[SciPy-user] Fitting with global parameters optimize.leastsq
iain at day-online.org.uk.invalid
Mon Nov 6 11:45:01 CST 2006
I apologise in advance if this has been covered elsewhere, I can't seem
to get my head around it.
I'm trying to globally fit a series of traces to the same function with
some common and some local parameters. I have a 2D array (raw_signals)
which contains each data trace as its columns. I have a 1D array of the
I'd like to fit an exponential of the form:
y(t) = A * exp(-t/B) + C
and I'd like C to be global across all data sets, but A and B to be
local to each trace.
So far I've put A and B into arrays ntraces long. I'm trying to keep the
code as general as possible as I've got lots to fit each with differing
numbers of traces.
I've followed the example on the SciPy cookbook and I see the principle
but I'm not sure ow to extend it in my case.
I've got some code which generates the error (cost) function as an array
of the same dimensions as raw_signals, but I can't see how to use
optimize.leastsq with that.
I hope this makes sense. I'll happily provide more info if needs be. Any
help would be greatly appreciated.
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