Oooh, this will be nice to have. This would be one of the few times I would
love to see unicode versions of these function names supplied, too.
On Wed, Nov 25, 2015 at 5:31 PM, Antonio Lara wrote:
> Hello, I have added three new functions to the file function_base.py in
>
Hello, I have added three new functions to the file function_base.py in the
numpy/lib folder. These are divergence, curl and laplacian (for the moment,
laplacian of a scalar field, maybe in the future I will try laplacian for a
vector field). The calculation method is based in the existing one for
On Wed, Jun 1, 2011 at 9:35 PM, David Cournapeau courn...@gmail.com wrote:
On Thu, Jun 2, 2011 at 1:49 AM, Mark Miller markperrymil...@gmail.com wrote:
Not quite. Bincount is fine if you have a set of approximately
sequential numbers. But if you don't
Even worse, it fails miserably if you
On Wed, Jun 1, 2011 at 22:06, Travis Oliphant oliph...@enthought.com wrote:
On May 31, 2011, at 8:08 PM, Charles R Harris wrote:
2) Ufunc fadd (nanadd?) Treats nan as zero in addition. Should make a faster
version of nansum possible.
+0 --- Some discussion at the data array summit led to
On Tue, May 31, 2011 at 8:41 PM, Charles R Harris
charlesr.har...@gmail.com wrote:
On Tue, May 31, 2011 at 8:50 PM, Bruce Southey bsout...@gmail.com wrote:
How about including all or some of Keith's Bottleneck package?
He has tried to include some of the discussed functions and tried to
make
I'd love to see something like a count_unique function included. The
numpy.unique function is handy, but it can be a little awkward to
efficiently go back and get counts of each unique value after the
fact.
-Mark
On Wed, Jun 1, 2011 at 8:17 AM, Keith Goodman kwgood...@gmail.com wrote:
On Tue,
would anyone object to fixing the numpy mean and stdv functions, so that they
always used a 64-bit value to track sums, or so that they used a running
calculation. That way
np.mean(np.zeros([4000,4000],'f4')+500)
would not equal 511.493408?
`
On May 31, 2011, at 6:08 PM, Charles R Harris
Short-circuiting find would be nice. Right now, to 'find' something you first
make a bool array, then iterate over it. If all you want is the first index
where x[i] = e, not very efficient.
What I just described is a find with a '==' predicate. Not sure if it's
worthwhile to consider other
On Wed, Jun 1, 2011 at 10:44, Craig Yoshioka crai...@me.com wrote:
would anyone object to fixing the numpy mean and stdv functions, so that they
always used a 64-bit value to track sums, or so that they used a running
calculation. That way
np.mean(np.zeros([4000,4000],'f4')+500)
would
On 06/01/2011 11:01 AM, Robert Kern wrote:
On Wed, Jun 1, 2011 at 10:44, Craig Yoshiokacrai...@me.com wrote:
would anyone object to fixing the numpy mean and stdv functions, so that
they always used a 64-bit value to track sums, or so that they used a
running calculation. That way
On Wed, Jun 1, 2011 at 11:11, Bruce Southey bsout...@gmail.com wrote:
On 06/01/2011 11:01 AM, Robert Kern wrote:
On Wed, Jun 1, 2011 at 10:44, Craig Yoshiokacrai...@me.com wrote:
would anyone object to fixing the numpy mean and stdv functions, so that
they always used a 64-bit value to track
yes, and its probably slower to boot. A quick benchmark on my computer shows
that:
a = np.zeros([4000,4000],'f4')+500
np.mean(a)
takes 0.02 secs
np.mean(a,dtype=np.float64)
takes 0.1 secs
np.mean(a.astype(np.float64))
takes 0.06 secs
so casting the whole array is almost 40% faster than
On Wed, Jun 1, 2011 at 11:31 AM, Mark Miller markperrymil...@gmail.com wrote:
I'd love to see something like a count_unique function included. The
numpy.unique function is handy, but it can be a little awkward to
efficiently go back and get counts of each unique value after the
fact.
Does
Not quite. Bincount is fine if you have a set of approximately
sequential numbers. But if you don't
a = numpy.array((1,500,1000))
a
array([ 1, 500, 1000])
b = numpy.bincount(a)
b
array([0, 1, 0, ..., 0, 0, 1])
len(b)
1001
-Mark
On Wed, Jun 1, 2011 at 9:32 AM, Skipper Seabold
On 5/31/11 6:08 PM, Charles R Harris wrote:
2) Ufunc fadd (nanadd?) Treats nan as zero in addition.
so:
In [53]: a
Out[53]: array([ 1., 2., nan])
In [54]: b
Out[54]: array([0, 1, 2])
In [55]: a + b
Out[55]: array([ 1., 3., nan])
and nanadd(a,b) would yield:
array([ 1., 3., 2.)
On Wed, Jun 1, 2011 at 12:30, Christopher Barker chris.bar...@noaa.gov wrote:
On 5/31/11 6:08 PM, Charles R Harris wrote:
2) Ufunc fadd (nanadd?) Treats nan as zero in addition.
so:
In [53]: a
Out[53]: array([ 1., 2., nan])
In [54]: b
Out[54]: array([0, 1, 2])
In [55]: a + b
My favorite missing extension to numpy functions
np.bincount with 2 (or more) dimensional weights for fast calculation
of group statistics.
