2009/3/7 Charles R Harris charlesr.har...@gmail.com:
a = np.zeros(6) # real
b= np.arange(6)*(2+3j) # complex
a[1] = b[1] # shouldn't this break?
What is the rationale behind this behaviour?
The same as this:
In [1]: a = zeros(2)
In [2]: a[0] = '1'
In [3]: a
Out[3]: array([ 1., 0.])
On Sat, Mar 7, 2009 at 03:30, Stéfan van der Walt ste...@sun.ac.za wrote:
2009/3/7 Charles R Harris charlesr.har...@gmail.com:
a = np.zeros(6) # real
b= np.arange(6)*(2+3j) # complex
a[1] = b[1] # shouldn't this break?
What is the rationale behind this behaviour?
The same as this:
In
2009/3/7 Robert Kern robert.k...@gmail.com:
In [5]: z = zeros(3, int)
In [6]: z[1] = 1.5
In [7]: z
Out[7]: array([0, 1, 0])
Blind moment, sorry. So, what is your take -- should this kind of
thing pass silently?
Regards
Stéfan
___
On Sat, Mar 7, 2009 at 04:10, Stéfan van der Walt ste...@sun.ac.za wrote:
2009/3/7 Robert Kern robert.k...@gmail.com:
In [5]: z = zeros(3, int)
In [6]: z[1] = 1.5
In [7]: z
Out[7]: array([0, 1, 0])
Blind moment, sorry. So, what is your take -- should this kind of
thing pass silently?
2009/3/7 Robert Kern robert.k...@gmail.com:
On Sat, Mar 7, 2009 at 04:10, Stéfan van der Walt ste...@sun.ac.za wrote:
2009/3/7 Robert Kern robert.k...@gmail.com:
In [5]: z = zeros(3, int)
In [6]: z[1] = 1.5
In [7]: z
Out[7]: array([0, 1, 0])
Blind moment, sorry. So, what is your take --
On Sat, Mar 7, 2009 at 5:18 AM, Robert Kern robert.k...@gmail.com wrote:
On Sat, Mar 7, 2009 at 04:10, Stéfan van der Walt ste...@sun.ac.za
wrote:
2009/3/7 Robert Kern robert.k...@gmail.com:
In [5]: z = zeros(3, int)
In [6]: z[1] = 1.5
In [7]: z
Out[7]: array([0, 1, 0])
Blind
On Sat, Mar 7, 2009 at 5:41 AM, Patrick Marsh patrickmars...@gmail.com wrote:
Greetings,
I am running Windows Vista Ultimate and trying to build numpy from the
SVN branch using MSVC 2003. I have been able to build previously, but
with my latest SVN update I am no longer able to build. My
I was wondering about the behavior of ndarray.astype when passed None.
Currently this defaults to float64, does anyone know why it doesn't default
to the instance's dtype? defaulting to float64 seems too arbitrary.
Thanks,
Darren
___
Numpy-discussion
On Wed, Mar 4, 2009 at 10:13 PM, David Cournapeau
da...@ar.media.kyoto-u.ac.jp wrote:
Is there a rationale for using cblas at all ? Why not using straight
C functions - it is not like we care about speed for tests, right ? Or
am I missing something ?
