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strict\";function r(t){this._root=t,this._startText=this.getText(),this._fallbackText=null}var i=n(3),o=n(18),a=n(172);i(r.prototype,{destructor:function(){this._root=null,this._startText=null,this._fallbackText=null},getText:function(){return\"value\"in this._root?this._root.value:this._root[a()]},getData:function(){if(this._fallbackText)return this._fallbackText;var t,e,n=this._startText,r=n.length,i=this.getText(),o=i.length;for(t=0;t<r&&n[t]===i[t];t++);var a=r-t;for(e=1;e<=a&&n[r-e]===i[o-e];e++);var u=e>1?1-e:void 0;return this._fallbackText=i.slice(t,u),this._fallbackText}}),o.addPoolingTo(r),t.exports=r},function(t,e,n){\"use strict\";var r=n(21),i=r.injection.MUST_USE_PROPERTY,o=r.injection.HAS_BOOLEAN_VALUE,a=r.injection.HAS_NUMERIC_VALUE,u=r.injection.HAS_POSITIVE_NUMERIC_VALUE,c=r.injection.HAS_OVERLOADED_BOOLEAN_VALUE,s={isCustomAttribute:RegExp.prototype.test.bind(new RegExp(\"^(data|aria)-[\"+r.ATTRIBUTE_NAME_CHAR+\"]*$\")),Properties:{accept:0,acceptCharset:0,accessKey:0,action:0,allowFullScreen:o,allowTransparency:0,alt:0,as:0,async:o,autoComplete:0,autoPlay:o,capture:o,cellPadding:0,cellSpacing:0,charSet:0,challenge:0,checked:i|o,cite:0,classID:0,className:0,cols:u,colSpan:0,content:0,contentEditable:0,contextMenu:0,controls:o,controlsList:0,coords:0,crossOrigin:0,data:0,dateTime:0,default:o,defer:o,dir:0,disabled:o,download:c,draggable:0,encType:0,form:0,formAction:0,formEncType:0,formMethod:0,formNoValidate:o,formTarget:0,frameBorder:0,headers:0,height:0,hidden:o,high:0,href:0,hrefLang:0,htmlFor:0,httpEquiv:0,icon:0,id:0,inputMode:0,integrity:0,is:0,keyParams:0,keyType:0,kind:0,label:0,lang:0,list:0,loop:o,low:0,manifest:0,marginHeight:0,marginWidth:0,max:0,maxLength:0,media:0,mediaGroup:0,method:0,min:0,minLength:0,multiple:i|o,muted:i|o,name:0,nonce:0,noValidate:o,open:o,optimum:0,pattern:0,placeholder:0,playsInline:o,poster:0,preload:0,profile:0,radioGroup:0,readOnly:o,referrerPolicy:0,rel:0,required:o,reversed:o,role:0,rows:u,rowSpan:a,sandbox:0,scope:0,scoped:o,scrolling:0,seamless:o,selected:i|o,shape:0,size:u,sizes:0,span:u,spellCheck:0,src:0,srcDoc:0,srcLang:0,srcSet:0,start:a,step:0,style:0,summary:0,tabIndex:0,target:0,title:0,type:0,useMap:0,value:0,width:0,wmode:0,wrap:0,about:0,datatype:0,inlist:0,prefix:0,property:0,resource:0,typeof:0,vocab:0,autoCapitalize:0,autoCorrect:0,autoSave:0,color:0,itemProp:0,itemScope:o,itemType:0,itemID:0,itemRef:0,results:0,security:0,unselectable:0},DOMAttributeNames:{acceptCharset:\"accept-charset\",className:\"class\",htmlFor:\"for\",httpEquiv:\"http-equiv\"},DOMPropertyNames:{},DOMMutationMethods:{value:function(t,e){if(null==e)return t.removeAttribute(\"value\");\"number\"!==t.type||!1===t.hasAttribute(\"value\")?t.setAttribute(\"value\",\"\"+e):t.validity&&!t.validity.badInput&&t.ownerDocument.activeElement!==t&&t.setAttribute(\"value\",\"\"+e)}}};t.exports=s},function(t,e,n){\"use strict\";(function(e){function r(t,e,n,r){var i=void 0===t[n];null!=e&&i&&(t[n]=o(e,!0))}var i=n(24),o=n(174),a=(n(85),n(96)),u=n(177);n(2);void 0!==e&&e.env;var c={instantiateChildren:function(t,e,n,i){if(null==t)return null;var o={};return u(t,r,o),o},updateChildren:function(t,e,n,r,u,c,s,l,f){if(e||t){var p,h;for(p in e)if(e.hasOwnProperty(p)){h=t&&t[p];var d=h&&h._currentElement,v=e[p];if(null!=h&&a(d,v))i.receiveComponent(h,v,u,l),e[p]=h;else{h&&(r[p]=i.getHostNode(h),i.unmountComponent(h,!1));var g=o(v,!0);e[p]=g;var m=i.mountComponent(g,u,c,s,l,f);n.push(m)}}for(p in t)!t.hasOwnProperty(p)||e&&e.hasOwnProperty(p)||(h=t[p],r[p]=i.getHostNode(h),i.unmountComponent(h,!1))}},unmountChildren:function(t,e){for(var n in t)if(t.hasOwnProperty(n)){var r=t[n];i.unmountComponent(r,e)}}};t.exports=c}).call(e,n(156))},function(t,e,n){\"use strict\";var r=n(82),i=n(364),o={processChildrenUpdates:i.dangerouslyProcessChildrenUpdates,replaceNodeWithMarkup:r.dangerouslyReplaceNodeWithMarkup};t.exports=o},function(t,e,n){\"use strict\";function r(t){}function i(t){return!(!t.prototype||!t.prototype.isReactComponent)}function o(t){return!(!t.prototype||!t.prototype.isPureReactComponent)}var a=n(1),u=n(3),c=n(26),s=n(87),l=n(15),f=n(88),p=n(39),h=(n(9),n(168)),d=n(24),v=n(51),g=(n(0),n(81)),m=n(96),y=(n(2),{ImpureClass:0,PureClass:1,StatelessFunctional:2});r.prototype.render=function(){var t=p.get(this)._currentElement.type,e=t(this.props,this.context,this.updater);return e};var _=1,b={construct:function(t){this._currentElement=t,this._rootNodeID=0,this._compositeType=null,this._instance=null,this._hostParent=null,this._hostContainerInfo=null,this._updateBatchNumber=null,this._pendingElement=null,this._pendingStateQueue=null,this._pendingReplaceState=!1,this._pendingForceUpdate=!1,this._renderedNodeType=null,this._renderedComponent=null,this._context=null,this._mountOrder=0,this._topLevelWrapper=null,this._pendingCallbacks=null,this._calledComponentWillUnmount=!1},mountComponent:function(t,e,n,u){this._context=u,this._mountOrder=_++,this._hostParent=e,this._hostContainerInfo=n;var s,l=this._currentElement.props,f=this._processContext(u),h=this._currentElement.type,d=t.getUpdateQueue(),g=i(h),m=this._constructComponent(g,l,f,d);g||null!=m&&null!=m.render?o(h)?this._compositeType=y.PureClass:this._compositeType=y.ImpureClass:(s=m,null===m||!1===m||c.isValidElement(m)||a(\"105\",h.displayName||h.name||\"Component\"),m=new r(h),this._compositeType=y.StatelessFunctional);m.props=l,m.context=f,m.refs=v,m.updater=d,this._instance=m,p.set(m,this);var b=m.state;void 0===b&&(m.state=b=null),(\"object\"!=typeof b||Array.isArray(b))&&a(\"106\",this.getName()||\"ReactCompositeComponent\"),this._pendingStateQueue=null,this._pendingReplaceState=!1,this._pendingForceUpdate=!1;var x;return x=m.unstable_handleError?this.performInitialMountWithErrorHandling(s,e,n,t,u):this.performInitialMount(s,e,n,t,u),m.componentDidMount&&t.getReactMountReady().enqueue(m.componentDidMount,m),x},_constructComponent:function(t,e,n,r){return this._constructComponentWithoutOwner(t,e,n,r)},_constructComponentWithoutOwner:function(t,e,n,r){var i=this._currentElement.type;return t?new i(e,n,r):i(e,n,r)},performInitialMountWithErrorHandling:function(t,e,n,r,i){var o,a=r.checkpoint();try{o=this.performInitialMount(t,e,n,r,i)}catch(u){r.rollback(a),this._instance.unstable_handleError(u),this._pendingStateQueue&&(this._instance.state=this._processPendingState(this._instance.props,this._instance.context)),a=r.checkpoint(),this._renderedComponent.unmountComponent(!0),r.rollback(a),o=this.performInitialMount(t,e,n,r,i)}return o},performInitialMount:function(t,e,n,r,i){var o=this._instance,a=0;o.componentWillMount&&(o.componentWillMount(),this._pendingStateQueue&&(o.state=this._processPendingState(o.props,o.context))),void 0===t&&(t=this._renderValidatedComponent());var u=h.getType(t);this._renderedNodeType=u;var c=this._instantiateReactComponent(t,u!==h.EMPTY);this._renderedComponent=c;var s=d.mountComponent(c,r,e,n,this._processChildContext(i),a);return s},getHostNode:function(){return d.getHostNode(this._renderedComponent)},unmountComponent:function(t){if(this._renderedComponent){var e=this._instance;if(e.componentWillUnmount&&!e._calledComponentWillUnmount)if(e._calledComponentWillUnmount=!0,t){var n=this.getName()+\".componentWillUnmount()\";f.invokeGuardedCallback(n,e.componentWillUnmount.bind(e))}else e.componentWillUnmount();this._renderedComponent&&(d.unmountComponent(this._renderedComponent,t),this._renderedNodeType=null,this._renderedComponent=null,this._instance=null),this._pendingStateQueue=null,this._pendingReplaceState=!1,this._pendingForceUpdate=!1,this._pendingCallbacks=null,this._pendingElement=null,this._context=null,this._rootNodeID=0,this._topLevelWrapper=null,p.remove(e)}},_maskContext:function(t){var e=this._currentElement.type,n=e.contextTypes;if(!n)return v;var r={};for(var i in n)r[i]=t[i];return r},_processContext:function(t){var e=this._maskContext(t);return e},_processChildContext:function(t){var e,n=this._currentElement.type,r=this._instance;if(r.getChildContext&&(e=r.getChildContext()),e){\"object\"!=typeof n.childContextTypes&&a(\"107\",this.getName()||\"ReactCompositeComponent\");for(var i in e)i in n.childContextTypes||a(\"108\",this.getName()||\"ReactCompositeComponent\",i);return u({},t,e)}return t},_checkContextTypes:function(t,e,n){},receiveComponent:function(t,e,n){var r=this._currentElement,i=this._context;this._pendingElement=null,this.updateComponent(e,r,t,i,n)},performUpdateIfNecessary:function(t){null!=this._pendingElement?d.receiveComponent(this,this._pendingElement,t,this._context):null!