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mekman opened this issue Sep 24, 2013 · 1 comment
Open

clarification: make_dmtx() #295

mekman opened this issue Sep 24, 2013 · 1 comment

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@mekman
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mekman commented Sep 24, 2013

Hi all,

I have some questions regarding the make_dmtx function here:
https://github.com/nipy/nipy/blob/master/nipy/modalities/fmri/design_matrix.py#L312

I could send a PR to clarify the docstring a bit, but would need some feedback first.

(1) The docstring says:

hfcut: float, optional
       cut frequency of the low-pass filter

But it actually means something like: High pass filter cutoff, in seconds, correct?

(2) hfcut has no effect if drift_model='blank', correct?

(3) from a quick look at the code it wasn't clear to me whether the additional regressors (add_regs) are also high-pass filtered. I don't think that is the case, but it should be, no?

Thanks,
Matthias

@bthirion
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On 24/09/2013 13:47, Matthias Ekman wrote:

Hi all,

I have some questions regarding the |make_dmtx| function here:
https://github.com/nipy/nipy/blob/master/nipy/modalities/fmri/design_matrix.py#L312

I could send a PR to clarify the docstring a bit, but would need tome
feedback first.

(1) The docstring says:

|hfcut: float, optional
cut frequency of the low-pass filter
|

But it actually means something like: High pass filter cutoff, in
seconds, correct?

 Hi Mathias,

You're right

(2) |hfcut| has no effect if |drift_model='blank'|, correct?

Indeed.

(3) from a quick look at the code it wasn't clear to me whether the
additional regressors (|add_regs|) are also high-pass filtered. I
don't think that is the case, but it should be, no?

You're right too -- although I do not think that this makes a difference
since including drifts + add_regs
or drifts + filtered addregs as regressors of no interest should not
change the results for the main regressors.
Nevertheless, for the sake of numerical accuracy, it is probably better
to filter them.

A PR is certainlyly welcome. Best,

Bertrand

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