On Jun 9, 2012, at 4:45 PM, josef.p...@gmail.com wrote:
> Is there a way to convert an array to string elements in numpy,
> without knowing the string length?
Not really. In the next release of NumPy you should be able to do.
result = array(arr2, str)
and it will determine the length of the
I use up-to-date Debian testing (wheezy), amd64 architecture.
From the docs for numpy.MachAr:
maxexp int Smallest (positive) power of ibeta that causes overflow.
On my machine, ibeta = 2 and maxexp = 16384.
For float64, float32, and float16 things behave as expected. For float128,
I get the m
[Manual PR notification]
-- Forwarded message --
From: timcera
Date: Sat, Jun 9, 2012 at 10:13 PM
Subject: [numpy] ENH: Initial implementation of a 'neighbor' calculation (#303)
To: njsmith
Each element is assigned the result of a function based on it's neighbors.
Neighbors are
Is there a way to convert an array to string elements in numpy,
without knowing the string length?
>>> arr2 = np.arange(8, 13)
>>> arr2.astype(str) # bad
array(['8', '9', '1', '1', '1'],
dtype='|S1')
>>> arr2.astype('S2')
array(['8', '9', '10', '11', '12'],
dtype='|S2')
>>> map(s
On Sat, Jun 9, 2012 at 2:12 PM, bob tnur wrote:
>>
>> how to save multiple files like cm1.txt,cm2.txt,cm3.txt etc and to
>> produce their corresponding outputs cm1.out,cm2.out,cm3.out etc.
>
> or how to modify this:
> np.savetxt(fname, (a,b), fmt='%4.8f')
>
You can save them to separate fi
>
> Hi every body!
> I have a &b numpy arrays
> a=np.loadtxt('çm1.txt', dtype=np.float, skiprows=2,usecols=[1])
> b=np.loadtxt('çm1.txt', dtype=('x', np.float64), skiprows=2,usecols=[2])
>
> how to save multiple files like cm1.txt,cm2.txt,cm3.txt etc and to
> produce their corresponding outputs
How do you want the output files to be formatted? Binary data? Textual
representation?
This function can do both:
http://docs.scipy.org/doc/numpy/reference/generated/numpy.ndarray.tofile.html
And numpy supports a variety of methods for outputting to files (and
reading data back in):
http://docs.s
On Fri, Jun 8, 2012 at 7:45 PM, Frédéric Bastien wrote:
> Hi,
>
> While reviewing the Theano op that wrap numpy.fill_diagonal, we found
> an unexpected behavior of it:
>
> # as expected for square matrix
> >>> a=numpy.zeros((5,5))
> >>> numpy.fill_diagonal(a, 10)
> >>> print a
>
> # as expected l
