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authorRaymond Hettinger <python@rcn.com>2014-04-10 01:18:01 -0600
committerRaymond Hettinger <python@rcn.com>2014-04-10 01:18:01 -0600
commit6ed7c20ce5b01b69abbc01b9a22bdd9983db9c01 (patch)
tree9aafcf6f9ad179f5705ec129f2aa3037a3b43cc0 /Lib/heapq.py
parentbed54b569a304ac020026b8aa764ef6932195fec (diff)
downloadcpython-git-6ed7c20ce5b01b69abbc01b9a22bdd9983db9c01.tar.gz
Update comment for the comparison table to use measured results rather than predicted.
Diffstat (limited to 'Lib/heapq.py')
-rw-r--r--Lib/heapq.py19
1 files changed, 10 insertions, 9 deletions
diff --git a/Lib/heapq.py b/Lib/heapq.py
index 789b17a693..88c7019abc 100644
--- a/Lib/heapq.py
+++ b/Lib/heapq.py
@@ -202,16 +202,17 @@ def _heapify_max(x):
# Number of comparisons for n random inputs, keeping the k smallest values:
# -----------------------------------------------------------
# Step Comparisons Action
-# 1 2*k heapify the first k-inputs
-# 2 n-k compare new input elements to top of heap
-# 3 k*lg2(k)*(ln(n)-lg(k)) add new extreme values to the heap
+# 1 1.66*k heapify the first k-inputs
+# 2 n - k compare new input elements to top of heap
+# 3 k*lg2(k)*(ln(n)-ln(k)) add new extreme values to the heap
# 4 k*lg2(k) final sort of the k most extreme values
#
-# n-random inputs k-extreme values number of comparisons % more than min()
-# --------------- ---------------- ------------------- -----------------
-# 10,000 100 13,634 36.3%
-# 100,000 100 105,163 5.2%
-# 1,000,000 100 1,006,694 0.7%
+# number of comparisons
+# n-random inputs k-extreme values average of 5 trials % more than min()
+# --------------- ---------------- ------------------- -----------------
+# 10,000 100 14,046 40.5%
+# 100,000 100 105,749 5.7%
+# 1,000,000 100 1,007,751 0.8%
#
# Computing the number of comparisons for step 3:
# -----------------------------------------------
@@ -234,7 +235,7 @@ def _heapify_max(x):
# comparisons = k * log(k, 2) * (log(n,e) - log(k, e))
#
# Worst-case for step 3:
-# ---------------------
+# ----------------------
# In the worst case, the input data is reversed sorted so that every new element
# must be inserted in the heap:
# comparisons = log(k, 2) * (n - k)