&hdZddlZddlmZejde ddlZddlZGddZ d d Z d Z d Z y#e$rddlm Z e ddwxYw) aCode for doing logistic regressions (DEPRECATED). Classes: - LogisticRegression Holds information for a LogisticRegression classifier. Functions: - train Train a new classifier. - calculate Calculate the probabilities of each class, given an observation. - classify Classify an observation into a class. This module has been deprecated, please consider an alternative like scikit-learn instead. N)BiopythonDeprecationWarningzThe 'Bio.LogisticRegression' module is deprecated and will be removed in a future release of Biopython. Consider using scikit-learn instead.)MissingPythonDependencyErrorzYPlease install NumPy if you want to use Bio.LogisticRegression. See http://www.numpy.org/ceZdZdZdZy)LogisticRegressionzHolds information necessary to do logistic regression classification. Attributes: - beta - List of the weights for each dimension. cg|_y)zInitialize the class.N)beta)selfs e/mounts/lovelace/software/anaconda3/envs/py312/lib/python3.12/site-packages/Bio/LogisticRegression.py__init__zLogisticRegression.__init__4s  N)__name__ __module__ __qualname____doc__r r r rr,s r rct|t|k7r tdt|}|ddhk7r td|d}t|t|ddz}}|dk(s|dk(r tdtj||f|}||ddddf<tj |}tj ||} tj||} d} d } d } d}dx}}|| kr\tjtj| |}|d|zz }| tj|zd| z tjd|z zz}t|}| |t||(||kr| d z} |} tj||z | krn|| }}|dz }tj||z}tj|| |z }tjtj|||}tj j#||}tj| d z d kDr|| z}| |z } || kr\t%d t'}t)| |_|S)a^Train a logistic regression classifier on a training set. Argument xs is a list of observations and ys is a list of the class assignments, which should be 0 or 1. xs and ys should contain the same number of elements. update_fn is an optional callback function that takes as parameters that iteration number and log likelihood. z$xs and ys should be the same length.rzClasses should be 0's and 1'sNdz.No observations or observation of 0 dimension.ig{Gz??g@gMbP?zDidn't converge.)len ValueErrorsetnpones transposeasarrayzerosexpdotlogsumiterfabsidentitynumpylinalgsolve RuntimeErrorrlistr)xsys update_fntypecodeclassesNndimsXXtyrMAX_ITERATIONSCONVERGE_THRESHOLDstepsizeiold_betaold_llikebetaXplogpllikWXtypXtWXdeltalrs r trainrC9s` 2w#b'?@@"gG1a&8992wBqE QuAAv!IJJ E H%AAaeH aB 2x A 88E8 $DNH AHx n tR() a&j !266!9}AA664y  dD !  hCwwth'+==!4( Q KKNQ vvb!a% vvbffRmQ' ""4. 778c> "U * X E  9 n <-..  B4jBG Ir ctjdg|z}tjtj|j|}|d|zz }d|z |gS)zCalculate the probability for each class. Arguments: - lr is a LogisticRegression object. - x is the observed data. Returns a list of the probability that it fits each class. rr)rrrrr)rBxr:r;s r calculaterFsQ C519A VVBFF277A& 'F!f*A E1:r c4t||}|d|dkDryy)z%Classify an observation into a class.rr)rF)rBrEprobss r classifyrIs$ b! E Qx%( r )NN)rwarningsBiorwarnr%r numpy.linalg ImportErrorrrrCrFrIrr r rOs{ +  A   HV" e0 & $  s >A