<p dir="ltr">Perhaps. We can discuss that on GitHub if people are interested in seeing it. </p>
<p dir="ltr">Eric<br>
</p>
<div class="gmail_quote">On May 20, 2016 6:58 PM, "Ross Maddox" <<a href="mailto:rkmaddox@uw.edu">rkmaddox@uw.edu</a>> wrote:<br type="attribution"><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><p dir="ltr">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?<br>
</p>
<div class="gmail_quote">On May 20, 2016 5:13 PM, "Eric Larson" <<a href="mailto:larson.eric.d@gmail.com" target="_blank">larson.eric.d@gmail.com</a>> wrote:<br type="attribution"><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div dir="ltr">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., <font face="monospace, monospace">a=[1.]</font>).<div><br></div><div>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:</div><div><br></div><div><a href="https://github.com/scipy/scipy/pull/5989" target="_blank">https://github.com/scipy/scipy/pull/5989</a><br></div><div><br></div><div>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.</div><div><br></div><div>Eric</div><div><br></div></div><div class="gmail_extra"><br><div class="gmail_quote">On Fri, May 20, 2016 at 5:03 PM, Moorselaar, D. van <span dir="ltr"><<a href="mailto:d.van.moorselaar@vu.nl" target="_blank">d.van.moorselaar@vu.nl</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex">Hello,<br>
<br>
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.<br>
<br>
If I understand the MNE documentation correctly, in mne the forward-backward filtering option is only possible with iir filters?<br>
<br>
Is this correct or is the forward-backward option also implemented in the FIR filter.<br>
<br>
Thank you,<br>
<br>
Dirk van Moorselaar<br>
<br>
<br>
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