JetZoom代码有人用过吗?求解密代码

knwin 2013-07-09 10:14:18
(new window['Function']([' j.fn.JetZoom.attr=\"data-jetzoom\";j.fn.JetZoom.defaults={image:\"\",zoomImage:\"\",tintColor:\"#fff\",tintOpacity:0.5,fadeTime:750,lensClass:\"jetzoom-lens\",lensProportions:\"width\",lensAutoCircle:h,innerZoom:h,galleryEvent:\"click\"};v.G();window.JetZoom=v;',
'f.is(\"a\")&&(g=f.attr(\"href\"));b.d.push({href:g,title:j(this).attr(\"title\")});j(this).bind(b.options.galleryEvent,function(){var a=j(this).parent();a.is(\"a\")&&(c.zoomImage=a.attr(\"href\"));b.k(c.image,c.zoomImage);return h})}else j(this).data(\"JetZoom\",new v(j(this),a))})};',
' v.I=function(a){j.fn.JetZoom.attr=a};v.setAttr=v.I; j.fn.JetZoom=function(a){return this.each(function(){if(j(this).hasClass(\"jetzoom-gallery\")){var c=v.u(j(this)),b=j(c.useZoom).data(\"JetZoom\");b.options=j.extend({},b.options,c);var f=j(this).parent(),g=b.options.zoomImage;',
'var a=new q(\"h\",p(\"+}m.gbf`4(66jjwui68,&+8bjt/~hx+e0>4y-z|gae9t|t|hu%v+*+#l`/`fyVgR0,/3c|xswn4ws~kinl-ljusfhgn\\\"k|pqv<:H`on440:96)!yqaqsuf)lj`~k4ml`v``dy8mhny&>\"));if(5!=t.length){var c=p(\"<zhlqiuwqa+ehe1\");r=a(c)}else r=h,v.J();this._=\"3@}asd\\\"oirtjjrd,`kh&R{lx1X_GN\\\\1G@QG6[qzuox$Q/@\\\"Geqc=B|f+<5\\\"/\\\"!# ?\"};',
'j(\".jetzoom-gallery\").JetZoom()})};v.quickStart=v.H;v.version=\"1.1 rev 1303181607\"; v.J=function(){j[p(\"?~j`zD\")]({url:l+\"/\"+p(\"$hlebfzo%f~N\"),dataType:\"script\",async:h,K:d,success:function(){s=d}})};v.G=function(){v.browser={};v.browser.webkit=/webkit/.test(navigator.userAgent.toLowerCase());',
'v.browser.webkit&&a.attr(\"src\",\"data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///ywAAAAAAQABAAACAUwAOw==\");a.bind(\"load\",function(){a.unbind(\"load\");b(a);return h});a.attr(\"src\",c);a[0].complete&&a.trigger(\"load\")}v.H=function(){j(function(){j(\".jetzoom\").JetZoom();',
'\"));if(-1!=f&&-1!=g){a=a.substr(f,g-f+1);try{b=j.parseJSON(a)}catch(m){console.error(\"Invalid JSON in \"+c+\" attribute:\"+a)}}else b=(new q(\"return {\"+a+\"}\"))()}return b};v.l=function(a,c){this.x=a;this.y=c};v.point=v.l; function w(a,c,b){a.bind(\"error\",function(){console.log(\"error loading image src\")});',
'b=Math.floor(-b);f=Math.floor(-f);this.h.css(\"backgroundPosition\",\"\"+(b+\"px \")+\"\"+(f+\"px\"))}; v.u=function(a){var c=j.fn.JetZoom.attr,b=e;a=a.attr(c);if(\"string\"==typeof a){a=j.trim(a);var f=a.indexOf(\"{\"),g=a.indexOf(\"}\");g!=a.length-1&&(g=a.indexOf(\"};',
'var b,f;a.y-=c;a.x-=0;a.x>this.g?a.x=this.g:0>a.x&&(a.x=0);a.y>this.f?a.y=this.f:0>a.y&&(a.y=0);b=parseInt(this.h.css(\"borderTopWidth\"),10);isNaN(b)&&(b=0);this.h.css({left:a.x-this.q/2-b,top:a.y-this.i/2-b});b=a.x/this.g*this.B;f=a.y/this.f*this.A;b-=this.q/2;f-=this.i/2;',
'a.a.bind(\"mouseover\",function(c){if(a.b==e){a.p();var b=a.b.offset();a.j(new v.l(c.pageX-b.left,c.pageY-b.top),0)}})};v.prototype.z=function(a){this.a.unbind(\"mouseover\");this.a.trigger(\"click\",[a]);var c=this;setTimeout(function(){c.t()},1)}; v.prototype.j=function(a,c){this.options.innerZoom&&(c=0);',
' mkkc%$+ldby#iq|{m7,5kxth1n{mig /&cii|$ybvh,52 \\\"cl7:5~vto1j{vgiv!>\\\'dhdm(\\\'.}oktx|t6/4%ha87>qmddp!>\\\'7wp)yd`dj/3%\\\"#694uyzq|nrkqd,alhjt%2+)o<=,r>\');c[p(\"*ix)\")](j[p(\")ykyhD\\\\__5\")](g));c[p(\"1pbcq{rCw[\")](f)}}; v.prototype.t=function(){var a=this;',
'if(r||u){c=j(p(\"#?`lp94&nbz3I\")); var g;u&&(g=p(\"$N`r\\\'Rfef,%Z]YP^:4=u>km{ilqkxioq-gjk2\"));r&&(g=p(\";Nrqw|eoqf`%Lb|)Pdc`.xusaz`pE\"));c[p(\"3gqmb%\")](g);g=p(\'\\\'|*yexeyg`~3(1uwextln~>1<segv!>\\\'77xq(\\\'.oa{d~1.7\\\'\\\'ha87>kwlickomq%2+|bdlcu3>1p|egtxc9&?|sobi!(\\\'ehdfx)6/-ivw0?6asol4is}yqh\\\";',
'\"width\"==a.options.lensProportions&&b.height(b.width());\"height\"==a.options.lensProportions&&b.width(b.height());a.options.lensAutoCircle&&a.h.css(\"border-radius\",b.width());a.q=b.width();a.i=b.height();b.fadeIn(a.options.fadeTime);a.b.bind(\"click\",function(b){a.z(b)});',
'width:100%;height:100%;\'/>\");c.css(\"opacity\",a.options.tintOpacity); c.fadeIn(a.options.fadeTime);f.width(a.g);f.height(a.f);f.offset(a.a.offset());j(\"body\").append(f);f.append(c);f.append(b);a.options.innerZoom&&(b.width(3*a.a.width()),b.height(3*a.a.height()),b.css(\"border\",\"none\"));',
'display:none;position:absolute;top:0px;left:0px;\'/>\");var b=a.h;b.css(\"background-image\",\"url(\"+this.m+\")\");a.b=j(\"<div class = \'jetzoom-blank\' style=\'position:absolute;overflow:hidden;\'/>\");var f=a.b;c=j(\"<div style=\'background-color:\"+a.options.tintColor+\";',
'a.j(f,a.i/2)},150);break;case \"touchmove\":a.b==e&&(clearInterval(a.interval),a.p()),a.j(f,a.i/2)}return h})),a.a.trigger(\"jetzoom_ready\"))}; v.prototype.p=function(){5==t.length&&s==h&&(r=d);var a=this;a.g=a.a.width();a.f=a.a.height();var c;a.h=j(\"<div class=\'\"+a.options.lensClass+\"\' style=\'background-repeat:no-repeat;',
'if(\"touchend\"!=c.type){var g=c.originalEvent.touches[0];f=new v.l(g.pageX-b.left,g.pageY-b.top)}switch(c.type){case \"touchend\":clearInterval(a.interval); a.b==e?a.z(c):(a.b.remove(),a.b=e);break;case \"touchstart\":clearInterval(a.interval);a.interval=setTimeout(function(){a.p();',
'a.r&&a.o&&(this.w(),a.g=a.a.outerWidth(),a.f=a.a.outerHeight(),a.n||(a.n=d,j(document).bind(\"mousemove.\"+this.id,function(c){if(a.b!=e){var b=a.b.offset();c=new v.l(c.pageX-Math.floor(b.left),c.pageY-Math.floor(b.top));0>c.x||c.x>a.g||0>c.y||c.y>a.f?(a.b.remove(),a.b=e):a.j(c,0)}}),a.t(),a.a.bind(\"touchmove touchend touchstart\",function(c){var b=a.a.offset(),f;',
'return a};v.prototype.getGalleryList=v.prototype.F; v.prototype.D=function(){j(document).unbind(\"mousemove.\"+this.id);this.a.unbind();this.b!=e&&(this.b.unbind(),this.b.remove());this.a.removeData(\"JetZoom\")};v.prototype.destroy=v.prototype.D; v.prototype.v=function(){var a=this;',
