It sounds like you have interactive mode on, in which case each pylab
function redraws the figure.
Yes - it was that simple (and stupid); thanks for your patience. Turning off
interactive mode and using the set_data approach leads to an execution time
of about 0.05 seconds (~30-fold
Eric and John,
Thanks for the information. You are right that this probably would have been a
premature optimisation, even if it weren't rendered useless by matplotlib
using doubles internally (which I hadn't realised). The thought just occurred
to me as I was writing the data-scaling part of
Boris Barbour wrote:
Eric and John,
Thanks for the information. You are right that this probably would have been a
premature optimisation, even if it weren't rendered useless by matplotlib
using doubles internally (which I hadn't realised). The thought just occurred
to me as I was writing
Hi,
I have lots of data acquired via analogue to digital conversion. The data is
consequently represented as integers (often 16 bit resolution). To obtain the
correct signal and plot it, these data must of course be multiplied by a
floating point scale factor. This seems potentially wasteful
Boris Barbour wrote:
Hi,
I have lots of data acquired via analogue to digital conversion. The data is
consequently represented as integers (often 16 bit resolution). To obtain the
correct signal and plot it, these data must of course be multiplied by a
floating point scale factor. This
On Sun, Aug 10, 2008 at 8:06 AM, Boris Barbour [EMAIL PROTECTED] wrote:
Hi,
I have lots of data acquired via analogue to digital conversion. The data is
consequently represented as integers (often 16 bit resolution). To obtain the
correct signal and plot it, these data must of course be
