Hi,
why is
bool(np.dtype(np.float))
False
?
I came across this when using this python idiom:
def f(dtype=None):
if not dtype:
print 'using default dtype'
If there is no good reason to have a False truth value, I would vote for
making it True since that is what one would expect
Hello List,
Can someone update us on the status of the date-times datatype?
Is it working yet? If not, what are the plans?
I really appreciate all the work and am looking forward to using the new
date-times,
Best regards, Mark
___
NumPy-Discussion
Hello everyone,
first, I'm really apologise for my English-skills. But I have only one
simple questions. Does NumPy work on Python3 now.
I read so many articles on the Internet, but you can only read some
speculation and not a clear state about this topic.
At the moment I try numpy1.5.1 on
On Fri, Dec 10, 2010 at 6:33 PM, Katharina ingwer.wur...@gmx.net wrote:
Hello everyone,
first, I'm really apologise for my English-skills. But I have only one
simple questions. Does NumPy work on Python3 now.
I read so many articles on the Internet, but you can only read some
speculation
On Fri, Dec 10, 2010 at 03:13, Nils Becker n.bec...@amolf.nl wrote:
Hi,
why is
bool(np.dtype(np.float))
False
?
I came across this when using this python idiom:
def f(dtype=None):
if not dtype:
print 'using default dtype'
The default truth value probably should be True,
On 12/10/2010 4:13 AM, Nils Becker wrote:
def f(dtype=None):
if not dtype:
I think you want:
if dtype is None:
fwiw,
Alan
___
NumPy-Discussion mailing list
NumPy-Discussion@scipy.org
On Fri, Dec 10, 2010 at 3:33 AM, Katharina ingwer.wur...@gmx.net wrote:
Hello everyone,
first, I'm really apologise for my English-skills. But I have only one
simple questions. Does NumPy work on Python3 now.
I read so many articles on the Internet, but you can only read some
speculation
On Wed, Dec 1, 2010 at 6:07 PM, Keith Goodman kwgood...@gmail.com wrote:
On Wed, Dec 1, 2010 at 5:53 PM, David da...@silveregg.co.jp wrote:
On 12/02/2010 04:47 AM, Keith Goodman wrote:
It's hard to write Cython code that can handle all dtypes and
arbitrary number of dimensions. The former is
Why does ddof=2 and ddof=3 give the same result?
np.var([1, 2, 3], ddof=0)
0.3
np.var([1, 2, 3], ddof=1)
1.0
np.var([1, 2, 3], ddof=2)
2.0
np.var([1, 2, 3], ddof=3)
2.0
np.var([1, 2, 3], ddof=4)
-2.0
I expected NaN for ddof=3.
On Fri, Dec 10, 2010 at 4:42 PM, Keith Goodman kwgood...@gmail.com wrote:
Why does ddof=2 and ddof=3 give the same result?
np.var([1, 2, 3], ddof=0)
0.3
np.var([1, 2, 3], ddof=1)
1.0
np.var([1, 2, 3], ddof=2)
2.0
np.var([1, 2, 3], ddof=3)
2.0
np.var([1, 2, 3],
On Fri, Dec 10, 2010 at 2:26 PM, josef.p...@gmail.com wrote:
On Fri, Dec 10, 2010 at 4:42 PM, Keith Goodman kwgood...@gmail.com wrote:
Why does ddof=2 and ddof=3 give the same result?
np.var([1, 2, 3], ddof=0)
0.3
np.var([1, 2, 3], ddof=1)
1.0
np.var([1, 2, 3], ddof=2)
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