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0,{scope:"PersonaPresence"}),$r=[Mr.lightBlue,Mr.blue,Mr.darkBlue,Mr.teal,Mr.green,Mr.darkGreen,Mr.lightPink,Mr.pink,Mr.magenta,Mr.purple,Mr.orange,Mr.lightRed,Mr.darkRed,Mr.violet,Mr.gold,Mr.burgundy,Mr.warmGray,Mr.cyan,Mr.rust,Mr.coolGray],ei=$r.length;function ti(e){var t=e.primaryText,o=e.text,n=e.initialsColor;return"string"==typeof n?n:function(){switch(n){case Mr.lightBlue:return"#4F6BED";case Mr.blue:return"#0078D4";case Mr.darkBlue:return"#004E8C";case Mr.teal:return"#038387";case Mr.lightGreen:case Mr.green:return"#498205";case Mr.darkGreen:return"#0B6A0B";case Mr.lightPink:return"#C239B3";case Mr.pink:return"#E3008C";case Mr.magenta:return"#881798";case Mr.purple:return"#5C2E91";case Mr.orange:return"#CA5010";case Mr.red:return"#EE1111";case Mr.lightRed:return"#D13438";case Mr.darkRed:return"#A4262C";case Mr.transparent:return"transparent";case Mr.violet:return"#8764B8";case Mr.gold:return"#986F0B";case Mr.burgundy:return"#750B1C";case Mr.warmGray:return"#7A7574";case Mr.cyan:return"#005B70";case Mr.rust:return"#8E562E";case Mr.coolGray:return"#69797E";case Mr.black:return"#1D1D1D";case Mr.gray:return"#393939"}}(n=void 0!==n?n:function(e){var t=Mr.blue;if(!e)return t;for(var o=0,n=e.length-1;0<=n;n--){var r=e.charCodeAt(n),i=n%8;o^=(r<<i)+(r>>8-i)}return $r[o%ei]}(o\|\|t))}var oi=Fn({cacheSize:100}),ni=Ao(function(e,t,o,n,r,i){return j(e,!i&&{backgroundColor:ti({text:n,initialsColor:t,primaryText:r}),color:o})}),ri={size:Pr.size48,presence:Rr.none,imageAlt:""},ii=gt.forwardRef(function(e,t){var o,n,r,i,s,a=Hn(ri,e),l=(o=a.onPhotoLoadingStateChange,n=a.imageUrl,r=gt.useState(mr.notLoaded),i=r[0],s=r[1],gt.useEffect(function(){s(mr.notLoaded)},[n]),[i,function(e){s(e),null==o\|\|o(e)}]),c=l[0],u=ai(l[1]),d=a.className,p=a.coinProps,h=a.showUnknownPersonaCoin,m=a.coinSize,g=a.styles,f=a.imageUrl,v=a.initialsColor,b=a.initialsTextColor,y=a.isOutOfOffice,C=a.onRenderCoin,_=a.onRenderPersonaCoin,S=void 0===_?void 0===C?u:C:_,x=a.onRenderInitials,k=void 0===x?li:x,w=a.presence,I=a.presenceTitle,D=a.presenceColors,E=a.primaryText,e=a.showInitialsUntilImageLoads,r=a.text,n=a.theme,i=a.size,l=ur(a,cr),C=ur(p\|\|{},cr),_=m?{width:m,height:m}:void 0,x=h,D={coinSize:m,isOutOfOffice:y,presence:w,presenceTitle:I,presenceColors:D,size:i,theme:n},m=oi(g,{theme:n,className:p&&p.className?p.className:d,size:i,coinSize:m,showUnknownPersonaCoin:h}),c=Boolean(c!==mr.loaded&&(e&&f\|\|!f\|\|c===mr.error\|\|x));return gt.createElement("div",ht({role:"presentation"},l,{className:m.coin,ref:t}),i!==Pr.size8&&i!==Pr.size10&&i!==Pr.tiny?gt.createElement("div",ht({role:"presentation"},C,{className:m.imageArea,style:_}),c&&gt.createElement("div",{className:ni(m.initials,v,b,r,E,h),style:_,"aria-hidden":"true"},k(a,li)),!x&&S(a,u),gt.createElement(Jr,ht({},D))):a.presence?gt.createElement(Jr,ht({},D)):gt.createElement(Wr,{iconName:"Contact",className:m.size10WithoutPresenceIcon}),a.children)});ii.displayName="PersonaCoinBase";var si,ai=function(c){return function(e){var t=e.coinSize,o=e.styles,n=e.imageUrl,r=e.imageAlt,i=e.imageShouldFadeIn,s=e.imageShouldStartVisible,a=e.theme,l=e.showUnknownPersonaCoin,e=e.size,e=void 0===e?ri.size:e;if(!n)return null;l=oi(o,{theme:a,size:e,showUnknownPersonaCoin:l}),e=t\|\|Gr[e];return gt.createElement(Ir,{className:l.image,imageFit:pr.cover,src:n,width:e,height:e,alt:r,shouldFadeIn:i,shouldStartVisible:s,onLoadingStateChange:c})}},li=function(e){var t=e.imageInitials,o=e.allowPhoneInitials,n=e.showUnknownPersonaCoin,r=e.text,i=e.primaryText,e=e.theme;if(n)return gt.createElement(Wr,{iconName:"Help"});e=Pn(e);return""!==(t=t\|\|Cr(r\|\|i\|\|"",e,o))?gt.createElement("span",null,t):gt.createElement(Wr,{iconName:"Contact"})},ci={coin:"ms-Persona-coin",imageArea:"ms-Persona-imageArea",image:"ms-Persona-image",initials:"ms-Persona-initials",size8:"ms-Persona--size8",size10:"ms-Persona--size10",size16:"ms-Persona--size16",size24:"ms-Persona--size24",size28:"ms-Persona--size28",size32:"ms-Persona--size32",size40:"ms-Persona--size40",size48:"ms-Persona--size48",size56:"ms-Persona--size56",size72:"ms-Persona--size72",size100:"ms-Persona--size100",size120:"ms-Persona--size120"},ui=In(ii,function(e){var t=e.className,o=e.theme,n=e.coinSize,r=o.palette,i=o.fonts,s=Kr(e.size),o=zo(ci,o),n=n\|\|e.size&&Gr[e.size]\|\|48;return{coin:[o.coin,i.medium,s.isSize8&&o.size8,s.isSize10&&o.size10,s.isSize16&&o.size16,s.isSize24&&o.size24,s.isSize28&&o.size28,s.isSize32&&o.size32,s.isSize40&&o.size40,s.isSize48&&o.size48,s.isSize56&&o.size56,s.isSize72&&o.size72,s.isSize100&&o.size100,s.isSize120&&o.size120,t],size10WithoutPresenceIcon:{fontSize:i.xSmall.fontSize,position:"absolute",top:"5px",right:"auto",left:0},imageArea:[o.imageArea,{position:"relative",textAlign:"center",flex:"0 0 auto",height:n,width:n},n<=10&&{overflow:"visible",background:"transparent",height:0,width:0}],image:[o.image,{marginRight:"10px",position:"absolute",top:0,left:0,width:"100%",height:"100%",border:0,borderRadius:"50%",perspective:"1px"},n<=10&&{overflow:"visible",background:"transparent",height:0,width:0},10<n&&{height:n,width:n}],initials:[o.initials,{borderRadius:"50%",color:e.showUnknownPersonaCoin?"rgb(168, 0, 0)":r.white,fontSize:i.large.fontSize,fontWeight:Fe.semibold,lineHeight:48===n?46:n,height:n,selectors:((r={})[Yt]=ht(ht({border:"1px solid WindowText"},{forcedColorAdjust:"none",MsHighContrastAdjust:"none"}),{color:"WindowText",boxSizing:"border-box",backgroundColor:"Window !important"}),r.i={fontWeight:Fe.semibold},r)},e.showUnknownPersonaCoin&&{backgroundColor:"rgb(234, 234, 234)"},n<32&&{fontSize:i.xSmall.fontSize},32<=n&&n<40&&{fontSize:i.medium.fontSize},40<=n&&n<56&&{fontSize:i.mediumPlus.fontSize},56<=n&&n<72&&{fontSize:i.xLarge.fontSize},72<=n&&n<100&&{fontSize:i.xxLarge.fontSize},100<=n&&{fontSize:i.superLarge.fontSize}]}},void 0,{scope:"PersonaCoin"}),di=(l(hi,si=gt.Component),hi.prototype.render=function(){var e=this.props,t=e.onRenderIcon,o=void 0===t?this._onRenderIcon:t,n=e.onRenderActivityDescription,r=void 0===n?this._onRenderActivityDescription:n,i=e.onRenderComments,s=void 0===i?this._onRenderComments:i,t=e.onRenderTimeStamp,n=void 0===t?this._onRenderTimeStamp:t,i=e.animateBeaconSignal,t=e.isCompact,e=this._getClassNames(this.props);return gt.createElement("div",{className:e.root,style:this.props.style},(this.props.activityPersonas\|\|this.props.activityIcon\|\|this.props.onRenderIcon)&&gt.createElement("div",{className:e.activityTypeIcon},i&&t&&gt.createElement("div",{className:e.pulsingBeacon}),o(this.props)),gt.createElement("div",{className:e.activityContent},r(this.props,this._onRenderActivityDescription),s(this.props,this._onRenderComments),n(this.props,this._onRenderTimeStamp)))},hi.prototype._getClassNames=function(e){return vn(Sn(void 0,e.styles,e.animateBeaconSignal,e.beaconColorOne,e.beaconColorTwo,e.isCompact),e.className,e.activityPersonas,e.isCompact)},hi),pi=function(){var e,t=qe();return!(null===(e=null==t?void 0:t.navigator)\|\|void 0===e\|\|!e.userAgent)&&-1<t.navigator.userAgent.indexOf("rv:11.0")};function hi(e){var l=si.call(this,e)\|\|this;return l._onRenderIcon=function(e){return e.activityPersonas?l._onRenderPersonaArray(e):l.props.activityIcon},l._onRenderActivityDescription=function(e){var t=l._getClassNames(e),e=e.activityDescription\|\|e.activityDescriptionText;return e?gt.createElement("span",{className:t.activityText},e):null},l._onRenderComments=function(e){var t=l._getClassNames(e),o=e.comments\|\|e.commentText;return!e.isCompact&&o?gt.createElement("div",{className:t.commentText},o):null},l._onRenderTimeStamp=function(e){var t=l._getClassNames(e);return!e.isCompact&&e.timeStamp?gt.createElement("div",{className:t.timeStamp},e.timeStamp):null},l._onRenderPersonaArray=function(e){var o,n,r,i,s=l._getClassNames(e),t=null,a=e.activityPersonas;return(a[0].imageUrl\|\|a[0].imageInitials)&&(o=[],n=1<a.length\|\|e.isCompact,r=e.isCompact?3:4,i=void 0,e.isCompact&&(i={display:"inline-block",width:"10px",minWidth:"10px",overflow:"visible"}),a.filter(function(e,t){return t<r}).forEach(function(e,t){o.push(gt.createElement(ui,ht({},e,{key:e.key\|\|t,className:s.activityPersona,size:n?Pr.size16:Pr.size32,style:i})))}),t=gt.createElement("div",{className:s.personaContainer},o)),t},l}function mi(o){for(var n=[],e=1;e<arguments.length;e++)n[e-1]=arguments[e];return n.length<2?n[0]:function(){for(var t=[],e=0;e<arguments.length;e++)t[e]=arguments[e];n.forEach(function(e){return e&&e.apply(o,t)})}}function gi(e,t){for(var o in t)t.hasOwnProperty(o)&&(e[o]=mi(e,e[o],t[o]))}function fi(e){gi(e,{componentDidMount:vi,componentDidUpdate:bi,componentWillUnmount:yi})}function vi(){Ci(this.props.componentRef,this)}function bi(e){e.componentRef!==this.props.componentRef&&(Ci(e.componentRef,null),Ci(this.props.componentRef,this))}function yi(){Ci(this.props.componentRef,null)}function Ci(e,t){e&&("object"==typeof e?e.current=t:"function"==typeof e&&e(t))}var _i,Si=(Ii.prototype.dispose=function(){if(this._isDisposed=!0,this._parent=null,this._timeoutIds){for(var e in this._timeoutIds)this._timeoutIds.hasOwnProperty(e)&&this.clearTimeout(parseInt(e,10));this._timeoutIds=null}if(this._immediateIds){for(e in this._immediateIds)this._immediateIds.hasOwnProperty(e)&&this.clearImmediate(parseInt(e,10));this._immediateIds=null}if(this._intervalIds){for(e in this._intervalIds)this._intervalIds.hasOwnProperty(e)&&this.clearInterval(parseInt(e,10));this._intervalIds=null}if(this._animationFrameIds){for(e in this._animationFrameIds)this._animationFrameIds.hasOwnProperty(e)&&this.cancelAnimationFrame(parseInt(e,10));this._animationFrameIds=null}},Ii.prototype.setTimeout=function(e,t){var o=this,n=0;return this._isDisposed\|\|(this._timeoutIds\|\|(this._timeoutIds={}),n=setTimeout(function(){try{o._timeoutIds&&delete o._timeoutIds[n],e.apply(o._parent)}catch(e){o._logError(e)}},t),this._timeoutIds[n]=!0),n},Ii.prototype.clearTimeout=function(e){this._timeoutIds&&this._timeoutIds[e]&&(clearTimeout(e),delete this._timeoutIds[e])},Ii.prototype.setImmediate=function(e,t){var o=this,n=0,t=qe(t);return this._isDisposed\|\|(this._immediateIds\|\|(this._immediateIds={}),n=t.setTimeout(function(){try{o._immediateIds&&delete o._immediateIds[n],e.apply(o._parent)}catch(e){o._logError(e)}},0),this._immediateIds[n]=!0),n},Ii.prototype.clearImmediate=function(e,t){t=qe(t);this._immediateIds&&this._immediateIds[e]&&(t.clearTimeout(e),delete this._immediateIds[e])},Ii.prototype.setInterval=function(e,t){var o=this,n=0;return this._isDisposed\|\|(this._intervalIds\|\|(this._intervalIds={}),n=setInterval(function(){try{e.apply(o._parent)}catch(e){o._logError(e)}},t),this._intervalIds[n]=!0),n},Ii.prototype.clearInterval=function(e){this._intervalIds&&this._intervalIds[e]&&(clearInterval(e),delete this._intervalIds[e])},Ii.prototype.throttle=function(r,e,t){var i=this;if(this._isDisposed)return this._noop;var s,a,l=e\|\|0,c=!0,u=!0,d=0,p=null;t&&"boolean"==typeof t.leading&&(c=t.leading),t&&"boolean"==typeof t.trailing&&(u=t.trailing);function h(e){var t=Date.now(),o=t-d,n=c?l-o:l;return l<=o&&(!e\|\|c)?(d=t,p&&(i.clearTimeout(p),p=null),s=r.apply(i._parent,a)):null===p&&u&&(p=i.setTimeout(h,n)),s}return function(){for(var e=[],t=0;t<arguments.length;t++)e[t]=arguments[t];return a=e,h(!0)}},Ii.prototype.debounce=function(t,e,o){var a=this;if(this._isDisposed){var n=function(){};return n.cancel=function(){},n.flush=function(){return null},n.pending=function(){return!1},n}var l,r,c=e\|\|0,u=!1,d=!0,p=null,h=0,m=Date.now(),g=null;o&&"boolean"==typeof o.leading&&(u=o.leading),o&&"boolean"==typeof o.trailing&&(d=o.trailing),o&&"number"==typeof o.maxWait&&!isNaN(o.maxWait)&&(p=o.maxWait);var i=function(e){g&&(a.clearTimeout(g),g=null),m=e},f=function(e){i(e),l=t.apply(a._parent,r)},v=function(e){var t=Date.now(),o=!1;e&&(u&&c<=t-h&&(o=!0),h=t);var n=t-h,r=c-n,i=t-m,s=!1;return null!==p&&(p<=i&&g?s=!0:r=Math.min(r,p-i)),c<=n\|\|s\|\|o?f(t):null!==g&&e\|\|!d\|\|(g=a.setTimeout(v,r)),l},e=function(){return!!g},o=function(){for(var e=[],t=0;t<arguments.length;t++)e[t]=arguments[t];return r=e,v(!0)};return o.cancel=function(){g&&i(Date.now())},o.flush=function(){return g&&f(Date.now()),l},o.pending=e,o},Ii.prototype.requestAnimationFrame=function(e,t){var o=this,n=0,r=qe(t);return this._isDisposed\|\|(this._animationFrameIds\|\|(this._animationFrameIds={}),t=function(){try{o._animationFrameIds&&delete o._animationFrameIds[n],e.apply(o._parent)}catch(e){o._logError(e)}},n=r.requestAnimationFrame?r.requestAnimationFrame(t):r.setTimeout(t,0),this._animationFrameIds[n]=!0),n},Ii.prototype.cancelAnimationFrame=function(e,t){t=qe(t);this._animationFrameIds&&this._animationFrameIds[e]&&(t.cancelAnimationFrame?t.cancelAnimationFrame(e):t.clearTimeout(e),delete this._animationFrameIds[e])},Ii.prototype._logError=function(e){this._onErrorHandler&&this._onErrorHandler(e)},Ii),xi="backward",ki=(l(wi,_i=gt.Component),wi.getDerivedStateFromProps=function(e,t){if(e.updateValueInWillReceiveProps){e=e.updateValueInWillReceiveProps();if(null!==e&&e!==t.inputValue&&!t.isComposing)return ht(ht({},t),{inputValue:e})}return null},Object.defineProperty(wi.prototype,"cursorLocation",{get:function(){if(this._inputElement.current){var e=this._inputElement.current;return"forward"!==e.selectionDirection?e.selectionEnd:e.selectionStart}return-1},enumerable:!1,configurable:!0}),Object.defineProperty(wi.prototype,"isValueSelected",{get:function(){return Boolean(this.inputElement&&this.inputElement.selectionStart!==this.inputElement.selectionEnd)},enumerable:!1,configurable:!0}),Object.defineProperty(wi.prototype,"value",{get:function(){return this._getControlledValue()\|\|this.state.inputValue\|\|""},enumerable:!1,configurable:!0}),Object.defineProperty(wi.prototype,"selectionStart",{get:function(){return this._inputElement.current?this._inputElement.current.selectionStart:-1},enumerable:!1,configurable:!0}),Object.defineProperty(wi.prototype,"selectionEnd",{get:function(){return this._inputElement.current?this._inputElement.current.selectionEnd:-1},enumerable:!1,configurable:!0}),Object.defineProperty(wi.prototype,"inputElement",{get:function(){return this._inputElement.current},enumerable:!1,configurable:!0}),wi.prototype.componentDidUpdate=function(e,t,o){var n=this.props,r=n.suggestedDisplayValue,i=n.shouldSelectFullInputValueInComponentDidUpdate,s=0;if(!n.preventValueSelection)if(this._autoFillEnabled&&this.value&&r&&Di(r,this.value)){n=!1;if((n=i?i():n)&&this._inputElement.current)this._inputElement.current.setSelectionRange(0,r.length,xi);else{for(;s<this.value.length&&this.value[s].toLocaleLowerCase()===r[s].toLocaleLowerCase();)s++;0<s&&this._inputElement.current&&this._inputElement.current.setSelectionRange(s,r.length,xi)}}else this._inputElement.current&&(null===o\|\|this._autoFillEnabled\|\|this.state.isComposing\|\|this._inputElement.current.setSelectionRange(o.start,o.end,o.dir))},wi.prototype.componentWillUnmount=function(){this._async.dispose()},wi.prototype.render=function(){var e=ur(this.props,Zn),t=ht(ht({},this.props.style),{fontFamily:"inherit"});return gt.createElement("input",ht({autoCapitalize:"off",autoComplete:"off","aria-autocomplete":"both"},e,{style:t,ref:this._inputElement,value:this._getDisplayValue(),onCompositionStart:this._onCompositionStart,onCompositionUpdate:this._onCompositionUpdate,onCompositionEnd:this._onCompositionEnd,onChange:this._onChanged,onInput:this._onInputChanged,onKeyDown:this._onKeyDown,onClick:this.props.onClick\|\|this._onClick,"data-lpignore":!0}))},wi.prototype.focus=function(){this._inputElement.current&&this._inputElement.current.focus()},wi.prototype.clear=function(){this._autoFillEnabled=!0,this._updateValue("",!1),this._inputElement.current&&this._inputElement.current.setSelectionRange(0,0)},wi.prototype.getSnapshotBeforeUpdate=function(){var e,t=this._inputElement.current;return t&&t.selectionStart!==this.value.length?{start:null!==(e=t.selectionStart)&&void 0!==e?e:t.value.length,end:null!==(e=t.selectionEnd)&&void 0!==e?e:t.value.length,dir:t.selectionDirection\|\|"backward"}:null},wi.prototype._getCurrentInputValue=function(e){return e&&e.target&&e.target.value?e.target.value:this.inputElement&&this.inputElement.value?this.inputElement.value:""},wi.prototype._tryEnableAutofill=function(e,t,o,n){!o&&e&&this._inputElement.current&&this._inputElement.current.selectionStart===e.length&&!this._autoFillEnabled&&(e.length>t.length\|\|n)&&(this._autoFillEnabled=!0)},wi.prototype._getDisplayValue=function(){return this._autoFillEnabled?(o=e=this.value,o=(t=this.props.suggestedDisplayValue)&&e&&Di(t,e)?t:o):this.value;var e,t,o},wi.prototype._getControlledValue=function(){var e=this.props.value;return void 0===e\|\|"string"==typeof e?e:(console.warn("props.value of Autofill should be a string, but it is "+e+" with type of "+typeof e),e.toString())},wi.defaultProps={enableAutofillOnKeyPress:[En.down,En.up]},wi);function wi(e){var i=_i.call(this,e)\|\|this;return i._inputElement=gt.createRef(),i._autoFillEnabled=!0,i._onCompositionStart=function(e){i.setState({isComposing:!0}),i._autoFillEnabled=!1},i._onCompositionUpdate=function(){pi()&&i._updateValue(i._getCurrentInputValue(),!0)},i._onCompositionEnd=function(e){var t=i._getCurrentInputValue();i._tryEnableAutofill(t,i.value,!1,!0),i.setState({isComposing:!1}),i._async.setTimeout(function(){i._updateValue(i._getCurrentInputValue(),!1)},0)},i._onClick=function(){i.value&&""!==i.value&&i._autoFillEnabled&&(i._autoFillEnabled=!1)},i._onKeyDown=function(e){if(i.props.onKeyDown&&i.props.onKeyDown(e),!e.nativeEvent.isComposing)switch(e.which){case En.backspace:i._autoFillEnabled=!1;break;case En.left:case En.right:i._autoFillEnabled&&(i.setState({inputValue:i.props.suggestedDisplayValue\|\|""}),i._autoFillEnabled=!1);break;default:i._autoFillEnabled\|\|-1!==i.props.enableAutofillOnKeyPress.indexOf(e.which)&&(i._autoFillEnabled=!0)}},i._onInputChanged=function(e){var t=i._getCurrentInputValue(e);i.state.isComposing\|\|i._tryEnableAutofill(t,i.value,e.nativeEvent.isComposing),pi()&&i.state.isComposing\|\|(e=void 0===(e=e.nativeEvent.isComposing)?i.state.isComposing:e,i._updateValue(t,e))},i._onChanged=function(){},i._updateValue=function(e,t){var o,n,r;!e&&e===i.value\|\|(n=(o=i.props).onInputChange,r=o.onInputValueChange,n&&(e=(null==n?void 0:n(e,t))\|\|""),i.setState({inputValue:e},function(){return null==r?void 0:r(e,t)}))},fi(i),i._async=new Si(i),i.state={inputValue:e.defaultVisibleValue\|\|"",isComposing:!1},i}function Ii(e,t){this._timeoutIds=null,this._immediateIds=null,this._intervalIds=null,this._animationFrameIds=null,this._isDisposed=!1,this._parent=e\|\|null,this._onErrorHandler=t,this._noop=function(){}}function Di(e,t){return e&&t&&0===e.toLocaleLowerCase().indexOf(t.toLocaleLowerCase())}var Ei,Ti,Pi,Ri=(l(Li,Pi=gt.Component),Li.prototype.componentDidMount=function(){var 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0===o?0:o;e&&r<e.length;r++)if(t(e[r],r)){n=r;break}return n}function Oi(e,t){t=Hi(e,t);if(!(t<0))return e[t]}function zi(e,t){for(var o=[],n=0;n<e;n++)o.push(t(n));return o}function Wi(e,n){return e.reduce(function(e,t,o){return o%n==0?e.push([t]):e[e.length-1].push(t),e},[])}function Vi(e,o){return e.filter(function(e,t){return o!==t})}function Ki(e,t,o){e=e.slice();return e[o]=t,e}function Gi(e,t,o){e=e.slice();return e.splice(t,0,o),e}function Ui(e){var t=[];return e.forEach(function(e){return t=t.concat(e)}),t}function ji(e,t){if(e.length!==t.length)return!1;for(var o=0;o<e.length;o++)if(e[o]!==t[o])return!1;return!0}(xe=Ei=Ei\|\|{})[xe.vertical=0]="vertical",xe[xe.horizontal=1]="horizontal",xe[xe.bidirectional=2]="bidirectional",xe[xe.domOrder=3]="domOrder";var qi=function(e){var o={refs:[]};return function(){for(var r,e=[],t=0;t<arguments.length;t++)e[t]=arguments[t];return o.resolver&&ji(o.refs,e)\|\|(o.resolver=(r=o,function(e){for(var t=0,o=r.refs;t<o.length;t++){var 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cs(e,t){if(!e\|\|e.disabled)return!1;var o=0,n=null;e&&e.getAttribute&&(n=e.getAttribute("tabIndex"))&&(o=parseInt(n,10));var r=e.getAttribute?e.getAttribute("data-is-focusable"):null,n=!!e&&"false"!==r&&("A"===e.tagName\|\|"BUTTON"===e.tagName\|\|"INPUT"===e.tagName\|\|"TEXTAREA"===e.tagName\|\|"SELECT"===e.tagName\|\|"true"===r\|\|null!==n&&0<=o);return(!t\|\|-1!==o)&&n}function us(e){return!!(e&&e.getAttribute&&e.getAttribute("data-focuszone-id"))}function ds(e){return!(!e\|\|!e.getAttribute\|\|"true"!==e.getAttribute("data-is-sub-focuszone"))}function ps(e){var t=ft(e),t=t&&t.activeElement;return!(!t\|\|!$i(e,t))}function hs(e,t){return"true"!==Ji(e,t)}var ms=void 0;function gs(e){e&&(ms?ms=e:(e=qe(ms=e))&&e.requestAnimationFrame(function(){ms&&ms.focus(),ms=void 0}))}function fs(e,t){for(var o=e,n=0,r=t;n<r.length;n++){var i=r[n],i=o.children[Math.min(i,o.children.length-1)];if(!i)break;o=i}return cs(o)&&as(o)?o:ss(e,o,!0)\|\|is(e,o)}function vs(e,t){for(var o=[];t&&e&&t!==e;){var n=Xi(t,!0);if(null===n)return[];o.unshift(Array.prototype.indexOf.call(n.children,t)),t=n}return o}var bs=qe()\|\|{};void 0===bs.__currentId__&&(bs.__currentId__=0);var ys,Cs=!1;function _s(e){var t;return Cs\|\|((t=v.getInstance())&&t.onReset&&t.onReset(Ss),Cs=!0),(void 0===e?"id__":e)+bs.__currentId__++}function Ss(e){bs.__currentId__=e=void 0===e?0:e}function xs(e){var t,o,o=(t="MouseEvents","function"==typeof Event?o=new Event(t):(o=document.createEvent("Event")).initEvent(t,!0,!0),o);o.initEvent("click",!0,!0),e.dispatchEvent(o)}var ks=0,ws=j({overflow:"hidden !important"}),Is="data-is-scrollable",Ds=function(e,t){var n,r;e&&(n=0,r=null,t.on(e,"touchstart",function(e){1===e.targetTouches.length&&(n=e.targetTouches[0].clientY)},{passive:!1}),t.on(e,"touchmove",function(e){var t,o;1===e.targetTouches.length&&(e.stopPropagation(),r)&&(t=e.targetTouches[0].clientY-n,o=Ns(e.target),0===(r=o?o:r).scrollTop&&0<t&&e.preventDefault(),r.scrollHeight-Math.ceil(r.scrollTop)<=r.clientHeight&&t<0&&e.preventDefault())},{passive:!1}),r=e)},Es=function(e,t){e&&t.on(e,"touchmove",function(e){e.stopPropagation()},{passive:!1})},Ts=function(e){e.preventDefault()};function Ps(){var e=ft();e&&e.body&&!ks&&(e.body.classList.add(ws),e.body.addEventListener("touchmove",Ts,{passive:!1,capture:!1})),ks++}function Rs(){var e;0<ks&&((e=ft())&&e.body&&1===ks&&(e.body.classList.remove(ws),e.body.removeEventListener("touchmove",Ts)),ks--)}function Ms(){var e;return void 0===ys&&((e=document.createElement("div")).style.setProperty("width","100px"),e.style.setProperty("height","100px"),e.style.setProperty("overflow","scroll"),e.style.setProperty("position","absolute"),e.style.setProperty("top","-9999px"),document.body.appendChild(e),ys=e.offsetWidth-e.clientWidth,document.body.removeChild(e)),ys}function Ns(e){for(var t=e,o=ft(e);t&&t!==o.body;){if("true"===t.getAttribute(Is))return t;t=t.parentElement}for(t=e;t&&t!==o.body;){if("false"!==t.getAttribute(Is)){var n=getComputedStyle(t),n=n?n.getPropertyValue("overflow-y"):"";if(n&&("scroll"===n\|\|"auto"===n))return t}t=t.parentElement}return t=!t\|\|t===o.body?qe(e):t}var Bs="data-portal-element";function Fs(e){e.setAttribute(Bs,"true")}function As(e,t){e=Qi(e,function(e){return t===e\|\|e.hasAttribute(Bs)});return null!==e&&e.hasAttribute(Bs)}var Ls,Hs,Os="data-is-focusable",zs="data-focuszone-id",Ws="tabindex",Vs="data-no-vertical-wrap",Ks="data-no-horizontal-wrap",Gs=999999999,Us=-999999999,js={},qs=new Set,Ys=["text","number","password","email","tel","url","search"],Zs=(l(Qs,Hs=gt.Component),Qs.getOuterZones=function(){return qs.size},Qs._onKeyDownCapture=function(e){e.which===En.tab&&qs.forEach(function(e){return e._updateTabIndexes()})},Qs.prototype.componentDidMount=function(){var e=this._root.current;if(js[this._id]=this,e){this._windowElement=qe(e);for(var t=Xi(e,!1);t&&t!==this._getDocument().body&&1===t.nodeType;){if(us(t)){this._isInnerZone=!0;break}t=Xi(t,!1)}this._isInnerZone\|\|(qs.add(this),this._windowElement&&1===qs.size&&this._windowElement.addEventListener("keydown",Qs._onKeyDownCapture,!0)),this._root.current&&this._root.current.addEventListener("blur",this._onBlur,!0),this._updateTabIndexes(),this.props.defaultTabbableElement&&"string"==typeof this.props.defaultTabbableElement?this._activeElement=this._getDocument().querySelector(this.props.defaultTabbableElement):this.props.defaultActiveElement&&(this._activeElement=this._getDocument().querySelector(this.props.defaultActiveElement)),this.props.shouldFocusOnMount&&this.focus()}},Qs.prototype.componentDidUpdate=function(){var e=this._root.current,t=this._getDocument();this.props.preventFocusRestoration\|\|!t\|\|!this._lastIndexPath\|\|t.activeElement!==t.body&&null!==t.activeElement&&t.activeElement!==e\|\|((e=fs(e,this._lastIndexPath))?(this._setActiveElement(e,!0),e.focus(),this._setParkedFocus(!1)):this._setParkedFocus(!0))},Qs.prototype.componentWillUnmount=function(){delete js[this._id],this._isInnerZone\|\|(qs.delete(this),this._windowElement&&0===qs.size&&this._windowElement.removeEventListener("keydown",Qs._onKeyDownCapture,!0)),this._root.current&&this._root.current.removeEventListener("blur",this._onBlur,!0),this._activeElement=null,this._defaultFocusElement=null},Qs.prototype.render=function(){var t=this,e=this.props,o=e.as,n=e.elementType,r=e.rootProps,i=e.ariaDescribedBy,s=e.ariaLabelledBy,a=e.className,e=ur(this.props,Wn),n=o\|\|n\|\|"div";this._evaluateFocusBeforeRender();var l=Wt();return gt.createElement(n,ht({"aria-labelledby":s,"aria-describedby":i},e,r,{className:Tr(Ls=Ls\|\|j({selectors:{":focus":{outline:"none"}}},"ms-FocusZone"),a),ref:this._mergedRef(this.props.elementRef,this._root),"data-focuszone-id":this._id,onKeyDown:function(e){return t._onKeyDown(e,l)},onFocus:this._onFocus,onMouseDownCapture:this._onMouseDown}),this.props.children)},Qs.prototype.focus=function(e){if(void 0===e&&(e=!1),this._root.current){if(!e&&"true"===this._root.current.getAttribute(Os)&&this._isInnerZone){var t=this._getOwnerZone(this._root.current);if(t===this._root.current)return!1;t=js[t.getAttribute(zs)];return!!t&&t.focusElement(this._root.current)}if(!e&&this._activeElement&&$i(this._root.current,this._activeElement)&&cs(this._activeElement))return this._activeElement.focus(),!0;e=this._root.current.firstChild;return this.focusElement(ss(this._root.current,e,!0))}return!1},Qs.prototype.focusLast=function(){if(this._root.current){var e=this._root.current&&this._root.current.lastChild;return this.focusElement(is(this._root.current,e,!0,!0,!0))}return!1},Qs.prototype.focusElement=function(e,t){var o=this.props,n=o.onBeforeFocus,o=o.shouldReceiveFocus;return!(o&&!o(e)\|\|n&&!n(e)\|\|!e\|\|(this._setActiveElement(e,t),this._activeElement&&this._activeElement.focus(),0))},Qs.prototype.setFocusAlignment=function(e){this._focusAlignment=e},Qs.prototype._evaluateFocusBeforeRender=function(){var e,t=this._root.current,o=this._getDocument();!o\|\|(e=o.activeElement)!==t&&(o=$i(t,e,!1),this._lastIndexPath=o?vs(t,e):void 0)},Qs.prototype._setParkedFocus=function(e){var t=this._root.current;t&&this._isParked!==e&&((this._isParked=e)?(this.props.allowFocusRoot\|\|(this._parkedTabIndex=t.getAttribute("tabindex"),t.setAttribute("tabindex","-1")),t.focus()):this.props.allowFocusRoot\|\|(this._parkedTabIndex?(t.setAttribute("tabindex",this._parkedTabIndex),this._parkedTabIndex=void 0):t.removeAttribute("tabindex")))},Qs.prototype._setActiveElement=function(e,t){var o=this._activeElement;this._activeElement=e,o&&(us(o)&&this._updateTabIndexes(o),o.tabIndex=-1),this._activeElement&&(this._focusAlignment&&!t\|\|this._setFocusAlignment(e,!0,!0),this._activeElement.tabIndex=0)},Qs.prototype._preventDefaultWhenHandled=function(e){this.props.preventDefaultWhenHandled&&e.preventDefault()},Qs.prototype._tryInvokeClickForFocusable=function(e){if(e===this._root.current)return!1;do{if("BUTTON"===e.tagName\|\|"A"===e.tagName\|\|"INPUT"===e.tagName\|\|"TEXTAREA"===e.tagName)return!1;if(this._isImmediateDescendantOfZone(e)&&"true"===e.getAttribute(Os)&&"true"!==e.getAttribute("data-disable-click-on-enter"))return xs(e),!0}while((e=Xi(e,!1))!==this._root.current);return!1},Qs.prototype._getFirstInnerZone=function(e){if(!(e=e\|\|this._activeElement\|\|this._root.current))return null;if(us(e))return js[e.getAttribute(zs)];for(var t=e.firstElementChild;t;){if(us(t))return js[t.getAttribute(zs)];var o=this._getFirstInnerZone(t);if(o)return o;t=t.nextElementSibling}return null},Qs.prototype._moveFocus=function(e,t,o,n){void 0===n&&(n=!0);var r=this._activeElement,i=-1,s=void 0,a=!1,l=this.props.direction===Ei.bidirectional;if(!r\|\|!this._root.current)return!1;if(this._isElementInput(r)&&!this._shouldInputLoseFocus(r,e))return!1;var c=l?r.getBoundingClientRect():null;do{if(r=(e?ss:is)(this._root.current,r),!l){s=r;break}if(r){var u=t(c,r.getBoundingClientRect());if(-1===u&&-1===i){s=r;break}if(-1<u&&(-1===i\|\|u<i)&&(i=u,s=r),0<=i&&u<0)break}}while(r);if(s&&s!==this._activeElement)a=!0,this.focusElement(s);else if(this.props.isCircularNavigation&&n)return e?this.focusElement(ss(this._root.current,this._root.current.firstElementChild,!0)):this.focusElement(is(this._root.current,this._root.current.lastElementChild,!0,!0,!0));return a},Qs.prototype._moveFocusDown=function(){var r=this,i=-1,s=this._focusAlignment.left\|\|this._focusAlignment.x\|\|0;return!!this._moveFocus(!0,function(e,t){var o=-1,n=Math.floor(t.top),e=Math.floor(e.bottom);return n<e?r._shouldWrapFocus(r._activeElement,Vs)?Gs:Us:((-1===i&&e<=n\|\|n===i)&&(i=n,o=s>=t.left&&s<=t.left+t.width?0:Math.abs(t.left+t.width/2-s)),o)})&&(this._setFocusAlignment(this._activeElement,!1,!0),!0)},Qs.prototype._moveFocusUp=function(){var i=this,s=-1,a=this._focusAlignment.left\|\|this._focusAlignment.x\|\|0;return!!this._moveFocus(!1,function(e,t){var o=-1,n=Math.floor(t.bottom),r=Math.floor(t.top),e=Math.floor(e.top);return e<n?i._shouldWrapFocus(i._activeElement,Vs)?Gs:Us:((-1===s&&n<=e\|\|r===s)&&(s=r,o=a>=t.left&&a<=t.left+t.width?0:Math.abs(t.left+t.width/2-a)),o)})&&(this._setFocusAlignment(this._activeElement,!1,!0),!0)},Qs.prototype._moveFocusLeft=function(n){var r=this,i=this._shouldWrapFocus(this._activeElement,Ks);return!!this._moveFocus(Pn(n),function(e,t){var o=-1;return(Pn(n)?parseFloat(t.top.toFixed(3))<parseFloat(e.bottom.toFixed(3)):parseFloat(t.bottom.toFixed(3))>parseFloat(e.top.toFixed(3)))&&t.right<=e.right&&r.props.direction!==Ei.vertical?o=e.right-t.right:i\|\|(o=Us),o},void 0,i)&&(this._setFocusAlignment(this._activeElement,!0,!1),!0)},Qs.prototype._moveFocusRight=function(n){var r=this,i=this._shouldWrapFocus(this._activeElement,Ks);return!!this._moveFocus(!Pn(n),function(e,t){var o=-1;return(Pn(n)?parseFloat(t.bottom.toFixed(3))>parseFloat(e.top.toFixed(3)):parseFloat(t.top.toFixed(3))<parseFloat(e.bottom.toFixed(3)))&&t.left>=e.left&&r.props.direction!==Ei.vertical?o=t.left-e.left:i\|\|(o=Us),o},void 0,i)&&(this._setFocusAlignment(this._activeElement,!0,!1),!0)},Qs.prototype._moveFocusPaging=function(e,t){void 0===t&&(t=!0);var o=this._activeElement;if(!o\|\|!this._root.current)return!1;if(this._isElementInput(o)&&!this._shouldInputLoseFocus(o,e))return!1;var n=Ns(o);if(!n)return!1;var r=-1,i=void 0,s=-1,a=-1,l=n.clientHeight,c=o.getBoundingClientRect();do{if(o=(e?ss:is)(this._root.current,o)){var u=o.getBoundingClientRect(),d=Math.floor(u.top),p=Math.floor(c.bottom),h=Math.floor(u.bottom),m=Math.floor(c.top),u=this._getHorizontalDistanceFromCenter(e,c,u);if(e&&p+l<d\|\|!e&&h<m-l)break;-1<u&&(e&&s<d?(s=d,r=u,i=o):!e&&h<a?(a=h,r=u,i=o):(-1===r\|\|u<=r)&&(r=u,i=o))}}while(o);n=!1;if(i&&i!==this._activeElement)n=!0,this.focusElement(i),this._setFocusAlignment(i,!1,!0);else if(this.props.isCircularNavigation&&t)return e?this.focusElement(ss(this._root.current,this._root.current.firstElementChild,!0)):this.focusElement(is(this._root.current,this._root.current.lastElementChild,!0,!0,!0));return n},Qs.prototype._setFocusAlignment=function(e,t,o){var n;this.props.direction!==Ei.bidirectional\|\|this._focusAlignment&&!t&&!o\|\|(e=(n=e.getBoundingClientRect()).left+n.width/2,n=n.top+n.height/2,this._focusAlignment\|\|(this._focusAlignment={left:e,top:n}),t&&(this._focusAlignment.left=e),o&&(this._focusAlignment.top=n))},Qs.prototype._isImmediateDescendantOfZone=function(e){return this._getOwnerZone(e)===this._root.current},Qs.prototype._getOwnerZone=function(e){for(var t=Xi(e,!1);t&&t!==this._root.current&&t!==this._getDocument().body;){if(us(t))return t;t=Xi(t,!1)}return t},Qs.prototype._updateTabIndexes=function(e){!this._activeElement&&this.props.defaultTabbableElement&&"function"==typeof this.props.defaultTabbableElement&&(this._activeElement=this.props.defaultTabbableElement(this._root.current)),!e&&this._root.current&&(this._defaultFocusElement=null,e=this._root.current,this._activeElement&&!$i(e,this._activeElement)&&(this._activeElement=null)),this._activeElement&&!cs(this._activeElement)&&(this._activeElement=null);for(var t=e&&e.children,o=0;t&&o<t.length;o++){var n=t[o];us(n)?"true"===n.getAttribute(Os)&&(this._isInnerZone\|\|(this._activeElement\|\|this._defaultFocusElement)&&this._activeElement!==n?"-1"!==n.getAttribute(Ws)&&n.setAttribute(Ws,"-1"):"0"!==(this._defaultFocusElement=n).getAttribute(Ws)&&n.setAttribute(Ws,"0")):(n.getAttribute&&"false"===n.getAttribute(Os)&&n.setAttribute(Ws,"-1"),cs(n)?this.props.disabled?n.setAttribute(Ws,"-1"):this._isInnerZone\|\|(this._activeElement\|\|this._defaultFocusElement)&&this._activeElement!==n?"-1"!==n.getAttribute(Ws)&&n.setAttribute(Ws,"-1"):"0"!==(this._defaultFocusElement=n).getAttribute(Ws)&&n.setAttribute(Ws,"0"):"svg"===n.tagName&&"false"!==n.getAttribute("focusable")&&n.setAttribute("focusable","false")),this._updateTabIndexes(n)}},Qs.prototype._isContentEditableElement=function(e){return 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t?this.persistedKeytips[e.uniqueID]=e:this.keytips[e.uniqueID]=e,!this.inKeytipMode&&this.delayUpdatingKeytipChange\|\|(t=t?gc.PERSISTED_KEYTIP_ADDED:gc.KEYTIP_ADDED,va.raise(this,t,{keytip:o,uniqueID:e.uniqueID})),e.uniqueID},zc.prototype.update=function(e,t){var o=this.addParentOverflow(e),e=this._getUniqueKtp(o,t),o=this.keytips[t];o&&(e.keytip.visible=o.keytip.visible,this.keytips[t]=e,delete this.sequenceMapping[o.keytip.keySequences.toString()],this.sequenceMapping[e.keytip.keySequences.toString()]=e.keytip,!this.inKeytipMode&&this.delayUpdatingKeytipChange\|\|va.raise(this,gc.KEYTIP_UPDATED,{keytip:e.keytip,uniqueID:e.uniqueID}))},zc.prototype.unregister=function(e,t,o){(o=void 0===o?!1:o)?delete this.persistedKeytips[t]:delete this.keytips[t],o\|\|delete 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zc(){this.keytips={},this.persistedKeytips={},this.sequenceMapping={},this.inKeytipMode=!1,this.shouldEnterKeytipMode=!0,this.delayUpdatingKeytipChange=!1}function Wc(e){return e.reduce(function(e,t){return e+Tc+t.split("").join(Tc)},Ec)}function Vc(e,t){var o=t.length,t=$e([],t).pop();return Gi($e([],e),o-1,t)}function Kc(e){return"["+Rc+'="'+Wc(e)+'"]'}function Gc(e){return"["+Mc+'="'+e+'"]'}function Uc(e){var t=" "+Bc;return e.length?t+" "+Wc(e):t}function jc(e){var t=gt.useRef(),o=e.keytipProps?ht({disabled:e.disabled},e.keytipProps):void 0,n=_l(Oc.getInstance()),r=Hc(e);gt.useLayoutEffect(function(){t.current&&o&&((null==r?void 0:r.keytipProps)!==e.keytipProps\|\|(null==r?void 0:r.disabled)!==e.disabled)&&n.update(o,t.current)}),gt.useLayoutEffect(function(){return o&&(t.current=n.register(o)),function(){o&&n.unregister(o,t.current)}},[]);var i,s,a,l={ariaDescribedBy:void 0,keytipId:void 0};return o&&(i=n,s=e.ariaDescribedBy,a=i.addParentOverflow(o),i=Ia(s,Uc(a.keySequences)),s=$e([],a.keySequences),l={ariaDescribedBy:i,keytipId:Wc(s=a.overflowSetSequence?Vc(s,a.overflowSetSequence):s)}),l}var qc,Yc=function(e){var t=e.children,o=jc(mt(e,["children"])),e=o.keytipId,o=o.ariaDescribedBy;return t(((t={})[Rc]=e,t[Mc]=e,t["aria-describedby"]=o,t))},Zc=(l(Qc,qc=Y),Qc.prototype.render=function(){var t=this,e=this.props,o=e.item,n=e.classNames,r=e.index,i=e.focusableElementIndex,s=e.totalItemCount,a=e.hasCheckmarks,l=e.hasIcons,c=e.contextualMenuItemAs,u=void 0===c?Dc:c,d=e.expandedMenuItemKey,p=e.onItemClick,h=e.openSubMenu,m=e.dismissSubMenu,g=e.dismissMenu,f=o.rel;o.target&&"_blank"===o.target.toLowerCase()&&(f=f\|\|"nofollow noopener noreferrer");var v=Ha(o),b=ur(o,qn),c=Oa(o),y=o.itemProps,C=o.ariaDescription,e=o.keytipProps;e&&v&&this._getMemoizedMenuButtonKeytipProps(e),C&&(this._ariaDescriptionId=_s());var e=Ia(o.ariaDescribedBy,C?this._ariaDescriptionId:void 0,b["aria-describedby"]),_={"aria-describedby":e};return gt.createElement("div",null,gt.createElement(Yc,{keytipProps:o.keytipProps,ariaDescribedBy:e,disabled:c},function(e){return gt.createElement("a",ht({},_,b,e,{ref:t._anchor,href:o.href,target:o.target,rel:f,className:n.root,role:"menuitem","aria-haspopup":v\|\|void 0,"aria-expanded":v?o.key===d:void 0,"aria-posinset":i+1,"aria-setsize":s,"aria-disabled":Oa(o),style:o.style,onClick:t._onItemClick,onMouseEnter:t._onItemMouseEnter,onMouseLeave:t._onItemMouseLeave,onMouseMove:t._onItemMouseMove,onKeyDown:v?t._onItemKeyDown:void 0}),gt.createElement(u,ht({componentRef:o.componentRef,item:o,classNames:n,index:r,onCheckmarkClick:a&&p?p:void 0,hasIcons:l,openSubMenu:h,dismissSubMenu:m,dismissMenu:g,getSubmenuTarget:t._getSubmenuTarget},y)),t._renderAriaDescription(C,n.screenReaderText))}))},Qc),Xc=Fn(),xe=gt.forwardRef(function(e,t){var o=e.styles,n=e.theme,r=e.getClassNames,e=e.className,e=Xc(o,{theme:n,getClassNames:r,className:e});return gt.createElement("span",{className:e.wrapper,ref:t},gt.createElement("span",{className:e.divider}))});function Qc(){var n=null!==qc&&qc.apply(this,arguments)\|\|this;return n._anchor=gt.createRef(),n._getMemoizedMenuButtonKeytipProps=Ao(function(e){return ht(ht({},e),{hasMenu:!0})}),n._getSubmenuTarget=function(){return n._anchor.current\|\|void 0},n._onItemClick=function(e){var t=n.props,o=t.item,t=t.onItemClick;t&&t(o,e)},n._renderAriaDescription=function(e,t){return e?gt.createElement("span",{id:n._ariaDescriptionId,className:t},e):null},n}xe.displayName="VerticalDividerBase";var Jc,$c,eu=In(xe,function(e){var t=e.theme,o=e.getClassNames,e=e.className;if(!t)throw new Error("Theme is undefined or 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gt.createElement("div",{"data-ktp-target":e["data-ktp-target"],ref:function(e){return t._splitButton=e},role:za(o),"aria-label":o.ariaLabel,className:n.splitContainer,"aria-disabled":Oa(o),"aria-expanded":d?o.key===u:void 0,"aria-haspopup":!0,"aria-describedby":Ia(o.ariaDescribedBy,p?t._ariaDescriptionId:void 0,e["aria-describedby"]),"aria-checked":o.isChecked\|\|o.checked,"aria-posinset":i+1,"aria-setsize":s,onMouseEnter:t._onItemMouseEnterPrimary,onMouseLeave:c?c.bind(t,ht(ht({},o),{subMenuProps:null,items:null})):void 0,onMouseMove:t._onItemMouseMovePrimary,onKeyDown:t._onItemKeyDown,onClick:t._executeItemClick,onTouchStart:t._onTouchStart,tabIndex:0,"data-is-focusable":!0,"aria-roledescription":o["aria-roledescription"]},t._renderSplitPrimaryButton(o,n,r,a,l),t._renderSplitDivider(o),t._renderSplitIconButton(o,n,r,e),t._renderAriaDescription(p,n.screenReaderText))})},ru.prototype._renderSplitPrimaryButton=function(e,t,o,n,r){var i=this.props,s=i.contextualMenuItemAs,a=void 0===s?Dc:s,s=i.onItemClick,i={key:e.key,disabled:Oa(e)\|\|e.primaryDisabled,name:e.name,text:e.text\|\|e.name,secondaryText:e.secondaryText,className:t.splitPrimary,canCheck:e.canCheck,isChecked:e.isChecked,checked:e.checked,iconProps:e.iconProps,onRenderIcon:e.onRenderIcon,data:e.data,"data-is-focusable":!1},e=e.itemProps;return gt.createElement("button",ht({},ur(i,Yn)),gt.createElement(a,ht({"data-is-focusable":!1,item:i,classNames:t,index:o,onCheckmarkClick:n&&s?s:void 0,hasIcons:r},e)))},ru.prototype._renderSplitDivider=function(e){e=e.getSplitButtonVerticalDividerClassNames\|\|kc;return gt.createElement(eu,{getClassNames:e})},ru.prototype._renderSplitIconButton=function(t,e,o,n){var r=this.props,i=r.contextualMenuItemAs,s=void 0===i?Dc:i,a=r.onItemMouseLeave,l=r.onItemMouseDown,c=r.openSubMenu,u=r.dismissSubMenu,i=r.dismissMenu,r={onClick:this._onIconItemClick,disabled:Oa(t),className:e.splitMenu,subMenuProps:t.subMenuProps,submenuIconProps:t.submenuIconProps,split:!0,key:t.key},a=ht(ht({},ur(r,Yn)),{onMouseEnter:this._onItemMouseEnterIcon,onMouseLeave:a?a.bind(this,t):void 0,onMouseDown:function(e){return l?l(t,e):void 0},onMouseMove:this._onItemMouseMoveIcon,"data-is-focusable":!1,"data-ktp-execute-target":n["data-ktp-execute-target"],"aria-hidden":!0}),n=t.itemProps;return gt.createElement("button",ht({},a),gt.createElement(s,ht({componentRef:t.componentRef,item:r,classNames:e,index:o,hasIcons:!1,openSubMenu:c,dismissSubMenu:u,dismissMenu:i,getSubmenuTarget:this._getSubmenuTarget},n)))},ru.prototype._handleTouchAndPointerEvent=function(e){var t=this,o=this.props.onTap;o&&o(e),this._lastTouchTimeoutId&&(this._async.clearTimeout(this._lastTouchTimeoutId),this._lastTouchTimeoutId=void 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ht(ht({},e),{hasMenu:!0})}),o._renderAriaDescription=function(e,t){return e?gt.createElement("span",{id:o._ariaDescriptionId,className:t},e):null},o._getSubmenuTarget=function(){return o._btn.current\|\|void 0},o}function ru(e){var r=$c.call(this,e)\|\|this;return r._getMemoizedMenuButtonKeytipProps=Ao(function(e){return ht(ht({},e),{hasMenu:!0})}),r._onItemKeyDown=function(e){var t=r.props,o=t.item,t=t.onItemKeyDown;e.which===En.enter?(r._executeItemClick(e),e.preventDefault(),e.stopPropagation()):t&&t(o,e)},r._getSubmenuTarget=function(){return r._splitButton},r._renderAriaDescription=function(e,t){return e?gt.createElement("span",{id:r._ariaDescriptionId,className:t},e):null},r._onItemMouseEnterPrimary=function(e){var t=r.props,o=t.item,t=t.onItemMouseEnter;t&&t(ht(ht({},o),{subMenuProps:void 0,items:void 0}),e,r._splitButton)},r._onItemMouseEnterIcon=function(e){var t=r.props,o=t.item,t=t.onItemMouseEnter;t&&t(o,e,r._splitButton)},r._onItemMouseMovePrimary=function(e){var t=r.props,o=t.item,t=t.onItemMouseMove;t&&t(ht(ht({},o),{subMenuProps:void 0,items:void 0}),e,r._splitButton)},r._onItemMouseMoveIcon=function(e){var t=r.props,o=t.item,t=t.onItemMouseMove;t&&t(o,e,r._splitButton)},r._onIconItemClick=function(e){var t=r.props,o=t.item,t=t.onItemClickBase;t&&t(o,e,r._splitButton\|\|e.currentTarget)},r._executeItemClick=function(e){var t=r.props,o=t.item,n=t.executeItemClick,t=t.onItemClick;if(!o.disabled&&!o.isDisabled)return r._processingTouch&&t?t(o,e):void(n&&n(o,e))},r._onTouchStart=function(e){!r._splitButton\|\|"onpointerdown"in r._splitButton\|\|r._handleTouchAndPointerEvent(e)},r._onPointerDown=function(e){"touch"===e.pointerType&&(r._handleTouchAndPointerEvent(e),e.preventDefault(),e.stopImmediatePropagation())},r._async=new Si(r),r._events=new va(r),r}function iu(e,t){t=gt.useRef(t);return t.current\|\|(t.current=_s(e)),t.current}var 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0===e?this._onRenderChildren:e,a=n.onRenderMenu,p=void 0===a?this._onRenderMenu:a,c=n.onRenderMenuIcon,h=void 0===c?this._onRenderMenuIcon:c,e=n.disabled,a=n.keytipProps;a&&s&&(a=this._getMemoizedMenuButtonKeytipProps(a));c=function(e){return gt.createElement(r,ht({},t,e),gt.createElement("span",{className:o._classNames.flexContainer,"data-automationid":"splitbuttonprimary"},l(n,o._onRenderIcon),o._onRenderTextContents(),u(n,o._onRenderAriaDescription),d(n,o._onRenderChildren),!o._isSplitButton&&(s\|\|i\|\|o.props.onRenderMenuIcon)&&h(o.props,o._onRenderMenuIcon),s&&!s.doNotLayer&&o._shouldRenderMenu()&&p(o._getMenuProps(s),o._onRenderMenu)))},c=a?gt.createElement(Yc,{keytipProps:this._isSplitButton?void 0:a,ariaDescribedBy:t["aria-describedby"],disabled:e},c):c();return s&&s.doNotLayer?gt.createElement(gt.Fragment,null,c,this._shouldRenderMenu()&&p(this._getMenuProps(s),this._onRenderMenu)):gt.createElement(gt.Fragment,null,c,gt.createElement(na,null))},Zu.prototype._shouldRenderMenu=function(){var e=this.state.menuHidden,t=this.props,o=t.persistMenu,t=t.renderPersistedMenuHiddenOnMount;return!e\|\|!(!o\|\|!this._renderedVisibleMenu&&!t)},Zu.prototype._hasText=function(){return null!==this.props.text&&(void 0!==this.props.text\|\|"string"==typeof this.props.children)},Zu.prototype._getMenuProps=function(e){var t=this.props.persistMenu,o=this.state.menuHidden;return e.ariaLabel\|\|e.labelElementId\|\|!this._hasText()\|\|(e=ht(ht({},e),{labelElementId:this._labelId})),ht(ht({id:this._labelId+"-menu",directionalHint:Pa.bottomLeftEdge},e),{shouldFocusOnContainer:this._menuShouldFocusOnContainer,shouldFocusOnMount:this._menuShouldFocusOnMount,hidden:t?o:void 0,className:Tr("ms-BaseButton-menuhost",e.className),target:(this._isSplitButton?this._splitButtonContainer:this._buttonElement).current,onDismiss:this._onDismissMenu})},Zu.prototype._onRenderSplitButtonContent=function(t,o){var n=this,e=this.props,r=e.styles,i=void 0===r?{}:r,s=e.disabled,a=e.allowDisabledFocus,l=e.checked,c=e.getSplitButtonClassNames,u=e.primaryDisabled,d=e.menuProps,p=e.toggle,h=e.role,r=e.primaryActionButtonProps,e=this.props.keytipProps,m=this.state.menuHidden,g=c?c(!!s,!m,!!l,!!a):i&&Gu(i,!!s,!m,!!l,!!u);pa(o,{onClick:void 0,onPointerDown:void 0,onPointerUp:void 0,tabIndex:-1,"data-is-focusable":!1}),e&&d&&(e=this._getMemoizedMenuButtonKeytipProps(e));var f=ur(o,[],["disabled"]);r&&pa(o,r);r=function(e){return gt.createElement("div",ht({},f,{"data-ktp-target":e?e["data-ktp-target"]:void 0,role:h\|\|"button","aria-disabled":s,"aria-haspopup":!0,"aria-expanded":!m,"aria-pressed":p?!!l:void 0,"aria-describedby":Ia(o["aria-describedby"],e?e["aria-describedby"]:void 0),className:g&&g.splitButtonContainer,onKeyDown:n._onSplitButtonContainerKeyDown,onTouchStart:n._onTouchStart,ref:n._splitButtonContainer,"data-is-focusable":!0,onClick:s\|\|u?void 0:n._onSplitButtonPrimaryClick,tabIndex:!s&&!u\|\|a?0:void 0,"aria-roledescription":o["aria-roledescription"],onFocusCapture:n._onSplitContainerFocusCapture}),gt.createElement("span",{style:{display:"flex"}},n._onRenderContent(t,o),n._onRenderSplitButtonMenuButton(g,e),n._onRenderSplitButtonDivider(g)))};return e?gt.createElement(Yc,{keytipProps:e,disabled:s},r):r()},Zu.prototype._onRenderSplitButtonDivider=function(e){return e&&e.divider?gt.createElement("span",{className:e.divider,"aria-hidden":!0,onClick:function(e){e.stopPropagation()}}):null},Zu.prototype._onRenderSplitButtonMenuButton=function(e,t){var o=this.props,n=o.allowDisabledFocus,r=o.checked,i=o.disabled,s=o.splitButtonMenuProps,a=o.splitButtonAriaLabel,l=o.primaryDisabled,c=this.state.menuHidden,o=this.props.menuIconProps;void 0===o&&(o={iconName:"ChevronDown"});c=ht(ht({},s),{styles:e,checked:r,disabled:i,allowDisabledFocus:n,onClick:this._onMenuClick,menuProps:void 0,iconProps:ht(ht({},o),{className:this._classNames.menuIcon}),ariaLabel:a,"aria-haspopup":!0,"aria-expanded":!c,"data-is-focusable":!1});return gt.createElement(Zu,ht({},c,{"data-ktp-execute-target":t&&t["data-ktp-execute-target"],onMouseDown:this._onMouseDown,tabIndex:l&&!n?0:-1}))},Zu.prototype._onPointerDown=function(e){var t=this.props.onPointerDown;t&&t(e),"touch"===e.pointerType&&(this._handleTouchAndPointerEvent(),e.preventDefault(),e.stopImmediatePropagation())},Zu.prototype._handleTouchAndPointerEvent=function(){var e=this;void 0!==this._lastTouchTimeoutId&&(this._async.clearTimeout(this._lastTouchTimeoutId),this._lastTouchTimeoutId=void 0),this._processingTouch=!0,this._lastTouchTimeoutId=this._async.setTimeout(function(){e._processingTouch=!1,e._lastTouchTimeoutId=void 0,e.focus()},500)},Zu.prototype._isValidMenuOpenKey=function(e){return this.props.menuTriggerKeyCode?e.which===this.props.menuTriggerKeyCode:!!this.props.menuProps&&e.which===En.down&&(e.altKey\|\|e.metaKey)},Zu.defaultProps={baseClassName:"ms-Button",styles:{},split:!1},Zu);function Zu(e){var s=qu.call(this,e)\|\|this;return s._buttonElement=gt.createRef(),s._splitButtonContainer=gt.createRef(),s._mergedRef=qi(),s._renderedVisibleMenu=!1,s._getMemoizedMenuButtonKeytipProps=Ao(function(e){return ht(ht({},e),{hasMenu:!0})}),s._onRenderIcon=function(e,t){var o=s.props.iconProps;if(o&&(void 0!==o.iconName\|\|o.imageProps)){var n=o.className,r=o.imageProps,i=mt(o,["className","imageProps"]);if(o.styles)return gt.createElement(Wr,ht({className:Tr(s._classNames.icon,n),imageProps:r},i));if(o.iconName)return gt.createElement(Lr,ht({className:Tr(s._classNames.icon,n)},i));if(r)return gt.createElement(Ta,ht({className:Tr(s._classNames.icon,n),imageProps:r},i))}return null},s._onRenderTextContents=function(){var e=s.props,t=e.text,o=e.children,n=e.secondaryText,r=void 0===n?s.props.description:n,n=e.onRenderText,n=void 0===n?s._onRenderText:n,e=e.onRenderDescription,e=void 0===e?s._onRenderDescription:e;return t\|\|"string"==typeof o\|\|r?gt.createElement("span",{className:s._classNames.textContainer},n(s.props,s._onRenderText),e(s.props,s._onRenderDescription)):[n(s.props,s._onRenderText),e(s.props,s._onRenderDescription)]},s._onRenderText=function(){var e=s.props.text,t=s.props.children;return void 0===e&&"string"==typeof t&&(e=t),s._hasText()?gt.createElement("span",{key:s._labelId,className:s._classNames.label,id:s._labelId},e):null},s._onRenderChildren=function(){var e=s.props.children;return"string"==typeof e?null:e},s._onRenderDescription=function(e){e=e.secondaryText,e=void 0===e?s.props.description:e;return e?gt.createElement("span",{key:s._descriptionId,className:s._classNames.description,id:s._descriptionId},e):null},s._onRenderAriaDescription=function(){var e=s.props.ariaDescription;return e?gt.createElement("span",{className:s._classNames.screenReaderText,id:s._ariaDescriptionId},e):null},s._onRenderMenuIcon=function(e){var t=s.props.menuIconProps;return gt.createElement(Lr,ht({iconName:"ChevronDown"},t,{className:s._classNames.menuIcon}))},s._onRenderMenu=function(e){var t=s.props.menuAs?ju(s.props.menuAs,Wu):Wu;return gt.createElement(t,ht({},e))},s._onDismissMenu=function(e){var t=s.props.menuProps;t&&t.onDismiss&&t.onDismiss(e),e&&e.defaultPrevented\|\|s._dismissMenu()},s._dismissMenu=function(){s._menuShouldFocusOnMount=void 0,s._menuShouldFocusOnContainer=void 0,s.setState({menuHidden:!0})},s._openMenu=function(e,t){void 0===t&&(t=!0),s.props.menuProps&&(s._menuShouldFocusOnContainer=e,s._menuShouldFocusOnMount=t,s._renderedVisibleMenu=!0,s.setState({menuHidden:!1}))},s._onToggleMenu=function(e){var t=!0;s.props.menuProps&&!1===s.props.menuProps.shouldFocusOnMount&&(t=!1),s.state.menuHidden?s._openMenu(e,t):s._dismissMenu()},s._onSplitContainerFocusCapture=function(e){var t=s._splitButtonContainer.current;!t\|\|e.target&&As(e.target,t)\|\|t.focus()},s._onSplitButtonPrimaryClick=function(e){s.state.menuHidden\|\|s._dismissMenu(),!s._processingTouch&&s.props.onClick?s.props.onClick(e):s._processingTouch&&s._onMenuClick(e)},s._onKeyDown=function(e){!s.props.disabled\|\|e.which!==En.enter&&e.which!==En.space?s.props.disabled\|\|(s.props.menuProps?s._onMenuKeyDown(e):void 0!==s.props.onKeyDown&&s.props.onKeyDown(e)):(e.preventDefault(),e.stopPropagation())},s._onKeyUp=function(e){s.props.disabled\|\|void 0===s.props.onKeyUp\|\|s.props.onKeyUp(e)},s._onKeyPress=function(e){s.props.disabled\|\|void 0===s.props.onKeyPress\|\|s.props.onKeyPress(e)},s._onMouseUp=function(e){s.props.disabled\|\|void 0===s.props.onMouseUp\|\|s.props.onMouseUp(e)},s._onMouseDown=function(e){s.props.disabled\|\|void 0===s.props.onMouseDown\|\|s.props.onMouseDown(e)},s._onClick=function(e){s.props.disabled\|\|(s.props.menuProps?s._onMenuClick(e):void 0!==s.props.onClick&&s.props.onClick(e))},s._onSplitButtonContainerKeyDown=function(e){e.which===En.enter\|\|e.which===En.space?s._buttonElement.current&&(s._buttonElement.current.click(),e.preventDefault(),e.stopPropagation()):s._onMenuKeyDown(e)},s._onMenuKeyDown=function(e){var t,o,n;s.props.disabled\|\|(s.props.onKeyDown&&s.props.onKeyDown(e),t=e.which===En.up,o=e.which===En.down,!e.defaultPrevented&&s._isValidMenuOpenKey(e)&&((n=s.props.onMenuClick)&&n(e,s.props),s._onToggleMenu(!1),e.preventDefault(),e.stopPropagation()),e.which!==En.enter&&e.which!==En.space\|\|vo(!0,e.target),e.altKey\|\|e.metaKey\|\|!t&&!o\|\|!s.state.menuHidden&&s.props.menuProps&&((void 0!==s._menuShouldFocusOnMount?s._menuShouldFocusOnMount:s.props.menuProps.shouldFocusOnMount)\|\|(e.preventDefault(),e.stopPropagation(),s._menuShouldFocusOnMount=!0,s.forceUpdate())))},s._onTouchStart=function(){!s._isSplitButton\|\|!s._splitButtonContainer.current\|\|"onpointerdown"in s._splitButtonContainer.current\|\|s._handleTouchAndPointerEvent()},s._onMenuClick=function(e){var t=s.props.onMenuClick;t&&t(e,s.props),e.defaultPrevented\|\|(t=0!==e.nativeEvent.detail\|\|"mouse"===e.nativeEvent.pointerType,s._onToggleMenu(t),e.preventDefault(),e.stopPropagation())},fi(s),s._async=new Si(s),s._events=new va(s),s.props.split,s._labelId=_s(),s._descriptionId=_s(),s._ariaDescriptionId=_s(),s.state={menuHidden:!0},s}function Xu(i,s,a){return function(r){var t,e=(l(o,t=gt.Component),o.prototype.componentDidMount=function(){yt.observe(this._onSettingChanged)},o.prototype.componentWillUnmount=function(){yt.unobserve(this._onSettingChanged)},o.prototype.render=function(){var n=this;return gt.createElement(xn.Consumer,null,function(e){var t=yt.getSettings(s,i,e.customizations),o=n.props;return t.styles&&"function"==typeof t.styles&&(t.styles=t.styles(ht(ht({},t),o))),a&&t.styles?(n._styleCache.default===t.styles&&n._styleCache.component===o.styles\|\|(e=un(t.styles,o.styles),n._styleCache.default=t.styles,n._styleCache.component=o.styles,n._styleCache.merged=e),gt.createElement(r,ht({},t,o,{styles:n._styleCache.merged}))):gt.createElement(r,ht({},t,o))})},o.prototype._onSettingChanged=function(){this.forceUpdate()},o.displayName="Customized"+i,o);function o(e){e=t.call(this,e)\|\|this;return e._styleCache={},e._onSettingChanged=e._onSettingChanged.bind(e),e}return hu(r,e)}}function Qu(e){return{fontSize:e,margin:"0 4px",height:"16px",lineHeight:"16px",textAlign:"center",flexShrink:0}}var Ju,$u,ed={outline:0},td=Ao(function(e){var t=e.semanticColors,o=e.effects,n=e.fonts,r=t.buttonBorder,i=t.disabledBackground,s=t.disabledText,t={left:-2,top:-2,bottom:-2,right:-2,outlineColor:"ButtonText"};return{root:[bo(e,{inset:1,highContrastStyle:t,borderColor:"transparent"}),e.fonts.medium,{boxSizing:"border-box",border:"1px solid "+r,userSelect:"none",display:"inline-block",textDecoration:"none",textAlign:"center",cursor:"pointer",padding:"0 16px",borderRadius:o.roundedCorner2,selectors:{":active > ":{position:"relative",left:0,top:0}}}],rootDisabled:[bo(e,{inset:1,highContrastStyle:t,borderColor:"transparent"}),{backgroundColor:i,borderColor:i,color:s,cursor:"default",selectors:{":hover":ed,":focus":ed}}],iconDisabled:{color:s,selectors:((i={})[Yt]={color:"GrayText"},i)},menuIconDisabled:{color:s,selectors:((s={})[Yt]={color:"GrayText"},s)},flexContainer:{display:"flex",height:"100%",flexWrap:"nowrap",justifyContent:"center",alignItems:"center"},description:{display:"block"},textContainer:{flexGrow:1,display:"block"},icon:Qu(n.mediumPlus.fontSize),menuIcon:Qu(n.small.fontSize),label:{margin:"0 4px",lineHeight:"100%",display:"block"},screenReaderText:So}}),od=Ao(function(e,t){var o,n=e.effects,r=e.palette,i=e.semanticColors,s={left:-2,top:-2,bottom:-2,right:-2,border:"none"},a={position:"absolute",width:1,right:31,top:8,bottom:8};return un({splitButtonContainer:[bo(e,{highContrastStyle:s,inset:2}),{display:"inline-flex",selectors:{".ms-Button--default":{borderTopRightRadius:"0",borderBottomRightRadius:"0",borderRight:"none"},".ms-Button--primary":{borderTopRightRadius:"0",borderBottomRightRadius:"0",border:"none",selectors:((o={})[Yt]=ht({color:"WindowText",backgroundColor:"Window",border:"1px solid WindowText",borderRightWidth:"0"},{forcedColorAdjust:"none",MsHighContrastAdjust:"none"}),o)},".ms-Button--primary + .ms-Button":{border:"none",selectors:((o={})[Yt]={border:"1px solid WindowText",borderLeftWidth:"0"},o)}}}],splitButtonContainerHovered:{selectors:{".ms-Button--primary":{selectors:((o={})[Yt]={color:"Window",backgroundColor:"Highlight"},o)},".ms-Button.is-disabled":{color:i.buttonTextDisabled,selectors:((i={})[Yt]={color:"GrayText",borderColor:"GrayText",backgroundColor:"Window"},i)}}},splitButtonContainerChecked:{selectors:{".ms-Button--primary":{selectors:((i={})[Yt]=ht({color:"Window",backgroundColor:"WindowText"},{forcedColorAdjust:"none",MsHighContrastAdjust:"none"}),i)}}},splitButtonContainerCheckedHovered:{selectors:{".ms-Button--primary":{selectors:((i={})[Yt]=ht({color:"Window",backgroundColor:"WindowText"},{forcedColorAdjust:"none",MsHighContrastAdjust:"none"}),i)}}},splitButtonContainerFocused:{outline:"none!important"},splitButtonMenuButton:((r={padding:6,height:"auto",boxSizing:"border-box",borderRadius:0,borderTopRightRadius:n.roundedCorner2,borderBottomRightRadius:n.roundedCorner2,border:"1px solid "+r.neutralSecondaryAlt,borderLeft:"none",outline:"transparent",userSelect:"none",display:"inline-block",textDecoration:"none",textAlign:"center",cursor:"pointer",verticalAlign:"top",width:32,marginLeft:-1,marginTop:0,marginRight:0,marginBottom:0})[Yt]={".ms-Button-menuIcon":{color:"WindowText"}},r),splitButtonDivider:ht(ht({},a),{selectors:((r={})[Yt]={backgroundColor:"WindowText"},r)}),splitButtonDividerDisabled:ht(ht({},a),{selectors:((a={})[Yt]={backgroundColor:"GrayText"},a)}),splitButtonMenuButtonDisabled:{pointerEvents:"none",border:"none",selectors:((a={":hover":{cursor:"default"},".ms-Button--primary":{selectors:((a={})[Yt]={color:"GrayText",borderColor:"GrayText",backgroundColor:"Window"},a)},".ms-Button-menuIcon":{selectors:((a={})[Yt]={color:"GrayText"},a)}})[Yt]={color:"GrayText",border:"1px solid GrayText",backgroundColor:"Window"},a)},splitButtonFlexContainer:{display:"flex",height:"100%",flexWrap:"nowrap",justifyContent:"center",alignItems:"center"},splitButtonContainerDisabled:{outline:"none",border:"none",selectors:((a={})[Yt]=ht({color:"GrayText",borderColor:"GrayText",backgroundColor:"Window"},{forcedColorAdjust:"none",MsHighContrastAdjust:"none"}),a)},splitButtonMenuFocused:ht({},bo(e,{highContrastStyle:s,inset:2}))},t)}),nd=Ao(function(e,t){var o=td(e),n=od(e),r=e.palette;return un(o,{root:{padding:"0 4px",width:"32px",height:"32px",backgroundColor:"transparent",border:"none",color:e.semanticColors.link},rootHovered:{color:r.themeDarkAlt,backgroundColor:r.neutralLighter,selectors:((e={})[Yt]={borderColor:"Highlight",color:"Highlight"},e)},rootHasMenu:{width:"auto"},rootPressed:{color:r.themeDark,backgroundColor:r.neutralLight},rootExpanded:{color:r.themeDark,backgroundColor:r.neutralLight},rootChecked:{color:r.themeDark,backgroundColor:r.neutralLight},rootCheckedHovered:{color:r.themeDark,backgroundColor:r.neutralQuaternaryAlt},rootDisabled:{color:r.neutralTertiaryAlt}},n,t)}),rd=(l(id,$u=gt.Component),id.prototype.render=function(){var e=this.props,t=e.styles,e=e.theme;return gt.createElement(Yu,ht({},this.props,{variantClassName:"ms-Button--icon",styles:nd(e,t),onRenderText:wa,onRenderDescription:wa}))},c([Xu("IconButton",["theme","styles"],!0)],id));function id(){return null!==$u&&$u.apply(this,arguments)\|\|this}(W=Ju=Ju\|\|{})[W.horizontal=0]="horizontal",W[W.vertical=1]="vertical";var sd=function(){var o={};return{getCachedMeasurement:function(e){if(e&&e.cacheKey&&o.hasOwnProperty(e.cacheKey))return o[e.cacheKey]},addMeasurementToCache:function(e,t){e.cacheKey&&(o[e.cacheKey]=t)}}},ad=function(e){var a,l=e=void 0===e?sd():e;function c(e,t){var o=l.getCachedMeasurement(e);if(void 0!==o)return o;t=t();return l.addMeasurementToCache(e,t),t}function u(e,t,o){for(var n=e,r=c(e,o);a<r;){var i=t(n);if(void 0===i)return{renderedData:n,resizeDirection:void 0,dataToMeasure:void 0};if(void 0===(r=l.getCachedMeasurement(i)))return{dataToMeasure:i,resizeDirection:"shrink"};n=i}return{renderedData:n,resizeDirection:void 0,dataToMeasure:void 0}}return{getNextState:function(e,t,o,n){if(void 0!==n\|\|void 0!==t.dataToMeasure){if(n){if(a&&t.renderedData&&!t.dataToMeasure)return ht(ht({},t),function(e,t,o,n){o=a<e?n?{resizeDirection:"grow",dataToMeasure:n(o)}:{resizeDirection:"shrink",dataToMeasure:t}:{resizeDirection:"shrink",dataToMeasure:o};return a=e,ht(ht({},o),{measureContainer:!1})}(n,e.data,t.renderedData,e.onGrowData));a=n}n=ht(ht({},t),{measureContainer:!1});return n=t.dataToMeasure?"grow"===t.resizeDirection&&e.onGrowData?ht(ht({},n),function(e,t,o,n){for(var r=e,i=c(e,o);i<a;){var s=t(r);if(void 0===s)return{renderedData:r,resizeDirection:void 0,dataToMeasure:void 0};if(void 0===(i=l.getCachedMeasurement(s)))return{dataToMeasure:s};r=s}return ht({resizeDirection:"shrink"},u(r,n,o))}(t.dataToMeasure,e.onGrowData,o,e.onReduceData)):ht(ht({},n),u(t.dataToMeasure,e.onReduceData,o)):n}},shouldRenderDataForMeasurement:function(e){return!(!e\|\|void 0!==l.getCachedMeasurement(e))},getInitialResizeGroupState:function(e){return{dataToMeasure:ht({},e),resizeDirection:"grow",measureContainer:!0}}}},ld=gt.createContext({isMeasured:!1}),cd={position:"fixed",visibility:"hidden"},ud={position:"relative"};function dd(e,t){var o;switch(t.type){case"resizeData":return ht({},t.value);case"dataToMeasure":return ht(ht({},e),{dataToMeasure:t.value,resizeDirection:"grow",measureContainer:!0});default:return ht(ht({},e),((o={})[t.type]=t.value,o))}}var pd={isMeasured:!0},hd=gt.forwardRef(function(e,t){var o=gt.useRef(null),n=_r(o,t),r=function(o,n){var r=_l(ad),i=gt.useRef(null),s=gt.useRef(null),a=gt.useRef(!1),e=Sl(),t=function(e,t,o){var n=_l(function(){return t.getInitialResizeGroupState(e.data)}),r=gt.useReducer(dd,n),i=r[0],s=r[1];gt.useEffect(function(){s({type:"dataToMeasure",value:e.data})},[e.data]);n=gt.useRef(n);return n.current=ht({},i),[n,gt.useCallback(function(e){e&&s({type:"resizeData",value:e})},[]),gt.useCallback(function(){o.current&&s({type:"measureContainer",value:!0})},[o])]}(o,r,n),l=t[0],c=t[1],u=t[2];gt.useEffect(function(){var e;l.current.renderedData&&(a.current=!0,null===(e=o.dataDidRender)\|\|void 0===e\|\|e.call(o,l.current.renderedData))}),gt.useEffect(function(){e.requestAnimationFrame(function(){var e,t=void 0;l.current.measureContainer&&n.current&&(e=n.current.getBoundingClientRect(),t=o.direction===Ju.vertical?e.height:e.width);t=r.getNextState(o,l.current,function(){var e=a.current?s:i;return e.current?o.direction===Ju.vertical?e.current.scrollHeight:e.current.scrollWidth:0},t);c(t)},n.current)}),xl(wl(),"resize",e.debounce(u,16,{leading:!0}));var d=r.shouldRenderDataForMeasurement(l.current.dataToMeasure),t=!a.current&&d;return[l.current.dataToMeasure,l.current.renderedData,u,i,s,d,t]}(e,o),i=r[0],s=r[1],a=r[2],l=r[3],c=r[4],u=r[5],t=r[6];gt.useImperativeHandle(e.componentRef,function(){return{remeasure:a}},[a]);o=e.className,r=e.onRenderData,e=ur(e,cr,["data"]);return gt.createElement("div",ht({},e,{className:o,ref:n}),gt.createElement("div",{style:ud},u&&!t&&gt.createElement("div",{style:cd,ref:c},gt.createElement(ld.Provider,{value:pd},r(i))),gt.createElement("div",{ref:l,style:t?cd:void 0,"data-automation-id":"visibleContent"},t?r(i):s&&r(s))))});hd.displayName="ResizeGroupBase";var md,gd=hd;function fd(e){return e.clientWidth<e.scrollWidth}function vd(e){return e.clientHeight<e.scrollHeight}function bd(e){return fd(e)\|\|vd(e)}(q=md=md\|\|{})[q.Parent=0]="Parent",q[q.Self=1]="Self";var yd,Cd,_d=Fn(),Sd=(l(kd,Cd=gt.Component),kd.prototype.render=function(){var e=this.props,t=e.className,o=e.calloutProps,n=e.directionalHint,r=e.directionalHintForRTL,i=e.styles,s=e.id,a=e.maxWidth,l=e.onRenderContent,c=void 0===l?this._onRenderContent:l,l=e.targetElement,e=e.theme;return this._classNames=_d(i,{theme:e,className:t\|\|o&&o.className,beakWidth:o&&o.beakWidth,gapSpace:o&&o.gapSpace,maxWidth:a}),gt.createElement(ac,ht({target:l,directionalHint:n,directionalHintForRTL:r},o,ur(this.props,cr,["id"]),{className:this._classNames.root}),gt.createElement("div",{className:this._classNames.content,id:s,onMouseEnter:this.props.onMouseEnter,onMouseLeave:this.props.onMouseLeave},c(this.props,this._onRenderContent)))},kd.defaultProps={directionalHint:Pa.topCenter,maxWidth:"364px",calloutProps:{isBeakVisible:!0,beakWidth:16,gapSpace:0,setInitialFocus:!0,doNotLayer:!1}},kd),xd=In(Sd,function(e){var t=e.className,o=e.beakWidth,n=void 0===o?16:o,r=e.gapSpace,i=void 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wd(){return null}var Id,Dd,Ed=Fn(),Td=(l(Ad,Dd=gt.Component),Ad.prototype.render=function(){var e=this.props,t=e.calloutProps,o=e.children,n=e.content,r=e.directionalHint,i=e.directionalHintForRTL,s=e.hostClassName,a=e.id,l=e.setAriaDescribedBy,c=void 0===l\|\|l,u=e.tooltipProps,d=e.styles,l=e.theme;this._classNames=Ed(d,{theme:l,className:s});e=this.state,d=e.isAriaPlaceholderRendered,l=e.isTooltipVisible,s=a\|\|this._defaultTooltipId,e=!!(n\|\|u&&u.onRenderContent&&u.onRenderContent()),a=l&&e;return gt.createElement("div",ht({className:this._classNames.root,ref:this._tooltipHost},{onFocusCapture:this._onTooltipFocus},{onBlurCapture:this._onTooltipBlur},{onMouseEnter:this._onTooltipMouseEnter,onMouseLeave:this._onTooltipMouseLeave,onKeyDown:this._onTooltipKeyDown,role:"none","aria-describedby":c&&l&&e?s:void 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t=!(!e.onClick&&!e.href);return{text:e.text,name:e.text,key:e.key,onClick:e.onClick?p._onBreadcrumbClicked.bind(p,e):null,href:e.href,disabled:!t,itemProps:t?void 0:Nd}}),u=t.length-1,d=n&&0!==n.length,t=t.map(function(e,t){var o=p._onRenderItem;return e.onRender&&(o=Ma(e.onRender,o)),i&&(o=Ma(i,o)),gt.createElement("li",{className:p._classNames.listItem,key:e.key\|\|String(t)},o(e),(t!==u\|\|d&&t===a-1)&&gt.createElement(r,{className:p._classNames.chevron,iconName:Pn(p.props.theme)?"ChevronLeft":"ChevronRight",item:e}))});d&&t.splice(a,0,gt.createElement("li",{className:p._classNames.overflow,key:"overflow"},gt.createElement(c\|\|rd,{className:p._classNames.overflowButton,iconProps:l?{}:{iconName:"More"},role:"button","aria-haspopup":"true",ariaLabel:s,onRenderMenuIcon:l\|\|wd,menuProps:{items:e,directionalHint:Pa.bottomLeftEdge}}),a!==1+u&&gt.createElement(r,{className:p._classNames.chevron,iconName:Pn(p.props.theme)?"ChevronLeft":"ChevronRight",item:n[n.length-1]})));n=ur(p.props,Wn,["className"]);return gt.createElement("div",ht({className:p._classNames.root,role:"navigation","aria-label":o},n),gt.createElement(Zs,ht({componentRef:p._focusZone,direction:Ei.horizontal},p.props.focusZoneProps),gt.createElement("ol",{className:p._classNames.list},t)))},p._onRenderItem=function(e){if(!e)return null;var t=e.as,o=e.href,n=e.onClick,r=e.isCurrentItem,i=e.text,s=e.onRenderContent,a=mt(e,["as","href","onClick","isCurrentItem","text","onRenderContent"]),l=Ld;return s&&(l=Ma(s,l)),p.props.onRenderItemContent&&(l=Ma(p.props.onRenderItemContent,l)),n\|\|o?gt.createElement(ua,ht({},a,{as:t,className:p._classNames.itemLink,href:o,"aria-current":r?"page":void 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n._tooltipHost.current}},n._onTooltipFocus=function(e){n._ignoreNextFocusEvent?n._ignoreNextFocusEvent=!1:n._onTooltipMouseEnter(e)},n._onTooltipBlur=function(e){n._ignoreNextFocusEvent=(null===document\|\|void 0===document?void 0:document.activeElement)===e.target,n._hideTooltip()},n._onTooltipMouseEnter=function(e){var t=n.props,o=t.overflowMode,t=t.delay;if(Ad._currentVisibleTooltip&&Ad._currentVisibleTooltip!==n&&Ad._currentVisibleTooltip.dismiss(),Ad._currentVisibleTooltip=n,void 0!==o){o=n._getTargetElement();if(o&&!bd(o))return}e.target&&As(e.target,n._getTargetElement())\|\|(n._clearDismissTimer(),n._clearOpenTimer(),t!==yd.zero?(n.setState({isAriaPlaceholderRendered:!0}),t=n._getDelayTime(t),n._openTimerId=n._async.setTimeout(function(){n._toggleTooltip(!0)},t)):n._toggleTooltip(!0))},n._onTooltipMouseLeave=function(e){var t=n.props.closeDelay;n._clearDismissTimer(),n._clearOpenTimer(),t?n._dismissTimerId=n._async.setTimeout(function(){n._toggleTooltip(!1)},t):n._toggleTooltip(!1),Ad._currentVisibleTooltip===n&&(Ad._currentVisibleTooltip=void 0)},n._onTooltipKeyDown=function(e){(e.which===En.escape\|\|e.ctrlKey)&&n.state.isTooltipVisible&&(n._hideTooltip(),e.stopPropagation())},n._clearDismissTimer=function(){n._async.clearTimeout(n._dismissTimerId)},n._clearOpenTimer=function(){n._async.clearTimeout(n._openTimerId)},n._hideTooltip=function(){n._clearOpenTimer(),n._clearDismissTimer(),n._toggleTooltip(!1)},n._toggleTooltip=function(e){n.state.isAriaPlaceholderRendered&&n.setState({isAriaPlaceholderRendered:!1}),n.state.isTooltipVisible!==e&&n.setState({isTooltipVisible:e},function(){return n.props.onTooltipToggle&&n.props.onTooltipToggle(e)})},n._getDelayTime=function(e){switch(e){case yd.medium:return 300;case yd.long:return 500;default:return 0}},fi(n),n.state={isAriaPlaceholderRendered:!1,isTooltipVisible:!1},n._async=new Si(n),n}function Ld(e){return e?gt.createElement(gt.Fragment,null,e.text):null}var Hd,Od,zd={root:"ms-Breadcrumb",list:"ms-Breadcrumb-list",listItem:"ms-Breadcrumb-listItem",chevron:"ms-Breadcrumb-chevron",overflow:"ms-Breadcrumb-overflow",overflowButton:"ms-Breadcrumb-overflowButton",itemLink:"ms-Breadcrumb-itemLink",item:"ms-Breadcrumb-item"},Wd={whiteSpace:"nowrap",textOverflow:"ellipsis",overflow:"hidden"},Vd=uo(0,ro),Kd=uo($t,io),Gd=In(Bd,function(e){var t=e.className,o=e.theme,n=o.palette,r=o.semanticColors,i=o.fonts,s=zo(zd,o),a=r.menuItemBackgroundHovered,l=r.menuItemBackgroundPressed,c=n.neutralSecondary,u=Fe.regular,d=n.neutralPrimary,p=n.neutralPrimary,h=Fe.semibold,e=n.neutralSecondary,r=n.neutralSecondary,p={fontWeight:h,color:p},l={":hover":{color:d,backgroundColor:a,cursor:"pointer",selectors:((a={})[Yt]={color:"Highlight",backgroundColor:"transparent"},a)},":active":{backgroundColor:l,color:d},"&:active:hover":{color:d,backgroundColor:l},"&:active, &:hover, &:active:hover":{textDecoration:"none"}},u={color:c,padding:"0 8px",lineHeight:36,fontSize:18,fontWeight:u};return{root:[s.root,i.medium,{margin:"11px 0 1px"},t],list:[s.list,{whiteSpace:"nowrap",padding:0,margin:0,display:"flex",alignItems:"stretch"}],listItem:[s.listItem,{listStyleType:"none",margin:"0",padding:"0",display:"flex",position:"relative",alignItems:"center",selectors:{"&:last-child 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t=e.semanticColors,o=e.palette,n=t.buttonBackground,r=t.buttonBackgroundPressed,i=t.buttonBackgroundHovered,s=t.buttonBackgroundDisabled,a=t.buttonText,l=t.buttonTextHovered,c=t.buttonTextDisabled,u=t.buttonTextChecked,d=t.buttonTextCheckedHovered;return{root:{backgroundColor:n,color:a},rootHovered:{backgroundColor:i,color:l,selectors:((l={})[Yt]={borderColor:"Highlight",color:"Highlight"},l)},rootPressed:{backgroundColor:r,color:u},rootExpanded:{backgroundColor:r,color:u},rootChecked:{backgroundColor:r,color:u},rootCheckedHovered:{backgroundColor:r,color:d},rootDisabled:{color:c,backgroundColor:s,selectors:((s={})[Yt]={color:"GrayText",borderColor:"GrayText",backgroundColor:"Window"},s)},splitButtonContainer:{selectors:((s={})[Yt]={border:"none"},s)},splitButtonMenuButton:{color:o.white,backgroundColor:"transparent",selectors:{":hover":{backgroundColor:o.neutralLight,selectors:((s={})[Yt]={color:"Highlight"},s)}}},splitButtonMenuButtonDisabled:{backgroundColor:t.buttonBackgroundDisabled,selectors:{":hover":{backgroundColor:t.buttonBackgroundDisabled}}},splitButtonDivider:ht(ht({},{position:"absolute",width:1,right:31,top:8,bottom:8}),{backgroundColor:o.neutralTertiaryAlt,selectors:((s={})[Yt]={backgroundColor:"WindowText"},s)}),splitButtonDividerDisabled:{backgroundColor:e.palette.neutralTertiaryAlt},splitButtonMenuButtonChecked:{backgroundColor:o.neutralQuaternaryAlt,selectors:{":hover":{backgroundColor:o.neutralQuaternaryAlt}}},splitButtonMenuButtonExpanded:{backgroundColor:o.neutralQuaternaryAlt,selectors:{":hover":{backgroundColor:o.neutralQuaternaryAlt}}},splitButtonMenuIcon:{color:t.buttonText},splitButtonMenuIconDisabled:{color:t.buttonTextDisabled}}}function jd(e){var t,o=e.palette,n=e.semanticColors;return{root:{backgroundColor:n.primaryButtonBackground,border:"1px solid "+n.primaryButtonBackground,color:n.primaryButtonText,selectors:((t={})[Yt]=ht({color:"Window",backgroundColor:"WindowText",borderColor:"WindowText"},{forcedColorAdjust:"none",MsHighContrastAdjust:"none"}),t["."+go+" &:focus"]={selectors:{":after":{border:"none",outlineColor:o.white}}},t)},rootHovered:{backgroundColor:n.primaryButtonBackgroundHovered,border:"1px solid "+n.primaryButtonBackgroundHovered,color:n.primaryButtonTextHovered,selectors:((e={})[Yt]={color:"Window",backgroundColor:"Highlight",borderColor:"Highlight"},e)},rootPressed:{backgroundColor:n.primaryButtonBackgroundPressed,border:"1px solid 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qd,Yd,Zd,Xd,Qd,Jd,$d,ep=Ao(function(e,t,o){var n=td(e),r=od(e);return un(n,{root:{minWidth:"80px",height:"32px"},label:{fontWeight:Fe.semibold}},(o?jd:Ud)(e),r,t)}),tp=(l(_p,$d=gt.Component),_p.prototype.render=function(){var e=this.props,t=e.primary,o=void 0!==t&&t,t=e.styles,e=e.theme;return gt.createElement(Yu,ht({},this.props,{variantClassName:o?"ms-Button--primary":"ms-Button--default",styles:ep(e,t,o),onRenderDescription:wa}))},c([Xu("DefaultButton",["theme","styles"],!0)],_p)),op=Ao(function(e,t){var o;return un(td(e),{root:{padding:"0 4px",height:"40px",color:e.palette.neutralPrimary,backgroundColor:"transparent",border:"1px solid 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r=l.dateRangeType,i=l.firstDayOfWeek,s=l.workWeekDays,s=zp(e,r===wp.WorkWeek?wp.Week:r,i,s);return o===n&&(!(!o\|\|!n)\|\|0<s.filter(function(e){return e.getTime()===t.getTime()}).length)}gt.useImperativeHandle(a.componentRef,function(){return{focus:function(){var e,t;null===(t=null===(e=n.current)\|\|void 0===e?void 0:e.focus)\|\|void 0===t\|\|t.call(e)}}},[]);var m=a.styles,g=a.theme,f=a.className,v=a.dateRangeType,t=a.showWeekNumbers,b=a.labelledBy,y=a.lightenDaysOutsideNavigatedMonth,c=a.animationDirection,C=ah(m,{theme:g,className:f,dateRangeType:v,showWeekNumbers:t,lightenDaysOutsideNavigatedMonth:void 0===y\|\|y,animationDirection:c,animateBackwards:s}),u=u(C,i),_={weeks:i,navigatedDayRef:n,calculateRoundedStyles:d,activeDescendantId:e,classNames:C,weekCorners:u,getDayInfosInRangeOfDay:function(e){var t=function(e,t){if(t&&e===wp.WorkWeek){for(var o=t.slice().sort(),n=!0,r=1;r<o.length;r++)if(o[r]!==o[r-1]+1){n=!1;break}if(!n\|\|0===t.length)return wp.Week}return 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t(){a===kh.Previous?null==l\|\|l():null==c\|\|c()}var o=e.styles,n=e.theme,r=e.className,i=void 0===(p=e.navigationIcons)?Ch:p,s=void 0===(h=e.strings)?Sh:h,a=e.direction,l=e.onSelectPrev,c=e.onSelectNext,u=e.fromYear,d=e.toYear,p=e.maxYear,h=e.minYear,n=_h(o,{theme:n,className:r}),r=a===kh.Previous?s.prevRangeAriaLabel:s.nextRangeAriaLabel,s=a===kh.Previous?-12:12,s=r?"string"==typeof r?r:r({fromYear:u+s,toYear:d+s}):void 0,h=a===kh.Previous?void 0!==h&&u<h:void 0!==p&&e.fromYear+12>p,e=Pn()?a===kh.Next:a===kh.Previous;return gt.createElement("button",{className:Tr(n.navigationButton,((p={})[n.disabled]=h,p)),onClick:h?void 0:t,onKeyDown:h?void 0:function(e){e.which===En.enter&&t()},type:"button",title:s,disabled:h},gt.createElement(Wr,{iconName:e?i.leftNavigation:i.rightNavigation}))}wh.displayName="CalendarYearNavArrow";function Ih(e){var t=e.styles,o=e.theme,n=e.className,n=_h(t,{theme:o,className:n});return 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&:hover":{outline:0},"::-ms-clear":{display:"none"}})[Yt]={background:"Window",color:u?"GrayText":"WindowText"},o)},Zo(E),h&&!b&&[I.unresizable,{resize:"none"}],h&&{minHeight:"inherit",lineHeight:17,flexGrow:1,paddingTop:6,paddingBottom:6,overflow:"auto",width:"100%"},h&&_&&{overflow:"hidden"},v&&!S&&{paddingRight:24},h&&v&&{paddingRight:40},u&&[{backgroundColor:x.disabledBackground,color:x.disabledText,borderColor:x.disabledBackground},Zo(T)],f&&{textAlign:"left"},d&&!g&&{selectors:((f={})[Yt]={paddingLeft:11,paddingRight:11},f)},d&&h&&!g&&{selectors:((g={})[Yt]={paddingTop:4},g)},C],icon:[h&&{paddingRight:24,alignItems:"flex-end"},{pointerEvents:"none",position:"absolute",bottom:6,right:8,top:"auto",fontSize:Ae.medium,lineHeight:18},u&&{color:x.disabledText}],description:[I.description,{color:x.bodySubtext,fontSize:w.xSmall.fontSize}],errorMessage:[I.errorMessage,Le.slideDownIn20,w.small,{color:x.errorText,margin:0,paddingTop:5,display:"flex",alignItems:"center"}],prefix:[I.prefix,D],suffix:[I.suffix,D],revealButton:[I.revealButton,"ms-Button","ms-Button--icon",bo(l,{inset:1}),{height:30,width:32,border:"none",padding:"0px 4px",backgroundColor:"transparent",color:x.link,selectors:{":hover":{outline:0,color:x.primaryButtonBackgroundHovered,backgroundColor:x.buttonBackgroundHovered,selectors:((x={})[Yt]={borderColor:"Highlight",color:"Highlight"},x)},":focus":{outline:0}}},v&&{marginRight:28}],revealSpan:{display:"flex",height:"100%",alignItems:"center"},revealIcon:{margin:"0px 4px",pointerEvents:"none",bottom:6,right:8,top:"auto",fontSize:Ae.medium,lineHeight:18},subComponentStyles:{label:(n=(v=e).underlined,r=e.disabled,i=e.focused,s=(v=e.theme).palette,a=v.fonts,function(){var e;return{root:[n&&r&&{color:s.neutralTertiary},n&&{fontSize:a.medium.fontSize,marginRight:8,paddingLeft:12,paddingRight:0,lineHeight:"22px",height:32},n&&i&&{selectors:((e={})[Yt]={height:31},e)}]}})}}},void 0,{scope:"TextField"}),Yg=Fn(),V=(l(af,jg=gt.Component),Object.defineProperty(af.prototype,"color",{get:function(){return this.state.color},enumerable:!1,configurable:!0}),af.prototype.componentDidUpdate=function(e,t){e!==this.props&&this.props.color&&this.setState({color:this.props.color})},af.prototype.componentWillUnmount=function(){this._disposeListeners()},af.prototype.render=function(){var e=this.props,t=e.minSize,o=e.theme,n=e.className,r=e.styles,i=e.ariaValueFormat,s=e.ariaLabel,a=e.ariaDescription,e=this.state.color,t=Yg(r,{theme:o,className:n,minSize:t}),i=i.replace("{0}",String(e.s)).replace("{1}",String(e.v));return gt.createElement("div",{ref:this._root,tabIndex:0,className:t.root,style:{backgroundColor:lg(e)},onMouseDown:this._onMouseDown,onKeyDown:this._onKeyDown,role:"slider","aria-valuetext":i,"aria-valuenow":this._isAdjustingSaturation?e.s:e.v,"aria-valuemin":0,"aria-valuemax":Lm,"aria-label":s,"aria-describedby":this._descriptionId,"data-is-focusable":!0},gt.createElement("div",{className:t.description,id:this._descriptionId},a),gt.createElement("div",{className:t.light}),gt.createElement("div",{className:t.dark}),gt.createElement("div",{className:t.thumb,style:{left:e.s+"%",top:Lm-e.v+"%",backgroundColor:e.str}}))},af.prototype._updateColor=function(e,t){var o=this.props.onChange,n=this.state.color;t.s===n.s&&t.v===n.v\|\|(o&&o(e,t),e.defaultPrevented\|\|(this.setState({color:t}),e.preventDefault()))},af.defaultProps={minSize:220,ariaLabel:"Saturation and brightness",ariaValueFormat:"Saturation {0} brightness {1}",ariaDescription:"Use left and right arrow keys to set saturation. Use up and down arrow keys to set brightness."},af),Zg=In(V,function(e){var t=e.className,o=e.theme,n=e.minSize,r=o.palette,e=o.effects;return{root:["ms-ColorPicker-colorRect",{position:"relative",marginBottom:8,border:"1px solid "+r.neutralLighter,borderRadius:e.roundedCorner2,minWidth:n,minHeight:n,outline:"none",selectors:((o={})[Yt]=ht({},{forcedColorAdjust:"none",MsHighContrastAdjust:"none"}),o["."+go+" &:focus"]=((n={outline:"1px solid "+r.neutralSecondary})[""+Yt]={outline:"2px solid CanvasText"},n),o)},t],light:["ms-ColorPicker-light",{position:"absolute",left:0,right:0,top:0,bottom:0,background:"linear-gradient(to right, white 0%, transparent 100%) /@noflip/"}],dark:["ms-ColorPicker-dark",{position:"absolute",left:0,right:0,top:0,bottom:0,background:"linear-gradient(to bottom, transparent 0, #000 100%)"}],thumb:["ms-ColorPicker-thumb",{position:"absolute",width:20,height:20,background:"white",border:"1px solid "+r.neutralSecondaryAlt,borderRadius:"50%",boxShadow:e.elevation8,transform:"translate(-50%, -50%)",selectors:{":before":{position:"absolute",left:0,right:0,top:0,bottom:0,border:"2px solid "+r.white,borderRadius:"50%",boxSizing:"border-box",content:'""'}}}],description:So}},void 0,{scope:"ColorRectangle"}),Xg=Fn(),xe=(l(sf,Ug=gt.Component),Object.defineProperty(sf.prototype,"value",{get:function(){return this.state.currentValue},enumerable:!1,configurable:!0}),sf.prototype.componentDidUpdate=function(e,t){e!==this.props&&void 0!==this.props.value&&this.setState({currentValue:this.props.value})},sf.prototype.componentWillUnmount=function(){this._disposeListeners()},sf.prototype.render=function(){var e=this._type,t=this._maxValue,o=this.props,n=o.overlayStyle,r=o.overlayColor,i=o.theme,s=o.className,a=o.styles,l=o.ariaLabel,o=void 0===l?e:l,l=this.value,i=Xg(a,{theme:i,className:s,type:e}),s=100l/t;return gt.createElement("div",{ref:this._root,className:i.root,tabIndex:0,onKeyDown:this._onKeyDown,onMouseDown:this._onMouseDown,role:"slider","aria-valuenow":l,"aria-valuetext":String(l),"aria-valuemin":0,"aria-valuemax":t,"aria-label":o,"data-is-focusable":!0},!(!r&&!n)&&gt.createElement("div",{className:i.sliderOverlay,style:r?{background:"transparency"===e?"linear-gradient(to right, #"+r+", transparent)":"linear-gradient(to right, transparent, #"+r+")"}:n}),gt.createElement("div",{className:i.sliderThumb,style:{left:s+"%"}}))},Object.defineProperty(sf.prototype,"_type",{get:function(){var e=this.props,t=e.isAlpha,e=e.type;return void 0===e?t?"alpha":"hue":e},enumerable:!1,configurable:!0}),Object.defineProperty(sf.prototype,"_maxValue",{get:function(){return"hue"===this._type?Am:zm},enumerable:!1,configurable:!0}),sf.prototype._updateValue=function(e,t){var o;t!==this.value&&((o=this.props.onChange)&&o(e,t),e.defaultPrevented\|\|(this.setState({currentValue:t}),e.preventDefault()))},sf.defaultProps={value:0},sf),Qg={background:"linear-gradient("+["to left","red 0","#f09 10%","#cd00ff 20%","#3200ff 30%","#06f 40%","#00fffd 50%","#0f6 60%","#35ff00 70%","#cdff00 80%","#f90 90%","red 100%"].join(",")+")"},Jg={backgroundImage:"url(data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAoAAAAKCAYAAACNMs+9AAAAJUlEQVQYV2N89erVfwY0ICYmxoguxjgUFKI7GsTH5m4M3w1ChQC1/Ca8i2n1WgAAAABJRU5ErkJggg==)"},$g=In(xe,function(e){var t=e.theme,o=e.className,n=e.type,r=e.isAlpha,i=void 0===r?"hue"!==(void 0===n?"hue":n):r,e=t.palette,n=t.effects;return{root:["ms-ColorPicker-slider",{position:"relative",height:20,marginBottom:8,border:"1px solid "+e.neutralLight,borderRadius:n.roundedCorner2,boxSizing:"border-box",outline:"none",forcedColorAdjust:"none",selectors:((r={})["."+go+" &:focus"]=((t={outline:"1px solid "+e.neutralSecondary})[""+Yt]={outline:"2px solid CanvasText"},t),r)},i?Jg:Qg,o],sliderOverlay:["ms-ColorPicker-sliderOverlay",{content:"",position:"absolute",left:0,right:0,top:0,bottom:0}],sliderThumb:["ms-ColorPicker-thumb","is-slider",{position:"absolute",width:20,height:20,background:"white",border:"1px solid "+e.neutralSecondaryAlt,borderRadius:"50%",boxShadow:n.elevation8,transform:"translate(-50%, -50%)",top:"50%",forcedColorAdjust:"auto"}]}},void 0,{scope:"ColorSlider"}),ef=Fn(),tf=["hex","r","g","b","a","t"],of={hex:"hexError",r:"redError",g:"greenError",b:"blueError",a:"alphaError",t:"transparencyError"},nf=(l(rf,Gg=gt.Component),Object.defineProperty(rf.prototype,"color",{get:function(){return this.state.color},enumerable:!1,configurable:!0}),rf.prototype.componentDidUpdate=function(e,t){e===this.props\|\|(e=lf(this.props))&&this._updateColor(void 0,e)},rf.prototype.render=function(){var o=this,e=this.props,t=this._strings,n=this._textLabels,r=e.theme,i=e.className,s=e.styles,a=e.alphaType,l=e.alphaSliderHidden,c=void 0===l?"none"===a:l,u=e.tooltipProps,d=this.state.color,p="transparency"===a,h=["hex","r","g","b",p?"t":"a"],m=p?d.t:d.a,l=p?n.t:n.a,g=ef(s,{theme:r,className:i,alphaType:a}),i=[n.r,d.r,n.g,d.g,n.b,d.b];c\|\|"number"!=typeof m\|\|i.push(l,m+"%");i=t.rootAriaLabelFormat.replace("{0}",i.join(" "));return gt.createElement("div",{className:g.root,role:"group","aria-label":i},gt.createElement("div",{className:g.panel},gt.createElement(Zg,{color:d,onChange:this._onSVChanged,ariaLabel:t.svAriaLabel,ariaDescription:t.svAriaDescription,ariaValueFormat:t.svAriaValueFormat,className:g.colorRectangle}),gt.createElement("div",{className:g.flexContainer},gt.createElement("div",{className:g.flexSlider},gt.createElement($g,{className:"is-hue",type:"hue",ariaLabel:t.hue\|\|t.hueAriaLabel,value:d.h,onChange:this._onHChanged}),!c&&gt.createElement($g,{className:"is-alpha",type:a,ariaLabel:p?t.transparencyAriaLabel:t.alphaAriaLabel,overlayColor:d.hex,value:m,onChange:this._onATChanged})),e.showPreview&&gt.createElement("div",{className:g.flexPreviewBox},gt.createElement("div",{className:g.colorSquare+" is-preview",style:{backgroundColor:d.str}}))),gt.createElement("table",{className:g.table,role:"group",cellPadding:"0",cellSpacing:"0"},gt.createElement("thead",null,gt.createElement("tr",{className:g.tableHeader},gt.createElement("td",{className:g.tableHexCell},n.hex),gt.createElement("td",null,n.r),gt.createElement("td",null,n.g),gt.createElement("td",null,n.b),!c&&gt.createElement("td",{className:g.tableAlphaCell},l))),gt.createElement("tbody",null,gt.createElement("tr",null,h.map(function(e){if(("a"===e\|\|"t"===e)&&c)return null;var t=o._getTooltipValue(e);return gt.createElement("td",{key:e},gt.createElement(Rd,ht({content:t,directionalHint:Pa.bottomCenter,role:"alert"},u),gt.createElement(qg,{className:g.input,onChange:o._textChangeHandlers[e],onBlur:o._onBlur,value:o._getDisplayValue(e),spellCheck:!1,ariaLabel:n[e],autoComplete:"off",invalid:!!t})))}))))))},rf.prototype._getDisplayValue=function(e){var t=this.state,o=t.color,t=t.editingColor;return t&&t.component===e?t.value:"hex"===e?o[e]\|\|"":"number"!=typeof o[e]\|\|isNaN(o[e])?"":String(o[e])},rf.prototype._getTooltipValue=function(e){var t=this.state.editingColor;if(t&&t.component===e){t=t.value;if(!("hex"===e&&t.length>=Wm&&t.length<=Vm))return this._strings[of[e]]}},rf.prototype._onTextChange=function(e,t,o){var n,r=this.state.color,i="hex"===e,s="a"===e,a="t"===e;o=(o\|\|"").substr(0,i?Vm:Gm),(i?Um:jm).test(o)&&(""!==o&&(i?o.length===Vm:s\|\|a?Number(o)<=zm:Number(o)<=Hm)?String(r[e])===o?this.state.editingColor&&this.setState({editingColor:void 0}):(n=i?sg("#"+o):a?Mg(r,Number(o)):ig(ht(ht({},r),((n={})[e]=Number(o),n))),this._updateColor(t,n)):this.setState({editingColor:{component:e,value:o}}))},rf.prototype._updateColor=function(e,t){var o,n;t&&(o=(n=this.state).color,n=n.editingColor,t.h===o.h&&t.str===o.str&&!n\|\|e&&this.props.onChange&&(this.props.onChange(e,t),e.defaultPrevented)\|\|this.setState({color:t,editingColor:void 0}))},rf.defaultProps={alphaType:"alpha",strings:{rootAriaLabelFormat:"Color picker, {0} selected.",hex:"Hex",red:"Red",green:"Green",blue:"Blue",alpha:"Alpha",transparency:"Transparency",hueAriaLabel:"Hue",svAriaLabel:V.defaultProps.ariaLabel,svAriaValueFormat:V.defaultProps.ariaValueFormat,svAriaDescription:V.defaultProps.ariaDescription,hexError:"Hex values must be between 3 and 6 characters long",alphaError:"Alpha must be between 0 and 100",transparencyError:"Transparency must be between 0 and 100",redError:"Red must be between 0 and 255",greenError:"Green must be between 0 and 255",blueError:"Blue must be between 0 and 255"}},rf);function rf(e){var l=Gg.call(this,e)\|\|this;l._onSVChanged=function(e,t){l._updateColor(e,t)},l._onHChanged=function(e,t){l._updateColor(e,ug(l.state.color,t))},l._onATChanged=function(e,t){var o="transparency"===l.props.alphaType?Mg:pg;l._updateColor(e,o(l.state.color,Math.round(t)))},l._onBlur=function(e){var t,o,n,r,i=l.state,s=i.color,a=i.editingColor;a&&(t=a.value,n="a"===(o=a.component),r="t"===o,t.length>=((i="hex"===o)?Wm:Km)&&(i\|\|!isNaN(Number(t)))?(a=void 0,a=i?sg("#"+gg(t)):n\|\|r?(n?pg:Mg)(s,Jm(Number(t),zm)):ig(hg(ht(ht({},s),((s={})[o]=Number(t),s)))),l._updateColor(e,a)):l.setState({editingColor:void 0}))},fi(l);var t=e.strings;t.hue&&Xo("ColorPicker property 'strings.hue' was used but has been deprecated. Use 'strings.hueAriaLabel' instead."),l.state={color:lf(e)\|\|sg("#ffffff")},l._textChangeHandlers={};for(var o=0,n=tf;o<n.length;o++){var r=n[o];l._textChangeHandlers[r]=l._onTextChange.bind(l,r)}var i=rf.defaultProps.strings;return l._textLabels={r:e.redLabel\|\|t.red\|\|i.red,g:e.greenLabel\|\|t.green\|\|i.green,b:e.blueLabel\|\|t.blue\|\|i.blue,a:e.alphaLabel\|\|t.alpha\|\|i.alpha,hex:e.hexLabel\|\|t.hex\|\|i.hex,t:t.transparency\|\|i.transparency},l._strings=ht(ht(ht({},i),{alphaAriaLabel:l._textLabels.a,transparencyAriaLabel:l._textLabels.t}),t),l}function sf(e){var r=Ug.call(this,e)\|\|this;return r._disposables=[],r._root=gt.createRef(),r._onKeyDown=function(e){var t=r.value,o=r._maxValue,n=e.shiftKey?10:1;switch(e.which){case En.left:t-=n;break;case En.right:t+=n;break;case En.home:t=0;break;case En.end:t=o;break;default:return}r._updateValue(e,Jm(t,o))},r._onMouseDown=function(e){var t=qe(r);t&&r._disposables.push(Wa(t,"mousemove",r._onMouseMove,!0),Wa(t,"mouseup",r._disposeListeners,!0)),r._onMouseMove(e)},r._onMouseMove=function(e){var t,o;r._root.current&&(o=r._maxValue,t=r._root.current.getBoundingClientRect(),t=(e.clientX-t.left)/t.width,o=Jm(Math.round(to),o),r._updateValue(e,o))},r._disposeListeners=function(){r._disposables.forEach(function(e){return e()}),r._disposables=[]},fi(r),"hue"===r._type\|\|e.overlayColor\|\|e.overlayStyle\|\|Xo("ColorSlider: 'overlayColor' is required when 'type' is \"alpha\" or \"transparency\""),r.state={currentValue:e.value\|\|0},r}function af(e){var i=jg.call(this,e)\|\|this;return i._disposables=[],i._root=gt.createRef(),i._isAdjustingSaturation=!0,i._descriptionId=_s("ColorRectangle-description"),i._onKeyDown=function(e){var t=i.state.color,o=t.s,n=t.v,r=e.shiftKey?10:1;switch(e.which){case En.up:i._isAdjustingSaturation=!1,n+=r;break;case En.down:i._isAdjustingSaturation=!1,n-=r;break;case En.left:i._isAdjustingSaturation=!0,o-=r;break;case En.right:i._isAdjustingSaturation=!0,o+=r;break;default:return}i._updateColor(e,cg(t,Jm(o,Fm),Jm(n,Lm)))},i._onMouseDown=function(e){i._disposables.push(Wa(window,"mousemove",i._onMouseMove,!0),Wa(window,"mouseup",i._disposeListeners,!0)),i._onMouseMove(e)},i._onMouseMove=function(e){var t,o,n,r;i._root.current&&(t=e,o=i.state.color,n=i._root.current.getBoundingClientRect(),r=(t.clientX-n.left)/n.width,n=(t.clientY-n.top)/n.height,(n=cg(o,Jm(Math.round(rFm),Fm),Jm(Math.round(Lm-nLm),Lm)))&&i._updateColor(e,n))},i._disposeListeners=function(){i._disposables.forEach(function(e){return e()}),i._disposables=[]},fi(i),i.state={color:e.color},i}function lf(e){e=e.color;return"string"==typeof e?sg(e):e}var cf,uf,df,pf=In(nf,function(e){var t=e.className,o=e.theme,e=e.alphaType;return{root:["ms-ColorPicker",o.fonts.medium,{position:"relative",maxWidth:300},t],panel:["ms-ColorPicker-panel",{padding:"16px"}],table:["ms-ColorPicker-table",{tableLayout:"fixed",width:"100%",selectors:{"tbody td:last-of-type .ms-ColorPicker-input":{paddingRight:0}}}],tableHeader:[o.fonts.small,{selectors:{td:{paddingBottom:4}}}],tableHexCell:{width:"25%"},tableAlphaCell:"transparency"===e&&{width:"22%"},colorSquare:["ms-ColorPicker-colorSquare",{width:48,height:48,margin:"0 0 0 8px",border:"1px solid #c8c6c4"}],flexContainer:{display:"flex"},flexSlider:{flexGrow:"1"},flexPreviewBox:{flexGrow:"0"},input:["ms-ColorPicker-input",{width:"100%",border:"none",boxSizing:"border-box",height:30,selectors:{"&.ms-TextField":{paddingRight:4},"& .ms-TextField-field":{minWidth:"auto",padding:5,textOverflow:"clip"}}}]}},void 0,{scope:"ColorPicker"}),hf=Ao(function(e){var e=e.semanticColors;return{backgroundColor:e.disabledBackground,color:e.disabledText,cursor:"default",selectors:((e={":after":{borderColor:e.disabledBackground}})[Yt]={color:"GrayText",selectors:{":after":{borderColor:"GrayText"}}},e)}}),mf={selectors:((G={})[Yt]=ht({backgroundColor:"Highlight",borderColor:"Highlight",color:"HighlightText"},{forcedColorAdjust:"none",MsHighContrastAdjust:"none"}),G)},gf={selectors:((Y={})[Yt]=ht({color:"WindowText",backgroundColor:"Window"},{forcedColorAdjust:"none",MsHighContrastAdjust:"none"}),Y)},ff=Ao(function(e,t,o,n,r,i){var s=e.palette,a=e.semanticColors,a={textHoveredColor:a.menuItemTextHovered,textSelectedColor:s.neutralDark,textDisabledColor:a.disabledText,backgroundHoveredColor:a.menuItemBackgroundHovered,backgroundPressedColor:a.menuItemBackgroundPressed};return un({root:[e.fonts.medium,{backgroundColor:n?a.backgroundHoveredColor:"transparent",boxSizing:"border-box",cursor:"pointer",display:r?"none":"block",width:"100%",height:"auto",minHeight:36,lineHeight:"20px",padding:"0 8px",position:"relative",borderWidth:"1px",borderStyle:"solid",borderColor:"transparent",borderRadius:0,wordWrap:"break-word",overflowWrap:"break-word",textAlign:"left",selectors:ht(ht(((n={})[Yt]={border:"none",borderColor:"Background"},n),!r&&{"&.ms-Checkbox":{display:"flex",alignItems:"center"}}),{"&.ms-Button--command:hover:active":{backgroundColor:a.backgroundPressedColor},".ms-Checkbox-label":{width:"100%"}})},i?[{backgroundColor:"transparent",color:a.textSelectedColor,selectors:{":hover":[{backgroundColor:a.backgroundHoveredColor},mf]}},bo(e,{inset:-1,isFocusedOnly:!1}),mf]:[]],rootHovered:{backgroundColor:a.backgroundHoveredColor,color:a.textHoveredColor},rootFocused:{backgroundColor:a.backgroundHoveredColor},rootDisabled:{color:a.textDisabledColor,cursor:"default"},optionText:{overflow:"hidden",whiteSpace:"nowrap",textOverflow:"ellipsis",minWidth:"0px",maxWidth:"100%",wordWrap:"break-word",overflowWrap:"break-word",display:"inline-block"},optionTextWrapper:{maxWidth:"100%",display:"flex",alignItems:"center"}},t,o)}),vf=Ao(function(e,t){var o,n=e.semanticColors,r=e.fonts,i={buttonTextColor:n.bodySubtext,buttonTextHoveredCheckedColor:n.buttonTextChecked,buttonBackgroundHoveredColor:n.listItemBackgroundHovered,buttonBackgroundCheckedColor:n.listItemBackgroundChecked,buttonBackgroundCheckedHoveredColor:n.listItemBackgroundCheckedHovered},n={selectors:((o={})[Yt]=ht({backgroundColor:"Highlight",borderColor:"Highlight",color:"HighlightText"},{forcedColorAdjust:"none",MsHighContrastAdjust:"none"}),o)};return un({root:{color:i.buttonTextColor,fontSize:r.small.fontSize,position:"absolute",top:0,height:"100%",lineHeight:30,width:32,textAlign:"center",cursor:"default",selectors:((o={})[Yt]=ht({backgroundColor:"ButtonFace",borderColor:"ButtonText",color:"ButtonText"},{forcedColorAdjust:"none",MsHighContrastAdjust:"none"}),o)},icon:{fontSize:r.small.fontSize},rootHovered:[{backgroundColor:i.buttonBackgroundHoveredColor,color:i.buttonTextHoveredCheckedColor,cursor:"pointer"},n],rootPressed:[{backgroundColor:i.buttonBackgroundCheckedColor,color:i.buttonTextHoveredCheckedColor},n],rootChecked:[{backgroundColor:i.buttonBackgroundCheckedColor,color:i.buttonTextHoveredCheckedColor},n],rootCheckedHovered:[{backgroundColor:i.buttonBackgroundCheckedHoveredColor,color:i.buttonTextHoveredCheckedColor},n],rootDisabled:[hf(e),{position:"absolute"}]},t)}),bf=Ao(function(e,t,o){var n=e.semanticColors,r=e.fonts,i=e.effects,s={textColor:n.inputText,borderColor:n.inputBorder,borderHoveredColor:n.inputBorderHovered,borderPressedColor:n.inputFocusBorderAlt,borderFocusedColor:n.inputFocusBorderAlt,backgroundColor:n.inputBackground,erroredColor:n.errorText},a={headerTextColor:n.menuHeader,dividerBorderColor:n.bodyDivider},l={selectors:((h={})[Yt]={color:"GrayText"},h)},c=[{color:n.inputPlaceholderText},l],u=[{color:n.inputTextHovered},l],d=[{color:n.disabledText},l],p=ht(ht({color:"HighlightText",backgroundColor:"Window"},{forcedColorAdjust:"none",MsHighContrastAdjust:"none"}),{selectors:{":after":{borderColor:"Highlight"}}}),h=_o(s.borderPressedColor,i.roundedCorner2,"border",0);return un({container:{},label:{},labelDisabled:{},root:[e.fonts.medium,{boxShadow:"none",marginLeft:"0",paddingRight:32,paddingLeft:9,color:s.textColor,position:"relative",outline:"0",userSelect:"none",backgroundColor:s.backgroundColor,cursor:"text",display:"block",height:32,whiteSpace:"nowrap",textOverflow:"ellipsis",boxSizing:"border-box",selectors:{".ms-Label":{display:"inline-block",marginBottom:"8px"},"&.is-open":{selectors:((l={})[Yt]=p,l)},":after":{pointerEvents:"none",content:"''",position:"absolute",left:0,top:0,bottom:0,right:0,borderWidth:"1px",borderStyle:"solid",borderColor:s.borderColor,borderRadius:i.roundedCorner2}}}],rootHovered:{selectors:((u={":after":{borderColor:s.borderHoveredColor},".ms-ComboBox-Input":[{color:n.inputTextHovered},Zo(u),gf]})[Yt]=ht(ht({color:"HighlightText",backgroundColor:"Window"},{forcedColorAdjust:"none",MsHighContrastAdjust:"none"}),{selectors:{":after":{borderColor:"Highlight"}}}),u)},rootPressed:[{position:"relative",selectors:((u={})[Yt]=p,u)}],rootFocused:[{selectors:((u={".ms-ComboBox-Input":[{color:n.inputTextHovered},gf]})[Yt]=p,u)},h],rootDisabled:hf(e),rootError:{selectors:{":after":{borderColor:s.erroredColor},":hover:after":{borderColor:n.inputBorderHovered}}},rootDisallowFreeForm:{},input:[Zo(c),{backgroundColor:s.backgroundColor,color:s.textColor,boxSizing:"border-box",width:"100%",height:"100%",borderStyle:"none",outline:"none",font:"inherit",textOverflow:"ellipsis",padding:"0",selectors:{"::-ms-clear":{display:"none"}}},gf],inputDisabled:[hf(e),Zo(d)],errorMessage:[e.fonts.small,{color:s.erroredColor,marginTop:"5px"}],callout:{boxShadow:i.elevation8},optionsContainerWrapper:{width:o},optionsContainer:{display:"block"},screenReaderText:So,header:[r.medium,{fontWeight:Fe.semibold,color:a.headerTextColor,backgroundColor:"none",borderStyle:"none",height:36,lineHeight:36,cursor:"default",padding:"0 8px",userSelect:"none",textAlign:"left",selectors:((r={})[Yt]=ht({color:"GrayText"},{forcedColorAdjust:"none",MsHighContrastAdjust:"none"}),r)}],divider:{height:1,backgroundColor:a.dividerBorderColor}},t)}),yf=Ao(function(e,t,o,n,r,i,s,a){return{container:j("ms-ComboBox-container",t,e.container),label:j(e.label,n&&e.labelDisabled),root:j("ms-ComboBox",a?e.rootError:o&&"is-open",r&&"is-required",e.root,!s&&e.rootDisallowFreeForm,a&&!i?e.rootError:!n&&i&&e.rootFocused,!n&&{selectors:{":hover":a?e.rootError:!o&&!i&&e.rootHovered,":active":a?e.rootError:e.rootPressed,":focus":a?e.rootError:e.rootFocused}},n&&["is-disabled",e.rootDisabled]),input:j("ms-ComboBox-Input",e.input,n&&e.inputDisabled),errorMessage:j(e.errorMessage),callout:j("ms-ComboBox-callout",e.callout),optionsContainerWrapper:j("ms-ComboBox-optionsContainerWrapper",e.optionsContainerWrapper),optionsContainer:j("ms-ComboBox-optionsContainer",e.optionsContainer),header:j("ms-ComboBox-header",e.header),divider:j("ms-ComboBox-divider",e.divider),screenReaderText:j(e.screenReaderText)}}),Cf=Ao(function(e){return{optionText:j("ms-ComboBox-optionText",e.optionText),root:j("ms-ComboBox-option",e.root,{selectors:{":hover":e.rootHovered,":focus":e.rootFocused,":active":e.rootPressed}}),optionTextWrapper:j(e.optionTextWrapper)}});function _f(e,t){for(var o=[],n=0,r=t;n<r.length;n++){var i=e[r[n]];i&&o.push(i)}return o}(ke=cf=cf\|\|{})[ke.Normal=0]="Normal",ke[ke.Divider=1]="Divider",ke[ke.Header=2]="Header",ke[ke.SelectAll=3]="SelectAll",(K=uf=uf\|\|{})[K.backward=-1]="backward",K[K.none=0]="none",K[K.forward=1]="forward",(U=df=df\|\|{})[U.clearAll=-2]="clearAll",U[U.default=-1]="default";var Sf=gt.memo(function(e){return(0,e.render)()},function(e,t){e.render;e=mt(e,["render"]);return t.render,da(e,mt(t,["render"]))}),xf={options:[],allowFreeform:!1,autoComplete:"on",buttonIconProps:{iconName:"ChevronDown"}},kf=gt.forwardRef(function(e,t){var o,n,r,i,s,a,l,c=Hn(xf,e),u=(c.ref,mt(c,["ref"])),d=gt.useRef(null),p=_r(d,t),c=(o=u.options,n=u.defaultSelectedKey,r=u.selectedKey,i=gt.useState(function(){return Ef(o,(e=Tf(n)).length?e:Tf(r));var e}),e=i[0],s=i[1],c=gt.useState(o),t=c[0],a=c[1],i=gt.useState(),c=i[0],l=i[1],gt.useEffect(function(){var e;void 0!==r&&(e=Tf(r),e=Ef(o,e),s(e)),a(o)},[o,r]),gt.useEffect(function(){null===r&&l(void 0)},[r]),[e,s,t,a,c,l]);return gt.createElement(If,ht({},u,{hoisted:{mergedRootRef:p,rootRef:d,selectedIndices:c[0],setSelectedIndices:c[1],currentOptions:c[2],setCurrentOptions:c[3],suggestedDisplayValue:c[4],setSuggestedDisplayValue:c[5]}}))});kf.displayName="ComboBox";var wf,If=(l(Df,wf=gt.Component),Object.defineProperty(Df.prototype,"selectedOptions",{get:function(){var e=this.props.hoisted;return _f(e.currentOptions,e.selectedIndices)},enumerable:!1,configurable:!0}),Df.prototype.componentDidMount=function(){this._comboBoxWrapper.current&&!this.props.disabled&&(this._events.on(this._comboBoxWrapper.current,"focus",this._onResolveOptions,!0),"onpointerdown"in this._comboBoxWrapper.current&&this._events.on(this._comboBoxWrapper.current,"pointerdown",this._onPointerDown,!0))},Df.prototype.componentDidUpdate=function(e,t){var o=this,n=this.props,r=n.allowFreeform,i=n.text,s=n.onMenuOpen,a=n.onMenuDismissed,l=n.hoisted.selectedIndices,c=this.state,n=c.isOpen,c=c.currentPendingValueValidIndex;!n\|\|t.isOpen&&t.currentPendingValueValidIndex===c\|\|this._async.setTimeout(function(){return o._scrollIntoView()},0),this._hasFocus()&&(n\|\|t.isOpen&&!n&&this._focusInputAfterClose&&this._autofill.current&&document.activeElement!==this._autofill.current.inputElement)&&this.focus(void 0,!0),this._focusInputAfterClose&&(t.isOpen&&!n\|\|this._hasFocus()&&(!n&&!this.props.multiSelect&&e.hoisted.selectedIndices&&l&&e.hoisted.selectedIndices[0]!==l[0]\|\|!r\|\|i!==e.text))&&this._onFocus(),this._notifyPendingValueChanged(t),n&&!t.isOpen&&s&&s(),!n&&t.isOpen&&a&&a()},Df.prototype.componentWillUnmount=function(){this._async.dispose(),this._events.dispose()},Df.prototype.render=function(){var e=this._id+"-error",t=this.props,o=t.className,n=t.disabled,r=t.required,i=t.errorMessage,s=t.onRenderContainer,a=void 0===s?this._onRenderContainer:s,l=t.onRenderLabel,c=void 0===l?this._onRenderLabel:l,u=t.onRenderList,d=void 0===u?this._onRenderList:u,p=t.onRenderItem,h=void 0===p?this._onRenderItem:p,m=t.onRenderOption,g=void 0===m?this._onRenderOptionContent:m,f=t.allowFreeform,v=t.styles,b=t.theme,s=t.persistMenu,l=t.multiSelect,u=t.hoisted,p=u.suggestedDisplayValue,m=u.selectedIndices,t=u.currentOptions,u=this.state.isOpen;this._currentVisibleValue=this._getVisibleValue();l=l?this._getMultiselectDisplayString(m,t,p):void 0,m=ur(this.props,cr,["onChange","value"]),p=!!(i&&0<i.length);this._classNames=this.props.getClassNames?this.props.getClassNames(b,!!u,!!n,!!r,!!this._hasFocus(),!!f,!!p,o):yf(bf(b,v),o,!!u,!!n,!!r,!!this._hasFocus(),!!f,!!p);f=this._renderComboBoxWrapper(l,e);return gt.createElement("div",ht({},m,{ref:this.props.hoisted.mergedRootRef,className:this._classNames.container}),c({props:this.props,multiselectAccessibleText:l},this._onRenderLabel),f,(s\|\|u)&&a(ht(ht({},this.props),{onRenderList:d,onRenderItem:h,onRenderOption:g,options:t.map(function(e,t){return ht(ht({},e),{index:t})}),onDismiss:this._onDismiss}),this._onRenderContainer),p&&gt.createElement("div",{role:"alert",id:e,className:this._classNames.errorMessage},i))},Df.prototype._getPendingString=function(e,t,o){return null!=e?e:Rf(t,o)?t[o].text:""},Df.prototype._getMultiselectDisplayString=function(e,t,o){for(var n=[],r=0;e&&r<e.length;r++){var i=e[r];t[i].itemType!==cf.SelectAll&&n.push(Rf(t,i)?t[i].text:o\|\|"")}var s=this.props.multiSelectDelimiter;return n.join(void 0===s?", ":s)},Df.prototype._processInputChangeWithFreeform=function(t){var e=this.props.hoisted.currentOptions,o=-1;if(""===t)return 1===(r=e.map(function(e,t){return ht(ht({},e),{index:t})}).filter(function(e){return Mf(e)&&Bf(e)===t})).length&&(o=r[0].index),void this._setPendingInfo(t,o,t);var n=t;t=t.toLocaleLowerCase();var r,i,s="";"on"===this.props.autoComplete?0<(r=e.map(function(e,t){return ht(ht({},e),{index:t})}).filter(function(e){return Mf(e)&&0===Bf(e).toLocaleLowerCase().indexOf(t)})).length&&(s=(i=Bf(r[0])).toLocaleLowerCase()!==t?i:"",o=r[0].index):1===(r=e.map(function(e,t){return ht(ht({},e),{index:t})}).filter(function(e){return Mf(e)&&Bf(e).toLocaleLowerCase()===t})).length&&(o=r[0].index),this._setPendingInfo(n,o,s)},Df.prototype._processInputChangeWithoutFreeform=function(t){var e=this,o=this.props.hoisted.currentOptions,n=this.state,r=n.currentPendingValue,n=n.currentPendingValueValidIndex;if("on"===this.props.autoComplete&&""!==t){this._autoCompleteTimeout&&(this._async.clearTimeout(this._autoCompleteTimeout),this._autoCompleteTimeout=void 0,t=(r\|\|"")+t);r=t;t=t.toLocaleLowerCase();o=o.map(function(e,t){return ht(ht({},e),{index:t})}).filter(function(e){return Mf(e)&&0===e.text.toLocaleLowerCase().indexOf(t)});return 0<o.length&&this._setPendingInfo(r,o[0].index,Bf(o[0])),void(this._autoCompleteTimeout=this._async.setTimeout(function(){e._autoCompleteTimeout=void 0},1e3))}n=0<=n?n:this._getFirstSelectedIndex();this._setPendingInfoFromIndex(n)},Df.prototype._getFirstSelectedIndex=function(){var e=this.props.hoisted.selectedIndices;return null!=e&&e.length?e[0]:-1},Df.prototype._getNextSelectableIndex=function(e,t){var o=this.props.hoisted.currentOptions,n=e+t;if(!Rf(o,n=Math.max(0,Math.min(o.length-1,n))))return-1;var r=o[n];if(!Nf(r)\|\|!0===r.hidden){if(t===uf.none\|\|!(0<n&&t<uf.none\|\|0<=n&&n<o.length&&t>uf.none))return e;n=this._getNextSelectableIndex(n,t)}return n},Df.prototype._setSelectedIndex=function(t,e,o){void 0===o&&(o=uf.none);var n=this.props,r=n.onChange,i=n.onPendingValueChanged,s=n.hoisted,n=s.selectedIndices,s=s.currentOptions,a=n?n.slice():[],l=s.slice();if(Rf(s,t=this._getNextSelectableIndex(t,o))){if(this.props.multiSelect\|\|a.length<1\|\|1===a.length&&a[0]!==t){var c,n=ht({},s[t]);if(!n\|\|n.disabled)return;this.props.multiSelect?(n.selected=void 0!==n.selected?!n.selected:a.indexOf(t)<0,n.itemType===cf.SelectAll?(a=[],n.selected?s.forEach(function(e,t){!e.disabled&&Nf(e)&&(a.push(t),l[t]=ht(ht({},e),{selected:!0}))}):l=s.map(function(e){return ht(ht({},e),{selected:!1})})):(n.selected&&a.indexOf(t)<0?a.push(t):!n.selected&&0<=a.indexOf(t)&&(a=a.filter(function(e){return e!==t})),l[t]=n,(o=l.filter(function(e){return e.itemType===cf.SelectAll})[0])&&(s=this._isSelectAllChecked(a),c=l.indexOf(o),s?(a.push(c),l[c]=ht(ht({},o),{selected:!0})):(a=a.filter(function(e){return e!==c}),l[c]=ht(ht({},o),{selected:!1}))))):a[0]=t,e.persist(),this.props.selectedKey\|\|null===this.props.selectedKey\|\|(this.props.hoisted.setSelectedIndices(a),this.props.hoisted.setCurrentOptions(l)),this._hasPendingValue&&i&&(i(),this._hasPendingValue=!1),r&&r(e,n,t,void 0)}this.props.multiSelect&&this.state.isOpen\|\|this._clearPendingInfo()}},Df.prototype._submitPendingValue=function(e){var t=this.props,o=t.onChange,n=t.allowFreeform,r=t.autoComplete,i=t.multiSelect,s=t.hoisted,a=s.currentOptions,l=this.state,c=l.currentPendingValue,u=l.currentPendingValueValidIndex,d=l.currentPendingValueValidIndexOnHover,t=this.props.hoisted.selectedIndices;if(!this._processingClearPendingInfo){if(n){if(null==c)return void(0<=d&&(this._setSelectedIndex(d,e),this._clearPendingInfo()));if(Rf(a,u)){var l=Bf(a[u]).toLocaleLowerCase(),n=this._autofill.current;if(c.toLocaleLowerCase()===l\|\|r&&0===l.indexOf(c.toLocaleLowerCase())&&null!=n&&n.isValueSelected&&c.length+(n.selectionEnd-n.selectionStart)===l.length\|\|(null===(n=null==n?void 0:n.inputElement)\|\|void 0===n?void 0:n.value.toLocaleLowerCase())===l)return this._setSelectedIndex(u,e),i&&this.state.isOpen?void 0:void this._clearPendingInfo()}o?o(e,void 0,void 0,c):(c={key:c\|\|_s(),text:c\|\|""},i&&(c.selected=!0),c=a.concat([c]),t&&(t=!i?[]:t).push(c.length-1),s.setCurrentOptions(c),s.setSelectedIndices(t))}else 0<=u?this._setSelectedIndex(u,e):0<=d&&this._setSelectedIndex(d,e);this._clearPendingInfo()}},Df.prototype._onCalloutLayerMounted=function(){this._gotMouseMove=!1},Df.prototype._renderSeparator=function(e){var t=e.index,e=e.key;return t&&0<t?gt.createElement("div",{role:"separator",key:e,className:this._classNames.divider}):null},Df.prototype._renderHeader=function(e){var t=this.props.onRenderOption,t=void 0===t?this._onRenderOptionContent:t;return gt.createElement("div",{id:e.id,key:e.key,className:this._classNames.header},t(e,this._onRenderOptionContent))},Df.prototype._isOptionHighlighted=function(e){var t=this.state.currentPendingValueValidIndexOnHover;return t!==df.clearAll&&(0<=t?t===e:this._isOptionSelected(e))},Df.prototype._isOptionSelected=function(e){return this._getPendingSelectedIndex(!0)===e},Df.prototype._isOptionChecked=function(e){return!(!this.props.multiSelect\|\|void 0===e\|\|!this.props.hoisted.selectedIndices)&&0<=this.props.hoisted.selectedIndices.indexOf(e)},Df.prototype._isOptionIndeterminate=function(e){var t=this.props,o=t.multiSelect,t=t.hoisted;if(o&&void 0!==e&&t.selectedIndices&&t.currentOptions){e=t.currentOptions[e];if(e&&e.itemType===cf.SelectAll)return 0<t.selectedIndices.length&&!this._isSelectAllChecked()}return!1},Df.prototype._isSelectAllChecked=function(e){var t=this.props,o=t.multiSelect,n=t.hoisted,t=n.currentOptions.find(function(e){return e.itemType===cf.SelectAll}),e=e\|\|n.selectedIndices;if(!o\|\|!e\|\|!t)return!1;var r=n.currentOptions.indexOf(t),e=e.filter(function(e){return e!==r}),n=n.currentOptions.filter(function(e){return!e.disabled&&e.itemType!==cf.SelectAll&&Nf(e)});return e.length===n.length},Df.prototype._getPendingSelectedIndex=function(e){var t=this.state,o=t.currentPendingValueValidIndex,t=t.currentPendingValue;return 0<=o\|\|e&&null!=t?o:this.props.multiSelect?0:this._getFirstSelectedIndex()},Df.prototype._scrollIntoView=function(){var e,t,o=this.props,n=o.onScrollToItem,r=o.scrollSelectedToTop,i=this.state,s=i.currentPendingValueValidIndex,a=i.currentPendingValue;n?n(0<=s\|\|""!==a?s:this._getFirstSelectedIndex()):this._selectedElement.current&&this._selectedElement.current.offsetParent&&(e=!0,this._comboBoxMenu.current&&this._comboBoxMenu.current.offsetParent?(t=this._comboBoxMenu.current.offsetParent,i=(o=this._selectedElement.current.offsetParent).offsetHeight,n=o.offsetTop,a=t.offsetHeight,o=(s=t.scrollTop)+a<n+i,n<s\|\|r?(e=!1,t.scrollTo(0,n)):o&&t.scrollTo(0,n-a+i)):this._selectedElement.current.offsetParent.scrollIntoView(e))},Df.prototype._onItemClick=function(t){var o=this,n=this.props.onItemClick,r=t.index;return function(e){o.props.multiSelect\|\|(o._autofill.current&&o._autofill.current.focus(),o.setState({isOpen:!1})),n&&n(e,t,r),o._setSelectedIndex(r,e)}},Df.prototype._resetSelectedIndex=function(){var e=this.props.hoisted.currentOptions;this._clearPendingInfo();var t=this._getFirstSelectedIndex();0<t&&t<e.length?this.props.hoisted.setSuggestedDisplayValue(e[t].text):this.props.text&&this.props.hoisted.setSuggestedDisplayValue(this.props.text)},Df.prototype._clearPendingInfo=function(){this._processingClearPendingInfo=!0,this.props.hoisted.setSuggestedDisplayValue(void 0),this.setState({currentPendingValue:void 0,currentPendingValueValidIndex:-1,currentPendingValueValidIndexOnHover:df.default},this._onAfterClearPendingInfo)},Df.prototype._setPendingInfo=function(e,t,o){void 0===t&&(t=-1),this._processingClearPendingInfo\|\|(this.props.hoisted.setSuggestedDisplayValue(o),this.setState({currentPendingValue:e\|\|"",currentPendingValueValidIndex:t,currentPendingValueValidIndexOnHover:df.default}))},Df.prototype._setPendingInfoFromIndex=function(e){var t=this.props.hoisted.currentOptions;0<=e&&e<t.length?