > arithmetic, as defined in the 2008 revision of the IEEE 754 standard
> > [0], in numpy?
> >
> >
On Wed, Sep 8, 2010 at 9:26 AM, Michael Gilbert wrote:
> Hi,
>
> Are there any plans to add support for decimal floating point
> arithmetic, as defined in the 2008 revision of the IEEE 754 standard
> [0], in numpy?
>
>
Not at the moment. There is currently no hardware or C support and adding
new
On Wed, Sep 8, 2010 at 10:26, Michael Gilbert
wrote:
> Hi,
>
> Are there any plans to add support for decimal floating point
> arithmetic, as defined in the 2008 revision of the IEEE 754 standard
> [0], in numpy?
No, there are no plans. Although IEEE 754-2008 defines the format and
semantics of s
Hi,
Are there any plans to add support for decimal floating point
arithmetic, as defined in the 2008 revision of the IEEE 754 standard
[0], in numpy?
Thanks for any info.
Best wishes,
Mike
[0] http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4610935&tag=1
___
josef.p...@gmail.com wrote:
> On Wed, Sep 8, 2010 at 10:53 AM, Neal Becker wrote:
>> josef.p...@gmail.com wrote:
>>
>>> On Wed, Sep 8, 2010 at 7:44 AM, Neal Becker wrote:
If I try to use vectorize on the result of functools.partial, I seem
to get:
ValueError: failed to deter
On Wed, Sep 8, 2010 at 10:53 AM, Neal Becker wrote:
> josef.p...@gmail.com wrote:
>
>> On Wed, Sep 8, 2010 at 7:44 AM, Neal Becker wrote:
>>> If I try to use vectorize on the result of functools.partial, I seem to
>>> get:
>>>
>>> ValueError: failed to determine the number of arguments for
>>>
josef.p...@gmail.com wrote:
> On Wed, Sep 8, 2010 at 7:44 AM, Neal Becker wrote:
>> If I try to use vectorize on the result of functools.partial, I seem to
>> get:
>>
>> ValueError: failed to determine the number of arguments for
>>
>>
>> Anything I can do about it?
>
> Set .nin (attribute of
rf1 = np.asarray(cursor1.fetchall(), dtype=np.float64).ravel()
did the trick, 1d is perfect
Thankyou very much!
Rui
From: "josef.p...@gmail.com"
To: Discussion of Numerical Python
Sent: Wed, September 8, 2010 3:30:54 PM
Subject: Re: [Numpy-discussion] Val
On 09/08/2010 08:30 AM, josef.p...@gmail.com wrote:
> On Wed, Sep 8, 2010 at 9:21 AM, Rui DaCosta wrote:
>> Thanks again,
>>
>> I was trying to
>> follow
>> http://www.scipy.org/Numpy_Example_List#head-779283aaa3cc20a3786ad33c2ee1fee9d68a4a53
>> but with the key difference being, that instead o
On Wed, Sep 8, 2010 at 9:21 AM, Rui DaCosta wrote:
> Thanks again,
>
> I was trying to
> follow http://www.scipy.org/Numpy_Example_List#head-779283aaa3cc20a3786ad33c2ee1fee9d68a4a53
> but with the key difference being, that instead of the data for the three
> arrays being constructed from literals
Thanks again,
I was trying to
follow
http://www.scipy.org/Numpy_Example_List#head-779283aaa3cc20a3786ad33c2ee1fee9d68a4a53
but with the key difference being, that instead of the data for the three
arrays
being constructed from literals, that i'd be sourcing from a relational
database. The
On Wed, Sep 8, 2010 at 4:38 AM, John Reid wrote:
> Hi,
>
> I recently upgraded to numpy 1.5.0 and now I get warnings when I take
> the logarithm of 0.
>
> In [5]: np.log(0.)
> Warning: divide by zero encountered in log
> Out[5]: -inf
>
>
> I want to evaluate x * log(x) where its value is defined a
On 9/8/2010 6:38 AM, John Reid wrote:
> def safe_x_log_x(x):
> "@return: x log(x) but replaces -inf with 0."
> l = np.log(x)
> result = x * l
> result[np.isneginf(l)] = 0.
> return result
Assuming x is known to contain nonnegative floats:
def safe_x_log_x(x):
x =
On Wed, Sep 8, 2010 at 8:08 AM, Rui DaCosta wrote:
> Thanks for your assistance,
> I was following this example:
> http://www.scipy.org/Numpy_Example_List#head-779283aaa3cc20a3786ad33c2ee1fee9d68a4a53
I didn't know,
If arrays are 1d, then numpy does the stacking for you., but it
doesn't work with
Thanks for your assistance,
I was following this example:
http://www.scipy.org/Numpy_Example_List#head-779283aaa3cc20a3786ad33c2ee1fee9d68a4a53
I intend to use different arrays once I have resolved this problem.
Trying your suggestion:
...
print (rf1)
print (np.corrcoef(rf1, rf1, rowvar=0))
r
On Wed, Sep 8, 2010 at 7:44 AM, Neal Becker wrote:
> If I try to use vectorize on the result of functools.partial, I seem to
> get:
>
> ValueError: failed to determine the number of arguments for
>
>
> Anything I can do about it?
Set .nin (attribute of vectorized function, I think) directly wit
Fernando Perez writes:
> Just let me know what you and the others (Keith, Skipper, Rob, etc)
> think and I'm more than happy to open the doors to make the process
> easier.
Well, the pull requests I posted to your repository are for fairly trivial fixes
(but some still need documentation and regre
If I try to use vectorize on the result of functools.partial, I seem to
get:
ValueError: failed to determine the number of arguments for
Anything I can do about it?
___
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On Wed, Sep 8, 2010 at 5:42 AM, RuiDC wrote:
>
> I'm getting this error, which must be a simple error in getting the result
> from the cursor in the right shape, how do I get the cursor into the array
> as a single dimension?:
>
> import numpy as np
> import sqlite3
> conn = sqlite3.conne
Hi,
I recently upgraded to numpy 1.5.0 and now I get warnings when I take
the logarithm of 0.
In [5]: np.log(0.)
Warning: divide by zero encountered in log
Out[5]: -inf
I want to evaluate x * log(x) where its value is defined as 0 when x=0
so I have the following function:
def safe_x_log_x(x
I'm getting this error, which must be a simple error in getting the result
from the cursor in the right shape, how do I get the cursor into the array
as a single dimension?:
import numpy as np
import sqlite3
conn = sqlite3.connect("simpledb")
cursor1 = conn.execute("select Log
Hi Lluis,
On Mon, Sep 6, 2010 at 12:17 PM, Lluís wrote:
> I started writing some fixes for DataArray, but some others need discussion on
> whether they should be implemented as I describe.
>
> To this extent, please see issues at http://github.com/fperez/datarray/issues
> and comment on them, so
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