\MhdZddlZddlmZgdZedddZeddd Zd Zed dd Z eddd Z edddZ dS)zS Utilities for generating random numbers, random sequences, and random selections. N)py_random_state)powerlaw_sequencezipf_rvcumulative_distributiondiscrete_sequencerandom_weighted_sampleweighted_choice@c>fdt|DS)zK Return sample sequence of length n from a power law distribution. c@g|]}dz S) paretovariate).0iexponentseeds ^/var/www/html/test/jupyter/venv/lib/python3.11/site-packages/networkx/utils/random_sequence.py z%powerlaw_sequence..s+ ? ? ?D  x!| , , ? ? ?)range)nrrs ``rrrs* @ ? ? ? ?eAhh ? ? ??rrcB|dkrtd|dkrtd|dz }d|z} d|z }|}t||d|z zz}dd|z z|z}||z|dz z|dz z ||z krni|S)awReturns a random value chosen from the Zipf distribution. The return value is an integer drawn from the probability distribution .. math:: p(x)=\frac{x^{-\alpha}}{\zeta(\alpha, x_{\min})}, where $\zeta(\alpha, x_{\min})$ is the Hurwitz zeta function. Parameters ---------- alpha : float Exponent value of the distribution xmin : int Minimum value seed : integer, random_state, or None (default) Indicator of random number generation state. See :ref:`Randomness`. Returns ------- x : int Random value from Zipf distribution Raises ------ ValueError: If xmin < 1 or If alpha <= 1 Notes ----- The rejection algorithm generates random values for a the power-law distribution in uniformly bounded expected time dependent on parameters. See [1]_ for details on its operation. Examples -------- >>> nx.utils.zipf_rv(alpha=2, xmin=3, seed=42) 8 References ---------- .. [1] Luc Devroye, Non-Uniform Random Variate Generation, Springer-Verlag, New York, 1986. rzxmin < 1za <= 1.0g?r ) ValueErrorrandomint) alphaxminra1buvxts rrr sb axx$$$ zz$$$ B 2A $++--  KKMM qcBhK'' ( ( C!G_ # q5AG C (AE 1 1   Hrcdg}t|}tt|D])}||||||z z*|S)zFReturns normalized cumulative distribution from discrete distribution.g)sumrlenappend) distributioncdfpsumrs rrrasc %C |  D 3|$$ % %44 3q6LOd223333 Jrcddl||n&|t|ntjdfdt |D}fd|D}|S)a# Return sample sequence of length n from a given discrete distribution or discrete cumulative distribution. One of the following must be specified. distribution = histogram of values, will be normalized cdistribution = normalized discrete cumulative distribution rNz8discrete_sequence: distribution or cdistribution missingc8g|]}S)r)rrrs rrz%discrete_sequence..s!000! 000rcBg|]}|dz Sr) bisect_left)rsbisectr+s rrz%discrete_sequence..s. < < rrndr?ws rr r sm ++--#gnn..// /C 1 q 77HHH r)r N)rN)NNN)N) __doc__networkxr5networkx.utilsr__all__rrrrrr r0rrrJs5 ******   @@@@= = = = @>          r