pyuncertainnumber.pba.ecdf

Classes

eCDF_bundle

a handy tuple of eCDF function q and p

Functions

transform_eCDF_bundle(e)	utility to tranform sps.ecdf to eCDF_bundle
pl_ecdf_bounds_2(q1, p1, q2, p2[, ax, marker])	plot the upper and lower bounding cdf functions with two sets of quantiles and probabilities
plot_two_eCDF_bundle(cdf1, cdf2[, ax])	plot upper and lower eCDF_bundle objects
pl_ecdf_bounding_bundles(b_l, b_r[, ax, legend, ...])
ecdf(d)	return the quantile and probability of a ecdf
get_ecdf(→ tuple)	compute the weighted ecdf from (precise) sample data

Module Contents

class pyuncertainnumber.pba.ecdf.eCDF_bundle

a handy tuple of eCDF function q and p

quantiles: numpy.ndarray

probabilities: numpy.ndarray

__repr__()

classmethod from_sps_ecdf(e)

utility to tranform sps.ecdf to eCDF_bundle

plot_bounds(other)

plot the lower and upper bounds

pyuncertainnumber.pba.ecdf.transform_eCDF_bundle(e)

utility to tranform sps.ecdf to eCDF_bundle

pyuncertainnumber.pba.ecdf.pl_ecdf_bounds_2(q1, p1, q2, p2, ax=None, marker='+')

plot the upper and lower bounding cdf functions with two sets of quantiles and probabilities

pyuncertainnumber.pba.ecdf.plot_two_eCDF_bundle(cdf1, cdf2, ax=None, **kwargs)

plot upper and lower eCDF_bundle objects

pyuncertainnumber.pba.ecdf.pl_ecdf_bounding_bundles(b_l: eCDF_bundle, b_r: eCDF_bundle, ax=None, legend=True, title=None, sig_level=None, bound_colors=None, label=None, alpha=None, linestyle=None, linewidth=None, return_ax=False)

pyuncertainnumber.pba.ecdf.ecdf(d)

return the quantile and probability of a ecdf

Note

Scott’s version which leads to doubling the length of quantiles and probabilities to make it a step function

pyuncertainnumber.pba.ecdf.get_ecdf(s, w=None, display=False) → tuple

compute the weighted ecdf from (precise) sample data

Parameters:

• s (array-like) – 1 dimensional precise sample data

• w (array-like) – weights

Note

• Sudret eq.1

Returns:

ecdf in the form of a tuple of q and p