reimplement percentile function

1 files changed, 11 insertions, 11 deletions

diff --git a/tools/profiling/latency_profile/profile_analyzer.py b/tools/profiling/latency_profile/profile_analyzer.py
index d4d14ef8c7..ad453a9eb0 100755
--- a/tools/profiling/latency_profile/profile_analyzer.py
+++ b/tools/profiling/latency_profile/profile_analyzer.py
@@ -184,24 +184,24 @@ for cs in call_stacks:
 
 def percentile(N, percent, key=lambda x: x):
     """
-    Find the percentile of a list of values.
+    Find the percentile of an already sorted list of values.
 
-    @parameter N - is a list of values. Note N MUST BE already sorted.
-    @parameter percent - a float value from 0.0 to 1.0.
+    @parameter N - is a list of values. MUST be already sorted.
+    @parameter percent - a float value from [0.0,1.0].
     @parameter key - optional key function to compute value from each element of N.
 
     @return - the percentile of the values
     """
     if not N:
         return None
-    k = (len(N) - 1) * percent
-    f = math.floor(k)
-    c = math.ceil(k)
-    if f == c:
-        return key(N[int(k)])
-    d0 = key(N[int(f)]) * (c - k)
-    d1 = key(N[int(c)]) * (k - f)
-    return d0 + d1
+    idx = (len(N) - 1) * percent
+    idx_floor = math.floor(idx)
+    idx_ceil = math.ceil(idx)
+    if idx_floor != idx_ceil:
+        # interpolate the nearest element values
+        return (key(N[int(idx_floor)]) * (idx_ceil - idx) +
+                key(N[int(idx_ceil)]) * (idx - idx_floor))
+    return key(N[int(idx)])
 
 
 def tidy_tag(tag):