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+# -*- coding: utf-8 -*-
+# libavg - Media Playback Engine.
+# Copyright (C) 2003-2014 Ulrich von Zadow
+#
+# This library is free software; you can redistribute it and/or
+# modify it under the terms of the GNU Lesser General Public
+# License as published by the Free Software Foundation; either
+# version 2 of the License, or (at your option) any later version.
+#
+# This library is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
+# Lesser General Public License for more details.
+#
+# You should have received a copy of the GNU Lesser General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
+#
+# Current versions can be found at www.libavg.de
+#
+
+import math
+
+# Input filter based on:
+# Casiez, G., Roussel, N. and Vogel, D. (2012). 1€ Filter: A Simple Speed-based Low-pass
+# Filter for Noisy Input in Interactive Systems. Proceedings of the ACM Conference on
+# Human Factors in Computing Systems (CHI '12). Austin, Texas (May 5-12, 2012). New York:
+# ACM Press, pp. 2527-2530.
+
+class LowPassFilter(object):
+
+ def __init__(self, alpha):
+ self.__setAlpha(alpha)
+ self.__y = None
+ self.__s = None
+
+ def __setAlpha(self, alpha):
+ alpha = float(alpha)
+ if alpha <= 0 or alpha > 1.0:
+ raise RuntimeError("LowPassFilter alpha (%s) should be in (0.0, 1.0]"%alpha)
+ self.__alpha = alpha
+
+ def apply(self, value, timestamp=None, alpha=None):
+ if alpha is not None:
+ self.__setAlpha(alpha)
+ if self.__y is None:
+ s = value
+ else:
+ s = self.__alpha*value + (1.0-self.__alpha)*self.__s
+ self.__y = value
+ self.__s = s
+ return s
+
+ def lastValue(self):
+ return self.__y
+
+
+class OneEuroFilter(object):
+
+ def __init__(self, mincutoff=1.0, beta=0.0, dcutoff=1.0):
+ if mincutoff<=0:
+ raise ValueError("mincutoff should be >0")
+ if dcutoff<=0:
+ raise ValueError("dcutoff should be >0")
+ self.__freq = 60 # Initial freq, updated as soon as we have > 1 sample
+ self.__mincutoff = float(mincutoff)
+ self.__beta = float(beta)
+ self.__dcutoff = float(dcutoff)
+ self.__x = LowPassFilter(self.__alpha(self.__mincutoff))
+ self.__dx = LowPassFilter(self.__alpha(self.__dcutoff))
+ self.__lasttime = None
+
+ def __alpha(self, cutoff):
+ te = 1.0 / self.__freq
+ tau = 1.0 / (2*math.pi*cutoff)
+ return 1.0 / (1.0 + tau/te)
+
+ def apply(self, x, timestamp):
+ timestamp /= 1000.
+ if self.__lasttime == timestamp:
+ return x
+ else:
+ # ---- update the sampling frequency based on timestamps
+ if self.__lasttime and timestamp:
+ self.__freq = 1.0 / (timestamp-self.__lasttime)
+ self.__lasttime = timestamp
+ # ---- estimate the current variation per second
+ prev_x = self.__x.lastValue()
+ dx = 0.0 if prev_x is None else (x-prev_x)*self.__freq # FIXME: 0.0 or value?
+ edx = self.__dx.apply(dx, timestamp, alpha=self.__alpha(self.__dcutoff))
+ # ---- use it to update the cutoff frequency
+ cutoff = self.__mincutoff + self.__beta*math.fabs(edx)
+ # ---- filter the given value
+ return self.__x.apply(x, timestamp, alpha=self.__alpha(cutoff))
+