Keep min and max values of dropped data points

ltsdb_json.py

@@ -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: