[med-svn] [python-mne] 234/376: basic band pass filter based on firwin2

[Yaroslav Halchenko]

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yoh pushed a commit to annotated tag v0.1
in repository python-mne.

commit f8a385eeaaef6b6925b0b6bdb62f561bd432f702
Author: Alexandre Gramfort <alexandre.gramfort at inria.fr>
Date:   Thu May 5 16:04:52 2011 -0400

    basic band pass filter based on firwin2
---
 mne/filter.py | 76 +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 76 insertions(+)

diff --git a/mne/filter.py b/mne/filter.py
new file mode 100644
index 0000000..a6a8be4
--- /dev/null
+++ b/mne/filter.py
@@ -0,0 +1,76 @@
+import numpy as np
+from scipy import signal
+from scipy.fftpack import fft, ifft
+
+
+def band_pass_filter(x, Fs, Fp1, Fp2):
+    """Bandpass filter for the signal x.
+
+    An acausal fft algorithm is applied (i.e. no phase shift). The filter
+    functions is constructed from a Hamming window (window used in "firwin2"
+    function) to avoid ripples in the frequency reponse (windowing is a
+    smoothing in frequency domain)
+
+    Parameters
+    ----------
+    x : 1d array
+        Signal to filter
+    Fs : float
+        sampling rate
+    Fp1 : float
+        low cut-off frequency
+    Fp2 : float
+        high cut-off frequency
+
+    Returns
+    -------
+    xf : array
+        x filtered
+
+    Notes
+    -----
+    The passbands (Fp1 Fp2) frequencies are defined in Hz as
+                     ----------
+                   /|         | \
+                  / |         |  \
+                 /  |         |   \
+                /   |         |    \
+      ----------    |         |     -----------------
+                    |         |
+              Fs1  Fp1       Fp2   Fs2
+
+    DEFAULTS values
+    Fs1 = Fp1 - 0.5 in Hz
+    Fs2 = Fp2 + 0.5 in Hz
+    """
+
+    # Default values in Hz
+    Fs1 = Fp1 - 0.5
+    Fs2 = Fp2 + 0.5
+
+    assert x.ndim == 1
+
+    # Make x EVEN
+    Norig = len(x)
+    if Norig % 2 == 1:
+        x = np.c_[x, 1]
+
+    # Normalize frequencies
+    Ns1 = Fs1 / (Fs / 2)
+    Ns2 = Fs2 / (Fs / 2)
+    Np1 = Fp1 / (Fs / 2)
+    Np2 = Fp2 / (Fs / 2)
+
+    # Construct the filter function H(f)
+    N = len(x)
+
+    B = signal.firwin2(N, [0, Ns1, Np1, Np2, Ns2, 1], [0, 0, 1, 1, 0, 0])
+
+    # Make zero-phase filter function
+    H = np.abs(fft(B))
+
+    xf = np.real(ifft(fft(x) * H))
+    xf = xf[:Norig]
+    x = x[:Norig]
+
+    return xf

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