==this._pendingStateQueue||this._pendingForceUpdate?this.updateComponent(t,this._currentElement,this._currentElement,this._context,this._context):this._updateBatchNumber=null},updateComponent:function(t,e,n,r,i){var o=this._instance;null==o&&a(\"136\",this.getName()||\"ReactCompositeComponent\");var u,c=!1;this._context===i?u=o.context:(u=this._processContext(i),c=!0);var s=e.props,l=n.props;e!==n&&(c=!0),c&&o.componentWillReceiveProps&&o.componentWillReceiveProps(l,u);var f=this._processPendingState(l,u),p=!0;this._pendingForceUpdate||(o.shouldComponentUpdate?p=o.shouldComponentUpdate(l,f,u):this._compositeType===y.PureClass&&(p=!g(s,l)||!g(o.state,f))),this._updateBatchNumber=null,p?(this._pendingForceUpdate=!1,this._performComponentUpdate(n,l,f,u,t,i)):(this._currentElement=n,this._context=i,o.props=l,o.state=f,o.context=u)},_processPendingState:function(t,e){var n=this._instance,r=this._pendingStateQueue,i=this._pendingReplaceState;if(this._pendingReplaceState=!1,this._pendingStateQueue=null,!r)return n.state;if(i&&1===r.length)return r[0];for(var o=u({},i?r[0]:n.state),a=i?1:0;a<r.length;a++){var c=r[a];u(o,\"function\"==typeof c?c.call(n,o,t,e):c)}return o},_performComponentUpdate:function(t,e,n,r,i,o){var a,u,c,s=this._instance,l=Boolean(s.componentDidUpdate);l&&(a=s.props,u=s.state,c=s.context),s.componentWillUpdate&&s.componentWillUpdate(e,n,r),this._currentElement=t,this._context=o,s.props=e,s.state=n,s.context=r,this._updateRenderedComponent(i,o),l&&i.getReactMountReady().enqueue(s.componentDidUpdate.bind(s,a,u,c),s)},_updateRenderedComponent:function(t,e){var n=this._renderedComponent,r=n._currentElement,i=this._renderValidatedComponent(),o=0;if(m(r,i))d.receiveComponent(n,i,t,this._processChildContext(e));else{var a=d.getHostNode(n);d.unmountComponent(n,!1);var u=h.getType(i);this._renderedNodeType=u;var c=this._instantiateReactComponent(i,u!==h.EMPTY);this._renderedComponent=c;var s=d.mountComponent(c,t,this._hostParent,this._hostContainerInfo,this._processChildContext(e),o);this._replaceNodeWithMarkup(a,s,n)}},_replaceNodeWithMarkup:function(t,e,n){s.replaceNodeWithMarkup(t,e,n)},_renderValidatedComponentWithoutOwnerOrContext:function(){var t=this._instance;return t.render()},_renderValidatedComponent:function(){var t;if(this._compositeType!==y.StatelessFunctional){l.current=this;try{t=this._renderValidatedComponentWithoutOwnerOrContext()}finally{l.current=null}}else t=this._renderValidatedComponentWithoutOwnerOrContext();return null===t||!1===t||c.isValidElement(t)||a(\"109\",this.getName()||\"ReactCompositeComponent\"),t},attachRef:function(t,e){var n=this.getPublicInstance();null==n&&a(\"110\");var r=e.getPublicInstance();(n.refs===v?n.refs={}:n.refs)[t]=r},detachRef:function(t){delete this.getPublicInstance().refs[t]},getName:function(){var t=this._currentElement.type,e=this._instance&&this._instance.constructor;return t.displayName||e&&e.displayName||t.name||e&&e.name||null},getPublicInstance:function(){var t=this._instance;return this._compositeType===y.StatelessFunctional?null:t},_instantiateReactComponent:null};t.exports=b},function(t,e,n){\"use strict\";var r=n(4),i=n(372),o=n(167),a=n(24),u=n(12),c=n(385),s=n(401),l=n(171),f=n(408);n(2);i.inject();var p={findDOMNode:s,render:o.render,unmountComponentAtNode:o.unmountComponentAtNode,version:c,unstable_batchedUpdates:u.batchedUpdates,unstable_renderSubtreeIntoContainer:f};\"undefined\"!=typeof __REACT_DEVTOOLS_GLOBAL_HOOK__&&\"function\"==typeof __REACT_DEVTOOLS_GLOBAL_HOOK__.inject&&__REACT_DEVTOOLS_GLOBAL_HOOK__.inject({ComponentTree:{getClosestInstanceFromNode:r.getClosestInstanceFromNode,getNodeFromInstance:function(t){return t._renderedComponent&&(t=l(t)),t?r.getNodeFromInstance(t):null}},Mount:o,Reconciler:a});t.exports=p},function(t,e,n){\"use strict\";function r(t){if(t){var e=t._currentElement._owner||null;if(e){var n=e.getName();if(n)return\" This DOM node was rendered by `\"+n+\"`.\"}}return\"\"}function i(t,e){e&&($[t._tag]&&(null!=e.children||null!=e.dangerouslySetInnerHTML)&&g(\"137\",t._tag,t._currentElement._owner?\" Check the render method of \"+t._currentElement._owner.getName()+\".\":\"\"),null!=e.dangerouslySetInnerHTML&&(null!=e.children&&g(\"60\"),\"object\"==typeof e.dangerouslySetInnerHTML&&z in e.dangerouslySetInnerHTML||g(\"61\")),null!=e.style&&\"object\"!=typeof e.style&&g(\"62\",r(t)))}function o(t,e,n,r){if(!(r instanceof D)){var i=t._hostContainerInfo,o=i._node&&i._node.nodeType===q,u=o?i._node:i._ownerDocument;B(e,u),r.getReactMountReady().enqueue(a,{inst:t,registrationName:e,listener:n})}}function a(){var t=this;k.putListener(t.inst,t.registrationName,t.listener)}function u(){var t=this;N.postMountWrapper(t)}function c(){var t=this;O.postMountWrapper(t)}function s(){var t=this;A.postMountWrapper(t)}function l(){L.track(this)}function f(){var t=this;t._rootNodeID||g(\"63\");var e=j(t);switch(e||g(\"64\"),t._tag){case\"iframe\":case\"object\":t._wrapperState.listeners=[M.trapBubbledEvent(\"topLoad\",\"load\",e)];break;case\"video\":case\"audio\":t._wrapperState.listeners=[];for(var n in Y)Y.hasOwnProperty(n)&&t._wrapperState.listeners.push(M.trapBubbledEvent(n,Y[n],e));break;case\"source\":t._wrapperState.listeners=[M.trapBubbledEvent(\"topError\",\"error\",e)];break;case\"img\":t._wrapperState.listeners=[M.trapBubbledEvent(\"topError\",\"error\",e),M.trapBubbledEvent(\"topLoad\",\"load\",e)];break;case\"form\":t._wrapperState.listeners=[M.trapBubbledEvent(\"topReset\",\"reset\",e),M.trapBubbledEvent(\"topSubmit\",\"submit\",e)];break;case\"input\":case\"select\":case\"textarea\":t._wrapperState.listeners=[M.trapBubbledEvent(\"topInvalid\",\"invalid\",e)]}}function p(){P.postUpdateWrapper(this)}function h(t){Z.call(Q,t)||(X.test(t)||g(\"65\",t),Q[t]=!0)}function d(t,e){return t.indexOf(\"-\")>=0||null!=e.is}function v(t){var e=t.type;h(e),this._currentElement=t,this._tag=e.toLowerCase(),this._namespaceURI=null,this._renderedChildren=null,this._previousStyle=null,this._previousStyleCopy=null,this._hostNode=null,this._hostParent=null,this._rootNodeID=0,this._domID=0,this._hostContainerInfo=null,this._wrapperState=null,this._topLevelWrapper=null,this._flags=0}var g=n(1),m=n(3),y=n(346),_=n(348),b=n(20),x=n(83),w=n(21),C=n(160),k=n(22),E=n(84),M=n(53),T=n(161),S=n(4),N=n(365),A=n(366),P=n(162),O=n(369),I=(n(9),n(378)),D=n(383),R=(n(11),n(56)),L=(n(0),n(95),n(81),n(173)),U=(n(97),n(2),T),F=k.deleteListener,j=S.getNodeFromInstance,B=M.listenTo,V=E.registrationNameModules,W={string:!0,number:!0},z=\"__html\",H={children:null,dangerouslySetInnerHTML:null,suppressContentEditableWarning:null},q=11,Y={topAbort:\"abort\",topCanPlay:\"canplay\",topCanPlayThrough:\"canplaythrough\",topDurationChange:\"durationchange\",topEmptied:\"emptied\",topEncrypted:\"encrypted\",topEnded:\"ended\",topError:\"error\",topLoadedData:\"loadeddata\",topLoadedMetadata:\"loadedmetadata\",topLoadStart:\"loadstart\",topPause:\"pause\",topPlay:\"play\",topPlaying:\"playing\",topProgress:\"progress\",topRateChange:\"ratechange\",topSeeked:\"seeked\",topSeeking:\"seeking\",topStalled:\"stalled\",topSuspend:\"suspend\",topTimeUpdate:\"timeupdate\",topVolumeChange:\"volumechange\",topWaiting:\"waiting\"},K={area:!0,base:!0,br:!0,col:!0,embed:!0,hr:!0,img:!0,input:!0,keygen:!0,link:!0,meta:!0,param:!0,source:!0,track:!0,wbr:!0},G={listing:!0,pre:!0,textarea:!0},$=m({menuitem:!0},K),X=/^[a-zA-Z][a-zA-Z:_\\.\\-\\d]*$/,Q={},Z={}.hasOwnProperty,J=1;v.displayName=\"ReactDOMComponent\",v.Mixin={mountComponent:function(t,e,n,r){this._rootNodeID=J++,this._domID=n._idCounter++,this._hostParent=e,this._hostContainerInfo=n;var o=this._currentElement.props;switch(this._tag){case\"audio\":case\"form\":case\"iframe\":case\"img\":case\"link\":case\"object\":case\"source\":case\"video\":this._wrapperState={listeners:null},t.getReactMountReady().enqueue(f,this);break;case\"input\":N.mountWrapper(this,o,e),o=N.getHostProps(this,o),t.getReactMountReady().enqueue(l,this),t.getReactMountReady().enqueue(f,this);break;case\"option\":A.mountWrapper(this,o,e),o=A.getHostProps(this,o);break;case\"select\":P.mountWrapper(this,o,e),o=P.getHostProps(this,o),t.getReactMountReady().enqueue(f,this);break;case\"textarea\":O.mountWrapper(this,o,e),o=O.getHostProps(this,o),t.getReactMountReady().enqueue(l,this),t.getReactMountReady().enqueue(f,this)}i(this,o);var a,p;null!=e?(a=e._namespaceURI,p=e._tag):n._tag&&(a=n._namespaceURI,p=n._tag),(null==a||a===x.svg&&\"foreignobject\"===p)&&(a=x.html),a===x.html&&(\"svg\"===this._tag?a=x.svg:\"math\"===this._tag&&(a=x.mathml)),this._namespaceURI=a;var h;if(t.useCreateElement){var d,v=n._ownerDocument;if(a===x.html)if(\"script\"===this._tag){var g=v.createElement(\"div\"),m=this._currentElement.type;g.innerHTML=\"<\"+m+\"></\"+m+\">\",d=g.removeChild(g.firstChild)}else d=o.is?v.createElement(this._currentElement.type,o.is):v.createElement(this._currentElement.type);else d=v.createElementNS(a,this._currentElement.type);S.precacheNode(this,d),this._flags|=U.hasCachedChildNodes,this._hostParent||C.setAttributeForRoot(d),this._updateDOMProperties(null,o,t);var _=b(d);this._createInitialChildren(t,o,r,_),h=_}else{var w=this._createOpenTagMarkupAndPutListeners(t,o),k=this._createContentMarkup(t,o,r);h=!k&&K[this._tag]?w+\"/>\":w+\">\"+k+\"</\"+this._currentElement.type+\">\"}switch(this._tag){case\"input\":t.getReactMountReady().enqueue(u,this),o.autoFocus&&t.getReactMountReady().enqueue(y.focusDOMComponent,this);break;case\"textarea\":t.getReactMountReady().enqueue(c,this),o.autoFocus&&t.getReactMountReady().enqueue(y.focusDOMComponent,this);break;case\"select\":case\"button\":o.autoFocus&&t.getReactMountReady().enqueue(y.focusDOMComponent,this);break;case\"option\":t.getReactMountReady().enqueue(s,this)}return h},_createOpenTagMarkupAndPutListeners:function(t,e){var n=\"<\"+this._currentElement.type;for(var r in e)if(e.hasOwnProperty(r)){var i=e[r];if(null!=i)if(V.hasOwnProperty(r))i&&o(this,r,i,t);else{\"style\"===r&&(i&&(i=this._previousStyleCopy=m({},e.style)),i=_.createMarkupForStyles(i,this));var a=null;null!=this._tag&&d(this._tag,e)?H.hasOwnProperty(r)||(a=C.createMarkupForCustomAttribute(r,i)):a=C.createMarkupForProperty(r,i),a&&(n+=\" \"+a)}}return t.renderToStaticMarkup?n:(this._hostParent||(n+=\" \"+C.createMarkupForRoot()),n+=\" \"+C.createMarkupForID(this._domID))},_createContentMarkup:function(t,e,n){var r=\"\",i=e.dangerouslySetInnerHTML;if(null!=i)null!=i.__html&&(r=i.__html);else{var o=W[typeof e.children]?e.children:null,a=null!=o?null:e.children;if(null!=o)r=R(o);else if(null!=a){var u=this.mountChildren(a,t,n);r=u.join(\"\")}}return G[this._tag]&&\"\\n\"===r.charAt(0)?\"\\n\"+r:r},_createInitialChildren:function(t,e,n,r){var i=e.dangerouslySetInnerHTML;if(null!=i)null!=i.__html&&b.queueHTML(r,i.__html);else{var o=W[typeof e.children]?e.children:null,a=null!=o?null:e.children;if(null!=o)\"\"!==o&&b.queueText(r,o);else if(null!=a)for(var u=this.mountChildren(a,t,n),c=0;c<u.length;c++)b.queueChild(r,u[c])}},receiveComponent:function(t,e,n){var r=this._currentElement;this._currentElement=t,this.updateComponent(e,r,t,n)},updateComponent:function(t,e,n,r){var o=e.props,a=this._currentElement.props;switch(this._tag){case\"input\":o=N.getHostProps(this,o),a=N.getHostProps(this,a);break;case\"option\":o=A.getHostProps(this,o),a=A.getHostProps(this,a);break;case\"select\":o=P.getHostProps(this,o),a=P.getHostProps(this,a);break;case\"textarea\":o=O.getHostProps(this,o),a=O.getHostProps(this,a)}switch(i(this,a),this._updateDOMProperties(o,a,t),this._updateDOMChildren(o,a,t,r),this._tag){case\"input\":N.updateWrapper(this),L.updateValueIfChanged(this);break;case\"textarea\":O.updateWrapper(this);break;case\"select\":t.getReactMountReady().enqueue(p,this)}},_updateDOMProperties:function(t,e,n){var r,i,a;for(r in t)if(!e.hasOwnProperty(r)&&t.hasOwnProperty(r)&&null!=t[r])if(\"style\"===r){var u=this._previousStyleCopy;for(i in u)u.hasOwnProperty(i)&&(a=a||{},a[i]=\"\");this._previousStyleCopy=null}else V.hasOwnProperty(r)?t[r]&&F(this,r):d(this._tag,t)?H.hasOwnProperty(r)||C.deleteValueForAttribute(j(this),r):(w.properties[r]||w.isCustomAttribute(r))&&C.deleteValueForProperty(j(this),r);for(r in e){var c=e[r],s=\"style\"===r?this._previousStyleCopy:null!=t?t[r]:void 0;if(e.hasOwnProperty(r)&&c!==s&&(null!=c||null!=s))if(\"style\"===r)if(c?c=this._previousStyleCopy=m({},c):this._previousStyleCopy=null,s){for(i in s)!s.hasOwnProperty(i)||c&&c.hasOwnProperty(i)||(a=a||{},a[i]=\"\");for(i in c)c.hasOwnProperty(i)&&s[i]!==c[i]&&(a=a||{},a[i]=c[i])}else a=c;else if(V.hasOwnProperty(r))c?o(this,r,c,n):s&&F(this,r);else if(d(this._tag,e))H.hasOwnProperty(r)||C.setValueForAttribute(j(this),r,c);else if(w.properties[r]||w.isCustomAttribute(r)){var l=j(this);null!=c?C.setValueForProperty(l,r,c):C.deleteValueForProperty(l,r)}}a&&_.setValueForStyles(j(this),a,this)},_updateDOMChildren:function(t,e,n,r){var i=W[typeof t.children]?t.children:null,o=W[typeof e.children]?e.children:null,a=t.dangerouslySetInnerHTML&&t.dangerouslySetInnerHTML.__html,u=e.dangerouslySetInnerHTML&&e.dangerouslySetInnerHTML.__html,c=null!=i?null:t.children,s=null!=o?null:e.children,l=null!=i||null!=a,f=null!=o||null!=u;null!=c&&null==s?this.updateChildren(null,n,r):l&&!f&&this.updateTextContent(\"\"),null!=o?i!==o&&this.updateTextContent(\"\"+o):null!=u?a!==u&&this.updateMarkup(\"\"+u):null!=s&&this.updateChildren(s,n,r)},getHostNode:function(){return j(this)},unmountComponent:function(t){switch(this._tag){case\"audio\":case\"form\":case\"iframe\":case\"img\":case\"link\":case\"object\":case\"source\":case\"video\":var e=this._wrapperState.listeners;if(e)for(var n=0;n<e.length;n++)e[n].remove();break;case\"input\":case\"textarea\":L.stopTracking(this);break;case\"html\":case\"head\":case\"body\":g(\"66\",this._tag)}this.unmountChildren(t),S.uncacheNode(this),k.deleteAllListeners(this),this._rootNodeID=0,this._domID=0,this._wrapperState=null},getPublicInstance:function(){return j(this)}},m(v.prototype,v.Mixin,I.Mixin),t.exports=v},function(t,e,n){\"use strict\";function r(t,e){var n={_topLevelWrapper:t,_idCounter:1,_ownerDocument:e?e.nodeType===i?e:e.ownerDocument:null,_node:e,_tag:e?e.nodeName.toLowerCase():null,_namespaceURI:e?e.namespaceURI:null};return n}var i=(n(97),9);t.exports=r},function(t,e,n){\"use strict\";var r=n(3),i=n(20),o=n(4),a=function(t){this._currentElement=null,this._hostNode=null,this._hostParent=null,this._hostContainerInfo=null,this._domID=0};r(a.prototype,{mountComponent:function(t,e,n,r){var a=n._idCounter++;this._domID=a,this._hostParent=e,this._hostContainerInfo=n;var u=\" react-empty: \"+this._domID+\" 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c=u.querySelectorAll(\"input[name=\"+JSON.stringify(\"\"+i)+'][type=\"radio\"]'),p=0;p<c.length;p++){var h=c[p];if(h!==o&&h.form===o.form){var d=l.getInstanceFromNode(h);d||a(\"90\"),f.asap(r,d)}}}return n}var a=n(1),u=n(3),c=n(160),s=n(86),l=n(4),f=n(12),p=(n(0),n(2),{getHostProps:function(t,e){var n=s.getValue(e),r=s.getChecked(e);return u({type:void 0,step:void 0,min:void 0,max:void 0},e,{defaultChecked:void 0,defaultValue:void 0,value:null!=n?n:t._wrapperState.initialValue,checked:null!=r?r:t._wrapperState.initialChecked,onChange:t._wrapperState.onChange})},mountWrapper:function(t,e){var n=e.defaultValue;t._wrapperState={initialChecked:null!=e.checked?e.checked:e.defaultChecked,initialValue:null!=e.value?e.value:n,listeners:null,onChange:o.bind(t),controlled:i(e)}},updateWrapper:function(t){var e=t._currentElement.props,n=e.checked;null!=n&&c.setValueForProperty(l.getNodeFromInstance(t),\"checked\",n||!1);var r=l.getNodeFromInstance(t),i=s.getValue(e);if(null!=i)if(0===i&&\"\"===r.value)r.value=\"0\";else if(\"number\"===e.type){var o=parseFloat(r.value,10)||0;(i!=o||i==o&&r.value!=i)&&(r.value=\"\"+i)}else r.value!==\"\"+i&&(r.value=\"\"+i);else null==e.value&&null!=e.defaultValue&&r.defaultValue!==\"\"+e.defaultValue&&(r.defaultValue=\"\"+e.defaultValue),null==e.checked&&null!=e.defaultChecked&&(r.defaultChecked=!!e.defaultChecked)},postMountWrapper:function(t){var e=t._currentElement.props,n=l.getNodeFromInstance(t);switch(e.type){case\"submit\":case\"reset\":break;case\"color\":case\"date\":case\"datetime\":case\"datetime-local\":case\"month\":case\"time\":case\"week\":n.value=\"\",n.value=n.defaultValue;break;default:n.value=n.value}var r=n.name;\"\"!==r&&(n.name=\"\"),n.defaultChecked=!n.defaultChecked,n.defaultChecked=!n.defaultChecked,\"\"!==r&&(n.name=r)}});t.exports=p},function(t,e,n){\"use strict\";function r(t){var e=\"\";return o.Children.forEach(t,function(t){null!=t&&(\"string\"==typeof t||\"number\"==typeof t?e+=t:c||(c=!0))}),e}var i=n(3),o=n(26),a=n(4),u=n(162),c=(n(2),!1),s={mountWrapper:function(t,e,n){var i=null;if(null!=n){var o=n;\"optgroup\"===o._tag&&(o=o._hostParent),null!=o&&\"select\"===o._tag&&(i=u.getSelectValueContext(o))}var a=null;if(null!=i){var c;if(c=null!=e.value?e.value+\"\":r(e.children),a=!1,Array.isArray(i)){for(var s=0;s<i.length;s++)if(\"\"+i[s]===c){a=!0;break}}else a=\"\"+i===c}t._wrapperState={selected:a}},postMountWrapper:function(t){var e=t._currentElement.props;if(null!=e.value){a.getNodeFromInstance(t).setAttribute(\"value\",e.value)}},getHostProps:function(t,e){var n=i({selected:void 0,children:void 0},e);null!