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OneEuroFilter.py
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OneEuroFilter.py
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# -*- coding: utf-8 -*-
#
# OneEuroFilter.py -
#
# Author: Nicolas Roussel (nicolas.roussel@inria.fr)
# Copyright 2019 Inria
#
# BSD License https://opensource.org/licenses/BSD-3-Clause
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
#
# 1. Redistributions of source code must retain the above copyright notice, this list of conditions
# and the following disclaimer.
#
# 2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions
# and the following disclaimer in the documentation and/or other materials provided with the distribution.
#
# 3. Neither the name of the copyright holder nor the names of its contributors may be used to endorse or
# promote products derived from this software without specific prior written permission.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES,
# INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
# DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
# SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
# LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
# CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
# SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
#
import math
# ----------------------------------------------------------------------------
class LowPassFilter(object):
def __init__(self, alpha):
self.__setAlpha(alpha)
self.__y = self.__s = None
def __setAlpha(self, alpha):
alpha = float(alpha)
if alpha<=0 or alpha>1.0:
raise ValueError("alpha (%s) should be in (0.0, 1.0]"%alpha)
self.__alpha = alpha
def __call__(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, freq, mincutoff=1.0, beta=0.0, dcutoff=1.0):
if freq<=0:
raise ValueError("freq should be >0")
if mincutoff<=0:
raise ValueError("mincutoff should be >0")
if dcutoff<=0:
raise ValueError("dcutoff should be >0")
self.__freq = float(freq)
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 __call__(self, x, timestamp=None):
# ---- 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(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(x, timestamp, alpha=self.__alpha(cutoff))
# ----------------------------------------------------------------------------
if __name__=="__main__":
import random
duration = 10.0 # seconds
config = {
'freq': 120, # Hz
'mincutoff': 1.0, # FIXME
'beta': 1.0, # FIXME
'dcutoff': 1.0 # this one should be ok
}
print ("#SRC OneEuroFilter.py")
print ("#CFG %s"%config)
print ("#LOG timestamp, signal, noisy, filtered")
f = OneEuroFilter(**config)
timestamp = 0.0 # seconds
while timestamp<duration:
signal = math.sin(timestamp)
noisy = signal + (random.random()-0.5)/5.0
filtered = f(noisy, timestamp)
print ("{0}, {1}, {2}, {3}".format(timestamp, signal, noisy, filtered))
timestamp += 1.0/config["freq"]