  # scipy stats.halfnorm () | python

NumPy | Python Methods and Functions

Parameters:
- & gt; q: lower and upper tail probability
- & gt; x: quantiles
- & gt; loc: [optional] location parameter. Default = 0
- & gt; scale: [optional] scale parameter. Default = 1
- & gt; size: [tuple of ints, optional] shape or random variates.
- & gt; moments: [optional] composed of letters [`mvsk`]; `m` = mean, `v` = variance, `s` = Fisher`s skew and `k` = Fisher`s kurtosis. (default = `mv`).

Results: Half-normal continuous random variable

Code # 1: Create a half-normal continuous random variable

 ` from ` ` scipy.stats ` ` import ` ` halfnorm ` ` `  ` numargs ` ` = ` ` halfnorm.numargs ` ` [] ` ` = ` ` [` ` 0.7 ` `,] ` ` * ` ` numargs ` ` rv ` ` = ` ` halfnorm () `   ` print ` ` (` ` "RV:" ` `, rv ) `

Output:

` RV: & lt; scipy.stats._distn_infrastructure.rv_frozen object at 0x000001E39B53B630 & gt; `

Code # 2: Seminormal Random Variables and Probability Distribution

 ` import ` ` numpy as np ` ` quantile ` ` = ` ` np.arange (` ` 0.01 ` `, ` ` 1 ` `, ` ` 0.1 ` `) `   ` # Random Variants ` ` R ` ` = ` ` halfnorm.rvs (scale ` ` = ` ` 2 ` `, size ` ` = ` ` 10 ` `) ` ` pr int ` ` (` ` "Random Variates:" ` `, R) `   ` # PDF ` ` R ` ` = ` ` halfnorm.pdf (quantile, loc ` ` = ` ` 0 ` `, scale ` ` = ` ` 1 ` `) ` ` print ` ` (` ` "Probability Distribution:" ` `, R) `

Output:

` Random Variates: [3.95023511 1.97013912 2.00977927 1.88217027 2.24680027 0.7298033 0.56769996 0.62071753 1.74743798 0.35512999] Probability Distribution: [0.79784467 0.79307193 0.78048376 0.76045271 0.73356332 0.70058376 0.66242936 0.62012057 0.57473779 0.52737608] `

Code # 3: Graphic representation.

 ` import ` ` numpy as np ` ` import ` ` matplotlib.pyplot as plt `   ` distribution ` ` = ` ` np.linspace (` ` 0 ` `, np.minimum (rv.dist.b, ` ` 3 ` `)) ` ` print ( "Distribution:" , distribution) ``   plot = plt.plot (distribution, rv.pdf (distributi on)) `

Output:

` Distribution: [0. 0.06122449 0.12244898 0.18367347 0.24489796 0.30612245 0.36734694 0.42857143 0.48979592 0.55102041 0.6122449 0.67346939 0.73469388 0.79591837 0.85714286 0.91836735 0.97959184 1.04081633 1.10204082 1.16326531 1.2244898 1.28571429 1.34693878 1.40816327 1.46938776 1.53061224 1.59183673 1.65306122 1.71428571 1.7755102 1.83673469 1.89795918 1.95918367 2.02040816 2.08163265 2.14285714 2.20408163 2.26530612 2.32653061 2.3877551 2.44897959 2.51020408 2.57142857 2.63265306 2.69387755 2.75510204 2.81632653 2.87755102 2.93877551 3. ] `

Code # 4: Various Positional Arguments

 ` import ` ` matplotlib. pyplot as plt ` ` import ` numpy as np   ` x ` ` = ` ` np.linspace (` ` 0 ` `, ` ` 5 ` `, ` ` 100 ` `) `   ` # Various positional arguments ` ` y1 ` ` = ` ` halfnorm.pdf (x, 1 , 3 ) `` y2 = halfnorm.pdf (x, 1 , 4 ) plt.plot (x, y1, "* " , x, y2, " r-- " ) `

Output: