ó
áp7]c           @   s  d  d l  Z d  d l j Z d d l m Z m Z d \ Z Z	 d Z
 d Z e j d e
 e ƒ d d … e j f Z e j e ƒ Z e j e d e j e j e ƒ ƒ d ƒ d d … e j f Z e d	 e j j e d ƒ Z d
 Z e d d e … d d … f Z e d d e … d d … f Z e j e d e d … d d … f e e d d d … d d … f f Z e j e d e d … d d … f e e d d d … d d … f f Z e j e j e d ƒ e j e d d e ƒ f ƒ Z e e e d e d d ƒZ e j  e ƒ Z! e j" ƒ  e j# e e d e e! d ƒ e j$ d ƒ e j" ƒ  e j# e e j% ƒ  d e d e! d ƒ e j$ d d ƒ d S(   iÿÿÿÿNi   (   t   GaussProcesst   kernel_euclidi2   i   i   i
   g{®Gáz„?gš™™™™™¹?i   i   t   kernelt
   ridgecoeffi   g-Cëâ6?t   bos   r.s4   euclid kernel: true y versus noisy y and estimated ys   bo-s   go-s   r.-s>   euclid kernel: true (green), noisy (blue) and estimated (red) t   observations(   i2   i   gü©ñÒMb@?(&   t   numpyt   npt   matplotlib.pyplott   pyplott   pltt   kernridgeregress_classR    R   t   mt   kt   uppert   scalet   linspacet   newaxist   xst   sint   xs1t   sumt   sqrtt   abst   y1truet   randomt   randnt   y1t   stridet   xstraint   ystraint   r_t   hstackt   aranget   indext   gp1t   predictt   yhatr1t   figuret   plott   titlet   ravel(    (    (    sO   lib/python2.7/site-packages/statsmodels/sandbox/regression/example_kernridge.pyt   <module>   s2   (?KK6	
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