§
    	\áj  ã                   ó  — d Z ddlZddlZddlmZ ej                             dd¦  «         ej                             de 	                    dd¦  «        d         ¦  «         ddl
Z
ddl
mZmZ ddlmZ d	Zd
Zi Zdd„Zdd„ZdS )a…  Prototype (bench only, the package is untouched): one scale for everything.

The encoder works at one scale eps, the finest detail the input supports: the point spacing s for a clean cloud, C sigma
when the noise sigma is larger (eps = max(s, C sigma), sigma given: the noise is a parameter). With f = eps / s:
  * surface: the surf slicer's robust-plane inlier distance (TAU), RIMLS support (H_SUPPORT) and band (BAND) times f;
  * small loops: the minimum loop area (MIN_LOOP spacings^2) times f^2;
  * parts (cuts="pointtest"): a track is cut only where one height fit fails to explain the points (pointfit.py, its
    margin of 2 spacings; scaling it by f was measured and changes little);
  * thin walls (thin=True, off by default): thinwall.py at the spacing scale (helps the clean loaf pan, costs a little
    under noise; scaling it by f deletes geometry).
For a clean cloud f = 1: the package's slicer with the point test.
Measured (report/eps_components.txt, eps_variants.txt, eps_minloop.txt): under per-point noise 5-30x fewer parts than
the package at about the noise level of error; C = 4; the minimum loop as eps^2 beats eps and a fixed one.
estimate_sigma (a local quadric fit) reads thick shapes' noise but takes thin walls for noise (report/sigma_estimators.txt).

    from eps import encode_eps
    d = encode_eps(points, up=(0, 0, 1), sigma=0.006 * diag)   # the noise, world units (0: clean)
é    N)ÚcKDTreez/home/joao/code/fcp_devel/apiú/é   )Ú_sliceÚ_surf)ÚPointSlicerg      @é@   é   é¸  c           	      ó¨  — t          j        | t          ¦  «        } t           j                             |¦  «                             t          | ¦  «        t          |t          | ¦  «        ¦  «        d¬¦  «        }t          | ¦  «         	                    | |         |¦  «        \  }}g }|D �]	}| |         | |          
                    d¦  «        z
  }	t           j                             |	j        |	z  ¦  «        \  }}
|	|
z  }|dd…df         |dd…df         |dd…df         }}}t           j        t          j        |¦  «        ||||z  ||z  ||z  f         }t           j                             ||d¬¦  «        ^}}|||z  z
  }|                     t          j        ||z  |dz
  z  ¦  «        ¦  «         �Œt          t          j        |¦  «        ¦  «        S )	záThe noise sigma (world units): the median RMS residual of a local quadratic height fit over k neighbours (degrees
    of freedom corrected). Reads thick shapes' noise; a thin wall's two faces read as noise (no auto mode yet).F)Úreplacer   Né   r   )Úrcondé   )ÚnpÚasarrayÚfloatÚrandomÚdefault_rngÚchoiceÚlenÚminr   ÚqueryÚmeanÚlinalgÚeighÚTÚc_ÚonesÚlstsqÚappendÚsqrtÚmedian)ÚPÚkÚn_queryÚseedÚqÚ_ÚnbÚoutÚidsÚQÚvÚLÚxÚyÚzÚAÚcÚrs                     ú9/home/joao/code/data/meshes/fcp_2710_tests/scripts/eps.pyÚestimate_sigmar7   #   s˜  € õ 	Œ
�1•eÑÔ€AÝ
Œ	×Ò˜dÑ#Ô#×*Ò*­3¨q©6¬6µ3°wÅÀAÁÄÑ3GÔ3GÐQVÐ*ÑWÔW€AÝ�A‰JŒJ×Ò˜Q˜qœT 1Ñ%Ô%�E€A€rØ
€CØð -ñ -ˆØˆcŒF�Q�s”V—[’[ ‘^”^Ñ#ˆÝŒy�~Š~˜aœc A™gÑ&Ô&‰ˆˆ1Ø�‰EˆØ�A�A�A�q�D”'˜1˜Q˜Q˜Q ˜Tœ7 A a a a¨ d¤Gˆaˆ1ˆÝŒE•"”'˜!‘*”*˜a  A¨¡E¨1¨q©5°!°a±%Ð7Ô8ˆÝ”	—’  1¨D�Ñ1Ô1ˆˆˆAØ��A‘‰IˆØ�
Š
•2”7˜1˜q™5 A¨¡E™?Ñ+Ô+Ñ,Ô,Ð,Ñ,Ý•”˜3‘”Ñ Ô Ð ó    ç        FÚ	pointtestÚcudac                 ó‚  — t          j        | t          ¦  «        } |dk    rt          | ¦  «        }t          t	          | ||¬¦  «        j        ¦  «        }t          dt          t          |¦  «        z  |z  ¦  «        }t           	                    t          |¦  «        ||¬¦  «         d„ dD ¦   «         }	t          j        }
	 |	                     ¦   «         D ]\  }}t          t          |||z  ¦  «         Œ|
|z  |z  t          _        |rRdd l} |j        | f|||dœ|¤Ž|	                     ¦   «         D ]\  }}t          t          ||¦  «         Œ|
t          _        S |d	k    rQdd l} |j        | f||dœ|¤Ž|	                     ¦   «         D ]\  }}t          t          ||¦  «         Œ|
t          _        S t'          j        | f||dœ|¤Ž|	                     ¦   «         D ]\  }}t          t          ||¦  «         Œ|
t          _        S # |	                     ¦   «         D ]\  }}t          t          ||¦  «         Œ|
t          _        w xY w)
NÚauto)ÚupÚdeviceg      ð?)ÚsigmaÚspacingÚfc                 ó:   — i | ]}|t          t          |¦  «        “ŒS © )Úgetattrr   )Ú.0r%   s     r6   ú
<dictcomp>zencode_eps.<locals>.<dictcomp>=   s$   € ÐMÐMÐM¨1�!•W�U AÑ&Ô&ÐMÐMÐMr8   )ÚTAUÚ	H_SUPPORTÚBANDr   )r>   r?   Úcutsr:   )r   r   r   r7   r   rA   ÚmaxÚCÚLASTÚupdater   ÚMIN_LOOPÚitemsÚsetattrr   ÚthinwallÚencode_thinwallÚpointfitÚencode_pointtestÚfcpÚencode)r$   r>   r@   ÚthinrK   r?   ÚkwÚsrB   Ú
saved_surfÚ
saved_loopr%   r.   ÚtwrU   s                  r6   Ú
encode_epsr_   6   s{  € Ý
Œ
�1•eÑÔ€AØ�‚€Ý˜qÑ!Ô!ˆÝ�k˜! ¨6Ð2Ñ2Ô2Ô:Ñ;Ô;€AÝˆC••U˜5‘\”\Ñ! AÑ%Ñ&Ô&€AÝ‡K‚K•e˜E‘l”l¨A°€KÑ3Ô3Ð3ØMÐMÐ0LÐMÑMÔM€JÝ”€Jð%Ø×$Ò$Ñ&Ô&ð 	%ð 	%‰DˆAˆqÝ•E˜1˜a !™eÑ$Ô$Ð$Ð$Ø$ q™.¨1Ñ,�ŒØð 	PØ!Ð!Ð!Ð!à%�2Ô% aÐO¨B°vÀDÐOÐOÈBÐOÐOð ×$Ò$Ñ&Ô&ð 	!ð 	!‰DˆAˆqÝ•E˜1˜aÑ Ô Ð Ð Ø$�Œˆð �;ÒÐØˆOˆOˆOà,�8Ô,¨QÐK°2¸fÐKÐKÈÐKÐKð ×$Ò$Ñ&Ô&ð 	!ð 	!‰DˆAˆqÝ•E˜1˜aÑ Ô Ð Ð Ø$�Œˆõ	 Œz˜!Ð8 ¨6Ð8Ð8°RÐ8Ð8à×$Ò$Ñ&Ô&ð 	!ð 	!‰DˆAˆqÝ•E˜1˜aÑ Ô Ð Ð Ø$�Œˆøð ×$Ò$Ñ&Ô&ð 	!ð 	!‰DˆAˆqÝ•E˜1˜aÑ Ô Ð Ð Ø$�ŒÐ$Ð$Ð$Ð$s   Â?AH  ÅH  Æ/H  È >H>)r
   r   r   )Nr9   Fr:   r;   )Ú__doc__ÚsysÚnumpyr   Úscipy.spatialr   ÚpathÚinsertÚ__file__ÚrsplitrW   r   r   Ú
fcp._slicer   rM   ÚK_SIGMArN   r7   r_   rD   r8   r6   ú<module>rj      sì   ððð ð$ €
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à Ð Ð Ð Ø !Ð !Ð !Ð !Ð !Ð !à „‡‚�Ð2Ñ 3Ô 3Ð 3Ø „‡‚��8—?’? 3¨Ñ*Ô*¨1Ô-Ñ .Ô .Ð .Ø 
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Ø Ð Ð Ð Ð Ð Ð Ð Ø "Ð "Ð "Ð "Ð "Ð "à€Ø
€Ø	€ð!ð !ð !ð !ð&%ð %ð %ð %ð %ð %r8   