=t._wrapperState.selected&&(n.selected=t._wrapperState.selected);var o=r(e.children);return o&&(n.children=o),n}};t.exports=s},function(t,e,n){\"use strict\";function r(t,e,n,r){return t===n&&e===r}function i(t){var e=document.selection,n=e.createRange(),r=n.text.length,i=n.duplicate();i.moveToElementText(t),i.setEndPoint(\"EndToStart\",n);var o=i.text.length;return{start:o,end:o+r}}function o(t){var e=window.getSelection&&window.getSelection();if(!e||0===e.rangeCount)return null;var n=e.anchorNode,i=e.anchorOffset,o=e.focusNode,a=e.focusOffset,u=e.getRangeAt(0);try{u.startContainer.nodeType,u.endContainer.nodeType}catch(t){return null}var c=r(e.anchorNode,e.anchorOffset,e.focusNode,e.focusOffset),s=c?0:u.toString().length,l=u.cloneRange();l.selectNodeContents(t),l.setEnd(u.startContainer,u.startOffset);var f=r(l.startContainer,l.startOffset,l.endContainer,l.endOffset),p=f?0:l.toString().length,h=p+s,d=document.createRange();d.setStart(n,i),d.setEnd(o,a);var v=d.collapsed;return{start:v?h:p,end:v?p:h}}function a(t,e){var n,r,i=document.selection.createRange().duplicate();void 0===e.end?(n=e.start,r=n):e.start>e.end?(n=e.end,r=e.start):(n=e.start,r=e.end),i.moveToElementText(t),i.moveStart(\"character\",n),i.setEndPoint(\"EndToStart\",i),i.moveEnd(\"character\",r-n),i.select()}function u(t,e){if(window.getSelection){var n=window.getSelection(),r=t[l()].length,i=Math.min(e.start,r),o=void 0===e.end?i:Math.min(e.end,r);if(!n.extend&&i>o){var a=o;o=i,i=a}var u=s(t,i),c=s(t,o);if(u&&c){var f=document.createRange();f.setStart(u.node,u.offset),n.removeAllRanges(),i>o?(n.addRange(f),n.extend(c.node,c.offset)):(f.setEnd(c.node,c.offset),n.addRange(f))}}}var c=n(6),s=n(405),l=n(172),f=c.canUseDOM&&\"selection\"in document&&!(\"getSelection\"in window),p={getOffsets:f?i:o,setOffsets:f?a:u};t.exports=p},function(t,e,n){\"use strict\";var r=n(1),i=n(3),o=n(82),a=n(20),u=n(4),c=n(56),s=(n(0),n(97),function(t){this._currentElement=t,this._stringText=\"\"+t,this._hostNode=null,this._hostParent=null,this._domID=0,this._mountIndex=0,this._closingComment=null,this._commentNodes=null});i(s.prototype,{mountComponent:function(t,e,n,r){var i=n._idCounter++,o=\" react-text: \"+i+\" \";if(this._domID=i,this._hostParent=e,t.useCreateElement){var s=n._ownerDocument,l=s.createComment(o),f=s.createComment(\" /react-text \"),p=a(s.createDocumentFragment());return a.queueChild(p,a(l)),this._stringText&&a.queueChild(p,a(s.createTextNode(this._stringText))),a.queueChild(p,a(f)),u.precacheNode(this,l),this._closingComment=f,p}var h=c(this._stringText);return t.renderToStaticMarkup?h:\"\\x3c!--\"+o+\"--\\x3e\"+h+\"\\x3c!-- /react-text --\\x3e\"},receiveComponent:function(t,e){if(t!==this._currentElement){this._currentElement=t;var n=\"\"+t;if(n!==this._stringText){this._stringText=n;var r=this.getHostNode();o.replaceDelimitedText(r[0],r[1],n)}}},getHostNode:function(){var t=this._commentNodes;if(t)return t;if(!this._closingComment)for(var e=u.getNodeFromInstance(this),n=e.nextSibling;;){if(null==n&&r(\"67\",this._domID),8===n.nodeType&&\" /react-text \"===n.nodeValue){this._closingComment=n;break}n=n.nextSibling}return t=[this._hostNode,this._closingComment],this._commentNodes=t,t},unmountComponent:function(){this._closingComment=null,this._commentNodes=null,u.uncacheNode(this)}}),t.exports=s},function(t,e,n){\"use strict\";function r(){this._rootNodeID&&l.updateWrapper(this)}function i(t){var e=this._currentElement.props,n=u.executeOnChange(e,t);return s.asap(r,this),n}var o=n(1),a=n(3),u=n(86),c=n(4),s=n(12),l=(n(0),n(2),{getHostProps:function(t,e){return null!=e.dangerouslySetInnerHTML&&o(\"91\"),a({},e,{value:void 0,defaultValue:void 0,children:\"\"+t._wrapperState.initialValue,onChange:t._wrapperState.onChange})},mountWrapper:function(t,e){var n=u.getValue(e),r=n;if(null==n){var a=e.defaultValue,c=e.children;null!=c&&(null!=a&&o(\"92\"),Array.isArray(c)&&(c.length<=1||o(\"93\"),c=c[0]),a=\"\"+c),null==a&&(a=\"\"),r=a}t._wrapperState={initialValue:\"\"+r,listeners:null,onChange:i.bind(t)}},updateWrapper:function(t){var e=t._currentElement.props,n=c.getNodeFromInstance(t),r=u.getValue(e);if(null!=r){var i=\"\"+r;i!==n.value&&(n.value=i),null==e.defaultValue&&(n.defaultValue=i)}null!=e.defaultValue&&(n.defaultValue=e.defaultValue)},postMountWrapper:function(t){var e=c.getNodeFromInstance(t),n=e.textContent;n===t._wrapperState.initialValue&&(e.value=n)}});t.exports=l},function(t,e,n){\"use strict\";function r(t,e){\"_hostNode\"in t||c(\"33\"),\"_hostNode\"in e||c(\"33\");for(var n=0,r=t;r;r=r._hostParent)n++;for(var i=0,o=e;o;o=o._hostParent)i++;for(;n-i>0;)t=t._hostParent,n--;for(;i-n>0;)e=e._hostParent,i--;for(var a=n;a--;){if(t===e)return t;t=t._hostParent,e=e._hostParent}return null}function i(t,e){\"_hostNode\"in 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i=n(345),o=n(347),a=n(349),u=n(351),c=n(352),s=n(355),l=n(357),f=n(360),p=n(4),h=n(362),d=n(370),v=n(368),g=n(371),m=n(375),y=n(376),_=n(381),b=n(386),x=n(387),w=n(388),C=!1;t.exports={inject:r}},function(t,e,n){\"use strict\";var r=\"function\"==typeof Symbol&&Symbol.for&&Symbol.for(\"react.element\")||60103;t.exports=r},function(t,e,n){\"use strict\";function r(t){i.enqueueEvents(t),i.processEventQueue(!1)}var i=n(22),o={handleTopLevel:function(t,e,n,o){r(i.extractEvents(t,e,n,o))}};t.exports=o},function(t,e,n){\"use strict\";function r(t){for(;t._hostParent;)t=t._hostParent;var e=f.getNodeFromInstance(t),n=e.parentNode;return f.getClosestInstanceFromNode(n)}function i(t,e){this.topLevelType=t,this.nativeEvent=e,this.ancestors=[]}function o(t){var e=h(t.nativeEvent),n=f.getClosestInstanceFromNode(e),i=n;do{t.ancestors.push(i),i=i&&r(i)}while(i);for(var o=0;o<t.ancestors.length;o++)n=t.ancestors[o],v._handleTopLevel(t.topLevelType,n,t.nativeEvent,h(t.nativeEvent))}function 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       "<IPython.core.display.HTML object>"
      ]
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    }
   ],
   "source": [
    "import shap\n",
    "import xgboost\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "from sklearn.model_selection import train_test_split\n",
    "import matplotlib.pylab as pl\n",
    "\n",
    "# print the JS visualization code to the notebook\n",
    "shap.initjs()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Import the column database"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>Reference</th>\n",
       "      <th>Specimen</th>\n",
       "      <th>Failure</th>\n",
       "      <th>a/D</th>\n",
       "      <th>P/fcAg</th>\n",
       "      <th>ρlfy/fc</th>\n",
       "      <th>ρsfyh/ft</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>Davey 1975</td>\n",
       "      <td>No. 1</td>\n",
       "      <td>1</td>\n",
       "      <td>5.50</td>\n",
       "      <td>0.055265</td>\n",
       "      <td>0.288491</td>\n",
       "      <td>0.368768</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>No. 2</td>\n",
       "      <td>1</td>\n",
       "      <td>3.50</td>\n",
       "      <td>0.052724</td>\n",
       "      <td>0.273751</td>\n",
       "      <td>0.360191</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>No. 3</td>\n",
       "      <td>1</td>\n",
       "      <td>6.50</td>\n",
       "      <td>0.054284</td>\n",
       "      <td>0.283370</td>\n",
       "      <td>0.400623</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>Munro et al. 1976</td>\n",
       "      <td>No. 1</td>\n",
       "      <td>1</td>\n",
       "      <td>5.46</td>\n",
       "      <td>0.003187</td>\n",
       "      <td>0.195795</td>\n",
       "      <td>1.213041</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>Ng et al. 1978</td>\n",
       "      <td>No. 2</td>\n",
       "      <td>1</td>\n",
       "      <td>5.36</td>\n",
       "      <td>0.011396</td>\n",
       "      <td>0.222759</td>\n",
       "      <td>1.289995</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0          Reference Specimen  Failure   a/D    P/fcAg   ρlfy/fc  \\\n",
       "0           1         Davey 1975    No. 1        1  5.50  0.055265  0.288491   \n",
       "1           2                NaN    No. 2        1  3.50  0.052724  0.273751   \n",
       "2           3                NaN    No. 3        1  6.50  0.054284  0.283370   \n",
       "3           4  Munro et al. 1976    No. 1        1  5.46  0.003187  0.195795   \n",
       "4           5     Ng et al. 1978    No. 2        1  5.36  0.011396  0.222759   \n",
       "\n",
       "   ρsfyh/ft  \n",
       "0  0.368768  \n",
       "1  0.360191  \n",
       "2  0.400623  \n",
       "3  1.213041  \n",
       "4  1.289995  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data1 = pd.read_excel('CircularColumnDatabase.xlsx', sheet_name='database')\n",
    "data1.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
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       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Failure</th>\n",
