U oe@sdZddlZddlmZedezddlZddlZWn*ek rbddlm Z e ddYnXGdddZ dd d Z d d Z d dZ dS)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 insead. 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/c@seZdZdZddZdS)LogisticRegressionzHolds information necessary to do logistic regression classification. Attributes: - beta - List of the weights for each dimension. cCs g|_dS)zInitialize the class.N)beta)selfr5lib/python3.8/site-packages/Bio/LogisticRegression.py__init__3szLogisticRegression.__init__N)__name__ __module__ __qualname____doc__r rrrrr+srcCst|t|krtdt|}|ddhkr4td|dkr@d}t|t|dd}}|dksj|dkrrtdt||f|}||ddddf<t|}t||} t||} d} d } d } d}d}}|| krtt | |}|d|}| t |d| t d|}t |}|dk r8|t ||dk rp||krX| d } |} t ||| krpq|| }}|d7}t||}t || |}t t |||}tj||}t | d d kr|| 9}| |7} qtd 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 ValueErrorsetnpZonesZ transposeasarrayZzerosexpdotlogsumiterZfabsZidentitynumpyZlinalgZsolve RuntimeErrorrlistr)ZxsZysZ update_fntypecodeclassesNZndimsXZXtyrZMAX_ITERATIONSZCONVERGE_THRESHOLDZstepsizeiZold_betaZold_llikebetaXpZlogpZllikWZXtypZXtWXZdeltalrrrrtrain8s\      $       r(cCs<tdg|}tt|j|}|d|}d||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)r'xr$r%rrr calculates  r*cCs"t||}|d|dkrdSdS)z%Classify an observation into a class.rr)r*)r'r)Zprobsrrrclassifys r+)NN)r warningsZBiorwarnrrZ numpy.linalg ImportErrorrrr(r*r+rrrrs(    K