Vpf'ddlmZddlmZddlmZddlZddlmZ ddl m Z m Z m Z mZddlmZmZddlmZddlmZmZeed d Gd d ZdZee ddZdS)) dataclass)partial)AnyN)jitlaxrandomvmap)check_arraylikepromote_dtypes_inexact)register_pytree_node_class)linalgspecialTF)frozeninitceZdZUdZeed<eed<eed<eed<eed<ddZd Zd Ze d Z e d Z e d Z dZdZdZdZdZddZdZdZddZddZdZdS) gaussian_kdeaGaussian Kernel Density Estimator JAX implementation of :class:`scipy.stats.gaussian_kde`. Parameters: dataset: arraylike, real-valued. Data from which to estimate the distribution. If 1D, shape is (n_data,). If 2D, shape is (n_dimensions, n_data). bw_method: string, scalar, or callable. Either "scott", "silverman", a scalar value, or a callable function which takes ``self`` as a parameter. weights: arraylike, optional. Weights of the same shape as the dataset. neffdatasetweights covarianceinv_covNctd|tj|}tjt j|tjrtd|jdkstd|j \}}|td|t||\}}tj |}|tj |z}|jdkrtdt||krtdn0t|\}tj|d|z |j}|d ||d ||d dtj |d zz }|d n|}|d krtj|d|dzz }n|dkr%tj||d zzdz d|dzz }nVtj|rt)|t*s|}n*t-|r ||}ntdtjtj|dd|}tj|} ||d zz} | |d zz } |d| |d| dS)Nrz*gaussian_kde does not support complex dataz.`dataset` input should have multiple elements.z*`weights` input should be one-dimensional.z%`weights` input should be of length n?)dtyperrrscottg silvermang@zD`bw_method` should be 'scott', 'silverman', a scalar, or a callable.F)rowvarbiasaweightsrr)r jnp atleast_2d issubdtyperrcomplexfloatingNotImplementedErrorsize ValueErrorshaper atleast_1dsumndimlenfull_setattrpowerisscalar isinstancestrcallablecovr inv) selfr bw_methodrdnrfactordata_covariance data_inv_covrrs X/var/www/html/nettyfy-visnx/env/lib/python3.11/site-packages/jax/_src/scipy/stats/kde.py__init__zgaussian_kde.__init__0sNG,,,nW%%G ~ci((#*=>>N  L M MM >/22L 619,JVQY&GMM, +++MM)W%%%%%c>t||||SN)object __setattr__)r8namevalues r?r0zgaussian_kde._setattr`s! tT5))) LrAcF|j|j|j|j|jfdfSrC)rrrrrr8s r? tree_flattenzgaussian_kde.tree_flattenfs* Y dlDO \   ""rAcJ~||}|d|d|d|d|d|d|d|d|d |d |S) Nrrrrrrrrr)__new__r0)clsaux_datachildrenkdes r?tree_unflattenzgaussian_kde.tree_unflattenjs ++c  CLL!%%%LLHQK(((LLHQK(((LLx{+++LLHQK((( JrAc&|jjdS)Nrrr*rIs r?r:zgaussian_kde.du < a  rAc&|jjdS)NrrTrIs r?r;zgaussian_kde.nyrUrActd|||}td|jj|jdddf|j|j}|dddfS)z.Evaluate the Gaussian KDE on the given points.evaluateFNrr _reshape_points_gaussian_kernel_evalrTrr)r8pointsresults r?rXzgaussian_kde.evaluate}shJ'''  ! !& ) )F "5$,.$,qqq$w:O#)8T\;;F !!!Q$<rAc,||SrCrX)r8r]s r?__call__zgaussian_kde.__call__s ==  rAcJtjtj|}tj|}|j|jfkrt d|j|j|j|jfkrt d|jtj|j |z}tj dtj z|jztj tj|dz}d|z }t|||j|j|S)z2Integrate the distribution weighted by a Gaussian.zmean does not have dimension z#covariance does not have dimension rrr)r#r+squeezer$r*r:r)r cho_factorrsqrtnppiproddiag_gaussian_kernel_convolverr)r8meanr6cholnorms r?integrate_gaussianzgaussian_kde.integrate_gaussians >#+d++ , ,D .  