numpy/lib/test_io.pyonly uses StringIO in the test, no actual csv file
If I give the filename than I get a TypeError: Can't convert 'bytes'
object to str implicitly
from the statsmodels mailing list example
data = recfromtxt(open('./star98.csv', U), delimiter=,, skip_header=1,
On Tue, Mar 29, 2011 at 8:13 AM, Pearu Peterson pearu.peter...@gmail.comwrote:
On Mon, Mar 28, 2011 at 10:44 PM, Sturla Molden stu...@molden.no wrote:
Den 28.03.2011 19:12, skrev Pearu Peterson:
FYI, f2py in numpy 1.6.x supports also assumed shape arrays.
How did you do that?
On 03/29/2011 09:35 AM, Pearu Peterson wrote:
On Tue, Mar 29, 2011 at 8:13 AM, Pearu Peterson
pearu.peter...@gmail.com mailto:pearu.peter...@gmail.com wrote:
On Mon, Mar 28, 2011 at 10:44 PM, Sturla Molden stu...@molden.no
mailto:stu...@molden.no wrote:
Den 28.03.2011
On Tue, Mar 29, 2011 at 11:03 AM, Dag Sverre Seljebotn
d.s.seljeb...@astro.uio.no wrote:
I think it should be a(1:n*stride:stride) or something.
Yes, it was my typo and I assumed that n is the length of the original
array.
Pearu
___
more python 3.2 fun
a npz file saved with python 2.6 (I guess) that I try to read with python 3.2
I have no clue, since I never use .npz files
arr =
np.load(r..\scikits\statsmodels\tsa\vector_ar\tests\results\vars_results.npz)
arr
numpy.lib.npyio.NpzFile object at 0x03874AC8
Tue, 29 Mar 2011 04:16:00 -0400, josef.pktd wrote:
Traceback (most recent call last):
File stdin, line 1, in module
File C:\Programs\Python32\lib\site-packages\numpy\lib\npyio.py,
line 222, in __getitem__
return format.read_array(value)
File
Tue, 29 Mar 2011 08:27:52 +, Pauli Virtanen wrote:
Tue, 29 Mar 2011 04:16:00 -0400, josef.pktd wrote:
Traceback (most recent call last):
File stdin, line 1, in module
File C:\Programs\Python32\lib\site-packages\numpy\lib\npyio.py,
line 222, in __getitem__
return
If I want to generate a string of random bits with equal probability I run
random.randint(0,2,size).
What if I want a specific proportion of bits? In other words, each bit is 1
with probability p1/2 and 0 with probability q=1-p?
thanks
___
Hi,
On Tue, Mar 29, 2011 at 12:00 PM, Alex Ter-Sarkissov ater1...@gmail.comwrote:
If I want to generate a string of random bits with equal probability I run
random.randint(0,2,size).
What if I want a specific proportion of bits? In other words, each bit is 1
with probability p1/2 and 0
On Tue, Mar 29, 2011 at 1:29 PM, eat e.antero.ta...@gmail.com wrote:
Hi,
On Tue, Mar 29, 2011 at 12:00 PM, Alex Ter-Sarkissov
ater1...@gmail.comwrote:
If I want to generate a string of random bits with equal probability I run
random.randint(0,2,size).
What if I want a specific
Den 29.03.2011 11:00, skrev Alex Ter-Sarkissov:
If I want to generate a string of random bits with equal probability I
run
random.randint(0,2,size).
What if I want a specific proportion of bits? In other words, each bit
is 1 with probability p1/2 and 0 with probability q=1-p?
Does this
Den 29.03.2011 14:56, skrev Sturla Molden:
import numpy as np
def randombits(n, p):
b = (np.random.rand(n*8).reshape((n,8)) p).astype(int)
return (b range(8)).sum(axis=1).astype(np.uint8)
n is the number of bytes. If you prefer to count in bits:
def randombits(n, p):
Hi all.
Sorry if this question has already been asked. I've searched the archive, but
could not find anything related, so here is my question.
I'm using np.histogram on a 4000x4000 array, each with 200 bins. I do that on
both dimensions, meaning I compute 8000 histograms. It takes around 5
Hi,
On Tue, Mar 29, 2011 at 4:29 PM, Éric Depagne e...@depagne.org wrote:
Hi all.
Sorry if this question has already been asked. I've searched the archive,
but
could not find anything related, so here is my question.
I'm using np.histogram on a 4000x4000 array, each with 200 bins. I do
On Tue, Mar 29, 2011 at 5:00 AM, Alex Ter-Sarkissov ater1...@gmail.com wrote:
If I want to generate a string of random bits with equal probability I run
random.randint(0,2,size).
