U Kv f @sdZddlZGdddZdS)zM Created on Tue May 27 13:23:24 2014 Author: Josef Perktold License: BSD-3 Nc@s.eZdZdZd ddZddZd d ZeZdS) StandardizeTransformaBclass to reparameterize a model for standardized exog Parameters ---------- data : array_like data that is standardized along axis=0 ddof : None or int degrees of freedom for calculation of standard deviation. default is 1, in contrast to numpy.std const_idx : None or int If None, then the presence of a constant is detected if the standard deviation of a column is **equal** to zero. A constant column is not transformed. If this is an integer, then the corresponding column will not be transformed. demean : bool, default is True If demean is true, then the data will be demeaned, otherwise it will only be rescaled. Notes ----- Warning: Not all options are tested and it is written for one use case. API changes are expected. This can be used to transform only the design matrix, exog, in a model, which is required in some discrete models when the endog cannot be rescaled or demeaned. The transformation is full rank and does not drop the constant. NTcCst|}|d|_|jddd|_|dkrbt|jdkd}t|dkrTd}ntt|}|dkr~d|j|<d|j|<|dkrd|_||_ dS)Nrr)ddofnF) npasarraymeanZstdscaleZnonzerolenintZsqueeze const_idx)selfdatarr ZdemeanrE/tmp/pip-unpacked-wheel-2v6byqio/statsmodels/tools/transform_model.py__init__+s     zStandardizeTransform.__init__cCs4|jdkrt||jSt||j|jSdS)z=standardize the data using the stored transformation N)rrrr )r rrrr transformAs zStandardizeTransform.transformcCs4||j}|jdkr0||j||j8<|S)aeTransform parameters of the standardized model to the original model Parameters ---------- params : ndarray parameters estimated with the standardized model Returns ------- params_new : ndarray parameters transformed to the parameterization of the original model r)r r rsum)r paramsZ params_newrrrtransform_paramsJs  z%StandardizeTransform.transform_params)rNT)__name__ __module__ __qualname____doc__rrr__call__rrrrr s   r)rZnumpyrrrrrrs