Allan,
I see with a google search on your name that you are in the physics
department at Rutgers. I got my BA in Physics there. 1975. Biological
physics. A thought: Is there an entropy that can be assigned to the dna in
an organism? I don't mean the usual thing, coupled to the heat bath.
Evolution
On Dec 6, 2015 6:03 PM, "Peter Creasey"
wrote:
>
> >
> > 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 c
>
> 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 = i
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. It didn't look e
On Fri, Dec 4, 2015 at 9:29 AM, Bryan Van de Ven
wrote:
>
>
>
> > On Dec 4, 2015, at 9:49 AM, Charles R Harris
> wrote:
> >
> >
> >
> > On Fri, Dec 4, 2015 at 2:40 AM, Julian Taylor <
> jtaylor.deb...@googlemail.com> wrote:
> > dropping 3.2: +-0 as it would remove some extra code in our broken p
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 fil
On Sun, Dec 6, 2015 at 10:07 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)).
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:
>
> spe
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
On Sun, Dec 6, 2015 at 1:40 AM, Jaime Fernández del Río <
jaime.f...@gmail.com> wrote:
> On Sun, Dec 6, 2015 at 4:15 AM, Charles R Harris <
> charlesr.har...@gmail.com> wrote:
>
>>
>>
>> On Sat, Dec 5, 2015 at 4:49 PM, Jaime Fernández del Río <
>> jaime.f...@gmail.com> wrote:
>>
>>> I'm alive and
On Sun, Dec 6, 2015 at 4:15 AM, Charles R Harris
wrote:
>
>
> On Sat, Dec 5, 2015 at 4:49 PM, Jaime Fernández del Río <
> jaime.f...@gmail.com> wrote:
>
>> I'm alive and well: trying to stay afloat on a sea of messaging
>> protocols, Java and Swiss bureaucracy, but doing great aside from that.
>>
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