From ec40a745f5ac32db7ea702d044e075a8a962305e Mon Sep 17 00:00:00 2001
From: Connor Olding <cloningdonor@gmail.com>
Date: Mon, 19 Feb 2018 04:04:28 -0800
Subject: [PATCH] update 38

---
 lib/smoothfft.py | 21 ++++++++++++++++++++-
 1 file changed, 20 insertions(+), 1 deletion(-)

diff --git a/lib/smoothfft.py b/lib/smoothfft.py
index e670cf0..70b9b96 100644
--- a/lib/smoothfft.py
+++ b/lib/smoothfft.py
@@ -31,10 +31,29 @@ def smoothfft2(xs, ys, bw=1, precision=512, compensate=True):
         # before optimizations: dist = np.abs(np.log2(xs2/(x + 1e-35)))/bw
         dist = np.abs(log2_xs2 - np.log2(x + 1e-35))/bw
         # window = np.maximum(0, 1 - dist) # triangle window
-        window = np.exp(-dist**2/(0.5/2))  # gaussian function (non-truncated)
+        window = np.exp(-dist**2/(0.5/2))  # gaussian window (non-truncated)
         ys2 += ys[i]*window
     if compensate:
         _, temp = smoothfft2(xs, np.ones(len(xs)),
                              bw=bw, precision=precision, compensate=False)
         ys2 /= temp
     return xs2, ys2
+
+
+def smoothfft3(ys, bw=1, precision=512):
+    """performs log-lin smoothing on magnitude data"""
+    size = len(ys)
+    xs = np.arange(0, 1, 1/size)
+
+    xs2 = np.logspace(-np.log2(size), 1, precision, base=2)
+    ys2 = np.zeros(precision)
+    comp = np.zeros(precision)
+
+    log2_xs2 = np.log2(xs2)
+    for i, x in enumerate(xs):
+        dist = np.abs(log2_xs2 - np.log2(x + 1e-35)) / bw
+        window = np.exp(-dist**2 * 4)  # gaussian window (non-truncated)
+        comp += window
+        ys2 += ys[i] * window
+
+    return xs2, ys2 / comp