C zdfY ?tv?? @ @@ yTVTV$$$ ETVEE F FF  T_s2 3 3D 8AI   &#(472C2C)D)D DD :D $T4t|%) + ++rAc |jdkrtdtj|dkstj|dkrtdtjtj|j}tj||jz |z }tj||jz |z }tj|j tj |tj |z zS)z1Integrate the distribution over the given limits.rz'integrate_box_1d() only handles 1D pdfsrz=the limits of integration in integrate_box_1d must be scalars) r:r)r#r-rcrerrr,rrndtr)r8lowhighsigmas r?integrate_box_1dzgaussian_kde.integrate_box_1ds v{{ @ A AA x}}SXd^^q00  I K KK K11 2 2E +sT\)U2 3 3C ;t|+u4 5 5D 74<7<#5#5 S8I8I#IJ K KKrAc $|j|jkrtdtj|j|jz}t jdtjz|jzt j t j |dz}d|z }|j |j kr||fn||f\}}ttt|||j|jd|j}t j||jzS)z8Integrate the product of two Gaussian KDE distributions.z$KDEs are not the same dimensionalityrrrrin_axes)r:r)r rdrr#rerfrgrhrir;r rrjrrr,)r8otherrlrmsmlgr^s r? integrate_kdezgaussian_kde.integrate_kdes w$& = > >>  T_u/?? @ @D 8AI   &#(472C2C)D)D DD :D"fuw..dE]]UDMFBT'3T4*&&Z))F 76BJ& ' ''rAc:tj|\}}tj||j||j}tj|t j|j|j j |j ||j j j }|j dd|f|zS)ajRandomly sample a dataset from the estimated pdf Args: key: a PRNG key used as the random key. shape: optional, a tuple of nonnegative integers specifying the result batch shape; that is, the prefix of the result shape excluding the last axis. Returns: The resampled dataset as an array with shape `(d,) + shape`. )r*p)r*rN) rsplitchoicer;rmultivariate_normalr#zerosr:rrrr\)r8keyr*ind_keyeps_keyindepss r?resamplezgaussian_kde.resamples|C((GW -u E E EC  $W%(Ytvt7L%M%M%)_+0+/<+=  ? ? ?@A  <3 # %%rAc,||S)zProbability density functionr`)r8xs r?pdfzgaussian_kde.pdfs ==  rActd|||}td|jj|jdddf|j|j}|dddfS)z Log probability density functionlogpdfTNrrY)r8rr^s r?rzgaussian_kde.logpdfshHa    QA "4aaag9N#$3 66F !!!Q$<rAc&~~~td)4This method is not implemented in the JAX interface.z>only 1D box integrations are supported; use `integrate_box_1d`r')r8 low_bounds high_boundsmaxptss r? integrate_boxzgaussian_kde.integrate_boxs!K H J JJrAc"~td)rz:dynamically changing the bandwidth method is not supportedr)r8r9s r? set_bandwidthzgaussian_kde.set_bandwidths D F FFrActjtj|tjrt dtj|}|j\}}||jkrV|dkr(||jkrtj ||jdf}n(td ||j|S)Nz1gaussian_kde does not support complex coordinatesrz2points have dimension {}, dataset has dimension {}) r#r%rrr&r'r$r*r:reshaper)format)r8r]r:ms r?rZzgaussian_kde._reshape_pointss ~ci'')<==?  = ? ?? ^F # #F .kernels[ S373:g.>#?#?@@@ @C $ WW   ## sws|| ##rAcRtd|dS)N)Nrrrvrr)r )rrr]reducevaluess r?z'_gaussian_kernel_eval..s>VV$FD$F$F$F%&%8%8)*,,,rA)r r*r)r choleskyr#dotr,rrirfrgr logsumexpr ) rr]rxi precisionr: whiteningreduced_kernel mapped_kernelrrrs ``` @@@r?r[r[so"8 fb)#%#%&&"i l1o!Xa[A @ A AA_A < = ==oit444) 769 % %& wr9" WSW hy!AgBE (:(::;($$$$$$!' 37  CG&,,,,,,,.~&&- r  rA) dataclassesr functoolsrtypingrnumpyrf jax.numpyr#jaxrrrr jax._src.numpy.utilr r jax._src.tree_utilr jax.scipyr rrrjr[r|rAr?rs]"!!!!!&&&&&&&&&&&&GGGGGGGG999999%%%%%%%% $U###OOOOOOO$#Od111 Q rA