a ߙfb1@sdZddlZddlZddlmZddlmZdgZdZ GdddZ Gdd d e ej Z Gd d d e ej ZGd d d ZGdddeeZee jej <dS)z. Distribution class and associated machinery. N)units)stats DistributiongtV?c@seZdZdZiZddZeddZddZedd Z dd d Z dddZ dddZ dddZ d ddZd!ddZddZddZd S)"ram A scalar value or array values with associated uncertainty distribution. This object will take its exact type from whatever the ``samples`` argument is. In general this is expected to be an `~astropy.units.Quantity` or `numpy.ndarray`, although anything compatible with `numpy.asanyarray` is possible. See also: https://docs.astropy.org/en/stable/uncertainty/ Parameters ---------- samples : array-like The distribution, with sampling along the *leading* axis. If 1D, the sole dimension is used as the sampling axis (i.e., it is a scalar distribution). cCst|tr|j}ntj|dd}|jdkr2tdtdg|j|jdffgd}t|}|j |}|dur|j |j }t|t |t fd|i}||j |<|j||d }|jdd|_|S) NC)orderz4Attempted to initialize a Distribution with a scalarsamples)namesZformats _samples_cls)dtypetype) isinstancer distributionnpZ asanyarrayshape TypeErrorr r _generated_subclassesget__name___DistributionReprArrayDistributionview)clsrZ new_dtypeZ samples_clsZnew_clsnew_nameselfrr7lib/python3.9/site-packages/astropy/uncertainty/core.py__new__*s*     zDistribution.__new__cCs|dSNrrrrrrrKszDistribution.distributioncOsjg}|dd}|r*tdd|D|d<|dvrn|dd}|durnt|dtsXJtt|dj|d<|D]L}t|tr||jqrt |dd} | r||d t j fqr||qrt |||i|} t| ts| f} |durd t | }g} t | |D]H\} } | dur$| | n(t | dd rB| t| n | | qt | d krb| S| dS) Noutcss"|]}t|tr|jn|VqdSN)rrr).0outputrrr Ssz/Distribution.__array_ufunc__..>reduce accumulateZreduceataxisrrr.r!F)poptuplerrrrangendimappendrgetattrrZnewaxislenzip)rZufuncmethodZinputskwargsZ convertedZoutputsr'Zinput_rZresultsZfinalsresultr#rrr__array_ufunc__Os>          zDistribution.__array_ufunc__cCs|jdjdS)zN The number of samples of this distribution. A single `int`. rr)r rrrrr n_samplesyszDistribution.n_samplesNcCs|jjd||dS)z\ The mean of this distribution. Arguments are as for `numpy.mean`. r )r'r r )rZmean)rr r rrrpdf_meanszDistribution.pdf_meanrcCs|jjd|||dS)zi The standard deviation of this distribution. Arguments are as for `numpy.std`. r r'r r ddof)rZstdrr r r8rrrpdf_stdszDistribution.pdf_stdcCs|jjd|||dS)z_ The variance of this distribution. Arguments are as for `numpy.var`. r r7)rvarr9rrrpdf_varszDistribution.pdf_varcCstj|jd|dS)aP The median of this distribution. Parameters ---------- out : array, optional Alternative output array in which to place the result. It must have the same shape and buffer length as the expected output, but the type (of the output) will be cast if necessary. r )r'r )rmedianr)rr rrr pdf_medians zDistribution.pdf_mediancCs.|j|d}t||}tj|jd|ddS)ac The median absolute deviation of this distribution. Parameters ---------- out : array, optional Alternative output array in which to place the result. It must have the same shape and buffer length as the expected output, but the type (of the output) will be cast if necessary. r r T)r'r Zoverwrite_input)r>rabsr=r)rr r=Zabsdiffrrrpdf_mads  zDistribution.pdf_madcCs|j|d}|t9}|S)a The median absolute deviation of this distribution rescaled to match the standard deviation for a normal distribution. Parameters ---------- out : array, optional Alternative output array in which to place the result. It must have the same shape and buffer length as the expected output, but the type (of the output) will be cast if necessary. r?)rASMAD_SCALE_FACTOR)rr r3rrrpdf_smads zDistribution.pdf_smadcKsJt|tjj}tj|j|fddi|}t|jdrB|j|S|SdS)a Compute percentiles of this Distribution. Parameters ---------- percentile : float or array of float or `~astropy.units.Quantity` The desired percentiles of the distribution (i.e., on [0,100]). `~astropy.units.Quantity` will be converted to percent, meaning that a ``dimensionless_unscaled`` `~astropy.units.Quantity` will be interpreted as a quantile. Additional keywords are passed into `numpy.percentile`. Returns ------- percentiles : `~astropy.units.Quantity` ['dimensionless'] The ``fracs`` percentiles of this distribution. r'r _new_viewN) uZQuantityZpercentvaluer percentilerhasattrrD)rrGr2Zpercsrrrpdf_percentiless   zDistribution.pdf_percentilesc Ks|j}||j|jd|jd}g}g}|D].}tj|fi|\}}||||q0t|}|j|j|jf} t|}|j|j|jf} || || fS)a\ Compute histogram over the samples in the distribution. Parameters ---------- All keyword arguments are passed into `astropy.stats.histogram`. Note That some of these options may not be valid for some multidimensional distributions. Returns ------- hist : array The values of the histogram. Trailing dimension is the histogram dimension. bin_edges : array of dtype float Return the bin edges ``(length(hist)+1)``. Trailing dimension is the bin histogram dimension. r ) rZreshapesizerrZ histogramr-rZarray) rr2ZdistrZ raveled_distrZnhistsZ bin_edgesdZnhistZbin_edgeZnh_shapeZbe_shaperrr pdf_histograms    zDistribution.pdf_histogram)NN)NNr)NNr)N)N)N)r __module__ __qualname____doc__rrpropertyrr4r5r6r:r<r>rArCrIrLrrrrrs ! *      c@seZdZdZdS)ScalarDistributionzScalar distribution. This class mostly exists to make `~numpy.array2print` possible for all subclasses. It is a scalar element, still with n_samples samples. N)rrMrNrOrrrrrQsrQcs0eZdZejZdfdd ZfddZZS)rNcs|dur(t|tjr(t|tjr(|}d}dd||fD}|dusXt|tjr~t|tr~|durr||jkrrtdt j |S|j j |}t|S)a2New view of array with the same data. Like `~numpy.ndarray.view` except that the result will always be a new `~astropy.uncertainty.Distribution` instance. If the requested ``type`` is a `~astropy.uncertainty.Distribution`, then no change in ``dtype`` is allowed. NcSsg|]}|dur|qSr!r)r"itemrrr #z*ArrayDistribution.view..z6cannot view as Distribution subclass with a new dtype.) rbuiltinsr issubclassrndarrayrr ValueErrorsuperrr)rr r Z view_argsr3 __class__rrrs    zArrayDistribution.viewcsJt|}|dkr&tt||jSt|tjrB|t|j fS|SdSr) rY __getitem__rrr rrvoidrQr )rrRr3rZrrr\0s   zArrayDistribution.__getitem__)NN) rrMrNrrWr rr\ __classcell__rrrZrrsrc@s$eZdZddZddZddZdS)rcCstt|j}|drB|d}||dd}d|jj||jS|d}||d}|jj|d|jSdS)N> r(r z<{} {} with n_samples={}>( with n_samples=)reprrendswithfindformatr[rr5)rZreprarrZ firstspaceZ firstparenrrr__repr__<s      z_DistributionRepr.__repr__cCst|j}d|j}||S)Nrb)strrr5)rZdistrstrtoaddrrr__str__Is  z_DistributionRepr.__str__cCsBt|jdr:|j}d|j}|dd||dSdSdS)N _repr_latex_z, \; n_{\rm samp}=r )rHrrkr5)rZ superlatexrirrrrkNs    z_DistributionRepr._repr_latex_N)rrMrNrgrjrkrrrrr;s rc@s eZdZdS)NdarrayDistributionN)rrMrNrrrrrlWsrl)rOrUZnumpyrZastropyrrEr__all__rBrr]rQrWrrrlrrrrrs  p -