Since nobody reacted, I removed the
On Sun, Feb 22, 2009 at 7:01 PM, Darren Dale dsdal...@gmail.com wrote:
On Sun, Feb 22, 2009 at 6:35 PM, Darren Dale dsdal...@gmail.com wrote:
On Sun, Feb 22, 2009 at 6:28 PM, Pierre GM pgmdevl...@gmail.com wrote:
On Feb 22, 2009, at 6:21 PM, Eric Firing wrote:
Darren Dale wrote:
Does
On Sat, Mar 7, 2009 at 6:01 AM, Charles R Harris
charlesr.har...@gmail.com wrote:
Hi David,
Currently,
bint.i = __STR2INTCST(ABCD);
It is probably more portable to just initialize the union
union {
char c[4];
npy_uint32 i;
} bint = {'A','B','C','D'};
Ah,
On Sat, Mar 7, 2009 at 11:41 AM, David Cournapeau courn...@gmail.comwrote:
On Sat, Mar 7, 2009 at 6:01 AM, Charles R Harris
charlesr.har...@gmail.com wrote:
Hi David,
Currently,
bint.i = __STR2INTCST(ABCD);
It is probably more portable to just initialize the union
union {
On Sun, Mar 8, 2009 at 2:52 AM, Charles R Harris
charlesr.har...@gmail.com wrote:
On Sat, Mar 7, 2009 at 11:41 AM, David Cournapeau courn...@gmail.com
wrote:
On Sat, Mar 7, 2009 at 6:01 AM, Charles R Harris
charlesr.har...@gmail.com wrote:
Hi David,
Currently,
bint.i =
On Sat, Mar 7, 2009 at 11:02 AM, David Cournapeau courn...@gmail.comwrote:
On Sun, Mar 8, 2009 at 2:52 AM, Charles R Harris
charlesr.har...@gmail.com wrote:
On Sat, Mar 7, 2009 at 11:41 AM, David Cournapeau courn...@gmail.com
wrote:
On Sat, Mar 7, 2009 at 6:01 AM, Charles R Harris
On Sat, Mar 7, 2009 at 11:20 AM, Charles R Harris charlesr.har...@gmail.com
wrote:
On Sat, Mar 7, 2009 at 11:02 AM, David Cournapeau courn...@gmail.comwrote:
On Sun, Mar 8, 2009 at 2:52 AM, Charles R Harris
charlesr.har...@gmail.com wrote:
On Sat, Mar 7, 2009 at 11:41 AM, David
On Sun, Mar 8, 2009 at 3:20 AM, Charles R Harris
charlesr.har...@gmail.com wrote:
The macro is ugly, unneeded, and obfuscating. Why construct a number from
characters and shifts when you can just *write it down*?
The idea was to replace the 'ABCD' multi-byte constant. If you think
that
Hi,
I'm having some difficulty understanding how these work and would be
grateful for any help.
In the simple case, I get what I expect:
In [42]: a = np.zeros((), dtype=[('f1', 'f8'),('f2', 'f8')])
In [43]: a == a
Out[43]: True
If one of the fields is itself an array, and the other is a
On Sat, Mar 7, 2009 at 11:57 AM, David Cournapeau courn...@gmail.comwrote:
On Sun, Mar 8, 2009 at 3:20 AM, Charles R Harris
charlesr.har...@gmail.com wrote:
The macro is ugly, unneeded, and obfuscating. Why construct a number from
characters and shifts when you can just *write it down*?
np.random.multinomial looks weird. Are these bugs, or is there
something not correct with the explanation.
Josef
from the help/ docstring:
np.random.multinomial(20, [1/6.]*6, size=2)
array([[3, 4, 3, 3, 4, 3],
[2, 4, 3, 4, 0, 7]])
For the first run, we threw 3 times 1, 4 times 2, etc.
On Sat, Mar 7, 2009 at 17:29, josef.p...@gmail.com wrote:
np.random.multinomial looks weird. Are these bugs, or is there
something not correct with the explanation.
I would like to know how you are interpreting the documentation.
Josef
from the help/ docstring:
np.random.multinomial(20,
On Sat, Mar 7, 2009 at 6:57 PM, Robert Kern robert.k...@gmail.com wrote:
On Sat, Mar 7, 2009 at 17:29, josef.p...@gmail.com wrote:
np.random.multinomial looks weird. Are these bugs, or is there
something not correct with the explanation.
I would like to know how you are interpreting the
On Sun, Mar 8, 2009 at 4:34 AM, Charles R Harris
charlesr.har...@gmail.com wrote:
On Sat, Mar 7, 2009 at 11:57 AM, David Cournapeau courn...@gmail.com
wrote:
On Sun, Mar 8, 2009 at 3:20 AM, Charles R Harris
charlesr.har...@gmail.com wrote:
The macro is ugly, unneeded, and obfuscating.
On Sat, Mar 7, 2009 at 11:10 PM, David Cournapeau courn...@gmail.comwrote:
snip
That's strange - I redid the compilation this morning, and I now get
the same results as you (modulo the function call - I forced the
function call because that's how it would work in numpy), that is the
return
On Sun, Mar 8, 2009 at 3:49 PM, Charles R Harris
charlesr.har...@gmail.com wrote:
So it's off to look at the
tickets and trying to fix bugs. Urrgh. Oh, and I suppose I should look into
the argmax/argmin functions and see how they handle nans.
I think they don't at the moment: they have an
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