(t=t[e],this._setPendingInfo(Bf(t),e,Bf(t))):this._clearPendingInfo()},Df.prototype._setPendingInfoFromIndexAndDirection=function(e,t){var o=this.props.hoisted.currentOptions;t===uf.forward&&e>=o.length-1?e=-1:t===uf.backward&&e<=0&&(e=o.length);var n=this._getNextSelectableIndex(e,t);e===n?t===uf.forward?e=this._getNextSelectableIndex(-1,t):t===uf.backward&&(e=this._getNextSelectableIndex(o.length,t)):e=n,Rf(o,e)&&this._setPendingInfoFromIndex(e)},Df.prototype._notifyPendingValueChanged=function(e){var t,o,n,r,i,s,a=this.props.onPendingValueChanged;a&&(t=this.props.hoisted.currentOptions,o=(r=this.state).currentPendingValue,n=r.currentPendingValueValidIndex,s=i=void 0,(r=r.currentPendingValueValidIndexOnHover)!==e.currentPendingValueValidIndexOnHover&&Rf(t,r)?i=r:n!==e.currentPendingValueValidIndex&&Rf(t,n)?i=n:o!==e.currentPendingValue&&(s=o),void 0===i&&void 0===s&&!this._hasPendingValue\|\|(a(void 0!==i?t[i]:void 0,i,s),this._hasPendingValue=void 0!==i\|\|void 0!==s))},Df.prototype._setOpenStateAndFocusOnClose=function(e,t){this._focusInputAfterClose=t,this.setState({isOpen:e})},Df.prototype._onOptionMouseEnter=function(e){this._shouldIgnoreMouseEvent()\|\|this.setState({currentPendingValueValidIndexOnHover:e})},Df.prototype._onOptionMouseMove=function(e){this._gotMouseMove=!0,this._isScrollIdle&&this.state.currentPendingValueValidIndexOnHover!==e&&this.setState({currentPendingValueValidIndexOnHover:e})},Df.prototype._shouldIgnoreMouseEvent=function(){return!this._isScrollIdle\|\|!this._gotMouseMove},Df.prototype._handleInputWhenDisabled=function(e){this.props.disabled&&(this.state.isOpen&&this.setState({isOpen:!1}),null!==e&&e.which!==En.tab&&e.which!==En.escape&&(e.which<112\|\|123<e.which)&&(e.stopPropagation(),e.preventDefault()))},Df.prototype._handleTouchAndPointerEvent=function(){var e=this;void 0!==this._lastTouchTimeoutId&&(this._async.clearTimeout(this._lastTouchTimeoutId),this._lastTouchTimeoutId=void 0),this._processingTouch=!0,this._lastTouchTimeoutId=this._async.setTimeout(function(){e._processingTouch=!1,e._lastTouchTimeoutId=void 0},500)},Df.prototype._getCaretButtonStyles=function(){var e=this.props.caretDownButtonStyles;return vf(this.props.theme,e)},Df.prototype._getCurrentOptionStyles=function(e){var t=this.props.comboBoxOptionStyles,o=e.styles;return ff(this.props.theme,t,o,this._isPendingOption(e),e.hidden,this._isOptionHighlighted(e.index))},Df.prototype._getAriaActiveDescendantValue=function(){var e=this.props.hoisted.selectedIndices,t=this.state,o=t.isOpen,t=t.currentPendingValueValidIndex,e=o&&null!=e&&e.length?this._id+"-list"+e[0]:void 0;return e=o&&this._hasFocus()&&-1!==t?this._id+"-list"+t:e},Df.prototype._getAriaAutoCompleteValue=function(){return this.props.disabled\|\|"on"!==this.props.autoComplete?"none":this.props.allowFreeform?"inline":"both"},Df.prototype._isPendingOption=function(e){return e&&e.index===this.state.currentPendingValueValidIndex},Df.prototype._hasFocus=function(){return"none"!==this.state.focusState},c([Xu("ComboBox",["theme","styles"],!0)],Df));function Df(e){var v=wf.call(this,e)\|\|this;return v._autofill=gt.createRef(),v._comboBoxWrapper=gt.createRef(),v._comboBoxMenu=gt.createRef(),v._selectedElement=gt.createRef(),v.focus=function(e,t){v.props.disabled\|\|(v._autofill.current&&(t?gs(v._autofill.current):v._autofill.current.focus(),e&&v.setState({isOpen:!0})),v._hasFocus()\|\|v.setState({focusState:"focused"}))},v.dismissMenu=function(){v.state.isOpen&&v.setState({isOpen:!1})},v._onUpdateValueInAutofillWillReceiveProps=function(){var e=v._autofill.current;if(!e)return null;if(null===e.value\|\|void 0===e.value)return null;var t=Pf(v._currentVisibleValue);return e.value!==t?t:e.value},v._renderComboBoxWrapper=function(e,t){var o=v.props,n=o.label,r=o.disabled,i=o.ariaLabel,s=o.ariaDescribedBy,a=o.required,l=o.errorMessage,c=o.buttonIconProps,u=o.isButtonAriaHidden,d=void 0===u\|\|u,p=o.title,h=o.placeholder,m=o.tabIndex,g=o.autofill,f=o.iconButtonProps,u=o.hoisted.suggestedDisplayValue,o=v.state.isOpen,h=v._hasFocus()&&v.props.multiSelect&&e?e:h;return gt.createElement("div",{"data-ktp-target":!0,ref:v._comboBoxWrapper,id:v._id+"wrapper",className:v._classNames.root,"aria-owns":o?v._id+"-list":void 0},gt.createElement(ki,ht({"data-ktp-execute-target":!0,"data-is-interactable":!r,componentRef:v._autofill,id:v._id+"-input",className:v._classNames.input,type:"text",onFocus:v._onFocus,onBlur:v._onBlur,onKeyDown:v._onInputKeyDown,onKeyUp:v._onInputKeyUp,onClick:v._onAutofillClick,onTouchStart:v._onTouchStart,onInputValueChange:v._onInputChange,"aria-expanded":o,"aria-autocomplete":v._getAriaAutoCompleteValue(),role:"combobox",readOnly:r,"aria-labelledby":n&&v._id+"-label","aria-label":i&&!n?i:void 0,"aria-describedby":void 0!==l?Ia(s,t):s,"aria-activedescendant":v._getAriaActiveDescendantValue(),"aria-required":a,"aria-disabled":r,"aria-controls":o?v._id+"-list":void 0,spellCheck:!1,defaultVisibleValue:v._currentVisibleValue,suggestedDisplayValue:u,updateValueInWillReceiveProps:v._onUpdateValueInAutofillWillReceiveProps,shouldSelectFullInputValueInComponentDidUpdate:v._onShouldSelectFullInputValueInAutofillComponentDidUpdate,title:p,preventValueSelection:!v._hasFocus(),placeholder:h,tabIndex:r?-1:m},g)),gt.createElement(rd,ht({className:"ms-ComboBox-CaretDown-button",styles:v._getCaretButtonStyles(),role:"presentation","aria-hidden":d,"data-is-focusable":!1,tabIndex:-1,onClick:v._onComboBoxClick,onBlur:v._onBlur,iconProps:c,disabled:r,checked:o},f)))},v._onShouldSelectFullInputValueInAutofillComponentDidUpdate=function(){return v._currentVisibleValue===v.props.hoisted.suggestedDisplayValue},v._getVisibleValue=function(){var e=v.props,t=e.text,o=e.allowFreeform,n=e.autoComplete,r=e.hoisted,i=r.suggestedDisplayValue,s=r.selectedIndices,a=r.currentOptions,l=v.state,c=l.currentPendingValueValidIndex,e=l.currentPendingValue,r=l.isOpen,l=Rf(a,c);if((!r\|\|!l)&&t&&null==e)return t;if(v.props.multiSelect){if(v._hasFocus()){var u="on"===n&&l?c:-1;return v._getPendingString(e,a,u)}return v._getMultiselectDisplayString(s,a,i)}return u=v._getFirstSelectedIndex(),o?v._getPendingString(e,a,u="on"===n&&l?c:u):l&&"on"===n?(u=c,e\|\|""):!v.state.isOpen&&e?Rf(a,u)?e:i\|\|"":Rf(a,u)?Bf(a[u]):i\|\|""},v._onInputChange=function(e){v.props.disabled?v._handleInputWhenDisabled(null):(v.props.onInputValueChange&&v.props.onInputValueChange(e),v.props.allowFreeform?v._processInputChangeWithFreeform(e):v._processInputChangeWithoutFreeform(e))},v._onFocus=function(){var e;null===(e=null===(e=v._autofill.current)\|\|void 0===e?void 0:e.inputElement)\|\|void 0===e\|\|e.select(),v._hasFocus()\|\|v.setState({focusState:"focusing"})},v._onResolveOptions=function(){var t;v.props.onResolveOptions&&(t=v.props.onResolveOptions($e([],v.props.hoisted.currentOptions)),Array.isArray(t)?v.props.hoisted.setCurrentOptions(t):t&&t.then&&(v._currentPromise=t).then(function(e){t===v._currentPromise&&v.props.hoisted.setCurrentOptions(e)}))},v._onBlur=function(e){var t=e.relatedTarget;if(t=null===e.relatedTarget?document.activeElement:t){var o=null===(n=v.props.hoisted.rootRef.current)\|\|void 0===n?void 0:n.contains(t),n=null===(r=v._comboBoxMenu.current)\|\|void 0===r?void 0:r.contains(t),r=v._comboBoxMenu.current&&Qi(v._comboBoxMenu.current,function(e){return e===t});if(o\|\|n\|\|r)return r&&v._hasFocus()&&(!v.props.multiSelect\|\|v.props.allowFreeform)&&v._submitPendingValue(e),e.preventDefault(),void e.stopPropagation()}v._hasFocus()&&(v.setState({focusState:"none"}),v.props.multiSelect&&!v.props.allowFreeform\|\|v._submitPendingValue(e))},v._onRenderContainer=function(e,t){var o=e.onRenderList,n=e.calloutProps,r=e.dropdownWidth,i=e.dropdownMaxWidth,s=e.onRenderUpperContent,a=void 0===s?v._onRenderUpperContent:s,l=e.onRenderLowerContent,c=void 0===l?v._onRenderLowerContent:l,u=e.useComboBoxAsMenuWidth,d=e.persistMenu,p=e.shouldRestoreFocus,h=void 0===p\|\|p,s=v.state.isOpen,l=v._id,p=u&&v._comboBoxWrapper.current?v._comboBoxWrapper.current.clientWidth+2:void 0;return gt.createElement(ac,ht({isBeakVisible:!1,gapSpace:0,doNotLayer:!1,directionalHint:Pa.bottomLeftEdge,directionalHintFixed:!1},n,{onLayerMounted:v._onLayerMounted,className:Tr(v._classNames.callout,null==n?void 0:n.className),target:v._comboBoxWrapper.current,onDismiss:v._onDismiss,onMouseDown:v._onCalloutMouseDown,onScroll:v._onScroll,setInitialFocus:!1,calloutWidth:u&&v._comboBoxWrapper.current?p:r,calloutMaxWidth:i\|\|p,hidden:d?!s:void 0,shouldRestoreFocus:h}),a(v.props,v._onRenderUpperContent),gt.createElement("div",{className:v._classNames.optionsContainerWrapper,ref:v._comboBoxMenu},null==o?void 0:o(ht(ht({},e),{id:l}),v._onRenderList)),c(v.props,v._onRenderLowerContent))},v._onLayerMounted=function(){v._onCalloutLayerMounted(),v._async.setTimeout(function(){v._scrollIntoView()},0),v.props.calloutProps&&v.props.calloutProps.onLayerMounted&&v.props.calloutProps.onLayerMounted()},v._onRenderLabel=function(e){var t=e.props,o=t.label,n=t.disabled,t=t.required;return o?gt.createElement(om,{id:v._id+"-label",disabled:n,required:t,className:v._classNames.label},o,e.multiselectAccessibleText&&gt.createElement("span",{className:v._classNames.screenReaderText},e.multiselectAccessibleText)):null},v._onRenderList=function(e){function n(){var e=s.id?[gt.createElement("div",{role:"group",key:s.id,"aria-labelledby":s.id},s.items)]:s.items;a=$e($e([],a),e),s={items:[]}}var t=e.onRenderItem,r=void 0===t?v._onRenderItem:t,o=e.label,i=e.ariaLabel,t=e.multiSelect,s={items:[]},a=[];e.options.forEach(function(e,t){!function(e,t){switch(e.itemType){case cf.Header:0<s.items.length&&n();var o=v._id+e.key;s.items.push(r(ht(ht({id:o},e),{index:t}),v._onRenderItem)),s.id=o;break;case cf.Divider:0<t&&s.items.push(r(ht(ht({},e),{index:t}),v._onRenderItem)),0<s.items.length&&n();break;default:s.items.push(r(ht(ht({},e),{index:t}),v._onRenderItem))}}(e,t)}),0<s.items.length&&n();e=v._id;return gt.createElement("div",{id:e+"-list",className:v._classNames.optionsContainer,"aria-labelledby":o&&e+"-label","aria-label":i&&!o?i:void 0,"aria-multiselectable":t?"true":void 0,role:"listbox"},a)},v._onRenderItem=function(e){switch(e.itemType){case cf.Divider:return v._renderSeparator(e);case cf.Header:return v._renderHeader(e);default:return v._renderOption(e)}},v._onRenderLowerContent=function(){return null},v._onRenderUpperContent=function(){return null},v._renderOption=function(e){function t(){return n(e,v._onRenderOptionContent)}var o=v.props.onRenderOption,n=void 0===o?v._onRenderOptionContent:o,r=v._id,i=v._isOptionSelected(e.index),s=v._isOptionChecked(e.index),a=v._isOptionIndeterminate(e.index),l=v._getCurrentOptionStyles(e),c=Cf(v._getCurrentOptionStyles(e)),u=e.title;return gt.createElement(Sf,{key:e.key,index:e.index,disabled:e.disabled,isSelected:i,isChecked:s,isIndeterminate:a,text:e.text,render:function(){return v.props.multiSelect?gt.createElement($h,{id:r+"-list"+e.index,ariaLabel:e.ariaLabel,key:e.key,styles:l,className:"ms-ComboBox-option",onChange:v._onItemClick(e),label:e.text,checked:s,indeterminate:a,title:u,disabled:e.disabled,onRenderLabel:t,inputProps:ht({"aria-selected":s?"true":"false",role:"option"},{"data-index":e.index,"data-is-focusable":!0})}):gt.createElement(up,{id:r+"-list"+e.index,key:e.key,"data-index":e.index,styles:l,checked:i,className:"ms-ComboBox-option",onClick:v._onItemClick(e),onMouseEnter:v._onOptionMouseEnter.bind(v,e.index),onMouseMove:v._onOptionMouseMove.bind(v,e.index),onMouseLeave:v._onOptionMouseLeave,role:"option","aria-selected":i?"true":"false",ariaLabel:e.ariaLabel,disabled:e.disabled,title:u},gt.createElement("span",{className:c.optionTextWrapper,ref:i?v._selectedElement:void 0},n(e,v._onRenderOptionContent)))},data:e.data})},v._onCalloutMouseDown=function(e){e.preventDefault()},v._onScroll=function(){v._isScrollIdle\|\|void 0===v._scrollIdleTimeoutId?v._isScrollIdle=!1:(v._async.clearTimeout(v._scrollIdleTimeoutId),v._scrollIdleTimeoutId=void 0),v._scrollIdleTimeoutId=v._async.setTimeout(function(){v._isScrollIdle=!0},250)},v._onRenderOptionContent=function(e){var t=Cf(v._getCurrentOptionStyles(e));return gt.createElement("span",{className:t.optionText},e.text)},v._onDismiss=function(){var e=v.props.onMenuDismiss;e&&e(),v.props.persistMenu&&v._onCalloutLayerMounted(),v._setOpenStateAndFocusOnClose(!1,!1),v._resetSelectedIndex()},v._onAfterClearPendingInfo=function(){v._processingClearPendingInfo=!1},v._onInputKeyDown=function(e){var t=v.props,o=t.disabled,n=t.allowFreeform,r=t.autoComplete,i=t.hoisted.currentOptions,t=v.state,s=t.isOpen,a=t.currentPendingValueValidIndexOnHover;if(v._lastKeyDownWasAltOrMeta=Ff(e),o)v._handleInputWhenDisabled(e);else{var l=v._getPendingSelectedIndex(!1);switch(e.which){case En.enter:v._autofill.current&&v._autofill.current.inputElement&&v._autofill.current.inputElement.select(),v._submitPendingValue(e),v.props.multiSelect&&s?v.setState({currentPendingValueValidIndex:l}):(s\|\|(!n\|\|void 0===v.state.currentPendingValue\|\|null===v.state.currentPendingValue\|\|v.state.currentPendingValue.length<=0)&&v.state.currentPendingValueValidIndex<0)&&v.setState({isOpen:!s});break;case En.tab:return v.props.multiSelect\|\|v._submitPendingValue(e),void(s&&v._setOpenStateAndFocusOnClose(!s,!1));case En.escape:if(v._resetSelectedIndex(),!s)return;v.setState({isOpen:!1});break;case En.up:if(a===df.clearAll&&(l=v.props.hoisted.currentOptions.length),e.altKey\|\|e.metaKey){if(s){v._setOpenStateAndFocusOnClose(!s,!0);break}return}e.preventDefault(),v._setPendingInfoFromIndexAndDirection(l,uf.backward);break;case En.down:e.altKey\|\|e.metaKey?v._setOpenStateAndFocusOnClose(!0,!0):(a===df.clearAll&&(l=-1),e.preventDefault(),v._setPendingInfoFromIndexAndDirection(l,uf.forward));break;case En.home:case En.end:if(n)return;var l=-1,c=uf.forward;e.which===En.end&&(l=i.length,c=uf.backward),v._setPendingInfoFromIndexAndDirection(l,c);break;case En.space:if(!n&&"off"===r)break;default:if(112<=e.which&&e.which<=123)return;if(e.keyCode===En.alt\|\|"Meta"===e.key)return;if(n\|\|"on"!==r)return;v._onInputChange(e.key)}e.stopPropagation(),e.preventDefault()}},v._onInputKeyUp=function(e){var t=v.props,o=t.disabled,n=t.allowFreeform,r=t.autoComplete,i=v.state.isOpen,t=v._lastKeyDownWasAltOrMeta&&Ff(e);v._lastKeyDownWasAltOrMeta=!1;t=t&&!(Na()\|\|Aa());o?v._handleInputWhenDisabled(e):e.which!==En.space?t&&i?v._setOpenStateAndFocusOnClose(!i,!0):("focusing"===v.state.focusState&&v.props.openOnKeyboardFocus&&v.setState({isOpen:!0}),"focused"!==v.state.focusState&&v.setState({focusState:"focused"})):n\|\|"off"!==r\|\|v._setOpenStateAndFocusOnClose(!i,!!i)},v._onOptionMouseLeave=function(){v._shouldIgnoreMouseEvent()\|\|v.props.persistMenu&&!v.state.isOpen\|\|v.setState({currentPendingValueValidIndexOnHover:df.clearAll})},v._onComboBoxClick=function(){var e=v.props.disabled,t=v.state.isOpen;e\|\|(v._setOpenStateAndFocusOnClose(!t,!1),v.setState({focusState:"focused"}))},v._onAutofillClick=function(){var e=v.props,t=e.disabled;e.allowFreeform&&!t?v.focus(v.state.isOpen\|\|v._processingTouch):v._onComboBoxClick()},v._onTouchStart=function(){!v._comboBoxWrapper.current\|\|"onpointerdown"in v._comboBoxWrapper\|\|v._handleTouchAndPointerEvent()},v._onPointerDown=function(e){"touch"===e.pointerType&&(v._handleTouchAndPointerEvent(),e.preventDefault(),e.stopImmediatePropagation())},fi(v),v._async=new Si(v),v._events=new va(v),v._id=e.id\|\|_s("ComboBox"),v._isScrollIdle=!0,v._processingTouch=!1,v._gotMouseMove=!1,v._processingClearPendingInfo=!1,v.state={isOpen:!1,focusState:"none",currentPendingValueValidIndex:-1,currentPendingValue:void 0,currentPendingValueValidIndexOnHover:df.default},v}function Ef(o,e){if(!o\|\|!e)return[];var n={};o.forEach(function(e,t){e.selected&&(n[t]=!0)});for(var t=0,r=e;t<r.length;t++)!function(t){var e=Hi(o,function(e){return e.key===t});-1<e&&(n[e]=!0)}(r[t]);return Object.keys(n).map(Number).sort()}function Tf(e){return void 0===e?[]:e instanceof Array?e:[e]}function Pf(e){return e\|\|""}function Rf(e,t){return!!e&&0<=t&&t<e.length}function Mf(e){return e.itemType!==cf.Header&&e.itemType!==cf.Divider&&e.itemType!==cf.SelectAll}function Nf(e){return e.itemType!==cf.Header&&e.itemType!==cf.Divider}function Bf(e){return e.useAriaLabelAsText&&e.ariaLabel?e.ariaLabel:e.text}function Ff(e){return e.which===En.alt\|\|"Meta"===e.key}var Af,Lf={auto:0,top:1,bottom:2,center:3},Hf={top:-1,bottom:-1,left:-1,right:-1,width:0,height:0},xe=function(e){return e.getBoundingClientRect()},Of=xe,zf=xe,Wf=(l(Vf,Af=gt.Component),Vf.getDerivedStateFromProps=function(e,t){return t.getDerivedStateFromProps(e,t)},Object.defineProperty(Vf.prototype,"pageRefs",{get:function(){return this._pageRefs},enumerable:!1,configurable:!0}),Vf.prototype.scrollToIndex=function(e,t,o){void 0===o&&(o=Lf.auto);for(var n=this.props.startIndex,r=n+this._getRenderCount(),i=this._allowedRect,s=0,a=n;a<r;a+=u){var l=this._getPageSpecification(a,i),c=l.height,u=l.itemCount;if(a<=e&&e<a+u){if(t&&this._scrollElement){for(var d=zf(this._scrollElement),p=this._scrollElement.scrollTop,l=this._scrollElement.scrollTop+d.height,h=e-a,m=0;m<h;++m)s+=t(a+m);var g=s+t(e);switch(o){case Lf.top:return void(this._scrollElement.scrollTop=s);case Lf.bottom:return void(this._scrollElement.scrollTop=g-d.height);case Lf.center:return void(this._scrollElement.scrollTop=(s+g-d.height)/2);case Lf.auto:}if(p<=s&&g<=l)return;s<p\|\|l<g&&(s=g-d.height)}return void(this._scrollElement&&(this._scrollElement.scrollTop=s))}s+=c}},Vf.prototype.getStartItemIndexInView=function(e){for(var t=0,o=this.state.pages\|\|[];t<o.length;t++){var n=o[t];if(!n.isSpacer&&(this._scrollTop\|\|0)>=n.top&&(this._scrollTop\|\|0)<=n.top+n.height){if(!e){var r=Math.floor(n.height/n.itemCount);return n.startIndex+Math.floor((this._scrollTop-n.top)/r)}for(var i=0,s=n.startIndex;s<n.startIndex+n.itemCount;s++){if(r=e(s),n.top+i<=this._scrollTop&&this._scrollTop<n.top+i+r)return s;i+=r}}}return 0},Vf.prototype.componentDidMount=function(){this.setState(this._updatePages(this.props,this.state)),this._measureVersion++,this._scrollElement=Ns(this._root.current),this._events.on(window,"resize",this._onAsyncResize),this._root.current&&this._events.on(this._root.current,"focus",this._onFocus,!0),this._scrollElement&&(this._events.on(this._scrollElement,"scroll",this._onScroll),this._events.on(this._scrollElement,"scroll",this._onAsyncScroll))},Vf.prototype.componentDidUpdate=function(e,t){var o=this.props,n=this.state;this.state.pagesVersion!==t.pagesVersion&&(!o.getPageHeight&&this._updatePageMeasurements(n.pages)?(this._materializedRect=null,this._hasCompletedFirstRender?this._onAsyncScroll():(this._hasCompletedFirstRender=!0,this.setState(this._updatePages(o,n)))):this._onAsyncIdle(),o.onPagesUpdated&&o.onPagesUpdated(n.pages))},Vf.prototype.componentWillUnmount=function(){this._async.dispose(),this._events.dispose(),delete this._scrollElement},Vf.prototype.shouldComponentUpdate=function(e,t){var o=this.state.pages,n=t.pages,r=!1;if(!t.isScrolling&&this.state.isScrolling)return!0;if(e.version!==this.props.version)return!0;if(e.items===this.props.items&&o.length===n.length)for(var i=0;i<o.length;i++){var s=o[i],a=n[i];if(s.key!==a.key\|\|s.itemCount!==a.itemCount){r=!0;break}}else r=!0;return r},Vf.prototype.forceUpdate=function(){this._invalidatePageCache(),this._updateRenderRects(this.props,this.state,!0),this.setState(this._updatePages(this.props,this.state)),this._measureVersion++,Af.prototype.forceUpdate.call(this)},Vf.prototype.getTotalListHeight=function(){return this._surfaceRect.height},Vf.prototype.render=function(){for(var e=this.props,t=e.className,o=e.role,n=void 0===o?"list":o,r=e.onRenderSurface,i=e.onRenderRoot,o=this.state.pages,e=void 0===o?[]:o,s=[],o=ur(this.props,cr),a=0,l=e;a<l.length;a++){var c=l[a];s.push(this._renderPage(c))}r=r?Ma(r,this._onRenderSurface):this._onRenderSurface;return(i?Ma(i,this._onRenderRoot):this._onRenderRoot)({rootRef:this._root,pages:e,surfaceElement:r({surfaceRef:this._surface,pages:e,pageElements:s,divProps:{role:"presentation",className:"ms-List-surface"}}),divProps:ht(ht({},o),{className:Tr("ms-List",t),role:0<s.length?n:void 0,"aria-label":0<s.length?o["aria-label"]:void 0})})},Vf.prototype._shouldVirtualize=function(e){var t=(e=void 0===e?this.props:e).onShouldVirtualize;return!t\|\|t(e)},Vf.prototype._invalidatePageCache=function(){this._pageCache={}},Vf.prototype._renderPage=function(t){var o=this,e=this.props.usePageCache;if(e&&(r=this._pageCache[t.key])&&r.pageElement)return r.pageElement;var n=this._getPageStyle(t),r=this.props.onRenderPage,n=(void 0===r?this._onRenderPage:r)({page:t,className:"ms-List-page",key:t.key,ref:function(e){o._pageRefs[t.key]=e},style:n,role:"presentation"},this._onRenderPage);return e&&0===t.startIndex&&(this._pageCache[t.key]={page:t,pageElement:n}),n},Vf.prototype._getPageStyle=function(e){var t=this.props.getPageStyle;return ht(ht({},t?t(e):{}),e.items?{}:{height:e.height})},Vf.prototype._onFocus=function(e){for(var t=e.target;t!==this._surface.current;){var o=t.getAttribute("data-list-index");if(o){this._focusedIndex=Number(o);break}t=Xi(t)}},Vf.prototype._onScroll=function(){this.state.isScrolling\|\|this.props.ignoreScrollingState\|\|this.setState({isScrolling:!0}),this._resetRequiredWindows(),this._onScrollingDone()},Vf.prototype._resetRequiredWindows=function(){this._requiredWindowsAhead=0,this._requiredWindowsBehind=0},Vf.prototype._onAsyncScroll=function(){var e,t;this._updateRenderRects(this.props,this.state),this._materializedRect&&(e=this._requiredRect,t=this._materializedRect,e.top>=t.top&&e.left>=t.left&&e.bottom<=t.bottom&&e.right<=t.right)\|\|this.setState(this._updatePages(this.props,this.state))},Vf.prototype._onAsyncIdle=function(){var e=this.props,t=e.renderedWindowsAhead,o=e.renderedWindowsBehind,n=this._requiredWindowsAhead,r=this._requiredWindowsBehind,i=Math.min(t,n+1),e=Math.min(o,r+1);i===n&&e===r\|\|(this._requiredWindowsAhead=i,this._requiredWindowsBehind=e,this._updateRenderRects(this.props,this.state),this.setState(this._updatePages(this.props,this.state))),(i<t\|\|e<o)&&this._onAsyncIdle()},Vf.prototype._onScrollingDone=function(){this.props.ignoreScrollingState\|\|this.setState({isScrolling:!1})},Vf.prototype._onAsyncResize=function(){this.forceUpdate()},Vf.prototype._updatePages=function(e,t){this._requiredRect\|\|this._updateRenderRects(e,t);var o=this._buildPages(e,t),e=t.pages;return this._notifyPageChanges(e,o.pages,this.props),ht(ht(ht({},t),o),{pagesVersion:{}})},Vf.prototype._notifyPageChanges=function(e,t,o){var n=o.onPageAdded,o=o.onPageRemoved;if(n\|\|o){for(var r={},i=0,s=e;i<s.length;i++)(a=s[i]).items&&(r[a.startIndex]=a);for(var a,l,c=0,u=t;c<u.length;c++)(a=u[c]).items&&(r[a.startIndex]?delete r[a.startIndex]:this._onPageAdded(a));for(l in r)r.hasOwnProperty(l)&&this._onPageRemoved(r[l])}},Vf.prototype._updatePageMeasurements=function(e){var t=!1;if(!this._shouldVirtualize())return t;for(var o=0;o<e.length;o++){var n=e[o];n.items&&(t=this._measurePage(n)\|\|t)}return t},Vf.prototype._measurePage=function(e){var t=!1,o=this._pageRefs[e.key],n=this._cachedPageHeights[e.startIndex];return!o\|\|!this._shouldVirtualize()\|\|n&&n.measureVersion===this._measureVersion\|\|((o={width:o.clientWidth,height:o.clientHeight}).height\|\|o.width)&&(t=e.height!==o.height,e.height=o.height,this._cachedPageHeights[e.startIndex]={height:o.height,measureVersion:this._measureVersion},this._estimatedPageHeight=Math.round((this._estimatedPageHeightthis._totalEstimates+o.height)/(this._totalEstimates+1)),this._totalEstimates++),t},Vf.prototype._onPageAdded=function(e){var t=this.props.onPageAdded;t&&t(e)},Vf.prototype._onPageRemoved=function(e){var t=this.props.onPageRemoved;t&&t(e)},Vf.prototype._buildPages=function(e,l){e.renderCount;for(var c=e.items,u=e.startIndex,t=e.getPageHeight,o=this._getRenderCount(e),d=ht({},Hf),p=[],h=1,m=0,g=null,f=this._focusedIndex,v=u+o,b=this._shouldVirtualize(e),y=0===this._estimatedPageHeight&&!t,C=this._allowedRect,_=this,n=u;n<v&&"break"!==function(t){var e=_._getPageSpecification(t,C),o=e.height,n=e.data,r=e.key;h=e.itemCount;var i=m+o-1,s=-1<Hi(l.pages,function(e){return e.items&&e.startIndex===t}),a=!C\|\|i>=C.top&&m<=C.bottom,e=!_._requiredRect\|\|i>=_._requiredRect.top&&m<=_._requiredRect.bottom;if(!y&&(e\|\|a&&s)\|\|!b\|\|t<=f&&f<t+h\|\|t===u?(g&&(p.push(g),g=null),s=Math.min(h,v-t),(s=_._createPage(r,c.slice(t,t+s),t,void 0,void 0,n)).top=m,s.height=o,_._visibleRect&&_._visibleRect.bottom&&(s.isVisible=i>=_._visibleRect.top&&m<=_._visibleRect.bottom),p.push(s),e&&_._allowedRect&&(e={top:m,bottom:i,height:o,left:C.left,right:C.right,width:C.width},(o=d).top=(e.top<o.top\|\|-1===o.top?e:o).top,o.left=(e.left<o.left\|\|-1===o.left?e:o).left,o.bottom=(e.bottom>o.bottom\|\|-1===o.bottom?e:o).bottom,o.right=(e.right>o.right\|\|-1===o.right?e:o).right,o.width=o.right-o.left+1,o.height=o.bottom-o.top+1)):((g=g\|\|_._createPage("spacer-"+t,void 0,t,0,void 0,n,!0)).height=(g.height\|\|0)+(i-m)+1,g.itemCount+=h),m+=i-m+1,y&&b)return"break"}(n);n+=h);return g&&(g.key="spacer-end",p.push(g)),this._materializedRect=d,ht(ht({},l),{pages:p,measureVersion:this._measureVersion})},Vf.prototype._getPageSpecification=function(e,t){var o=this.props.getPageSpecification;if(o){var n=o(e,t),o=n.itemCount,r=void 0===o?this._getItemCountForPage(e,t):o,o=n.height;return{itemCount:r,height:void 0===o?this._getPageHeight(e,t,r):o,data:n.data,key:n.key}}return{itemCount:r=this._getItemCountForPage(e,t),height:this._getPageHeight(e,t,r)}},Vf.prototype._getPageHeight=function(e,t,o){if(this.props.getPageHeight)return this.props.getPageHeight(e,t,o);e=this._cachedPageHeights[e];return e?e.height:this._estimatedPageHeight\|\|30},Vf.prototype._getItemCountForPage=function(e,t){return(this.props.getItemCountForPage?this.props.getItemCountForPage(e,t):10)\|\|10},Vf.prototype._createPage=function(e,t,o,n,r,i,s){void 0===o&&(o=-1),void 0===n&&(n=t?t.length:0),void 0===r&&(r={});var a=this._pageCache[e=e\|\|"page-"+o];return a&&a.page?a.page:{key:e,startIndex:o,itemCount:n,items:t,style:r,top:0,height:0,data:i,isSpacer:s\|\|!1}},Vf.prototype._getRenderCount=function(e){var t=e\|\|this.props,o=t.items,e=t.startIndex,t=t.renderCount;return void 0===t?o?o.length-e:0:t},Vf.prototype._updateRenderRects=function(e,t,o){var n,r=e.renderedWindowsAhead,i=e.renderedWindowsBehind,s=t.pages;this._shouldVirtualize(e)&&(n=this._surfaceRect\|\|ht({},Hf),t=this._scrollElement&&this._scrollElement.scrollHeight,e=this._scrollElement?this._scrollElement.scrollTop:0,this._surface.current&&(o\|\|!s\|\|!this._surfaceRect\|\|!t\|\|t!==this._scrollHeight\|\|Math.abs(this._scrollTop-e)>this._estimatedPageHeight/3)&&(n=this._surfaceRect=Of(this._surface.current),this._scrollTop=e),!o&&t&&t===this._scrollHeight\|\|this._measureVersion++,this._scrollHeight=t\|\|0,o=Math.max(0,-n.top),t=qe(this._root.current),t={top:o,left:n.left,bottom:o+t.innerHeight,right:n.right,width:n.width,height:t.innerHeight},this._requiredRect=Kf(t,this._requiredWindowsBehind,this._requiredWindowsAhead),this._allowedRect=Kf(t,i,r),this._visibleRect=t)},Vf.defaultProps={startIndex:0,onRenderCell:function(e,t,o){return gt.createElement(gt.Fragment,null,e&&e.name\|\|"")},renderedWindowsAhead:2,renderedWindowsBehind:2},Vf);function Vf(e){var m=Af.call(this,e)\|\|this;return m._root=gt.createRef(),m._surface=gt.createRef(),m._pageRefs={},m._getDerivedStateFromProps=function(e,t){return e.items!==m.props.items\|\|e.renderCount!==m.props.renderCount\|\|e.startIndex!==m.props.startIndex\|\|e.version!==m.props.version?(m._resetRequiredWindows(),m._requiredRect=null,m._measureVersion++,m._invalidatePageCache(),m._updatePages(e,t)):t},m._onRenderRoot=function(e){var t=e.rootRef,o=e.surfaceElement,e=e.divProps;return gt.createElement("div",ht({ref:t},e),o)},m._onRenderSurface=function(e){var t=e.surfaceRef,o=e.pageElements,e=e.divProps;return gt.createElement("div",ht({ref:t},e),o)},m._onRenderPage=function(e,t){for(var o=m.props,n=o.onRenderCell,r=o.role,i=e.page,o=i.items,s=void 0===o?[]:o,a=i.startIndex,e=mt(e,["page"]),l=void 0===r?"listitem":"presentation",c=[],u=0;u<s.length;u++){var d=a+u,p=s[u],h=m.props.getKey?m.props.getKey(p,d):p&&p.key;null==h&&(h=d),c.push(gt.createElement("div",{role:l,className:"ms-List-cell",key:h,"data-list-index":d,"data-automationid":"ListCell"},n&&n(p,d,m.props.ignoreScrollingState?void 0:m.state.isScrolling)))}return gt.createElement("div",ht({},e),c)},fi(m),m.state={pages:[],isScrolling:!1,getDerivedStateFromProps:m._getDerivedStateFromProps},m._async=new Si(m),m._events=new va(m),m._estimatedPageHeight=0,m._totalEstimates=0,m._requiredWindowsAhead=0,m._requiredWindowsBehind=0,m._measureVersion=0,m._onAsyncScroll=m._async.debounce(m._onAsyncScroll,100,{leading:!1,maxWait:500}),m._onAsyncIdle=m._async.debounce(m._onAsyncIdle,200,{leading:!1}),m._onAsyncResize=m._async.debounce(m._onAsyncResize,16,{leading:!1}),m._onScrollingDone=m._async.debounce(m._onScrollingDone,500,{leading:!1}),m._cachedPageHeights={},m._estimatedPageHeight=0,m._focusedIndex=-1,m._pageCache={},m}function Kf(e,t,o){var n=e.top-te.height,o=e.height+(t+o)e.height;return{top:n,bottom:n+o,height:o,left:e.left,right:e.right,width:e.width}}function Gf(e,t,o){for(var n=0,r=e;n<r.length;n++){var i=r[n];o[t.register(i,!0)]=i}}function Uf(e,t){for(var o=0,n=Object.keys(t);o<n.length;o++){var r=n[o];e.unregister(t[r],r,!0),delete t[r]}}function jf(e){var t,o,n,r,s=Oc.getInstance(),i=e.className,a=e.overflowItems,l=e.keytipSequences,c=e.itemSubMenuProvider,u=e.onRenderOverflowButton,d=_l({}),p=gt.useCallback(function(e){return c?c(e):e.subMenuProps?e.subMenuProps.items:void 0},[c]),h=gt.useMemo(function(){var r=[],i=[];return l?null==a\|\|a.forEach(function(e){var t,o,n=e.keytipProps;n?(o={content:n.content,keySequences:n.keySequences,disabled:n.disabled\|\|!(!e.disabled&&!e.isDisabled),hasDynamicChildren:n.hasDynamicChildren,hasMenu:n.hasMenu},n.hasDynamicChildren\|\|p(e)?(o.onExecute=s.menuExecute.bind(s,l,null===(t=null==e?void 0:e.keytipProps)\|\|void 0===t?void 0:t.keySequences),o.hasOverflowSubMenu=!0):o.onExecute=n.onExecute,r.push(o),n=ht(ht({},e),{keytipProps:ht(ht({},n),{overflowSetSequence:l})}),null==i\|\|i.push(n)):null==i\|\|i.push(e)}):i=a,{modifiedOverflowItems:i,keytipsToRegister:r}},[a,p,s,l]),e=h.modifiedOverflowItems;return t=d,o=h.keytipsToRegister,n=s,r=Hc(t),gt.useEffect(function(){r&&(Uf(n,r),Gf(o,n,t))}),gt.useEffect(function(){return Gf(o,n,t),function(){Uf(n,t)}},[]),gt.createElement("div",{className:i},u(e))}var qf,Yf=(l(Qf,qf=gt.Component),Object.defineProperty(Qf.prototype,"selectedOptions",{get:function(){return this._comboBox.current?this._comboBox.current.selectedOptions:[]},enumerable:!1,configurable:!0}),Qf.prototype.dismissMenu=function(){if(this._comboBox.current)return this._comboBox.current.dismissMenu()},Qf.prototype.focus=function(e,t){return!!this._comboBox.current&&(this._comboBox.current.focus(e,t),!0)},Qf.prototype.render=function(){return gt.createElement(kf,ht({},this.props,{componentRef:this._comboBox,onRenderList:this._onRenderList,onScrollToItem:this._onScrollToItem}))},Qf),Zf=Fn(),Xf=gt.forwardRef(function(e,t){var o,n=gt.useRef(null),r=_r(n,t);o=n,gt.useImperativeHandle(e.componentRef,function(){return{focus:function(){var e=!1;return e=o.current?rs(o.current):e},focusElement:function(e){var t=!1;return!!e&&(o.current&&$i(o.current,e)&&(e.focus(),t=document.activeElement===e),t)}}},[o]);var i=e.items,s=e.overflowItems,a=e.className,l=e.styles,c=e.vertical,t=e.role,n=e.overflowSide,n=void 0===n?"end":n,u=e.onRenderItem,d=Zf(l,{className:a,vertical:c}),s=!!s&&0<s.length;return gt.createElement("div",ht({},ur(e,cr),{role:t\|\|"group","aria-orientation":"menubar"===t?!0===c?"vertical":"horizontal":void 0,className:d.root,ref:r}),"start"===n&&s&&gt.createElement(jf,ht({},e,{className:d.overflowButton})),i&&i.map(function(e,t){return gt.createElement("div",{className:d.item,key:e.key,role:"none"},u(e))}),"end"===n&&s&&gt.createElement(jf,ht({},e,{className:d.overflowButton})))});function Qf(e){var n=qf.call(this,e)\|\|this;return n._comboBox=gt.createRef(),n._list=gt.createRef(),n._onRenderList=function(e){var t=e.id,o=e.onRenderItem;return gt.createElement(Wf,{componentRef:n._list,role:"listbox",id:t+"-list","aria-labelledby":t+"-label",items:e.options,onRenderCell:o?function(e){return o(e)}:function(){return null}})},n._onScrollToItem=function(e){n._list.current&&n._list.current.scrollToIndex(e)},fi(n),n}Xf.displayName="OverflowSet";var Jf,$f={flexShrink:0,display:"inherit"},ev=In(Xf,function(e){var t=e.className;return{root:["ms-OverflowSet",{position:"relative",display:"flex",flexWrap:"nowrap"},e.vertical&&{flexDirection:"column"},t],item:["ms-OverflowSet-item",$f],overflowButton:["ms-OverflowSet-overflowButton",$f]}},void 0,{scope:"OverflowSet"}),tv=Ao(function(e){var t={height:"100%"},o={whiteSpace:"nowrap"},n=e\|\|{},r=n.root,e=n.label,n=mt(n,["root","label"]);return ht(ht({},n),{root:r?[t,r]:t,label:e?[o,e]:o})}),ov=Fn(),nv=(l(cv,Jf=gt.Component),cv.prototype.render=function(){var e=this.props,t=e.items,o=e.overflowItems,n=e.farItems,r=e.styles,i=e.theme,s=e.dataDidRender,a=e.onReduceData,l=void 0===a?this._onReduceData:a,a=e.onGrowData,a=void 0===a?this._onGrowData:a,e=e.resizeGroupAs,e=void 0===e?gd:e,o={primaryItems:$e([],t),overflowItems:$e([],o),minimumOverflowItems:$e([],o).length,farItems:n,cacheKey:this._computeCacheKey({primaryItems:$e([],t),overflow:o&&0<o.length})};this._classNames=ov(r,{theme:i});i=ur(this.props,cr);return gt.createElement(e,ht({},i,{componentRef:this._resizeGroup,data:o,onReduceData:l,onGrowData:a,onRenderData:this._onRenderData,dataDidRender:s}))},cv.prototype.focus=function(){var e=this._overflowSet.current;e&&e.focus()},cv.prototype.remeasure=function(){this._resizeGroup.current&&this._resizeGroup.current.remeasure()},cv.prototype._onButtonClick=function(t){return function(e){t.inactive\|\|t.onClick&&t.onClick(e,t)}},cv.prototype._computeCacheKey=function(e){var t=e.primaryItems,e=e.overflow;return[t&&t.reduce(function(e,t){var o=t.cacheKey;return e+(void 0===o?t.key:o)},""),e?"overflow":""].join("")},cv.defaultProps={items:[],overflowItems:[]},cv),rv=In(nv,function(e){var t=e.className,o=e.theme,e=o.semanticColors;return{root:[o.fonts.medium,"ms-CommandBar",{display:"flex",backgroundColor:e.bodyBackground,padding:"0 14px 0 24px",height:44},t],primarySet:["ms-CommandBar-primaryCommand",{flexGrow:"1",display:"flex",alignItems:"stretch"}],secondarySet:["ms-CommandBar-secondaryCommand",{flexShrink:"0",display:"flex",alignItems:"stretch"}]}},void 0,{scope:"CommandBar"}),iv=ht(ht({},bh),{prevMonthAriaLabel:"Go to previous month",nextMonthAriaLabel:"Go to next 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o,n,r,i,s,a,l,c,u,d,p,h,m,g,f,v,b,y,C,_,S,x,k,w,I,D,E,T=Hn(av,e),P=T.firstDayOfWeek,R=T.strings,M=T.label,N=T.theme,B=T.className,F=T.styles,A=T.initialPickerDate,L=T.isRequired,H=T.disabled,O=T.ariaLabel,z=T.pickerAriaLabel,W=T.placeholder,V=T.allowTextInput,K=T.borderless,G=T.minDate,U=T.maxDate,j=T.showCloseButton,q=T.calendarProps,Y=T.calloutProps,Z=T.textField,X=T.underlined,Q=T.allFocusable,J=T.calendarAs,$=void 0===J?Oh:J,ee=T.tabIndex,te=T.disableAutoFocus,oe=void 0===te\|\|te,ne=iu("DatePicker",T.id),re=iu("DatePicker-Callout"),ie=gt.useRef(null),se=gt.useRef(null),ae=(D=gt.useRef(null),E=gt.useRef(!1),[D,function(){var e,t;null===(t=null===(e=D.current)\|\|void 0===e?void 0:e.focus)\|\|void 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ke=sv(F,{theme:N,className:B,disabled:H,underlined:X,label:!!M,isDatePickerShown:pe}),F=ur(T,cr,["value"]),N=Z&&Z.iconProps,B=Z&&Z.id&&Z.id!==ne?Z.id:ne+"-label",ne=!V&&!H;return gt.createElement("div",ht({},F,{className:ke.root,ref:t}),gt.createElement("div",{ref:se,"aria-owns":pe?re:void 0,className:ke.wrapper},gt.createElement(qg,ht({role:"combobox",label:M,"aria-expanded":pe,ariaLabel:O,"aria-haspopup":"dialog","aria-controls":pe?re:void 0,required:L,disabled:H,errorMessage:J,placeholder:W,borderless:K,value:me,componentRef:le,underlined:X,tabIndex:ee,readOnly:!V},Z,{id:B,className:Tr(ke.textField,Z&&Z.className),iconProps:ht(ht({iconName:"Calendar"},N),{className:Tr(ke.icon,N&&N.className),onClick:function(e){e.stopPropagation(),pe\|\|T.disabled?T.allowTextInput&&Se():_e()}}),onRenderDescription:function(e,t){return gt.createElement(gt.Fragment,null,e.description?t(e):null,gt.createElement("div",{"aria-live":"assertive",className:ke.statusMessage},ye))},onKeyDown:function(e){switch(e.which){case En.enter:e.preventDefault(),e.stopPropagation(),pe?T.allowTextInput&&Se():(ve(),_e());break;case En.escape:e.stopPropagation(),xe();break;case En.down:e.altKey&&!pe&&_e()}},onFocus:function(){oe\|\|V\|\|(ue.current\|\|_e(),ue.current=!1)},onBlur:function(e){ve()},onClick:function(e){!T.openOnClick&&T.disableAutoFocus\|\|pe\|\|T.disabled?T.allowTextInput&&Se():_e()},onChange:function(e,t){var o,n=T.textField;V&&(pe&&Se(),fe(t)),null===(o=null==n?void 0:n.onChange)\|\|void 0===o\|\|o.call(n,e,t)},onRenderInput:ne?function(e){e=ur(e,cr);return gt.createElement("div",ht({},e,{className:Tr(e.className,ke.readOnlyTextField),tabIndex:ee\|\|0}),me\|\|gt.createElement("span",{className:ke.readOnlyPlaceholder},W))}:void 0}))),pe&&gt.createElement(ac,ht({id:re,role:"dialog",ariaLabel:z,isBeakVisible:!1,gapSpace:0,doNotLayer:!1,target:se.current,directionalHint:Pa.bottomLeftEdge},Y,{className:Tr(ke.callout,Y&&Y.className),onDismiss:function(e){xe()},onPositioned:function(){var e=!0;T.calloutProps&&void 0!==T.calloutProps.setInitialFocus&&(e=T.calloutProps.setInitialFocus),ie.current&&e&&ie.current.focus()}}),gt.createElement(Wh,{isClickableOutsideFocusTrap:!0,disableFirstFocus:oe},gt.createElement($,ht({},q,{onSelectDate:function(e){T.calendarProps&&T.calendarProps.onSelectDate&&T.calendarProps.onSelectDate(e),xe(e)},onDismiss:xe,isMonthPickerVisible:T.isMonthPickerVisible,showMonthPickerAsOverlay:T.showMonthPickerAsOverlay,today:T.today,value:te\|\|A,firstDayOfWeek:P,strings:R,highlightCurrentMonth:T.highlightCurrentMonth,highlightSelectedMonth:T.highlightSelectedMonth,showWeekNumbers:T.showWeekNumbers,firstWeekOfYear:T.firstWeekOfYear,showGoToToday:T.showGoToToday,dateTimeFormatter:T.dateTimeFormatter,minDate:G,maxDate:U,componentRef:ie,showCloseButton:j,allFocusable:Q})))))});function cv(e){var l=Jf.call(this,e)\|\|this;return l._overflowSet=gt.createRef(),l._resizeGroup=gt.createRef(),l._onRenderData=function(e){var t=l.props,o=t.ariaLabel,n=t.primaryGroupAriaLabel,r=t.farItemsGroupAriaLabel,t=e.farItems&&0<e.farItems.length;return gt.createElement(Zs,{className:Tr(l._classNames.root),direction:Ei.horizontal,role:"menubar","aria-label":o},gt.createElement(ev,{role:t?"group":"none","aria-label":t?n:void 0,componentRef:l._overflowSet,className:Tr(l._classNames.primarySet),items:e.primaryItems,overflowItems:e.overflowItems.length?e.overflowItems:void 0,onRenderItem:l._onRenderItem,onRenderOverflowButton:l._onRenderOverflowButton}),t&&gt.createElement(ev,{role:"group","aria-label":r,className:Tr(l._classNames.secondarySet),items:e.farItems,onRenderItem:l._onRenderItem,onRenderOverflowButton:wa}))},l._onRenderItem=function(e){if(e.onRender)return e.onRender(e,function(){});var t=e.text\|\|e.name,o=ht(ht({allowDisabledFocus:!0,role:"menuitem"},e),{styles:tv(e.buttonStyles),className:Tr("ms-CommandBarItem-link",e.className),text:e.iconOnly?void 0:t,menuProps:e.subMenuProps,onClick:l._onButtonClick(e)});return e.iconOnly&&(void 0!==t\|\|e.tooltipHostProps)?gt.createElement(Rd,ht({role:"none",content:t,setAriaDescribedBy:!1},e.tooltipHostProps),l._commandButton(e,o)):l._commandButton(e,o)},l._commandButton=function(e,t){var o=l.props.buttonAs,n=e.commandBarButtonAs,e=cp;return n&&(e=ju(n,e)),o&&(e=ju(o,e)),gt.createElement(e,ht({},t))},l._onRenderOverflowButton=function(e){var t=l.props.overflowButtonProps,t=void 0===t?{}:t,e=$e($e([],t.menuProps?t.menuProps.items:[]),e),e=ht(ht({role:"menuitem"},t),{styles:ht({menuIcon:{fontSize:"17px"}},t.styles),className:Tr("ms-CommandBar-overflowButton",t.className),menuProps:ht(ht({},t.menuProps),{items:e}),menuIconProps:ht({iconName:"More"},t.menuIconProps)}),t=l.props.overflowButtonAs?ju(l.props.overflowButtonAs,cp):cp;return gt.createElement(t,ht({},e))},l._onReduceData=function(e){var t=l.props,o=t.shiftOnReduce,n=t.onDataReduced,r=e.primaryItems,i=e.overflowItems,t=(e.cacheKey,r[o?0:r.length-1]);if(void 0!==t){t.renderedInOverflow=!0;var i=$e([t],i),r=o?r.slice(1):r.slice(0,-1),e=ht(ht({},e),{primaryItems:r,overflowItems:i}),s=l._computeCacheKey({primaryItems:r,overflow:0<i.length});return n&&n(t),e.cacheKey=s,e}},l._onGrowData=function(e){var t=l.props,o=t.shiftOnReduce,n=t.onDataGrown,r=e.minimumOverflowItems,i=e.primaryItems,s=e.overflowItems,t=(e.cacheKey,s[0]);if(void 0!==t&&s.length>r){t.renderedInOverflow=!1;var s=s.slice(1),i=o?$e([t],i):$e($e([],i),[t]),e=ht(ht({},e),{primaryItems:i,overflowItems:s}),a=l._computeCacheKey({primaryItems:i,overflow:0<s.length});return n&&n(t),e.cacheKey=a,e}},fi(l),l}function uv(e,t,o){return t&&0<Op(t,e)\|\|o&&Op(o,e)<0}lv.displayName="DatePickerBase";var dv,pv,hv={root:"ms-DatePicker",callout:"ms-DatePicker-callout",withLabel:"ms-DatePicker-event--with-label",withoutLabel:"ms-DatePicker-event--without-label",disabled:"msDatePickerDisabled "},mv=In(lv,function(e){var t=e.className,o=e.theme,n=e.disabled,r=e.underlined,i=e.label,s=e.isDatePickerShown,a=o.palette,l=o.semanticColors,c=o.fonts,e=zo(hv,o),a={color:a.neutralSecondary,fontSize:Be.icon,lineHeight:"18px",pointerEvents:"none",position:"absolute",right:"4px",padding:"5px"};return{root:[e.root,o.fonts.large,s&&"is-open",Uo,t],textField:[{position:"relative",selectors:{"& input[readonly]":{cursor:"pointer"},input:{selectors:{"::-ms-clear":{display:"none"}}}}},n&&{selectors:{"& input[readonly]":{cursor:"default"}}}],callout:[e.callout],icon:[a,i?e.withLabel:e.withoutLabel,{paddingTop:"7px"},!n&&[e.disabled,{pointerEvents:"initial",cursor:"pointer"}],n&&{color:l.disabledText,cursor:"default"}],statusMessage:[c.small,{color:l.errorText,marginTop:5}],readOnlyTextField:[{cursor:"pointer",height:32,lineHeight:30,overflow:"hidden",textOverflow:"ellipsis"},r&&{lineHeight:34}],readOnlyPlaceholder:((l={color:l.inputPlaceholderText})[Yt]={color:"GrayText"},l)}},void 0,{scope:"DatePicker"}),gv="change";(V=dv=dv\|\|{})[V.none=0]="none",V[V.single=1]="single",V[V.multiple=2]="multiple",(G=pv=pv\|\|{})[G.horizontal=0]="horizontal",G[G.vertical=1]="vertical";var fv=(vv.prototype.canSelectItem=function(e,t){return!("number"==typeof t&&t<0)&&this._canSelectItem(e,t)},vv.prototype.getKey=function(e,t){t=this._getKey(e,t);return"number"==typeof t\|\|t?""+t:""},vv.prototype.setChangeEvents=function(e,t){this._changeEventSuppressionCount+=e?-1:1,0===this._changeEventSuppressionCount&&this._hasChanged&&(this._hasChanged=!1,t\|\|this._change())},vv.prototype.isModal=function(){return this._isModal},vv.prototype.setModal=function(e){this._isModal!==e&&(this.setChangeEvents(!1),(this._isModal=e)\|\|this.setAllSelected(!1),this._change(),this.setChangeEvents(!0))},vv.prototype.setItems=function(e,t){void 0===t&&(t=!0);var o={},n={},r=!1;this.setChangeEvents(!1);for(var i,s=this._unselectableCount=0;s<e.length;s++)!(l=e[s])\|\|(i=this.getKey(l,s))&&(o[i]=s),n[s]=l&&!this.canSelectItem(l),n[s]&&this._unselectableCount++;!t&&0!==e.length\|\|this._setAllSelected(!1,!0);var a,l,c,u,d={},p=0;for(a in this._exemptedIndices)this._exemptedIndices.hasOwnProperty(a)&&(c=Number(a),r=void 0===(u=(u=(l=this._items[c])?this.getKey(l,Number(c)):void 0)?o[u]:c)\|\|(d[u]=!0,p++,r\|\|u!==c));this._items&&0===this._exemptedCount&&e.length!==this._items.length&&this._isAllSelected&&(r=!0),this._exemptedIndices=d,this._exemptedCount=p,this._keyToIndexMap=o,this._unselectableIndices=n,this._items=e,this._selectedItems=null,r&&(this._updateCount(),this._change()),this.setChangeEvents(!0)},vv.prototype.getItems=function(){return this._items},vv.prototype.getSelection=function(){if(!this._selectedItems){this._selectedItems=[];var e=this._items;if(e)for(var t=0;t<e.length;t++)this.isIndexSelected(t)&&this._selectedItems.push(e[t])}return this._selectedItems},vv.prototype.getSelectedCount=function(){return this._isAllSelected?this._items.length-this._exemptedCount-this._unselectableCount:this._exemptedCount},vv.prototype.getSelectedIndices=function(){if(!this._selectedIndices){this._selectedIndices=[];var e=this._items;if(e)for(var t=0;t<e.length;t++)this.isIndexSelected(t)&&this._selectedIndices.push(t)}return this._selectedIndices},vv.prototype.isRangeSelected=function(e,t){if(0===t)return!1;for(var o=e+t,n=e;n<o;n++)if(!this.isIndexSelected(n))return!1;return!0},vv.prototype.isAllSelected=function(){var e=this._items.length-this._unselectableCount;return this.mode===dv.single&&(e=Math.min(e,1)),0<this.count&&this._isAllSelected&&0===this._exemptedCount\|\|!this._isAllSelected&&this._exemptedCount===e&&0<e},vv.prototype.isKeySelected=function(e){e=this._keyToIndexMap[e];return this.isIndexSelected(e)},vv.prototype.isIndexSelected=function(e){return!!(0<this.count&&this._isAllSelected&&!this._exemptedIndices[e]&&!this._unselectableIndices[e]\|\|!this._isAllSelected&&this._exemptedIndices[e])},vv.prototype.setAllSelected=function(e){var t;e&&this.mode!==dv.multiple\|\|(t=this._items?this._items.length-this._unselectableCount:0,this.setChangeEvents(!1),0<t&&(0<this._exemptedCount\|\|e!==this._isAllSelected)&&(this._exemptedIndices={},(e!==this._isAllSelected\|\|0<this._exemptedCount)&&(this._exemptedCount=0,this._isAllSelected=e,this._change()),this._updateCount()),this.setChangeEvents(!0))},vv.prototype.setKeySelected=function(e,t,o){e=this._keyToIndexMap[e];0<=e&&this.setIndexSelected(e,t,o)},vv.prototype.setIndexSelected=function(e,t,o){var n;this.mode===dv.none\|\|(e=Math.min(Math.max(0,e),this._items.length-1))<0\|\|e>=this._items.length\|\|(this.setChangeEvents(!1),n=this._exemptedIndices[e],this._unselectableIndices[e]\|\|(t&&this.mode===dv.single&&this._setAllSelected(!1,!0),n&&(t&&this._isAllSelected\|\|!t&&!this._isAllSelected)&&(delete this._exemptedIndices[e],this._exemptedCount--),!n&&(t&&!this._isAllSelected\|\|!t&&this._isAllSelected)&&(this._exemptedIndices[e]=!0,this._exemptedCount++),o&&(this._anchoredIndex=e)),this._updateCount(),this.setChangeEvents(!0))},vv.prototype.selectToKey=function(e,t){this.selectToIndex(this._keyToIndexMap[e],t)},vv.prototype.selectToIndex=function(e,t){if(this.mode!==dv.none)if(this.mode!==dv.single){var o=this._anchoredIndex\|\|0,n=Math.min(e,o),r=Math.max(e,o);for(this.setChangeEvents(!1),t&&this._setAllSelected(!1,!0);n<=r;n++)this.setIndexSelected(n,!0,!1);this.setChangeEvents(!0)}else this.setIndexSelected(e,!0,!0)},vv.prototype.toggleAllSelected=function(){this.setAllSelected(!this.isAllSelected())},vv.prototype.toggleKeySelected=function(e){this.setKeySelected(e,!this.isKeySelected(e),!0)},vv.prototype.toggleIndexSelected=function(e){this.setIndexSelected(e,!this.isIndexSelected(e),!0)},vv.prototype.toggleRangeSelected=function(e,t){if(this.mode!==dv.none){var o=this.isRangeSelected(e,t),n=e+t;if(!(this.mode===dv.single&&1<t)){this.setChangeEvents(!1);for(var r=e;r<n;r++)this.setIndexSelected(r,!o,!1);this.setChangeEvents(!0)}}},vv.prototype._updateCount=function(e){void 0===e&&(e=!1);var t=this.getSelectedCount();t!==this.count&&(this.count=t,this._change()),this.count\|\|e\|\|this.setModal(!1)},vv.prototype._setAllSelected=function(e,t){var o;void 0===t&&(t=!1),e&&this.mode!==dv.multiple\|\|(o=this._items?this._items.length-this._unselectableCount:0,this.setChangeEvents(!1),0<o&&(0<this._exemptedCount\|\|e!==this._isAllSelected)&&(this._exemptedIndices={},(e!==this._isAllSelected\|\|0<this._exemptedCount)&&(this._exemptedCount=0,this._isAllSelected=e,this._change()),this._updateCount(t)),this.setChangeEvents(!0))},vv.prototype._change=function(){0===this._changeEventSuppressionCount?(this._selectedItems=null,this._selectedIndices=void 0,va.raise(this,gv),this._onSelectionChanged&&this._onSelectionChanged()):this._hasChanged=!0},vv);function vv(){for(var e=[],t=0;t<arguments.length;t++)e[t]=arguments[t];var o=e[0]\|\|{},n=o.onSelectionChanged,r=o.getKey,i=o.canSelectItem,s=void 0===i?function(){return!0}:i,i=o.items,o=o.selectionMode,o=void 0===o?dv.multiple:o;this.mode=o,this._getKey=r\|\|bv,this._changeEventSuppressionCount=0,this._exemptedCount=0,this._anchoredIndex=0,this._unselectableCount=0,this._onSelectionChanged=n,this._canSelectItem=s,this._isModal=!1,this.setItems(i\|\|[],!0),this.count=this.getSelectedCount()}function bv(e,t){e=(e\|\|{}).key;return void 0===e?""+t:e}var yv,Cv,_v,Sv,xv,kv,wv,Iv="data-selection-index",Dv="data-selection-toggle",Ev="data-selection-invoke",Tv="data-selection-all-toggle",Pv=(l(Rv,wv=gt.Component),Rv.getDerivedStateFromProps=function(e,t){e=e.selection.isModal&&e.selection.isModal();return ht(ht({},t),{isModal:e})},Rv.prototype.componentDidMount=function(){var e=qe(this._root.current);this._events.on(e,"keydown, keyup",this._updateModifiers,!0),this._events.on(document,"click",this._findScrollParentAndTryClearOnEmptyClick),this._events.on(document.body,"touchstart",this._onTouchStartCapture,!0),this._events.on(document.body,"touchend",this._onTouchStartCapture,!0),this._events.on(this.props.selection,"change",this._onSelectionChange)},Rv.prototype.render=function(){var e=this.state.isModal;return gt.createElement("div",{className:Tr("ms-SelectionZone",this.props.className,{"ms-SelectionZone--modal":!!e}),ref:this._root,onKeyDown:this._onKeyDown,onMouseDown:this._onMouseDown,onKeyDownCapture:this._onKeyDownCapture,onClick:this._onClick,role:"presentation",onDoubleClick:this._onDoubleClick,onContextMenu:this._onContextMenu,onMouseDownCapture:this._onMouseDownCapture,onFocusCapture:this._onFocus,"data-selection-is-modal":!!e\|\|void 0},this.props.children,gt.createElement(na,null))},Rv.prototype.componentDidUpdate=function(e){var t=this.props.selection;t!==e.selection&&(this._events.off(e.selection),this._events.on(t,"change",this._onSelectionChange))},Rv.prototype.componentWillUnmount=function(){this._events.dispose(),this._async.dispose()},Rv.prototype._isSelectionDisabled=function(e){if(this._getSelectionMode()===dv.none)return!0;for(;e!==this._root.current;){if(this._hasAttribute(e,"data-selection-disabled"))return!0;e=Xi(e)}return!1},Rv.prototype._onToggleAllClick=function(e){var t=this.props.selection;this._getSelectionMode()===dv.multiple&&(t.toggleAllSelected(),e.stopPropagation(),e.preventDefault())},Rv.prototype._onToggleClick=function(e,t){var o=this.props.selection,n=this._getSelectionMode();if(o.setChangeEvents(!1),this.props.enterModalOnTouch&&this._isTouch&&!o.isIndexSelected(t)&&o.setModal&&(o.setModal(!0),this._setIsTouch(!1)),n===dv.multiple)o.toggleIndexSelected(t);else{if(n!==dv.single)return void o.setChangeEvents(!0);var r=o.isIndexSelected(t),n=o.isModal&&o.isModal();o.setAllSelected(!1),o.setIndexSelected(t,!r,!0),n&&o.setModal&&o.setModal(!0)}o.setChangeEvents(!0),e.stopPropagation()},Rv.prototype._onInvokeClick=function(e,t){var o=this.props,n=o.selection,o=o.onItemInvoked;o&&(o(n.getItems()[t],t,e.nativeEvent),e.preventDefault(),e.stopPropagation())},Rv.prototype._onItemSurfaceClick=function(e,t){var o=this.props.selection,n=this._isCtrlPressed\|\|this._isMetaPressed,r=this._getSelectionMode();r===dv.multiple?this._isShiftPressed&&!this._isTabPressed?o.selectToIndex(t,!n):n?o.toggleIndexSelected(t):this._clearAndSelectIndex(t):r===dv.single&&this._clearAndSelectIndex(t)},Rv.prototype._onInvokeMouseDown=function(e,t){this.props.selection.isIndexSelected(t)\|\|this._clearAndSelectIndex(t)},Rv.prototype._findScrollParentAndTryClearOnEmptyClick=function(e){var t=Ns(this._root.current);this._events.off(document,"click",this._findScrollParentAndTryClearOnEmptyClick),this._events.on(t,"click",this._tryClearOnEmptyClick),(t&&e.target instanceof Node&&t.contains(e.target)\|\|t===e.target)&&this._tryClearOnEmptyClick(e)},Rv.prototype._tryClearOnEmptyClick=function(e){!this.props.selectionPreservedOnEmptyClick&&this._isNonHandledClick(e.target)&&this.props.selection.setAllSelected(!1)},Rv.prototype._clearAndSelectIndex=function(e){var t,o=this.props.selection;1===o.getSelectedCount()&&o.isIndexSelected(e)\|\|(t=o.isModal&&o.isModal(),o.setChangeEvents(!1),o.setAllSelected(!1),o.setIndexSelected(e,!0,!0),(t\|\|this.props.enterModalOnTouch&&this._isTouch)&&(o.setModal&&o.setModal(!0),this._isTouch&&this._setIsTouch(!1)),o.setChangeEvents(!0))},Rv.prototype._updateModifiers=function(e){this._isShiftPressed=e.shiftKey,this._isCtrlPressed=e.ctrlKey,this._isMetaPressed=e.metaKey;e=e.keyCode;this._isTabPressed=!!e&&e===En.tab},Rv.prototype._findItemRoot=function(e){for(var t=this.props.selection;e!==this._root.current;){var o=e.getAttribute(Iv),n=Number(o);if(null!==o&&0<=n&&n<t.getItems().length)break;e=Xi(e)}if(e!==this._root.current)return e},Rv.prototype._getItemIndex=function(e){return Number(e.getAttribute(Iv))},Rv.prototype._shouldAutoSelect=function(e){return this._hasAttribute(e,"data-selection-select")},Rv.prototype._hasAttribute=function(e,t){for(var o=!1;!o&&e!==this._root.current;)o="true"===e.getAttribute(t),e=Xi(e);return o},Rv.prototype._isInputElement=function(e){return"INPUT"===e.tagName\|\|"TEXTAREA"===e.tagName},Rv.prototype._isNonHandledClick=function(e){var t=ft();if(t&&e)for(;e&&e!==t.documentElement;){if(cs(e))return!1;e=Xi(e)}return!0},Rv.prototype._handleNextFocus=function(e){var t=this;this._shouldHandleFocusTimeoutId&&(this._async.clearTimeout(this._shouldHandleFocusTimeoutId),this._shouldHandleFocusTimeoutId=void 0),(this._shouldHandleFocus=e)&&this._async.setTimeout(function(){t._shouldHandleFocus=!1},100)},Rv.prototype._setIsTouch=function(e){var t=this;this._isTouchTimeoutId&&(this._async.clearTimeout(this._isTouchTimeoutId),this._isTouchTimeoutId=void 0),this._isTouch=!0,e&&this._async.setTimeout(function(){t._isTouch=!1},300)},Rv.prototype._getSelectionMode=function(){var e=this.props.selection,t=this.props.selectionMode;return void 0===t?e?e.mode:dv.none:t},Rv.defaultProps={isSelectedOnFocus:!0,selectionMode:dv.multiple},Rv);function Rv(e){var c=wv.call(this,e)\|\|this;c._root=gt.createRef(),c.ignoreNextFocus=function(){c._handleNextFocus(!1)},c._onSelectionChange=function(){var e=c.props.selection,e=e.isModal&&e.isModal();c.setState({isModal:e})},c._onMouseDownCapture=function(e){var t=e.target;if(document.activeElement===t\|\|$i(document.activeElement,t)){if($i(t,c._root.current))for(;t!==c._root.current;){if(c._hasAttribute(t,Ev)){c.ignoreNextFocus();break}t=Xi(t)}}else c.ignoreNextFocus()},c._onFocus=function(e){var t=e.target,o=c.props.selection,n=c._isCtrlPressed\|\|c._isMetaPressed,r=c._getSelectionMode();c._shouldHandleFocus&&r!==dv.none&&(r=c._hasAttribute(t,Dv),t=c._findItemRoot(t),!r&&t&&(t=c._getItemIndex(t),n?(o.setIndexSelected(t,o.isIndexSelected(t),!0),c.props.enterModalOnTouch&&c._isTouch&&o.setModal&&(o.setModal(!0),c._setIsTouch(!1))):c.props.isSelectedOnFocus&&c._onItemSurfaceClick(e,t))),c._handleNextFocus(!1)},c._onMouseDown=function(e){c._updateModifiers(e);var t=e.target,o=c._findItemRoot(t);if(!c._isSelectionDisabled(t))for(;t!==c._root.current&&!c._hasAttribute(t,Tv);){if(o){if(c._hasAttribute(t,Dv))break;if(c._hasAttribute(t,Ev))break;if(!(t!==o&&!c._shouldAutoSelect(t)\|\|c._isShiftPressed\|\|c._isCtrlPressed\|\|c._isMetaPressed)){c._onInvokeMouseDown(e,c._getItemIndex(o));break}if(c.props.disableAutoSelectOnInputElements&&("A"===t.tagName\|\|"BUTTON"===t.tagName\|\|"INPUT"===t.tagName))return}t=Xi(t)}},c._onTouchStartCapture=function(e){c._setIsTouch(!0)},c._onClick=function(e){var t=c.props.enableTouchInvocationTarget,o=void 0!==t&&t;c._updateModifiers(e);for(var n=e.target,r=c._findItemRoot(n),i=c._isSelectionDisabled(n);n!==c._root.current;){if(c._hasAttribute(n,Tv)){i\|\|c._onToggleAllClick(e);break}if(r){var s=c._getItemIndex(r);if(c._hasAttribute(n,Dv)){i\|\|(c._isShiftPressed?c._onItemSurfaceClick(e,s):c._onToggleClick(e,s));break}if(c._isTouch&&o&&c._hasAttribute(n,"data-selection-touch-invoke")\|\|c._hasAttribute(n,Ev)){c._onInvokeClick(e,s);break}if(n===r){i\|\|c._onItemSurfaceClick(e,s);break}if("A"===n.tagName\|\|"BUTTON"===n.tagName\|\|"INPUT"===n.tagName)return}n=Xi(n)}},c._onContextMenu=function(e){var t=e.target,o=c.props,n=o.onItemContextMenu,o=o.selection;!n\|\|(t=c._findItemRoot(t))&&(t=c._getItemIndex(t),c._onInvokeMouseDown(e,t),n(o.getItems()[t],t,e.nativeEvent)\|\|e.preventDefault())},c._onDoubleClick=function(e){var t=e.target,o=c.props.onItemInvoked,n=c._findItemRoot(t);if(n&&o&&!c._isInputElement(t)){for(var r=c._getItemIndex(n);t!==c._root.current&&!c._hasAttribute(t,Dv)&&!c._hasAttribute(t,Ev);){if(t===n){c._onInvokeClick(e,r);break}t=Xi(t)}Xi(t)}},c._onKeyDownCapture=function(e){c._updateModifiers(e),c._handleNextFocus(!0)},c._onKeyDown=function(e){c._updateModifiers(e);var t=e.target,o=c._isSelectionDisabled(t),n=c.props.selection,r=e.which===En.a&&(c._isCtrlPressed\|\|c._isMetaPressed),i=e.which===En.escape;if(!c._isInputElement(t)){var s=c._getSelectionMode();if(r&&s===dv.multiple&&!n.isAllSelected())return o\|\|n.setAllSelected(!0),e.stopPropagation(),void e.preventDefault();if(i&&0<n.getSelectedCount())return o\|\|n.setAllSelected(!1),e.stopPropagation(),void e.preventDefault();var a=c._findItemRoot(t);if(a)for(var l=c._getItemIndex(a);t!==c._root.current&&!c._hasAttribute(t,Dv);){if(c._shouldAutoSelect(t)){o\|\|c._onInvokeMouseDown(e,l);break}if(!(e.which!==En.enter&&e.which!==En.space\|\|"BUTTON"!==t.tagName&&"A"!==t.tagName&&"INPUT"!==t.tagName))return!1;if(t===a){if(e.which===En.enter)return c._onInvokeClick(e,l),void e.preventDefault();if(e.which===En.space)return o\|\|c._onToggleClick(e,l),void e.preventDefault();break}t=Xi(t)}}},c._events=new va(c),c._async=new Si(c),fi(c);e=c.props.selection,e=e.isModal&&e.isModal();return c.state={isModal:e},c}(Y=yv=yv\|\|{})[Y.hidden=0]="hidden",Y[Y.visible=1]="visible",(ke=Cv=Cv\|\|{})[ke.disabled=0]="disabled",ke[ke.clickable=1]="clickable",ke[ke.hasDropdown=2]="hasDropdown",(K=_v=_v\|\|{})[K.unconstrained=0]="unconstrained",K[K.horizontalConstrained=1]="horizontalConstrained",(U=Sv=Sv\|\|{})[U.outside=0]="outside",U[U.surface=1]="surface",U[U.header=2]="header",(xe=xv=xv\|\|{})[xe.fixedColumns=0]="fixedColumns",xe[xe.justified=1]="justified",(V=kv=kv\|\|{})[V.onHover=0]="onHover",V[V.always=1]="always",V[V.hidden=2]="hidden";var Mv=function(e){var t=e.count,o=e.indentWidth,e=e.role;return 0<t?gt.createElement("span",{className:"ms-GroupSpacer",style:{display:"inline-block",width:t(void 0===o?36:o)},role:void 0===e?"presentation":e}):null},Nv={label:Vn,audio:Kn,video:Gn,ol:Un,li:jn,a:qn,button:Yn,input:Zn,textarea:Xn,select:Qn,option:Jn,table:$n,tr:er,th:tr,td:or,colGroup:nr,col:rr,form:ir,iframe:sr,img:ar};function Bv(e,t,o){return ur(t,e&&Nv[e]\|\|Wn,o)}function Fv(e){var t=e.theme,e=void 0===(o=e.cellStyleProps)?Lv:o,o=t.semanticColors;return[zo(Wv,t).cell,bo(t),{color:o.bodyText,position:"relative",display:"inline-block",boxSizing:"border-box",padding:"0 "+e.cellRightPadding+"px 0 "+e.cellLeftPadding+"px",lineHeight:"inherit",margin:"0",height:42,verticalAlign:"top",whiteSpace:"nowrap",textOverflow:"ellipsis",textAlign:"left"}]}var Av={root:"ms-DetailsRow",compact:"ms-DetailsList--Compact",cell:"ms-DetailsRow-cell",cellAnimation:"ms-DetailsRow-cellAnimation",cellCheck:"ms-DetailsRow-cellCheck",check:"ms-DetailsRow-check",cellMeasurer:"ms-DetailsRow-cellMeasurer",listCellFirstChild:"ms-List-cell:first-child",isContentUnselectable:"is-contentUnselectable",isSelected:"is-selected",isCheckVisible:"is-check-visible",isRowHeader:"is-row-header",fields:"ms-DetailsRow-fields"},Lv={cellLeftPadding:12,cellRightPadding:8,cellExtraRightPadding:24},Hv={rowHeight:42,compactRowHeight:32},Ov=ht(ht({},Hv),{rowVerticalPadding:11,compactRowVerticalPadding:6}),zv=function(e){var t=e.theme,o=e.isSelected,n=e.canSelect,r=e.droppingClassName,i=e.anySelected,s=e.isCheckVisible,a=e.checkboxCellClassName,l=e.compact,c=e.className,u=e.cellStyleProps,d=void 0===u?Lv:u,p=e.enableUpdateAnimations,h=e.disabled,m=t.palette,g=t.fonts,f=m.neutralPrimary,v=m.white,b=m.neutralSecondary,y=m.neutralLighter,C=m.neutralLight,_=m.neutralDark,S=m.neutralQuaternaryAlt,x=t.semanticColors,k=x.focusBorder,u=x.linkHovered,e=zo(Av,t),m={defaultHeaderText:f,defaultMetaText:b,defaultBackground:v,defaultHoverHeaderText:_,defaultHoverMetaText:f,defaultHoverBackground:y,selectedHeaderText:_,selectedMetaText:f,selectedBackground:C,selectedHoverHeaderText:_,selectedHoverMetaText:f,selectedHoverBackground:S,focusHeaderText:_,focusMetaText:f,focusBackground:C,focusHoverBackground:S},f=[bo(t,{inset:-1,borderColor:k,outlineColor:v,highContrastStyle:{top:2,right:2,bottom:2,left:2}}),e.isSelected,{color:m.selectedMetaText,background:m.selectedBackground,borderBottom:"1px solid "+v,selectors:((x={"&:before":{position:"absolute",display:"block",top:-1,height:1,bottom:0,left:0,right:0,content:"",borderTop:"1px solid "+v}})["."+e.cell+" > ."+ca.root]={color:u,selectors:((_={})[Yt]={color:"HighlightText"},_)},x["&:hover"]={background:m.selectedHoverBackground,color:m.selectedHoverMetaText,selectors:((f={})[Yt]={background:"Highlight",selectors:((C={})["."+e.cell]={color:"HighlightText"},C["."+e.cell+" > ."+ca.root]={forcedColorAdjust:"none",color:"HighlightText"},C)},f["."+e.isRowHeader]={color:m.selectedHoverHeaderText,selectors:((S={})[Yt]={color:"HighlightText"},S)},f)},x["&:focus"]={background:m.focusBackground,selectors:((_={})["."+e.cell]={color:m.focusMetaText,selectors:((C={})[Yt]={color:"HighlightText",selectors:{"> a":{color:"HighlightText"}}},C)},_["."+e.isRowHeader]={color:m.focusHeaderText,selectors:((S={})[Yt]={color:"HighlightText"},S)},_[Yt]={background:"Highlight"},_)},x[Yt]=ht(ht({background:"Highlight",color:"HighlightText"},{forcedColorAdjust:"none",MsHighContrastAdjust:"none"}),{selectors:{a:{color:"HighlightText"}}}),x["&:focus:hover"]={background:m.focusHoverBackground},x)}],C=[e.isContentUnselectable,{userSelect:"none",cursor:"default"}],S={minHeight:Ov.compactRowHeight,border:0},_={minHeight:Ov.compactRowHeight,paddingTop:Ov.compactRowVerticalPadding,paddingBottom:Ov.compactRowVerticalPadding,paddingLeft:d.cellLeftPadding+"px"},h=[bo(t,{inset:-1}),e.cell,{display:"inline-block",position:"relative",boxSizing:"border-box",minHeight:Ov.rowHeight,verticalAlign:"top",whiteSpace:"nowrap",overflow:"hidden",textOverflow:"ellipsis",paddingTop:Ov.rowVerticalPadding,paddingBottom:Ov.rowVerticalPadding,paddingLeft:d.cellLeftPadding+"px",selectors:((x={"& > button":{maxWidth:"100%"}})["[data-is-focusable='true']"]=bo(t,{inset:-1,borderColor:b,outlineColor:v}),x)},o&&{selectors:((x={})[Yt]=ht({background:"Highlight",color:"HighlightText"},{forcedColorAdjust:"none",MsHighContrastAdjust:"none"}),x)},l&&_,h&&{opacity:.5}];return{root:[e.root,Le.fadeIn400,r,t.fonts.small,s&&e.isCheckVisible,bo(t,{borderColor:k,outlineColor:v}),{borderBottom:"1px solid "+y,background:m.defaultBackground,color:m.defaultMetaText,display:"inline-flex",minWidth:"100%",minHeight:Ov.rowHeight,whiteSpace:"nowrap",padding:0,boxSizing:"border-box",verticalAlign:"top",textAlign:"left",selectors:((v={})["."+e.listCellFirstChild+" &:before"]={display:"none"},v["&:hover"]={background:m.defaultHoverBackground,color:m.defaultHoverMetaText,selectors:((y={})["."+e.isRowHeader]={color:m.defaultHoverHeaderText},y["."+e.cell+" > ."+ca.root]={color:u},y)},v["&:hover ."+e.check]={opacity:1},v["."+go+" &:focus ."+e.check]={opacity:1},v[".ms-GroupSpacer"]={flexShrink:0,flexGrow:0},v)},o&&f,!n&&C,l&&S,c],cellUnpadded:{paddingRight:d.cellRightPadding+"px"},cellPadded:{paddingRight:d.cellExtraRightPadding+d.cellRightPadding+"px",selectors:((d={})["&."+e.cellCheck]={paddingRight:0},d)},cell:h,cellAnimation:p&&Ie.slideLeftIn40,cellMeasurer:[e.cellMeasurer,{overflow:"visible",whiteSpace:"nowrap"}],checkCell:[h,e.cellCheck,a,{padding:0,paddingTop:1,marginTop:-1,flexShrink:0}],checkCover:{position:"absolute",top:-1,left:0,bottom:0,right:0,display:i?"block":"none"},fields:[e.fields,{display:"flex",alignItems:"stretch"}],isRowHeader:[e.isRowHeader,{color:m.defaultHeaderText,fontSize:g.medium.fontSize},o&&{color:m.selectedHeaderText,fontWeight:Fe.semibold,selectors:((m={})[Yt]={color:"HighlightText"},m)}],isMultiline:[h,{whiteSpace:"normal",wordBreak:"break-word",textOverflow:"clip"}],check:[e.check]}},Wv={tooltipHost:"ms-TooltipHost",root:"ms-DetailsHeader",cell:"ms-DetailsHeader-cell",cellIsCheck:"ms-DetailsHeader-cellIsCheck",collapseButton:"ms-DetailsHeader-collapseButton",isCollapsed:"is-collapsed",isAllSelected:"is-allSelected",isSelectAllHidden:"is-selectAllHidden",isResizingColumn:"is-resizingColumn",cellSizer:"ms-DetailsHeader-cellSizer",isResizing:"is-resizing",dropHintCircleStyle:"ms-DetailsHeader-dropHintCircleStyle",dropHintCaretStyle:"ms-DetailsHeader-dropHintCaretStyle",dropHintLineStyle:"ms-DetailsHeader-dropHintLineStyle",cellTitle:"ms-DetailsHeader-cellTitle",cellName:"ms-DetailsHeader-cellName",filterChevron:"ms-DetailsHeader-filterChevron",gripperBarVertical:"ms-DetailsColumn-gripperBarVertical",checkTooltip:"ms-DetailsHeader-checkTooltip",check:"ms-DetailsHeader-check"},Vv={root:"ms-DetailsRow-check",isDisabled:"ms-DetailsRow-check--isDisabled",isHeader:"ms-DetailsRow-check--isHeader"},Kv=Fn(),Gv=gt.memo(function(e){return gt.createElement(qh,{theme:e.theme,checked:e.checked,className:e.className,useFastIcons:!0})});function Uv(e){return gt.createElement(qh,{checked:e.checked})}function jv(e){return gt.createElement(Gv,{theme:e.theme,checked:e.checked})}function qv(t){return function(e){return e?e.column.isIconOnly?gt.createElement("span",{className:t.accessibleLabel},e.column.name):gt.createElement(gt.Fragment,null,e.column.name):null}}var Yv,Zv,Xv=In(function(e){var t=e.isVisible,o=void 0!==t&&t,n=e.canSelect,r=void 0!==n&&n,i=e.anySelected,s=void 0!==i&&i,a=e.selected,l=void 0!==a&&a,c=e.selectionMode,u=e.isHeader,d=void 0!==u&&u,p=e.className,t=(e.checkClassName,e.styles),n=e.theme,i=e.compact,a=e.onRenderDetailsCheckbox,u=e.useFastIcons,u=void 0===u\|\|u,e=mt(e,["isVisible","canSelect","anySelected","selected","selectionMode","isHeader","className","checkClassName","styles","theme","compact","onRenderDetailsCheckbox","useFastIcons"]),u=u?jv:Uv,u=a?Ma(a,u):u,o=Kv(t,{theme:n,canSelect:r,selected:l,anySelected:s,className:p,isHeader:d,isVisible:o,compact:i}),i={checked:l,theme:n},n=Bv("div",e,["aria-label","aria-labelledby","aria-describedby"]),c=c===dv.single?"radio":"checkbox";return r?gt.createElement("div",ht({},e,{role:c,className:Tr(o.root,o.check),"aria-checked":l,"data-selection-toggle":!0,"data-automationid":"DetailsRowCheck",tabIndex:-1}),u(i)):gt.createElement("div",ht({},n,{className:Tr(o.root,o.check)}))},function(e){var t=e.theme,o=e.className,n=e.isHeader,r=e.selected,i=e.anySelected,s=e.canSelect,a=e.compact,l=e.isVisible,c=zo(Vv,t),u=Hv.rowHeight,e=Hv.compactRowHeight,u=n?42:a?e:u,i=l\|\|r\|\|i;return{root:[c.root,o],check:[!s&&c.isDisabled,n&&c.isHeader,bo(t),t.fonts.small,jh.checkHost,{display:"flex",alignItems:"center",justifyContent:"center",cursor:"default",boxSizing:"border-box",verticalAlign:"top",background:"none",backgroundColor:"transparent",border:"none",opacity:i?1:0,height:u,width:48,padding:0,margin:0}],isDisabled:[]}},void 0,{scope:"DetailsRowCheck"},!0),Qv=(nb.prototype.dispose=function(){this._events&&this._events.dispose()},nb.prototype.subscribe=function(n,r,o){var i=this;this._initialized\|\|(this._events=new va(this),(t=ft())&&(this._events.on(t.body,"mouseup",this._onMouseUp.bind(this),!0),this._events.on(t,"mouseup",this._onDocumentMouseUp.bind(this),!0)),this._initialized=!0);var s,a,l,c,u,d,p,h,e=o.key,m=void 0===e?""+ ++this._lastId:e,g=[];if(o&&n){var t=o.eventMap,f=o.context,v=o.updateDropState,e={root:n,options:o,key:m},b=this._isDraggable(e),y=this._isDroppable(e);if((b\|\|y)&&t)for(var C=0,_=t;C<_.length;C++){var S=_[C],S={callback:S.callback.bind(null,f),eventName:S.eventName};g.push(S),this._events.on(n,S.eventName,S.callback)}y&&(a=function(e){e.isHandled\|\|(e.isHandled=!0,i._dragEnterCounts[m]--,0===i._dragEnterCounts[m]&&v(!1,e))},l=function(e){e.preventDefault(),e.isHandled\|\|(e.isHandled=!0,i._dragEnterCounts[m]++,1===i._dragEnterCounts[m]&&v(!0,e))},c=function(e){i._dragEnterCounts[m]=0,v(!1,e)},u=function(e){i._dragEnterCounts[m]=0,v(!1,e),o.onDrop&&o.onDrop(o.context.data,e)},d=function(e){e.preventDefault(),o.onDragOver&&o.onDragOver(o.context.data,e)},this._dragEnterCounts[m]=0,r.on(n,"dragenter",l),r.on(n,"dragleave",a),r.on(n,"dragend",c),r.on(n,"drop",u),r.on(n,"dragover",d)),b&&(p=this._onMouseDown.bind(this,e),c=this._onDragEnd.bind(this,e),s=function(e){var t=o;t&&t.onDragStart&&t.onDragStart(t.context.data,t.context.index,i._selection.getSelection(),e),i._isDragging=!0,e.dataTransfer&&e.dataTransfer.setData("id",n.id)},r.on(n,"dragstart",s),r.on(n,"mousedown",p),r.on(n,"dragend",c)),h={target:e,dispose:function(){if(i._activeTargets[m]===h&&delete i._activeTargets[m],n){for(var e=0,t=g;e<t.length;e++){var o=t[e];i._events.off(n,o.eventName,o.callback)}y&&(r.off(n,"dragenter",l),r.off(n,"dragleave",a),r.off(n,"dragend",c),r.off(n,"dragover",d),r.off(n,"drop",u)),b&&(r.off(n,"dragstart",s),r.off(n,"mousedown",p),r.off(n,"dragend",c))}}},this._activeTargets[m]=h}return{key:m,dispose:function(){h&&h.dispose()}}},nb.prototype.unsubscribe=function(e,t){t=this._activeTargets[t];t&&t.dispose()},nb.prototype._onDragEnd=function(e,t){e=e.options;e.onDragEnd&&e.onDragEnd(e.context.data,t)},nb.prototype._onMouseUp=function(e){if(this._isDragging=!1,this._dragData){for(var t=0,o=Object.keys(this._activeTargets);t<o.length;t++){var n=o[t],n=this._activeTargets[n];n.target.root&&(this._events.off(n.target.root,"mousemove"),this._events.off(n.target.root,"mouseleave"))}this._dragData.dropTarget&&(va.raise(this._dragData.dropTarget.root,"dragleave"),va.raise(this._dragData.dropTarget.root,"drop"))}this._dragData=null},nb.prototype._onDocumentMouseUp=function(e){var t=ft();t&&e.target===t.documentElement&&this._onMouseUp(e)},nb.prototype._onMouseMove=function(e,t){var o=t.buttons;this._dragData&&1!==(void 0===o?1:o)?this._onMouseUp(t):(o=e.root,t=e.key,this._isDragging&&this._isDroppable(e)&&this._dragData&&this._dragData.dropTarget&&this._dragData.dropTarget.key!==t&&!this._isChild(o,this._dragData.dropTarget.root)&&0<this._dragEnterCounts[this._dragData.dropTarget.key]&&(va.raise(this._dragData.dropTarget.root,"dragleave"),va.raise(o,"dragenter"),this._dragData.dropTarget=e))},nb.prototype._onMouseLeave=function(e,t){this._isDragging&&this._dragData&&this._dragData.dropTarget&&this._dragData.dropTarget.key===e.key&&(va.raise(e.root,"dragleave"),this._dragData.dropTarget=void 0)},nb.prototype._onMouseDown=function(e,t){if(0===t.button)if(this._isDraggable(e)){this._dragData={clientX:t.clientX,clientY:t.clientY,eventTarget:t.target,dragTarget:e};for(var o=0,n=Object.keys(this._activeTargets);o<n.length;o++){var r=n[o],r=this._activeTargets[r];r.target.root&&(this._events.on(r.target.root,"mousemove",this._onMouseMove.bind(this,r.target)),this._events.on(r.target.root,"mouseleave",this._onMouseLeave.bind(this,r.target)))}}else this._dragData=null},nb.prototype._isChild=function(e,t){for(;t&&t.parentElement;){if(t.parentElement===e)return!0;t=t.parentElement}return!1},nb.prototype._isDraggable=function(e){e=e.options;return!(!e.canDrag\|\|!e.canDrag(e.context.data))},nb.prototype._isDroppable=function(e){var t=e.options,e=this._dragData&&this._dragData.dragTarget?this._dragData.dragTarget.options.context:void 0;return!(!t.canDrop\|\|!t.canDrop(t.context,e))},nb),Jv=Fn(),$v=(l(ob,Zv=gt.Component),ob.prototype.render=function(){var e=this.props,t=e.column,o=e.parentId,n=e.isDraggable,r=e.styles,i=e.theme,s=e.cellStyleProps,a=void 0===s?Lv:s,l=e.useFastIcons,c=void 0===l\|\|l,u=this.props.onRenderColumnHeaderTooltip,s=void 0===u?this._onRenderColumnHeaderTooltip:u;this._classNames=Jv(r,{theme:i,headerClassName:t.headerClassName,iconClassName:t.iconClassName,isActionable:t.columnActionsMode!==Cv.disabled,isEmpty:!t.name,isIconVisible:t.isSorted\|\|t.isGrouped\|\|t.isFiltered,isPadded:t.isPadded,isIconOnly:t.isIconOnly,cellStyleProps:a,transitionDurationDrag:200,transitionDurationDrop:1500});e=this._classNames,l=c?Lr:Wr,u=t.onRenderFilterIcon?Ma(t.onRenderFilterIcon,this._onRenderFilterIcon(this._classNames)):this._onRenderFilterIcon(this._classNames),r=t.onRenderHeader?Ma(t.onRenderHeader,qv(this._classNames)):qv(this._classNames),i=t.columnActionsMode!==Cv.disabled&&(void 0!==t.onColumnClick\|\|void 0!==this.props.onColumnClick),c={"aria-label":t.ariaLabel\|\|(t.isIconOnly?t.name:void 0),"aria-labelledby":t.ariaLabel\|\|t.isIconOnly?void 0:o+"-"+t.key+"-name","aria-describedby":!this.props.onRenderColumnHeaderTooltip&&this._hasAccessibleDescription()?o+"-"+t.key+"-tooltip":void 0};return gt.createElement(gt.Fragment,null,gt.createElement("div",ht({key:t.key,ref:this._root,role:"columnheader"},!i&&c,{"aria-sort":t.isSorted?t.isSortedDescending?"descending":"ascending":"none","data-is-focusable":i\|\|t.columnActionsMode===Cv.disabled?void 0:"true",className:e.root,"data-is-draggable":n,draggable:n,style:{width:t.calculatedWidth+a.cellLeftPadding+a.cellRightPadding+(t.isPadded?a.cellExtraRightPadding:0)},"data-automationid":"ColumnsHeaderColumn","data-item-key":t.key}),n&&gt.createElement(l,{iconName:"GripperBarVertical",className:e.gripperBarVerticalStyle}),s({hostClassName:e.cellTooltip,id:o+"-"+t.key+"-tooltip",setAriaDescribedBy:!1,column:t,content:t.columnActionsMode!==Cv.disabled?t.ariaLabel:"",children:gt.createElement("span",ht({id:o+"-"+t.key,className:e.cellTitle,"data-is-focusable":i&&t.columnActionsMode!==Cv.disabled?"true":void 0,role:i?"button":void 0},i&&c,{onContextMenu:this._onColumnContextMenu,onClick:this._onColumnClick,"aria-haspopup":t.columnActionsMode===Cv.hasDropdown?"menu":void 0,"aria-expanded":t.columnActionsMode===Cv.hasDropdown?!!t.isMenuOpen:void 0}),gt.createElement("span",{id:o+"-"+t.key+"-name",className:e.cellName},(t.iconName\|\|t.iconClassName)&&gt.createElement(l,{className:e.iconClassName,iconName:t.iconName}),r(this.props)),t.isFiltered&&gt.createElement(l,{className:e.nearIcon,iconName:"Filter"}),t.isSorted&&gt.createElement(l,{className:e.sortIcon,iconName:t.isSortedDescending?"SortDown":"SortUp"}),t.isGrouped&&gt.createElement(l,{className:e.nearIcon,iconName:"GroupedDescending"}),t.columnActionsMode===Cv.hasDropdown&&!t.isIconOnly&&u({"aria-hidden":!0,columnProps:this.props,className:e.filterChevron,iconName:"ChevronDown"}))},this._onRenderColumnHeaderTooltip)),this.props.onRenderColumnHeaderTooltip?null:this._renderAccessibleDescription())},ob.prototype.componentDidMount=function(){var e=this;this.props.dragDropHelper&&this.props.isDraggable&&this._addDragDropHandling();var t=this._classNames;this.props.isDropped&&(this._root.current&&(this._root.current.classList.add(t.borderAfterDropping),this._async.setTimeout(function(){e._root.current&&e._root.current.classList.add(t.noBorderAfterDropping)},20)),this._async.setTimeout(function(){e._root.current&&(e._root.current.classList.remove(t.borderAfterDropping),e._root.current.classList.remove(t.noBorderAfterDropping))},1520))},ob.prototype.componentWillUnmount=function(){this._dragDropSubscription&&(this._dragDropSubscription.dispose(),delete this._dragDropSubscription),this._async.dispose(),this._events.dispose()},ob.prototype.componentDidUpdate=function(){!this._dragDropSubscription&&this.props.dragDropHelper&&this.props.isDraggable&&this._addDragDropHandling(),this._dragDropSubscription&&!this.props.isDraggable&&(this._dragDropSubscription.dispose(),this._events.off(this._root.current,"mousedown"),delete this._dragDropSubscription)},ob.prototype._getColumnDragDropOptions=function(){var e=this,t=this.props.columnIndex;return{selectionIndex:t,context:{data:t,index:t},canDrag:function(){return e.props.isDraggable},canDrop:function(){return!1},onDragStart:this._onDragStart,updateDropState:function(){},onDrop:function(){},onDragEnd:this._onDragEnd}},ob.prototype._hasAccessibleDescription=function(){var e=this.props.column;return!!(e.filterAriaLabel\|\|e.sortAscendingAriaLabel\|\|e.sortDescendingAriaLabel\|\|e.groupAriaLabel)},ob.prototype._renderAccessibleDescription=function(){var e=this.props,t=e.column,o=e.parentId,e=this._classNames;return this._hasAccessibleDescription()&&!this.props.onRenderColumnHeaderTooltip?gt.createElement("label",{key:t.key+"_label",id:o+"-"+t.key+"-tooltip",className:e.accessibleLabel,hidden:!0},t.isFiltered&&t.filterAriaLabel\|\|null,t.isSorted&&(t.isSortedDescending?t.sortDescendingAriaLabel:t.sortAscendingAriaLabel)\|\|null,t.isGrouped&&t.groupAriaLabel\|\|null):null},ob.prototype._addDragDropHandling=function(){this._dragDropSubscription=this.props.dragDropHelper.subscribe(this._root.current,this._events,this._getColumnDragDropOptions()),this._events.on(this._root.current,"mousedown",this._onRootMouseDown)},ob),eb={isActionable:"is-actionable",cellIsCheck:"ms-DetailsHeader-cellIsCheck",collapseButton:"ms-DetailsHeader-collapseButton",isCollapsed:"is-collapsed",isAllSelected:"is-allSelected",isSelectAllHidden:"is-selectAllHidden",isResizingColumn:"is-resizingColumn",isEmpty:"is-empty",isIconVisible:"is-icon-visible",cellSizer:"ms-DetailsHeader-cellSizer",isResizing:"is-resizing",dropHintCircleStyle:"ms-DetailsHeader-dropHintCircleStyle",dropHintLineStyle:"ms-DetailsHeader-dropHintLineStyle",cellTitle:"ms-DetailsHeader-cellTitle",cellName:"ms-DetailsHeader-cellName",filterChevron:"ms-DetailsHeader-filterChevron",gripperBarVerticalStyle:"ms-DetailsColumn-gripperBar",nearIcon:"ms-DetailsColumn-nearIcon"},tb=In($v,function(e){var t=e.theme,o=e.headerClassName,n=e.iconClassName,r=e.isActionable,i=e.isEmpty,s=e.isIconVisible,a=e.isPadded,l=e.isIconOnly,c=e.cellStyleProps,u=void 0===c?Lv:c,d=e.transitionDurationDrag,p=e.transitionDurationDrop,h=t.semanticColors,m=t.palette,g=t.fonts,f=zo(eb,t),v={iconForegroundColor:h.bodySubtext,headerForegroundColor:h.bodyText,headerBackgroundColor:h.bodyBackground,dropdownChevronForegroundColor:m.neutralSecondary,resizerColor:m.neutralTertiaryAlt},b={color:v.iconForegroundColor,opacity:1,paddingLeft:8},y={outline:"1px solid "+m.themePrimary},c={outlineColor:"transparent"};return{root:[Fv(e),g.small,r&&[f.isActionable,{selectors:{":hover":{color:h.bodyText,background:h.listHeaderBackgroundHovered},":active":{background:h.listHeaderBackgroundPressed}}}],i&&[f.isEmpty,{textOverflow:"clip"}],s&&f.isIconVisible,a&&{paddingRight:u.cellExtraRightPadding+u.cellRightPadding},{selectors:{':hover i[data-icon-name="GripperBarVertical"]':{display:"block"}}},o],gripperBarVerticalStyle:{display:"none",position:"absolute",textAlign:"left",color:m.neutralTertiary,left:1},nearIcon:[f.nearIcon,b],sortIcon:[b,{paddingLeft:4,position:"relative",top:1}],iconClassName:[{color:v.iconForegroundColor,opacity:1},n],filterChevron:[f.filterChevron,{color:v.dropdownChevronForegroundColor,paddingLeft:6,verticalAlign:"middle",fontSize:g.small.fontSize}],cellTitle:[f.cellTitle,bo(t),ht({display:"flex",flexDirection:"row",justifyContent:"flex-start",alignItems:"stretch",boxSizing:"border-box",overflow:"hidden",padding:"0 "+u.cellRightPadding+"px 0 "+u.cellLeftPadding+"px"},l?{alignContent:"flex-end",maxHeight:"100%",flexWrap:"wrap-reverse"}:{})],cellName:[f.cellName,{flex:"0 1 auto",overflow:"hidden",textOverflow:"ellipsis",fontWeight:Fe.semibold,fontSize:g.medium.fontSize},l&&{selectors:((l={})["."+f.nearIcon]={paddingLeft:0},l)}],cellTooltip:{display:"block",position:"absolute",top:0,left:0,bottom:0,right:0},accessibleLabel:So,borderWhileDragging:y,noBorderWhileDragging:[c,{transition:"outline "+d+"ms ease"}],borderAfterDropping:y,noBorderAfterDropping:[c,{transition:"outline "+p+"ms ease"}]}},void 0,{scope:"DetailsColumn"});function ob(e){var i=Zv.call(this,e)\|\|this;return i._root=gt.createRef(),i._onRenderFilterIcon=function(e){return function(e){var t=e.columnProps,e=mt(e,["columnProps"]),t=null!=t&&t.useFastIcons?Lr:Wr;return gt.createElement(t,ht({},e))}},i._onRenderColumnHeaderTooltip=function(e){return gt.createElement("span",{className:e.hostClassName},e.children)},i._onColumnClick=function(e){var t=i.props,o=t.onColumnClick,t=t.column;t.columnActionsMode!==Cv.disabled&&(t.onColumnClick&&t.onColumnClick(e,t),o&&o(e,t))},i._onDragStart=function(e,t,o,n){var r=i._classNames;t&&(i._updateHeaderDragInfo(t),i._root.current.classList.add(r.borderWhileDragging),i._async.setTimeout(function(){i._root.current&&i._root.current.classList.add(r.noBorderWhileDragging)},20))},i._onDragEnd=function(e,t){var o=i._classNames;t&&i._updateHeaderDragInfo(-1,t),i._root.current.classList.remove(o.borderWhileDragging),i._root.current.classList.remove(o.noBorderWhileDragging)},i._updateHeaderDragInfo=function(e,t){i.props.setDraggedItemIndex&&i.props.setDraggedItemIndex(e),i.props.updateDragInfo&&i.props.updateDragInfo({itemIndex:e},t)},i._onColumnContextMenu=function(e){var t=i.props,o=t.onColumnContextMenu,t=t.column;t.onColumnContextMenu&&(t.onColumnContextMenu(t,e),e.preventDefault()),o&&(o(t,e),e.preventDefault())},i._onRootMouseDown=function(e){i.props.isDraggable&&0===e.button&&e.stopPropagation()},fi(i),i._async=new Si(i),i._events=new va(i),i}function nb(e){this._selection=e.selection,this._dragEnterCounts={},this._activeTargets={},this._lastId=0,this._initialized=!1}(G=Yv=Yv\|\|{})[G.none=0]="none",G[G.hidden=1]="hidden",G[G.visible=2]="visible";var rb,ib=Fn(),sb=[],ab=(l(lb,rb=gt.Component),lb.prototype.componentDidMount=function(){var e=this.props.selection;this._events.on(e,gv,this._onSelectionChanged),this._rootElement.current&&(this._events.on(this._rootElement.current,"mousedown",this._onRootMouseDown),this._events.on(this._rootElement.current,"keydown",this._onRootKeyDown),this._getColumnReorderProps()&&(this._subscriptionObject=this._dragDropHelper.subscribe(this._rootElement.current,this._events,this._getHeaderDragDropOptions())))},lb.prototype.componentDidUpdate=function(e){var t,o;this._getColumnReorderProps()?!this._subscriptionObject&&this._rootElement.current&&(this._subscriptionObject=this._dragDropHelper.subscribe(this._rootElement.current,this._events,this._getHeaderDragDropOptions())):this._subscriptionObject&&(this._subscriptionObject.dispose(),delete this._subscriptionObject),this.props!==e&&0<=this._onDropIndexInfo.sourceIndex&&0<=this._onDropIndexInfo.targetIndex&&(t=e.columns,o=this.props.columns,(void 0===t?sb:t)[this._onDropIndexInfo.sourceIndex].key===(void 0===o?sb:o)[this._onDropIndexInfo.targetIndex].key&&(this._onDropIndexInfo={sourceIndex:-1,targetIndex:-1})),this.props.isAllCollapsed!==e.isAllCollapsed&&this.setState({isAllCollapsed:this.props.isAllCollapsed})},lb.prototype.componentWillUnmount=function(){this._subscriptionObject&&(this._subscriptionObject.dispose(),delete this._subscriptionObject),this._dragDropHelper.dispose(),this._events.dispose()},lb.prototype.render=function(){var n=this,e=this.props,t=e.columns,r=void 0===t?sb:t,o=e.ariaLabel,i=e.ariaLabelForToggleAllGroupsButton,s=e.ariaLabelForSelectAllCheckbox,a=e.selectAllVisibility,l=e.ariaLabelForSelectionColumn,c=e.indentWidth,u=e.onColumnClick,d=e.onColumnContextMenu,p=e.onRenderColumnHeaderTooltip,h=void 0===p?this._onRenderColumnHeaderTooltip:p,m=e.styles,g=e.selectionMode,f=e.theme,v=e.onRenderDetailsCheckbox,b=e.groupNestingDepth,y=e.useFastIcons,C=e.checkboxVisibility,_=e.className,S=this.state,x=S.isAllSelected,k=S.columnResizeDetails,t=S.isSizing,p=S.isAllCollapsed,e=a!==Yv.none,S=a===Yv.hidden,C=C===kv.always,w=this._getColumnReorderProps(),I=w&&w.frozenColumnCountFromStart?w.frozenColumnCountFromStart:0,D=w&&w.frozenColumnCountFromEnd?w.frozenColumnCountFromEnd:0;this._classNames=ib(m,{theme:f,isAllSelected:x,isSelectAllHidden:a===Yv.hidden,isResizingColumn:!!k&&t,isSizing:t,isAllCollapsed:p,isCheckboxHidden:S,className:_});var a=this._classNames,k=y?Lr:Wr,_=0<b&&this.props.collapseAllVisibility===yv.visible,E=1+(e?1:0)+(_?1:0),f=Pn(f);return gt.createElement(Zs,{role:"row","aria-label":o,className:a.root,componentRef:this._rootComponent,elementRef:this._rootElement,onMouseMove:this._onRootMouseMove,"data-automationid":"DetailsHeader",direction:Ei.horizontal},e?[gt.createElement("div",{key:"__checkbox",className:a.cellIsCheck,"aria-labelledby":this._id+"-checkTooltip",onClick:S?void 0:this._onSelectAllClicked,role:"columnheader"},h({hostClassName:a.checkTooltip,id:this._id+"-checkTooltip",setAriaDescribedBy:!1,content:s,children:gt.createElement(Xv,{id:this._id+"-check","aria-label":g===dv.multiple?s:l,"data-is-focusable":!S\|\|void 0,isHeader:!0,selected:x,anySelected:!1,canSelect:!S,className:a.check,onRenderDetailsCheckbox:v,useFastIcons:y,isVisible:C})},this._onRenderColumnHeaderTooltip)),this.props.onRenderColumnHeaderTooltip?null:s&&!S?gt.createElement("label",{key:"__checkboxLabel",id:this._id+"-checkTooltip",className:a.accessibleLabel,"aria-hidden":!0},s):l&&S?gt.createElement("label",{key:"__checkboxLabel",id:this._id+"-checkTooltip",className:a.accessibleLabel,"aria-hidden":!0},l):null]:null,_?gt.createElement("div",{className:a.cellIsGroupExpander,onClick:this._onToggleCollapseAll,"data-is-focusable":!0,"aria-label":i,"aria-expanded":!p,role:"columnheader"},gt.createElement(k,{className:a.collapseButton,iconName:f?"ChevronLeftMed":"ChevronRightMed"})):null,gt.createElement(Mv,{indentWidth:c,role:"gridcell",count:b-1}),r.map(function(e,t){var o=!!w&&I<=t&&t<r.length-D;return[w&&(o\|\|t===r.length-D)&&n._renderDropHint(t),gt.createElement(tb,{column:e,styles:e.styles,key:e.key,columnIndex:E+t,parentId:n._id,isDraggable:o,updateDragInfo:n._updateDragInfo,dragDropHelper:n._dragDropHelper,onColumnClick:u,onColumnContextMenu:d,onRenderColumnHeaderTooltip:n.props.onRenderColumnHeaderTooltip,isDropped:n._onDropIndexInfo.targetIndex===t,cellStyleProps:n.props.cellStyleProps,useFastIcons:y}),n._renderColumnDivider(t)]}),w&&0===D&&this._renderDropHint(r.length),t&&gt.createElement(sc,null,gt.createElement("div",{className:a.sizingOverlay,onMouseMove:this._onSizerMouseMove,onMouseUp:this._onSizerMouseUp})))},lb.prototype.focus=function(){var e;return!(null===(e=this._rootComponent.current)\|\|void 0===e\|\|!e.focus())},lb.prototype._getColumnReorderProps=function(){var e=this.props,t=e.columnReorderOptions;return e.columnReorderProps\|\|t&&ht(ht({},t),{onColumnDragEnd:void 0})},lb.prototype._getHeaderDragDropOptions=function(){return{selectionIndex:1,context:{data:this,index:0},canDrag:function(){return!1},canDrop:function(){return!0},onDragStart:function(){},updateDropState:this._updateDroppingState,onDrop:this._onDrop,onDragEnd:function(){},onDragOver:this._onDragOver}},lb.prototype._isValidCurrentDropHintIndex=function(){return 0<=this._currentDropHintIndex},lb.prototype._isCheckboxColumnHidden=function(){var e=this.props,t=e.selectionMode,e=e.checkboxVisibility;return t===dv.none\|\|e===kv.hidden},lb.prototype._resetDropHints=function(){0<=this._currentDropHintIndex&&(this._updateDropHintElement(this._dropHintDetails[this._currentDropHintIndex].dropHintElementRef,"none"),this._currentDropHintIndex=-1)},lb.prototype._updateDropHintElement=function(e,t){e.childNodes[1].style.display=t,e.childNodes[0].style.display=t},lb.prototype._isEventOnHeader=function(e){if(this._rootElement.current){var t=this._rootElement.current.getBoundingClientRect();if(e.clientX>t.left&&e.clientX<t.right&&e.clientY>t.top&&e.clientY<t.bottom)return Sv.header}},lb.prototype._renderColumnDivider=function(e){var t=this.props.columns,o=(void 0===t?sb:t)[e],t=o.onRenderDivider;return t?t({column:o,columnIndex:e},this._renderColumnSizer):this._renderColumnSizer({column:o,columnIndex:e})},lb.prototype._renderDropHint=function(e){var t=this._classNames,o=this.props.useFastIcons?Lr:Wr;return gt.createElement("div",{key:"dropHintKey",className:t.dropHintStyle,id:"columnDropHint_"+e},gt.createElement("div",{role:"presentation",key:"dropHintCircleKey",className:t.dropHintCaretStyle,"data-is-focusable":!1,"data-sizer-index":e,"aria-hidden":!0},gt.createElement(o,{iconName:"CircleShapeSolid"})),gt.createElement("div",{key:"dropHintLineKey","aria-hidden":!0,"data-is-focusable":!1,"data-sizer-index":e,className:t.dropHintLineStyle}))},lb.prototype._onSizerDoubleClick=function(e,t){var o=this.props,n=o.onColumnAutoResized,o=o.columns;n&&n((void 0===o?sb:o)[e],e)},lb.prototype._onSelectionChanged=function(){var e=!!this.props.selection&&this.props.selection.isAllSelected();this.state.isAllSelected!==e&&this.setState({isAllSelected:e})},lb.defaultProps={selectAllVisibility:Yv.visible,collapseAllVisibility:yv.visible,useFastIcons:!0},lb);function lb(e){var u=rb.call(this,e)\|\|this;return u._rootElement=gt.createRef(),u._rootComponent=gt.createRef(),u._draggedColumnIndex=-1,u._dropHintDetails={},u._updateDroppingState=function(e,t){0<=u._draggedColumnIndex&&"drop"!==t.type&&!e&&u._resetDropHints()},u._onDragOver=function(e,t){0<=u._draggedColumnIndex&&(t.stopPropagation(),u._computeDropHintToBeShown(t.clientX))},u._onDrop=function(e,t){var o,n,r=u._getColumnReorderProps();0<=u._draggedColumnIndex&&t&&(o=u._draggedColumnIndex>u._currentDropHintIndex?u._currentDropHintIndex:u._currentDropHintIndex-1,n=u._isValidCurrentDropHintIndex(),t.stopPropagation(),n&&(u._onDropIndexInfo.sourceIndex=u._draggedColumnIndex,u._onDropIndexInfo.targetIndex=o,r.onColumnDrop?(n={draggedIndex:u._draggedColumnIndex,targetIndex:o},r.onColumnDrop(n)):r.handleColumnReorder&&r.handleColumnReorder(u._draggedColumnIndex,o))),u._resetDropHints(),u._dropHintDetails={},u._draggedColumnIndex=-1},u._updateDragInfo=function(e,t){var o=u._getColumnReorderProps(),e=e.itemIndex;0<=e?(u._draggedColumnIndex=u._isCheckboxColumnHidden()?e-1:e-2,u._getDropHintPositions(),o.onColumnDragStart&&o.onColumnDragStart(!0)):t&&0<=u._draggedColumnIndex&&(u._resetDropHints(),u._draggedColumnIndex=-1,u._dropHintDetails={},o.onColumnDragEnd)&&(e=u._isEventOnHeader(t),o.onColumnDragEnd({dropLocation:e},t))},u._getDropHintPositions=function(){for(var e,t,o,n=u.props.columns,r=void 0===n?sb:n,n=u._getColumnReorderProps(),i=0,s=0,a=n.frozenColumnCountFromStart\|\|0,l=n.frozenColumnCountFromEnd\|\|0,c=a;c<r.length-l+1;c++)!u._rootElement.current\|\|(t=u._rootElement.current.querySelectorAll("#columnDropHint_"+c)[0])&&(c===a?(i=t.offsetLeft,s=t.offsetLeft,e=t):(o=(t.offsetLeft+i)/2,u._dropHintDetails[c-1]={originX:i,startX:s,endX:o,dropHintElementRef:e},s=o,i=(e=t).offsetLeft,c===r.length-l&&(u._dropHintDetails[c]={originX:i,startX:s,endX:t.offsetLeft,dropHintElementRef:e})))},u._computeDropHintToBeShown=function(e){var t=Pn(u.props.theme);if(u._rootElement.current){var o=e-u._rootElement.current.getBoundingClientRect().left,n=u._currentDropHintIndex;if(!u._isValidCurrentDropHintIndex()\|\|!cb(t,o,u._dropHintDetails[n].startX,u._dropHintDetails[n].endX)){var r=u.props.columns,i=void 0===r?sb:r,e=u._getColumnReorderProps(),r=e.frozenColumnCountFromStart\|\|0,e=e.frozenColumnCountFromEnd\|\|0,e=i.length-e,s=-1;if(ub(t,o,u._dropHintDetails[r].endX)?s=r:db(t,o,u._dropHintDetails[e].startX)?s=e:u._isValidCurrentDropHintIndex()&&(u._dropHintDetails[n+1]&&cb(t,o,u._dropHintDetails[n+1].startX,u._dropHintDetails[n+1].endX)?s=n+1:u._dropHintDetails[n-1]&&cb(t,o,u._dropHintDetails[n-1].startX,u._dropHintDetails[n-1].endX)&&(s=n-1)),-1===s)for(var a=r,l=e;a<l;){var c=Math.ceil((l+a)/2);if(cb(t,o,u._dropHintDetails[c].startX,u._dropHintDetails[c].endX)){s=c;break}ub(t,o,u._dropHintDetails[c].originX)?l=c:db(t,o,u._dropHintDetails[c].originX)&&(a=c)}s===u._draggedColumnIndex\|\|s===u._draggedColumnIndex+1?u._isValidCurrentDropHintIndex()&&u._resetDropHints():n!==s&&0<=s&&(u._resetDropHints(),u._updateDropHintElement(u._dropHintDetails[s].dropHintElementRef,"inline-block"),u._currentDropHintIndex=s)}}},u._renderColumnSizer=function(e){var t=e.columnIndex,o=u.props.columns,n=void 0===o?sb:o,r=n[t],e=u.state.columnResizeDetails,o=u._classNames;return r.isResizable?gt.createElement("div",{key:r.key+"_sizer","aria-hidden":!0,role:"button","data-is-focusable":!1,onClick:pb,"data-sizer-index":t,onBlur:u._onSizerBlur,className:Tr(o.cellSizer,t<n.length-1?o.cellSizerStart:o.cellSizerEnd,((n={})[o.cellIsResizing]=e&&e.columnIndex===t,n)),onDoubleClick:u._onSizerDoubleClick.bind(u,t)}):null},u._onRenderColumnHeaderTooltip=function(e){return gt.createElement("span",{className:e.hostClassName},e.children)},u._onSelectAllClicked=function(){var e=u.props.selection;e&&e.toggleAllSelected()},u._onRootMouseDown=function(e){var t=e.target.getAttribute("data-sizer-index"),o=Number(t),n=u.props.columns;null!==t&&0===e.button&&(u.setState({columnResizeDetails:{columnIndex:o,columnMinWidth:(void 0===n?sb:n)[o].calculatedWidth,originX:e.clientX}}),e.preventDefault(),e.stopPropagation())},u._onRootMouseMove=function(e){var t=u.state,o=t.columnResizeDetails,t=t.isSizing;o&&!t&&e.clientX!==o.originX&&u.setState({isSizing:!0})},u._onRootKeyDown=function(e){var t=u.state,o=t.columnResizeDetails,n=t.isSizing,r=u.props,i=r.columns,t=void 0===i?sb:i,i=r.onColumnResized,r=e.target.getAttribute("data-sizer-index");r&&!n&&(n=Number(r),o?(r=void 0,e.which===En.enter?(u.setState({columnResizeDetails:void 0}),e.preventDefault(),e.stopPropagation()):e.which===En.left?r=Pn(u.props.theme)?1:-1:e.which===En.right&&(r=Pn(u.props.theme)?-1:1),r&&(e.shiftKey\|\|(r=10),u.setState({columnResizeDetails:ht(ht({},o),{columnMinWidth:o.columnMinWidth+r})}),i&&i(t[n],o.columnMinWidth+r,n),e.preventDefault(),e.stopPropagation())):e.which===En.enter&&(u.setState({columnResizeDetails:{columnIndex:n,columnMinWidth:t[n].calculatedWidth}}),e.preventDefault(),e.stopPropagation()))},u._onSizerMouseMove=function(e){var t=e.buttons,o=u.props,n=o.onColumnIsSizingChanged,r=o.onColumnResized,i=o.columns,o=void 0===i?sb:i,i=u.state.columnResizeDetails;void 0===t\|\|1===t?(e.clientX!==i.originX&&n&&n(o[i.columnIndex],!0),r&&(n=e.clientX-i.originX,Pn(u.props.theme)&&(n=-n),r(o[i.columnIndex],i.columnMinWidth+n,i.columnIndex))):u._onSizerMouseUp(e)},u._onSizerBlur=function(e){u.state.columnResizeDetails&&u.setState({columnResizeDetails:void 0,isSizing:!1})},u._onSizerMouseUp=function(e){var t=u.props,o=t.columns,n=void 0===o?sb:o,o=t.onColumnIsSizingChanged,t=u.state.columnResizeDetails;u.setState({columnResizeDetails:void 0,isSizing:!1}),o&&o(n[t.columnIndex],!1)},u._onToggleCollapseAll=function(){var e=u.props.onToggleCollapseAll,t=!u.state.isAllCollapsed;u.setState({isAllCollapsed:t}),e&&e(t)},fi(u),u._events=new va(u),u.state={columnResizeDetails:void 0,isAllCollapsed:u.props.isAllCollapsed,isAllSelected:!!u.props.selection&&u.props.selection.isAllSelected()},u._onDropIndexInfo={sourceIndex:-1,targetIndex:-1},u._id=_s("header"),u._currentDropHintIndex=-1,u._dragDropHelper=new Qv({selection:{getSelection:function(){}},minimumPixelsForDrag:u.props.minimumPixelsForDrag}),u}function cb(e,t,o,n){return e?t<=o&&n<=t:o<=t&&t<=n}function ub(e,t,o){return e?o<=t:t<=o}function db(e,t,o){return e?t<=o:o<=t}function pb(e){e.stopPropagation()}var hb,mb=In(ab,function(e){var t=e.theme,o=e.className,n=e.isAllSelected,r=e.isResizingColumn,i=e.isSizing,s=e.isAllCollapsed,a=e.cellStyleProps,l=void 0===a?Lv:a,c=t.semanticColors,u=t.palette,d=t.fonts,p=zo(Wv,t),h={iconForegroundColor:c.bodySubtext,headerForegroundColor:c.bodyText,headerBackgroundColor:c.bodyBackground,resizerColor:u.neutralTertiaryAlt},m={opacity:1,transition:"opacity 0.3s linear"},a=Fv(e);return{root:[p.root,d.small,{display:"inline-block",background:h.headerBackgroundColor,position:"relative",minWidth:"100%",verticalAlign:"top",height:42,lineHeight:42,whiteSpace:"nowrap",boxSizing:"content-box",paddingBottom:"1px",paddingTop:"16px",borderBottom:"1px solid "+c.bodyDivider,cursor:"default",userSelect:"none",selectors:((e={})["&:hover ."+p.check]={opacity:1},e["& ."+p.tooltipHost+" ."+p.checkTooltip]={display:"block"},e)},n&&p.isAllSelected,r&&p.isResizingColumn,o],check:[p.check,{height:42},{selectors:((o={})["."+go+" 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0===e.calculatedWidth?"auto":e.calculatedWidth+s.cellLeftPadding+s.cellRightPadding+(e.isPadded?s.cellExtraRightPadding:0),n=e.onRender,r=void 0===n?c:n,n=e.getValueKey,n=void 0===n?u:n,r=d&&e.key in d?d[e.key]:r?r(a,l,e):"boolean"==typeof(t=null==(t=a&&e&&e.fieldName?a[e.fieldName]:"")?"":t)?t.toString():t,t=m[e.key],n=p&&n?n(a,l,e):void 0,t=void 0!==n&&void 0!==t&&n!==t?!0:!1;m[e.key]=n;n=e.key+(void 0!==n?"-"+n:"");return gt.createElement("div",{key:n,id:e.isRowHeader?h:void 0,role:e.isRowHeader?"rowheader":"gridcell","aria-readonly":!0,className:Tr(e.className,e.isMultiline&&i.isMultiline,e.isRowHeader&&i.isRowHeader,i.cell,e.isPadded?i.cellPadded:i.cellUnpadded,t&&i.cellAnimation),style:{width:o},"data-automationid":"DetailsRowCell","data-automation-key":e.key},r)}))},fb=Fn(),vb=[],bb=(l(yb,hb=gt.Component),yb.getDerivedStateFromProps=function(e,t){return ht(ht({},t),{selectionState:Cb(e)})},yb.prototype.componentDidMount=function(){var e=this.props,t=e.dragDropHelper,o=e.selection,n=e.item,e=e.onDidMount;t&&this._root.current&&(this._dragDropSubscription=t.subscribe(this._root.current,this._events,this._getRowDragDropOptions())),o&&this._events.on(o,gv,this._onSelectionChanged),e&&n&&(this._onDidMountCalled=!0,e(this))},yb.prototype.componentDidUpdate=function(e){var t=this.state,o=this.props,n=o.item,o=o.onDidMount,t=t.columnMeasureInfo;this.props.itemIndex===e.itemIndex&&this.props.item===e.item&&this.props.dragDropHelper===e.dragDropHelper\|\|(this._dragDropSubscription&&(this._dragDropSubscription.dispose(),delete this._dragDropSubscription),this.props.dragDropHelper&&this._root.current&&(this._dragDropSubscription=this.props.dragDropHelper.subscribe(this._root.current,this._events,this._getRowDragDropOptions()))),t&&0<=t.index&&this._cellMeasurer.current&&(e=this._cellMeasurer.current.getBoundingClientRect().width,t.onMeasureDone(e),this.setState({columnMeasureInfo:void 0})),n&&o&&!this._onDidMountCalled&&(this._onDidMountCalled=!0,o(this))},yb.prototype.componentWillUnmount=function(){var e=this.props,t=e.item,e=e.onWillUnmount;e&&t&&e(this),this._dragDropSubscription&&(this._dragDropSubscription.dispose(),delete this._dragDropSubscription),this._events.dispose()},yb.prototype.shouldComponentUpdate=function(e,t){if(this.props.useReducedRowRenderer){var o=Cb(e);return this.state.selectionState.isSelected!==o.isSelected\|\|!da(this.props,e)}return!0},yb.prototype.render=function(){var e=this.props,t=e.className,o=e.columns,n=void 0===o?vb:o,r=e.dragDropEvents,i=e.item,s=e.itemIndex,a=e.id,l=e.flatIndexOffset,c=void 0===l?2:l,u=e.onRenderCheck,d=void 0===u?this._onRenderCheck:u,p=e.onRenderDetailsCheckbox,h=e.onRenderItemColumn,m=e.getCellValueKey,g=e.selectionMode,f=e.rowWidth,v=void 0===f?0:f,b=e.checkboxVisibility,y=e.getRowAriaLabel,C=e.getRowAriaDescription,_=e.getRowAriaDescribedBy,S=e.checkButtonAriaLabel,x=e.checkboxCellClassName,k=e.rowFieldsAs,w=void 0===k?gb:k,I=e.selection,D=e.indentWidth,E=e.enableUpdateAnimations,T=e.compact,P=e.theme,R=e.styles,M=e.cellsByColumn,N=e.groupNestingDepth,B=e.useFastIcons,F=void 0===B\|\|B,A=e.cellStyleProps,L=e.group,H=e.focusZoneProps,O=e.disabled,z=void 0!==O&&O,W=this.state,o=W.columnMeasureInfo,l=W.isDropping,u=this.state.selectionState,f=u.isSelected,k=void 0!==f&&f,B=u.isSelectionModal,e=void 0!==B&&B,O=r?!(!r.canDrag\|\|!r.canDrag(i)):void 0,W=l?this._droppingClassNames\|\|"is-dropping":"",f=y?y(i):void 0,u=C?C(i):void 0,B=_?_(i):void 0,r=!!I&&I.canSelectItem(i,s)&&!z,l=g===dv.multiple,y=g!==dv.none&&b!==kv.hidden,C=g===dv.none?void 0:k,_=L?s-L.startIndex+1:void 0,I=L?L.count:void 0,L=H?H.direction:Ei.horizontal;this._classNames=ht(ht({},this._classNames),fb(R,{theme:P,isSelected:k,canSelect:!l,anySelected:e,checkboxCellClassName:x,droppingClassName:W,className:t,compact:T,enableUpdateAnimations:E,cellStyleProps:A,disabled:z}));t={isMultiline:this._classNames.isMultiline,isRowHeader:this._classNames.isRowHeader,cell:this._classNames.cell,cellAnimation:this._classNames.cellAnimation,cellPadded:this._classNames.cellPadded,cellUnpadded:this._classNames.cellUnpadded,fields:this._classNames.fields};da(this._rowClassNames\|\|{},t)\|\|(this._rowClassNames=t);E=gt.createElement(w,{rowClassNames:this._rowClassNames,rowHeaderId:a+"-header",cellsByColumn:M,columns:n,item:i,itemIndex:s,columnStartIndex:(y?1:0)+(N?1:0),onRenderItemColumn:h,getCellValueKey:m,enableUpdateAnimations:E,cellStyleProps:A}),A=this.props.role\|\|"row";return this._ariaRowDescriptionId=_s("DetailsRow-description"),gt.createElement(Zs,ht({"data-is-focusable":!0},ur(this.props,cr),"boolean"==typeof O?{"data-is-draggable":O,draggable:O}:{},H,{direction:L,elementRef:this._root,componentRef:this._focusZone,role:A,"aria-label":f,"aria-disabled":z\|\|void 0,"aria-describedby":u?this._ariaRowDescriptionId:B,className:this._classNames.root,"data-selection-index":s,"data-selection-touch-invoke":!0,"data-selection-disabled":z\|\|void 0,"data-item-index":s,"aria-rowindex":void 0===_?s+c:void 0,"aria-level":N&&N+1\|\|void 0,"aria-posinset":_,"aria-setsize":I,"data-automationid":"DetailsRow",style:{minWidth:v},"aria-selected":C,allowFocusRoot:!0}),u?gt.createElement("span",{key:"description",role:"presentation",hidden:!0,id:this._ariaRowDescriptionId},u):null,y&&gt.createElement("div",{role:"gridcell","data-selection-toggle":!0,className:this._classNames.checkCell},d({id:a?a+"-checkbox":void 0,selected:k,selectionMode:g,anySelected:e,"aria-label":S,"aria-labelledby":a?a+"-checkbox "+a+"-header":void 0,canSelect:r,compact:T,className:this._classNames.check,theme:P,isVisible:b===kv.always,onRenderDetailsCheckbox:p,useFastIcons:F})),gt.createElement(Mv,{indentWidth:D,role:"gridcell",count:N-(this.props.collapseAllVisibility===yv.hidden?1:0)}),i&&E,o&&gt.createElement("span",{role:"presentation",className:Tr(this._classNames.cellMeasurer,this._classNames.cell),ref:this._cellMeasurer},gt.createElement(w,{rowClassNames:this._rowClassNames,rowHeaderId:a+"-header",columns:[o.column],item:i,itemIndex:s,columnStartIndex:(y?1:0)+(N?1:0)+n.length,onRenderItemColumn:h,getCellValueKey:m})),gt.createElement("span",{role:"checkbox",className:this._classNames.checkCover,"aria-checked":k,"data-selection-toggle":!0}))},yb.prototype.measureCell=function(e,t){var o=this.props.columns,o=ht({},(void 0===o?vb:o)[e]);o.minWidth=0,o.maxWidth=999999,delete o.calculatedWidth,this.setState({columnMeasureInfo:{index:e,column:o,onMeasureDone:t}})},yb.prototype.focus=function(e){var t;return void 0===e&&(e=!1),!(null===(t=this._focusZone.current)\|\|void 0===t\|\|!t.focus(e))},yb.prototype._onRenderCheck=function(e){return gt.createElement(Xv,ht({},e))},yb.prototype._getRowDragDropOptions=function(){var e=this.props,t=e.item,o=e.itemIndex,n=e.dragDropEvents;return{eventMap:e.eventsToRegister,selectionIndex:o,context:{data:t,index:o},canDrag:n.canDrag,canDrop:n.canDrop,onDragStart:n.onDragStart,updateDropState:this._updateDroppingState,onDrop:n.onDrop,onDragEnd:n.onDragEnd,onDragOver:n.onDragOver}},yb);function yb(e){var i=hb.call(this,e)\|\|this;return i._root=gt.createRef(),i._cellMeasurer=gt.createRef(),i._focusZone=gt.createRef(),i._onSelectionChanged=function(){var e=Cb(i.props);da(e,i.state.selectionState)\|\|i.setState({selectionState:e})},i._updateDroppingState=function(e,t){var o=i.state.isDropping,n=i.props,r=n.dragDropEvents,n=n.item;e?r.onDragEnter&&(i._droppingClassNames=r.onDragEnter(n,t)):r.onDragLeave&&r.onDragLeave(n,t),o!==e&&i.setState({isDropping:e})},fi(i),i._events=new va(i),i.state={selectionState:Cb(e),columnMeasureInfo:void 0,isDropping:!1},i._droppingClassNames="",i}function Cb(e){var t=e.itemIndex,e=e.selection;return{isSelected:!(null==e\|\|!e.isIndexSelected(t)),isSelectionModal:!(null===(t=null==e?void 0:e.isModal)\|\|void 0===t\|\|!t.call(e))}}var _b,Sb,xb=In(bb,zv,void 0,{scope:"DetailsRow"}),kb={root:"ms-GroupedList",compact:"ms-GroupedList--Compact",group:"ms-GroupedList-group",link:"ms-Link",listCell:"ms-List-cell"},wb={root:"ms-GroupHeader",compact:"ms-GroupHeader--compact",check:"ms-GroupHeader-check",dropIcon:"ms-GroupHeader-dropIcon",expand:"ms-GroupHeader-expand",isCollapsed:"is-collapsed",title:"ms-GroupHeader-title",isSelected:"is-selected",iconTag:"ms-Icon--Tag",group:"ms-GroupedList-group",isDropping:"is-dropping"},Ib="cubic-bezier(0.390, 0.575, 0.565, 1.000)";(Y=_b=_b\|\|{})[Y.xSmall=0]="xSmall",Y[Y.small=1]="small",Y[Y.medium=2]="medium",Y[Y.large=3]="large",(ke=Sb=Sb\|\|{})[ke.normal=0]="normal",ke[ke.large=1]="large";var Db,Eb,Tb,Pb,Rb=Fn(),Mb=(l(e0,Pb=gt.Component),e0.prototype.render=function(){var e=this.props,t=e.type,o=e.size,n=e.ariaLabel,r=e.ariaLive,i=e.styles,s=e.label,a=e.theme,l=e.className,c=e.labelPosition,u=n,e=ur(this.props,cr,["size"]),n=o;void 0===o&&void 0!==t&&(n=t===Sb.large?_b.large:_b.medium);c=Rb(i,{theme:a,size:n,className:l,labelPosition:c});return gt.createElement("div",ht({},e,{className:c.root}),gt.createElement("div",{className:c.circle}),s&&gt.createElement("div",{className:c.label},s),u&&gt.createElement("div",{role:"status","aria-live":r},gt.createElement(Ri,null,gt.createElement("div",{className:c.screenReaderText},u))))},e0.defaultProps={size:_b.medium,ariaLive:"polite",labelPosition:"bottom"},e0),Nb={root:"ms-Spinner",circle:"ms-Spinner-circle",label:"ms-Spinner-label"},Bb=Ao(function(){return O({"0%":{transform:"rotate(0deg)"},"100%":{transform:"rotate(360deg)"}})}),Fb=In(Mb,function(e){var t=e.theme,o=e.size,n=e.className,r=e.labelPosition,i=t.palette,e=zo(Nb,t);return{root:[e.root,{display:"flex",flexDirection:"column",alignItems:"center",justifyContent:"center"},"top"===r&&{flexDirection:"column-reverse"},"right"===r&&{flexDirection:"row"},"left"===r&&{flexDirection:"row-reverse"},n],circle:[e.circle,{boxSizing:"border-box",borderRadius:"50%",border:"1.5px solid "+i.themeLight,borderTopColor:i.themePrimary,animationName:Bb(),animationDuration:"1.3s",animationIterationCount:"infinite",animationTimingFunction:"cubic-bezier(.53,.21,.29,.67)",selectors:((n={})[Yt]=ht({borderTopColor:"Highlight"},{forcedColorAdjust:"none",MsHighContrastAdjust:"none"}),n)},o===_b.xSmall&&["ms-Spinner--xSmall",{width:12,height:12}],o===_b.small&&["ms-Spinner--small",{width:16,height:16}],o===_b.medium&&["ms-Spinner--medium",{width:20,height:20}],o===_b.large&&["ms-Spinner--large",{width:28,height:28}]],label:[e.label,t.fonts.small,{color:i.themePrimary,margin:"8px 0 0",textAlign:"center"},"top"===r&&{margin:"0 0 8px"},"right"===r&&{margin:"0 0 0 8px"},"left"===r&&{margin:"0 8px 0 0"}],screenReaderText:So}},void 0,{scope:"Spinner"}),Ab=Fn(),K=(l($b,Tb=gt.Component),$b.getDerivedStateFromProps=function(e,t){if(e.group){var o=e.group.isCollapsed,n=e.isGroupLoading,e=!o&&n&&n(e.group);return ht(ht({},t),{isCollapsed:o\|\|!1,isLoadingVisible:e\|\|!1})}return t},$b.prototype.render=function(){var e=this.props,t=e.group,o=e.groupLevel,n=void 0===o?0:o,r=e.viewport,i=e.selectionMode,s=e.loadingText,a=e.isSelected,l=void 0!==a&&a,c=e.selected,u=void 0!==c&&c,d=e.indentWidth,p=e.onRenderTitle,h=void 0===p?this._onRenderTitle:p,m=e.onRenderGroupHeaderCheckbox,g=e.isCollapsedGroupSelectVisible,f=void 0===g\|\|g,v=e.expandButtonProps,b=e.expandButtonIcon,y=e.selectAllButtonProps,C=e.theme,_=e.styles,S=e.className,x=e.compact,o=e.ariaPosInSet,a=e.ariaSetSize,c=e.ariaRowIndex,p=e.useFastIcons?this._fastDefaultCheckboxRender:this._defaultCheckboxRender,g=m?Ma(m,p):p,e=this.state,m=e.isCollapsed,p=e.isLoadingVisible,e=i===dv.multiple,f=e&&(f\|\|!(t&&t.isCollapsed)),u=u\|\|l,l=Pn(C);return this._classNames=Ab(_,{theme:C,className:S,selected:u,isCollapsed:m,compact:x}),t?gt.createElement("div",{className:this._classNames.root,style:r?{minWidth:r.width}:{},onClick:this._onHeaderClick,role:"row","aria-setsize":a,"aria-posinset":o,"aria-rowindex":c,"data-is-focusable":!0,onKeyUp:this._onKeyUp,"aria-label":t.ariaLabel,"aria-labelledby":t.ariaLabel?void 0:this._id,"aria-expanded":!this.state.isCollapsed,"aria-selected":e?u:void 0,"aria-level":n+1},gt.createElement("div",{className:this._classNames.groupHeaderContainer,role:"presentation"},f?gt.createElement("div",{role:"gridcell"},gt.createElement("button",ht({"data-is-focusable":!1,type:"button",className:this._classNames.check,role:"checkbox",id:this._id+"-check","aria-checked":u,"aria-labelledby":this._id+"-check "+this._id,"data-selection-toggle":!0,onClick:this._onToggleSelectGroupClick},y),g({checked:u,theme:C},g))):i!==dv.none&&gt.createElement(Mv,{indentWidth:48,count:1}),gt.createElement(Mv,{indentWidth:d,count:n}),gt.createElement("div",{className:this._classNames.dropIcon,role:"presentation"},gt.createElement(Wr,{iconName:"Tag"})),gt.createElement("div",{role:"gridcell"},gt.createElement("button",ht({"data-is-focusable":!1,type:"button",className:this._classNames.expand,onClick:this._onToggleClick,"aria-expanded":!this.state.isCollapsed},v),gt.createElement(Wr,{className:this._classNames.expandIsCollapsed,iconName:b\|\|(l?"ChevronLeftMed":"ChevronRightMed")}))),h(this.props,this._onRenderTitle),p&&gt.createElement(Fb,{label:s}))):null},$b.prototype._defaultCheckboxRender=function(e){return gt.createElement(qh,{checked:e.checked})},$b.prototype._fastDefaultCheckboxRender=function(e){return gt.createElement(Lb,{theme:e.theme,checked:e.checked})},$b.defaultProps={expandButtonProps:{"aria-label":"expand collapse group"}},$b),Lb=gt.memo(function(e){return gt.createElement(qh,{theme:e.theme,checked:e.checked,className:e.className,useFastIcons:!0})}),Hb=In(K,function(e){var t,o=e.theme,n=e.className,r=e.selected,i=e.isCollapsed,s=e.compact,a=Lv.cellLeftPadding,l=s?40:48,c=o.semanticColors,u=o.palette,d=o.fonts,p=zo(wb,o),h=[bo(o),{cursor:"default",background:"none",backgroundColor:"transparent",border:"none",padding:0}];return{root:[p.root,bo(o),o.fonts.medium,{borderBottom:"1px solid "+c.listBackground,cursor:"default",userSelect:"none",selectors:((t={":hover":{background:c.listItemBackgroundHovered,color:c.actionLinkHovered}})["&:hover ."+p.check]={opacity:1},t["."+go+" &:focus ."+p.check]={opacity:1},t[":global(."+p.group+"."+p.isDropping+")"]={selectors:((e={})["& > ."+p.root+" ."+p.dropIcon]={transition:"transform "+we.durationValue4+" cubic-bezier(0.075, 0.820, 0.165, 1.000) opacity "+we.durationValue1+" "+Ib,transitionDelay:we.durationValue3,opacity:1,transform:"rotate(0.2deg) scale(1);"},e["."+p.check]={opacity:0},e)},t)},r&&[p.isSelected,{background:c.listItemBackgroundChecked,selectors:((c={":hover":{background:c.listItemBackgroundCheckedHovered}})[""+p.check]={opacity:1},c)}],s&&[p.compact,{border:"none"}],n],groupHeaderContainer:[{display:"flex",alignItems:"center",height:l}],headerCount:[{padding:"0px 4px"}],check:[p.check,h,{display:"flex",alignItems:"center",justifyContent:"center",paddingTop:1,marginTop:-1,opacity:0,width:48,height:l,selectors:((n={})["."+go+" &:focus"]={opacity:1},n)}],expand:[p.expand,h,{display:"flex",alignItems:"center",justifyContent:"center",fontSize:d.small.fontSize,width:36,height:l,color:r?u.neutralPrimary:u.neutralSecondary,selectors:{":hover":{backgroundColor:r?u.neutralQuaternary:u.neutralLight},":active":{backgroundColor:r?u.neutralTertiaryAlt:u.neutralQuaternaryAlt}}}],expandIsCollapsed:[i?[p.isCollapsed,{transform:"rotate(0deg)",transformOrigin:"50% 50%",transition:"transform .1s linear"}]:{transform:Pn(o)?"rotate(-90deg)":"rotate(90deg)",transformOrigin:"50% 50%",transition:"transform .1s linear"}],title:[p.title,{paddingLeft:a,fontSize:(s?d.medium:d.mediumPlus).fontSize,fontWeight:i?Fe.regular:Fe.semibold,cursor:"pointer",outline:0,whiteSpace:"nowrap",textOverflow:"ellipsis"}],dropIcon:[p.dropIcon,{position:"absolute",left:-26,fontSize:Ae.large,color:u.neutralSecondary,transition:"transform "+we.durationValue2+" cubic-bezier(0.600, -0.280, 0.735, 0.045), opacity "+we.durationValue4+" "+Ib,opacity:0,transform:"rotate(0.2deg) scale(0.65)",transformOrigin:"10px 10px",selectors:((u={})[":global(."+p.iconTag+")"]={position:"absolute"},u)}]}},void 0,{scope:"GroupHeader"}),Ob={root:"ms-GroupShowAll",link:"ms-Link"},zb=Fn(),Wb=In(function(e){var t=e.group,o=e.groupLevel,n=e.showAllLinkText,r=void 0===n?"Show All":n,i=e.styles,n=e.theme,s=e.onToggleSummarize,i=zb(i,{theme:n}),n=(0,gt.useCallback)(function(e){s(t),e.stopPropagation(),e.preventDefault()},[s,t]);return t?gt.createElement("div",{className:i.root},gt.createElement(Mv,{count:o}),gt.createElement(ua,{onClick:n},r)):null},function(e){var t=e.theme,o=t.fonts,e=zo(Ob,t);return{root:[e.root,{position:"relative",padding:"10px 84px",cursor:"pointer",selectors:((t={})["."+e.link]={fontSize:o.small.fontSize},t)}]}},void 0,{scope:"GroupShowAll"}),Vb={root:"ms-groupFooter"},Kb=Fn(),Gb=In(function(e){var t=e.group,o=e.groupLevel,n=e.footerText,r=e.indentWidth,i=e.styles,e=e.theme,e=Kb(i,{theme:e});return t&&n?gt.createElement("div",{className:e.root},gt.createElement(Mv,{indentWidth:r,count:o}),n):null},function(e){var t=e.theme,o=e.className,e=zo(Vb,t);return{root:[t.fonts.medium,e.root,{position:"relative",padding:"5px 38px"},o]}},void 0,{scope:"GroupFooter"}),Ub=(l(Jb,Eb=gt.Component),Jb.prototype.componentDidMount=function(){var e=this.props,t=e.dragDropHelper,e=e.selection;t&&this._root.current&&(this._dragDropSubscription=t.subscribe(this._root.current,this._events,this._getGroupDragDropOptions())),e&&this._events.on(e,gv,this._onSelectionChange)},Jb.prototype.componentWillUnmount=function(){this._events.dispose(),this._dragDropSubscription&&this._dragDropSubscription.dispose()},Jb.prototype.componentDidUpdate=function(e){this.props.group===e.group&&this.props.groupIndex===e.groupIndex&&this.props.dragDropHelper===e.dragDropHelper\|\|(this._dragDropSubscription&&(this._dragDropSubscription.dispose(),delete this._dragDropSubscription),this.props.dragDropHelper&&this._root.current&&(this._dragDropSubscription=this.props.dragDropHelper.subscribe(this._root.current,this._events,this._getGroupDragDropOptions())))},Jb.prototype.render=function(){var e=this.props,t=e.getGroupItemLimit,o=e.group,n=e.groupIndex,r=e.headerProps,i=e.showAllProps,s=e.footerProps,a=e.viewport,l=e.selectionMode,c=e.onRenderGroupHeader,u=void 0===c?this._onRenderGroupHeader:c,d=e.onRenderGroupShowAll,p=void 0===d?this._onRenderGroupShowAll:d,h=e.onRenderGroupFooter,m=void 0===h?this._onRenderGroupFooter:h,g=e.onShouldVirtualize,f=e.groupedListClassNames,v=e.groups,b=e.compact,c=e.listProps,d=void 0===c?{}:c,h=this.state.isSelected,e=o&&t?t(o):1/0,c=o&&!o.children&&!o.isCollapsed&&!o.isShowingAll&&(o.count>e\|\|o.hasMoreData),t=o&&o.children&&0<o.children.length,d=d.version,b={group:o,groupIndex:n,groupLevel:o?o.level:0,isSelected:h,selected:h,viewport:a,selectionMode:l,groups:v,compact:b},n={groupedListId:this._id,ariaSetSize:v?v.length:void 0,ariaPosInSet:void 0!==n?n+1:void 0},n=ht(ht(ht({},r),b),n),i=ht(ht({},i),b),s=ht(ht({},s),b),b=!!this.props.dragDropHelper&&this._getGroupDragDropOptions().canDrag(o)&&!!this.props.dragDropEvents.canDragGroups;return gt.createElement("div",ht({ref:this._root},b&&{draggable:!0},{className:Tr(f&&f.group,this._getDroppingClassName()),role:"presentation"}),u(n,this._onRenderGroupHeader),o&&o.isCollapsed?null:t?gt.createElement(Wf,{role:"presentation",ref:this._list,items:o?o.children:[],onRenderCell:this._renderSubGroup,getItemCountForPage:this._returnOne,onShouldVirtualize:g,version:d,id:this._id}):this._onRenderGroup(e),o&&o.isCollapsed?null:c&&p(i,this._onRenderGroupShowAll),m(s,this._onRenderGroupFooter))},Jb.prototype.forceUpdate=function(){Eb.prototype.forceUpdate.call(this),this.forceListUpdate()},Jb.prototype.forceListUpdate=function(){var e,t=this.props.group;if(this._list.current){if(this._list.current.forceUpdate(),t&&t.children&&0<t.children.length)for(var o=t.children.length,n=0;n<o;n++)(e=this._list.current.pageRefs["subGroup_"+String(n)])&&e.forceListUpdate()}else(e=this._subGroupRefs["subGroup_"+String(0)])&&e.forceListUpdate()},Jb.prototype._onSelectionChange=function(){var e=this.props,t=e.group,e=e.selection;e&&t&&((t=e.isRangeSelected(t.startIndex,t.count))!==this.state.isSelected&&this.setState({isSelected:t}))},Jb.prototype._onRenderGroupCell=function(o,n,r){return function(e,t){return o(n,e,t,r)}},Jb.prototype._onRenderGroup=function(e){var t=this.props,o=t.group,n=t.items,r=t.onRenderCell,i=t.listProps,s=t.groupNestingDepth,a=t.onShouldVirtualize,l=t.groupProps,c=o&&!o.isShowingAll?o.count:n.length,t=o?o.startIndex:0;return gt.createElement(Wf,ht({role:l&&l.role?l.role:"rowgroup","aria-label":null==o?void 0:o.name,items:n,onRenderCell:this._onRenderGroupCell(r,s,o),ref:this._list,renderCount:Math.min(c,e),startIndex:t,onShouldVirtualize:a,id:this._id},i))},Jb.prototype._returnOne=function(){return 1},Jb.prototype._getGroupKey=function(e,t){return"group-"+(e&&e.key?e.key:String(e.level)+String(t))},Jb.prototype._getDroppingClassName=function(){var e=this.state.isDropping,t=this.props,o=t.group,t=t.groupedListClassNames;return Tr((e=!(!o\|\|!e))&&this._droppingClassName,e&&"is-dropping",e&&t&&t.groupIsDropping)},Jb),jb=Fn(),qb=Hv.rowHeight,Yb=Hv.compactRowHeight,Zb=(l(Qb,Db=gt.Component),Qb.getDerivedStateFromProps=function(e,t){var o=e.groups,n=e.selectionMode,r=e.compact,i=e.items,s=e.listProps,a=s&&s.version,e=ht(ht({},t),{selectionMode:n,compact:r,groups:o,listProps:s}),s=!1;return a===(t.listProps&&t.listProps.version)&&i===t.items&&o===t.groups&&n===t.selectionMode&&r===t.compact\|\|(s=!0),o!==t.groups&&(e=ht(ht({},e),{groups:o})),e=(s=n!==t.selectionMode\|\|r!==t.compact?!0:s)?ht(ht({},e),{version:{}}):e},Qb.prototype.scrollToIndex=function(e,t,o){this._list.current&&this._list.current.scrollToIndex(e,t,o)},Qb.prototype.getStartItemIndexInView=function(){return this._list.current.getStartItemIndexInView()\|\|0},Qb.prototype.componentDidMount=function(){var e=this.props,t=e.groupProps,e=e.groups;t&&t.isAllGroupsCollapsed&&this._setGroupsCollapsedState(void 0===e?[]:e,t.isAllGroupsCollapsed)},Qb.prototype.render=function(){var e=this.props,t=e.className,o=e.usePageCache,n=e.onShouldVirtualize,r=e.theme,i=e.role,s=void 0===i?"treegrid":i,a=e.styles,l=e.compact,c=e.focusZoneProps,u=void 0===c?{}:c,i=e.rootListProps,c=void 0===i?{}:i,e=this.state,i=e.groups,e=e.version;this._classNames=jb(a,{theme:r,className:t,compact:l});l=u.shouldEnterInnerZone,l=void 0===l?this._isInnerZoneKeystroke:l;return gt.createElement(Zs,ht({direction:Ei.vertical,"data-automationid":"GroupedList","data-is-scrollable":"false",role:"presentation"},u,{shouldEnterInnerZone:l,className:Tr(this._classNames.root,u.className)}),i?gt.createElement(Wf,ht({ref:this._list,role:s,items:i,onRenderCell:this._renderGroup,getItemCountForPage:this._returnOne,getPageHeight:this._getPageHeight,getPageSpecification:this._getPageSpecification,usePageCache:o,onShouldVirtualize:n,version:e},c)):this._renderGroup(void 0,0))},Qb.prototype.forceUpdate=function(){Db.prototype.forceUpdate.call(this),this._forceListUpdates()},Qb.prototype.toggleCollapseAll=function(e){var t=this.state.groups,o=void 0===t?[]:t,t=this.props.groupProps,t=t&&t.onToggleCollapseAll;0<o.length&&(t&&t(e),this._setGroupsCollapsedState(o,e),this._updateIsSomeGroupExpanded(),this.forceUpdate())},Qb.prototype._setGroupsCollapsedState=function(e,t){for(var o=0;o<e.length;o++)e[o].isCollapsed=t},Qb.prototype._returnOne=function(){return 1},Qb.prototype._getGroupKey=function(e,t){return"group-"+(e&&e.key?e.key:String(t))},Qb.prototype._getGroupNestingDepth=function(){for(var e=0,t=this.state.groups;t&&0<t.length;)e++,t=t[0].children;return e},Qb.prototype._forceListUpdates=function(e){this.setState({version:{}})},Qb.prototype._computeIsSomeGroupExpanded=function(e){var t=this;return!(!e\|\|!e.some(function(e){return e.children?t._computeIsSomeGroupExpanded(e.children):!e.isCollapsed}))},Qb.prototype._updateIsSomeGroupExpanded=function(){var e=this.state.groups,t=this.props.onGroupExpandStateChanged,e=this._computeIsSomeGroupExpanded(e);this._isSomeGroupExpanded!==e&&(t&&t(e),this._isSomeGroupExpanded=e)},Qb.defaultProps={selectionMode:dv.multiple,isHeaderVisible:!0,groupProps:{},compact:!1},Qb),Xb=In(Zb,function(e){var t=e.theme,o=e.className,n=e.compact,r=t.palette,e=zo(kb,t);return{root:[e.root,t.fonts.small,{position:"relative",selectors:((t={})["."+e.listCell]={minHeight:38},t)},n&&[e.compact,{selectors:((n={})["."+e.listCell]={minHeight:32},n)}],o],group:[e.group,{transition:"background-color "+we.durationValue2+" cubic-bezier(0.445, 0.050, 0.550, 0.950)"}],groupIsDropping:{backgroundColor:r.neutralLight}}},void 0,{scope:"GroupedList"});function Qb(e){var y=Db.call(this,e)\|\|this;y._list=gt.createRef(),y._renderGroup=function(e,t){var o=y.props,n=o.dragDropEvents,r=o.dragDropHelper,i=o.eventsToRegister,s=o.groupProps,a=o.items,l=o.listProps,c=o.onRenderCell,u=o.selectionMode,d=o.selection,p=o.viewport,h=o.onShouldVirtualize,m=o.groups,g=o.compact,f={onToggleSelectGroup:y._onToggleSelectGroup,onToggleCollapse:y._onToggleCollapse,onToggleSummarize:y._onToggleSummarize},v=ht(ht({},s.headerProps),f),b=ht(ht({},s.showAllProps),f),o=ht(ht({},s.footerProps),f),f=y._getGroupNestingDepth();if(!s.showEmptyGroups&&e&&0===e.count)return null;l=ht(ht({},l\|\|{}),{version:y.state.version});return gt.createElement(Ub,{key:y._getGroupKey(e,t),dragDropEvents:n,dragDropHelper:r,eventsToRegister:i,footerProps:o,getGroupItemLimit:s&&s.getGroupItemLimit,group:e,groupIndex:t,groupNestingDepth:f,groupProps:s,headerProps:v,listProps:l,items:a,onRenderCell:c,onRenderGroupHeader:s.onRenderHeader,onRenderGroupShowAll:s.onRenderShowAll,onRenderGroupFooter:s.onRenderFooter,selectionMode:u,selection:d,showAllProps:b,viewport:p,onShouldVirtualize:h,groupedListClassNames:y._classNames,groups:m,compact:g})},y._getDefaultGroupItemLimit=function(e){return e.children&&0<e.children.length?e.children.length:e.count},y._getGroupItemLimit=function(e){var t=y.props.groupProps;return(t&&t.getGroupItemLimit?t.getGroupItemLimit:y._getDefaultGroupItemLimit)(e)},y._getGroupHeight=function(e){var t=y.props.compact?Yb:qb;return t+(e.isCollapsed?0:ty._getGroupItemLimit(e))},y._getPageHeight=function(e){var t=y.state.groups,o=y.props.getGroupHeight,o=void 0===o?y._getGroupHeight:o,t=t&&t[e];return t?o(t,e):0},y._onToggleCollapse=function(e){var t=y.props.groupProps,t=t&&t.headerProps&&t.headerProps.onToggleCollapse;e&&(t&&t(e),e.isCollapsed=!e.isCollapsed,y._updateIsSomeGroupExpanded(),y.forceUpdate())},y._onToggleSelectGroup=function(e){var t=y.props,o=t.selection,t=t.selectionMode;e&&o&&t===dv.multiple&&o.toggleRangeSelected(e.startIndex,e.count)},y._isInnerZoneKeystroke=function(e){return e.which===Mn(En.right)},y._onToggleSummarize=function(e){var t=y.props.groupProps,t=t&&t.showAllProps&&t.showAllProps.onToggleSummarize;t?t(e):(e&&(e.isShowingAll=!e.isShowingAll),y.forceUpdate())},y._getPageSpecification=function(e){var t=y.state.groups,e=t&&t[e];return{key:e&&e.key}},fi(y),y._isSomeGroupExpanded=y._computeIsSomeGroupExpanded(e.groups);var t=e.listProps,t=(void 0===t?{}:t).version;return y.state={groups:e.groups,items:e.items,listProps:e.listProps,version:void 0===t?{}:t},y}function Jb(e){var x=Eb.call(this,e)\|\|this;x._root=gt.createRef(),x._list=gt.createRef(),x._subGroupRefs={},x._droppingClassName="",x._onRenderGroupHeader=function(e){return gt.createElement(Hb,ht({},e))},x._onRenderGroupShowAll=function(e){return gt.createElement(Wb,ht({},e))},x._onRenderGroupFooter=function(e){return gt.createElement(Gb,ht({},e))},x._renderSubGroup=function(e,t){var o=x.props,n=o.dragDropEvents,r=o.dragDropHelper,i=o.eventsToRegister,s=o.getGroupItemLimit,a=o.groupNestingDepth,l=o.groupProps,c=o.items,u=o.headerProps,d=o.showAllProps,p=o.footerProps,h=o.listProps,m=o.onRenderCell,g=o.selection,f=o.selectionMode,v=o.viewport,b=o.onRenderGroupHeader,y=o.onRenderGroupShowAll,C=o.onRenderGroupFooter,_=o.onShouldVirtualize,S=o.group,o=o.compact,a=e.level?e.level+1:a;return!e\|\|0<e.count\|\|l&&l.showEmptyGroups?gt.createElement(Jb,{ref:function(e){return x._subGroupRefs["subGroup_"+t]=e},key:x._getGroupKey(e,t),dragDropEvents:n,dragDropHelper:r,eventsToRegister:i,footerProps:p,getGroupItemLimit:s,group:e,groupIndex:t,groupNestingDepth:a,groupProps:l,headerProps:u,items:c,listProps:h,onRenderCell:m,selection:g,selectionMode:f,showAllProps:d,viewport:v,onRenderGroupHeader:b,onRenderGroupShowAll:y,onRenderGroupFooter:C,onShouldVirtualize:_,groups:S?S.children:[],compact:o}):null},x._getGroupDragDropOptions=function(){var e=x.props,t=e.group,o=e.groupIndex,n=e.dragDropEvents;return{eventMap:e.eventsToRegister,selectionIndex:-1,context:{data:t,index:o,isGroup:!0},updateDropState:x._updateDroppingState,canDrag:n.canDrag,canDrop:n.canDrop,onDrop:n.onDrop,onDragStart:n.onDragStart,onDragEnter:n.onDragEnter,onDragLeave:n.onDragLeave,onDragEnd:n.onDragEnd,onDragOver:n.onDragOver}},x._updateDroppingState=function(e,t){var o=x.state.isDropping,n=x.props,r=n.dragDropEvents,n=n.group;o!==e&&(o?r&&r.onDragLeave&&r.onDragLeave(n,t):r&&r.onDragEnter&&(x._droppingClassName=r.onDragEnter(n,t)),x.setState({isDropping:e}))};var t=e.selection,e=e.group;return fi(x),x._id=_s("GroupedListSection"),x.state={isDropping:!1,isSelected:!(!t\|\|!e)&&t.isRangeSelected(e.startIndex,e.count)},x._events=new va(x),x}function $b(e){var r=Tb.call(this,e)\|\|this;return r._toggleCollapse=function(){var e=r.props,t=e.group,o=e.onToggleCollapse,n=e.isGroupLoading,e=!r.state.isCollapsed,n=!e&&n&&n(t);r.setState({isCollapsed:e,isLoadingVisible:n}),o&&o(t)},r._onKeyUp=function(e){var t=r.props,o=t.group,t=t.onGroupHeaderKeyUp;t&&t(e,o),e.defaultPrevented\|\|(o=r.state.isCollapsed&&e.which===Mn(En.right,r.props.theme),(!r.state.isCollapsed&&e.which===Mn(En.left,r.props.theme)\|\|o)&&(r._toggleCollapse(),e.stopPropagation(),e.preventDefault()))},r._onToggleClick=function(e){r._toggleCollapse(),e.stopPropagation(),e.preventDefault()},r._onToggleSelectGroupClick=function(e){var t=r.props,o=t.onToggleSelectGroup,t=t.group;o&&o(t),e.preventDefault(),e.stopPropagation()},r._onHeaderClick=function(){var e=r.props,t=e.group,o=e.onGroupHeaderClick,e=e.onToggleSelectGroup;o?o(t):e&&e(t)},r._onRenderTitle=function(e){var t=e.group,e=e.ariaColSpan;return t?gt.createElement("div",{className:r._classNames.title,id:r._id,role:"gridcell","aria-colspan":e},gt.createElement("span",null,t.name),gt.createElement("span",{className:r._classNames.headerCount},"(",t.count,t.hasMoreData&&"+",")")):null},r._id=_s("GroupHeader"),r.state={isCollapsed:r.props.group&&r.props.group.isCollapsed,isLoadingVisible:!1},r}function e0(){return null!==Pb&&Pb.apply(this,arguments)\|\|this}function t0(e){var t;return e&&(e===window?t={left:0,top:0,width:window.innerWidth,height:window.innerHeight,right:window.innerWidth,bottom:window.innerHeight}:e.getBoundingClientRect&&(t=e.getBoundingClientRect())),t}function o0(t){return l(e,o=du),e.prototype.componentDidMount=function(){var e=this,t=this.props,o=t.delayFirstMeasure,n=t.disableResizeObserver,r=t.skipViewportMeasures,t=qe(this._root.current);this._onAsyncResize=this._async.debounce(this._onAsyncResize,500,{leading:!1}),r\|\|(!n&&this._isResizeObserverAvailable()?this._registerResizeObserver():this._events.on(t,"resize",this._onAsyncResize),o?this._async.setTimeout(function(){e._updateViewport()},500):this._updateViewport())},e.prototype.componentDidUpdate=function(e){var t=e.skipViewportMeasures,o=this.props,n=o.disableResizeObserver,e=o.skipViewportMeasures,o=qe(this._root.current);e!==t&&(e?(this._unregisterResizeObserver(),this._events.off(o,"resize",this._onAsyncResize)):(!n&&this._isResizeObserverAvailable()?this._viewportResizeObserver\|\|this._registerResizeObserver():this._events.on(o,"resize",this._onAsyncResize),this._updateViewport()))},e.prototype.componentWillUnmount=function(){this._events.dispose(),this._async.dispose(),this._unregisterResizeObserver()},e.prototype.render=function(){var e=this.state.viewport,e=0<e.width&&0<e.height?e:void 0;return gt.createElement("div",{className:"ms-Viewport",ref:this._root,style:{minWidth:1,minHeight:1}},gt.createElement(t,ht({ref:this._updateComposedComponentRef,viewport:e},this.props)))},e.prototype.forceUpdate=function(){this._updateViewport(!0)},e.prototype._onAsyncResize=function(){this._updateViewport()},e.prototype._isResizeObserverAvailable=function(){var e=qe(this._root.current);return e&&e.ResizeObserver},e;function e(e){var r=o.call(this,e)\|\|this;return r._root=gt.createRef(),r._registerResizeObserver=function(){var e=qe(r._root.current);r._viewportResizeObserver=new e.ResizeObserver(r._onAsyncResize),r._viewportResizeObserver.observe(r._root.current)},r._unregisterResizeObserver=function(){r._viewportResizeObserver&&(r._viewportResizeObserver.disconnect(),delete r._viewportResizeObserver)},r._updateViewport=function(e){var t=r.state.viewport,o=r._root.current,n=t0(Ns(o)),o=t0(o);((o&&o.width)!==t.width\|\|(n&&n.height)!==t.height)&&r._resizeAttempts<3&&o&&n?(r._resizeAttempts++,r.setState({viewport:{width:o.width,height:n.height}},function(){r._updateViewport(e)})):(r._resizeAttempts=0,e&&r._composedComponentInstance&&r._composedComponentInstance.forceUpdate())},r._async=new Si(r),r._events=new va(r),r._resizeAttempts=0,r.state={viewport:{width:0,height:0}},r}var o}function n0(i){var s,a=i.selection,e=i.ariaLabelForListHeader,t=i.ariaLabelForSelectAllCheckbox,o=i.ariaLabelForSelectionColumn,n=i.className,l=i.checkboxVisibility,c=i.compact,r=i.constrainMode,u=i.dragDropEvents,d=i.groups,p=i.groupProps,h=i.indentWidth,m=i.items,g=i.isPlaceholderData,f=i.isHeaderVisible,v=i.layoutMode,b=i.onItemInvoked,y=i.onItemContextMenu,C=i.onColumnHeaderClick,_=i.onColumnHeaderContextMenu,S=void 0===(We=i.selectionMode)?a.mode:We,x=i.selectionPreservedOnEmptyClick,k=i.selectionZoneProps,w=i.ariaLabel,I=i.ariaLabelForGrid,D=i.rowElementEventMap,E=void 0!==(Ve=i.shouldApplyApplicationRole)&&Ve,T=i.getKey,P=i.listProps,R=i.usePageCache,M=i.onShouldVirtualize,N=i.viewport,B=i.minimumPixelsForDrag,F=i.getGroupHeight,A=i.styles,L=i.theme,H=void 0===(qe=i.cellStyleProps)?Lv:qe,O=i.onRenderCheckbox,z=i.useFastIcons,W=i.dragDropHelper,V=i.adjustedColumns,K=i.isCollapsed,G=i.isSizing,U=i.isSomeGroupExpanded,j=i.version,q=i.rootRef,Y=i.listRef,Z=i.focusZoneRef,X=i.columnReorderOptions,Q=i.groupedListRef,J=i.headerRef,$=i.onGroupExpandStateChanged,ee=i.onColumnIsSizingChanged,te=i.onRowDidMount,oe=i.onRowWillUnmount,ne=i.disableSelectionZone,re=i.onColumnResized,ie=i.onColumnAutoResized,se=i.onToggleCollapse,ae=i.onActiveRowChanged,le=i.onBlur,ce=i.rowElementEventMap,ue=i.onRenderMissingItem,de=i.onRenderItemColumn,pe=i.getCellValueKey,he=i.getRowAriaLabel,me=i.getRowAriaDescribedBy,ge=i.checkButtonAriaLabel,fe=i.checkButtonGroupAriaLabel,ve=i.checkboxCellClassName,be=i.useReducedRowRenderer,ye=i.enableUpdateAnimations,Ce=i.enterModalSelectionOnTouch,_e=i.onRenderDefaultRow,Se=i.selectionZoneRef,xe=i.focusZoneProps,ke=i.role\|\|"grid",we=_s("row"),Ie=function(){for(var e=0,t=d;t&&0<t.length;)e++,t=t[0].children;return e}(),De=(s=d,gt.useMemo(function(){var e={};if(s)for(var t=1,o=1,n=0,r=s;n<r.length;n++){var i=r[n];e[i.key]={numOfGroupHeadersBeforeItem:o,totalRowCount:t},o++,t+=i.count+1}return e},[s])),Ee=gt.useMemo(function(){return ht({renderedWindowsAhead:G?0:2,renderedWindowsBehind:G?0:2,getKey:T,version:j},P)},[G,T,j,P]),Te=Yv.none;S===dv.single&&(Te=Yv.hidden),S===dv.multiple&&(Te=(Je=void 0===(Je=p&&p.headerProps&&p.headerProps.isCollapsedGroupSelectVisible)?!0:Je)\|\|!d\|\|U?Yv.visible:Yv.hidden),l===kv.hidden&&(Te=Yv.none);var Pe=gt.useCallback(function(e){return gt.createElement(mb,ht({},e))},[]),Re=gt.useCallback(function(){return null},[]),Me=i.onRenderDetailsHeader,Ne=gt.useMemo(function(){return Me?Ma(Me,Pe):Pe},[Me,Pe]),Be=i.onRenderDetailsFooter,Fe=gt.useMemo(function(){return 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gt.createElement("div",ht({ref:q,className:Ve.root,"data-automationid":"DetailsList","data-is-scrollable":"false","aria-label":w},E?{role:"application"}:{}),gt.createElement(na,null),gt.createElement("div",{role:ke,"aria-label":I,"aria-rowcount":g?-1:ze,"aria-colcount":We,"aria-readonly":"true","aria-busy":g},gt.createElement("div",{onKeyDown:M,role:"presentation",className:Ve.headerWrapper},f&&Ne({componentRef:J,selectionMode:S,layoutMode:v,selection:a,columns:V,onColumnClick:C,onColumnContextMenu:_,onColumnResized:re,onColumnIsSizingChanged:ee,onColumnAutoResized:ie,groupNestingDepth:Ie,isAllCollapsed:K,onToggleCollapseAll:se,ariaLabel:e,ariaLabelForSelectAllCheckbox:t,ariaLabelForSelectionColumn:o,selectAllVisibility:Te,collapseAllVisibility:p&&p.collapseAllVisibility,viewport:N,columnReorderProps:Oe,minimumPixelsForDrag:B,cellStyleProps:H,checkboxVisibility:l,indentWidth:h,onRenderDetailsCheckbox:O,rowWidth:Ye(V),useFastIcons:z},Ne)),gt.createElement("div",{onKeyDown:Ee,role:"presentation",className:Ve.contentWrapper},ne?R:gt.createElement(Pv,ht({ref:Se,selection:a,selectionPreservedOnEmptyClick:x,selectionMode:S,onItemInvoked:b,onItemContextMenu:y,enterModalOnTouch:Ce},k\|\|{}),R)),Fe(ht({},Ae))))}var r0,i0=Fn(),s0=100,a0=(l(l0,r0=gt.Component),l0.getDerivedStateFromProps=function(e,t){return t.getDerivedStateFromProps(e,t)},l0.prototype.scrollToIndex=function(e,t,o){this._list.current&&this._list.current.scrollToIndex(e,t,o),this._groupedList.current&&this._groupedList.current.scrollToIndex(e,t,o)},l0.prototype.focusIndex=function(e,t,o,n){void 0===t&&(t=!1);var r=this.props.items[e];r&&(this.scrollToIndex(e,o,n),e=this._getItemKey(r,e),(e=this._activeRows[e])&&this._setFocusToRow(e,t))},l0.prototype.getStartItemIndexInView=function(){return this._list&&this._list.current?this._list.current.getStartItemIndexInView():this._groupedList&&this._groupedList.current?this._groupedList.current.getStartItemIndexInView():0},l0.prototype.updateColumn=function(t,e){var o=this.props,n=o.columns,r=void 0===n?[]:n,i=o.selectionMode,s=o.checkboxVisibility,a=o.columnReorderOptions,n=e.width,o=e.newColumnIndex,e=r.findIndex(function(e){return e.key===t.key});n&&this._onColumnResized(t,n,e),void 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0!==this._initialFocusedIndex&&(n=this.props.items[this._initialFocusedIndex])&&(r=this._getItemKey(n,this._initialFocusedIndex),(o=this._activeRows[r])&&this._setFocusToRowIfPending(o)),this.props.items!==e.items&&0<this.props.items.length&&-1!==this.state.focusedItemIndex&&!$i(this._root.current,document.activeElement,!1)&&(e=this.state.focusedItemIndex<this.props.items.length?this.state.focusedItemIndex:this.props.items.length-1,n=this.props.items[e],r=this._getItemKey(n,this.state.focusedItemIndex),(o=this._activeRows[r])?this._setFocusToRow(o):this._initialFocusedIndex=e),this.props.onDidUpdate&&this.props.onDidUpdate(this)},l0.prototype.render=function(){return gt.createElement(n0,ht({},this.props,this.state,{selection:this._selection,dragDropHelper:this._dragDropHelper,rootRef:this._root,listRef:this._list,groupedListRef:this._groupedList,focusZoneRef:this._focusZone,headerRef:this._header,selectionZoneRef:this._selectionZone,onGroupExpandStateChanged:this._onGroupExpandStateChanged,onColumnIsSizingChanged:this._onColumnIsSizingChanged,onRowDidMount:this._onRowDidMount,onRowWillUnmount:this._onRowWillUnmount,onColumnResized:this._onColumnResized,onColumnAutoResized:this._onColumnAutoResized,onToggleCollapse:this._onToggleCollapse,onActiveRowChanged:this._onActiveRowChanged,onBlur:this._onBlur,onRenderDefaultRow:this._onRenderRow}))},l0.prototype.forceUpdate=function(){r0.prototype.forceUpdate.call(this),this._forceListUpdates()},l0.prototype._getGroupNestingDepth=function(){for(var e=0,t=this.props.groups;t&&0<t.length;)e++,t=t[0].children;return e},l0.prototype._setFocusToRowIfPending=function(e){var t=e.props.itemIndex;void 0!==this._initialFocusedIndex&&t===this._initialFocusedIndex&&(this._setFocusToRow(e),delete this._initialFocusedIndex)},l0.prototype._setFocusToRow=function(e,t){void 0===t&&(t=!1),this._selectionZone.current&&this._selectionZone.current.ignoreNextFocus(),this._async.setTimeout(function(){e.focus(t)},0)},l0.prototype._forceListUpdates=function(){this._groupedList.current&&this._groupedList.current.forceUpdate(),this._list.current&&this._list.current.forceUpdate()},l0.prototype._notifyColumnsResized=function(){this.state.adjustedColumns.forEach(function(e){e.onColumnResize&&e.onColumnResize(e.currentWidth)})},l0.prototype._adjustColumns=function(e,t,o,n){o=this._getAdjustedColumns(e,t,o,n),n=this.props.viewport,n=n&&n.width?n.width:0;return ht(ht({},t),{adjustedColumns:o,lastWidth:n})},l0.prototype._getAdjustedColumns=function(e,t,o,n){var r,i=this,s=e.items,a=e.layoutMode,l=e.selectionMode,c=e.viewport,u=c&&c.width?c.width:0,d=e.columns,p=this.props?this.props.columns:[],c=t?t.lastWidth:-1,t=t?t.lastSelectionMode:void 0;return o\|\|c!==u\|\|t!==l\|\|p&&d!==p?(d=d\|\|c0(s,!0),a===xv.fixedColumns?(r=this._getFixedColumns(d,u,e)).forEach(function(e){i._rememberCalculatedWidth(e,e.calculatedWidth)}):(r=this._getJustifiedColumns(d,u,e)).forEach(function(e){i._getColumnOverride(e.key).currentWidth=e.calculatedWidth}),r):d\|\|[]},l0.prototype._getFixedColumns=function(e,t,o){var n=this,r=this.props,i=r.selectionMode,s=void 0===i?this._selection.mode:i,a=r.checkboxVisibility,i=r.flexMargin,l=r.skipViewportMeasures,c=t-(i\|\|0),u=0;e.forEach(function(e){l\|\|!e.flexGrow?c-=e.maxWidth\|\|e.minWidth\|\|s0:(c-=e.minWidth\|\|s0,u+=e.flexGrow),c-=u0(e,o,!0)});var s=s!==dv.none&&a!==kv.hidden?48:0,a=36this._getGroupNestingDepth(),d=(c-=s+a)/u;return l\|\|e.forEach(function(e){var t,o=ht(ht({},e),n._columnOverrides[e.key]);o.flexGrow&&o.maxWidth&&(0<(e=(t=o.flexGrowd+o.minWidth)-o.maxWidth)&&(c+=e,u-=e/(t-o.minWidth)o.flexGrow))}),d=0<c?c/u:0,e.map(function(e){e=ht(ht({},e),n._columnOverrides[e.key]);return!l&&e.flexGrow&&c<=0\|\|e.calculatedWidth\|\|(!l&&e.flexGrow?(e.calculatedWidth=e.minWidth+e.flexGrowd,e.calculatedWidth=Math.min(e.calculatedWidth,e.maxWidth\|\|Number.MAX_VALUE)):e.calculatedWidth=e.maxWidth\|\|e.minWidth\|\|s0),e})},l0.prototype._getJustifiedColumns=function(e,t,n){var r=this,o=n.selectionMode,i=void 0===o?this._selection.mode:o,o=n.checkboxVisibility,i=i!==dv.none&&o!==kv.hidden?48:0,o=36this._getGroupNestingDepth(),s=0,a=0,l=t-(i+o),c=e.map(function(e,t){var o=ht(ht({},e),{calculatedWidth:e.minWidth\|\|s0}),e=ht(ht({},o),r._columnOverrides[e.key]);return o.isCollapsible\|\|o.isCollapsable\|\|(a+=u0(o,n)),s+=u0(e,n),e});if(l<a)return c;for(var u=c.length-1;0<=u&&l<s;){var d,p=(f=c[u]).minWidth\|\|s0,h=s-l;f.calculatedWidth-p>=h\|\|!f.isCollapsible&&!f.isCollapsable?(d=f.calculatedWidth,f.calculatedWidth=Math.max(f.calculatedWidth-h,p),s-=d-f.calculatedWidth):(s-=u0(f,n),c.splice(u,1)),u--}for(var m=0;m<c.length&&s<l;m++){var g,f=c[m],v=m===c.length-1,b=this._columnOverrides[f.key];b&&b.calculatedWidth&&!v\|\|(g=l-s,b=void 0,b=v?g:(v=f.maxWidth,p=f.minWidth\|\|v\|\|s0,v?Math.min(g,v-p):g),f.calculatedWidth=f.calculatedWidth+b,s+=b)}return c},l0.prototype._rememberCalculatedWidth=function(e,t){e=this._getColumnOverride(e.key);e.calculatedWidth=t,e.currentWidth=t},l0.prototype._getColumnOverride=function(e){return this._columnOverrides[e]=this._columnOverrides[e]\|\|{}},l0.prototype._getItemKey=function(e,t){var o=this.props.getKey,n=void 0;return e&&(n=e.key),n=(n=o?o(e,t):n)\|\|t},l0.defaultProps={layoutMode:xv.justified,selectionMode:dv.multiple,constrainMode:_v.horizontalConstrained,checkboxVisibility:kv.onHover,isHeaderVisible:!0,compact:!1,useFastIcons:!0},c([o0],l0));function l0(e){var h=r0.call(this,e)\|\|this;return h._root=gt.createRef(),h._header=gt.createRef(),h._groupedList=gt.createRef(),h._list=gt.createRef(),h._focusZone=gt.createRef(),h._selectionZone=gt.createRef(),h._onRenderRow=function(e,t){return gt.createElement(xb,ht({},e))},h._getDerivedStateFromProps=function(e,t){var o=h.props,n=o.checkboxVisibility,r=o.items,i=o.setKey,s=o.selectionMode,a=void 0===s?h._selection.mode:s,l=o.columns,c=o.viewport,u=o.compact,d=o.dragDropEvents,p=(h.props.groupProps\|\|{}).isAllGroupsCollapsed,s=void 0===p?void 0:p,o=e.viewport&&e.viewport.width\|\|0,p=c&&c.width\|\|0,c=e.setKey!==i\|\|void 0===e.setKey,i=!1;e.layoutMode!==h.props.layoutMode&&(i=!0);return c&&(h._initialFocusedIndex=e.initialFocusedIndex,t=ht(ht({},t),{focusedItemIndex:void 0!==h._initialFocusedIndex?h._initialFocusedIndex:-1})),h.props.disableSelectionZone\|\|e.items===r\|\|h._selection.setItems(e.items,c),e.checkboxVisibility===n&&e.columns===l&&o===p&&e.compact===u\|\|(i=!0),t=ht(ht({},t),h._adjustColumns(e,t,!0)),e.selectionMode!==a&&(i=!0),void 0===s&&e.groupProps&&void 0!==e.groupProps.isAllGroupsCollapsed&&(t=ht(ht({},t),{isCollapsed:e.groupProps.isAllGroupsCollapsed,isSomeGroupExpanded:!e.groupProps.isAllGroupsCollapsed})),e.dragDropEvents!==d&&(h._dragDropHelper&&h._dragDropHelper.dispose(),h._dragDropHelper=e.dragDropEvents?new Qv({selection:h._selection,minimumPixelsForDrag:e.minimumPixelsForDrag}):void 0,i=!0),t=i?ht(ht({},t),{version:{}}):t},h._onGroupExpandStateChanged=function(e){h.setState({isSomeGroupExpanded:e})},h._onColumnIsSizingChanged=function(e,t){h.setState({isSizing:t})},h._onRowDidMount=function(e){var t=e.props,o=t.item,n=t.itemIndex,t=h._getItemKey(o,n);h._activeRows[t]=e,h._setFocusToRowIfPending(e);e=h.props.onRowDidMount;e&&e(o,n)},h._onRowWillUnmount=function(e){var t=h.props.onRowWillUnmount,o=e.props,n=o.item,e=o.itemIndex,o=h._getItemKey(n,e);delete h._activeRows[o],t&&t(n,e)},h._onToggleCollapse=function(e){h.setState({isCollapsed:e}),h._groupedList.current&&h._groupedList.current.toggleCollapseAll(e)},h._onColumnResized=function(e,t,o){t=Math.max(e.minWidth\|\|s0,t);h.props.onColumnResize&&h.props.onColumnResize(e,t,o),h._rememberCalculatedWidth(e,t),h.setState(ht(ht({},h._adjustColumns(h.props,h.state,!0,o)),{version:{}}))},h._onColumnAutoResized=function(t,o){var e,n=0,r=0,i=Object.keys(h._activeRows).length;for(e in h._activeRows)h._activeRows.hasOwnProperty(e)&&h._activeRows[e].measureCell(o,function(e){n=Math.max(n,e),++r===i&&h._onColumnResized(t,n,o)})},h._onActiveRowChanged=function(e,t){var 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c,u=e[0];for(c in u)u.hasOwnProperty(c)&&l.push({key:c,name:c,fieldName:c,minWidth:s0,maxWidth:300,isCollapsable:!!l.length,isCollapsible:!!l.length,isMultiline:void 0!==s&&s,isSorted:n===c,isSortedDescending:!!r,isRowHeader:!1,columnActionsMode:null!=a?a:Cv.clickable,isResizable:t,onColumnClick:o,isGrouped:i===c})}return l}function u0(e,t,o){t=t.cellStyleProps,t=void 0===t?Lv:t;return(o?0:e.calculatedWidth)+t.cellLeftPadding+t.cellRightPadding+(e.isPadded?t.cellExtraRightPadding:0)}var d0,p0={root:"ms-DetailsList",compact:"ms-DetailsList--Compact",contentWrapper:"ms-DetailsList-contentWrapper",headerWrapper:"ms-DetailsList-headerWrapper",isFixed:"is-fixed",isHorizontalConstrained:"is-horizontalConstrained",listCell:"ms-List-cell"},h0=In(a0,function(e){var t=e.theme,o=e.className,n=e.isHorizontalConstrained,r=e.compact,i=e.isFixed,s=t.semanticColors,e=zo(p0,t);return{root:[e.root,t.fonts.small,{position:"relative",color:s.listText,selectors:((s={})["& 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t,o;r.props.handleSelector&&!r._matchesSelector(e.target,r.props.handleSelector)\|\|r.props.preventDragSelector&&r._matchesSelector(e.target,r.props.preventDragSelector)\|\|(r._touchId=r._getTouchId(e),void 0!==(t=r._getControlPosition(e))&&(o=r._createDragDataFromPosition(t),r.props.onStart&&r.props.onStart(e,o),r.setState({isDragging:!0,lastPosition:t}),r._events=[Wa(document.body,r._currentEventType.move,r._onDrag,!0),Wa(document.body,r._currentEventType.stop,r._onDragStop,!0)]))},r._onDrag=function(e){"touchmove"===e.type&&e.preventDefault();var t,o,n=r._getControlPosition(e);n&&(o=(t=r._createUpdatedDragData(r._createDragDataFromPosition(n))).position,r.props.onDragChange&&r.props.onDragChange(e,t),r.setState({position:o,lastPosition:n}))},r._onDragStop=function(e){var t;!r.state.isDragging\|\|(t=r._getControlPosition(e))&&(t=r._createDragDataFromPosition(t),r.setState({isDragging:!1,lastPosition:void 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t=e.className,o=e.containerClassName,n=e.scrollableContentClassName,r=e.isOpen,i=e.isVisible,s=e.hasBeenOpened,a=e.modalRectangleTop,l=e.theme,c=e.topOffsetFixed,u=e.isModeless,d=e.layerClassName,p=e.isDefaultDragHandle,h=e.windowInnerHeight,m=l.palette,g=l.effects,e=l.fonts,l=zo(v0,l);return{root:[l.root,e.medium,{backgroundColor:"transparent",position:u?"absolute":"fixed",height:"100%",width:"100%",display:"flex",alignItems:"center",justifyContent:"center",opacity:0,pointerEvents:"none",transition:"opacity "+f0},c&&"number"==typeof a&&s&&{alignItems:"flex-start"},r&&l.isOpen,i&&{opacity:1,pointerEvents:"auto"},t],main:[l.main,{boxShadow:g.elevation64,borderRadius:g.roundedCorner2,backgroundColor:m.white,boxSizing:"border-box",position:"relative",textAlign:"left",outline:"3px solid transparent",maxHeight:"calc(100% - 32px)",maxWidth:"calc(100% - 32px)",minHeight:"176px",minWidth:"288px",overflowY:"auto",zIndex:u?mo.Layer:void 0},c&&"number"==typeof 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gt.Children.map(this.props.children,function(e){return e?gt.createElement("span",{className:t._classNames.action},e):null})},ty),z0={actions:"ms-Dialog-actions",action:"ms-Dialog-action",actionsRight:"ms-Dialog-actionsRight"},W0=In(O0,function(e){var t=e.className,e=e.theme,e=zo(z0,e);return{actions:[e.actions,{position:"relative",width:"100%",minHeight:"24px",lineHeight:"24px",margin:"16px 0 0",fontSize:"0",selectors:{".ms-Button":{lineHeight:"normal"}}},t],action:[e.action,{margin:"0 4px"}],actionsRight:[e.actionsRight,{textAlign:"right",marginRight:"-4px",fontSize:"0"}]}},void 0,{scope:"DialogFooter"}),V0=Fn(),K0=gt.createElement(W0,null).type,G0=(l(ey,A0=gt.Component),ey.prototype.render=function(){var e,t=this.props,o=t.showCloseButton,n=t.className,r=t.closeButtonAriaLabel,i=t.onDismiss,s=t.subTextId,a=t.subText,l=t.titleProps,c=void 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gt.Children.map(this.props.children,function(e){("object"==typeof e&&null!==e&&e.type===K0?t.footers:t.contents).push(e)}),t},ey.defaultProps={showCloseButton:!1,className:"",topButtonsProps:[],closeButtonAriaLabel:"Close"},c([Cu],ey)),U0={contentLgHeader:"ms-Dialog-lgHeader",close:"ms-Dialog--close",subText:"ms-Dialog-subText",header:"ms-Dialog-header",headerLg:"ms-Dialog--lgHeader",button:"ms-Dialog-button ms-Dialog-button--close",inner:"ms-Dialog-inner",content:"ms-Dialog-content",title:"ms-Dialog-title"},j0=In(G0,function(e){var t=e.className,o=e.theme,n=e.isLargeHeader,r=e.isClose,i=e.hidden,s=e.isMultiline,a=e.draggableHeaderClassName,l=o.palette,c=o.fonts,u=o.effects,e=o.semanticColors,o=zo(U0,o);return{content:[n&&[o.contentLgHeader,{borderTop:"4px solid "+l.themePrimary}],r&&o.close,{flexGrow:1,overflowY:"hidden"},t],subText:[o.subText,c.medium,{margin:"0 0 24px 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r._rootElement=gt.createRef(),r._onClick=function(e){r._onAction(e)},r._onKeyDown=function(e){e.which!==En.enter&&e.which!==En.space\|\|r._onAction(e)},r._onAction=function(e){var t=r.props,o=t.onClick,n=t.onClickHref,t=t.onClickTarget;o?o(e):!o&&n&&(t?window.open(n,t,"noreferrer noopener nofollow"):window.location.href=n,e.preventDefault(),e.stopPropagation())},fi(r),r}(xe=oy=oy\|\|{})[xe.smallFluid=0]="smallFluid",xe[xe.smallFixedFar=1]="smallFixedFar",xe[xe.smallFixedNear=2]="smallFixedNear",xe[xe.medium=3]="medium",xe[xe.large=4]="large",xe[xe.largeFixed=5]="largeFixed",xe[xe.extraLarge=6]="extraLarge",xe[xe.custom=7]="custom",xe[xe.customNear=8]="customNear";var nC,rC=Fn();(V=nC=nC\|\|{})[V.closed=0]="closed",V[V.animatingOpen=1]="animatingOpen",V[V.open=2]="open",V[V.animatingClosed=3]="animatingClosed";var iC,sC=(l(yC,iC=gt.Component),yC.getDerivedStateFromProps=function(e,t){return void 0===e.isOpen?null:!e.isOpen\|\|t.visibility!==nC.closed&&t.visibility!==nC.animatingClosed?e.isOpen\|\|t.visibility!==nC.open&&t.visibility!==nC.animatingOpen?null:{visibility:nC.animatingClosed}:{visibility:nC.animatingOpen}},yC.prototype.componentDidMount=function(){this._events.on(window,"resize",this._updateFooterPosition),this._shouldListenForOuterClick(this.props)&&this._events.on(document.body,"mousedown",this._dismissOnOuterClick,!0),this.props.isOpen&&this.setState({visibility:nC.animatingOpen})},yC.prototype.componentDidUpdate=function(e,t){var o=this._shouldListenForOuterClick(this.props),e=this._shouldListenForOuterClick(e);this.state.visibility!==t.visibility&&(this._clearExistingAnimationTimer(),this.state.visibility===nC.animatingOpen?this._animateTo(nC.open):this.state.visibility===nC.animatingClosed&&this._animateTo(nC.closed)),o&&!e?this._events.on(document.body,"mousedown",this._dismissOnOuterClick,!0):!o&&e&&this._events.off(document.body,"mousedown",this._dismissOnOuterClick,!0)},yC.prototype.componentWillUnmount=function(){this._async.dispose(),this._events.dispose()},yC.prototype.render=function(){var e=this.props,t=e.className,o=void 0===t?"":t,n=e.elementToFocusOnDismiss,r=e.firstFocusableSelector,i=e.focusTrapZoneProps,s=e.forceFocusInsideTrap,a=e.hasCloseButton,l=e.headerText,c=e.headerClassName,u=void 0===c?"":c,d=e.ignoreExternalFocusing,p=e.isBlocking,h=e.isFooterAtBottom,m=e.isLightDismiss,g=e.isHiddenOnDismiss,f=e.layerProps,v=e.overlayProps,b=e.popupProps,y=e.type,C=e.styles,_=e.theme,S=e.customWidth,x=e.onLightDismissClick,k=void 0===x?this._onPanelClick:x,w=e.onRenderNavigation,I=void 0===w?this._onRenderNavigation:w,D=e.onRenderHeader,E=void 0===D?this._onRenderHeader:D,T=e.onRenderBody,P=void 0===T?this._onRenderBody:T,t=e.onRenderFooter,c=void 0===t?this._onRenderFooter:t,x=this.state,w=x.isFooterSticky,D=x.visibility,T=x.id,e=y===oy.smallFixedNear\|\|y===oy.customNear,t=Pn(_)?e:!e,x=y===oy.custom\|\|y===oy.customNear?{width:S}:{},e=ur(this.props,cr),S=this.isActive,D=D===nC.animatingClosed\|\|D===nC.animatingOpen;if(this._headerTextId=l&&T+"-headerText",!S&&!D&&!g)return null;this._classNames=rC(C,{theme:_,className:o,focusTrapZoneClassName:i?i.className:void 0,hasCloseButton:a,headerClassName:u,isAnimating:D,isFooterSticky:w,isFooterAtBottom:h,isOnRightSide:t,isOpen:S,isHiddenOnDismiss:g,type:y,hasCustomNavigation:this._hasCustomNavigation});var R,t=this._classNames,y=this._allowTouchBodyScroll;return p&&S&&(R=gt.createElement(_0,ht({className:t.overlay,isDarkThemed:!1,onClick:m?k:void 0,allowTouchBodyScroll:y},v))),gt.createElement(sc,ht({},f),gt.createElement(Pl,ht({role:"dialog","aria-modal":p?"true":void 0,ariaLabelledBy:this._headerTextId\|\|void 0,onDismiss:this.dismiss,className:t.hiddenPanel},b),gt.createElement("div",ht({"aria-hidden":!S&&D},e,{ref:this._panel,className:t.root}),R,gt.createElement(Wh,ht({ignoreExternalFocusing:d,forceFocusInsideTrap:!(!p\|\|g&&!S)&&s,firstFocusableSelector:r,isClickableOutsideFocusTrap:!0},i,{className:t.main,style:x,elementToFocusOnDismiss:n}),gt.createElement("div",{className:t.contentInner},gt.createElement("div",{ref:this._allowScrollOnPanel,className:t.scrollableContent,"data-is-scrollable":!0},gt.createElement("div",{className:t.commands,"data-is-visible":!0},I(this.props,this._onRenderNavigation)),(this._hasCustomNavigation\|\|!a)&&E(this.props,this._onRenderHeader,this._headerTextId),P(this.props,this._onRenderBody),c(this.props,this._onRenderFooter)))))))},yC.prototype.open=function(){void 0===this.props.isOpen&&(this.isActive\|\|this.setState({visibility:nC.animatingOpen}))},yC.prototype.close=function(){void 0===this.props.isOpen&&this.isActive&&this.setState({visibility:nC.animatingClosed})},Object.defineProperty(yC.prototype,"isActive",{get:function(){return this.state.visibility===nC.open\|\|this.state.visibility===nC.animatingOpen},enumerable:!1,configurable:!0}),yC.prototype._shouldListenForOuterClick=function(e){return!!e.isBlocking&&!!e.isOpen},yC.prototype._updateFooterPosition=function(){var e,t=this._scrollableContent;t&&(e=t.clientHeight,t=t.scrollHeight,this.setState({isFooterSticky:e<t}))},yC.prototype._dismissOnOuterClick=function(e){var t=this._panel.current;this.isActive&&t&&!e.defaultPrevented&&($i(t,e.target)\|\|(this.props.onOuterClick?this.props.onOuterClick(e):this.dismiss(e)))},yC.defaultProps={isHiddenOnDismiss:!1,isOpen:void 0,isBlocking:!0,hasCloseButton:!0,type:oy.smallFixedFar},yC),aC={root:"ms-Panel",main:"ms-Panel-main",commands:"ms-Panel-commands",contentInner:"ms-Panel-contentInner",scrollableContent:"ms-Panel-scrollableContent",navigation:"ms-Panel-navigation",closeButton:"ms-Panel-closeButton ms-PanelAction-close",header:"ms-Panel-header",headerText:"ms-Panel-headerText",content:"ms-Panel-content",footer:"ms-Panel-footer",footerInner:"ms-Panel-footerInner",isOpen:"is-open",hasCloseButton:"ms-Panel--hasCloseButton",smallFluid:"ms-Panel--smFluid",smallFixedNear:"ms-Panel--smLeft",smallFixedFar:"ms-Panel--sm",medium:"ms-Panel--md",large:"ms-Panel--lg",largeFixed:"ms-Panel--fixed",extraLarge:"ms-Panel--xl",custom:"ms-Panel--custom",customNear:"ms-Panel--customLeft"},lC="auto",cC=((G={})["@media (min-width: "+$t+"px)"]={width:340},G),uC=((Y={})["@media (min-width: "+eo+"px)"]={width:592},Y["@media (min-width: "+to+"px)"]={width:644},Y),dC=((ke={})["@media (min-width: "+co+"px)"]={left:48,width:"auto"},ke["@media (min-width: "+oo+"px)"]={left:428},ke),pC=((K={})["@media (min-width: "+oo+"px)"]={left:lC,width:940},K),hC=((U={})["@media (min-width: "+oo+"px)"]={left:176},U),mC={paddingLeft:"24px",paddingRight:"24px"},gC=In(sC,function(e){var t,o=e.className,n=e.focusTrapZoneClassName,r=e.hasCloseButton,i=e.headerClassName,s=e.isAnimating,a=e.isFooterSticky,l=e.isFooterAtBottom,c=e.isOnRightSide,u=e.isOpen,d=e.isHiddenOnDismiss,p=e.hasCustomNavigation,h=e.theme,m=e.type,g=void 0===m?oy.smallFixedFar:m,f=h.effects,v=h.fonts,b=h.semanticColors,e=zo(aC,h),m=g===oy.custom\|\|g===oy.customNear;return{root:[e.root,h.fonts.medium,u&&e.isOpen,r&&e.hasCloseButton,{pointerEvents:"none",position:"absolute",top:0,left:0,right:0,bottom:0},m&&c&&e.custom,m&&!c&&e.customNear,o],overlay:[{pointerEvents:"auto",cursor:"pointer"},u&&s&&Le.fadeIn100,!u&&s&&Le.fadeOut100],hiddenPanel:[!u&&!s&&d&&{visibility:"hidden"}],main:[e.main,{backgroundColor:b.bodyBackground,boxShadow:f.elevation64,pointerEvents:"auto",position:"absolute",display:"flex",flexDirection:"column",overflowX:"hidden",overflowY:"auto",WebkitOverflowScrolling:"touch",bottom:0,top:0,left:lC,right:0,width:"100%",selectors:ht(((f={})[Yt]={borderLeft:"3px solid "+b.variantBorder,borderRight:"3px solid "+b.variantBorder},f),function(e){var t;switch(e){case oy.smallFixedFar:t=ht({},cC);break;case oy.medium:t=ht(ht({},cC),uC);break;case oy.large:t=ht(ht(ht({},cC),uC),dC);break;case oy.largeFixed:t=ht(ht(ht(ht({},cC),uC),dC),pC);break;case oy.extraLarge:t=ht(ht(ht(ht({},cC),uC),dC),hC)}return t}(g))},g===oy.smallFluid&&{left:0},g===oy.smallFixedNear&&{left:0,right:lC,width:272},g===oy.customNear&&{right:"auto",left:0},m&&{maxWidth:"100vw"},u&&s&&!c&&Le.slideRightIn40,u&&s&&c&&Le.slideLeftIn40,!u&&s&&!c&&Le.slideLeftOut40,!u&&s&&c&&Le.slideRightOut40,n],commands:[e.commands,{marginTop:18,background:"inherit",selectors:((n={})["@media (min-height: "+$t+"px)"]={position:"sticky",top:0,zIndex:1},n)},p&&{marginTop:"inherit"}],navigation:[e.navigation,{display:"flex",justifyContent:"flex-end"},p&&{height:"44px"}],contentInner:[e.contentInner,{display:"flex",flexDirection:"column",flexGrow:1,overflowY:"hidden",background:"inherit"}],header:[e.header,mC,{alignSelf:"flex-start"},r&&!p&&{flexGrow:1},p&&{flexShrink:0}],headerText:[e.headerText,v.xLarge,{color:b.bodyText,lineHeight:"27px",overflowWrap:"break-word",wordWrap:"break-word",wordBreak:"break-word",hyphens:"auto"},i],scrollableContent:[e.scrollableContent,{overflowY:"auto",background:"inherit"},l&&{flexGrow:1,display:"inherit",flexDirection:"inherit"}],content:[e.content,mC,{paddingBottom:20},l&&{selectors:((t={})["@media (min-height: "+$t+"px)"]={flexGrow:1},t)}],footer:[e.footer,{flexShrink:0,borderTop:"1px solid transparent",transition:"opacity "+we.durationValue3+" "+we.easeFunction2,selectors:((t={})["@media (min-height: "+$t+"px)"]={position:"sticky",bottom:0},t)},a&&{background:b.bodyBackground,borderTopColor:b.variantBorder}],footerInner:[e.footerInner,mC,{paddingBottom:16,paddingTop:16}],subComponentStyles:{closeButton:{root:[e.closeButton,{marginRight:14,color:h.palette.neutralSecondary,fontSize:Ae.large},p&&{marginRight:0,height:"auto",width:"44px"}],rootHovered:{color:h.palette.neutralPrimary}}}}},void 0,{scope:"Panel"}),fC=Fn(),vC={options:[]},bC=gt.forwardRef(function(e,t){var s,o,n,r,a,l,c,u,d,p,i=Hn(vC,e),h=gt.useRef(null),m=_r(t,h),g=Su(h,i.responsiveMode),h=(o=i.defaultSelectedKeys,n=i.selectedKeys,r=i.defaultSelectedKey,e=i.selectedKey,a=i.options,l=i.multiSelect,c=Hc(a),t=gt.useState([]),h=t[0],u=t[1],d=a!==c,p=Hc(s=l?d&&void 0!==o?o:n:d&&void 0!==r?r:e),gt.useEffect(function(){function i(t){return Hi(a,function(e){return null!=t?e.key===t:e.selected\|\|e.isSelected})}void 0===s&&c\|\|s===p&&!d\|\|u(function(){if(void 0===s)return l?a.map(function(e,t){return e.selected?t:-1}).filter(function(e){return-1!==e}):-1!==(n=i(null))?[n]:[];if(!Array.isArray(s))return-1!==(n=i(s))?[n]:[];for(var e=[],t=0,o=s;t<o.length;t++){var n,r=o[t];-1!==(n=i(r))&&e.push(n)}return e}())},[d,l,c,p,a,s]),[h,u]);return gt.createElement(_C,ht({},i,{responsiveMode:g,hoisted:{rootRef:m,selectedIndices:h[0],setSelectedIndices:h[1]}}))});function yC(e){var r=iC.call(this,e)\|\|this;r._panel=gt.createRef(),r._animationCallback=null,r._hasCustomNavigation=!(!r.props.onRenderNavigation&&!r.props.onRenderNavigationContent),r.dismiss=function(e){r.props.onDismiss&&r.isActive&&r.props.onDismiss(e),e&&e.defaultPrevented\|\|r.close()},r._allowScrollOnPanel=function(e){e?(r._allowTouchBodyScroll?Es:Ds)(e,r._events):r._events.off(r._scrollableContent),r._scrollableContent=e},r._onRenderNavigation=function(e){if(!r.props.onRenderNavigationContent&&!r.props.onRenderNavigation&&!r.props.hasCloseButton)return null;var t=r.props.onRenderNavigationContent,t=void 0===t?r._onRenderNavigationContent:t;return gt.createElement("div",{className:r._classNames.navigation},t(e,r._onRenderNavigationContent))},r._onRenderNavigationContent=function(e){var t=e.closeButtonAriaLabel,o=e.hasCloseButton,e=e.onRenderHeader,e=void 0===e?r._onRenderHeader:e;if(o){o=null===(o=r._classNames.subComponentStyles)\|\|void 0===o?void 0:o.closeButton();return gt.createElement(gt.Fragment,null,!r._hasCustomNavigation&&e(r.props,r._onRenderHeader,r._headerTextId),gt.createElement(rd,{styles:o,className:r._classNames.closeButton,onClick:r._onPanelClick,ariaLabel:t,title:t,"data-is-visible":!0,iconProps:{iconName:"Cancel"}}))}return null},r._onRenderHeader=function(e,t,o){var n=e.headerText,e=e.headerTextProps,e=void 0===e?{}:e;return n?gt.createElement("div",{className:r._classNames.header},gt.createElement("div",ht({id:o,role:"heading","aria-level":1},e,{className:Tr(r._classNames.headerText,e.className)}),n)):null},r._onRenderBody=function(e){return gt.createElement("div",{className:r._classNames.content},e.children)},r._onRenderFooter=function(e){var t=r.props.onRenderFooterContent,t=void 0===t?null:t;return t?gt.createElement("div",{className:r._classNames.footer},gt.createElement("div",{className:r._classNames.footerInner},t())):null},r._animateTo=function(e){e===nC.open&&r.props.onOpen&&r.props.onOpen(),r._animationCallback=r._async.setTimeout(function(){r.setState({visibility:e}),r._onTransitionComplete()},200)},r._clearExistingAnimationTimer=function(){null!==r._animationCallback&&r._async.clearTimeout(r._animationCallback)},r._onPanelClick=function(e){r.dismiss(e)},r._onTransitionComplete=function(){r._updateFooterPosition(),r.state.visibility===nC.open&&r.props.onOpened&&r.props.onOpened(),r.state.visibility===nC.closed&&r.props.onDismissed&&r.props.onDismissed()};e=r.props.allowTouchBodyScroll;return r._allowTouchBodyScroll=void 0!==e&&e,r._async=new Si(r),r._events=new va(r),fi(r),r.state={isFooterSticky:!1,visibility:nC.closed,id:_s("Panel")},r}bC.displayName="DropdownBase";var CC,_C=(l(DC,CC=gt.Component),Object.defineProperty(DC.prototype,"selectedOptions",{get:function(){var e=this.props;return _f(e.options,e.hoisted.selectedIndices)},enumerable:!1,configurable:!0}),DC.prototype.componentWillUnmount=function(){clearTimeout(this._scrollIdleTimeoutId)},DC.prototype.componentDidUpdate=function(e,t){!0===t.isOpen&&!1===this.state.isOpen&&(this._gotMouseMove=!1,this._hasBeenPositioned=!1,this.props.onDismiss&&this.props.onDismiss())},DC.prototype.render=function(){var e=this._id,t=this.props,o=t.className,n=t.label,r=t.options,i=t.ariaLabel,s=t.required,a=t.errorMessage,l=t.styles,c=t.theme,u=t.panelProps,d=t.calloutProps,p=t.onRenderTitle,h=void 0===p?this._getTitle:p,m=t.onRenderContainer,g=void 0===m?this._onRenderContainer:m,f=t.onRenderCaretDown,v=void 0===f?this._onRenderCaretDown:f,b=t.onRenderLabel,y=void 0===b?this._onRenderLabel:b,C=t.hoisted.selectedIndices,_=this.state,S=_.isOpen,x=_.calloutRenderEdge,p=_.hasFocus,m=t.onRenderPlaceholder\|\|t.onRenderPlaceHolder\|\|this._getPlaceholder;r!==this._sizePosCache.cachedOptions&&this._sizePosCache.updateOptions(r);f=_f(r,C),b=ur(t,cr),_=this._isDisabled(),r=e+"-errorMessage",C=!_&&S&&1===C.length&&0<=C[0]?this._listId+C[0]:void 0;this._classNames=fC(l,{theme:c,className:o,hasError:!!(a&&0<a.length),hasLabel:!!n,isOpen:S,required:s,disabled:_,isRenderingPlaceholder:!f.length,panelClassName:u?u.className:void 0,calloutClassName:d?d.className:void 0,calloutRenderEdge:x});x=!!a&&0<a.length;return gt.createElement("div",{className:this._classNames.root,ref:this.props.hoisted.rootRef,"aria-owns":S?this._listId:void 0},y(this.props,this._onRenderLabel),gt.createElement("div",ht({"data-is-focusable":!_,"data-ktp-target":!0,ref:this._dropDown,id:e,tabIndex:_?-1:0,role:"combobox","aria-haspopup":"listbox","aria-expanded":S?"true":"false","aria-label":i,"aria-labelledby":n&&!i?Ia(this._labelId,this._optionId):void 0,"aria-describedby":x?this._id+"-errorMessage":void 0,"aria-activedescendant":C,"aria-required":s,"aria-disabled":_,"aria-controls":S?this._listId:void 0},b,{className:this._classNames.dropdown,onBlur:this._onDropdownBlur,onKeyDown:this._onDropdownKeyDown,onKeyUp:this._onDropdownKeyUp,onClick:this._onDropdownClick,onMouseDown:this._onDropdownMouseDown,onFocus:this._onFocus}),gt.createElement("span",{id:this._optionId,className:this._classNames.title,"aria-live":p?"polite":void 0,"aria-atomic":!!p\|\|void 0,"aria-invalid":x},f.length?h(f,this._onRenderTitle):m(t,this._onRenderPlaceholder)),gt.createElement("span",{className:this._classNames.caretDownWrapper},v(t,this._onRenderCaretDown))),S&&g(ht(ht({},t),{onDismiss:this._onDismiss}),this._onRenderContainer),x&&gt.createElement("div",{role:"alert",id:r,className:this._classNames.errorMessage},a))},DC.prototype.focus=function(e){this._dropDown.current&&(this._dropDown.current.focus(),e&&this.setState({isOpen:!0}))},DC.prototype.setSelectedIndex=function(e,t){var o=this.props,n=o.options,r=o.selectedKey,i=o.selectedKeys,s=o.multiSelect,a=o.notifyOnReselect,l=o.hoisted.selectedIndices,c=void 0===l?[]:l,o=!!c&&-1<c.indexOf(t),l=[];t=Math.max(0,Math.min(n.length-1,t)),void 0===r&&void 0===i?(s\|\|a\|\|t!==c[0])&&(s?(l=c?this._copyArray(c):[],o?-1<(c=l.indexOf(t))&&l.splice(c,1):l.push(t)):l=[t],e.persist(),this.props.hoisted.setSelectedIndices(l),this._onChange(e,n,t,o,s)):this._onChange(e,n,t,o,s)},DC.prototype._copyArray=function(e){for(var t=[],o=0,n=e;o<n.length;o++){var r=n[o];t.push(r)}return t},DC.prototype._moveIndex=function(e,t,o,n){var r=this.props.options;if(n===o\|\|0===r.length)return n;o>=r.length?o=0:o<0&&(o=r.length-1);for(var i=0;r[o].itemType===cf.Header\|\|r[o].itemType===cf.Divider\|\|r[o].disabled;){if(i>=r.length)return n;o+t<0?o=r.length:o+t>=r.length&&(o=-1),o+=t,i++}return this.setSelectedIndex(e,o),o},DC.prototype._renderFocusableList=function(e){var t=e.onRenderList,o=void 0===t?this._onRenderList:t,n=e.label,r=e.ariaLabel,t=e.multiSelect;return gt.createElement("div",{className:this._classNames.dropdownItemsWrapper,onKeyDown:this._onZoneKeyDown,onKeyUp:this._onZoneKeyUp,ref:this._host,tabIndex:0},gt.createElement(Zs,{ref:this._focusZone,direction:Ei.vertical,id:this._listId,className:this._classNames.dropdownItems,role:"listbox","aria-label":r,"aria-labelledby":n&&!r?this._labelId:void 0,"aria-multiselectable":t},o(e,this._onRenderList)))},DC.prototype._renderSeparator=function(e){var t=e.index,e=e.key;return 0<t?gt.createElement("div",{role:"separator",key:e,className:this._classNames.dropdownDivider}):null},DC.prototype._renderHeader=function(e){var t=this.props.onRenderOption,o=void 0===t?this._onRenderOption:t,n=e.key,t=e.id;return gt.createElement("div",{id:t,key:n,className:this._classNames.dropdownItemHeader},o(e,this._onRenderOption))},DC.prototype._onItemMouseEnter=function(e,t){this._shouldIgnoreMouseEvent()\|\|t.currentTarget.focus()},DC.prototype._onItemMouseMove=function(e,t){t=t.currentTarget;this._gotMouseMove=!0,this._isScrollIdle&&document.activeElement!==t&&t.focus()},DC.prototype._shouldIgnoreMouseEvent=function(){return!this._isScrollIdle\|\|!this._gotMouseMove},DC.prototype._isAltOrMeta=function(e){return e.which===En.alt\|\|"Meta"===e.key},DC.prototype._shouldHandleKeyUp=function(e){e=this._lastKeyDownWasAltOrMeta&&this._isAltOrMeta(e);return this._lastKeyDownWasAltOrMeta=!1,!!e&&!(Na()\|\|Aa())},DC.prototype._shouldOpenOnFocus=function(){var e=this.state.hasFocus,t=this.props.openOnKeyboardFocus;return!this._isFocusedByClick&&!0===t&&!e},DC.defaultProps={options:[]},DC),SC={root:"ms-Dropdown-container",label:"ms-Dropdown-label",dropdown:"ms-Dropdown",title:"ms-Dropdown-title",caretDownWrapper:"ms-Dropdown-caretDownWrapper",caretDown:"ms-Dropdown-caretDown",callout:"ms-Dropdown-callout",panel:"ms-Dropdown-panel",dropdownItems:"ms-Dropdown-items",dropdownItem:"ms-Dropdown-item",dropdownDivider:"ms-Dropdown-divider",dropdownOptionText:"ms-Dropdown-optionText",dropdownItemHeader:"ms-Dropdown-header",titleIsPlaceHolder:"ms-Dropdown-titleIsPlaceHolder",titleHasError:"ms-Dropdown-title--hasError"},V=((xe={})[Yt+", "+Zt.replace("@media ","")]=ht({},{forcedColorAdjust:"none",MsHighContrastAdjust:"none"}),xe),xC={selectors:ht(((G={})[Yt]={backgroundColor:"Highlight",borderColor:"Highlight",color:"HighlightText"},G),V)},kC={selectors:((Y={})[Yt]={borderColor:"Highlight"},Y)},wC=uo(0,$t),IC=In(bC,function(e){var t=e.theme,o=e.hasError,n=e.hasLabel,r=e.className,i=e.isOpen,s=e.disabled,a=e.required,l=e.isRenderingPlaceholder,c=e.panelClassName,u=e.calloutClassName,d=e.calloutRenderEdge;if(!t)throw new Error("theme is undefined or null in base Dropdown getStyles function.");function p(e){return{selectors:((e={"&:hover:focus":[{color:g.menuItemTextHovered,backgroundColor:(e=void 0===e?!1:e)?S:g.menuItemBackgroundHovered},xC],"&:focus":[{backgroundColor:e?S:"transparent"},xC],"&:active":[{color:g.menuItemTextHovered,backgroundColor:e?g.menuItemBackgroundHovered:g.menuBackground},xC]})["."+go+" &:focus:after"]={left:0,top:0,bottom:0,right:0},e[Yt]={border:"none"},e)}}var h=zo(SC,t),m=t.palette,g=t.semanticColors,f=t.effects,v=t.fonts,b={color:g.menuItemTextHovered},y={color:g.menuItemText},C={borderColor:g.errorText},_=[h.dropdownItem,{backgroundColor:"transparent",boxSizing:"border-box",cursor:"pointer",display:"flex",alignItems:"center",padding:"0 8px",width:"100%",minHeight:36,lineHeight:20,height:0,position:"relative",border:"1px solid transparent",borderRadius:0,wordWrap:"break-word",overflowWrap:"break-word",textAlign:"left",".ms-Button-flexContainer":{width:"100%"}}],S=g.menuItemBackgroundPressed,x=$e($e([],_),[{backgroundColor:S,color:g.menuItemTextHovered},p(!0),xC]),k=$e($e([],_),[{color:g.disabledText,cursor:"default",selectors:((w={})[Yt]={color:"GrayText",border:"none"},w)}]),e=d===Ba.bottom?f.roundedCorner2+" "+f.roundedCorner2+" 0 0":"0 0 "+f.roundedCorner2+" "+f.roundedCorner2,w=d===Ba.bottom?"0 0 "+f.roundedCorner2+" "+f.roundedCorner2:f.roundedCorner2+" "+f.roundedCorner2+" 0 0";return{root:[h.root,r],label:h.label,dropdown:[h.dropdown,Uo,v.medium,{color:g.menuItemText,borderColor:g.focusBorder,position:"relative",outline:0,userSelect:"none",selectors:((d={})["&:hover ."+h.title]=[!s&&b,{borderColor:i?m.neutralSecondary:m.neutralPrimary},kC],d["&:focus ."+h.title]=[!s&&b,{selectors:((r={})[Yt]={color:"Highlight"},r)}],d["&:focus:after"]=[{pointerEvents:"none",content:"''",position:"absolute",boxSizing:"border-box",top:"0px",left:"0px",width:"100%",height:"100%",border:s?"none":"2px solid "+m.themePrimary,borderRadius:"2px",selectors:((r={})[Yt]={color:"Highlight"},r)}],d["&:active ."+h.title]=[!s&&b,{borderColor:m.themePrimary},kC],d["&:hover ."+h.caretDown]=!s&&y,d["&:focus ."+h.caretDown]=[!s&&y,{selectors:((b={})[Yt]={color:"Highlight"},b)}],d["&:active ."+h.caretDown]=!s&&y,d["&:hover ."+h.titleIsPlaceHolder]=!s&&y,d["&:focus ."+h.titleIsPlaceHolder]=!s&&y,d["&:active ."+h.titleIsPlaceHolder]=!s&&y,d["&:hover ."+h.titleHasError]=C,d["&:active ."+h.titleHasError]=C,d)},i&&"is-open",s&&"is-disabled",a&&"is-required",a&&!n&&{selectors:((n={":before":{content:"''",color:g.errorText,position:"absolute",top:-5,right:-10}})[Yt]={selectors:{":after":{right:-14}}},n)}],title:[h.title,Uo,{backgroundColor:g.inputBackground,borderWidth:1,borderStyle:"solid",borderColor:g.inputBorder,borderRadius:i?e:f.roundedCorner2,cursor:"pointer",display:"block",height:32,lineHeight:30,padding:"0 28px 0 8px",position:"relative",overflow:"hidden",whiteSpace:"nowrap",textOverflow:"ellipsis"},l&&[h.titleIsPlaceHolder,{color:g.inputPlaceholderText}],o&&[h.titleHasError,C],s&&{backgroundColor:g.disabledBackground,border:"none",color:g.disabledText,cursor:"default",selectors:((C={})[Yt]=ht({border:"1px solid GrayText",color:"GrayText",backgroundColor:"Window"},{forcedColorAdjust:"none",MsHighContrastAdjust:"none"}),C)}],caretDownWrapper:[h.caretDownWrapper,{height:32,lineHeight:30,paddingTop:1,position:"absolute",right:8,top:0},!s&&{cursor:"pointer"}],caretDown:[h.caretDown,{color:m.neutralSecondary,fontSize:v.small.fontSize,pointerEvents:"none"},s&&{color:g.disabledText,selectors:((s={})[Yt]=ht({color:"GrayText"},{forcedColorAdjust:"none",MsHighContrastAdjust:"none"}),s)}],errorMessage:ht(ht({color:g.errorText},t.fonts.small),{paddingTop:5}),callout:[h.callout,{boxShadow:f.elevation8,borderRadius:w,selectors:((f={})[".ms-Callout-main"]={borderRadius:w},f)},u],dropdownItemsWrapper:{selectors:{"&:focus":{outline:0}}},dropdownItems:[h.dropdownItems,{display:"block"}],dropdownItem:$e($e([],_),[p()]),dropdownItemSelected:x,dropdownItemDisabled:k,dropdownItemSelectedAndDisabled:[x,k,{backgroundColor:"transparent"}],dropdownItemHidden:$e($e([],_),[{display:"none"}]),dropdownDivider:[h.dropdownDivider,{height:1,backgroundColor:g.bodyDivider}],dropdownOptionText:[h.dropdownOptionText,{overflow:"hidden",whiteSpace:"nowrap",textOverflow:"ellipsis",minWidth:0,maxWidth:"100%",wordWrap:"break-word",overflowWrap:"break-word",margin:"1px"}],dropdownItemHeader:[h.dropdownItemHeader,ht(ht({},v.medium),{fontWeight:Fe.semibold,color:g.menuHeader,background:"none",backgroundColor:"transparent",border:"none",height:36,lineHeight:36,cursor:"default",padding:"0 8px",userSelect:"none",textAlign:"left",selectors:((v={})[Yt]=ht({color:"GrayText"},{forcedColorAdjust:"none",MsHighContrastAdjust:"none"}),v)})],subComponentStyles:{label:{root:{display:"inline-block"}},multiSelectItem:{root:{padding:0},label:{alignSelf:"stretch",padding:"0 8px",width:"100%"},input:{selectors:((v={})["."+go+" &:focus + label::before"]={outlineOffset:"0px"},v)}},panel:{root:[c],main:{selectors:((c={})[wC]={width:272},c)},contentInner:{padding:"0 0 20px"}}}}},void 0,{scope:"Dropdown"});function DC(e){var l=CC.call(this,e)\|\|this;l._host=gt.createRef(),l._focusZone=gt.createRef(),l._dropDown=gt.createRef(),l._scrollIdleDelay=250,l._sizePosCache=new Uy,l._requestAnimationFrame=Gy(l),l._onChange=function(e,t,o,n,r){var i=l.props,s=i.onChange,i=i.onChanged;(s\|\|i)&&(t=r?ht(ht({},t[o]),{selected:!n}):t[o],s&&s(ht(ht({},e),{target:l._dropDown.current}),t,o),i&&i(t,o))},l._getPlaceholder=function(){return l.props.placeholder\|\|l.props.placeHolder},l._getTitle=function(e,t){var o=l.props.multiSelectDelimiter,o=void 0===o?", ":o;return e.map(function(e){return e.text}).join(o)},l._onRenderTitle=function(e){return gt.createElement(gt.Fragment,null,l._getTitle(e))},l._onRenderPlaceholder=function(e){return l._getPlaceholder()?gt.createElement(gt.Fragment,null,l._getPlaceholder()):null},l._onRenderContainer=function(e){var t=e.calloutProps,o=e.panelProps,n=l.props,r=n.responsiveMode,i=n.dropdownWidth,s=r<=cu.medium,a=l._classNames.subComponentStyles?l._classNames.subComponentStyles.panel:void 0,n=void 0,r=void 0;return"auto"===i?r=l._dropDown.current?l._dropDown.current.clientWidth:0:n=i\|\|(l._dropDown.current?l._dropDown.current.clientWidth:0),s?gt.createElement(gC,ht({isOpen:!0,isLightDismiss:!0,onDismiss:l._onDismiss,hasCloseButton:!1,styles:a},o),l._renderFocusableList(e)):gt.createElement(ac,ht({isBeakVisible:!1,gapSpace:0,doNotLayer:!1,directionalHintFixed:!1,directionalHint:Pa.bottomLeftEdge,calloutWidth:n,calloutMinWidth:r},t,{className:l._classNames.callout,target:l._dropDown.current,onDismiss:l._onDismiss,onScroll:l._onScroll,onPositioned:l._onPositioned}),l._renderFocusableList(e))},l._onRenderCaretDown=function(e){return gt.createElement(Wr,{className:l._classNames.caretDown,iconName:"ChevronDown","aria-hidden":!0})},l._onRenderList=function(e){function n(){var e=i.id?[gt.createElement("div",{role:"group",key:i.id,"aria-labelledby":i.id},i.items)]:i.items;o=$e($e([],o),e),i={items:[]}}var t=e.onRenderItem,r=void 0===t?l._onRenderItem:t,i={items:[]},o=[];return e.options.forEach(function(e,t){!function(e,t){switch(e.itemType){case cf.Header:0<i.items.length&&n();var o=l._id+e.key;i.items.push(r(ht(ht({id:o},e),{index:t}),l._onRenderItem)),i.id=o;break;case cf.Divider:0<t&&i.items.push(r(ht(ht({},e),{index:t}),l._onRenderItem)),0<i.items.length&&n();break;default:i.items.push(r(ht(ht({},e),{index:t}),l._onRenderItem))}}(e,t)}),0<i.items.length&&n(),gt.createElement(gt.Fragment,null,o)},l._onRenderItem=function(e){switch(e.itemType){case cf.Divider:return l._renderSeparator(e);case cf.Header:return l._renderHeader(e);default:return l._renderOption(e)}},l._renderOption=function(e){var t=l.props,o=t.onRenderOption,n=void 0===o?l._onRenderOption:o,r=t.hoisted.selectedIndices,i=void 0===r?[]:r,o=!(void 0===e.index\|\|!i)&&-1<i.indexOf(e.index),t=e.hidden?l._classNames.dropdownItemHidden:o&&!0===e.disabled?l._classNames.dropdownItemSelectedAndDisabled:o?l._classNames.dropdownItemSelected:!0===e.disabled?l._classNames.dropdownItemDisabled:l._classNames.dropdownItem,r=e.title,i=l._classNames.subComponentStyles?l._classNames.subComponentStyles.multiSelectItem:void 0;return l.props.multiSelect?gt.createElement($h,{id:l._listId+e.index,key:e.key,disabled:e.disabled,onChange:l._onItemClick(e),inputProps:ht({"aria-selected":o,onMouseEnter:l._onItemMouseEnter.bind(l,e),onMouseLeave:l._onMouseItemLeave.bind(l,e),onMouseMove:l._onItemMouseMove.bind(l,e),role:"option"},{"data-index":e.index,"data-is-focusable":!e.disabled}),label:e.text,title:r,onRenderLabel:l._onRenderItemLabel.bind(l,e),className:t,checked:o,styles:i,ariaPositionInSet:l._sizePosCache.positionInSet(e.index),ariaSetSize:l._sizePosCache.optionSetSize,ariaLabel:e.ariaLabel}):gt.createElement(up,{id:l._listId+e.index,key:e.key,"data-index":e.index,"data-is-focusable":!e.disabled,disabled:e.disabled,className:t,onClick:l._onItemClick(e),onMouseEnter:l._onItemMouseEnter.bind(l,e),onMouseLeave:l._onMouseItemLeave.bind(l,e),onMouseMove:l._onItemMouseMove.bind(l,e),role:"option","aria-selected":o?"true":"false",ariaLabel:e.ariaLabel,title:r,"aria-posinset":l._sizePosCache.positionInSet(e.index),"aria-setsize":l._sizePosCache.optionSetSize},n(e,l._onRenderOption))},l._onRenderOption=function(e){return gt.createElement("span",{className:l._classNames.dropdownOptionText},e.text)},l._onRenderItemLabel=function(e){var t=l.props.onRenderOption;return(void 0===t?l._onRenderOption:t)(e,l._onRenderOption)},l._onPositioned=function(e){l._focusZone.current&&l._requestAnimationFrame(function(){var e=l.props.hoisted.selectedIndices;l._focusZone.current&&(!l._hasBeenPositioned&&e&&e[0]&&!l.props.options[e[0]].disabled?((e=ft().getElementById(l._id+"-list"+e[0]))&&l._focusZone.current.focusElement(e),l._hasBeenPositioned=!0):l._focusZone.current.focus())}),l.state.calloutRenderEdge&&l.state.calloutRenderEdge===e.targetEdge\|\|l.setState({calloutRenderEdge:e.targetEdge})},l._onItemClick=function(t){return function(e){t.disabled\|\|(l.setSelectedIndex(e,t.index),l.props.multiSelect\|\|l.setState({isOpen:!1}))}},l._onScroll=function(){l._isScrollIdle\|\|void 0===l._scrollIdleTimeoutId?l._isScrollIdle=!1:(clearTimeout(l._scrollIdleTimeoutId),l._scrollIdleTimeoutId=void 0),l._scrollIdleTimeoutId=window.setTimeout(function(){l._isScrollIdle=!0},l._scrollIdleDelay)},l._onMouseItemLeave=function(e,t){if(!l._shouldIgnoreMouseEvent()&&l._host.current)if(l._host.current.setActive)try{l._host.current.setActive()}catch(e){}else l._host.current.focus()},l._onDismiss=function(){l.setState({isOpen:!1})},l._onDropdownBlur=function(e){l._isDisabled()\|\|l.state.isOpen\|\|(l.setState({hasFocus:!1}),l.props.onBlur&&l.props.onBlur(e))},l._onDropdownKeyDown=function(e){if(!l._isDisabled()&&(l._lastKeyDownWasAltOrMeta=l._isAltOrMeta(e),!l.props.onKeyDown\|\|(l.props.onKeyDown(e),!e.defaultPrevented))){var t,o=l.props.hoisted.selectedIndices.length?l.props.hoisted.selectedIndices[0]:-1,n=e.altKey\|\|e.metaKey,r=l.state.isOpen;switch(e.which){case En.enter:l.setState({isOpen:!r});break;case En.escape:if(!r)return;l.setState({isOpen:!1});break;case En.up:if(n){if(r){l.setState({isOpen:!1});break}return}l.props.multiSelect?l.setState({isOpen:!0}):l._isDisabled()\|\|(t=l._moveIndex(e,-1,o-1,o));break;case En.down:n&&(e.stopPropagation(),e.preventDefault()),n&&!r\|\|l.props.multiSelect?l.setState({isOpen:!0}):l._isDisabled()\|\|(t=l._moveIndex(e,1,o+1,o));break;case En.home:l.props.multiSelect\|\|(t=l._moveIndex(e,1,0,o));break;case En.end:l.props.multiSelect\|\|(t=l._moveIndex(e,-1,l.props.options.length-1,o));break;case En.space:break;default:return}t!==o&&(e.stopPropagation(),e.preventDefault())}},l._onDropdownKeyUp=function(e){var t,o;l._isDisabled()\|\|(t=l._shouldHandleKeyUp(e),o=l.state.isOpen,l.props.onKeyUp&&(l.props.onKeyUp(e),e.defaultPrevented)\|\|(e.which===En.space?(l.setState({isOpen:!o}),e.stopPropagation(),e.preventDefault()):t&&o&&l.setState({isOpen:!1})))},l._onZoneKeyDown=function(e){var t;l._lastKeyDownWasAltOrMeta=l._isAltOrMeta(e);var o=e.altKey\|\|e.metaKey;switch(e.which){case En.up:o?l.setState({isOpen:!1}):l._host.current&&(t=ts(l._host.current,l._host.current.lastChild,!0));break;case En.home:case En.end:case En.pageUp:case En.pageDown:break;case En.down:!o&&l._host.current&&(t=es(l._host.current,l._host.current.firstChild,!0));break;case En.escape:l.setState({isOpen:!1});break;case En.tab:return void l.setState({isOpen:!1});default:return}t&&t.focus(),e.stopPropagation(),e.preventDefault()},l._onZoneKeyUp=function(e){l._shouldHandleKeyUp(e)&&l.state.isOpen&&(l.setState({isOpen:!1}),e.preventDefault())},l._onDropdownClick=function(e){l.props.onClick&&(l.props.onClick(e),e.defaultPrevented)\|\|(e=l.state.isOpen,l._isDisabled()\|\|l._shouldOpenOnFocus()\|\|l.setState({isOpen:!e}),l._isFocusedByClick=!1)},l._onDropdownMouseDown=function(){l._isFocusedByClick=!0},l._onFocus=function(e){l._isDisabled()\|\|(l.props.onFocus&&l.props.onFocus(e),e={hasFocus:!0},l._shouldOpenOnFocus()&&(e.isOpen=!0),l.setState(e))},l._isDisabled=function(){var e=l.props.disabled,t=l.props.isDisabled;return e=void 0===e?t:e},l._onRenderLabel=function(e){var t=e.label,o=e.required,n=e.disabled,e=l._classNames.subComponentStyles?l._classNames.subComponentStyles.label:void 0;return t?gt.createElement(om,{className:l._classNames.label,id:l._labelId,required:o,styles:e,disabled:n},t):null},fi(l),e.multiSelect,e.selectedKey,e.selectedKeys,e.defaultSelectedKey,e.defaultSelectedKeys;var t=e.options;return l._id=e.id\|\|_s("Dropdown"),l._labelId=l._id+"-label",l._listId=l._id+"-list",l._optionId=l._id+"-option",l._isScrollIdle=!0,l._hasBeenPositioned=!1,l._sizePosCache.updateOptions(t),l.state={isOpen:!1,hasFocus:!1,calloutRenderEdge:void 0},l}IC.displayName="Dropdown",Dt([{rawString:".pickerText_cc9894a7{display:-webkit-box;display:-ms-flexbox;display:flex;-ms-flex-wrap:wrap;flex-wrap:wrap;-webkit-box-align:center;-ms-flex-align:center;align-items:center;-webkit-box-sizing:border-box;box-sizing:border-box;border:1px solid "},{theme:"neutralTertiary",defaultValue:"#a19f9d"},{rawString:";min-width:180px;padding:1px;min-height:32px}.pickerText_cc9894a7:hover{border-color:"},{theme:"themeLight",defaultValue:"#c7e0f4"},{rawString:"}.pickerInput_cc9894a7{height:34px;border:none;-webkit-box-flex:1;-ms-flex-positive:1;flex-grow:1;outline:0;padding:0 6px 0;margin:1px}.pickerInput_cc9894a7::-ms-clear{display:none}"}]);var EC,TC="pickerText_cc9894a7",PC="pickerInput_cc9894a7",RC=e,MC=(l(NC,EC=gt.Component),Object.defineProperty(NC.prototype,"items",{get:function(){var e,t;return null!==(t=null!==(t=null!==(e=this.props.selectedItems)&&void 0!==e?e:null===(t=this.selectedItemsList.current)\|\|void 0===t?void 0:t.items)&&void 0!==t?t:this.props.defaultSelectedItems)&&void 0!==t?t:null},enumerable:!1,configurable:!0}),NC.prototype.componentDidMount=function(){this.forceUpdate()},NC.prototype.focus=function(){this.input.current&&this.input.current.focus()},NC.prototype.clearInput=function(){this.input.current&&this.input.current.clear()},Object.defineProperty(NC.prototype,"inputElement",{get:function(){return this.input.current&&this.input.current.inputElement},enumerable:!1,configurable:!0}),Object.defineProperty(NC.prototype,"highlightedItems",{get:function(){return this.selectedItemsList.current?this.selectedItemsList.current.highlightedItems():[]},enumerable:!1,configurable:!0}),NC.prototype.render=function(){var e=this.props,t=e.className,o=e.inputProps,n=e.disabled,r=e.focusZoneProps,i=this.floatingPicker.current&&-1!==this.floatingPicker.current.currentSelectedSuggestionIndex?"sug-"+this.floatingPicker.current.currentSelectedSuggestionIndex:void 0,e=!!this.floatingPicker.current&&this.floatingPicker.current.isSuggestionsShown;return gt.createElement("div",{ref:this.root,className:Tr("ms-BasePicker ms-BaseExtendedPicker",t\|\|""),onKeyDown:this.onBackspace,onCopy:this.onCopy},gt.createElement(Zs,ht({direction:Ei.bidirectional},r),gt.createElement(Pv,{selection:this.selection,selectionMode:dv.multiple},gt.createElement("div",{className:Tr("ms-BasePicker-text",RC.pickerText),role:"list"},this.props.headerComponent,this.renderSelectedItemsList(),this.canAddItems()&&gt.createElement(ki,ht({},o,{className:Tr("ms-BasePicker-input",RC.pickerInput),ref:this.input,onFocus:this.onInputFocus,onClick:this.onInputClick,onInputValueChange:this.onInputChange,"aria-activedescendant":i,"aria-owns":e?"suggestion-list":void 0,"aria-expanded":e,"aria-haspopup":"true",role:"combobox",disabled:n,onPaste:this.onPaste}))))),this.renderFloatingPicker())},Object.defineProperty(NC.prototype,"floatingPickerProps",{get:function(){return this.props.floatingPickerProps},enumerable:!1,configurable:!0}),Object.defineProperty(NC.prototype,"selectedItemsListProps",{get:function(){return this.props.selectedItemsListProps},enumerable:!1,configurable:!0}),NC.prototype.canAddItems=function(){var e=this.props.itemLimit;return void 0===e\|\|this.items.length<e},NC.prototype.renderFloatingPicker=function(){var e=this.props.onRenderFloatingPicker;return gt.createElement(e,ht({componentRef:this.floatingPicker,onChange:this._onSuggestionSelected,onSuggestionsHidden:this._onSuggestionsShownOrHidden,onSuggestionsShown:this._onSuggestionsShownOrHidden,inputElement:this.input.current?this.input.current.inputElement:void 0,selectedItems:this.items,suggestionItems:this.props.suggestionItems\|\|void 0},this.floatingPickerProps))},NC.prototype.renderSelectedItemsList=function(){var e=this.props.onRenderSelectedItems;return gt.createElement(e,ht({componentRef:this.selectedItemsList,selection:this.selection,selectedItems:this.props.selectedItems\|\|void 0,onItemsDeleted:this.props.selectedItems?this.props.onItemsRemoved:void 0},this.selectedItemsListProps))},NC.prototype._addProcessedItem=function(e){this.props.onItemAdded&&this.props.onItemAdded(e),this.selectedItemsList.current&&this.selectedItemsList.current.addItems([e]),this.input.current&&this.input.current.clear(),this.floatingPicker.current&&this.floatingPicker.current.hidePicker(),this.focus()},NC);function NC(e){var r=EC.call(this,e)\|\|this;return r.floatingPicker=gt.createRef(),r.selectedItemsList=gt.createRef(),r.root=gt.createRef(),r.input=gt.createRef(),r.onSelectionChange=function(){r.forceUpdate()},r.onInputChange=function(e,t){t\|\|(r.setState({queryString:e}),r.floatingPicker.current&&r.floatingPicker.current.onQueryStringChanged(e))},r.onInputFocus=function(e){r.selectedItemsList.current&&r.selectedItemsList.current.unselectAll(),r.props.inputProps&&r.props.inputProps.onFocus&&r.props.inputProps.onFocus(e)},r.onInputClick=function(e){var t;r.selectedItemsList.current&&r.selectedItemsList.current.unselectAll(),r.floatingPicker.current&&r.inputElement&&(t=""===r.inputElement.value\|\|r.inputElement.value!==r.floatingPicker.current.inputText,r.floatingPicker.current.showPicker(t))},r.onBackspace=function(e){e.which===En.backspace&&r.selectedItemsList.current&&r.items.length&&(r.input.current&&!r.input.current.isValueSelected&&r.input.current.inputElement===e.currentTarget.ownerDocument.activeElement&&0===r.input.current.cursorLocation?(r.floatingPicker.current&&r.floatingPicker.current.hidePicker(),e.preventDefault(),r.selectedItemsList.current.removeItemAt(r.items.length-1),r._onSelectedItemsChanged()):r.selectedItemsList.current.hasSelectedItems()&&(r.floatingPicker.current&&r.floatingPicker.current.hidePicker(),e.preventDefault(),r.selectedItemsList.current.removeSelectedItems(),r._onSelectedItemsChanged()))},r.onCopy=function(e){r.selectedItemsList.current&&r.selectedItemsList.current.onCopy(e)},r.onPaste=function(e){var t;r.props.onPaste&&(t=e.clipboardData.getData("Text"),e.preventDefault(),r.props.onPaste(t))},r._onSuggestionSelected=function(e){var t,o=r.props.currentRenderedQueryString,n=r.state.queryString;void 0!==o&&o!==n\|\|null!==(n=r.props.onItemSelected?r.props.onItemSelected(e):e)&&((e=n)&&n.then?n.then(function(e){t=e,r._addProcessedItem(t)}):(t=e,r._addProcessedItem(t)))},r._onSelectedItemsChanged=function(){r.focus()},r._onSuggestionsShownOrHidden=function(){r.forceUpdate()},fi(r),r.selection=new fv({onSelectionChanged:function(){return r.onSelectionChange()}}),r.state={queryString:""},r}Dt([{rawString:".resultContent_ae2a2ef5{display:table-row}.resultContent_ae2a2ef5 .resultItem_ae2a2ef5{display:table-cell;vertical-align:bottom}.peoplePickerPersona_ae2a2ef5{width:180px}.peoplePickerPersona_ae2a2ef5 .ms-Persona-details{width:100%}.peoplePicker_ae2a2ef5 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t=e.className,o=e.showSecondaryText,n=e.theme,r=n.semanticColors,i=n.fonts,s=zo(ZC,n),a=Kr(e.size),l=Ur(e.presence),c="16px",e={color:r.bodySubtext,fontWeight:Fe.regular,fontSize:i.small.fontSize};return{root:[s.root,n.fonts.medium,Uo,{color:r.bodyText,position:"relative",height:Nr.size48,minWidth:Nr.size48,display:"flex",alignItems:"center",selectors:{".contextualHost":{display:"none"}}},a.isSize8&&[s.size8,{height:Nr.size8,minWidth:Nr.size8}],a.isSize10&&[s.size10,{height:Nr.size10,minWidth:Nr.size10}],a.isSize16&&[s.size16,{height:Nr.size16,minWidth:Nr.size16}],a.isSize24&&[s.size24,{height:Nr.size24,minWidth:Nr.size24}],a.isSize24&&o&&{height:"36px"},a.isSize28&&[s.size28,{height:Nr.size28,minWidth:Nr.size28}],a.isSize28&&o&&{height:"32px"},a.isSize32&&[s.size32,{height:Nr.size32,minWidth:Nr.size32}],a.isSize40&&[s.size40,{height:Nr.size40,minWidth:Nr.size40}],a.isSize48&&s.size48,a.isSize56&&[s.size56,{height:Nr.size56,minWidth:Nr.size56}],a.isSize72&&[s.size72,{height:Nr.size72,minWidth:Nr.size72}],a.isSize100&&[s.size100,{height:Nr.size100,minWidth:Nr.size100}],a.isSize120&&[s.size120,{height:Nr.size120,minWidth:Nr.size120}],l.isAvailable&&s.available,l.isAway&&s.away,l.isBlocked&&s.blocked,l.isBusy&&s.busy,l.isDoNotDisturb&&s.doNotDisturb,l.isOffline&&s.offline,t],details:[s.details,{padding:"0 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0,{scope:"Persona"}),QC=Fn(),JC=(l(t_,YC=gt.Component),t_.prototype.render=function(){var e=this.props.overflowButtonProps,t=this.props,o=t.chevronButtonProps,n=t.maxDisplayablePersonas,r=t.personas,i=t.overflowPersonas,s=t.showAddButton,a=t.ariaLabel,l=t.showTooltip,c=void 0===l\|\|l,t=this._classNames,l="number"==typeof n?Math.min(r.length,n):r.length;o&&!e&&(e=o);n=i&&0<i.length,o=n?r:r.slice(0,l),l=(n?i:r.slice(l))\|\|[];return gt.createElement("div",{className:t.root},this.onRenderAriaDescription(),gt.createElement("div",{className:t.itemContainer},s?this._getAddNewElement():null,gt.createElement("ul",{className:t.members,"aria-label":a},this._onRenderVisiblePersonas(o,0===l.length&&1===r.length,c)),e?this._getOverflowElement(l):null))},t_.prototype.onRenderAriaDescription=function(){var e=this.props.ariaDescription,t=this._classNames;return e&&gt.createElement("span",{className:t.screenReaderOnly,id:this._ariaDescriptionId},e)},t_.prototype._onRenderVisiblePersonas=function(e,n,r){var i=this,t=this.props,o=t.onRenderPersona,s=void 0===o?this._getPersonaControl:o,t=t.onRenderPersonaCoin,a=void 0===t?this._getPersonaCoinControl:t;return e.map(function(e,t){var o=n?s(e,i._getPersonaControl):a(e,i._getPersonaCoinControl);return gt.createElement("li",{key:(n?"persona":"personaCoin")+"-"+t,className:i._classNames.member},e.onClick?i._getElementWithOnClickEvent(o,e,r,t):i._getElementWithoutOnClickEvent(o,e,r,t))})},t_.prototype._getElementWithOnClickEvent=function(e,t,o,n){var r=t.keytipProps;return gt.createElement(KC,ht({},ur(t,Yn),this._getElementProps(t,o,n),{keytipProps:r,onClick:this._onPersonaClick.bind(this,t)}),e)},t_.prototype._getElementWithoutOnClickEvent=function(e,t,o,n){return gt.createElement("div",ht({},ur(t,Yn),this._getElementProps(t,o,n)),e)},t_.prototype._getElementProps=function(e,t,o){var n=this._classNames;return{key:(e.imageUrl?"i":"")+o,"data-is-focusable":!0,className:n.itemButton,title:t?e.personaName:void 0,onMouseMove:this._onPersonaMouseMove.bind(this,e),onMouseOut:this._onPersonaMouseOut.bind(this,e)}},t_.prototype._getOverflowElement=function(e){switch(this.props.overflowButtonType){case BC.descriptive:return this._getDescriptiveOverflowElement(e);case BC.downArrow:return this._getIconElement("ChevronDown");case BC.more:return this._getIconElement("More");default:return null}},t_.prototype._getDescriptiveOverflowElement=function(e){var t=this.props.personaSize;if(!e\|\|e.length<1)return null;var o=e.map(function(e){return e.personaName}).join(", "),n=ht({title:o},this.props.overflowButtonProps),o=Math.max(e.length,0),e=this._classNames;return gt.createElement(KC,ht({},n,{ariaDescription:n.title,className:e.descriptiveOverflowButton}),gt.createElement(ui,{size:t,onRenderInitials:this._renderInitialsNotPictured(o),initialsColor:Mr.transparent}))},t_.prototype._getIconElement=function(e){var t=this.props,o=t.overflowButtonProps,n=t.personaSize,t=this._classNames;return gt.createElement(KC,ht({},o,{className:t.overflowButton}),gt.createElement(ui,{size:n,onRenderInitials:this._renderInitials(e,!0),initialsColor:Mr.transparent}))},t_.prototype._getAddNewElement=function(){var e=this.props,t=e.addButtonProps,o=e.personaSize,e=this._classNames;return 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(-ms-high-contrast:active){.itemButton_2f55324e.itemButton_2f55324e{color:WindowText}}.itemButton_2f55324e.itemButton_2f55324e:hover{color:"},{theme:"neutralDark",defaultValue:"#201f1e"},{rawString:"}.closeButton_2f55324e.closeButton_2f55324e{padding:0 4px;height:auto;width:32px}@media screen and (-ms-high-contrast:active){.closeButton_2f55324e.closeButton_2f55324e{color:WindowText}}.closeButton_2f55324e.closeButton_2f55324e:hover{background:"},{theme:"neutralTertiaryAlt",defaultValue:"#c8c6c4"},{rawString:";color:"},{theme:"neutralDark",defaultValue:"#201f1e"},{rawString:"}.suggestionsAvailable_2f55324e{position:absolute;width:1px;height:1px;padding:0;margin:-1px;overflow:hidden;clip:rect(0,0,0,0);border:0}"}]);var n_,r_="root_2f55324e",i_="suggestionsItem_2f55324e",s_="closeButton_2f55324e",a_="suggestionsItemIsSuggested_2f55324e",l_="itemButton_2f55324e",c_="actionButton_2f55324e",u_="buttonSelected_2f55324e",d_="suggestionsTitle_2f55324e",p_="suggestionsContainer_2f55324e",h_="suggestionsNone_2f55324e",m_="suggestionsSpinner_2f55324e",g_="suggestionsAvailable_2f55324e",f_=o,v_=Fn(),b_=(l(y_,n_=gt.Component),y_.prototype.render=function(){var e=this.props,t=e.suggestionModel,o=e.RenderSuggestion,n=e.onClick,r=e.className,i=e.id,s=e.onRemoveItem,a=e.isSelectedOverride,l=e.removeButtonAriaLabel,c=e.styles,u=e.theme,e=e.removeButtonIconProps,r=c?v_(c,{theme:u,className:r,suggested:t.selected\|\|a}):{root:Tr("ms-Suggestions-item",f_.suggestionsItem,((u={})["is-suggested "+f_.suggestionsItemIsSuggested]=t.selected\|\|a,u),r),itemButton:Tr("ms-Suggestions-itemButton",f_.itemButton),closeButton:Tr("ms-Suggestions-closeButton",f_.closeButton)};return gt.createElement("div",{className:r.root,role:"presentation"},gt.createElement(up,{onClick:n,className:r.itemButton,id:i,"aria-selected":t.selected,role:"option","aria-label":t.ariaLabel},o(t.item,this.props)),this.props.showRemoveButton?gt.createElement(rd,{iconProps:null!=e?e:{iconName:"Cancel"},styles:{icon:{fontSize:"12px"}},title:l,ariaLabel:l,onClick:s,className:r.closeButton}):null)},y_);function y_(e){e=n_.call(this,e)\|\|this;return fi(e),e}Dt([{rawString:".suggestionsContainer_a151d363{overflow-y:auto;overflow-x:hidden;max-height:300px}.suggestionsContainer_a151d363 .ms-Suggestion-item:hover{background-color:"},{theme:"neutralLighter",defaultValue:"#f3f2f1"},{rawString:";cursor:pointer}.suggestionsContainer_a151d363 .is-suggested{background-color:"},{theme:"themeLighter",defaultValue:"#deecf9"},{rawString:"}.suggestionsContainer_a151d363 .is-suggested:hover{background-color:"},{theme:"themeLight",defaultValue:"#c7e0f4"},{rawString:";cursor:pointer}"}]);var C_,__="suggestionsContainer_a151d363",S_=n,x_=(l(k_,C_=gt.Component),k_.prototype.nextSuggestion=function(){var e=this.props.suggestions;if(e&&0<e.length){if(-1===this.currentIndex)return this.setSelectedSuggestion(0),!0;if(this.currentIndex<e.length-1)return this.setSelectedSuggestion(this.currentIndex+1),!0;if(this.props.shouldLoopSelection&&this.currentIndex===e.length-1)return this.setSelectedSuggestion(0),!0}return!1},k_.prototype.previousSuggestion=function(){var e=this.props.suggestions;if(e&&0<e.length){if(-1===this.currentIndex)return this.setSelectedSuggestion(e.length-1),!0;if(0<this.currentIndex)return this.setSelectedSuggestion(this.currentIndex-1),!0;if(this.props.shouldLoopSelection&&0===this.currentIndex)return this.setSelectedSuggestion(e.length-1),!0}return!1},Object.defineProperty(k_.prototype,"selectedElement",{get:function(){return this._selectedElement.current\|\|void 0},enumerable:!1,configurable:!0}),k_.prototype.getCurrentItem=function(){return this.props.suggestions[this.currentIndex]},k_.prototype.getSuggestionAtIndex=function(e){return this.props.suggestions[e]},k_.prototype.hasSuggestionSelected=function(){return-1!==this.currentIndex&&this.currentIndex<this.props.suggestions.length},k_.prototype.removeSuggestion=function(e){this.props.suggestions.splice(e,1)},k_.prototype.deselectAllSuggestions=function(){-1<this.currentIndex&&this.props.suggestions[this.currentIndex]&&(this.props.suggestions[this.currentIndex].selected=!1,this.currentIndex=-1,this.forceUpdate())},k_.prototype.setSelectedSuggestion=function(e){var t=this.props.suggestions;e>t.length-1\|\|e<0?(this.currentIndex=0,this.currentSuggestion.selected=!1,this.currentSuggestion=t[0],this.currentSuggestion.selected=!0):(-1<this.currentIndex&&t[this.currentIndex]&&(t[this.currentIndex].selected=!1),t[e].selected=!0,this.currentIndex=e,this.currentSuggestion=t[e]),this.forceUpdate()},k_.prototype.componentDidUpdate=function(){this.scrollSelected()},k_.prototype.render=function(){var o=this,e=this.props,n=e.onRenderSuggestion,r=e.suggestionsItemClassName,t=e.resultsMaximumNumber,i=e.showRemoveButtons,s=e.suggestionsContainerAriaLabel,a=this.SuggestionsItemOfProperType,e=this.props.suggestions;return t&&(e=e.slice(0,t)),gt.createElement("div",{className:Tr("ms-Suggestions-container",S_.suggestionsContainer),id:"suggestion-list",role:"list","aria-label":s},e.map(function(e,t){return gt.createElement("div",{ref:e.selected\|\|t===o.currentIndex?o._selectedElement:void 0,key:e.item.key\|\|t,id:"sug-"+t,role:"listitem","aria-label":e.ariaLabel},gt.createElement(a,{id:"sug-item"+t,suggestionModel:e,RenderSuggestion:n,onClick:o._onClickTypedSuggestionsItem(e.item,t),className:r,showRemoveButton:i,onRemoveItem:o._onRemoveTypedSuggestionsItem(e.item,t),isSelectedOverride:t===o.currentIndex}))}))},k_.prototype.scrollSelected=function(){var e;void 0!==(null===(e=this._selectedElement.current)\|\|void 0===e?void 0:e.scrollIntoView)&&this._selectedElement.current.scrollIntoView(!1)},k_);function k_(e){var n=C_.call(this,e)\|\|this;return n._selectedElement=gt.createRef(),n.SuggestionsItemOfProperType=b_,n._onClickTypedSuggestionsItem=function(t,o){return function(e){n.props.onSuggestionClick(e,t,o)}},n._onRemoveTypedSuggestionsItem=function(t,o){return function(e){(0,n.props.onSuggestionRemove)(e,t,o),e.stopPropagation()}},fi(n),n.currentIndex=-1,n}Dt([{rawString:".root_e4eecb3d{min-width:260px}.actionButton_e4eecb3d{background:0 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(-ms-high-contrast:active){.itemButton_e4eecb3d{color:WindowText}}.screenReaderOnly_e4eecb3d{position:absolute;width:1px;height:1px;padding:0;margin:-1px;overflow:hidden;clip:rect(0,0,0,0);border:0}"}]);var w_,I_="root_e4eecb3d",D_="actionButton_e4eecb3d",E_="buttonSelected_e4eecb3d",T_="suggestionsTitle_e4eecb3d",P_="suggestionsSpinner_e4eecb3d",R_="itemButton_e4eecb3d",M_="screenReaderOnly_e4eecb3d",N_=r;(K=w_=w_\|\|{})[K.header=0]="header",K[K.suggestion=1]="suggestion",K[K.footer=2]="footer";var B_,F_,A_,L_=(l(K_,A_=gt.Component),K_.prototype.render=function(){var e=this.props,t=e.renderItem,o=e.onExecute,n=e.isSelected,r=e.id,e=e.className;return o?gt.createElement("div",{id:r,onClick:o,className:Tr("ms-Suggestions-sectionButton",e,N_.actionButton,((o={})["is-selected "+N_.buttonSelected]=n,o))},t()):gt.createElement("div",{id:r,className:Tr("ms-Suggestions-section",e,N_.suggestionsTitle)},t())},K_),H_=(l(V_,F_=gt.Component),V_.prototype.componentDidMount=function(){this.resetSelectedItem()},V_.prototype.componentDidUpdate=function(e){var t=this;this.scrollSelected(),e.suggestions&&e.suggestions!==this.props.suggestions&&this.setState({suggestions:this.props.suggestions},function(){t.resetSelectedItem()})},V_.prototype.componentWillUnmount=function(){var e;null===(e=this._suggestions.current)\|\|void 0===e\|\|e.deselectAllSuggestions()},V_.prototype.render=function(){var e=this.props,t=e.className,o=e.headerItemsProps,n=e.footerItemsProps,r=e.suggestionsAvailableAlertText,i=j(So),e=this.state.suggestions&&0<this.state.suggestions.length&&r;return gt.createElement("div",{className:Tr("ms-Suggestions",t\|\|"",N_.root)},o&&this.renderHeaderItems(),this._renderSuggestions(),n&&this.renderFooterItems(),e?gt.createElement("span",{role:"alert","aria-live":"polite",className:i},r):null)},Object.defineProperty(V_.prototype,"currentSuggestion",{get:function(){var e;return(null===(e=this._suggestions.current)\|\|void 0===e?void 0:e.getCurrentItem())\|\|void 0},enumerable:!1,configurable:!0}),Object.defineProperty(V_.prototype,"currentSuggestionIndex",{get:function(){return this._suggestions.current?this._suggestions.current.currentIndex:-1},enumerable:!1,configurable:!0}),Object.defineProperty(V_.prototype,"selectedElement",{get:function(){var e;return this._selectedElement.current\|\|(null===(e=this._suggestions.current)\|\|void 0===e?void 0:e.selectedElement)},enumerable:!1,configurable:!0}),V_.prototype.hasSuggestionSelected=function(){var e;return(null===(e=this._suggestions.current)\|\|void 0===e?void 0:e.hasSuggestionSelected())\|\|!1},V_.prototype.hasSelection=function(){var e=this.state,t=e.selectedHeaderIndex,e=e.selectedFooterIndex;return-1!==t\|\|this.hasSuggestionSelected()\|\|-1!==e},V_.prototype.executeSelectedAction=function(){var e,t=this.props,o=t.headerItemsProps,n=t.footerItemsProps,r=this.state,t=r.selectedHeaderIndex,r=r.selectedFooterIndex;o&&-1!==t&&t<o.length?(e=o[t]).onExecute&&e.onExecute():null!==(e=this._suggestions.current)&&void 0!==e&&e.hasSuggestionSelected()?this.props.completeSuggestion():n&&-1!==r&&r<n.length&&((r=n[r]).onExecute&&r.onExecute())},V_.prototype.removeSuggestion=function(e){var t;null===(t=this._suggestions.current)\|\|void 0===t\|\|t.removeSuggestion(e\|\|(null===(e=this._suggestions.current)\|\|void 0===e?void 0:e.currentIndex))},V_.prototype.handleKeyDown=function(e){var t,o=this.state,n=o.selectedHeaderIndex,r=o.selectedFooterIndex,i=!1;return e===En.down?-1!==n\|\|null!==(o=this._suggestions.current)&&void 0!==o&&o.hasSuggestionSelected()\|\|-1!==r?-1!==n?(this.selectNextItem(w_.header),i=!0):null!==(t=this._suggestions.current)&&void 0!==t&&t.hasSuggestionSelected()?(this.selectNextItem(w_.suggestion),i=!0):-1!==r&&(this.selectNextItem(w_.footer),i=!0):this.selectFirstItem():e===En.up?-1!==n\|\|null!==(t=this._suggestions.current)&&void 0!==t&&t.hasSuggestionSelected()\|\|-1!==r?-1!==n?(this.selectPreviousItem(w_.header),i=!0):null!==(n=this._suggestions.current)&&void 0!==n&&n.hasSuggestionSelected()?(this.selectPreviousItem(w_.suggestion),i=!0):-1!==r&&(this.selectPreviousItem(w_.footer),i=!0):this.selectLastItem():e!==En.enter&&e!==En.tab\|\|this.hasSelection()&&(this.executeSelectedAction(),i=!0),i},V_.prototype.scrollSelected=function(){this._selectedElement.current&&this._selectedElement.current.scrollIntoView(!1)},V_.prototype.renderHeaderItems=function(){var n=this,e=this.props,t=e.headerItemsProps,e=e.suggestionsHeaderContainerAriaLabel,r=this.state.selectedHeaderIndex;return t?gt.createElement("div",{className:Tr("ms-Suggestions-headerContainer",N_.suggestionsContainer),id:"suggestionHeader-list",role:"list","aria-label":e},t.map(function(e,t){var o=-1!==r&&r===t;return e.shouldShow()?gt.createElement("div",{ref:o?n._selectedElement:void 0,id:"sug-header"+t,key:"sug-header"+t,role:"listitem","aria-label":e.ariaLabel},gt.createElement(L_,{id:"sug-header-item"+t,isSelected:o,renderItem:e.renderItem,onExecute:e.onExecute,className:e.className})):null})):null},V_.prototype.renderFooterItems=function(){var n=this,e=this.props,t=e.footerItemsProps,e=e.suggestionsFooterContainerAriaLabel,r=this.state.selectedFooterIndex;return t?gt.createElement("div",{className:Tr("ms-Suggestions-footerContainer",N_.suggestionsContainer),id:"suggestionFooter-list",role:"list","aria-label":e},t.map(function(e,t){var o=-1!==r&&r===t;return e.shouldShow()?gt.createElement("div",{ref:o?n._selectedElement:void 0,id:"sug-footer"+t,key:"sug-footer"+t,role:"listitem","aria-label":e.ariaLabel},gt.createElement(L_,{id:"sug-footer-item"+t,isSelected:o,renderItem:e.renderItem,onExecute:e.onExecute,className:e.className})):null})):null},V_.prototype._renderSuggestions=function(){var e=this.SuggestionsOfProperType;return gt.createElement(e,ht({ref:this._suggestions},this.props,{suggestions:this.state.suggestions}))},V_.prototype.selectNextItem=function(e,t){e!==t?this._selectNextItemOfItemType(e,(t=void 0!==t?t:e)===e?this._getCurrentIndexForType(e):void 0)\|\|this.selectNextItem(this._getNextItemSectionType(e),t):this._selectNextItemOfItemType(e)},V_.prototype.selectPreviousItem=function(e,t){e!==t?this._selectPreviousItemOfItemType(e,(t=void 0!==t?t:e)===e?this._getCurrentIndexForType(e):void 0)\|\|this.selectPreviousItem(this._getPreviousItemSectionType(e),t):this._selectPreviousItemOfItemType(e)},V_.prototype.resetSelectedItem=function(){var e;this.setState({selectedHeaderIndex:-1,selectedFooterIndex:-1}),null===(e=this._suggestions.current)\|\|void 0===e\|\|e.deselectAllSuggestions(),void 0!==this.props.shouldSelectFirstItem&&!this.props.shouldSelectFirstItem()\|\|this.selectFirstItem()},V_.prototype.selectFirstItem=function(){this._selectNextItemOfItemType(w_.header)\|\|this._selectNextItemOfItemType(w_.suggestion)\|\|this._selectNextItemOfItemType(w_.footer)},V_.prototype.selectLastItem=function(){this._selectPreviousItemOfItemType(w_.footer)\|\|this._selectPreviousItemOfItemType(w_.suggestion)\|\|this._selectPreviousItemOfItemType(w_.header)},V_.prototype._selectNextItemOfItemType=function(e,t){var o;if(void 0===t&&(t=-1),e===w_.suggestion){if(this.state.suggestions.length>t+1)return null===(o=this._suggestions.current)\|\|void 0===o\|\|o.setSelectedSuggestion(t+1),this.setState({selectedHeaderIndex:-1,selectedFooterIndex:-1}),!0}else{var n=e===w_.header,r=n?this.props.headerItemsProps:this.props.footerItemsProps;if(r&&r.length>t+1)for(var i=t+1;i<r.length;i++){var s=r[i];if(s.onExecute&&s.shouldShow())return this.setState({selectedHeaderIndex:n?i:-1}),this.setState({selectedFooterIndex:n?-1:i}),null===(s=this._suggestions.current)\|\|void 0===s\|\|s.deselectAllSuggestions(),!0}}return!1},V_.prototype._selectPreviousItemOfItemType=function(e,t){var o;if(e===w_.suggestion){if(0<(n=void 0!==t?t:this.state.suggestions.length))return null===(o=this._suggestions.current)\|\|void 0===o\|\|o.setSelectedSuggestion(n-1),this.setState({selectedHeaderIndex:-1,selectedFooterIndex:-1}),!0}else{var n,r=e===w_.header,i=r?this.props.headerItemsProps:this.props.footerItemsProps;if(i&&0<(n=void 0!==t?t:i.length))for(var s=n-1;0<=s;s--){var a=i[s];if(a.onExecute&&a.shouldShow())return this.setState({selectedHeaderIndex:r?s:-1}),this.setState({selectedFooterIndex:r?-1:s}),null===(a=this._suggestions.current)\|\|void 0===a\|\|a.deselectAllSuggestions(),!0}}return!1},V_.prototype._getCurrentIndexForType=function(e){switch(e){case w_.header:return this.state.selectedHeaderIndex;case w_.suggestion:return this._suggestions.current.currentIndex;case w_.footer:return this.state.selectedFooterIndex}},V_.prototype._getNextItemSectionType=function(e){switch(e){case w_.header:return w_.suggestion;case w_.suggestion:return w_.footer;case w_.footer:return w_.header}},V_.prototype._getPreviousItemSectionType=function(e){switch(e){case w_.header:return w_.footer;case w_.suggestion:return w_.header;case w_.footer:return w_.suggestion}},V_),O_=t,z_=(l(W_,B_=gt.Component),Object.defineProperty(W_.prototype,"inputText",{get:function(){return this.state.queryString},enumerable:!1,configurable:!0}),Object.defineProperty(W_.prototype,"suggestions",{get:function(){return this.suggestionStore.suggestions},enumerable:!1,configurable:!0}),W_.prototype.forceResolveSuggestion=function(){this.suggestionsControl.current&&this.suggestionsControl.current.hasSuggestionSelected()?this.completeSuggestion():this._onValidateInput()},Object.defineProperty(W_.prototype,"currentSelectedSuggestionIndex",{get:function(){return this.suggestionsControl.current?this.suggestionsControl.current.currentSuggestionIndex:-1},enumerable:!1,configurable:!0}),Object.defineProperty(W_.prototype,"isSuggestionsShown",{get:function(){return void 0!==this.state.suggestionsVisible&&this.state.suggestionsVisible},enumerable:!1,configurable:!0}),W_.prototype.componentDidMount=function(){this._bindToInputElement(),this.isComponentMounted=!0,this._onResolveSuggestions=this._async.debounce(this._onResolveSuggestions,this.props.resolveDelay)},W_.prototype.componentDidUpdate=function(){this._bindToInputElement()},W_.prototype.componentWillUnmount=function(){this._unbindFromInputElement(),this.isComponentMounted=!1},W_.prototype.updateSuggestions=function(e,t){void 0===t&&(t=!1),this.suggestionStore.updateSuggestions(e),t&&this.forceUpdate()},W_.prototype.render=function(){var e=this.props.className;return gt.createElement("div",{ref:this.root,className:Tr("ms-BasePicker ms-BaseFloatingPicker",e\|\|"")},this.renderSuggestions())},W_.prototype.renderSuggestions=function(){var e=this.SuggestionsControlOfProperType;return this.props.suggestionItems&&this.suggestionStore.updateSuggestions(this.props.suggestionItems),this.state.suggestionsVisible?gt.createElement(ac,ht({className:O_.callout,isBeakVisible:!1,gapSpace:5,target:this.props.inputElement,onDismiss:this.hidePicker,directionalHint:Pa.bottomLeftEdge,directionalHintForRTL:Pa.bottomRightEdge,calloutWidth:this.props.calloutWidth\|\|0},this.props.pickerCalloutProps),gt.createElement(e,ht({onRenderSuggestion:this.props.onRenderSuggestionsItem,onSuggestionClick:this.onSuggestionClick,onSuggestionRemove:this.onSuggestionRemove,suggestions:this.suggestionStore.getSuggestions(),componentRef:this.suggestionsControl,completeSuggestion:this.completeSuggestion,shouldLoopSelection:!1},this.props.pickerSuggestionsProps))):null},W_.prototype.onSelectionChange=function(){this.forceUpdate()},W_.prototype.updateValue=function(e){""===e?this.updateSuggestionWithZeroState():this._onResolveSuggestions(e)},W_.prototype.updateSuggestionWithZeroState=function(){var e;this.props.onZeroQuerySuggestion?(e=(0,this.props.onZeroQuerySuggestion)(this.props.selectedItems),this.updateSuggestionsList(e)):this.hidePicker()},W_.prototype.updateSuggestionsList=function(t){var o=this;Array.isArray(t)?this.updateSuggestions(t,!0):t&&t.then&&(this.currentPromise=t).then(function(e){t===o.currentPromise&&o.isComponentMounted&&o.updateSuggestions(e,!0)})},W_.prototype.onChange=function(e){this.props.onChange&&this.props.onChange(e)},W_.prototype._updateActiveDescendant=function(){var e;this.props.inputElement&&this.suggestionsControl.current&&this.suggestionsControl.current.selectedElement&&((e=this.suggestionsControl.current.selectedElement.getAttribute("id"))&&this.props.inputElement.setAttribute("aria-activedescendant",e))},W_.prototype._onResolveSuggestions=function(e){e=this.props.onResolveSuggestions(e,this.props.selectedItems);this._updateSuggestionsVisible(!0),null!==e&&this.updateSuggestionsList(e)},W_.prototype._updateSuggestionsVisible=function(e){e?this.showPicker():this.hidePicker()},W_.prototype._bindToInputElement=function(){this.props.inputElement&&!this.state.didBind&&(this.props.inputElement.addEventListener("keydown",this.onKeyDown),this.setState({didBind:!0}))},W_.prototype._unbindFromInputElement=function(){this.props.inputElement&&this.state.didBind&&(this.props.inputElement.removeEventListener("keydown",this.onKeyDown),this.setState({didBind:!1}))},W_);function W_(e){var n=B_.call(this,e)\|\|this;return n.root=gt.createRef(),n.suggestionsControl=gt.createRef(),n.SuggestionsControlOfProperType=H_,n.isComponentMounted=!1,n.onQueryStringChanged=function(e){e!==n.state.queryString&&(n.setState({queryString:e}),n.props.onInputChanged&&n.props.onInputChanged(e),n.updateValue(e))},n.hidePicker=function(){var e=n.isSuggestionsShown;n.setState({suggestionsVisible:!1}),n.props.onSuggestionsHidden&&e&&n.props.onSuggestionsHidden()},n.showPicker=function(e){void 0===e&&(e=!1);var t=n.isSuggestionsShown;n.setState({suggestionsVisible:!0});var o=n.props.inputElement?n.props.inputElement.value:"";e&&n.updateValue(o),n.props.onSuggestionsShown&&!t&&n.props.onSuggestionsShown()},n.completeSuggestion=function(){n.suggestionsControl.current&&n.suggestionsControl.current.hasSuggestionSelected()&&n.onChange(n.suggestionsControl.current.currentSuggestion.item)},n.onSuggestionClick=function(e,t,o){n.onChange(t),n._updateSuggestionsVisible(!1)},n.onSuggestionRemove=function(e,t,o){n.props.onRemoveSuggestion&&n.props.onRemoveSuggestion(t),n.suggestionsControl.current&&n.suggestionsControl.current.removeSuggestion(o)},n.onKeyDown=function(e){if(n.state.suggestionsVisible&&(!n.props.inputElement\|\|n.props.inputElement.contains(e.target))){var t=e.which;switch(t){case En.escape:n.hidePicker(),e.preventDefault(),e.stopPropagation();break;case En.tab:case En.enter:!e.shiftKey&&!e.ctrlKey&&n.suggestionsControl.current&&n.suggestionsControl.current.handleKeyDown(t)?(e.preventDefault(),e.stopPropagation()):n._onValidateInput();break;case En.del:n.props.onRemoveSuggestion&&n.suggestionsControl.current&&n.suggestionsControl.current.hasSuggestionSelected&&n.suggestionsControl.current.currentSuggestion&&e.shiftKey&&(n.props.onRemoveSuggestion(n.suggestionsControl.current.currentSuggestion.item),n.suggestionsControl.current.removeSuggestion(),n.forceUpdate(),e.stopPropagation());break;case En.up:case En.down:n.suggestionsControl.current&&n.suggestionsControl.current.handleKeyDown(t)&&(e.preventDefault(),e.stopPropagation(),n._updateActiveDescendant())}}},n._onValidateInput=function(){var e;n.state.queryString&&n.props.onValidateInput&&n.props.createGenericItem&&(e=n.props.createGenericItem(n.state.queryString,n.props.onValidateInput(n.state.queryString)),e=n.suggestionStore.convertSuggestionsToSuggestionItems([e]),n.onChange(e[0].item))},n._async=new Si(n),fi(n),n.suggestionStore=e.suggestionsStore,n.state={queryString:"",didBind:!1},n}function V_(e){var t=F_.call(this,e)\|\|this;return 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this.suggestions[e]},tS.prototype.removeSuggestion=function(e){this.suggestions.splice(e,1)},tS.prototype.convertSuggestionsToSuggestionItems=function(e){return Array.isArray(e)?e.map(this._ensureSuggestionModel):[]},tS),eS={host:"ms-HoverCard-host"};function tS(e){var t=this;this._isSuggestionModel=function(e){return void 0!==e.item},this._ensureSuggestionModel=function(e){return t._isSuggestionModel(e)?e:{item:e,selected:!1,ariaLabel:void 0!==t.getAriaLabel?t.getAriaLabel(e):e.name\|\|e.text\|\|e.primaryText}},this.suggestions=[],this.getAriaLabel=e&&e.getAriaLabel}(U=Q_=Q_\|\|{})[U.hover=0]="hover",U[U.hotKey=1]="hotKey",(xe=J_=J_\|\|{}).plain="PlainCard",xe.expanding="ExpandingCard";var oS,nS={root:"ms-ExpandingCard-root",compactCard:"ms-ExpandingCard-compactCard",expandedCard:"ms-ExpandingCard-expandedCard",expandedCardScroll:"ms-ExpandingCard-expandedCardScrollRegion"};(G=oS=oS\|\|{})[G.compact=0]="compact",G[G.expanded=1]="expanded";function rS(e){var t=void 0===(u=e.gapSpace)?0:u,o=void 0===(d=e.directionalHint)?Pa.bottomLeftEdge:d,n=e.directionalHintFixed,r=e.targetElement,i=e.firstFocus,s=e.trapFocus,a=e.onLeave,l=e.className,c=e.finalHeight,u=e.content,d=e.calloutProps,d=ht(ht(ht({},ur(e,cr)),{className:l,target:r,isBeakVisible:!1,directionalHint:o,directionalHintFixed:n,finalHeight:c,minPagePadding:24,onDismiss:a,gapSpace:t}),d);return gt.createElement(gt.Fragment,null,s?gt.createElement(Kh,ht({},d,{focusTrapProps:{forceFocusInsideTrap:!1,isClickableOutsideFocusTrap:!0,disableFirstFocus:!i}}),u):gt.createElement(ac,ht({},d),u))}var iS,sS,aS,lS=Fn(),cS=(l(CS,aS=gt.Component),CS.prototype.componentDidMount=function(){this._checkNeedsScroll()},CS.prototype.componentWillUnmount=function(){this._async.dispose()},CS.prototype.render=function(){var e=this.props,t=e.styles,o=e.compactCardHeight,n=e.expandedCardHeight,r=e.theme,i=e.mode,s=e.className,a=this.state,l=a.needsScroll,e=a.firstFrameRendered,a=o+n;this._classNames=lS(t,{theme:r,compactCardHeight:o,className:s,expandedCardHeight:n,needsScroll:l,expandedCardFirstFrameRendered:i===oS.expanded&&e});e=gt.createElement("div",{onMouseEnter:this.props.onEnter,onMouseLeave:this.props.onLeave,onKeyDown:this._onKeyDown},this._onRenderCompactCard(),this._onRenderExpandedCard());return gt.createElement(rS,ht({},this.props,{content:e,finalHeight:a,className:this._classNames.root}))},CS.defaultProps={compactCardHeight:156,expandedCardHeight:384,directionalHintFixed:!0},CS),uS=In(cS,function(e){var t=e.theme,o=e.needsScroll,n=e.expandedCardFirstFrameRendered,r=e.compactCardHeight,i=e.expandedCardHeight,s=e.className,a=t.palette,e=zo(nS,t);return{root:[e.root,{width:320,pointerEvents:"none",selectors:((t={})[Yt]={border:"1px solid WindowText"},t)},s],compactCard:[e.compactCard,{pointerEvents:"auto",position:"relative",height:r}],expandedCard:[e.expandedCard,{height:1,overflowY:"hidden",pointerEvents:"auto",transition:"height 0.467s cubic-bezier(0.5, 0, 0, 1)",selectors:{":before":{content:'""',position:"relative",display:"block",top:0,left:24,width:272,height:1,backgroundColor:a.neutralLighter}}},n&&{height:i}],expandedCardScroll:[e.expandedCardScroll,o&&{height:"100%",boxSizing:"border-box",overflowY:"auto"}]}},void 0,{scope:"ExpandingCard"}),dS={root:"ms-PlainCard-root"},pS=Fn(),hS=(l(yS,sS=gt.Component),yS.prototype.render=function(){var e=this.props,t=e.styles,o=e.theme,e=e.className;this._classNames=pS(t,{theme:o,className:e});e=gt.createElement("div",{onMouseEnter:this.props.onEnter,onMouseLeave:this.props.onLeave,onKeyDown:this._onKeyDown},this.props.onRenderPlainCard(this.props.renderData));return gt.createElement(rS,ht({},this.props,{content:e,className:this._classNames.root}))},yS),mS=In(hS,function(e){var t=e.theme,e=e.className;return{root:[zo(dS,t).root,{pointerEvents:"auto",selectors:((t={})[Yt]={border:"1px solid WindowText"},t)},e]}},void 0,{scope:"PlainCard"}),gS=Fn(),fS=(l(bS,iS=gt.Component),bS.prototype.componentDidMount=function(){this._setEventListeners()},bS.prototype.componentWillUnmount=function(){this._async.dispose(),this._events.dispose()},bS.prototype.componentDidUpdate=function(e,t){var o=this;e.target!==this.props.target&&(this._events.off(),this._setEventListeners()),t.isHoverCardVisible!==this.state.isHoverCardVisible&&(this.state.isHoverCardVisible?(this._async.setTimeout(function(){o.setState({mode:oS.expanded},function(){o.props.onCardExpand&&o.props.onCardExpand()})},this.props.expandedCardOpenDelay),this.props.onCardVisible&&this.props.onCardVisible()):(this.setState({mode:oS.compact}),this.props.onCardHide&&this.props.onCardHide()))},bS.prototype.render=function(){var e=this.props,t=e.expandingCardProps,o=e.children,n=e.id,r=e.setAriaDescribedBy,i=void 0===r\|\|r,s=e.styles,a=e.theme,l=e.className,c=e.type,u=e.plainCardProps,d=e.trapFocus,p=e.setInitialFocus,h=this.state,r=h.isHoverCardVisible,e=h.mode,h=h.openMode,n=n\|\|_s("hoverCard");this._classNames=gS(s,{theme:a,className:l});h=ht(ht({},ur(this.props,cr)),{id:n,trapFocus:!!d,firstFocus:p\|\|h===Q_.hotKey,targetElement:this._getTargetElement(this.props.target),onEnter:this._cardOpen,onLeave:this._childDismissEvent}),e=ht(ht(ht({},t),h),{mode:e}),h=ht(ht({},u),h);return gt.createElement("div",{className:this._classNames.host,ref:this._hoverCard,"aria-describedby":i&&r?n:void 0,"data-is-focusable":!this.props.target},o,r&&(c===J_.expanding?gt.createElement(uS,ht({},e)):gt.createElement(mS,ht({},h))))},bS.prototype._getTargetElement=function(e){switch(typeof e){case"string":return ft().querySelector(e);case"object":return e;default:return this._hoverCard.current\|\|void 0}},bS.prototype._shouldBlockHoverCard=function(){return!(!this.props.shouldBlockHoverCard\|\|!this.props.shouldBlockHoverCard())},bS.defaultProps={cardOpenDelay:500,cardDismissDelay:100,expandedCardOpenDelay:1500,instantOpenOnClick:!1,setInitialFocus:!1,openHotKey:En.c,type:J_.expanding},bS),vS=In(fS,function(e){var t=e.className,e=e.theme;return{host:[zo(eS,e).host,t]}},void 0,{scope:"HoverCard"});function bS(e){var r=iS.call(this,e)\|\|this;return r._hoverCard=gt.createRef(),r.dismiss=function(e){r._async.clearTimeout(r._openTimerId),r._async.clearTimeout(r._dismissTimerId),e?r._dismissTimerId=r._async.setTimeout(function(){r._setDismissedState()},r.props.cardDismissDelay):r._setDismissedState()},r._cardOpen=function(e){r._shouldBlockHoverCard()\|\|"keydown"===e.type&&e.which!==r.props.openHotKey\|\|(r._async.clearTimeout(r._dismissTimerId),"mouseenter"===e.type&&(r._currentMouseTarget=e.currentTarget),r._executeCardOpen(e))},r._executeCardOpen=function(t){r._async.clearTimeout(r._openTimerId),r._openTimerId=r._async.setTimeout(function(){r.setState(function(e){return e.isHoverCardVisible?e:{isHoverCardVisible:!0,mode:oS.compact,openMode:"keydown"===t.type?Q_.hotKey:Q_.hover}})},r.props.cardOpenDelay)},r._cardDismiss=function(e,t){e?t instanceof MouseEvent&&("keydown"===t.type&&t.which!==En.escape\|\|r.props.sticky\|\|r._currentMouseTarget!==t.currentTarget&&t.which!==En.escape\|\|r.dismiss(!0)):r.props.sticky&&!(t instanceof MouseEvent)&&t.nativeEvent instanceof MouseEvent&&"mouseleave"===t.type\|\|r.dismiss(!0)},r._setDismissedState=function(){r.setState({isHoverCardVisible:!1,mode:oS.compact,openMode:Q_.hover})},r._instantOpenAsExpanded=function(e){r._async.clearTimeout(r._dismissTimerId),r.setState(function(e){return e.isHoverCardVisible?e:{isHoverCardVisible:!0,mode:oS.expanded}})},r._setEventListeners=function(){var e=r.props,t=e.trapFocus,o=e.instantOpenOnClick,n=e.eventListenerTarget,e=n?r._getTargetElement(n):r._getTargetElement(r.props.target),n=r._nativeDismissEvent;e&&(r._events.on(e,"mouseenter",r._cardOpen),r._events.on(e,"mouseleave",n),t?r._events.on(e,"keydown",r._cardOpen):(r._events.on(e,"focus",r._cardOpen),r._events.on(e,"blur",n)),o?r._events.on(e,"click",r._instantOpenAsExpanded):(r._events.on(e,"mousedown",n),r._events.on(e,"keydown",n)))},fi(r),r._async=new Si(r),r._events=new va(r),r._nativeDismissEvent=r._cardDismiss.bind(r,!0),r._childDismissEvent=r._cardDismiss.bind(r,!1),r.state={isHoverCardVisible:!1,mode:oS.compact,openMode:Q_.hover},r}function yS(e){var t=sS.call(this,e)\|\|this;return t._onKeyDown=function(e){e.which===En.escape&&t.props.onLeave&&t.props.onLeave(e)},fi(t),t}function CS(e){var t=aS.call(this,e)\|\|this;return t._expandedElem=gt.createRef(),t._onKeyDown=function(e){e.which===En.escape&&t.props.onLeave&&t.props.onLeave(e)},t._onRenderCompactCard=function(){return gt.createElement("div",{className:t._classNames.compactCard},t.props.onRenderCompactCard(t.props.renderData))},t._onRenderExpandedCard=function(){return t.state.firstFrameRendered\|\|t._async.requestAnimationFrame(function(){t.setState({firstFrameRendered:!0})}),gt.createElement("div",{className:t._classNames.expandedCard,ref:t._expandedElem},gt.createElement("div",{className:t._classNames.expandedCardScroll},t.props.onRenderExpandedCard&&t.props.onRenderExpandedCard(t.props.renderData)))},t._checkNeedsScroll=function(){var e=t.props.expandedCardHeight;t._async.requestAnimationFrame(function(){t._expandedElem.current&&t._expandedElem.current.scrollHeight>=e&&t.setState({needsScroll:!0})})},t._async=new Si(t),fi(t),t.state={firstFrameRendered:!1,needsScroll:!1},t}function _S(e,t){en({style:{MozOsxFontSmoothing:"grayscale",WebkitFontSmoothing:"antialiased",fontStyle:"normal",fontWeight:"normal",speak:"none"},fontFace:{fontFamily:'"FabricMDL2Icons"',src:"url('"+(e=void 0===e?"":e)+"fabric-icons-a13498cf.woff') 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0===t&&(t="https://spoppe-b.azureedge.net/files/fabric-cdn-prod_20210407.001/assets/icons/"),[_S,SS,xS,kS,wS,IS,DS,ES,TS,PS,RS,MS,NS,BS,FS,AS,LS,HS,OS].forEach(function(e){return e(t,o)}),on("trash","delete"),on("onedrive","onedrivelogo"),on("alertsolid12","eventdatemissed12"),on("sixpointstar","6pointstar"),on("twelvepointstar","12pointstar"),on("toggleon","toggleleft"),on("toggleoff","toggleright")}function WS(e){e=ft().querySelectorAll(e);return Array.from(e).find(ls)}fn("@fluentui/font-icons-mdl2","8.1.21");function VS(e){return{container:[],root:[{border:"none",boxShadow:"none"}],beak:[],beakCurtain:[],calloutMain:[{backgroundColor:"transparent"}]}}var KS,GS,V=(l(YS,GS=gt.Component),YS.prototype.render=function(){var e=this.props,t=e.content,o=e.styles,n=e.theme,r=e.disabled,e=e.visible,e=Fn()(o,{theme:n,disabled:r,visible:e});return gt.createElement("div",{className:e.container},gt.createElement("span",{className:e.root},t))},YS),US=In(V,function(e){var t=e.theme,o=e.disabled,n=e.visible;return{container:[{backgroundColor:t.palette.neutralDark},o&&{opacity:.5,selectors:((e={})[Yt]={color:"GrayText",opacity:1},e)},!n&&{visibility:"hidden"}],root:[t.fonts.medium,{textAlign:"center",paddingLeft:"3px",paddingRight:"3px",backgroundColor:t.palette.neutralDark,color:t.palette.neutralLight,minWidth:"11px",lineHeight:"17px",height:"17px",display:"inline-block"},o&&{color:t.palette.neutralTertiaryAlt}]}},void 0,{scope:"KeytipContent"}),jS=(l(qS,KS=gt.Component),qS.prototype.render=function(){var t,e=this.props,o=e.keySequences,n=e.offset,r=e.overflowSetSequence,e=this.props.calloutProps,o=WS(Kc(r?Vc(o,r):o));return o?(r=o,(e=n?ht(ht({},e),{coverTarget:!0,directionalHint:Pa.topLeftEdge}):e)&&void 0!==e.directionalHint\|\|(e=ht(ht({},e),{directionalHint:Pa.bottomCenter})),gt.createElement(ac,ht({},e,{isBeakVisible:!1,doNotLayer:!0,minPagePadding:0,styles:n?(t=n,function(e){return pn({container:[],root:[{border:"none",boxShadow:"none"}],beak:[],beakCurtain:[],calloutMain:[{backgroundColor:"transparent"}]},{root:[{marginLeft:t.left\|\|t.x,marginTop:t.top\|\|t.y}]})}):VS,preventDismissOnScroll:!0,target:r}),gt.createElement(US,ht({},this.props)))):gt.createElement(gt.Fragment,null)},qS);function qS(){return null!==KS&&KS.apply(this,arguments)\|\|this}function YS(){return null!==GS&&GS.apply(this,arguments)\|\|this}function ZS(e){var e=jc(e),n=e.keytipId,r=e.ariaDescribedBy;return gt.useCallback(function(e){var t,o;e&&(t=QS(e,Rc)\|\|e,o=QS(e,Mc)\|\|t,e=QS(e,Nc)\|\|o,XS(t,Rc,n),XS(o,Mc,n),XS(e,"aria-describedby",r,!0))},[n,r])}function XS(e,t,o,n){var r;void 0===n&&(n=!1),e&&o&&(r=o,!n\|\|(n=e.getAttribute(t))&&-1===n.indexOf(o)&&(r=n+" "+o),e.setAttribute(t,r))}function QS(e,t){return e.querySelector("["+t+"]")}function JS(e){return{root:[{zIndex:mo.KeytipLayer}]}}var $S=(ex.prototype.addNode=function(e,t,o){var n=this._getFullSequence(e),r=Wc(n);n.pop();n=this._getParentID(n),o=this._createNode(r,n,[],e,o);this.nodeMap[t]=o,this.getNodes([n]).forEach(function(e){return e.children.push(r)})},ex.prototype.updateNode=function(e,t){var o=this._getFullSequence(e),n=Wc(o);o.pop();var o=this._getParentID(o),r=this.nodeMap[t],t=r.parent;r&&(t!==o&&this._removeChildFromParents(t,r.id),r.id!==n&&this.getNodes([o]).forEach(function(e){var t=e.children.indexOf(r.id);0<=t?e.children[t]=n:e.children.push(n)}),r.id=n,r.keySequences=e.keySequences,r.overflowSetSequence=e.overflowSetSequence,r.onExecute=e.onExecute,r.onReturn=e.onReturn,r.hasDynamicChildren=e.hasDynamicChildren,r.hasMenu=e.hasMenu,r.parent=o,r.disabled=e.disabled)},ex.prototype.removeNode=function(e,t){var o=this._getFullSequence(e),e=Wc(o);o.pop(),this._removeChildFromParents(this._getParentID(o),e),this.nodeMap[t]&&delete this.nodeMap[t]},ex.prototype.getExactMatchedNode=function(t,e){var o=this,n=this.getNodes(e.children).filter(function(e){return o._getNodeSequence(e)===t&&!e.disabled});if(0!==n.length){var r=n[0];if(1===n.length)return r;var i=r.keySequences,e=r.overflowSetSequence,i=Kc(e?Vc(i,e):i),i=document.querySelectorAll(i);if(n.length<i.length)return r;i=Array.from(i).findIndex(ls);return-1!==i?n[i]:n.find(function(e){return e.hasOverflowSubMenu})\|\|r}},ex.prototype.getPartiallyMatchedNodes=function(t,e){var o=this;return this.getNodes(e.children).filter(function(e){return 0===o._getNodeSequence(e).indexOf(t)&&!e.disabled})},ex.prototype.getChildren=function(e){var o=this;if(!e&&!(e=this.currentKeytip))return[];var n=e.children;return Object.keys(this.nodeMap).reduce(function(e,t){return 0<=n.indexOf(o.nodeMap[t].id)&&!o.nodeMap[t].persisted&&e.push(o.nodeMap[t].id),e},[])},ex.prototype.getNodes=function(o){var n=this;return Object.keys(this.nodeMap).reduce(function(e,t){return 0<=o.indexOf(n.nodeMap[t].id)&&e.push(n.nodeMap[t]),e},[])},ex.prototype.getNode=function(t){return Oi(ga(this.nodeMap),function(e){return e.id===t})},ex.prototype.isCurrentKeytipParent=function(e){if(this.currentKeytip){var t=$e([],e.keySequences);(t=e.overflowSetSequence?Vc(t,e.overflowSetSequence):t).pop();e=0===t.length?this.root.id:Wc(t),t=!1;return(t=this.currentKeytip.overflowSetSequence?Wc(this.currentKeytip.keySequences)===e:t)\|\|this.currentKeytip.id===e}return!1},ex.prototype._getParentID=function(e){return 0===e.length?this.root.id:Wc(e)},ex.prototype._getFullSequence=function(e){var t=$e([],e.keySequences);return t=e.overflowSetSequence?Vc(t,e.overflowSetSequence):t},ex.prototype._getNodeSequence=function(e){var t=$e([],e.keySequences);return(t=e.overflowSetSequence?Vc(t,e.overflowSetSequence):t)[t.length-1]},ex.prototype._createNode=function(o,e,t,n,r){var i=this,s=n.keySequences,a=n.hasDynamicChildren,l=n.overflowSetSequence,c=n.hasMenu,u=n.onExecute,d=n.onReturn,p=n.disabled,n=n.hasOverflowSubMenu,n={id:o,keySequences:s,overflowSetSequence:l,parent:e,children:t,onExecute:u,onReturn:d,hasDynamicChildren:a,hasMenu:c,disabled:p,persisted:r,hasOverflowSubMenu:n};return n.children=Object.keys(this.nodeMap).reduce(function(e,t){return i.nodeMap[t].parent===o&&e.push(i.nodeMap[t].id),e},[]),n},ex.prototype._removeChildFromParents=function(e,o){this.getNodes([e]).forEach(function(e){var t=e.children.indexOf(o);0<=t&&e.children.splice(t,1)})},ex);function ex(){this.nodeMap={},this.root={id:Bc,children:[],parent:"",keySequences:[]},this.nodeMap[this.root.id]=this.root}function tx(e,t){if(e.key!==t.key)return!1;var o=e.modifierKeys,n=t.modifierKeys;if(!o&&n\|\|o&&!n)return!1;if(o&&n){if(o.length!==n.length)return!1;for(var o=o.sort(),n=n.sort(),r=0;r<o.length;r++)if(o[r]!==n[r])return!1}return!0}function ox(e,t){return!!Oi(e,function(e){return tx(e,t)})}var nx,Y={key:Na()?"Control":"Meta",modifierKeys:[En.alt]},ke=Y,n={key:"Escape"},rx=Fn(),ix=(l(ax,nx=gt.Component),ax.prototype.render=function(){var o=this,e=this.props,t=e.content,n=e.styles,r=this.state,e=r.keytips,r=r.visibleKeytips;return this._classNames=rx(n,{}),gt.createElement(sc,{styles:JS},gt.createElement("span",{id:Bc,className:this._classNames.innerContent},""+t+Fc),e&&e.map(function(e,t){return gt.createElement("span",{key:t,id:Wc(e.keySequences),className:o._classNames.innerContent},e.keySequences.join(Fc))}),r&&r.map(function(e){return gt.createElement(jS,ht({key:Wc(e.keySequences)},e))}))},ax.prototype.componentDidMount=function(){this._events.on(window,"mouseup",this._onDismiss,!0),this._events.on(window,"pointerup",this._onDismiss,!0),this._events.on(window,"resize",this._onDismiss),this._events.on(window,"keydown",this._onKeyDown,!0),this._events.on(window,"keypress",this._onKeyPress,!0),this._events.on(window,"scroll",this._onDismiss,!0),this._events.on(this._keytipManager,gc.ENTER_KEYTIP_MODE,this._enterKeytipMode),this._events.on(this._keytipManager,gc.EXIT_KEYTIP_MODE,this._exitKeytipMode)},ax.prototype.componentWillUnmount=function(){this._async.dispose(),this._events.dispose()},ax.prototype.getCurrentSequence=function(){return this._currentSequence},ax.prototype.getKeytipTree=function(){return this._keytipTree},ax.prototype.processTransitionInput=function(e,t){var o=this._keytipTree.currentKeytip;ox(this.props.keytipExitSequences,e)&&o?(this._keyHandled=!0,this._exitKeytipMode(t)):ox(this.props.keytipReturnSequences,e)?o&&(this._keyHandled=!0,o.id===this._keytipTree.root.id?this._exitKeytipMode(t):(o.onReturn&&o.onReturn(this._getKtpExecuteTarget(o),this._getKtpTarget(o)),this._currentSequence="",this._keytipTree.currentKeytip=this._keytipTree.getNode(o.parent),this.showKeytips(this._keytipTree.getChildren()),this._warnIfDuplicateKeytips())):ox(this.props.keytipStartSequences,e)&&!o&&(this._keyHandled=!0,this._enterKeytipMode(e),this._warnIfDuplicateKeytips())},ax.prototype.processInput=function(e,t){var o=this._currentSequence+e,n=this._keytipTree.currentKeytip;if(n){e=this._keytipTree.getExactMatchedNode(o,n);if(e){this._keytipTree.currentKeytip=n=e;e=this._keytipTree.getChildren();return n.onExecute&&(n.onExecute(this._getKtpExecuteTarget(n),this._getKtpTarget(n)),n=this._keytipTree.currentKeytip),0!==e.length\|\|n.hasDynamicChildren\|\|n.hasMenu?(this.showKeytips(e),this._warnIfDuplicateKeytips()):this._exitKeytipMode(t),void(this._currentSequence="")}n=this._keytipTree.getPartiallyMatchedNodes(o,n);0<n.length&&(n=n.filter(function(e){return!e.persisted}).map(function(e){return e.id}),this.showKeytips(n),this._currentSequence=o)}},ax.prototype.showKeytips=function(e){for(var t=0,o=this._keytipManager.getKeytips();t<o.length;t++){var n=o[t],r=Wc(n.keySequences);n.overflowSetSequence&&(r=Wc(Vc(n.keySequences,n.overflowSetSequence))),0<=e.indexOf(r)?n.visible=!0:n.visible=!1}this._setKeytips()},ax.prototype._enterKeytipMode=function(e){this._keytipManager.shouldEnterKeytipMode&&(this._keytipManager.delayUpdatingKeytipChange&&(this._buildTree(),this._setKeytips()),this._keytipTree.currentKeytip=this._keytipTree.root,this.showKeytips(this._keytipTree.getChildren()),this._setInKeytipMode(!0),this.props.onEnterKeytipMode&&this.props.onEnterKeytipMode(e))},ax.prototype._buildTree=function(){this._keytipTree=new $S;for(var e=0,t=Object.keys(this._keytipManager.keytips);e<t.length;e++){var o=t[e],n=this._keytipManager.keytips[o];this._keytipTree.addNode(n.keytip,n.uniqueID)}for(var r=0,i=Object.keys(this._keytipManager.persistedKeytips);r<i.length;r++)o=i[r],n=this._keytipManager.persistedKeytips[o],this._keytipTree.addNode(n.keytip,n.uniqueID)},ax.prototype._exitKeytipMode=function(e){this._keytipTree.currentKeytip=void 0,this._currentSequence="",this.showKeytips([]),this._delayedQueueTimeout&&this._async.clearTimeout(this._delayedQueueTimeout),this._delayedKeytipQueue=[],this._setInKeytipMode(!1),this.props.onExitKeytipMode&&this.props.onExitKeytipMode(e)},ax.prototype._setKeytips=function(e){void 0===e&&(e=this._keytipManager.getKeytips()),this.setState({keytips:e,visibleKeytips:this._getVisibleKeytips(e)})},ax.prototype._persistedKeytipExecute=function(e,t){this._newCurrentKeytipSequences=t;e=this._keytipTree.getNode(Wc(e));e&&e.onExecute&&e.onExecute(this._getKtpExecuteTarget(e),this._getKtpTarget(e))},ax.prototype._getVisibleKeytips=function(e){var o={};return e.filter(function(e){var t=Wc(e.keySequences);return e.overflowSetSequence&&(t=Wc(Vc(e.keySequences,e.overflowSetSequence))),o[t]=o[t]?o[t]+1:1,e.visible&&1===o[t]})},ax.prototype._getModifierKey=function(e,t){var o=[];return t.altKey&&"Alt"!==e&&o.push(En.alt),t.ctrlKey&&"Control"!==e&&o.push(En.ctrl),t.shiftKey&&"Shift"!==e&&o.push(En.shift),t.metaKey&&"Meta"!==e&&o.push(En.leftWindow),o.length?o:void 0},ax.prototype._triggerKeytipImmediately=function(e){var t=$e([],e.keySequences);e.overflowSetSequence&&(t=Vc(t,e.overflowSetSequence)),this._keytipTree.currentKeytip=this._keytipTree.getNode(Wc(t)),this._keytipTree.currentKeytip&&((t=this._keytipTree.getChildren()).length&&this.showKeytips(t),this._keytipTree.currentKeytip.onExecute&&this._keytipTree.currentKeytip.onExecute(this._getKtpExecuteTarget(this._keytipTree.currentKeytip),this._getKtpTarget(this._keytipTree.currentKeytip))),this._newCurrentKeytipSequences=void 0},ax.prototype._addKeytipToQueue=function(e){var t=this;this._delayedKeytipQueue.push(e),this._delayedQueueTimeout&&this._async.clearTimeout(this._delayedQueueTimeout),this._delayedQueueTimeout=this._async.setTimeout(function(){t._delayedKeytipQueue.length&&(t.showKeytips(t._delayedKeytipQueue),t._delayedKeytipQueue=[])},300)},ax.prototype._removeKeytipFromQueue=function(e){var t=this,e=this._delayedKeytipQueue.indexOf(e);0<=e&&(this._delayedKeytipQueue.splice(e,1),this._delayedQueueTimeout&&this._async.clearTimeout(this._delayedQueueTimeout),this._delayedQueueTimeout=this._async.setTimeout(function(){t._delayedKeytipQueue.length&&(t.showKeytips(t._delayedKeytipQueue),t._delayedKeytipQueue=[])},300))},ax.prototype._getKtpExecuteTarget=function(e){return ft().querySelector(Gc(e.id))},ax.prototype._getKtpTarget=function(e){return ft().querySelector(Kc(e.keySequences))},ax.prototype._isCurrentKeytipAnAlias=function(e){var t=this._keytipTree.currentKeytip;return!(!t\|\|!t.overflowSetSequence&&!t.persisted\|\|!ji(e.keySequences,t.keySequences))},ax.defaultProps={keytipStartSequences:[Y],keytipExitSequences:[ke],keytipReturnSequences:[n],content:""},ax),sx=In(ix,function(e){return{innerContent:[{position:"absolute",width:0,height:0,margin:0,padding:0,border:0,overflow:"hidden",visibility:"hidden"}]}},void 0,{scope:"KeytipLayer"});function ax(e,t){var n=nx.call(this,e,t)\|\|this;n._keytipManager=Oc.getInstance(),n._delayedKeytipQueue=[],n._keyHandled=!1,n._onDismiss=function(e){n.state.inKeytipMode&&n._exitKeytipMode(e)},n._onKeyDown=function(e){n._keyHandled=!1;var t=e.key;switch(t){case"Tab":case"Enter":case"Spacebar":case" ":case"ArrowUp":case"Up":case"ArrowDown":case"Down":case"ArrowLeft":case"Left":case"ArrowRight":case"Right":n.state.inKeytipMode&&(n._keyHandled=!0,n._exitKeytipMode(e));break;default:"Esc"===t?t="Escape":"OS"!==t&&"Win"!==t\|\|(t="Meta");var o={key:t};o.modifierKeys=n._getModifierKey(t,e),n.processTransitionInput(o,e)}},n._onKeyPress=function(e){n.state.inKeytipMode&&!n._keyHandled&&(n.processInput(e.key.toLocaleLowerCase(),e),e.preventDefault(),e.stopPropagation())},n._onKeytipAdded=function(e){var t,o=e.keytip,e=e.uniqueID;n._keytipTree.addNode(o,e),n._setKeytips(),n._keytipTree.isCurrentKeytipParent(o)&&(n._delayedKeytipQueue=n._delayedKeytipQueue.concat((null===(e=n._keytipTree.currentKeytip)\|\|void 0===e?void 0:e.children)\|\|[]),n._addKeytipToQueue(Wc(o.keySequences)),n._keytipTree.currentKeytip&&n._keytipTree.currentKeytip.hasDynamicChildren&&n._keytipTree.currentKeytip.children.indexOf(o.id)<0)&&(t=n._keytipTree.getNode(n._keytipTree.currentKeytip.id))&&(n._keytipTree.currentKeytip=t),n._persistedKeytipChecks(o)},n._onKeytipUpdated=function(e){var t=e.keytip,e=e.uniqueID;n._keytipTree.updateNode(t,e),n._setKeytips(),n._keytipTree.isCurrentKeytipParent(t)&&(n._delayedKeytipQueue=n._delayedKeytipQueue.concat((null===(e=n._keytipTree.currentKeytip)\|\|void 0===e?void 0:e.children)\|\|[]),n._addKeytipToQueue(Wc(t.keySequences))),n._persistedKeytipChecks(t)},n._persistedKeytipChecks=function(e){var t;n._newCurrentKeytipSequences&&ji(e.keySequences,n._newCurrentKeytipSequences)&&n._triggerKeytipImmediately(e),n._isCurrentKeytipAnAlias(e)&&(t=e.keySequences,e.overflowSetSequence&&(t=Vc(t,e.overflowSetSequence)),n._keytipTree.currentKeytip=n._keytipTree.getNode(Wc(t)))},n._onKeytipRemoved=function(e){var t=e.keytip,e=e.uniqueID;n._removeKeytipFromQueue(Wc(t.keySequences)),n._keytipTree.removeNode(t,e),n._setKeytips()},n._onPersistedKeytipAdded=function(e){var t=e.keytip,e=e.uniqueID;n._keytipTree.addNode(t,e,!0)},n._onPersistedKeytipRemoved=function(e){var t=e.keytip,e=e.uniqueID;n._keytipTree.removeNode(t,e)},n._onPersistedKeytipExecute=function(e){n._persistedKeytipExecute(e.overflowButtonSequences,e.keytipSequences)},n._setInKeytipMode=function(e){n.setState({inKeytipMode:e}),n._keytipManager.inKeytipMode=e},n._warnIfDuplicateKeytips=function(){var e=n._getDuplicateIds(n._keytipTree.getChildren());e.length&&Xo("Duplicate keytips found for "+e.join(", "))},n._getDuplicateIds=function(e){var t={};return e.filter(function(e){return t[e]=t[e]?t[e]+1:1,2===t[e]})},fi(n),n._events=new va(n),n._async=new Si(n);t=n._keytipManager.getKeytips();return n.state={inKeytipMode:!1,keytips:t,visibleKeytips:n._getVisibleKeytips(t)},n._buildTree(),n._currentSequence="",n._events.on(n._keytipManager,gc.KEYTIP_ADDED,n._onKeytipAdded),n._events.on(n._keytipManager,gc.KEYTIP_UPDATED,n._onKeytipUpdated),n._events.on(n._keytipManager,gc.KEYTIP_REMOVED,n._onKeytipRemoved),n._events.on(n._keytipManager,gc.PERSISTED_KEYTIP_ADDED,n._onPersistedKeytipAdded),n._events.on(n._keytipManager,gc.PERSISTED_KEYTIP_REMOVED,n._onPersistedKeytipRemoved),n._events.on(n._keytipManager,gc.PERSISTED_KEYTIP_EXECUTE,n._onPersistedKeytipExecute),n}function lx(e){for(var t={},o=0,n=e.keytips;o<n.length;o++)cx(t,[],n[o]);return t}function cx(e,t,o){var n=o.sequence\|\|o.content.toLocaleLowerCase(),r=t.concat(n),n=ht(ht({},o.optionalProps),{keySequences:r,content:o.content});if(e[o.id]=n,o.children)for(var i=0,s=o.children;i<s.length;i++)cx(e,r,s[i])}fn("@fluentui/react","8.52.2");var ux=function(e){var t=e.id,o=e.className;return gt.useEffect(function(){ec(t)},[]),dx(function(){ec(t)}),gt.createElement("div",ht({},e,{className:Tr("ms-LayerHost",o)}))},dx=function(e){var t=gt.useRef(e);t.current=e,gt.useEffect(function(){return function(){t.current&&t.current()}},[])},px=(hx.prototype.dispose=function(){this._events.dispose(),this._stopScroll()},hx.prototype._onMouseMove=function(e){this._computeScrollVelocity(e)},hx.prototype._onTouchMove=function(e){0<e.touches.length&&this._computeScrollVelocity(e)},hx.prototype._computeScrollVelocity=function(e){var t,o,n,r,i,s,a,l;this._scrollRect&&(o="clientX"in e?(t=e.clientX,e.clientY):(t=e.touches[0].clientX,e.touches[0].clientY),s=this._scrollRect.top,a=this._scrollRect.left,l=s+this._scrollRect.height-100,e=a+this._scrollRect.width-100,o<s+100\|\|l<o?(r=o,n=s,i=l,this._isVerticalScroll=!0):(r=t,n=a,i=e,this._isVerticalScroll=!1),this._scrollVelocity=r<n+100?Math.max(-15,(100-(r-n))/100-15):i<r?Math.min(15,(r-i)/10015):0,this._scrollVelocity?this._startScroll():this._stopScroll())},hx.prototype._startScroll=function(){this._timeoutId\|\|this._incrementScroll()},hx.prototype._incrementScroll=function(){this._scrollableParent&&(this._isVerticalScroll?this._scrollableParent.scrollTop+=Math.round(this._scrollVelocity):this._scrollableParent.scrollLeft+=Math.round(this._scrollVelocity)),this._timeoutId=setTimeout(this._incrementScroll,16)},hx.prototype._stopScroll=function(){this._timeoutId&&(clearTimeout(this._timeoutId),delete this._timeoutId)},hx);function hx(e){this._events=new va(this),this._scrollableParent=Ns(e),this._incrementScroll=this._incrementScroll.bind(this),this._scrollRect=t0(this._scrollableParent),this._scrollableParent===window&&(this._scrollableParent=document.body),this._scrollableParent&&(this._events.on(window,"mousemove",this._onMouseMove,!0),this._events.on(window,"touchmove",this._onTouchMove,!0))}function mx(e,t){var o=e.left\|\|e.x\|\|0,n=e.top\|\|e.y\|\|0,e=t.left\|\|t.x\|\|0,t=t.top\|\|t.y\|\|0;return Math.sqrt(Math.pow(o-e,2)+Math.pow(n-t,2))}function gx(e){var t=e.contentSize,o=e.boundsSize,n=e.mode,r=e.maxScale,i=t.width/t.height,e=o.width/o.height,o=("contain"===(void 0===n?"contain":n)?e<i:i<e)?o.width/t.width:o.height/t.height,o=Math.min(void 0===r?1:r,o);return{width:t.widtho,height:t.heighto}}function fx(e){e=/[1-9]([0]+$)\|\.([0-9])/.exec(String(e));return e?e[1]?-e[1].length:e[2]?e[2].length:0:0}function vx(e,t,o){void 0===o&&(o=10);t=Math.pow(o,t);return Math.round(et)/t}var bx,yx,Cx=Fn(),_x=In((l(Sx,yx=gt.Component),Sx.prototype.componentDidMount=function(){this._scrollableParent=Ns(this._root.current),this._scrollableSurface=this._scrollableParent===window?document.body:this._scrollableParent;var e=this.props.isDraggingConstrainedToRoot?this._root.current:this._scrollableSurface;this._events.on(e,"mousedown",this._onMouseDown),this._events.on(e,"touchstart",this._onTouchStart,!0),this._events.on(e,"pointerdown",this._onPointerDown,!0)},Sx.prototype.componentWillUnmount=function(){this._autoScroll&&this._autoScroll.dispose(),delete this._scrollableParent,delete this._scrollableSurface,this._events.dispose(),this._async.dispose()},Sx.prototype.render=function(){var e=this.props,t=e.rootProps,o=e.children,n=e.theme,r=e.className,i=e.styles,e=this.state.dragRect,r=Cx(i,{theme:n,className:r});return gt.createElement("div",ht({},t,{className:r.root,ref:this._root}),o,e&&gt.createElement("div",{className:r.dragMask}),e&&gt.createElement("div",{className:r.box,style:e},gt.createElement("div",{className:r.boxFill})))},Sx.prototype._isMouseEventOnScrollbar=function(e){var t=e.target,o=t.offsetWidth-t.clientWidth,n=t.offsetHeight-t.clientHeight;if(o\|\|n){n=t.getBoundingClientRect();if(Pn(this.props.theme)){if(e.clientX<n.left+o)return!0}else if(e.clientX>n.left+t.clientWidth)return!0;if(e.clientY>n.top+t.clientHeight)return!0}return!1},Sx.prototype._getRootRect=function(){return{left:this._rootRect.left+(this._scrollableSurface?this._scrollLeft-this._scrollableSurface.scrollLeft:this._scrollLeft),top:this._rootRect.top+(this._scrollableSurface?this._scrollTop-this._scrollableSurface.scrollTop:this._scrollTop),width:this._rootRect.width,height:this._rootRect.height}},Sx.prototype._onAsyncMouseMove=function(e){var t=this;this._async.requestAnimationFrame(function(){t._onMouseMove(e)}),e.stopPropagation(),e.preventDefault()},Sx.prototype._onMouseMove=function(e){if(this._autoScroll){void 0!==e.clientX&&(this._lastMouseEvent=e);var t,o=this._getRootRect(),n={left:e.clientX-o.left,top:e.clientY-o.top};return this._dragOrigin\|\|(this._dragOrigin=n),void 0!==e.buttons&&0===e.buttons?this._onMouseUp(e):(this.state.dragRect\|\|5<mx(this._dragOrigin,n))&&(this.state.dragRect\|\|(t=this.props.selection,e.shiftKey\|\|t.setAllSelected(!1),this._preservedIndicies=t&&t.getSelectedIndices&&t.getSelectedIndices()),t=this.props.isDraggingConstrainedToRoot?{left:Math.max(0,Math.min(o.width,this._lastMouseEvent.clientX-o.left)),top:Math.max(0,Math.min(o.height,this._lastMouseEvent.clientY-o.top))}:{left:this._lastMouseEvent.clientX-o.left,top:this._lastMouseEvent.clientY-o.top},t={left:Math.min(this._dragOrigin.left\|\|0,t.left),top:Math.min(this._dragOrigin.top\|\|0,t.top),width:Math.abs(t.left-(this._dragOrigin.left\|\|0)),height:Math.abs(t.top-(this._dragOrigin.top\|\|0))},this._evaluateSelection(t,o),this.setState({dragRect:t})),!1}},Sx.prototype._onMouseUp=function(e){this._events.off(window),this._events.off(this._scrollableParent,"scroll"),this._autoScroll&&this._autoScroll.dispose(),this._autoScroll=this._dragOrigin=this._lastMouseEvent=void 0,this._selectedIndicies=this._itemRectCache=void 0,this.state.dragRect&&(this.setState({dragRect:void 0}),e.preventDefault(),e.stopPropagation())},Sx.prototype._isPointInRectangle=function(e,t){return!!t.top&&e.top<t.top&&e.bottom>t.top&&!!t.left&&e.left<t.left&&e.right>t.left},Sx.prototype._isDragStartInSelection=function(e){var t=this.props.selection;if(!this._root.current\|\|t&&0===t.getSelectedCount())return!1;for(var o=this._root.current.querySelectorAll("[data-selection-index]"),n=0;n<o.length;n++){var r=o[n],i=Number(r.getAttribute("data-selection-index"));if(t.isIndexSelected(i)){r=r.getBoundingClientRect();if(this._isPointInRectangle(r,{left:e.clientX,top:e.clientY}))return!0}}return!1},Sx.prototype._isInSelectionToggle=function(e){for(var t=e.target;t&&t!==this._root.current;){if("true"===t.getAttribute("data-selection-toggle"))return!0;t=t.parentElement}return!1},Sx.prototype._evaluateSelection=function(e,t){if(e&&this._root.current){var o=this.props.selection,n=this._root.current.querySelectorAll("[data-selection-index]");this._itemRectCache\|\|(this._itemRectCache={});for(var r=0;r<n.length;r++){var i=n[r],s=i.getAttribute("data-selection-index"),a=this._itemRectCache[s];a\|\|0<(a={left:(a=i.getBoundingClientRect()).left-t.left,top:a.top-t.top,width:a.width,height:a.height,right:a.left-t.left+a.width,bottom:a.top-t.top+a.height}).width&&0<a.height&&(this._itemRectCache[s]=a),a.top<e.top+e.height&&a.bottom>e.top&&a.left<e.left+e.width&&a.right>e.left?this._selectedIndicies[s]=!0:delete this._selectedIndicies[s]}var l=this._allSelectedIndices\|\|{};for(s in this._allSelectedIndices={},this._selectedIndicies)this._selectedIndicies.hasOwnProperty(s)&&(this._allSelectedIndices[s]=!0);if(this._preservedIndicies)for(var c=0,u=this._preservedIndicies;c<u.length;c++)s=u[c],this._allSelectedIndices[s]=!0;var d=!1;for(s in this._allSelectedIndices)if(this._allSelectedIndices[s]!==l[s]){d=!0;break}if(!d)for(var s in l)if(this._allSelectedIndices[s]!==l[s]){d=!0;break}if(d){o.setChangeEvents(!1),o.setAllSelected(!1);for(var p=0,h=Object.keys(this._allSelectedIndices);p<h.length;p++)s=h[p],o.setIndexSelected(Number(s),!0,!1);o.setChangeEvents(!0)}}},Sx.defaultProps={rootTagName:"div",rootProps:{},isEnabled:!0},Sx),function(e){var t=e.theme,e=e.className,t=t.palette;return{root:[e,{position:"relative",cursor:"default"}],dragMask:[{position:"absolute",background:"rgba(255, 0, 0, 0)",left:0,top:0,right:0,bottom:0,selectors:((e={})[Yt]={background:"none",backgroundColor:"transparent"},e)}],box:[{position:"absolute",boxSizing:"border-box",border:"1px solid "+t.themePrimary,pointerEvents:"none",zIndex:10,selectors:((e={})[Yt]={borderColor:"Highlight"},e)}],boxFill:[{position:"absolute",boxSizing:"border-box",backgroundColor:t.themePrimary,opacity:.1,left:0,top:0,right:0,bottom:0,selectors:((t={})[Yt]={background:"none",backgroundColor:"transparent"},t)}]}},void 0,{scope:"MarqueeSelection"});function Sx(e){var n=yx.call(this,e)\|\|this;return n._root=gt.createRef(),n._onMouseDown=function(e){var t=n.props,o=t.isEnabled,t=t.onShouldStartSelection;n._isMouseEventOnScrollbar(e)\|\|n._isInSelectionToggle(e)\|\|n._isTouch\|\|!o\|\|n._isDragStartInSelection(e)\|\|t&&!t(e)\|\|n._scrollableSurface&&0===e.button&&n._root.current&&(n._selectedIndicies={},n._preservedIndicies=void 0,n._events.on(window,"mousemove",n._onAsyncMouseMove,!0),n._events.on(n._scrollableParent,"scroll",n._onAsyncMouseMove),n._events.on(window,"click",n._onMouseUp,!0),n._autoScroll=new px(n._root.current),n._scrollTop=n._scrollableSurface.scrollTop,n._scrollLeft=n._scrollableSurface.scrollLeft,n._rootRect=n._root.current.getBoundingClientRect(),n._onMouseMove(e))},n._onTouchStart=function(e){n._isTouch=!0,n._async.setTimeout(function(){n._isTouch=!1},0)},n._onPointerDown=function(e){"touch"===e.pointerType&&(n._isTouch=!0,n._async.setTimeout(function(){n._isTouch=!1},0))},fi(n),n._async=new Si(n),n._events=new va(n),n.state={dragRect:void 0},n}(r=bx=bx\|\|{})[r.info=0]="info",r[r.error=1]="error",r[r.blocked=2]="blocked",r[r.severeWarning=3]="severeWarning",r[r.success=4]="success",r[r.warning=5]="warning";var xx=((K={})[bx.info]="Info",K[bx.warning]="Info",K[bx.error]="ErrorBadge",K[bx.blocked]="Blocked2",K[bx.severeWarning]="Warning",K[bx.success]="Completed",K),kx=Fn(),wx=gt.forwardRef(function(e,t){var o=E0(!1),n=o[0],r=o[1].toggle,i=iu("MessageBar"),s=e.actions,a=e.className,l=e.children,c=e.overflowButtonAriaLabel,u=e.dismissIconProps,d=e.styles,p=e.theme,h=e.messageBarType,m=void 0===h?bx.info:h,g=e.onDismiss,f=void 0===g?void 0:g,v=e.isMultiline,b=void 0===v\|\|v,y=e.truncated,C=e.dismissButtonAriaLabel,o=e.messageBarIconProps,h=e.role,g=e.delayedRender,v=void 0===g\|\|g,g=e.expandButtonProps,e=ur(e,Wn,["className","role"]),d=kx(d,{theme:p,messageBarType:m\|\|bx.info,onDismiss:void 0!==f,actions:void 0!==s,truncated:y,isMultiline:b,expandSingleLine:n,className:a}),p={iconName:n?"DoubleChevronUp":"DoubleChevronDown"},a=s\|\|f?{"aria-describedby":i,role:"region"}:{},s=s?gt.createElement("div",{className:d.actions},s):null,C=f?gt.createElement(rd,{disabled:!1,className:d.dismissal,onClick:f,iconProps:u\|\|{iconName:"Clear"},title:C,ariaLabel:C}):null;return gt.createElement("div",ht({ref:t,className:d.root},a),gt.createElement("div",{className:d.content},gt.createElement("div",{className:d.iconContainer,"aria-hidden":!0},o?gt.createElement(Wr,ht({},o,{className:Tr(d.icon,o.className)})):gt.createElement(Wr,{iconName:xx[m],className:d.icon})),gt.createElement("div",{className:d.text,id:i,role:h\|\|function(e){switch(e){case bx.blocked:case bx.error:case bx.severeWarning:return"alert"}return"status"}(m),"aria-live":function(e){switch(e){case bx.blocked:case bx.error:case bx.severeWarning:return"assertive"}return"polite"}(m)},gt.createElement("span",ht({className:d.innerText},e),v?gt.createElement(Ri,null,gt.createElement("span",null,l)):gt.createElement("span",null,l))),!b&&!s&&y&&gt.createElement("div",{className:d.expandSingleLine},gt.createElement(rd,ht({disabled:!1,className:d.expand,onClick:r,iconProps:p,ariaLabel:c,"aria-expanded":n},g))),!b&&s,!b&&C&&gt.createElement("div",{className:d.dismissSingleLine},C),b&&C),b&&s)});wx.displayName="MessageBar";var Ix,Dx={root:"ms-MessageBar",error:"ms-MessageBar--error",blocked:"ms-MessageBar--blocked",severeWarning:"ms-MessageBar--severeWarning",success:"ms-MessageBar--success",warning:"ms-MessageBar--warning",multiline:"ms-MessageBar-multiline",singleline:"ms-MessageBar-singleline",dismissalSingleLine:"ms-MessageBar-dismissalSingleLine",expandingSingleLine:"ms-MessageBar-expandingSingleLine",content:"ms-MessageBar-content",iconContainer:"ms-MessageBar-icon",text:"ms-MessageBar-text",innerText:"ms-MessageBar-innerText",dismissSingleLine:"ms-MessageBar-dismissSingleLine",expandSingleLine:"ms-MessageBar-expandSingleLine",dismissal:"ms-MessageBar-dismissal",expand:"ms-MessageBar-expand",actions:"ms-MessageBar-actions",actionsSingleline:"ms-MessageBar-actionsSingleLine"},Ex=((t={})[bx.error]="errorBackground",t[bx.blocked]="errorBackground",t[bx.success]="successBackground",t[bx.warning]="warningBackground",t[bx.severeWarning]="severeWarningBackground",t[bx.info]="infoBackground",t),Tx=((U={})[bx.error]="rgba(255, 0, 0, 0.3)",U[bx.blocked]="rgba(255, 0, 0, 0.3)",U[bx.success]="rgba(48, 241, 73, 0.3)",U[bx.warning]="rgba(255, 254, 57, 0.3)",U[bx.severeWarning]="rgba(255, 0, 0, 0.3)",U[bx.info]="Window",U),Px=((xe={})[bx.error]="errorIcon",xe[bx.blocked]="errorIcon",xe[bx.success]="successIcon",xe[bx.warning]="warningIcon",xe[bx.severeWarning]="severeWarningIcon",xe[bx.info]="infoIcon",xe),Rx=In(wx,function(e){var t=e.theme,o=e.className,n=e.onDismiss,r=e.truncated,i=e.isMultiline,s=e.expandSingleLine,a=e.messageBarType,l=void 0===a?bx.info:a,c=t.semanticColors,u=t.fonts,d=uo(0,ro),e=zo(Dx,t),a={fontSize:Ae.xSmall,height:10,lineHeight:"10px",color:c.messageText,selectors:((a={})[Yt]=ht(ht({},{forcedColorAdjust:"none",MsHighContrastAdjust:"none"}),{color:"WindowText"}),a)},t=[bo(t,{inset:1,highContrastStyle:{outlineOffset:"-6px",outline:"1px solid Highlight"},borderColor:"transparent"}),{flexShrink:0,width:32,height:32,padding:"8px 12px",selectors:{"& .ms-Button-icon":a,":hover":{backgroundColor:"transparent"},":active":{backgroundColor:"transparent"}}}];return{root:[e.root,u.medium,l===bx.error&&e.error,l===bx.blocked&&e.blocked,l===bx.severeWarning&&e.severeWarning,l===bx.success&&e.success,l===bx.warning&&e.warning,i?e.multiline:e.singleline,!i&&n&&e.dismissalSingleLine,!i&&r&&e.expandingSingleLine,{background:c[Ex[l]],color:c.messageText,minHeight:32,width:"100%",display:"flex",wordBreak:"break-word",selectors:((a={".ms-Link":{color:c.messageLink,selectors:{":hover":{color:c.messageLinkHovered}}}})[Yt]=ht(ht({},{forcedColorAdjust:"none",MsHighContrastAdjust:"none"}),{background:Tx[l],border:"1px solid WindowText",color:"WindowText"}),a)},i&&{flexDirection:"column"},o],content:[e.content,{display:"flex",width:"100%",lineHeight:"normal"}],iconContainer:[e.iconContainer,{fontSize:Ae.medium,minWidth:16,minHeight:16,display:"flex",flexShrink:0,margin:"8px 0 8px 12px"}],icon:{color:c[Px[l]],selectors:((l={})[Yt]=ht(ht({},{forcedColorAdjust:"none",MsHighContrastAdjust:"none"}),{color:"WindowText"}),l)},text:[e.text,ht(ht({minWidth:0,display:"flex",flexGrow:1,margin:8},u.small),{selectors:((u={})[Yt]=ht({},{forcedColorAdjust:"none",MsHighContrastAdjust:"none"}),u)}),!n&&{marginRight:12}],innerText:[e.innerText,{lineHeight:16,selectors:{"& span a:last-child":{paddingLeft:4}}},r&&{overflow:"visible",whiteSpace:"pre-wrap"},!i&&{overflow:"hidden",textOverflow:"ellipsis",whiteSpace:"nowrap"},!i&&!r&&{selectors:((r={})[d]={overflow:"visible",whiteSpace:"pre-wrap"},r)},s&&{overflow:"visible",whiteSpace:"pre-wrap"}],dismissSingleLine:e.dismissSingleLine,expandSingleLine:e.expandSingleLine,dismissal:[e.dismissal,t],expand:[e.expand,t],actions:[i?e.actions:e.actionsSingleline,{display:"flex",flexGrow:0,flexShrink:0,flexBasis:"auto",flexDirection:"row-reverse",alignItems:"center",margin:"0 12px 0 8px",selectors:{"& button:nth-child(n+2)":{marginLeft:8}}},i&&{marginBottom:8},n&&!i&&{marginRight:0}]}},void 0,{scope:"MessageBar"}),Mx={root:"ms-Nav",linkText:"ms-Nav-linkText",compositeLink:"ms-Nav-compositeLink",link:"ms-Nav-link",chevronButton:"ms-Nav-chevronButton",chevronIcon:"ms-Nav-chevron",navItem:"ms-Nav-navItem",navItems:"ms-Nav-navItems",group:"ms-Nav-group",groupContent:"ms-Nav-groupContent"},Nx={textContainer:{overflow:"hidden"},label:{whiteSpace:"nowrap",textOverflow:"ellipsis",overflow:"hidden"}};function Bx(e){return!!e&&!/^[a-z0-9+-.]+:\/\//i.test(e)}var Fx,Ax,Lx=Fn(),Hx=(l(zx,Ax=gt.Component),zx.prototype.render=function(){var e=this.props,t=e.styles,o=e.groups,n=e.className,r=e.isOnTop,i=e.theme;if(!o)return null;e=o.map(this._renderGroup),o=Lx(t,{theme:i,className:n,isOnTop:r,groups:o});return gt.createElement(Zs,{direction:Ei.vertical,componentRef:this._focusZone},gt.createElement("nav",{role:"navigation",className:o.root,"aria-label":this.props.ariaLabel},e))},Object.defineProperty(zx.prototype,"selectedKey",{get:function(){return this.state.selectedKey},enumerable:!1,configurable:!0}),zx.prototype.focus=function(e){return void 0===e&&(e=!1),!(!this._focusZone\|\|!this._focusZone.current)&&this._focusZone.current.focus(e)},zx.prototype._renderNavLink=function(e,t,o){var n=this.props,r=n.styles,i=n.groups,s=n.theme,a=e.icon\|\|e.iconProps,l=this._isLinkSelected(e),n=e.ariaCurrent,n=void 0===n?"page":n,s=Lx(r,{theme:s,isSelected:l,isDisabled:e.disabled,isButtonEntry:e.onClick&&!e.forceAnchor,leftPadding:14o+3+(a?0:24),groups:i}),o=e.url&&e.target&&!Bx(e.url)?"noopener noreferrer":void 0,a=this.props.linkAs?ju(this.props.linkAs,np):np,i=this.props.onRenderLink?Ma(this.props.onRenderLink,this._onRenderLink):this._onRenderLink;return gt.createElement(a,{className:s.link,styles:Nx,href:e.url\|\|(e.forceAnchor?"#":void 0),iconProps:e.iconProps\|\|{iconName:e.icon},onClick:(e.onClick?this._onNavButtonLinkClicked:this._onNavAnchorLinkClicked).bind(this,e),title:void 0!==e.title?e.title:e.name,target:e.target,rel:o,disabled:e.disabled,"aria-current":l?n:void 0,"aria-label":e.ariaLabel\|\|void 0,link:e},i(e))},zx.prototype._renderCompositeLink=function(e,t,o){var n=ht({},ur(e,cr,["onClick"])),r=this.props,i=r.expandButtonAriaLabel,s=r.styles,a=r.groups,r=r.theme,r=Lx(s,{theme:r,isExpanded:!!e.isExpanded,isSelected:this._isLinkSelected(e),isLink:!0,isDisabled:e.disabled,position:14o+1,groups:a}),a="";return e.links&&0<e.links.length&&(a=e.collapseAriaLabel\|\|e.expandAriaLabel?e.isExpanded?e.collapseAriaLabel:e.expandAriaLabel:i?e.name+" "+i:e.name),gt.createElement("div",ht({},n,{key:e.key\|\|t,className:r.compositeLink}),e.links&&0<e.links.length?gt.createElement("button",{className:r.chevronButton,onClick:this._onLinkExpandClicked.bind(this,e),"aria-label":a,"aria-expanded":e.isExpanded?"true":"false"},gt.createElement(Wr,{className:r.chevronIcon,iconName:"ChevronDown"})):null,this._renderNavLink(e,t,o))},zx.prototype._renderLink=function(e,t,o){var n=this.props,r=n.styles,i=n.groups,n=n.theme,i=Lx(r,{theme:n,groups:i});return gt.createElement("li",{key:e.key\|\|t,role:"listitem",className:i.navItem},this._renderCompositeLink(e,t,o),e.isExpanded?this._renderLinks(e.links,++o):null)},zx.prototype._renderLinks=function(e,o){var n=this;if(!e\|\|!e.length)return null;var t=e.map(function(e,t){return n._renderLink(e,t,o)}),r=this.props,i=r.styles,e=r.groups,r=r.theme,e=Lx(i,{theme:r,groups:e});return gt.createElement("ul",{role:"list",className:e.navItems},t)},zx.prototype._onGroupHeaderClicked=function(e,t){e.onHeaderClick&&e.onHeaderClick(t,this._isGroupExpanded(e)),void 0===e.isExpanded&&this._toggleCollapsed(e),t&&(t.preventDefault(),t.stopPropagation())},zx.prototype._onLinkExpandClicked=function(e,t){var o=this.props.onLinkExpandClick;o&&o(t,e),t.defaultPrevented\|\|(e.isExpanded=!e.isExpanded,this.setState({isLinkExpandStateChanged:!0})),t.preventDefault(),t.stopPropagation()},zx.prototype._preventBounce=function(e,t){!e.url&&e.forceAnchor&&t.preventDefault()},zx.prototype._onNavAnchorLinkClicked=function(e,t){this._preventBounce(e,t),this.props.onLinkClick&&this.props.onLinkClick(t,e),!e.url&&e.links&&0<e.links.length&&this._onLinkExpandClicked(e,t),this.setState({selectedKey:e.key})},zx.prototype._onNavButtonLinkClicked=function(e,t){this._preventBounce(e,t),e.onClick&&e.onClick(t,e),!e.url&&e.links&&0<e.links.length&&this._onLinkExpandClicked(e,t),this.setState({selectedKey:e.key})},zx.prototype._isLinkSelected=function(e){if(void 0!==this.props.selectedKey)return e.key===this.props.selectedKey;if(void 0!==this.state.selectedKey)return e.key===this.state.selectedKey;if(void 0===qe()\|\|!e.url)return!1;(Ix=Ix\|\|document.createElement("a")).href=e.url\|\|"";var t=Ix.href;return location.href===t\|\|location.protocol+"//"+location.host+location.pathname===t\|\|!!location.hash&&(location.hash===e.url\|\|(Ix.href=location.hash.substring(1),Ix.href===t))},zx.prototype._isGroupExpanded=function(e){return void 0!==e.isExpanded?e.isExpanded:e.name&&this.state.isGroupCollapsed.hasOwnProperty(e.name)?!this.state.isGroupCollapsed[e.name]:void 0===e.collapseByDefault\|\|!e.collapseByDefault},zx.prototype._toggleCollapsed=function(e){var t;e.name&&(t=ht(ht({},this.state.isGroupCollapsed),((t={})[e.name]=this._isGroupExpanded(e),t)),this.setState({isGroupCollapsed:t}))},zx.defaultProps={groups:null},zx),Ox=In(Hx,function(e){var t=e.className,o=e.theme,n=e.isOnTop,r=e.isExpanded,i=e.isGroup,s=e.isLink,a=e.isSelected,l=e.isDisabled,c=e.isButtonEntry,u=e.navHeight,d=void 0===u?44:u,p=e.position,h=e.leftPadding,m=void 0===h?20:h,g=e.leftPaddingExpanded,f=void 0===g?28:g,v=e.rightPadding,u=void 0===v?20:v,h=o.palette,g=o.semanticColors,e=o.fonts,v=zo(Mx,o);return{root:[v.root,t,e.medium,{overflowY:"auto",userSelect:"none",WebkitOverflowScrolling:"touch"},n&&[{position:"absolute"},Le.slideRightIn40]],linkText:[v.linkText,{margin:"0 4px",overflow:"hidden",verticalAlign:"middle",textAlign:"left",textOverflow:"ellipsis"}],compositeLink:[v.compositeLink,{display:"block",position:"relative",color:g.bodyText},r&&"is-expanded",a&&"is-selected",l&&"is-disabled",l&&{color:g.disabledText}],link:[v.link,bo(o),{display:"block",position:"relative",height:d,width:"100%",lineHeight:d+"px",textDecoration:"none",cursor:"pointer",textOverflow:"ellipsis",whiteSpace:"nowrap",overflow:"hidden",paddingLeft:m,paddingRight:u,color:g.bodyText,selectors:((m={})[Yt]={border:0,selectors:{":focus":{border:"1px solid WindowText"}}},m)},!l&&{selectors:{".ms-Nav-compositeLink:hover &":{backgroundColor:g.bodyBackgroundHovered}}},a&&{color:g.bodyTextChecked,fontWeight:Fe.semibold,backgroundColor:g.bodyBackgroundChecked,selectors:{"&:after":{borderLeft:"2px solid "+h.themePrimary,content:'""',position:"absolute",top:0,right:0,bottom:0,left:0,pointerEvents:"none"}}},l&&{color:g.disabledText},c&&{color:h.themePrimary}],chevronButton:[v.chevronButton,bo(o),e.small,{display:"block",textAlign:"left",lineHeight:d+"px",margin:"5px 0",padding:"0px, "+u+"px, 0px, "+f+"px",border:"none",textOverflow:"ellipsis",whiteSpace:"nowrap",overflow:"hidden",cursor:"pointer",color:g.bodyText,backgroundColor:"transparent",selectors:{"&:visited":{color:g.bodyText}}},i&&{fontSize:e.large.fontSize,width:"100%",height:d,borderBottom:"1px solid "+g.bodyDivider},s&&{display:"block",width:f-2,height:d-2,position:"absolute",top:"1px",left:p+"px",zIndex:mo.Nav,padding:0,margin:0},a&&{color:h.themePrimary,backgroundColor:h.neutralLighterAlt,selectors:{"&:after":{borderLeft:"2px solid "+h.themePrimary,content:'""',position:"absolute",top:0,right:0,bottom:0,left:0,pointerEvents:"none"}}}],chevronIcon:[v.chevronIcon,{position:"absolute",left:"8px",height:d,display:"inline-flex",alignItems:"center",lineHeight:d+"px",fontSize:e.small.fontSize,transition:"transform .1s linear"},r&&{transform:"rotate(-180deg)"},s&&{top:0}],navItem:[v.navItem,{padding:0}],navItems:[v.navItems,{listStyleType:"none",padding:0,margin:0}],group:[v.group,r&&"is-expanded"],groupContent:[v.groupContent,{display:"none",marginBottom:"40px"},Le.slideDownIn20,r&&{display:"block"}]}},void 0,{scope:"Nav"});function zx(e){var a=Ax.call(this,e)\|\|this;return a._focusZone=gt.createRef(),a._onRenderLink=function(e){var t=a.props,o=t.styles,n=t.groups,t=t.theme,n=Lx(o,{theme:t,groups:n});return gt.createElement("div",{className:n.linkText},e.name)},a._renderGroup=function(o,e){var t=a.props,n=t.styles,r=t.groups,i=t.theme,s=t.onRenderGroupHeader,t=void 0===s?a._renderGroupHeader:s,s=a._isGroupExpanded(o),r=Lx(n,{theme:i,isGroup:!0,isExpanded:s,groups:r}),s=ht(ht({},o),{isExpanded:s,onHeaderClick:function(e,t){a._onGroupHeaderClicked(o,e)}});return gt.createElement("div",{key:e,className:r.group},s.name?t(s,a._renderGroupHeader):null,gt.createElement("div",{className:r.groupContent},a._renderLinks(s.links,0)))},a._renderGroupHeader=function(e){var t=a.props,o=t.styles,n=t.groups,r=t.theme,t=t.expandButtonAriaLabel,i=e.isExpanded,n=Lx(o,{theme:r,isGroup:!0,isExpanded:i,groups:n}),t=(i?e.collapseAriaLabel:e.expandAriaLabel)\|\|t,s=e.onHeaderClick;return gt.createElement("button",{className:n.chevronButton,onClick:s?function(e){s(e,i)}:void 0,"aria-label":t,"aria-expanded":i},gt.createElement(Wr,{className:n.chevronIcon,iconName:"ChevronDown"}),e.name)},fi(a),a.state={isGroupCollapsed:{},isLinkExpandStateChanged:!1,selectedKey:e.initialSelectedKey\|\|e.selectedKey},a}(G=Fx=Fx\|\|{})[G.none=0]="none",G[G.forceResolve=1]="forceResolve",G[G.searchMore=2]="searchMore";var Wx,Vx,Kx={root:"ms-Suggestions-item",itemButton:"ms-Suggestions-itemButton",closeButton:"ms-Suggestions-closeButton",isSuggested:"is-suggested"},Gx=o,Ux=Fn(),jx=In(b_,function(e){var t,o=e.className,n=e.theme,r=e.suggested,i=n.palette,s=n.semanticColors,a=zo(Kx,n);return{root:[a.root,{display:"flex",alignItems:"stretch",boxSizing:"border-box",width:"100%",position:"relative",selectors:{"&:hover":{background:s.menuItemBackgroundHovered},"&:hover .ms-Suggestions-closeButton":{display:"block"}}},r&&{selectors:((t={})["."+go+" &"]={selectors:((e={})["."+a.closeButton]={display:"block",background:s.menuItemBackgroundPressed},e)},t[":after"]={pointerEvents:"none",content:'""',position:"absolute",left:0,top:0,bottom:0,right:0,border:"1px solid "+n.semanticColors.focusBorder},t)},o],itemButton:[a.itemButton,{width:"100%",padding:0,border:"none",height:"100%",minWidth:0,overflow:"hidden",selectors:((o={})[Yt]={color:"WindowText",selectors:{":hover":ht({background:"Highlight",color:"HighlightText"},{forcedColorAdjust:"none",MsHighContrastAdjust:"none"})}},o[":hover"]={color:s.menuItemTextHovered},o)},r&&[a.isSuggested,{background:s.menuItemBackgroundPressed,selectors:((s={":hover":{background:s.menuDivider}})[Yt]=ht({background:"Highlight",color:"HighlightText"},{forcedColorAdjust:"none",MsHighContrastAdjust:"none"}),s)}]],closeButton:[a.closeButton,{display:"none",color:i.neutralSecondary,padding:"0 4px",height:"auto",width:32,selectors:((a={":hover, :active":{background:i.neutralTertiaryAlt,color:i.neutralDark}})[Yt]={color:"WindowText"},a)},r&&((r={})["."+go+" &"]={selectors:{":hover, :active":{background:i.neutralTertiary}}},r.selectors={":hover, :active":{background:i.neutralTertiary,color:i.neutralPrimary}},r)]}},void 0,{scope:"SuggestionItem"}),qx=(l(Qx,Vx=gt.Component),Qx.prototype.componentDidMount=function(){this.scrollSelected(),this.activeSelectedElement=this._selectedElement?this._selectedElement.current:null},Qx.prototype.componentDidUpdate=function(){this._selectedElement.current&&this.activeSelectedElement!==this._selectedElement.current&&(this.scrollSelected(),this.activeSelectedElement=this._selectedElement.current)},Qx.prototype.render=function(){var e=this,t=this.props,o=t.forceResolveText,n=t.mostRecentlyUsedHeaderText,r=t.searchForMoreIcon,i=t.searchForMoreText,s=t.className,a=t.moreSuggestionsAvailable,l=t.noResultsFoundText,c=t.suggestions,u=t.isLoading,d=t.isSearching,p=t.loadingText,h=t.onRenderNoResultFound,m=t.searchingText,g=t.isMostRecentlyUsedVisible,f=t.resultsMaximumNumber,v=t.resultsFooterFull,b=t.resultsFooter,y=t.isResultsFooterVisible,C=void 0===y\|\|y,_=t.suggestionsHeaderText,S=t.suggestionsClassName,x=t.theme,k=t.styles,y=t.suggestionsListId,t=t.suggestionsContainerAriaLabel;this._classNames=k?Ux(k,{theme:x,className:s,suggestionsClassName:S,forceResolveButtonSelected:this.state.selectedActionType===Fx.forceResolve,searchForMoreButtonSelected:this.state.selectedActionType===Fx.searchMore}):{root:Tr("ms-Suggestions",s,Gx.root),title:Tr("ms-Suggestions-title",Gx.suggestionsTitle),searchForMoreButton:Tr("ms-SearchMore-button",Gx.actionButton,((s={})["is-selected "+Gx.buttonSelected]=this.state.selectedActionType===Fx.searchMore,s)),forceResolveButton:Tr("ms-forceResolve-button",Gx.actionButton,((s={})["is-selected "+Gx.buttonSelected]=this.state.selectedActionType===Fx.forceResolve,s)),suggestionsAvailable:Tr("ms-Suggestions-suggestionsAvailable",Gx.suggestionsAvailable),suggestionsContainer:Tr("ms-Suggestions-container",Gx.suggestionsContainer,S),noSuggestions:Tr("ms-Suggestions-none",Gx.suggestionsNone)};var S=this._classNames.subComponentStyles?this._classNames.subComponentStyles.spinner:void 0,S=k?{styles:S}:{className:Tr("ms-Suggestions-spinner",Gx.suggestionsSpinner)},w=function(){return gt.createElement("div",{id:"sug-noResultsFound",role:"option"},h?h(void 0,w):gt.createElement("div",{className:e._classNames.noSuggestions},l))},_=_;g&&n&&(_=n);n=void 0;C&&(n=c.length>=f?v:b);v=!(c&&c.length\|\|u),b=this.state.selectedActionType===Fx.forceResolve?"sug-selectedAction":void 0,c=this.state.selectedActionType===Fx.searchMore?"sug-selectedAction":void 0;return gt.createElement("div",{className:this._classNames.root,"aria-label":t\|\|_,id:y,role:"listbox"},gt.createElement(Bi,{message:this._getAlertText(),"aria-live":"polite"}),_?gt.createElement("div",{className:this._classNames.title},_):null,o&&this._shouldShowForceResolve()&&gt.createElement(up,{componentRef:this._forceResolveButton,className:this._classNames.forceResolveButton,id:b,onClick:this._forceResolve,"data-automationid":"sug-forceResolve"},o),u&&gt.createElement(Fb,ht({},S,{label:p})),v?w():this._renderSuggestions(),i&&a&&gt.createElement(up,{componentRef:this._searchForMoreButton,className:this._classNames.searchForMoreButton,iconProps:r\|\|{iconName:"Search"},id:c,onClick:this._getMoreResults,"data-automationid":"sug-searchForMore",role:"option"},i),d?gt.createElement(Fb,ht({},S,{label:m})):null,!n\|\|a\|\|g\|\|d?null:gt.createElement("div",{className:this._classNames.title},n(this.props)))},Qx.prototype.hasSuggestedAction=function(){return!!this._searchForMoreButton.current\|\|!!this._forceResolveButton.current},Qx.prototype.hasSuggestedActionSelected=function(){return this.state.selectedActionType!==Fx.none},Qx.prototype.executeSelectedAction=function(){switch(this.state.selectedActionType){case Fx.forceResolve:this._forceResolve();break;case Fx.searchMore:this._getMoreResults()}},Qx.prototype.focusAboveSuggestions=function(){this._forceResolveButton.current?this.setState({selectedActionType:Fx.forceResolve}):this._searchForMoreButton.current&&this.setState({selectedActionType:Fx.searchMore})},Qx.prototype.focusBelowSuggestions=function(){this._searchForMoreButton.current?this.setState({selectedActionType:Fx.searchMore}):this._forceResolveButton.current&&this.setState({selectedActionType:Fx.forceResolve})},Qx.prototype.focusSearchForMoreButton=function(){this._searchForMoreButton.current&&this._searchForMoreButton.current.focus()},Qx.prototype.scrollSelected=function(){var e,t,o,n,r;this._selectedElement.current&&this._scrollContainer.current&&void 0!==this._scrollContainer.current.scrollTo&&(e=(n=this._selectedElement.current).offsetHeight,t=n.offsetTop,o=(r=this._scrollContainer.current).offsetHeight,r=(n=r.scrollTop)+o<t+e,t<n?this._scrollContainer.current.scrollTo(0,t):r&&this._scrollContainer.current.scrollTo(0,t-o+e))},Qx.prototype._renderSuggestions=function(){var o=this,e=this.props,n=e.onRenderSuggestion,r=e.removeSuggestionAriaLabel,i=e.suggestionsItemClassName,t=e.resultsMaximumNumber,s=e.showRemoveButtons,a=e.removeButtonIconProps,e=this.props.suggestions,l=jx,c=-1;return e.some(function(e,t){return!!e.selected&&(c=t,!0)}),0===(e=t?t<=c?e.slice(c-t+1,c+1):e.slice(0,t):e).length?null:gt.createElement("div",{className:this._classNames.suggestionsContainer,ref:this._scrollContainer,role:"presentation"},e.map(function(e,t){return gt.createElement("div",{ref:e.selected?o._selectedElement:void 0,key:e.item.key\|\|t,role:"presentation"},gt.createElement(l,{suggestionModel:e,RenderSuggestion:n,onClick:o._onClickTypedSuggestionsItem(e.item,t),className:i,showRemoveButton:s,removeButtonAriaLabel:r,onRemoveItem:o._onRemoveTypedSuggestionsItem(e.item,t),id:"sug-"+t,removeButtonIconProps:a}))}))},Qx),Yx=(Xx.prototype.updateSuggestions=function(e,t){e&&0<e.length?(this.suggestions=this.convertSuggestionsToSuggestionItems(e),this.currentIndex=t\|\|0,-1===t?this.currentSuggestion=void 0:void 0!==t&&(this.suggestions[t].selected=!0,this.currentSuggestion=this.suggestions[t])):(this.suggestions=[],this.currentIndex=-1,this.currentSuggestion=void 0)},Xx.prototype.nextSuggestion=function(){if(this.suggestions&&this.suggestions.length){if(this.currentIndex<this.suggestions.length-1)return this.setSelectedSuggestion(this.currentIndex+1),!0;if(this.currentIndex===this.suggestions.length-1)return this.setSelectedSuggestion(0),!0}return!1},Xx.prototype.previousSuggestion=function(){if(this.suggestions&&this.suggestions.length){if(0<this.currentIndex)return this.setSelectedSuggestion(this.currentIndex-1),!0;if(0===this.currentIndex)return this.setSelectedSuggestion(this.suggestions.length-1),!0}return!1},Xx.prototype.getSuggestions=function(){return this.suggestions},Xx.prototype.getCurrentItem=function(){return this.currentSuggestion},Xx.prototype.getSuggestionAtIndex=function(e){return this.suggestions[e]},Xx.prototype.hasSelectedSuggestion=function(){return!!this.currentSuggestion},Xx.prototype.removeSuggestion=function(e){this.suggestions.splice(e,1)},Xx.prototype.createGenericSuggestion=function(e){e=this.convertSuggestionsToSuggestionItems([e])[0];this.currentSuggestion=e},Xx.prototype.convertSuggestionsToSuggestionItems=function(e){return Array.isArray(e)?e.map(this._ensureSuggestionModel):[]},Xx.prototype.deselectAllSuggestions=function(){-1<this.currentIndex&&(this.suggestions[this.currentIndex].selected=!1,this.currentIndex=-1)},Xx.prototype.setSelectedSuggestion=function(e){e>this.suggestions.length-1\|\|e<0?(this.currentIndex=0,this.currentSuggestion.selected=!1,this.currentSuggestion=this.suggestions[0],this.currentSuggestion.selected=!0):(-1<this.currentIndex&&(this.suggestions[this.currentIndex].selected=!1),this.suggestions[e].selected=!0,this.currentIndex=e,this.currentSuggestion=this.suggestions[e])},Xx),Zx={root:"ms-Suggestions",suggestionsContainer:"ms-Suggestions-container",title:"ms-Suggestions-title",forceResolveButton:"ms-forceResolve-button",searchForMoreButton:"ms-SearchMore-button",spinner:"ms-Suggestions-spinner",noSuggestions:"ms-Suggestions-none",suggestionsAvailable:"ms-Suggestions-suggestionsAvailable",isSelected:"is-selected"};function Xx(){var t=this;this._isSuggestionModel=function(e){return void 0!==e.item},this._ensureSuggestionModel=function(e){return t._isSuggestionModel(e)?e:{item:e,selected:!1,ariaLabel:e.name\|\|e.primaryText}},this.suggestions=[],this.currentIndex=-1}function Qx(e){var s=Vx.call(this,e)\|\|this;return s._forceResolveButton=gt.createRef(),s._searchForMoreButton=gt.createRef(),s._selectedElement=gt.createRef(),s._scrollContainer=gt.createRef(),s.tryHandleKeyDown=function(e,t){var o=!1,n=null,r=s.state.selectedActionType,i=s.props.suggestions.length;if(e===En.down)switch(r){case Fx.forceResolve:n=0<i?(s._refocusOnSuggestions(e),Fx.none):s._searchForMoreButton.current?Fx.searchMore:Fx.forceResolve;break;case Fx.searchMore:n=s._forceResolveButton.current?Fx.forceResolve:0<i?(s._refocusOnSuggestions(e),Fx.none):Fx.searchMore;break;case Fx.none:-1===t&&s._forceResolveButton.current&&(n=Fx.forceResolve)}else if(e===En.up)switch(r){case Fx.forceResolve:s._searchForMoreButton.current?n=Fx.searchMore:0<i&&(s._refocusOnSuggestions(e),n=Fx.none);break;case Fx.searchMore:0<i?(s._refocusOnSuggestions(e),n=Fx.none):s._forceResolveButton.current&&(n=Fx.forceResolve);break;case Fx.none:-1===t&&s._searchForMoreButton.current&&(n=Fx.searchMore)}return null!==n&&(s.setState({selectedActionType:n}),o=!0),o},s._getAlertText=function(){var e=s.props,t=e.isLoading,o=e.isSearching,n=e.suggestions,r=e.suggestionsAvailableAlertText,e=e.noResultsFoundText;if(!t&&!o){if(0<n.length)return r\|\|"";if(e)return e}return""},s._getMoreResults=function(){s.props.onGetMoreResults&&(s.props.onGetMoreResults(),s.setState({selectedActionType:Fx.none}))},s._forceResolve=function(){s.props.createGenericItem&&s.props.createGenericItem()},s._shouldShowForceResolve=function(){return!!s.props.showForceResolve&&s.props.showForceResolve()},s._onClickTypedSuggestionsItem=function(t,o){return function(e){s.props.onSuggestionClick(e,t,o)}},s._refocusOnSuggestions=function(e){"function"==typeof s.props.refocusSuggestions&&s.props.refocusSuggestions(e)},s._onRemoveTypedSuggestionsItem=function(t,o){return function(e){(0,s.props.onSuggestionRemove)(e,t,o),e.stopPropagation()}},fi(s),s.state={selectedActionType:Fx.none},s}function Jx(e){var t=e.className,o=e.suggestionsClassName,n=e.theme,r=e.forceResolveButtonSelected,i=e.searchForMoreButtonSelected,s=n.palette,a=n.semanticColors,l=n.fonts,c=zo(Zx,n),e={backgroundColor:"transparent",border:0,cursor:"pointer",margin:0,paddingLeft:8,position:"relative",borderTop:"1px solid "+s.neutralLight,height:40,textAlign:"left",width:"100%",fontSize:l.small.fontSize,selectors:{":hover":{backgroundColor:a.menuItemBackgroundPressed,cursor:"pointer"},":focus, :active":{backgroundColor:s.themeLight},".ms-Button-icon":{fontSize:l.mediumPlus.fontSize,width:25},".ms-Button-label":{margin:"0 4px 0 9px"}}},n={backgroundColor:s.themeLight,selectors:((n={})[Yt]=ht({backgroundColor:"Highlight",borderColor:"Highlight",color:"HighlightText"},{forcedColorAdjust:"none",MsHighContrastAdjust:"none"}),n)};return{root:[c.root,{minWidth:260},t],suggestionsContainer:[c.suggestionsContainer,{overflowY:"auto",overflowX:"hidden",maxHeight:300,transform:"translate3d(0,0,0)"},o],title:[c.title,{padding:"0 12px",fontSize:l.small.fontSize,color:s.themePrimary,lineHeight:40,borderBottom:"1px solid "+a.menuItemBackgroundPressed}],forceResolveButton:[c.forceResolveButton,e,r&&[c.isSelected,n]],searchForMoreButton:[c.searchForMoreButton,e,i&&[c.isSelected,n]],noSuggestions:[c.noSuggestions,{textAlign:"center",color:s.neutralSecondary,fontSize:l.small.fontSize,lineHeight:30}],suggestionsAvailable:[c.suggestionsAvailable,So],subComponentStyles:{spinner:{root:[c.spinner,{margin:"5px 0",paddingLeft:14,textAlign:"left",whiteSpace:"nowrap",lineHeight:20,fontSize:l.small.fontSize}],circle:{display:"inline-block",verticalAlign:"middle"},label:{display:"inline-block",verticalAlign:"middle",margin:"0 10px 0 16px"}}}}}(V=Wx=Wx\|\|{})[V.valid=0]="valid",V[V.warning=1]="warning",V[V.invalid=2]="invalid",Dt([{rawString:".pickerText_15a92175{display:-webkit-box;display:-ms-flexbox;display:flex;-ms-flex-wrap:wrap;flex-wrap:wrap;-webkit-box-align:center;-ms-flex-align:center;align-items:center;-webkit-box-sizing:border-box;box-sizing:border-box;border:1px solid "},{theme:"neutralTertiary",defaultValue:"#a19f9d"},{rawString:";min-width:180px;min-height:30px}.pickerText_15a92175:hover{border-color:"},{theme:"inputBorderHovered",defaultValue:"#323130"},{rawString:"}.pickerText_15a92175.inputFocused_15a92175{position:relative;border-color:"},{theme:"inputFocusBorderAlt",defaultValue:"#0078d4"},{rawString:"}.pickerText_15a92175.inputFocused_15a92175:after{pointer-events:none;content:'';position:absolute;left:-1px;top:-1px;bottom:-1px;right:-1px;border:2px solid "},{theme:"inputFocusBorderAlt",defaultValue:"#0078d4"},{rawString:"}@media screen and (-ms-high-contrast:active){.pickerText_15a92175.inputDisabled_15a92175{position:relative;border-color:GrayText}.pickerText_15a92175.inputDisabled_15a92175:after{pointer-events:none;content:'';position:absolute;left:0;top:0;bottom:0;right:0;background-color:Window}}.pickerInput_15a92175{height:34px;border:none;-webkit-box-flex:1;-ms-flex-positive:1;flex-grow:1;outline:0;padding:0 6px 0;-ms-flex-item-align:end;align-self:flex-end}.pickerItems_15a92175{display:-webkit-box;display:-ms-flexbox;display:flex;-ms-flex-wrap:wrap;flex-wrap:wrap;max-width:100%}.screenReaderOnly_15a92175{position:absolute;width:1px;height:1px;padding:0;margin:-1px;overflow:hidden;clip:rect(0,0,0,0);border:0}"}]);var $x,ek,tk="pickerText_15a92175",ok="inputFocused_15a92175",nk="inputDisabled_15a92175",rk="pickerInput_15a92175",ik="pickerItems_15a92175",sk="screenReaderOnly_15a92175",ak=i,lk=Fn(),ck=(l(_k,ek=gt.Component),_k.getDerivedStateFromProps=function(e){return e.selectedItems?{items:e.selectedItems}:null},Object.defineProperty(_k.prototype,"items",{get:function(){return this.state.items},enumerable:!1,configurable:!0}),_k.prototype.componentDidMount=function(){this.selection.setItems(this.state.items),this._onResolveSuggestions=this._async.debounce(this._onResolveSuggestions,this.props.resolveDelay)},_k.prototype.componentDidUpdate=function(e,t){var o;this.state.items&&this.state.items!==t.items&&(o=this.selection.getSelectedIndices()[0],this.selection.setItems(this.state.items),this.state.isFocused&&(this.state.items.length<t.items.length?(this.selection.setIndexSelected(o,!1,!0),this.resetFocus(o)):this.state.items.length>t.items.length&&!this.canAddItems()&&this.resetFocus(this.state.items.length-1)))},_k.prototype.componentWillUnmount=function(){this.currentPromise&&(this.currentPromise=void 0),this._async.dispose()},_k.prototype.focus=function(){this.input.current&&this.input.current.focus()},_k.prototype.focusInput=function(){this.input.current&&this.input.current.focus()},_k.prototype.completeSuggestion=function(e){this.suggestionStore.hasSelectedSuggestion()&&this.input.current?this.completeSelection(this.suggestionStore.currentSuggestion.item):e&&this._completeGenericSuggestion()},_k.prototype.render=function(){var e=this.state,t=e.suggestedDisplayValue,o=e.isFocused,n=e.items,r=this.props,i=r.className,s=r.inputProps,a=r.disabled,l=r.selectionAriaLabel,c=r.selectionRole,u=void 0===c?"list":c,e=r.theme,c=r.styles,r=this.state.suggestionsVisible?this._ariaMap.suggestionList:"",o=c?lk(c,{theme:e,className:i,isFocused:o,disabled:a,inputClassName:s&&s.className}):{root:Tr("ms-BasePicker",i\|\|""),text:Tr("ms-BasePicker-text",ak.pickerText,this.state.isFocused&&ak.inputFocused),itemsWrapper:ak.pickerItems,input:Tr("ms-BasePicker-input",ak.pickerInput,s&&s.className),screenReaderText:ak.screenReaderOnly},i=this.props["aria-label"]\|\|(null==s?void 0:s["aria-label"]);return gt.createElement("div",{ref:this.root,className:o.root,onKeyDown:this.onKeyDown,onFocus:this.onFocus,onBlur:this.onBlur},this.renderCustomAlert(o.screenReaderText),gt.createElement("span",{id:this._ariaMap.selectedItems+"-label",hidden:!0},l\|\|i),gt.createElement(Pv,{selection:this.selection,selectionMode:dv.multiple},gt.createElement("div",{className:o.text,"aria-owns":r},0<n.length&&gt.createElement("span",{id:this._ariaMap.selectedItems,className:o.itemsWrapper,role:u,"aria-labelledby":this._ariaMap.selectedItems+"-label"},this.renderItems()),this.canAddItems()&&gt.createElement(ki,ht({spellCheck:!1},s,{className:o.input,componentRef:this.input,id:null!=s&&s.id?s.id:this._ariaMap.combobox,onClick:this.onClick,onFocus:this.onInputFocus,onBlur:this.onInputBlur,onInputValueChange:this.onInputChange,suggestedDisplayValue:t,"aria-activedescendant":this.getActiveDescendant(),"aria-controls":r,"aria-describedby":0<n.length?this._ariaMap.selectedItems:void 0,"aria-expanded":!!this.state.suggestionsVisible,"aria-haspopup":"listbox","aria-label":i,role:"combobox",disabled:a,onInputChange:this.props.onInputChange})))),this.renderSuggestions())},_k.prototype.canAddItems=function(){var e=this.state.items,t=this.props.itemLimit;return void 0===t\|\|e.length<t},_k.prototype.renderSuggestions=function(){var e=this._styledSuggestions;return this.state.suggestionsVisible&&this.input?gt.createElement(ac,ht({isBeakVisible:!1,gapSpace:5,target:this.input.current?this.input.current.inputElement:void 0,onDismiss:this.dismissSuggestions,directionalHint:Pa.bottomLeftEdge,directionalHintForRTL:Pa.bottomRightEdge},this.props.pickerCalloutProps),gt.createElement(e,ht({onRenderSuggestion:this.props.onRenderSuggestionsItem,onSuggestionClick:this.onSuggestionClick,onSuggestionRemove:this.onSuggestionRemove,suggestions:this.suggestionStore.getSuggestions(),componentRef:this.suggestionElement,onGetMoreResults:this.onGetMoreResults,moreSuggestionsAvailable:this.state.moreSuggestionsAvailable,isLoading:this.state.suggestionsLoading,isSearching:this.state.isSearching,isMostRecentlyUsedVisible:this.state.isMostRecentlyUsedVisible,isResultsFooterVisible:this.state.isResultsFooterVisible,refocusSuggestions:this.refocusSuggestions,removeSuggestionAriaLabel:this.props.removeButtonAriaLabel,suggestionsListId:this._ariaMap.suggestionList,createGenericItem:this._completeGenericSuggestion},this.props.pickerSuggestionsProps))):null},_k.prototype.renderItems=function(){var o=this,e=this.props,n=e.disabled,r=e.removeButtonAriaLabel,i=e.removeButtonIconProps,s=this.props.onRenderItem,t=this.state,e=t.items,a=t.selectedIndices;return e.map(function(e,t){return s({item:e,index:t,key:e.key\|\|t,selected:-1!==a.indexOf(t),onRemoveItem:function(){return o.removeItem(e)},disabled:n,onItemChange:o.onItemChange,removeButtonAriaLabel:r,removeButtonIconProps:i})})},_k.prototype.resetFocus=function(e){var t=this.state.items;t.length&&0<=e?(e=this.root.current&&this.root.current.querySelectorAll("[data-selection-index]")[Math.min(e,t.length-1)])&&e.focus():this.canAddItems()?this.input.current&&this.input.current.focus():this.resetFocus(t.length-1)},_k.prototype.onSuggestionSelect=function(){var e;this.suggestionStore.currentSuggestion&&(e=this.input.current?this.input.current.value:"",e=this._getTextFromItem(this.suggestionStore.currentSuggestion.item,e),this.setState({suggestedDisplayValue:e}))},_k.prototype.onSelectionChange=function(){this.setState({selectedIndices:this.selection.getSelectedIndices()})},_k.prototype.updateSuggestions=function(e){this.suggestionStore.updateSuggestions(e,0),this.forceUpdate()},_k.prototype.onEmptyInputFocus=function(){var e=this.props.onEmptyResolveSuggestions\|\|this.props.onEmptyInputFocus;e&&(e=e(this.state.items),this.updateSuggestionsList(e),this.setState({isMostRecentlyUsedVisible:!0,suggestionsVisible:!0,moreSuggestionsAvailable:!1}))},_k.prototype.updateValue=function(e){this._onResolveSuggestions(e)},_k.prototype.updateSuggestionsList=function(t,o){var n=this;Array.isArray(t)?this._updateAndResolveValue(o,t):t&&t.then&&(this.setState({suggestionsLoading:!0}),this.suggestionStore.updateSuggestions([]),void 0!==o?this.setState({suggestionsVisible:this._getShowSuggestions()}):this.setState({suggestionsVisible:this.input.current&&this.input.current.inputElement===document.activeElement}),(this.currentPromise=t).then(function(e){t===n.currentPromise&&n._updateAndResolveValue(o,e)}))},_k.prototype.resolveNewValue=function(e,t){var o=this;this.updateSuggestions(t);t=void 0;this.suggestionStore.currentSuggestion&&(t=this._getTextFromItem(this.suggestionStore.currentSuggestion.item,e)),this.setState({suggestedDisplayValue:t,suggestionsVisible:this._getShowSuggestions()},function(){return o.setState({suggestionsLoading:!1})})},_k.prototype.onChange=function(e){this.props.onChange&&this.props.onChange(e)},_k.prototype.onBackspace=function(e){(this.state.items.length&&!this.input.current\|\|this.input.current&&!this.input.current.isValueSelected&&0===this.input.current.cursorLocation)&&(0<this.selection.getSelectedCount()?this.removeItems(this.selection.getSelection()):this.removeItem(this.state.items[this.state.items.length-1]))},_k.prototype.getActiveDescendant=function(){var e;if(!this.state.suggestionsLoading){var t=this.suggestionStore.currentIndex;return t<0?null!==(e=this.suggestionElement.current)&&void 0!==e&&e.hasSuggestedAction()?"sug-selectedAction":0===this.suggestionStore.suggestions.length?"sug-noResultsFound":void 0:"sug-"+t}},_k.prototype.getSuggestionsAlert=function(e){void 0===e&&(e=ak.screenReaderOnly);var t=this.suggestionStore.currentIndex;if(this.props.enableSelectedSuggestionAlert){t=-1<t?this.suggestionStore.getSuggestionAtIndex(this.suggestionStore.currentIndex):void 0,t=t?t.ariaLabel:void 0;return gt.createElement("div",{id:this._ariaMap.selectedSuggestionAlert,className:e},t+" ")}},_k.prototype.renderCustomAlert=function(e){void 0===e&&(e=ak.screenReaderOnly);var t=this.props.suggestionRemovedText,o="";return this.state.selectionRemoved&&(o=Jp(void 0===t?"removed {0}":t,this._getTextFromItem(this.state.selectionRemoved,""))),gt.createElement("div",{className:e,id:this._ariaMap.selectedSuggestionAlert,"aria-live":"assertive"},this.getSuggestionsAlert(e),o)},_k.prototype._updateAndResolveValue=function(e,t){void 0!==e?this.resolveNewValue(e,t):(this.suggestionStore.updateSuggestions(t,-1),this.state.suggestionsLoading&&this.setState({suggestionsLoading:!1}))},_k.prototype._updateSelectedItems=function(e){var t=this;this.props.selectedItems?this.onChange(e):this.setState({items:e},function(){t._onSelectedItemsUpdated(e)})},_k.prototype._onSelectedItemsUpdated=function(e){this.onChange(e)},_k.prototype._getShowSuggestions=function(){return void 0!==this.input.current&&null!==this.input.current&&this.input.current.inputElement===document.activeElement&&""!==this.input.current.value},_k.prototype._getTextFromItem=function(e,t){return this.props.getTextFromItem?this.props.getTextFromItem(e,t):""},_k),uk=(l(Ck,$x=ck),Ck.prototype.render=function(){var e=this.state,t=e.suggestedDisplayValue,o=e.isFocused,n=this.props,r=n.className,i=n.inputProps,s=n.disabled,a=n.selectionAriaLabel,l=n.selectionRole,c=void 0===l?"list":l,e=n.theme,l=n.styles,n=this.state.suggestionsVisible?this._ariaMap.suggestionList:"",o=l?lk(l,{theme:e,className:r,isFocused:o,inputClassName:i&&i.className}):{root:Tr("ms-BasePicker",r\|\|""),text:Tr("ms-BasePicker-text",ak.pickerText,this.state.isFocused&&ak.inputFocused,s&&ak.inputDisabled),itemsWrapper:ak.pickerItems,input:Tr("ms-BasePicker-input",ak.pickerInput,i&&i.className),screenReaderText:ak.screenReaderOnly},r=this.props["aria-label"]\|\|(null==i?void 0:i["aria-label"]);return gt.createElement("div",{ref:this.root,onBlur:this.onBlur,onFocus:this.onFocus},gt.createElement("div",{className:o.root,onKeyDown:this.onKeyDown},this.renderCustomAlert(o.screenReaderText),gt.createElement("div",{className:o.text,"aria-owns":n\|\|void 0},gt.createElement(ki,ht({},i,{className:o.input,componentRef:this.input,onFocus:this.onInputFocus,onBlur:this.onInputBlur,onClick:this.onClick,onInputValueChange:this.onInputChange,suggestedDisplayValue:t,"aria-activedescendant":this.getActiveDescendant(),"aria-controls":n\|\|void 0,"aria-expanded":!!this.state.suggestionsVisible,"aria-haspopup":"listbox","aria-label":r,role:"combobox",id:null!=i&&i.id?i.id:this._ariaMap.combobox,disabled:s,onInputChange:this.props.onInputChange})))),this.renderSuggestions(),gt.createElement(Pv,{selection:this.selection,selectionMode:dv.single},gt.createElement("div",{id:this._ariaMap.selectedItems,className:"ms-BasePicker-selectedItems",role:c,"aria-label":a\|\|r},this.renderItems())))},Ck.prototype.onBackspace=function(e){},Ck),dk={root:"ms-PickerPersona-container",itemContent:"ms-PickerItem-content",removeButton:"ms-PickerItem-removeButton",isSelected:"is-selected",isInvalid:"is-invalid"},pk=Fn(),hk=function(e){var t=e.item,o=e.onRemoveItem,n=e.index,r=e.selected,i=e.removeButtonAriaLabel,s=e.styles,a=e.theme,l=e.className,c=e.disabled,u=e.removeButtonIconProps,e=_s(),a=pk(s,{theme:a,className:l,selected:r,disabled:c,invalid:t.ValidationState===Wx.warning}),l=a.subComponentStyles?a.subComponentStyles.persona:void 0,r=a.subComponentStyles?a.subComponentStyles.personaCoin:void 0;return gt.createElement("div",{className:a.root,role:"listitem"},gt.createElement("div",{className:a.itemContent,id:"selectedItemPersona-"+e},gt.createElement(XC,ht({size:Pr.size24,styles:l,coinProps:{styles:r}},t))),gt.createElement(rd,{id:e,onClick:o,disabled:c,iconProps:null!=u?u:{iconName:"Cancel"},styles:{icon:{fontSize:"12px"}},className:a.removeButton,ariaLabel:i,"aria-labelledby":e+" selectedItemPersona-"+e,"data-selection-index":n}))},mk=In(hk,function(e){var t,o=e.className,n=e.theme,r=e.selected,i=e.invalid,s=e.disabled,a=n.palette,l=n.semanticColors,c=n.fonts,e=zo(dk,n),u=[r&&!i&&!s&&{color:a.white,selectors:((t={":hover":{color:a.white}})[Yt]={color:"HighlightText"},t)},(i&&!r\|\|i&&r&&s)&&{color:a.redDark,borderBottom:"2px dotted "+a.redDark,selectors:((t={})["."+e.root+":hover &"]={color:a.redDark},t)},i&&r&&!s&&{color:a.white,borderBottom:"2px dotted "+a.white},s&&{selectors:((u={})[Yt]={color:"GrayText"},u)}],c=[i&&{fontSize:c.xLarge.fontSize}];return{root:[e.root,bo(n,{inset:-2}),{borderRadius:15,display:"inline-flex",alignItems:"center",background:a.neutralLighter,margin:"1px 2px",cursor:"default",userSelect:"none",maxWidth:300,verticalAlign:"middle",minWidth:0,selectors:((n={":hover":{background:r\|\|s?"":a.neutralLight}})[Yt]=[{border:"1px solid WindowText"},s&&{borderColor:"GrayText"}],n)},r&&!s&&[e.isSelected,{background:a.themePrimary,selectors:((n={})[Yt]=ht({borderColor:"HighLight",background:"Highlight"},{forcedColorAdjust:"none",MsHighContrastAdjust:"none"}),n)}],i&&[e.isInvalid],i&&r&&!s&&{background:a.redDark},o],itemContent:[e.itemContent,{flex:"0 1 auto",minWidth:0,maxWidth:"100%",overflow:"hidden"}],removeButton:[e.removeButton,{borderRadius:15,color:a.neutralPrimary,flex:"0 0 auto",width:24,height:24,selectors:{":hover":{background:a.neutralTertiaryAlt,color:a.neutralDark}}},r&&[{color:a.white,selectors:((r={":hover":{color:a.white,background:a.themeDark},":active":{color:a.white,background:a.themeDarker}})[Yt]={color:"HighlightText"},r)},i&&{selectors:{":hover":{background:a.red},":active":{background:a.redDark}}}],s&&{selectors:((s={})["."+Vu.msButtonIcon]={color:l.buttonText},s)}],subComponentStyles:{persona:{primaryText:u},personaCoin:{initials:c}}}},void 0,{scope:"PeoplePickerItem"}),gk={root:"ms-PeoplePicker-personaContent",personaWrapper:"ms-PeoplePicker-Persona"},fk=Fn(),vk=function(e){var t=e.personaProps,o=e.suggestionsProps,n=e.compact,r=e.styles,i=e.theme,e=e.className,o=fk(r,{theme:i,className:o&&o.suggestionsItemClassName\|\|e}),e=o.subComponentStyles&&o.subComponentStyles.persona?o.subComponentStyles.persona:void 0;return gt.createElement("div",{className:o.root},gt.createElement(XC,ht({size:Pr.size24,styles:e,className:o.personaWrapper,showSecondaryText:!n,showOverflowTooltip:!1},t)))},bk=In(vk,function(e){var t=e.className,o=e.theme,n=zo(gk,o),e={selectors:((e={})["."+Kx.isSuggested+" &"]={selectors:((o={})[Yt]={color:"HighlightText"},o)},e["."+n.root+":hover &"]={selectors:((o={})[Yt]={color:"HighlightText"},o)},e)};return{root:[n.root,{width:"100%",padding:"4px 12px"},t],personaWrapper:[n.personaWrapper,{width:180}],subComponentStyles:{persona:{primaryText:e,secondaryText:e}}}},void 0,{scope:"PeoplePickerItemSuggestion"}),yk={root:"ms-BasePicker",text:"ms-BasePicker-text",itemsWrapper:"ms-BasePicker-itemsWrapper",input:"ms-BasePicker-input"};function Ck(){return null!==$x&&$x.apply(this,arguments)\|\|this}function _k(e){var n=ek.call(this,e)\|\|this;n.root=gt.createRef(),n.input=gt.createRef(),n.suggestionElement=gt.createRef(),n.SuggestionOfProperType=qx,n._styledSuggestions=In(n.SuggestionOfProperType,Jx,void 0,{scope:"Suggestions"}),n.dismissSuggestions=function(t){function e(){var e=!0;n.props.onDismiss&&(e=n.props.onDismiss(t,n.suggestionStore.currentSuggestion?n.suggestionStore.currentSuggestion.item:void 0)),t&&t.defaultPrevented\|\|!1===e\|\|!n.canAddItems()\|\|!n.suggestionStore.hasSelectedSuggestion()\|\|!n.state.suggestedDisplayValue\|\|n.addItemByIndex(0)}n.currentPromise?n.currentPromise.then(e):e(),n.setState({suggestionsVisible:!1})},n.refocusSuggestions=function(e){n.resetFocus(),n.suggestionStore.suggestions&&0<n.suggestionStore.suggestions.length&&(e===En.up?n.suggestionStore.setSelectedSuggestion(n.suggestionStore.suggestions.length-1):e===En.down&&n.suggestionStore.setSelectedSuggestion(0))},n.onInputChange=function(e){n.updateValue(e),n.setState({moreSuggestionsAvailable:!0,isMostRecentlyUsedVisible:!1})},n.onSuggestionClick=function(e,t,o){n.addItemByIndex(o)},n.onSuggestionRemove=function(e,t,o){n.props.onRemoveSuggestion&&n.props.onRemoveSuggestion(t),n.suggestionStore.removeSuggestion(o)},n.onInputFocus=function(e){n.selection.setAllSelected(!1),n.state.isFocused\|\|(n._userTriggeredSuggestions(),n.props.inputProps&&n.props.inputProps.onFocus&&n.props.inputProps.onFocus(e))},n.onInputBlur=function(e){n.props.inputProps&&n.props.inputProps.onBlur&&n.props.inputProps.onBlur(e)},n.onBlur=function(e){var t;n.state.isFocused&&(t=e.relatedTarget,(t=null===e.relatedTarget?document.activeElement:t)&&!$i(n.root.current,t)&&(n.setState({isFocused:!1}),n.props.onBlur&&n.props.onBlur(e)))},n.onClick=function(e){void 0!==n.props.inputProps&&void 0!==n.props.inputProps.onClick&&n.props.inputProps.onClick(e),0===e.button&&n._userTriggeredSuggestions()},n.onFocus=function(){n.state.isFocused\|\|n.setState({isFocused:!0})},n.onKeyDown=function(e){var t=e.which;switch(t){case En.escape:n.state.suggestionsVisible&&(n.setState({suggestionsVisible:!1}),e.preventDefault(),e.stopPropagation());break;case En.tab:case En.enter:n.suggestionElement.current&&n.suggestionElement.current.hasSuggestedActionSelected()?n.suggestionElement.current.executeSelectedAction():!e.shiftKey&&n.suggestionStore.hasSelectedSuggestion()&&n.state.suggestionsVisible?(n.completeSuggestion(),e.preventDefault(),e.stopPropagation()):n._completeGenericSuggestion();break;case En.backspace:n.props.disabled\|\|n.onBackspace(e),e.stopPropagation();break;case En.del:n.props.disabled\|\|(n.input.current&&e.target===n.input.current.inputElement&&n.state.suggestionsVisible&&-1!==n.suggestionStore.currentIndex?(n.props.onRemoveSuggestion&&n.props.onRemoveSuggestion(n.suggestionStore.currentSuggestion.item),n.suggestionStore.removeSuggestion(n.suggestionStore.currentIndex),n.forceUpdate()):n.onBackspace(e)),e.stopPropagation();break;case En.up:n.input.current&&e.target===n.input.current.inputElement&&n.state.suggestionsVisible&&(n.suggestionElement.current&&n.suggestionElement.current.tryHandleKeyDown(t,n.suggestionStore.currentIndex)?(e.preventDefault(),e.stopPropagation(),n.forceUpdate()):n.suggestionElement.current&&n.suggestionElement.current.hasSuggestedAction()&&0===n.suggestionStore.currentIndex?(e.preventDefault(),e.stopPropagation(),n.suggestionElement.current.focusAboveSuggestions(),n.suggestionStore.deselectAllSuggestions(),n.forceUpdate()):n.suggestionStore.previousSuggestion()&&(e.preventDefault(),e.stopPropagation(),n.onSuggestionSelect()));break;case En.down:n.input.current&&e.target===n.input.current.inputElement&&n.state.suggestionsVisible&&(n.suggestionElement.current&&n.suggestionElement.current.tryHandleKeyDown(t,n.suggestionStore.currentIndex)?(e.preventDefault(),e.stopPropagation(),n.forceUpdate()):n.suggestionElement.current&&n.suggestionElement.current.hasSuggestedAction()&&n.suggestionStore.currentIndex+1===n.suggestionStore.suggestions.length?(e.preventDefault(),e.stopPropagation(),n.suggestionElement.current.focusBelowSuggestions(),n.suggestionStore.deselectAllSuggestions(),n.forceUpdate()):n.suggestionStore.nextSuggestion()&&(e.preventDefault(),e.stopPropagation(),n.onSuggestionSelect()))}},n.onItemChange=function(e,t){var o=n.state.items;0<=t&&((o=o)[t]=e,n._updateSelectedItems(o))},n.onGetMoreResults=function(){n.setState({isSearching:!0},function(){var e,t;n.props.onGetMoreResults&&n.input.current?(t=e=n.props.onGetMoreResults(n.input.current.value,n.state.items),Array.isArray(e)?(n.updateSuggestions(e),n.setState({isSearching:!1})):t.then&&t.then(function(e){n.updateSuggestions(e),n.setState({isSearching:!1})})):n.setState({isSearching:!1}),n.input.current&&n.input.current.focus(),n.setState({moreSuggestionsAvailable:!1,isResultsFooterVisible:!0})})},n.completeSelection=function(e){n.addItem(e),n.updateValue(""),n.input.current&&n.input.current.clear(),n.setState({suggestionsVisible:!1})},n.addItemByIndex=function(e){n.completeSelection(n.suggestionStore.getSuggestionAtIndex(e).item)},n.addItem=function(e){var t=n.props.onItemSelected?n.props.onItemSelected(e):e;null!==t&&((e=t)&&t.then?t.then(function(e){e=n.state.items.concat([e]);n._updateSelectedItems(e)}):(e=n.state.items.concat([e]),n._updateSelectedItems(e)),n.setState({suggestedDisplayValue:"",selectionRemoved:void 0}))},n.removeItem=function(e){var t=n.state.items,o=t.indexOf(e);0<=o&&(o=t.slice(0,o).concat(t.slice(o+1)),n.setState({selectionRemoved:e}),n._updateSelectedItems(o))},n.removeItems=function(t){var e=n.state.items.filter(function(e){return-1===t.indexOf(e)});n._updateSelectedItems(e)},n._shouldFocusZoneEnterInnerZone=function(e){if(n.state.suggestionsVisible)switch(e.which){case En.up:case En.down:return!0}return e.which===En.enter},n._onResolveSuggestions=function(e){var t=n.props.onResolveSuggestions(e,n.state.items);null!==t&&n.updateSuggestionsList(t,e)},n._completeGenericSuggestion=function(){var e;n.props.onValidateInput&&n.input.current&&n.props.onValidateInput(n.input.current.value)!==Wx.invalid&&n.props.createGenericItem&&(e=n.props.createGenericItem(n.input.current.value,n.props.onValidateInput(n.input.current.value)),n.suggestionStore.createGenericSuggestion(e),n.completeSuggestion())},n._userTriggeredSuggestions=function(){var e;n.state.suggestionsVisible\|\|((e=n.input.current?n.input.current.value:"")?0===n.suggestionStore.suggestions.length?n._onResolveSuggestions(e):n.setState({isMostRecentlyUsedVisible:!1,suggestionsVisible:!0}):n.onEmptyInputFocus())},fi(n),n._async=new Si(n);e=e.selectedItems\|\|e.defaultSelectedItems\|\|[];return n._id=_s(),n._ariaMap={selectedItems:"selected-items-"+n._id,selectedSuggestionAlert:"selected-suggestion-alert-"+n._id,suggestionList:"suggestion-list-"+n._id,combobox:"combobox-"+n._id},n.suggestionStore=new Yx,n.selection=new fv({onSelectionChanged:function(){return n.onSelectionChange()}}),n.selection.setItems(e),n.state={items:e,suggestedDisplayValue:"",isMostRecentlyUsedVisible:!1,moreSuggestionsAvailable:!1,isFocused:!1,isSearching:!1,selectedIndices:[],selectionRemoved:void 0},n}function Sk(e){var t=e.className,o=e.theme,n=e.isFocused,r=e.inputClassName,i=e.disabled;if(!o)throw new Error("theme is undefined or null in base BasePicker getStyles function.");var s=o.semanticColors,a=o.effects,l=o.fonts,c=s.inputBorder,u=s.inputBorderHovered,d=s.inputFocusBorderAlt,p=zo(yk,o),e=[l.medium,{color:s.inputPlaceholderText,opacity:1,selectors:((h={})[Yt]={color:"GrayText"},h)}],h={color:s.disabledText,selectors:((o={})[Yt]={color:"GrayText"},o)},o="rgba(218, 218, 218, 0.29)";return{root:[p.root,t],text:[p.text,{display:"flex",position:"relative",flexWrap:"wrap",alignItems:"center",boxSizing:"border-box",minWidth:180,minHeight:30,border:"1px solid "+c,borderRadius:a.roundedCorner2},!n&&!i&&{selectors:{":hover":{borderColor:u}}},n&&!i&&_o(d,a.roundedCorner2),i&&{borderColor:o,selectors:((o={":after":{content:'""',position:"absolute",top:0,right:0,bottom:0,left:0,background:o}})[Yt]={borderColor:"GrayText",selectors:{":after":{background:"none"}}},o)}],itemsWrapper:[p.itemsWrapper,{display:"flex",flexWrap:"wrap",maxWidth:"100%"}],input:[p.input,l.medium,{height:30,border:"none",flexGrow:1,outline:"none",padding:"0 6px 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null!==xk&&xk.apply(this,arguments)\|\|this}function Bk(){return null!==kk&&kk.apply(this,arguments)\|\|this}function Fk(){return null!==wk&&wk.apply(this,arguments)\|\|this}function Ak(){return null!==Ik&&Ik.apply(this,arguments)\|\|this}function Lk(){return null!==Dk&&Dk.apply(this,arguments)\|\|this}function Hk(e,t){var o={key:e,primaryText:e,imageInitials:"!",ValidationState:t};return t!==Wx.warning&&(o.imageInitials=Cr(e,Pn())),o}var Ok,zk=In(Pk,Sk,void 0,{scope:"NormalPeoplePicker"}),Wk=In(Rk,Sk,void 0,{scope:"CompactPeoplePicker"}),Vk=In(Mk,Sk,void 0,{scope:"ListPeoplePickerBase"}),Kk={root:"ms-TagItem",text:"ms-TagItem-text",close:"ms-TagItem-close",isSelected:"is-selected"},Gk=Fn(),Uk=function(e){var t=e.theme,o=e.styles,n=e.selected,r=e.disabled,i=e.enableTagFocusInDisabledPicker,s=e.children,a=e.className,l=e.index,c=e.onRemoveItem,u=e.removeButtonAriaLabel,d=e.title,d=void 0===d?"string"==typeof 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t=e.className,o=e.theme,n=e.selected,r=e.disabled,i=o.palette,s=o.effects,a=o.fonts,l=o.semanticColors,e=zo(Kk,o);return{root:[e.root,a.medium,bo(o),{boxSizing:"content-box",flexShrink:"1",margin:2,height:26,lineHeight:26,cursor:"default",userSelect:"none",display:"flex",flexWrap:"nowrap",maxWidth:300,minWidth:0,borderRadius:s.roundedCorner2,color:l.inputText,background:i.neutralLighter,selectors:((l={":hover":[!r&&!n&&{color:i.neutralDark,background:i.neutralLight,selectors:{".ms-TagItem-close":{color:i.neutralPrimary}}},r&&{background:i.neutralLighter}],":focus-within":[!r&&{background:i.themePrimary,color:i.white}]})[Yt]={border:"1px solid "+(n?"WindowFrame":"WindowText")},l)},r&&{selectors:((l={})[Yt]={borderColor:"GrayText"},l)},n&&!r&&[e.isSelected],t],text:[e.text,{overflow:"hidden",textOverflow:"ellipsis",whiteSpace:"nowrap",minWidth:30,margin:"0 8px"},r&&{selectors:((t={})[Yt]={color:"GrayText"},t)}],close:[e.close,{color:i.neutralSecondary,width:30,height:"100%",flex:"0 0 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0===s?c.props.title:s,l=t.styles,s=t.theme,t="number"==typeof c.props.percentComplete?Math.min(100,Math.max(0,100c.props.percentComplete)):void 0,l=gw(l,{theme:s,className:r,barHeight:n,indeterminate:void 0===t}),s={width:void 0!==t?t+"%":void 0,transition:void 0!==t&&t<.01?"none":void 0},r=void 0!==t?0:void 0,n=void 0!==t?100:void 0,t=void 0!==t?Math.floor(t):void 0;return gt.createElement("div",{className:l.itemProgress},gt.createElement("div",{className:l.progressTrack}),gt.createElement("div",{className:l.progressBar,style:s,role:"progressbar","aria-describedby":i?c._descriptionId:void 0,"aria-labelledby":a?c._labelId:void 0,"aria-valuemin":r,"aria-valuemax":n,"aria-valuenow":t,"aria-valuetext":o}))};e=_s("progress-indicator");return c._labelId=e+"-label",c._descriptionId=e+"-description",c}function xw(e,t){return{color:e,selectors:((e={})[Yt]={color:t},e)}}(n=hw=hw\|\|{})[n.Small=0]="Small",n[n.Large=1]="Large";function kw(e){return gt.createElement("div",{className:e.classNames.ratingStar},gt.createElement(Wr,{className:e.classNames.ratingStarBack,iconName:0===e.fillPercentage\|\|100===e.fillPercentage?e.icon:e.unselectedIcon}),!e.disabled&&gt.createElement(Wr,{className:e.classNames.ratingStarFront,iconName:e.icon,style:{width:e.fillPercentage+"%"}}))}function ww(e,t){return e+"-star-"+(t-1)}var Iw=Fn(),Dw=gt.forwardRef(function(e,t){var o,i=iu("Rating"),s=iu("RatingLabel"),n=e.ariaLabel,a=e.ariaLabelFormat,l=e.disabled,r=e.getAriaLabel,c=e.styles,u=e.min,d=void 0===u?e.allowZeroStars?0:1:u,p=e.max,h=void 0===p?5:p,m=e.readOnly,g=e.size,u=e.theme,p=e.icon,f=void 0===p?"FavoriteStarFill":p,p=e.unselectedIcon,v=void 0===p?"FavoriteStar":p,b=e.onRenderStar,p=Math.max(d,0),d=Fh(e.rating,e.defaultRating,e.onChange),y=d[0],C=d[1],_=(d=h,Math.min(Math.max(null!=y?y:p,p),d));d=e.componentRef,o=_,gt.useImperativeHandle(d,function(){return{rating:o}},[o]);for(var e=ur(e,cr),S=Iw(c,{disabled:l,readOnly:m,theme:u}),u=null==r?void 0:r(_,h),r=n\|\|u,x=[],k=1;k<=h;k++)!function(t){var e,o,n,r=(r=t,e=_,o=Math.ceil(e),n=100,r===e?n=100:r===o?n=e%1100:o<r&&(n=0),n),n=function(e){void 0!==y&&Math.ceil(y)===t\|\|C(t,e)};x.push(gt.createElement("button",ht({className:Tr(S.ratingButton,g===hw.Large?S.ratingStarIsLarge:S.ratingStarIsSmall),id:ww(i,t),key:t},t===Math.ceil(_)&&{"data-is-current":!0},{onFocus:n,onClick:n,disabled:!(!l&&!m),role:"radio","aria-hidden":m?"true":void 0,type:"button","aria-checked":t===Math.ceil(_)}),gt.createElement("span",{id:s+"-"+t,className:S.labelText},Jp(a\|\|"",t,h)),(r={fillPercentage:r,disabled:l,classNames:S,icon:0<r?f:v,starNum:t,unselectedIcon:v},b?b(r):gt.createElement(kw,ht({},r)))))}(k);n=g===hw.Large?S.rootIsLarge:S.rootIsSmall;return gt.createElement("div",ht({ref:t,className:Tr("ms-Rating-star",S.root,n),"aria-label":m?void 0:r,id:i,role:m?void 0:"radiogroup"},e),gt.createElement(Zs,ht({direction:Ei.bidirectional,className:Tr(S.ratingFocusZone,n),defaultActiveElement:"#"+ww(i,Math.ceil(_))},m&&{allowFocusRoot:!0,disabled:!0,role:"textbox","aria-label":u,"aria-readonly":!0,"data-is-focusable":!0,tabIndex:0}),x))});Dw.displayName="RatingBase";var Ew,Tw=In(Dw,function(e){var t=e.disabled,o=e.readOnly,n=e.theme,r=n.semanticColors,i=n.palette,s=zo(_w,n),a=i.neutralSecondary,l=i.themePrimary,e=i.themeDark,i=i.neutralPrimary,r=r.disabledBodySubtext;return{root:[s.root,n.fonts.medium,!t&&!o&&{selectors:{"&:hover":{selectors:{".ms-RatingStar-back":xw(i,"Highlight")}}}}],rootIsSmall:[s.rootIsSmall,{height:"32px"}],rootIsLarge:[s.rootIsLarge,{height:"36px"}],ratingStar:[s.ratingStar,{display:"inline-block",position:"relative",height:"inherit"}],ratingStarBack:[s.ratingStarBack,{color:a,width:"100%"},t&&xw(r,"GrayText")],ratingStarFront:[s.ratingStarFront,{position:"absolute",height:"100 %",left:"0",top:"0",textAlign:"center",verticalAlign:"middle",overflow:"hidden"},xw(i,"Highlight")],ratingButton:[bo(n),s.ratingButton,{backgroundColor:"transparent",padding:"8px 2px",boxSizing:"content-box",margin:"0px",border:"none",cursor:"pointer",selectors:{"&:disabled":{cursor:"default"},"&[disabled]":{cursor:"default"}}},!t&&!o&&{selectors:{"&:hover ~ .ms-Rating-button":{selectors:{".ms-RatingStar-back":xw(a,"WindowText"),".ms-RatingStar-front":xw(a,"WindowText")}},"&:hover":{selectors:{".ms-RatingStar-back":{color:l},".ms-RatingStar-front":{color:e}}}}},t&&{cursor:"default"}],ratingStarIsSmall:[s.ratingStarIsSmall,{fontSize:"16px",lineHeight:"16px",height:"16px"}],ratingStarIsLarge:[s.ratingStartIsLarge,{fontSize:"20px",lineHeight:"20px",height:"20px"}],labelText:[s.labelText,So],ratingFocusZone:[bo(n),s.ratingFocusZone,{display:"inline-block"}]}},void 0,{scope:"Rating"}),Pw={root:"ms-ScrollablePane",contentContainer:"ms-ScrollablePane--contentContainer"},Rw={auto:"auto",always:"always"},Mw=gt.createContext({scrollablePane:void 0}),Nw=Fn(),Bw=(l(Vw,Ew=gt.Component),Object.defineProperty(Vw.prototype,"root",{get:function(){return this._root.current},enumerable:!1,configurable:!0}),Object.defineProperty(Vw.prototype,"stickyAbove",{get:function(){return this._stickyAboveRef.current},enumerable:!1,configurable:!0}),Object.defineProperty(Vw.prototype,"stickyBelow",{get:function(){return this._stickyBelowRef.current},enumerable:!1,configurable:!0}),Object.defineProperty(Vw.prototype,"contentContainer",{get:function(){return this._contentContainer.current},enumerable:!1,configurable:!0}),Vw.prototype.componentDidMount=function(){var n=this,e=this.props.initialScrollPosition;this._events.on(this.contentContainer,"scroll",this._onScroll),this._events.on(window,"resize",this._onWindowResize),this.contentContainer&&e&&(this.contentContainer.scrollTop=e),this.setStickiesDistanceFromTop(),this._stickies.forEach(function(e){n.sortSticky(e)}),this.notifySubscribers(),"MutationObserver"in window&&(this._mutationObserver=new MutationObserver(function(t){var o,e=n._getScrollbarHeight();e!==n.state.scrollbarHeight&&n.setState({scrollbarHeight:e}),n.notifySubscribers(),t.some(function(e){return null!==this.stickyAbove&&null!==this.stickyBelow&&(this.stickyAbove.contains(e.target)\|\|this.stickyBelow.contains(e.target))}.bind(n))?n.updateStickyRefHeights():(o=[],n._stickies.forEach(function(e){e.root&&e.root.contains(t[0].target)&&o.push(e)}),o.length&&o.forEach(function(e){e.forceUpdate()}))}),this.root&&this._mutationObserver.observe(this.root,{childList:!0,attributes:!0,subtree:!0,characterData:!0}))},Vw.prototype.componentWillUnmount=function(){this._events.dispose(),this._async.dispose(),this._mutationObserver&&this._mutationObserver.disconnect()},Vw.prototype.shouldComponentUpdate=function(e,t){return this.props.children!==e.children\|\|this.props.initialScrollPosition!==e.initialScrollPosition\|\|this.props.className!==e.className\|\|this.state.stickyTopHeight!==t.stickyTopHeight\|\|this.state.stickyBottomHeight!==t.stickyBottomHeight\|\|this.state.scrollbarWidth!==t.scrollbarWidth\|\|this.state.scrollbarHeight!==t.scrollbarHeight},Vw.prototype.componentDidUpdate=function(e,t){var o=this.props.initialScrollPosition;this.contentContainer&&"number"==typeof o&&e.initialScrollPosition!==o&&(this.contentContainer.scrollTop=o),t.stickyTopHeight===this.state.stickyTopHeight&&t.stickyBottomHeight===this.state.stickyBottomHeight\|\|this.notifySubscribers(),this._async.setTimeout(this._onWindowResize,0)},Vw.prototype.render=function(){var e=this.props,t=e.className,o=e.scrollContainerFocus,n=e.scrollContainerAriaLabel,r=e.theme,i=e.styles,s=this.state,e=s.stickyTopHeight,s=s.stickyBottomHeight,t=Nw(i,{theme:r,className:t,scrollbarVisibility:this.props.scrollbarVisibility}),n=o?{role:"group",tabIndex:0,"aria-label":n}:{};return gt.createElement("div",ht({},ur(this.props,cr),{ref:this._root,className:t.root}),gt.createElement("div",{ref:this._stickyAboveRef,className:t.stickyAbove,style:this._getStickyContainerStyle(e,!0)}),gt.createElement("div",ht({ref:this._contentContainer},n,{className:t.contentContainer,"data-is-scrollable":!0}),gt.createElement(Mw.Provider,{value:this._getScrollablePaneContext()},this.props.children)),gt.createElement("div",{className:t.stickyBelow,style:this._getStickyContainerStyle(s,!1)},gt.createElement("div",{ref:this._stickyBelowRef,className:t.stickyBelowItems})))},Vw.prototype.setStickiesDistanceFromTop=function(){var t=this;this.contentContainer&&this._stickies.forEach(function(e){e.setDistanceFromTop(t.contentContainer)})},Vw.prototype.forceLayoutUpdate=function(){this._onWindowResize()},Vw.prototype._checkStickyStatus=function(e){this.stickyAbove&&this.stickyBelow&&this.contentContainer&&e.nonStickyContent&&(e.state.isStickyTop\|\|e.state.isStickyBottom?(e.state.isStickyTop&&!this.stickyAbove.contains(e.nonStickyContent)&&e.stickyContentTop&&e.addSticky(e.stickyContentTop),e.state.isStickyBottom&&!this.stickyBelow.contains(e.nonStickyContent)&&e.stickyContentBottom&&e.addSticky(e.stickyContentBottom)):this.contentContainer.contains(e.nonStickyContent)\|\|e.resetSticky())},Vw.prototype._getScrollbarWidth=function(){var e=this.contentContainer;return e?e.offsetWidth-e.clientWidth:0},Vw.prototype._getScrollbarHeight=function(){var e=this.contentContainer;return e?e.offsetHeight-e.clientHeight:0},Vw),Fw=In(Bw,function(e){var t=e.className,o=e.theme,n=zo(Pw,o),r={position:"absolute",pointerEvents:"none"},i={position:"absolute",top:0,right:0,bottom:0,left:0,WebkitOverflowScrolling:"touch"};return{root:[n.root,o.fonts.medium,i,t],contentContainer:[n.contentContainer,{overflowY:"always"===e.scrollbarVisibility?"scroll":"auto"},i],stickyAbove:[{top:0,zIndex:1,selectors:((i={})[Yt]={borderBottom:"1px solid WindowText"},i)},r],stickyBelow:[{bottom:0,selectors:((i={})[Yt]={borderTop:"1px solid WindowText"},i)},r],stickyBelowItems:[{bottom:0},r,{width:"100%"}]}},void 0,{scope:"ScrollablePane"}),Aw="SearchBox",Lw={root:{height:"auto"},icon:{fontSize:"12px"}},Hw={iconName:"Clear"},Ow={ariaLabel:"Clear text"},zw=Fn(),Ww=gt.forwardRef(function(o,e){var t,n,r=o.ariaLabel,i=o.className,s=o.defaultValue,a=void 0===s?"":s,l=o.disabled,c=o.underlined,u=o.styles,d=o.labelText,p=o.placeholder,h=void 0===p?d:p,m=o.theme,g=o.clearButtonProps,f=void 0===g?Ow:g,v=o.disableAnimation,b=void 0!==v&&v,s=o.showIcon,d=void 0!==s&&s,y=o.onClear,C=o.onBlur,_=o.onEscape,S=o.onSearch,x=o.onKeyDown,p=o.iconProps,g=o.role,k=o.onChange,w=o.onChanged,v=gt.useState(!1),s=v[0],I=v[1],D=gt.useRef(),v=Fh(o.value,a,function(e,t){e&&e.timeStamp===D.current\|\|(D.current=null==e?void 0:e.timeStamp,null==k\|\|k(e,t),null==w\|\|w(t))}),a=v[0],E=v[1],T=String(a),a=gt.useRef(null),P=gt.useRef(null),a=_r(a,e),e=iu(Aw,o.id),R=f.onClick,u=zw(u,{theme:m,className:i,underlined:c,hasFocus:s,disabled:l,hasInput:0<T.length,disableAnimation:b,showIcon:d}),m=ur(o,Zn,["className","placeholder","onFocus","onBlur","value","role"]),M=gt.useCallback(function(e){var t;null==y\|\|y(e),e.defaultPrevented\|\|(E(""),null===(t=P.current)\|\|void 0===t\|\|t.focus(),e.stopPropagation(),e.preventDefault())},[y,E]),i=gt.useCallback(function(e){null==R\|\|R(e),e.defaultPrevented\|\|M(e)},[R,M]),c=gt.useCallback(function(e){I(!1),null==C\|\|C(e)},[C]),b=function(e){E(e.target.value,e)};return d=o.componentRef,t=P,n=s,gt.useImperativeHandle(d,function(){return{focus:function(){var e;return null===(e=t.current)\|\|void 0===e?void 0:e.focus()},hasFocus:function(){return n}}},[t,n]),gt.createElement("div",{role:g,ref:a,className:u.root,onFocusCapture:function(e){var t;I(!0),null===(t=o.onFocus)\|\|void 0===t\|\|t.call(o,e)}},gt.createElement("div",{className:u.iconContainer,onClick:function(){P.current&&(P.current.focus(),P.current.selectionStart=P.current.selectionEnd=0)},"aria-hidden":!0},gt.createElement(Wr,ht({iconName:"Search"},p,{className:u.icon}))),gt.createElement("input",ht({},m,{id:e,className:u.field,placeholder:h,onChange:b,onInput:b,onBlur:c,onKeyDown:function(e){switch(e.which){case En.escape:null==_\|\|_(e),T&&!e.defaultPrevented&&M(e);break;case En.enter:S&&(S(T),e.preventDefault(),e.stopPropagation());break;default:null==x\|\|x(e),e.defaultPrevented&&e.stopPropagation()}},value:T,disabled:l,role:"searchbox","aria-label":r,ref:P})),0<T.length&&gt.createElement("div",{className:u.clearButton},gt.createElement(rd,ht({onBlur:c,styles:Lw,iconProps:Hw},f,{onClick:i}))))});function Vw(e){var u=Ew.call(this,e)\|\|this;return u._root=gt.createRef(),u._stickyAboveRef=gt.createRef(),u._stickyBelowRef=gt.createRef(),u._contentContainer=gt.createRef(),u.subscribe=function(e){u._subscribers.add(e)},u.unsubscribe=function(e){u._subscribers.delete(e)},u.addSticky=function(e){u._stickies.add(e),u.contentContainer&&(e.setDistanceFromTop(u.contentContainer),u.sortSticky(e))},u.removeSticky=function(e){u._stickies.delete(e),u._removeStickyFromContainers(e),u.notifySubscribers()},u.sortSticky=function(e,t){u.stickyAbove&&u.stickyBelow&&(t&&u._removeStickyFromContainers(e),e.canStickyTop&&e.stickyContentTop&&u._addToStickyContainer(e,u.stickyAbove,e.stickyContentTop),e.canStickyBottom&&e.stickyContentBottom&&u._addToStickyContainer(e,u.stickyBelow,e.stickyContentBottom))},u.updateStickyRefHeights=function(){var e=u._stickies,n=0,r=0;e.forEach(function(e){var t=e.state,o=t.isStickyTop,t=t.isStickyBottom;e.nonStickyContent&&(o&&(n+=e.nonStickyContent.offsetHeight),t&&(r+=e.nonStickyContent.offsetHeight),u._checkStickyStatus(e))}),u.setState({stickyTopHeight:n,stickyBottomHeight:r})},u.notifySubscribers=function(){u.contentContainer&&u._subscribers.forEach(function(e){e(u.contentContainer,u.stickyBelow)})},u.getScrollPosition=function(){return u.contentContainer?u.contentContainer.scrollTop:0},u.syncScrollSticky=function(e){e&&u.contentContainer&&e.syncScroll(u.contentContainer)},u._getScrollablePaneContext=function(){return{scrollablePane:{subscribe:u.subscribe,unsubscribe:u.unsubscribe,addSticky:u.addSticky,removeSticky:u.removeSticky,updateStickyRefHeights:u.updateStickyRefHeights,sortSticky:u.sortSticky,notifySubscribers:u.notifySubscribers,syncScrollSticky:u.syncScrollSticky}}},u._addToStickyContainer=function(t,o,e){if(o.children.length){if(!o.contains(e)){var n=[].slice.call(o.children),r=[];u._stickies.forEach(function(e){(o===u.stickyAbove&&t.canStickyTop\|\|t.canStickyBottom)&&r.push(e)});for(var i=void 0,s=0,a=r.sort(function(e,t){return(e.state.distanceFromTop\|\|0)-(t.state.distanceFromTop\|\|0)}).filter(function(e){e=o===u.stickyAbove?e.stickyContentTop:e.stickyContentBottom;return!!e&&-1<n.indexOf(e)});s<a.length;s++){var l=a[s];if((l.state.distanceFromTop\|\|0)>=(t.state.distanceFromTop\|\|0)){i=l;break}}var c=null;i&&(c=o===u.stickyAbove?i.stickyContentTop:i.stickyContentBottom),o.insertBefore(e,c)}}else o.appendChild(e)},u._removeStickyFromContainers=function(e){u.stickyAbove&&e.stickyContentTop&&u.stickyAbove.contains(e.stickyContentTop)&&u.stickyAbove.removeChild(e.stickyContentTop),u.stickyBelow&&e.stickyContentBottom&&u.stickyBelow.contains(e.stickyContentBottom)&&u.stickyBelow.removeChild(e.stickyContentBottom)},u._onWindowResize=function(){var e=u._getScrollbarWidth(),t=u._getScrollbarHeight();u.setState({scrollbarWidth:e,scrollbarHeight:t}),u.notifySubscribers()},u._getStickyContainerStyle=function(e,t){return ht(ht({height:e},Pn(u.props.theme)?{right:"0",left:(u.state.scrollbarWidth\|\|u._getScrollbarWidth()\|\|0)+"px"}:{left:"0",right:(u.state.scrollbarWidth\|\|u._getScrollbarWidth()\|\|0)+"px"}),t?{top:"0"}:{bottom:(u.state.scrollbarHeight\|\|u._getScrollbarHeight()\|\|0)+"px"})},u._onScroll=function(){var t=u.contentContainer;t&&u._stickies.forEach(function(e){e.syncScroll(t)}),u._notifyThrottled()},u._subscribers=new Set,u._stickies=new Set,fi(u),u._async=new Si(u),u._events=new va(u),u.state={stickyTopHeight:0,stickyBottomHeight:0,scrollbarWidth:0,scrollbarHeight:0},u._notifyThrottled=u._async.throttle(u.notifySubscribers,50),u}Ww.displayName=Aw;var Kw,Gw={root:"ms-SearchBox",iconContainer:"ms-SearchBox-iconContainer",icon:"ms-SearchBox-icon",clearButton:"ms-SearchBox-clearButton",field:"ms-SearchBox-field"},Uw=In(Ww,function(e){var t=e.theme,o=e.underlined,n=e.disabled,r=e.hasFocus,i=e.className,s=e.hasInput,a=e.disableAnimation,l=e.showIcon,c=t.palette,u=t.fonts,d=t.semanticColors,p=t.effects,h=zo(Gw,t),m={color:d.inputPlaceholderText,opacity:1},g=c.neutralSecondary,f=c.neutralPrimary,v=c.neutralLighter,b=c.neutralLighter,e=c.neutralLighter;return{root:[h.root,u.medium,Uo,{color:d.inputText,backgroundColor:d.inputBackground,display:"flex",flexDirection:"row",flexWrap:"nowrap",alignItems:"stretch",padding:"1px 0 1px 4px",borderRadius:p.roundedCorner2,border:"1px solid "+d.inputBorder,height:32,selectors:((c={})[Yt]={borderColor:"WindowText"},c[":hover"]={borderColor:d.inputBorderHovered,selectors:((u={})[Yt]={borderColor:"Highlight"},u)},c[":hover ."+h.iconContainer]={color:d.inputIconHovered},c)},!r&&s&&{selectors:((c={})[":hover ."+h.iconContainer]={width:4},c[":hover ."+h.icon]={opacity:0,pointerEvents:"none"},c)},r&&["is-active",{position:"relative"},_o(d.inputFocusBorderAlt,o?0:p.roundedCorner2,o?"borderBottom":"border")],l&&[{selectors:((p={})[":hover ."+h.iconContainer]={width:32},p[":hover ."+h.icon]={opacity:1},p)}],n&&["is-disabled",{borderColor:v,backgroundColor:e,pointerEvents:"none",cursor:"default",selectors:((e={})[Yt]={borderColor:"GrayText"},e)}],o&&["is-underlined",{borderWidth:"0 0 1px 0",borderRadius:0,padding:"1px 0 1px 8px"}],o&&n&&{backgroundColor:"transparent"},s&&"can-clear",i],iconContainer:[h.iconContainer,{display:"flex",flexDirection:"column",justifyContent:"center",flexShrink:0,fontSize:16,width:32,textAlign:"center",color:d.inputIcon,cursor:"text"},r&&{width:4},n&&{color:d.inputIconDisabled},!a&&{transition:"width 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e.selectedItems?{items:e.selectedItems}:null},Object.defineProperty(qw.prototype,"items",{get:function(){return this.state.items},enumerable:!1,configurable:!0}),qw.prototype.removeSelectedItems=function(){this.state.items.length&&0<this.selection.getSelectedCount()&&this.removeItems(this.selection.getSelection())},qw.prototype.updateItems=function(e,t){var o=this;this.props.selectedItems?this.onChange(e):this.setState({items:e},function(){o._onSelectedItemsUpdated(e,t)})},qw.prototype.hasSelectedItems=function(){return 0<this.selection.getSelectedCount()},qw.prototype.componentDidUpdate=function(e,t){this.state.items&&this.state.items!==t.items&&this.selection.setItems(this.state.items)},qw.prototype.unselectAll=function(){this.selection.setAllSelected(!1)},qw.prototype.highlightedItems=function(){return this.selection.getSelection()},qw.prototype.componentDidMount=function(){this.selection.setItems(this.state.items)},Object.defineProperty(qw.prototype,"selection",{get:function(){var 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function(e){e.stopPropagation(),e.preventDefault(),t&&t()}},w1),h1=(l(k1,Jw=gt.Component),k1.prototype.render=function(){return gt.createElement("div",{ref:this.itemElement,onContextMenu:this._onClick},this.props.renderedItem,this.state.contextualMenuVisible?gt.createElement(Wu,{items:this.props.menuItems,shouldFocusOnMount:!0,target:this.itemElement.current,onDismiss:this._onCloseContextualMenu,directionalHint:Pa.bottomLeftEdge}):null)},k1),m1={root:"ms-EditingItem",input:"ms-EditingItem-input"},g1=(l(x1,Qw=gt.Component),x1.prototype.componentDidMount=function(){var e=(0,this.props.getEditingItemText)(this.props.item);this._editingFloatingPicker.current&&this._editingFloatingPicker.current.onQueryStringChanged(e),this._editingInput.value=e,this._editingInput.focus()},x1.prototype.render=function(){var e=_s(),t=ur(this.props,Zn),o=Fn()(Yw);return gt.createElement("div",{"aria-labelledby":"editingItemPersona-"+e,className:o.root},gt.createElement("input",ht({autoCapitalize:"off",autoComplete:"off"},t,{ref:this._resolveInputRef,onChange:this._onInputChange,onKeyDown:this._onInputKeyDown,onBlur:this._onInputBlur,onClick:this._onInputClick,"data-lpignore":!0,className:o.input,id:e})),this._renderEditingSuggestions())},x1.prototype._onInputKeyDown=function(e){e.which!==En.backspace&&e.which!==En.del\|\|e.stopPropagation()},x1),f1=(l(S1,Xw=jw),S1),v1=(l(_1,Zw=f1),_1.prototype._renderItem=function(e,t){var o=this,n=this.props.removeButtonAriaLabel,r=this.props.onExpandGroup,i={item:e,index:t,key:e.key\|\|t,selected:this.selection.isIndexSelected(t),onRemoveItem:function(){return o.removeItem(e)},onItemChange:this.onItemChange,removeButtonAriaLabel:n,onCopyItem:function(e){return o.copyItems([e])},onExpandItem:r?function(){return r(e)}:void 0,menuItems:this._createMenuItems(e)},t=0<i.menuItems.length;if(e.isEditing&&t)return gt.createElement(g1,ht({},i,{onRenderFloatingPicker:this.props.onRenderFloatingPicker,floatingPickerProps:this.props.floatingPickerProps,onEditingComplete:this._completeEditing,getEditingItemText:this.props.getEditingItemText}));n=(0,this.props.onRenderItem)(i);return t?gt.createElement(h1,{key:i.key,renderedItem:n,beginEditing:this._beginEditing,menuItems:this._createMenuItems(i.item),item:i.item}):n},_1.prototype._createMenuItems=function(e){var o=this,t=[];return this.props.editMenuItemText&&this.props.getEditingItemText&&t.push({key:"Edit",text:this.props.editMenuItemText,onClick:function(e,t){o._beginEditing(t.data)},data:e}),this.props.removeMenuItemText&&t.push({key:"Remove",text:this.props.removeMenuItemText,onClick:function(e,t){o.removeItem(t.data)},data:e}),this.props.copyMenuItemText&&t.push({key:"Copy",text:this.props.copyMenuItemText,onClick:function(e,t){o.props.onCopyItems&&o.copyItems([t.data])},data:e}),t},_1.defaultProps={onRenderItem:function(e){return 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e=this._getContext().scrollablePane;e&&(e.subscribe(this._onScrollEvent),e.addSticky(this))},AI.prototype.componentWillUnmount=function(){var e=this._getContext().scrollablePane;e&&(e.unsubscribe(this._onScrollEvent),e.removeSticky(this))},AI.prototype.componentDidUpdate=function(e,t){var o,n,r,i,s=this._getContext().scrollablePane;s&&(o=(i=this.state).isStickyBottom,n=i.isStickyTop,r=i.distanceFromTop,i=!1,t.distanceFromTop!==r&&(s.sortSticky(this,!0),i=!0),t.isStickyTop===n&&t.isStickyBottom===o\|\|(this._activeElement&&this._activeElement.focus(),s.updateStickyRefHeights(),i=!0),i&&s.syncScrollSticky(this))},AI.prototype.shouldComponentUpdate=function(e,t){if(!this.context.scrollablePane)return!0;var o=this.state,n=o.isStickyTop,r=o.isStickyBottom,o=o.distanceFromTop;return n!==t.isStickyTop\|\|r!==t.isStickyBottom\|\|this.props.stickyPosition!==e.stickyPosition\|\|this.props.children!==e.children\|\|o!==t.distanceFromTop\|\|LI(this._nonStickyContent,this._stickyContentTop)\|\|LI(this._nonStickyContent,this._stickyContentBottom)\|\|LI(this._nonStickyContent,this._placeHolder)},AI.prototype.render=function(){var e=this.state,t=e.isStickyTop,o=e.isStickyBottom,n=this.props,e=n.stickyClassName,n=n.children;return this.context.scrollablePane?gt.createElement("div",{ref:this._root},this.canStickyTop&&gt.createElement("div",{ref:this._stickyContentTop,style:{pointerEvents:t?"auto":"none"}},gt.createElement("div",{style:this._getStickyPlaceholderHeight(t)})),this.canStickyBottom&&gt.createElement("div",{ref:this._stickyContentBottom,style:{pointerEvents:o?"auto":"none"}},gt.createElement("div",{style:this._getStickyPlaceholderHeight(o)})),gt.createElement("div",{style:this._getNonStickyPlaceholderHeightAndWidth(),ref:this._placeHolder},(t\|\|o)&&gt.createElement("span",{style:So},n),gt.createElement("div",{ref:this._nonStickyContent,className:t\|\|o?e:void 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o=e.coinSize,n=e.isOutOfOffice,r=e.styles,i=e.presence,s=e.theme,a=e.presenceTitle,l=e.presenceColors,c=_r(t,gt.useRef(null)),u=Kr(e.size),d=!(u.isSize8\|\|u.isSize10\|\|u.isSize16\|\|u.isSize24\|\|u.isSize28\|\|u.isSize32)&&(!o\|\|32<o),t=o?o/3<40?o/3+"px":"40px":"",u=o?{fontSize:o?o/6<20?o/6+"px":"20px":"",lineHeight:t}:void 0,t=o?{width:t,height:t}:void 0,l=jr(r,{theme:s,presence:i,size:e.size,isOutOfOffice:n,presenceColors:l});return i===Rr.none?null:gt.createElement("div",{role:"presentation",className:l.presence,style:t,title:a,ref:c},d&&gt.createElement(Wr,{className:l.presenceIcon,iconName:function(e,t){if(e){var o="SkypeArrow";switch(Rr[e]){case"online":return"SkypeCheck";case"away":return t?o:"SkypeClock";case"dnd":return"SkypeMinus";case"offline":return t?o:""}return""}}(e.presence,e.isOutOfOffice),style:u}))});U.displayName="PersonaPresenceBase";var qr={presence:"ms-Persona-presence",presenceIcon:"ms-Persona-presenceIcon"};function Yr(e){return{color:e,borderColor:e}}function Zr(e,t){return{selectors:{":before":{border:e+" solid "+t}}}}function Xr(e){return{height:e,width:e}}function Qr(e){return{backgroundColor:e}}var Jr=In(U,function(e){var t,o,n=e.theme,r=e.presenceColors,i=n.semanticColors,s=n.fonts,a=zo(qr,n),l=Kr(e.size),c=Ur(e.presence),u=r&&r.available\|\|"#6BB700",d=r&&r.away\|\|"#FFAA44",p=r&&r.busy\|\|"#C43148",h=r&&r.dnd\|\|"#C50F1F",m=r&&r.offline\|\|"#8A8886",g=r&&r.oof\|\|"#B4009E",f=r&&r.background\|\|i.bodyBackground,n=c.isOffline\|\|e.isOutOfOffice&&(c.isAvailable\|\|c.isBusy\|\|c.isAway\|\|c.isDoNotDisturb),r=l.isSize72\|\|l.isSize100?"2px":"1px";return{presence:[a.presence,ht(ht({position:"absolute",height:Br.size12,width:Br.size12,borderRadius:"50%",top:"auto",right:"-2px",bottom:"-2px",border:"2px solid "+f,textAlign:"center",boxSizing:"content-box",backgroundClip:"border-box"},{forcedColorAdjust:"none",MsHighContrastAdjust:"none"}),{selectors:((i={})[Yt]={borderColor:"Window",backgroundColor:"WindowText"},i)}),(l.isSize8\|\|l.isSize10)&&{right:"auto",top:"7px",left:0,border:0,selectors:((t={})[Yt]={top:"9px",border:"1px solid WindowText"},t)},(l.isSize8\|\|l.isSize10\|\|l.isSize24\|\|l.isSize28\|\|l.isSize32)&&Xr(Br.size8),(l.isSize40\|\|l.isSize48)&&Xr(Br.size12),l.isSize16&&{height:Br.size6,width:Br.size6,borderWidth:"1.5px"},l.isSize56&&Xr(Br.size16),l.isSize72&&Xr(Br.size20),l.isSize100&&Xr(Br.size28),l.isSize120&&Xr(Br.size32),c.isAvailable&&{backgroundColor:u,selectors:((t={})[Yt]=Qr("Highlight"),t)},c.isAway&&Qr(d),c.isBlocked&&[{selectors:((o={":after":l.isSize40\|\|l.isSize48\|\|l.isSize72\|\|l.isSize100?{content:'""',width:"100%",height:r,backgroundColor:p,transform:"translateY(-50%) rotate(-45deg)",position:"absolute",top:"50%",left:0}:void 0})[Yt]={selectors:{":after":{width:"calc(100% - 4px)",left:"2px",backgroundColor:"Window"}}},o)}],c.isBusy&&Qr(p),c.isDoNotDisturb&&Qr(h),c.isOffline&&Qr(m),(n\|\|c.isBlocked)&&[{backgroundColor:f,selectors:((o={":before":{content:'""',width:"100%",height:"100%",position:"absolute",top:0,left:0,border:r+" solid "+p,borderRadius:"50%",boxSizing:"border-box"}})[Yt]={backgroundColor:"WindowText",selectors:{":before":{width:"calc(100% - 2px)",height:"calc(100% - 2px)",top:"1px",left:"1px",borderColor:"Window"}}},o)}],n&&c.isAvailable&&Zr(r,u),n&&c.isBusy&&Zr(r,p),n&&c.isAway&&Zr(r,g),n&&c.isDoNotDisturb&&Zr(r,h),n&&c.isOffline&&Zr(r,m),n&&c.isOffline&&e.isOutOfOffice&&Zr(r,g)],presenceIcon:[a.presenceIcon,{color:f,fontSize:"6px",lineHeight:Br.size12,verticalAlign:"top",selectors:((f={})[Yt]={color:"Window"},f)},l.isSize56&&{fontSize:"8px",lineHeight:Br.size16},l.isSize72&&{fontSize:s.small.fontSize,lineHeight:Br.size20},l.isSize100&&{fontSize:s.medium.fontSize,lineHeight:Br.size28},l.isSize120&&{fontSize:s.medium.fontSize,lineHeight:Br.size32},c.isAway&&{position:"relative",left:n?void 0:"1px"},n&&c.isAvailable&&Yr(u),n&&c.isBusy&&Yr(p),n&&c.isAway&&Yr(g),n&&c.isDoNotDisturb&&Yr(h),n&&c.isOffline&&Yr(m),n&&c.isOffline&&e.isOutOfOffice&&Yr(g)]}},void 0,{scope:"PersonaPresence"}),$r=[Mr.lightBlue,Mr.blue,Mr.darkBlue,Mr.teal,Mr.green,Mr.darkGreen,Mr.lightPink,Mr.pink,Mr.magenta,Mr.purple,Mr.orange,Mr.lightRed,Mr.darkRed,Mr.violet,Mr.gold,Mr.burgundy,Mr.warmGray,Mr.cyan,Mr.rust,Mr.coolGray],ei=$r.length;function ti(e){var t=e.primaryText,o=e.text,n=e.initialsColor;return"string"==typeof n?n:function(){switch(n){case Mr.lightBlue:return"#4F6BED";case Mr.blue:return"#0078D4";case Mr.darkBlue:return"#004E8C";case Mr.teal:return"#038387";case Mr.lightGreen:case Mr.green:return"#498205";case Mr.darkGreen:return"#0B6A0B";case Mr.lightPink:return"#C239B3";case Mr.pink:return"#E3008C";case Mr.magenta:return"#881798";case Mr.purple:return"#5C2E91";case Mr.orange:return"#CA5010";case Mr.red:return"#EE1111";case Mr.lightRed:return"#D13438";case Mr.darkRed:return"#A4262C";case Mr.transparent:return"transparent";case Mr.violet:return"#8764B8";case Mr.gold:return"#986F0B";case Mr.burgundy:return"#750B1C";case Mr.warmGray:return"#7A7574";case Mr.cyan:return"#005B70";case Mr.rust:return"#8E562E";case Mr.coolGray:return"#69797E";case Mr.black:return"#1D1D1D";case Mr.gray:return"#393939"}}(n=void 0!