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Keep min and max values of dropped data points

This commit is contained in:
Peter J. Holzer 2023-01-05 15:14:28 +01:00
parent c5b8476a42
commit ca0ce798da
1 changed files with 27 additions and 2 deletions
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29
ltsdb_json.py
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@ -43,6 +43,31 @@ class LTS:
json.dump({"description": self.description, "data": self.data}, fh)
self.rebuild_index()
def pop(self, i):
# Pop the element at index i and adjust the min/max values of the
# neighbours.
# We might also want to adjust the value of the neighbours to some
# (weighted) average, but I'm not sure if this is actually a good idea.
data = self.data
old = data.pop(i) # after that the neighbours are at i-1, i
min_v = old[2] if len(old) >= 4 else old[1]
max_v = old[3] if len(old) >= 4 else old[1]
if i > 0:
if len(data[i-1]) == 2:
data[i-1] = [data[i-1][0], data[i-1][1], data[i-1][1], data[i-1][1]]
if min_v < data[i-1][2]:
data[i-1][2] = min_v
if max_v > data[i-1][3]:
data[i-1][3] = max_v
if i < len(data):
if len(data[i]) == 2:
data[i] = [data[i][0], data[i][1], data[i][1], data[i][1]]
if min_v < data[i][2]:
data[i][2] = min_v
if max_v > data[i][3]:
data[i][3] = max_v
return old
def shrink(self):
# Remove one element in such a way that the distributions gets closer
# to an exponential curve through the first and the last few data
@ -61,7 +86,7 @@ class LTS:
t_ideal = (math.exp(k * (n - i)/n) - 1) * (n * dt)
if t_last - data[i][0] > t_ideal:
log.debug("%s - %s > %s -> popping element %s", t_last, data[i][0], t_ideal, i)
data.pop(i)
self.pop(i)
break
else:
# Well, it works mostly. Sometimes all the real points are below
@ -71,7 +96,7 @@ class LTS:
# narrow range just before that.
i = random.randrange(int(n*0.98), int(n*0.99))
log.debug("no match -> popping element %s", i)
data.pop(i)
self.pop(i)
def add(self, ts, value):
while len(self.data) >= self.limit: