Update docs.

[python_utils.git] / math_utils.py

diff --git a/math_utils.py b/math_utils.py
index 270df8ccb3e8a1fcd5ea3f955438f800fcb69807..ed9c2f450f0fb0a9b121069a19d4a0b1fe7acfba 100644 (file)
--- a/math_utils.py
+++ b/math_utils.py
@@ -41,6 +41,8 @@ class NumericPopulation(object):
         self.lowers, self.highers = [], []
         self.aggregate = 0.0
         self.sorted_copy: Optional[List[float]] = None
+        self.maximum = None
+        self.minimum = None
 
     def add_number(self, number: float):
         """Adds a number to the population.  Runtime complexity of this
@@ -52,6 +54,10 @@ class NumericPopulation(object):
             heappush(self.lowers, -number)  # for lowers we need a max heap
         self.aggregate += number
         self._rebalance()
+        if not self.maximum or number > self.maximum:
+            self.maximum = number
+        if not self.minimum or number < self.minimum:
+            self.minimum = number
 
     def _rebalance(self):
         if len(self.lowers) - len(self.highers) > 1:
@@ -96,9 +102,18 @@ class NumericPopulation(object):
             variance += (n - mean) ** 2
         for n in self.highers:
             variance += (n - mean) ** 2
-        count = len(self.lowers) + len(self.highers) - 1
+        count = len(self.lowers) + len(self.highers)
         return math.sqrt(variance) / count
 
+    def _create_sorted_copy_if_needed(self, count: int):
+        if not self.sorted_copy or count != len(self.sorted_copy):
+            self.sorted_copy = []
+            for x in self.lowers:
+                self.sorted_copy.append(-x)
+            for x in self.highers:
+                self.sorted_copy.append(x)
+            self.sorted_copy = sorted(self.sorted_copy)
+
     def get_percentile(self, n: float) -> float:
         """Returns the number at approximately pn% (i.e. the nth percentile)
         of the distribution in O(n log n) time.  Not thread-safe;
@@ -108,17 +123,11 @@ class NumericPopulation(object):
         if n == 50:
             return self.get_median()
         count = len(self.lowers) + len(self.highers)
-        if self.sorted_copy is not None:
-            if count == len(self.sorted_copy):
-                index = round(count * (n / 100.0))
-                assert 0 <= index < count
-                return self.sorted_copy[index]
-        self.sorted_copy = [-x for x in self.lowers]
-        for x in self.highers:
-            self.sorted_copy.append(x)
-        self.sorted_copy = sorted(self.sorted_copy)
+        self._create_sorted_copy_if_needed(count)
+        assert self.sorted_copy
         index = round(count * (n / 100.0))
-        assert 0 <= index < count
+        index = max(0, index)
+        index = min(count - 1, index)
         return self.sorted_copy[index]