==n?n:function(e){var t=Mr.blue;if(!e)return t;for(var o=0,n=e.length-1;0<=n;n--){var r=e.charCodeAt(n),i=n%8;o^=(r<<i)+(r>>8-i)}return $r[o%ei]}(o\|\|t))}var oi=Fn({cacheSize:100}),ni=Ao(function(e,t,o,n,r,i){return j(e,!i&&{backgroundColor:ti({text:n,initialsColor:t,primaryText:r}),color:o})}),ri={size:Pr.size48,presence:Rr.none,imageAlt:""},ii=gt.forwardRef(function(e,t){var o,n,r,i,s,a=Hn(ri,e),l=(o=a.onPhotoLoadingStateChange,n=a.imageUrl,r=gt.useState(mr.notLoaded),i=r[0],s=r[1],gt.useEffect(function(){s(mr.notLoaded)},[n]),[i,function(e){s(e),null==o\|\|o(e)}]),c=l[0],u=ai(l[1]),d=a.className,p=a.coinProps,h=a.showUnknownPersonaCoin,m=a.coinSize,g=a.styles,f=a.imageUrl,v=a.initialsColor,b=a.initialsTextColor,y=a.isOutOfOffice,C=a.onRenderCoin,_=a.onRenderPersonaCoin,S=void 0===_?void 0===C?u:C:_,x=a.onRenderInitials,k=void 0===x?li:x,w=a.presence,I=a.presenceTitle,D=a.presenceColors,E=a.primaryText,e=a.showInitialsUntilImageLoads,r=a.text,n=a.theme,i=a.size,l=ur(a,cr),C=ur(p\|\|{},cr),_=m?{width:m,height:m}:void 0,x=h,D={coinSize:m,isOutOfOffice:y,presence:w,presenceTitle:I,presenceColors:D,size:i,theme:n},m=oi(g,{theme:n,className:p&&p.className?p.className:d,size:i,coinSize:m,showUnknownPersonaCoin:h}),c=Boolean(c!==mr.loaded&&(e&&f\|\|!f\|\|c===mr.error\|\|x));return gt.createElement("div",ht({role:"presentation"},l,{className:m.coin,ref:t}),i!==Pr.size8&&i!==Pr.size10&&i!==Pr.tiny?gt.createElement("div",ht({role:"presentation"},C,{className:m.imageArea,style:_}),c&&gt.createElement("div",{className:ni(m.initials,v,b,r,E,h),style:_,"aria-hidden":"true"},k(a,li)),!x&&S(a,u),gt.createElement(Jr,ht({},D))):a.presence?gt.createElement(Jr,ht({},D)):gt.createElement(Wr,{iconName:"Contact",className:m.size10WithoutPresenceIcon}),a.children)});ii.displayName="PersonaCoinBase";var si,ai=function(c){return function(e){var t=e.coinSize,o=e.styles,n=e.imageUrl,r=e.imageAlt,i=e.imageShouldFadeIn,s=e.imageShouldStartVisible,a=e.theme,l=e.showUnknownPersonaCoin,e=e.size,e=void 0===e?ri.size:e;if(!n)return null;l=oi(o,{theme:a,size:e,showUnknownPersonaCoin:l}),e=t\|\|Gr[e];return gt.createElement(Ir,{className:l.image,imageFit:pr.cover,src:n,width:e,height:e,alt:r,shouldFadeIn:i,shouldStartVisible:s,onLoadingStateChange:c})}},li=function(e){var t=e.imageInitials,o=e.allowPhoneInitials,n=e.showUnknownPersonaCoin,r=e.text,i=e.primaryText,e=e.theme;if(n)return gt.createElement(Wr,{iconName:"Help"});e=Pn(e);return""!==(t=t\|\|Cr(r\|\|i\|\|"",e,o))?gt.createElement("span",null,t):gt.createElement(Wr,{iconName:"Contact"})},ci={coin:"ms-Persona-coin",imageArea:"ms-Persona-imageArea",image:"ms-Persona-image",initials:"ms-Persona-initials",size8:"ms-Persona--size8",size10:"ms-Persona--size10",size16:"ms-Persona--size16",size24:"ms-Persona--size24",size28:"ms-Persona--size28",size32:"ms-Persona--size32",size40:"ms-Persona--size40",size48:"ms-Persona--size48",size56:"ms-Persona--size56",size72:"ms-Persona--size72",size100:"ms-Persona--size100",size120:"ms-Persona--size120"},ui=In(ii,function(e){var t=e.className,o=e.theme,n=e.coinSize,r=o.palette,i=o.fonts,s=Kr(e.size),o=zo(ci,o),n=n\|\|e.size&&Gr[e.size]\|\|48;return{coin:[o.coin,i.medium,s.isSize8&&o.size8,s.isSize10&&o.size10,s.isSize16&&o.size16,s.isSize24&&o.size24,s.isSize28&&o.size28,s.isSize32&&o.size32,s.isSize40&&o.size40,s.isSize48&&o.size48,s.isSize56&&o.size56,s.isSize72&&o.size72,s.isSize100&&o.size100,s.isSize120&&o.size120,t],size10WithoutPresenceIcon:{fontSize:i.xSmall.fontSize,position:"absolute",top:"5px",right:"auto",left:0},imageArea:[o.imageArea,{position:"relative",textAlign:"center",flex:"0 0 auto",height:n,width:n},n<=10&&{overflow:"visible",background:"transparent",height:0,width:0}],image:[o.image,{marginRight:"10px",position:"absolute",top:0,left:0,width:"100%",height:"100%",border:0,borderRadius:"50%",perspective:"1px"},n<=10&&{overflow:"visible",background:"transparent",height:0,width:0},10<n&&{height:n,width:n}],initials:[o.initials,{borderRadius:"50%",color:e.showUnknownPersonaCoin?"rgb(168, 0, 0)":r.white,fontSize:i.large.fontSize,fontWeight:Fe.semibold,lineHeight:48===n?46:n,height:n,selectors:((r={})[Yt]=ht(ht({border:"1px solid WindowText"},{forcedColorAdjust:"none",MsHighContrastAdjust:"none"}),{color:"WindowText",boxSizing:"border-box",backgroundColor:"Window !important"}),r.i={fontWeight:Fe.semibold},r)},e.showUnknownPersonaCoin&&{backgroundColor:"rgb(234, 234, 234)"},n<32&&{fontSize:i.xSmall.fontSize},32<=n&&n<40&&{fontSize:i.medium.fontSize},40<=n&&n<56&&{fontSize:i.mediumPlus.fontSize},56<=n&&n<72&&{fontSize:i.xLarge.fontSize},72<=n&&n<100&&{fontSize:i.xxLarge.fontSize},100<=n&&{fontSize:i.superLarge.fontSize}]}},void 0,{scope:"PersonaCoin"}),di=(l(hi,si=gt.Component),hi.prototype.render=function(){var e=this.props,t=e.onRenderIcon,o=void 0===t?this._onRenderIcon:t,n=e.onRenderActivityDescription,r=void 0===n?this._onRenderActivityDescription:n,i=e.onRenderComments,s=void 0===i?this._onRenderComments:i,t=e.onRenderTimeStamp,n=void 0===t?this._onRenderTimeStamp:t,i=e.animateBeaconSignal,t=e.isCompact,e=this._getClassNames(this.props);return gt.createElement("div",{className:e.root,style:this.props.style},(this.props.activityPersonas\|\|this.props.activityIcon\|\|this.props.onRenderIcon)&&gt.createElement("div",{className:e.activityTypeIcon},i&&t&&gt.createElement("div",{className:e.pulsingBeacon}),o(this.props)),gt.createElement("div",{className:e.activityContent},r(this.props,this._onRenderActivityDescription),s(this.props,this._onRenderComments),n(this.props,this._onRenderTimeStamp)))},hi.prototype._getClassNames=function(e){return vn(Sn(void 0,e.styles,e.animateBeaconSignal,e.beaconColorOne,e.beaconColorTwo,e.isCompact),e.className,e.activityPersonas,e.isCompact)},hi),pi=function(){var e,t=qe();return!(null===(e=null==t?void 0:t.navigator)\|\|void 0===e\|\|!e.userAgent)&&-1<t.navigator.userAgent.indexOf("rv:11.0")};function hi(e){var l=si.call(this,e)\|\|this;return l._onRenderIcon=function(e){return e.activityPersonas?l._onRenderPersonaArray(e):l.props.activityIcon},l._onRenderActivityDescription=function(e){var t=l._getClassNames(e),e=e.activityDescription\|\|e.activityDescriptionText;return e?gt.createElement("span",{className:t.activityText},e):null},l._onRenderComments=function(e){var t=l._getClassNames(e),o=e.comments\|\|e.commentText;return!e.isCompact&&o?gt.createElement("div",{className:t.commentText},o):null},l._onRenderTimeStamp=function(e){var t=l._getClassNames(e);return!e.isCompact&&e.timeStamp?gt.createElement("div",{className:t.timeStamp},e.timeStamp):null},l._onRenderPersonaArray=function(e){var o,n,r,i,s=l._getClassNames(e),t=null,a=e.activityPersonas;return(a[0].imageUrl\|\|a[0].imageInitials)&&(o=[],n=1<a.length\|\|e.isCompact,r=e.isCompact?3:4,i=void 0,e.isCompact&&(i={display:"inline-block",width:"10px",minWidth:"10px",overflow:"visible"}),a.filter(function(e,t){return t<r}).forEach(function(e,t){o.push(gt.createElement(ui,ht({},e,{key:e.key\|\|t,className:s.activityPersona,size:n?Pr.size16:Pr.size32,style:i})))}),t=gt.createElement("div",{className:s.personaContainer},o)),t},l}function mi(o){for(var n=[],e=1;e<arguments.length;e++)n[e-1]=arguments[e];return n.length<2?n[0]:function(){for(var t=[],e=0;e<arguments.length;e++)t[e]=arguments[e];n.forEach(function(e){return e&&e.apply(o,t)})}}function gi(e,t){for(var o in t)t.hasOwnProperty(o)&&(e[o]=mi(e,e[o],t[o]))}function fi(e){gi(e,{componentDidMount:vi,componentDidUpdate:bi,componentWillUnmount:yi})}function vi(){Ci(this.props.componentRef,this)}function bi(e){e.componentRef!==this.props.componentRef&&(Ci(e.componentRef,null),Ci(this.props.componentRef,this))}function yi(){Ci(this.props.componentRef,null)}function Ci(e,t){e&&("object"==typeof e?e.current=t:"function"==typeof e&&e(t))}var _i,Si=(Ii.prototype.dispose=function(){if(this._isDisposed=!0,this._parent=null,this._timeoutIds){for(var e in 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this._timeoutIds[e])},Ii.prototype.setImmediate=function(e,t){var o=this,n=0,t=qe(t);return this._isDisposed\|\|(this._immediateIds\|\|(this._immediateIds={}),n=t.setTimeout(function(){try{o._immediateIds&&delete o._immediateIds[n],e.apply(o._parent)}catch(e){o._logError(e)}},0),this._immediateIds[n]=!0),n},Ii.prototype.clearImmediate=function(e,t){t=qe(t);this._immediateIds&&this._immediateIds[e]&&(t.clearTimeout(e),delete this._immediateIds[e])},Ii.prototype.setInterval=function(e,t){var o=this,n=0;return this._isDisposed\|\|(this._intervalIds\|\|(this._intervalIds={}),n=setInterval(function(){try{e.apply(o._parent)}catch(e){o._logError(e)}},t),this._intervalIds[n]=!0),n},Ii.prototype.clearInterval=function(e){this._intervalIds&&this._intervalIds[e]&&(clearInterval(e),delete this._intervalIds[e])},Ii.prototype.throttle=function(r,e,t){var i=this;if(this._isDisposed)return this._noop;var s,a,l=e\|\|0,c=!0,u=!0,d=0,p=null;t&&"boolean"==typeof t.leading&&(c=t.leading),t&&"boolean"==typeof t.trailing&&(u=t.trailing);function h(e){var t=Date.now(),o=t-d,n=c?l-o:l;return l<=o&&(!e\|\|c)?(d=t,p&&(i.clearTimeout(p),p=null),s=r.apply(i._parent,a)):null===p&&u&&(p=i.setTimeout(h,n)),s}return function(){for(var e=[],t=0;t<arguments.length;t++)e[t]=arguments[t];return a=e,h(!0)}},Ii.prototype.debounce=function(t,e,o){var a=this;if(this._isDisposed){var n=function(){};return n.cancel=function(){},n.flush=function(){return null},n.pending=function(){return!1},n}var l,r,c=e\|\|0,u=!1,d=!0,p=null,h=0,m=Date.now(),g=null;o&&"boolean"==typeof o.leading&&(u=o.leading),o&&"boolean"==typeof o.trailing&&(d=o.trailing),o&&"number"==typeof o.maxWait&&!isNaN(o.maxWait)&&(p=o.maxWait);var i=function(e){g&&(a.clearTimeout(g),g=null),m=e},f=function(e){i(e),l=t.apply(a._parent,r)},v=function(e){var t=Date.now(),o=!1;e&&(u&&c<=t-h&&(o=!0),h=t);var n=t-h,r=c-n,i=t-m,s=!1;return null!==p&&(p<=i&&g?s=!0:r=Math.min(r,p-i)),c<=n\|\|s\|\|o?f(t):null!==g&&e\|\|!d\|\|(g=a.setTimeout(v,r)),l},e=function(){return!!g},o=function(){for(var e=[],t=0;t<arguments.length;t++)e[t]=arguments[t];return r=e,v(!0)};return o.cancel=function(){g&&i(Date.now())},o.flush=function(){return g&&f(Date.now()),l},o.pending=e,o},Ii.prototype.requestAnimationFrame=function(e,t){var o=this,n=0,r=qe(t);return this._isDisposed\|\|(this._animationFrameIds\|\|(this._animationFrameIds={}),t=function(){try{o._animationFrameIds&&delete o._animationFrameIds[n],e.apply(o._parent)}catch(e){o._logError(e)}},n=r.requestAnimationFrame?r.requestAnimationFrame(t):r.setTimeout(t,0),this._animationFrameIds[n]=!0),n},Ii.prototype.cancelAnimationFrame=function(e,t){t=qe(t);this._animationFrameIds&&this._animationFrameIds[e]&&(t.cancelAnimationFrame?t.cancelAnimationFrame(e):t.clearTimeout(e),delete this._animationFrameIds[e])},Ii.prototype._logError=function(e){this._onErrorHandler&&this._onErrorHandler(e)},Ii),xi="backward",ki=(l(wi,_i=gt.Component),wi.getDerivedStateFromProps=function(e,t){if(e.updateValueInWillReceiveProps){e=e.updateValueInWillReceiveProps();if(null!==e&&e!==t.inputValue&&!t.isComposing)return ht(ht({},t),{inputValue:e})}return null},Object.defineProperty(wi.prototype,"cursorLocation",{get:function(){if(this._inputElement.current){var e=this._inputElement.current;return"forward"!==e.selectionDirection?e.selectionEnd:e.selectionStart}return-1},enumerable:!1,configurable:!0}),Object.defineProperty(wi.prototype,"isValueSelected",{get:function(){return Boolean(this.inputElement&&this.inputElement.selectionStart!==this.inputElement.selectionEnd)},enumerable:!1,configurable:!0}),Object.defineProperty(wi.prototype,"value",{get:function(){return this._getControlledValue()\|\|this.state.inputValue\|\|""},enumerable:!1,configurable:!0}),Object.defineProperty(wi.prototype,"selectionStart",{get:function(){return this._inputElement.current?this._inputElement.current.selectionStart:-1},enumerable:!1,configurable:!0}),Object.defineProperty(wi.prototype,"selectionEnd",{get:function(){return this._inputElement.current?this._inputElement.current.selectionEnd:-1},enumerable:!1,configurable:!0}),Object.defineProperty(wi.prototype,"inputElement",{get:function(){return this._inputElement.current},enumerable:!1,configurable:!0}),wi.prototype.componentDidUpdate=function(e,t,o){var n=this.props,r=n.suggestedDisplayValue,i=n.shouldSelectFullInputValueInComponentDidUpdate,s=0;if(!n.preventValueSelection)if(this._autoFillEnabled&&this.value&&r&&Di(r,this.value)){n=!1;if((n=i?i():n)&&this._inputElement.current)this._inputElement.current.setSelectionRange(0,r.length,xi);else{for(;s<this.value.length&&this.value[s].toLocaleLowerCase()===r[s].toLocaleLowerCase();)s++;0<s&&this._inputElement.current&&this._inputElement.current.setSelectionRange(s,r.length,xi)}}else this._inputElement.current&&(null===o\|\|this._autoFillEnabled\|\|this.state.isComposing\|\|this._inputElement.current.setSelectionRange(o.start,o.end,o.dir))},wi.prototype.componentWillUnmount=function(){this._async.dispose()},wi.prototype.render=function(){var e=ur(this.props,Zn),t=ht(ht({},this.props.style),{fontFamily:"inherit"});return gt.createElement("input",ht({autoCapitalize:"off",autoComplete:"off","aria-autocomplete":"both"},e,{style:t,ref:this._inputElement,value:this._getDisplayValue(),onCompositionStart:this._onCompositionStart,onCompositionUpdate:this._onCompositionUpdate,onCompositionEnd:this._onCompositionEnd,onChange:this._onChanged,onInput:this._onInputChanged,onKeyDown:this._onKeyDown,onClick:this.props.onClick\|\|this._onClick,"data-lpignore":!0}))},wi.prototype.focus=function(){this._inputElement.current&&this._inputElement.current.focus()},wi.prototype.clear=function(){this._autoFillEnabled=!0,this._updateValue("",!1),this._inputElement.current&&this._inputElement.current.setSelectionRange(0,0)},wi.prototype.getSnapshotBeforeUpdate=function(){var e,t=this._inputElement.current;return t&&t.selectionStart!==this.value.length?{start:null!==(e=t.selectionStart)&&void 0!==e?e:t.value.length,end:null!==(e=t.selectionEnd)&&void 0!==e?e:t.value.length,dir:t.selectionDirection\|\|"backward"}:null},wi.prototype._getCurrentInputValue=function(e){return e&&e.target&&e.target.value?e.target.value:this.inputElement&&this.inputElement.value?this.inputElement.value:""},wi.prototype._tryEnableAutofill=function(e,t,o,n){!o&&e&&this._inputElement.current&&this._inputElement.current.selectionStart===e.length&&!this._autoFillEnabled&&(e.length>t.length\|\|n)&&(this._autoFillEnabled=!0)},wi.prototype._getDisplayValue=function(){return this._autoFillEnabled?(o=e=this.value,o=(t=this.props.suggestedDisplayValue)&&e&&Di(t,e)?t:o):this.value;var e,t,o},wi.prototype._getControlledValue=function(){var e=this.props.value;return void 0===e\|\|"string"==typeof e?e:(console.warn("props.value of Autofill should be a string, but it is "+e+" with type of "+typeof e),e.toString())},wi.defaultProps={enableAutofillOnKeyPress:[En.down,En.up]},wi);function wi(e){var i=_i.call(this,e)\|\|this;return i._inputElement=gt.createRef(),i._autoFillEnabled=!0,i._onCompositionStart=function(e){i.setState({isComposing:!0}),i._autoFillEnabled=!1},i._onCompositionUpdate=function(){pi()&&i._updateValue(i._getCurrentInputValue(),!0)},i._onCompositionEnd=function(e){var t=i._getCurrentInputValue();i._tryEnableAutofill(t,i.value,!1,!0),i.setState({isComposing:!1}),i._async.setTimeout(function(){i._updateValue(i._getCurrentInputValue(),!1)},0)},i._onClick=function(){i.value&&""!==i.value&&i._autoFillEnabled&&(i._autoFillEnabled=!1)},i._onKeyDown=function(e){if(i.props.onKeyDown&&i.props.onKeyDown(e),!e.nativeEvent.isComposing)switch(e.which){case En.backspace:i._autoFillEnabled=!1;break;case En.left:case En.right:i._autoFillEnabled&&(i.setState({inputValue:i.props.suggestedDisplayValue\|\|""}),i._autoFillEnabled=!1);break;default:i._autoFillEnabled\|\|-1!==i.props.enableAutofillOnKeyPress.indexOf(e.which)&&(i._autoFillEnabled=!0)}},i._onInputChanged=function(e){var t=i._getCurrentInputValue(e);i.state.isComposing\|\|i._tryEnableAutofill(t,i.value,e.nativeEvent.isComposing),pi()&&i.state.isComposing\|\|(e=void 0===(e=e.nativeEvent.isComposing)?i.state.isComposing:e,i._updateValue(t,e))},i._onChanged=function(){},i._updateValue=function(e,t){var o,n,r;!e&&e===i.value\|\|(n=(o=i.props).onInputChange,r=o.onInputValueChange,n&&(e=(null==n?void 0:n(e,t))\|\|""),i.setState({inputValue:e},function(){return null==r?void 0:r(e,t)}))},fi(i),i._async=new Si(i),i.state={inputValue:e.defaultVisibleValue\|\|"",isComposing:!1},i}function Ii(e,t){this._timeoutIds=null,this._immediateIds=null,this._intervalIds=null,this._animationFrameIds=null,this._isDisposed=!1,this._parent=e\|\|null,this._onErrorHandler=t,this._noop=function(){}}function Di(e,t){return e&&t&&0===e.toLocaleLowerCase().indexOf(t.toLocaleLowerCase())}var Ei,Ti,Pi,Ri=(l(Li,Pi=gt.Component),Li.prototype.componentDidMount=function(){var e=this,t=this.props.delay;this._timeoutId=window.setTimeout(function(){e.setState({isRendered:!0})},t)},Li.prototype.componentWillUnmount=function(){this._timeoutId&&clearTimeout(this._timeoutId)},Li.prototype.render=function(){return this.state.isRendered?gt.Children.only(this.props.children):null},Li.defaultProps={delay:0},Li),Mi=Fn(),Ni=(l(Ai,Ti=gt.Component),Ai.prototype.render=function(){var e=this.props,t=e.message,o=e.styles,n=e.as,n=void 0===n?"div":n,e=e.className,e=Mi(o,{className:e});return gt.createElement(n,ht({role:"status",className:e.root},ur(this.props,cr,["className"])),gt.createElement(Ri,null,gt.createElement("div",{className:e.screenReaderText},t)))},Ai.defaultProps={"aria-live":"polite"},Ai),Bi=In(Ni,function(e){return{root:e.className,screenReaderText:So}}),Fi={none:0,all:1,inputOnly:2};function Ai(){return null!==Ti&&Ti.apply(this,arguments)\|\|this}function Li(e){e=Pi.call(this,e)\|\|this;return e.state={isRendered:!1},e}function Hi(e,t,o){for(var n=-1,r=o=void 0===o?0:o;e&&r<e.length;r++)if(t(e[r],r)){n=r;break}return n}function Oi(e,t){t=Hi(e,t);if(!(t<0))return e[t]}function zi(e,t){for(var o=[],n=0;n<e;n++)o.push(t(n));return o}function Wi(e,n){return e.reduce(function(e,t,o){return o%n==0?e.push([t]):e[e.length-1].push(t),e},[])}function Vi(e,o){return e.filter(function(e,t){return o!==t})}function Ki(e,t,o){e=e.slice();return e[o]=t,e}function Gi(e,t,o){e=e.slice();return e.splice(t,0,o),e}function Ui(e){var t=[];return e.forEach(function(e){return t=t.concat(e)}),t}function ji(e,t){if(e.length!==t.length)return!1;for(var o=0;o<e.length;o++)if(e[o]!==t[o])return!1;return!0}(xe=Ei=Ei\|\|{})[xe.vertical=0]="vertical",xe[xe.horizontal=1]="horizontal",xe[xe.bidirectional=2]="bidirectional",xe[xe.domOrder=3]="domOrder";var qi=function(e){var o={refs:[]};return function(){for(var r,e=[],t=0;t<arguments.length;t++)e[t]=arguments[t];return o.resolver&&ji(o.refs,e)\|\|(o.resolver=(r=o,function(e){for(var t=0,o=r.refs;t<o.length;t++){var 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cs(e,t){if(!e\|\|e.disabled)return!1;var o=0,n=null;e&&e.getAttribute&&(n=e.getAttribute("tabIndex"))&&(o=parseInt(n,10));var r=e.getAttribute?e.getAttribute("data-is-focusable"):null,n=!!e&&"false"!==r&&("A"===e.tagName\|\|"BUTTON"===e.tagName\|\|"INPUT"===e.tagName\|\|"TEXTAREA"===e.tagName\|\|"SELECT"===e.tagName\|\|"true"===r\|\|null!==n&&0<=o);return(!t\|\|-1!==o)&&n}function us(e){return!!(e&&e.getAttribute&&e.getAttribute("data-focuszone-id"))}function ds(e){return!(!e\|\|!e.getAttribute\|\|"true"!==e.getAttribute("data-is-sub-focuszone"))}function ps(e){var t=ft(e),t=t&&t.activeElement;return!(!t\|\|!$i(e,t))}function hs(e,t){return"true"!==Ji(e,t)}var ms=void 0;function gs(e){e&&(ms?ms=e:(e=qe(ms=e))&&e.requestAnimationFrame(function(){ms&&ms.focus(),ms=void 0}))}function fs(e,t){for(var o=e,n=0,r=t;n<r.length;n++){var i=r[n],i=o.children[Math.min(i,o.children.length-1)];if(!i)break;o=i}return cs(o)&&as(o)?o:ss(e,o,!0)\|\|is(e,o)}function vs(e,t){for(var o=[];t&&e&&t!==e;){var n=Xi(t,!0);if(null===n)return[];o.unshift(Array.prototype.indexOf.call(n.children,t)),t=n}return o}var bs=qe()\|\|{};void 0===bs.__currentId__&&(bs.__currentId__=0);var ys,Cs=!1;function _s(e){var t;return Cs\|\|((t=v.getInstance())&&t.onReset&&t.onReset(Ss),Cs=!0),(void 0===e?"id__":e)+bs.__currentId__++}function Ss(e){bs.__currentId__=e=void 0===e?0:e}function xs(e){var t,o,o=(t="MouseEvents","function"==typeof Event?o=new Event(t):(o=document.createEvent("Event")).initEvent(t,!0,!0),o);o.initEvent("click",!0,!0),e.dispatchEvent(o)}var ks=0,ws=j({overflow:"hidden !important"}),Is="data-is-scrollable",Ds=function(e,t){var n,r;e&&(n=0,r=null,t.on(e,"touchstart",function(e){1===e.targetTouches.length&&(n=e.targetTouches[0].clientY)},{passive:!1}),t.on(e,"touchmove",function(e){var t,o;1===e.targetTouches.length&&(e.stopPropagation(),r)&&(t=e.targetTouches[0].clientY-n,o=Ns(e.target),0===(r=o?o:r).scrollTop&&0<t&&e.preventDefault(),r.scrollHeight-Math.ceil(r.scrollTop)<=r.clientHeight&&t<0&&e.preventDefault())},{passive:!1}),r=e)},Es=function(e,t){e&&t.on(e,"touchmove",function(e){e.stopPropagation()},{passive:!1})},Ts=function(e){e.preventDefault()};function Ps(){var e=ft();e&&e.body&&!ks&&(e.body.classList.add(ws),e.body.addEventListener("touchmove",Ts,{passive:!1,capture:!1})),ks++}function Rs(){var e;0<ks&&((e=ft())&&e.body&&1===ks&&(e.body.classList.remove(ws),e.body.removeEventListener("touchmove",Ts)),ks--)}function Ms(){var e;return void 0===ys&&((e=document.createElement("div")).style.setProperty("width","100px"),e.style.setProperty("height","100px"),e.style.setProperty("overflow","scroll"),e.style.setProperty("position","absolute"),e.style.setProperty("top","-9999px"),document.body.appendChild(e),ys=e.offsetWidth-e.clientWidth,document.body.removeChild(e)),ys}function Ns(e){for(var t=e,o=ft(e);t&&t!==o.body;){if("true"===t.getAttribute(Is))return t;t=t.parentElement}for(t=e;t&&t!==o.body;){if("false"!==t.getAttribute(Is)){var n=getComputedStyle(t),n=n?n.getPropertyValue("overflow-y"):"";if(n&&("scroll"===n\|\|"auto"===n))return t}t=t.parentElement}return t=!t\|\|t===o.body?qe(e):t}var Bs="data-portal-element";function Fs(e){e.setAttribute(Bs,"true")}function As(e,t){e=Qi(e,function(e){return t===e\|\|e.hasAttribute(Bs)});return null!==e&&e.hasAttribute(Bs)}var 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this.props.defaultTabbableElement?this._activeElement=this._getDocument().querySelector(this.props.defaultTabbableElement):this.props.defaultActiveElement&&(this._activeElement=this._getDocument().querySelector(this.props.defaultActiveElement)),this.props.shouldFocusOnMount&&this.focus()}},Qs.prototype.componentDidUpdate=function(){var e=this._root.current,t=this._getDocument();this.props.preventFocusRestoration\|\|!t\|\|!this._lastIndexPath\|\|t.activeElement!==t.body&&null!==t.activeElement&&t.activeElement!==e\|\|((e=fs(e,this._lastIndexPath))?(this._setActiveElement(e,!0),e.focus(),this._setParkedFocus(!1)):this._setParkedFocus(!0))},Qs.prototype.componentWillUnmount=function(){delete js[this._id],this._isInnerZone\|\|(qs.delete(this),this._windowElement&&0===qs.size&&this._windowElement.removeEventListener("keydown",Qs._onKeyDownCapture,!0)),this._root.current&&this._root.current.removeEventListener("blur",this._onBlur,!0),this._activeElement=null,this._defaultFocusElement=null},Qs.prototype.render=function(){var t=this,e=this.props,o=e.as,n=e.elementType,r=e.rootProps,i=e.ariaDescribedBy,s=e.ariaLabelledBy,a=e.className,e=ur(this.props,Wn),n=o\|\|n\|\|"div";this._evaluateFocusBeforeRender();var l=Wt();return gt.createElement(n,ht({"aria-labelledby":s,"aria-describedby":i},e,r,{className:Tr(Ls=Ls\|\|j({selectors:{":focus":{outline:"none"}}},"ms-FocusZone"),a),ref:this._mergedRef(this.props.elementRef,this._root),"data-focuszone-id":this._id,onKeyDown:function(e){return t._onKeyDown(e,l)},onFocus:this._onFocus,onMouseDownCapture:this._onMouseDown}),this.props.children)},Qs.prototype.focus=function(e){if(void 0===e&&(e=!1),this._root.current){if(!e&&"true"===this._root.current.getAttribute(Os)&&this._isInnerZone){var t=this._getOwnerZone(this._root.current);if(t===this._root.current)return!1;t=js[t.getAttribute(zs)];return!!t&&t.focusElement(this._root.current)}if(!e&&this._activeElement&&$i(this._root.current,this._activeElement)&&cs(this._activeElement))return this._activeElement.focus(),!0;e=this._root.current.firstChild;return this.focusElement(ss(this._root.current,e,!0))}return!1},Qs.prototype.focusLast=function(){if(this._root.current){var e=this._root.current&&this._root.current.lastChild;return this.focusElement(is(this._root.current,e,!0,!0,!0))}return!1},Qs.prototype.focusElement=function(e,t){var o=this.props,n=o.onBeforeFocus,o=o.shouldReceiveFocus;return!(o&&!o(e)\|\|n&&!n(e)\|\|!e\|\|(this._setActiveElement(e,t),this._activeElement&&this._activeElement.focus(),0))},Qs.prototype.setFocusAlignment=function(e){this._focusAlignment=e},Qs.prototype._evaluateFocusBeforeRender=function(){var e,t=this._root.current,o=this._getDocument();!o\|\|(e=o.activeElement)!==t&&(o=$i(t,e,!1),this._lastIndexPath=o?vs(t,e):void 0)},Qs.prototype._setParkedFocus=function(e){var t=this._root.current;t&&this._isParked!==e&&((this._isParked=e)?(this.props.allowFocusRoot\|\|(this._parkedTabIndex=t.getAttribute("tabindex"),t.setAttribute("tabindex","-1")),t.focus()):this.props.allowFocusRoot\|\|(this._parkedTabIndex?(t.setAttribute("tabindex",this._parkedTabIndex),this._parkedTabIndex=void 0):t.removeAttribute("tabindex")))},Qs.prototype._setActiveElement=function(e,t){var o=this._activeElement;this._activeElement=e,o&&(us(o)&&this._updateTabIndexes(o),o.tabIndex=-1),this._activeElement&&(this._focusAlignment&&!t\|\|this._setFocusAlignment(e,!0,!0),this._activeElement.tabIndex=0)},Qs.prototype._preventDefaultWhenHandled=function(e){this.props.preventDefaultWhenHandled&&e.preventDefault()},Qs.prototype._tryInvokeClickForFocusable=function(e){if(e===this._root.current)return!1;do{if("BUTTON"===e.tagName\|\|"A"===e.tagName\|\|"INPUT"===e.tagName\|\|"TEXTAREA"===e.tagName)return!1;if(this._isImmediateDescendantOfZone(e)&&"true"===e.getAttribute(Os)&&"true"!==e.getAttribute("data-disable-click-on-enter"))return xs(e),!0}while((e=Xi(e,!1))!==this._root.current);return!1},Qs.prototype._getFirstInnerZone=function(e){if(!(e=e\|\|this._activeElement\|\|this._root.current))return null;if(us(e))return js[e.getAttribute(zs)];for(var t=e.firstElementChild;t;){if(us(t))return js[t.getAttribute(zs)];var o=this._getFirstInnerZone(t);if(o)return o;t=t.nextElementSibling}return null},Qs.prototype._moveFocus=function(e,t,o,n){void 0===n&&(n=!0);var r=this._activeElement,i=-1,s=void 0,a=!1,l=this.props.direction===Ei.bidirectional;if(!r\|\|!this._root.current)return!1;if(this._isElementInput(r)&&!this._shouldInputLoseFocus(r,e))return!1;var c=l?r.getBoundingClientRect():null;do{if(r=(e?ss:is)(this._root.current,r),!l){s=r;break}if(r){var u=t(c,r.getBoundingClientRect());if(-1===u&&-1===i){s=r;break}if(-1<u&&(-1===i\|\|u<i)&&(i=u,s=r),0<=i&&u<0)break}}while(r);if(s&&s!==this._activeElement)a=!0,this.focusElement(s);else if(this.props.isCircularNavigation&&n)return e?this.focusElement(ss(this._root.current,this._root.current.firstElementChild,!0)):this.focusElement(is(this._root.current,this._root.current.lastElementChild,!0,!0,!0));return a},Qs.prototype._moveFocusDown=function(){var r=this,i=-1,s=this._focusAlignment.left\|\|this._focusAlignment.x\|\|0;return!!this._moveFocus(!0,function(e,t){var o=-1,n=Math.floor(t.top),e=Math.floor(e.bottom);return n<e?r._shouldWrapFocus(r._activeElement,Vs)?Gs:Us:((-1===i&&e<=n\|\|n===i)&&(i=n,o=s>=t.left&&s<=t.left+t.width?0:Math.abs(t.left+t.width/2-s)),o)})&&(this._setFocusAlignment(this._activeElement,!1,!0),!0)},Qs.prototype._moveFocusUp=function(){var i=this,s=-1,a=this._focusAlignment.left\|\|this._focusAlignment.x\|\|0;return!!this._moveFocus(!1,function(e,t){var o=-1,n=Math.floor(t.bottom),r=Math.floor(t.top),e=Math.floor(e.top);return e<n?i._shouldWrapFocus(i._activeElement,Vs)?Gs:Us:((-1===s&&n<=e\|\|r===s)&&(s=r,o=a>=t.left&&a<=t.left+t.width?0:Math.abs(t.left+t.width/2-a)),o)})&&(this._setFocusAlignment(this._activeElement,!1,!0),!0)},Qs.prototype._moveFocusLeft=function(n){var r=this,i=this._shouldWrapFocus(this._activeElement,Ks);return!!this._moveFocus(Pn(n),function(e,t){var o=-1;return(Pn(n)?parseFloat(t.top.toFixed(3))<parseFloat(e.bottom.toFixed(3)):parseFloat(t.bottom.toFixed(3))>parseFloat(e.top.toFixed(3)))&&t.right<=e.right&&r.props.direction!==Ei.vertical?o=e.right-t.right:i\|\|(o=Us),o},void 0,i)&&(this._setFocusAlignment(this._activeElement,!0,!1),!0)},Qs.prototype._moveFocusRight=function(n){var r=this,i=this._shouldWrapFocus(this._activeElement,Ks);return!!this._moveFocus(!Pn(n),function(e,t){var o=-1;return(Pn(n)?parseFloat(t.bottom.toFixed(3))>parseFloat(e.top.toFixed(3)):parseFloat(t.top.toFixed(3))<parseFloat(e.bottom.toFixed(3)))&&t.left>=e.left&&r.props.direction!==Ei.vertical?o=t.left-e.left:i\|\|(o=Us),o},void 0,i)&&(this._setFocusAlignment(this._activeElement,!0,!1),!0)},Qs.prototype._moveFocusPaging=function(e,t){void 0===t&&(t=!0);var o=this._activeElement;if(!o\|\|!this._root.current)return!1;if(this._isElementInput(o)&&!this._shouldInputLoseFocus(o,e))return!1;var n=Ns(o);if(!n)return!1;var r=-1,i=void 0,s=-1,a=-1,l=n.clientHeight,c=o.getBoundingClientRect();do{if(o=(e?ss:is)(this._root.current,o)){var u=o.getBoundingClientRect(),d=Math.floor(u.top),p=Math.floor(c.bottom),h=Math.floor(u.bottom),m=Math.floor(c.top),u=this._getHorizontalDistanceFromCenter(e,c,u);if(e&&p+l<d\|\|!e&&h<m-l)break;-1<u&&(e&&s<d?(s=d,r=u,i=o):!e&&h<a?(a=h,r=u,i=o):(-1===r\|\|u<=r)&&(r=u,i=o))}}while(o);n=!1;if(i&&i!==this._activeElement)n=!0,this.focusElement(i),this._setFocusAlignment(i,!1,!0);else if(this.props.isCircularNavigation&&t)return e?this.focusElement(ss(this._root.current,this._root.current.firstElementChild,!0)):this.focusElement(is(this._root.current,this._root.current.lastElementChild,!0,!0,!0));return n},Qs.prototype._setFocusAlignment=function(e,t,o){var n;this.props.direction!==Ei.bidirectional\|\|this._focusAlignment&&!t&&!o\|\|(e=(n=e.getBoundingClientRect()).left+n.width/2,n=n.top+n.height/2,this._focusAlignment\|\|(this._focusAlignment={left:e,top:n}),t&&(this._focusAlignment.left=e),o&&(this._focusAlignment.top=n))},Qs.prototype._isImmediateDescendantOfZone=function(e){return this._getOwnerZone(e)===this._root.current},Qs.prototype._getOwnerZone=function(e){for(var t=Xi(e,!1);t&&t!==this._root.current&&t!==this._getDocument().body;){if(us(t))return t;t=Xi(t,!1)}return t},Qs.prototype._updateTabIndexes=function(e){!this._activeElement&&this.props.defaultTabbableElement&&"function"==typeof this.props.defaultTabbableElement&&(this._activeElement=this.props.defaultTabbableElement(this._root.current)),!e&&this._root.current&&(this._defaultFocusElement=null,e=this._root.current,this._activeElement&&!$i(e,this._activeElement)&&(this._activeElement=null)),this._activeElement&&!cs(this._activeElement)&&(this._activeElement=null);for(var t=e&&e.children,o=0;t&&o<t.length;o++){var n=t[o];us(n)?"true"===n.getAttribute(Os)&&(this._isInnerZone\|\|(this._activeElement\|\|this._defaultFocusElement)&&this._activeElement!==n?"-1"!==n.getAttribute(Ws)&&n.setAttribute(Ws,"-1"):"0"!==(this._defaultFocusElement=n).getAttribute(Ws)&&n.setAttribute(Ws,"0")):(n.getAttribute&&"false"===n.getAttribute(Os)&&n.setAttribute(Ws,"-1"),cs(n)?this.props.disabled?n.setAttribute(Ws,"-1"):this._isInnerZone\|\|(this._activeElement\|\|this._defaultFocusElement)&&this._activeElement!==n?"-1"!==n.getAttribute(Ws)&&n.setAttribute(Ws,"-1"):"0"!==(this._defaultFocusElement=n).getAttribute(Ws)&&n.setAttribute(Ws,"0"):"svg"===n.tagName&&"false"!==n.getAttribute("focusable")&&n.setAttribute("focusable","false")),this._updateTabIndexes(n)}},Qs.prototype._isContentEditableElement=function(e){return e&&"true"===e.getAttribute("contenteditable")},Qs.prototype._isElementInput=function(e){return!(!e\|\|!e.tagName\|\|"input"!==e.tagName.toLowerCase()&&"textarea"!==e.tagName.toLowerCase())},Qs.prototype._shouldInputLoseFocus=function(e,t){if(!this._processingTabKey&&e&&e.type&&-1<Ys.indexOf(e.type.toLowerCase())){var o=e.selectionStart,n=o!==e.selectionEnd,r=e.value,i=e.readOnly;if(n\|\|0<o&&!t&&!i\|\|o!==r.length&&t&&!i\|\|this.props.handleTabKey&&(!this.props.shouldInputLoseFocusOnArrowKey\|\|!this.props.shouldInputLoseFocusOnArrowKey(e)))return!1}return!0},Qs.prototype._shouldWrapFocus=function(e,t){return!this.props.checkForNoWrap\|\|hs(e,t)},Qs.prototype._portalContainsElement=function(e){return e&&!!this._root.current&&As(e,this._root.current)},Qs.prototype._getDocument=function(){return 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d=!p._activeElement;t&&t!==p._activeElement&&((o\|\|d)&&p._setFocusAlignment(t,!0,!0),p._activeElement=t,d&&p._updateTabIndexes()),n&&n(p._activeElement,e),(i\|\|r)&&e.stopPropagation(),a?a(e):s&&s()}},p._onBlur=function(){p._setParkedFocus(!1)},p._onMouseDown=function(e){if(!p._portalContainsElement(e.target)&&!p.props.disabled){for(var t=e.target,o=[];t&&t!==p._root.current;)o.push(t),t=Xi(t,!1);for(;o.length&&((t=o.pop())&&cs(t)&&p._setActiveElement(t,!0),!us(t)););}},p._onKeyDown=function(e,t){if(!p._portalContainsElement(e.target)){var o=p.props,n=o.direction,r=o.disabled,i=o.isInnerZoneKeystroke,s=o.pagingSupportDisabled,o=o.shouldEnterInnerZone;if(!(r\|\|(p.props.onKeyDown&&p.props.onKeyDown(e),e.isDefaultPrevented()\|\|p._getDocument().activeElement===p._root.current&&p._isInnerZone))){if((o&&o(e)\|\|i&&i(e))&&p._isImmediateDescendantOfZone(e.target)){i=p._getFirstInnerZone();if(i){if(!i.focus(!0))return}else{if(!ds(e.target))return;if(!p.focusElement(ss(e.target,e.target.firstChild,!0)))return}}else{if(e.altKey)return;switch(e.which){case En.space:if(p._shouldRaiseClicksOnSpace&&p._tryInvokeClickForFocusable(e.target))break;return;case En.left:if(n!==Ei.vertical&&(p._preventDefaultWhenHandled(e),p._moveFocusLeft(t)))break;return;case En.right:if(n!==Ei.vertical&&(p._preventDefaultWhenHandled(e),p._moveFocusRight(t)))break;return;case En.up:if(n!==Ei.horizontal&&(p._preventDefaultWhenHandled(e),p._moveFocusUp()))break;return;case En.down:if(n!==Ei.horizontal&&(p._preventDefaultWhenHandled(e),p._moveFocusDown()))break;return;case En.pageDown:if(!s&&p._moveFocusPaging(!0))break;return;case En.pageUp:if(!s&&p._moveFocusPaging(!1))break;return;case En.tab:if(p.props.allowTabKey\|\|p.props.handleTabKey===Fi.all\|\|p.props.handleTabKey===Fi.inputOnly&&p._isElementInput(e.target)){var a;if(p._processingTabKey=!0,a=n!==Ei.vertical&&p._shouldWrapFocus(p._activeElement,Ks)?(Pn(t)?!e.shiftKey:e.shiftKey)?p._moveFocusLeft(t):p._moveFocusRight(t):e.shiftKey?p._moveFocusUp():p._moveFocusDown(),p._processingTabKey=!1,a)break;p.props.shouldResetActiveElementWhenTabFromZone&&(p._activeElement=null)}return;case En.home:if(p._isContentEditableElement(e.target)\|\|p._isElementInput(e.target)&&!p._shouldInputLoseFocus(e.target,!1))return!1;var l=p._root.current&&p._root.current.firstChild;if(p._root.current&&l&&p.focusElement(ss(p._root.current,l,!0)))break;return;case En.end:if(p._isContentEditableElement(e.target)\|\|p._isElementInput(e.target)&&!p._shouldInputLoseFocus(e.target,!0))return!1;l=p._root.current&&p._root.current.lastChild;if(p._root.current&&p.focusElement(is(p._root.current,l,!0,!0,!0)))break;return;case En.enter:if(p._shouldRaiseClicksOnEnter&&p._tryInvokeClickForFocusable(e.target))break;return;default:return}}e.preventDefault(),e.stopPropagation()}}},p._getHorizontalDistanceFromCenter=function(e,t,o){var n=p._focusAlignment.left\|\|p._focusAlignment.x\|\|0,r=Math.floor(o.top),i=Math.floor(t.bottom),s=Math.floor(o.bottom),t=Math.floor(t.top);return e&&i<r\|\|!e&&s<t?n>=o.left&&n<=o.left+o.width?0:Math.abs(o.left+o.width/2-n):p._shouldWrapFocus(p._activeElement,Vs)?Gs:Us},fi(p),p._id=_s("FocusZone"),p._focusAlignment={left:0,top:0},p._processingTabKey=!1;var o=null===(t=null!==(o=e.shouldRaiseClicks)&&void 0!==o?o:Qs.defaultProps.shouldRaiseClicks)\|\|void 0===t\|\|t;return 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pn(yc(e),{wrapper:{position:"absolute",right:28,selectors:((e={})[xc]={right:32},e)},divider:{height:16,width:1}})}),wc={item:"ms-ContextualMenu-item",divider:"ms-ContextualMenu-divider",root:"ms-ContextualMenu-link",isChecked:"is-checked",isExpanded:"is-expanded",isDisabled:"is-disabled",linkContent:"ms-ContextualMenu-linkContent",linkContentMenu:"ms-ContextualMenu-linkContent",icon:"ms-ContextualMenu-icon",iconColor:"ms-ContextualMenu-iconColor",checkmarkIcon:"ms-ContextualMenu-checkmarkIcon",subMenuIcon:"ms-ContextualMenu-submenuIcon",label:"ms-ContextualMenu-itemText",secondaryText:"ms-ContextualMenu-secondaryText",splitMenu:"ms-ContextualMenu-splitMenu",screenReaderText:"ms-ContextualMenu-screenReaderText"},Ic=Ao(function(e,t,o,n,r,i,s,a,l,c,u,d){var p,h=Sc(e),m=zo(wc,e);return pn({item:[m.item,h.item,s],divider:[m.divider,h.divider,a],root:[m.root,h.root,n&&[m.isChecked,h.rootChecked],r&&h.anchorLink,o&&[m.isExpanded,h.rootExpanded],t&&[m.isDisabled,h.rootDisabled],!t&&!o&&[{selectors:((r={":hover":h.rootHovered,":active":h.rootPressed})["."+go+" &:focus, ."+go+" &:focus:hover"]=h.rootFocused,r["."+go+" &:hover"]={background:"inherit;"},r)}],d],splitPrimary:[h.root,{width:"calc(100% - 28px)"},n&&["is-checked",h.rootChecked],(t\|\|u)&&["is-disabled",h.rootDisabled],!(t\|\|u)&&!n&&[{selectors:((p={":hover":h.rootHovered})[":hover ~ ."+m.splitMenu]=h.rootHovered,p[":active"]=h.rootPressed,p["."+go+" &:focus, ."+go+" &:focus:hover"]=h.rootFocused,p["."+go+" &:hover"]={background:"inherit;"},p)}]],splitMenu:[m.splitMenu,h.root,{flexBasis:"0",padding:"0 8px",minWidth:"28px"},o&&["is-expanded",h.rootExpanded],t&&["is-disabled",h.rootDisabled],!t&&!o&&[{selectors:((p={":hover":h.rootHovered,":active":h.rootPressed})["."+go+" &:focus, ."+go+" 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0,{scope:"ContextualMenuItem"}),Y=(l(Ac,fc=gt.Component),Ac.prototype.shouldComponentUpdate=function(e){return!da(e,this.props)},Ac),Ec="ktp",Tc="-",Pc=Ec+Tc,Rc="data-ktp-target",Mc="data-ktp-execute-target",Nc="data-ktp-aria-target",Bc="ktp-layer-id",Fc=", ";function Ac(e){var n=fc.call(this,e)\|\|this;return n._onItemMouseEnter=function(e){var t=n.props,o=t.item,t=t.onItemMouseEnter;t&&t(o,e,e.currentTarget)},n._onItemClick=function(e){var t=n.props,o=t.item,t=t.onItemClickBase;t&&t(o,e,e.currentTarget)},n._onItemMouseLeave=function(e){var t=n.props,o=t.item,t=t.onItemMouseLeave;t&&t(o,e)},n._onItemKeyDown=function(e){var t=n.props,o=t.item,t=t.onItemKeyDown;t&&t(o,e)},n._onItemMouseMove=function(e){var t=n.props,o=t.item,t=t.onItemMouseMove;t&&t(o,e,e.currentTarget)},n._getSubmenuTarget=function(){},fi(n),n}function Lc(e){var n=vc.call(this,e)\|\|this;return n.openSubMenu=function(){var e=n.props,t=e.item,o=e.openSubMenu,e=e.getSubmenuTarget;e&&(e=e(),Ha(t)&&o&&e&&o(t,e))},n.dismissSubMenu=function(){var e=n.props,t=e.item,e=e.dismissSubMenu;Ha(t)&&e&&e()},n.dismissMenu=function(e){var t=n.props.dismissMenu;t&&t(void 0,e)},fi(n),n}function Hc(e){var t=(0,gt.useRef)();return(0,gt.useEffect)(function(){t.current=e}),t.current}(U=gc=gc\|\|{}).KEYTIP_ADDED="keytipAdded",U.KEYTIP_REMOVED="keytipRemoved",U.KEYTIP_UPDATED="keytipUpdated",U.PERSISTED_KEYTIP_ADDED="persistedKeytipAdded",U.PERSISTED_KEYTIP_REMOVED="persistedKeytipRemoved",U.PERSISTED_KEYTIP_EXECUTE="persistedKeytipExecute",U.ENTER_KEYTIP_MODE="enterKeytipMode",U.EXIT_KEYTIP_MODE="exitKeytipMode";var Oc=(zc.getInstance=function(){return this._instance},zc.prototype.init=function(e){this.delayUpdatingKeytipChange=e},zc.prototype.register=function(e,t){var o=e;(t=void 0===t?!1:t)\|\|(o=this.addParentOverflow(e),this.sequenceMapping[o.keySequences.toString()]=o);e=this._getUniqueKtp(o);return t?this.persistedKeytips[e.uniqueID]=e:this.keytips[e.uniqueID]=e,!this.inKeytipMode&&this.delayUpdatingKeytipChange\|\|(t=t?gc.PERSISTED_KEYTIP_ADDED:gc.KEYTIP_ADDED,va.raise(this,t,{keytip:o,uniqueID:e.uniqueID})),e.uniqueID},zc.prototype.update=function(e,t){var o=this.addParentOverflow(e),e=this._getUniqueKtp(o,t),o=this.keytips[t];o&&(e.keytip.visible=o.keytip.visible,this.keytips[t]=e,delete this.sequenceMapping[o.keytip.keySequences.toString()],this.sequenceMapping[e.keytip.keySequences.toString()]=e.keytip,!this.inKeytipMode&&this.delayUpdatingKeytipChange\|\|va.raise(this,gc.KEYTIP_UPDATED,{keytip:e.keytip,uniqueID:e.uniqueID}))},zc.prototype.unregister=function(e,t,o){(o=void 0===o?!1:o)?delete this.persistedKeytips[t]:delete this.keytips[t],o\|\|delete this.sequenceMapping[e.keySequences.toString()];o=o?gc.PERSISTED_KEYTIP_REMOVED:gc.KEYTIP_REMOVED;!this.inKeytipMode&&this.delayUpdatingKeytipChange\|\|va.raise(this,o,{keytip:e,uniqueID:t})},zc.prototype.enterKeytipMode=function(){va.raise(this,gc.ENTER_KEYTIP_MODE)},zc.prototype.exitKeytipMode=function(){va.raise(this,gc.EXIT_KEYTIP_MODE)},zc.prototype.getKeytips=function(){var t=this;return Object.keys(this.keytips).map(function(e){return t.keytips[e].keytip})},zc.prototype.addParentOverflow=function(e){var t=$e([],e.keySequences);if(t.pop(),0!==t.length){t=this.sequenceMapping[t.toString()];if(t&&t.overflowSetSequence)return ht(ht({},e),{overflowSetSequence:t.overflowSetSequence})}return e},zc.prototype.menuExecute=function(e,t){va.raise(this,gc.PERSISTED_KEYTIP_EXECUTE,{overflowButtonSequences:e,keytipSequences:t})},zc.prototype._getUniqueKtp=function(e,t){return void 0===t&&(t=_s()),{keytip:ht({},e),uniqueID:t}},zc._instance=new zc,zc);function zc(){this.keytips={},this.persistedKeytips={},this.sequenceMapping={},this.inKeytipMode=!1,this.shouldEnterKeytipMode=!0,this.delayUpdatingKeytipChange=!1}function Wc(e){return e.reduce(function(e,t){return e+Tc+t.split("").join(Tc)},Ec)}function Vc(e,t){var o=t.length,t=$e([],t).pop();return Gi($e([],e),o-1,t)}function Kc(e){return"["+Rc+'="'+Wc(e)+'"]'}function Gc(e){return"["+Mc+'="'+e+'"]'}function Uc(e){var t=" "+Bc;return e.length?t+" "+Wc(e):t}function jc(e){var t=gt.useRef(),o=e.keytipProps?ht({disabled:e.disabled},e.keytipProps):void 0,n=_l(Oc.getInstance()),r=Hc(e);gt.useLayoutEffect(function(){t.current&&o&&((null==r?void 0:r.keytipProps)!==e.keytipProps\|\|(null==r?void 0:r.disabled)!==e.disabled)&&n.update(o,t.current)}),gt.useLayoutEffect(function(){return o&&(t.current=n.register(o)),function(){o&&n.unregister(o,t.current)}},[]);var i,s,a,l={ariaDescribedBy:void 0,keytipId:void 0};return o&&(i=n,s=e.ariaDescribedBy,a=i.addParentOverflow(o),i=Ia(s,Uc(a.keySequences)),s=$e([],a.keySequences),l={ariaDescribedBy:i,keytipId:Wc(s=a.overflowSetSequence?Vc(s,a.overflowSetSequence):s)}),l}var qc,Yc=function(e){var t=e.children,o=jc(mt(e,["children"])),e=o.keytipId,o=o.ariaDescribedBy;return t(((t={})[Rc]=e,t[Mc]=e,t["aria-describedby"]=o,t))},Zc=(l(Qc,qc=Y),Qc.prototype.render=function(){var t=this,e=this.props,o=e.item,n=e.classNames,r=e.index,i=e.focusableElementIndex,s=e.totalItemCount,a=e.hasCheckmarks,l=e.hasIcons,c=e.contextualMenuItemAs,u=void 0===c?Dc:c,d=e.expandedMenuItemKey,p=e.onItemClick,h=e.openSubMenu,m=e.dismissSubMenu,g=e.dismissMenu,f=o.rel;o.target&&"_blank"===o.target.toLowerCase()&&(f=f\|\|"nofollow noopener noreferrer");var v=Ha(o),b=ur(o,qn),c=Oa(o),y=o.itemProps,C=o.ariaDescription,e=o.keytipProps;e&&v&&this._getMemoizedMenuButtonKeytipProps(e),C&&(this._ariaDescriptionId=_s());var e=Ia(o.ariaDescribedBy,C?this._ariaDescriptionId:void 0,b["aria-describedby"]),_={"aria-describedby":e};return gt.createElement("div",null,gt.createElement(Yc,{keytipProps:o.keytipProps,ariaDescribedBy:e,disabled:c},function(e){return gt.createElement("a",ht({},_,b,e,{ref:t._anchor,href:o.href,target:o.target,rel:f,className:n.root,role:"menuitem","aria-haspopup":v\|\|void 0,"aria-expanded":v?o.key===d:void 0,"aria-posinset":i+1,"aria-setsize":s,"aria-disabled":Oa(o),style:o.style,onClick:t._onItemClick,onMouseEnter:t._onItemMouseEnter,onMouseLeave:t._onItemMouseLeave,onMouseMove:t._onItemMouseMove,onKeyDown:v?t._onItemKeyDown:void 0}),gt.createElement(u,ht({componentRef:o.componentRef,item:o,classNames:n,index:r,onCheckmarkClick:a&&p?p:void 0,hasIcons:l,openSubMenu:h,dismissSubMenu:m,dismissMenu:g,getSubmenuTarget:t._getSubmenuTarget},y)),t._renderAriaDescription(C,n.screenReaderText))}))},Qc),Xc=Fn(),xe=gt.forwardRef(function(e,t){var o=e.styles,n=e.theme,r=e.getClassNames,e=e.className,e=Xc(o,{theme:n,getClassNames:r,className:e});return gt.createElement("span",{className:e.wrapper,ref:t},gt.createElement("span",{className:e.divider}))});function Qc(){var n=null!==qc&&qc.apply(this,arguments)\|\|this;return n._anchor=gt.createRef(),n._getMemoizedMenuButtonKeytipProps=Ao(function(e){return ht(ht({},e),{hasMenu:!0})}),n._getSubmenuTarget=function(){return n._anchor.current\|\|void 0},n._onItemClick=function(e){var t=n.props,o=t.item,t=t.onItemClick;t&&t(o,e)},n._renderAriaDescription=function(e,t){return e?gt.createElement("span",{id:n._ariaDescriptionId,className:t},e):null},n}xe.displayName="VerticalDividerBase";var Jc,$c,eu=In(xe,function(e){var t=e.theme,o=e.getClassNames,e=e.className;if(!t)throw new Error("Theme is undefined or 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gt.createElement("div",{"data-ktp-target":e["data-ktp-target"],ref:function(e){return t._splitButton=e},role:za(o),"aria-label":o.ariaLabel,className:n.splitContainer,"aria-disabled":Oa(o),"aria-expanded":d?o.key===u:void 0,"aria-haspopup":!0,"aria-describedby":Ia(o.ariaDescribedBy,p?t._ariaDescriptionId:void 0,e["aria-describedby"]),"aria-checked":o.isChecked\|\|o.checked,"aria-posinset":i+1,"aria-setsize":s,onMouseEnter:t._onItemMouseEnterPrimary,onMouseLeave:c?c.bind(t,ht(ht({},o),{subMenuProps:null,items:null})):void 0,onMouseMove:t._onItemMouseMovePrimary,onKeyDown:t._onItemKeyDown,onClick:t._executeItemClick,onTouchStart:t._onTouchStart,tabIndex:0,"data-is-focusable":!0,"aria-roledescription":o["aria-roledescription"]},t._renderSplitPrimaryButton(o,n,r,a,l),t._renderSplitDivider(o),t._renderSplitIconButton(o,n,r,e),t._renderAriaDescription(p,n.screenReaderText))})},ru.prototype._renderSplitPrimaryButton=function(e,t,o,n,r){var i=this.props,s=i.contextualMenuItemAs,a=void 0===s?Dc:s,s=i.onItemClick,i={key:e.key,disabled:Oa(e)\|\|e.primaryDisabled,name:e.name,text:e.text\|\|e.name,secondaryText:e.secondaryText,className:t.splitPrimary,canCheck:e.canCheck,isChecked:e.isChecked,checked:e.checked,iconProps:e.iconProps,onRenderIcon:e.onRenderIcon,data:e.data,"data-is-focusable":!1},e=e.itemProps;return gt.createElement("button",ht({},ur(i,Yn)),gt.createElement(a,ht({"data-is-focusable":!1,item:i,classNames:t,index:o,onCheckmarkClick:n&&s?s:void 0,hasIcons:r},e)))},ru.prototype._renderSplitDivider=function(e){e=e.getSplitButtonVerticalDividerClassNames\|\|kc;return gt.createElement(eu,{getClassNames:e})},ru.prototype._renderSplitIconButton=function(t,e,o,n){var r=this.props,i=r.contextualMenuItemAs,s=void 0===i?Dc:i,a=r.onItemMouseLeave,l=r.onItemMouseDown,c=r.openSubMenu,u=r.dismissSubMenu,i=r.dismissMenu,r={onClick:this._onIconItemClick,disabled:Oa(t),className:e.splitMenu,subMenuProps:t.subMenuProps,submenuIconProps:t.submenuIconProps,split:!0,key:t.key},a=ht(ht({},ur(r,Yn)),{onMouseEnter:this._onItemMouseEnterIcon,onMouseLeave:a?a.bind(this,t):void 0,onMouseDown:function(e){return l?l(t,e):void 0},onMouseMove:this._onItemMouseMoveIcon,"data-is-focusable":!1,"data-ktp-execute-target":n["data-ktp-execute-target"],"aria-hidden":!0}),n=t.itemProps;return gt.createElement("button",ht({},a),gt.createElement(s,ht({componentRef:t.componentRef,item:r,classNames:e,index:o,hasIcons:!1,openSubMenu:c,dismissSubMenu:u,dismissMenu:i,getSubmenuTarget:this._getSubmenuTarget},n)))},ru.prototype._handleTouchAndPointerEvent=function(e){var t=this,o=this.props.onTap;o&&o(e),this._lastTouchTimeoutId&&(this._async.clearTimeout(this._lastTouchTimeoutId),this._lastTouchTimeoutId=void 0),this._processingTouch=!0,this._lastTouchTimeoutId=this._async.setTimeout(function(){t._processingTouch=!1,t._lastTouchTimeoutId=void 0},500)},ru),ou=(l(nu,Jc=Y),nu.prototype.render=function(){var t=this,e=this.props,o=e.item,n=e.classNames,r=e.index,i=e.focusableElementIndex,s=e.totalItemCount,a=e.hasCheckmarks,l=e.hasIcons,c=e.contextualMenuItemAs,u=void 0===c?Dc:c,d=e.expandedMenuItemKey,p=e.onItemMouseDown,h=e.onItemClick,m=e.openSubMenu,g=e.dismissSubMenu,f=e.dismissMenu,v=La(o),b=null!==v,y=za(o),C=Ha(o),_=o.itemProps,c=o.ariaLabel,S=o.ariaDescription,x=ur(o,Yn);delete x.disabled;e=o.role\|\|y;S&&(this._ariaDescriptionId=_s());var y=Ia(o.ariaDescribedBy,S?this._ariaDescriptionId:void 0,x["aria-describedby"]),k={className:n.root,onClick:this._onItemClick,onKeyDown:C?this._onItemKeyDown:void 0,onMouseEnter:this._onItemMouseEnter,onMouseLeave:this._onItemMouseLeave,onMouseDown:function(e){return p?p(o,e):void 0},onMouseMove:this._onItemMouseMove,href:o.href,title:o.title,"aria-label":c,"aria-describedby":y,"aria-haspopup":C\|\|void 0,"aria-expanded":C?o.key===d:void 0,"aria-posinset":i+1,"aria-setsize":s,"aria-disabled":Oa(o),"aria-checked":"menuitemcheckbox"!==e&&"menuitemradio"!==e\|\|!b?void 0:!!v,"aria-selected":"menuitem"===e&&b?!!v:void 0,role:e,style:o.style},e=o.keytipProps;return e&&C&&(e=this._getMemoizedMenuButtonKeytipProps(e)),gt.createElement(Yc,{keytipProps:e,ariaDescribedBy:y,disabled:Oa(o)},function(e){return gt.createElement("button",ht({ref:t._btn},x,k,e),gt.createElement(u,ht({componentRef:o.componentRef,item:o,classNames:n,index:r,onCheckmarkClick:a&&h?h:void 0,hasIcons:l,openSubMenu:m,dismissSubMenu:g,dismissMenu:f,getSubmenuTarget:t._getSubmenuTarget},_)),t._renderAriaDescription(S,n.screenReaderText))})},nu);function nu(){var o=null!==Jc&&Jc.apply(this,arguments)\|\|this;return o._btn=gt.createRef(),o._getMemoizedMenuButtonKeytipProps=Ao(function(e){return ht(ht({},e),{hasMenu:!0})}),o._renderAriaDescription=function(e,t){return e?gt.createElement("span",{id:o._ariaDescriptionId,className:t},e):null},o._getSubmenuTarget=function(){return o._btn.current\|\|void 0},o}function ru(e){var r=$c.call(this,e)\|\|this;return r._getMemoizedMenuButtonKeytipProps=Ao(function(e){return ht(ht({},e),{hasMenu:!0})}),r._onItemKeyDown=function(e){var t=r.props,o=t.item,t=t.onItemKeyDown;e.which===En.enter?(r._executeItemClick(e),e.preventDefault(),e.stopPropagation()):t&&t(o,e)},r._getSubmenuTarget=function(){return r._splitButton},r._renderAriaDescription=function(e,t){return e?gt.createElement("span",{id:r._ariaDescriptionId,className:t},e):null},r._onItemMouseEnterPrimary=function(e){var t=r.props,o=t.item,t=t.onItemMouseEnter;t&&t(ht(ht({},o),{subMenuProps:void 0,items:void 0}),e,r._splitButton)},r._onItemMouseEnterIcon=function(e){var t=r.props,o=t.item,t=t.onItemMouseEnter;t&&t(o,e,r._splitButton)},r._onItemMouseMovePrimary=function(e){var 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r=t;return Lo(function(e){if(t===e)throw new Error("Attempted to compose a component with itself.");var o=e,n=Lo(function(t){return function(e){return gt.createElement(o,ht({},e,{defaultRender:t}))}});return function(e){var t=e.defaultRender;return gt.createElement(r,ht({},e,{defaultRender:t?n(t):o}))}})});function ju(e,t){return Uu(e)(t)}var qu,Yu=(l(Zu,qu=gt.Component),Object.defineProperty(Zu.prototype,"_isSplitButton",{get:function(){return!!this.props.menuProps&&!!this.props.onClick&&!0===this.props.split},enumerable:!1,configurable:!0}),Zu.prototype.render=function(){var e=this.props,t=e.ariaDescription,o=e.ariaLabel,n=e.ariaHidden,r=e.className,i=e.disabled,s=e.allowDisabledFocus,a=e.primaryDisabled,l=e.secondaryText,c=void 0===l?this.props.description:l,u=e.href,d=e.iconProps,p=e.menuIconProps,h=e.styles,m=e.checked,g=e.variantClassName,f=e.theme,v=e.toggle,b=e.getClassNames,l=e.role,e=this.state.menuHidden,a=i\|\|a;this._classNames=b?b(f,r,g,d&&d.className,p&&p.className,a,m,!e,!!this.props.menuProps,this.props.split,!!s):Ku(f,h,r,g,d&&d.className,p&&p.className,a,!!this.props.menuProps,m,!e,this.props.split);h=this._ariaDescriptionId,r=this._labelId,g=this._descriptionId,d=!a&&!!u,p=d?"a":"button",u=ur(pa(d?{}:{type:"button"},this.props.rootProps,this.props),d?qn:Yn,["disabled"]),d=o\|\|u["aria-label"],o=void 0;t?o=h:c&&this.props.onRenderDescription!==wa?o=g:u["aria-describedby"]&&(o=u["aria-describedby"]);g=void 0;u["aria-labelledby"]?g=u["aria-labelledby"]:o&&!d&&(g=this._hasText()?r:void 0);var i=!(!1===this.props["data-is-focusable"]\|\|i&&!s\|\|this._isSplitButton),l="menuitemcheckbox"===l\|\|"checkbox"===l,m=l\|\|!0===v?!!m:void 0,i=pa(u,((i={className:this._classNames.root,ref:this._mergedRef(this.props.elementRef,this._buttonElement),disabled:a&&!s,onKeyDown:this._onKeyDown,onKeyPress:this._onKeyPress,onKeyUp:this._onKeyUp,onMouseDown:this._onMouseDown,onMouseUp:this._onMouseUp,onClick:this._onClick,"aria-label":d,"aria-labelledby":g,"aria-describedby":o,"aria-disabled":a,"data-is-focusable":i})[l?"aria-checked":"aria-pressed"]=m,i));return n&&(i["aria-hidden"]=!0),this._isSplitButton?this._onRenderSplitButtonContent(p,i):(this.props.menuProps&&(n=void 0===(n=this.props.menuProps.id)?this._labelId+"-menu":n,pa(i,{"aria-expanded":!e,"aria-controls":e?null:n,"aria-haspopup":!0})),this._onRenderContent(p,i))},Zu.prototype.componentDidMount=function(){this._isSplitButton&&this._splitButtonContainer.current&&("onpointerdown"in this._splitButtonContainer.current&&this._events.on(this._splitButtonContainer.current,"pointerdown",this._onPointerDown,!0),"onpointerup"in this._splitButtonContainer.current&&this.props.onPointerUp&&this._events.on(this._splitButtonContainer.current,"pointerup",this.props.onPointerUp,!0))},Zu.prototype.componentDidUpdate=function(e,t){this.props.onAfterMenuDismiss&&!t.menuHidden&&this.state.menuHidden&&this.props.onAfterMenuDismiss()},Zu.prototype.componentWillUnmount=function(){this._async.dispose(),this._events.dispose()},Zu.prototype.focus=function(){this._isSplitButton&&this._splitButtonContainer.current?(vo(!0),this._splitButtonContainer.current.focus()):this._buttonElement.current&&(vo(!0),this._buttonElement.current.focus())},Zu.prototype.dismissMenu=function(){this._dismissMenu()},Zu.prototype.openMenu=function(e,t){this._openMenu(e,t)},Zu.prototype._onRenderContent=function(e,t){var o=this,n=this.props,r=e,i=n.menuIconProps,s=n.menuProps,a=n.onRenderIcon,l=void 0===a?this._onRenderIcon:a,c=n.onRenderAriaDescription,u=void 0===c?this._onRenderAriaDescription:c,e=n.onRenderChildren,d=void 0===e?this._onRenderChildren:e,a=n.onRenderMenu,p=void 0===a?this._onRenderMenu:a,c=n.onRenderMenuIcon,h=void 0===c?this._onRenderMenuIcon:c,e=n.disabled,a=n.keytipProps;a&&s&&(a=this._getMemoizedMenuButtonKeytipProps(a));c=function(e){return gt.createElement(r,ht({},t,e),gt.createElement("span",{className:o._classNames.flexContainer,"data-automationid":"splitbuttonprimary"},l(n,o._onRenderIcon),o._onRenderTextContents(),u(n,o._onRenderAriaDescription),d(n,o._onRenderChildren),!o._isSplitButton&&(s\|\|i\|\|o.props.onRenderMenuIcon)&&h(o.props,o._onRenderMenuIcon),s&&!s.doNotLayer&&o._shouldRenderMenu()&&p(o._getMenuProps(s),o._onRenderMenu)))},c=a?gt.createElement(Yc,{keytipProps:this._isSplitButton?void 0:a,ariaDescribedBy:t["aria-describedby"],disabled:e},c):c();return s&&s.doNotLayer?gt.createElement(gt.Fragment,null,c,this._shouldRenderMenu()&&p(this._getMenuProps(s),this._onRenderMenu)):gt.createElement(gt.Fragment,null,c,gt.createElement(na,null))},Zu.prototype._shouldRenderMenu=function(){var e=this.state.menuHidden,t=this.props,o=t.persistMenu,t=t.renderPersistedMenuHiddenOnMount;return!e\|\|!(!o\|\|!this._renderedVisibleMenu&&!t)},Zu.prototype._hasText=function(){return null!==this.props.text&&(void 0!==this.props.text\|\|"string"==typeof this.props.children)},Zu.prototype._getMenuProps=function(e){var t=this.props.persistMenu,o=this.state.menuHidden;return e.ariaLabel\|\|e.labelElementId\|\|!this._hasText()\|\|(e=ht(ht({},e),{labelElementId:this._labelId})),ht(ht({id:this._labelId+"-menu",directionalHint:Pa.bottomLeftEdge},e),{shouldFocusOnContainer:this._menuShouldFocusOnContainer,shouldFocusOnMount:this._menuShouldFocusOnMount,hidden:t?o:void 0,className:Tr("ms-BaseButton-menuhost",e.className),target:(this._isSplitButton?this._splitButtonContainer:this._buttonElement).current,onDismiss:this._onDismissMenu})},Zu.prototype._onRenderSplitButtonContent=function(t,o){var n=this,e=this.props,r=e.styles,i=void 0===r?{}:r,s=e.disabled,a=e.allowDisabledFocus,l=e.checked,c=e.getSplitButtonClassNames,u=e.primaryDisabled,d=e.menuProps,p=e.toggle,h=e.role,r=e.primaryActionButtonProps,e=this.props.keytipProps,m=this.state.menuHidden,g=c?c(!!s,!m,!!l,!!a):i&&Gu(i,!!s,!m,!!l,!!u);pa(o,{onClick:void 0,onPointerDown:void 0,onPointerUp:void 0,tabIndex:-1,"data-is-focusable":!1}),e&&d&&(e=this._getMemoizedMenuButtonKeytipProps(e));var f=ur(o,[],["disabled"]);r&&pa(o,r);r=function(e){return gt.createElement("div",ht({},f,{"data-ktp-target":e?e["data-ktp-target"]:void 0,role:h\|\|"button","aria-disabled":s,"aria-haspopup":!0,"aria-expanded":!m,"aria-pressed":p?!!l:void 0,"aria-describedby":Ia(o["aria-describedby"],e?e["aria-describedby"]:void 0),className:g&&g.splitButtonContainer,onKeyDown:n._onSplitButtonContainerKeyDown,onTouchStart:n._onTouchStart,ref:n._splitButtonContainer,"data-is-focusable":!0,onClick:s\|\|u?void 0:n._onSplitButtonPrimaryClick,tabIndex:!s&&!u\|\|a?0:void 0,"aria-roledescription":o["aria-roledescription"],onFocusCapture:n._onSplitContainerFocusCapture}),gt.createElement("span",{style:{display:"flex"}},n._onRenderContent(t,o),n._onRenderSplitButtonMenuButton(g,e),n._onRenderSplitButtonDivider(g)))};return e?gt.createElement(Yc,{keytipProps:e,disabled:s},r):r()},Zu.prototype._onRenderSplitButtonDivider=function(e){return e&&e.divider?gt.createElement("span",{className:e.divider,"aria-hidden":!0,onClick:function(e){e.stopPropagation()}}):null},Zu.prototype._onRenderSplitButtonMenuButton=function(e,t){var o=this.props,n=o.allowDisabledFocus,r=o.checked,i=o.disabled,s=o.splitButtonMenuProps,a=o.splitButtonAriaLabel,l=o.primaryDisabled,c=this.state.menuHidden,o=this.props.menuIconProps;void 0===o&&(o={iconName:"ChevronDown"});c=ht(ht({},s),{styles:e,checked:r,disabled:i,allowDisabledFocus:n,onClick:this._onMenuClick,menuProps:void 0,iconProps:ht(ht({},o),{className:this._classNames.menuIcon}),ariaLabel:a,"aria-haspopup":!0,"aria-expanded":!c,"data-is-focusable":!1});return gt.createElement(Zu,ht({},c,{"data-ktp-execute-target":t&&t["data-ktp-execute-target"],onMouseDown:this._onMouseDown,tabIndex:l&&!n?0:-1}))},Zu.prototype._onPointerDown=function(e){var t=this.props.onPointerDown;t&&t(e),"touch"===e.pointerType&&(this._handleTouchAndPointerEvent(),e.preventDefault(),e.stopImmediatePropagation())},Zu.prototype._handleTouchAndPointerEvent=function(){var e=this;void 0!==this._lastTouchTimeoutId&&(this._async.clearTimeout(this._lastTouchTimeoutId),this._lastTouchTimeoutId=void 0),this._processingTouch=!0,this._lastTouchTimeoutId=this._async.setTimeout(function(){e._processingTouch=!1,e._lastTouchTimeoutId=void 0,e.focus()},500)},Zu.prototype._isValidMenuOpenKey=function(e){return this.props.menuTriggerKeyCode?e.which===this.props.menuTriggerKeyCode:!!this.props.menuProps&&e.which===En.down&&(e.altKey\|\|e.metaKey)},Zu.defaultProps={baseClassName:"ms-Button",styles:{},split:!1},Zu);function Zu(e){var s=qu.call(this,e)\|\|this;return s._buttonElement=gt.createRef(),s._splitButtonContainer=gt.createRef(),s._mergedRef=qi(),s._renderedVisibleMenu=!1,s._getMemoizedMenuButtonKeytipProps=Ao(function(e){return ht(ht({},e),{hasMenu:!0})}),s._onRenderIcon=function(e,t){var o=s.props.iconProps;if(o&&(void 0!==o.iconName\|\|o.imageProps)){var n=o.className,r=o.imageProps,i=mt(o,["className","imageProps"]);if(o.styles)return gt.createElement(Wr,ht({className:Tr(s._classNames.icon,n),imageProps:r},i));if(o.iconName)return gt.createElement(Lr,ht({className:Tr(s._classNames.icon,n)},i));if(r)return gt.createElement(Ta,ht({className:Tr(s._classNames.icon,n),imageProps:r},i))}return null},s._onRenderTextContents=function(){var e=s.props,t=e.text,o=e.children,n=e.secondaryText,r=void 0===n?s.props.description:n,n=e.onRenderText,n=void 0===n?s._onRenderText:n,e=e.onRenderDescription,e=void 0===e?s._onRenderDescription:e;return t\|\|"string"==typeof o\|\|r?gt.createElement("span",{className:s._classNames.textContainer},n(s.props,s._onRenderText),e(s.props,s._onRenderDescription)):[n(s.props,s._onRenderText),e(s.props,s._onRenderDescription)]},s._onRenderText=function(){var e=s.props.text,t=s.props.children;return void 0===e&&"string"==typeof t&&(e=t),s._hasText()?gt.createElement("span",{key:s._labelId,className:s._classNames.label,id:s._labelId},e):null},s._onRenderChildren=function(){var e=s.props.children;return"string"==typeof e?null:e},s._onRenderDescription=function(e){e=e.secondaryText,e=void 0===e?s.props.description:e;return e?gt.createElement("span",{key:s._descriptionId,className:s._classNames.description,id:s._descriptionId},e):null},s._onRenderAriaDescription=function(){var e=s.props.ariaDescription;return e?gt.createElement("span",{className:s._classNames.screenReaderText,id:s._ariaDescriptionId},e):null},s._onRenderMenuIcon=function(e){var t=s.props.menuIconProps;return gt.createElement(Lr,ht({iconName:"ChevronDown"},t,{className:s._classNames.menuIcon}))},s._onRenderMenu=function(e){var t=s.props.menuAs?ju(s.props.menuAs,Wu):Wu;return gt.createElement(t,ht({},e))},s._onDismissMenu=function(e){var t=s.props.menuProps;t&&t.onDismiss&&t.onDismiss(e),e&&e.defaultPrevented\|\|s._dismissMenu()},s._dismissMenu=function(){s._menuShouldFocusOnMount=void 0,s._menuShouldFocusOnContainer=void 0,s.setState({menuHidden:!0})},s._openMenu=function(e,t){void 0===t&&(t=!0),s.props.menuProps&&(s._menuShouldFocusOnContainer=e,s._menuShouldFocusOnMount=t,s._renderedVisibleMenu=!0,s.setState({menuHidden:!1}))},s._onToggleMenu=function(e){var t=!0;s.props.menuProps&&!1===s.props.menuProps.shouldFocusOnMount&&(t=!1),s.state.menuHidden?s._openMenu(e,t):s._dismissMenu()},s._onSplitContainerFocusCapture=function(e){var t=s._splitButtonContainer.current;!t\|\|e.target&&As(e.target,t)\|\|t.focus()},s._onSplitButtonPrimaryClick=function(e){s.state.menuHidden\|\|s._dismissMenu(),!s._processingTouch&&s.props.onClick?s.props.onClick(e):s._processingTouch&&s._onMenuClick(e)},s._onKeyDown=function(e){!s.props.disabled\|\|e.which!==En.enter&&e.which!==En.space?s.props.disabled\|\|(s.props.menuProps?s._onMenuKeyDown(e):void 0!==s.props.onKeyDown&&s.props.onKeyDown(e)):(e.preventDefault(),e.stopPropagation())},s._onKeyUp=function(e){s.props.disabled\|\|void 0===s.props.onKeyUp\|\|s.props.onKeyUp(e)},s._onKeyPress=function(e){s.props.disabled\|\|void 0===s.props.onKeyPress\|\|s.props.onKeyPress(e)},s._onMouseUp=function(e){s.props.disabled\|\|void 0===s.props.onMouseUp\|\|s.props.onMouseUp(e)},s._onMouseDown=function(e){s.props.disabled\|\|void 0===s.props.onMouseDown\|\|s.props.onMouseDown(e)},s._onClick=function(e){s.props.disabled\|\|(s.props.menuProps?s._onMenuClick(e):void 0!==s.props.onClick&&s.props.onClick(e))},s._onSplitButtonContainerKeyDown=function(e){e.which===En.enter\|\|e.which===En.space?s._buttonElement.current&&(s._buttonElement.current.click(),e.preventDefault(),e.stopPropagation()):s._onMenuKeyDown(e)},s._onMenuKeyDown=function(e){var t,o,n;s.props.disabled\|\|(s.props.onKeyDown&&s.props.onKeyDown(e),t=e.which===En.up,o=e.which===En.down,!e.defaultPrevented&&s._isValidMenuOpenKey(e)&&((n=s.props.onMenuClick)&&n(e,s.props),s._onToggleMenu(!1),e.preventDefault(),e.stopPropagation()),e.which!==En.enter&&e.which!==En.space\|\|vo(!0,e.target),e.altKey\|\|e.metaKey\|\|!t&&!o\|\|!s.state.menuHidden&&s.props.menuProps&&((void 0!==s._menuShouldFocusOnMount?s._menuShouldFocusOnMount:s.props.menuProps.shouldFocusOnMount)\|\|(e.preventDefault(),e.stopPropagation(),s._menuShouldFocusOnMount=!0,s.forceUpdate())))},s._onTouchStart=function(){!s._isSplitButton\|\|!s._splitButtonContainer.current\|\|"onpointerdown"in s._splitButtonContainer.current\|\|s._handleTouchAndPointerEvent()},s._onMenuClick=function(e){var t=s.props.onMenuClick;t&&t(e,s.props),e.defaultPrevented\|\|(t=0!==e.nativeEvent.detail\|\|"mouse"===e.nativeEvent.pointerType,s._onToggleMenu(t),e.preventDefault(),e.stopPropagation())},fi(s),s._async=new Si(s),s._events=new va(s),s.props.split,s._labelId=_s(),s._descriptionId=_s(),s._ariaDescriptionId=_s(),s.state={menuHidden:!0},s}function Xu(i,s,a){return function(r){var t,e=(l(o,t=gt.Component),o.prototype.componentDidMount=function(){yt.observe(this._onSettingChanged)},o.prototype.componentWillUnmount=function(){yt.unobserve(this._onSettingChanged)},o.prototype.render=function(){var n=this;return gt.createElement(xn.Consumer,null,function(e){var t=yt.getSettings(s,i,e.customizations),o=n.props;return t.styles&&"function"==typeof t.styles&&(t.styles=t.styles(ht(ht({},t),o))),a&&t.styles?(n._styleCache.default===t.styles&&n._styleCache.component===o.styles\|\|(e=un(t.styles,o.styles),n._styleCache.default=t.styles,n._styleCache.component=o.styles,n._styleCache.merged=e),gt.createElement(r,ht({},t,o,{styles:n._styleCache.merged}))):gt.createElement(r,ht({},t,o))})},o.prototype._onSettingChanged=function(){this.forceUpdate()},o.displayName="Customized"+i,o);function o(e){e=t.call(this,e)\|\|this;return e._styleCache={},e._onSettingChanged=e._onSettingChanged.bind(e),e}return hu(r,e)}}function Qu(e){return{fontSize:e,margin:"0 4px",height:"16px",lineHeight:"16px",textAlign:"center",flexShrink:0}}var Ju,$u,ed={outline:0},td=Ao(function(e){var t=e.semanticColors,o=e.effects,n=e.fonts,r=t.buttonBorder,i=t.disabledBackground,s=t.disabledText,t={left:-2,top:-2,bottom:-2,right:-2,outlineColor:"ButtonText"};return{root:[bo(e,{inset:1,highContrastStyle:t,borderColor:"transparent"}),e.fonts.medium,{boxSizing:"border-box",border:"1px solid "+r,userSelect:"none",display:"inline-block",textDecoration:"none",textAlign:"center",cursor:"pointer",padding:"0 16px",borderRadius:o.roundedCorner2,selectors:{":active > ":{position:"relative",left:0,top:0}}}],rootDisabled:[bo(e,{inset:1,highContrastStyle:t,borderColor:"transparent"}),{backgroundColor:i,borderColor:i,color:s,cursor:"default",selectors:{":hover":ed,":focus":ed}}],iconDisabled:{color:s,selectors:((i={})[Yt]={color:"GrayText"},i)},menuIconDisabled:{color:s,selectors:((s={})[Yt]={color:"GrayText"},s)},flexContainer:{display:"flex",height:"100%",flexWrap:"nowrap",justifyContent:"center",alignItems:"center"},description:{display:"block"},textContainer:{flexGrow:1,display:"block"},icon:Qu(n.mediumPlus.fontSize),menuIcon:Qu(n.small.fontSize),label:{margin:"0 4px",lineHeight:"100%",display:"block"},screenReaderText:So}}),od=Ao(function(e,t){var o,n=e.effects,r=e.palette,i=e.semanticColors,s={left:-2,top:-2,bottom:-2,right:-2,border:"none"},a={position:"absolute",width:1,right:31,top:8,bottom:8};return un({splitButtonContainer:[bo(e,{highContrastStyle:s,inset:2}),{display:"inline-flex",selectors:{".ms-Button--default":{borderTopRightRadius:"0",borderBottomRightRadius:"0",borderRight:"none"},".ms-Button--primary":{borderTopRightRadius:"0",borderBottomRightRadius:"0",border:"none",selectors:((o={})[Yt]=ht({color:"WindowText",backgroundColor:"Window",border:"1px solid WindowText",borderRightWidth:"0"},{forcedColorAdjust:"none",MsHighContrastAdjust:"none"}),o)},".ms-Button--primary + .ms-Button":{border:"none",selectors:((o={})[Yt]={border:"1px solid WindowText",borderLeftWidth:"0"},o)}}}],splitButtonContainerHovered:{selectors:{".ms-Button--primary":{selectors:((o={})[Yt]={color:"Window",backgroundColor:"Highlight"},o)},".ms-Button.is-disabled":{color:i.buttonTextDisabled,selectors:((i={})[Yt]={color:"GrayText",borderColor:"GrayText",backgroundColor:"Window"},i)}}},splitButtonContainerChecked:{selectors:{".ms-Button--primary":{selectors:((i={})[Yt]=ht({color:"Window",backgroundColor:"WindowText"},{forcedColorAdjust:"none",MsHighContrastAdjust:"none"}),i)}}},splitButtonContainerCheckedHovered:{selectors:{".ms-Button--primary":{selectors:((i={})[Yt]=ht({color:"Window",backgroundColor:"WindowText"},{forcedColorAdjust:"none",MsHighContrastAdjust:"none"}),i)}}},splitButtonContainerFocused:{outline:"none!important"},splitButtonMenuButton:((r={padding:6,height:"auto",boxSizing:"border-box",borderRadius:0,borderTopRightRadius:n.roundedCorner2,borderBottomRightRadius:n.roundedCorner2,border:"1px solid "+r.neutralSecondaryAlt,borderLeft:"none",outline:"transparent",userSelect:"none",display:"inline-block",textDecoration:"none",textAlign:"center",cursor:"pointer",verticalAlign:"top",width:32,marginLeft:-1,marginTop:0,marginRight:0,marginBottom:0})[Yt]={".ms-Button-menuIcon":{color:"WindowText"}},r),splitButtonDivider:ht(ht({},a),{selectors:((r={})[Yt]={backgroundColor:"WindowText"},r)}),splitButtonDividerDisabled:ht(ht({},a),{selectors:((a={})[Yt]={backgroundColor:"GrayText"},a)}),splitButtonMenuButtonDisabled:{pointerEvents:"none",border:"none",selectors:((a={":hover":{cursor:"default"},".ms-Button--primary":{selectors:((a={})[Yt]={color:"GrayText",borderColor:"GrayText",backgroundColor:"Window"},a)},".ms-Button-menuIcon":{selectors:((a={})[Yt]={color:"GrayText"},a)}})[Yt]={color:"GrayText",border:"1px solid GrayText",backgroundColor:"Window"},a)},splitButtonFlexContainer:{display:"flex",height:"100%",flexWrap:"nowrap",justifyContent:"center",alignItems:"center"},splitButtonContainerDisabled:{outline:"none",border:"none",selectors:((a={})[Yt]=ht({color:"GrayText",borderColor:"GrayText",backgroundColor:"Window"},{forcedColorAdjust:"none",MsHighContrastAdjust:"none"}),a)},splitButtonMenuFocused:ht({},bo(e,{highContrastStyle:s,inset:2}))},t)}),nd=Ao(function(e,t){var o=td(e),n=od(e),r=e.palette;return un(o,{root:{padding:"0 4px",width:"32px",height:"32px",backgroundColor:"transparent",border:"none",color:e.semanticColors.link},rootHovered:{color:r.themeDarkAlt,backgroundColor:r.neutralLighter,selectors:((e={})[Yt]={borderColor:"Highlight",color:"Highlight"},e)},rootHasMenu:{width:"auto"},rootPressed:{color:r.themeDark,backgroundColor:r.neutralLight},rootExpanded:{color:r.themeDark,backgroundColor:r.neutralLight},rootChecked:{color:r.themeDark,backgroundColor:r.neutralLight},rootCheckedHovered:{color:r.themeDark,backgroundColor:r.neutralQuaternaryAlt},rootDisabled:{color:r.neutralTertiaryAlt}},n,t)}),rd=(l(id,$u=gt.Component),id.prototype.render=function(){var e=this.props,t=e.styles,e=e.theme;return gt.createElement(Yu,ht({},this.props,{variantClassName:"ms-Button--icon",styles:nd(e,t),onRenderText:wa,onRenderDescription:wa}))},c([Xu("IconButton",["theme","styles"],!0)],id));function id(){return 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t=!(!e.onClick&&!e.href);return{text:e.text,name:e.text,key:e.key,onClick:e.onClick?p._onBreadcrumbClicked.bind(p,e):null,href:e.href,disabled:!t,itemProps:t?void 0:Nd}}),u=t.length-1,d=n&&0!==n.length,t=t.map(function(e,t){var o=p._onRenderItem;return e.onRender&&(o=Ma(e.onRender,o)),i&&(o=Ma(i,o)),gt.createElement("li",{className:p._classNames.listItem,key:e.key\|\|String(t)},o(e),(t!==u\|\|d&&t===a-1)&&gt.createElement(r,{className:p._classNames.chevron,iconName:Pn(p.props.theme)?"ChevronLeft":"ChevronRight",item:e}))});d&&t.splice(a,0,gt.createElement("li",{className:p._classNames.overflow,key:"overflow"},gt.createElement(c\|\|rd,{className:p._classNames.overflowButton,iconProps:l?{}:{iconName:"More"},role:"button","aria-haspopup":"true",ariaLabel:s,onRenderMenuIcon:l\|\|wd,menuProps:{items:e,directionalHint:Pa.bottomLeftEdge}}),a!==1+u&&gt.createElement(r,{className:p._classNames.chevron,iconName:Pn(p.props.theme)?"ChevronLeft":"ChevronRight",item:n[n.length-1]})));n=ur(p.props,Wn,["className"]);return gt.createElement("div",ht({className:p._classNames.root,role:"navigation","aria-label":o},n),gt.createElement(Zs,ht({componentRef:p._focusZone,direction:Ei.horizontal},p.props.focusZoneProps),gt.createElement("ol",{className:p._classNames.list},t)))},p._onRenderItem=function(e){if(!e)return null;var t=e.as,o=e.href,n=e.onClick,r=e.isCurrentItem,i=e.text,s=e.onRenderContent,a=mt(e,["as","href","onClick","isCurrentItem","text","onRenderContent"]),l=Ld;return s&&(l=Ma(s,l)),p.props.onRenderItemContent&&(l=Ma(p.props.onRenderItemContent,l)),n\|\|o?gt.createElement(ua,ht({},a,{as:t,className:p._classNames.itemLink,href:o,"aria-current":r?"page":void 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n._tooltipHost.current}},n._onTooltipFocus=function(e){n._ignoreNextFocusEvent?n._ignoreNextFocusEvent=!1:n._onTooltipMouseEnter(e)},n._onTooltipBlur=function(e){n._ignoreNextFocusEvent=(null===document\|\|void 0===document?void 0:document.activeElement)===e.target,n._hideTooltip()},n._onTooltipMouseEnter=function(e){var t=n.props,o=t.overflowMode,t=t.delay;if(Ad._currentVisibleTooltip&&Ad._currentVisibleTooltip!==n&&Ad._currentVisibleTooltip.dismiss(),Ad._currentVisibleTooltip=n,void 0!==o){o=n._getTargetElement();if(o&&!bd(o))return}e.target&&As(e.target,n._getTargetElement())\|\|(n._clearDismissTimer(),n._clearOpenTimer(),t!==yd.zero?(n.setState({isAriaPlaceholderRendered:!0}),t=n._getDelayTime(t),n._openTimerId=n._async.setTimeout(function(){n._toggleTooltip(!0)},t)):n._toggleTooltip(!0))},n._onTooltipMouseLeave=function(e){var t=n.props.closeDelay;n._clearDismissTimer(),n._clearOpenTimer(),t?n._dismissTimerId=n._async.setTimeout(function(){n._toggleTooltip(!1)},t):n._toggleTooltip(!1),Ad._currentVisibleTooltip===n&&(Ad._currentVisibleTooltip=void 0)},n._onTooltipKeyDown=function(e){(e.which===En.escape\|\|e.ctrlKey)&&n.state.isTooltipVisible&&(n._hideTooltip(),e.stopPropagation())},n._clearDismissTimer=function(){n._async.clearTimeout(n._dismissTimerId)},n._clearOpenTimer=function(){n._async.clearTimeout(n._openTimerId)},n._hideTooltip=function(){n._clearOpenTimer(),n._clearDismissTimer(),n._toggleTooltip(!1)},n._toggleTooltip=function(e){n.state.isAriaPlaceholderRendered&&n.setState({isAriaPlaceholderRendered:!1}),n.state.isTooltipVisible!==e&&n.setState({isTooltipVisible:e},function(){return n.props.onTooltipToggle&&n.props.onTooltipToggle(e)})},n._getDelayTime=function(e){switch(e){case yd.medium:return 300;case yd.long:return 500;default:return 0}},fi(n),n.state={isAriaPlaceholderRendered:!1,isTooltipVisible:!1},n._async=new Si(n),n}function Ld(e){return e?gt.createElement(gt.Fragment,null,e.text):null}var Hd,Od,zd={root:"ms-Breadcrumb",list:"ms-Breadcrumb-list",listItem:"ms-Breadcrumb-listItem",chevron:"ms-Breadcrumb-chevron",overflow:"ms-Breadcrumb-overflow",overflowButton:"ms-Breadcrumb-overflowButton",itemLink:"ms-Breadcrumb-itemLink",item:"ms-Breadcrumb-item"},Wd={whiteSpace:"nowrap",textOverflow:"ellipsis",overflow:"hidden"},Vd=uo(0,ro),Kd=uo($t,io),Gd=In(Bd,function(e){var t=e.className,o=e.theme,n=o.palette,r=o.semanticColors,i=o.fonts,s=zo(zd,o),a=r.menuItemBackgroundHovered,l=r.menuItemBackgroundPressed,c=n.neutralSecondary,u=Fe.regular,d=n.neutralPrimary,p=n.neutralPrimary,h=Fe.semibold,e=n.neutralSecondary,r=n.neutralSecondary,p={fontWeight:h,color:p},l={":hover":{color:d,backgroundColor:a,cursor:"pointer",selectors:((a={})[Yt]={color:"Highlight",backgroundColor:"transparent"},a)},":active":{backgroundColor:l,color:d},"&:active:hover":{color:d,backgroundColor:l},"&:active, &:hover, &:active:hover":{textDecoration:"none"}},u={color:c,padding:"0 8px",lineHeight:36,fontSize:18,fontWeight:u};return{root:[s.root,i.medium,{margin:"11px 0 1px"},t],list:[s.list,{whiteSpace:"nowrap",padding:0,margin:0,display:"flex",alignItems:"stretch"}],listItem:[s.listItem,{listStyleType:"none",margin:"0",padding:"0",display:"flex",position:"relative",alignItems:"center",selectors:{"&:last-child 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t=e.semanticColors,o=e.palette,n=t.buttonBackground,r=t.buttonBackgroundPressed,i=t.buttonBackgroundHovered,s=t.buttonBackgroundDisabled,a=t.buttonText,l=t.buttonTextHovered,c=t.buttonTextDisabled,u=t.buttonTextChecked,d=t.buttonTextCheckedHovered;return{root:{backgroundColor:n,color:a},rootHovered:{backgroundColor:i,color:l,selectors:((l={})[Yt]={borderColor:"Highlight",color:"Highlight"},l)},rootPressed:{backgroundColor:r,color:u},rootExpanded:{backgroundColor:r,color:u},rootChecked:{backgroundColor:r,color:u},rootCheckedHovered:{backgroundColor:r,color:d},rootDisabled:{color:c,backgroundColor:s,selectors:((s={})[Yt]={color:"GrayText",borderColor:"GrayText",backgroundColor:"Window"},s)},splitButtonContainer:{selectors:((s={})[Yt]={border:"none"},s)},splitButtonMenuButton:{color:o.white,backgroundColor:"transparent",selectors:{":hover":{backgroundColor:o.neutralLight,selectors:((s={})[Yt]={color:"Highlight"},s)}}},splitButtonMenuButtonDisabled:{backgroundColor:t.buttonBackgroundDisabled,selectors:{":hover":{backgroundColor:t.buttonBackgroundDisabled}}},splitButtonDivider:ht(ht({},{position:"absolute",width:1,right:31,top:8,bottom:8}),{backgroundColor:o.neutralTertiaryAlt,selectors:((s={})[Yt]={backgroundColor:"WindowText"},s)}),splitButtonDividerDisabled:{backgroundColor:e.palette.neutralTertiaryAlt},splitButtonMenuButtonChecked:{backgroundColor:o.neutralQuaternaryAlt,selectors:{":hover":{backgroundColor:o.neutralQuaternaryAlt}}},splitButtonMenuButtonExpanded:{backgroundColor:o.neutralQuaternaryAlt,selectors:{":hover":{backgroundColor:o.neutralQuaternaryAlt}}},splitButtonMenuIcon:{color:t.buttonText},splitButtonMenuIconDisabled:{color:t.buttonTextDisabled}}}function 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v=!1,e=(e=o,!(o=l)\|\|e!==wp.WorkWeek\|\|function(e,t){for(var o=new Set(e),n=0,r=0,i=e;r<i.length;r++){var s=(i[r]+1)%7;o.has(s)&&t!==s\|\|n++}return n<2}(o,n)&&0!==o.length?e:wp.Week),b=[];t&&(b=zp(t,e,n,l,c),b=oh(b,i,s));for(var y=!0,C=0;y;C++){for(var _=[],v=!0,S=0;S<Dp;S++)!function(){var t=new Date(g.getTime()),e={key:g.toString(),date:g.getDate().toString(),originalDate:t,isInMonth:g.getMonth()===m.getMonth(),isToday:Hp(h,g),isSelected:Wp(g,b),isInBounds:!ih(g,p),isMarked:(null==d?void 0:d.some(function(e){return Hp(t,e)}))\|\|!1};_.push(e),e.isInMonth&&(v=!1),g.setDate(g.getDate()+1)}();y=a?C<a+1:!v\|\|0===C,f.push(_)}return f}(c),t=o[1][0].originalDate,n=o[o.length-1][6].originalDate,r=(null===(e=c.getMarkedDays)\|\|void 0===e?void 0:e.call(c,t,n))\|\|[],i=[],s=0;s<o.length;s++){for(var a=[],l=0;l<Dp;l++)!function(e){var t=o[s][e],e=ht(ht({onSelected:function(){return u(t.originalDate)},setRef:d(t.key)},t),{isMarked:t.isMarked\|\|(null==r?void 0:r.some(function(e){return 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r=l.dateRangeType,i=l.firstDayOfWeek,s=l.workWeekDays,s=zp(e,r===wp.WorkWeek?wp.Week:r,i,s);return o===n&&(!(!o\|\|!n)\|\|0<s.filter(function(e){return e.getTime()===t.getTime()}).length)}gt.useImperativeHandle(a.componentRef,function(){return{focus:function(){var e,t;null===(t=null===(e=n.current)\|\|void 0===e?void 0:e.focus)\|\|void 0===t\|\|t.call(e)}}},[]);var m=a.styles,g=a.theme,f=a.className,v=a.dateRangeType,t=a.showWeekNumbers,b=a.labelledBy,y=a.lightenDaysOutsideNavigatedMonth,c=a.animationDirection,C=ah(m,{theme:g,className:f,dateRangeType:v,showWeekNumbers:t,lightenDaysOutsideNavigatedMonth:void 0===y\|\|y,animationDirection:c,animateBackwards:s}),u=u(C,i),_={weeks:i,navigatedDayRef:n,calculateRoundedStyles:d,activeDescendantId:e,classNames:C,weekCorners:u,getDayInfosInRangeOfDay:function(e){var t=function(e,t){if(t&&e===wp.WorkWeek){for(var o=t.slice().sort(),n=!0,r=1;r<o.length;r++)if(o[r]!==o[r-1]+1){n=!1;break}if(!n\|\|0===t.length)return wp.Week}return 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gt.createElement("div",{className:n.navigationButtonsContainer},gt.createElement(wh,ht({},e,{direction:kh.Previous})),gt.createElement(wh,ht({},e,{direction:kh.Next})))}Ih.displayName="CalendarYearNav";function Dh(o){function t(){var e;null===(e=o.onHeaderSelect)\|\|void 0===e\|\|e.call(o,!0)}var e=o.styles,n=o.theme,r=o.className,i=o.fromYear,s=o.toYear,a=void 0===(u=o.strings)?Sh:u,l=o.animateBackwards,c=o.animationDirection,u=function(e){var t;return null!==(t=null===(t=o.onRenderYear)\|\|void 0===t?void 0:t.call(o,e))&&void 0!==t?t:e},l=_h(e,{theme:n,className:r,hasHeaderClickCallback:!!o.onHeaderSelect,animateBackwards:l,animationDirection:c});if(o.onHeaderSelect){c=a.rangeAriaLabel,a=a.headerAriaLabelFormatString,c=c?"string"==typeof c?c:c(o):void 0,c=a?Jp(a,c):c;return gt.createElement("button",{className:l.currentItemButton,onClick:t,onKeyDown:function(e){e.which!==En.enter&&e.which!==En.space\|\|t()},"aria-label":c,role:"button",type:"button","aria-atomic":!0,"aria-live":"polite"},u(i)," - ",u(s))}return gt.createElement("div",{className:l.current},u(i)," - ",u(s))}Dh.displayName="CalendarYearTitle";function Eh(e){var t=e.styles,o=e.theme,n=e.className,r=e.animateBackwards,i=e.animationDirection,s=e.onRenderTitle,i=_h(t,{theme:o,className:n,hasHeaderClickCallback:!!e.onHeaderSelect,animateBackwards:r,animationDirection:i});return gt.createElement("div",{className:i.headerContainer},null!==(s=null==s?void 0:s(e))&&void 0!==s?s:gt.createElement(Dh,ht({},e)),gt.createElement(Ih,ht({},e)))}var Th;Eh.displayName="CalendarYearHeader",(ke=Th=Th\|\|{})[ke.Previous=0]="Previous",ke[ke.Next=1]="Next";K=function(e){var t,o,n,r,i,s=(r=e.selectedYear,i=e.navigatedYear,r=r\|\|i\|\|(new Date).getFullYear(),i=10Math.floor(r/10),(r=Hc(i))&&r!==i?i<r:void 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Kg={root:"ms-TextField",description:"ms-TextField-description",errorMessage:"ms-TextField-errorMessage",field:"ms-TextField-field",fieldGroup:"ms-TextField-fieldGroup",prefix:"ms-TextField-prefix",suffix:"ms-TextField-suffix",wrapper:"ms-TextField-wrapper",revealButton:"ms-TextField-reveal",multiline:"ms-TextField--multiline",borderless:"ms-TextField--borderless",underlined:"ms-TextField--underlined",unresizable:"ms-TextField--unresizable",required:"is-required",disabled:"is-disabled",active:"is-active"};var Gg,Ug,jg,qg=In(Og,function(e){var t,o,n,r,i,s,a,l=e.theme,c=e.className,u=e.disabled,d=e.focused,p=e.required,h=e.multiline,m=e.hasLabel,g=e.borderless,f=e.underlined,v=e.hasIcon,b=e.resizable,y=e.hasErrorMessage,C=e.inputClassName,_=e.autoAdjustHeight,S=e.hasRevealButton,x=l.semanticColors,k=l.effects,w=l.fonts,I=zo(Kg,l),D={background:x.disabledBackground,color:u?x.disabledText:x.inputPlaceholderText,display:"flex",alignItems:"center",padding:"0 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"+x.inputBorder,borderRadius:k.roundedCorner2,background:x.inputBackground,cursor:"text",height:32,display:"flex",flexDirection:"row",alignItems:"stretch",position:"relative"},h&&{minHeight:"60px",height:"auto",display:"flex"},!d&&!u&&{selectors:{":hover":{borderColor:x.inputBorderHovered,selectors:((t={})[Yt]=ht({borderColor:"Highlight"},{forcedColorAdjust:"none",MsHighContrastAdjust:"none"}),t)}}},d&&!f&&_o(y?x.errorText:x.inputFocusBorderAlt,k.roundedCorner2),u&&{borderColor:x.disabledBackground,selectors:((k={})[Yt]=ht({borderColor:"GrayText"},{forcedColorAdjust:"none",MsHighContrastAdjust:"none"}),k),cursor:"default"},g&&{border:"none"},g&&d&&{border:"none",selectors:{":after":{border:"none"}}},f&&{flex:"1 1 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&:hover":{outline:0},"::-ms-clear":{display:"none"}})[Yt]={background:"Window",color:u?"GrayText":"WindowText"},o)},Zo(E),h&&!b&&[I.unresizable,{resize:"none"}],h&&{minHeight:"inherit",lineHeight:17,flexGrow:1,paddingTop:6,paddingBottom:6,overflow:"auto",width:"100%"},h&&_&&{overflow:"hidden"},v&&!S&&{paddingRight:24},h&&v&&{paddingRight:40},u&&[{backgroundColor:x.disabledBackground,color:x.disabledText,borderColor:x.disabledBackground},Zo(T)],f&&{textAlign:"left"},d&&!g&&{selectors:((f={})[Yt]={paddingLeft:11,paddingRight:11},f)},d&&h&&!g&&{selectors:((g={})[Yt]={paddingTop:4},g)},C],icon:[h&&{paddingRight:24,alignItems:"flex-end"},{pointerEvents:"none",position:"absolute",bottom:6,right:8,top:"auto",fontSize:Ae.medium,lineHeight:18},u&&{color:x.disabledText}],description:[I.description,{color:x.bodySubtext,fontSize:w.xSmall.fontSize}],errorMessage:[I.errorMessage,Le.slideDownIn20,w.small,{color:x.errorText,margin:0,paddingTop:5,display:"flex",alignItems:"center"}],prefix:[I.prefix,D],suffix:[I.suffix,D],revealButton:[I.revealButton,"ms-Button","ms-Button--icon",bo(l,{inset:1}),{height:30,width:32,border:"none",padding:"0px 4px",backgroundColor:"transparent",color:x.link,selectors:{":hover":{outline:0,color:x.primaryButtonBackgroundHovered,backgroundColor:x.buttonBackgroundHovered,selectors:((x={})[Yt]={borderColor:"Highlight",color:"Highlight"},x)},":focus":{outline:0}}},v&&{marginRight:28}],revealSpan:{display:"flex",height:"100%",alignItems:"center"},revealIcon:{margin:"0px 4px",pointerEvents:"none",bottom:6,right:8,top:"auto",fontSize:Ae.medium,lineHeight:18},subComponentStyles:{label:(n=(v=e).underlined,r=e.disabled,i=e.focused,s=(v=e.theme).palette,a=v.fonts,function(){var e;return{root:[n&&r&&{color:s.neutralTertiary},n&&{fontSize:a.medium.fontSize,marginRight:8,paddingLeft:12,paddingRight:0,lineHeight:"22px",height:32},n&&i&&{selectors:((e={})[Yt]={height:31},e)}]}})}}},void 0,{scope:"TextField"}),Yg=Fn(),V=(l(af,jg=gt.Component),Object.defineProperty(af.prototype,"color",{get:function(){return this.state.color},enumerable:!1,configurable:!0}),af.prototype.componentDidUpdate=function(e,t){e!==this.props&&this.props.color&&this.setState({color:this.props.color})},af.prototype.componentWillUnmount=function(){this._disposeListeners()},af.prototype.render=function(){var e=this.props,t=e.minSize,o=e.theme,n=e.className,r=e.styles,i=e.ariaValueFormat,s=e.ariaLabel,a=e.ariaDescription,e=this.state.color,t=Yg(r,{theme:o,className:n,minSize:t}),i=i.replace("{0}",String(e.s)).replace("{1}",String(e.v));return gt.createElement("div",{ref:this._root,tabIndex:0,className:t.root,style:{backgroundColor:lg(e)},onMouseDown:this._onMouseDown,onKeyDown:this._onKeyDown,role:"slider","aria-valuetext":i,"aria-valuenow":this._isAdjustingSaturation?e.s:e.v,"aria-valuemin":0,"aria-valuemax":Lm,"aria-label":s,"aria-describedby":this._descriptionId,"data-is-focusable":!0},gt.createElement("div",{className:t.description,id:this._descriptionId},a),gt.createElement("div",{className:t.light}),gt.createElement("div",{className:t.dark}),gt.createElement("div",{className:t.thumb,style:{left:e.s+"%",top:Lm-e.v+"%",backgroundColor:e.str}}))},af.prototype._updateColor=function(e,t){var o=this.props.onChange,n=this.state.color;t.s===n.s&&t.v===n.v\|\|(o&&o(e,t),e.defaultPrevented\|\|(this.setState({color:t}),e.preventDefault()))},af.defaultProps={minSize:220,ariaLabel:"Saturation and brightness",ariaValueFormat:"Saturation {0} brightness {1}",ariaDescription:"Use left and right arrow keys to set saturation. Use up and down arrow keys to set brightness."},af),Zg=In(V,function(e){var t=e.className,o=e.theme,n=e.minSize,r=o.palette,e=o.effects;return{root:["ms-ColorPicker-colorRect",{position:"relative",marginBottom:8,border:"1px solid "+r.neutralLighter,borderRadius:e.roundedCorner2,minWidth:n,minHeight:n,outline:"none",selectors:((o={})[Yt]=ht({},{forcedColorAdjust:"none",MsHighContrastAdjust:"none"}),o["."+go+" &:focus"]=((n={outline:"1px solid "+r.neutralSecondary})[""+Yt]={outline:"2px solid CanvasText"},n),o)},t],light:["ms-ColorPicker-light",{position:"absolute",left:0,right:0,top:0,bottom:0,background:"linear-gradient(to right, white 0%, transparent 100%) /@noflip/"}],dark:["ms-ColorPicker-dark",{position:"absolute",left:0,right:0,top:0,bottom:0,background:"linear-gradient(to bottom, transparent 0, #000 100%)"}],thumb:["ms-ColorPicker-thumb",{position:"absolute",width:20,height:20,background:"white",border:"1px solid "+r.neutralSecondaryAlt,borderRadius:"50%",boxShadow:e.elevation8,transform:"translate(-50%, -50%)",selectors:{":before":{position:"absolute",left:0,right:0,top:0,bottom:0,border:"2px solid "+r.white,borderRadius:"50%",boxSizing:"border-box",content:'""'}}}],description:So}},void 0,{scope:"ColorRectangle"}),Xg=Fn(),xe=(l(sf,Ug=gt.Component),Object.defineProperty(sf.prototype,"value",{get:function(){return this.state.currentValue},enumerable:!1,configurable:!0}),sf.prototype.componentDidUpdate=function(e,t){e!==this.props&&void 0!==this.props.value&&this.setState({currentValue:this.props.value})},sf.prototype.componentWillUnmount=function(){this._disposeListeners()},sf.prototype.render=function(){var e=this._type,t=this._maxValue,o=this.props,n=o.overlayStyle,r=o.overlayColor,i=o.theme,s=o.className,a=o.styles,l=o.ariaLabel,o=void 0===l?e:l,l=this.value,i=Xg(a,{theme:i,className:s,type:e}),s=100l/t;return gt.createElement("div",{ref:this._root,className:i.root,tabIndex:0,onKeyDown:this._onKeyDown,onMouseDown:this._onMouseDown,role:"slider","aria-valuenow":l,"aria-valuetext":String(l),"aria-valuemin":0,"aria-valuemax":t,"aria-label":o,"data-is-focusable":!0},!(!r&&!n)&&gt.createElement("div",{className:i.sliderOverlay,style:r?{background:"transparency"===e?"linear-gradient(to right, #"+r+", transparent)":"linear-gradient(to right, transparent, #"+r+")"}:n}),gt.createElement("div",{className:i.sliderThumb,style:{left:s+"%"}}))},Object.defineProperty(sf.prototype,"_type",{get:function(){var e=this.props,t=e.isAlpha,e=e.type;return void 0===e?t?"alpha":"hue":e},enumerable:!1,configurable:!0}),Object.defineProperty(sf.prototype,"_maxValue",{get:function(){return"hue"===this._type?Am:zm},enumerable:!1,configurable:!0}),sf.prototype._updateValue=function(e,t){var o;t!==this.value&&((o=this.props.onChange)&&o(e,t),e.defaultPrevented\|\|(this.setState({currentValue:t}),e.preventDefault()))},sf.defaultProps={value:0},sf),Qg={background:"linear-gradient("+["to left","red 0","#f09 10%","#cd00ff 20%","#3200ff 30%","#06f 40%","#00fffd 50%","#0f6 60%","#35ff00 70%","#cdff00 80%","#f90 90%","red 100%"].join(",")+")"},Jg={backgroundImage:"url(data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAoAAAAKCAYAAACNMs+9AAAAJUlEQVQYV2N89erVfwY0ICYmxoguxjgUFKI7GsTH5m4M3w1ChQC1/Ca8i2n1WgAAAABJRU5ErkJggg==)"},$g=In(xe,function(e){var t=e.theme,o=e.className,n=e.type,r=e.isAlpha,i=void 0===r?"hue"!==(void 0===n?"hue":n):r,e=t.palette,n=t.effects;return{root:["ms-ColorPicker-slider",{position:"relative",height:20,marginBottom:8,border:"1px solid "+e.neutralLight,borderRadius:n.roundedCorner2,boxSizing:"border-box",outline:"none",forcedColorAdjust:"none",selectors:((r={})["."+go+" &:focus"]=((t={outline:"1px solid "+e.neutralSecondary})[""+Yt]={outline:"2px solid CanvasText"},t),r)},i?Jg:Qg,o],sliderOverlay:["ms-ColorPicker-sliderOverlay",{content:"",position:"absolute",left:0,right:0,top:0,bottom:0}],sliderThumb:["ms-ColorPicker-thumb","is-slider",{position:"absolute",width:20,height:20,background:"white",border:"1px solid "+e.neutralSecondaryAlt,borderRadius:"50%",boxShadow:n.elevation8,transform:"translate(-50%, -50%)",top:"50%",forcedColorAdjust:"auto"}]}},void 0,{scope:"ColorSlider"}),ef=Fn(),tf=["hex","r","g","b","a","t"],of={hex:"hexError",r:"redError",g:"greenError",b:"blueError",a:"alphaError",t:"transparencyError"},nf=(l(rf,Gg=gt.Component),Object.defineProperty(rf.prototype,"color",{get:function(){return this.state.color},enumerable:!1,configurable:!0}),rf.prototype.componentDidUpdate=function(e,t){e===this.props\|\|(e=lf(this.props))&&this._updateColor(void 0,e)},rf.prototype.render=function(){var o=this,e=this.props,t=this._strings,n=this._textLabels,r=e.theme,i=e.className,s=e.styles,a=e.alphaType,l=e.alphaSliderHidden,c=void 0===l?"none"===a:l,u=e.tooltipProps,d=this.state.color,p="transparency"===a,h=["hex","r","g","b",p?"t":"a"],m=p?d.t:d.a,l=p?n.t:n.a,g=ef(s,{theme:r,className:i,alphaType:a}),i=[n.r,d.r,n.g,d.g,n.b,d.b];c\|\|"number"!=typeof m\|\|i.push(l,m+"%");i=t.rootAriaLabelFormat.replace("{0}",i.join(" "));return gt.createElement("div",{className:g.root,role:"group","aria-label":i},gt.createElement("div",{className:g.panel},gt.createElement(Zg,{color:d,onChange:this._onSVChanged,ariaLabel:t.svAriaLabel,ariaDescription:t.svAriaDescription,ariaValueFormat:t.svAriaValueFormat,className:g.colorRectangle}),gt.createElement("div",{className:g.flexContainer},gt.createElement("div",{className:g.flexSlider},gt.createElement($g,{className:"is-hue",type:"hue",ariaLabel:t.hue\|\|t.hueAriaLabel,value:d.h,onChange:this._onHChanged}),!c&&gt.createElement($g,{className:"is-alpha",type:a,ariaLabel:p?t.transparencyAriaLabel:t.alphaAriaLabel,overlayColor:d.hex,value:m,onChange:this._onATChanged})),e.showPreview&&gt.createElement("div",{className:g.flexPreviewBox},gt.createElement("div",{className:g.colorSquare+" is-preview",style:{backgroundColor:d.str}}))),gt.createElement("table",{className:g.table,role:"group",cellPadding:"0",cellSpacing:"0"},gt.createElement("thead",null,gt.createElement("tr",{className:g.tableHeader},gt.createElement("td",{className:g.tableHexCell},n.hex),gt.createElement("td",null,n.r),gt.createElement("td",null,n.g),gt.createElement("td",null,n.b),!c&&gt.createElement("td",{className:g.tableAlphaCell},l))),gt.createElement("tbody",null,gt.createElement("tr",null,h.map(function(e){if(("a"===e\|\|"t"===e)&&c)return null;var t=o._getTooltipValue(e);return gt.createElement("td",{key:e},gt.createElement(Rd,ht({content:t,directionalHint:Pa.bottomCenter,role:"alert"},u),gt.createElement(qg,{className:g.input,onChange:o._textChangeHandlers[e],onBlur:o._onBlur,value:o._getDisplayValue(e),spellCheck:!1,ariaLabel:n[e],autoComplete:"off",invalid:!!t})))}))))))},rf.prototype._getDisplayValue=function(e){var t=this.state,o=t.color,t=t.editingColor;return t&&t.component===e?t.value:"hex"===e?o[e]\|\|"":"number"!=typeof o[e]\|\|isNaN(o[e])?"":String(o[e])},rf.prototype._getTooltipValue=function(e){var t=this.state.editingColor;if(t&&t.component===e){t=t.value;if(!("hex"===e&&t.length>=Wm&&t.length<=Vm))return this._strings[of[e]]}},rf.prototype._onTextChange=function(e,t,o){var n,r=this.state.color,i="hex"===e,s="a"===e,a="t"===e;o=(o\|\|"").substr(0,i?Vm:Gm),(i?Um:jm).test(o)&&(""!==o&&(i?o.length===Vm:s\|\|a?Number(o)<=zm:Number(o)<=Hm)?String(r[e])===o?this.state.editingColor&&this.setState({editingColor:void 0}):(n=i?sg("#"+o):a?Mg(r,Number(o)):ig(ht(ht({},r),((n={})[e]=Number(o),n))),this._updateColor(t,n)):this.setState({editingColor:{component:e,value:o}}))},rf.prototype._updateColor=function(e,t){var o,n;t&&(o=(n=this.state).color,n=n.editingColor,t.h===o.h&&t.str===o.str&&!n\|\|e&&this.props.onChange&&(this.props.onChange(e,t),e.defaultPrevented)\|\|this.setState({color:t,editingColor:void 0}))},rf.defaultProps={alphaType:"alpha",strings:{rootAriaLabelFormat:"Color picker, {0} selected.",hex:"Hex",red:"Red",green:"Green",blue:"Blue",alpha:"Alpha",transparency:"Transparency",hueAriaLabel:"Hue",svAriaLabel:V.defaultProps.ariaLabel,svAriaValueFormat:V.defaultProps.ariaValueFormat,svAriaDescription:V.defaultProps.ariaDescription,hexError:"Hex values must be between 3 and 6 characters long",alphaError:"Alpha must be between 0 and 100",transparencyError:"Transparency must be between 0 and 100",redError:"Red must be between 0 and 255",greenError:"Green must be between 0 and 255",blueError:"Blue must be between 0 and 255"}},rf);function rf(e){var l=Gg.call(this,e)\|\|this;l._onSVChanged=function(e,t){l._updateColor(e,t)},l._onHChanged=function(e,t){l._updateColor(e,ug(l.state.color,t))},l._onATChanged=function(e,t){var o="transparency"===l.props.alphaType?Mg:pg;l._updateColor(e,o(l.state.color,Math.round(t)))},l._onBlur=function(e){var t,o,n,r,i=l.state,s=i.color,a=i.editingColor;a&&(t=a.value,n="a"===(o=a.component),r="t"===o,t.length>=((i="hex"===o)?Wm:Km)&&(i\|\|!isNaN(Number(t)))?(a=void 0,a=i?sg("#"+gg(t)):n\|\|r?(n?pg:Mg)(s,Jm(Number(t),zm)):ig(hg(ht(ht({},s),((s={})[o]=Number(t),s)))),l._updateColor(e,a)):l.setState({editingColor:void 0}))},fi(l);var t=e.strings;t.hue&&Xo("ColorPicker property 'strings.hue' was used but has been deprecated. Use 'strings.hueAriaLabel' instead."),l.state={color:lf(e)\|\|sg("#ffffff")},l._textChangeHandlers={};for(var o=0,n=tf;o<n.length;o++){var r=n[o];l._textChangeHandlers[r]=l._onTextChange.bind(l,r)}var i=rf.defaultProps.strings;return l._textLabels={r:e.redLabel\|\|t.red\|\|i.red,g:e.greenLabel\|\|t.green\|\|i.green,b:e.blueLabel\|\|t.blue\|\|i.blue,a:e.alphaLabel\|\|t.alpha\|\|i.alpha,hex:e.hexLabel\|\|t.hex\|\|i.hex,t:t.transparency\|\|i.transparency},l._strings=ht(ht(ht({},i),{alphaAriaLabel:l._textLabels.a,transparencyAriaLabel:l._textLabels.t}),t),l}function sf(e){var r=Ug.call(this,e)\|\|this;return r._disposables=[],r._root=gt.createRef(),r._onKeyDown=function(e){var t=r.value,o=r._maxValue,n=e.shiftKey?10:1;switch(e.which){case En.left:t-=n;break;case En.right:t+=n;break;case En.home:t=0;break;case En.end:t=o;break;default:return}r._updateValue(e,Jm(t,o))},r._onMouseDown=function(e){var t=qe(r);t&&r._disposables.push(Wa(t,"mousemove",r._onMouseMove,!0),Wa(t,"mouseup",r._disposeListeners,!0)),r._onMouseMove(e)},r._onMouseMove=function(e){var t,o;r._root.current&&(o=r._maxValue,t=r._root.current.getBoundingClientRect(),t=(e.clientX-t.left)/t.width,o=Jm(Math.round(to),o),r._updateValue(e,o))},r._disposeListeners=function(){r._disposables.forEach(function(e){return e()}),r._disposables=[]},fi(r),"hue"===r._type\|\|e.overlayColor\|\|e.overlayStyle\|\|Xo("ColorSlider: 'overlayColor' is required when 'type' is \"alpha\" or \"transparency\""),r.state={currentValue:e.value\|\|0},r}function af(e){var i=jg.call(this,e)\|\|this;return i._disposables=[],i._root=gt.createRef(),i._isAdjustingSaturation=!0,i._descriptionId=_s("ColorRectangle-description"),i._onKeyDown=function(e){var t=i.state.color,o=t.s,n=t.v,r=e.shiftKey?10:1;switch(e.which){case En.up:i._isAdjustingSaturation=!1,n+=r;break;case En.down:i._isAdjustingSaturation=!1,n-=r;break;case En.left:i._isAdjustingSaturation=!0,o-=r;break;case En.right:i._isAdjustingSaturation=!0,o+=r;break;default:return}i._updateColor(e,cg(t,Jm(o,Fm),Jm(n,Lm)))},i._onMouseDown=function(e){i._disposables.push(Wa(window,"mousemove",i._onMouseMove,!0),Wa(window,"mouseup",i._disposeListeners,!0)),i._onMouseMove(e)},i._onMouseMove=function(e){var t,o,n,r;i._root.current&&(t=e,o=i.state.color,n=i._root.current.getBoundingClientRect(),r=(t.clientX-n.left)/n.width,n=(t.clientY-n.top)/n.height,(n=cg(o,Jm(Math.round(rFm),Fm),Jm(Math.round(Lm-nLm),Lm)))&&i._updateColor(e,n))},i._disposeListeners=function(){i._disposables.forEach(function(e){return e()}),i._disposables=[]},fi(i),i.state={color:e.color},i}function lf(e){e=e.color;return"string"==typeof e?sg(e):e}var cf,uf,df,pf=In(nf,function(e){var t=e.className,o=e.theme,e=e.alphaType;return{root:["ms-ColorPicker",o.fonts.medium,{position:"relative",maxWidth:300},t],panel:["ms-ColorPicker-panel",{padding:"16px"}],table:["ms-ColorPicker-table",{tableLayout:"fixed",width:"100%",selectors:{"tbody td:last-of-type .ms-ColorPicker-input":{paddingRight:0}}}],tableHeader:[o.fonts.small,{selectors:{td:{paddingBottom:4}}}],tableHexCell:{width:"25%"},tableAlphaCell:"transparency"===e&&{width:"22%"},colorSquare:["ms-ColorPicker-colorSquare",{width:48,height:48,margin:"0 0 0 8px",border:"1px solid #c8c6c4"}],flexContainer:{display:"flex"},flexSlider:{flexGrow:"1"},flexPreviewBox:{flexGrow:"0"},input:["ms-ColorPicker-input",{width:"100%",border:"none",boxSizing:"border-box",height:30,selectors:{"&.ms-TextField":{paddingRight:4},"& .ms-TextField-field":{minWidth:"auto",padding:5,textOverflow:"clip"}}}]}},void 0,{scope:"ColorPicker"}),hf=Ao(function(e){var e=e.semanticColors;return{backgroundColor:e.disabledBackground,color:e.disabledText,cursor:"default",selectors:((e={":after":{borderColor:e.disabledBackground}})[Yt]={color:"GrayText",selectors:{":after":{borderColor:"GrayText"}}},e)}}),mf={selectors:((G={})[Yt]=ht({backgroundColor:"Highlight",borderColor:"Highlight",color:"HighlightText"},{forcedColorAdjust:"none",MsHighContrastAdjust:"none"}),G)},gf={selectors:((Y={})[Yt]=ht({color:"WindowText",backgroundColor:"Window"},{forcedColorAdjust:"none",MsHighContrastAdjust:"none"}),Y)},ff=Ao(function(e,t,o,n,r,i){var s=e.palette,a=e.semanticColors,a={textHoveredColor:a.menuItemTextHovered,textSelectedColor:s.neutralDark,textDisabledColor:a.disabledText,backgroundHoveredColor:a.menuItemBackgroundHovered,backgroundPressedColor:a.menuItemBackgroundPressed};return un({root:[e.fonts.medium,{backgroundColor:n?a.backgroundHoveredColor:"transparent",boxSizing:"border-box",cursor:"pointer",display:r?"none":"block",width:"100%",height:"auto",minHeight:36,lineHeight:"20px",padding:"0 8px",position:"relative",borderWidth:"1px",borderStyle:"solid",borderColor:"transparent",borderRadius:0,wordWrap:"break-word",overflowWrap:"break-word",textAlign:"left",selectors:ht(ht(((n={})[Yt]={border:"none",borderColor:"Background"},n),!r&&{"&.ms-Checkbox":{display:"flex",alignItems:"center"}}),{"&.ms-Button--command:hover:active":{backgroundColor:a.backgroundPressedColor},".ms-Checkbox-label":{width:"100%"}})},i?[{backgroundColor:"transparent",color:a.textSelectedColor,selectors:{":hover":[{backgroundColor:a.backgroundHoveredColor},mf]}},bo(e,{inset:-1,isFocusedOnly:!1}),mf]:[]],rootHovered:{backgroundColor:a.backgroundHoveredColor,color:a.textHoveredColor},rootFocused:{backgroundColor:a.backgroundHoveredColor},rootDisabled:{color:a.textDisabledColor,cursor:"default"},optionText:{overflow:"hidden",whiteSpace:"nowrap",textOverflow:"ellipsis",minWidth:"0px",maxWidth:"100%",wordWrap:"break-word",overflowWrap:"break-word",display:"inline-block"},optionTextWrapper:{maxWidth:"100%",display:"flex",alignItems:"center"}},t,o)}),vf=Ao(function(e,t){var o,n=e.semanticColors,r=e.fonts,i={buttonTextColor:n.bodySubtext,buttonTextHoveredCheckedColor:n.buttonTextChecked,buttonBackgroundHoveredColor:n.listItemBackgroundHovered,buttonBackgroundCheckedColor:n.listItemBackgroundChecked,buttonBackgroundCheckedHoveredColor:n.listItemBackgroundCheckedHovered},n={selectors:((o={})[Yt]=ht({backgroundColor:"Highlight",borderColor:"Highlight",color:"HighlightText"},{forcedColorAdjust:"none",MsHighContrastAdjust:"none"}),o)};return un({root:{color:i.buttonTextColor,fontSize:r.small.fontSize,position:"absolute",top:0,height:"100%",lineHeight:30,width:32,textAlign:"center",cursor:"default",selectors:((o={})[Yt]=ht({backgroundColor:"ButtonFace",borderColor:"ButtonText",color:"ButtonText"},{forcedColorAdjust:"none",MsHighContrastAdjust:"none"}),o)},icon:{fontSize:r.small.fontSize},rootHovered:[{backgroundColor:i.buttonBackgroundHoveredColor,color:i.buttonTextHoveredCheckedColor,cursor:"pointer"},n],rootPressed:[{backgroundColor:i.buttonBackgroundCheckedColor,color:i.buttonTextHoveredCheckedColor},n],rootChecked:[{backgroundColor:i.buttonBackgroundCheckedColor,color:i.buttonTextHoveredCheckedColor},n],rootCheckedHovered:[{backgroundColor:i.buttonBackgroundCheckedHoveredColor,color:i.buttonTextHoveredCheckedColor},n],rootDisabled:[hf(e),{position:"absolute"}]},t)}),bf=Ao(function(e,t,o){var n=e.semanticColors,r=e.fonts,i=e.effects,s={textColor:n.inputText,borderColor:n.inputBorder,borderHoveredColor:n.inputBorderHovered,borderPressedColor:n.inputFocusBorderAlt,borderFocusedColor:n.inputFocusBorderAlt,backgroundColor:n.inputBackground,erroredColor:n.errorText},a={headerTextColor:n.menuHeader,dividerBorderColor:n.bodyDivider},l={selectors:((h={})[Yt]={color:"GrayText"},h)},c=[{color:n.inputPlaceholderText},l],u=[{color:n.inputTextHovered},l],d=[{color:n.disabledText},l],p=ht(ht({color:"HighlightText",backgroundColor:"Window"},{forcedColorAdjust:"none",MsHighContrastAdjust:"none"}),{selectors:{":after":{borderColor:"Highlight"}}}),h=_o(s.borderPressedColor,i.roundedCorner2,"border",0);return un({container:{},label:{},labelDisabled:{},root:[e.fonts.medium,{boxShadow:"none",marginLeft:"0",paddingRight:32,paddingLeft:9,color:s.textColor,position:"relative",outline:"0",userSelect:"none",backgroundColor:s.backgroundColor,cursor:"text",display:"block",height:32,whiteSpace:"nowrap",textOverflow:"ellipsis",boxSizing:"border-box",selectors:{".ms-Label":{display:"inline-block",marginBottom:"8px"},"&.is-open":{selectors:((l={})[Yt]=p,l)},":after":{pointerEvents:"none",content:"''",position:"absolute",left:0,top:0,bottom:0,right:0,borderWidth:"1px",borderStyle:"solid",borderColor:s.borderColor,borderRadius:i.roundedCorner2}}}],rootHovered:{selectors:((u={":after":{borderColor:s.borderHoveredColor},".ms-ComboBox-Input":[{color:n.inputTextHovered},Zo(u),gf]})[Yt]=ht(ht({color:"HighlightText",backgroundColor:"Window"},{forcedColorAdjust:"none",MsHighContrastAdjust:"none"}),{selectors:{":after":{borderColor:"Highlight"}}}),u)},rootPressed:[{position:"relative",selectors:((u={})[Yt]=p,u)}],rootFocused:[{selectors:((u={".ms-ComboBox-Input":[{color:n.inputTextHovered},gf]})[Yt]=p,u)},h],rootDisabled:hf(e),rootError:{selectors:{":after":{borderColor:s.erroredColor},":hover:after":{borderColor:n.inputBorderHovered}}},rootDisallowFreeForm:{},input:[Zo(c),{backgroundColor:s.backgroundColor,color:s.textColor,boxSizing:"border-box",width:"100%",height:"100%",borderStyle:"none",outline:"none",font:"inherit",textOverflow:"ellipsis",padding:"0",selectors:{"::-ms-clear":{display:"none"}}},gf],inputDisabled:[hf(e),Zo(d)],errorMessage:[e.fonts.small,{color:s.erroredColor,marginTop:"5px"}],callout:{boxShadow:i.elevation8},optionsContainerWrapper:{width:o},optionsContainer:{display:"block"},screenReaderText:So,header:[r.medium,{fontWeight:Fe.semibold,color:a.headerTextColor,backgroundColor:"none",borderStyle:"none",height:36,lineHeight:36,cursor:"default",padding:"0 8px",userSelect:"none",textAlign:"left",selectors:((r={})[Yt]=ht({color:"GrayText"},{forcedColorAdjust:"none",MsHighContrastAdjust:"none"}),r)}],divider:{height:1,backgroundColor:a.dividerBorderColor}},t)}),yf=Ao(function(e,t,o,n,r,i,s,a){return{container:j("ms-ComboBox-container",t,e.container),label:j(e.label,n&&e.labelDisabled),root:j("ms-ComboBox",a?e.rootError:o&&"is-open",r&&"is-required",e.root,!s&&e.rootDisallowFreeForm,a&&!i?e.rootError:!n&&i&&e.rootFocused,!n&&{selectors:{":hover":a?e.rootError:!o&&!i&&e.rootHovered,":active":a?e.rootError:e.rootPressed,":focus":a?e.rootError:e.rootFocused}},n&&["is-disabled",e.rootDisabled]),input:j("ms-ComboBox-Input",e.input,n&&e.inputDisabled),errorMessage:j(e.errorMessage),callout:j("ms-ComboBox-callout",e.callout),optionsContainerWrapper:j("ms-ComboBox-optionsContainerWrapper",e.optionsContainerWrapper),optionsContainer:j("ms-ComboBox-optionsContainer",e.optionsContainer),header:j("ms-ComboBox-header",e.header),divider:j("ms-ComboBox-divider",e.divider),screenReaderText:j(e.screenReaderText)}}),Cf=Ao(function(e){return{optionText:j("ms-ComboBox-optionText",e.optionText),root:j("ms-ComboBox-option",e.root,{selectors:{":hover":e.rootHovered,":focus":e.rootFocused,":active":e.rootPressed}}),optionTextWrapper:j(e.optionTextWrapper)}});function _f(e,t){for(var o=[],n=0,r=t;n<r.length;n++){var i=e[r[n]];i&&o.push(i)}return o}(ke=cf=cf\|\|{})[ke.Normal=0]="Normal",ke[ke.Divider=1]="Divider",ke[ke.Header=2]="Header",ke[ke.SelectAll=3]="SelectAll",(K=uf=uf\|\|{})[K.backward=-1]="backward",K[K.none=0]="none",K[K.forward=1]="forward",(U=df=df\|\|{})[U.clearAll=-2]="clearAll",U[U.default=-1]="default";var Sf=gt.memo(function(e){return(0,e.render)()},function(e,t){e.render;e=mt(e,["render"]);return t.render,da(e,mt(t,["render"]))}),xf={options:[],allowFreeform:!1,autoComplete:"on",buttonIconProps:{iconName:"ChevronDown"}},kf=gt.forwardRef(function(e,t){var o,n,r,i,s,a,l,c=Hn(xf,e),u=(c.ref,mt(c,["ref"])),d=gt.useRef(null),p=_r(d,t),c=(o=u.options,n=u.defaultSelectedKey,r=u.selectedKey,i=gt.useState(function(){return Ef(o,(e=Tf(n)).length?e:Tf(r));var e}),e=i[0],s=i[1],c=gt.useState(o),t=c[0],a=c[1],i=gt.useState(),c=i[0],l=i[1],gt.useEffect(function(){var e;void 0!==r&&(e=Tf(r),e=Ef(o,e),s(e)),a(o)},[o,r]),gt.useEffect(function(){null===r&&l(void 0)},[r]),[e,s,t,a,c,l]);return gt.createElement(If,ht({},u,{hoisted:{mergedRootRef:p,rootRef:d,selectedIndices:c[0],setSelectedIndices:c[1],currentOptions:c[2],setCurrentOptions:c[3],suggestedDisplayValue:c[4],setSuggestedDisplayValue:c[5]}}))});kf.displayName="ComboBox";var wf,If=(l(Df,wf=gt.Component),Object.defineProperty(Df.prototype,"selectedOptions",{get:function(){var e=this.props.hoisted;return _f(e.currentOptions,e.selectedIndices)},enumerable:!1,configurable:!0}),Df.prototype.componentDidMount=function(){this._comboBoxWrapper.current&&!this.props.disabled&&(this._events.on(this._comboBoxWrapper.current,"focus",this._onResolveOptions,!0),"onpointerdown"in this._comboBoxWrapper.current&&this._events.on(this._comboBoxWrapper.current,"pointerdown",this._onPointerDown,!0))},Df.prototype.componentDidUpdate=function(e,t){var o=this,n=this.props,r=n.allowFreeform,i=n.text,s=n.onMenuOpen,a=n.onMenuDismissed,l=n.hoisted.selectedIndices,c=this.state,n=c.isOpen,c=c.currentPendingValueValidIndex;!n\|\|t.isOpen&&t.currentPendingValueValidIndex===c\|\|this._async.setTimeout(function(){return o._scrollIntoView()},0),this._hasFocus()&&(n\|\|t.isOpen&&!n&&this._focusInputAfterClose&&this._autofill.current&&document.activeElement!==this._autofill.current.inputElement)&&this.focus(void 0,!0),this._focusInputAfterClose&&(t.isOpen&&!n\|\|this._hasFocus()&&(!n&&!this.props.multiSelect&&e.hoisted.selectedIndices&&l&&e.hoisted.selectedIndices[0]!==l[0]\|\|!r\|\|i!==e.text))&&this._onFocus(),this._notifyPendingValueChanged(t),n&&!t.isOpen&&s&&s(),!n&&t.isOpen&&a&&a()},Df.prototype.componentWillUnmount=function(){this._async.dispose(),this._events.dispose()},Df.prototype.render=function(){var e=this._id+"-error",t=this.props,o=t.className,n=t.disabled,r=t.required,i=t.errorMessage,s=t.onRenderContainer,a=void 0===s?this._onRenderContainer:s,l=t.onRenderLabel,c=void 0===l?this._onRenderLabel:l,u=t.onRenderList,d=void 0===u?this._onRenderList:u,p=t.onRenderItem,h=void 0===p?this._onRenderItem:p,m=t.onRenderOption,g=void 0===m?this._onRenderOptionContent:m,f=t.allowFreeform,v=t.styles,b=t.theme,s=t.persistMenu,l=t.multiSelect,u=t.hoisted,p=u.suggestedDisplayValue,m=u.selectedIndices,t=u.currentOptions,u=this.state.isOpen;this._currentVisibleValue=this._getVisibleValue();l=l?this._getMultiselectDisplayString(m,t,p):void 0,m=ur(this.props,cr,["onChange","value"]),p=!!(i&&0<i.length);this._classNames=this.props.getClassNames?this.props.getClassNames(b,!!u,!!n,!!r,!!this._hasFocus(),!!f,!!p,o):yf(bf(b,v),o,!!u,!!n,!!r,!!this._hasFocus(),!!f,!!p);f=this._renderComboBoxWrapper(l,e);return gt.createElement("div",ht({},m,{ref:this.props.hoisted.mergedRootRef,className:this._classNames.container}),c({props:this.props,multiselectAccessibleText:l},this._onRenderLabel),f,(s\|\|u)&&a(ht(ht({},this.props),{onRenderList:d,onRenderItem:h,onRenderOption:g,options:t.map(function(e,t){return ht(ht({},e),{index:t})}),onDismiss:this._onDismiss}),this._onRenderContainer),p&&gt.createElement("div",{role:"alert",id:e,className:this._classNames.errorMessage},i))},Df.prototype._getPendingString=function(e,t,o){return null!=e?e:Rf(t,o)?t[o].text:""},Df.prototype._getMultiselectDisplayString=function(e,t,o){for(var n=[],r=0;e&&r<e.length;r++){var i=e[r];t[i].itemType!==cf.SelectAll&&n.push(Rf(t,i)?t[i].text:o\|\|"")}var s=this.props.multiSelectDelimiter;return n.join(void 0===s?", ":s)},Df.prototype._processInputChangeWithFreeform=function(t){var e=this.props.hoisted.currentOptions,o=-1;if(""===t)return 1===(r=e.map(function(e,t){return ht(ht({},e),{index:t})}).filter(function(e){return Mf(e)&&Bf(e)===t})).length&&(o=r[0].index),void this._setPendingInfo(t,o,t);var n=t;t=t.toLocaleLowerCase();var r,i,s="";"on"===this.props.autoComplete?0<(r=e.map(function(e,t){return ht(ht({},e),{index:t})}).filter(function(e){return Mf(e)&&0===Bf(e).toLocaleLowerCase().indexOf(t)})).length&&(s=(i=Bf(r[0])).toLocaleLowerCase()!==t?i:"",o=r[0].index):1===(r=e.map(function(e,t){return ht(ht({},e),{index:t})}).filter(function(e){return Mf(e)&&Bf(e).toLocaleLowerCase()===t})).length&&(o=r[0].index),this._setPendingInfo(n,o,s)},Df.prototype._processInputChangeWithoutFreeform=function(t){var e=this,o=this.props.hoisted.currentOptions,n=this.state,r=n.currentPendingValue,n=n.currentPendingValueValidIndex;if("on"===this.props.autoComplete&&""!==t){this._autoCompleteTimeout&&(this._async.clearTimeout(this._autoCompleteTimeout),this._autoCompleteTimeout=void 0,t=(r\|\|"")+t);r=t;t=t.toLocaleLowerCase();o=o.map(function(e,t){return ht(ht({},e),{index:t})}).filter(function(e){return Mf(e)&&0===e.text.toLocaleLowerCase().indexOf(t)});return 0<o.length&&this._setPendingInfo(r,o[0].index,Bf(o[0])),void(this._autoCompleteTimeout=this._async.setTimeout(function(){e._autoCompleteTimeout=void 0},1e3))}n=0<=n?n:this._getFirstSelectedIndex();this._setPendingInfoFromIndex(n)},Df.prototype._getFirstSelectedIndex=function(){var e=this.props.hoisted.selectedIndices;return null!=e&&e.length?e[0]:-1},Df.prototype._getNextSelectableIndex=function(e,t){var o=this.props.hoisted.currentOptions,n=e+t;if(!Rf(o,n=Math.max(0,Math.min(o.length-1,n))))return-1;var r=o[n];if(!Nf(r)\|\|!0===r.hidden){if(t===uf.none\|\|!(0<n&&t<uf.none\|\|0<=n&&n<o.length&&t>uf.none))return e;n=this._getNextSelectableIndex(n,t)}return n},Df.prototype._setSelectedIndex=function(t,e,o){void 0===o&&(o=uf.none);var n=this.props,r=n.onChange,i=n.onPendingValueChanged,s=n.hoisted,n=s.selectedIndices,s=s.currentOptions,a=n?n.slice():[],l=s.slice();if(Rf(s,t=this._getNextSelectableIndex(t,o))){if(this.props.multiSelect\|\|a.length<1\|\|1===a.length&&a[0]!==t){var c,n=ht({},s[t]);if(!n\|\|n.disabled)return;this.props.multiSelect?(n.selected=void 0!==n.selected?!n.selected:a.indexOf(t)<0,n.itemType===cf.SelectAll?(a=[],n.selected?s.forEach(function(e,t){!e.disabled&&Nf(e)&&(a.push(t),l[t]=ht(ht({},e),{selected:!0}))}):l=s.map(function(e){return ht(ht({},e),{selected:!1})})):(n.selected&&a.indexOf(t)<0?a.push(t):!n.selected&&0<=a.indexOf(t)&&(a=a.filter(function(e){return e!==t})),l[t]=n,(o=l.filter(function(e){return e.itemType===cf.SelectAll})[0])&&(s=this._isSelectAllChecked(a),c=l.indexOf(o),s?(a.push(c),l[c]=ht(ht({},o),{selected:!0})):(a=a.filter(function(e){return e!==c}),l[c]=ht(ht({},o),{selected:!1}))))):a[0]=t,e.persist(),this.props.selectedKey\|\|null===this.props.selectedKey\|\|(this.props.hoisted.setSelectedIndices(a),this.props.hoisted.setCurrentOptions(l)),this._hasPendingValue&&i&&(i(),this._hasPendingValue=!1),r&&r(e,n,t,void 0)}this.props.multiSelect&&this.state.isOpen\|\|this._clearPendingInfo()}},Df.prototype._submitPendingValue=function(e){var t=this.props,o=t.onChange,n=t.allowFreeform,r=t.autoComplete,i=t.multiSelect,s=t.hoisted,a=s.currentOptions,l=this.state,c=l.currentPendingValue,u=l.currentPendingValueValidIndex,d=l.currentPendingValueValidIndexOnHover,t=this.props.hoisted.selectedIndices;if(!this._processingClearPendingInfo){if(n){if(null==c)return void(0<=d&&(this._setSelectedIndex(d,e),this._clearPendingInfo()));if(Rf(a,u)){var l=Bf(a[u]).toLocaleLowerCase(),n=this._autofill.current;if(c.toLocaleLowerCase()===l\|\|r&&0===l.indexOf(c.toLocaleLowerCase())&&null!=n&&n.isValueSelected&&c.length+(n.selectionEnd-n.selectionStart)===l.length\|\|(null===(n=null==n?void 0:n.inputElement)\|\|void 0===n?void 0:n.value.toLocaleLowerCase())===l)return this._setSelectedIndex(u,e),i&&this.state.isOpen?void 0:void this._clearPendingInfo()}o?o(e,void 0,void 0,c):(c={key:c\|\|_s(),text:c\|\|""},i&&(c.selected=!0),c=a.concat([c]),t&&(t=!i?[]:t).push(c.length-1),s.setCurrentOptions(c),s.setSelectedIndices(t))}else 0<=u?this._setSelectedIndex(u,e):0<=d&&this._setSelectedIndex(d,e);this._clearPendingInfo()}},Df.prototype._onCalloutLayerMounted=function(){this._gotMouseMove=!1},Df.prototype._renderSeparator=function(e){var t=e.index,e=e.key;return t&&0<t?gt.createElement("div",{role:"separator",key:e,className:this._classNames.divider}):null},Df.prototype._renderHeader=function(e){var t=this.props.onRenderOption,t=void 0===t?this._onRenderOptionContent:t;return gt.createElement("div",{id:e.id,key:e.key,className:this._classNames.header},t(e,this._onRenderOptionContent))},Df.prototype._isOptionHighlighted=function(e){var t=this.state.currentPendingValueValidIndexOnHover;return t!==df.clearAll&&(0<=t?t===e:this._isOptionSelected(e))},Df.prototype._isOptionSelected=function(e){return this._getPendingSelectedIndex(!0)===e},Df.prototype._isOptionChecked=function(e){return!(!this.props.multiSelect\|\|void 0===e\|\|!this.props.hoisted.selectedIndices)&&0<=this.props.hoisted.selectedIndices.indexOf(e)},Df.prototype._isOptionIndeterminate=function(e){var t=this.props,o=t.multiSelect,t=t.hoisted;if(o&&void 0!==e&&t.selectedIndices&&t.currentOptions){e=t.currentOptions[e];if(e&&e.itemType===cf.SelectAll)return 0<t.selectedIndices.length&&!this._isSelectAllChecked()}return!1},Df.prototype._isSelectAllChecked=function(e){var t=this.props,o=t.multiSelect,n=t.hoisted,t=n.currentOptions.find(function(e){return e.itemType===cf.SelectAll}),e=e\|\|n.selectedIndices;if(!o\|\|!e\|\|!t)return!1;var r=n.currentOptions.indexOf(t),e=e.filter(function(e){return e!==r}),n=n.currentOptions.filter(function(e){return!e.disabled&&e.itemType!==cf.SelectAll&&Nf(e)});return e.length===n.length},Df.prototype._getPendingSelectedIndex=function(e){var t=this.state,o=t.currentPendingValueValidIndex,t=t.currentPendingValue;return 0<=o\|\|e&&null!=t?o:this.props.multiSelect?0:this._getFirstSelectedIndex()},Df.prototype._scrollIntoView=function(){var e,t,o=this.props,n=o.onScrollToItem,r=o.scrollSelectedToTop,i=this.state,s=i.currentPendingValueValidIndex,a=i.currentPendingValue;n?n(0<=s\|\|""!==a?s:this._getFirstSelectedIndex()):this._selectedElement.current&&this._selectedElement.current.offsetParent&&(e=!0,this._comboBoxMenu.current&&this._comboBoxMenu.current.offsetParent?(t=this._comboBoxMenu.current.offsetParent,i=(o=this._selectedElement.current.offsetParent).offsetHeight,n=o.offsetTop,a=t.offsetHeight,o=(s=t.scrollTop)+a<n+i,n<s\|\|r?(e=!1,t.scrollTo(0,n)):o&&t.scrollTo(0,n-a+i)):this._selectedElement.current.offsetParent.scrollIntoView(e))},Df.prototype._onItemClick=function(t){var o=this,n=this.props.onItemClick,r=t.index;return function(e){o.props.multiSelect\|\|(o._autofill.current&&o._autofill.current.focus(),o.setState({isOpen:!1})),n&&n(e,t,r),o._setSelectedIndex(r,e)}},Df.prototype._resetSelectedIndex=function(){var e=this.props.hoisted.currentOptions;this._clearPendingInfo();var t=this._getFirstSelectedIndex();0<t&&t<e.length?this.props.hoisted.setSuggestedDisplayValue(e[t].text):this.props.text&&this.props.hoisted.setSuggestedDisplayValue(this.props.text)},Df.prototype._clearPendingInfo=function(){this._processingClearPendingInfo=!0,this.props.hoisted.setSuggestedDisplayValue(void 0),this.setState({currentPendingValue:void 0,currentPendingValueValidIndex:-1,currentPendingValueValidIndexOnHover:df.default},this._onAfterClearPendingInfo)},Df.prototype._setPendingInfo=function(e,t,o){void 0===t&&(t=-1),this._processingClearPendingInfo\|\|(this.props.hoisted.setSuggestedDisplayValue(o),this.setState({currentPendingValue:e\|\|"",currentPendingValueValidIndex:t,currentPendingValueValidIndexOnHover:df.default}))},Df.prototype._setPendingInfoFromIndex=function(e){var t=this.props.hoisted.currentOptions;0<=e&&e<t.length?(t=t[e],this._setPendingInfo(Bf(t),e,Bf(t))):this._clearPendingInfo()},Df.prototype._setPendingInfoFromIndexAndDirection=function(e,t){var o=this.props.hoisted.currentOptions;t===uf.forward&&e>=o.length-1?e=-1:t===uf.backward&&e<=0&&(e=o.length);var n=this._getNextSelectableIndex(e,t);e===n?t===uf.forward?e=this._getNextSelectableIndex(-1,t):t===uf.backward&&(e=this._getNextSelectableIndex(o.length,t)):e=n,Rf(o,e)&&this._setPendingInfoFromIndex(e)},Df.prototype._notifyPendingValueChanged=function(e){var t,o,n,r,i,s,a=this.props.onPendingValueChanged;a&&(t=this.props.hoisted.currentOptions,o=(r=this.state).currentPendingValue,n=r.currentPendingValueValidIndex,s=i=void 0,(r=r.currentPendingValueValidIndexOnHover)!==e.currentPendingValueValidIndexOnHover&&Rf(t,r)?i=r:n!==e.currentPendingValueValidIndex&&Rf(t,n)?i=n:o!==e.currentPendingValue&&(s=o),void 0===i&&void 0===s&&!this._hasPendingValue\|\|(a(void 0!==i?t[i]:void 0,i,s),this._hasPendingValue=void 0!==i\|\|void 0!==s))},Df.prototype._setOpenStateAndFocusOnClose=function(e,t){this._focusInputAfterClose=t,this.setState({isOpen:e})},Df.prototype._onOptionMouseEnter=function(e){this._shouldIgnoreMouseEvent()\|\|this.setState({currentPendingValueValidIndexOnHover:e})},Df.prototype._onOptionMouseMove=function(e){this._gotMouseMove=!0,this._isScrollIdle&&this.state.currentPendingValueValidIndexOnHover!==e&&this.setState({currentPendingValueValidIndexOnHover:e})},Df.prototype._shouldIgnoreMouseEvent=function(){return!this._isScrollIdle\|\|!this._gotMouseMove},Df.prototype._handleInputWhenDisabled=function(e){this.props.disabled&&(this.state.isOpen&&this.setState({isOpen:!1}),null!==e&&e.which!==En.tab&&e.which!==En.escape&&(e.which<112\|\|123<e.which)&&(e.stopPropagation(),e.preventDefault()))},Df.prototype._handleTouchAndPointerEvent=function(){var e=this;void 0!==this._lastTouchTimeoutId&&(this._async.clearTimeout(this._lastTouchTimeoutId),this._lastTouchTimeoutId=void 0),this._processingTouch=!0,this._lastTouchTimeoutId=this._async.setTimeout(function(){e._processingTouch=!1,e._lastTouchTimeoutId=void 0},500)},Df.prototype._getCaretButtonStyles=function(){var e=this.props.caretDownButtonStyles;return vf(this.props.theme,e)},Df.prototype._getCurrentOptionStyles=function(e){var t=this.props.comboBoxOptionStyles,o=e.styles;return ff(this.props.theme,t,o,this._isPendingOption(e),e.hidden,this._isOptionHighlighted(e.index))},Df.prototype._getAriaActiveDescendantValue=function(){var e=this.props.hoisted.selectedIndices,t=this.state,o=t.isOpen,t=t.currentPendingValueValidIndex,e=o&&null!=e&&e.length?this._id+"-list"+e[0]:void 0;return e=o&&this._hasFocus()&&-1!==t?this._id+"-list"+t:e},Df.prototype._getAriaAutoCompleteValue=function(){return this.props.disabled\|\|"on"!==this.props.autoComplete?"none":this.props.allowFreeform?"inline":"both"},Df.prototype._isPendingOption=function(e){return e&&e.index===this.state.currentPendingValueValidIndex},Df.prototype._hasFocus=function(){return"none"!==this.state.focusState},c([Xu("ComboBox",["theme","styles"],!0)],Df));function Df(e){var v=wf.call(this,e)\|\|this;return v._autofill=gt.createRef(),v._comboBoxWrapper=gt.createRef(),v._comboBoxMenu=gt.createRef(),v._selectedElement=gt.createRef(),v.focus=function(e,t){v.props.disabled\|\|(v._autofill.current&&(t?gs(v._autofill.current):v._autofill.current.focus(),e&&v.setState({isOpen:!0})),v._hasFocus()\|\|v.setState({focusState:"focused"}))},v.dismissMenu=function(){v.state.isOpen&&v.setState({isOpen:!1})},v._onUpdateValueInAutofillWillReceiveProps=function(){var e=v._autofill.current;if(!e)return null;if(null===e.value\|\|void 0===e.value)return null;var t=Pf(v._currentVisibleValue);return e.value!==t?t:e.value},v._renderComboBoxWrapper=function(e,t){var o=v.props,n=o.label,r=o.disabled,i=o.ariaLabel,s=o.ariaDescribedBy,a=o.required,l=o.errorMessage,c=o.buttonIconProps,u=o.isButtonAriaHidden,d=void 0===u\|\|u,p=o.title,h=o.placeholder,m=o.tabIndex,g=o.autofill,f=o.iconButtonProps,u=o.hoisted.suggestedDisplayValue,o=v.state.isOpen,h=v._hasFocus()&&v.props.multiSelect&&e?e:h;return gt.createElement("div",{"data-ktp-target":!0,ref:v._comboBoxWrapper,id:v._id+"wrapper",className:v._classNames.root,"aria-owns":o?v._id+"-list":void 0},gt.createElement(ki,ht({"data-ktp-execute-target":!0,"data-is-interactable":!r,componentRef:v._autofill,id:v._id+"-input",className:v._classNames.input,type:"text",onFocus:v._onFocus,onBlur:v._onBlur,onKeyDown:v._onInputKeyDown,onKeyUp:v._onInputKeyUp,onClick:v._onAutofillClick,onTouchStart:v._onTouchStart,onInputValueChange:v._onInputChange,"aria-expanded":o,"aria-autocomplete":v._getAriaAutoCompleteValue(),role:"combobox",readOnly:r,"aria-labelledby":n&&v._id+"-label","aria-label":i&&!n?i:void 0,"aria-describedby":void 0!==l?Ia(s,t):s,"aria-activedescendant":v._getAriaActiveDescendantValue(),"aria-required":a,"aria-disabled":r,"aria-controls":o?v._id+"-list":void 0,spellCheck:!1,defaultVisibleValue:v._currentVisibleValue,suggestedDisplayValue:u,updateValueInWillReceiveProps:v._onUpdateValueInAutofillWillReceiveProps,shouldSelectFullInputValueInComponentDidUpdate:v._onShouldSelectFullInputValueInAutofillComponentDidUpdate,title:p,preventValueSelection:!v._hasFocus(),placeholder:h,tabIndex:r?-1:m},g)),gt.createElement(rd,ht({className:"ms-ComboBox-CaretDown-button",styles:v._getCaretButtonStyles(),role:"presentation","aria-hidden":d,"data-is-focusable":!1,tabIndex:-1,onClick:v._onComboBoxClick,onBlur:v._onBlur,iconProps:c,disabled:r,checked:o},f)))},v._onShouldSelectFullInputValueInAutofillComponentDidUpdate=function(){return v._currentVisibleValue===v.props.hoisted.suggestedDisplayValue},v._getVisibleValue=function(){var e=v.props,t=e.text,o=e.allowFreeform,n=e.autoComplete,r=e.hoisted,i=r.suggestedDisplayValue,s=r.selectedIndices,a=r.currentOptions,l=v.state,c=l.currentPendingValueValidIndex,e=l.currentPendingValue,r=l.isOpen,l=Rf(a,c);if((!r\|\|!l)&&t&&null==e)return t;if(v.props.multiSelect){if(v._hasFocus()){var u="on"===n&&l?c:-1;return v._getPendingString(e,a,u)}return v._getMultiselectDisplayString(s,a,i)}return u=v._getFirstSelectedIndex(),o?v._getPendingString(e,a,u="on"===n&&l?c:u):l&&"on"===n?(u=c,e\|\|""):!v.state.isOpen&&e?Rf(a,u)?e:i\|\|"":Rf(a,u)?Bf(a[u]):i\|\|""},v._onInputChange=function(e){v.props.disabled?v._handleInputWhenDisabled(null):(v.props.onInputValueChange&&v.props.onInputValueChange(e),v.props.allowFreeform?v._processInputChangeWithFreeform(e):v._processInputChangeWithoutFreeform(e))},v._onFocus=function(){var e;null===(e=null===(e=v._autofill.current)\|\|void 0===e?void 0:e.inputElement)\|\|void 0===e\|\|e.select(),v._hasFocus()\|\|v.setState({focusState:"focusing"})},v._onResolveOptions=function(){var t;v.props.onResolveOptions&&(t=v.props.onResolveOptions($e([],v.props.hoisted.currentOptions)),Array.isArray(t)?v.props.hoisted.setCurrentOptions(t):t&&t.then&&(v._currentPromise=t).then(function(e){t===v._currentPromise&&v.props.hoisted.setCurrentOptions(e)}))},v._onBlur=function(e){var t=e.relatedTarget;if(t=null===e.relatedTarget?document.activeElement:t){var o=null===(n=v.props.hoisted.rootRef.current)\|\|void 0===n?void 0:n.contains(t),n=null===(r=v._comboBoxMenu.current)\|\|void 0===r?void 0:r.contains(t),r=v._comboBoxMenu.current&&Qi(v._comboBoxMenu.current,function(e){return e===t});if(o\|\|n\|\|r)return r&&v._hasFocus()&&(!v.props.multiSelect\|\|v.props.allowFreeform)&&v._submitPendingValue(e),e.preventDefault(),void e.stopPropagation()}v._hasFocus()&&(v.setState({focusState:"none"}),v.props.multiSelect&&!v.props.allowFreeform\|\|v._submitPendingValue(e))},v._onRenderContainer=function(e,t){var o=e.onRenderList,n=e.calloutProps,r=e.dropdownWidth,i=e.dropdownMaxWidth,s=e.onRenderUpperContent,a=void 0===s?v._onRenderUpperContent:s,l=e.onRenderLowerContent,c=void 0===l?v._onRenderLowerContent:l,u=e.useComboBoxAsMenuWidth,d=e.persistMenu,p=e.shouldRestoreFocus,h=void 0===p\|\|p,s=v.state.isOpen,l=v._id,p=u&&v._comboBoxWrapper.current?v._comboBoxWrapper.current.clientWidth+2:void 0;return gt.createElement(ac,ht({isBeakVisible:!1,gapSpace:0,doNotLayer:!1,directionalHint:Pa.bottomLeftEdge,directionalHintFixed:!1},n,{onLayerMounted:v._onLayerMounted,className:Tr(v._classNames.callout,null==n?void 0:n.className),target:v._comboBoxWrapper.current,onDismiss:v._onDismiss,onMouseDown:v._onCalloutMouseDown,onScroll:v._onScroll,setInitialFocus:!1,calloutWidth:u&&v._comboBoxWrapper.current?p:r,calloutMaxWidth:i\|\|p,hidden:d?!s:void 0,shouldRestoreFocus:h}),a(v.props,v._onRenderUpperContent),gt.createElement("div",{className:v._classNames.optionsContainerWrapper,ref:v._comboBoxMenu},null==o?void 0:o(ht(ht({},e),{id:l}),v._onRenderList)),c(v.props,v._onRenderLowerContent))},v._onLayerMounted=function(){v._onCalloutLayerMounted(),v._async.setTimeout(function(){v._scrollIntoView()},0),v.props.calloutProps&&v.props.calloutProps.onLayerMounted&&v.props.calloutProps.onLayerMounted()},v._onRenderLabel=function(e){var t=e.props,o=t.label,n=t.disabled,t=t.required;return o?gt.createElement(om,{id:v._id+"-label",disabled:n,required:t,className:v._classNames.label},o,e.multiselectAccessibleText&&gt.createElement("span",{className:v._classNames.screenReaderText},e.multiselectAccessibleText)):null},v._onRenderList=function(e){function n(){var e=s.id?[gt.createElement("div",{role:"group",key:s.id,"aria-labelledby":s.id},s.items)]:s.items;a=$e($e([],a),e),s={items:[]}}var t=e.onRenderItem,r=void 0===t?v._onRenderItem:t,o=e.label,i=e.ariaLabel,t=e.multiSelect,s={items:[]},a=[];e.options.forEach(function(e,t){!function(e,t){switch(e.itemType){case cf.Header:0<s.items.length&&n();var o=v._id+e.key;s.items.push(r(ht(ht({id:o},e),{index:t}),v._onRenderItem)),s.id=o;break;case cf.Divider:0<t&&s.items.push(r(ht(ht({},e),{index:t}),v._onRenderItem)),0<s.items.length&&n();break;default:s.items.push(r(ht(ht({},e),{index:t}),v._onRenderItem))}}(e,t)}),0<s.items.length&&n();e=v._id;return gt.createElement("div",{id:e+"-list",className:v._classNames.optionsContainer,"aria-labelledby":o&&e+"-label","aria-label":i&&!o?i:void 0,"aria-multiselectable":t?"true":void 0,role:"listbox"},a)},v._onRenderItem=function(e){switch(e.itemType){case cf.Divider:return v._renderSeparator(e);case cf.Header:return v._renderHeader(e);default:return v._renderOption(e)}},v._onRenderLowerContent=function(){return null},v._onRenderUpperContent=function(){return null},v._renderOption=function(e){function t(){return n(e,v._onRenderOptionContent)}var o=v.props.onRenderOption,n=void 0===o?v._onRenderOptionContent:o,r=v._id,i=v._isOptionSelected(e.index),s=v._isOptionChecked(e.index),a=v._isOptionIndeterminate(e.index),l=v._getCurrentOptionStyles(e),c=Cf(v._getCurrentOptionStyles(e)),u=e.title;return gt.createElement(Sf,{key:e.key,index:e.index,disabled:e.disabled,isSelected:i,isChecked:s,isIndeterminate:a,text:e.text,render:function(){return v.props.multiSelect?gt.createElement($h,{id:r+"-list"+e.index,ariaLabel:e.ariaLabel,key:e.key,styles:l,className:"ms-ComboBox-option",onChange:v._onItemClick(e),label:e.text,checked:s,indeterminate:a,title:u,disabled:e.disabled,onRenderLabel:t,inputProps:ht({"aria-selected":s?"true":"false",role:"option"},{"data-index":e.index,"data-is-focusable":!0})}):gt.createElement(up,{id:r+"-list"+e.index,key:e.key,"data-index":e.index,styles:l,checked:i,className:"ms-ComboBox-option",onClick:v._onItemClick(e),onMouseEnter:v._onOptionMouseEnter.bind(v,e.index),onMouseMove:v._onOptionMouseMove.bind(v,e.index),onMouseLeave:v._onOptionMouseLeave,role:"option","aria-selected":i?"true":"false",ariaLabel:e.ariaLabel,disabled:e.disabled,title:u},gt.createElement("span",{className:c.optionTextWrapper,ref:i?v._selectedElement:void 0},n(e,v._onRenderOptionContent)))},data:e.data})},v._onCalloutMouseDown=function(e){e.preventDefault()},v._onScroll=function(){v._isScrollIdle\|\|void 0===v._scrollIdleTimeoutId?v._isScrollIdle=!1:(v._async.clearTimeout(v._scrollIdleTimeoutId),v._scrollIdleTimeoutId=void 0),v._scrollIdleTimeoutId=v._async.setTimeout(function(){v._isScrollIdle=!0},250)},v._onRenderOptionContent=function(e){var t=Cf(v._getCurrentOptionStyles(e));return gt.createElement("span",{className:t.optionText},e.text)},v._onDismiss=function(){var e=v.props.onMenuDismiss;e&&e(),v.props.persistMenu&&v._onCalloutLayerMounted(),v._setOpenStateAndFocusOnClose(!1,!1),v._resetSelectedIndex()},v._onAfterClearPendingInfo=function(){v._processingClearPendingInfo=!1},v._onInputKeyDown=function(e){var t=v.props,o=t.disabled,n=t.allowFreeform,r=t.autoComplete,i=t.hoisted.currentOptions,t=v.state,s=t.isOpen,a=t.currentPendingValueValidIndexOnHover;if(v._lastKeyDownWasAltOrMeta=Ff(e),o)v._handleInputWhenDisabled(e);else{var l=v._getPendingSelectedIndex(!1);switch(e.which){case En.enter:v._autofill.current&&v._autofill.current.inputElement&&v._autofill.current.inputElement.select(),v._submitPendingValue(e),v.props.multiSelect&&s?v.setState({currentPendingValueValidIndex:l}):(s\|\|(!n\|\|void 0===v.state.currentPendingValue\|\|null===v.state.currentPendingValue\|\|v.state.currentPendingValue.length<=0)&&v.state.currentPendingValueValidIndex<0)&&v.setState({isOpen:!s});break;case En.tab:return v.props.multiSelect\|\|v._submitPendingValue(e),void(s&&v._setOpenStateAndFocusOnClose(!s,!1));case En.escape:if(v._resetSelectedIndex(),!s)return;v.setState({isOpen:!1});break;case En.up:if(a===df.clearAll&&(l=v.props.hoisted.currentOptions.length),e.altKey\|\|e.metaKey){if(s){v._setOpenStateAndFocusOnClose(!s,!0);break}return}e.preventDefault(),v._setPendingInfoFromIndexAndDirection(l,uf.backward);break;case En.down:e.altKey\|\|e.metaKey?v._setOpenStateAndFocusOnClose(!0,!0):(a===df.clearAll&&(l=-1),e.preventDefault(),v._setPendingInfoFromIndexAndDirection(l,uf.forward));break;case En.home:case En.end:if(n)return;var l=-1,c=uf.forward;e.which===En.end&&(l=i.length,c=uf.backward),v._setPendingInfoFromIndexAndDirection(l,c);break;case En.space:if(!n&&"off"===r)break;default:if(112<=e.which&&e.which<=123)return;if(e.keyCode===En.alt\|\|"Meta"===e.key)return;if(n\|\|"on"!==r)return;v._onInputChange(e.key)}e.stopPropagation(),e.preventDefault()}},v._onInputKeyUp=function(e){var t=v.props,o=t.disabled,n=t.allowFreeform,r=t.autoComplete,i=v.state.isOpen,t=v._lastKeyDownWasAltOrMeta&&Ff(e);v._lastKeyDownWasAltOrMeta=!1;t=t&&!(Na()\|\|Aa());o?v._handleInputWhenDisabled(e):e.which!==En.space?t&&i?v._setOpenStateAndFocusOnClose(!i,!0):("focusing"===v.state.focusState&&v.props.openOnKeyboardFocus&&v.setState({isOpen:!0}),"focused"!==v.state.focusState&&v.setState({focusState:"focused"})):n\|\|"off"!==r\|\|v._setOpenStateAndFocusOnClose(!i,!!i)},v._onOptionMouseLeave=function(){v._shouldIgnoreMouseEvent()\|\|v.props.persistMenu&&!v.state.isOpen\|\|v.setState({currentPendingValueValidIndexOnHover:df.clearAll})},v._onComboBoxClick=function(){var e=v.props.disabled,t=v.state.isOpen;e\|\|(v._setOpenStateAndFocusOnClose(!t,!1),v.setState({focusState:"focused"}))},v._onAutofillClick=function(){var e=v.props,t=e.disabled;e.allowFreeform&&!t?v.focus(v.state.isOpen\|\|v._processingTouch):v._onComboBoxClick()},v._onTouchStart=function(){!v._comboBoxWrapper.current\|\|"onpointerdown"in v._comboBoxWrapper\|\|v._handleTouchAndPointerEvent()},v._onPointerDown=function(e){"touch"===e.pointerType&&(v._handleTouchAndPointerEvent(),e.preventDefault(),e.stopImmediatePropagation())},fi(v),v._async=new Si(v),v._events=new va(v),v._id=e.id\|\|_s("ComboBox"),v._isScrollIdle=!0,v._processingTouch=!1,v._gotMouseMove=!1,v._processingClearPendingInfo=!1,v.state={isOpen:!1,focusState:"none",currentPendingValueValidIndex:-1,currentPendingValue:void 0,currentPendingValueValidIndexOnHover:df.default},v}function Ef(o,e){if(!o\|\|!e)return[];var n={};o.forEach(function(e,t){e.selected&&(n[t]=!0)});for(var t=0,r=e;t<r.length;t++)!function(t){var e=Hi(o,function(e){return e.key===t});-1<e&&(n[e]=!0)}(r[t]);return Object.keys(n).map(Number).sort()}function Tf(e){return void 0===e?[]:e instanceof Array?e:[e]}function Pf(e){return e\|\|""}function Rf(e,t){return!!e&&0<=t&&t<e.length}function Mf(e){return e.itemType!==cf.Header&&e.itemType!==cf.Divider&&e.itemType!==cf.SelectAll}function Nf(e){return e.itemType!==cf.Header&&e.itemType!==cf.Divider}function Bf(e){return e.useAriaLabelAsText&&e.ariaLabel?e.ariaLabel:e.text}function Ff(e){return e.which===En.alt\|\|"Meta"===e.key}var Af,Lf={auto:0,top:1,bottom:2,center:3},Hf={top:-1,bottom:-1,left:-1,right:-1,width:0,height:0},xe=function(e){return e.getBoundingClientRect()},Of=xe,zf=xe,Wf=(l(Vf,Af=gt.Component),Vf.getDerivedStateFromProps=function(e,t){return t.getDerivedStateFromProps(e,t)},Object.defineProperty(Vf.prototype,"pageRefs",{get:function(){return this._pageRefs},enumerable:!1,configurable:!0}),Vf.prototype.scrollToIndex=function(e,t,o){void 0===o&&(o=Lf.auto);for(var n=this.props.startIndex,r=n+this._getRenderCount(),i=this._allowedRect,s=0,a=n;a<r;a+=u){var l=this._getPageSpecification(a,i),c=l.height,u=l.itemCount;if(a<=e&&e<a+u){if(t&&this._scrollElement){for(var d=zf(this._scrollElement),p=this._scrollElement.scrollTop,l=this._scrollElement.scrollTop+d.height,h=e-a,m=0;m<h;++m)s+=t(a+m);var g=s+t(e);switch(o){case Lf.top:return void(this._scrollElement.scrollTop=s);case Lf.bottom:return void(this._scrollElement.scrollTop=g-d.height);case Lf.center:return void(this._scrollElement.scrollTop=(s+g-d.height)/2);case Lf.auto:}if(p<=s&&g<=l)return;s<p\|\|l<g&&(s=g-d.height)}return void(this._scrollElement&&(this._scrollElement.scrollTop=s))}s+=c}},Vf.prototype.getStartItemIndexInView=function(e){for(var t=0,o=this.state.pages\|\|[];t<o.length;t++){var n=o[t];if(!n.isSpacer&&(this._scrollTop\|\|0)>=n.top&&(this._scrollTop\|\|0)<=n.top+n.height){if(!e){var r=Math.floor(n.height/n.itemCount);return n.startIndex+Math.floor((this._scrollTop-n.top)/r)}for(var i=0,s=n.startIndex;s<n.startIndex+n.itemCount;s++){if(r=e(s),n.top+i<=this._scrollTop&&this._scrollTop<n.top+i+r)return s;i+=r}}}return 0},Vf.prototype.componentDidMount=function(){this.setState(this._updatePages(this.props,this.state)),this._measureVersion++,this._scrollElement=Ns(this._root.current),this._events.on(window,"resize",this._onAsyncResize),this._root.current&&this._events.on(this._root.current,"focus",this._onFocus,!0),this._scrollElement&&(this._events.on(this._scrollElement,"scroll",this._onScroll),this._events.on(this._scrollElement,"scroll",this._onAsyncScroll))},Vf.prototype.componentDidUpdate=function(e,t){var o=this.props,n=this.state;this.state.pagesVersion!==t.pagesVersion&&(!o.getPageHeight&&this._updatePageMeasurements(n.pages)?(this._materializedRect=null,this._hasCompletedFirstRender?this._onAsyncScroll():(this._hasCompletedFirstRender=!0,this.setState(this._updatePages(o,n)))):this._onAsyncIdle(),o.onPagesUpdated&&o.onPagesUpdated(n.pages))},Vf.prototype.componentWillUnmount=function(){this._async.dispose(),this._events.dispose(),delete this._scrollElement},Vf.prototype.shouldComponentUpdate=function(e,t){var o=this.state.pages,n=t.pages,r=!1;if(!t.isScrolling&&this.state.isScrolling)return!0;if(e.version!==this.props.version)return!0;if(e.items===this.props.items&&o.length===n.length)for(var i=0;i<o.length;i++){var s=o[i],a=n[i];if(s.key!==a.key\|\|s.itemCount!==a.itemCount){r=!0;break}}else r=!0;return r},Vf.prototype.forceUpdate=function(){this._invalidatePageCache(),this._updateRenderRects(this.props,this.state,!0),this.setState(this._updatePages(this.props,this.state)),this._measureVersion++,Af.prototype.forceUpdate.call(this)},Vf.prototype.getTotalListHeight=function(){return this._surfaceRect.height},Vf.prototype.render=function(){for(var e=this.props,t=e.className,o=e.role,n=void 0===o?"list":o,r=e.onRenderSurface,i=e.onRenderRoot,o=this.state.pages,e=void 0===o?[]:o,s=[],o=ur(this.props,cr),a=0,l=e;a<l.length;a++){var c=l[a];s.push(this._renderPage(c))}r=r?Ma(r,this._onRenderSurface):this._onRenderSurface;return(i?Ma(i,this._onRenderRoot):this._onRenderRoot)({rootRef:this._root,pages:e,surfaceElement:r({surfaceRef:this._surface,pages:e,pageElements:s,divProps:{role:"presentation",className:"ms-List-surface"}}),divProps:ht(ht({},o),{className:Tr("ms-List",t),role:0<s.length?n:void 0,"aria-label":0<s.length?o["aria-label"]:void 0})})},Vf.prototype._shouldVirtualize=function(e){var t=(e=void 0===e?this.props:e).onShouldVirtualize;return!t\|\|t(e)},Vf.prototype._invalidatePageCache=function(){this._pageCache={}},Vf.prototype._renderPage=function(t){var o=this,e=this.props.usePageCache;if(e&&(r=this._pageCache[t.key])&&r.pageElement)return r.pageElement;var n=this._getPageStyle(t),r=this.props.onRenderPage,n=(void 0===r?this._onRenderPage:r)({page:t,className:"ms-List-page",key:t.key,ref:function(e){o._pageRefs[t.key]=e},style:n,role:"presentation"},this._onRenderPage);return e&&0===t.startIndex&&(this._pageCache[t.key]={page:t,pageElement:n}),n},Vf.prototype._getPageStyle=function(e){var t=this.props.getPageStyle;return ht(ht({},t?t(e):{}),e.items?{}:{height:e.height})},Vf.prototype._onFocus=function(e){for(var t=e.target;t!==this._surface.current;){var o=t.getAttribute("data-list-index");if(o){this._focusedIndex=Number(o);break}t=Xi(t)}},Vf.prototype._onScroll=function(){this.state.isScrolling\|\|this.props.ignoreScrollingState\|\|this.setState({isScrolling:!0}),this._resetRequiredWindows(),this._onScrollingDone()},Vf.prototype._resetRequiredWindows=function(){this._requiredWindowsAhead=0,this._requiredWindowsBehind=0},Vf.prototype._onAsyncScroll=function(){var e,t;this._updateRenderRects(this.props,this.state),this._materializedRect&&(e=this._requiredRect,t=this._materializedRect,e.top>=t.top&&e.left>=t.left&&e.bottom<=t.bottom&&e.right<=t.right)\|\|this.setState(this._updatePages(this.props,this.state))},Vf.prototype._onAsyncIdle=function(){var e=this.props,t=e.renderedWindowsAhead,o=e.renderedWindowsBehind,n=this._requiredWindowsAhead,r=this._requiredWindowsBehind,i=Math.min(t,n+1),e=Math.min(o,r+1);i===n&&e===r\|\|(this._requiredWindowsAhead=i,this._requiredWindowsBehind=e,this._updateRenderRects(this.props,this.state),this.setState(this._updatePages(this.props,this.state))),(i<t\|\|e<o)&&this._onAsyncIdle()},Vf.prototype._onScrollingDone=function(){this.props.ignoreScrollingState\|\|this.setState({isScrolling:!1})},Vf.prototype._onAsyncResize=function(){this.forceUpdate()},Vf.prototype._updatePages=function(e,t){this._requiredRect\|\|this._updateRenderRects(e,t);var o=this._buildPages(e,t),e=t.pages;return this._notifyPageChanges(e,o.pages,this.props),ht(ht(ht({},t),o),{pagesVersion:{}})},Vf.prototype._notifyPageChanges=function(e,t,o){var n=o.onPageAdded,o=o.onPageRemoved;if(n\|\|o){for(var r={},i=0,s=e;i<s.length;i++)(a=s[i]).items&&(r[a.startIndex]=a);for(var a,l,c=0,u=t;c<u.length;c++)(a=u[c]).items&&(r[a.startIndex]?delete r[a.startIndex]:this._onPageAdded(a));for(l in r)r.hasOwnProperty(l)&&this._onPageRemoved(r[l])}},Vf.prototype._updatePageMeasurements=function(e){var t=!1;if(!this._shouldVirtualize())return t;for(var o=0;o<e.length;o++){var n=e[o];n.items&&(t=this._measurePage(n)\|\|t)}return t},Vf.prototype._measurePage=function(e){var t=!1,o=this._pageRefs[e.key],n=this._cachedPageHeights[e.startIndex];return!o\|\|!this._shouldVirtualize()\|\|n&&n.measureVersion===this._measureVersion\|\|((o={width:o.clientWidth,height:o.clientHeight}).height\|\|o.width)&&(t=e.height!==o.height,e.height=o.height,this._cachedPageHeights[e.startIndex]={height:o.height,measureVersion:this._measureVersion},this._estimatedPageHeight=Math.round((this._estimatedPageHeightthis._totalEstimates+o.height)/(this._totalEstimates+1)),this._totalEstimates++),t},Vf.prototype._onPageAdded=function(e){var t=this.props.onPageAdded;t&&t(e)},Vf.prototype._onPageRemoved=function(e){var t=this.props.onPageRemoved;t&&t(e)},Vf.prototype._buildPages=function(e,l){e.renderCount;for(var c=e.items,u=e.startIndex,t=e.getPageHeight,o=this._getRenderCount(e),d=ht({},Hf),p=[],h=1,m=0,g=null,f=this._focusedIndex,v=u+o,b=this._shouldVirtualize(e),y=0===this._estimatedPageHeight&&!t,C=this._allowedRect,_=this,n=u;n<v&&"break"!==function(t){var e=_._getPageSpecification(t,C),o=e.height,n=e.data,r=e.key;h=e.itemCount;var i=m+o-1,s=-1<Hi(l.pages,function(e){return e.items&&e.startIndex===t}),a=!C\|\|i>=C.top&&m<=C.bottom,e=!_._requiredRect\|\|i>=_._requiredRect.top&&m<=_._requiredRect.bottom;if(!y&&(e\|\|a&&s)\|\|!b\|\|t<=f&&f<t+h\|\|t===u?(g&&(p.push(g),g=null),s=Math.min(h,v-t),(s=_._createPage(r,c.slice(t,t+s),t,void 0,void 0,n)).top=m,s.height=o,_._visibleRect&&_._visibleRect.bottom&&(s.isVisible=i>=_._visibleRect.top&&m<=_._visibleRect.bottom),p.push(s),e&&_._allowedRect&&(e={top:m,bottom:i,height:o,left:C.left,right:C.right,width:C.width},(o=d).top=(e.top<o.top\|\|-1===o.top?e:o).top,o.left=(e.left<o.left\|\|-1===o.left?e:o).left,o.bottom=(e.bottom>o.bottom\|\|-1===o.bottom?e:o).bottom,o.right=(e.right>o.right\|\|-1===o.right?e:o).right,o.width=o.right-o.left+1,o.height=o.bottom-o.top+1)):((g=g\|\|_._createPage("spacer-"+t,void 0,t,0,void 0,n,!0)).height=(g.height\|\|0)+(i-m)+1,g.itemCount+=h),m+=i-m+1,y&&b)return"break"}(n);n+=h);return g&&(g.key="spacer-end",p.push(g)),this._materializedRect=d,ht(ht({},l),{pages:p,measureVersion:this._measureVersion})},Vf.prototype._getPageSpecification=function(e,t){var o=this.props.getPageSpecification;if(o){var n=o(e,t),o=n.itemCount,r=void 0===o?this._getItemCountForPage(e,t):o,o=n.height;return{itemCount:r,height:void 0===o?this._getPageHeight(e,t,r):o,data:n.data,key:n.key}}return{itemCount:r=this._getItemCountForPage(e,t),height:this._getPageHeight(e,t,r)}},Vf.prototype._getPageHeight=function(e,t,o){if(this.props.getPageHeight)return this.props.getPageHeight(e,t,o);e=this._cachedPageHeights[e];return e?e.height:this._estimatedPageHeight\|\|30},Vf.prototype._getItemCountForPage=function(e,t){return(this.props.getItemCountForPage?this.props.getItemCountForPage(e,t):10)\|\|10},Vf.prototype._createPage=function(e,t,o,n,r,i,s){void 0===o&&(o=-1),void 0===n&&(n=t?t.length:0),void 0===r&&(r={});var a=this._pageCache[e=e\|\|"page-"+o];return a&&a.page?a.page:{key:e,startIndex:o,itemCount:n,items:t,style:r,top:0,height:0,data:i,isSpacer:s\|\|!1}},Vf.prototype._getRenderCount=function(e){var t=e\|\|this.props,o=t.items,e=t.startIndex,t=t.renderCount;return void 0===t?o?o.length-e:0:t},Vf.prototype._updateRenderRects=function(e,t,o){var n,r=e.renderedWindowsAhead,i=e.renderedWindowsBehind,s=t.pages;this._shouldVirtualize(e)&&(n=this._surfaceRect\|\|ht({},Hf),t=this._scrollElement&&this._scrollElement.scrollHeight,e=this._scrollElement?this._scrollElement.scrollTop:0,this._surface.current&&(o\|\|!s\|\|!this._surfaceRect\|\|!t\|\|t!==this._scrollHeight\|\|Math.abs(this._scrollTop-e)>this._estimatedPageHeight/3)&&(n=this._surfaceRect=Of(this._surface.current),this._scrollTop=e),!o&&t&&t===this._scrollHeight\|\|this._measureVersion++,this._scrollHeight=t\|\|0,o=Math.max(0,-n.top),t=qe(this._root.current),t={top:o,left:n.left,bottom:o+t.innerHeight,right:n.right,width:n.width,height:t.innerHeight},this._requiredRect=Kf(t,this._requiredWindowsBehind,this._requiredWindowsAhead),this._allowedRect=Kf(t,i,r),this._visibleRect=t)},Vf.defaultProps={startIndex:0,onRenderCell:function(e,t,o){return gt.createElement(gt.Fragment,null,e&&e.name\|\|"")},renderedWindowsAhead:2,renderedWindowsBehind:2},Vf);function Vf(e){var m=Af.call(this,e)\|\|this;return m._root=gt.createRef(),m._surface=gt.createRef(),m._pageRefs={},m._getDerivedStateFromProps=function(e,t){return e.items!==m.props.items\|\|e.renderCount!==m.props.renderCount\|\|e.startIndex!==m.props.startIndex\|\|e.version!==m.props.version?(m._resetRequiredWindows(),m._requiredRect=null,m._measureVersion++,m._invalidatePageCache(),m._updatePages(e,t)):t},m._onRenderRoot=function(e){var t=e.rootRef,o=e.surfaceElement,e=e.divProps;return gt.createElement("div",ht({ref:t},e),o)},m._onRenderSurface=function(e){var t=e.surfaceRef,o=e.pageElements,e=e.divProps;return gt.createElement("div",ht({ref:t},e),o)},m._onRenderPage=function(e,t){for(var o=m.props,n=o.onRenderCell,r=o.role,i=e.page,o=i.items,s=void 0===o?[]:o,a=i.startIndex,e=mt(e,["page"]),l=void 0===r?"listitem":"presentation",c=[],u=0;u<s.length;u++){var d=a+u,p=s[u],h=m.props.getKey?m.props.getKey(p,d):p&&p.key;null==h&&(h=d),c.push(gt.createElement("div",{role:l,className:"ms-List-cell",key:h,"data-list-index":d,"data-automationid":"ListCell"},n&&n(p,d,m.props.ignoreScrollingState?void 0:m.state.isScrolling)))}return gt.createElement("div",ht({},e),c)},fi(m),m.state={pages:[],isScrolling:!1,getDerivedStateFromProps:m._getDerivedStateFromProps},m._async=new Si(m),m._events=new va(m),m._estimatedPageHeight=0,m._totalEstimates=0,m._requiredWindowsAhead=0,m._requiredWindowsBehind=0,m._measureVersion=0,m._onAsyncScroll=m._async.debounce(m._onAsyncScroll,100,{leading:!1,maxWait:500}),m._onAsyncIdle=m._async.debounce(m._onAsyncIdle,200,{leading:!1}),m._onAsyncResize=m._async.debounce(m._onAsyncResize,16,{leading:!1}),m._onScrollingDone=m._async.debounce(m._onScrollingDone,500,{leading:!1}),m._cachedPageHeights={},m._estimatedPageHeight=0,m._focusedIndex=-1,m._pageCache={},m}function Kf(e,t,o){var n=e.top-te.height,o=e.height+(t+o)e.height;return{top:n,bottom:n+o,height:o,left:e.left,right:e.right,width:e.width}}function Gf(e,t,o){for(var n=0,r=e;n<r.length;n++){var i=r[n];o[t.register(i,!0)]=i}}function Uf(e,t){for(var o=0,n=Object.keys(t);o<n.length;o++){var r=n[o];e.unregister(t[r],r,!0),delete t[r]}}function jf(e){var t,o,n,r,s=Oc.getInstance(),i=e.className,a=e.overflowItems,l=e.keytipSequences,c=e.itemSubMenuProvider,u=e.onRenderOverflowButton,d=_l({}),p=gt.useCallback(function(e){return c?c(e):e.subMenuProps?e.subMenuProps.items:void 0},[c]),h=gt.useMemo(function(){var r=[],i=[];return l?null==a\|\|a.forEach(function(e){var t,o,n=e.keytipProps;n?(o={content:n.content,keySequences:n.keySequences,disabled:n.disabled\|\|!(!e.disabled&&!e.isDisabled),hasDynamicChildren:n.hasDynamicChildren,hasMenu:n.hasMenu},n.hasDynamicChildren\|\|p(e)?(o.onExecute=s.menuExecute.bind(s,l,null===(t=null==e?void 0:e.keytipProps)\|\|void 0===t?void 0:t.keySequences),o.hasOverflowSubMenu=!0):o.onExecute=n.onExecute,r.push(o),n=ht(ht({},e),{keytipProps:ht(ht({},n),{overflowSetSequence:l})}),null==i\|\|i.push(n)):null==i\|\|i.push(e)}):i=a,{modifiedOverflowItems:i,keytipsToRegister:r}},[a,p,s,l]),e=h.modifiedOverflowItems;return t=d,o=h.keytipsToRegister,n=s,r=Hc(t),gt.useEffect(function(){r&&(Uf(n,r),Gf(o,n,t))}),gt.useEffect(function(){return Gf(o,n,t),function(){Uf(n,t)}},[]),gt.createElement("div",{className:i},u(e))}var qf,Yf=(l(Qf,qf=gt.Component),Object.defineProperty(Qf.prototype,"selectedOptions",{get:function(){return this._comboBox.current?this._comboBox.current.selectedOptions:[]},enumerable:!1,configurable:!0}),Qf.prototype.dismissMenu=function(){if(this._comboBox.current)return this._comboBox.current.dismissMenu()},Qf.prototype.focus=function(e,t){return!!this._comboBox.current&&(this._comboBox.current.focus(e,t),!0)},Qf.prototype.render=function(){return gt.createElement(kf,ht({},this.props,{componentRef:this._comboBox,onRenderList:this._onRenderList,onScrollToItem:this._onScrollToItem}))},Qf),Zf=Fn(),Xf=gt.forwardRef(function(e,t){var o,n=gt.useRef(null),r=_r(n,t);o=n,gt.useImperativeHandle(e.componentRef,function(){return{focus:function(){var e=!1;return e=o.current?rs(o.current):e},focusElement:function(e){var t=!1;return!!e&&(o.current&&$i(o.current,e)&&(e.focus(),t=document.activeElement===e),t)}}},[o]);var i=e.items,s=e.overflowItems,a=e.className,l=e.styles,c=e.vertical,t=e.role,n=e.overflowSide,n=void 0===n?"end":n,u=e.onRenderItem,d=Zf(l,{className:a,vertical:c}),s=!!s&&0<s.length;return gt.createElement("div",ht({},ur(e,cr),{role:t\|\|"group","aria-orientation":"menubar"===t?!0===c?"vertical":"horizontal":void 0,className:d.root,ref:r}),"start"===n&&s&&gt.createElement(jf,ht({},e,{className:d.overflowButton})),i&&i.map(function(e,t){return gt.createElement("div",{className:d.item,key:e.key,role:"none"},u(e))}),"end"===n&&s&&gt.createElement(jf,ht({},e,{className:d.overflowButton})))});function Qf(e){var n=qf.call(this,e)\|\|this;return n._comboBox=gt.createRef(),n._list=gt.createRef(),n._onRenderList=function(e){var t=e.id,o=e.onRenderItem;return gt.createElement(Wf,{componentRef:n._list,role:"listbox",id:t+"-list","aria-labelledby":t+"-label",items:e.options,onRenderCell:o?function(e){return o(e)}:function(){return null}})},n._onScrollToItem=function(e){n._list.current&&n._list.current.scrollToIndex(e)},fi(n),n}Xf.displayName="OverflowSet";var Jf,$f={flexShrink:0,display:"inherit"},ev=In(Xf,function(e){var t=e.className;return{root:["ms-OverflowSet",{position:"relative",display:"flex",flexWrap:"nowrap"},e.vertical&&{flexDirection:"column"},t],item:["ms-OverflowSet-item",$f],overflowButton:["ms-OverflowSet-overflowButton",$f]}},void 0,{scope:"OverflowSet"}),tv=Ao(function(e){var t={height:"100%"},o={whiteSpace:"nowrap"},n=e\|\|{},r=n.root,e=n.label,n=mt(n,["root","label"]);return ht(ht({},n),{root:r?[t,r]:t,label:e?[o,e]:o})}),ov=Fn(),nv=(l(cv,Jf=gt.Component),cv.prototype.render=function(){var e=this.props,t=e.items,o=e.overflowItems,n=e.farItems,r=e.styles,i=e.theme,s=e.dataDidRender,a=e.onReduceData,l=void 0===a?this._onReduceData:a,a=e.onGrowData,a=void 0===a?this._onGrowData:a,e=e.resizeGroupAs,e=void 0===e?gd:e,o={primaryItems:$e([],t),overflowItems:$e([],o),minimumOverflowItems:$e([],o).length,farItems:n,cacheKey:this._computeCacheKey({primaryItems:$e([],t),overflow:o&&0<o.length})};this._classNames=ov(r,{theme:i});i=ur(this.props,cr);return gt.createElement(e,ht({},i,{componentRef:this._resizeGroup,data:o,onReduceData:l,onGrowData:a,onRenderData:this._onRenderData,dataDidRender:s}))},cv.prototype.focus=function(){var e=this._overflowSet.current;e&&e.focus()},cv.prototype.remeasure=function(){this._resizeGroup.current&&this._resizeGroup.current.remeasure()},cv.prototype._onButtonClick=function(t){return function(e){t.inactive\|\|t.onClick&&t.onClick(e,t)}},cv.prototype._computeCacheKey=function(e){var t=e.primaryItems,e=e.overflow;return[t&&t.reduce(function(e,t){var o=t.cacheKey;return e+(void 0===o?t.key:o)},""),e?"overflow":""].join("")},cv.defaultProps={items:[],overflowItems:[]},cv),rv=In(nv,function(e){var t=e.className,o=e.theme,e=o.semanticColors;return{root:[o.fonts.medium,"ms-CommandBar",{display:"flex",backgroundColor:e.bodyBackground,padding:"0 14px 0 24px",height:44},t],primarySet:["ms-CommandBar-primaryCommand",{flexGrow:"1",display:"flex",alignItems:"stretch"}],secondarySet:["ms-CommandBar-secondaryCommand",{flexShrink:"0",display:"flex",alignItems:"stretch"}]}},void 0,{scope:"CommandBar"}),iv=ht(ht({},bh),{prevMonthAriaLabel:"Go to previous month",nextMonthAriaLabel:"Go to next month",prevYearAriaLabel:"Go to previous year",nextYearAriaLabel:"Go to next year",closeButtonAriaLabel:"Close date picker",isRequiredErrorMessage:"Field is required",invalidInputErrorMessage:"Invalid date format",isResetStatusMessage:'Invalid entry "{0}", date reset to "{1}"'}),sv=Fn(),av={allowTextInput:!1,formatDate:function(e){return e?e.toDateString():""},parseDateFromString:function(e){e=Date.parse(e);return e?new Date(e):null},firstDayOfWeek:Sp.Sunday,initialPickerDate:new Date,isRequired:!1,isMonthPickerVisible:!0,showMonthPickerAsOverlay:!1,strings:iv,highlightCurrentMonth:!1,highlightSelectedMonth:!1,borderless:!1,pickerAriaLabel:"Calendar",showWeekNumbers:!1,firstWeekOfYear:kp.FirstDay,showGoToToday:!0,showCloseButton:!1,underlined:!1,allFocusable:!1},lv=gt.forwardRef(function(e,t){var o,n,r,i,s,a,l,c,u,d,p,h,m,g,f,v,b,y,C,_,S,x,k,w,I,D,E,T=Hn(av,e),P=T.firstDayOfWeek,R=T.strings,M=T.label,N=T.theme,B=T.className,F=T.styles,A=T.initialPickerDate,L=T.isRequired,H=T.disabled,O=T.ariaLabel,z=T.pickerAriaLabel,W=T.placeholder,V=T.allowTextInput,K=T.borderless,G=T.minDate,U=T.maxDate,j=T.showCloseButton,q=T.calendarProps,Y=T.calloutProps,Z=T.textField,X=T.underlined,Q=T.allFocusable,J=T.calendarAs,$=void 0===J?Oh:J,ee=T.tabIndex,te=T.disableAutoFocus,oe=void 0===te\|\|te,ne=iu("DatePicker",T.id),re=iu("DatePicker-Callout"),ie=gt.useRef(null),se=gt.useRef(null),ae=(D=gt.useRef(null),E=gt.useRef(!1),[D,function(){var e,t;null===(t=null===(e=D.current)\|\|void 0===e?void 0:e.focus)\|\|void 0===t\|\|t.call(e)},E,function(){E.current=!0}]),le=ae[0],ce=ae[1],ue=ae[2],de=ae[3],J=(_=ce,S=(e=T).allowTextInput,x=e.onAfterMenuDismiss,e=gt.useState(!1),k=e[0],e=e[1],w=gt.useRef(!1),I=Sl(),gt.useEffect(function(){w.current&&!k&&(S&&I.requestAnimationFrame(_),null==x\|\|x()),w.current=!0},[k]),[k,e]),pe=J[0],he=J[1],J=(f=(te=T).formatDate,v=te.value,b=te.onSelectDate,ae=Fh(v,void 0,function(e,t){return null==b?void 0:b(t)}),e=ae[0],y=ae[1],te=gt.useState(function(){return v&&f?f(v):""}),ae=te[0],C=te[1],gt.useEffect(function(){C(v&&f?f(v):"")},[f,v]),[e,ae,function(e){y(e),C(e&&f?f(e):"")},C]),te=J[0],me=J[1],ge=J[2],fe=J[3],e=(o=te,n=ge,r=me,e=pe,i=(ae=T).isRequired,s=ae.allowTextInput,a=ae.strings,l=ae.parseDateFromString,c=ae.onSelectDate,u=ae.formatDate,d=ae.minDate,p=ae.maxDate,J=gt.useState(),h=J[0],m=J[1],ae=gt.useState(),J=ae[0],g=ae[1],gt.useEffect(function(){i&&!o?m(a.isRequiredErrorMessage\|\|" "):o&&uv(o,d,p)?m(a.isOutOfBoundsErrorMessage\|\|" "):m(void 0)},[d&&qp(d),p&&qp(p),o&&qp(o),i]),[e?void 0:h,function(e){var t;void 0===e&&(e=null),s?r\|\|e?o&&!h&&u&&u(null!=e?e:o)===r\|\|(!(e=e\|\|l(r))\|\|isNaN(e.getTime())?(n(o),t=u?u(o):"",t=a.isResetStatusMessage?Jp(a.isResetStatusMessage,r,t):a.invalidInputErrorMessage\|\|"",g(t)):uv(e,d,p)?m(a.isOutOfBoundsErrorMessage\|\|" "):(n(e),m(void 0),g(void 0))):(m(i?a.isRequiredErrorMessage\|\|" ":void 0),null==c\|\|c(e)):i&&!r?m(a.isRequiredErrorMessage\|\|" "):(m(void 0),g(void 0))},m,e?void 0:J,g]),J=e[0],ve=e[1],be=e[2],ye=e[3],Ce=e[4],_e=gt.useCallback(function(){pe\|\|(de(),he(!0))},[pe,de,he]);gt.useImperativeHandle(T.componentRef,function(){return{focus:ce,reset:function(){he(!1),ge(void 0),be(void 0),Ce(void 0)},showDatePickerPopup:_e}},[ce,be,he,ge,Ce,_e]);function Se(e){pe&&(he(!1),ve(e),!V&&e&&ge(e))}function xe(e){de(),Se(e)}var ke=sv(F,{theme:N,className:B,disabled:H,underlined:X,label:!!M,isDatePickerShown:pe}),F=ur(T,cr,["value"]),N=Z&&Z.iconProps,B=Z&&Z.id&&Z.id!==ne?Z.id:ne+"-label",ne=!V&&!H;return gt.createElement("div",ht({},F,{className:ke.root,ref:t}),gt.createElement("div",{ref:se,"aria-owns":pe?re:void 0,className:ke.wrapper},gt.createElement(qg,ht({role:"combobox",label:M,"aria-expanded":pe,ariaLabel:O,"aria-haspopup":"dialog","aria-controls":pe?re:void 0,required:L,disabled:H,errorMessage:J,placeholder:W,borderless:K,value:me,componentRef:le,underlined:X,tabIndex:ee,readOnly:!V},Z,{id:B,className:Tr(ke.textField,Z&&Z.className),iconProps:ht(ht({iconName:"Calendar"},N),{className:Tr(ke.icon,N&&N.className),onClick:function(e){e.stopPropagation(),pe\|\|T.disabled?T.allowTextInput&&Se():_e()}}),onRenderDescription:function(e,t){return gt.createElement(gt.Fragment,null,e.description?t(e):null,gt.createElement("div",{"aria-live":"assertive",className:ke.statusMessage},ye))},onKeyDown:function(e){switch(e.which){case En.enter:e.preventDefault(),e.stopPropagation(),pe?T.allowTextInput&&Se():(ve(),_e());break;case En.escape:e.stopPropagation(),xe();break;case En.down:e.altKey&&!pe&&_e()}},onFocus:function(){oe\|\|V\|\|(ue.current\|\|_e(),ue.current=!1)},onBlur:function(e){ve()},onClick:function(e){!T.openOnClick&&T.disableAutoFocus\|\|pe\|\|T.disabled?T.allowTextInput&&Se():_e()},onChange:function(e,t){var o,n=T.textField;V&&(pe&&Se(),fe(t)),null===(o=null==n?void 0:n.onChange)\|\|void 0===o\|\|o.call(n,e,t)},onRenderInput:ne?function(e){e=ur(e,cr);return gt.createElement("div",ht({},e,{className:Tr(e.className,ke.readOnlyTextField),tabIndex:ee\|\|0}),me\|\|gt.createElement("span",{className:ke.readOnlyPlaceholder},W))}:void 0}))),pe&&gt.createElement(ac,ht({id:re,role:"dialog",ariaLabel:z,isBeakVisible:!1,gapSpace:0,doNotLayer:!1,target:se.current,directionalHint:Pa.bottomLeftEdge},Y,{className:Tr(ke.callout,Y&&Y.className),onDismiss:function(e){xe()},onPositioned:function(){var e=!0;T.calloutProps&&void 0!==T.calloutProps.setInitialFocus&&(e=T.calloutProps.setInitialFocus),ie.current&&e&&ie.current.focus()}}),gt.createElement(Wh,{isClickableOutsideFocusTrap:!0,disableFirstFocus:oe},gt.createElement($,ht({},q,{onSelectDate:function(e){T.calendarProps&&T.calendarProps.onSelectDate&&T.calendarProps.onSelectDate(e),xe(e)},onDismiss:xe,isMonthPickerVisible:T.isMonthPickerVisible,showMonthPickerAsOverlay:T.showMonthPickerAsOverlay,today:T.today,value:te\|\|A,firstDayOfWeek:P,strings:R,highlightCurrentMonth:T.highlightCurrentMonth,highlightSelectedMonth:T.highlightSelectedMonth,showWeekNumbers:T.showWeekNumbers,firstWeekOfYear:T.firstWeekOfYear,showGoToToday:T.showGoToToday,dateTimeFormatter:T.dateTimeFormatter,minDate:G,maxDate:U,componentRef:ie,showCloseButton:j,allFocusable:Q})))))});function cv(e){var l=Jf.call(this,e)\|\|this;return l._overflowSet=gt.createRef(),l._resizeGroup=gt.createRef(),l._onRenderData=function(e){var t=l.props,o=t.ariaLabel,n=t.primaryGroupAriaLabel,r=t.farItemsGroupAriaLabel,t=e.farItems&&0<e.farItems.length;return gt.createElement(Zs,{className:Tr(l._classNames.root),direction:Ei.horizontal,role:"menubar","aria-label":o},gt.createElement(ev,{role:t?"group":"none","aria-label":t?n:void 0,componentRef:l._overflowSet,className:Tr(l._classNames.primarySet),items:e.primaryItems,overflowItems:e.overflowItems.length?e.overflowItems:void 0,onRenderItem:l._onRenderItem,onRenderOverflowButton:l._onRenderOverflowButton}),t&&gt.createElement(ev,{role:"group","aria-label":r,className:Tr(l._classNames.secondarySet),items:e.farItems,onRenderItem:l._onRenderItem,onRenderOverflowButton:wa}))},l._onRenderItem=function(e){if(e.onRender)return e.onRender(e,function(){});var t=e.text\|\|e.name,o=ht(ht({allowDisabledFocus:!0,role:"menuitem"},e),{styles:tv(e.buttonStyles),className:Tr("ms-CommandBarItem-link",e.className),text:e.iconOnly?void 0:t,menuProps:e.subMenuProps,onClick:l._onButtonClick(e)});return e.iconOnly&&(void 0!==t\|\|e.tooltipHostProps)?gt.createElement(Rd,ht({role:"none",content:t,setAriaDescribedBy:!1},e.tooltipHostProps),l._commandButton(e,o)):l._commandButton(e,o)},l._commandButton=function(e,t){var o=l.props.buttonAs,n=e.commandBarButtonAs,e=cp;return n&&(e=ju(n,e)),o&&(e=ju(o,e)),gt.createElement(e,ht({},t))},l._onRenderOverflowButton=function(e){var t=l.props.overflowButtonProps,t=void 0===t?{}:t,e=$e($e([],t.menuProps?t.menuProps.items:[]),e),e=ht(ht({role:"menuitem"},t),{styles:ht({menuIcon:{fontSize:"17px"}},t.styles),className:Tr("ms-CommandBar-overflowButton",t.className),menuProps:ht(ht({},t.menuProps),{items:e}),menuIconProps:ht({iconName:"More"},t.menuIconProps)}),t=l.props.overflowButtonAs?ju(l.props.overflowButtonAs,cp):cp;return gt.createElement(t,ht({},e))},l._onReduceData=function(e){var t=l.props,o=t.shiftOnReduce,n=t.onDataReduced,r=e.primaryItems,i=e.overflowItems,t=(e.cacheKey,r[o?0:r.length-1]);if(void 0!==t){t.renderedInOverflow=!0;var i=$e([t],i),r=o?r.slice(1):r.slice(0,-1),e=ht(ht({},e),{primaryItems:r,overflowItems:i}),s=l._computeCacheKey({primaryItems:r,overflow:0<i.length});return n&&n(t),e.cacheKey=s,e}},l._onGrowData=function(e){var t=l.props,o=t.shiftOnReduce,n=t.onDataGrown,r=e.minimumOverflowItems,i=e.primaryItems,s=e.overflowItems,t=(e.cacheKey,s[0]);if(void 0!==t&&s.length>r){t.renderedInOverflow=!1;var s=s.slice(1),i=o?$e([t],i):$e($e([],i),[t]),e=ht(ht({},e),{primaryItems:i,overflowItems:s}),a=l._computeCacheKey({primaryItems:i,overflow:0<s.length});return n&&n(t),e.cacheKey=a,e}},fi(l),l}function uv(e,t,o){return t&&0<Op(t,e)\|\|o&&Op(o,e)<0}lv.displayName="DatePickerBase";var dv,pv,hv={root:"ms-DatePicker",callout:"ms-DatePicker-callout",withLabel:"ms-DatePicker-event--with-label",withoutLabel:"ms-DatePicker-event--without-label",disabled:"msDatePickerDisabled "},mv=In(lv,function(e){var t=e.className,o=e.theme,n=e.disabled,r=e.underlined,i=e.label,s=e.isDatePickerShown,a=o.palette,l=o.semanticColors,c=o.fonts,e=zo(hv,o),a={color:a.neutralSecondary,fontSize:Be.icon,lineHeight:"18px",pointerEvents:"none",position:"absolute",right:"4px",padding:"5px"};return{root:[e.root,o.fonts.large,s&&"is-open",Uo,t],textField:[{position:"relative",selectors:{"& input[readonly]":{cursor:"pointer"},input:{selectors:{"::-ms-clear":{display:"none"}}}}},n&&{selectors:{"& input[readonly]":{cursor:"default"}}}],callout:[e.callout],icon:[a,i?e.withLabel:e.withoutLabel,{paddingTop:"7px"},!n&&[e.disabled,{pointerEvents:"initial",cursor:"pointer"}],n&&{color:l.disabledText,cursor:"default"}],statusMessage:[c.small,{color:l.errorText,marginTop:5}],readOnlyTextField:[{cursor:"pointer",height:32,lineHeight:30,overflow:"hidden",textOverflow:"ellipsis"},r&&{lineHeight:34}],readOnlyPlaceholder:((l={color:l.inputPlaceholderText})[Yt]={color:"GrayText"},l)}},void 0,{scope:"DatePicker"}),gv="change";(V=dv=dv\|\|{})[V.none=0]="none",V[V.single=1]="single",V[V.multiple=2]="multiple",(G=pv=pv\|\|{})[G.horizontal=0]="horizontal",G[G.vertical=1]="vertical";var fv=(vv.prototype.canSelectItem=function(e,t){return!("number"==typeof t&&t<0)&&this._canSelectItem(e,t)},vv.prototype.getKey=function(e,t){t=this._getKey(e,t);return"number"==typeof t\|\|t?""+t:""},vv.prototype.setChangeEvents=function(e,t){this._changeEventSuppressionCount+=e?-1:1,0===this._changeEventSuppressionCount&&this._hasChanged&&(this._hasChanged=!1,t\|\|this._change())},vv.prototype.isModal=function(){return this._isModal},vv.prototype.setModal=function(e){this._isModal!==e&&(this.setChangeEvents(!1),(this._isModal=e)\|\|this.setAllSelected(!1),this._change(),this.setChangeEvents(!0))},vv.prototype.setItems=function(e,t){void 0===t&&(t=!0);var o={},n={},r=!1;this.setChangeEvents(!1);for(var i,s=this._unselectableCount=0;s<e.length;s++)!(l=e[s])\|\|(i=this.getKey(l,s))&&(o[i]=s),n[s]=l&&!this.canSelectItem(l),n[s]&&this._unselectableCount++;!t&&0!==e.length\|\|this._setAllSelected(!1,!0);var a,l,c,u,d={},p=0;for(a in this._exemptedIndices)this._exemptedIndices.hasOwnProperty(a)&&(c=Number(a),r=void 0===(u=(u=(l=this._items[c])?this.getKey(l,Number(c)):void 0)?o[u]:c)\|\|(d[u]=!0,p++,r\|\|u!==c));this._items&&0===this._exemptedCount&&e.length!==this._items.length&&this._isAllSelected&&(r=!0),this._exemptedIndices=d,this._exemptedCount=p,this._keyToIndexMap=o,this._unselectableIndices=n,this._items=e,this._selectedItems=null,r&&(this._updateCount(),this._change()),this.setChangeEvents(!0)},vv.prototype.getItems=function(){return this._items},vv.prototype.getSelection=function(){if(!this._selectedItems){this._selectedItems=[];var e=this._items;if(e)for(var t=0;t<e.length;t++)this.isIndexSelected(t)&&this._selectedItems.push(e[t])}return this._selectedItems},vv.prototype.getSelectedCount=function(){return this._isAllSelected?this._items.length-this._exemptedCount-this._unselectableCount:this._exemptedCount},vv.prototype.getSelectedIndices=function(){if(!this._selectedIndices){this._selectedIndices=[];var e=this._items;if(e)for(var t=0;t<e.length;t++)this.isIndexSelected(t)&&this._selectedIndices.push(t)}return this._selectedIndices},vv.prototype.isRangeSelected=function(e,t){if(0===t)return!1;for(var o=e+t,n=e;n<o;n++)if(!this.isIndexSelected(n))return!1;return!0},vv.prototype.isAllSelected=function(){var e=this._items.length-this._unselectableCount;return this.mode===dv.single&&(e=Math.min(e,1)),0<this.count&&this._isAllSelected&&0===this._exemptedCount\|\|!this._isAllSelected&&this._exemptedCount===e&&0<e},vv.prototype.isKeySelected=function(e){e=this._keyToIndexMap[e];return this.isIndexSelected(e)},vv.prototype.isIndexSelected=function(e){return!!(0<this.count&&this._isAllSelected&&!this._exemptedIndices[e]&&!this._unselectableIndices[e]\|\|!this._isAllSelected&&this._exemptedIndices[e])},vv.prototype.setAllSelected=function(e){var t;e&&this.mode!==dv.multiple\|\|(t=this._items?this._items.length-this._unselectableCount:0,this.setChangeEvents(!1),0<t&&(0<this._exemptedCount\|\|e!==this._isAllSelected)&&(this._exemptedIndices={},(e!==this._isAllSelected\|\|0<this._exemptedCount)&&(this._exemptedCount=0,this._isAllSelected=e,this._change()),this._updateCount()),this.setChangeEvents(!0))},vv.prototype.setKeySelected=function(e,t,o){e=this._keyToIndexMap[e];0<=e&&this.setIndexSelected(e,t,o)},vv.prototype.setIndexSelected=function(e,t,o){var n;this.mode===dv.none\|\|(e=Math.min(Math.max(0,e),this._items.length-1))<0\|\|e>=this._items.length\|\|(this.setChangeEvents(!1),n=this._exemptedIndices[e],this._unselectableIndices[e]\|\|(t&&this.mode===dv.single&&this._setAllSelected(!1,!0),n&&(t&&this._isAllSelected\|\|!t&&!this._isAllSelected)&&(delete this._exemptedIndices[e],this._exemptedCount--),!n&&(t&&!this._isAllSelected\|\|!t&&this._isAllSelected)&&(this._exemptedIndices[e]=!0,this._exemptedCount++),o&&(this._anchoredIndex=e)),this._updateCount(),this.setChangeEvents(!0))},vv.prototype.selectToKey=function(e,t){this.selectToIndex(this._keyToIndexMap[e],t)},vv.prototype.selectToIndex=function(e,t){if(this.mode!==dv.none)if(this.mode!==dv.single){var o=this._anchoredIndex\|\|0,n=Math.min(e,o),r=Math.max(e,o);for(this.setChangeEvents(!1),t&&this._setAllSelected(!1,!0);n<=r;n++)this.setIndexSelected(n,!0,!1);this.setChangeEvents(!0)}else this.setIndexSelected(e,!0,!0)},vv.prototype.toggleAllSelected=function(){this.setAllSelected(!this.isAllSelected())},vv.prototype.toggleKeySelected=function(e){this.setKeySelected(e,!this.isKeySelected(e),!0)},vv.prototype.toggleIndexSelected=function(e){this.setIndexSelected(e,!this.isIndexSelected(e),!0)},vv.prototype.toggleRangeSelected=function(e,t){if(this.mode!==dv.none){var o=this.isRangeSelected(e,t),n=e+t;if(!(this.mode===dv.single&&1<t)){this.setChangeEvents(!1);for(var r=e;r<n;r++)this.setIndexSelected(r,!o,!1);this.setChangeEvents(!0)}}},vv.prototype._updateCount=function(e){void 0===e&&(e=!1);var t=this.getSelectedCount();t!==this.count&&(this.count=t,this._change()),this.count\|\|e\|\|this.setModal(!1)},vv.prototype._setAllSelected=function(e,t){var o;void 0===t&&(t=!1),e&&this.mode!==dv.multiple\|\|(o=this._items?this._items.length-this._unselectableCount:0,this.setChangeEvents(!1),0<o&&(0<this._exemptedCount\|\|e!==this._isAllSelected)&&(this._exemptedIndices={},(e!==this._isAllSelected\|\|0<this._exemptedCount)&&(this._exemptedCount=0,this._isAllSelected=e,this._change()),this._updateCount(t)),this.setChangeEvents(!0))},vv.prototype._change=function(){0===this._changeEventSuppressionCount?(this._selectedItems=null,this._selectedIndices=void 0,va.raise(this,gv),this._onSelectionChanged&&this._onSelectionChanged()):this._hasChanged=!0},vv);function vv(){for(var e=[],t=0;t<arguments.length;t++)e[t]=arguments[t];var o=e[0]\|\|{},n=o.onSelectionChanged,r=o.getKey,i=o.canSelectItem,s=void 0===i?function(){return!0}:i,i=o.items,o=o.selectionMode,o=void 0===o?dv.multiple:o;this.mode=o,this._getKey=r\|\|bv,this._changeEventSuppressionCount=0,this._exemptedCount=0,this._anchoredIndex=0,this._unselectableCount=0,this._onSelectionChanged=n,this._canSelectItem=s,this._isModal=!1,this.setItems(i\|\|[],!0),this.count=this.getSelectedCount()}function bv(e,t){e=(e\|\|{}).key;return void 0===e?""+t:e}var yv,Cv,_v,Sv,xv,kv,wv,Iv="data-selection-index",Dv="data-selection-toggle",Ev="data-selection-invoke",Tv="data-selection-all-toggle",Pv=(l(Rv,wv=gt.Component),Rv.getDerivedStateFromProps=function(e,t){e=e.selection.isModal&&e.selection.isModal();return ht(ht({},t),{isModal:e})},Rv.prototype.componentDidMount=function(){var e=qe(this._root.current);this._events.on(e,"keydown, keyup",this._updateModifiers,!0),this._events.on(document,"click",this._findScrollParentAndTryClearOnEmptyClick),this._events.on(document.body,"touchstart",this._onTouchStartCapture,!0),this._events.on(document.body,"touchend",this._onTouchStartCapture,!0),this._events.on(this.props.selection,"change",this._onSelectionChange)},Rv.prototype.render=function(){var e=this.state.isModal;return gt.createElement("div",{className:Tr("ms-SelectionZone",this.props.className,{"ms-SelectionZone--modal":!!e}),ref:this._root,onKeyDown:this._onKeyDown,onMouseDown:this._onMouseDown,onKeyDownCapture:this._onKeyDownCapture,onClick:this._onClick,role:"presentation",onDoubleClick:this._onDoubleClick,onContextMenu:this._onContextMenu,onMouseDownCapture:this._onMouseDownCapture,onFocusCapture:this._onFocus,"data-selection-is-modal":!!e\|\|void 0},this.props.children,gt.createElement(na,null))},Rv.prototype.componentDidUpdate=function(e){var t=this.props.selection;t!==e.selection&&(this._events.off(e.selection),this._events.on(t,"change",this._onSelectionChange))},Rv.prototype.componentWillUnmount=function(){this._events.dispose(),this._async.dispose()},Rv.prototype._isSelectionDisabled=function(e){if(this._getSelectionMode()===dv.none)return!0;for(;e!==this._root.current;){if(this._hasAttribute(e,"data-selection-disabled"))return!0;e=Xi(e)}return!1},Rv.prototype._onToggleAllClick=function(e){var t=this.props.selection;this._getSelectionMode()===dv.multiple&&(t.toggleAllSelected(),e.stopPropagation(),e.preventDefault())},Rv.prototype._onToggleClick=function(e,t){var o=this.props.selection,n=this._getSelectionMode();if(o.setChangeEvents(!1),this.props.enterModalOnTouch&&this._isTouch&&!o.isIndexSelected(t)&&o.setModal&&(o.setModal(!0),this._setIsTouch(!1)),n===dv.multiple)o.toggleIndexSelected(t);else{if(n!==dv.single)return void o.setChangeEvents(!0);var r=o.isIndexSelected(t),n=o.isModal&&o.isModal();o.setAllSelected(!1),o.setIndexSelected(t,!r,!0),n&&o.setModal&&o.setModal(!0)}o.setChangeEvents(!0),e.stopPropagation()},Rv.prototype._onInvokeClick=function(e,t){var o=this.props,n=o.selection,o=o.onItemInvoked;o&&(o(n.getItems()[t],t,e.nativeEvent),e.preventDefault(),e.stopPropagation())},Rv.prototype._onItemSurfaceClick=function(e,t){var o=this.props.selection,n=this._isCtrlPressed\|\|this._isMetaPressed,r=this._getSelectionMode();r===dv.multiple?this._isShiftPressed&&!this._isTabPressed?o.selectToIndex(t,!n):n?o.toggleIndexSelected(t):this._clearAndSelectIndex(t):r===dv.single&&this._clearAndSelectIndex(t)},Rv.prototype._onInvokeMouseDown=function(e,t){this.props.selection.isIndexSelected(t)\|\|this._clearAndSelectIndex(t)},Rv.prototype._findScrollParentAndTryClearOnEmptyClick=function(e){var t=Ns(this._root.current);this._events.off(document,"click",this._findScrollParentAndTryClearOnEmptyClick),this._events.on(t,"click",this._tryClearOnEmptyClick),(t&&e.target instanceof Node&&t.contains(e.target)\|\|t===e.target)&&this._tryClearOnEmptyClick(e)},Rv.prototype._tryClearOnEmptyClick=function(e){!this.props.selectionPreservedOnEmptyClick&&this._isNonHandledClick(e.target)&&this.props.selection.setAllSelected(!1)},Rv.prototype._clearAndSelectIndex=function(e){var t,o=this.props.selection;1===o.getSelectedCount()&&o.isIndexSelected(e)\|\|(t=o.isModal&&o.isModal(),o.setChangeEvents(!1),o.setAllSelected(!1),o.setIndexSelected(e,!0,!0),(t\|\|this.props.enterModalOnTouch&&this._isTouch)&&(o.setModal&&o.setModal(!0),this._isTouch&&this._setIsTouch(!1)),o.setChangeEvents(!0))},Rv.prototype._updateModifiers=function(e){this._isShiftPressed=e.shiftKey,this._isCtrlPressed=e.ctrlKey,this._isMetaPressed=e.metaKey;e=e.keyCode;this._isTabPressed=!!e&&e===En.tab},Rv.prototype._findItemRoot=function(e){for(var t=this.props.selection;e!==this._root.current;){var o=e.getAttribute(Iv),n=Number(o);if(null!==o&&0<=n&&n<t.getItems().length)break;e=Xi(e)}if(e!==this._root.current)return e},Rv.prototype._getItemIndex=function(e){return Number(e.getAttribute(Iv))},Rv.prototype._shouldAutoSelect=function(e){return this._hasAttribute(e,"data-selection-select")},Rv.prototype._hasAttribute=function(e,t){for(var o=!1;!o&&e!==this._root.current;)o="true"===e.getAttribute(t),e=Xi(e);return o},Rv.prototype._isInputElement=function(e){return"INPUT"===e.tagName\|\|"TEXTAREA"===e.tagName},Rv.prototype._isNonHandledClick=function(e){var t=ft();if(t&&e)for(;e&&e!==t.documentElement;){if(cs(e))return!1;e=Xi(e)}return!0},Rv.prototype._handleNextFocus=function(e){var t=this;this._shouldHandleFocusTimeoutId&&(this._async.clearTimeout(this._shouldHandleFocusTimeoutId),this._shouldHandleFocusTimeoutId=void 0),(this._shouldHandleFocus=e)&&this._async.setTimeout(function(){t._shouldHandleFocus=!1},100)},Rv.prototype._setIsTouch=function(e){var t=this;this._isTouchTimeoutId&&(this._async.clearTimeout(this._isTouchTimeoutId),this._isTouchTimeoutId=void 0),this._isTouch=!0,e&&this._async.setTimeout(function(){t._isTouch=!1},300)},Rv.prototype._getSelectionMode=function(){var e=this.props.selection,t=this.props.selectionMode;return void 0===t?e?e.mode:dv.none:t},Rv.defaultProps={isSelectedOnFocus:!0,selectionMode:dv.multiple},Rv);function Rv(e){var c=wv.call(this,e)\|\|this;c._root=gt.createRef(),c.ignoreNextFocus=function(){c._handleNextFocus(!1)},c._onSelectionChange=function(){var e=c.props.selection,e=e.isModal&&e.isModal();c.setState({isModal:e})},c._onMouseDownCapture=function(e){var t=e.target;if(document.activeElement===t\|\|$i(document.activeElement,t)){if($i(t,c._root.current))for(;t!==c._root.current;){if(c._hasAttribute(t,Ev)){c.ignoreNextFocus();break}t=Xi(t)}}else c.ignoreNextFocus()},c._onFocus=function(e){var t=e.target,o=c.props.selection,n=c._isCtrlPressed\|\|c._isMetaPressed,r=c._getSelectionMode();c._shouldHandleFocus&&r!==dv.none&&(r=c._hasAttribute(t,Dv),t=c._findItemRoot(t),!r&&t&&(t=c._getItemIndex(t),n?(o.setIndexSelected(t,o.isIndexSelected(t),!0),c.props.enterModalOnTouch&&c._isTouch&&o.setModal&&(o.setModal(!0),c._setIsTouch(!1))):c.props.isSelectedOnFocus&&c._onItemSurfaceClick(e,t))),c._handleNextFocus(!1)},c._onMouseDown=function(e){c._updateModifiers(e);var t=e.target,o=c._findItemRoot(t);if(!c._isSelectionDisabled(t))for(;t!==c._root.current&&!c._hasAttribute(t,Tv);){if(o){if(c._hasAttribute(t,Dv))break;if(c._hasAttribute(t,Ev))break;if(!(t!==o&&!c._shouldAutoSelect(t)\|\|c._isShiftPressed\|\|c._isCtrlPressed\|\|c._isMetaPressed)){c._onInvokeMouseDown(e,c._getItemIndex(o));break}if(c.props.disableAutoSelectOnInputElements&&("A"===t.tagName\|\|"BUTTON"===t.tagName\|\|"INPUT"===t.tagName))return}t=Xi(t)}},c._onTouchStartCapture=function(e){c._setIsTouch(!0)},c._onClick=function(e){var t=c.props.enableTouchInvocationTarget,o=void 0!==t&&t;c._updateModifiers(e);for(var n=e.target,r=c._findItemRoot(n),i=c._isSelectionDisabled(n);n!==c._root.current;){if(c._hasAttribute(n,Tv)){i\|\|c._onToggleAllClick(e);break}if(r){var s=c._getItemIndex(r);if(c._hasAttribute(n,Dv)){i\|\|(c._isShiftPressed?c._onItemSurfaceClick(e,s):c._onToggleClick(e,s));break}if(c._isTouch&&o&&c._hasAttribute(n,"data-selection-touch-invoke")\|\|c._hasAttribute(n,Ev)){c._onInvokeClick(e,s);break}if(n===r){i\|\|c._onItemSurfaceClick(e,s);break}if("A"===n.tagName\|\|"BUTTON"===n.tagName\|\|"INPUT"===n.tagName)return}n=Xi(n)}},c._onContextMenu=function(e){var t=e.target,o=c.props,n=o.onItemContextMenu,o=o.selection;!n\|\|(t=c._findItemRoot(t))&&(t=c._getItemIndex(t),c._onInvokeMouseDown(e,t),n(o.getItems()[t],t,e.nativeEvent)\|\|e.preventDefault())},c._onDoubleClick=function(e){var t=e.target,o=c.props.onItemInvoked,n=c._findItemRoot(t);if(n&&o&&!c._isInputElement(t)){for(var r=c._getItemIndex(n);t!==c._root.current&&!c._hasAttribute(t,Dv)&&!c._hasAttribute(t,Ev);){if(t===n){c._onInvokeClick(e,r);break}t=Xi(t)}Xi(t)}},c._onKeyDownCapture=function(e){c._updateModifiers(e),c._handleNextFocus(!0)},c._onKeyDown=function(e){c._updateModifiers(e);var t=e.target,o=c._isSelectionDisabled(t),n=c.props.selection,r=e.which===En.a&&(c._isCtrlPressed\|\|c._isMetaPressed),i=e.which===En.escape;if(!c._isInputElement(t)){var s=c._getSelectionMode();if(r&&s===dv.multiple&&!n.isAllSelected())return o\|\|n.setAllSelected(!0),e.stopPropagation(),void e.preventDefault();if(i&&0<n.getSelectedCount())return o\|\|n.setAllSelected(!1),e.stopPropagation(),void e.preventDefault();var a=c._findItemRoot(t);if(a)for(var l=c._getItemIndex(a);t!==c._root.current&&!c._hasAttribute(t,Dv);){if(c._shouldAutoSelect(t)){o\|\|c._onInvokeMouseDown(e,l);break}if(!(e.which!==En.enter&&e.which!==En.space\|\|"BUTTON"!==t.tagName&&"A"!==t.tagName&&"INPUT"!==t.tagName))return!1;if(t===a){if(e.which===En.enter)return c._onInvokeClick(e,l),void e.preventDefault();if(e.which===En.space)return o\|\|c._onToggleClick(e,l),void e.preventDefault();break}t=Xi(t)}}},c._events=new va(c),c._async=new Si(c),fi(c);e=c.props.selection,e=e.isModal&&e.isModal();return c.state={isModal:e},c}(Y=yv=yv\|\|{})[Y.hidden=0]="hidden",Y[Y.visible=1]="visible",(ke=Cv=Cv\|\|{})[ke.disabled=0]="disabled",ke[ke.clickable=1]="clickable",ke[ke.hasDropdown=2]="hasDropdown",(K=_v=_v\|\|{})[K.unconstrained=0]="unconstrained",K[K.horizontalConstrained=1]="horizontalConstrained",(U=Sv=Sv\|\|{})[U.outside=0]="outside",U[U.surface=1]="surface",U[U.header=2]="header",(xe=xv=xv\|\|{})[xe.fixedColumns=0]="fixedColumns",xe[xe.justified=1]="justified",(V=kv=kv\|\|{})[V.onHover=0]="onHover",V[V.always=1]="always",V[V.hidden=2]="hidden";var Mv=function(e){var t=e.count,o=e.indentWidth,e=e.role;return 0<t?gt.createElement("span",{className:"ms-GroupSpacer",style:{display:"inline-block",width:t(void 0===o?36:o)},role:void 0===e?"presentation":e}):null},Nv={label:Vn,audio:Kn,video:Gn,ol:Un,li:jn,a:qn,button:Yn,input:Zn,textarea:Xn,select:Qn,option:Jn,table:$n,tr:er,th:tr,td:or,colGroup:nr,col:rr,form:ir,iframe:sr,img:ar};function Bv(e,t,o){return ur(t,e&&Nv[e]\|\|Wn,o)}function Fv(e){var t=e.theme,e=void 0===(o=e.cellStyleProps)?Lv:o,o=t.semanticColors;return[zo(Wv,t).cell,bo(t),{color:o.bodyText,position:"relative",display:"inline-block",boxSizing:"border-box",padding:"0 "+e.cellRightPadding+"px 0 "+e.cellLeftPadding+"px",lineHeight:"inherit",margin:"0",height:42,verticalAlign:"top",whiteSpace:"nowrap",textOverflow:"ellipsis",textAlign:"left"}]}var Av={root:"ms-DetailsRow",compact:"ms-DetailsList--Compact",cell:"ms-DetailsRow-cell",cellAnimation:"ms-DetailsRow-cellAnimation",cellCheck:"ms-DetailsRow-cellCheck",check:"ms-DetailsRow-check",cellMeasurer:"ms-DetailsRow-cellMeasurer",listCellFirstChild:"ms-List-cell:first-child",isContentUnselectable:"is-contentUnselectable",isSelected:"is-selected",isCheckVisible:"is-check-visible",isRowHeader:"is-row-header",fields:"ms-DetailsRow-fields"},Lv={cellLeftPadding:12,cellRightPadding:8,cellExtraRightPadding:24},Hv={rowHeight:42,compactRowHeight:32},Ov=ht(ht({},Hv),{rowVerticalPadding:11,compactRowVerticalPadding:6}),zv=function(e){var t=e.theme,o=e.isSelected,n=e.canSelect,r=e.droppingClassName,i=e.anySelected,s=e.isCheckVisible,a=e.checkboxCellClassName,l=e.compact,c=e.className,u=e.cellStyleProps,d=void 0===u?Lv:u,p=e.enableUpdateAnimations,h=e.disabled,m=t.palette,g=t.fonts,f=m.neutralPrimary,v=m.white,b=m.neutralSecondary,y=m.neutralLighter,C=m.neutralLight,_=m.neutralDark,S=m.neutralQuaternaryAlt,x=t.semanticColors,k=x.focusBorder,u=x.linkHovered,e=zo(Av,t),m={defaultHeaderText:f,defaultMetaText:b,defaultBackground:v,defaultHoverHeaderText:_,defaultHoverMetaText:f,defaultHoverBackground:y,selectedHeaderText:_,selectedMetaText:f,selectedBackground:C,selectedHoverHeaderText:_,selectedHoverMetaText:f,selectedHoverBackground:S,focusHeaderText:_,focusMetaText:f,focusBackground:C,focusHoverBackground:S},f=[bo(t,{inset:-1,borderColor:k,outlineColor:v,highContrastStyle:{top:2,right:2,bottom:2,left:2}}),e.isSelected,{color:m.selectedMetaText,background:m.selectedBackground,borderBottom:"1px solid "+v,selectors:((x={"&:before":{position:"absolute",display:"block",top:-1,height:1,bottom:0,left:0,right:0,content:"",borderTop:"1px solid "+v}})["."+e.cell+" > ."+ca.root]={color:u,selectors:((_={})[Yt]={color:"HighlightText"},_)},x["&:hover"]={background:m.selectedHoverBackground,color:m.selectedHoverMetaText,selectors:((f={})[Yt]={background:"Highlight",selectors:((C={})["."+e.cell]={color:"HighlightText"},C["."+e.cell+" > ."+ca.root]={forcedColorAdjust:"none",color:"HighlightText"},C)},f["."+e.isRowHeader]={color:m.selectedHoverHeaderText,selectors:((S={})[Yt]={color:"HighlightText"},S)},f)},x["&:focus"]={background:m.focusBackground,selectors:((_={})["."+e.cell]={color:m.focusMetaText,selectors:((C={})[Yt]={color:"HighlightText",selectors:{"> a":{color:"HighlightText"}}},C)},_["."+e.isRowHeader]={color:m.focusHeaderText,selectors:((S={})[Yt]={color:"HighlightText"},S)},_[Yt]={background:"Highlight"},_)},x[Yt]=ht(ht({background:"Highlight",color:"HighlightText"},{forcedColorAdjust:"none",MsHighContrastAdjust:"none"}),{selectors:{a:{color:"HighlightText"}}}),x["&:focus:hover"]={background:m.focusHoverBackground},x)}],C=[e.isContentUnselectable,{userSelect:"none",cursor:"default"}],S={minHeight:Ov.compactRowHeight,border:0},_={minHeight:Ov.compactRowHeight,paddingTop:Ov.compactRowVerticalPadding,paddingBottom:Ov.compactRowVerticalPadding,paddingLeft:d.cellLeftPadding+"px"},h=[bo(t,{inset:-1}),e.cell,{display:"inline-block",position:"relative",boxSizing:"border-box",minHeight:Ov.rowHeight,verticalAlign:"top",whiteSpace:"nowrap",overflow:"hidden",textOverflow:"ellipsis",paddingTop:Ov.rowVerticalPadding,paddingBottom:Ov.rowVerticalPadding,paddingLeft:d.cellLeftPadding+"px",selectors:((x={"& > button":{maxWidth:"100%"}})["[data-is-focusable='true']"]=bo(t,{inset:-1,borderColor:b,outlineColor:v}),x)},o&&{selectors:((x={})[Yt]=ht({background:"Highlight",color:"HighlightText"},{forcedColorAdjust:"none",MsHighContrastAdjust:"none"}),x)},l&&_,h&&{opacity:.5}];return{root:[e.root,Le.fadeIn400,r,t.fonts.small,s&&e.isCheckVisible,bo(t,{borderColor:k,outlineColor:v}),{borderBottom:"1px solid "+y,background:m.defaultBackground,color:m.defaultMetaText,display:"inline-flex",minWidth:"100%",minHeight:Ov.rowHeight,whiteSpace:"nowrap",padding:0,boxSizing:"border-box",verticalAlign:"top",textAlign:"left",selectors:((v={})["."+e.listCellFirstChild+" &:before"]={display:"none"},v["&:hover"]={background:m.defaultHoverBackground,color:m.defaultHoverMetaText,selectors:((y={})["."+e.isRowHeader]={color:m.defaultHoverHeaderText},y["."+e.cell+" > ."+ca.root]={color:u},y)},v["&:hover ."+e.check]={opacity:1},v["."+go+" &:focus ."+e.check]={opacity:1},v[".ms-GroupSpacer"]={flexShrink:0,flexGrow:0},v)},o&&f,!n&&C,l&&S,c],cellUnpadded:{paddingRight:d.cellRightPadding+"px"},cellPadded:{paddingRight:d.cellExtraRightPadding+d.cellRightPadding+"px",selectors:((d={})["&."+e.cellCheck]={paddingRight:0},d)},cell:h,cellAnimation:p&&Ie.slideLeftIn40,cellMeasurer:[e.cellMeasurer,{overflow:"visible",whiteSpace:"nowrap"}],checkCell:[h,e.cellCheck,a,{padding:0,paddingTop:1,marginTop:-1,flexShrink:0}],checkCover:{position:"absolute",top:-1,left:0,bottom:0,right:0,display:i?"block":"none"},fields:[e.fields,{display:"flex",alignItems:"stretch"}],isRowHeader:[e.isRowHeader,{color:m.defaultHeaderText,fontSize:g.medium.fontSize},o&&{color:m.selectedHeaderText,fontWeight:Fe.semibold,selectors:((m={})[Yt]={color:"HighlightText"},m)}],isMultiline:[h,{whiteSpace:"normal",wordBreak:"break-word",textOverflow:"clip"}],check:[e.check]}},Wv={tooltipHost:"ms-TooltipHost",root:"ms-DetailsHeader",cell:"ms-DetailsHeader-cell",cellIsCheck:"ms-DetailsHeader-cellIsCheck",collapseButton:"ms-DetailsHeader-collapseButton",isCollapsed:"is-collapsed",isAllSelected:"is-allSelected",isSelectAllHidden:"is-selectAllHidden",isResizingColumn:"is-resizingColumn",cellSizer:"ms-DetailsHeader-cellSizer",isResizing:"is-resizing",dropHintCircleStyle:"ms-DetailsHeader-dropHintCircleStyle",dropHintCaretStyle:"ms-DetailsHeader-dropHintCaretStyle",dropHintLineStyle:"ms-DetailsHeader-dropHintLineStyle",cellTitle:"ms-DetailsHeader-cellTitle",cellName:"ms-DetailsHeader-cellName",filterChevron:"ms-DetailsHeader-filterChevron",gripperBarVertical:"ms-DetailsColumn-gripperBarVertical",checkTooltip:"ms-DetailsHeader-checkTooltip",check:"ms-DetailsHeader-check"},Vv={root:"ms-DetailsRow-check",isDisabled:"ms-DetailsRow-check--isDisabled",isHeader:"ms-DetailsRow-check--isHeader"},Kv=Fn(),Gv=gt.memo(function(e){return gt.createElement(qh,{theme:e.theme,checked:e.checked,className:e.className,useFastIcons:!0})});function Uv(e){return gt.createElement(qh,{checked:e.checked})}function jv(e){return gt.createElement(Gv,{theme:e.theme,checked:e.checked})}function qv(t){return function(e){return e?e.column.isIconOnly?gt.createElement("span",{className:t.accessibleLabel},e.column.name):gt.createElement(gt.Fragment,null,e.column.name):null}}var Yv,Zv,Xv=In(function(e){var t=e.isVisible,o=void 0!==t&&t,n=e.canSelect,r=void 0!==n&&n,i=e.anySelected,s=void 0!==i&&i,a=e.selected,l=void 0!==a&&a,c=e.selectionMode,u=e.isHeader,d=void 0!==u&&u,p=e.className,t=(e.checkClassName,e.styles),n=e.theme,i=e.compact,a=e.onRenderDetailsCheckbox,u=e.useFastIcons,u=void 0===u\|\|u,e=mt(e,["isVisible","canSelect","anySelected","selected","selectionMode","isHeader","className","checkClassName","styles","theme","compact","onRenderDetailsCheckbox","useFastIcons"]),u=u?jv:Uv,u=a?Ma(a,u):u,o=Kv(t,{theme:n,canSelect:r,selected:l,anySelected:s,className:p,isHeader:d,isVisible:o,compact:i}),i={checked:l,theme:n},n=Bv("div",e,["aria-label","aria-labelledby","aria-describedby"]),c=c===dv.single?"radio":"checkbox";return r?gt.createElement("div",ht({},e,{role:c,className:Tr(o.root,o.check),"aria-checked":l,"data-selection-toggle":!0,"data-automationid":"DetailsRowCheck",tabIndex:-1}),u(i)):gt.createElement("div",ht({},n,{className:Tr(o.root,o.check)}))},function(e){var t=e.theme,o=e.className,n=e.isHeader,r=e.selected,i=e.anySelected,s=e.canSelect,a=e.compact,l=e.isVisible,c=zo(Vv,t),u=Hv.rowHeight,e=Hv.compactRowHeight,u=n?42:a?e:u,i=l\|\|r\|\|i;return{root:[c.root,o],check:[!s&&c.isDisabled,n&&c.isHeader,bo(t),t.fonts.small,jh.checkHost,{display:"flex",alignItems:"center",justifyContent:"center",cursor:"default",boxSizing:"border-box",verticalAlign:"top",background:"none",backgroundColor:"transparent",border:"none",opacity:i?1:0,height:u,width:48,padding:0,margin:0}],isDisabled:[]}},void 0,{scope:"DetailsRowCheck"},!0),Qv=(nb.prototype.dispose=function(){this._events&&this._events.dispose()},nb.prototype.subscribe=function(n,r,o){var i=this;this._initialized\|\|(this._events=new va(this),(t=ft())&&(this._events.on(t.body,"mouseup",this._onMouseUp.bind(this),!0),this._events.on(t,"mouseup",this._onDocumentMouseUp.bind(this),!0)),this._initialized=!0);var s,a,l,c,u,d,p,h,e=o.key,m=void 0===e?""+ ++this._lastId:e,g=[];if(o&&n){var t=o.eventMap,f=o.context,v=o.updateDropState,e={root:n,options:o,key:m},b=this._isDraggable(e),y=this._isDroppable(e);if((b\|\|y)&&t)for(var C=0,_=t;C<_.length;C++){var S=_[C],S={callback:S.callback.bind(null,f),eventName:S.eventName};g.push(S),this._events.on(n,S.eventName,S.callback)}y&&(a=function(e){e.isHandled\|\|(e.isHandled=!0,i._dragEnterCounts[m]--,0===i._dragEnterCounts[m]&&v(!1,e))},l=function(e){e.preventDefault(),e.isHandled\|\|(e.isHandled=!0,i._dragEnterCounts[m]++,1===i._dragEnterCounts[m]&&v(!0,e))},c=function(e){i._dragEnterCounts[m]=0,v(!1,e)},u=function(e){i._dragEnterCounts[m]=0,v(!1,e),o.onDrop&&o.onDrop(o.context.data,e)},d=function(e){e.preventDefault(),o.onDragOver&&o.onDragOver(o.context.data,e)},this._dragEnterCounts[m]=0,r.on(n,"dragenter",l),r.on(n,"dragleave",a),r.on(n,"dragend",c),r.on(n,"drop",u),r.on(n,"dragover",d)),b&&(p=this._onMouseDown.bind(this,e),c=this._onDragEnd.bind(this,e),s=function(e){var t=o;t&&t.onDragStart&&t.onDragStart(t.context.data,t.context.index,i._selection.getSelection(),e),i._isDragging=!0,e.dataTransfer&&e.dataTransfer.setData("id",n.id)},r.on(n,"dragstart",s),r.on(n,"mousedown",p),r.on(n,"dragend",c)),h={target:e,dispose:function(){if(i._activeTargets[m]===h&&delete i._activeTargets[m],n){for(var e=0,t=g;e<t.length;e++){var o=t[e];i._events.off(n,o.eventName,o.callback)}y&&(r.off(n,"dragenter",l),r.off(n,"dragleave",a),r.off(n,"dragend",c),r.off(n,"dragover",d),r.off(n,"drop",u)),b&&(r.off(n,"dragstart",s),r.off(n,"mousedown",p),r.off(n,"dragend",c))}}},this._activeTargets[m]=h}return{key:m,dispose:function(){h&&h.dispose()}}},nb.prototype.unsubscribe=function(e,t){t=this._activeTargets[t];t&&t.dispose()},nb.prototype._onDragEnd=function(e,t){e=e.options;e.onDragEnd&&e.onDragEnd(e.context.data,t)},nb.prototype._onMouseUp=function(e){if(this._isDragging=!1,this._dragData){for(var t=0,o=Object.keys(this._activeTargets);t<o.length;t++){var n=o[t],n=this._activeTargets[n];n.target.root&&(this._events.off(n.target.root,"mousemove"),this._events.off(n.target.root,"mouseleave"))}this._dragData.dropTarget&&(va.raise(this._dragData.dropTarget.root,"dragleave"),va.raise(this._dragData.dropTarget.root,"drop"))}this._dragData=null},nb.prototype._onDocumentMouseUp=function(e){var t=ft();t&&e.target===t.documentElement&&this._onMouseUp(e)},nb.prototype._onMouseMove=function(e,t){var o=t.buttons;this._dragData&&1!==(void 0===o?1:o)?this._onMouseUp(t):(o=e.root,t=e.key,this._isDragging&&this._isDroppable(e)&&this._dragData&&this._dragData.dropTarget&&this._dragData.dropTarget.key!==t&&!this._isChild(o,this._dragData.dropTarget.root)&&0<this._dragEnterCounts[this._dragData.dropTarget.key]&&(va.raise(this._dragData.dropTarget.root,"dragleave"),va.raise(o,"dragenter"),this._dragData.dropTarget=e))},nb.prototype._onMouseLeave=function(e,t){this._isDragging&&this._dragData&&this._dragData.dropTarget&&this._dragData.dropTarget.key===e.key&&(va.raise(e.root,"dragleave"),this._dragData.dropTarget=void 0)},nb.prototype._onMouseDown=function(e,t){if(0===t.button)if(this._isDraggable(e)){this._dragData={clientX:t.clientX,clientY:t.clientY,eventTarget:t.target,dragTarget:e};for(var o=0,n=Object.keys(this._activeTargets);o<n.length;o++){var r=n[o],r=this._activeTargets[r];r.target.root&&(this._events.on(r.target.root,"mousemove",this._onMouseMove.bind(this,r.target)),this._events.on(r.target.root,"mouseleave",this._onMouseLeave.bind(this,r.target)))}}else this._dragData=null},nb.prototype._isChild=function(e,t){for(;t&&t.parentElement;){if(t.parentElement===e)return!0;t=t.parentElement}return!1},nb.prototype._isDraggable=function(e){e=e.options;return!(!e.canDrag\|\|!e.canDrag(e.context.data))},nb.prototype._isDroppable=function(e){var t=e.options,e=this._dragData&&this._dragData.dragTarget?this._dragData.dragTarget.options.context:void 0;return!(!t.canDrop\|\|!t.canDrop(t.context,e))},nb),Jv=Fn(),$v=(l(ob,Zv=gt.Component),ob.prototype.render=function(){var e=this.props,t=e.column,o=e.parentId,n=e.isDraggable,r=e.styles,i=e.theme,s=e.cellStyleProps,a=void 0===s?Lv:s,l=e.useFastIcons,c=void 0===l\|\|l,u=this.props.onRenderColumnHeaderTooltip,s=void 0===u?this._onRenderColumnHeaderTooltip:u;this._classNames=Jv(r,{theme:i,headerClassName:t.headerClassName,iconClassName:t.iconClassName,isActionable:t.columnActionsMode!==Cv.disabled,isEmpty:!t.name,isIconVisible:t.isSorted\|\|t.isGrouped\|\|t.isFiltered,isPadded:t.isPadded,isIconOnly:t.isIconOnly,cellStyleProps:a,transitionDurationDrag:200,transitionDurationDrop:1500});e=this._classNames,l=c?Lr:Wr,u=t.onRenderFilterIcon?Ma(t.onRenderFilterIcon,this._onRenderFilterIcon(this._classNames)):this._onRenderFilterIcon(this._classNames),r=t.onRenderHeader?Ma(t.onRenderHeader,qv(this._classNames)):qv(this._classNames),i=t.columnActionsMode!==Cv.disabled&&(void 0!==t.onColumnClick\|\|void 0!==this.props.onColumnClick),c={"aria-label":t.ariaLabel\|\|(t.isIconOnly?t.name:void 0),"aria-labelledby":t.ariaLabel\|\|t.isIconOnly?void 0:o+"-"+t.key+"-name","aria-describedby":!this.props.onRenderColumnHeaderTooltip&&this._hasAccessibleDescription()?o+"-"+t.key+"-tooltip":void 0};return gt.createElement(gt.Fragment,null,gt.createElement("div",ht({key:t.key,ref:this._root,role:"columnheader"},!i&&c,{"aria-sort":t.isSorted?t.isSortedDescending?"descending":"ascending":"none","data-is-focusable":i\|\|t.columnActionsMode===Cv.disabled?void 0:"true",className:e.root,"data-is-draggable":n,draggable:n,style:{width:t.calculatedWidth+a.cellLeftPadding+a.cellRightPadding+(t.isPadded?a.cellExtraRightPadding:0)},"data-automationid":"ColumnsHeaderColumn","data-item-key":t.key}),n&&gt.createElement(l,{iconName:"GripperBarVertical",className:e.gripperBarVerticalStyle}),s({hostClassName:e.cellTooltip,id:o+"-"+t.key+"-tooltip",setAriaDescribedBy:!1,column:t,content:t.columnActionsMode!==Cv.disabled?t.ariaLabel:"",children:gt.createElement("span",ht({id:o+"-"+t.key,className:e.cellTitle,"data-is-focusable":i&&t.columnActionsMode!==Cv.disabled?"true":void 0,role:i?"button":void 0},i&&c,{onContextMenu:this._onColumnContextMenu,onClick:this._onColumnClick,"aria-haspopup":t.columnActionsMode===Cv.hasDropdown?"menu":void 0,"aria-expanded":t.columnActionsMode===Cv.hasDropdown?!!t.isMenuOpen:void 0}),gt.createElement("span",{id:o+"-"+t.key+"-name",className:e.cellName},(t.iconName\|\|t.iconClassName)&&gt.createElement(l,{className:e.iconClassName,iconName:t.iconName}),r(this.props)),t.isFiltered&&gt.createElement(l,{className:e.nearIcon,iconName:"Filter"}),t.isSorted&&gt.createElement(l,{className:e.sortIcon,iconName:t.isSortedDescending?"SortDown":"SortUp"}),t.isGrouped&&gt.createElement(l,{className:e.nearIcon,iconName:"GroupedDescending"}),t.columnActionsMode===Cv.hasDropdown&&!t.isIconOnly&&u({"aria-hidden":!0,columnProps:this.props,className:e.filterChevron,iconName:"ChevronDown"}))},this._onRenderColumnHeaderTooltip)),this.props.onRenderColumnHeaderTooltip?null:this._renderAccessibleDescription())},ob.prototype.componentDidMount=function(){var e=this;this.props.dragDropHelper&&this.props.isDraggable&&this._addDragDropHandling();var t=this._classNames;this.props.isDropped&&(this._root.current&&(this._root.current.classList.add(t.borderAfterDropping),this._async.setTimeout(function(){e._root.current&&e._root.current.classList.add(t.noBorderAfterDropping)},20)),this._async.setTimeout(function(){e._root.current&&(e._root.current.classList.remove(t.borderAfterDropping),e._root.current.classList.remove(t.noBorderAfterDropping))},1520))},ob.prototype.componentWillUnmount=function(){this._dragDropSubscription&&(this._dragDropSubscription.dispose(),delete this._dragDropSubscription),this._async.dispose(),this._events.dispose()},ob.prototype.componentDidUpdate=function(){!this._dragDropSubscription&&this.props.dragDropHelper&&this.props.isDraggable&&this._addDragDropHandling(),this._dragDropSubscription&&!this.props.isDraggable&&(this._dragDropSubscription.dispose(),this._events.off(this._root.current,"mousedown"),delete this._dragDropSubscription)},ob.prototype._getColumnDragDropOptions=function(){var e=this,t=this.props.columnIndex;return{selectionIndex:t,context:{data:t,index:t},canDrag:function(){return e.props.isDraggable},canDrop:function(){return!1},onDragStart:this._onDragStart,updateDropState:function(){},onDrop:function(){},onDragEnd:this._onDragEnd}},ob.prototype._hasAccessibleDescription=function(){var e=this.props.column;return!!(e.filterAriaLabel\|\|e.sortAscendingAriaLabel\|\|e.sortDescendingAriaLabel\|\|e.groupAriaLabel)},ob.prototype._renderAccessibleDescription=function(){var e=this.props,t=e.column,o=e.parentId,e=this._classNames;return this._hasAccessibleDescription()&&!this.props.onRenderColumnHeaderTooltip?gt.createElement("label",{key:t.key+"_label",id:o+"-"+t.key+"-tooltip",className:e.accessibleLabel,hidden:!0},t.isFiltered&&t.filterAriaLabel\|\|null,t.isSorted&&(t.isSortedDescending?t.sortDescendingAriaLabel:t.sortAscendingAriaLabel)\|\|null,t.isGrouped&&t.groupAriaLabel\|\|null):null},ob.prototype._addDragDropHandling=function(){this._dragDropSubscription=this.props.dragDropHelper.subscribe(this._root.current,this._events,this._getColumnDragDropOptions()),this._events.on(this._root.current,"mousedown",this._onRootMouseDown)},ob),eb={isActionable:"is-actionable",cellIsCheck:"ms-DetailsHeader-cellIsCheck",collapseButton:"ms-DetailsHeader-collapseButton",isCollapsed:"is-collapsed",isAllSelected:"is-allSelected",isSelectAllHidden:"is-selectAllHidden",isResizingColumn:"is-resizingColumn",isEmpty:"is-empty",isIconVisible:"is-icon-visible",cellSizer:"ms-DetailsHeader-cellSizer",isResizing:"is-resizing",dropHintCircleStyle:"ms-DetailsHeader-dropHintCircleStyle",dropHintLineStyle:"ms-DetailsHeader-dropHintLineStyle",cellTitle:"ms-DetailsHeader-cellTitle",cellName:"ms-DetailsHeader-cellName",filterChevron:"ms-DetailsHeader-filterChevron",gripperBarVerticalStyle:"ms-DetailsColumn-gripperBar",nearIcon:"ms-DetailsColumn-nearIcon"},tb=In($v,function(e){var t=e.theme,o=e.headerClassName,n=e.iconClassName,r=e.isActionable,i=e.isEmpty,s=e.isIconVisible,a=e.isPadded,l=e.isIconOnly,c=e.cellStyleProps,u=void 0===c?Lv:c,d=e.transitionDurationDrag,p=e.transitionDurationDrop,h=t.semanticColors,m=t.palette,g=t.fonts,f=zo(eb,t),v={iconForegroundColor:h.bodySubtext,headerForegroundColor:h.bodyText,headerBackgroundColor:h.bodyBackground,dropdownChevronForegroundColor:m.neutralSecondary,resizerColor:m.neutralTertiaryAlt},b={color:v.iconForegroundColor,opacity:1,paddingLeft:8},y={outline:"1px solid "+m.themePrimary},c={outlineColor:"transparent"};return{root:[Fv(e),g.small,r&&[f.isActionable,{selectors:{":hover":{color:h.bodyText,background:h.listHeaderBackgroundHovered},":active":{background:h.listHeaderBackgroundPressed}}}],i&&[f.isEmpty,{textOverflow:"clip"}],s&&f.isIconVisible,a&&{paddingRight:u.cellExtraRightPadding+u.cellRightPadding},{selectors:{':hover i[data-icon-name="GripperBarVertical"]':{display:"block"}}},o],gripperBarVerticalStyle:{display:"none",position:"absolute",textAlign:"left",color:m.neutralTertiary,left:1},nearIcon:[f.nearIcon,b],sortIcon:[b,{paddingLeft:4,position:"relative",top:1}],iconClassName:[{color:v.iconForegroundColor,opacity:1},n],filterChevron:[f.filterChevron,{color:v.dropdownChevronForegroundColor,paddingLeft:6,verticalAlign:"middle",fontSize:g.small.fontSize}],cellTitle:[f.cellTitle,bo(t),ht({display:"flex",flexDirection:"row",justifyContent:"flex-start",alignItems:"stretch",boxSizing:"border-box",overflow:"hidden",padding:"0 "+u.cellRightPadding+"px 0 "+u.cellLeftPadding+"px"},l?{alignContent:"flex-end",maxHeight:"100%",flexWrap:"wrap-reverse"}:{})],cellName:[f.cellName,{flex:"0 1 auto",overflow:"hidden",textOverflow:"ellipsis",fontWeight:Fe.semibold,fontSize:g.medium.fontSize},l&&{selectors:((l={})["."+f.nearIcon]={paddingLeft:0},l)}],cellTooltip:{display:"block",position:"absolute",top:0,left:0,bottom:0,right:0},accessibleLabel:So,borderWhileDragging:y,noBorderWhileDragging:[c,{transition:"outline "+d+"ms ease"}],borderAfterDropping:y,noBorderAfterDropping:[c,{transition:"outline "+p+"ms ease"}]}},void 0,{scope:"DetailsColumn"});function ob(e){var i=Zv.call(this,e)\|\|this;return i._root=gt.createRef(),i._onRenderFilterIcon=function(e){return function(e){var t=e.columnProps,e=mt(e,["columnProps"]),t=null!=t&&t.useFastIcons?Lr:Wr;return gt.createElement(t,ht({},e))}},i._onRenderColumnHeaderTooltip=function(e){return gt.createElement("span",{className:e.hostClassName},e.children)},i._onColumnClick=function(e){var t=i.props,o=t.onColumnClick,t=t.column;t.columnActionsMode!==Cv.disabled&&(t.onColumnClick&&t.onColumnClick(e,t),o&&o(e,t))},i._onDragStart=function(e,t,o,n){var r=i._classNames;t&&(i._updateHeaderDragInfo(t),i._root.current.classList.add(r.borderWhileDragging),i._async.setTimeout(function(){i._root.current&&i._root.current.classList.add(r.noBorderWhileDragging)},20))},i._onDragEnd=function(e,t){var o=i._classNames;t&&i._updateHeaderDragInfo(-1,t),i._root.current.classList.remove(o.borderWhileDragging),i._root.current.classList.remove(o.noBorderWhileDragging)},i._updateHeaderDragInfo=function(e,t){i.props.setDraggedItemIndex&&i.props.setDraggedItemIndex(e),i.props.updateDragInfo&&i.props.updateDragInfo({itemIndex:e},t)},i._onColumnContextMenu=function(e){var t=i.props,o=t.onColumnContextMenu,t=t.column;t.onColumnContextMenu&&(t.onColumnContextMenu(t,e),e.preventDefault()),o&&(o(t,e),e.preventDefault())},i._onRootMouseDown=function(e){i.props.isDraggable&&0===e.button&&e.stopPropagation()},fi(i),i._async=new Si(i),i._events=new va(i),i}function nb(e){this._selection=e.selection,this._dragEnterCounts={},this._activeTargets={},this._lastId=0,this._initialized=!1}(G=Yv=Yv\|\|{})[G.none=0]="none",G[G.hidden=1]="hidden",G[G.visible=2]="visible";var rb,ib=Fn(),sb=[],ab=(l(lb,rb=gt.Component),lb.prototype.componentDidMount=function(){var e=this.props.selection;this._events.on(e,gv,this._onSelectionChanged),this._rootElement.current&&(this._events.on(this._rootElement.current,"mousedown",this._onRootMouseDown),this._events.on(this._rootElement.current,"keydown",this._onRootKeyDown),this._getColumnReorderProps()&&(this._subscriptionObject=this._dragDropHelper.subscribe(this._rootElement.current,this._events,this._getHeaderDragDropOptions())))},lb.prototype.componentDidUpdate=function(e){var t,o;this._getColumnReorderProps()?!this._subscriptionObject&&this._rootElement.current&&(this._subscriptionObject=this._dragDropHelper.subscribe(this._rootElement.current,this._events,this._getHeaderDragDropOptions())):this._subscriptionObject&&(this._subscriptionObject.dispose(),delete this._subscriptionObject),this.props!==e&&0<=this._onDropIndexInfo.sourceIndex&&0<=this._onDropIndexInfo.targetIndex&&(t=e.columns,o=this.props.columns,(void 0===t?sb:t)[this._onDropIndexInfo.sourceIndex].key===(void 0===o?sb:o)[this._onDropIndexInfo.targetIndex].key&&(this._onDropIndexInfo={sourceIndex:-1,targetIndex:-1})),this.props.isAllCollapsed!==e.isAllCollapsed&&this.setState({isAllCollapsed:this.props.isAllCollapsed})},lb.prototype.componentWillUnmount=function(){this._subscriptionObject&&(this._subscriptionObject.dispose(),delete this._subscriptionObject),this._dragDropHelper.dispose(),this._events.dispose()},lb.prototype.render=function(){var n=this,e=this.props,t=e.columns,r=void 0===t?sb:t,o=e.ariaLabel,i=e.ariaLabelForToggleAllGroupsButton,s=e.ariaLabelForSelectAllCheckbox,a=e.selectAllVisibility,l=e.ariaLabelForSelectionColumn,c=e.indentWidth,u=e.onColumnClick,d=e.onColumnContextMenu,p=e.onRenderColumnHeaderTooltip,h=void 0===p?this._onRenderColumnHeaderTooltip:p,m=e.styles,g=e.selectionMode,f=e.theme,v=e.onRenderDetailsCheckbox,b=e.groupNestingDepth,y=e.useFastIcons,C=e.checkboxVisibility,_=e.className,S=this.state,x=S.isAllSelected,k=S.columnResizeDetails,t=S.isSizing,p=S.isAllCollapsed,e=a!==Yv.none,S=a===Yv.hidden,C=C===kv.always,w=this._getColumnReorderProps(),I=w&&w.frozenColumnCountFromStart?w.frozenColumnCountFromStart:0,D=w&&w.frozenColumnCountFromEnd?w.frozenColumnCountFromEnd:0;this._classNames=ib(m,{theme:f,isAllSelected:x,isSelectAllHidden:a===Yv.hidden,isResizingColumn:!!k&&t,isSizing:t,isAllCollapsed:p,isCheckboxHidden:S,className:_});var a=this._classNames,k=y?Lr:Wr,_=0<b&&this.props.collapseAllVisibility===yv.visible,E=1+(e?1:0)+(_?1:0),f=Pn(f);return gt.createElement(Zs,{role:"row","aria-label":o,className:a.root,componentRef:this._rootComponent,elementRef:this._rootElement,onMouseMove:this._onRootMouseMove,"data-automationid":"DetailsHeader",direction:Ei.horizontal},e?[gt.createElement("div",{key:"__checkbox",className:a.cellIsCheck,"aria-labelledby":this._id+"-checkTooltip",onClick:S?void 0:this._onSelectAllClicked,role:"columnheader"},h({hostClassName:a.checkTooltip,id:this._id+"-checkTooltip",setAriaDescribedBy:!1,content:s,children:gt.createElement(Xv,{id:this._id+"-check","aria-label":g===dv.multiple?s:l,"data-is-focusable":!S\|\|void 0,isHeader:!0,selected:x,anySelected:!1,canSelect:!S,className:a.check,onRenderDetailsCheckbox:v,useFastIcons:y,isVisible:C})},this._onRenderColumnHeaderTooltip)),this.props.onRenderColumnHeaderTooltip?null:s&&!S?gt.createElement("label",{key:"__checkboxLabel",id:this._id+"-checkTooltip",className:a.accessibleLabel,"aria-hidden":!0},s):l&&S?gt.createElement("label",{key:"__checkboxLabel",id:this._id+"-checkTooltip",className:a.accessibleLabel,"aria-hidden":!0},l):null]:null,_?gt.createElement("div",{className:a.cellIsGroupExpander,onClick:this._onToggleCollapseAll,"data-is-focusable":!0,"aria-label":i,"aria-expanded":!p,role:"columnheader"},gt.createElement(k,{className:a.collapseButton,iconName:f?"ChevronLeftMed":"ChevronRightMed"})):null,gt.createElement(Mv,{indentWidth:c,role:"gridcell",count:b-1}),r.map(function(e,t){var o=!!w&&I<=t&&t<r.length-D;return[w&&(o\|\|t===r.length-D)&&n._renderDropHint(t),gt.createElement(tb,{column:e,styles:e.styles,key:e.key,columnIndex:E+t,parentId:n._id,isDraggable:o,updateDragInfo:n._updateDragInfo,dragDropHelper:n._dragDropHelper,onColumnClick:u,onColumnContextMenu:d,onRenderColumnHeaderTooltip:n.props.onRenderColumnHeaderTooltip,isDropped:n._onDropIndexInfo.targetIndex===t,cellStyleProps:n.props.cellStyleProps,useFastIcons:y}),n._renderColumnDivider(t)]}),w&&0===D&&this._renderDropHint(r.length),t&&gt.createElement(sc,null,gt.createElement("div",{className:a.sizingOverlay,onMouseMove:this._onSizerMouseMove,onMouseUp:this._onSizerMouseUp})))},lb.prototype.focus=function(){var e;return!(null===(e=this._rootComponent.current)\|\|void 0===e\|\|!e.focus())},lb.prototype._getColumnReorderProps=function(){var e=this.props,t=e.columnReorderOptions;return e.columnReorderProps\|\|t&&ht(ht({},t),{onColumnDragEnd:void 0})},lb.prototype._getHeaderDragDropOptions=function(){return{selectionIndex:1,context:{data:this,index:0},canDrag:function(){return!1},canDrop:function(){return!0},onDragStart:function(){},updateDropState:this._updateDroppingState,onDrop:this._onDrop,onDragEnd:function(){},onDragOver:this._onDragOver}},lb.prototype._isValidCurrentDropHintIndex=function(){return 0<=this._currentDropHintIndex},lb.prototype._isCheckboxColumnHidden=function(){var e=this.props,t=e.selectionMode,e=e.checkboxVisibility;return t===dv.none\|\|e===kv.hidden},lb.prototype._resetDropHints=function(){0<=this._currentDropHintIndex&&(this._updateDropHintElement(this._dropHintDetails[this._currentDropHintIndex].dropHintElementRef,"none"),this._currentDropHintIndex=-1)},lb.prototype._updateDropHintElement=function(e,t){e.childNodes[1].style.display=t,e.childNodes[0].style.display=t},lb.prototype._isEventOnHeader=function(e){if(this._rootElement.current){var t=this._rootElement.current.getBoundingClientRect();if(e.clientX>t.left&&e.clientX<t.right&&e.clientY>t.top&&e.clientY<t.bottom)return Sv.header}},lb.prototype._renderColumnDivider=function(e){var t=this.props.columns,o=(void 0===t?sb:t)[e],t=o.onRenderDivider;return t?t({column:o,columnIndex:e},this._renderColumnSizer):this._renderColumnSizer({column:o,columnIndex:e})},lb.prototype._renderDropHint=function(e){var t=this._classNames,o=this.props.useFastIcons?Lr:Wr;return gt.createElement("div",{key:"dropHintKey",className:t.dropHintStyle,id:"columnDropHint_"+e},gt.createElement("div",{role:"presentation",key:"dropHintCircleKey",className:t.dropHintCaretStyle,"data-is-focusable":!1,"data-sizer-index":e,"aria-hidden":!0},gt.createElement(o,{iconName:"CircleShapeSolid"})),gt.createElement("div",{key:"dropHintLineKey","aria-hidden":!0,"data-is-focusable":!1,"data-sizer-index":e,className:t.dropHintLineStyle}))},lb.prototype._onSizerDoubleClick=function(e,t){var o=this.props,n=o.onColumnAutoResized,o=o.columns;n&&n((void 0===o?sb:o)[e],e)},lb.prototype._onSelectionChanged=function(){var e=!!this.props.selection&&this.props.selection.isAllSelected();this.state.isAllSelected!==e&&this.setState({isAllSelected:e})},lb.defaultProps={selectAllVisibility:Yv.visible,collapseAllVisibility:yv.visible,useFastIcons:!0},lb);function lb(e){var u=rb.call(this,e)\|\|this;return u._rootElement=gt.createRef(),u._rootComponent=gt.createRef(),u._draggedColumnIndex=-1,u._dropHintDetails={},u._updateDroppingState=function(e,t){0<=u._draggedColumnIndex&&"drop"!==t.type&&!e&&u._resetDropHints()},u._onDragOver=function(e,t){0<=u._draggedColumnIndex&&(t.stopPropagation(),u._computeDropHintToBeShown(t.clientX))},u._onDrop=function(e,t){var o,n,r=u._getColumnReorderProps();0<=u._draggedColumnIndex&&t&&(o=u._draggedColumnIndex>u._currentDropHintIndex?u._currentDropHintIndex:u._currentDropHintIndex-1,n=u._isValidCurrentDropHintIndex(),t.stopPropagation(),n&&(u._onDropIndexInfo.sourceIndex=u._draggedColumnIndex,u._onDropIndexInfo.targetIndex=o,r.onColumnDrop?(n={draggedIndex:u._draggedColumnIndex,targetIndex:o},r.onColumnDrop(n)):r.handleColumnReorder&&r.handleColumnReorder(u._draggedColumnIndex,o))),u._resetDropHints(),u._dropHintDetails={},u._draggedColumnIndex=-1},u._updateDragInfo=function(e,t){var o=u._getColumnReorderProps(),e=e.itemIndex;0<=e?(u._draggedColumnIndex=u._isCheckboxColumnHidden()?e-1:e-2,u._getDropHintPositions(),o.onColumnDragStart&&o.onColumnDragStart(!0)):t&&0<=u._draggedColumnIndex&&(u._resetDropHints(),u._draggedColumnIndex=-1,u._dropHintDetails={},o.onColumnDragEnd)&&(e=u._isEventOnHeader(t),o.onColumnDragEnd({dropLocation:e},t))},u._getDropHintPositions=function(){for(var e,t,o,n=u.props.columns,r=void 0===n?sb:n,n=u._getColumnReorderProps(),i=0,s=0,a=n.frozenColumnCountFromStart\|\|0,l=n.frozenColumnCountFromEnd\|\|0,c=a;c<r.length-l+1;c++)!u._rootElement.current\|\|(t=u._rootElement.current.querySelectorAll("#columnDropHint_"+c)[0])&&(c===a?(i=t.offsetLeft,s=t.offsetLeft,e=t):(o=(t.offsetLeft+i)/2,u._dropHintDetails[c-1]={originX:i,startX:s,endX:o,dropHintElementRef:e},s=o,i=(e=t).offsetLeft,c===r.length-l&&(u._dropHintDetails[c]={originX:i,startX:s,endX:t.offsetLeft,dropHintElementRef:e})))},u._computeDropHintToBeShown=function(e){var t=Pn(u.props.theme);if(u._rootElement.current){var o=e-u._rootElement.current.getBoundingClientRect().left,n=u._currentDropHintIndex;if(!u._isValidCurrentDropHintIndex()\|\|!cb(t,o,u._dropHintDetails[n].startX,u._dropHintDetails[n].endX)){var r=u.props.columns,i=void 0===r?sb:r,e=u._getColumnReorderProps(),r=e.frozenColumnCountFromStart\|\|0,e=e.frozenColumnCountFromEnd\|\|0,e=i.length-e,s=-1;if(ub(t,o,u._dropHintDetails[r].endX)?s=r:db(t,o,u._dropHintDetails[e].startX)?s=e:u._isValidCurrentDropHintIndex()&&(u._dropHintDetails[n+1]&&cb(t,o,u._dropHintDetails[n+1].startX,u._dropHintDetails[n+1].endX)?s=n+1:u._dropHintDetails[n-1]&&cb(t,o,u._dropHintDetails[n-1].startX,u._dropHintDetails[n-1].endX)&&(s=n-1)),-1===s)for(var a=r,l=e;a<l;){var c=Math.ceil((l+a)/2);if(cb(t,o,u._dropHintDetails[c].startX,u._dropHintDetails[c].endX)){s=c;break}ub(t,o,u._dropHintDetails[c].originX)?l=c:db(t,o,u._dropHintDetails[c].originX)&&(a=c)}s===u._draggedColumnIndex\|\|s===u._draggedColumnIndex+1?u._isValidCurrentDropHintIndex()&&u._resetDropHints():n!==s&&0<=s&&(u._resetDropHints(),u._updateDropHintElement(u._dropHintDetails[s].dropHintElementRef,"inline-block"),u._currentDropHintIndex=s)}}},u._renderColumnSizer=function(e){var t=e.columnIndex,o=u.props.columns,n=void 0===o?sb:o,r=n[t],e=u.state.columnResizeDetails,o=u._classNames;return r.isResizable?gt.createElement("div",{key:r.key+"_sizer","aria-hidden":!0,role:"button","data-is-focusable":!1,onClick:pb,"data-sizer-index":t,onBlur:u._onSizerBlur,className:Tr(o.cellSizer,t<n.length-1?o.cellSizerStart:o.cellSizerEnd,((n={})[o.cellIsResizing]=e&&e.columnIndex===t,n)),onDoubleClick:u._onSizerDoubleClick.bind(u,t)}):null},u._onRenderColumnHeaderTooltip=function(e){return gt.createElement("span",{className:e.hostClassName},e.children)},u._onSelectAllClicked=function(){var e=u.props.selection;e&&e.toggleAllSelected()},u._onRootMouseDown=function(e){var t=e.target.getAttribute("data-sizer-index"),o=Number(t),n=u.props.columns;null!==t&&0===e.button&&(u.setState({columnResizeDetails:{columnIndex:o,columnMinWidth:(void 0===n?sb:n)[o].calculatedWidth,originX:e.clientX}}),e.preventDefault(),e.stopPropagation())},u._onRootMouseMove=function(e){var t=u.state,o=t.columnResizeDetails,t=t.isSizing;o&&!t&&e.clientX!==o.originX&&u.setState({isSizing:!0})},u._onRootKeyDown=function(e){var t=u.state,o=t.columnResizeDetails,n=t.isSizing,r=u.props,i=r.columns,t=void 0===i?sb:i,i=r.onColumnResized,r=e.target.getAttribute("data-sizer-index");r&&!n&&(n=Number(r),o?(r=void 0,e.which===En.enter?(u.setState({columnResizeDetails:void 0}),e.preventDefault(),e.stopPropagation()):e.which===En.left?r=Pn(u.props.theme)?1:-1:e.which===En.right&&(r=Pn(u.props.theme)?-1:1),r&&(e.shiftKey\|\|(r=10),u.setState({columnResizeDetails:ht(ht({},o),{columnMinWidth:o.columnMinWidth+r})}),i&&i(t[n],o.columnMinWidth+r,n),e.preventDefault(),e.stopPropagation())):e.which===En.enter&&(u.setState({columnResizeDetails:{columnIndex:n,columnMinWidth:t[n].calculatedWidth}}),e.preventDefault(),e.stopPropagation()))},u._onSizerMouseMove=function(e){var t=e.buttons,o=u.props,n=o.onColumnIsSizingChanged,r=o.onColumnResized,i=o.columns,o=void 0===i?sb:i,i=u.state.columnResizeDetails;void 0===t\|\|1===t?(e.clientX!==i.originX&&n&&n(o[i.columnIndex],!0),r&&(n=e.clientX-i.originX,Pn(u.props.theme)&&(n=-n),r(o[i.columnIndex],i.columnMinWidth+n,i.columnIndex))):u._onSizerMouseUp(e)},u._onSizerBlur=function(e){u.state.columnResizeDetails&&u.setState({columnResizeDetails:void 0,isSizing:!1})},u._onSizerMouseUp=function(e){var t=u.props,o=t.columns,n=void 0===o?sb:o,o=t.onColumnIsSizingChanged,t=u.state.columnResizeDetails;u.setState({columnResizeDetails:void 0,isSizing:!1}),o&&o(n[t.columnIndex],!1)},u._onToggleCollapseAll=function(){var e=u.props.onToggleCollapseAll,t=!u.state.isAllCollapsed;u.setState({isAllCollapsed:t}),e&&e(t)},fi(u),u._events=new va(u),u.state={columnResizeDetails:void 0,isAllCollapsed:u.props.isAllCollapsed,isAllSelected:!!u.props.selection&&u.props.selection.isAllSelected()},u._onDropIndexInfo={sourceIndex:-1,targetIndex:-1},u._id=_s("header"),u._currentDropHintIndex=-1,u._dragDropHelper=new Qv({selection:{getSelection:function(){}},minimumPixelsForDrag:u.props.minimumPixelsForDrag}),u}function cb(e,t,o,n){return e?t<=o&&n<=t:o<=t&&t<=n}function ub(e,t,o){return e?o<=t:t<=o}function db(e,t,o){return e?t<=o:o<=t}function pb(e){e.stopPropagation()}var hb,mb=In(ab,function(e){var t=e.theme,o=e.className,n=e.isAllSelected,r=e.isResizingColumn,i=e.isSizing,s=e.isAllCollapsed,a=e.cellStyleProps,l=void 0===a?Lv:a,c=t.semanticColors,u=t.palette,d=t.fonts,p=zo(Wv,t),h={iconForegroundColor:c.bodySubtext,headerForegroundColor:c.bodyText,headerBackgroundColor:c.bodyBackground,resizerColor:u.neutralTertiaryAlt},m={opacity:1,transition:"opacity 0.3s linear"},a=Fv(e);return{root:[p.root,d.small,{display:"inline-block",background:h.headerBackgroundColor,position:"relative",minWidth:"100%",verticalAlign:"top",height:42,lineHeight:42,whiteSpace:"nowrap",boxSizing:"content-box",paddingBottom:"1px",paddingTop:"16px",borderBottom:"1px solid "+c.bodyDivider,cursor:"default",userSelect:"none",selectors:((e={})["&:hover ."+p.check]={opacity:1},e["& ."+p.tooltipHost+" ."+p.checkTooltip]={display:"block"},e)},n&&p.isAllSelected,r&&p.isResizingColumn,o],check:[p.check,{height:42},{selectors:((o={})["."+go+" &:focus"]={opacity:1},o)}],cellWrapperPadded:{paddingRight:l.cellExtraRightPadding+l.cellRightPadding},cellIsCheck:[a,p.cellIsCheck,{position:"relative",padding:0,margin:0,display:"inline-flex",alignItems:"center",border:"none"},n&&{opacity:1}],cellIsGroupExpander:[a,{display:"inline-flex",alignItems:"center",justifyContent:"center",fontSize:d.small.fontSize,padding:0,border:"none",width:36,color:u.neutralSecondary,selectors:{":hover":{backgroundColor:u.neutralLighter},":active":{backgroundColor:u.neutralLight}}}],cellIsActionable:{selectors:{":hover":{color:c.bodyText,background:c.listHeaderBackgroundHovered},":active":{background:c.listHeaderBackgroundPressed}}},cellIsEmpty:{textOverflow:"clip"},cellSizer:[p.cellSizer,{selectors:{"&::-moz-focus-inner":{border:0},"&":{outline:"transparent"}}},{display:"inline-block",position:"relative",cursor:"ew-resize",bottom:0,top:0,overflow:"hidden",height:"inherit",background:"transparent",zIndex:1,width:16,selectors:((h={":after":{content:'""',position:"absolute",top:0,bottom:0,width:1,background:h.resizerColor,opacity:0,left:"50%"},":focus:after":m,":hover:after":m})["&."+p.isResizing+":after"]=[m,{boxShadow:"0 0 5px 0 rgba(0, 0, 0, 0.4)"}],h)}],cellIsResizing:p.isResizing,cellSizerStart:{margin:"0 -8px"},cellSizerEnd:{margin:0,marginLeft:-16},collapseButton:[p.collapseButton,{transformOrigin:"50% 50%",transition:"transform .1s linear"},s?[p.isCollapsed,{transform:"rotate(0deg)"}]:{transform:Pn(t)?"rotate(-90deg)":"rotate(90deg)"}],checkTooltip:p.checkTooltip,sizingOverlay:i&&{position:"absolute",left:0,top:0,right:0,bottom:0,cursor:"ew-resize",background:"rgba(255, 255, 255, 0)",selectors:((i={})[Yt]=ht({background:"transparent"},{forcedColorAdjust:"none",MsHighContrastAdjust:"none"}),i)},accessibleLabel:So,dropHintCircleStyle:[p.dropHintCircleStyle,{display:"inline-block",visibility:"hidden",position:"absolute",bottom:0,height:9,width:9,borderRadius:"50%",marginLeft:-5,top:34,overflow:"visible",zIndex:10,border:"1px solid "+u.themePrimary,background:u.white}],dropHintCaretStyle:[p.dropHintCaretStyle,{display:"none",position:"absolute",top:-28,left:-6.5,fontSize:d.medium.fontSize,color:u.themePrimary,overflow:"visible",zIndex:10}],dropHintLineStyle:[p.dropHintLineStyle,{display:"none",position:"absolute",bottom:0,top:0,overflow:"hidden",height:42,width:1,background:u.themePrimary,zIndex:10}],dropHintStyle:{display:"inline-block",position:"absolute"}}},void 0,{scope:"DetailsHeader"}),gb=function(e){var t=e.columns,i=e.rowClassNames,o=e.cellStyleProps,s=void 0===o?Lv:o,a=e.item,l=e.itemIndex,c=e.onRenderItemColumn,u=e.getCellValueKey,d=e.cellsByColumn,p=e.enableUpdateAnimations,h=e.rowHeaderId,e=gt.useRef(),m=e.current\|\|(e.current={});return gt.createElement("div",{className:i.fields,"data-automationid":"DetailsRowFields",role:"presentation"},t.map(function(e){var t,o=void 0===e.calculatedWidth?"auto":e.calculatedWidth+s.cellLeftPadding+s.cellRightPadding+(e.isPadded?s.cellExtraRightPadding:0),n=e.onRender,r=void 0===n?c:n,n=e.getValueKey,n=void 0===n?u:n,r=d&&e.key in d?d[e.key]:r?r(a,l,e):"boolean"==typeof(t=null==(t=a&&e&&e.fieldName?a[e.fieldName]:"")?"":t)?t.toString():t,t=m[e.key],n=p&&n?n(a,l,e):void 0,t=void 0!==n&&void 0!==t&&n!==t?!0:!1;m[e.key]=n;n=e.key+(void 0!==n?"-"+n:"");return gt.createElement("div",{key:n,id:e.isRowHeader?h:void 0,role:e.isRowHeader?"rowheader":"gridcell","aria-readonly":!0,className:Tr(e.className,e.isMultiline&&i.isMultiline,e.isRowHeader&&i.isRowHeader,i.cell,e.isPadded?i.cellPadded:i.cellUnpadded,t&&i.cellAnimation),style:{width:o},"data-automationid":"DetailsRowCell","data-automation-key":e.key},r)}))},fb=Fn(),vb=[],bb=(l(yb,hb=gt.Component),yb.getDerivedStateFromProps=function(e,t){return ht(ht({},t),{selectionState:Cb(e)})},yb.prototype.componentDidMount=function(){var e=this.props,t=e.dragDropHelper,o=e.selection,n=e.item,e=e.onDidMount;t&&this._root.current&&(this._dragDropSubscription=t.subscribe(this._root.current,this._events,this._getRowDragDropOptions())),o&&this._events.on(o,gv,this._onSelectionChanged),e&&n&&(this._onDidMountCalled=!0,e(this))},yb.prototype.componentDidUpdate=function(e){var t=this.state,o=this.props,n=o.item,o=o.onDidMount,t=t.columnMeasureInfo;this.props.itemIndex===e.itemIndex&&this.props.item===e.item&&this.props.dragDropHelper===e.dragDropHelper\|\|(this._dragDropSubscription&&(this._dragDropSubscription.dispose(),delete this._dragDropSubscription),this.props.dragDropHelper&&this._root.current&&(this._dragDropSubscription=this.props.dragDropHelper.subscribe(this._root.current,this._events,this._getRowDragDropOptions()))),t&&0<=t.index&&this._cellMeasurer.current&&(e=this._cellMeasurer.current.getBoundingClientRect().width,t.onMeasureDone(e),this.setState({columnMeasureInfo:void 0})),n&&o&&!this._onDidMountCalled&&(this._onDidMountCalled=!0,o(this))},yb.prototype.componentWillUnmount=function(){var e=this.props,t=e.item,e=e.onWillUnmount;e&&t&&e(this),this._dragDropSubscription&&(this._dragDropSubscription.dispose(),delete this._dragDropSubscription),this._events.dispose()},yb.prototype.shouldComponentUpdate=function(e,t){if(this.props.useReducedRowRenderer){var o=Cb(e);return this.state.selectionState.isSelected!==o.isSelected\|\|!da(this.props,e)}return!0},yb.prototype.render=function(){var e=this.props,t=e.className,o=e.columns,n=void 0===o?vb:o,r=e.dragDropEvents,i=e.item,s=e.itemIndex,a=e.id,l=e.flatIndexOffset,c=void 0===l?2:l,u=e.onRenderCheck,d=void 0===u?this._onRenderCheck:u,p=e.onRenderDetailsCheckbox,h=e.onRenderItemColumn,m=e.getCellValueKey,g=e.selectionMode,f=e.rowWidth,v=void 0===f?0:f,b=e.checkboxVisibility,y=e.getRowAriaLabel,C=e.getRowAriaDescription,_=e.getRowAriaDescribedBy,S=e.checkButtonAriaLabel,x=e.checkboxCellClassName,k=e.rowFieldsAs,w=void 0===k?gb:k,I=e.selection,D=e.indentWidth,E=e.enableUpdateAnimations,T=e.compact,P=e.theme,R=e.styles,M=e.cellsByColumn,N=e.groupNestingDepth,B=e.useFastIcons,F=void 0===B\|\|B,A=e.cellStyleProps,L=e.group,H=e.focusZoneProps,O=e.disabled,z=void 0!==O&&O,W=this.state,o=W.columnMeasureInfo,l=W.isDropping,u=this.state.selectionState,f=u.isSelected,k=void 0!==f&&f,B=u.isSelectionModal,e=void 0!==B&&B,O=r?!(!r.canDrag\|\|!r.canDrag(i)):void 0,W=l?this._droppingClassNames\|\|"is-dropping":"",f=y?y(i):void 0,u=C?C(i):void 0,B=_?_(i):void 0,r=!!I&&I.canSelectItem(i,s)&&!z,l=g===dv.multiple,y=g!==dv.none&&b!==kv.hidden,C=g===dv.none?void 0:k,_=L?s-L.startIndex+1:void 0,I=L?L.count:void 0,L=H?H.direction:Ei.horizontal;this._classNames=ht(ht({},this._classNames),fb(R,{theme:P,isSelected:k,canSelect:!l,anySelected:e,checkboxCellClassName:x,droppingClassName:W,className:t,compact:T,enableUpdateAnimations:E,cellStyleProps:A,disabled:z}));t={isMultiline:this._classNames.isMultiline,isRowHeader:this._classNames.isRowHeader,cell:this._classNames.cell,cellAnimation:this._classNames.cellAnimation,cellPadded:this._classNames.cellPadded,cellUnpadded:this._classNames.cellUnpadded,fields:this._classNames.fields};da(this._rowClassNames\|\|{},t)\|\|(this._rowClassNames=t);E=gt.createElement(w,{rowClassNames:this._rowClassNames,rowHeaderId:a+"-header",cellsByColumn:M,columns:n,item:i,itemIndex:s,columnStartIndex:(y?1:0)+(N?1:0),onRenderItemColumn:h,getCellValueKey:m,enableUpdateAnimations:E,cellStyleProps:A}),A=this.props.role\|\|"row";return this._ariaRowDescriptionId=_s("DetailsRow-description"),gt.createElement(Zs,ht({"data-is-focusable":!0},ur(this.props,cr),"boolean"==typeof O?{"data-is-draggable":O,draggable:O}:{},H,{direction:L,elementRef:this._root,componentRef:this._focusZone,role:A,"aria-label":f,"aria-disabled":z\|\|void 0,"aria-describedby":u?this._ariaRowDescriptionId:B,className:this._classNames.root,"data-selection-index":s,"data-selection-touch-invoke":!0,"data-selection-disabled":z\|\|void 0,"data-item-index":s,"aria-rowindex":void 0===_?s+c:void 0,"aria-level":N&&N+1\|\|void 0,"aria-posinset":_,"aria-setsize":I,"data-automationid":"DetailsRow",style:{minWidth:v},"aria-selected":C,allowFocusRoot:!0}),u?gt.createElement("span",{key:"description",role:"presentation",hidden:!0,id:this._ariaRowDescriptionId},u):null,y&&gt.createElement("div",{role:"gridcell","data-selection-toggle":!0,className:this._classNames.checkCell},d({id:a?a+"-checkbox":void 0,selected:k,selectionMode:g,anySelected:e,"aria-label":S,"aria-labelledby":a?a+"-checkbox "+a+"-header":void 0,canSelect:r,compact:T,className:this._classNames.check,theme:P,isVisible:b===kv.always,onRenderDetailsCheckbox:p,useFastIcons:F})),gt.createElement(Mv,{indentWidth:D,role:"gridcell",count:N-(this.props.collapseAllVisibility===yv.hidden?1:0)}),i&&E,o&&gt.createElement("span",{role:"presentation",className:Tr(this._classNames.cellMeasurer,this._classNames.cell),ref:this._cellMeasurer},gt.createElement(w,{rowClassNames:this._rowClassNames,rowHeaderId:a+"-header",columns:[o.column],item:i,itemIndex:s,columnStartIndex:(y?1:0)+(N?1:0)+n.length,onRenderItemColumn:h,getCellValueKey:m})),gt.createElement("span",{role:"checkbox",className:this._classNames.checkCover,"aria-checked":k,"data-selection-toggle":!0}))},yb.prototype.measureCell=function(e,t){var o=this.props.columns,o=ht({},(void 0===o?vb:o)[e]);o.minWidth=0,o.maxWidth=999999,delete o.calculatedWidth,this.setState({columnMeasureInfo:{index:e,column:o,onMeasureDone:t}})},yb.prototype.focus=function(e){var t;return void 0===e&&(e=!1),!(null===(t=this._focusZone.current)\|\|void 0===t\|\|!t.focus(e))},yb.prototype._onRenderCheck=function(e){return gt.createElement(Xv,ht({},e))},yb.prototype._getRowDragDropOptions=function(){var e=this.props,t=e.item,o=e.itemIndex,n=e.dragDropEvents;return{eventMap:e.eventsToRegister,selectionIndex:o,context:{data:t,index:o},canDrag:n.canDrag,canDrop:n.canDrop,onDragStart:n.onDragStart,updateDropState:this._updateDroppingState,onDrop:n.onDrop,onDragEnd:n.onDragEnd,onDragOver:n.onDragOver}},yb);function yb(e){var i=hb.call(this,e)\|\|this;return i._root=gt.createRef(),i._cellMeasurer=gt.createRef(),i._focusZone=gt.createRef(),i._onSelectionChanged=function(){var e=Cb(i.props);da(e,i.state.selectionState)\|\|i.setState({selectionState:e})},i._updateDroppingState=function(e,t){var o=i.state.isDropping,n=i.props,r=n.dragDropEvents,n=n.item;e?r.onDragEnter&&(i._droppingClassNames=r.onDragEnter(n,t)):r.onDragLeave&&r.onDragLeave(n,t),o!==e&&i.setState({isDropping:e})},fi(i),i._events=new va(i),i.state={selectionState:Cb(e),columnMeasureInfo:void 0,isDropping:!1},i._droppingClassNames="",i}function Cb(e){var t=e.itemIndex,e=e.selection;return{isSelected:!(null==e\|\|!e.isIndexSelected(t)),isSelectionModal:!(null===(t=null==e?void 0:e.isModal)\|\|void 0===t\|\|!t.call(e))}}var _b,Sb,xb=In(bb,zv,void 0,{scope:"DetailsRow"}),kb={root:"ms-GroupedList",compact:"ms-GroupedList--Compact",group:"ms-GroupedList-group",link:"ms-Link",listCell:"ms-List-cell"},wb={root:"ms-GroupHeader",compact:"ms-GroupHeader--compact",check:"ms-GroupHeader-check",dropIcon:"ms-GroupHeader-dropIcon",expand:"ms-GroupHeader-expand",isCollapsed:"is-collapsed",title:"ms-GroupHeader-title",isSelected:"is-selected",iconTag:"ms-Icon--Tag",group:"ms-GroupedList-group",isDropping:"is-dropping"},Ib="cubic-bezier(0.390, 0.575, 0.565, 1.000)";(Y=_b=_b\|\|{})[Y.xSmall=0]="xSmall",Y[Y.small=1]="small",Y[Y.medium=2]="medium",Y[Y.large=3]="large",(ke=Sb=Sb\|\|{})[ke.normal=0]="normal",ke[ke.large=1]="large";var Db,Eb,Tb,Pb,Rb=Fn(),Mb=(l(e0,Pb=gt.Component),e0.prototype.render=function(){var e=this.props,t=e.type,o=e.size,n=e.ariaLabel,r=e.ariaLive,i=e.styles,s=e.label,a=e.theme,l=e.className,c=e.labelPosition,u=n,e=ur(this.props,cr,["size"]),n=o;void 0===o&&void 0!==t&&(n=t===Sb.large?_b.large:_b.medium);c=Rb(i,{theme:a,size:n,className:l,labelPosition:c});return gt.createElement("div",ht({},e,{className:c.root}),gt.createElement("div",{className:c.circle}),s&&gt.createElement("div",{className:c.label},s),u&&gt.createElement("div",{role:"status","aria-live":r},gt.createElement(Ri,null,gt.createElement("div",{className:c.screenReaderText},u))))},e0.defaultProps={size:_b.medium,ariaLive:"polite",labelPosition:"bottom"},e0),Nb={root:"ms-Spinner",circle:"ms-Spinner-circle",label:"ms-Spinner-label"},Bb=Ao(function(){return O({"0%":{transform:"rotate(0deg)"},"100%":{transform:"rotate(360deg)"}})}),Fb=In(Mb,function(e){var t=e.theme,o=e.size,n=e.className,r=e.labelPosition,i=t.palette,e=zo(Nb,t);return{root:[e.root,{display:"flex",flexDirection:"column",alignItems:"center",justifyContent:"center"},"top"===r&&{flexDirection:"column-reverse"},"right"===r&&{flexDirection:"row"},"left"===r&&{flexDirection:"row-reverse"},n],circle:[e.circle,{boxSizing:"border-box",borderRadius:"50%",border:"1.5px solid "+i.themeLight,borderTopColor:i.themePrimary,animationName:Bb(),animationDuration:"1.3s",animationIterationCount:"infinite",animationTimingFunction:"cubic-bezier(.53,.21,.29,.67)",selectors:((n={})[Yt]=ht({borderTopColor:"Highlight"},{forcedColorAdjust:"none",MsHighContrastAdjust:"none"}),n)},o===_b.xSmall&&["ms-Spinner--xSmall",{width:12,height:12}],o===_b.small&&["ms-Spinner--small",{width:16,height:16}],o===_b.medium&&["ms-Spinner--medium",{width:20,height:20}],o===_b.large&&["ms-Spinner--large",{width:28,height:28}]],label:[e.label,t.fonts.small,{color:i.themePrimary,margin:"8px 0 0",textAlign:"center"},"top"===r&&{margin:"0 0 8px"},"right"===r&&{margin:"0 0 0 8px"},"left"===r&&{margin:"0 8px 0 0"}],screenReaderText:So}},void 0,{scope:"Spinner"}),Ab=Fn(),K=(l($b,Tb=gt.Component),$b.getDerivedStateFromProps=function(e,t){if(e.group){var o=e.group.isCollapsed,n=e.isGroupLoading,e=!o&&n&&n(e.group);return ht(ht({},t),{isCollapsed:o\|\|!1,isLoadingVisible:e\|\|!1})}return t},$b.prototype.render=function(){var e=this.props,t=e.group,o=e.groupLevel,n=void 0===o?0:o,r=e.viewport,i=e.selectionMode,s=e.loadingText,a=e.isSelected,l=void 0!==a&&a,c=e.selected,u=void 0!==c&&c,d=e.indentWidth,p=e.onRenderTitle,h=void 0===p?this._onRenderTitle:p,m=e.onRenderGroupHeaderCheckbox,g=e.isCollapsedGroupSelectVisible,f=void 0===g\|\|g,v=e.expandButtonProps,b=e.expandButtonIcon,y=e.selectAllButtonProps,C=e.theme,_=e.styles,S=e.className,x=e.compact,o=e.ariaPosInSet,a=e.ariaSetSize,c=e.ariaRowIndex,p=e.useFastIcons?this._fastDefaultCheckboxRender:this._defaultCheckboxRender,g=m?Ma(m,p):p,e=this.state,m=e.isCollapsed,p=e.isLoadingVisible,e=i===dv.multiple,f=e&&(f\|\|!(t&&t.isCollapsed)),u=u\|\|l,l=Pn(C);return this._classNames=Ab(_,{theme:C,className:S,selected:u,isCollapsed:m,compact:x}),t?gt.createElement("div",{className:this._classNames.root,style:r?{minWidth:r.width}:{},onClick:this._onHeaderClick,role:"row","aria-setsize":a,"aria-posinset":o,"aria-rowindex":c,"data-is-focusable":!0,onKeyUp:this._onKeyUp,"aria-label":t.ariaLabel,"aria-labelledby":t.ariaLabel?void 0:this._id,"aria-expanded":!this.state.isCollapsed,"aria-selected":e?u:void 0,"aria-level":n+1},gt.createElement("div",{className:this._classNames.groupHeaderContainer,role:"presentation"},f?gt.createElement("div",{role:"gridcell"},gt.createElement("button",ht({"data-is-focusable":!1,type:"button",className:this._classNames.check,role:"checkbox",id:this._id+"-check","aria-checked":u,"aria-labelledby":this._id+"-check "+this._id,"data-selection-toggle":!0,onClick:this._onToggleSelectGroupClick},y),g({checked:u,theme:C},g))):i!==dv.none&&gt.createElement(Mv,{indentWidth:48,count:1}),gt.createElement(Mv,{indentWidth:d,count:n}),gt.createElement("div",{className:this._classNames.dropIcon,role:"presentation"},gt.createElement(Wr,{iconName:"Tag"})),gt.createElement("div",{role:"gridcell"},gt.createElement("button",ht({"data-is-focusable":!1,type:"button",className:this._classNames.expand,onClick:this._onToggleClick,"aria-expanded":!this.state.isCollapsed},v),gt.createElement(Wr,{className:this._classNames.expandIsCollapsed,iconName:b\|\|(l?"ChevronLeftMed":"ChevronRightMed")}))),h(this.props,this._onRenderTitle),p&&gt.createElement(Fb,{label:s}))):null},$b.prototype._defaultCheckboxRender=function(e){return gt.createElement(qh,{checked:e.checked})},$b.prototype._fastDefaultCheckboxRender=function(e){return gt.createElement(Lb,{theme:e.theme,checked:e.checked})},$b.defaultProps={expandButtonProps:{"aria-label":"expand collapse group"}},$b),Lb=gt.memo(function(e){return gt.createElement(qh,{theme:e.theme,checked:e.checked,className:e.className,useFastIcons:!0})}),Hb=In(K,function(e){var t,o=e.theme,n=e.className,r=e.selected,i=e.isCollapsed,s=e.compact,a=Lv.cellLeftPadding,l=s?40:48,c=o.semanticColors,u=o.palette,d=o.fonts,p=zo(wb,o),h=[bo(o),{cursor:"default",background:"none",backgroundColor:"transparent",border:"none",padding:0}];return{root:[p.root,bo(o),o.fonts.medium,{borderBottom:"1px solid "+c.listBackground,cursor:"default",userSelect:"none",selectors:((t={":hover":{background:c.listItemBackgroundHovered,color:c.actionLinkHovered}})["&:hover ."+p.check]={opacity:1},t["."+go+" &:focus ."+p.check]={opacity:1},t[":global(."+p.group+"."+p.isDropping+")"]={selectors:((e={})["& > ."+p.root+" ."+p.dropIcon]={transition:"transform "+we.durationValue4+" cubic-bezier(0.075, 0.820, 0.165, 1.000) opacity "+we.durationValue1+" "+Ib,transitionDelay:we.durationValue3,opacity:1,transform:"rotate(0.2deg) scale(1);"},e["."+p.check]={opacity:0},e)},t)},r&&[p.isSelected,{background:c.listItemBackgroundChecked,selectors:((c={":hover":{background:c.listItemBackgroundCheckedHovered}})[""+p.check]={opacity:1},c)}],s&&[p.compact,{border:"none"}],n],groupHeaderContainer:[{display:"flex",alignItems:"center",height:l}],headerCount:[{padding:"0px 4px"}],check:[p.check,h,{display:"flex",alignItems:"center",justifyContent:"center",paddingTop:1,marginTop:-1,opacity:0,width:48,height:l,selectors:((n={})["."+go+" &:focus"]={opacity:1},n)}],expand:[p.expand,h,{display:"flex",alignItems:"center",justifyContent:"center",fontSize:d.small.fontSize,width:36,height:l,color:r?u.neutralPrimary:u.neutralSecondary,selectors:{":hover":{backgroundColor:r?u.neutralQuaternary:u.neutralLight},":active":{backgroundColor:r?u.neutralTertiaryAlt:u.neutralQuaternaryAlt}}}],expandIsCollapsed:[i?[p.isCollapsed,{transform:"rotate(0deg)",transformOrigin:"50% 50%",transition:"transform .1s linear"}]:{transform:Pn(o)?"rotate(-90deg)":"rotate(90deg)",transformOrigin:"50% 50%",transition:"transform .1s linear"}],title:[p.title,{paddingLeft:a,fontSize:(s?d.medium:d.mediumPlus).fontSize,fontWeight:i?Fe.regular:Fe.semibold,cursor:"pointer",outline:0,whiteSpace:"nowrap",textOverflow:"ellipsis"}],dropIcon:[p.dropIcon,{position:"absolute",left:-26,fontSize:Ae.large,color:u.neutralSecondary,transition:"transform "+we.durationValue2+" cubic-bezier(0.600, -0.280, 0.735, 0.045), opacity "+we.durationValue4+" "+Ib,opacity:0,transform:"rotate(0.2deg) scale(0.65)",transformOrigin:"10px 10px",selectors:((u={})[":global(."+p.iconTag+")"]={position:"absolute"},u)}]}},void 0,{scope:"GroupHeader"}),Ob={root:"ms-GroupShowAll",link:"ms-Link"},zb=Fn(),Wb=In(function(e){var t=e.group,o=e.groupLevel,n=e.showAllLinkText,r=void 0===n?"Show All":n,i=e.styles,n=e.theme,s=e.onToggleSummarize,i=zb(i,{theme:n}),n=(0,gt.useCallback)(function(e){s(t),e.stopPropagation(),e.preventDefault()},[s,t]);return t?gt.createElement("div",{className:i.root},gt.createElement(Mv,{count:o}),gt.createElement(ua,{onClick:n},r)):null},function(e){var t=e.theme,o=t.fonts,e=zo(Ob,t);return{root:[e.root,{position:"relative",padding:"10px 84px",cursor:"pointer",selectors:((t={})["."+e.link]={fontSize:o.small.fontSize},t)}]}},void 0,{scope:"GroupShowAll"}),Vb={root:"ms-groupFooter"},Kb=Fn(),Gb=In(function(e){var t=e.group,o=e.groupLevel,n=e.footerText,r=e.indentWidth,i=e.styles,e=e.theme,e=Kb(i,{theme:e});return t&&n?gt.createElement("div",{className:e.root},gt.createElement(Mv,{indentWidth:r,count:o}),n):null},function(e){var t=e.theme,o=e.className,e=zo(Vb,t);return{root:[t.fonts.medium,e.root,{position:"relative",padding:"5px 38px"},o]}},void 0,{scope:"GroupFooter"}),Ub=(l(Jb,Eb=gt.Component),Jb.prototype.componentDidMount=function(){var e=this.props,t=e.dragDropHelper,e=e.selection;t&&this._root.current&&(this._dragDropSubscription=t.subscribe(this._root.current,this._events,this._getGroupDragDropOptions())),e&&this._events.on(e,gv,this._onSelectionChange)},Jb.prototype.componentWillUnmount=function(){this._events.dispose(),this._dragDropSubscription&&this._dragDropSubscription.dispose()},Jb.prototype.componentDidUpdate=function(e){this.props.group===e.group&&this.props.groupIndex===e.groupIndex&&this.props.dragDropHelper===e.dragDropHelper\|\|(this._dragDropSubscription&&(this._dragDropSubscription.dispose(),delete this._dragDropSubscription),this.props.dragDropHelper&&this._root.current&&(this._dragDropSubscription=this.props.dragDropHelper.subscribe(this._root.current,this._events,this._getGroupDragDropOptions())))},Jb.prototype.render=function(){var e=this.props,t=e.getGroupItemLimit,o=e.group,n=e.groupIndex,r=e.headerProps,i=e.showAllProps,s=e.footerProps,a=e.viewport,l=e.selectionMode,c=e.onRenderGroupHeader,u=void 0===c?this._onRenderGroupHeader:c,d=e.onRenderGroupShowAll,p=void 0===d?this._onRenderGroupShowAll:d,h=e.onRenderGroupFooter,m=void 0===h?this._onRenderGroupFooter:h,g=e.onShouldVirtualize,f=e.groupedListClassNames,v=e.groups,b=e.compact,c=e.listProps,d=void 0===c?{}:c,h=this.state.isSelected,e=o&&t?t(o):1/0,c=o&&!o.children&&!o.isCollapsed&&!o.isShowingAll&&(o.count>e\|\|o.hasMoreData),t=o&&o.children&&0<o.children.length,d=d.version,b={group:o,groupIndex:n,groupLevel:o?o.level:0,isSelected:h,selected:h,viewport:a,selectionMode:l,groups:v,compact:b},n={groupedListId:this._id,ariaSetSize:v?v.length:void 0,ariaPosInSet:void 0!==n?n+1:void 0},n=ht(ht(ht({},r),b),n),i=ht(ht({},i),b),s=ht(ht({},s),b),b=!!this.props.dragDropHelper&&this._getGroupDragDropOptions().canDrag(o)&&!!this.props.dragDropEvents.canDragGroups;return gt.createElement("div",ht({ref:this._root},b&&{draggable:!0},{className:Tr(f&&f.group,this._getDroppingClassName()),role:"presentation"}),u(n,this._onRenderGroupHeader),o&&o.isCollapsed?null:t?gt.createElement(Wf,{role:"presentation",ref:this._list,items:o?o.children:[],onRenderCell:this._renderSubGroup,getItemCountForPage:this._returnOne,onShouldVirtualize:g,version:d,id:this._id}):this._onRenderGroup(e),o&&o.isCollapsed?null:c&&p(i,this._onRenderGroupShowAll),m(s,this._onRenderGroupFooter))},Jb.prototype.forceUpdate=function(){Eb.prototype.forceUpdate.call(this),this.forceListUpdate()},Jb.prototype.forceListUpdate=function(){var e,t=this.props.group;if(this._list.current){if(this._list.current.forceUpdate(),t&&t.children&&0<t.children.length)for(var o=t.children.length,n=0;n<o;n++)(e=this._list.current.pageRefs["subGroup_"+String(n)])&&e.forceListUpdate()}else(e=this._subGroupRefs["subGroup_"+String(0)])&&e.forceListUpdate()},Jb.prototype._onSelectionChange=function(){var e=this.props,t=e.group,e=e.selection;e&&t&&((t=e.isRangeSelected(t.startIndex,t.count))!==this.state.isSelected&&this.setState({isSelected:t}))},Jb.prototype._onRenderGroupCell=function(o,n,r){return function(e,t){return o(n,e,t,r)}},Jb.prototype._onRenderGroup=function(e){var t=this.props,o=t.group,n=t.items,r=t.onRenderCell,i=t.listProps,s=t.groupNestingDepth,a=t.onShouldVirtualize,l=t.groupProps,c=o&&!o.isShowingAll?o.count:n.length,t=o?o.startIndex:0;return gt.createElement(Wf,ht({role:l&&l.role?l.role:"rowgroup","aria-label":null==o?void 0:o.name,items:n,onRenderCell:this._onRenderGroupCell(r,s,o),ref:this._list,renderCount:Math.min(c,e),startIndex:t,onShouldVirtualize:a,id:this._id},i))},Jb.prototype._returnOne=function(){return 1},Jb.prototype._getGroupKey=function(e,t){return"group-"+(e&&e.key?e.key:String(e.level)+String(t))},Jb.prototype._getDroppingClassName=function(){var e=this.state.isDropping,t=this.props,o=t.group,t=t.groupedListClassNames;return Tr((e=!(!o\|\|!e))&&this._droppingClassName,e&&"is-dropping",e&&t&&t.groupIsDropping)},Jb),jb=Fn(),qb=Hv.rowHeight,Yb=Hv.compactRowHeight,Zb=(l(Qb,Db=gt.Component),Qb.getDerivedStateFromProps=function(e,t){var o=e.groups,n=e.selectionMode,r=e.compact,i=e.items,s=e.listProps,a=s&&s.version,e=ht(ht({},t),{selectionMode:n,compact:r,groups:o,listProps:s}),s=!1;return a===(t.listProps&&t.listProps.version)&&i===t.items&&o===t.groups&&n===t.selectionMode&&r===t.compact\|\|(s=!0),o!==t.groups&&(e=ht(ht({},e),{groups:o})),e=(s=n!==t.selectionMode\|\|r!==t.compact?!0:s)?ht(ht({},e),{version:{}}):e},Qb.prototype.scrollToIndex=function(e,t,o){this._list.current&&this._list.current.scrollToIndex(e,t,o)},Qb.prototype.getStartItemIndexInView=function(){return this._list.current.getStartItemIndexInView()\|\|0},Qb.prototype.componentDidMount=function(){var e=this.props,t=e.groupProps,e=e.groups;t&&t.isAllGroupsCollapsed&&this._setGroupsCollapsedState(void 0===e?[]:e,t.isAllGroupsCollapsed)},Qb.prototype.render=function(){var e=this.props,t=e.className,o=e.usePageCache,n=e.onShouldVirtualize,r=e.theme,i=e.role,s=void 0===i?"treegrid":i,a=e.styles,l=e.compact,c=e.focusZoneProps,u=void 0===c?{}:c,i=e.rootListProps,c=void 0===i?{}:i,e=this.state,i=e.groups,e=e.version;this._classNames=jb(a,{theme:r,className:t,compact:l});l=u.shouldEnterInnerZone,l=void 0===l?this._isInnerZoneKeystroke:l;return gt.createElement(Zs,ht({direction:Ei.vertical,"data-automationid":"GroupedList","data-is-scrollable":"false",role:"presentation"},u,{shouldEnterInnerZone:l,className:Tr(this._classNames.root,u.className)}),i?gt.createElement(Wf,ht({ref:this._list,role:s,items:i,onRenderCell:this._renderGroup,getItemCountForPage:this._returnOne,getPageHeight:this._getPageHeight,getPageSpecification:this._getPageSpecification,usePageCache:o,onShouldVirtualize:n,version:e},c)):this._renderGroup(void 0,0))},Qb.prototype.forceUpdate=function(){Db.prototype.forceUpdate.call(this),this._forceListUpdates()},Qb.prototype.toggleCollapseAll=function(e){var t=this.state.groups,o=void 0===t?[]:t,t=this.props.groupProps,t=t&&t.onToggleCollapseAll;0<o.length&&(t&&t(e),this._setGroupsCollapsedState(o,e),this._updateIsSomeGroupExpanded(),this.forceUpdate())},Qb.prototype._setGroupsCollapsedState=function(e,t){for(var o=0;o<e.length;o++)e[o].isCollapsed=t},Qb.prototype._returnOne=function(){return 1},Qb.prototype._getGroupKey=function(e,t){return"group-"+(e&&e.key?e.key:String(t))},Qb.prototype._getGroupNestingDepth=function(){for(var e=0,t=this.state.groups;t&&0<t.length;)e++,t=t[0].children;return e},Qb.prototype._forceListUpdates=function(e){this.setState({version:{}})},Qb.prototype._computeIsSomeGroupExpanded=function(e){var t=this;return!(!e\|\|!e.some(function(e){return e.children?t._computeIsSomeGroupExpanded(e.children):!e.isCollapsed}))},Qb.prototype._updateIsSomeGroupExpanded=function(){var e=this.state.groups,t=this.props.onGroupExpandStateChanged,e=this._computeIsSomeGroupExpanded(e);this._isSomeGroupExpanded!==e&&(t&&t(e),this._isSomeGroupExpanded=e)},Qb.defaultProps={selectionMode:dv.multiple,isHeaderVisible:!0,groupProps:{},compact:!1},Qb),Xb=In(Zb,function(e){var t=e.theme,o=e.className,n=e.compact,r=t.palette,e=zo(kb,t);return{root:[e.root,t.fonts.small,{position:"relative",selectors:((t={})["."+e.listCell]={minHeight:38},t)},n&&[e.compact,{selectors:((n={})["."+e.listCell]={minHeight:32},n)}],o],group:[e.group,{transition:"background-color "+we.durationValue2+" cubic-bezier(0.445, 0.050, 0.550, 0.950)"}],groupIsDropping:{backgroundColor:r.neutralLight}}},void 0,{scope:"GroupedList"});function Qb(e){var y=Db.call(this,e)\|\|this;y._list=gt.createRef(),y._renderGroup=function(e,t){var o=y.props,n=o.dragDropEvents,r=o.dragDropHelper,i=o.eventsToRegister,s=o.groupProps,a=o.items,l=o.listProps,c=o.onRenderCell,u=o.selectionMode,d=o.selection,p=o.viewport,h=o.onShouldVirtualize,m=o.groups,g=o.compact,f={onToggleSelectGroup:y._onToggleSelectGroup,onToggleCollapse:y._onToggleCollapse,onToggleSummarize:y._onToggleSummarize},v=ht(ht({},s.headerProps),f),b=ht(ht({},s.showAllProps),f),o=ht(ht({},s.footerProps),f),f=y._getGroupNestingDepth();if(!s.showEmptyGroups&&e&&0===e.count)return null;l=ht(ht({},l\|\|{}),{version:y.state.version});return gt.createElement(Ub,{key:y._getGroupKey(e,t),dragDropEvents:n,dragDropHelper:r,eventsToRegister:i,footerProps:o,getGroupItemLimit:s&&s.getGroupItemLimit,group:e,groupIndex:t,groupNestingDepth:f,groupProps:s,headerProps:v,listProps:l,items:a,onRenderCell:c,onRenderGroupHeader:s.onRenderHeader,onRenderGroupShowAll:s.onRenderShowAll,onRenderGroupFooter:s.onRenderFooter,selectionMode:u,selection:d,showAllProps:b,viewport:p,onShouldVirtualize:h,groupedListClassNames:y._classNames,groups:m,compact:g})},y._getDefaultGroupItemLimit=function(e){return e.children&&0<e.children.length?e.children.length:e.count},y._getGroupItemLimit=function(e){var t=y.props.groupProps;return(t&&t.getGroupItemLimit?t.getGroupItemLimit:y._getDefaultGroupItemLimit)(e)},y._getGroupHeight=function(e){var t=y.props.compact?Yb:qb;return t+(e.isCollapsed?0:ty._getGroupItemLimit(e))},y._getPageHeight=function(e){var t=y.state.groups,o=y.props.getGroupHeight,o=void 0===o?y._getGroupHeight:o,t=t&&t[e];return t?o(t,e):0},y._onToggleCollapse=function(e){var t=y.props.groupProps,t=t&&t.headerProps&&t.headerProps.onToggleCollapse;e&&(t&&t(e),e.isCollapsed=!e.isCollapsed,y._updateIsSomeGroupExpanded(),y.forceUpdate())},y._onToggleSelectGroup=function(e){var t=y.props,o=t.selection,t=t.selectionMode;e&&o&&t===dv.multiple&&o.toggleRangeSelected(e.startIndex,e.count)},y._isInnerZoneKeystroke=function(e){return e.which===Mn(En.right)},y._onToggleSummarize=function(e){var t=y.props.groupProps,t=t&&t.showAllProps&&t.showAllProps.onToggleSummarize;t?t(e):(e&&(e.isShowingAll=!e.isShowingAll),y.forceUpdate())},y._getPageSpecification=function(e){var t=y.state.groups,e=t&&t[e];return{key:e&&e.key}},fi(y),y._isSomeGroupExpanded=y._computeIsSomeGroupExpanded(e.groups);var t=e.listProps,t=(void 0===t?{}:t).version;return y.state={groups:e.groups,items:e.items,listProps:e.listProps,version:void 0===t?{}:t},y}function Jb(e){var x=Eb.call(this,e)\|\|this;x._root=gt.createRef(),x._list=gt.createRef(),x._subGroupRefs={},x._droppingClassName="",x._onRenderGroupHeader=function(e){return gt.createElement(Hb,ht({},e))},x._onRenderGroupShowAll=function(e){return gt.createElement(Wb,ht({},e))},x._onRenderGroupFooter=function(e){return gt.createElement(Gb,ht({},e))},x._renderSubGroup=function(e,t){var o=x.props,n=o.dragDropEvents,r=o.dragDropHelper,i=o.eventsToRegister,s=o.getGroupItemLimit,a=o.groupNestingDepth,l=o.groupProps,c=o.items,u=o.headerProps,d=o.showAllProps,p=o.footerProps,h=o.listProps,m=o.onRenderCell,g=o.selection,f=o.selectionMode,v=o.viewport,b=o.onRenderGroupHeader,y=o.onRenderGroupShowAll,C=o.onRenderGroupFooter,_=o.onShouldVirtualize,S=o.group,o=o.compact,a=e.level?e.level+1:a;return!e\|\|0<e.count\|\|l&&l.showEmptyGroups?gt.createElement(Jb,{ref:function(e){return x._subGroupRefs["subGroup_"+t]=e},key:x._getGroupKey(e,t),dragDropEvents:n,dragDropHelper:r,eventsToRegister:i,footerProps:p,getGroupItemLimit:s,group:e,groupIndex:t,groupNestingDepth:a,groupProps:l,headerProps:u,items:c,listProps:h,onRenderCell:m,selection:g,selectionMode:f,showAllProps:d,viewport:v,onRenderGroupHeader:b,onRenderGroupShowAll:y,onRenderGroupFooter:C,onShouldVirtualize:_,groups:S?S.children:[],compact:o}):null},x._getGroupDragDropOptions=function(){var e=x.props,t=e.group,o=e.groupIndex,n=e.dragDropEvents;return{eventMap:e.eventsToRegister,selectionIndex:-1,context:{data:t,index:o,isGroup:!0},updateDropState:x._updateDroppingState,canDrag:n.canDrag,canDrop:n.canDrop,onDrop:n.onDrop,onDragStart:n.onDragStart,onDragEnter:n.onDragEnter,onDragLeave:n.onDragLeave,onDragEnd:n.onDragEnd,onDragOver:n.onDragOver}},x._updateDroppingState=function(e,t){var o=x.state.isDropping,n=x.props,r=n.dragDropEvents,n=n.group;o!==e&&(o?r&&r.onDragLeave&&r.onDragLeave(n,t):r&&r.onDragEnter&&(x._droppingClassName=r.onDragEnter(n,t)),x.setState({isDropping:e}))};var t=e.selection,e=e.group;return fi(x),x._id=_s("GroupedListSection"),x.state={isDropping:!1,isSelected:!(!t\|\|!e)&&t.isRangeSelected(e.startIndex,e.count)},x._events=new va(x),x}function $b(e){var r=Tb.call(this,e)\|\|this;return r._toggleCollapse=function(){var e=r.props,t=e.group,o=e.onToggleCollapse,n=e.isGroupLoading,e=!r.state.isCollapsed,n=!e&&n&&n(t);r.setState({isCollapsed:e,isLoadingVisible:n}),o&&o(t)},r._onKeyUp=function(e){var t=r.props,o=t.group,t=t.onGroupHeaderKeyUp;t&&t(e,o),e.defaultPrevented\|\|(o=r.state.isCollapsed&&e.which===Mn(En.right,r.props.theme),(!r.state.isCollapsed&&e.which===Mn(En.left,r.props.theme)\|\|o)&&(r._toggleCollapse(),e.stopPropagation(),e.preventDefault()))},r._onToggleClick=function(e){r._toggleCollapse(),e.stopPropagation(),e.preventDefault()},r._onToggleSelectGroupClick=function(e){var t=r.props,o=t.onToggleSelectGroup,t=t.group;o&&o(t),e.preventDefault(),e.stopPropagation()},r._onHeaderClick=function(){var e=r.props,t=e.group,o=e.onGroupHeaderClick,e=e.onToggleSelectGroup;o?o(t):e&&e(t)},r._onRenderTitle=function(e){var t=e.group,e=e.ariaColSpan;return t?gt.createElement("div",{className:r._classNames.title,id:r._id,role:"gridcell","aria-colspan":e},gt.createElement("span",null,t.name),gt.createElement("span",{className:r._classNames.headerCount},"(",t.count,t.hasMoreData&&"+",")")):null},r._id=_s("GroupHeader"),r.state={isCollapsed:r.props.group&&r.props.group.isCollapsed,isLoadingVisible:!1},r}function e0(){return null!==Pb&&Pb.apply(this,arguments)\|\|this}function t0(e){var t;return e&&(e===window?t={left:0,top:0,width:window.innerWidth,height:window.innerHeight,right:window.innerWidth,bottom:window.innerHeight}:e.getBoundingClientRect&&(t=e.getBoundingClientRect())),t}function o0(t){return l(e,o=du),e.prototype.componentDidMount=function(){var e=this,t=this.props,o=t.delayFirstMeasure,n=t.disableResizeObserver,r=t.skipViewportMeasures,t=qe(this._root.current);this._onAsyncResize=this._async.debounce(this._onAsyncResize,500,{leading:!1}),r\|\|(!n&&this._isResizeObserverAvailable()?this._registerResizeObserver():this._events.on(t,"resize",this._onAsyncResize),o?this._async.setTimeout(function(){e._updateViewport()},500):this._updateViewport())},e.prototype.componentDidUpdate=function(e){var t=e.skipViewportMeasures,o=this.props,n=o.disableResizeObserver,e=o.skipViewportMeasures,o=qe(this._root.current);e!==t&&(e?(this._unregisterResizeObserver(),this._events.off(o,"resize",this._onAsyncResize)):(!n&&this._isResizeObserverAvailable()?this._viewportResizeObserver\|\|this._registerResizeObserver():this._events.on(o,"resize",this._onAsyncResize),this._updateViewport()))},e.prototype.componentWillUnmount=function(){this._events.dispose(),this._async.dispose(),this._unregisterResizeObserver()},e.prototype.render=function(){var e=this.state.viewport,e=0<e.width&&0<e.height?e:void 0;return gt.createElement("div",{className:"ms-Viewport",ref:this._root,style:{minWidth:1,minHeight:1}},gt.createElement(t,ht({ref:this._updateComposedComponentRef,viewport:e},this.props)))},e.prototype.forceUpdate=function(){this._updateViewport(!0)},e.prototype._onAsyncResize=function(){this._updateViewport()},e.prototype._isResizeObserverAvailable=function(){var e=qe(this._root.current);return e&&e.ResizeObserver},e;function e(e){var r=o.call(this,e)\|\|this;return r._root=gt.createRef(),r._registerResizeObserver=function(){var e=qe(r._root.current);r._viewportResizeObserver=new e.ResizeObserver(r._onAsyncResize),r._viewportResizeObserver.observe(r._root.current)},r._unregisterResizeObserver=function(){r._viewportResizeObserver&&(r._viewportResizeObserver.disconnect(),delete r._viewportResizeObserver)},r._updateViewport=function(e){var t=r.state.viewport,o=r._root.current,n=t0(Ns(o)),o=t0(o);((o&&o.width)!==t.width\|\|(n&&n.height)!==t.height)&&r._resizeAttempts<3&&o&&n?(r._resizeAttempts++,r.setState({viewport:{width:o.width,height:n.height}},function(){r._updateViewport(e)})):(r._resizeAttempts=0,e&&r._composedComponentInstance&&r._composedComponentInstance.forceUpdate())},r._async=new Si(r),r._events=new va(r),r._resizeAttempts=0,r.state={viewport:{width:0,height:0}},r}var o}function n0(i){var s,a=i.selection,e=i.ariaLabelForListHeader,t=i.ariaLabelForSelectAllCheckbox,o=i.ariaLabelForSelectionColumn,n=i.className,l=i.checkboxVisibility,c=i.compact,r=i.constrainMode,u=i.dragDropEvents,d=i.groups,p=i.groupProps,h=i.indentWidth,m=i.items,g=i.isPlaceholderData,f=i.isHeaderVisible,v=i.layoutMode,b=i.onItemInvoked,y=i.onItemContextMenu,C=i.onColumnHeaderClick,_=i.onColumnHeaderContextMenu,S=void 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e}(),De=(s=d,gt.useMemo(function(){var e={};if(s)for(var t=1,o=1,n=0,r=s;n<r.length;n++){var i=r[n];e[i.key]={numOfGroupHeadersBeforeItem:o,totalRowCount:t},o++,t+=i.count+1}return e},[s])),Ee=gt.useMemo(function(){return ht({renderedWindowsAhead:G?0:2,renderedWindowsBehind:G?0:2,getKey:T,version:j},P)},[G,T,j,P]),Te=Yv.none;S===dv.single&&(Te=Yv.hidden),S===dv.multiple&&(Te=(Je=void 0===(Je=p&&p.headerProps&&p.headerProps.isCollapsedGroupSelectVisible)?!0:Je)\|\|!d\|\|U?Yv.visible:Yv.hidden),l===kv.hidden&&(Te=Yv.none);var Pe=gt.useCallback(function(e){return gt.createElement(mb,ht({},e))},[]),Re=gt.useCallback(function(){return null},[]),Me=i.onRenderDetailsHeader,Ne=gt.useMemo(function(){return Me?Ma(Me,Pe):Pe},[Me,Pe]),Be=i.onRenderDetailsFooter,Fe=gt.useMemo(function(){return 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e.which===Mn(En.right,L)},[L]),le=ht(ht({},xe),{componentRef:xe&&xe.componentRef?xe.componentRef:Z,className:Ve.focusZone,direction:xe?xe.direction:Ei.vertical,shouldEnterInnerZone:xe&&xe.shouldEnterInnerZone?xe.shouldEnterInnerZone:U,onActiveElementChanged:xe&&xe.onActiveElementChanged?xe.onActiveElementChanged:ae,shouldRaiseClicksOnEnter:!1,onBlur:xe&&xe.onBlur?xe.onBlur:le}),R=d?gt.createElement(Xb,{focusZoneProps:le,componentRef:Q,groups:d,groupProps:qe,items:m,onRenderCell:Qe,role:"presentation",selection:a,selectionMode:l!==kv.hidden?S:dv.none,dragDropEvents:u,dragDropHelper:W,eventsToRegister:D,listProps:Ee,onGroupExpandStateChanged:$,usePageCache:R,onShouldVirtualize:M,getGroupHeight:F,compact:c}):gt.createElement(Zs,ht({},le),gt.createElement(Wf,ht({ref:Y,role:"presentation",items:m,onRenderCell:Je(0),usePageCache:R,onShouldVirtualize:M},Ee))),M=gt.useCallback(function(e){e.which===En.down&&Z.current&&Z.current.focus()&&(0===a.getSelectedIndices().length&&a.setIndexSelected(0,!0,!1),e.preventDefault(),e.stopPropagation())},[a,Z]),Ee=gt.useCallback(function(e){e.which!==En.up\|\|e.altKey\|\|J.current&&J.current.focus()&&(e.preventDefault(),e.stopPropagation())},[J]);return gt.createElement("div",ht({ref:q,className:Ve.root,"data-automationid":"DetailsList","data-is-scrollable":"false","aria-label":w},E?{role:"application"}:{}),gt.createElement(na,null),gt.createElement("div",{role:ke,"aria-label":I,"aria-rowcount":g?-1:ze,"aria-colcount":We,"aria-readonly":"true","aria-busy":g},gt.createElement("div",{onKeyDown:M,role:"presentation",className:Ve.headerWrapper},f&&Ne({componentRef:J,selectionMode:S,layoutMode:v,selection:a,columns:V,onColumnClick:C,onColumnContextMenu:_,onColumnResized:re,onColumnIsSizingChanged:ee,onColumnAutoResized:ie,groupNestingDepth:Ie,isAllCollapsed:K,onToggleCollapseAll:se,ariaLabel:e,ariaLabelForSelectAllCheckbox:t,ariaLabelForSelectionColumn:o,selectAllVisibility:Te,collapseAllVisibility:p&&p.collapseAllVisibility,viewport:N,columnReorderProps:Oe,minimumPixelsForDrag:B,cellStyleProps:H,checkboxVisibility:l,indentWidth:h,onRenderDetailsCheckbox:O,rowWidth:Ye(V),useFastIcons:z},Ne)),gt.createElement("div",{onKeyDown:Ee,role:"presentation",className:Ve.contentWrapper},ne?R:gt.createElement(Pv,ht({ref:Se,selection:a,selectionPreservedOnEmptyClick:x,selectionMode:S,onItemInvoked:b,onItemContextMenu:y,enterModalOnTouch:Ce},k\|\|{}),R)),Fe(ht({},Ae))))}var r0,i0=Fn(),s0=100,a0=(l(l0,r0=gt.Component),l0.getDerivedStateFromProps=function(e,t){return t.getDerivedStateFromProps(e,t)},l0.prototype.scrollToIndex=function(e,t,o){this._list.current&&this._list.current.scrollToIndex(e,t,o),this._groupedList.current&&this._groupedList.current.scrollToIndex(e,t,o)},l0.prototype.focusIndex=function(e,t,o,n){void 0===t&&(t=!1);var r=this.props.items[e];r&&(this.scrollToIndex(e,o,n),e=this._getItemKey(r,e),(e=this._activeRows[e])&&this._setFocusToRow(e,t))},l0.prototype.getStartItemIndexInView=function(){return this._list&&this._list.current?this._list.current.getStartItemIndexInView():this._groupedList&&this._groupedList.current?this._groupedList.current.getStartItemIndexInView():0},l0.prototype.updateColumn=function(t,e){var o=this.props,n=o.columns,r=void 0===n?[]:n,i=o.selectionMode,s=o.checkboxVisibility,a=o.columnReorderOptions,n=e.width,o=e.newColumnIndex,e=r.findIndex(function(e){return e.key===t.key});n&&this._onColumnResized(t,n,e),void 0!==o&&a&&(n=i===dv.none\|\|s===kv.hidden,i=(s!==kv.hidden?2:1)+e,s=n?i-1:i-2,i=null!==(e=a.frozenColumnCountFromStart)&&void 0!==e?e:0,e=null!==(e=a.frozenColumnCountFromEnd)&&void 0!==e?e:0,i<=(o=n?o-1:o-2)&&o<r.length-e&&(a.onColumnDrop?a.onColumnDrop({draggedIndex:s,targetIndex:o}):a.handleColumnReorder&&a.handleColumnReorder(s,o)))},l0.prototype.componentWillUnmount=function(){this._dragDropHelper&&this._dragDropHelper.dispose(),this._async.dispose()},l0.prototype.componentDidUpdate=function(e,t){var o,n,r;this._notifyColumnsResized(),void 0!==this._initialFocusedIndex&&(n=this.props.items[this._initialFocusedIndex])&&(r=this._getItemKey(n,this._initialFocusedIndex),(o=this._activeRows[r])&&this._setFocusToRowIfPending(o)),this.props.items!==e.items&&0<this.props.items.length&&-1!==this.state.focusedItemIndex&&!$i(this._root.current,document.activeElement,!1)&&(e=this.state.focusedItemIndex<this.props.items.length?this.state.focusedItemIndex:this.props.items.length-1,n=this.props.items[e],r=this._getItemKey(n,this.state.focusedItemIndex),(o=this._activeRows[r])?this._setFocusToRow(o):this._initialFocusedIndex=e),this.props.onDidUpdate&&this.props.onDidUpdate(this)},l0.prototype.render=function(){return gt.createElement(n0,ht({},this.props,this.state,{selection:this._selection,dragDropHelper:this._dragDropHelper,rootRef:this._root,listRef:this._list,groupedListRef:this._groupedList,focusZoneRef:this._focusZone,headerRef:this._header,selectionZoneRef:this._selectionZone,onGroupExpandStateChanged:this._onGroupExpandStateChanged,onColumnIsSizingChanged:this._onColumnIsSizingChanged,onRowDidMount:this._onRowDidMount,onRowWillUnmount:this._onRowWillUnmount,onColumnResized:this._onColumnResized,onColumnAutoResized:this._onColumnAutoResized,onToggleCollapse:this._onToggleCollapse,onActiveRowChanged:this._onActiveRowChanged,onBlur:this._onBlur,onRenderDefaultRow:this._onRenderRow}))},l0.prototype.forceUpdate=function(){r0.prototype.forceUpdate.call(this),this._forceListUpdates()},l0.prototype._getGroupNestingDepth=function(){for(var e=0,t=this.props.groups;t&&0<t.length;)e++,t=t[0].children;return e},l0.prototype._setFocusToRowIfPending=function(e){var t=e.props.itemIndex;void 0!==this._initialFocusedIndex&&t===this._initialFocusedIndex&&(this._setFocusToRow(e),delete this._initialFocusedIndex)},l0.prototype._setFocusToRow=function(e,t){void 0===t&&(t=!1),this._selectionZone.current&&this._selectionZone.current.ignoreNextFocus(),this._async.setTimeout(function(){e.focus(t)},0)},l0.prototype._forceListUpdates=function(){this._groupedList.current&&this._groupedList.current.forceUpdate(),this._list.current&&this._list.current.forceUpdate()},l0.prototype._notifyColumnsResized=function(){this.state.adjustedColumns.forEach(function(e){e.onColumnResize&&e.onColumnResize(e.currentWidth)})},l0.prototype._adjustColumns=function(e,t,o,n){o=this._getAdjustedColumns(e,t,o,n),n=this.props.viewport,n=n&&n.width?n.width:0;return ht(ht({},t),{adjustedColumns:o,lastWidth:n})},l0.prototype._getAdjustedColumns=function(e,t,o,n){var r,i=this,s=e.items,a=e.layoutMode,l=e.selectionMode,c=e.viewport,u=c&&c.width?c.width:0,d=e.columns,p=this.props?this.props.columns:[],c=t?t.lastWidth:-1,t=t?t.lastSelectionMode:void 0;return o\|\|c!==u\|\|t!==l\|\|p&&d!==p?(d=d\|\|c0(s,!0),a===xv.fixedColumns?(r=this._getFixedColumns(d,u,e)).forEach(function(e){i._rememberCalculatedWidth(e,e.calculatedWidth)}):(r=this._getJustifiedColumns(d,u,e)).forEach(function(e){i._getColumnOverride(e.key).currentWidth=e.calculatedWidth}),r):d\|\|[]},l0.prototype._getFixedColumns=function(e,t,o){var n=this,r=this.props,i=r.selectionMode,s=void 0===i?this._selection.mode:i,a=r.checkboxVisibility,i=r.flexMargin,l=r.skipViewportMeasures,c=t-(i\|\|0),u=0;e.forEach(function(e){l\|\|!e.flexGrow?c-=e.maxWidth\|\|e.minWidth\|\|s0:(c-=e.minWidth\|\|s0,u+=e.flexGrow),c-=u0(e,o,!0)});var s=s!==dv.none&&a!==kv.hidden?48:0,a=36this._getGroupNestingDepth(),d=(c-=s+a)/u;return l\|\|e.forEach(function(e){var t,o=ht(ht({},e),n._columnOverrides[e.key]);o.flexGrow&&o.maxWidth&&(0<(e=(t=o.flexGrowd+o.minWidth)-o.maxWidth)&&(c+=e,u-=e/(t-o.minWidth)o.flexGrow))}),d=0<c?c/u:0,e.map(function(e){e=ht(ht({},e),n._columnOverrides[e.key]);return!l&&e.flexGrow&&c<=0\|\|e.calculatedWidth\|\|(!l&&e.flexGrow?(e.calculatedWidth=e.minWidth+e.flexGrowd,e.calculatedWidth=Math.min(e.calculatedWidth,e.maxWidth\|\|Number.MAX_VALUE)):e.calculatedWidth=e.maxWidth\|\|e.minWidth\|\|s0),e})},l0.prototype._getJustifiedColumns=function(e,t,n){var r=this,o=n.selectionMode,i=void 0===o?this._selection.mode:o,o=n.checkboxVisibility,i=i!==dv.none&&o!==kv.hidden?48:0,o=36this._getGroupNestingDepth(),s=0,a=0,l=t-(i+o),c=e.map(function(e,t){var o=ht(ht({},e),{calculatedWidth:e.minWidth\|\|s0}),e=ht(ht({},o),r._columnOverrides[e.key]);return o.isCollapsible\|\|o.isCollapsable\|\|(a+=u0(o,n)),s+=u0(e,n),e});if(l<a)return c;for(var u=c.length-1;0<=u&&l<s;){var d,p=(f=c[u]).minWidth\|\|s0,h=s-l;f.calculatedWidth-p>=h\|\|!f.isCollapsible&&!f.isCollapsable?(d=f.calculatedWidth,f.calculatedWidth=Math.max(f.calculatedWidth-h,p),s-=d-f.calculatedWidth):(s-=u0(f,n),c.splice(u,1)),u--}for(var m=0;m<c.length&&s<l;m++){var g,f=c[m],v=m===c.length-1,b=this._columnOverrides[f.key];b&&b.calculatedWidth&&!v\|\|(g=l-s,b=void 0,b=v?g:(v=f.maxWidth,p=f.minWidth\|\|v\|\|s0,v?Math.min(g,v-p):g),f.calculatedWidth=f.calculatedWidth+b,s+=b)}return c},l0.prototype._rememberCalculatedWidth=function(e,t){e=this._getColumnOverride(e.key);e.calculatedWidth=t,e.currentWidth=t},l0.prototype._getColumnOverride=function(e){return this._columnOverrides[e]=this._columnOverrides[e]\|\|{}},l0.prototype._getItemKey=function(e,t){var o=this.props.getKey,n=void 0;return e&&(n=e.key),n=(n=o?o(e,t):n)\|\|t},l0.defaultProps={layoutMode:xv.justified,selectionMode:dv.multiple,constrainMode:_v.horizontalConstrained,checkboxVisibility:kv.onHover,isHeaderVisible:!0,compact:!1,useFastIcons:!0},c([o0],l0));function l0(e){var h=r0.call(this,e)\|\|this;return h._root=gt.createRef(),h._header=gt.createRef(),h._groupedList=gt.createRef(),h._list=gt.createRef(),h._focusZone=gt.createRef(),h._selectionZone=gt.createRef(),h._onRenderRow=function(e,t){return gt.createElement(xb,ht({},e))},h._getDerivedStateFromProps=function(e,t){var o=h.props,n=o.checkboxVisibility,r=o.items,i=o.setKey,s=o.selectionMode,a=void 0===s?h._selection.mode:s,l=o.columns,c=o.viewport,u=o.compact,d=o.dragDropEvents,p=(h.props.groupProps\|\|{}).isAllGroupsCollapsed,s=void 0===p?void 0:p,o=e.viewport&&e.viewport.width\|\|0,p=c&&c.width\|\|0,c=e.setKey!==i\|\|void 0===e.setKey,i=!1;e.layoutMode!==h.props.layoutMode&&(i=!0);return c&&(h._initialFocusedIndex=e.initialFocusedIndex,t=ht(ht({},t),{focusedItemIndex:void 0!==h._initialFocusedIndex?h._initialFocusedIndex:-1})),h.props.disableSelectionZone\|\|e.items===r\|\|h._selection.setItems(e.items,c),e.checkboxVisibility===n&&e.columns===l&&o===p&&e.compact===u\|\|(i=!0),t=ht(ht({},t),h._adjustColumns(e,t,!0)),e.selectionMode!==a&&(i=!0),void 0===s&&e.groupProps&&void 0!==e.groupProps.isAllGroupsCollapsed&&(t=ht(ht({},t),{isCollapsed:e.groupProps.isAllGroupsCollapsed,isSomeGroupExpanded:!e.groupProps.isAllGroupsCollapsed})),e.dragDropEvents!==d&&(h._dragDropHelper&&h._dragDropHelper.dispose(),h._dragDropHelper=e.dragDropEvents?new Qv({selection:h._selection,minimumPixelsForDrag:e.minimumPixelsForDrag}):void 0,i=!0),t=i?ht(ht({},t),{version:{}}):t},h._onGroupExpandStateChanged=function(e){h.setState({isSomeGroupExpanded:e})},h._onColumnIsSizingChanged=function(e,t){h.setState({isSizing:t})},h._onRowDidMount=function(e){var t=e.props,o=t.item,n=t.itemIndex,t=h._getItemKey(o,n);h._activeRows[t]=e,h._setFocusToRowIfPending(e);e=h.props.onRowDidMount;e&&e(o,n)},h._onRowWillUnmount=function(e){var t=h.props.onRowWillUnmount,o=e.props,n=o.item,e=o.itemIndex,o=h._getItemKey(n,e);delete h._activeRows[o],t&&t(n,e)},h._onToggleCollapse=function(e){h.setState({isCollapsed:e}),h._groupedList.current&&h._groupedList.current.toggleCollapseAll(e)},h._onColumnResized=function(e,t,o){t=Math.max(e.minWidth\|\|s0,t);h.props.onColumnResize&&h.props.onColumnResize(e,t,o),h._rememberCalculatedWidth(e,t),h.setState(ht(ht({},h._adjustColumns(h.props,h.state,!0,o)),{version:{}}))},h._onColumnAutoResized=function(t,o){var e,n=0,r=0,i=Object.keys(h._activeRows).length;for(e in h._activeRows)h._activeRows.hasOwnProperty(e)&&h._activeRows[e].measureCell(o,function(e){n=Math.max(n,e),++r===i&&h._onColumnResized(t,n,o)})},h._onActiveRowChanged=function(e,t){var o=h.props,n=o.items,o=o.onActiveItemChanged;e&&e.getAttribute("data-item-index")&&(0<=(e=Number(e.getAttribute("data-item-index")))&&(o&&o(n[e],e,t),h.setState({focusedItemIndex:e})))},h._onBlur=function(e){h.setState({focusedItemIndex:-1})},fi(h),h._async=new Si(h),h._activeRows={},h._columnOverrides={},h.state={focusedItemIndex:-1,lastWidth:0,adjustedColumns:h._getAdjustedColumns(e,void 0),isSizing:!1,isCollapsed:e.groupProps&&e.groupProps.isAllGroupsCollapsed,isSomeGroupExpanded:e.groupProps&&!e.groupProps.isAllGroupsCollapsed,version:{},getDerivedStateFromProps:h._getDerivedStateFromProps},h._selection=e.selection\|\|new fv({onSelectionChanged:void 0,getKey:e.getKey,selectionMode:e.selectionMode}),h.props.disableSelectionZone\|\|h._selection.setItems(e.items,!1),h._dragDropHelper=e.dragDropEvents?new Qv({selection:h._selection,minimumPixelsForDrag:e.minimumPixelsForDrag}):void 0,h._initialFocusedIndex=e.initialFocusedIndex,h}function c0(e,t,o,n,r,i,s,a){var l=[];if(e&&e.length){var c,u=e[0];for(c in u)u.hasOwnProperty(c)&&l.push({key:c,name:c,fieldName:c,minWidth:s0,maxWidth:300,isCollapsable:!!l.length,isCollapsible:!!l.length,isMultiline:void 0!==s&&s,isSorted:n===c,isSortedDescending:!!r,isRowHeader:!1,columnActionsMode:null!=a?a:Cv.clickable,isResizable:t,onColumnClick:o,isGrouped:i===c})}return l}function u0(e,t,o){t=t.cellStyleProps,t=void 0===t?Lv:t;return(o?0:e.calculatedWidth)+t.cellLeftPadding+t.cellRightPadding+(e.isPadded?t.cellExtraRightPadding:0)}var d0,p0={root:"ms-DetailsList",compact:"ms-DetailsList--Compact",contentWrapper:"ms-DetailsList-contentWrapper",headerWrapper:"ms-DetailsList-headerWrapper",isFixed:"is-fixed",isHorizontalConstrained:"is-horizontalConstrained",listCell:"ms-List-cell"},h0=In(a0,function(e){var t=e.theme,o=e.className,n=e.isHorizontalConstrained,r=e.compact,i=e.isFixed,s=t.semanticColors,e=zo(p0,t);return{root:[e.root,t.fonts.small,{position:"relative",color:s.listText,selectors:((s={})["& 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e=this.props,t=e.isDarkThemed,o=e.className,n=e.theme,r=e.styles,e=ur(this.props,cr),t=b0(r,{theme:n,className:o,isDark:t});return gt.createElement("div",ht({},e,{className:t.root}))},D0),C0={root:"ms-Overlay",rootDark:"ms-Overlay--dark"},_0=In(y0,function(e){var t=e.className,o=e.theme,n=e.isNone,r=e.isDark,i=o.palette,e=zo(C0,o);return{root:[e.root,o.fonts.medium,{backgroundColor:i.whiteTranslucent40,top:0,right:0,bottom:0,left:0,position:"absolute",selectors:((o={})[Yt]={border:"1px solid WindowText",opacity:0},o)},n&&{visibility:"hidden"},r&&[e.rootDark,{backgroundColor:i.blackTranslucent40}],t]}},void 0,{scope:"Overlay"}),S0=Ao(function(e,t){return{root:j(e,t&&{touchAction:"none",selectors:{"& 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0===this._touchId\|\|t){e=t\|\|e;return{x:e.clientX,y:e.clientY}}},I0.prototype._getActiveTouch=function(e){return e.targetTouches&&this._findTouchInTouchList(e.targetTouches)\|\|e.changedTouches&&this._findTouchInTouchList(e.changedTouches)},I0.prototype._getTouchId=function(e){e=e.targetTouches&&e.targetTouches[0]\|\|e.changedTouches&&e.changedTouches[0];if(e)return e.identifier},I0.prototype._matchesSelector=function(e,t){if(!e\|\|e===document.body)return!1;var o=e.matches\|\|e.webkitMatchesSelector\|\|e.msMatchesSelector;return!!o&&(o.call(e,t)\|\|this._matchesSelector(e.parentElement,t))},I0.prototype._findTouchInTouchList=function(e){if(void 0!==this._touchId)for(var t=0;t<e.length;t++)if(e[t].identifier===this._touchId)return e[t]},I0.prototype._createDragDataFromPosition=function(e){var t=this.state.lastPosition;return void 0===t?{delta:{x:0,y:0},lastPosition:e,position:e}:{delta:{x:e.x-t.x,y:e.y-t.y},lastPosition:t,position:e}},I0.prototype._createUpdatedDragData=function(e){var t=this.state.position;return{position:{x:t.x+e.delta.x,y:t.y+e.delta.y},delta:e.delta,lastPosition:t}},I0);function I0(e){var r=m0.call(this,e)\|\|this;return r._currentEventType=k0,r._events=[],r._onMouseDown=function(e){var t=gt.Children.only(r.props.children).props.onMouseDown;return t&&t(e),r._currentEventType=k0,r._onDragStart(e)},r._onMouseUp=function(e){var t=gt.Children.only(r.props.children).props.onMouseUp;return t&&t(e),r._currentEventType=k0,r._onDragStop(e)},r._onTouchStart=function(e){var t=gt.Children.only(r.props.children).props.onTouchStart;return t&&t(e),r._currentEventType=x0,r._onDragStart(e)},r._onTouchEnd=function(e){var t=gt.Children.only(r.props.children).props.onTouchEnd;t&&t(e),r._currentEventType=x0,r._onDragStop(e)},r._onDragStart=function(e){if("number"==typeof e.button&&0!==e.button)return!1;var t,o;r.props.handleSelector&&!r._matchesSelector(e.target,r.props.handleSelector)\|\|r.props.preventDragSelector&&r._matchesSelector(e.target,r.props.preventDragSelector)\|\|(r._touchId=r._getTouchId(e),void 0!==(t=r._getControlPosition(e))&&(o=r._createDragDataFromPosition(t),r.props.onStart&&r.props.onStart(e,o),r.setState({isDragging:!0,lastPosition:t}),r._events=[Wa(document.body,r._currentEventType.move,r._onDrag,!0),Wa(document.body,r._currentEventType.stop,r._onDragStop,!0)]))},r._onDrag=function(e){"touchmove"===e.type&&e.preventDefault();var t,o,n=r._getControlPosition(e);n&&(o=(t=r._createUpdatedDragData(r._createDragDataFromPosition(n))).position,r.props.onDragChange&&r.props.onDragChange(e,t),r.setState({position:o,lastPosition:n}))},r._onDragStop=function(e){var t;!r.state.isDragging\|\|(t=r._getControlPosition(e))&&(t=r._createDragDataFromPosition(t),r.setState({isDragging:!1,lastPosition:void 0}),r.props.onStop&&r.props.onStop(e,t),r.props.position&&r.setState({position:r.props.position}),r._events.forEach(function(e){return e()}))},r.state={isDragging:!1,position:r.props.position\|\|{x:0,y:0},lastPosition:void 0},r}function D0(e){var t=g0.call(this,e)\|\|this;fi(t);e=t.props.allowTouchBodyScroll;return t._allowTouchBodyScroll=void 0!==e&&e,t}function E0(e){var t=gt.useState(e),e=t[0],o=t[1];return[e,{setTrue:_l(function(){return function(){o(!0)}}),setFalse:_l(function(){return function(){o(!1)}}),toggle:_l(function(){return function(){o(function(e){return!e})}})}]}var T0={x:0,y:0},P0={isOpen:!1,isDarkOverlay:!0,className:"",containerClassName:""},R0=Fn(),M0=gt.forwardRef(function(e,t){function o(){var e=L.current;(e=null==e?void 0:e.getBoundingClientRect())&&(E&&Z(e.top),ee&&($.minPosition={x:-e.left,y:-e.top},$.maxPosition={x:e.left,y:e.top}))}function n(){var e;$.lastSetCoordinates=T0,J(),$.isInKeyboardMoveMode=!1,U(!1),Y(T0),null===(e=$.disposeOnKeyUp)\|\|void 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r,i,s=Hn(P0,e),a=s.allowTouchBodyScroll,l=s.className,c=s.children,u=s.containerClassName,d=s.scrollableContentClassName,p=s.elementToFocusOnDismiss,h=s.firstFocusableSelector,m=s.forceFocusInsideTrap,g=s.ignoreExternalFocusing,f=s.isBlocking,v=s.isAlert,b=s.isClickableOutsideFocusTrap,y=s.isDarkOverlay,C=s.onDismiss,_=s.layerProps,S=s.overlay,x=s.isOpen,k=s.titleAriaId,w=s.styles,I=s.subtitleAriaId,D=s.theme,E=s.topOffsetFixed,T=s.responsiveMode,P=s.onLayerDidMount,R=s.isModeless,M=s.dragOptions,N=s.onDismissed,B=s.enableAriaHiddenSiblings,F=gt.useRef(null),A=gt.useRef(null),L=gt.useRef(null),H=_r(F,t),O=Su(H),z=iu("ModalFocusTrapZone"),W=wl(),e=Tm(),V=e.setTimeout,K=e.clearTimeout,F=gt.useState(x),G=F[0],U=F[1],t=gt.useState(x),e=t[0],j=t[1],F=gt.useState(T0),q=F[0],Y=F[1],t=gt.useState(),F=t[0],Z=t[1],t=E0(!1),X=t[0],t=t[1],Q=t.toggle,J=t.setFalse,$=_l(function(){return{onModalCloseTimer:0,allowTouchBodyScroll:a,scrollableContent:null,lastSetCoordinates:T0,events:new 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e(e){if(e.altKey&&e.ctrlKey&&e.keyCode===En.space)return e.preventDefault(),void e.stopPropagation();if(X&&(e.altKey\|\|e.keyCode===En.escape)&&J(),!$.isInKeyboardMoveMode\|\|e.keyCode!==En.escape&&e.keyCode!==En.enter\|\|($.isInKeyboardMoveMode=!1,e.preventDefault(),e.stopPropagation()),$.isInKeyboardMoveMode){var t=!0,o=(n=10,e.shiftKey?e.ctrlKey\|\|(n=50):e.ctrlKey&&(n=1),n);switch(e.keyCode){case En.escape:Y($.lastSetCoordinates);case En.enter:$.lastSetCoordinates=T0;break;case En.up:Y(function(e){return{x:e.x,y:te("y",e.y-o)}});break;case En.down:Y(function(e){return{x:e.x,y:te("y",e.y+o)}});break;case En.left:Y(function(e){return{x:te("x",e.x-o),y:e.y}});break;case En.right:Y(function(e){return{x:te("x",e.x+o),y:e.y}});break;default:t=!1}t&&(e.preventDefault(),e.stopPropagation())}var n}$.lastSetCoordinates=q,J(),$.isInKeyboardMoveMode=!0,$.events.on(W,"keydown",e,!0),$.disposeOnKeyDown=function(){$.events.off(W,"keydown",e,!0),$.disposeOnKeyDown=void 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this._classNames=Ay(r,{theme:i,className:s,showAsSecondaryTitle:n}),o&&e&&a?gt.createElement("div",{className:this._classNames.root,ref:this._titleElement,title:t},e,"…",a):gt.createElement("div",{className:this._classNames.root,ref:this._titleElement,title:t,style:this._needMeasurement?{whiteSpace:"nowrap"}:void 0},t)},Object.defineProperty(Zy.prototype,"_needMeasurement",{get:function(){return!!this.props.shouldTruncate&&void 0===this._clientWidth},enumerable:!1,configurable:!0}),Zy.prototype._updateTruncation=function(){var e=this;this._timerId\|\|(this._timerId=this._async.setTimeout(function(){delete e._timerId,e._clientWidth=void 0,e.setState({truncatedTitleFirstPiece:void 0,truncatedTitleSecondPiece:void 0})},250))},Zy),function(e){var t=e.theme,o=e.className,n=e.showAsSecondaryTitle,r=t.palette,e=t.fonts;return{root:[zo(fy,t).root,n?e.medium:e.large,{padding:"8px 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this._classNames=Wy(n,{theme:r,className:i}),gt.createElement("div",{className:this._classNames.root},t&&gt.createElement(Wr,ht({},e)),o)},qy),Vy={root:"ms-DocumentCardStatus"},Ky=In(U,function(e){var t=e.className,o=e.theme,n=o.palette,e=o.fonts;return{root:[zo(Vy,o).root,e.medium,{margin:"8px 16px",color:n.neutralPrimary,backgroundColor:n.neutralLighter,height:"32px"},t]}},void 0,{scope:"DocumentCardStatus"}),Gy=function(o){var n;return function(e){n\|\|(n=new Set,gi(o,{componentWillUnmount:function(){n.forEach(function(e){return cancelAnimationFrame(e)})}}));var t=requestAnimationFrame(function(){n.delete(t),e()});n.add(t)}},Uy=(jy.prototype.updateOptions=function(e){for(var t=[],o=0,n=0;n<e.length;n++)e[n].itemType===cf.Divider\|\|e[n].itemType===cf.Header?t.push(n):e[n].hidden\|\|o++;this._size=o,this._displayOnlyOptionsCache=t,this._cachedOptions=$e([],e)},Object.defineProperty(jy.prototype,"optionSetSize",{get:function(){return this._size},enumerable:!1,configurable:!0}),Object.defineProperty(jy.prototype,"cachedOptions",{get:function(){return this._cachedOptions},enumerable:!1,configurable:!0}),jy.prototype.positionInSet=function(e){if(void 0!==e){for(var t=0;e>this._displayOnlyOptionsCache[t];)t++;if(this._displayOnlyOptionsCache[t]===e)throw new Error("Unexpected: Option at index "+e+" is not a selectable element.");return e-t+1}},jy);function jy(){this._size=0}function qy(e){e=ny.call(this,e)\|\|this;return fi(e),e}function Yy(e){e=ry.call(this,e)\|\|this;return fi(e),e}function Zy(e){var i=iy.call(this,e)\|\|this;return i._titleElement=gt.createRef(),i._truncateTitle=function(){i._needMeasurement&&i._async.requestAnimationFrame(i._truncateWhenInAnimation)},i._truncateWhenInAnimation=function(){var e=i.props.title,t=i._titleElement.current;if(t){var o=getComputedStyle(t);if(o.width&&o.lineHeight&&o.height){var n=t.clientWidth,r=t.scrollWidth;i._clientWidth=n;n=Math.floor((parseInt(o.height,10)+5)/parseInt(o.lineHeight,10));t.style.whiteSpace="";n=r/(parseInt(o.width,10)n);if(1<n){n=e.length/n-3;return i.setState({truncatedTitleFirstPiece:e.slice(0,n/2),truncatedTitleSecondPiece:e.slice(e.length-n/2)})}}}},i._shrinkTitle=function(){var e=i.state,t=e.truncatedTitleFirstPiece,o=e.truncatedTitleSecondPiece;t&&o&&((e=i._titleElement.current)&&(e.scrollHeight>e.clientHeight+5\|\|e.scrollWidth>e.clientWidth)&&i.setState({truncatedTitleFirstPiece:t.slice(0,t.length-1),truncatedTitleSecondPiece:o.slice(1)}))},fi(i),i._async=new Si(i),i._events=new va(i),i._clientWidth=void 0,i.state={truncatedTitleFirstPiece:void 0,truncatedTitleSecondPiece:void 0},i}function Xy(e){var t=sy.call(this,e)\|\|this;return t._onImageLoad=function(){t.setState({imageHasLoaded:!0})},fi(t),t.state={imageHasLoaded:!1},t}function Qy(e){var r=ay.call(this,e)\|\|this;return r._renderPreviewList=function(e){var t=r.props,o=t.getOverflowDocumentCountText,n=t.maxDisplayCount,t=void 0===n?3:n,n=e.length-t,n=n?o?o(n):"+"+n:null,t=e.slice(0,t).map(function(e,t){return gt.createElement("li",{key:t},gt.createElement(Ir,{className:r._classNames.fileListIcon,src:e.iconSrc,role:"presentation",alt:"",width:"16px",height:"16px"}),gt.createElement(ua,ht({className:r._classNames.fileListLink,href:e.url},e.linkProps),e.name))});return gt.createElement("div",null,gt.createElement("ul",{className:r._classNames.fileList},t),n&&gt.createElement("span",{className:r._classNames.fileListOverflowText},n))},fi(r),r}function Jy(e){e=ly.call(this,e)\|\|this;return fi(e),e}function $y(e){e=cy.call(this,e)\|\|this;return fi(e),e}function eC(e){e=uy.call(this,e)\|\|this;return fi(e),e}function tC(e){e=dy.call(this,e)\|\|this;return fi(e),e}function oC(e){var r=py.call(this,e)\|\|this;return r._rootElement=gt.createRef(),r._onClick=function(e){r._onAction(e)},r._onKeyDown=function(e){e.which!==En.enter&&e.which!==En.space\|\|r._onAction(e)},r._onAction=function(e){var t=r.props,o=t.onClick,n=t.onClickHref,t=t.onClickTarget;o?o(e):!o&&n&&(t?window.open(n,t,"noreferrer noopener nofollow"):window.location.href=n,e.preventDefault(),e.stopPropagation())},fi(r),r}(xe=oy=oy\|\|{})[xe.smallFluid=0]="smallFluid",xe[xe.smallFixedFar=1]="smallFixedFar",xe[xe.smallFixedNear=2]="smallFixedNear",xe[xe.medium=3]="medium",xe[xe.large=4]="large",xe[xe.largeFixed=5]="largeFixed",xe[xe.extraLarge=6]="extraLarge",xe[xe.custom=7]="custom",xe[xe.customNear=8]="customNear";var nC,rC=Fn();(V=nC=nC\|\|{})[V.closed=0]="closed",V[V.animatingOpen=1]="animatingOpen",V[V.open=2]="open",V[V.animatingClosed=3]="animatingClosed";var iC,sC=(l(yC,iC=gt.Component),yC.getDerivedStateFromProps=function(e,t){return void 0===e.isOpen?null:!e.isOpen\|\|t.visibility!==nC.closed&&t.visibility!==nC.animatingClosed?e.isOpen\|\|t.visibility!==nC.open&&t.visibility!==nC.animatingOpen?null:{visibility:nC.animatingClosed}:{visibility:nC.animatingOpen}},yC.prototype.componentDidMount=function(){this._events.on(window,"resize",this._updateFooterPosition),this._shouldListenForOuterClick(this.props)&&this._events.on(document.body,"mousedown",this._dismissOnOuterClick,!0),this.props.isOpen&&this.setState({visibility:nC.animatingOpen})},yC.prototype.componentDidUpdate=function(e,t){var o=this._shouldListenForOuterClick(this.props),e=this._shouldListenForOuterClick(e);this.state.visibility!==t.visibility&&(this._clearExistingAnimationTimer(),this.state.visibility===nC.animatingOpen?this._animateTo(nC.open):this.state.visibility===nC.animatingClosed&&this._animateTo(nC.closed)),o&&!e?this._events.on(document.body,"mousedown",this._dismissOnOuterClick,!0):!o&&e&&this._events.off(document.body,"mousedown",this._dismissOnOuterClick,!0)},yC.prototype.componentWillUnmount=function(){this._async.dispose(),this._events.dispose()},yC.prototype.render=function(){var e=this.props,t=e.className,o=void 0===t?"":t,n=e.elementToFocusOnDismiss,r=e.firstFocusableSelector,i=e.focusTrapZoneProps,s=e.forceFocusInsideTrap,a=e.hasCloseButton,l=e.headerText,c=e.headerClassName,u=void 0===c?"":c,d=e.ignoreExternalFocusing,p=e.isBlocking,h=e.isFooterAtBottom,m=e.isLightDismiss,g=e.isHiddenOnDismiss,f=e.layerProps,v=e.overlayProps,b=e.popupProps,y=e.type,C=e.styles,_=e.theme,S=e.customWidth,x=e.onLightDismissClick,k=void 0===x?this._onPanelClick:x,w=e.onRenderNavigation,I=void 0===w?this._onRenderNavigation:w,D=e.onRenderHeader,E=void 0===D?this._onRenderHeader:D,T=e.onRenderBody,P=void 0===T?this._onRenderBody:T,t=e.onRenderFooter,c=void 0===t?this._onRenderFooter:t,x=this.state,w=x.isFooterSticky,D=x.visibility,T=x.id,e=y===oy.smallFixedNear\|\|y===oy.customNear,t=Pn(_)?e:!e,x=y===oy.custom\|\|y===oy.customNear?{width:S}:{},e=ur(this.props,cr),S=this.isActive,D=D===nC.animatingClosed\|\|D===nC.animatingOpen;if(this._headerTextId=l&&T+"-headerText",!S&&!D&&!g)return null;this._classNames=rC(C,{theme:_,className:o,focusTrapZoneClassName:i?i.className:void 0,hasCloseButton:a,headerClassName:u,isAnimating:D,isFooterSticky:w,isFooterAtBottom:h,isOnRightSide:t,isOpen:S,isHiddenOnDismiss:g,type:y,hasCustomNavigation:this._hasCustomNavigation});var R,t=this._classNames,y=this._allowTouchBodyScroll;return p&&S&&(R=gt.createElement(_0,ht({className:t.overlay,isDarkThemed:!1,onClick:m?k:void 0,allowTouchBodyScroll:y},v))),gt.createElement(sc,ht({},f),gt.createElement(Pl,ht({role:"dialog","aria-modal":p?"true":void 0,ariaLabelledBy:this._headerTextId\|\|void 0,onDismiss:this.dismiss,className:t.hiddenPanel},b),gt.createElement("div",ht({"aria-hidden":!S&&D},e,{ref:this._panel,className:t.root}),R,gt.createElement(Wh,ht({ignoreExternalFocusing:d,forceFocusInsideTrap:!(!p\|\|g&&!S)&&s,firstFocusableSelector:r,isClickableOutsideFocusTrap:!0},i,{className:t.main,style:x,elementToFocusOnDismiss:n}),gt.createElement("div",{className:t.contentInner},gt.createElement("div",{ref:this._allowScrollOnPanel,className:t.scrollableContent,"data-is-scrollable":!0},gt.createElement("div",{className:t.commands,"data-is-visible":!0},I(this.props,this._onRenderNavigation)),(this._hasCustomNavigation\|\|!a)&&E(this.props,this._onRenderHeader,this._headerTextId),P(this.props,this._onRenderBody),c(this.props,this._onRenderFooter)))))))},yC.prototype.open=function(){void 0===this.props.isOpen&&(this.isActive\|\|this.setState({visibility:nC.animatingOpen}))},yC.prototype.close=function(){void 0===this.props.isOpen&&this.isActive&&this.setState({visibility:nC.animatingClosed})},Object.defineProperty(yC.prototype,"isActive",{get:function(){return this.state.visibility===nC.open\|\|this.state.visibility===nC.animatingOpen},enumerable:!1,configurable:!0}),yC.prototype._shouldListenForOuterClick=function(e){return!!e.isBlocking&&!!e.isOpen},yC.prototype._updateFooterPosition=function(){var e,t=this._scrollableContent;t&&(e=t.clientHeight,t=t.scrollHeight,this.setState({isFooterSticky:e<t}))},yC.prototype._dismissOnOuterClick=function(e){var t=this._panel.current;this.isActive&&t&&!e.defaultPrevented&&($i(t,e.target)\|\|(this.props.onOuterClick?this.props.onOuterClick(e):this.dismiss(e)))},yC.defaultProps={isHiddenOnDismiss:!1,isOpen:void 0,isBlocking:!0,hasCloseButton:!0,type:oy.smallFixedFar},yC),aC={root:"ms-Panel",main:"ms-Panel-main",commands:"ms-Panel-commands",contentInner:"ms-Panel-contentInner",scrollableContent:"ms-Panel-scrollableContent",navigation:"ms-Panel-navigation",closeButton:"ms-Panel-closeButton ms-PanelAction-close",header:"ms-Panel-header",headerText:"ms-Panel-headerText",content:"ms-Panel-content",footer:"ms-Panel-footer",footerInner:"ms-Panel-footerInner",isOpen:"is-open",hasCloseButton:"ms-Panel--hasCloseButton",smallFluid:"ms-Panel--smFluid",smallFixedNear:"ms-Panel--smLeft",smallFixedFar:"ms-Panel--sm",medium:"ms-Panel--md",large:"ms-Panel--lg",largeFixed:"ms-Panel--fixed",extraLarge:"ms-Panel--xl",custom:"ms-Panel--custom",customNear:"ms-Panel--customLeft"},lC="auto",cC=((G={})["@media (min-width: "+$t+"px)"]={width:340},G),uC=((Y={})["@media (min-width: "+eo+"px)"]={width:592},Y["@media (min-width: "+to+"px)"]={width:644},Y),dC=((ke={})["@media (min-width: "+co+"px)"]={left:48,width:"auto"},ke["@media (min-width: "+oo+"px)"]={left:428},ke),pC=((K={})["@media (min-width: "+oo+"px)"]={left:lC,width:940},K),hC=((U={})["@media (min-width: "+oo+"px)"]={left:176},U),mC={paddingLeft:"24px",paddingRight:"24px"},gC=In(sC,function(e){var t,o=e.className,n=e.focusTrapZoneClassName,r=e.hasCloseButton,i=e.headerClassName,s=e.isAnimating,a=e.isFooterSticky,l=e.isFooterAtBottom,c=e.isOnRightSide,u=e.isOpen,d=e.isHiddenOnDismiss,p=e.hasCustomNavigation,h=e.theme,m=e.type,g=void 0===m?oy.smallFixedFar:m,f=h.effects,v=h.fonts,b=h.semanticColors,e=zo(aC,h),m=g===oy.custom\|\|g===oy.customNear;return{root:[e.root,h.fonts.medium,u&&e.isOpen,r&&e.hasCloseButton,{pointerEvents:"none",position:"absolute",top:0,left:0,right:0,bottom:0},m&&c&&e.custom,m&&!c&&e.customNear,o],overlay:[{pointerEvents:"auto",cursor:"pointer"},u&&s&&Le.fadeIn100,!u&&s&&Le.fadeOut100],hiddenPanel:[!u&&!s&&d&&{visibility:"hidden"}],main:[e.main,{backgroundColor:b.bodyBackground,boxShadow:f.elevation64,pointerEvents:"auto",position:"absolute",display:"flex",flexDirection:"column",overflowX:"hidden",overflowY:"auto",WebkitOverflowScrolling:"touch",bottom:0,top:0,left:lC,right:0,width:"100%",selectors:ht(((f={})[Yt]={borderLeft:"3px solid "+b.variantBorder,borderRight:"3px solid "+b.variantBorder},f),function(e){var t;switch(e){case oy.smallFixedFar:t=ht({},cC);break;case oy.medium:t=ht(ht({},cC),uC);break;case oy.large:t=ht(ht(ht({},cC),uC),dC);break;case oy.largeFixed:t=ht(ht(ht(ht({},cC),uC),dC),pC);break;case oy.extraLarge:t=ht(ht(ht(ht({},cC),uC),dC),hC)}return t}(g))},g===oy.smallFluid&&{left:0},g===oy.smallFixedNear&&{left:0,right:lC,width:272},g===oy.customNear&&{right:"auto",left:0},m&&{maxWidth:"100vw"},u&&s&&!c&&Le.slideRightIn40,u&&s&&c&&Le.slideLeftIn40,!u&&s&&!c&&Le.slideLeftOut40,!u&&s&&c&&Le.slideRightOut40,n],commands:[e.commands,{marginTop:18,background:"inherit",selectors:((n={})["@media (min-height: "+$t+"px)"]={position:"sticky",top:0,zIndex:1},n)},p&&{marginTop:"inherit"}],navigation:[e.navigation,{display:"flex",justifyContent:"flex-end"},p&&{height:"44px"}],contentInner:[e.contentInner,{display:"flex",flexDirection:"column",flexGrow:1,overflowY:"hidden",background:"inherit"}],header:[e.header,mC,{alignSelf:"flex-start"},r&&!p&&{flexGrow:1},p&&{flexShrink:0}],headerText:[e.headerText,v.xLarge,{color:b.bodyText,lineHeight:"27px",overflowWrap:"break-word",wordWrap:"break-word",wordBreak:"break-word",hyphens:"auto"},i],scrollableContent:[e.scrollableContent,{overflowY:"auto",background:"inherit"},l&&{flexGrow:1,display:"inherit",flexDirection:"inherit"}],content:[e.content,mC,{paddingBottom:20},l&&{selectors:((t={})["@media (min-height: "+$t+"px)"]={flexGrow:1},t)}],footer:[e.footer,{flexShrink:0,borderTop:"1px solid transparent",transition:"opacity "+we.durationValue3+" "+we.easeFunction2,selectors:((t={})["@media (min-height: "+$t+"px)"]={position:"sticky",bottom:0},t)},a&&{background:b.bodyBackground,borderTopColor:b.variantBorder}],footerInner:[e.footerInner,mC,{paddingBottom:16,paddingTop:16}],subComponentStyles:{closeButton:{root:[e.closeButton,{marginRight:14,color:h.palette.neutralSecondary,fontSize:Ae.large},p&&{marginRight:0,height:"auto",width:"44px"}],rootHovered:{color:h.palette.neutralPrimary}}}}},void 0,{scope:"Panel"}),fC=Fn(),vC={options:[]},bC=gt.forwardRef(function(e,t){var s,o,n,r,a,l,c,u,d,p,i=Hn(vC,e),h=gt.useRef(null),m=_r(t,h),g=Su(h,i.responsiveMode),h=(o=i.defaultSelectedKeys,n=i.selectedKeys,r=i.defaultSelectedKey,e=i.selectedKey,a=i.options,l=i.multiSelect,c=Hc(a),t=gt.useState([]),h=t[0],u=t[1],d=a!==c,p=Hc(s=l?d&&void 0!==o?o:n:d&&void 0!==r?r:e),gt.useEffect(function(){function i(t){return Hi(a,function(e){return null!=t?e.key===t:e.selected\|\|e.isSelected})}void 0===s&&c\|\|s===p&&!d\|\|u(function(){if(void 0===s)return l?a.map(function(e,t){return e.selected?t:-1}).filter(function(e){return-1!==e}):-1!==(n=i(null))?[n]:[];if(!Array.isArray(s))return-1!==(n=i(s))?[n]:[];for(var e=[],t=0,o=s;t<o.length;t++){var n,r=o[t];-1!==(n=i(r))&&e.push(n)}return e}())},[d,l,c,p,a,s]),[h,u]);return gt.createElement(_C,ht({},i,{responsiveMode:g,hoisted:{rootRef:m,selectedIndices:h[0],setSelectedIndices:h[1]}}))});function yC(e){var r=iC.call(this,e)\|\|this;r._panel=gt.createRef(),r._animationCallback=null,r._hasCustomNavigation=!(!r.props.onRenderNavigation&&!r.props.onRenderNavigationContent),r.dismiss=function(e){r.props.onDismiss&&r.isActive&&r.props.onDismiss(e),e&&e.defaultPrevented\|\|r.close()},r._allowScrollOnPanel=function(e){e?(r._allowTouchBodyScroll?Es:Ds)(e,r._events):r._events.off(r._scrollableContent),r._scrollableContent=e},r._onRenderNavigation=function(e){if(!r.props.onRenderNavigationContent&&!r.props.onRenderNavigation&&!r.props.hasCloseButton)return null;var t=r.props.onRenderNavigationContent,t=void 0===t?r._onRenderNavigationContent:t;return gt.createElement("div",{className:r._classNames.navigation},t(e,r._onRenderNavigationContent))},r._onRenderNavigationContent=function(e){var t=e.closeButtonAriaLabel,o=e.hasCloseButton,e=e.onRenderHeader,e=void 0===e?r._onRenderHeader:e;if(o){o=null===(o=r._classNames.subComponentStyles)\|\|void 0===o?void 0:o.closeButton();return gt.createElement(gt.Fragment,null,!r._hasCustomNavigation&&e(r.props,r._onRenderHeader,r._headerTextId),gt.createElement(rd,{styles:o,className:r._classNames.closeButton,onClick:r._onPanelClick,ariaLabel:t,title:t,"data-is-visible":!0,iconProps:{iconName:"Cancel"}}))}return null},r._onRenderHeader=function(e,t,o){var n=e.headerText,e=e.headerTextProps,e=void 0===e?{}:e;return n?gt.createElement("div",{className:r._classNames.header},gt.createElement("div",ht({id:o,role:"heading","aria-level":1},e,{className:Tr(r._classNames.headerText,e.className)}),n)):null},r._onRenderBody=function(e){return gt.createElement("div",{className:r._classNames.content},e.children)},r._onRenderFooter=function(e){var t=r.props.onRenderFooterContent,t=void 0===t?null:t;return t?gt.createElement("div",{className:r._classNames.footer},gt.createElement("div",{className:r._classNames.footerInner},t())):null},r._animateTo=function(e){e===nC.open&&r.props.onOpen&&r.props.onOpen(),r._animationCallback=r._async.setTimeout(function(){r.setState({visibility:e}),r._onTransitionComplete()},200)},r._clearExistingAnimationTimer=function(){null!==r._animationCallback&&r._async.clearTimeout(r._animationCallback)},r._onPanelClick=function(e){r.dismiss(e)},r._onTransitionComplete=function(){r._updateFooterPosition(),r.state.visibility===nC.open&&r.props.onOpened&&r.props.onOpened(),r.state.visibility===nC.closed&&r.props.onDismissed&&r.props.onDismissed()};e=r.props.allowTouchBodyScroll;return r._allowTouchBodyScroll=void 0!==e&&e,r._async=new Si(r),r._events=new va(r),fi(r),r.state={isFooterSticky:!1,visibility:nC.closed,id:_s("Panel")},r}bC.displayName="DropdownBase";var CC,_C=(l(DC,CC=gt.Component),Object.defineProperty(DC.prototype,"selectedOptions",{get:function(){var e=this.props;return _f(e.options,e.hoisted.selectedIndices)},enumerable:!1,configurable:!0}),DC.prototype.componentWillUnmount=function(){clearTimeout(this._scrollIdleTimeoutId)},DC.prototype.componentDidUpdate=function(e,t){!0===t.isOpen&&!1===this.state.isOpen&&(this._gotMouseMove=!1,this._hasBeenPositioned=!1,this.props.onDismiss&&this.props.onDismiss())},DC.prototype.render=function(){var e=this._id,t=this.props,o=t.className,n=t.label,r=t.options,i=t.ariaLabel,s=t.required,a=t.errorMessage,l=t.styles,c=t.theme,u=t.panelProps,d=t.calloutProps,p=t.onRenderTitle,h=void 0===p?this._getTitle:p,m=t.onRenderContainer,g=void 0===m?this._onRenderContainer:m,f=t.onRenderCaretDown,v=void 0===f?this._onRenderCaretDown:f,b=t.onRenderLabel,y=void 0===b?this._onRenderLabel:b,C=t.hoisted.selectedIndices,_=this.state,S=_.isOpen,x=_.calloutRenderEdge,p=_.hasFocus,m=t.onRenderPlaceholder\|\|t.onRenderPlaceHolder\|\|this._getPlaceholder;r!==this._sizePosCache.cachedOptions&&this._sizePosCache.updateOptions(r);f=_f(r,C),b=ur(t,cr),_=this._isDisabled(),r=e+"-errorMessage",C=!_&&S&&1===C.length&&0<=C[0]?this._listId+C[0]:void 0;this._classNames=fC(l,{theme:c,className:o,hasError:!!(a&&0<a.length),hasLabel:!!n,isOpen:S,required:s,disabled:_,isRenderingPlaceholder:!f.length,panelClassName:u?u.className:void 0,calloutClassName:d?d.className:void 0,calloutRenderEdge:x});x=!!a&&0<a.length;return gt.createElement("div",{className:this._classNames.root,ref:this.props.hoisted.rootRef,"aria-owns":S?this._listId:void 0},y(this.props,this._onRenderLabel),gt.createElement("div",ht({"data-is-focusable":!_,"data-ktp-target":!0,ref:this._dropDown,id:e,tabIndex:_?-1:0,role:"combobox","aria-haspopup":"listbox","aria-expanded":S?"true":"false","aria-label":i,"aria-labelledby":n&&!i?Ia(this._labelId,this._optionId):void 0,"aria-describedby":x?this._id+"-errorMessage":void 0,"aria-activedescendant":C,"aria-required":s,"aria-disabled":_,"aria-controls":S?this._listId:void 0},b,{className:this._classNames.dropdown,onBlur:this._onDropdownBlur,onKeyDown:this._onDropdownKeyDown,onKeyUp:this._onDropdownKeyUp,onClick:this._onDropdownClick,onMouseDown:this._onDropdownMouseDown,onFocus:this._onFocus}),gt.createElement("span",{id:this._optionId,className:this._classNames.title,"aria-live":p?"polite":void 0,"aria-atomic":!!p\|\|void 0,"aria-invalid":x},f.length?h(f,this._onRenderTitle):m(t,this._onRenderPlaceholder)),gt.createElement("span",{className:this._classNames.caretDownWrapper},v(t,this._onRenderCaretDown))),S&&g(ht(ht({},t),{onDismiss:this._onDismiss}),this._onRenderContainer),x&&gt.createElement("div",{role:"alert",id:r,className:this._classNames.errorMessage},a))},DC.prototype.focus=function(e){this._dropDown.current&&(this._dropDown.current.focus(),e&&this.setState({isOpen:!0}))},DC.prototype.setSelectedIndex=function(e,t){var o=this.props,n=o.options,r=o.selectedKey,i=o.selectedKeys,s=o.multiSelect,a=o.notifyOnReselect,l=o.hoisted.selectedIndices,c=void 0===l?[]:l,o=!!c&&-1<c.indexOf(t),l=[];t=Math.max(0,Math.min(n.length-1,t)),void 0===r&&void 0===i?(s\|\|a\|\|t!==c[0])&&(s?(l=c?this._copyArray(c):[],o?-1<(c=l.indexOf(t))&&l.splice(c,1):l.push(t)):l=[t],e.persist(),this.props.hoisted.setSelectedIndices(l),this._onChange(e,n,t,o,s)):this._onChange(e,n,t,o,s)},DC.prototype._copyArray=function(e){for(var t=[],o=0,n=e;o<n.length;o++){var r=n[o];t.push(r)}return t},DC.prototype._moveIndex=function(e,t,o,n){var r=this.props.options;if(n===o\|\|0===r.length)return n;o>=r.length?o=0:o<0&&(o=r.length-1);for(var i=0;r[o].itemType===cf.Header\|\|r[o].itemType===cf.Divider\|\|r[o].disabled;){if(i>=r.length)return n;o+t<0?o=r.length:o+t>=r.length&&(o=-1),o+=t,i++}return this.setSelectedIndex(e,o),o},DC.prototype._renderFocusableList=function(e){var t=e.onRenderList,o=void 0===t?this._onRenderList:t,n=e.label,r=e.ariaLabel,t=e.multiSelect;return gt.createElement("div",{className:this._classNames.dropdownItemsWrapper,onKeyDown:this._onZoneKeyDown,onKeyUp:this._onZoneKeyUp,ref:this._host,tabIndex:0},gt.createElement(Zs,{ref:this._focusZone,direction:Ei.vertical,id:this._listId,className:this._classNames.dropdownItems,role:"listbox","aria-label":r,"aria-labelledby":n&&!r?this._labelId:void 0,"aria-multiselectable":t},o(e,this._onRenderList)))},DC.prototype._renderSeparator=function(e){var t=e.index,e=e.key;return 0<t?gt.createElement("div",{role:"separator",key:e,className:this._classNames.dropdownDivider}):null},DC.prototype._renderHeader=function(e){var t=this.props.onRenderOption,o=void 0===t?this._onRenderOption:t,n=e.key,t=e.id;return gt.createElement("div",{id:t,key:n,className:this._classNames.dropdownItemHeader},o(e,this._onRenderOption))},DC.prototype._onItemMouseEnter=function(e,t){this._shouldIgnoreMouseEvent()\|\|t.currentTarget.focus()},DC.prototype._onItemMouseMove=function(e,t){t=t.currentTarget;this._gotMouseMove=!0,this._isScrollIdle&&document.activeElement!==t&&t.focus()},DC.prototype._shouldIgnoreMouseEvent=function(){return!this._isScrollIdle\|\|!this._gotMouseMove},DC.prototype._isAltOrMeta=function(e){return e.which===En.alt\|\|"Meta"===e.key},DC.prototype._shouldHandleKeyUp=function(e){e=this._lastKeyDownWasAltOrMeta&&this._isAltOrMeta(e);return this._lastKeyDownWasAltOrMeta=!1,!!e&&!(Na()\|\|Aa())},DC.prototype._shouldOpenOnFocus=function(){var e=this.state.hasFocus,t=this.props.openOnKeyboardFocus;return!this._isFocusedByClick&&!0===t&&!e},DC.defaultProps={options:[]},DC),SC={root:"ms-Dropdown-container",label:"ms-Dropdown-label",dropdown:"ms-Dropdown",title:"ms-Dropdown-title",caretDownWrapper:"ms-Dropdown-caretDownWrapper",caretDown:"ms-Dropdown-caretDown",callout:"ms-Dropdown-callout",panel:"ms-Dropdown-panel",dropdownItems:"ms-Dropdown-items",dropdownItem:"ms-Dropdown-item",dropdownDivider:"ms-Dropdown-divider",dropdownOptionText:"ms-Dropdown-optionText",dropdownItemHeader:"ms-Dropdown-header",titleIsPlaceHolder:"ms-Dropdown-titleIsPlaceHolder",titleHasError:"ms-Dropdown-title--hasError"},V=((xe={})[Yt+", "+Zt.replace("@media ","")]=ht({},{forcedColorAdjust:"none",MsHighContrastAdjust:"none"}),xe),xC={selectors:ht(((G={})[Yt]={backgroundColor:"Highlight",borderColor:"Highlight",color:"HighlightText"},G),V)},kC={selectors:((Y={})[Yt]={borderColor:"Highlight"},Y)},wC=uo(0,$t),IC=In(bC,function(e){var t=e.theme,o=e.hasError,n=e.hasLabel,r=e.className,i=e.isOpen,s=e.disabled,a=e.required,l=e.isRenderingPlaceholder,c=e.panelClassName,u=e.calloutClassName,d=e.calloutRenderEdge;if(!t)throw new Error("theme is undefined or null in base Dropdown getStyles function.");function p(e){return{selectors:((e={"&:hover:focus":[{color:g.menuItemTextHovered,backgroundColor:(e=void 0===e?!1:e)?S:g.menuItemBackgroundHovered},xC],"&:focus":[{backgroundColor:e?S:"transparent"},xC],"&:active":[{color:g.menuItemTextHovered,backgroundColor:e?g.menuItemBackgroundHovered:g.menuBackground},xC]})["."+go+" &:focus:after"]={left:0,top:0,bottom:0,right:0},e[Yt]={border:"none"},e)}}var h=zo(SC,t),m=t.palette,g=t.semanticColors,f=t.effects,v=t.fonts,b={color:g.menuItemTextHovered},y={color:g.menuItemText},C={borderColor:g.errorText},_=[h.dropdownItem,{backgroundColor:"transparent",boxSizing:"border-box",cursor:"pointer",display:"flex",alignItems:"center",padding:"0 8px",width:"100%",minHeight:36,lineHeight:20,height:0,position:"relative",border:"1px solid transparent",borderRadius:0,wordWrap:"break-word",overflowWrap:"break-word",textAlign:"left",".ms-Button-flexContainer":{width:"100%"}}],S=g.menuItemBackgroundPressed,x=$e($e([],_),[{backgroundColor:S,color:g.menuItemTextHovered},p(!0),xC]),k=$e($e([],_),[{color:g.disabledText,cursor:"default",selectors:((w={})[Yt]={color:"GrayText",border:"none"},w)}]),e=d===Ba.bottom?f.roundedCorner2+" "+f.roundedCorner2+" 0 0":"0 0 "+f.roundedCorner2+" "+f.roundedCorner2,w=d===Ba.bottom?"0 0 "+f.roundedCorner2+" "+f.roundedCorner2:f.roundedCorner2+" "+f.roundedCorner2+" 0 0";return{root:[h.root,r],label:h.label,dropdown:[h.dropdown,Uo,v.medium,{color:g.menuItemText,borderColor:g.focusBorder,position:"relative",outline:0,userSelect:"none",selectors:((d={})["&:hover ."+h.title]=[!s&&b,{borderColor:i?m.neutralSecondary:m.neutralPrimary},kC],d["&:focus ."+h.title]=[!s&&b,{selectors:((r={})[Yt]={color:"Highlight"},r)}],d["&:focus:after"]=[{pointerEvents:"none",content:"''",position:"absolute",boxSizing:"border-box",top:"0px",left:"0px",width:"100%",height:"100%",border:s?"none":"2px solid "+m.themePrimary,borderRadius:"2px",selectors:((r={})[Yt]={color:"Highlight"},r)}],d["&:active ."+h.title]=[!s&&b,{borderColor:m.themePrimary},kC],d["&:hover ."+h.caretDown]=!s&&y,d["&:focus ."+h.caretDown]=[!s&&y,{selectors:((b={})[Yt]={color:"Highlight"},b)}],d["&:active ."+h.caretDown]=!s&&y,d["&:hover ."+h.titleIsPlaceHolder]=!s&&y,d["&:focus ."+h.titleIsPlaceHolder]=!s&&y,d["&:active ."+h.titleIsPlaceHolder]=!s&&y,d["&:hover ."+h.titleHasError]=C,d["&:active ."+h.titleHasError]=C,d)},i&&"is-open",s&&"is-disabled",a&&"is-required",a&&!n&&{selectors:((n={":before":{content:"''",color:g.errorText,position:"absolute",top:-5,right:-10}})[Yt]={selectors:{":after":{right:-14}}},n)}],title:[h.title,Uo,{backgroundColor:g.inputBackground,borderWidth:1,borderStyle:"solid",borderColor:g.inputBorder,borderRadius:i?e:f.roundedCorner2,cursor:"pointer",display:"block",height:32,lineHeight:30,padding:"0 28px 0 8px",position:"relative",overflow:"hidden",whiteSpace:"nowrap",textOverflow:"ellipsis"},l&&[h.titleIsPlaceHolder,{color:g.inputPlaceholderText}],o&&[h.titleHasError,C],s&&{backgroundColor:g.disabledBackground,border:"none",color:g.disabledText,cursor:"default",selectors:((C={})[Yt]=ht({border:"1px solid GrayText",color:"GrayText",backgroundColor:"Window"},{forcedColorAdjust:"none",MsHighContrastAdjust:"none"}),C)}],caretDownWrapper:[h.caretDownWrapper,{height:32,lineHeight:30,paddingTop:1,position:"absolute",right:8,top:0},!s&&{cursor:"pointer"}],caretDown:[h.caretDown,{color:m.neutralSecondary,fontSize:v.small.fontSize,pointerEvents:"none"},s&&{color:g.disabledText,selectors:((s={})[Yt]=ht({color:"GrayText"},{forcedColorAdjust:"none",MsHighContrastAdjust:"none"}),s)}],errorMessage:ht(ht({color:g.errorText},t.fonts.small),{paddingTop:5}),callout:[h.callout,{boxShadow:f.elevation8,borderRadius:w,selectors:((f={})[".ms-Callout-main"]={borderRadius:w},f)},u],dropdownItemsWrapper:{selectors:{"&:focus":{outline:0}}},dropdownItems:[h.dropdownItems,{display:"block"}],dropdownItem:$e($e([],_),[p()]),dropdownItemSelected:x,dropdownItemDisabled:k,dropdownItemSelectedAndDisabled:[x,k,{backgroundColor:"transparent"}],dropdownItemHidden:$e($e([],_),[{display:"none"}]),dropdownDivider:[h.dropdownDivider,{height:1,backgroundColor:g.bodyDivider}],dropdownOptionText:[h.dropdownOptionText,{overflow:"hidden",whiteSpace:"nowrap",textOverflow:"ellipsis",minWidth:0,maxWidth:"100%",wordWrap:"break-word",overflowWrap:"break-word",margin:"1px"}],dropdownItemHeader:[h.dropdownItemHeader,ht(ht({},v.medium),{fontWeight:Fe.semibold,color:g.menuHeader,background:"none",backgroundColor:"transparent",border:"none",height:36,lineHeight:36,cursor:"default",padding:"0 8px",userSelect:"none",textAlign:"left",selectors:((v={})[Yt]=ht({color:"GrayText"},{forcedColorAdjust:"none",MsHighContrastAdjust:"none"}),v)})],subComponentStyles:{label:{root:{display:"inline-block"}},multiSelectItem:{root:{padding:0},label:{alignSelf:"stretch",padding:"0 8px",width:"100%"},input:{selectors:((v={})["."+go+" &:focus + label::before"]={outlineOffset:"0px"},v)}},panel:{root:[c],main:{selectors:((c={})[wC]={width:272},c)},contentInner:{padding:"0 0 20px"}}}}},void 0,{scope:"Dropdown"});function DC(e){var l=CC.call(this,e)\|\|this;l._host=gt.createRef(),l._focusZone=gt.createRef(),l._dropDown=gt.createRef(),l._scrollIdleDelay=250,l._sizePosCache=new Uy,l._requestAnimationFrame=Gy(l),l._onChange=function(e,t,o,n,r){var i=l.props,s=i.onChange,i=i.onChanged;(s\|\|i)&&(t=r?ht(ht({},t[o]),{selected:!n}):t[o],s&&s(ht(ht({},e),{target:l._dropDown.current}),t,o),i&&i(t,o))},l._getPlaceholder=function(){return l.props.placeholder\|\|l.props.placeHolder},l._getTitle=function(e,t){var o=l.props.multiSelectDelimiter,o=void 0===o?", ":o;return e.map(function(e){return e.text}).join(o)},l._onRenderTitle=function(e){return gt.createElement(gt.Fragment,null,l._getTitle(e))},l._onRenderPlaceholder=function(e){return l._getPlaceholder()?gt.createElement(gt.Fragment,null,l._getPlaceholder()):null},l._onRenderContainer=function(e){var t=e.calloutProps,o=e.panelProps,n=l.props,r=n.responsiveMode,i=n.dropdownWidth,s=r<=cu.medium,a=l._classNames.subComponentStyles?l._classNames.subComponentStyles.panel:void 0,n=void 0,r=void 0;return"auto"===i?r=l._dropDown.current?l._dropDown.current.clientWidth:0:n=i\|\|(l._dropDown.current?l._dropDown.current.clientWidth:0),s?gt.createElement(gC,ht({isOpen:!0,isLightDismiss:!0,onDismiss:l._onDismiss,hasCloseButton:!1,styles:a},o),l._renderFocusableList(e)):gt.createElement(ac,ht({isBeakVisible:!1,gapSpace:0,doNotLayer:!1,directionalHintFixed:!1,directionalHint:Pa.bottomLeftEdge,calloutWidth:n,calloutMinWidth:r},t,{className:l._classNames.callout,target:l._dropDown.current,onDismiss:l._onDismiss,onScroll:l._onScroll,onPositioned:l._onPositioned}),l._renderFocusableList(e))},l._onRenderCaretDown=function(e){return gt.createElement(Wr,{className:l._classNames.caretDown,iconName:"ChevronDown","aria-hidden":!0})},l._onRenderList=function(e){function n(){var e=i.id?[gt.createElement("div",{role:"group",key:i.id,"aria-labelledby":i.id},i.items)]:i.items;o=$e($e([],o),e),i={items:[]}}var t=e.onRenderItem,r=void 0===t?l._onRenderItem:t,i={items:[]},o=[];return e.options.forEach(function(e,t){!function(e,t){switch(e.itemType){case cf.Header:0<i.items.length&&n();var o=l._id+e.key;i.items.push(r(ht(ht({id:o},e),{index:t}),l._onRenderItem)),i.id=o;break;case cf.Divider:0<t&&i.items.push(r(ht(ht({},e),{index:t}),l._onRenderItem)),0<i.items.length&&n();break;default:i.items.push(r(ht(ht({},e),{index:t}),l._onRenderItem))}}(e,t)}),0<i.items.length&&n(),gt.createElement(gt.Fragment,null,o)},l._onRenderItem=function(e){switch(e.itemType){case cf.Divider:return l._renderSeparator(e);case cf.Header:return l._renderHeader(e);default:return l._renderOption(e)}},l._renderOption=function(e){var t=l.props,o=t.onRenderOption,n=void 0===o?l._onRenderOption:o,r=t.hoisted.selectedIndices,i=void 0===r?[]:r,o=!(void 0===e.index\|\|!i)&&-1<i.indexOf(e.index),t=e.hidden?l._classNames.dropdownItemHidden:o&&!0===e.disabled?l._classNames.dropdownItemSelectedAndDisabled:o?l._classNames.dropdownItemSelected:!0===e.disabled?l._classNames.dropdownItemDisabled:l._classNames.dropdownItem,r=e.title,i=l._classNames.subComponentStyles?l._classNames.subComponentStyles.multiSelectItem:void 0;return l.props.multiSelect?gt.createElement($h,{id:l._listId+e.index,key:e.key,disabled:e.disabled,onChange:l._onItemClick(e),inputProps:ht({"aria-selected":o,onMouseEnter:l._onItemMouseEnter.bind(l,e),onMouseLeave:l._onMouseItemLeave.bind(l,e),onMouseMove:l._onItemMouseMove.bind(l,e),role:"option"},{"data-index":e.index,"data-is-focusable":!e.disabled}),label:e.text,title:r,onRenderLabel:l._onRenderItemLabel.bind(l,e),className:t,checked:o,styles:i,ariaPositionInSet:l._sizePosCache.positionInSet(e.index),ariaSetSize:l._sizePosCache.optionSetSize,ariaLabel:e.ariaLabel}):gt.createElement(up,{id:l._listId+e.index,key:e.key,"data-index":e.index,"data-is-focusable":!e.disabled,disabled:e.disabled,className:t,onClick:l._onItemClick(e),onMouseEnter:l._onItemMouseEnter.bind(l,e),onMouseLeave:l._onMouseItemLeave.bind(l,e),onMouseMove:l._onItemMouseMove.bind(l,e),role:"option","aria-selected":o?"true":"false",ariaLabel:e.ariaLabel,title:r,"aria-posinset":l._sizePosCache.positionInSet(e.index),"aria-setsize":l._sizePosCache.optionSetSize},n(e,l._onRenderOption))},l._onRenderOption=function(e){return gt.createElement("span",{className:l._classNames.dropdownOptionText},e.text)},l._onRenderItemLabel=function(e){var t=l.props.onRenderOption;return(void 0===t?l._onRenderOption:t)(e,l._onRenderOption)},l._onPositioned=function(e){l._focusZone.current&&l._requestAnimationFrame(function(){var e=l.props.hoisted.selectedIndices;l._focusZone.current&&(!l._hasBeenPositioned&&e&&e[0]&&!l.props.options[e[0]].disabled?((e=ft().getElementById(l._id+"-list"+e[0]))&&l._focusZone.current.focusElement(e),l._hasBeenPositioned=!0):l._focusZone.current.focus())}),l.state.calloutRenderEdge&&l.state.calloutRenderEdge===e.targetEdge\|\|l.setState({calloutRenderEdge:e.targetEdge})},l._onItemClick=function(t){return function(e){t.disabled\|\|(l.setSelectedIndex(e,t.index),l.props.multiSelect\|\|l.setState({isOpen:!1}))}},l._onScroll=function(){l._isScrollIdle\|\|void 0===l._scrollIdleTimeoutId?l._isScrollIdle=!1:(clearTimeout(l._scrollIdleTimeoutId),l._scrollIdleTimeoutId=void 0),l._scrollIdleTimeoutId=window.setTimeout(function(){l._isScrollIdle=!0},l._scrollIdleDelay)},l._onMouseItemLeave=function(e,t){if(!l._shouldIgnoreMouseEvent()&&l._host.current)if(l._host.current.setActive)try{l._host.current.setActive()}catch(e){}else l._host.current.focus()},l._onDismiss=function(){l.setState({isOpen:!1})},l._onDropdownBlur=function(e){l._isDisabled()\|\|l.state.isOpen\|\|(l.setState({hasFocus:!1}),l.props.onBlur&&l.props.onBlur(e))},l._onDropdownKeyDown=function(e){if(!l._isDisabled()&&(l._lastKeyDownWasAltOrMeta=l._isAltOrMeta(e),!l.props.onKeyDown\|\|(l.props.onKeyDown(e),!e.defaultPrevented))){var t,o=l.props.hoisted.selectedIndices.length?l.props.hoisted.selectedIndices[0]:-1,n=e.altKey\|\|e.metaKey,r=l.state.isOpen;switch(e.which){case En.enter:l.setState({isOpen:!r});break;case En.escape:if(!r)return;l.setState({isOpen:!1});break;case En.up:if(n){if(r){l.setState({isOpen:!1});break}return}l.props.multiSelect?l.setState({isOpen:!0}):l._isDisabled()\|\|(t=l._moveIndex(e,-1,o-1,o));break;case En.down:n&&(e.stopPropagation(),e.preventDefault()),n&&!r\|\|l.props.multiSelect?l.setState({isOpen:!0}):l._isDisabled()\|\|(t=l._moveIndex(e,1,o+1,o));break;case En.home:l.props.multiSelect\|\|(t=l._moveIndex(e,1,0,o));break;case En.end:l.props.multiSelect\|\|(t=l._moveIndex(e,-1,l.props.options.length-1,o));break;case En.space:break;default:return}t!==o&&(e.stopPropagation(),e.preventDefault())}},l._onDropdownKeyUp=function(e){var t,o;l._isDisabled()\|\|(t=l._shouldHandleKeyUp(e),o=l.state.isOpen,l.props.onKeyUp&&(l.props.onKeyUp(e),e.defaultPrevented)\|\|(e.which===En.space?(l.setState({isOpen:!o}),e.stopPropagation(),e.preventDefault()):t&&o&&l.setState({isOpen:!1})))},l._onZoneKeyDown=function(e){var t;l._lastKeyDownWasAltOrMeta=l._isAltOrMeta(e);var o=e.altKey\|\|e.metaKey;switch(e.which){case En.up:o?l.setState({isOpen:!1}):l._host.current&&(t=ts(l._host.current,l._host.current.lastChild,!0));break;case En.home:case En.end:case En.pageUp:case En.pageDown:break;case En.down:!o&&l._host.current&&(t=es(l._host.current,l._host.current.firstChild,!0));break;case En.escape:l.setState({isOpen:!1});break;case En.tab:return void l.setState({isOpen:!1});default:return}t&&t.focus(),e.stopPropagation(),e.preventDefault()},l._onZoneKeyUp=function(e){l._shouldHandleKeyUp(e)&&l.state.isOpen&&(l.setState({isOpen:!1}),e.preventDefault())},l._onDropdownClick=function(e){l.props.onClick&&(l.props.onClick(e),e.defaultPrevented)\|\|(e=l.state.isOpen,l._isDisabled()\|\|l._shouldOpenOnFocus()\|\|l.setState({isOpen:!e}),l._isFocusedByClick=!1)},l._onDropdownMouseDown=function(){l._isFocusedByClick=!0},l._onFocus=function(e){l._isDisabled()\|\|(l.props.onFocus&&l.props.onFocus(e),e={hasFocus:!0},l._shouldOpenOnFocus()&&(e.isOpen=!0),l.setState(e))},l._isDisabled=function(){var e=l.props.disabled,t=l.props.isDisabled;return e=void 0===e?t:e},l._onRenderLabel=function(e){var t=e.label,o=e.required,n=e.disabled,e=l._classNames.subComponentStyles?l._classNames.subComponentStyles.label:void 0;return t?gt.createElement(om,{className:l._classNames.label,id:l._labelId,required:o,styles:e,disabled:n},t):null},fi(l),e.multiSelect,e.selectedKey,e.selectedKeys,e.defaultSelectedKey,e.defaultSelectedKeys;var t=e.options;return l._id=e.id\|\|_s("Dropdown"),l._labelId=l._id+"-label",l._listId=l._id+"-list",l._optionId=l._id+"-option",l._isScrollIdle=!0,l._hasBeenPositioned=!1,l._sizePosCache.updateOptions(t),l.state={isOpen:!1,hasFocus:!1,calloutRenderEdge:void 0},l}IC.displayName="Dropdown",Dt([{rawString:".pickerText_cc9894a7{display:-webkit-box;display:-ms-flexbox;display:flex;-ms-flex-wrap:wrap;flex-wrap:wrap;-webkit-box-align:center;-ms-flex-align:center;align-items:center;-webkit-box-sizing:border-box;box-sizing:border-box;border:1px solid "},{theme:"neutralTertiary",defaultValue:"#a19f9d"},{rawString:";min-width:180px;padding:1px;min-height:32px}.pickerText_cc9894a7:hover{border-color:"},{theme:"themeLight",defaultValue:"#c7e0f4"},{rawString:"}.pickerInput_cc9894a7{height:34px;border:none;-webkit-box-flex:1;-ms-flex-positive:1;flex-grow:1;outline:0;padding:0 6px 0;margin:1px}.pickerInput_cc9894a7::-ms-clear{display:none}"}]);var EC,TC="pickerText_cc9894a7",PC="pickerInput_cc9894a7",RC=e,MC=(l(NC,EC=gt.Component),Object.defineProperty(NC.prototype,"items",{get:function(){var e,t;return null!==(t=null!==(t=null!==(e=this.props.selectedItems)&&void 0!==e?e:null===(t=this.selectedItemsList.current)\|\|void 0===t?void 0:t.items)&&void 0!==t?t:this.props.defaultSelectedItems)&&void 0!==t?t:null},enumerable:!1,configurable:!0}),NC.prototype.componentDidMount=function(){this.forceUpdate()},NC.prototype.focus=function(){this.input.current&&this.input.current.focus()},NC.prototype.clearInput=function(){this.input.current&&this.input.current.clear()},Object.defineProperty(NC.prototype,"inputElement",{get:function(){return this.input.current&&this.input.current.inputElement},enumerable:!1,configurable:!0}),Object.defineProperty(NC.prototype,"highlightedItems",{get:function(){return this.selectedItemsList.current?this.selectedItemsList.current.highlightedItems():[]},enumerable:!1,configurable:!0}),NC.prototype.render=function(){var e=this.props,t=e.className,o=e.inputProps,n=e.disabled,r=e.focusZoneProps,i=this.floatingPicker.current&&-1!==this.floatingPicker.current.currentSelectedSuggestionIndex?"sug-"+this.floatingPicker.current.currentSelectedSuggestionIndex:void 0,e=!!this.floatingPicker.current&&this.floatingPicker.current.isSuggestionsShown;return gt.createElement("div",{ref:this.root,className:Tr("ms-BasePicker ms-BaseExtendedPicker",t\|\|""),onKeyDown:this.onBackspace,onCopy:this.onCopy},gt.createElement(Zs,ht({direction:Ei.bidirectional},r),gt.createElement(Pv,{selection:this.selection,selectionMode:dv.multiple},gt.createElement("div",{className:Tr("ms-BasePicker-text",RC.pickerText),role:"list"},this.props.headerComponent,this.renderSelectedItemsList(),this.canAddItems()&&gt.createElement(ki,ht({},o,{className:Tr("ms-BasePicker-input",RC.pickerInput),ref:this.input,onFocus:this.onInputFocus,onClick:this.onInputClick,onInputValueChange:this.onInputChange,"aria-activedescendant":i,"aria-owns":e?"suggestion-list":void 0,"aria-expanded":e,"aria-haspopup":"true",role:"combobox",disabled:n,onPaste:this.onPaste}))))),this.renderFloatingPicker())},Object.defineProperty(NC.prototype,"floatingPickerProps",{get:function(){return this.props.floatingPickerProps},enumerable:!1,configurable:!0}),Object.defineProperty(NC.prototype,"selectedItemsListProps",{get:function(){return this.props.selectedItemsListProps},enumerable:!1,configurable:!0}),NC.prototype.canAddItems=function(){var e=this.props.itemLimit;return void 0===e\|\|this.items.length<e},NC.prototype.renderFloatingPicker=function(){var e=this.props.onRenderFloatingPicker;return gt.createElement(e,ht({componentRef:this.floatingPicker,onChange:this._onSuggestionSelected,onSuggestionsHidden:this._onSuggestionsShownOrHidden,onSuggestionsShown:this._onSuggestionsShownOrHidden,inputElement:this.input.current?this.input.current.inputElement:void 0,selectedItems:this.items,suggestionItems:this.props.suggestionItems\|\|void 0},this.floatingPickerProps))},NC.prototype.renderSelectedItemsList=function(){var e=this.props.onRenderSelectedItems;return gt.createElement(e,ht({componentRef:this.selectedItemsList,selection:this.selection,selectedItems:this.props.selectedItems\|\|void 0,onItemsDeleted:this.props.selectedItems?this.props.onItemsRemoved:void 0},this.selectedItemsListProps))},NC.prototype._addProcessedItem=function(e){this.props.onItemAdded&&this.props.onItemAdded(e),this.selectedItemsList.current&&this.selectedItemsList.current.addItems([e]),this.input.current&&this.input.current.clear(),this.floatingPicker.current&&this.floatingPicker.current.hidePicker(),this.focus()},NC);function NC(e){var r=EC.call(this,e)\|\|this;return r.floatingPicker=gt.createRef(),r.selectedItemsList=gt.createRef(),r.root=gt.createRef(),r.input=gt.createRef(),r.onSelectionChange=function(){r.forceUpdate()},r.onInputChange=function(e,t){t\|\|(r.setState({queryString:e}),r.floatingPicker.current&&r.floatingPicker.current.onQueryStringChanged(e))},r.onInputFocus=function(e){r.selectedItemsList.current&&r.selectedItemsList.current.unselectAll(),r.props.inputProps&&r.props.inputProps.onFocus&&r.props.inputProps.onFocus(e)},r.onInputClick=function(e){var t;r.selectedItemsList.current&&r.selectedItemsList.current.unselectAll(),r.floatingPicker.current&&r.inputElement&&(t=""===r.inputElement.value\|\|r.inputElement.value!==r.floatingPicker.current.inputText,r.floatingPicker.current.showPicker(t))},r.onBackspace=function(e){e.which===En.backspace&&r.selectedItemsList.current&&r.items.length&&(r.input.current&&!r.input.current.isValueSelected&&r.input.current.inputElement===e.currentTarget.ownerDocument.activeElement&&0===r.input.current.cursorLocation?(r.floatingPicker.current&&r.floatingPicker.current.hidePicker(),e.preventDefault(),r.selectedItemsList.current.removeItemAt(r.items.length-1),r._onSelectedItemsChanged()):r.selectedItemsList.current.hasSelectedItems()&&(r.floatingPicker.current&&r.floatingPicker.current.hidePicker(),e.preventDefault(),r.selectedItemsList.current.removeSelectedItems(),r._onSelectedItemsChanged()))},r.onCopy=function(e){r.selectedItemsList.current&&r.selectedItemsList.current.onCopy(e)},r.onPaste=function(e){var t;r.props.onPaste&&(t=e.clipboardData.getData("Text"),e.preventDefault(),r.props.onPaste(t))},r._onSuggestionSelected=function(e){var t,o=r.props.currentRenderedQueryString,n=r.state.queryString;void 0!==o&&o!==n\|\|null!==(n=r.props.onItemSelected?r.props.onItemSelected(e):e)&&((e=n)&&n.then?n.then(function(e){t=e,r._addProcessedItem(t)}):(t=e,r._addProcessedItem(t)))},r._onSelectedItemsChanged=function(){r.focus()},r._onSuggestionsShownOrHidden=function(){r.forceUpdate()},fi(r),r.selection=new fv({onSelectionChanged:function(){return r.onSelectionChange()}}),r.state={queryString:""},r}Dt([{rawString:".resultContent_ae2a2ef5{display:table-row}.resultContent_ae2a2ef5 .resultItem_ae2a2ef5{display:table-cell;vertical-align:bottom}.peoplePickerPersona_ae2a2ef5{width:180px}.peoplePickerPersona_ae2a2ef5 .ms-Persona-details{width:100%}.peoplePicker_ae2a2ef5 .ms-BasePicker-text{min-height:40px}.peoplePickerPersonaContent_ae2a2ef5{display:-webkit-box;display:-ms-flexbox;display:flex;width:100%;-webkit-box-pack:justify;-ms-flex-pack:justify;justify-content:space-between;-webkit-box-align:center;-ms-flex-align:center;align-items:center}"}]);var BC,FC,AC,LC=(l(zC,AC=MC),zC),HC=(l(OC,FC=LC),OC);function OC(){return null!==FC&&FC.apply(this,arguments)\|\|this}function zC(){return null!==AC&&AC.apply(this,arguments)\|\|this}(ke=BC=BC\|\|{})[ke.none=0]="none",ke[ke.descriptive=1]="descriptive",ke[ke.more=2]="more",ke[ke.downArrow=3]="downArrow";var WC,VC=Ao(function(e,t,o){var n=td(e),r=un(n,o);return ht(ht({},r),{root:[n.root,t,e.fonts.medium,o&&o.root]})}),KC=(l(qC,WC=gt.Component),qC.prototype.render=function(){var e=this.props,t=e.className,o=e.styles,e=mt(e,["className","styles"]),o=VC(this.props.theme,t,o);return gt.createElement(Yu,ht({},e,{variantClassName:"ms-Button--facepile",styles:o,onRenderDescription:wa}))},c([Xu("FacepileButton",["theme","styles"],!0)],qC)),GC=Fn(),UC={size:Pr.size48,presence:Rr.none,imageAlt:"",showOverflowTooltip:!0},jC=gt.forwardRef(function(e,t){function o(){return r.text\|\|r.primaryText\|\|""}function n(e,t,o){return gt.createElement("div",{dir:"auto",className:e},t&&t(r,o))}var r=Hn(UC,e),i=_r(t,gt.useRef(null)),s=function(e,t){return void 0===t&&(t=!0),e?t?function(){return gt.createElement(Rd,{content:e,overflowMode:md.Parent,directionalHint:Pa.topLeftEdge},e)}:function(){return gt.createElement(gt.Fragment,null,e)}:void 0},a=s(o(),r.showOverflowTooltip),l=s(r.secondaryText,r.showOverflowTooltip),c=s(r.tertiaryText,r.showOverflowTooltip),u=s(r.optionalText,r.showOverflowTooltip),d=r.hidePersonaDetails,p=r.onRenderOptionalText,h=void 0===p?u:p,m=r.onRenderPrimaryText,g=void 0===m?a:m,f=r.onRenderSecondaryText,v=void 0===f?l:f,b=r.onRenderTertiaryText,y=void 0===b?c:b,C=r.onRenderPersonaCoin,_=void 0===C?function(e){return gt.createElement(ui,ht({},e))}:C,S=r.size,x=r.allowPhoneInitials,k=r.className,w=r.coinProps,I=r.showUnknownPersonaCoin,D=r.coinSize,E=r.styles,T=r.imageAlt,P=r.imageInitials,R=r.imageShouldFadeIn,M=r.imageShouldStartVisible,N=r.imageUrl,B=r.initialsColor,F=r.initialsTextColor,A=r.isOutOfOffice,L=r.onPhotoLoadingStateChange,e=r.onRenderCoin,t=r.onRenderInitials,s=r.presence,p=r.presenceTitle,m=r.presenceColors,f=r.showInitialsUntilImageLoads,b=r.showSecondaryText,C=r.theme,w=ht({allowPhoneInitials:x,showUnknownPersonaCoin:I,coinSize:D,imageAlt:T,imageInitials:P,imageShouldFadeIn:R,imageShouldStartVisible:M,imageUrl:N,initialsColor:B,initialsTextColor:F,onPhotoLoadingStateChange:L,onRenderCoin:e,onRenderInitials:t,presence:s,presenceTitle:p,showInitialsUntilImageLoads:f,size:S,text:o(),isOutOfOffice:A,presenceColors:m},w),b=GC(E,{theme:C,className:k,showSecondaryText:b,presence:s,size:S}),s=ur(r,cr),u=gt.createElement("div",{className:b.details},n(b.primaryText,g,a),n(b.secondaryText,v,l),n(b.tertiaryText,y,c),n(b.optionalText,h,u),r.children);return gt.createElement("div",ht({},s,{ref:i,className:b.root,style:D?{height:D,minWidth:D}:void 0}),_(w,_),(!d\|\|S===Pr.size8\|\|S===Pr.size10\|\|S===Pr.tiny)&&u)});function qC(){return null!==WC&&WC.apply(this,arguments)\|\|this}jC.displayName="PersonaBase";var YC,ZC={root:"ms-Persona",size8:"ms-Persona--size8",size10:"ms-Persona--size10",size16:"ms-Persona--size16",size24:"ms-Persona--size24",size28:"ms-Persona--size28",size32:"ms-Persona--size32",size40:"ms-Persona--size40",size48:"ms-Persona--size48",size56:"ms-Persona--size56",size72:"ms-Persona--size72",size100:"ms-Persona--size100",size120:"ms-Persona--size120",available:"ms-Persona--online",away:"ms-Persona--away",blocked:"ms-Persona--blocked",busy:"ms-Persona--busy",doNotDisturb:"ms-Persona--donotdisturb",offline:"ms-Persona--offline",details:"ms-Persona-details",primaryText:"ms-Persona-primaryText",secondaryText:"ms-Persona-secondaryText",tertiaryText:"ms-Persona-tertiaryText",optionalText:"ms-Persona-optionalText",textContent:"ms-Persona-textContent"},XC=In(jC,function(e){var t=e.className,o=e.showSecondaryText,n=e.theme,r=n.semanticColors,i=n.fonts,s=zo(ZC,n),a=Kr(e.size),l=Ur(e.presence),c="16px",e={color:r.bodySubtext,fontWeight:Fe.regular,fontSize:i.small.fontSize};return{root:[s.root,n.fonts.medium,Uo,{color:r.bodyText,position:"relative",height:Nr.size48,minWidth:Nr.size48,display:"flex",alignItems:"center",selectors:{".contextualHost":{display:"none"}}},a.isSize8&&[s.size8,{height:Nr.size8,minWidth:Nr.size8}],a.isSize10&&[s.size10,{height:Nr.size10,minWidth:Nr.size10}],a.isSize16&&[s.size16,{height:Nr.size16,minWidth:Nr.size16}],a.isSize24&&[s.size24,{height:Nr.size24,minWidth:Nr.size24}],a.isSize24&&o&&{height:"36px"},a.isSize28&&[s.size28,{height:Nr.size28,minWidth:Nr.size28}],a.isSize28&&o&&{height:"32px"},a.isSize32&&[s.size32,{height:Nr.size32,minWidth:Nr.size32}],a.isSize40&&[s.size40,{height:Nr.size40,minWidth:Nr.size40}],a.isSize48&&s.size48,a.isSize56&&[s.size56,{height:Nr.size56,minWidth:Nr.size56}],a.isSize72&&[s.size72,{height:Nr.size72,minWidth:Nr.size72}],a.isSize100&&[s.size100,{height:Nr.size100,minWidth:Nr.size100}],a.isSize120&&[s.size120,{height:Nr.size120,minWidth:Nr.size120}],l.isAvailable&&s.available,l.isAway&&s.away,l.isBlocked&&s.blocked,l.isBusy&&s.busy,l.isDoNotDisturb&&s.doNotDisturb,l.isOffline&&s.offline,t],details:[s.details,{padding:"0 24px 0 16px",minWidth:0,width:"100%",textAlign:"left",display:"flex",flexDirection:"column",justifyContent:"space-around"},(a.isSize8\|\|a.isSize10)&&{paddingLeft:17},(a.isSize24\|\|a.isSize28\|\|a.isSize32)&&{padding:"0 8px"},(a.isSize40\|\|a.isSize48)&&{padding:"0 12px"}],primaryText:[s.primaryText,jo,{color:r.bodyText,fontWeight:Fe.regular,fontSize:i.medium.fontSize,selectors:{":hover":{color:r.inputTextHovered}}},o&&{height:c,lineHeight:c,overflowX:"hidden"},(a.isSize8\|\|a.isSize10)&&{fontSize:i.small.fontSize,lineHeight:Nr.size8},a.isSize16&&{lineHeight:Nr.size28},(a.isSize24\|\|a.isSize28\|\|a.isSize32\|\|a.isSize40\|\|a.isSize48)&&o&&{height:18},(a.isSize56\|\|a.isSize72\|\|a.isSize100\|\|a.isSize120)&&{fontSize:i.xLarge.fontSize},(a.isSize56\|\|a.isSize72\|\|a.isSize100\|\|a.isSize120)&&o&&{height:22}],secondaryText:[s.secondaryText,jo,e,(a.isSize8\|\|a.isSize10\|\|a.isSize16\|\|a.isSize24\|\|a.isSize28\|\|a.isSize32)&&{display:"none"},o&&{display:"block",height:c,lineHeight:c,overflowX:"hidden"},a.isSize24&&o&&{height:18},(a.isSize56\|\|a.isSize72\|\|a.isSize100\|\|a.isSize120)&&{fontSize:i.medium.fontSize},(a.isSize56\|\|a.isSize72\|\|a.isSize100\|\|a.isSize120)&&o&&{height:18}],tertiaryText:[s.tertiaryText,jo,e,{display:"none",fontSize:i.medium.fontSize},(a.isSize72\|\|a.isSize100\|\|a.isSize120)&&{display:"block"}],optionalText:[s.optionalText,jo,e,{display:"none",fontSize:i.medium.fontSize},(a.isSize100\|\|a.isSize120)&&{display:"block"}],textContent:[s.textContent,jo]}},void 0,{scope:"Persona"}),QC=Fn(),JC=(l(t_,YC=gt.Component),t_.prototype.render=function(){var e=this.props.overflowButtonProps,t=this.props,o=t.chevronButtonProps,n=t.maxDisplayablePersonas,r=t.personas,i=t.overflowPersonas,s=t.showAddButton,a=t.ariaLabel,l=t.showTooltip,c=void 0===l\|\|l,t=this._classNames,l="number"==typeof n?Math.min(r.length,n):r.length;o&&!e&&(e=o);n=i&&0<i.length,o=n?r:r.slice(0,l),l=(n?i:r.slice(l))\|\|[];return gt.createElement("div",{className:t.root},this.onRenderAriaDescription(),gt.createElement("div",{className:t.itemContainer},s?this._getAddNewElement():null,gt.createElement("ul",{className:t.members,"aria-label":a},this._onRenderVisiblePersonas(o,0===l.length&&1===r.length,c)),e?this._getOverflowElement(l):null))},t_.prototype.onRenderAriaDescription=function(){var e=this.props.ariaDescription,t=this._classNames;return e&&gt.createElement("span",{className:t.screenReaderOnly,id:this._ariaDescriptionId},e)},t_.prototype._onRenderVisiblePersonas=function(e,n,r){var i=this,t=this.props,o=t.onRenderPersona,s=void 0===o?this._getPersonaControl:o,t=t.onRenderPersonaCoin,a=void 0===t?this._getPersonaCoinControl:t;return e.map(function(e,t){var o=n?s(e,i._getPersonaControl):a(e,i._getPersonaCoinControl);return gt.createElement("li",{key:(n?"persona":"personaCoin")+"-"+t,className:i._classNames.member},e.onClick?i._getElementWithOnClickEvent(o,e,r,t):i._getElementWithoutOnClickEvent(o,e,r,t))})},t_.prototype._getElementWithOnClickEvent=function(e,t,o,n){var r=t.keytipProps;return gt.createElement(KC,ht({},ur(t,Yn),this._getElementProps(t,o,n),{keytipProps:r,onClick:this._onPersonaClick.bind(this,t)}),e)},t_.prototype._getElementWithoutOnClickEvent=function(e,t,o,n){return gt.createElement("div",ht({},ur(t,Yn),this._getElementProps(t,o,n)),e)},t_.prototype._getElementProps=function(e,t,o){var n=this._classNames;return{key:(e.imageUrl?"i":"")+o,"data-is-focusable":!0,className:n.itemButton,title:t?e.personaName:void 0,onMouseMove:this._onPersonaMouseMove.bind(this,e),onMouseOut:this._onPersonaMouseOut.bind(this,e)}},t_.prototype._getOverflowElement=function(e){switch(this.props.overflowButtonType){case BC.descriptive:return this._getDescriptiveOverflowElement(e);case BC.downArrow:return this._getIconElement("ChevronDown");case BC.more:return this._getIconElement("More");default:return null}},t_.prototype._getDescriptiveOverflowElement=function(e){var t=this.props.personaSize;if(!e\|\|e.length<1)return null;var o=e.map(function(e){return e.personaName}).join(", "),n=ht({title:o},this.props.overflowButtonProps),o=Math.max(e.length,0),e=this._classNames;return gt.createElement(KC,ht({},n,{ariaDescription:n.title,className:e.descriptiveOverflowButton}),gt.createElement(ui,{size:t,onRenderInitials:this._renderInitialsNotPictured(o),initialsColor:Mr.transparent}))},t_.prototype._getIconElement=function(e){var t=this.props,o=t.overflowButtonProps,n=t.personaSize,t=this._classNames;return gt.createElement(KC,ht({},o,{className:t.overflowButton}),gt.createElement(ui,{size:n,onRenderInitials:this._renderInitials(e,!0),initialsColor:Mr.transparent}))},t_.prototype._getAddNewElement=function(){var e=this.props,t=e.addButtonProps,o=e.personaSize,e=this._classNames;return gt.createElement(KC,ht({},t,{className:e.addButton}),gt.createElement(ui,{size:o,onRenderInitials:this._renderInitials("AddFriend")}))},t_.prototype._onPersonaClick=function(e,t){e.onClick(t,e),t.preventDefault(),t.stopPropagation()},t_.prototype._onPersonaMouseMove=function(e,t){e.onMouseMove&&e.onMouseMove(t,e)},t_.prototype._onPersonaMouseOut=function(e,t){e.onMouseOut&&e.onMouseOut(t,e)},t_.prototype._renderInitials=function(e,t){var o=this._classNames;return function(){return gt.createElement(Wr,{iconName:e,className:t?o.overflowInitialsIcon:""})}},t_.prototype._renderInitialsNotPictured=function(e){var t=this._classNames;return function(){return gt.createElement("span",{className:t.overflowInitialsIcon},e<100?"+"+e:"99+")}},t_.defaultProps={maxDisplayablePersonas:5,personas:[],overflowPersonas:[],personaSize:Pr.size32},t_),$C={root:"ms-Facepile",addButton:"ms-Facepile-addButton ms-Facepile-itemButton",descriptiveOverflowButton:"ms-Facepile-descriptiveOverflowButton ms-Facepile-itemButton",itemButton:"ms-Facepile-itemButton ms-Facepile-person",itemContainer:"ms-Facepile-itemContainer",members:"ms-Facepile-members",member:"ms-Facepile-member",overflowButton:"ms-Facepile-overflowButton ms-Facepile-itemButton"},e_=In(JC,function(e){var t=e.className,o=e.theme,n=e.spacingAroundItemButton,r=void 0===n?2:n,i=o.palette,s=o.fonts,e=zo($C,o),n={textAlign:"center",padding:0,borderRadius:"50%",verticalAlign:"top",display:"inline",backgroundColor:"transparent",border:"none",selectors:{"&::-moz-focus-inner":{padding:0,border:0}}};return{root:[e.root,o.fonts.medium,{width:"auto"},t],addButton:[e.addButton,bo(o,{inset:-1}),n,{fontSize:s.medium.fontSize,color:i.white,backgroundColor:i.themePrimary,marginRight:2r+"px",selectors:{"&:hover":{backgroundColor:i.themeDark},"&:focus":{backgroundColor:i.themeDark},"&:active":{backgroundColor:i.themeDarker},"&:disabled":{backgroundColor:i.neutralTertiaryAlt}}}],descriptiveOverflowButton:[e.descriptiveOverflowButton,bo(o,{inset:-1}),n,{fontSize:s.small.fontSize,color:i.neutralSecondary,backgroundColor:i.neutralLighter,marginLeft:2r+"px"}],itemButton:[e.itemButton,n],itemContainer:[e.itemContainer,{display:"flex"}],members:[e.members,{display:"flex",overflow:"hidden",listStyleType:"none",padding:0,margin:"-"+r+"px"}],member:[e.member,{display:"inline-flex",flex:"0 0 auto",margin:r+"px"}],overflowButton:[e.overflowButton,bo(o,{inset:-1}),n,{fontSize:s.medium.fontSize,color:i.neutralSecondary,backgroundColor:i.neutralLighter,marginLeft:2r+"px"}],overflowInitialsIcon:[{color:i.neutralPrimary,selectors:((i={})[Yt]={color:"WindowText"},i)}],screenReaderOnly:So}},void 0,{scope:"Facepile"});function t_(e){var n=YC.call(this,e)\|\|this;return n._classNames=QC(n.props.styles,{theme:n.props.theme,className:n.props.className}),n._getPersonaControl=function(e){var t=n.props,o=t.getPersonaProps,t=t.personaSize;return gt.createElement(XC,ht({imageInitials:e.imageInitials,imageUrl:e.imageUrl,initialsColor:e.initialsColor,allowPhoneInitials:e.allowPhoneInitials,text:e.personaName,size:t},o?o(e):null,{styles:{details:{flex:"1 0 auto"}}}))},n._getPersonaCoinControl=function(e){var t=n.props,o=t.getPersonaProps,t=t.personaSize;return gt.createElement(ui,ht({imageInitials:e.imageInitials,imageUrl:e.imageUrl,initialsColor:e.initialsColor,allowPhoneInitials:e.allowPhoneInitials,text:e.personaName,size:t},o?o(e):null))},fi(n),n._ariaDescriptionId=_s(),n}Dt([{rawString:".callout_0508e60b .ms-Suggestions-itemButton{padding:0;border:none}.callout_0508e60b .ms-Suggestions{min-width:300px}"}]);var o_="callout_0508e60b";Dt([{rawString:".root_2f55324e{min-width:260px}.suggestionsItem_2f55324e{display:-webkit-box;display:-ms-flexbox;display:flex;-webkit-box-align:stretch;-ms-flex-align:stretch;align-items:stretch;-webkit-box-sizing:border-box;box-sizing:border-box;width:100%;position:relative;overflow:hidden}.suggestionsItem_2f55324e:hover{background:"},{theme:"neutralLighter",defaultValue:"#f3f2f1"},{rawString:"}.suggestionsItem_2f55324e:hover 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.actionButton_2f55324e{text-align:right}.actionButton_2f55324e:hover{background-color:"},{theme:"neutralLight",defaultValue:"#edebe9"},{rawString:";cursor:pointer}.actionButton_2f55324e:active,.actionButton_2f55324e:focus{background-color:"},{theme:"themeLight",defaultValue:"#c7e0f4"},{rawString:"}.actionButton_2f55324e .ms-Button-icon{font-size:16px;width:25px}.actionButton_2f55324e .ms-Button-label{margin:0 4px 0 9px}html[dir=rtl] .actionButton_2f55324e .ms-Button-label{margin:0 9px 0 4px}.buttonSelected_2f55324e{background-color:"},{theme:"themeLight",defaultValue:"#c7e0f4"},{rawString:"}.suggestionsTitle_2f55324e{padding:0 12px;color:"},{theme:"themePrimary",defaultValue:"#0078d4"},{rawString:";font-size:12px;line-height:40px;border-bottom:1px solid "},{theme:"neutralLight",defaultValue:"#edebe9"},{rawString:"}.suggestionsContainer_2f55324e{overflow-y:auto;overflow-x:hidden;max-height:300px;border-bottom:1px solid "},{theme:"neutralLight",defaultValue:"#edebe9"},{rawString:"}.suggestionsNone_2f55324e{text-align:center;color:#797775;font-size:12px;line-height:30px}.suggestionsSpinner_2f55324e{margin:5px 0;white-space:nowrap;line-height:20px;font-size:12px}html[dir=ltr] .suggestionsSpinner_2f55324e{padding-left:14px}html[dir=rtl] .suggestionsSpinner_2f55324e{padding-right:14px}html[dir=ltr] .suggestionsSpinner_2f55324e{text-align:left}html[dir=rtl] .suggestionsSpinner_2f55324e{text-align:right}.suggestionsSpinner_2f55324e .ms-Spinner-circle{display:inline-block;vertical-align:middle}.suggestionsSpinner_2f55324e .ms-Spinner-label{display:inline-block;margin:0 10px 0 16px;vertical-align:middle}html[dir=rtl] .suggestionsSpinner_2f55324e .ms-Spinner-label{margin:0 16px 0 10px}.itemButton_2f55324e.itemButton_2f55324e{width:100%;padding:0;min-width:0;height:100%}@media screen and (-ms-high-contrast:active){.itemButton_2f55324e.itemButton_2f55324e{color:WindowText}}.itemButton_2f55324e.itemButton_2f55324e:hover{color:"},{theme:"neutralDark",defaultValue:"#201f1e"},{rawString:"}.closeButton_2f55324e.closeButton_2f55324e{padding:0 4px;height:auto;width:32px}@media screen and (-ms-high-contrast:active){.closeButton_2f55324e.closeButton_2f55324e{color:WindowText}}.closeButton_2f55324e.closeButton_2f55324e:hover{background:"},{theme:"neutralTertiaryAlt",defaultValue:"#c8c6c4"},{rawString:";color:"},{theme:"neutralDark",defaultValue:"#201f1e"},{rawString:"}.suggestionsAvailable_2f55324e{position:absolute;width:1px;height:1px;padding:0;margin:-1px;overflow:hidden;clip:rect(0,0,0,0);border:0}"}]);var n_,r_="root_2f55324e",i_="suggestionsItem_2f55324e",s_="closeButton_2f55324e",a_="suggestionsItemIsSuggested_2f55324e",l_="itemButton_2f55324e",c_="actionButton_2f55324e",u_="buttonSelected_2f55324e",d_="suggestionsTitle_2f55324e",p_="suggestionsContainer_2f55324e",h_="suggestionsNone_2f55324e",m_="suggestionsSpinner_2f55324e",g_="suggestionsAvailable_2f55324e",f_=o,v_=Fn(),b_=(l(y_,n_=gt.Component),y_.prototype.render=function(){var e=this.props,t=e.suggestionModel,o=e.RenderSuggestion,n=e.onClick,r=e.className,i=e.id,s=e.onRemoveItem,a=e.isSelectedOverride,l=e.removeButtonAriaLabel,c=e.styles,u=e.theme,e=e.removeButtonIconProps,r=c?v_(c,{theme:u,className:r,suggested:t.selected\|\|a}):{root:Tr("ms-Suggestions-item",f_.suggestionsItem,((u={})["is-suggested "+f_.suggestionsItemIsSuggested]=t.selected\|\|a,u),r),itemButton:Tr("ms-Suggestions-itemButton",f_.itemButton),closeButton:Tr("ms-Suggestions-closeButton",f_.closeButton)};return gt.createElement("div",{className:r.root,role:"presentation"},gt.createElement(up,{onClick:n,className:r.itemButton,id:i,"aria-selected":t.selected,role:"option","aria-label":t.ariaLabel},o(t.item,this.props)),this.props.showRemoveButton?gt.createElement(rd,{iconProps:null!