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Kirill Smelkov
cpython
Commits
6ed7c20c
Commit
6ed7c20c
authored
Apr 10, 2014
by
Raymond Hettinger
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Update comment for the comparison table to use measured results rather than predicted.
parent
bed54b56
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Lib/heapq.py
Lib/heapq.py
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Lib/heapq.py
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6ed7c20c
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@@ -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)-l
g
(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)-l
n
(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:
# -----------------------------------------------
...
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@@ -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)
...
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