大约有 800 项符合查询结果（耗时：0.0183秒） [XML]
How do I efficiently iterate over each entry in a Java Map?
...rror Units
test3_UsingForEachAndJava8 avgt 10 0.308 ± 0.021 µs/op
test10_UsingEclipseMap avgt 10 0.309 ± 0.009 µs/op
test1_UsingWhileAndMapEntry avgt 10 0.380 ± 0.014 µs/op
test6_UsingForAndIterator avgt 10 0.387 ± 0.016 µs/op
test2_Us...
Cosmic Rays: what is the probability they will affect a program?
...M, then the failure probability would be
60 × 20 × 1024²
1 - (1 - 1.4e-15) = 1.8e-6 a.k.a. "5 nines"
Error checking can help to reduce the aftermath of failure. Also, because of more compact size of chips as commented by Joe, the failure rate could be differen...
Find element's index in pandas Series
...randint(0,10,10000))
In [9]: %timeit s[s == 5]
1000 loops, best of 3: 203 µs per loop
In [12]: i = Index(s)
In [13]: %timeit i.get_loc(5)
1000 loops, best of 3: 226 µs per loop
As Viktor points out, there is a one-time creation overhead to creating an index (its incurred when you actually DO ...
Generate a random point within a circle (uniformly)
...
Oh, nice! To be clear, when you say random(min_radius², max_radius²), do you mean something equivalent to random() * (max_radius² - min_radius²) + min_radius², where random() returns a uniform value between 0 and 1?
– aioobe
Jul 31 '1...
Cartesian product of x and y array points into single array of 2D points
...1000)]
Test results:
In [2]: test_all(*(x100 * 2))
repeat_product:
67.5 µs ± 633 ns per loop (mean ± std. dev. of 7 runs, 10000 loops each)
dstack_product:
67.7 µs ± 1.09 µs per loop (mean ± std. dev. of 7 runs, 10000 loops each)
cartesian_product:
33.4 µs ± 558 ns per loop (mean ± std....
How to determine whether a Pandas Column contains a particular value
...10]: x = pd.Series(range(1000000))
In [13]: timeit 999999 in x.values
567 µs ± 25.6 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each)
In [15]: timeit x.isin([999999]).any()
9.54 ms ± 291 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)
In [16]: timeit (x == 999999).any()
6....
Why isn't my Pandas 'apply' function referencing multiple columns working? [closed]
... that an intermediate result is being cached. 1000 loops, best of
3: 481 µs per loop
Example 2: vectorize using pandas.apply():
%%timeit
df['a'] % df['c']
The slowest run took 458.85 times longer than the fastest. This could
mean that an intermediate result is being cached. 10000 loops...
iPhone: How to get current milliseconds?
...if portability is a priority for you.
iPhone 4S
CACurrentMediaTime: 1.33 µs/call
gettimeofday: 1.38 µs/call
[NSDate timeIntervalSinceReferenceDate]: 1.45 µs/call
CFAbsoluteTimeGetCurrent: 1.48 µs/call
[[NSDate date] timeIntervalSince1970]: 4.93 µs/call
iPad 3
CACurrentMediaTime: 1.25 µs/c...
How to compare Unicode characters that “look alike”?
...ain(string[] args)
{
char first = 'μ';
char second = 'µ';
// Technically you only need to normalize U+00B5 to obtain U+03BC, but
// if you're unsure which character is which, you can safely normalize both
string firstNormalized = first.ToString().Normal...
Circle line-segment collision detection algorithm?
...ithm
// compute the euclidean distance between A and B
LAB = sqrt( (Bx-Ax)²+(By-Ay)² )
// compute the direction vector D from A to B
Dx = (Bx-Ax)/LAB
Dy = (By-Ay)/LAB
// the equation of the line AB is x = Dx*t + Ax, y = Dy*t + Ay with 0 <= t <= LAB.
// compute the distance between the po...