DjdZddlZddlmZddlmZddlmZm Z m Z m Z m Z m Z GddZGdd eZGd d eZy) zM Created on Wed Feb 17 15:35:23 2021 Author: Josef Perktold License: BSD-3 N)stats)cache_readonly)_Grid cdf2prob_grid prob2cdf_grid_eval_bernstein_dd_eval_bernstein_2d_eval_bernstein_1dcNeZdZdZdZedZedZdZ dZ dZ dZ y ) BernsteinDistributionaDistribution based on Bernstein Polynomials on unit hypercube. Parameters ---------- cdf_grid : array_like cdf values on a equal spaced grid of the unit hypercube [0, 1]^d. The dimension of the arrays define how many random variables are included in the multivariate distribution. Attributes ---------- cdf_grid : grid of cdf values prob_grid : grid of cell or bin probabilities k_dim : (int) number of components, dimension of random variable k_grid : (tuple) shape of cdf_grid k_grid_product : (int) total number of bins in grid _grid : Grid instance with helper methods and attributes c(tj|x|_}|j|_|j |_tj|j Dcgc]}|dz  c}|_t|j |_ ycc}w)N) npasarraycdf_gridndimk_dimshapek_gridprodk_grid_productr_grid)selfris gC:\Crop_Prediction\Backend\crop-ai-system\venv\Lib\site-packages\statsmodels/distributions/bernstein.py__init__zBernsteinDistribution.__init__&sg#%::h#77 ]] nn  ggDKK&@qqs&@A4;;' 'As Bc Ntj|}tj|dkstj|dkDr td|jdk(r |dddf}|j d}tj |dk(r|g|z}|Dcgc]}tjd|z d|dz!}}tj||d\}}t|Dcgc] }|ddk( c}sJ|t|z}t|} || Scc}wcc}w) aoCreate distribution instance from data using histogram binning. Classmethod to construct a distribution instance. Parameters ---------- data : array_like Data with observation in rows and random variables in columns. Data can be 1-dimensional in the univariate case. k_bins : int or list Number or edges of bins to be used in numpy histogramdd. If k_bins is a scalar int, then the number of bins of each component will be equal to it. Returns ------- Instance of a Bernstein distribution rrzdata needs to be in [0, 1]NF)binsdensity) rrany ValueErrorrrsizelinspace histogramddalllenr) clsdatak_binsrnir ceeirs r from_datazBernsteinDistribution.from_data-s(zz$ 66$( rvvdQh/9: : 99>4=D 1  776?a X%F:@AB BGQQ/AA~~du=1+2BqEQJ+,, SY #8}B,s $D$D"c0t|jdS)N)prepend)rr)rs r prob_gridzBernsteinDistribution.prob_gridUsT]]D99ctj|}|jdk(r|jdk(r |dddf}t ||j }|S)acdf values evaluated at x. Parameters ---------- x : array_like Points of multivariate random variable at which cdf is evaluated. This can be a single point with length equal to the dimension of the random variable, or two dimensional with points (observations) in rows and random variables in columns. In the univariate case, a 1-dimensional x will be interpreted as different points for evaluation. Returns ------- pdf values Notes ----- Warning: 2-dim x with many points can be memory intensive because currently the bernstein polynomials will be evaluated in a fully vectorized computation. rN)rrrrrrrxcdf_s rcdfzBernsteinDistribution.cdfYsH. JJqM 66Q;4::?!T' A!!T]]3 r4ctj|}|jdk(r|jdk(r |dddf}|jt ||j z}|S)apdf values evaluated at x. Parameters ---------- x : array_like Points of multivariate random variable at which pdf is evaluated. This can be a single point with length equal to the dimension of the random variable, or two dimensional with points (observations) in rows and random variables in columns. In the univariate case, a 1-dimensional x will be interpreted as different points for evaluation. Returns ------- cdf values Notes ----- Warning: 2-dim x with many points can be memory intensive because currently the bernstein polynomials will be evaluated in a fully vectorized computation. rN)rrrrrrr3rr7pdf_s rpdfzBernsteinDistribution.pdfvsT. JJqM 66Q;4::?!T' A""%74>>%JJ r4c|jdk(r|Sdg|jz}tj|dk(r|g}|D]}tddd||<|jt |}t |}|S)aFGet marginal BernsteinDistribution. Parameters ---------- idx : int or list of int Index or indices of the component for which the marginal distribution is returned. Returns ------- BernsteinDistribution instance for the marginal distribution. rrN)rrrslicertupler )ridxsliicdf_m bpd_marginals r get_marginalz"BernsteinDistribution.get_marginals~ ::?KTDJJ  88C=B %C -B4t,BrF - eBi(,U3 r4c tjj||jj }|j }g}t t|D]}||dk7s tj||jj}g}t |D]s}|j|} |jj|||} |jtjj!| | zdz| d| z zdz||u|jtj"|tj$|} | S)zGenerate random numbers from distribution. Parameters ---------- nobs : int Number of random observations to generate. rr)r$)rrandom multinomialr3flattenrranger( unravel_indexrrr x_marginalappendrbetarvs column_stack concatenate) rnobsrvs_mnlk_comprvs_mrrBrvsijnxgirvsms rrQzBernsteinDistribution.rvss'))''dnn.D.D.FGs7|$ 4AqzQ&&q$..*>*>?vAA AA**//23q6:CKK q3w{A3K!O4;AJ!/!@A A R__T23 4~~e$ r4N) __name__ __module__ __qualname____doc__r classmethodr0rr3r9r=rGrQr?r4rr r sI&(%%N:::<6r4r ceZdZdZdZy)BernsteinDistributionBVc2t||j}|SN)r rr6s rr9zBernsteinDistributionBV.cdfs!!T]]3 r4cL|jt||jz}|Sre)rr r3r;s rr=zBernsteinDistributionBV.pdfs#""%74>>%JJ r4Nr]r^r_r9r=r?r4rrcrcs r4rcceZdZddZddZy)BernsteinDistributionUVc6t||j|}|SN)method)r r)rr7rlr8s rr9zBernsteinDistributionUV.cdfs!!T]]6B r4cP|jt||j|z}|Srk)rr r3)rr7rlr<s rr=zBernsteinDistributionUV.pdfs,""%74>>?E&GG r4N)binomrgr?r4rriris  r4ri)r`numpyrscipyrstatsmodels.tools.decoratorsrstatsmodels.distributions.toolsrrrrr r r rcrir?r4rrssH7DD vvr 3  3 r4