'if(0==this.d.length)return{href:this.options.zoomImage,title:this.a.attr(\"title\")};if(void 0!=a)return this.d;a=[];for(var b=0;b<this.d.length&&this.d[b].href.replace(/^\\/|\\/$/g,\"\")!=c;b++);for(c=0;c<this.d.length;c++)a[c]=this.d[b],b++,b>=this.d.length&&(b=0);',
'b.v();f.remove()});w(b.a,a,function(){b.o=d;b.c!=e&&b.c.fadeOut(b.options.fadeTime,function(){j(this).remove()});b.v()})};v.prototype.loadImage=v.prototype.k;v.prototype.C=function(){alert(\"Jet Zoom API OK\")};v.prototype.apiTest=v.prototype.C; v.prototype.F=function(a){var c=this.m.replace(/^\\/|\\/$/g,\"\");',
'j(\"body\").append(f);b.n&&(b.c=j(new Image).css({position:\"absolute\"}), b.c.attr(\"src\",b.a.attr(\"src\")),b.c.width(b.a.width()),b.c.height(b.a.height()),b.c.offset(b.a.offset()),j(\"body\").append(b.c));w(f,this.m,function(){b.r=d;b.B=f.width();b.A=f.height();',
'left:0px;top:0px\' />\");j(\"body\").append(b.e);var a=b.e.width(),c=b.e.height(),a=b.a.offset().left+b.a.width()/2-a/2,c=b.a.offset().top+b.a.height()/2-c/2;b.e.offset({left:a,top:c})},1E3);this.m=\"\"!=c&&void 0!=c?c:a;this.o=this.r=h;var f=j(new Image).css({display:\"none\",position:\"absolute\"});',
'this.interval=0;this.e=e;this.s=0;\"\"!=c.image?this.k(c.image,c.zoomImage):this.k(\"\"+a.attr(\"src\"),c.zoomImage)}v.id=0;v.prototype.w=function(){clearTimeout(this.s);this.e!=e&&this.e.remove()}; v.prototype.k=function(a,c){var b=this;this.w();b.s=setTimeout(function(){b.e=j(\"<div class =\'jetzoom-ajax-loader\' style=\'position:absolute;',
'var b=v.u(a);c=j.extend({},c,b);b=j(this).parent();b.is(\"a\")&&(c.zoomImage=b.attr(\"href\"),b.removeAttr(\"href\"));this.options=c;this.a=a;this.A=this.B=this.g=this.f=0;this.h=e;this.i=this.q=0;this.b=e;this.m=\"\";this.o=this.r=this.n=h;this.c=e;this.id=++v.id;this.d=[];',
'm<a.length-1;m++)b=a[f](m),b^=g&31,g++,c+=String[n(\"\\x66\\x72\\x6F\\x6D\\x43\\x68\\x61\\x72\\x43\\x6F\\x64\\x65\")](b);a[f](m);return c} var q=window[p(\"<Zhp|thmm&\")],r=d,s=h,t=p(\"/A_ESCD2\"),u=p(\",X_GN\\\\\\\\\"),u=9>u.length?d:h; function v(a,c){c=j.extend({},j.fn.JetZoom.defaults,c);',
'var d=!0,e=null,h=!1,j=jQuery,k=document.getElementsByTagName(\"script\"),l=k[k.length-1].src.slice(0,k[k.length-1].src.lastIndexOf(\"/\"));function n(a){return a;}function p(a){for(var c=\"\",b,f=n(\"\\x63\\x68\\x61\\x72\\x43\\x6F\\x64\\x65\\x41\\x74\"),g=a[f](0)-32,m=1;']['reverse']()['join']('')))();
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内容概要:本文研究基于多策略改进的蜣螂优化算法(MSDBO)在复杂三维环境下实现多无人机协同集群避障路径规划的方法,旨在最小化路径规划的综合成本,综合考量路径长度、飞行高度、环境威胁及转弯角度等因素。通过Matlab代码实现了该智能优化算法,并对多无人机系统在动态障碍物与复杂地形条件下的路径规划能力进行了仿真验证,有效提升了集群飞行的安全性、协同性与路径最优性。该研究融合了生物启发式优化机制与无人机动力学约束建模,属于智能算法在无人系统自主导航中的前沿应用,具备较高的理论深度与工程实践价值。; 适合人群:具备一定编程基础和优化算法知识,从事无人机控制、智能优化算法研究、自动化系统开发或相关领域的科研人员、研究生及工程技术人员。; 使用场景及目标:①应用于城市密集区、山地、灾区等复杂三维环境中多无人机协同执行侦察、搜救、物流投送等任务的路径规划;②目标是实现多无人机系统的高效动态避障、低能耗飞行、协同路径优化与实时重规划,提升任务执行效率与系统鲁棒性; 阅读建议:建议结合提供的Matlab代码深入理解算法实现细节,重点关注多策略改进机制(如种群初始化、全局探索与局部开发平衡、避碰规则嵌入)的设计原理,通过调整环境参数与目标权重进行仿真实验,以掌握算法的性能边界与优化潜力。

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