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Fitting empirical distribution to theoretical ones with Scipy (Python)?
... # Get sane start and end points of distribution
start = dist.ppf(0.01, *arg, loc=loc, scale=scale) if arg else dist.ppf(0.01, loc=loc, scale=scale)
end = dist.ppf(0.99, *arg, loc=loc, scale=scale) if arg else dist.ppf(0.99, loc=loc, scale=scale)
# Build PDF and turn into pandas Seri...
Seeding the random number generator in Javascript
...llions of random numbers (see Birthday problem).
xoshiro128**
As of May 2018, xoshiro128** is the new member of the Xorshift family, by Vigna & Blackman (professor Vigna was also responsible for the Xorshift128+ algorithm powering most Math.random implementations under the hood). It is the fas...
Is pass-by-value a reasonable default in C++11?
...he place..
– stijn
May 28 '13 at 14:01
1
There is one risk with const&, that has tripped me u...
Check if an element's content is overflowing?
...m/gist/2462915
And an explanation you can find here: http://lea.verou.me/2012/04/background-attachment-local/.
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application/x-www-form-urlencoded or multipart/form-data?
...8/….
– Joshcodes
Apr 30 '14 at 22:01
21
@EML, This doesn't make sense at all. Obviously the bou...
Are global variables bad? [closed]
...
– noɥʇʎԀʎzɐɹƆ
Jul 8 '16 at 22:01
3
@noɥʇʎԀʎzɐɹƆ Here you go! i.imgur.com/RwRgJLZ.jp...
google oauth2 redirect_uri with several parameters
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answered Jul 14 '12 at 11:01
ruforufo
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...
How to read keyboard-input?
..._str.
# The rest of your program goes here.
time.sleep(0.01)
print("End.")
if (__name__ == '__main__'):
main()
2. Same Python 3 code as above, but with extensive explanatory comments:
"""
read_keyboard_input.py
Gabriel Staples
www.ElectricRCAircraftGuy.com
14 Nov. 20...
Is Java Regex Thread Safe?
...32
Sam
6,01244 gold badges3838 silver badges5252 bronze badges
answered Sep 1 '09 at 1:14
Vineet ReynoldsVinee...
How to do exponential and logarithmic curve fitting in Python? I found only polynomial fitting
...9])
>>> numpy.polyfit(x, numpy.log(y), 1)
array([ 0.10502711, -0.40116352])
# y ≈ exp(-0.401) * exp(0.105 * x) = 0.670 * exp(0.105 * x)
# (^ biased towards small values)
>>> numpy.polyfit(x, numpy.log(y), 1, w=numpy.sqrt(y))
array([ 0.06009446, 1.41648096])
# y ≈ exp(1.4...