This is documentation for an old release of SciPy (version 0.11.0). Read this page in the documentation of the latest stable release (version 1.14.1).
A folded normal continuous random variable.
Continuous random variables are defined from a standard form and may require some shape parameters to complete its specification. Any optional keyword parameters can be passed to the methods of the RV object as given below:
Parameters : | x : array_like
q : array_like
c : array_like
loc : array_like, optional
scale : array_like, optional
size : int or tuple of ints, optional
moments : str, optional
Alternatively, the object may be called (as a function) to fix the shape, : location, and scale parameters returning a “frozen” continuous RV object: : rv = foldnorm(c, loc=0, scale=1) :
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Notes
The probability density function for foldnorm is:
foldnormal.pdf(x, c) = sqrt(2/pi) * cosh(c*x) * exp(-(x**2+c**2)/2)
for c >= 0.
Examples
>>> from scipy.stats import foldnorm
>>> numargs = foldnorm.numargs
>>> [ c ] = [0.9,] * numargs
>>> rv = foldnorm(c)
Display frozen pdf
>>> x = np.linspace(0, np.minimum(rv.dist.b, 3))
>>> h = plt.plot(x, rv.pdf(x))
Here, rv.dist.b is the right endpoint of the support of rv.dist.
Check accuracy of cdf and ppf
>>> prb = foldnorm.cdf(x, c)
>>> h = plt.semilogy(np.abs(x - foldnorm.ppf(prb, c)) + 1e-20)
Random number generation
>>> R = foldnorm.rvs(c, size=100)
Methods
rvs(c, loc=0, scale=1, size=1) | Random variates. |
pdf(x, c, loc=0, scale=1) | Probability density function. |
logpdf(x, c, loc=0, scale=1) | Log of the probability density function. |
cdf(x, c, loc=0, scale=1) | Cumulative density function. |
logcdf(x, c, loc=0, scale=1) | Log of the cumulative density function. |
sf(x, c, loc=0, scale=1) | Survival function (1-cdf — sometimes more accurate). |
logsf(x, c, loc=0, scale=1) | Log of the survival function. |
ppf(q, c, loc=0, scale=1) | Percent point function (inverse of cdf — percentiles). |
isf(q, c, loc=0, scale=1) | Inverse survival function (inverse of sf). |
moment(n, c, loc=0, scale=1) | Non-central moment of order n |
stats(c, loc=0, scale=1, moments=’mv’) | Mean(‘m’), variance(‘v’), skew(‘s’), and/or kurtosis(‘k’). |
entropy(c, loc=0, scale=1) | (Differential) entropy of the RV. |
fit(data, c, loc=0, scale=1) | Parameter estimates for generic data. |
expect(func, c, loc=0, scale=1, lb=None, ub=None, conditional=False, **kwds) | Expected value of a function (of one argument) with respect to the distribution. |
median(c, loc=0, scale=1) | Median of the distribution. |
mean(c, loc=0, scale=1) | Mean of the distribution. |
var(c, loc=0, scale=1) | Variance of the distribution. |
std(c, loc=0, scale=1) | Standard deviation of the distribution. |
interval(alpha, c, loc=0, scale=1) | Endpoints of the range that contains alpha percent of the distribution |