Josef
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On Thu, Jun 2, 2011 at 1:49 AM, Mark Miller markperrymil...@gmail.com wrote:
Not quite. Bincount is fine if you have a set of approximately
sequential numbers. But if you don't
Even worse, it fails miserably if you sequential numbers but with a high shift.
np.bincount([10001,
On May 31, 2011, at 8:08 PM, Charles R Harris wrote:
Hi All,
I've been contemplating new functions that could be added to numpy and
thought I'd run them by folks to see if there is any interest.
1) Modified sort/argsort functions that return the maximum k values.
This is easy to do
Hi All,
I've been contemplating new functions that could be added to numpy and
thought I'd run them by folks to see if there is any interest.
1) Modified sort/argsort functions that return the maximum k values.
This is easy to do with heapsort and almost as easy with mergesort.
2) Ufunc
On Tue, May 31, 2011 at 20:08, Charles R Harris
charlesr.har...@gmail.com wrote:
Hi All,
I've been contemplating new functions that could be added to numpy and
thought I'd run them by folks to see if there is any interest.
1) Modified sort/argsort functions that return the maximum k values.
On Tue, May 31, 2011 at 8:08 PM, Charles R Harris charlesr.har...@gmail.com
wrote:
Hi All,
I've been contemplating new functions that could be added to numpy and
thought I'd run them by folks to see if there is any interest.
1) Modified sort/argsort functions that return the maximum k
On Tue, May 31, 2011 at 7:18 PM, Warren Weckesser
warren.weckes...@enthought.com wrote:
On Tue, May 31, 2011 at 8:08 PM, Charles R Harris
charlesr.har...@gmail.com wrote:
Hi All,
I've been contemplating new functions that could be added to numpy and
thought I'd run them by folks to see
On Tue, May 31, 2011 at 8:18 PM, Warren Weckesser
warren.weckes...@enthought.com wrote:
On Tue, May 31, 2011 at 8:08 PM, Charles R Harris
charlesr.har...@gmail.com wrote:
Hi All,
I've been contemplating new functions that could be added to numpy and
thought I'd run them by folks to see
On 06/01/2011 10:08 AM, Charles R Harris wrote:
Hi All,
I've been contemplating new functions that could be added to numpy and
thought I'd run them by folks to see if there is any interest.
1) Modified sort/argsort functions that return the maximum k values.
This is easy to do with
On Tue, May 31, 2011 at 7:33 PM, David da...@silveregg.co.jp wrote:
On 06/01/2011 10:08 AM, Charles R Harris wrote:
Hi All,
I've been contemplating new functions that could be added to numpy and
thought I'd run them by folks to see if there is any interest.
1) Modified sort/argsort
On Tue, May 31, 2011 at 9:31 PM, Benjamin Root ben.r...@ou.edu wrote:
On Tue, May 31, 2011 at 8:18 PM, Warren Weckesser
warren.weckes...@enthought.com wrote:
On Tue, May 31, 2011 at 8:08 PM, Charles R Harris
charlesr.har...@gmail.com wrote:
Hi All,
I've been contemplating new functions
On 06/01/2011 10:34 AM, Charles R Harris wrote:
On Tue, May 31, 2011 at 7:33 PM, David da...@silveregg.co.jp
mailto:da...@silveregg.co.jp wrote:
On 06/01/2011 10:08 AM, Charles R Harris wrote:
Hi All,
I've been contemplating new functions that could be added to
On Tue, May 31, 2011 at 8:26 PM, Charles R Harris charlesr.har...@gmail.com
wrote:
On Tue, May 31, 2011 at 7:18 PM, Warren Weckesser
warren.weckes...@enthought.com wrote:
On Tue, May 31, 2011 at 8:08 PM, Charles R Harris
charlesr.har...@gmail.com wrote:
Hi All,
I've been
On Tue, May 31, 2011 at 9:53 PM, Warren Weckesser
warren.weckes...@enthought.com wrote:
On Tue, May 31, 2011 at 8:36 PM, Skipper Seabold jsseab...@gmail.com
wrote:
I don't know if it's one pass off the top of my head, but I've used
percentile for interpercentile ranges.
[docs]
[1]: X =
On Tue, May 31, 2011 at 8:00 PM, Skipper Seabold jsseab...@gmail.comwrote:
On Tue, May 31, 2011 at 9:53 PM, Warren Weckesser
warren.weckes...@enthought.com wrote:
On Tue, May 31, 2011 at 8:36 PM, Skipper Seabold jsseab...@gmail.com
wrote:
I don't know if it's one pass off the top of
On Tue, May 31, 2011 at 9:26 PM, Charles R Harris
charlesr.har...@gmail.com wrote:
On Tue, May 31, 2011 at 8:00 PM, Skipper Seabold jsseab...@gmail.com
wrote:
On Tue, May 31, 2011 at 9:53 PM, Warren Weckesser
warren.weckes...@enthought.com wrote:
On Tue, May 31, 2011 at 8:36 PM,
On Tue, May 31, 2011 at 8:50 PM, Bruce Southey bsout...@gmail.com wrote:
On Tue, May 31, 2011 at 9:26 PM, Charles R Harris
charlesr.har...@gmail.com wrote:
On Tue, May 31, 2011 at 8:00 PM, Skipper Seabold jsseab...@gmail.com
wrote:
On Tue, May 31, 2011 at 9:53 PM, Warren Weckesser
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