       "      <th>a/D</th>\n",
       "      <th>P/fcAg</th>\n",
       "      <th>ρlfy/fc</th>\n",
       "      <th>ρsfyh/ft</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>5.50</td>\n",
       "      <td>0.055265</td>\n",
       "      <td>0.288491</td>\n",
       "      <td>0.368768</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>3.50</td>\n",
       "      <td>0.052724</td>\n",
       "      <td>0.273751</td>\n",
       "      <td>0.360191</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>6.50</td>\n",
       "      <td>0.054284</td>\n",
       "      <td>0.283370</td>\n",
       "      <td>0.400623</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>5.46</td>\n",
       "      <td>0.003187</td>\n",
       "      <td>0.195795</td>\n",
       "      <td>1.213041</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>5.36</td>\n",
       "      <td>0.011396</td>\n",
       "      <td>0.222759</td>\n",
       "      <td>1.289995</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Failure   a/D    P/fcAg   ρlfy/fc  ρsfyh/ft\n",
       "0        1  5.50  0.055265  0.288491  0.368768\n",
       "1        1  3.50  0.052724  0.273751  0.360191\n",
       "2        1  6.50  0.054284  0.283370  0.400623\n",
       "3        1  5.46  0.003187  0.195795  1.213041\n",
       "4        1  5.36  0.011396  0.222759  1.289995"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data=data1.loc[:, 'Failure':'ρsfyh/ft']\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Generate X and y data\n",
    "X = data.loc[:, data.columns != 'Failure']\n",
    "y=data['Failure']\n",
    "#X.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Split the data into training and test\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3, random_state=0)\n",
    "\n",
    "from sklearn.preprocessing import MinMaxScaler\n",
    "scaler = MinMaxScaler()\n",
    "X_train = scaler.fit_transform(X_train)\n",
    "X_test = scaler.transform(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy of RF classifier on training set: 0.99\n",
      "Accuracy of RF classifier on test set: 0.82\n"
     ]
    }
   ],
   "source": [
    "from sklearn.ensemble import RandomForestClassifier\n",
    "from sklearn.datasets import make_classification\n",
    "RF1 = RandomForestClassifier(n_estimators= 200, min_samples_split= 5, min_samples_leaf= 1, max_depth=70, bootstrap= 'False')\n",
    "RF1.fit(X_train, y_train)\n",
    "print('Accuracy of RF classifier on training set: {:.2f}'\n",
    "     .format(RF1.score(X_train, y_train)))\n",
    "print('Accuracy of RF classifier on test set: {:.2f}'\n",
    "     .format(RF1.score(X_test, y_test)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[152   1   0]\n",
      " [  1  30   0]\n",
      " [  0   0  33]]\n"
     ]
    }
   ],
   "source": [
    "# Confusion matrix fr training set\n",
    "y_pred_train = RF1.predict(X_train)\n",
    "from sklearn.metrics import confusion_matrix\n",
    "confusion_matrix = confusion_matrix(y_train, y_pred_train)\n",
    "print(confusion_matrix)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[57  6  1]\n",
      " [ 1 13  5]\n",
      " [ 1  3  7]]\n"
     ]
    }
   ],
   "source": [
    "# Confusion matrix fr test set\n",
    "y_pred_test = RF1.predict(X_test)\n",
    "from sklearn.metrics import confusion_matrix\n",
    "confusion_matrix = confusion_matrix(y_test, y_pred_test)\n",
    "print(confusion_matrix)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Explain the SHAP model's predictions on the entire dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_shap = scaler.transform(X)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_shap = pd.DataFrame(X_shap, columns = X.columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x223.2 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "explainer = shap.TreeExplainer(RF1)\n",
    "shap_values = explainer.shap_values(X_shap)\n",
    "shap.summary_plot(shap_values, X_shap)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### The bar plot shows the importance lists of the most significant variables for the failure modes in descending order"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Individual value plot"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "shap_value[0] corresponds to class zero, shap_value[1] corresponds to class one,..."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Features that push the prediction higher (to the right) are shown in red, and those pushing the prediction lower are in blue."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "<div id='iITUWRCS4ORLEOCKNQDOM'>\n",
       "<div style='color: #900; text-align: center;'>\n",
       "  <b>Visualization omitted, Javascript library not loaded!</b><br>\n",
       "  Have you run `initjs()` in this notebook? If this notebook was from another\n",
       "  user you must also trust this notebook (File -> Trust notebook). If you are viewing\n",
       "  this notebook on github the Javascript has been stripped for security. If you are using\n",
       "  JupyterLab this error is because a JupyterLab extension has not yet been written.\n",
       "</div></div>\n",
       " <script>\n",
       "   if (window.SHAP) SHAP.ReactDom.render(\n",
       "    SHAP.React.createElement(SHAP.AdditiveForceVisualizer, {\"outNames\": [\"output value\"], \"baseValue\": 0.7047004608294931, \"outValue\": 0.9130000000000003, \"link\": \"identity\", \"featureNames\": [\"a/D\", \"P/fcAg\", \"\\u03c1lfy/fc\", \"\\u03c1sfyh/ft\"], \"features\": {\"0\": {\"effect\": 0.27899441500311206, \"value\": 0.49489795918367346}, \"1\": {\"effect\": 0.0049709566888754535, \"value\": 0.07895018534438693}, \"2\": {\"effect\": 0.005091961508891314, \"value\": 0.32213819957899353}, \"3\": {\"effect\": -0.08075779403037162, \"value\": 0.09788152790783837}}, \"plot_cmap\": \"RdBu\", \"labelMargin\": 20}),\n",
       "    document.getElementById('iITUWRCS4ORLEOCKNQDOM')\n",
       "  );\n",
       "</script>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Single value explainer\n",
    "shap.force_plot(explainer.expected_value[0], shap_values[0][0,:], X_shap.iloc[0,:])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Thr selected column corresponds to the flexural mode of failure. The predicted value (0.30) is higher than the base value.\n",
    "\n",
    "#### ρvfyv/ft and ρlfy/fc push the value down"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x223.2 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "shap.decision_plot(explainer.expected_value[0], shap_values[0][0,:], X_shap.iloc[0,:])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Entire value plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "<div id='iZ8KYNIL12I5W8PXGFDJH'>\n",
       "<div style='color: #900; text-align: center;'>\n",
       "  <b>Visualization omitted, Javascript library not loaded!</b><br>\n",
       "  Have you run `initjs()` in this notebook? If this notebook was from another\n",
       "  user you must also trust this notebook (File -> Trust notebook). If you are viewing\n",
       "  this notebook on github the Javascript has been stripped for security. If you are using\n",
       "  JupyterLab this error is because a JupyterLab extension has not yet been written.\n",
       "</div></div>\n",
       " <script>\n",
       "   if (window.SHAP) SHAP.ReactDom.render(\n",
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       "    document.getElementById('iZ8KYNIL12I5W8PXGFDJH')\n",
       "  );\n",
       "</script>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "shap.force_plot(explainer.expected_value[1], shap_values[0][:len(X_shap),:], X_shap.iloc[:len(X_shap),:])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Importance plots for various modes of failure"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### In the following plots, the horizontal location shows whether the effect of that value is associated with a higher or lower prediction."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x223.2 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Importance of Shap value for Class 0 prediction\n",
    "import matplotlib.pyplot as plt\n",
    "plt.rcParams[\"font.family\"] = \"Times New Roman\"\n",
    "plt.rcParams.update({'font.size': 20})\n",
    "shap.summary_plot(shap_values[0], X_shap,  show=False)\n",
    "#plt.savefig('Figure6_flexure.eps',format='eps', dpi=1000)\n",
    "\n",
    "#beingsaved.savefig('destination_path.eps', format='eps', dpi=1000)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Class 0 corresponds to flexure mode of failure. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x223.2 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Importance of Shap value for Class2\n",
