o h:@stzddlZWneefyddlmZYnwejZddlmZmZm Z ddl m Z m Z ee e fZ ee e fZee ZeeZe edfZeeZee ZdZejejejejejejejejejejejd dede d ed e d ef d d ZdededefddZdedededefddZejejejejejejejejejdeededede de de f ddZejejejejejejejejed d/dedede defddZ ejejejejejejeejdeddfdedede de fd d!Z!d"e"d#efd$d%Z#d&ed#ed'efd(d)Z$ *d0dedede defd+d,Z% *d0dededede def d-d.Z&dS)1N)cython)SequenceTupleUnion)IntegralReal) jnx1x2d1d2scalexdcoordsrc1rd1rc2rd2cCsddg}dD]t}g||<}||||||||f\}} } } || kr>t|} | | kr5|| g| n|dg| q|| krL| |}} | | } } | | | |} |D]#}||}||krc| }n|| krj| }n ||| }| |}||qVqt|S)zGiven two reference coordinates `rc1` & `rc2` and their respective delta vectors `rd1` & `rd2`, returns interpolated deltas for the set of coordinates `coords`.Nrr)lenextendappendzip)rrrrr out_arraysr outr r r rr rpairrrnudger!h/var/www/html/construction_image-detection-poc/venv/lib/python3.10/site-packages/fontTools/varLib/iup.py iup_segments2 $    r#deltasreturnc Cst|t|ks Jd|vr|St|}ddt|D}|s$dg|Sg}t|}t|}|dkrUd|||df\}}} } |t||||| || || || ||||D]4} | |dkr|d| || f\}}} } |t||||| || || || ||| | }q^||dkr|d|||df\}}} } |t||||| || || || t|t|ksJt|t|f|S)zFor the contour given in `coords`, interpolate any missing delta values in delta vector `deltas`. Returns fully filled-out delta vector.NcSsg|] \}}|dur|qSNr!).0ivr!r!r" gsziup_contour..)rrrr)r enumerateiternextrr#r) r$rr indicesritstarti1i2ri1ri2endr!r!r" iup_contour[sJ " " "$r7endscCst||krt||r|ddnddksJt|}||d|d|d|dg}g}d}|D]}|d7}t||||||}|||}q2|S)zFor the outline given in `coords`, with contour endpoints given in sorted increasing order in `ends`, interpolate any missing delta values in delta vector `deltas`. Returns fully filled-out delta vector.r+rr)sortedrr7r)r$rr8r rr1r6contourr!r!r" iup_deltas0   r>)r(r rypqr(r tolerancecsh||dksJt||d|||||||||}||d|}tfddt||DS)zReturn true if the deltas for points at `i` and `j` (`i < j`) can be successfully used to interpolate deltas for points in between them within provided error tolerance.r;rc3s6|]\\}}\}}tt||||kVqdSr&abscomplex)r'rr?r@rArBr!r" s  z%can_iup_in_between..)r#allr)r$rr(r rBinterpr!rFr"can_iup_in_betweens , rJ)cjdjlcjldjncjndjforceforcedcCst|t|ks Jt|}t}tt|dddD]}||d||d}}||||}} |||d|||d} } dD]} | | } || }|| }|| }| | }| | }||kro||}}||}}n ||}}||}}d}||krt|||krt||krd}na|| kr|krnnt||||krt|||ksnd}n=||kr| |krt||krt|||kr|||k||kkrd}nt||krt|||kr|||k||kkrd}|r||nqFq|S)aThe forced set is a conservative set of points on the contour that must be encoded explicitly (ie. cannot be interpolated). Calculating this set allows for significantly speeding up the dynamic-programming, as well as resolve circularity in DP. The set is precise; that is, if an index is in the returned set, then there is no way that IUP can generate delta for that point, given `coords` and `deltas`. rr+rFT)rsetrangerDminmaxadd)r$rrBr rRr(ldlcrcndncr rKrLrMrNrOrPc1c2r rrQr!r!r"_iup_contour_bound_forced_setsZ"    *   r_)r(r best_costbest_jcostrRrBlookbackc Cst|}|dur |}t|t}ddi}ddi}td|D]M}||dd} | ||<|d||<|d|vr7qt|dt||ddD]$} || d} | | krbt||| ||rb| ||<} | ||<| |vrhnqDq||fS)aStraightforward Dynamic-Programming. For each index i, find least-costly encoding of points 0 to i where i is explicitly encoded. We find this by considering all previous explicit points j and check whether interpolation can fill points between j and i. Note that solution always encodes last point explicitly. Higher-level is responsible for removing that restriction. As major speedup, we stop looking further whenever we see a "forced" point.Nr+rrr;)rrU MAX_LOOKBACKrTrVrJ) r$rrRrBrcr costschainr(r`r rbr!r!r"_iup_contour_optimize_dp%s,     rhlkcCs8t|}||;}|s |S|||d|d||S)z{Rotate list by k items forward. Ie. item at position 0 will be at position k in returned list. Negative k is allowed.N)r)rirjr r!r!r" _rot_listZs  rksr cs$;s|Sfdd|DS)Ncsh|]}|qSr!r!)r'r)rjr r!r" hsz_rot_set..r!)rlrjr r!rmr"_rot_setdsroc st}tfddDrdg|S|dkrSdtfddDr3gdg|dSt|}|r|dt|}|dksIJt|t||}t|||}t||\}}t|d}|durz|||}|dusm d|ksJ|ffdd t |Dt| St||||\}}d|d} t |dt|dD]7} t| }|| |krۈ||||}|| |ks|| |kr|| || |} | | kr| } q|ksJ|ffd d t |DS) zFor contour with coordinates `coords`, optimize a set of delta values `deltas` within error `tolerance`. Returns delta vector that has most number of None items instead of the input delta. c3s |] }tt|kVqdSr&rC)r'r@rFr!r"rGzsz'iup_contour_optimize..Nrrc3s|]}|kVqdSr&r!)r'r)d0r!r"rGsr+cs g|] }|vr |ndqSr&r!r'r()r$solutionr!r"r* z(iup_contour_optimize..cs g|] }|vr |ndqSr&r!rr)best_solr$r!r"r*rt) rrHr_rVrkrorhrSrWremoverT) r$rrBr rRrjrgrfr(r`r1rbr!)rurqr$rsrBr"iup_contour_optimizeks\              rwc Cst||krt||r|ddnddksJt|}||d|d|d|dg}g}d}|D])}t|||d|||d|}t|||dksRJ|||d}q2|S)aFor the outline given in `coords`, with contour endpoints given in sorted increasing order in `ends`, optimize a set of delta values `deltas` within error `tolerance`. Returns delta vector that has most number of None items instead of the input delta. r+rrr9r:r;)r<rrwr) r$rr8rBr rr1r6r=r!r!r"iup_delta_optimizes0    rx)r)rp)'rAttributeError ImportErrorfontTools.misccompiledCOMPILEDtypingrrrnumbersrr_Point_Delta _PointSegment _DeltaSegment _DeltaOrNone_DeltaOrNoneSegment _Endpointsrecfunclocalsintdoubler#r7r>inlinereturnsrJrSr_rhlistrkrorwrxr!r!r!r"s     34    Q  ,  i