def __init__(self, *args, **kwargs):
# base class ctor first
ScalarFilterBase.__init__(self, *args, **kwargs)
# all poly emas have an order
self._order = kwargs.get('order', 1)
self._zero_based_order = self._order - 1
#--------------------------------------------------------------------
# buffers
# 1 linear buffer for lags on output y[n]
self._Ycoef = [0.0 for x in range(self._order)]
# 1 circular buffer for lags on output y[n]
self._yn = FixedLengthCircularBuffer(self._order)
# we only have 1 x[n] for polyemas
self._Xcoef = 1.0
self._xn = 0.0
#--------------------------------------------------------------------
# initialization
self._init = False
self._v0 = 0.0
#--------------------------------------------------------------------
# filter parameters
self._inv_gain = 1.0 # gain adjustment
self._M1 = 1.0 # location parameter
#--------------------------------------------------------------------
# event count to determine when the filter is ready
self._event_count = 0
#--------------------------------------------------------------------
# in this pythonic environ need to have more explicit assurance that the filter is made
self._is_made = False
class ScalarPolyEma(ScalarFilterBase):
def __init__(self, *args, **kwargs):
# base class ctor first
ScalarFilterBase.__init__(self, *args, **kwargs)
# all poly emas have an order
self._order = kwargs.get('order', 1)
self._zero_based_order = self._order - 1
#--------------------------------------------------------------------
# buffers
# 1 linear buffer for lags on output y[n]
self._Ycoef = [0.0 for x in range(self._order)]
# 1 circular buffer for lags on output y[n]
self._yn = FixedLengthCircularBuffer(self._order)
# we only have 1 x[n] for polyemas
self._Xcoef = 1.0
self._xn = 0.0
#--------------------------------------------------------------------
# initialization
self._init = False
self._v0 = 0.0
#--------------------------------------------------------------------
# filter parameters
self._inv_gain = 1.0 # gain adjustment
self._M1 = 1.0 # location parameter
#--------------------------------------------------------------------
# event count to determine when the filter is ready
self._event_count = 0
#--------------------------------------------------------------------
# in this pythonic environ need to have more explicit assurance that the filter is made
self._is_made = False
#--------------------------------------------------------------------
# main interface
# a filter must be made, to make a filter the location parameter M1 is required
def make(self, M1):
# capture
self._M1 = M1
# 1) adjust M1 by order m
M1_by_m = float(M1) / self._order
# 2) compute parameter p
p = M1_by_m / (M1_by_m + 1.0)
# 3) compute gain adjustment
self._inv_gain = pow((1.0 - p), self._order)
# 4) compute Ycoef for recursion
# The convolution below expands (1-p z^-1)^order as polynomial coefs to z^-1.
# There are (order + 1) terms, the first term is 1. Thus:
# 1 + phi_1 z^-1 + phi_2 z^-2 + .. + phi_m z^-m
poly_expansion = reduce( lambda x,y: numpy.convolve(x,y), [[1, -p] for x in range(self._order)] )
# Keep only (phi_1, phi_2, .., phi_m) in an m-size linear buffer.
# In addition, flip coef sign to reflect that these terms are shifted to the rhs of the finite-diff eq
self._Ycoef = [ -poly_expansion[i] for i in range(len(poly_expansion)) if i > 0 ]
# prepare the filter
self.reset()
# declare
self._is_made = True
def reset(self):
self._v0 = 0.0
self._init = False
self._xn = 0.0
self._event_count = 0
self._yn.reset()
def relevel(self, v = 0.0):
self.reset()
self._v0 = v
self._init = True
def update(self, v):
# capture level if filter is uninitialized
self._update(v)
# update xn
self._xn = v - self._v0
# prepare yn circ buf
self._yn.toFirst()
# the recursion is
# phi_1 y[n-1] + phi_2 y[n-2] + .. + phi_m y[n-m] + inv_gain x[n]
#
# the linear buffer phi -> Ycoef[i] has its index increment
# the circular buffer yn is called with .prev() to get lag values
yn = sum( [ self._Ycoef[i] * self._yn.prev() for i in range(self._order) ] )
yn += self._inv_gain * self._xn
# push this update to the yn circ buff
self._yn.push(yn)
# lastly, incr the event counter
self._event_count += 1
def value(self):
# must restore the initial offset and apply the filter weight
return (self._yn.first() + self._v0) * self._weight
def initial_value(self):
# return _v0 regardless of _init status
return self._v0
def isReady(self):
# is-ready might be based on several scales, right now I'll just use M1
return self._is_made and (self._event_count > self._M1)
def isMade(self):
return self._is_made
#--------------------------------------------------------------------
# getters
def getOrder(self):
return self._order
def getLocation(self):
return self._M1
def getName(self):
return self._name
def getWeight(self):
return self._weight
def getInvGain(self):
return self._inv_gain
def getEventCount(self):
return self._event_count
#--------------------------------------------------------------------
# reports
def writeRecursion(self, logger):
pass
def writeFilterAttributes(self, logger):
pass
# local methods
def _update(self, v):
if not self._init:
self._v0 = v
self._init = True
def _initialize(self):
pass
def _getCoefs(self):
return [self._Xcoef, self._Ycoef]
