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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...
Insert an element at a specific index in a list and return the updated list
...ents for Python 3.4.5:
Mine answer using sliced insertion - Fastest (3.08 µsec per loop)
mquadri$ python3 -m timeit -s "a = list(range(1000))" "b = a[:]; b[500:500] = [3]"
100000 loops, best of 3: 3.08 µsec per loop
ATOzTOA's accepted answer based on merge of sliced lists - Second (6.71 µsec...
“Cloning” row or column vectors
...t;>> %timeit np.array(np.broadcast_to(x, (reps, n)))
10.2 ms ± 62.3 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)
>>> %timeit np.repeat(x[np.newaxis, :], reps, axis=0)
9.88 ms ± 52.4 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)
>>> %timeit np.ti...
Python dictionary: Get list of values for list of keys
...imeit map(lambda _: m[_], l) # using 'map'
1000000 loops, best of 3: 1.66 µs per loop
In[5]: %timeit list(m[_] for _ in l) # a generator expression passed to a list constructor.
1000000 loops, best of 3: 1.65 µs per loop
In[6]: %timeit map(m.__getitem__, l)
The slowest run took 4.01 times longer...
Return multiple columns from pandas apply()
...best of 3: 2.61 ms per loop
Return tuple:
1000 loops, best of 3: 819 µs per loop
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Difference between getContext() , getApplicationContext() , getBaseContext() and “this”
...| NO¹ | NO¹ |
| Layout Inflation | NO² | YES | NO² | NO² | NO² |
| Start a Service | YES | YES | YES | YES | YES |
| Bind to a Service | YES | Y...
How to select rows from a DataFrame based on column values?
...imeit mask = df['A'].values == 'foo'
%timeit mask = df['A'] == 'foo'
5.84 µs ± 195 ns per loop (mean ± std. dev. of 7 runs, 100000 loops each)
166 µs ± 4.45 µs per loop (mean ± std. dev. of 7 runs, 10000 loops each)
Evaluating the mask with the numpy array is ~ 30 times faster. This is pa...
The most efficient way to implement an integer based power function pow(int, int)
...n chain for a¹⁵ above, the subproblem for a⁶ must be computed as (a³)² since a³ is re-used (as opposed to, say, a⁶ = a²(a²)², which also requires three multiplies).
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How to calculate moving average using NumPy?
...an ± std. dev. of 7 runs, 1 loop each)
scipy.convolve :
1.07 ms ± 26.7 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each)
scipy.convolve, edge handling :
4.68 ms ± 9.69 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)
numpy.cumsum :
5.31 ms ± 5.11 µs per loop (mean ± s...
Set value for particular cell in pandas DataFrame using index
...
In [18]: %timeit df.set_value('C', 'x', 10)
100000 loops, best of 3: 2.9 µs per loop
In [20]: %timeit df['x']['C'] = 10
100000 loops, best of 3: 6.31 µs per loop
In [81]: %timeit df.at['C', 'x'] = 10
100000 loops, best of 3: 9.2 µs per loop
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