On Tue, Mar 18, 2008 at 4:25 AM, Chris Withers <[EMAIL PROTECTED]> wrote:
> Robert Kern wrote:
> > Appending to a list is almost always better than growing an array by
> > concatenation. If you have a real need for speed, though, there are a
> > few tricks you can do at the expense of complexity
Alexander Michael wrote:
> Be default (if I understand correctly) the passing a regular array to
> MaskedArray will not copy it, so it less redundant than it may at
> first appear. The MaskedArray provides as masked *view* of the
> underlying array data you give it.
Cool, that was exactly what I w
On Tue, Mar 18, 2008 at 5:27 AM, Chris Withers <[EMAIL PROTECTED]> wrote:
> Travis E. Oliphant wrote:
> > Generally, arrays are not efficiently re-sized. It is best to
> > pre-allocate, or simply create a list by appending and then convert to
> > an array after the fact as you have done.
>
> T
Travis E. Oliphant wrote:
> Generally, arrays are not efficiently re-sized. It is best to
> pre-allocate, or simply create a list by appending and then convert to
> an array after the fact as you have done.
True, although that feels like iterating over the data twice for no
reason, which feels
Robert Kern wrote:
> Appending to a list is almost always better than growing an array by
> concatenation. If you have a real need for speed, though, there are a
> few tricks you can do at the expense of complexity.
I don't for this project but I might in future, where can I read about this?
chee
On 17/03/2008, Alan G Isaac <[EMAIL PROTECTED]> wrote:
> > Alan suggested:
>
> >> 1. http://www.scipy.org/Numpy_Example_List_With_Doc
>
> On Mon, 17 Mar 2008, Chris Withers apparently wrote:
>
> > Yeah, read that, wood, trees, can't tell the...
>
> Oh, then you might want
> http://www.scipy.org
> Alan suggested:
>> 1. http://www.scipy.org/Numpy_Example_List_With_Doc
On Mon, 17 Mar 2008, Chris Withers apparently wrote:
> Yeah, read that, wood, trees, can't tell the...
Oh, then you might want
http://www.scipy.org/Tentative_NumPy_Tutorial
or the other stuff at
http://www.scipy.or
Chris Withers wrote:
> Hi All,
>
> I'm using xlrd to read an excel workbook containing several columns of
> data as follows:
>
Generally, arrays are not efficiently re-sized. It is best to
pre-allocate, or simply create a list by appending and then convert to
an array after the fact as you h
On Mon, Mar 17, 2008 at 12:16 PM, Chris Withers <[EMAIL PROTECTED]> wrote:
> Charles Doutriaux wrote:
> > 1-)You could use the concatenate function to grow an array as you go.
>
> Thanks. Would it be more efficient to build the whole set of arrays as
> lists first or build them as arrays and use
Alan G Isaac wrote:
> On Mon, 17 Mar 2008, Chris Withers apparently wrote:
>> woefully inadequate state of the currently available free
>> documentation
>
> 1. http://www.scipy.org/Numpy_Example_List_With_Doc
Yeah, read that, wood, trees, can't tell the...
> 2. write some
Small problem with t
Charles Doutriaux wrote:
> 1-)You could use the concatenate function to grow an array as you go.
Thanks. Would it be more efficient to build the whole set of arrays as
lists first or build them as arrays and use concatenate?
> 2-) assumnig you still have your list
>
> b=numpy.array(data[name])
On Mon, 17 Mar 2008, Chris Withers apparently wrote:
> woefully inadequate state of the currently available free
> documentation
1. http://www.scipy.org/Numpy_Example_List_With_Doc
2. write some
Cheers,
Alan Isaac
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Numpy-discussion mailing list
Hi Chris,
1-)You could use the concatenate function to grow an array as you go.
2-) assumnig you still have your list
b=numpy.array(data[name])
bmasked=numpy.ma.masked_equal(b,-1)
Chris Withers wrote:
> Hi All,
>
> I'm using xlrd to read an excel workbook containing several columns of
> data
Hi All,
I'm using xlrd to read an excel workbook containing several columns of
data as follows:
for r in range(1,sheet.nrows):
date = \
datetime(*xlrd.xldate_as_tuple(sheet.cell_value(r,0),book.datemode))
if date_cut_off and date < date_cut_off:
continue
for c in range(le
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