    "shap.summary_plot(shap_values[1], X_shap, show=False)\n",
    "#plt.savefig('Figure6_shear-flexure.eps',format='eps', dpi=1000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x223.2 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Importance of Shap value for Class3\n",
    "shap.summary_plot(shap_values[2], X_shap,   show=False)\n",
    "#plt.savefig('Figure6_shear.eps',format='eps', dpi=1000)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Class 2 corresponds to shear mode of failure. The plot shows that if a/D is high, the model is less inclined to predict shear mode of failure"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Dependance plot"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "SHAP dependence plots shows the marginal effect of a feature  on the expected prediction. The dependence plot helps to see the underlying relation  (e.g., linear, curve, complex,..) of the feature on the outcome. The most dependant variable to the selected variable is shown as a bar on the right side of the axis."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 540x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 540x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 540x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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XxQtLye4ZyZChMbX2bX9lPdbv3K0XLytg77w8Uo45+MW8exzZHZdHEfBZsJbK7WWNlt/0xEpW3WLwJEYw+s2jSTn6wOsQ8AXY9uI6/KU+si8aiCfh4IN/W4pIjaJsg5Ob0JMYgSvC+ePXrXcsR149sD2r1uYiUmvcdLkUESHcdHV1zW17W2s/BQ5tjbrUJcFShK3CAh93/XELRXv9KAVXXZvJ2PHxVfvjRyaTO2MzAK4YNzEDElrkuhHxHjxlfgKAslCe0/CMdF+Rl5U3zoOAxbu7gpW/nsek+VMO+NrLr5rD1ufXArD9tQ1MmHXKAZ+rPYz61xEsv/YH/CU+htx/OMrtjPRUlPjYOGs38RnRZB+a3M61bBuD7huDN6+C0nVF9L56KHFDukb388GQpARCHID16yoo2uusqWUtLFpYQnz/WJ6a5yMrQXHDbaNwRbkpXbOX7IsGEtMrrkWu6/K46HVaL7a8lwNAr6m9GykMyq2qxqNU5MFNA8j7bHvV68IfduMr8nao1mX8sGTGfX5yrfd8FX7evPJHdq91WpzH/3Zol+iKjUyJYvRbx7R3NToYCZZCNFuvPpFERyvKy51A1Kt/NMc8X87OYENve5GHR25rnVmqE56cwPaz+uCKdNHjuB4NlvPERTDyuUmsuvVHIpIiGP7EhIO6bsqxmWx7cR0AiWNTO1SgbEj+xtKqQAmw+vPcLhEsRfNJy1KIA5CWFsHv/tATM7eY7F6RJPSPY+e35VX7f9zWeut6u9wusieH9gc964L+ZF3Qv0WuO2L6RJInpOMv8ZF9cecY40tMgGh/BeVuZwwvI397E0eIriqc5wtLsBRhrXefKHr3cf7IVvosh2e5qoLkuSM7XyJ1l8dFr8sHt3c1WlR07i7OWTqDJRnDSagsZkyMHzi1vaslwpC0LIU4SP815TzyUSk941xcfHIMo7I9TMqEJZfOomR5AX1vGk7m2X0J+C2lu8qJTY3CFSGPEYeFQT1I6+7h2I3fOds3/LJ96yPCVodvWWqtVwFnGWOWtXJ9hNhPfnGAm18uxhcAdgVIjCnn6iOSWHDuV+x825kNu+jn3xA5N56v/7KUXUsLSOwdx5SXjiSue0zjJxetLz4GZt0Hr38PvVLh7EntXSMRpgJh3LIM9db7E2BrzTe01ke0fHWE2F+F1zqBMqikwrn/LJyzu1a55c+sYdfSAgD2bi5hxRsb26qKoik9UuDXUyRQikaF8+LPoQbLPsB8rfUXwZ+vgf+1Yr2EqNKjm5urT3BaiIkxit+c6jwi0u2o7tWFFKRNqp0dJTr5wB8CL/9iI1sy/k5O3AMUP7fwgM8jhAidrfMTTkIds1wMPAmU1njvwJ+8FqKZfnt6HNeeHEukByLczh3nqOcnEZkaRfHyAvreOJz0U3tSlF/Jpi930P2wFIaf36/B81X8sBXlVkTqrHr35187k8Au5+Oef+VHxP1yJCqq+UP81lqqU1cKIRoTbq3JmkL99t+PEyiHA15jzCqt9dzWq5YQ+4uLqv1FckW6GfbouFrvjb1xOGNvHN7oefZcP5Pixw0ACb+fRPK9x+5XRrn3XctHD99KiD8fRvUG8yC4mu6Q2TE/j0+vn0vlXi/jbxnByAsHNHlMlxYIwKZdkJ7ojHHWJ78IFm+CCYMhWlLHdUbhHCxD7YbNBFbgtDAXaK3n4WR4FyIseZfksmvkP8nt8TClzy+oet9aS/GT86u2i/85v77DSXn6FNz9kkmPzCGCCpTPDws2wG9eDOn6s+5dQtnuCvyVAWbfv4SKvZX7F5qzCv7xIazauv++rsTnhyn3Qf+roM8V8OO6/ct8tRTSL4Jj/whpv4KdBW1eTdH6wrkbNtRgeT/wZyDeGBMLnAVc1Wq1EiKoMM+Lt6L5yQf2XvMhvmW7COwopvDy9wjscZKhK6XwDEqpKhcxOKXe46Mm9SR7/TXETKqTvSevKKTruzw17pBdav8VST5dCEfcDtc9C2NvhbVd+EH971fCh8GblvxieKie6RC3vAj7lrgqqYA/v9l29RNtpjNM8PnWGPOqMaYUwBiTAzScXVqIgxQIWP71wCbuumwld12+kpx1ja/8Ude+ZaKck1lsjem06R/8nNgLRxH3f4eQ+vbPGj5HwFL21/+DfWOVCTHw0EUhXf/IPx5KUr94olMiOequ0UTG10lb9/ECp+sRoKgMvl0e0nk7pbQEqDmum1FPwvG67/WRpa46o84QLFO11lXjm1rrE4HjW6dKQsCm1aUsmbMXgNIiP1/M2Nms4+PvPx6fy00A2JmQASnRVfs8/ZJJffF0Up6fgqdnYr3HF+2q4F+/+IEnb9zIW5f8Ft/KJ2DvK5BWf/m60kYk8/OPTuDCWacw5Kw++xc4clj166gIGDeoOb9e5zKiNzxzFYwdCBccBXefv3+ZN2+G4b0gNgomHwa3ntk2dSuvhG+WwYbcpsvOXQML1h/QZawNt05HUVeDE3y01icDe4wxc4H/Aou11n6c8UuL0xUrRKuIja+dyq7ox104TzCFZuXvDD0C23Hho6woiR9P+oyxn50U8szUhW/lsGezMxs2Z0EhazZlM2xI08f5KwPsXlZAXPdo4rNiGy545gR4//cwdy2cergTMBqw/LHlrH5qFbE94xh9/+FEpUaR1Ce+wfId0iUnOD8NiY+BZY+2XX0AKrxwzB/ghzUQ4YF3boVTdf1lr3sG/vGR8/qP58Kfzwv5MiueWMGS+xajlOLwhzT9z2uZPMMdUTjfMjQ2G/Yh4ILg69XAGOA4nNbo18aY0AZvhDgA3XtGM2RPHjmRcUSXV5Kybhve4kOJqNud2YC+i74gmR0AJNkC3lueycJh/yOpXzxTXz+KqKTGZ1NGxtYO1lFxTU8c91cGeP+i78idn4870sVJT4yn10+6N3zAqbrhP75Bu+buZOlflgBQuaeSD87+Cm+kmwm3juCQi7twa7QtmLVOoATw+uCZz+r/9woE4MmZ1dtPfBRysLTWsuSexc5rLOameV08WIZX12tNjXXDPmeMWRx8fbkxptwY86Ex5n1jTJHW+si2qKDouob3djNq8XoGrd5CUnYMniYCVqDSx84Pt1C6oYiE1Ooxyki8FAcbeYUbipl59Zwmr+2bs52Y4nI8Xh+9+0bRS6ew+LNdrPw+v6rLbP6Tq3j3gm+Z9+hyrLXsWrqH3Pn5gBM4l7++4QB/82pbP6o9UzYyOBa78Nk1B33uDqWkHH72APS5HG5+oW2u2Tvd6SLfZ1ADS7W5XNC/e9Pl6mH9ddpS4dy0agPhPBu2sb8+RVrrV4FyYITWemSNfW5gHDCs3iOFaAHjHhvPisdW4Cv2MuSaoY12ofrKfXzT6z94851HNIacfjS9c/6DC8vS5CFURFSPWZbkltc6tnBTMS63IqGnkxko4Auw9d0c0gIBLIqIslKevHQBhble59xHdEOPj8c8ugKAHT/mkdQnnh5j03BFuAgEA1piCyxG3fvMPqx+anX17xl8/jO+RyNdvJ3Rw+/CjOBNzt/eg+NGNdkqP2i90uC938HTn8CAzMZbix/eAX96AyLc9Y+5NsDlcRGZHEllgfO5jcnu2rmMw7ll2WCwNMY8p7WeAxwKxABf19itgNBmOrQCrfU1QCWQBTxqjCmosa8PzmMunxtjXmqnKoqDZAMB1J/fZejMFbiOGYQne0yj5bc+s6YqUAKs/Nzyff+z8Fg/hZGJuDyKgM+5Vx11UXWCgHmPLmfBk6tBwcTbRjLKtxF17bMMihiGjwgUAQJxWaxfGUtqWQWVkR52zsjju5m1O2VKcstJyI7lpCfGs+L1DST2imsyOUIoUg5JQT+sWfnESiIzovFmxOCJ8jD+NyMO+twdSkntGxyKy+sv19JOHO38NGVgD3j5xgO6xGkLp7D0/qW4o1yM+M3Ipg/oxDpksAQIrjKyTGu9wRgzu+Y+rfVnrVqzBmitxwDjjTEXBruC7wR+vW+/MWaT1nobTutXdFCB1wz+v38BgH/5dtTonngua7jnP3ZQgtN1o6Ai1k1llItSVyTW7QS1wWf1ZsApPYlKiiBtWDLgPBqy8Jlgd6aFBU+tZti8l8n39ybWG82W+FTyYhJgq5e4eGeyj8fnB6C8ovra8VkxDJ7aC4C4jGgSe8WR2DsOd2TLLBHW/xcD6P+LLp4B6IbT4N15sHIrnDwazhzf3jVqMZ4oD6PvDCEgdwGtt5z7wQsp3V3dQBl8b0vLVyckU4F9S4UtBF6iRrAMqiddiuhIbH6dx3jzS/cr4yv2svKmeZSuKaLX5YOJObkH2xfkVw3Ex5d6KekWTcqQRCbdfgieqNr3T8qliE2PpmS78wxnXPdo9gSyKSeJGL+PAYW57I2MoSgyqsF6Dprai4E/zSauewylu8t5b9q3VBb5AKgorGTM1UMP/H+CqJaVAiseh+KyhtPhiQ7P1k3eEUY64uLPmcC84OtynK7YZtFaXw5cDpCZmdlyNRMtxj1tPP7nZ2MXbkEN74H7ktpLO5VvLWXd3YvY+txaAAq+30nMZX1Q1ZntcAUg4LMUbS2lssi7X7AEmPzUBOY+vBxXhGLCrSMpnz8fcpxmowtw2wBRlT7KY2pM9PAAPkDBmv/msPbdHE594QhcHldVoASqlgsTLUgCZadmwzdWdshgmQvsm92QADTvaXXAGDMdmA4wbdq0cJt0JQCVHEukuQ12FkFGAirYnRoIBPh20DuUb6zd8rR+S+rCpWyKSK+aMepR5UAUFQVeZt+3hOP/Nna/66QOSeKn0ydWbUdddQi7fj8Hi5s9UdHE2CKG7ipgjTub/F7pZP8knaPvOZzFz69h3iPOBB8bgB0L8hk1bQBJfeIo3OTUrd9Jzb6PE6JL6xQtS631aCAZmAOMMMb82Gq1atwM4Prg61HAu1rrVJwECuHc5S2aSbld2PTqQAmw4uof9guUACnHZzJo/B42P7ed7TFZJFcWkuTbQx5OmrSAP7SPRvRvTyD7m3kEPl5Erwofhd5syseO4eT/nFkr20+vo7sz/5+r8FcGcEUosiekExHn4YzXjybn21wSesaSOSb1IP8PCNG12JYZ5m8VIQVLrfVtODNM3zTGfKW1Hqy1nmCMeaJ1q7c/Y8wCrfVyrfWlQG/gDuBF4D5gjta6O3AIkKa1fscYU9jWdRQHz1pL/sXvU/LiYjyDUsiYeT6evsmUba4dKN2JEUz4/qfEDUlEuV1MXno/9uv/4R3cm1e8E6DET0SsmwmhzjJ0uXB9dHvVuGdyA8XShiUz9c2j2T53N93HpJI+0ikZ3S2SQaf3OrBfWoguzro7fsvySJwluSYHtz8FlgJtHiwBjDEP1nnr9Br7cpFUfB1exdebKfmXkxPDtzqfwnu+I/XZ0xh092HkfbqNSo+LvO7RRPdLoHCvl/h9rc93bkMBkcAFxV4KNxST1C9+/0TmLSB1aBKpQ+tJ+i2EOCCBMO6GDbXROzPYQts3vnccIc441VrH1tlOqJmUXYj6qLozV4MrfyQdnsoxW8+hZHwaldEe9m4v49Pr59abiDoyPoL0Ud1aJVAKIVqeddX+CSehVmez1vpx4Hit9V+BZ4E/hHjspXW2S4BHQjxWdFFRE3uS+PtJuLrHUZyVwYKXdvPt0Hfwl1USlRFT6w7UW+LD+mSelhAdnXWpWj/hJNTnLP+ntV4GnAhEAJOMMUsbKq+1VsBlwLlAb6311Bq7o4H6V9wVoobke4+lonsi229cgE8F8K0p4ou+73DoJycy7uYRfHXbfAK+AONvHo4rIsxuQ4UQzdYpHh0xxqwF1gJoraO01r8yxrzYQPG3gfdxWpAnAO/U2OenOqmAEA27+mm6PzmTFFwsYSy7VA98eRW8+8tvmfrm0fzqh1OwfktkgnSzCtEZhFtrsqZQZ8MG2D8J/FacWaj1KTPGPL/vWGNMzbyyaK1DT8svOq3iZXvY8dI6YgYkknXpICipIDBrPap/Gq5oFytf3MTi7ucCkFm+HVsEJXEeAl5L7oL8qrR1QgjR2kJtWZ5njHlz34bWeizQrZHyS7TWQ4AyYKLWumaXrQtnncx7m1tZ0XlU7irnx598hG+PM0/Mt6WIzBkfUbF0N35XBFG/P56lCSMhuNLIjugeeKOhJDkad2RaE+8AACAASURBVJSLHmPT2rP6QohWEAjfhmXIY5Zv1tmep7X+DvikgUNeAR4GRgOpwC9r7FM4KeskWHZhpasKqwIlQOXMVZQuLaCIdAhAyT1zURkDqLkIwcQXjqA4t4LsiemkDGq3RW+EEK2kM3TD/rHOW/2ABpeAN8bk4EzuQWt9szHm4Trnk+cgu7j4Q7oR0z+BsvVFACRMHUT53BVVnf0B3MRVlLE3xllNRClF3xOzcXlkIo8QnVU4T/AJ9S/PUTj3+Pt+lUU4iQrqpbU+W2sdDVA3UAbfm9HMeopOJlDup/sv+9P71pGM+WoymbeNJXJKzbXELQGXcy+ncGLouv9taI+qCiHaiFWq1k84CXXM8mJjzOaab2itG0v/vwS4LlhmPvCxMcbXSHnRhVTuLOP7Pv8hUO6sDRmRGkW3ozNJeed8XLd9wZ7H5+IpD+Bz105MsPWL7Qz6WRdf11GITqxDjllqrY+qs923TpHJwO/rO9YYswp4MHjcGODWYNae74AvjTHyBHkXtvW5NVWBEmDrP1fR99ZRKJciqo+fhPI8yuhG3727WJOciV+5sEqRPklW8RCiM+uoY5b78q/uv+quYwANBMuajDHzcVqXaK1/Avwx+DjJ3c2pqOg8EsfVnska3T++6nXh4q2kso1K4kiuhF7e7azs2Zus4/ow9Jw+bV1VIUQbCucxy8aC5fXGmB8a2qm1bvYS8MaYb4FvtdZHNPdY0TkUVVjuKE2jx1kjmTR7Pd0GJ3Do+ydU7U+4+GjK//0ZWeVL2JSYzqKX7+WyU+QxESG6gtYap1RKRQKTcCam5gKzrLUh5Tffp8Fg2USgjMN5LGRlUxfQWv8SuAHnucx9E4oygPgGDxKd1s0fV/LMj34YMZzoQ4ez4dcxeGKrvyDx4/uTu+gxPpu5GZPSl7jKSFZs9TEsW3LvC9HZtcaYpVLqQpxHGVOonqS6Uyl1pbX2v6GeJ9RHR64EbsRZ+ajmca+HcPhfgd8CW3AmNSqcVUtEF7SxoHq4utwHO4otmQm1vyHdB6eyY1MMr7xXCpTx+uxyvri9G+mJ8tiIEJ1ZS7cslVKn4Cz88RTwHpAD9AROAV5WSp1grZ0TyrlCvV0fB0wFTgPeAnoBoQ4gzTDGvFzzDa312hCPFZ3MdeM9fL2xkrQ9e3njk//S79W9VPz2aKIuG1+r3MJNPpS1WKXYW2ZZv9MvwVKITq4VxiyvAk601tZMuboS+Ewp9RZwM3BOKCcKNVhuNMas1FqPBFzGmO+01n/BydSzH631NKqbuxu01vcDy2sUOQa4OMRri05kylAPKy71Uz7xdbJytmOBsivfIeKkwbj6OBkUfRV+Jn68CL00j5zkBL47YRTDs92Nn1gI0eEFWn7MMqdOoKxirZ2tlNoS6olCDZYxWuutOK3Jz7TWGTSe0GAakI+TG3afmhl/Dgm1gqLzKXxvI9H5NT4aAYstqR5rX/tuDt6leQD0Kiji3h57SIjJaOtqCiHaWCu0LLc2sX9bqCcKNTfs77TW9xpjfFrrM3DGHGc3csiNxpjlAFrrVGNMXs2dWmt5srwLUy7F0tRedCsvJtrvo+yUUSQPr76XqpvSLiFeWpVCdAUHMmaplIoFZgFTrbUb6+weqJRKoFaW6Vp6h3qdUCf4/A1nkg7GmEJqr0+5n32BMugDrfVdwEf7khEYY9aFWkHR+aQOS2JuTDzvDdB4lOX0vx9fa//AKT3ZOmcXm7/OpcfYVIad16+daiqEaEsHOMHnKqC8gX2/Ai5sYN++TJrXhXKRULthc4AbtNZ+4O26qe+acCXOYyP3a60LgNeMMRubcbzoZLYHOxqsUnhRzJqzl0JfAj/JVvRJUrg8Lo796+HtXEshRFtrbjesUmoa8CYwpYEifwJeAgL17HPjDBmGJNRu2L8DaK0jgZ9prf8EvGGMmRnCsQuDL78Mpr77Rmu9DPgXzkxZb6iVFZ1D5uGpVa839ujG9bszqfgwQHIU/DjNTf/kME7jIYRoM0qpy4HLa7w13Vo7PbjvKGCdtTZHNdwi/cha2+AKDEqpJ0KtS6jdsL2AYuASnCZvAfBNiMcejhPBbwJOAF4AHgGScFqb/w1m9hFdRO+junPsA2PI+XYni0cPpmK780EvqIBPN1mukGApRJdUNzdsMDBOb6D4tUBGMFCOBl5XSk2x1u6qUSZVKXUnzmTTD621S+ucf3eodQu1G3YWkAh8AEwzxsxqrLDWOgHwG2NKgbk43biPA5cZY4qCxbZqrZ8DPiL0ZzZFJ5C/ei/f372YyiIf7s0Kxh4KgEvBYRkSKIXoqpozZmmtPXffa6XUV8BFdQIl1tqPgY+VUlHAqUqpc4BC4H/W2mbNnQk1WP4AXGuM2RFi+fdw7gZeBZ7GyTNb3xJd5cDbIZ5TdBLrPtxCZZHzcRixKIeHTs5mc990TumnGNdDgqUQXVVrrTpira0AZgAzlFLxwFSl1NXABmvtP0I5R6jB8jJjzJ5m1G2ZMebV4Osv6wZKrXVfY8xGY8x6nO5Z0YUk90+otX3+CDdZ4+XxECG6vANMSmCtPabpU6spwNVAFM5MWDfOeGjLBctmBkqALVrrk3H6iY/RWufW2OcCfkaI03VF5zPo9F5UFFSyY2E+vY/uTtb49PaukhAiDLTyepa/BB7FySD3EU6O2MjGDqiptZZyeBJnrcvRQH9geI19ChiBBMsubeSFAxh5oeSmEEJUa60luoJ+sNZ+rJRKBZZZa79WSn2IM+m0Sa0SLI0xBcCtAFrrS40xz9bcr7U+ujWuK4QQouOyqlUXSxiulPoBp2X5gVKqEhgZ6sENBkutdSLwz+DJ3gP+uC8DT3PUDJRaawUkGGPqTWwrOi7/F6sIfLwc16T+bI9MZdsnW0kdk8qACwdidxbh+/272OIKPHdMxjUyq72rK4QIQ63cDXsFMMhaW6aUughnOPCWUA9urGX5D+BIYB5OyqAcGn7epUFa61eAz4A3gO+Avlrre4wxf2vuuUR4CszbhPekf4A/wK6IBD7NOhyf24X9YAtFuysYPvNLAp+sAKDym7VEbbkH5ZLltoQQtbVmN6y11o+zPBfW2s3A35tzfGN/sbKA4caYc4BRwJADrOMuY8wLwA3B62U1cV3RwQTmbQK/k01qXVx3cLmwEW5wuZg7fQ17v9lUXXh7IQRXGNleZPlsnZ/80mZ3WAghOiNV5yeMNNayXBhMKoAxplBrvbjmTq31McaYr0K4xlqtdSrwa+B8Y0y51rp7Uwc1Rmt9DVCJE3gfDY6R7tt3HpCOk4/2BWNMzsFcSzjWvJfD2ndz6DY4kbE3DMcd6WLhxzuZ/Z/tJMYmcUJCAklFRRREJeGNdOOLcOONjkJhmZc2iGO3LALAdeF4VEI0y3YGOPLZcgrKITtRMffyKLJkcWchurRWnuBzUBoLlmdrrfvX2O4ZXJ4LnOdTxgC9QrhGLvAhThful1rrG4CpwG8OoL4E88uON8ZcqLU+ErgTJxCjtc4CLjbGnKS17omTNejMA7mOqLZ7RQFf3vojWMj5dieR8RH0P7MP7z+yHhuA3cCrI47n0A2rKPFEY63FGxMFSmFRrOnehyJPLGMvH0Df2yYA8NpiHwXBdQK27rW8t8rPFWMlWArRlbXymOVBaSxYbgGWUJ2tfVGNfS4gdb8j6jcP2ANcD/wcJ6PPgXbpghNolwVfL8TJKP/r4PZkYB2AMWaL1nqC1tptjPHXPIHWuio5b2Zm5kFUpWso3lrqLGSzb3tbKRVlAWyNPP6VngjWJvcEINbn32+9nIKoeFLOH8W+hMdD0moHxsGpEiiF6Oo6asvyamPM4oZ2aq1nhHiN54HtwOE4k4TGA5fhBM0DkYkTgMFJl5dVZ19+jW0/kBG8fhVjTFVy3mnTpsmA2T47C+CR9yEqAm46HRJi2LVkD1//YUFVkYh4D0PP7UtGv1hGn5zOwpm7iI5zk+Lz4QdSsqIJrCgkJqqCsrgoUJDYzc2kO8aQ1De+6jzTRnvYVmyZvy3AqYPdHNtfMvgI0dV1yGDZWKAM6kXt1maD1zDGXFBj+2utdY9QKteAXCA2+DoB2FlnX83nZmJwWrUiFCffDQud1WwKP1xO0g9/Zt6jK6jYU72K2k+fmUjGqG4ATLl5AMdf1pvIaDcELCW5ZeR9l4u5xZCcX0pyfilDrx3GIbcfUusyhRWWE970Y3IVurubM4ZJoBRChHewbHbfl9a6m9b6VuDFEA95q573DmaCzwyczEDgzNJ9V2udqrV2Ae/jZAdCa90bmGOMaWgFbVGT11cVKAHcC9fxxXOb8MRUBzLlgvjuMbUOi02MwBPpwhPtJqlPPD2n9CJpWBIAMZkx9P9lf+p6YanFBBMgmlxnWwghrFK1fsJJyBl8tNYTgCuBc3CeVdkW4qGfaq3fonqMMwVI11pPwelGzTXGXBJqPYwxC7TWy7XWlwK9gTtwAvd9xpg5WuvXgrNlM3CS5opQRHgwPYehtzjPQ67MGMyPH+zkysdHUb6nkpLtZRx62SDis2IbPMWsLwpYvayUIbePZ0JPF7E9Y4mIi9ivXHydtxJCzs4ohBDto9FgqbWOw0k+eyXQA1gKjDbGrNFaDwzlAsaYlcHHOQbjPNJR83YhBshubqWNMQ/Weev0GvtCyvMnavMHLLcdcyFXLZqNz+VmdfpAkmLdJGTHcvrLP2ny+EXzinjlaWcFt3nf7eXq3/VkRD2BEuCikYo52xWfb7Kc0EfxqxHhdQcphGgf4daarKmxdHcPA5cCa3AyHbwO/NoYswbAGLM21IsEZ6OuCP6IMOR2KX41rIDcdWnkxaXiCfg4d2RxyMdv31JRazt3ayUjRtdf1uNSPHuyjFMKIWrrkMESuAdnFmkasMoYU6m1lsGlTmxaxl6Y/Xz1GxPPDvnYw8Yn8Nl7+ZSVBIhPcHOIjm/6ICGEqCGcn7NscIKPMWaPMeYh4HdAqtb6DmCk1toDoLVudvepaFulu8tZ8u91bPgkxOHlsybA0OA/a49ucPFxIV+re1YUdzzUj6tu68nvH+pHWveGByJfXBrgF+/7mb4o0GAZIUTX06En+ARXGvkQ+DCY0edmrXUCzkzUMxo9WLSbisIK/nf+NxTllAIw7qbhjLigP3u3lJDUOw5PTD3/9CkJMP8hWLsD+mZAQsz+ZWr4cVuAx+d4yUpQ/OGYCJJTnJ/GfLwhwEUfO0HytZWW9Fg4c5AkJBBCdNxu2P0YY9YDfw1O/HmqdaokDkZg217yJjyJJyef4Qmp/NBjECjFxi+2s+y1DZRsLyOxTxxnvHoUMalR+58gJgpG9WnyOgVllhP+VV6Vsm5POTw5pelprSvyam8vz4MzB4XymwkhOrtwDpYN3tJrrTMa2meMKSG4uLMIL+X3f0lETj4K6FOUR2aJk2PeE+0mf4+f/IxubCiP5v2/rMJXeeDdoNuKbFWgBFi+M7RzTR2oSAs2WLtFw9mDw/fLIYRoWx21G/YWrfXLDexTwAVIwAw73oLas1IDSnHMX8dQVuRjwRY3BAfQVy4u5aN/bGDKTQMO6DqDUxU/6ePi200BlIKLDgutk6JfsmLpRW4W7LQcmq7oER9eXwghRPsJtwBZU6PBEriZ6uciLbWfkbRIsAw7G9xxRMQnk1pWzObENHbGJTP1jN7sWFcC/95Zq+y2VSW1tnOLApzzSjkrdvoZG+Ele/Ue+vSJ5PqbskhMrP2oh8et+PRXUXy5IUCPBMWhmaGNO+bsteQUwXG9FZHu8P1iCCHaXkcNltcZY57Yt6G1/q0x5q/B1y6cZOgizLyQNIg55x/G8K078LvdTOnrLLSc0TeW/ocnsv7HvVVlhx7Rrdaxf/qskm83Ogu0fEQEpygPvrUVfPzBHs49Pw2Au7/y8uD3XvomK2acF8XkQaE/L/nJxgCnvxOgwg+TsuCLc91EecL3yyGEaFs2jP8cNBYsX6qzXfWMpTEmoLV+rXWqJELl9wVY/nU+ygXDj0rF5VbEjUyncoGXhX17orDcfbuTZdDlVpx/zzC2rihi+9oSUrJjGDg2udb5vP7a568ahQx+gFfuCvDHL5yk6ktyLb/7zMtbP69nklADHpjrBEqAWdtg3g44smdzf2shRGfVUVuW3jrbdX+LuvtFG3vm6iXs2lgGwNx3dnDxYyO58exEdpfsZWuenwuOjaVP9+p/Ypdb0WtkIr1GJtZ7vjuOi+S7TX7W7A5wRLyP3rt89B0SzSmnOi3QuhkpAs1IUWGtZU6NhdIU0DMh9OOFEJ1fRw2WZ1O7dVn3T+NZwCstXiMREuv3s2tDKQQ/XFtXOqnpMpLdTL+hW2OHNqhviouVN8fhD1jcLgXUPs+wdBd3HO3hoe999ElW3HdC489U1lTug5Iat1dpMdA3KXy/GEKIthfooMHyRa31Y1QHyWit9W3B1wpnLUkJlm3AVvqwM35ERUfAGYehlIIrngEObZXrPfidj8d+8DGgm+L1cyPJTqyevHP38ZHcfXzzlwmJiVBcfohi+mLn43TbeElEIISoze7XgRk+GguWTwNvsH+LEsCNs1SXaGXecj+VZz9F9AfznX+IUT1xzbwJ9a5hUlIls/qNA2DUcamNnidUS3ID/O4zpwm4vcjy+8+8vHhW6OOS+wQClju/9DInJ8DUYW6uGR/B0ye5ufwQS2wEDEsN3y+FEKJ9dNRu2PuMMTkN7dRar26F+ogaFn6yk/ceXg+Bwzmmj59JmxbBki0EpjyKe9Jgjv/fdxy2dSlqVC+63faHZp9//cytrPrPJpL6JzDupuF4otxU+GrfG5X7DqzuTxsf93ztHPzZ+gBD01wcP8DN4Znh+2UQQrSvDhks6wuUWusBwCnAImPMN61Zsa5s4w+7+fjv69mV7wcUKMVXg8YxbvMSPDYAS7bC14/BPz4mpdwL1/202dcoWF/E5zcZrN+S8+1OPFFuxt00HJ3t5qqxHp4yPnonKf50bOjjkjVtKqgddDcXyoI1QojGdchgqbXeBqwEnjbGvKG1ngjMBHYDe7TW040xT7dRPbuMkrxyXv3dSvweD7UmICuFX7nw2ADqlxMgLhp+O/XAr5NbjvVXB7CiLSX4fJbVq8r4/Wg3j54SQ8RBJA34vzEenl/gY1cJDElTnDHUTaXfMmONJdYDUwYoZ+xVCCE6gMa6YcuBnxlj9mit3cBzwFLg+OC+Z3DGNUUL2raoEL97/wf93ZGKObdfyeYcHwOOz+InB3md7mNS6D46hdyF+Xhi3Qw9ry+PPLSNZUvLnPR1l2Rw1DH1P2ISiiFpLlZfH8O6PZZhaYrYSMXk//iZudEJ0DeMUTxynCwALYSo1lGTEswwxuwJvr4CGASMNcaUAWitd7R25bqiXod3w+P34/M4/zSRHug/IYXsofF8/uxmAHL+tYX0PrEMPSLlgK/jiXJz2r+PJH9VIXGZMRT5XSxb6pzfWvj6y8KDCpYAyTGKw2OcT39Jpa0KlAAz1lgeCX25TCFEFxDOj440Nn8/HkBr3Qe4B3jGGLOwxv4jW7NiXVV0UiSXPXMofftFMlzH85v3xnPOHwfvt0JIUV7lQV/LHekifVQ3YtOjSUzyEBdX/XHIynIeDykst5z3ZgWHPlHGP3448DwUcZGKETUm7I6TiT5CiDo66qojH2qtFwI9gWUEk6ZrrUcA18FB9wSKBqQNSGDa02NqvXfoSeks+Ggne3dVktozmhFHt8yjIvvExLi45bYsZn5UQFKyh6lnOa3WP33p5Y2lTo666z7wcmRvN6N7HNgzkp+d6+ax+QHiIhQ3jgmvL4IQov2FW4CsqbHZsO9qrWcBmcByY8y+pk0AeDz4I9pIUkYUVz17KAW5FaRkReOJbPmH+vv2i+aKqzNrvZdXWnsWa37Zgc9qzYxT3PcTGacUQtQvnLthG12E0BizG2f2a833VrRqjUSDImPcZPSNbdNr3nJEBDPX+tlZAqcNdnF0X8m8I4RoHR11go9oB7aoDPvXD6CoHHXTZFSftHatzyGZLjbdFENemSUrQR73EEK0no6a7k60A3vRszDDOK/fXwhrHkC5nNZcYG85Rbd+in9zIXE3TiDqpIFtUqfoCEV2RPh+iIUQnUOH7YYVLe/jq2azfW4eKUMSOP3lo1CuOh+OBZuqX6/fBUXlkOR0vRbdPJOyZ+cDUPnVRtLX34A7s2XWufpyc4BvtsCIbpbnjZdIN7wwNZJusU13u767JsCVM/1EuOCFU9wcJ121QogD0CEn+IiWN+u+xWz+MheA3Pl7mHn1HCY/NbF2oQsmwj3vOq9PORSVVD1G6d9YUF2uzEsgt6RFguVXmwOc8FbAWZ/SWii14LeMfKKcrb+pf4w0r8xyw2d+tuy1zN0OZcEcshd/6Gfj1RIshRDNJ8FSALDjx7xa23krC/cr47r7Z9hjhzktylMOqbUv9voJVH6zCSr9RE4eiGdkRovU67utNRZyVgrcCvyW7UUNH3PjZ35eWbb/zFi/pIAVQhygQPjGSgmWbenQSwbx+U2manvYef0o2ePl1dtXkLu+lBHHpDL11oGo44bXe3z0lCGkr7uBQG4JntGZKHf9LbjtxZbPNlmGp6qQVvk4oY/irtngDeC0LIMrj/Tt1vCx24prb8d4IMoNT50sj4YIIQ6MtCw7obyNJaz9fAcDju2Oy6NY82ku/Y5OI2Ng/Sni7PZC+qX7OflxzYq3c+g/OZvBU3vz/iPr2bG2FIClX+QxaEI3Rh7T8AxYd88k3D2TGty/s8SiX/azrRhcCv431cVpAxrvFp2QpZj1Czffb7Uclm55dp6LmAh4dHLDK478ZryLWVv9lPvg7CGKN6e6ZaasEOKgBGQ2bOeycc5u/nfDAgDmTF9f9f6c6euYfO8ohpxQ+8F+/1er8Z76JJRWknlEf3p/fj0qyglEuzaW1iq7ZVlRo8GyKbO22apWX8DCO2sspw1o+jidqdDBVuhRvZtuHU7u72Lz1Yq8MhiSggRKIcRBk5ZlC9FaHwuMD25+aIxZXGd/InANkGWMua616vHdYw2vez3ribX7B8t/fgOlTi5X+/16ArM34D5mMACDJ3Zjy/JiokrKiNtbQvG3lfgu6YUn+sD+aUamKaLdUO5kqKsKgA3x+S2VfiishI83WGZtCTCom+KmcS48dWfq1pEeq0hv2xwJQohOTMYsW4DWOhp4ABgHRAKfaq2PNsZUTSkxxuzVWv8IDGnNuiRmxZC3rqTeffEZUbW2K3P2UrSqhLh9b3hcqJ7JVfsnnp1F/toitr/kLOKSvzCfD/5vFme8dlSz6+UPWH79pZ9yP3hczjJYV41uuAv2qw1+pr5WQWE5eKJd+Fz7WpSWvZVwz1Ey/iiEaDvNfc5SKeUB/gJMBIqAM6215a1QtUZXHQk3k4DdxhhrjKkAYoHe9ZQ7+OU4mnDaA4eS1DMG5YKEzGgSe0ajXBDfPYozHz+8qpy/uJJFg99g9eIodpJGeUY6EW9egmtg9SxWl1sxeHhMrfMXbKgzeyZE134e4P1gr7AvAF9sbnxq6m2feikMfqx85QFnck/QolyZ1iqECHs9gbustUcCEUCrZWoJy5al1vpP7P9L/wJ4rcZ2OZAFbKKZtNaXA5cDZGZmNlF6fy6Xi4vebnqFsuKvt+Itt4CLLWQTWeZGnzl6v3J9ju2BK3IRgeAyXL2P6d7sOgH8sL12gIus0zC01uILQITbuXuLj6z/PAr4xYiOdB8lhOgMmjtmaa3dCKCUigW+tdYubYVqAWEaLI0xf6r7ntb6BeDaGm8lADsP8PzTgekA06ZNa7UmVMyYDJQLbHC9lugGZspGJ0dy3swTWPTcWroNTGD4ef0O6Hqn9Vcs2On8OjEeePbk6oA3a7OfM16tIL8M/nxsBHccE8E/T4vkVzMq2VVqGZLpxutyMTpdcd4wF2NkvUkhRBurO2aplKpq2ARNt9ZOr1MmEfgD8Aul1H+ttYtao25hGSwb8B1O3zRa6yjAa4xZp7WOBTDGlDZ2cHuI7BHHsA8