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Jul 14, 2013, 9:32:52 AM7/14/13

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Hi,

I've got a lo of voltage traces with EPSPs. I've got the basics of setting the cursors and fitting a function to my raw data. What I'd like to do is to then convert the fitted function into a numpy array (over a set range) which I can use to subtract from other traces. Is there an easy way to access the output of the least_sq() to do this or is it just a matter of defining a dual exponential and inserting the time constant values. If the latter is the case, what is the equation for least_sq(5)?

I don't know what 'factor' refers to in the output or how it produces an EPSP like shape when both time constants are outputted as positive numbers.

Jul 14, 2013, 9:37:02 AM7/14/13

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Also I am using the latest version of stimfit on windows 7

Jul 14, 2013, 10:29:54 AM7/14/13

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On Sun, Jul 14, 2013 at 06:32:52AM -0700, Andrew Micallef wrote:

> I've got a lo of voltage traces with EPSPs. I've got the basics of

> setting the cursors and fitting a function to my raw data. What I'd

> like to do is to then convert the fitted function into a numpy array

> (over a set range) which I can use to subtract from other traces.

stf.get_fit() returns the evaluated function as a NumPy array. First
> I've got a lo of voltage traces with EPSPs. I've got the basics of

> setting the cursors and fitting a function to my raw data. What I'd

> like to do is to then convert the fitted function into a numpy array

> (over a set range) which I can use to subtract from other traces.

dimension is time, second dimension are the function evaluation

results.

> Is there an easy way to access the output of the least_sq() to do

> this or is it just a matter of defining a dual exponential and

> inserting the time constant values. If the latter is the case, what

> is the equation for least_sq(5)?

http://www.stimfit.org/doc/doxygen/html/group__stfgen.html#ga4dd9d335d263c75d61961db8bb1fe1e2

The corresponding source code is here:

https://code.google.com/p/stimfit/source/browse/src/stimfit/math/funclib.cpp#260

The function is called "stf::fexpbde". We are not performing any

normalization at present; i.e. the amplitude factor p[3] will be

different from the maximum of the function.

Best,

Christoph

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