B Z@sddlZddlmZddlZddlZdZddZ dddZ dd Z d d Z dd dZ dddZGdddeZddZdddZdS)NZrestructuredtextcCs6tt|tjd}t|d|t|dS)z Return the reciprocal of an array, setting all entries less than or equal to 0 to 0. Therefore, it presumes that X should be positive in general. rg)npZmaximumasarrayastypefloat64greaterZ less_equal)Xxr -szclean0..)raddreduceZ flatnonzeroarray transpose)rZcolsumvalr )rr clean0(sr"-q=cCsht|}t|jdkrLtj|}ttj t || | tj Sttt|d SdS)zZ Return the rank of a matrix X based on its generalized inverse, not the SVD. rgN)rrlenrscipylinalgZsvdvalsintrrrmaxrZint32Zalltruer)rZcondDr r r rank0s   (r*cCs|dkrt|}tj|dd\}}}t|}|ddd}g}x*t|D]}||dd||fqJWtt| tj S)z Return a matrix whose column span is the same as X. If the rank of X is known it can be specified as r -- no check is made to ensure that this really is the rank of X. Nr)Z full_matrices) r*LZsvdrargsortrangeappendrr rr)rrVr)Uordervaluerr r r fullrank<s  r5c@s"eZdZdZd ddZddZdS) StepFunctiona A basic step function: values at the ends are handled in the simplest way possible: everything to the left of x[0] is set to ival; everything to the right of x[-1] is set to y[-1]. Examples -------- >>> from numpy import arange >>> from statsmodels.sandbox.utils_old import StepFunction >>> >>> x = arange(20) >>> y = arange(20) >>> f = StepFunction(x, y) >>> >>> print f(3.2) 3.0 >>> print f([[3.2,4.5],[24,-3.1]]) [[ 3. 4.] [ 19. 0.]] FcCst|}t|}|j|jkr(tdt|jdkr>tdttj g|g|_t|g|g|_|st |j}t |j|d|_t |j|d|_|jjd|_ dS)Nz3in StepFunction: x and y do not have the same shapez.in StepFunction: x and y must be 1-dimensionalr) rrr ValueErrorr$Zhstackinfryr-Ztaken)selfrr;Zivalsorted_xZ_yZasortr r r __init__fs    zStepFunction.__init__cCs"t|j|d}|j}|j|S)Nr8)rZ searchsortedrrr;)r=ZtimeZtindrr r r __call__yszStepFunction.__call__N)r7F)__name__ __module__ __qualname____doc__r@rAr r r r r6Ps r6cCsNtj|dd}|tj|jdd|_|jd}t|d|}t||S)z9 Return the ECDF of an array as a step function. T)copyr)r g?)rrsortrrZaranger6)valuesrr<r;r r r ECDFs  rITcKs`|r||f|}n.g}x|D]}|||f|qWt|}t|}tj||||S)z Given a monotone function fn (no checking is done to verify monotonicity) and a set of x values, return an linearly interpolated approximation to its inverse from its values on x. )r/rrr-r%Z interpolateZinterp1d)fnrZ vectorizedkeywordsr;r?rr r r monotone_fn_inverters   rL)r r)r#)N)T)ZnumpyrZ numpy.linalgr&r,Zscipy.interpolater%Z scipy.linalgZ __docformat__r rrr"r*r5objectr6rIrLr r r r s    /