What if I want a specific proportion of bits? In other words, each bit is 1
with probability p1/2 and 0 with
FWIW, have you considered to use
http://docs.scipy.org/doc/numpy/reference/generated/numpy.histogramdd.html#
numpy.histogramdd
Regards,
eat
I tried, but I get a
/usr/lib/pymodules/python2.6/numpy/lib/function_base.pyc in
histogramdd(sample, bins, range, normed, weights)
370 #
Den 29.03.2011 15:46, skrev Daniel Lepage:
x = (np.random.random(size) p)
This will not work. A boolean array is not compactly stored, but an
array of bytes. Only the first bit 0 is 1 with probability p, bits 1 to
7 bits are 1 with probability 0. We thus have to do this 8 times for
each
Den 29.03.2011 16:49, skrev Sturla Molden:
Only the first bit 0 is 1 with probability p, bits 1 to 7 bits are 1
with probability 0.
That should read:
Only bit 0 is 1 with probability p, bits 1 to 7 are 1 with probability 0.
Sorry :)
Sturla
___
On Tue, Mar 29, 2011 at 09:49, Sturla Molden stu...@molden.no wrote:
Den 29.03.2011 15:46, skrev Daniel Lepage:
x = (np.random.random(size) p)
This will not work. A boolean array is not compactly stored, but an
array of bytes. Only the first bit 0 is 1 with probability p, bits 1 to
7 bits
Hi,
On Tue, Mar 29, 2011 at 5:13 PM, Éric Depagne e...@depagne.org wrote:
FWIW, have you considered to use
http://docs.scipy.org/doc/numpy/reference/generated/numpy.histogramdd.html#
numpy.histogramdd
Regards,
eat
I tried, but I get a
Den 29.03.2011 16:49, skrev Sturla Molden:
This will not work. A boolean array is not compactly stored, but an
array of bytes. Only the first bit 0 is 1 with probability p, bits 1 to
7 bits are 1 with probability 0. We thus have to do this 8 times for
each byte, shift left by range(8), and
On Tue, Mar 29, 2011 at 11:59 AM, Sturla Molden stu...@molden.no wrote:
Den 29.03.2011 16:49, skrev Sturla Molden:
This will not work. A boolean array is not compactly stored, but an
array of bytes. Only the first bit 0 is 1 with probability p, bits 1 to
7 bits are 1 with probability 0.
sortind = np.argsort(x['name'], kind='mergesort'); x[sortind]
The indirect sorting method that was suggested works for doing stable sort
on recarrays / structured arrays based on a single-column.
# It is necessary to specify kind='mergesort' because argsort is not stable:
On Tue, Mar 29, 2011 at 13:33, butt...@gmail.com wrote:
Any suggestions on how to achieve stable sort based on multiple columns with
numpy ?
http://docs.scipy.org/doc/numpy/reference/generated/numpy.lexsort.html#numpy.lexsort
It uses mergesort for stability.
--
Robert Kern
I have come to
np.lexsort does the job for both the single or multi-column stable
sort cases, thanks.
a = np.array([('a', 1, 1), ('a', 0, 1), ('a', 0, 0), ('b', 0, 2)],
dtype=[('name', '|S10'), ('x', 'i4'), ('y', 'i4')])
sortind = np.lexsort([a['x'], a['name']])
sortind
array([1, 2, 0, 3], dtype=int64)
On Sun, Mar 27, 2011 at 11:56 AM, Ralf Gommers
ralf.gomm...@googlemail.com wrote:
Hi all,
For the 1.6 release #1628 needs to be resolved. A while ago there was
a discussion about the normed keyword in histogram, which ATM has
changed behavior compared to numpy 1.5.1. The preferred fix as I
On Sun, Mar 27, 2011 at 12:09 PM, Paul Anton Letnes
paul.anton.let...@gmail.com wrote:
I am sure someone has been using this functionality to convert floats to
ints. Changing will break their code. I am not sure how big a deal that would
be. Also, I am of the opinion that one should _first_
In article
AANLkTi=eeg8kl7639imrtl-ihg1ncqyolddsid5tf...@mail.gmail.com,
Ralf Gommers ralf.gomm...@googlemail.com wrote:
Hi,
I am pleased to announce the availability of the first beta of NumPy
1.6.0. Due to the extensive changes in the Numpy core for this
release, the beta testing phase
Hi,
On Mon, Mar 28, 2011 at 11:29 PM, josef.p...@gmail.com wrote:
numpy/lib/test_io.py only uses StringIO in the test, no actual csv file
If I give the filename than I get a TypeError: Can't convert 'bytes'
object to str implicitly
from the statsmodels mailing list example
data =
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