[Mne_analysis] FIR filter in mne

[Eric Larson]

Perhaps. We can discuss that on GitHub if people are interested in seeing
it.

Eric
On May 20, 2016 6:58 PM, "Ross Maddox" <rkmaddox at uw.edu> wrote:

> Using the iir code for fir filtering would work, but it would miss out on
> all the speed benefits of fir filtering, especially when doing zero phase
> (i.e. forward backward). Should we expose _overlap_add_filter?
> On May 20, 2016 5:13 PM, "Eric Larson" <larson.eric.d at gmail.com> wrote:
>
>> You can use the IIR code -- a FIR filter can be expressed as an IIR
>> filter with a [1] for the denominator coefficient (i.e., a=[1.]).
>>
>> If you need the FIR coefficients to be identical and want to stay in
>> Python, you'll have to wait until `firls` is implemented in SciPy:
>>
>> https://github.com/scipy/scipy/pull/5989
>>
>> In the meantime, though, you could compute the filter coefficients in
>> MATLAB, save them, and load them in Python. Also, make sure they used
>> forward-backward (acausal) filtering, and not one-pass (causal) FIR
>> filtering, as they will produce different results.
>>
>> Eric
>>
>>
>> On Fri, May 20, 2016 at 5:03 PM, Moorselaar, D. van <
>> d.van.moorselaar at vu.nl> wrote:
>>
>>> Hello,
>>>
>>> I am trying to replicate an EEG study that used Matlab with mne. This
>>> study reported to have used a bandpass two-way least-squares finite impulse
>>> response filter for power analyses.
>>>
>>> If I understand the MNE documentation correctly, in mne the
>>> forward-backward filtering option is only possible with iir filters?
>>>
>>> Is this correct or is the forward-backward option also implemented in
>>> the FIR filter.
>>>
>>> Thank you,
>>>
>>> Dirk van Moorselaar
>>>
>>>
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