def get_endpoints(self):
if isnan(self.m) and isnan(self.b) :
p1 = (self.originalX,self.x1)
p2 = (self.originalX,self.x2)
else:
p1 = (self.x1,self.gety(self.x1))
p2 = (self.x2,self.gety(self.x2))
return p1,p2
def delNaN(xlist,ylist):
"""
If nan values found in ylist associated values in xlist will be removed
INPUT : two lists of equal length
OUTPUT: two lists of equal length
"""
xy_tuplelist = get_tuples_from_lists(xlist,ylist)
for xy_tuple in xy_tuplelist[:]:
if isnan(xy_tuple[1]):
xy_tuplelist.remove(xy_tuple)
xlist,ylist = get_lists_from_tuples(xy_tuplelist)
return xlist,ylist
def gety(self,x):
# gety function that remembers and starts with the previous found segment index
# the assumption is that linesegs will be queried linearly, thereor saving muuultiple passes
iRange = deque(range(len(self.segs)))
iRange.rotate(self.iRemember) # cycles to last remembered index
for i in iRange:
seg = self.segs[i]
y = seg.gety(x) # if x outside the bounds of seg, returns None
if not isnan(y):
self.iRemember=i
return round(y,6)
#if x>seg.x1 and x<seg.x2 and seg.originalX!=None:
# self.iRemember=i
# return seg.gety(x)
# if no corresponging time found return nan
return nan
def timeseries_subtraction(segs1, segs2, times):
"""
input two xbd_sensors and optionally xinterval in integer seconds
xinterval=0 -> original-x points of both continuous-sensors is polled
xinterval=positive -> second difference between polled points
xinterval=negative ->
output a new xbd_sensor containing cont1-cont2 y-data polled xinterval seconds appart
"""
nancount = 0
ylist = []
for x in times:
# gety is a function from func_continuous.py's LineSegs class
y = segs2.gety(x)-segs1.gety(x)
ylist.append(y)
if isnan(y): nancount += 1
print 'len(x),len(y),nancount=',len(times),len(ylist), nancount
return ylist
