Re: [Numpy-discussion] NumPy-Discussion Digest, Vol 111, Issue 9

[Nathaniel Smith]

On Dec 7, 2015 3:41 AM, "Sydney Shall"  wrote:
> In fact, biological evolution does just the opposite. [...]

Hi all,

Can I suggest that any further follow-ups to this no-doubt fascinating
discussion be taken off-list? No need to acknowledge or apologize or
anything, just trying to keep the noise down.

Cheers,
-n
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Re: [Numpy-discussion] Where is Jaime?

[Charles R Harris]

On Mon, Dec 7, 2015 at 2:25 AM, Sturla Molden 
wrote:

> Charles R Harris  wrote:
>
> > The cash economy is nothing to sniff at ;) It is big in NYC and other
> > places with high taxes and bureaucratic meddling. Cash was one of the
> great
> > inventions.
>
> Yeah, there is a Sicilian New Yorker called "Gambino" who has been
> advertising "protection from ISIS" in European newspapers lately. From what
> I read his father was big at selling protection for cash, and now he is
> taking up his father's business and selling protection from ISIS. To prove
> his value, he claimed ISIS is so afraid of his organisation that Sicily is
> a place they never dare visit. Presumably Gambino's business model depends
> on a cash based economy, or at least it did.
>

That's interesting, sounds like "The Moon is a Harsh Mistress" come to life
;)

Chuck
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Re: [Numpy-discussion] When to stop supporting Python 2.6?

[Sturla Molden]

Charles R Harris  wrote:

> As a strawman proposal, how about dropping moving to 2.7 and 3.4 minimum
> supported version next fall, say around numpy 1.12 or 1.13 depending on how
> the releases go.
> 
> I would like to here from the scipy folks first.

Personally I would be in favor of this, because 2.7 and 3.4 are the minimum
versions anyone should consider to use. However, for SciPy which heavily
depends on Python code, the real improvement will be when we can bump the
minimum Python version to 3.5 and write x @ y instead of dot(x,y). I am not
sure of bumping the minimum version to 3.4 before that is worth it or not.
But certainly dropping 2.6 might be a good thing already now, so we can
start to use bytes, bytearray, memoryview, etc.

Sturla

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Re: [Numpy-discussion] Where is Jaime?

[Sturla Molden]

Charles R Harris  wrote:

> The cash economy is nothing to sniff at ;) It is big in NYC and other
> places with high taxes and bureaucratic meddling. Cash was one of the great
> inventions.

Yeah, there is a Sicilian New Yorker called "Gambino" who has been
advertising "protection from ISIS" in European newspapers lately. From what
I read his father was big at selling protection for cash, and now he is
taking up his father's business and selling protection from ISIS. To prove
his value, he claimed ISIS is so afraid of his organisation that Sicily is
a place they never dare visit. Presumably Gambino's business model depends
on a cash based economy, or at least it did.

Sturla

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Re: [Numpy-discussion] NumPy-Discussion Digest, Vol 111, Issue 9

[Sydney Shall]

On 07/12/2015 09:38, numpy-discussion-requ...@scipy.org wrote:

Message: 4
Date: Sun, 06 Dec 2015 22:01:40 -0500
From: "DAVID SAROFF (RIT Student)"
To: Discussion of Numerical Python
Cc: Stefi Baum
Subject: Re: [Numpy-discussion] array of random numbers fails to
construct
Message-ID:

Re: [Numpy-discussion] Where is Jaime?

[Peter Creasey]

>> >
>> > Is the interp fix in the google pipeline or do we need a workaround?
>> >
>>
>> Oooh, if someone is looking at changing interp, is there any chance
>> that fp could be extended to take complex128 rather than just float
>> values? I.e. so that I could write:
>>
>> >>> y = interp(mu, theta, m)
>> rather than
>> >>> y = interp(mu, theta, m.real) + 1.0j*interp(mu, theta, m.imag)
>>
>> which *sounds* like it might be simple and more (Num)pythonic.
>
> That sounds like an excellent improvement and you should submit a PR
> implementing it :-).
>
> "The interp fix" in question though is a regression in 1.10 that's blocking
> 1.10.2, and needs a quick minimal fix asap.
>


Good answer - as soon as I hit 'send' I wondered how many bugs get
introduced by people trying to attach feature requests to bug fixes. I
will take a look at the code later and pm you if I get anywhere...