mk3PbD9iiCmJ7RVH06WYSTty/9zi+RyxH3HFIPWcJ3V1Hujk0I0BuCZw/TNEtuvqTd+snXnYH/w/94QsvlxzuYXCai9mXRx/UNYUQoqXUTaQeDIzT6y9dVWYv8Bul1CLgMmo3qlpMh+lrC45T/klr/VvgZpz/KeDMfr0GQGsdAxwJDNJa1zee2eaSJ/cm7aQeqPX5lLy7kU1T3qNycyOpcQ7Szwa7uPowV61ACVBzcq3bBREd5l9eCNFVBJSq9dNMq4BWW0KyI7UsMcZ8CHxY570Ha7wuA+4J/oSNytXVOV1thR9vThGRvUPP6Zq7rZKnH9xC/i4vJ5yewmnnpje7Do+fGskF/6lgZwncfVwEaXHSzSqECC8HMBv2ROAW4A3A0kQr9GB0qGDZUXW7bARFH23EVgaIGdedGN28nK7vvraT3G3OJN+P3s5DT0oks2dUE0fVNizdxfyrYpouKIQQ7aS5z1laaz8FPm2VytQhwbINJJ7aj8ErplGZU0Ts+ExcUc383173bquJD9TqfMuyPMuR2Yr02OrCM9cH+MvsAN3j4LET3XSv07rcUexMDsqMl1anEKLtSbo7QWT/JCL7N5zTtTFn/CKdndsqyd/t5fjTUsjMbrhVed93Pu78zo/P7SI7QfHjNCco7im3nDnDX7WUli/g5+2zqv/5H5nn56bPnWm7fzvexY1jJSGBEKJtSbo7cVAyMiO5/aGmHye547NK7v0mGA1dAbbi4YvNlvOHKQrKq9echP1XDbn9mwD7nqH5w7cBCZZCiDYXzunuZE5kJzF7s59/L6wRDQMWFzA81fn09UtWTAkmVI90wW0Tqv/pv94coNRbfWiqPE0ihGgHBzkbtlVJyzIMrdljeW+dZVQanNi36fuZO7+o5K6vfLXeS4iGV850cWiG84F7eWmAD4Kp8A7PhFMHVn8Q315VOy/D5Y3kkYCafAAAFUJJREFUkxVCiNYiY5YiZFuKLONf8bMnmLP19dPg50PrD17/XeHj8Tk+vtgQqPX+ZYe7ufPYCLITq497dlGAQDAmzt4GK/NgZPAJlDHdqz+gHhecNlCCpRCi7fnDN1ZKsAw383bYqkAJ8MlGy8+HOq937/ZSUhqgd69IPl0X4MzX9s8ZnxwND5wUSXJM7U/dsDTF1zlOtEyKgqz46n0XHeLCAmaH5czB6v/bu/Mwqaozj+PfW13V3TTQbE2zCYKKCgiKHPcxChOXJBi3GPcnQeMWTaIJTow+STRmMTFRknGWoJFETdQxLuMYV9QgSEx81QQBEYW4IJvsDb3VcuePW9DVZVc3LbXcwt/neerpvkvdfrvqVL33nHvuOUyoD3GJFZHdVtiaXjMpWYbMpEEetZWwJZ0HJ48ICs+8F7cy8/YPSaXgyCN7snlsv48+2ffZKxEnmagm+/6SX0yJ0KcqqLl+bVKE/lnJdNqECNN2bbQ9EZFdEuYOPkqWITOi1uMv51TwyNs+EwbC1L2DJtEnnthMKt3aOn/+Ni6b3JeelbCtxadXa4KU51HbEmdd0ufBl5u5eEr7WZlrYh43HaseriISXrpmKd0yts5jbF37QlNXF+Xd94LqZk1NhEkjo7x2WZT/ez3OLx9qoikaYW3PoBvrsobwFjgRkVySIW6GVU+OkGts9bnqiVbm9O3NyANqGDEixskn96G6KsLoAREuOTxGv14eG2oqSUU8UhGPXy/SxM0iIvmkmmXIXTs7zi9fCm4LeYxeTF25jnfu20giASef1JdvPp1gYaSq3RlZMpXraCIi4RXma5aqWYbcsg1tmS+JR2NF8Ja9/Mo2AO5fmCAZibQbP3bPviEucSIiOSTx2j3CRMky5C49JEZlul/O0EScfq1BLXPvvYLxYScN+ehb2DNWtPBERPIm6bV/hImaYUNu4rAI3zu+itqoz2nDo7wwpw+1fSo44dO1ADx4VhU/mdvKfQuSvLcFelXCjz9dWeKoRUS6T/dZyseysdln4qw4azcmwYcPjo5y05n92+3Tt4fHT4+v4qfHw5Zmn+ooVEbDW+BERHJRb1jp1NJVCX7/YhNLVrYf3/XZd1KsXZ+EFODDz16Is2Zr7p6utdWeEqWIlK1E1iNMVLMsscUfJDjllk20xKEqCg9e2ZfxI4K3pSXePjH6Pqxq8BmkyZlFZDekmqXkNHdJKy3p6bFaEjBnSdt4r1NGVtAj43Rm/wEeB2jcVhHZTSW89o8wUbIssYkjY0TShcLz4OCRbdnxuj8naSJCZczjUlfBgsuriVaErASJiORJAq/dI0zUDFtih+4d467LanlxaZzD94lx5L5BT9ZFH6aYtSAFnkcrHssbPGJKlCKyG4uH+CtOyTIEjt6/kqP3b3+7R22VR4UHyfRly/7VIS5FIiJ5ENc1S+mu4bUevz2pggn1Hp/bx+PW4zRjiIjs3uJZjzBRzbJIVm71ueTpFKu2+Vx3eIRTR3d9nnLe+ArOG68kKSKfDI0hrlkqWRbJhU8kefLNBHgeZ37os/JSj7qaXSsYja0+f1+dYlS/CEN6h7eQiYjsjKYQf40pWRZBKuXz5zdbIX1XSDzps6U1Sl3G/Mxvr0kwf2mcg/aMMmFE14O7NrT4HHVHM6+v8elVCc98qYrDh6sWKiLlqzVkPWAzKVkWwaZmaG67fZLaqM9eGTODvL0mwUk3b6KxFaIR+NqpvVm0CdzQCJcc0j5xLn/oXZbes4xN/XryVv0YiEXZ2gq/eTWhZCki5S28uVLJshj613gcMzLCnHeC6bYude2T2ktvxWlMJ9NGz+NbzyZI4XHHK0miEY8LJwVv0+ZlDcz/1t/wUwDr+cKYCPccOg6Avfupr5aISKEoWRbJk+dX8eDiJH2qPabu1z5ZHrRnjFgFxJMQj0RIZZxe/WN123yWzeub04kycEK/FjbvV8GEQR7Tj9JbKSJlTh18pDrmce6BwcudTAU3T1akh+45YHiUe6/ow5wlrYwcFOXrz6dY1eBTFYUzxrUl1h4Dq4NmivS9l6OGVPLouVVF/T9ERD6JlCyL4JUVSb7zRDNVUY8p+0b5zuw4nudx5ymVnD0hSsr3uWMJPLo0ylGNEf5yUYxXVqY4oD7CvnWRHVNvNa1p3pEoARKNYRuXX0RkF6hmmR/OucnAYenFx81sQdb2bwJnA72Ai81sbpFDpDXh85tXEzTF4SuTotRWe0yd1cjqhiDL/WlRK17Kx494fPUxn7MnRHlgcYqZrwbtqw8uSXHYMI+rjwzemu8808pNcxP0roKHT+vDgAn9WL9gI5HKCPucOarY/56ISOGEN1eWT7J0zlUDPwMOBSqBZ5xzx5iZn94+GPiHmd3inPsMcCvgih3nBY+08vsFSQD+uDjJ9KMqWN3gU+H74PtEEsmgPKQg2RR0ymnKqiA2p5dXbklx09xgoaEFrpubYt4Dk1n32np6Dquh94heRfqvRESKIbzZsmySJXAksC6dHFucczXACOBdADNbDaxO7zsfWJnrQM65i4GLAQYPHpyX4F54J0k8Cc/9M7lj3V/eT/HF+1MMjccZ1dSKD/wzVsH6iuA65MSBwX5njYtw70KPp5f7TBricfkhwfbqqLej4w9AnyqIVlcw+Ij6vMQsIhIq4c2V4UyWzrnrgX2yVp8D3Jux3AwMJZ0ss3we+FGu45vZTGAmwPnnn+/n2m9nTX+ylV/MD2qAe/dv64FzQL3HwjUpRjYFt9p6wPBEckeyvPKYoHNOddTjqXMraUn4VEXbSkv/Go+7T6vk+8/Hqe/p8Z8ntR9sXURkt6Jk2T1mdn32OufcLOCKjFW9gbUd7DcS2GJmfy1UfNlmvdbWjrp8g893J8d4+J8wur+H58VJrvPwfJ+451ER87jqqEpOOLCayfu2H3AgM1Fud+b4KGeOD+XbJCKSZ+HNluV0J/s8YBiAc64KiJvZMudcTbpJFufcnsA4M/tf51zMOTewGIGNq297GccO9Pj1Gx4LN3g8/DZU9o5xwmdqScQitEYiNCU9Zr/QxBEjNdqOiEg7XtYjRMomWZpZC3C9c+7bwLeAi9KbLgcud86NBWYDNzjnDFgENBUjtj+eWcVnRkcY2BMG9fZY29i27ZVVKX7wUorGjJc6mYKV61MdHElE5JMsvNmyrNr3zOxx4PGsdTdnLI4ubkQBH3h2eYrWJDy3PMWw+iQfNEaCLc1B75wPYxUMbgmaa2t7eIwcVDbnKSIixRGu/NhOWSXLsNrU7NPa1gmWD9YmgSQ1MWhsCWqQ/oBKvn5IFRsaUlzy2Z5EIkqWIiLtKFnu3vari3D62AgPLm7ftNoYh17JJLGkz5hIki8f1x8vxCNUiIiUVni/H1W9yZO7Tquif4+Prh/SHGevbc1sXR9nxVoNTyciklN4L1kqWeZLTaXHs1+u5pwJEQ4c5HHwEI9T9khR25qgyvep9n2m/XAdr73ZUupQRUTCyfPaP0JEzbB5dNCQCL//QjUAry7cxlO3LmcMFcyN9gPPoyUOj7zQyMT9NFOIiEg5UbLMsyUrE8xd2IJ34TNM2LAVgOjYETw/KeioO6RO91eKiJQbJcs8WvxBglNu2USvDY3cmE6UAMPXbGSvETHc6EqmTe1dwghFREKsGy2vnufVArOAccBS4Gzf97cVJjBds8yrF9+M0xKHjT2rWdm3bUaQZUMG8NbqJJee2puqWLja4UVEwqNbPXw+BVwAjAG2AdMKGZlqlnl08KgoFRFIEmHG1EM54d2VbCDKwlGDqUiBv8tDtouI7Ma6UZfwff+xHU/zvJfoZKapfFCyzKNJo2L84fI+zFvaSs/3k/xjU29inkfveILW6hgxvdoiIrllJUvP83ZMp5g20/f9mR08cyTwHwWLCyXLvDt8dIwxdR7XXLoCD4j6PqO3bqO5uYKG5oHU9lAzrIhIx9p/P6YTY0fJse0ZnncqcKvv+wW9kV3XLAugogIiWZ1evcoItT30couI5NTNQQk8zzseeN33/fc8zxtWyND07V0AvWqjnHfJYGr7VhCpilAztJprvz2k1GGJiOw2PM+7ErgduM/zvFeB7xby76kZtkAOOLgXRxzTp9RhiIiUj+518JkBzChYLFmULPNsa0OS6Ve9Q0uzj+fB9GuGMnZcTanDEhEJv5ANcZdJzbB5du8fPqSlObhHxPfhthmrShyRiIjsKtUs86wy1v78I5HMsaOIiLQX3oqlapb5dt6X6ohVtr3jZ5zZv4TRiIiUk/DO0aVkmWcLFzQRb80cqmfn3vCNb29h4d3LWLtgY2ECExEJu/DmSjXD5tuWLe3bXbds7rodduOyBh4+Yw6JpiRehcfnZh3F0EPrChWiiIh0k2qWeeYO6cWIPYP5KgcMiHLslNoun7Pq5XUkmoKk6id9VsxbW9AYRURCSTXLT44eNRG+e8MebFifoF+/CmKVXZ+P1B/Yj0jMIxUPmm8HuwGFDlNERLpBybIAolGP+kGxnd6/bkxfTrrraN6ft4ZBB/Vn+NGDChidiEhIhfg+SyXLkBg0sT+DJqrnrIhIGClZiohIOIS3YqkOPiIiIl1RzVJERMIhxDVLJUsREQmJ8GZLJUsREQmH8OZKXbMUERHpimqWIiISDiGuWZZVsnTOTQYOSy8+bmYLsrafAkwD9gUuNLP5RQ5RRER2Q2XTDOucqwZ+BvwUuBW4zTmXfR6yzMxOBn4EnFbkEEVEZFeEeGzYskmWwJHAOjPzzawFqAFGZO5gZq+nf60FbityfCIispsKZTOsc+56YJ+s1ecA92YsNwNDgXeznnsa8G9Af+CHOY5/MXAxwODBg/MSs4iI7CKNDds9ZnZ99jrn3CzgioxVvYGPzGVlZg8552YDC8mRLM1sJjAT4Pzzz/c72kdERIosvLkynMkyh3nATwCcc1VA3MyWOedqAMyscfuOZrbFOffczhz0jTfeWOece7frPdupA9Z18zmlpHgLr9xiVryFV24xdzfeJ83sxHwG4E+PhjZder5fPhUr59xngfFABfCEmb3mnLs6vXkG8BTwHLASmGtmbxUoDjMzV4hjF4LiLbxyi1nxFl65xVxu8RZbOdUsMbPHgcez1t2csTiluBGJiMgnQTn1hhURESkJJcuPZ2apA+gmxVt45Raz4i28cou53OItqrK6ZikiIlIKqlmKiIh0QclSRESkC2XVG7bYnHOXA60EIwX90sw2ZWw7CxgI9ANmmdn7pYmyTRfxVgN/BQYAL5vZqaWJsj3n3P7AzcDPzWxO1rZOB84vhc7iTW+fDewPrACOMrNkkUPMjKUWmAWMA5YCZ5vZtoztYSzDXcUcqnLsnIsS3P99BNAAnGpmzRnbw1iGO405vU9oynFYqGaZg3PuYOAwM7sdeBb4fsa2ocAFZvbvwJ3Ar0oTZZvO4k27AJhqZnuU+gsmk5ktIfjAtrsZeScHzi+6XPHCjllvrku/xoeH4AvmUwTv+xhgG8GMPEA4y3BazpjTwlaO9wB+YGb/AsTIGKYzrGWYTmKGUJbjUFCyzO0UYFH697+nl7c7EVgGYGYrgMOdcxXFDe8jcsab/oAeC/zNOXeHc65X8cPrVGsH67ocOL+EOooXYDLwoHPuIefcoGIG1BEze8zMNpuZD7xEMFjHdmEsw53GHMZybGbvmFlDeiSxuWa2MGNzKMtwFzFDyMpxWChZ5jYY2JD+ffug7R1tA0gC9UWKK5ec8aY/rF8ERgEJ4Jbih9dt2a9x9nsQOmb2DWBP4DXg7hKHk20k8GjGchjLcLaRZMQc1nKcbjq+AbjYOXdgxqbQluFOYg57OS4ZJcvc1hCcCcJHB23P3AbQA9hYpLhy6SxeANLXJb5OcC0i7LJf4w7/p7Axs6SZ3UgwTVwoOOdOBW41s0TG6jCW4R1yxAyErxyb2RYzuxr4NnBRxqbQluFOYt6+PXTluNSULHN7CDgo/ft44FHn3ADnXAR4jKADAs65EcBL2RfIS6CzeNn+E+gDzC5BfDvFOdfXORcjGDh/WHrdjoHzSxpcBzLiJeO1rgZeKGlgac6544HXzew959ywkJdhoNOYw16O3wTeKLMynB1zKMtxGGhQgk6kB2nfSHCd4Vbgd8CPzewl59w0grPGeuBOM+vuzCV5lytegg4pDxA0ab0N/LajM/ZScM7tSTBP6Z8ImtVuBuaY2QMdDZxfukgDueIlGMB/LvAMwRfQ3WbWUKo4AZxzVwJXAR8SnBj/jaAZMMxlOGfMhLAcO+eOA6YD9wM+cA/BZy/MZThnzISwHIeFkqWIiEgX1AwrIiLSBSVLERGRLihZioiIdEHJUkREpAtKliIiIl3QQOoiJeSc6wdcRjBe5wHASWa2OWufccAM4B4z+12O4+wPTDCz/0nfN3kuwS0LNcDpGt9TZNeoZilSWtcCr5nZVwlmqv9IUjOzRQTDpnU2CPfnCQYaAPgF8AhwXnrdV/IZsMgnkZKlSGkdBDQBmNk9ZrY1x35NXRynxswaM49pZimCIde+mJdIRT7BNCiBSJ4558YAxwFnENQUpwGHEAysvTdQb2ZnO+cuAq4Bngb+TDCjxiUEU6297JybCPw3MJVgpKCFBIOLnwZcY2Z3pf/eJGCYmT3qnJtOUFv9L2A+cDzwOeA24I5OkrGIdEI1S5E8Sk+se6OZ/Qo4BlhFkPCuBu5Nz+gwGyA99+j7wP1mdj/B4OArCIZGg2BS5hvN7MP0cr2ZXUEw+PU3Mv7sicCT6WP+HNgC3G5mfwIeBlaY2QwlSpGPT8lSJL/2BeoA0s2g3yeY1/AZYLFz7lrgvo6eaGZxgkmYr0qvOhF4ImOXxemfKwgS6fY5HmNmlmuOTRHJAyVLkfwamLX8PsG0TN8DzgHOAuZ1MtHyTOC4dNPq5hy9WH3aPrtHE8xuISIFpGQpkl8e0D9j+TDg18AVZvZMenkUwdyG2/ff8Tk0sy3AnQS9We/dib83BXi+gxi2HzMJVDnnoukJf0XkY9B9liL5V+ecuwpYDfQluJXjTefc8PS6H5rZJufcsQT3Vp7unHvHzJannz8DGL992Tm3D3Bg+vfngH8F6p1zRwN+Zu3TOXc6MAQ41zl3J7AIGEDQvHtlgf9vkd2WesOK5FE6AX7PzKbswjHGEQwwsDM1SxEpAtUsRfKrB9D8cZ7onNsbqCIYROCafAYlIrtG1yxF8msYwUAAH8cVwFPAI2bWkr+QRGRXqRlWRESkC6pZioiIdEHJUkREpAtKliIiIl1QshQREemCkqWIiEgXlCxFRES68P/uuWn8Wsp/qAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 540x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the dependance plot for class 0\n",
    "n=1\n",
    "for name in X_shap.columns:\n",
    "    shap.dependence_plot(name, shap_values[0], X, display_features=X_shap, show=False )\n",
    "    #plt.savefig('name.eps',format='eps', dpi=1000)\n",
    "#     plt.savefig(\"Graph_Column\" + str(n) +\".eps\", format=\"EPS\")\n",
    "#     n=n+1\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}