Hi Gokhan - easy - we are not dealing with the measurement part at all, only with the analysis of data that has already been measured, so if you don't think a pico-second representation is appropriate for your data (and it probably is appropriate for very few kinds of data...), then use the right temporal resolution for your data. Best - Ariel On Wed, Feb 24, 2010 at 9:10 AM, Gökhan Sever <gokhansever@gmail.com> wrote:
On Wed, Feb 24, 2010 at 12:32 AM, Ariel Rokem <arokem@berkeley.edu> wrote:
Hi everyone,
Gokhan is referring to this:
http://nipy.sourceforge.net/nitime/
For an exposition, see our Scipy conference proceedings paper (a pdf of which can be found here: http://argentum.ucbso.berkeley.edu/papers/Rokem2009Nitime.pdf).
We are still working on it. The intention of the library is to support analysis of data from neuroscience experiments, because we are neuroscientists, but so far, I don't think that we have made any design decisions that would preclude other scientists from using our time-series objects. In fact, the time-series objects we have designed support temporal resolutions as fast as picoseconds (the representation of time is done in int64, in order to avoid float-precision issues). It is still under development and we have yet to make a release of this, but the code (in development) is already available on github and the tests therein can direct you on the possible usage:
http://github.com/fperez/nitime
Cheers,
Ariel
Hi Ariel,
What kind of interface do you use to measure pico-second resolutions? Are you talking measurements from only one instrument at a time?
In our work even at 1 Hz levels we encounter issues like time-syncing different measurements since we interface many different instruments with one main data acquisition unit. This is mainly due to one instrument sits under the far edge of a wing the other one is inside the cabin sampling air from outside. It is usually a good idea to sample fastest the system and probes permits, in the end they would be easily averaged to a lower acceptable resolution range.
Your job should be very hard indeed if you are dealing with a couple different instruments at that high measurement rates.
-- Gökhan
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-- Ariel Rokem Helen Wills Neuroscience Institute University of California, Berkeley http://argentum.ucbso.berkeley.edu/ariel