Peter
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Re: [Numpy-discussion] array of random numbers fails to construct

[Elliot Hallmark]

David,

>I'm concluding that the .astype(np.uint8) is applied after the array is
constructed, instead of during the process.

That is how python works in general.  astype is a method of an array, so
randint needs to return the array before there is something with an astype
method to call.  A dtype keyword arg to randint, on the otherhand, would
influence the construction of the array.

Elliot
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[Numpy-discussion] Numpy 1.10.2rc2 released

[Charles R Harris]

Hi All,

I'm pleased to announce the release of Numpy 1.10.2rc2. After two months of
stomping bugs I think the house is clean and we are almost ready to put it
up for sale. However, bugs are persistent and may show up at anytime, so
please inspect and test thoroughly.  Windows binaries and source releases
can be found at the usual place on Sourceforge
. If there
are no reports of problems in the next week I plan to release the final.
Further bug squashing will be left to the 1.11 release except possibly for
regressions. The release notes give more detail on the changes.
*bon appétit,*

Chuck
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Re: [Numpy-discussion] array of random numbers fails to construct

[Warren Weckesser]

On Sun, Dec 6, 2015 at 6:55 PM, Allan Haldane 
wrote:

>
> I've also often wanted to generate large datasets of random uint8 and
> uint16. As a workaround, this is something I have used:
>
> np.ndarray(100, 'u1', np.random.bytes(100))
>
> It has also crossed my mind that np.random.randint and np.random.rand
> could use an extra 'dtype' keyword.



+1.  Not a high priority, but it would be nice.

Warren



> It didn't look easy to implement though.
>
> Allan
>
> On 12/06/2015 04:55 PM, DAVID SAROFF (RIT Student) wrote:
>
>> Matthew,
>>
>> That looks right. I'm concluding that the .astype(np.uint8) is applied
>> after the array is constructed, instead of during the process. This
>> random array is a test case. In the production analysis of radio
>> telescope data this is how the data comes in, and there is no  problem
>> with 10GBy files.
>> linearInputData = np.fromfile(dataFile, dtype = np.uint8, count = -1)
>> spectrumArray = linearInputData.reshape(nSpectra,sizeSpectrum)
>>
>>
>> On Sun, Dec 6, 2015 at 4:07 PM, Matthew Brett > > wrote:
>>
>> Hi,
>>
>> On Sun, Dec 6, 2015 at 12:39 PM, DAVID SAROFF (RIT Student)
>> > wrote:
>> > This works. A big array of eight bit random numbers is constructed:
>> >
>> > import numpy as np
>> >
>> > spectrumArray = np.random.randint(0,255,
>> (2**20,2**12)).astype(np.uint8)
>> >
>> >
>> >
>> > This fails. It eats up all 64GBy of RAM:
>> >
>> > spectrumArray = np.random.randint(0,255,
>> (2**21,2**12)).astype(np.uint8)
>> >
>> >
>> > The difference is a factor of two, 2**21 rather than 2**20, for the
>> extent
>> > of the first axis.
>>
>> I think what's happening is that this:
>>
>> np.random.randint(0,255, (2**21,2**12))
>>
>> creates 2**33 random integers, which (on 64-bit) will be of dtype
>> int64 = 8 bytes, giving total size 2 ** (21 + 12 + 6) = 2 ** 39 bytes
>> = 512 GiB.
>>
>> Cheers,
>>
>> Matthew
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>>
>>
>>
>> --
>> David P. Saroff
>> Rochester Institute of Technology
>> 54 Lomb Memorial Dr, Rochester, NY 14623
>> david.sar...@mail.rit.edu  | (434)
>> 227-6242
>>
>>
>>
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