Draw samples from a Rayleigh distribution.
The
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and Weibull distributions are generalizations of the
Rayleigh.
| Parameters : | scale : scalar
Scale, also equals the mode. Should be >= 0.
size : int or tuple of ints, optional
Shape of the output. Default is None, in which case a single
value is returned.
|
|---|
Notes
The probability density function for the Rayleigh distribution is
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rman-x-2011-07-01, ngerman-x-2011-07-01, afrikaans, ancientgreek, ibycus, arabi
c, armenian, basque, bulgarian, catalan, pinyin, coptic, croatian, czech, danis
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h, french, friulan, galician, german, ngerman, swissgerman, monogreek, greek, h
ungarian, icelandic, assamese, bengali, gujarati, hindi, kannada, malayalam, ma
rathi, oriya, panjabi, tamil, telugu, indonesian, interlingua, irish, italian,
kurmanji, lao, latin, latvian, lithuanian, mongolian, mongolianlmc, bokmal, nyn
orsk, polish, portuguese, romanian, romansh, russian, sanskrit, serbian, serbia
nc, slovak, slovenian, spanish, swedish, turkish, turkmen, ukrainian, uppersorb
ian, welsh, loaded.
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The Rayleigh distribution arises if the wind speed and wind direction are
both gaussian variables, then the vector wind velocity forms a Rayleigh
distribution. The Rayleigh distribution is used to model the expected
output from wind turbines.
References
- ..[1] Brighton Webs Ltd., Rayleigh Distribution,
- http://www.brighton-webs.co.uk/distributions/rayleigh.asp
- ..[2] Wikipedia, “Rayleigh distribution”
- http://en.wikipedia.org/wiki/Rayleigh_distribution
Examples
Draw values from the distribution and plot the histogram
>>> values = hist(np.random.rayleigh(3, 100000), bins=200, normed=True)
Wave heights tend to follow a Rayleigh distribution. If the mean wave
height is 1 meter, what fraction of waves are likely to be larger than 3
meters?
>>> meanvalue = 1
>>> modevalue = np.sqrt(2 / np.pi) * meanvalue
>>> s = np.random.rayleigh(modevalue, 1000000)
The percentage of waves larger than 3 meters is:
>>> 100.*sum(s>3)/1000000.
0.087300000000000003