=e?e:{iconName:"Cancel"},styles:{icon:{fontSize:"12px"}},title:l,ariaLabel:l,onClick:s,className:r.closeButton}):null)},y_);function y_(e){e=n_.call(this,e)\|\|this;return fi(e),e}Dt([{rawString:".suggestionsContainer_a151d363{overflow-y:auto;overflow-x:hidden;max-height:300px}.suggestionsContainer_a151d363 .ms-Suggestion-item:hover{background-color:"},{theme:"neutralLighter",defaultValue:"#f3f2f1"},{rawString:";cursor:pointer}.suggestionsContainer_a151d363 .is-suggested{background-color:"},{theme:"themeLighter",defaultValue:"#deecf9"},{rawString:"}.suggestionsContainer_a151d363 .is-suggested:hover{background-color:"},{theme:"themeLight",defaultValue:"#c7e0f4"},{rawString:";cursor:pointer}"}]);var C_,__="suggestionsContainer_a151d363",S_=n,x_=(l(k_,C_=gt.Component),k_.prototype.nextSuggestion=function(){var e=this.props.suggestions;if(e&&0<e.length){if(-1===this.currentIndex)return this.setSelectedSuggestion(0),!0;if(this.currentIndex<e.length-1)return this.setSelectedSuggestion(this.currentIndex+1),!0;if(this.props.shouldLoopSelection&&this.currentIndex===e.length-1)return this.setSelectedSuggestion(0),!0}return!1},k_.prototype.previousSuggestion=function(){var e=this.props.suggestions;if(e&&0<e.length){if(-1===this.currentIndex)return this.setSelectedSuggestion(e.length-1),!0;if(0<this.currentIndex)return this.setSelectedSuggestion(this.currentIndex-1),!0;if(this.props.shouldLoopSelection&&0===this.currentIndex)return this.setSelectedSuggestion(e.length-1),!0}return!1},Object.defineProperty(k_.prototype,"selectedElement",{get:function(){return this._selectedElement.current\|\|void 0},enumerable:!1,configurable:!0}),k_.prototype.getCurrentItem=function(){return this.props.suggestions[this.currentIndex]},k_.prototype.getSuggestionAtIndex=function(e){return this.props.suggestions[e]},k_.prototype.hasSuggestionSelected=function(){return-1!==this.currentIndex&&this.currentIndex<this.props.suggestions.length},k_.prototype.removeSuggestion=function(e){this.props.suggestions.splice(e,1)},k_.prototype.deselectAllSuggestions=function(){-1<this.currentIndex&&this.props.suggestions[this.currentIndex]&&(this.props.suggestions[this.currentIndex].selected=!1,this.currentIndex=-1,this.forceUpdate())},k_.prototype.setSelectedSuggestion=function(e){var t=this.props.suggestions;e>t.length-1\|\|e<0?(this.currentIndex=0,this.currentSuggestion.selected=!1,this.currentSuggestion=t[0],this.currentSuggestion.selected=!0):(-1<this.currentIndex&&t[this.currentIndex]&&(t[this.currentIndex].selected=!1),t[e].selected=!0,this.currentIndex=e,this.currentSuggestion=t[e]),this.forceUpdate()},k_.prototype.componentDidUpdate=function(){this.scrollSelected()},k_.prototype.render=function(){var o=this,e=this.props,n=e.onRenderSuggestion,r=e.suggestionsItemClassName,t=e.resultsMaximumNumber,i=e.showRemoveButtons,s=e.suggestionsContainerAriaLabel,a=this.SuggestionsItemOfProperType,e=this.props.suggestions;return t&&(e=e.slice(0,t)),gt.createElement("div",{className:Tr("ms-Suggestions-container",S_.suggestionsContainer),id:"suggestion-list",role:"list","aria-label":s},e.map(function(e,t){return gt.createElement("div",{ref:e.selected\|\|t===o.currentIndex?o._selectedElement:void 0,key:e.item.key\|\|t,id:"sug-"+t,role:"listitem","aria-label":e.ariaLabel},gt.createElement(a,{id:"sug-item"+t,suggestionModel:e,RenderSuggestion:n,onClick:o._onClickTypedSuggestionsItem(e.item,t),className:r,showRemoveButton:i,onRemoveItem:o._onRemoveTypedSuggestionsItem(e.item,t),isSelectedOverride:t===o.currentIndex}))}))},k_.prototype.scrollSelected=function(){var e;void 0!==(null===(e=this._selectedElement.current)\|\|void 0===e?void 0:e.scrollIntoView)&&this._selectedElement.current.scrollIntoView(!1)},k_);function k_(e){var n=C_.call(this,e)\|\|this;return n._selectedElement=gt.createRef(),n.SuggestionsItemOfProperType=b_,n._onClickTypedSuggestionsItem=function(t,o){return function(e){n.props.onSuggestionClick(e,t,o)}},n._onRemoveTypedSuggestionsItem=function(t,o){return function(e){(0,n.props.onSuggestionRemove)(e,t,o),e.stopPropagation()}},fi(n),n.currentIndex=-1,n}Dt([{rawString:".root_e4eecb3d{min-width:260px}.actionButton_e4eecb3d{background:0 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(-ms-high-contrast:active){.buttonSelected_e4eecb3d:hover{background-color:Highlight;color:HighlightText}}@media screen and (-ms-high-contrast:active){.buttonSelected_e4eecb3d{background-color:Highlight;color:HighlightText;-ms-high-contrast-adjust:none}}.suggestionsTitle_e4eecb3d{font-size:12px}.suggestionsSpinner_e4eecb3d{margin:5px 0;white-space:nowrap;line-height:20px;font-size:12px}html[dir=ltr] .suggestionsSpinner_e4eecb3d{padding-left:14px}html[dir=rtl] .suggestionsSpinner_e4eecb3d{padding-right:14px}html[dir=ltr] .suggestionsSpinner_e4eecb3d{text-align:left}html[dir=rtl] .suggestionsSpinner_e4eecb3d{text-align:right}.suggestionsSpinner_e4eecb3d .ms-Spinner-circle{display:inline-block;vertical-align:middle}.suggestionsSpinner_e4eecb3d .ms-Spinner-label{display:inline-block;margin:0 10px 0 16px;vertical-align:middle}html[dir=rtl] .suggestionsSpinner_e4eecb3d .ms-Spinner-label{margin:0 16px 0 10px}.itemButton_e4eecb3d{height:100%;width:100%;padding:7px 12px}@media screen and (-ms-high-contrast:active){.itemButton_e4eecb3d{color:WindowText}}.screenReaderOnly_e4eecb3d{position:absolute;width:1px;height:1px;padding:0;margin:-1px;overflow:hidden;clip:rect(0,0,0,0);border:0}"}]);var w_,I_="root_e4eecb3d",D_="actionButton_e4eecb3d",E_="buttonSelected_e4eecb3d",T_="suggestionsTitle_e4eecb3d",P_="suggestionsSpinner_e4eecb3d",R_="itemButton_e4eecb3d",M_="screenReaderOnly_e4eecb3d",N_=r;(K=w_=w_\|\|{})[K.header=0]="header",K[K.suggestion=1]="suggestion",K[K.footer=2]="footer";var B_,F_,A_,L_=(l(K_,A_=gt.Component),K_.prototype.render=function(){var e=this.props,t=e.renderItem,o=e.onExecute,n=e.isSelected,r=e.id,e=e.className;return o?gt.createElement("div",{id:r,onClick:o,className:Tr("ms-Suggestions-sectionButton",e,N_.actionButton,((o={})["is-selected "+N_.buttonSelected]=n,o))},t()):gt.createElement("div",{id:r,className:Tr("ms-Suggestions-section",e,N_.suggestionsTitle)},t())},K_),H_=(l(V_,F_=gt.Component),V_.prototype.componentDidMount=function(){this.resetSelectedItem()},V_.prototype.componentDidUpdate=function(e){var t=this;this.scrollSelected(),e.suggestions&&e.suggestions!==this.props.suggestions&&this.setState({suggestions:this.props.suggestions},function(){t.resetSelectedItem()})},V_.prototype.componentWillUnmount=function(){var e;null===(e=this._suggestions.current)\|\|void 0===e\|\|e.deselectAllSuggestions()},V_.prototype.render=function(){var e=this.props,t=e.className,o=e.headerItemsProps,n=e.footerItemsProps,r=e.suggestionsAvailableAlertText,i=j(So),e=this.state.suggestions&&0<this.state.suggestions.length&&r;return gt.createElement("div",{className:Tr("ms-Suggestions",t\|\|"",N_.root)},o&&this.renderHeaderItems(),this._renderSuggestions(),n&&this.renderFooterItems(),e?gt.createElement("span",{role:"alert","aria-live":"polite",className:i},r):null)},Object.defineProperty(V_.prototype,"currentSuggestion",{get:function(){var e;return(null===(e=this._suggestions.current)\|\|void 0===e?void 0:e.getCurrentItem())\|\|void 0},enumerable:!1,configurable:!0}),Object.defineProperty(V_.prototype,"currentSuggestionIndex",{get:function(){return this._suggestions.current?this._suggestions.current.currentIndex:-1},enumerable:!1,configurable:!0}),Object.defineProperty(V_.prototype,"selectedElement",{get:function(){var e;return this._selectedElement.current\|\|(null===(e=this._suggestions.current)\|\|void 0===e?void 0:e.selectedElement)},enumerable:!1,configurable:!0}),V_.prototype.hasSuggestionSelected=function(){var e;return(null===(e=this._suggestions.current)\|\|void 0===e?void 0:e.hasSuggestionSelected())\|\|!1},V_.prototype.hasSelection=function(){var e=this.state,t=e.selectedHeaderIndex,e=e.selectedFooterIndex;return-1!==t\|\|this.hasSuggestionSelected()\|\|-1!==e},V_.prototype.executeSelectedAction=function(){var e,t=this.props,o=t.headerItemsProps,n=t.footerItemsProps,r=this.state,t=r.selectedHeaderIndex,r=r.selectedFooterIndex;o&&-1!==t&&t<o.length?(e=o[t]).onExecute&&e.onExecute():null!==(e=this._suggestions.current)&&void 0!==e&&e.hasSuggestionSelected()?this.props.completeSuggestion():n&&-1!==r&&r<n.length&&((r=n[r]).onExecute&&r.onExecute())},V_.prototype.removeSuggestion=function(e){var t;null===(t=this._suggestions.current)\|\|void 0===t\|\|t.removeSuggestion(e\|\|(null===(e=this._suggestions.current)\|\|void 0===e?void 0:e.currentIndex))},V_.prototype.handleKeyDown=function(e){var t,o=this.state,n=o.selectedHeaderIndex,r=o.selectedFooterIndex,i=!1;return e===En.down?-1!==n\|\|null!==(o=this._suggestions.current)&&void 0!==o&&o.hasSuggestionSelected()\|\|-1!==r?-1!==n?(this.selectNextItem(w_.header),i=!0):null!==(t=this._suggestions.current)&&void 0!==t&&t.hasSuggestionSelected()?(this.selectNextItem(w_.suggestion),i=!0):-1!==r&&(this.selectNextItem(w_.footer),i=!0):this.selectFirstItem():e===En.up?-1!==n\|\|null!==(t=this._suggestions.current)&&void 0!==t&&t.hasSuggestionSelected()\|\|-1!==r?-1!==n?(this.selectPreviousItem(w_.header),i=!0):null!==(n=this._suggestions.current)&&void 0!==n&&n.hasSuggestionSelected()?(this.selectPreviousItem(w_.suggestion),i=!0):-1!==r&&(this.selectPreviousItem(w_.footer),i=!0):this.selectLastItem():e!==En.enter&&e!==En.tab\|\|this.hasSelection()&&(this.executeSelectedAction(),i=!0),i},V_.prototype.scrollSelected=function(){this._selectedElement.current&&this._selectedElement.current.scrollIntoView(!1)},V_.prototype.renderHeaderItems=function(){var n=this,e=this.props,t=e.headerItemsProps,e=e.suggestionsHeaderContainerAriaLabel,r=this.state.selectedHeaderIndex;return t?gt.createElement("div",{className:Tr("ms-Suggestions-headerContainer",N_.suggestionsContainer),id:"suggestionHeader-list",role:"list","aria-label":e},t.map(function(e,t){var o=-1!==r&&r===t;return e.shouldShow()?gt.createElement("div",{ref:o?n._selectedElement:void 0,id:"sug-header"+t,key:"sug-header"+t,role:"listitem","aria-label":e.ariaLabel},gt.createElement(L_,{id:"sug-header-item"+t,isSelected:o,renderItem:e.renderItem,onExecute:e.onExecute,className:e.className})):null})):null},V_.prototype.renderFooterItems=function(){var n=this,e=this.props,t=e.footerItemsProps,e=e.suggestionsFooterContainerAriaLabel,r=this.state.selectedFooterIndex;return t?gt.createElement("div",{className:Tr("ms-Suggestions-footerContainer",N_.suggestionsContainer),id:"suggestionFooter-list",role:"list","aria-label":e},t.map(function(e,t){var o=-1!==r&&r===t;return e.shouldShow()?gt.createElement("div",{ref:o?n._selectedElement:void 0,id:"sug-footer"+t,key:"sug-footer"+t,role:"listitem","aria-label":e.ariaLabel},gt.createElement(L_,{id:"sug-footer-item"+t,isSelected:o,renderItem:e.renderItem,onExecute:e.onExecute,className:e.className})):null})):null},V_.prototype._renderSuggestions=function(){var e=this.SuggestionsOfProperType;return gt.createElement(e,ht({ref:this._suggestions},this.props,{suggestions:this.state.suggestions}))},V_.prototype.selectNextItem=function(e,t){e!==t?this._selectNextItemOfItemType(e,(t=void 0!==t?t:e)===e?this._getCurrentIndexForType(e):void 0)\|\|this.selectNextItem(this._getNextItemSectionType(e),t):this._selectNextItemOfItemType(e)},V_.prototype.selectPreviousItem=function(e,t){e!==t?this._selectPreviousItemOfItemType(e,(t=void 0!==t?t:e)===e?this._getCurrentIndexForType(e):void 0)\|\|this.selectPreviousItem(this._getPreviousItemSectionType(e),t):this._selectPreviousItemOfItemType(e)},V_.prototype.resetSelectedItem=function(){var e;this.setState({selectedHeaderIndex:-1,selectedFooterIndex:-1}),null===(e=this._suggestions.current)\|\|void 0===e\|\|e.deselectAllSuggestions(),void 0!==this.props.shouldSelectFirstItem&&!this.props.shouldSelectFirstItem()\|\|this.selectFirstItem()},V_.prototype.selectFirstItem=function(){this._selectNextItemOfItemType(w_.header)\|\|this._selectNextItemOfItemType(w_.suggestion)\|\|this._selectNextItemOfItemType(w_.footer)},V_.prototype.selectLastItem=function(){this._selectPreviousItemOfItemType(w_.footer)\|\|this._selectPreviousItemOfItemType(w_.suggestion)\|\|this._selectPreviousItemOfItemType(w_.header)},V_.prototype._selectNextItemOfItemType=function(e,t){var o;if(void 0===t&&(t=-1),e===w_.suggestion){if(this.state.suggestions.length>t+1)return null===(o=this._suggestions.current)\|\|void 0===o\|\|o.setSelectedSuggestion(t+1),this.setState({selectedHeaderIndex:-1,selectedFooterIndex:-1}),!0}else{var n=e===w_.header,r=n?this.props.headerItemsProps:this.props.footerItemsProps;if(r&&r.length>t+1)for(var i=t+1;i<r.length;i++){var s=r[i];if(s.onExecute&&s.shouldShow())return this.setState({selectedHeaderIndex:n?i:-1}),this.setState({selectedFooterIndex:n?-1:i}),null===(s=this._suggestions.current)\|\|void 0===s\|\|s.deselectAllSuggestions(),!0}}return!1},V_.prototype._selectPreviousItemOfItemType=function(e,t){var o;if(e===w_.suggestion){if(0<(n=void 0!==t?t:this.state.suggestions.length))return null===(o=this._suggestions.current)\|\|void 0===o\|\|o.setSelectedSuggestion(n-1),this.setState({selectedHeaderIndex:-1,selectedFooterIndex:-1}),!0}else{var n,r=e===w_.header,i=r?this.props.headerItemsProps:this.props.footerItemsProps;if(i&&0<(n=void 0!==t?t:i.length))for(var s=n-1;0<=s;s--){var a=i[s];if(a.onExecute&&a.shouldShow())return this.setState({selectedHeaderIndex:r?s:-1}),this.setState({selectedFooterIndex:r?-1:s}),null===(a=this._suggestions.current)\|\|void 0===a\|\|a.deselectAllSuggestions(),!0}}return!1},V_.prototype._getCurrentIndexForType=function(e){switch(e){case w_.header:return this.state.selectedHeaderIndex;case w_.suggestion:return this._suggestions.current.currentIndex;case w_.footer:return this.state.selectedFooterIndex}},V_.prototype._getNextItemSectionType=function(e){switch(e){case w_.header:return w_.suggestion;case w_.suggestion:return w_.footer;case w_.footer:return w_.header}},V_.prototype._getPreviousItemSectionType=function(e){switch(e){case w_.header:return w_.footer;case w_.suggestion:return w_.header;case w_.footer:return w_.suggestion}},V_),O_=t,z_=(l(W_,B_=gt.Component),Object.defineProperty(W_.prototype,"inputText",{get:function(){return this.state.queryString},enumerable:!1,configurable:!0}),Object.defineProperty(W_.prototype,"suggestions",{get:function(){return this.suggestionStore.suggestions},enumerable:!1,configurable:!0}),W_.prototype.forceResolveSuggestion=function(){this.suggestionsControl.current&&this.suggestionsControl.current.hasSuggestionSelected()?this.completeSuggestion():this._onValidateInput()},Object.defineProperty(W_.prototype,"currentSelectedSuggestionIndex",{get:function(){return this.suggestionsControl.current?this.suggestionsControl.current.currentSuggestionIndex:-1},enumerable:!1,configurable:!0}),Object.defineProperty(W_.prototype,"isSuggestionsShown",{get:function(){return void 0!==this.state.suggestionsVisible&&this.state.suggestionsVisible},enumerable:!1,configurable:!0}),W_.prototype.componentDidMount=function(){this._bindToInputElement(),this.isComponentMounted=!0,this._onResolveSuggestions=this._async.debounce(this._onResolveSuggestions,this.props.resolveDelay)},W_.prototype.componentDidUpdate=function(){this._bindToInputElement()},W_.prototype.componentWillUnmount=function(){this._unbindFromInputElement(),this.isComponentMounted=!1},W_.prototype.updateSuggestions=function(e,t){void 0===t&&(t=!1),this.suggestionStore.updateSuggestions(e),t&&this.forceUpdate()},W_.prototype.render=function(){var e=this.props.className;return gt.createElement("div",{ref:this.root,className:Tr("ms-BasePicker ms-BaseFloatingPicker",e\|\|"")},this.renderSuggestions())},W_.prototype.renderSuggestions=function(){var e=this.SuggestionsControlOfProperType;return this.props.suggestionItems&&this.suggestionStore.updateSuggestions(this.props.suggestionItems),this.state.suggestionsVisible?gt.createElement(ac,ht({className:O_.callout,isBeakVisible:!1,gapSpace:5,target:this.props.inputElement,onDismiss:this.hidePicker,directionalHint:Pa.bottomLeftEdge,directionalHintForRTL:Pa.bottomRightEdge,calloutWidth:this.props.calloutWidth\|\|0},this.props.pickerCalloutProps),gt.createElement(e,ht({onRenderSuggestion:this.props.onRenderSuggestionsItem,onSuggestionClick:this.onSuggestionClick,onSuggestionRemove:this.onSuggestionRemove,suggestions:this.suggestionStore.getSuggestions(),componentRef:this.suggestionsControl,completeSuggestion:this.completeSuggestion,shouldLoopSelection:!1},this.props.pickerSuggestionsProps))):null},W_.prototype.onSelectionChange=function(){this.forceUpdate()},W_.prototype.updateValue=function(e){""===e?this.updateSuggestionWithZeroState():this._onResolveSuggestions(e)},W_.prototype.updateSuggestionWithZeroState=function(){var e;this.props.onZeroQuerySuggestion?(e=(0,this.props.onZeroQuerySuggestion)(this.props.selectedItems),this.updateSuggestionsList(e)):this.hidePicker()},W_.prototype.updateSuggestionsList=function(t){var o=this;Array.isArray(t)?this.updateSuggestions(t,!0):t&&t.then&&(this.currentPromise=t).then(function(e){t===o.currentPromise&&o.isComponentMounted&&o.updateSuggestions(e,!0)})},W_.prototype.onChange=function(e){this.props.onChange&&this.props.onChange(e)},W_.prototype._updateActiveDescendant=function(){var e;this.props.inputElement&&this.suggestionsControl.current&&this.suggestionsControl.current.selectedElement&&((e=this.suggestionsControl.current.selectedElement.getAttribute("id"))&&this.props.inputElement.setAttribute("aria-activedescendant",e))},W_.prototype._onResolveSuggestions=function(e){e=this.props.onResolveSuggestions(e,this.props.selectedItems);this._updateSuggestionsVisible(!0),null!==e&&this.updateSuggestionsList(e)},W_.prototype._updateSuggestionsVisible=function(e){e?this.showPicker():this.hidePicker()},W_.prototype._bindToInputElement=function(){this.props.inputElement&&!this.state.didBind&&(this.props.inputElement.addEventListener("keydown",this.onKeyDown),this.setState({didBind:!0}))},W_.prototype._unbindFromInputElement=function(){this.props.inputElement&&this.state.didBind&&(this.props.inputElement.removeEventListener("keydown",this.onKeyDown),this.setState({didBind:!1}))},W_);function W_(e){var n=B_.call(this,e)\|\|this;return n.root=gt.createRef(),n.suggestionsControl=gt.createRef(),n.SuggestionsControlOfProperType=H_,n.isComponentMounted=!1,n.onQueryStringChanged=function(e){e!==n.state.queryString&&(n.setState({queryString:e}),n.props.onInputChanged&&n.props.onInputChanged(e),n.updateValue(e))},n.hidePicker=function(){var e=n.isSuggestionsShown;n.setState({suggestionsVisible:!1}),n.props.onSuggestionsHidden&&e&&n.props.onSuggestionsHidden()},n.showPicker=function(e){void 0===e&&(e=!1);var t=n.isSuggestionsShown;n.setState({suggestionsVisible:!0});var o=n.props.inputElement?n.props.inputElement.value:"";e&&n.updateValue(o),n.props.onSuggestionsShown&&!t&&n.props.onSuggestionsShown()},n.completeSuggestion=function(){n.suggestionsControl.current&&n.suggestionsControl.current.hasSuggestionSelected()&&n.onChange(n.suggestionsControl.current.currentSuggestion.item)},n.onSuggestionClick=function(e,t,o){n.onChange(t),n._updateSuggestionsVisible(!1)},n.onSuggestionRemove=function(e,t,o){n.props.onRemoveSuggestion&&n.props.onRemoveSuggestion(t),n.suggestionsControl.current&&n.suggestionsControl.current.removeSuggestion(o)},n.onKeyDown=function(e){if(n.state.suggestionsVisible&&(!n.props.inputElement\|\|n.props.inputElement.contains(e.target))){var t=e.which;switch(t){case En.escape:n.hidePicker(),e.preventDefault(),e.stopPropagation();break;case En.tab:case En.enter:!e.shiftKey&&!e.ctrlKey&&n.suggestionsControl.current&&n.suggestionsControl.current.handleKeyDown(t)?(e.preventDefault(),e.stopPropagation()):n._onValidateInput();break;case En.del:n.props.onRemoveSuggestion&&n.suggestionsControl.current&&n.suggestionsControl.current.hasSuggestionSelected&&n.suggestionsControl.current.currentSuggestion&&e.shiftKey&&(n.props.onRemoveSuggestion(n.suggestionsControl.current.currentSuggestion.item),n.suggestionsControl.current.removeSuggestion(),n.forceUpdate(),e.stopPropagation());break;case En.up:case En.down:n.suggestionsControl.current&&n.suggestionsControl.current.handleKeyDown(t)&&(e.preventDefault(),e.stopPropagation(),n._updateActiveDescendant())}}},n._onValidateInput=function(){var e;n.state.queryString&&n.props.onValidateInput&&n.props.createGenericItem&&(e=n.props.createGenericItem(n.state.queryString,n.props.onValidateInput(n.state.queryString)),e=n.suggestionStore.convertSuggestionsToSuggestionItems([e]),n.onChange(e[0].item))},n._async=new Si(n),fi(n),n.suggestionStore=e.suggestionsStore,n.state={queryString:"",didBind:!1},n}function V_(e){var t=F_.call(this,e)\|\|this;return t._selectedElement=gt.createRef(),t._suggestions=gt.createRef(),t.SuggestionsOfProperType=x_,fi(t),t.state={selectedHeaderIndex:-1,selectedFooterIndex:-1,suggestions:e.suggestions},t}function K_(e){e=A_.call(this,e)\|\|this;return fi(e),e}Dt([{rawString:".resultContent_a17eb2a2{display:table-row}.resultContent_a17eb2a2 .resultItem_a17eb2a2{display:table-cell;vertical-align:bottom}.peoplePickerPersona_a17eb2a2{width:180px}.peoplePickerPersona_a17eb2a2 .ms-Persona-details{width:100%}.peoplePicker_a17eb2a2 .ms-BasePicker-text{min-height:40px}.peoplePickerPersonaContent_a17eb2a2{display:-webkit-box;display:-ms-flexbox;display:flex;width:100%;-webkit-box-pack:justify;-ms-flex-pack:justify;justify-content:space-between;-webkit-box-align:center;-ms-flex-align:center;align-items:center;padding:7px 12px}"}]);var G_,U_,j_=(l(Z_,U_=z_),Z_),q_=(l(Y_,G_=j_),Y_.defaultProps={onRenderSuggestionsItem:function(e,t){return e=ht({},e),ht({},t),gt.createElement("div",{className:Tr("ms-PeoplePicker-personaContent","peoplePickerPersonaContent_a17eb2a2")},gt.createElement(XC,ht({presence:void 0!==e.presence?e.presence:Rr.none,size:Pr.size40,className:Tr("ms-PeoplePicker-Persona","peoplePickerPersona_a17eb2a2"),showSecondaryText:!0},e)))},createGenericItem:X_},Y_);function Y_(){return null!==G_&&G_.apply(this,arguments)\|\|this}function Z_(){return null!==U_&&U_.apply(this,arguments)\|\|this}function X_(e,t){var o={key:e,primaryText:e,imageInitials:"!",isValid:t};return t\|\|(o.imageInitials=Cr(e,Pn())),o}var Q_,J_,$_=(tS.prototype.updateSuggestions=function(e){e&&0<e.length?this.suggestions=this.convertSuggestionsToSuggestionItems(e):this.suggestions=[]},tS.prototype.getSuggestions=function(){return this.suggestions},tS.prototype.getSuggestionAtIndex=function(e){return this.suggestions[e]},tS.prototype.removeSuggestion=function(e){this.suggestions.splice(e,1)},tS.prototype.convertSuggestionsToSuggestionItems=function(e){return Array.isArray(e)?e.map(this._ensureSuggestionModel):[]},tS),eS={host:"ms-HoverCard-host"};function tS(e){var t=this;this._isSuggestionModel=function(e){return void 0!==e.item},this._ensureSuggestionModel=function(e){return t._isSuggestionModel(e)?e:{item:e,selected:!1,ariaLabel:void 0!==t.getAriaLabel?t.getAriaLabel(e):e.name\|\|e.text\|\|e.primaryText}},this.suggestions=[],this.getAriaLabel=e&&e.getAriaLabel}(U=Q_=Q_\|\|{})[U.hover=0]="hover",U[U.hotKey=1]="hotKey",(xe=J_=J_\|\|{}).plain="PlainCard",xe.expanding="ExpandingCard";var oS,nS={root:"ms-ExpandingCard-root",compactCard:"ms-ExpandingCard-compactCard",expandedCard:"ms-ExpandingCard-expandedCard",expandedCardScroll:"ms-ExpandingCard-expandedCardScrollRegion"};(G=oS=oS\|\|{})[G.compact=0]="compact",G[G.expanded=1]="expanded";function rS(e){var t=void 0===(u=e.gapSpace)?0:u,o=void 0===(d=e.directionalHint)?Pa.bottomLeftEdge:d,n=e.directionalHintFixed,r=e.targetElement,i=e.firstFocus,s=e.trapFocus,a=e.onLeave,l=e.className,c=e.finalHeight,u=e.content,d=e.calloutProps,d=ht(ht(ht({},ur(e,cr)),{className:l,target:r,isBeakVisible:!1,directionalHint:o,directionalHintFixed:n,finalHeight:c,minPagePadding:24,onDismiss:a,gapSpace:t}),d);return gt.createElement(gt.Fragment,null,s?gt.createElement(Kh,ht({},d,{focusTrapProps:{forceFocusInsideTrap:!1,isClickableOutsideFocusTrap:!0,disableFirstFocus:!i}}),u):gt.createElement(ac,ht({},d),u))}var iS,sS,aS,lS=Fn(),cS=(l(CS,aS=gt.Component),CS.prototype.componentDidMount=function(){this._checkNeedsScroll()},CS.prototype.componentWillUnmount=function(){this._async.dispose()},CS.prototype.render=function(){var e=this.props,t=e.styles,o=e.compactCardHeight,n=e.expandedCardHeight,r=e.theme,i=e.mode,s=e.className,a=this.state,l=a.needsScroll,e=a.firstFrameRendered,a=o+n;this._classNames=lS(t,{theme:r,compactCardHeight:o,className:s,expandedCardHeight:n,needsScroll:l,expandedCardFirstFrameRendered:i===oS.expanded&&e});e=gt.createElement("div",{onMouseEnter:this.props.onEnter,onMouseLeave:this.props.onLeave,onKeyDown:this._onKeyDown},this._onRenderCompactCard(),this._onRenderExpandedCard());return gt.createElement(rS,ht({},this.props,{content:e,finalHeight:a,className:this._classNames.root}))},CS.defaultProps={compactCardHeight:156,expandedCardHeight:384,directionalHintFixed:!0},CS),uS=In(cS,function(e){var t=e.theme,o=e.needsScroll,n=e.expandedCardFirstFrameRendered,r=e.compactCardHeight,i=e.expandedCardHeight,s=e.className,a=t.palette,e=zo(nS,t);return{root:[e.root,{width:320,pointerEvents:"none",selectors:((t={})[Yt]={border:"1px solid WindowText"},t)},s],compactCard:[e.compactCard,{pointerEvents:"auto",position:"relative",height:r}],expandedCard:[e.expandedCard,{height:1,overflowY:"hidden",pointerEvents:"auto",transition:"height 0.467s cubic-bezier(0.5, 0, 0, 1)",selectors:{":before":{content:'""',position:"relative",display:"block",top:0,left:24,width:272,height:1,backgroundColor:a.neutralLighter}}},n&&{height:i}],expandedCardScroll:[e.expandedCardScroll,o&&{height:"100%",boxSizing:"border-box",overflowY:"auto"}]}},void 0,{scope:"ExpandingCard"}),dS={root:"ms-PlainCard-root"},pS=Fn(),hS=(l(yS,sS=gt.Component),yS.prototype.render=function(){var e=this.props,t=e.styles,o=e.theme,e=e.className;this._classNames=pS(t,{theme:o,className:e});e=gt.createElement("div",{onMouseEnter:this.props.onEnter,onMouseLeave:this.props.onLeave,onKeyDown:this._onKeyDown},this.props.onRenderPlainCard(this.props.renderData));return gt.createElement(rS,ht({},this.props,{content:e,className:this._classNames.root}))},yS),mS=In(hS,function(e){var t=e.theme,e=e.className;return{root:[zo(dS,t).root,{pointerEvents:"auto",selectors:((t={})[Yt]={border:"1px solid WindowText"},t)},e]}},void 0,{scope:"PlainCard"}),gS=Fn(),fS=(l(bS,iS=gt.Component),bS.prototype.componentDidMount=function(){this._setEventListeners()},bS.prototype.componentWillUnmount=function(){this._async.dispose(),this._events.dispose()},bS.prototype.componentDidUpdate=function(e,t){var o=this;e.target!==this.props.target&&(this._events.off(),this._setEventListeners()),t.isHoverCardVisible!==this.state.isHoverCardVisible&&(this.state.isHoverCardVisible?(this._async.setTimeout(function(){o.setState({mode:oS.expanded},function(){o.props.onCardExpand&&o.props.onCardExpand()})},this.props.expandedCardOpenDelay),this.props.onCardVisible&&this.props.onCardVisible()):(this.setState({mode:oS.compact}),this.props.onCardHide&&this.props.onCardHide()))},bS.prototype.render=function(){var e=this.props,t=e.expandingCardProps,o=e.children,n=e.id,r=e.setAriaDescribedBy,i=void 0===r\|\|r,s=e.styles,a=e.theme,l=e.className,c=e.type,u=e.plainCardProps,d=e.trapFocus,p=e.setInitialFocus,h=this.state,r=h.isHoverCardVisible,e=h.mode,h=h.openMode,n=n\|\|_s("hoverCard");this._classNames=gS(s,{theme:a,className:l});h=ht(ht({},ur(this.props,cr)),{id:n,trapFocus:!!d,firstFocus:p\|\|h===Q_.hotKey,targetElement:this._getTargetElement(this.props.target),onEnter:this._cardOpen,onLeave:this._childDismissEvent}),e=ht(ht(ht({},t),h),{mode:e}),h=ht(ht({},u),h);return gt.createElement("div",{className:this._classNames.host,ref:this._hoverCard,"aria-describedby":i&&r?n:void 0,"data-is-focusable":!this.props.target},o,r&&(c===J_.expanding?gt.createElement(uS,ht({},e)):gt.createElement(mS,ht({},h))))},bS.prototype._getTargetElement=function(e){switch(typeof e){case"string":return ft().querySelector(e);case"object":return e;default:return this._hoverCard.current\|\|void 0}},bS.prototype._shouldBlockHoverCard=function(){return!(!this.props.shouldBlockHoverCard\|\|!this.props.shouldBlockHoverCard())},bS.defaultProps={cardOpenDelay:500,cardDismissDelay:100,expandedCardOpenDelay:1500,instantOpenOnClick:!1,setInitialFocus:!1,openHotKey:En.c,type:J_.expanding},bS),vS=In(fS,function(e){var t=e.className,e=e.theme;return{host:[zo(eS,e).host,t]}},void 0,{scope:"HoverCard"});function bS(e){var r=iS.call(this,e)\|\|this;return r._hoverCard=gt.createRef(),r.dismiss=function(e){r._async.clearTimeout(r._openTimerId),r._async.clearTimeout(r._dismissTimerId),e?r._dismissTimerId=r._async.setTimeout(function(){r._setDismissedState()},r.props.cardDismissDelay):r._setDismissedState()},r._cardOpen=function(e){r._shouldBlockHoverCard()\|\|"keydown"===e.type&&e.which!==r.props.openHotKey\|\|(r._async.clearTimeout(r._dismissTimerId),"mouseenter"===e.type&&(r._currentMouseTarget=e.currentTarget),r._executeCardOpen(e))},r._executeCardOpen=function(t){r._async.clearTimeout(r._openTimerId),r._openTimerId=r._async.setTimeout(function(){r.setState(function(e){return e.isHoverCardVisible?e:{isHoverCardVisible:!0,mode:oS.compact,openMode:"keydown"===t.type?Q_.hotKey:Q_.hover}})},r.props.cardOpenDelay)},r._cardDismiss=function(e,t){e?t instanceof MouseEvent&&("keydown"===t.type&&t.which!==En.escape\|\|r.props.sticky\|\|r._currentMouseTarget!==t.currentTarget&&t.which!==En.escape\|\|r.dismiss(!0)):r.props.sticky&&!(t instanceof MouseEvent)&&t.nativeEvent instanceof MouseEvent&&"mouseleave"===t.type\|\|r.dismiss(!0)},r._setDismissedState=function(){r.setState({isHoverCardVisible:!1,mode:oS.compact,openMode:Q_.hover})},r._instantOpenAsExpanded=function(e){r._async.clearTimeout(r._dismissTimerId),r.setState(function(e){return e.isHoverCardVisible?e:{isHoverCardVisible:!0,mode:oS.expanded}})},r._setEventListeners=function(){var e=r.props,t=e.trapFocus,o=e.instantOpenOnClick,n=e.eventListenerTarget,e=n?r._getTargetElement(n):r._getTargetElement(r.props.target),n=r._nativeDismissEvent;e&&(r._events.on(e,"mouseenter",r._cardOpen),r._events.on(e,"mouseleave",n),t?r._events.on(e,"keydown",r._cardOpen):(r._events.on(e,"focus",r._cardOpen),r._events.on(e,"blur",n)),o?r._events.on(e,"click",r._instantOpenAsExpanded):(r._events.on(e,"mousedown",n),r._events.on(e,"keydown",n)))},fi(r),r._async=new Si(r),r._events=new va(r),r._nativeDismissEvent=r._cardDismiss.bind(r,!0),r._childDismissEvent=r._cardDismiss.bind(r,!1),r.state={isHoverCardVisible:!1,mode:oS.compact,openMode:Q_.hover},r}function yS(e){var t=sS.call(this,e)\|\|this;return t._onKeyDown=function(e){e.which===En.escape&&t.props.onLeave&&t.props.onLeave(e)},fi(t),t}function CS(e){var t=aS.call(this,e)\|\|this;return t._expandedElem=gt.createRef(),t._onKeyDown=function(e){e.which===En.escape&&t.props.onLeave&&t.props.onLeave(e)},t._onRenderCompactCard=function(){return gt.createElement("div",{className:t._classNames.compactCard},t.props.onRenderCompactCard(t.props.renderData))},t._onRenderExpandedCard=function(){return t.state.firstFrameRendered\|\|t._async.requestAnimationFrame(function(){t.setState({firstFrameRendered:!0})}),gt.createElement("div",{className:t._classNames.expandedCard,ref:t._expandedElem},gt.createElement("div",{className:t._classNames.expandedCardScroll},t.props.onRenderExpandedCard&&t.props.onRenderExpandedCard(t.props.renderData)))},t._checkNeedsScroll=function(){var e=t.props.expandedCardHeight;t._async.requestAnimationFrame(function(){t._expandedElem.current&&t._expandedElem.current.scrollHeight>=e&&t.setState({needsScroll:!0})})},t._async=new Si(t),fi(t),t.state={firstFrameRendered:!1,needsScroll:!1},t}function _S(e,t){en({style:{MozOsxFontSmoothing:"grayscale",WebkitFontSmoothing:"antialiased",fontStyle:"normal",fontWeight:"normal",speak:"none"},fontFace:{fontFamily:'"FabricMDL2Icons"',src:"url('"+(e=void 0===e?"":e)+"fabric-icons-a13498cf.woff') 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0===t&&(t="https://spoppe-b.azureedge.net/files/fabric-cdn-prod_20210407.001/assets/icons/"),[_S,SS,xS,kS,wS,IS,DS,ES,TS,PS,RS,MS,NS,BS,FS,AS,LS,HS,OS].forEach(function(e){return e(t,o)}),on("trash","delete"),on("onedrive","onedrivelogo"),on("alertsolid12","eventdatemissed12"),on("sixpointstar","6pointstar"),on("twelvepointstar","12pointstar"),on("toggleon","toggleleft"),on("toggleoff","toggleright")}function WS(e){e=ft().querySelectorAll(e);return Array.from(e).find(ls)}fn("@fluentui/font-icons-mdl2","8.1.21");function VS(e){return{container:[],root:[{border:"none",boxShadow:"none"}],beak:[],beakCurtain:[],calloutMain:[{backgroundColor:"transparent"}]}}var KS,GS,V=(l(YS,GS=gt.Component),YS.prototype.render=function(){var e=this.props,t=e.content,o=e.styles,n=e.theme,r=e.disabled,e=e.visible,e=Fn()(o,{theme:n,disabled:r,visible:e});return gt.createElement("div",{className:e.container},gt.createElement("span",{className:e.root},t))},YS),US=In(V,function(e){var t=e.theme,o=e.disabled,n=e.visible;return{container:[{backgroundColor:t.palette.neutralDark},o&&{opacity:.5,selectors:((e={})[Yt]={color:"GrayText",opacity:1},e)},!n&&{visibility:"hidden"}],root:[t.fonts.medium,{textAlign:"center",paddingLeft:"3px",paddingRight:"3px",backgroundColor:t.palette.neutralDark,color:t.palette.neutralLight,minWidth:"11px",lineHeight:"17px",height:"17px",display:"inline-block"},o&&{color:t.palette.neutralTertiaryAlt}]}},void 0,{scope:"KeytipContent"}),jS=(l(qS,KS=gt.Component),qS.prototype.render=function(){var t,e=this.props,o=e.keySequences,n=e.offset,r=e.overflowSetSequence,e=this.props.calloutProps,o=WS(Kc(r?Vc(o,r):o));return o?(r=o,(e=n?ht(ht({},e),{coverTarget:!0,directionalHint:Pa.topLeftEdge}):e)&&void 0!==e.directionalHint\|\|(e=ht(ht({},e),{directionalHint:Pa.bottomCenter})),gt.createElement(ac,ht({},e,{isBeakVisible:!1,doNotLayer:!0,minPagePadding:0,styles:n?(t=n,function(e){return pn({container:[],root:[{border:"none",boxShadow:"none"}],beak:[],beakCurtain:[],calloutMain:[{backgroundColor:"transparent"}]},{root:[{marginLeft:t.left\|\|t.x,marginTop:t.top\|\|t.y}]})}):VS,preventDismissOnScroll:!0,target:r}),gt.createElement(US,ht({},this.props)))):gt.createElement(gt.Fragment,null)},qS);function qS(){return null!==KS&&KS.apply(this,arguments)\|\|this}function YS(){return null!==GS&&GS.apply(this,arguments)\|\|this}function ZS(e){var e=jc(e),n=e.keytipId,r=e.ariaDescribedBy;return gt.useCallback(function(e){var t,o;e&&(t=QS(e,Rc)\|\|e,o=QS(e,Mc)\|\|t,e=QS(e,Nc)\|\|o,XS(t,Rc,n),XS(o,Mc,n),XS(e,"aria-describedby",r,!0))},[n,r])}function XS(e,t,o,n){var r;void 0===n&&(n=!1),e&&o&&(r=o,!n\|\|(n=e.getAttribute(t))&&-1===n.indexOf(o)&&(r=n+" "+o),e.setAttribute(t,r))}function QS(e,t){return e.querySelector("["+t+"]")}function JS(e){return{root:[{zIndex:mo.KeytipLayer}]}}var $S=(ex.prototype.addNode=function(e,t,o){var 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o=this,n=this.getNodes(e.children).filter(function(e){return o._getNodeSequence(e)===t&&!e.disabled});if(0!==n.length){var r=n[0];if(1===n.length)return r;var i=r.keySequences,e=r.overflowSetSequence,i=Kc(e?Vc(i,e):i),i=document.querySelectorAll(i);if(n.length<i.length)return r;i=Array.from(i).findIndex(ls);return-1!==i?n[i]:n.find(function(e){return e.hasOverflowSubMenu})\|\|r}},ex.prototype.getPartiallyMatchedNodes=function(t,e){var o=this;return this.getNodes(e.children).filter(function(e){return 0===o._getNodeSequence(e).indexOf(t)&&!e.disabled})},ex.prototype.getChildren=function(e){var o=this;if(!e&&!(e=this.currentKeytip))return[];var n=e.children;return Object.keys(this.nodeMap).reduce(function(e,t){return 0<=n.indexOf(o.nodeMap[t].id)&&!o.nodeMap[t].persisted&&e.push(o.nodeMap[t].id),e},[])},ex.prototype.getNodes=function(o){var n=this;return Object.keys(this.nodeMap).reduce(function(e,t){return 0<=o.indexOf(n.nodeMap[t].id)&&e.push(n.nodeMap[t]),e},[])},ex.prototype.getNode=function(t){return Oi(ga(this.nodeMap),function(e){return e.id===t})},ex.prototype.isCurrentKeytipParent=function(e){if(this.currentKeytip){var t=$e([],e.keySequences);(t=e.overflowSetSequence?Vc(t,e.overflowSetSequence):t).pop();e=0===t.length?this.root.id:Wc(t),t=!1;return(t=this.currentKeytip.overflowSetSequence?Wc(this.currentKeytip.keySequences)===e:t)\|\|this.currentKeytip.id===e}return!1},ex.prototype._getParentID=function(e){return 0===e.length?this.root.id:Wc(e)},ex.prototype._getFullSequence=function(e){var t=$e([],e.keySequences);return t=e.overflowSetSequence?Vc(t,e.overflowSetSequence):t},ex.prototype._getNodeSequence=function(e){var t=$e([],e.keySequences);return(t=e.overflowSetSequence?Vc(t,e.overflowSetSequence):t)[t.length-1]},ex.prototype._createNode=function(o,e,t,n,r){var i=this,s=n.keySequences,a=n.hasDynamicChildren,l=n.overflowSetSequence,c=n.hasMenu,u=n.onExecute,d=n.onReturn,p=n.disabled,n=n.hasOverflowSubMenu,n={id:o,keySequences:s,overflowSetSequence:l,parent:e,children:t,onExecute:u,onReturn:d,hasDynamicChildren:a,hasMenu:c,disabled:p,persisted:r,hasOverflowSubMenu:n};return n.children=Object.keys(this.nodeMap).reduce(function(e,t){return i.nodeMap[t].parent===o&&e.push(i.nodeMap[t].id),e},[]),n},ex.prototype._removeChildFromParents=function(e,o){this.getNodes([e]).forEach(function(e){var t=e.children.indexOf(o);0<=t&&e.children.splice(t,1)})},ex);function ex(){this.nodeMap={},this.root={id:Bc,children:[],parent:"",keySequences:[]},this.nodeMap[this.root.id]=this.root}function tx(e,t){if(e.key!==t.key)return!1;var o=e.modifierKeys,n=t.modifierKeys;if(!o&&n\|\|o&&!n)return!1;if(o&&n){if(o.length!==n.length)return!1;for(var o=o.sort(),n=n.sort(),r=0;r<o.length;r++)if(o[r]!==n[r])return!1}return!0}function ox(e,t){return!!Oi(e,function(e){return 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gt.createElement(jS,ht({key:Wc(e.keySequences)},e))}))},ax.prototype.componentDidMount=function(){this._events.on(window,"mouseup",this._onDismiss,!0),this._events.on(window,"pointerup",this._onDismiss,!0),this._events.on(window,"resize",this._onDismiss),this._events.on(window,"keydown",this._onKeyDown,!0),this._events.on(window,"keypress",this._onKeyPress,!0),this._events.on(window,"scroll",this._onDismiss,!0),this._events.on(this._keytipManager,gc.ENTER_KEYTIP_MODE,this._enterKeytipMode),this._events.on(this._keytipManager,gc.EXIT_KEYTIP_MODE,this._exitKeytipMode)},ax.prototype.componentWillUnmount=function(){this._async.dispose(),this._events.dispose()},ax.prototype.getCurrentSequence=function(){return this._currentSequence},ax.prototype.getKeytipTree=function(){return this._keytipTree},ax.prototype.processTransitionInput=function(e,t){var o=this._keytipTree.currentKeytip;ox(this.props.keytipExitSequences,e)&&o?(this._keyHandled=!0,this._exitKeytipMode(t)):ox(this.props.keytipReturnSequences,e)?o&&(this._keyHandled=!0,o.id===this._keytipTree.root.id?this._exitKeytipMode(t):(o.onReturn&&o.onReturn(this._getKtpExecuteTarget(o),this._getKtpTarget(o)),this._currentSequence="",this._keytipTree.currentKeytip=this._keytipTree.getNode(o.parent),this.showKeytips(this._keytipTree.getChildren()),this._warnIfDuplicateKeytips())):ox(this.props.keytipStartSequences,e)&&!o&&(this._keyHandled=!0,this._enterKeytipMode(e),this._warnIfDuplicateKeytips())},ax.prototype.processInput=function(e,t){var o=this._currentSequence+e,n=this._keytipTree.currentKeytip;if(n){e=this._keytipTree.getExactMatchedNode(o,n);if(e){this._keytipTree.currentKeytip=n=e;e=this._keytipTree.getChildren();return n.onExecute&&(n.onExecute(this._getKtpExecuteTarget(n),this._getKtpTarget(n)),n=this._keytipTree.currentKeytip),0!==e.length\|\|n.hasDynamicChildren\|\|n.hasMenu?(this.showKeytips(e),this._warnIfDuplicateKeytips()):this._exitKeytipMode(t),void(this._currentSequence="")}n=this._keytipTree.getPartiallyMatchedNodes(o,n);0<n.length&&(n=n.filter(function(e){return!e.persisted}).map(function(e){return e.id}),this.showKeytips(n),this._currentSequence=o)}},ax.prototype.showKeytips=function(e){for(var t=0,o=this._keytipManager.getKeytips();t<o.length;t++){var n=o[t],r=Wc(n.keySequences);n.overflowSetSequence&&(r=Wc(Vc(n.keySequences,n.overflowSetSequence))),0<=e.indexOf(r)?n.visible=!0:n.visible=!1}this._setKeytips()},ax.prototype._enterKeytipMode=function(e){this._keytipManager.shouldEnterKeytipMode&&(this._keytipManager.delayUpdatingKeytipChange&&(this._buildTree(),this._setKeytips()),this._keytipTree.currentKeytip=this._keytipTree.root,this.showKeytips(this._keytipTree.getChildren()),this._setInKeytipMode(!0),this.props.onEnterKeytipMode&&this.props.onEnterKeytipMode(e))},ax.prototype._buildTree=function(){this._keytipTree=new $S;for(var e=0,t=Object.keys(this._keytipManager.keytips);e<t.length;e++){var o=t[e],n=this._keytipManager.keytips[o];this._keytipTree.addNode(n.keytip,n.uniqueID)}for(var r=0,i=Object.keys(this._keytipManager.persistedKeytips);r<i.length;r++)o=i[r],n=this._keytipManager.persistedKeytips[o],this._keytipTree.addNode(n.keytip,n.uniqueID)},ax.prototype._exitKeytipMode=function(e){this._keytipTree.currentKeytip=void 0,this._currentSequence="",this.showKeytips([]),this._delayedQueueTimeout&&this._async.clearTimeout(this._delayedQueueTimeout),this._delayedKeytipQueue=[],this._setInKeytipMode(!1),this.props.onExitKeytipMode&&this.props.onExitKeytipMode(e)},ax.prototype._setKeytips=function(e){void 0===e&&(e=this._keytipManager.getKeytips()),this.setState({keytips:e,visibleKeytips:this._getVisibleKeytips(e)})},ax.prototype._persistedKeytipExecute=function(e,t){this._newCurrentKeytipSequences=t;e=this._keytipTree.getNode(Wc(e));e&&e.onExecute&&e.onExecute(this._getKtpExecuteTarget(e),this._getKtpTarget(e))},ax.prototype._getVisibleKeytips=function(e){var o={};return e.filter(function(e){var t=Wc(e.keySequences);return e.overflowSetSequence&&(t=Wc(Vc(e.keySequences,e.overflowSetSequence))),o[t]=o[t]?o[t]+1:1,e.visible&&1===o[t]})},ax.prototype._getModifierKey=function(e,t){var o=[];return t.altKey&&"Alt"!==e&&o.push(En.alt),t.ctrlKey&&"Control"!==e&&o.push(En.ctrl),t.shiftKey&&"Shift"!==e&&o.push(En.shift),t.metaKey&&"Meta"!==e&&o.push(En.leftWindow),o.length?o:void 0},ax.prototype._triggerKeytipImmediately=function(e){var t=$e([],e.keySequences);e.overflowSetSequence&&(t=Vc(t,e.overflowSetSequence)),this._keytipTree.currentKeytip=this._keytipTree.getNode(Wc(t)),this._keytipTree.currentKeytip&&((t=this._keytipTree.getChildren()).length&&this.showKeytips(t),this._keytipTree.currentKeytip.onExecute&&this._keytipTree.currentKeytip.onExecute(this._getKtpExecuteTarget(this._keytipTree.currentKeytip),this._getKtpTarget(this._keytipTree.currentKeytip))),this._newCurrentKeytipSequences=void 0},ax.prototype._addKeytipToQueue=function(e){var t=this;this._delayedKeytipQueue.push(e),this._delayedQueueTimeout&&this._async.clearTimeout(this._delayedQueueTimeout),this._delayedQueueTimeout=this._async.setTimeout(function(){t._delayedKeytipQueue.length&&(t.showKeytips(t._delayedKeytipQueue),t._delayedKeytipQueue=[])},300)},ax.prototype._removeKeytipFromQueue=function(e){var t=this,e=this._delayedKeytipQueue.indexOf(e);0<=e&&(this._delayedKeytipQueue.splice(e,1),this._delayedQueueTimeout&&this._async.clearTimeout(this._delayedQueueTimeout),this._delayedQueueTimeout=this._async.setTimeout(function(){t._delayedKeytipQueue.length&&(t.showKeytips(t._delayedKeytipQueue),t._delayedKeytipQueue=[])},300))},ax.prototype._getKtpExecuteTarget=function(e){return ft().querySelector(Gc(e.id))},ax.prototype._getKtpTarget=function(e){return ft().querySelector(Kc(e.keySequences))},ax.prototype._isCurrentKeytipAnAlias=function(e){var t=this._keytipTree.currentKeytip;return!(!t\|\|!t.overflowSetSequence&&!t.persisted\|\|!ji(e.keySequences,t.keySequences))},ax.defaultProps={keytipStartSequences:[Y],keytipExitSequences:[ke],keytipReturnSequences:[n],content:""},ax),sx=In(ix,function(e){return{innerContent:[{position:"absolute",width:0,height:0,margin:0,padding:0,border:0,overflow:"hidden",visibility:"hidden"}]}},void 0,{scope:"KeytipLayer"});function ax(e,t){var n=nx.call(this,e,t)\|\|this;n._keytipManager=Oc.getInstance(),n._delayedKeytipQueue=[],n._keyHandled=!1,n._onDismiss=function(e){n.state.inKeytipMode&&n._exitKeytipMode(e)},n._onKeyDown=function(e){n._keyHandled=!1;var t=e.key;switch(t){case"Tab":case"Enter":case"Spacebar":case" ":case"ArrowUp":case"Up":case"ArrowDown":case"Down":case"ArrowLeft":case"Left":case"ArrowRight":case"Right":n.state.inKeytipMode&&(n._keyHandled=!0,n._exitKeytipMode(e));break;default:"Esc"===t?t="Escape":"OS"!==t&&"Win"!==t\|\|(t="Meta");var o={key:t};o.modifierKeys=n._getModifierKey(t,e),n.processTransitionInput(o,e)}},n._onKeyPress=function(e){n.state.inKeytipMode&&!n._keyHandled&&(n.processInput(e.key.toLocaleLowerCase(),e),e.preventDefault(),e.stopPropagation())},n._onKeytipAdded=function(e){var t,o=e.keytip,e=e.uniqueID;n._keytipTree.addNode(o,e),n._setKeytips(),n._keytipTree.isCurrentKeytipParent(o)&&(n._delayedKeytipQueue=n._delayedKeytipQueue.concat((null===(e=n._keytipTree.currentKeytip)\|\|void 0===e?void 0:e.children)\|\|[]),n._addKeytipToQueue(Wc(o.keySequences)),n._keytipTree.currentKeytip&&n._keytipTree.currentKeytip.hasDynamicChildren&&n._keytipTree.currentKeytip.children.indexOf(o.id)<0)&&(t=n._keytipTree.getNode(n._keytipTree.currentKeytip.id))&&(n._keytipTree.currentKeytip=t),n._persistedKeytipChecks(o)},n._onKeytipUpdated=function(e){var t=e.keytip,e=e.uniqueID;n._keytipTree.updateNode(t,e),n._setKeytips(),n._keytipTree.isCurrentKeytipParent(t)&&(n._delayedKeytipQueue=n._delayedKeytipQueue.concat((null===(e=n._keytipTree.currentKeytip)\|\|void 0===e?void 0:e.children)\|\|[]),n._addKeytipToQueue(Wc(t.keySequences))),n._persistedKeytipChecks(t)},n._persistedKeytipChecks=function(e){var t;n._newCurrentKeytipSequences&&ji(e.keySequences,n._newCurrentKeytipSequences)&&n._triggerKeytipImmediately(e),n._isCurrentKeytipAnAlias(e)&&(t=e.keySequences,e.overflowSetSequence&&(t=Vc(t,e.overflowSetSequence)),n._keytipTree.currentKeytip=n._keytipTree.getNode(Wc(t)))},n._onKeytipRemoved=function(e){var t=e.keytip,e=e.uniqueID;n._removeKeytipFromQueue(Wc(t.keySequences)),n._keytipTree.removeNode(t,e),n._setKeytips()},n._onPersistedKeytipAdded=function(e){var t=e.keytip,e=e.uniqueID;n._keytipTree.addNode(t,e,!0)},n._onPersistedKeytipRemoved=function(e){var t=e.keytip,e=e.uniqueID;n._keytipTree.removeNode(t,e)},n._onPersistedKeytipExecute=function(e){n._persistedKeytipExecute(e.overflowButtonSequences,e.keytipSequences)},n._setInKeytipMode=function(e){n.setState({inKeytipMode:e}),n._keytipManager.inKeytipMode=e},n._warnIfDuplicateKeytips=function(){var e=n._getDuplicateIds(n._keytipTree.getChildren());e.length&&Xo("Duplicate keytips found for "+e.join(", "))},n._getDuplicateIds=function(e){var t={};return e.filter(function(e){return t[e]=t[e]?t[e]+1:1,2===t[e]})},fi(n),n._events=new va(n),n._async=new Si(n);t=n._keytipManager.getKeytips();return n.state={inKeytipMode:!1,keytips:t,visibleKeytips:n._getVisibleKeytips(t)},n._buildTree(),n._currentSequence="",n._events.on(n._keytipManager,gc.KEYTIP_ADDED,n._onKeytipAdded),n._events.on(n._keytipManager,gc.KEYTIP_UPDATED,n._onKeytipUpdated),n._events.on(n._keytipManager,gc.KEYTIP_REMOVED,n._onKeytipRemoved),n._events.on(n._keytipManager,gc.PERSISTED_KEYTIP_ADDED,n._onPersistedKeytipAdded),n._events.on(n._keytipManager,gc.PERSISTED_KEYTIP_REMOVED,n._onPersistedKeytipRemoved),n._events.on(n._keytipManager,gc.PERSISTED_KEYTIP_EXECUTE,n._onPersistedKeytipExecute),n}function lx(e){for(var t={},o=0,n=e.keytips;o<n.length;o++)cx(t,[],n[o]);return t}function cx(e,t,o){var n=o.sequence\|\|o.content.toLocaleLowerCase(),r=t.concat(n),n=ht(ht({},o.optionalProps),{keySequences:r,content:o.content});if(e[o.id]=n,o.children)for(var i=0,s=o.children;i<s.length;i++)cx(e,r,s[i])}fn("@fluentui/react","8.52.2");var ux=function(e){var t=e.id,o=e.className;return gt.useEffect(function(){ec(t)},[]),dx(function(){ec(t)}),gt.createElement("div",ht({},e,{className:Tr("ms-LayerHost",o)}))},dx=function(e){var t=gt.useRef(e);t.current=e,gt.useEffect(function(){return function(){t.current&&t.current()}},[])},px=(hx.prototype.dispose=function(){this._events.dispose(),this._stopScroll()},hx.prototype._onMouseMove=function(e){this._computeScrollVelocity(e)},hx.prototype._onTouchMove=function(e){0<e.touches.length&&this._computeScrollVelocity(e)},hx.prototype._computeScrollVelocity=function(e){var t,o,n,r,i,s,a,l;this._scrollRect&&(o="clientX"in e?(t=e.clientX,e.clientY):(t=e.touches[0].clientX,e.touches[0].clientY),s=this._scrollRect.top,a=this._scrollRect.left,l=s+this._scrollRect.height-100,e=a+this._scrollRect.width-100,o<s+100\|\|l<o?(r=o,n=s,i=l,this._isVerticalScroll=!0):(r=t,n=a,i=e,this._isVerticalScroll=!1),this._scrollVelocity=r<n+100?Math.max(-15,(100-(r-n))/100-15):i<r?Math.min(15,(r-i)/10015):0,this._scrollVelocity?this._startScroll():this._stopScroll())},hx.prototype._startScroll=function(){this._timeoutId\|\|this._incrementScroll()},hx.prototype._incrementScroll=function(){this._scrollableParent&&(this._isVerticalScroll?this._scrollableParent.scrollTop+=Math.round(this._scrollVelocity):this._scrollableParent.scrollLeft+=Math.round(this._scrollVelocity)),this._timeoutId=setTimeout(this._incrementScroll,16)},hx.prototype._stopScroll=function(){this._timeoutId&&(clearTimeout(this._timeoutId),delete this._timeoutId)},hx);function hx(e){this._events=new va(this),this._scrollableParent=Ns(e),this._incrementScroll=this._incrementScroll.bind(this),this._scrollRect=t0(this._scrollableParent),this._scrollableParent===window&&(this._scrollableParent=document.body),this._scrollableParent&&(this._events.on(window,"mousemove",this._onMouseMove,!0),this._events.on(window,"touchmove",this._onTouchMove,!0))}function mx(e,t){var o=e.left\|\|e.x\|\|0,n=e.top\|\|e.y\|\|0,e=t.left\|\|t.x\|\|0,t=t.top\|\|t.y\|\|0;return Math.sqrt(Math.pow(o-e,2)+Math.pow(n-t,2))}function gx(e){var t=e.contentSize,o=e.boundsSize,n=e.mode,r=e.maxScale,i=t.width/t.height,e=o.width/o.height,o=("contain"===(void 0===n?"contain":n)?e<i:i<e)?o.width/t.width:o.height/t.height,o=Math.min(void 0===r?1:r,o);return{width:t.widtho,height:t.heighto}}function fx(e){e=/[1-9]([0]+$)\|\.([0-9])/.exec(String(e));return e?e[1]?-e[1].length:e[2]?e[2].length:0:0}function vx(e,t,o){void 0===o&&(o=10);t=Math.pow(o,t);return Math.round(et)/t}var bx,yx,Cx=Fn(),_x=In((l(Sx,yx=gt.Component),Sx.prototype.componentDidMount=function(){this._scrollableParent=Ns(this._root.current),this._scrollableSurface=this._scrollableParent===window?document.body:this._scrollableParent;var e=this.props.isDraggingConstrainedToRoot?this._root.current:this._scrollableSurface;this._events.on(e,"mousedown",this._onMouseDown),this._events.on(e,"touchstart",this._onTouchStart,!0),this._events.on(e,"pointerdown",this._onPointerDown,!0)},Sx.prototype.componentWillUnmount=function(){this._autoScroll&&this._autoScroll.dispose(),delete this._scrollableParent,delete this._scrollableSurface,this._events.dispose(),this._async.dispose()},Sx.prototype.render=function(){var e=this.props,t=e.rootProps,o=e.children,n=e.theme,r=e.className,i=e.styles,e=this.state.dragRect,r=Cx(i,{theme:n,className:r});return gt.createElement("div",ht({},t,{className:r.root,ref:this._root}),o,e&&gt.createElement("div",{className:r.dragMask}),e&&gt.createElement("div",{className:r.box,style:e},gt.createElement("div",{className:r.boxFill})))},Sx.prototype._isMouseEventOnScrollbar=function(e){var t=e.target,o=t.offsetWidth-t.clientWidth,n=t.offsetHeight-t.clientHeight;if(o\|\|n){n=t.getBoundingClientRect();if(Pn(this.props.theme)){if(e.clientX<n.left+o)return!0}else if(e.clientX>n.left+t.clientWidth)return!0;if(e.clientY>n.top+t.clientHeight)return!0}return!1},Sx.prototype._getRootRect=function(){return{left:this._rootRect.left+(this._scrollableSurface?this._scrollLeft-this._scrollableSurface.scrollLeft:this._scrollLeft),top:this._rootRect.top+(this._scrollableSurface?this._scrollTop-this._scrollableSurface.scrollTop:this._scrollTop),width:this._rootRect.width,height:this._rootRect.height}},Sx.prototype._onAsyncMouseMove=function(e){var t=this;this._async.requestAnimationFrame(function(){t._onMouseMove(e)}),e.stopPropagation(),e.preventDefault()},Sx.prototype._onMouseMove=function(e){if(this._autoScroll){void 0!==e.clientX&&(this._lastMouseEvent=e);var t,o=this._getRootRect(),n={left:e.clientX-o.left,top:e.clientY-o.top};return this._dragOrigin\|\|(this._dragOrigin=n),void 0!==e.buttons&&0===e.buttons?this._onMouseUp(e):(this.state.dragRect\|\|5<mx(this._dragOrigin,n))&&(this.state.dragRect\|\|(t=this.props.selection,e.shiftKey\|\|t.setAllSelected(!1),this._preservedIndicies=t&&t.getSelectedIndices&&t.getSelectedIndices()),t=this.props.isDraggingConstrainedToRoot?{left:Math.max(0,Math.min(o.width,this._lastMouseEvent.clientX-o.left)),top:Math.max(0,Math.min(o.height,this._lastMouseEvent.clientY-o.top))}:{left:this._lastMouseEvent.clientX-o.left,top:this._lastMouseEvent.clientY-o.top},t={left:Math.min(this._dragOrigin.left\|\|0,t.left),top:Math.min(this._dragOrigin.top\|\|0,t.top),width:Math.abs(t.left-(this._dragOrigin.left\|\|0)),height:Math.abs(t.top-(this._dragOrigin.top\|\|0))},this._evaluateSelection(t,o),this.setState({dragRect:t})),!1}},Sx.prototype._onMouseUp=function(e){this._events.off(window),this._events.off(this._scrollableParent,"scroll"),this._autoScroll&&this._autoScroll.dispose(),this._autoScroll=this._dragOrigin=this._lastMouseEvent=void 0,this._selectedIndicies=this._itemRectCache=void 0,this.state.dragRect&&(this.setState({dragRect:void 0}),e.preventDefault(),e.stopPropagation())},Sx.prototype._isPointInRectangle=function(e,t){return!!t.top&&e.top<t.top&&e.bottom>t.top&&!!t.left&&e.left<t.left&&e.right>t.left},Sx.prototype._isDragStartInSelection=function(e){var t=this.props.selection;if(!this._root.current\|\|t&&0===t.getSelectedCount())return!1;for(var o=this._root.current.querySelectorAll("[data-selection-index]"),n=0;n<o.length;n++){var r=o[n],i=Number(r.getAttribute("data-selection-index"));if(t.isIndexSelected(i)){r=r.getBoundingClientRect();if(this._isPointInRectangle(r,{left:e.clientX,top:e.clientY}))return!0}}return!1},Sx.prototype._isInSelectionToggle=function(e){for(var t=e.target;t&&t!==this._root.current;){if("true"===t.getAttribute("data-selection-toggle"))return!0;t=t.parentElement}return!1},Sx.prototype._evaluateSelection=function(e,t){if(e&&this._root.current){var o=this.props.selection,n=this._root.current.querySelectorAll("[data-selection-index]");this._itemRectCache\|\|(this._itemRectCache={});for(var r=0;r<n.length;r++){var i=n[r],s=i.getAttribute("data-selection-index"),a=this._itemRectCache[s];a\|\|0<(a={left:(a=i.getBoundingClientRect()).left-t.left,top:a.top-t.top,width:a.width,height:a.height,right:a.left-t.left+a.width,bottom:a.top-t.top+a.height}).width&&0<a.height&&(this._itemRectCache[s]=a),a.top<e.top+e.height&&a.bottom>e.top&&a.left<e.left+e.width&&a.right>e.left?this._selectedIndicies[s]=!0:delete this._selectedIndicies[s]}var l=this._allSelectedIndices\|\|{};for(s in this._allSelectedIndices={},this._selectedIndicies)this._selectedIndicies.hasOwnProperty(s)&&(this._allSelectedIndices[s]=!0);if(this._preservedIndicies)for(var c=0,u=this._preservedIndicies;c<u.length;c++)s=u[c],this._allSelectedIndices[s]=!0;var d=!1;for(s in this._allSelectedIndices)if(this._allSelectedIndices[s]!==l[s]){d=!0;break}if(!d)for(var s in l)if(this._allSelectedIndices[s]!==l[s]){d=!0;break}if(d){o.setChangeEvents(!1),o.setAllSelected(!1);for(var p=0,h=Object.keys(this._allSelectedIndices);p<h.length;p++)s=h[p],o.setIndexSelected(Number(s),!0,!1);o.setChangeEvents(!0)}}},Sx.defaultProps={rootTagName:"div",rootProps:{},isEnabled:!0},Sx),function(e){var t=e.theme,e=e.className,t=t.palette;return{root:[e,{position:"relative",cursor:"default"}],dragMask:[{position:"absolute",background:"rgba(255, 0, 0, 0)",left:0,top:0,right:0,bottom:0,selectors:((e={})[Yt]={background:"none",backgroundColor:"transparent"},e)}],box:[{position:"absolute",boxSizing:"border-box",border:"1px solid "+t.themePrimary,pointerEvents:"none",zIndex:10,selectors:((e={})[Yt]={borderColor:"Highlight"},e)}],boxFill:[{position:"absolute",boxSizing:"border-box",backgroundColor:t.themePrimary,opacity:.1,left:0,top:0,right:0,bottom:0,selectors:((t={})[Yt]={background:"none",backgroundColor:"transparent"},t)}]}},void 0,{scope:"MarqueeSelection"});function Sx(e){var n=yx.call(this,e)\|\|this;return n._root=gt.createRef(),n._onMouseDown=function(e){var t=n.props,o=t.isEnabled,t=t.onShouldStartSelection;n._isMouseEventOnScrollbar(e)\|\|n._isInSelectionToggle(e)\|\|n._isTouch\|\|!o\|\|n._isDragStartInSelection(e)\|\|t&&!t(e)\|\|n._scrollableSurface&&0===e.button&&n._root.current&&(n._selectedIndicies={},n._preservedIndicies=void 0,n._events.on(window,"mousemove",n._onAsyncMouseMove,!0),n._events.on(n._scrollableParent,"scroll",n._onAsyncMouseMove),n._events.on(window,"click",n._onMouseUp,!0),n._autoScroll=new px(n._root.current),n._scrollTop=n._scrollableSurface.scrollTop,n._scrollLeft=n._scrollableSurface.scrollLeft,n._rootRect=n._root.current.getBoundingClientRect(),n._onMouseMove(e))},n._onTouchStart=function(e){n._isTouch=!0,n._async.setTimeout(function(){n._isTouch=!1},0)},n._onPointerDown=function(e){"touch"===e.pointerType&&(n._isTouch=!0,n._async.setTimeout(function(){n._isTouch=!1},0))},fi(n),n._async=new Si(n),n._events=new va(n),n.state={dragRect:void 0},n}(r=bx=bx\|\|{})[r.info=0]="info",r[r.error=1]="error",r[r.blocked=2]="blocked",r[r.severeWarning=3]="severeWarning",r[r.success=4]="success",r[r.warning=5]="warning";var xx=((K={})[bx.info]="Info",K[bx.warning]="Info",K[bx.error]="ErrorBadge",K[bx.blocked]="Blocked2",K[bx.severeWarning]="Warning",K[bx.success]="Completed",K),kx=Fn(),wx=gt.forwardRef(function(e,t){var o=E0(!1),n=o[0],r=o[1].toggle,i=iu("MessageBar"),s=e.actions,a=e.className,l=e.children,c=e.overflowButtonAriaLabel,u=e.dismissIconProps,d=e.styles,p=e.theme,h=e.messageBarType,m=void 0===h?bx.info:h,g=e.onDismiss,f=void 0===g?void 0:g,v=e.isMultiline,b=void 0===v\|\|v,y=e.truncated,C=e.dismissButtonAriaLabel,o=e.messageBarIconProps,h=e.role,g=e.delayedRender,v=void 0===g\|\|g,g=e.expandButtonProps,e=ur(e,Wn,["className","role"]),d=kx(d,{theme:p,messageBarType:m\|\|bx.info,onDismiss:void 0!==f,actions:void 0!==s,truncated:y,isMultiline:b,expandSingleLine:n,className:a}),p={iconName:n?"DoubleChevronUp":"DoubleChevronDown"},a=s\|\|f?{"aria-describedby":i,role:"region"}:{},s=s?gt.createElement("div",{className:d.actions},s):null,C=f?gt.createElement(rd,{disabled:!1,className:d.dismissal,onClick:f,iconProps:u\|\|{iconName:"Clear"},title:C,ariaLabel:C}):null;return gt.createElement("div",ht({ref:t,className:d.root},a),gt.createElement("div",{className:d.content},gt.createElement("div",{className:d.iconContainer,"aria-hidden":!0},o?gt.createElement(Wr,ht({},o,{className:Tr(d.icon,o.className)})):gt.createElement(Wr,{iconName:xx[m],className:d.icon})),gt.createElement("div",{className:d.text,id:i,role:h\|\|function(e){switch(e){case bx.blocked:case bx.error:case bx.severeWarning:return"alert"}return"status"}(m),"aria-live":function(e){switch(e){case bx.blocked:case bx.error:case bx.severeWarning:return"assertive"}return"polite"}(m)},gt.createElement("span",ht({className:d.innerText},e),v?gt.createElement(Ri,null,gt.createElement("span",null,l)):gt.createElement("span",null,l))),!b&&!s&&y&&gt.createElement("div",{className:d.expandSingleLine},gt.createElement(rd,ht({disabled:!1,className:d.expand,onClick:r,iconProps:p,ariaLabel:c,"aria-expanded":n},g))),!b&&s,!b&&C&&gt.createElement("div",{className:d.dismissSingleLine},C),b&&C),b&&s)});wx.displayName="MessageBar";var Ix,Dx={root:"ms-MessageBar",error:"ms-MessageBar--error",blocked:"ms-MessageBar--blocked",severeWarning:"ms-MessageBar--severeWarning",success:"ms-MessageBar--success",warning:"ms-MessageBar--warning",multiline:"ms-MessageBar-multiline",singleline:"ms-MessageBar-singleline",dismissalSingleLine:"ms-MessageBar-dismissalSingleLine",expandingSingleLine:"ms-MessageBar-expandingSingleLine",content:"ms-MessageBar-content",iconContainer:"ms-MessageBar-icon",text:"ms-MessageBar-text",innerText:"ms-MessageBar-innerText",dismissSingleLine:"ms-MessageBar-dismissSingleLine",expandSingleLine:"ms-MessageBar-expandSingleLine",dismissal:"ms-MessageBar-dismissal",expand:"ms-MessageBar-expand",actions:"ms-MessageBar-actions",actionsSingleline:"ms-MessageBar-actionsSingleLine"},Ex=((t={})[bx.error]="errorBackground",t[bx.blocked]="errorBackground",t[bx.success]="successBackground",t[bx.warning]="warningBackground",t[bx.severeWarning]="severeWarningBackground",t[bx.info]="infoBackground",t),Tx=((U={})[bx.error]="rgba(255, 0, 0, 0.3)",U[bx.blocked]="rgba(255, 0, 0, 0.3)",U[bx.success]="rgba(48, 241, 73, 0.3)",U[bx.warning]="rgba(255, 254, 57, 0.3)",U[bx.severeWarning]="rgba(255, 0, 0, 0.3)",U[bx.info]="Window",U),Px=((xe={})[bx.error]="errorIcon",xe[bx.blocked]="errorIcon",xe[bx.success]="successIcon",xe[bx.warning]="warningIcon",xe[bx.severeWarning]="severeWarningIcon",xe[bx.info]="infoIcon",xe),Rx=In(wx,function(e){var t=e.theme,o=e.className,n=e.onDismiss,r=e.truncated,i=e.isMultiline,s=e.expandSingleLine,a=e.messageBarType,l=void 0===a?bx.info:a,c=t.semanticColors,u=t.fonts,d=uo(0,ro),e=zo(Dx,t),a={fontSize:Ae.xSmall,height:10,lineHeight:"10px",color:c.messageText,selectors:((a={})[Yt]=ht(ht({},{forcedColorAdjust:"none",MsHighContrastAdjust:"none"}),{color:"WindowText"}),a)},t=[bo(t,{inset:1,highContrastStyle:{outlineOffset:"-6px",outline:"1px solid Highlight"},borderColor:"transparent"}),{flexShrink:0,width:32,height:32,padding:"8px 12px",selectors:{"& .ms-Button-icon":a,":hover":{backgroundColor:"transparent"},":active":{backgroundColor:"transparent"}}}];return{root:[e.root,u.medium,l===bx.error&&e.error,l===bx.blocked&&e.blocked,l===bx.severeWarning&&e.severeWarning,l===bx.success&&e.success,l===bx.warning&&e.warning,i?e.multiline:e.singleline,!i&&n&&e.dismissalSingleLine,!i&&r&&e.expandingSingleLine,{background:c[Ex[l]],color:c.messageText,minHeight:32,width:"100%",display:"flex",wordBreak:"break-word",selectors:((a={".ms-Link":{color:c.messageLink,selectors:{":hover":{color:c.messageLinkHovered}}}})[Yt]=ht(ht({},{forcedColorAdjust:"none",MsHighContrastAdjust:"none"}),{background:Tx[l],border:"1px solid WindowText",color:"WindowText"}),a)},i&&{flexDirection:"column"},o],content:[e.content,{display:"flex",width:"100%",lineHeight:"normal"}],iconContainer:[e.iconContainer,{fontSize:Ae.medium,minWidth:16,minHeight:16,display:"flex",flexShrink:0,margin:"8px 0 8px 12px"}],icon:{color:c[Px[l]],selectors:((l={})[Yt]=ht(ht({},{forcedColorAdjust:"none",MsHighContrastAdjust:"none"}),{color:"WindowText"}),l)},text:[e.text,ht(ht({minWidth:0,display:"flex",flexGrow:1,margin:8},u.small),{selectors:((u={})[Yt]=ht({},{forcedColorAdjust:"none",MsHighContrastAdjust:"none"}),u)}),!n&&{marginRight:12}],innerText:[e.innerText,{lineHeight:16,selectors:{"& span a:last-child":{paddingLeft:4}}},r&&{overflow:"visible",whiteSpace:"pre-wrap"},!i&&{overflow:"hidden",textOverflow:"ellipsis",whiteSpace:"nowrap"},!i&&!r&&{selectors:((r={})[d]={overflow:"visible",whiteSpace:"pre-wrap"},r)},s&&{overflow:"visible",whiteSpace:"pre-wrap"}],dismissSingleLine:e.dismissSingleLine,expandSingleLine:e.expandSingleLine,dismissal:[e.dismissal,t],expand:[e.expand,t],actions:[i?e.actions:e.actionsSingleline,{display:"flex",flexGrow:0,flexShrink:0,flexBasis:"auto",flexDirection:"row-reverse",alignItems:"center",margin:"0 12px 0 8px",selectors:{"& button:nth-child(n+2)":{marginLeft:8}}},i&&{marginBottom:8},n&&!i&&{marginRight:0}]}},void 0,{scope:"MessageBar"}),Mx={root:"ms-Nav",linkText:"ms-Nav-linkText",compositeLink:"ms-Nav-compositeLink",link:"ms-Nav-link",chevronButton:"ms-Nav-chevronButton",chevronIcon:"ms-Nav-chevron",navItem:"ms-Nav-navItem",navItems:"ms-Nav-navItems",group:"ms-Nav-group",groupContent:"ms-Nav-groupContent"},Nx={textContainer:{overflow:"hidden"},label:{whiteSpace:"nowrap",textOverflow:"ellipsis",overflow:"hidden"}};function Bx(e){return!!e&&!/^[a-z0-9+-.]+:\/\//i.test(e)}var Fx,Ax,Lx=Fn(),Hx=(l(zx,Ax=gt.Component),zx.prototype.render=function(){var e=this.props,t=e.styles,o=e.groups,n=e.className,r=e.isOnTop,i=e.theme;if(!o)return null;e=o.map(this._renderGroup),o=Lx(t,{theme:i,className:n,isOnTop:r,groups:o});return gt.createElement(Zs,{direction:Ei.vertical,componentRef:this._focusZone},gt.createElement("nav",{role:"navigation",className:o.root,"aria-label":this.props.ariaLabel},e))},Object.defineProperty(zx.prototype,"selectedKey",{get:function(){return this.state.selectedKey},enumerable:!1,configurable:!0}),zx.prototype.focus=function(e){return void 0===e&&(e=!1),!(!this._focusZone\|\|!this._focusZone.current)&&this._focusZone.current.focus(e)},zx.prototype._renderNavLink=function(e,t,o){var n=this.props,r=n.styles,i=n.groups,s=n.theme,a=e.icon\|\|e.iconProps,l=this._isLinkSelected(e),n=e.ariaCurrent,n=void 0===n?"page":n,s=Lx(r,{theme:s,isSelected:l,isDisabled:e.disabled,isButtonEntry:e.onClick&&!e.forceAnchor,leftPadding:14o+3+(a?0:24),groups:i}),o=e.url&&e.target&&!Bx(e.url)?"noopener noreferrer":void 0,a=this.props.linkAs?ju(this.props.linkAs,np):np,i=this.props.onRenderLink?Ma(this.props.onRenderLink,this._onRenderLink):this._onRenderLink;return gt.createElement(a,{className:s.link,styles:Nx,href:e.url\|\|(e.forceAnchor?"#":void 0),iconProps:e.iconProps\|\|{iconName:e.icon},onClick:(e.onClick?this._onNavButtonLinkClicked:this._onNavAnchorLinkClicked).bind(this,e),title:void 0!==e.title?e.title:e.name,target:e.target,rel:o,disabled:e.disabled,"aria-current":l?n:void 0,"aria-label":e.ariaLabel\|\|void 0,link:e},i(e))},zx.prototype._renderCompositeLink=function(e,t,o){var n=ht({},ur(e,cr,["onClick"])),r=this.props,i=r.expandButtonAriaLabel,s=r.styles,a=r.groups,r=r.theme,r=Lx(s,{theme:r,isExpanded:!!e.isExpanded,isSelected:this._isLinkSelected(e),isLink:!0,isDisabled:e.disabled,position:14o+1,groups:a}),a="";return e.links&&0<e.links.length&&(a=e.collapseAriaLabel\|\|e.expandAriaLabel?e.isExpanded?e.collapseAriaLabel:e.expandAriaLabel:i?e.name+" "+i:e.name),gt.createElement("div",ht({},n,{key:e.key\|\|t,className:r.compositeLink}),e.links&&0<e.links.length?gt.createElement("button",{className:r.chevronButton,onClick:this._onLinkExpandClicked.bind(this,e),"aria-label":a,"aria-expanded":e.isExpanded?"true":"false"},gt.createElement(Wr,{className:r.chevronIcon,iconName:"ChevronDown"})):null,this._renderNavLink(e,t,o))},zx.prototype._renderLink=function(e,t,o){var n=this.props,r=n.styles,i=n.groups,n=n.theme,i=Lx(r,{theme:n,groups:i});return gt.createElement("li",{key:e.key\|\|t,role:"listitem",className:i.navItem},this._renderCompositeLink(e,t,o),e.isExpanded?this._renderLinks(e.links,++o):null)},zx.prototype._renderLinks=function(e,o){var n=this;if(!e\|\|!e.length)return null;var t=e.map(function(e,t){return n._renderLink(e,t,o)}),r=this.props,i=r.styles,e=r.groups,r=r.theme,e=Lx(i,{theme:r,groups:e});return gt.createElement("ul",{role:"list",className:e.navItems},t)},zx.prototype._onGroupHeaderClicked=function(e,t){e.onHeaderClick&&e.onHeaderClick(t,this._isGroupExpanded(e)),void 0===e.isExpanded&&this._toggleCollapsed(e),t&&(t.preventDefault(),t.stopPropagation())},zx.prototype._onLinkExpandClicked=function(e,t){var o=this.props.onLinkExpandClick;o&&o(t,e),t.defaultPrevented\|\|(e.isExpanded=!e.isExpanded,this.setState({isLinkExpandStateChanged:!0})),t.preventDefault(),t.stopPropagation()},zx.prototype._preventBounce=function(e,t){!e.url&&e.forceAnchor&&t.preventDefault()},zx.prototype._onNavAnchorLinkClicked=function(e,t){this._preventBounce(e,t),this.props.onLinkClick&&this.props.onLinkClick(t,e),!e.url&&e.links&&0<e.links.length&&this._onLinkExpandClicked(e,t),this.setState({selectedKey:e.key})},zx.prototype._onNavButtonLinkClicked=function(e,t){this._preventBounce(e,t),e.onClick&&e.onClick(t,e),!e.url&&e.links&&0<e.links.length&&this._onLinkExpandClicked(e,t),this.setState({selectedKey:e.key})},zx.prototype._isLinkSelected=function(e){if(void 0!==this.props.selectedKey)return e.key===this.props.selectedKey;if(void 0!==this.state.selectedKey)return e.key===this.state.selectedKey;if(void 0===qe()\|\|!e.url)return!1;(Ix=Ix\|\|document.createElement("a")).href=e.url\|\|"";var t=Ix.href;return location.href===t\|\|location.protocol+"//"+location.host+location.pathname===t\|\|!!location.hash&&(location.hash===e.url\|\|(Ix.href=location.hash.substring(1),Ix.href===t))},zx.prototype._isGroupExpanded=function(e){return void 0!==e.isExpanded?e.isExpanded:e.name&&this.state.isGroupCollapsed.hasOwnProperty(e.name)?!this.state.isGroupCollapsed[e.name]:void 0===e.collapseByDefault\|\|!e.collapseByDefault},zx.prototype._toggleCollapsed=function(e){var t;e.name&&(t=ht(ht({},this.state.isGroupCollapsed),((t={})[e.name]=this._isGroupExpanded(e),t)),this.setState({isGroupCollapsed:t}))},zx.defaultProps={groups:null},zx),Ox=In(Hx,function(e){var t=e.className,o=e.theme,n=e.isOnTop,r=e.isExpanded,i=e.isGroup,s=e.isLink,a=e.isSelected,l=e.isDisabled,c=e.isButtonEntry,u=e.navHeight,d=void 0===u?44:u,p=e.position,h=e.leftPadding,m=void 0===h?20:h,g=e.leftPaddingExpanded,f=void 0===g?28:g,v=e.rightPadding,u=void 0===v?20:v,h=o.palette,g=o.semanticColors,e=o.fonts,v=zo(Mx,o);return{root:[v.root,t,e.medium,{overflowY:"auto",userSelect:"none",WebkitOverflowScrolling:"touch"},n&&[{position:"absolute"},Le.slideRightIn40]],linkText:[v.linkText,{margin:"0 4px",overflow:"hidden",verticalAlign:"middle",textAlign:"left",textOverflow:"ellipsis"}],compositeLink:[v.compositeLink,{display:"block",position:"relative",color:g.bodyText},r&&"is-expanded",a&&"is-selected",l&&"is-disabled",l&&{color:g.disabledText}],link:[v.link,bo(o),{display:"block",position:"relative",height:d,width:"100%",lineHeight:d+"px",textDecoration:"none",cursor:"pointer",textOverflow:"ellipsis",whiteSpace:"nowrap",overflow:"hidden",paddingLeft:m,paddingRight:u,color:g.bodyText,selectors:((m={})[Yt]={border:0,selectors:{":focus":{border:"1px solid WindowText"}}},m)},!l&&{selectors:{".ms-Nav-compositeLink:hover &":{backgroundColor:g.bodyBackgroundHovered}}},a&&{color:g.bodyTextChecked,fontWeight:Fe.semibold,backgroundColor:g.bodyBackgroundChecked,selectors:{"&:after":{borderLeft:"2px solid "+h.themePrimary,content:'""',position:"absolute",top:0,right:0,bottom:0,left:0,pointerEvents:"none"}}},l&&{color:g.disabledText},c&&{color:h.themePrimary}],chevronButton:[v.chevronButton,bo(o),e.small,{display:"block",textAlign:"left",lineHeight:d+"px",margin:"5px 0",padding:"0px, "+u+"px, 0px, "+f+"px",border:"none",textOverflow:"ellipsis",whiteSpace:"nowrap",overflow:"hidden",cursor:"pointer",color:g.bodyText,backgroundColor:"transparent",selectors:{"&:visited":{color:g.bodyText}}},i&&{fontSize:e.large.fontSize,width:"100%",height:d,borderBottom:"1px solid "+g.bodyDivider},s&&{display:"block",width:f-2,height:d-2,position:"absolute",top:"1px",left:p+"px",zIndex:mo.Nav,padding:0,margin:0},a&&{color:h.themePrimary,backgroundColor:h.neutralLighterAlt,selectors:{"&:after":{borderLeft:"2px solid "+h.themePrimary,content:'""',position:"absolute",top:0,right:0,bottom:0,left:0,pointerEvents:"none"}}}],chevronIcon:[v.chevronIcon,{position:"absolute",left:"8px",height:d,display:"inline-flex",alignItems:"center",lineHeight:d+"px",fontSize:e.small.fontSize,transition:"transform .1s linear"},r&&{transform:"rotate(-180deg)"},s&&{top:0}],navItem:[v.navItem,{padding:0}],navItems:[v.navItems,{listStyleType:"none",padding:0,margin:0}],group:[v.group,r&&"is-expanded"],groupContent:[v.groupContent,{display:"none",marginBottom:"40px"},Le.slideDownIn20,r&&{display:"block"}]}},void 0,{scope:"Nav"});function zx(e){var a=Ax.call(this,e)\|\|this;return a._focusZone=gt.createRef(),a._onRenderLink=function(e){var t=a.props,o=t.styles,n=t.groups,t=t.theme,n=Lx(o,{theme:t,groups:n});return gt.createElement("div",{className:n.linkText},e.name)},a._renderGroup=function(o,e){var t=a.props,n=t.styles,r=t.groups,i=t.theme,s=t.onRenderGroupHeader,t=void 0===s?a._renderGroupHeader:s,s=a._isGroupExpanded(o),r=Lx(n,{theme:i,isGroup:!0,isExpanded:s,groups:r}),s=ht(ht({},o),{isExpanded:s,onHeaderClick:function(e,t){a._onGroupHeaderClicked(o,e)}});return gt.createElement("div",{key:e,className:r.group},s.name?t(s,a._renderGroupHeader):null,gt.createElement("div",{className:r.groupContent},a._renderLinks(s.links,0)))},a._renderGroupHeader=function(e){var t=a.props,o=t.styles,n=t.groups,r=t.theme,t=t.expandButtonAriaLabel,i=e.isExpanded,n=Lx(o,{theme:r,isGroup:!0,isExpanded:i,groups:n}),t=(i?e.collapseAriaLabel:e.expandAriaLabel)\|\|t,s=e.onHeaderClick;return gt.createElement("button",{className:n.chevronButton,onClick:s?function(e){s(e,i)}:void 0,"aria-label":t,"aria-expanded":i},gt.createElement(Wr,{className:n.chevronIcon,iconName:"ChevronDown"}),e.name)},fi(a),a.state={isGroupCollapsed:{},isLinkExpandStateChanged:!1,selectedKey:e.initialSelectedKey\|\|e.selectedKey},a}(G=Fx=Fx\|\|{})[G.none=0]="none",G[G.forceResolve=1]="forceResolve",G[G.searchMore=2]="searchMore";var Wx,Vx,Kx={root:"ms-Suggestions-item",itemButton:"ms-Suggestions-itemButton",closeButton:"ms-Suggestions-closeButton",isSuggested:"is-suggested"},Gx=o,Ux=Fn(),jx=In(b_,function(e){var t,o=e.className,n=e.theme,r=e.suggested,i=n.palette,s=n.semanticColors,a=zo(Kx,n);return{root:[a.root,{display:"flex",alignItems:"stretch",boxSizing:"border-box",width:"100%",position:"relative",selectors:{"&:hover":{background:s.menuItemBackgroundHovered},"&:hover .ms-Suggestions-closeButton":{display:"block"}}},r&&{selectors:((t={})["."+go+" &"]={selectors:((e={})["."+a.closeButton]={display:"block",background:s.menuItemBackgroundPressed},e)},t[":after"]={pointerEvents:"none",content:'""',position:"absolute",left:0,top:0,bottom:0,right:0,border:"1px solid "+n.semanticColors.focusBorder},t)},o],itemButton:[a.itemButton,{width:"100%",padding:0,border:"none",height:"100%",minWidth:0,overflow:"hidden",selectors:((o={})[Yt]={color:"WindowText",selectors:{":hover":ht({background:"Highlight",color:"HighlightText"},{forcedColorAdjust:"none",MsHighContrastAdjust:"none"})}},o[":hover"]={color:s.menuItemTextHovered},o)},r&&[a.isSuggested,{background:s.menuItemBackgroundPressed,selectors:((s={":hover":{background:s.menuDivider}})[Yt]=ht({background:"Highlight",color:"HighlightText"},{forcedColorAdjust:"none",MsHighContrastAdjust:"none"}),s)}]],closeButton:[a.closeButton,{display:"none",color:i.neutralSecondary,padding:"0 4px",height:"auto",width:32,selectors:((a={":hover, :active":{background:i.neutralTertiaryAlt,color:i.neutralDark}})[Yt]={color:"WindowText"},a)},r&&((r={})["."+go+" &"]={selectors:{":hover, :active":{background:i.neutralTertiary}}},r.selectors={":hover, :active":{background:i.neutralTertiary,color:i.neutralPrimary}},r)]}},void 0,{scope:"SuggestionItem"}),qx=(l(Qx,Vx=gt.Component),Qx.prototype.componentDidMount=function(){this.scrollSelected(),this.activeSelectedElement=this._selectedElement?this._selectedElement.current:null},Qx.prototype.componentDidUpdate=function(){this._selectedElement.current&&this.activeSelectedElement!==this._selectedElement.current&&(this.scrollSelected(),this.activeSelectedElement=this._selectedElement.current)},Qx.prototype.render=function(){var e=this,t=this.props,o=t.forceResolveText,n=t.mostRecentlyUsedHeaderText,r=t.searchForMoreIcon,i=t.searchForMoreText,s=t.className,a=t.moreSuggestionsAvailable,l=t.noResultsFoundText,c=t.suggestions,u=t.isLoading,d=t.isSearching,p=t.loadingText,h=t.onRenderNoResultFound,m=t.searchingText,g=t.isMostRecentlyUsedVisible,f=t.resultsMaximumNumber,v=t.resultsFooterFull,b=t.resultsFooter,y=t.isResultsFooterVisible,C=void 0===y\|\|y,_=t.suggestionsHeaderText,S=t.suggestionsClassName,x=t.theme,k=t.styles,y=t.suggestionsListId,t=t.suggestionsContainerAriaLabel;this._classNames=k?Ux(k,{theme:x,className:s,suggestionsClassName:S,forceResolveButtonSelected:this.state.selectedActionType===Fx.forceResolve,searchForMoreButtonSelected:this.state.selectedActionType===Fx.searchMore}):{root:Tr("ms-Suggestions",s,Gx.root),title:Tr("ms-Suggestions-title",Gx.suggestionsTitle),searchForMoreButton:Tr("ms-SearchMore-button",Gx.actionButton,((s={})["is-selected "+Gx.buttonSelected]=this.state.selectedActionType===Fx.searchMore,s)),forceResolveButton:Tr("ms-forceResolve-button",Gx.actionButton,((s={})["is-selected "+Gx.buttonSelected]=this.state.selectedActionType===Fx.forceResolve,s)),suggestionsAvailable:Tr("ms-Suggestions-suggestionsAvailable",Gx.suggestionsAvailable),suggestionsContainer:Tr("ms-Suggestions-container",Gx.suggestionsContainer,S),noSuggestions:Tr("ms-Suggestions-none",Gx.suggestionsNone)};var S=this._classNames.subComponentStyles?this._classNames.subComponentStyles.spinner:void 0,S=k?{styles:S}:{className:Tr("ms-Suggestions-spinner",Gx.suggestionsSpinner)},w=function(){return gt.createElement("div",{id:"sug-noResultsFound",role:"option"},h?h(void 0,w):gt.createElement("div",{className:e._classNames.noSuggestions},l))},_=_;g&&n&&(_=n);n=void 0;C&&(n=c.length>=f?v:b);v=!(c&&c.length\|\|u),b=this.state.selectedActionType===Fx.forceResolve?"sug-selectedAction":void 0,c=this.state.selectedActionType===Fx.searchMore?"sug-selectedAction":void 0;return gt.createElement("div",{className:this._classNames.root,"aria-label":t\|\|_,id:y,role:"listbox"},gt.createElement(Bi,{message:this._getAlertText(),"aria-live":"polite"}),_?gt.createElement("div",{className:this._classNames.title},_):null,o&&this._shouldShowForceResolve()&&gt.createElement(up,{componentRef:this._forceResolveButton,className:this._classNames.forceResolveButton,id:b,onClick:this._forceResolve,"data-automationid":"sug-forceResolve"},o),u&&gt.createElement(Fb,ht({},S,{label:p})),v?w():this._renderSuggestions(),i&&a&&gt.createElement(up,{componentRef:this._searchForMoreButton,className:this._classNames.searchForMoreButton,iconProps:r\|\|{iconName:"Search"},id:c,onClick:this._getMoreResults,"data-automationid":"sug-searchForMore",role:"option"},i),d?gt.createElement(Fb,ht({},S,{label:m})):null,!n\|\|a\|\|g\|\|d?null:gt.createElement("div",{className:this._classNames.title},n(this.props)))},Qx.prototype.hasSuggestedAction=function(){return!!this._searchForMoreButton.current\|\|!!this._forceResolveButton.current},Qx.prototype.hasSuggestedActionSelected=function(){return this.state.selectedActionType!==Fx.none},Qx.prototype.executeSelectedAction=function(){switch(this.state.selectedActionType){case Fx.forceResolve:this._forceResolve();break;case Fx.searchMore:this._getMoreResults()}},Qx.prototype.focusAboveSuggestions=function(){this._forceResolveButton.current?this.setState({selectedActionType:Fx.forceResolve}):this._searchForMoreButton.current&&this.setState({selectedActionType:Fx.searchMore})},Qx.prototype.focusBelowSuggestions=function(){this._searchForMoreButton.current?this.setState({selectedActionType:Fx.searchMore}):this._forceResolveButton.current&&this.setState({selectedActionType:Fx.forceResolve})},Qx.prototype.focusSearchForMoreButton=function(){this._searchForMoreButton.current&&this._searchForMoreButton.current.focus()},Qx.prototype.scrollSelected=function(){var e,t,o,n,r;this._selectedElement.current&&this._scrollContainer.current&&void 0!==this._scrollContainer.current.scrollTo&&(e=(n=this._selectedElement.current).offsetHeight,t=n.offsetTop,o=(r=this._scrollContainer.current).offsetHeight,r=(n=r.scrollTop)+o<t+e,t<n?this._scrollContainer.current.scrollTo(0,t):r&&this._scrollContainer.current.scrollTo(0,t-o+e))},Qx.prototype._renderSuggestions=function(){var o=this,e=this.props,n=e.onRenderSuggestion,r=e.removeSuggestionAriaLabel,i=e.suggestionsItemClassName,t=e.resultsMaximumNumber,s=e.showRemoveButtons,a=e.removeButtonIconProps,e=this.props.suggestions,l=jx,c=-1;return e.some(function(e,t){return!!e.selected&&(c=t,!0)}),0===(e=t?t<=c?e.slice(c-t+1,c+1):e.slice(0,t):e).length?null:gt.createElement("div",{className:this._classNames.suggestionsContainer,ref:this._scrollContainer,role:"presentation"},e.map(function(e,t){return gt.createElement("div",{ref:e.selected?o._selectedElement:void 0,key:e.item.key\|\|t,role:"presentation"},gt.createElement(l,{suggestionModel:e,RenderSuggestion:n,onClick:o._onClickTypedSuggestionsItem(e.item,t),className:i,showRemoveButton:s,removeButtonAriaLabel:r,onRemoveItem:o._onRemoveTypedSuggestionsItem(e.item,t),id:"sug-"+t,removeButtonIconProps:a}))}))},Qx),Yx=(Xx.prototype.updateSuggestions=function(e,t){e&&0<e.length?(this.suggestions=this.convertSuggestionsToSuggestionItems(e),this.currentIndex=t\|\|0,-1===t?this.currentSuggestion=void 0:void 0!==t&&(this.suggestions[t].selected=!0,this.currentSuggestion=this.suggestions[t])):(this.suggestions=[],this.currentIndex=-1,this.currentSuggestion=void 0)},Xx.prototype.nextSuggestion=function(){if(this.suggestions&&this.suggestions.length){if(this.currentIndex<this.suggestions.length-1)return this.setSelectedSuggestion(this.currentIndex+1),!0;if(this.currentIndex===this.suggestions.length-1)return this.setSelectedSuggestion(0),!0}return!1},Xx.prototype.previousSuggestion=function(){if(this.suggestions&&this.suggestions.length){if(0<this.currentIndex)return this.setSelectedSuggestion(this.currentIndex-1),!0;if(0===this.currentIndex)return this.setSelectedSuggestion(this.suggestions.length-1),!0}return!1},Xx.prototype.getSuggestions=function(){return this.suggestions},Xx.prototype.getCurrentItem=function(){return this.currentSuggestion},Xx.prototype.getSuggestionAtIndex=function(e){return this.suggestions[e]},Xx.prototype.hasSelectedSuggestion=function(){return!!this.currentSuggestion},Xx.prototype.removeSuggestion=function(e){this.suggestions.splice(e,1)},Xx.prototype.createGenericSuggestion=function(e){e=this.convertSuggestionsToSuggestionItems([e])[0];this.currentSuggestion=e},Xx.prototype.convertSuggestionsToSuggestionItems=function(e){return Array.isArray(e)?e.map(this._ensureSuggestionModel):[]},Xx.prototype.deselectAllSuggestions=function(){-1<this.currentIndex&&(this.suggestions[this.currentIndex].selected=!1,this.currentIndex=-1)},Xx.prototype.setSelectedSuggestion=function(e){e>this.suggestions.length-1\|\|e<0?(this.currentIndex=0,this.currentSuggestion.selected=!1,this.currentSuggestion=this.suggestions[0],this.currentSuggestion.selected=!0):(-1<this.currentIndex&&(this.suggestions[this.currentIndex].selected=!1),this.suggestions[e].selected=!0,this.currentIndex=e,this.currentSuggestion=this.suggestions[e])},Xx),Zx={root:"ms-Suggestions",suggestionsContainer:"ms-Suggestions-container",title:"ms-Suggestions-title",forceResolveButton:"ms-forceResolve-button",searchForMoreButton:"ms-SearchMore-button",spinner:"ms-Suggestions-spinner",noSuggestions:"ms-Suggestions-none",suggestionsAvailable:"ms-Suggestions-suggestionsAvailable",isSelected:"is-selected"};function Xx(){var t=this;this._isSuggestionModel=function(e){return void 0!==e.item},this._ensureSuggestionModel=function(e){return t._isSuggestionModel(e)?e:{item:e,selected:!1,ariaLabel:e.name\|\|e.primaryText}},this.suggestions=[],this.currentIndex=-1}function Qx(e){var s=Vx.call(this,e)\|\|this;return s._forceResolveButton=gt.createRef(),s._searchForMoreButton=gt.createRef(),s._selectedElement=gt.createRef(),s._scrollContainer=gt.createRef(),s.tryHandleKeyDown=function(e,t){var o=!1,n=null,r=s.state.selectedActionType,i=s.props.suggestions.length;if(e===En.down)switch(r){case Fx.forceResolve:n=0<i?(s._refocusOnSuggestions(e),Fx.none):s._searchForMoreButton.current?Fx.searchMore:Fx.forceResolve;break;case Fx.searchMore:n=s._forceResolveButton.current?Fx.forceResolve:0<i?(s._refocusOnSuggestions(e),Fx.none):Fx.searchMore;break;case Fx.none:-1===t&&s._forceResolveButton.current&&(n=Fx.forceResolve)}else if(e===En.up)switch(r){case Fx.forceResolve:s._searchForMoreButton.current?n=Fx.searchMore:0<i&&(s._refocusOnSuggestions(e),n=Fx.none);break;case Fx.searchMore:0<i?(s._refocusOnSuggestions(e),n=Fx.none):s._forceResolveButton.current&&(n=Fx.forceResolve);break;case Fx.none:-1===t&&s._searchForMoreButton.current&&(n=Fx.searchMore)}return null!==n&&(s.setState({selectedActionType:n}),o=!0),o},s._getAlertText=function(){var e=s.props,t=e.isLoading,o=e.isSearching,n=e.suggestions,r=e.suggestionsAvailableAlertText,e=e.noResultsFoundText;if(!t&&!o){if(0<n.length)return r\|\|"";if(e)return e}return""},s._getMoreResults=function(){s.props.onGetMoreResults&&(s.props.onGetMoreResults(),s.setState({selectedActionType:Fx.none}))},s._forceResolve=function(){s.props.createGenericItem&&s.props.createGenericItem()},s._shouldShowForceResolve=function(){return!!s.props.showForceResolve&&s.props.showForceResolve()},s._onClickTypedSuggestionsItem=function(t,o){return function(e){s.props.onSuggestionClick(e,t,o)}},s._refocusOnSuggestions=function(e){"function"==typeof s.props.refocusSuggestions&&s.props.refocusSuggestions(e)},s._onRemoveTypedSuggestionsItem=function(t,o){return function(e){(0,s.props.onSuggestionRemove)(e,t,o),e.stopPropagation()}},fi(s),s.state={selectedActionType:Fx.none},s}function Jx(e){var t=e.className,o=e.suggestionsClassName,n=e.theme,r=e.forceResolveButtonSelected,i=e.searchForMoreButtonSelected,s=n.palette,a=n.semanticColors,l=n.fonts,c=zo(Zx,n),e={backgroundColor:"transparent",border:0,cursor:"pointer",margin:0,paddingLeft:8,position:"relative",borderTop:"1px solid "+s.neutralLight,height:40,textAlign:"left",width:"100%",fontSize:l.small.fontSize,selectors:{":hover":{backgroundColor:a.menuItemBackgroundPressed,cursor:"pointer"},":focus, :active":{backgroundColor:s.themeLight},".ms-Button-icon":{fontSize:l.mediumPlus.fontSize,width:25},".ms-Button-label":{margin:"0 4px 0 9px"}}},n={backgroundColor:s.themeLight,selectors:((n={})[Yt]=ht({backgroundColor:"Highlight",borderColor:"Highlight",color:"HighlightText"},{forcedColorAdjust:"none",MsHighContrastAdjust:"none"}),n)};return{root:[c.root,{minWidth:260},t],suggestionsContainer:[c.suggestionsContainer,{overflowY:"auto",overflowX:"hidden",maxHeight:300,transform:"translate3d(0,0,0)"},o],title:[c.title,{padding:"0 12px",fontSize:l.small.fontSize,color:s.themePrimary,lineHeight:40,borderBottom:"1px solid "+a.menuItemBackgroundPressed}],forceResolveButton:[c.forceResolveButton,e,r&&[c.isSelected,n]],searchForMoreButton:[c.searchForMoreButton,e,i&&[c.isSelected,n]],noSuggestions:[c.noSuggestions,{textAlign:"center",color:s.neutralSecondary,fontSize:l.small.fontSize,lineHeight:30}],suggestionsAvailable:[c.suggestionsAvailable,So],subComponentStyles:{spinner:{root:[c.spinner,{margin:"5px 0",paddingLeft:14,textAlign:"left",whiteSpace:"nowrap",lineHeight:20,fontSize:l.small.fontSize}],circle:{display:"inline-block",verticalAlign:"middle"},label:{display:"inline-block",verticalAlign:"middle",margin:"0 10px 0 16px"}}}}}(V=Wx=Wx\|\|{})[V.valid=0]="valid",V[V.warning=1]="warning",V[V.invalid=2]="invalid",Dt([{rawString:".pickerText_15a92175{display:-webkit-box;display:-ms-flexbox;display:flex;-ms-flex-wrap:wrap;flex-wrap:wrap;-webkit-box-align:center;-ms-flex-align:center;align-items:center;-webkit-box-sizing:border-box;box-sizing:border-box;border:1px solid "},{theme:"neutralTertiary",defaultValue:"#a19f9d"},{rawString:";min-width:180px;min-height:30px}.pickerText_15a92175:hover{border-color:"},{theme:"inputBorderHovered",defaultValue:"#323130"},{rawString:"}.pickerText_15a92175.inputFocused_15a92175{position:relative;border-color:"},{theme:"inputFocusBorderAlt",defaultValue:"#0078d4"},{rawString:"}.pickerText_15a92175.inputFocused_15a92175:after{pointer-events:none;content:'';position:absolute;left:-1px;top:-1px;bottom:-1px;right:-1px;border:2px solid "},{theme:"inputFocusBorderAlt",defaultValue:"#0078d4"},{rawString:"}@media screen and (-ms-high-contrast:active){.pickerText_15a92175.inputDisabled_15a92175{position:relative;border-color:GrayText}.pickerText_15a92175.inputDisabled_15a92175:after{pointer-events:none;content:'';position:absolute;left:0;top:0;bottom:0;right:0;background-color:Window}}.pickerInput_15a92175{height:34px;border:none;-webkit-box-flex:1;-ms-flex-positive:1;flex-grow:1;outline:0;padding:0 6px 0;-ms-flex-item-align:end;align-self:flex-end}.pickerItems_15a92175{display:-webkit-box;display:-ms-flexbox;display:flex;-ms-flex-wrap:wrap;flex-wrap:wrap;max-width:100%}.screenReaderOnly_15a92175{position:absolute;width:1px;height:1px;padding:0;margin:-1px;overflow:hidden;clip:rect(0,0,0,0);border:0}"}]);var $x,ek,tk="pickerText_15a92175",ok="inputFocused_15a92175",nk="inputDisabled_15a92175",rk="pickerInput_15a92175",ik="pickerItems_15a92175",sk="screenReaderOnly_15a92175",ak=i,lk=Fn(),ck=(l(_k,ek=gt.Component),_k.getDerivedStateFromProps=function(e){return e.selectedItems?{items:e.selectedItems}:null},Object.defineProperty(_k.prototype,"items",{get:function(){return this.state.items},enumerable:!1,configurable:!0}),_k.prototype.componentDidMount=function(){this.selection.setItems(this.state.items),this._onResolveSuggestions=this._async.debounce(this._onResolveSuggestions,this.props.resolveDelay)},_k.prototype.componentDidUpdate=function(e,t){var o;this.state.items&&this.state.items!==t.items&&(o=this.selection.getSelectedIndices()[0],this.selection.setItems(this.state.items),this.state.isFocused&&(this.state.items.length<t.items.length?(this.selection.setIndexSelected(o,!1,!0),this.resetFocus(o)):this.state.items.length>t.items.length&&!this.canAddItems()&&this.resetFocus(this.state.items.length-1)))},_k.prototype.componentWillUnmount=function(){this.currentPromise&&(this.currentPromise=void 0),this._async.dispose()},_k.prototype.focus=function(){this.input.current&&this.input.current.focus()},_k.prototype.focusInput=function(){this.input.current&&this.input.current.focus()},_k.prototype.completeSuggestion=function(e){this.suggestionStore.hasSelectedSuggestion()&&this.input.current?this.completeSelection(this.suggestionStore.currentSuggestion.item):e&&this._completeGenericSuggestion()},_k.prototype.render=function(){var e=this.state,t=e.suggestedDisplayValue,o=e.isFocused,n=e.items,r=this.props,i=r.className,s=r.inputProps,a=r.disabled,l=r.selectionAriaLabel,c=r.selectionRole,u=void 0===c?"list":c,e=r.theme,c=r.styles,r=this.state.suggestionsVisible?this._ariaMap.suggestionList:"",o=c?lk(c,{theme:e,className:i,isFocused:o,disabled:a,inputClassName:s&&s.className}):{root:Tr("ms-BasePicker",i\|\|""),text:Tr("ms-BasePicker-text",ak.pickerText,this.state.isFocused&&ak.inputFocused),itemsWrapper:ak.pickerItems,input:Tr("ms-BasePicker-input",ak.pickerInput,s&&s.className),screenReaderText:ak.screenReaderOnly},i=this.props["aria-label"]\|\|(null==s?void 0:s["aria-label"]);return gt.createElement("div",{ref:this.root,className:o.root,onKeyDown:this.onKeyDown,onFocus:this.onFocus,onBlur:this.onBlur},this.renderCustomAlert(o.screenReaderText),gt.createElement("span",{id:this._ariaMap.selectedItems+"-label",hidden:!0},l\|\|i),gt.createElement(Pv,{selection:this.selection,selectionMode:dv.multiple},gt.createElement("div",{className:o.text,"aria-owns":r},0<n.length&&gt.createElement("span",{id:this._ariaMap.selectedItems,className:o.itemsWrapper,role:u,"aria-labelledby":this._ariaMap.selectedItems+"-label"},this.renderItems()),this.canAddItems()&&gt.createElement(ki,ht({spellCheck:!1},s,{className:o.input,componentRef:this.input,id:null!=s&&s.id?s.id:this._ariaMap.combobox,onClick:this.onClick,onFocus:this.onInputFocus,onBlur:this.onInputBlur,onInputValueChange:this.onInputChange,suggestedDisplayValue:t,"aria-activedescendant":this.getActiveDescendant(),"aria-controls":r,"aria-describedby":0<n.length?this._ariaMap.selectedItems:void 0,"aria-expanded":!!this.state.suggestionsVisible,"aria-haspopup":"listbox","aria-label":i,role:"combobox",disabled:a,onInputChange:this.props.onInputChange})))),this.renderSuggestions())},_k.prototype.canAddItems=function(){var e=this.state.items,t=this.props.itemLimit;return void 0===t\|\|e.length<t},_k.prototype.renderSuggestions=function(){var e=this._styledSuggestions;return this.state.suggestionsVisible&&this.input?gt.createElement(ac,ht({isBeakVisible:!1,gapSpace:5,target:this.input.current?this.input.current.inputElement:void 0,onDismiss:this.dismissSuggestions,directionalHint:Pa.bottomLeftEdge,directionalHintForRTL:Pa.bottomRightEdge},this.props.pickerCalloutProps),gt.createElement(e,ht({onRenderSuggestion:this.props.onRenderSuggestionsItem,onSuggestionClick:this.onSuggestionClick,onSuggestionRemove:this.onSuggestionRemove,suggestions:this.suggestionStore.getSuggestions(),componentRef:this.suggestionElement,onGetMoreResults:this.onGetMoreResults,moreSuggestionsAvailable:this.state.moreSuggestionsAvailable,isLoading:this.state.suggestionsLoading,isSearching:this.state.isSearching,isMostRecentlyUsedVisible:this.state.isMostRecentlyUsedVisible,isResultsFooterVisible:this.state.isResultsFooterVisible,refocusSuggestions:this.refocusSuggestions,removeSuggestionAriaLabel:this.props.removeButtonAriaLabel,suggestionsListId:this._ariaMap.suggestionList,createGenericItem:this._completeGenericSuggestion},this.props.pickerSuggestionsProps))):null},_k.prototype.renderItems=function(){var o=this,e=this.props,n=e.disabled,r=e.removeButtonAriaLabel,i=e.removeButtonIconProps,s=this.props.onRenderItem,t=this.state,e=t.items,a=t.selectedIndices;return e.map(function(e,t){return s({item:e,index:t,key:e.key\|\|t,selected:-1!==a.indexOf(t),onRemoveItem:function(){return o.removeItem(e)},disabled:n,onItemChange:o.onItemChange,removeButtonAriaLabel:r,removeButtonIconProps:i})})},_k.prototype.resetFocus=function(e){var t=this.state.items;t.length&&0<=e?(e=this.root.current&&this.root.current.querySelectorAll("[data-selection-index]")[Math.min(e,t.length-1)])&&e.focus():this.canAddItems()?this.input.current&&this.input.current.focus():this.resetFocus(t.length-1)},_k.prototype.onSuggestionSelect=function(){var e;this.suggestionStore.currentSuggestion&&(e=this.input.current?this.input.current.value:"",e=this._getTextFromItem(this.suggestionStore.currentSuggestion.item,e),this.setState({suggestedDisplayValue:e}))},_k.prototype.onSelectionChange=function(){this.setState({selectedIndices:this.selection.getSelectedIndices()})},_k.prototype.updateSuggestions=function(e){this.suggestionStore.updateSuggestions(e,0),this.forceUpdate()},_k.prototype.onEmptyInputFocus=function(){var e=this.props.onEmptyResolveSuggestions\|\|this.props.onEmptyInputFocus;e&&(e=e(this.state.items),this.updateSuggestionsList(e),this.setState({isMostRecentlyUsedVisible:!0,suggestionsVisible:!0,moreSuggestionsAvailable:!1}))},_k.prototype.updateValue=function(e){this._onResolveSuggestions(e)},_k.prototype.updateSuggestionsList=function(t,o){var n=this;Array.isArray(t)?this._updateAndResolveValue(o,t):t&&t.then&&(this.setState({suggestionsLoading:!0}),this.suggestionStore.updateSuggestions([]),void 0!==o?this.setState({suggestionsVisible:this._getShowSuggestions()}):this.setState({suggestionsVisible:this.input.current&&this.input.current.inputElement===document.activeElement}),(this.currentPromise=t).then(function(e){t===n.currentPromise&&n._updateAndResolveValue(o,e)}))},_k.prototype.resolveNewValue=function(e,t){var o=this;this.updateSuggestions(t);t=void 0;this.suggestionStore.currentSuggestion&&(t=this._getTextFromItem(this.suggestionStore.currentSuggestion.item,e)),this.setState({suggestedDisplayValue:t,suggestionsVisible:this._getShowSuggestions()},function(){return o.setState({suggestionsLoading:!1})})},_k.prototype.onChange=function(e){this.props.onChange&&this.props.onChange(e)},_k.prototype.onBackspace=function(e){(this.state.items.length&&!this.input.current\|\|this.input.current&&!this.input.current.isValueSelected&&0===this.input.current.cursorLocation)&&(0<this.selection.getSelectedCount()?this.removeItems(this.selection.getSelection()):this.removeItem(this.state.items[this.state.items.length-1]))},_k.prototype.getActiveDescendant=function(){var e;if(!this.state.suggestionsLoading){var t=this.suggestionStore.currentIndex;return t<0?null!==(e=this.suggestionElement.current)&&void 0!==e&&e.hasSuggestedAction()?"sug-selectedAction":0===this.suggestionStore.suggestions.length?"sug-noResultsFound":void 0:"sug-"+t}},_k.prototype.getSuggestionsAlert=function(e){void 0===e&&(e=ak.screenReaderOnly);var t=this.suggestionStore.currentIndex;if(this.props.enableSelectedSuggestionAlert){t=-1<t?this.suggestionStore.getSuggestionAtIndex(this.suggestionStore.currentIndex):void 0,t=t?t.ariaLabel:void 0;return gt.createElement("div",{id:this._ariaMap.selectedSuggestionAlert,className:e},t+" ")}},_k.prototype.renderCustomAlert=function(e){void 0===e&&(e=ak.screenReaderOnly);var t=this.props.suggestionRemovedText,o="";return this.state.selectionRemoved&&(o=Jp(void 0===t?"removed {0}":t,this._getTextFromItem(this.state.selectionRemoved,""))),gt.createElement("div",{className:e,id:this._ariaMap.selectedSuggestionAlert,"aria-live":"assertive"},this.getSuggestionsAlert(e),o)},_k.prototype._updateAndResolveValue=function(e,t){void 0!==e?this.resolveNewValue(e,t):(this.suggestionStore.updateSuggestions(t,-1),this.state.suggestionsLoading&&this.setState({suggestionsLoading:!1}))},_k.prototype._updateSelectedItems=function(e){var t=this;this.props.selectedItems?this.onChange(e):this.setState({items:e},function(){t._onSelectedItemsUpdated(e)})},_k.prototype._onSelectedItemsUpdated=function(e){this.onChange(e)},_k.prototype._getShowSuggestions=function(){return void 0!==this.input.current&&null!==this.input.current&&this.input.current.inputElement===document.activeElement&&""!==this.input.current.value},_k.prototype._getTextFromItem=function(e,t){return this.props.getTextFromItem?this.props.getTextFromItem(e,t):""},_k),uk=(l(Ck,$x=ck),Ck.prototype.render=function(){var e=this.state,t=e.suggestedDisplayValue,o=e.isFocused,n=this.props,r=n.className,i=n.inputProps,s=n.disabled,a=n.selectionAriaLabel,l=n.selectionRole,c=void 0===l?"list":l,e=n.theme,l=n.styles,n=this.state.suggestionsVisible?this._ariaMap.suggestionList:"",o=l?lk(l,{theme:e,className:r,isFocused:o,inputClassName:i&&i.className}):{root:Tr("ms-BasePicker",r\|\|""),text:Tr("ms-BasePicker-text",ak.pickerText,this.state.isFocused&&ak.inputFocused,s&&ak.inputDisabled),itemsWrapper:ak.pickerItems,input:Tr("ms-BasePicker-input",ak.pickerInput,i&&i.className),screenReaderText:ak.screenReaderOnly},r=this.props["aria-label"]\|\|(null==i?void 0:i["aria-label"]);return gt.createElement("div",{ref:this.root,onBlur:this.onBlur,onFocus:this.onFocus},gt.createElement("div",{className:o.root,onKeyDown:this.onKeyDown},this.renderCustomAlert(o.screenReaderText),gt.createElement("div",{className:o.text,"aria-owns":n\|\|void 0},gt.createElement(ki,ht({},i,{className:o.input,componentRef:this.input,onFocus:this.onInputFocus,onBlur:this.onInputBlur,onClick:this.onClick,onInputValueChange:this.onInputChange,suggestedDisplayValue:t,"aria-activedescendant":this.getActiveDescendant(),"aria-controls":n\|\|void 0,"aria-expanded":!!this.state.suggestionsVisible,"aria-haspopup":"listbox","aria-label":r,role:"combobox",id:null!=i&&i.id?i.id:this._ariaMap.combobox,disabled:s,onInputChange:this.props.onInputChange})))),this.renderSuggestions(),gt.createElement(Pv,{selection:this.selection,selectionMode:dv.single},gt.createElement("div",{id:this._ariaMap.selectedItems,className:"ms-BasePicker-selectedItems",role:c,"aria-label":a\|\|r},this.renderItems())))},Ck.prototype.onBackspace=function(e){},Ck),dk={root:"ms-PickerPersona-container",itemContent:"ms-PickerItem-content",removeButton:"ms-PickerItem-removeButton",isSelected:"is-selected",isInvalid:"is-invalid"},pk=Fn(),hk=function(e){var t=e.item,o=e.onRemoveItem,n=e.index,r=e.selected,i=e.removeButtonAriaLabel,s=e.styles,a=e.theme,l=e.className,c=e.disabled,u=e.removeButtonIconProps,e=_s(),a=pk(s,{theme:a,className:l,selected:r,disabled:c,invalid:t.ValidationState===Wx.warning}),l=a.subComponentStyles?a.subComponentStyles.persona:void 0,r=a.subComponentStyles?a.subComponentStyles.personaCoin:void 0;return gt.createElement("div",{className:a.root,role:"listitem"},gt.createElement("div",{className:a.itemContent,id:"selectedItemPersona-"+e},gt.createElement(XC,ht({size:Pr.size24,styles:l,coinProps:{styles:r}},t))),gt.createElement(rd,{id:e,onClick:o,disabled:c,iconProps:null!=u?u:{iconName:"Cancel"},styles:{icon:{fontSize:"12px"}},className:a.removeButton,ariaLabel:i,"aria-labelledby":e+" selectedItemPersona-"+e,"data-selection-index":n}))},mk=In(hk,function(e){var t,o=e.className,n=e.theme,r=e.selected,i=e.invalid,s=e.disabled,a=n.palette,l=n.semanticColors,c=n.fonts,e=zo(dk,n),u=[r&&!i&&!s&&{color:a.white,selectors:((t={":hover":{color:a.white}})[Yt]={color:"HighlightText"},t)},(i&&!r\|\|i&&r&&s)&&{color:a.redDark,borderBottom:"2px dotted "+a.redDark,selectors:((t={})["."+e.root+":hover &"]={color:a.redDark},t)},i&&r&&!s&&{color:a.white,borderBottom:"2px dotted "+a.white},s&&{selectors:((u={})[Yt]={color:"GrayText"},u)}],c=[i&&{fontSize:c.xLarge.fontSize}];return{root:[e.root,bo(n,{inset:-2}),{borderRadius:15,display:"inline-flex",alignItems:"center",background:a.neutralLighter,margin:"1px 2px",cursor:"default",userSelect:"none",maxWidth:300,verticalAlign:"middle",minWidth:0,selectors:((n={":hover":{background:r\|\|s?"":a.neutralLight}})[Yt]=[{border:"1px solid WindowText"},s&&{borderColor:"GrayText"}],n)},r&&!s&&[e.isSelected,{background:a.themePrimary,selectors:((n={})[Yt]=ht({borderColor:"HighLight",background:"Highlight"},{forcedColorAdjust:"none",MsHighContrastAdjust:"none"}),n)}],i&&[e.isInvalid],i&&r&&!s&&{background:a.redDark},o],itemContent:[e.itemContent,{flex:"0 1 auto",minWidth:0,maxWidth:"100%",overflow:"hidden"}],removeButton:[e.removeButton,{borderRadius:15,color:a.neutralPrimary,flex:"0 0 auto",width:24,height:24,selectors:{":hover":{background:a.neutralTertiaryAlt,color:a.neutralDark}}},r&&[{color:a.white,selectors:((r={":hover":{color:a.white,background:a.themeDark},":active":{color:a.white,background:a.themeDarker}})[Yt]={color:"HighlightText"},r)},i&&{selectors:{":hover":{background:a.red},":active":{background:a.redDark}}}],s&&{selectors:((s={})["."+Vu.msButtonIcon]={color:l.buttonText},s)}],subComponentStyles:{persona:{primaryText:u},personaCoin:{initials:c}}}},void 0,{scope:"PeoplePickerItem"}),gk={root:"ms-PeoplePicker-personaContent",personaWrapper:"ms-PeoplePicker-Persona"},fk=Fn(),vk=function(e){var t=e.personaProps,o=e.suggestionsProps,n=e.compact,r=e.styles,i=e.theme,e=e.className,o=fk(r,{theme:i,className:o&&o.suggestionsItemClassName\|\|e}),e=o.subComponentStyles&&o.subComponentStyles.persona?o.subComponentStyles.persona:void 0;return gt.createElement("div",{className:o.root},gt.createElement(XC,ht({size:Pr.size24,styles:e,className:o.personaWrapper,showSecondaryText:!n,showOverflowTooltip:!1},t)))},bk=In(vk,function(e){var t=e.className,o=e.theme,n=zo(gk,o),e={selectors:((e={})["."+Kx.isSuggested+" &"]={selectors:((o={})[Yt]={color:"HighlightText"},o)},e["."+n.root+":hover &"]={selectors:((o={})[Yt]={color:"HighlightText"},o)},e)};return{root:[n.root,{width:"100%",padding:"4px 12px"},t],personaWrapper:[n.personaWrapper,{width:180}],subComponentStyles:{persona:{primaryText:e,secondaryText:e}}}},void 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t;n.state.isFocused&&(t=e.relatedTarget,(t=null===e.relatedTarget?document.activeElement:t)&&!$i(n.root.current,t)&&(n.setState({isFocused:!1}),n.props.onBlur&&n.props.onBlur(e)))},n.onClick=function(e){void 0!==n.props.inputProps&&void 0!==n.props.inputProps.onClick&&n.props.inputProps.onClick(e),0===e.button&&n._userTriggeredSuggestions()},n.onFocus=function(){n.state.isFocused\|\|n.setState({isFocused:!0})},n.onKeyDown=function(e){var t=e.which;switch(t){case En.escape:n.state.suggestionsVisible&&(n.setState({suggestionsVisible:!1}),e.preventDefault(),e.stopPropagation());break;case En.tab:case En.enter:n.suggestionElement.current&&n.suggestionElement.current.hasSuggestedActionSelected()?n.suggestionElement.current.executeSelectedAction():!e.shiftKey&&n.suggestionStore.hasSelectedSuggestion()&&n.state.suggestionsVisible?(n.completeSuggestion(),e.preventDefault(),e.stopPropagation()):n._completeGenericSuggestion();break;case En.backspace:n.props.disabled\|\|n.onBackspace(e),e.stopPropagation();break;case En.del:n.props.disabled\|\|(n.input.current&&e.target===n.input.current.inputElement&&n.state.suggestionsVisible&&-1!==n.suggestionStore.currentIndex?(n.props.onRemoveSuggestion&&n.props.onRemoveSuggestion(n.suggestionStore.currentSuggestion.item),n.suggestionStore.removeSuggestion(n.suggestionStore.currentIndex),n.forceUpdate()):n.onBackspace(e)),e.stopPropagation();break;case 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e,t;n.props.onGetMoreResults&&n.input.current?(t=e=n.props.onGetMoreResults(n.input.current.value,n.state.items),Array.isArray(e)?(n.updateSuggestions(e),n.setState({isSearching:!1})):t.then&&t.then(function(e){n.updateSuggestions(e),n.setState({isSearching:!1})})):n.setState({isSearching:!1}),n.input.current&&n.input.current.focus(),n.setState({moreSuggestionsAvailable:!1,isResultsFooterVisible:!0})})},n.completeSelection=function(e){n.addItem(e),n.updateValue(""),n.input.current&&n.input.current.clear(),n.setState({suggestionsVisible:!1})},n.addItemByIndex=function(e){n.completeSelection(n.suggestionStore.getSuggestionAtIndex(e).item)},n.addItem=function(e){var t=n.props.onItemSelected?n.props.onItemSelected(e):e;null!==t&&((e=t)&&t.then?t.then(function(e){e=n.state.items.concat([e]);n._updateSelectedItems(e)}):(e=n.state.items.concat([e]),n._updateSelectedItems(e)),n.setState({suggestedDisplayValue:"",selectionRemoved:void 0}))},n.removeItem=function(e){var t=n.state.items,o=t.indexOf(e);0<=o&&(o=t.slice(0,o).concat(t.slice(o+1)),n.setState({selectionRemoved:e}),n._updateSelectedItems(o))},n.removeItems=function(t){var e=n.state.items.filter(function(e){return-1===t.indexOf(e)});n._updateSelectedItems(e)},n._shouldFocusZoneEnterInnerZone=function(e){if(n.state.suggestionsVisible)switch(e.which){case En.up:case En.down:return!0}return e.which===En.enter},n._onResolveSuggestions=function(e){var t=n.props.onResolveSuggestions(e,n.state.items);null!==t&&n.updateSuggestionsList(t,e)},n._completeGenericSuggestion=function(){var e;n.props.onValidateInput&&n.input.current&&n.props.onValidateInput(n.input.current.value)!==Wx.invalid&&n.props.createGenericItem&&(e=n.props.createGenericItem(n.input.current.value,n.props.onValidateInput(n.input.current.value)),n.suggestionStore.createGenericSuggestion(e),n.completeSuggestion())},n._userTriggeredSuggestions=function(){var e;n.state.suggestionsVisible\|\|((e=n.input.current?n.input.current.value:"")?0===n.suggestionStore.suggestions.length?n._onResolveSuggestions(e):n.setState({isMostRecentlyUsedVisible:!1,suggestionsVisible:!0}):n.onEmptyInputFocus())},fi(n),n._async=new Si(n);e=e.selectedItems\|\|e.defaultSelectedItems\|\|[];return n._id=_s(),n._ariaMap={selectedItems:"selected-items-"+n._id,selectedSuggestionAlert:"selected-suggestion-alert-"+n._id,suggestionList:"suggestion-list-"+n._id,combobox:"combobox-"+n._id},n.suggestionStore=new Yx,n.selection=new fv({onSelectionChanged:function(){return n.onSelectionChange()}}),n.selection.setItems(e),n.state={items:e,suggestedDisplayValue:"",isMostRecentlyUsedVisible:!1,moreSuggestionsAvailable:!1,isFocused:!1,isSearching:!1,selectedIndices:[],selectionRemoved:void 0},n}function Sk(e){var t=e.className,o=e.theme,n=e.isFocused,r=e.inputClassName,i=e.disabled;if(!o)throw new Error("theme is undefined or null in base BasePicker getStyles function.");var s=o.semanticColors,a=o.effects,l=o.fonts,c=s.inputBorder,u=s.inputBorderHovered,d=s.inputFocusBorderAlt,p=zo(yk,o),e=[l.medium,{color:s.inputPlaceholderText,opacity:1,selectors:((h={})[Yt]={color:"GrayText"},h)}],h={color:s.disabledText,selectors:((o={})[Yt]={color:"GrayText"},o)},o="rgba(218, 218, 218, 0.29)";return{root:[p.root,t],text:[p.text,{display:"flex",position:"relative",flexWrap:"wrap",alignItems:"center",boxSizing:"border-box",minWidth:180,minHeight:30,border:"1px solid "+c,borderRadius:a.roundedCorner2},!n&&!i&&{selectors:{":hover":{borderColor:u}}},n&&!i&&_o(d,a.roundedCorner2),i&&{borderColor:o,selectors:((o={":after":{content:'""',position:"absolute",top:0,right:0,bottom:0,left:0,background:o}})[Yt]={borderColor:"GrayText",selectors:{":after":{background:"none"}}},o)}],itemsWrapper:[p.itemsWrapper,{display:"flex",flexWrap:"wrap",maxWidth:"100%"}],input:[p.input,l.medium,{height:30,border:"none",flexGrow:1,outline:"none",padding:"0 6px 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null!==xk&&xk.apply(this,arguments)\|\|this}function Bk(){return null!==kk&&kk.apply(this,arguments)\|\|this}function Fk(){return null!==wk&&wk.apply(this,arguments)\|\|this}function Ak(){return null!==Ik&&Ik.apply(this,arguments)\|\|this}function Lk(){return null!==Dk&&Dk.apply(this,arguments)\|\|this}function Hk(e,t){var o={key:e,primaryText:e,imageInitials:"!",ValidationState:t};return t!==Wx.warning&&(o.imageInitials=Cr(e,Pn())),o}var Ok,zk=In(Pk,Sk,void 0,{scope:"NormalPeoplePicker"}),Wk=In(Rk,Sk,void 0,{scope:"CompactPeoplePicker"}),Vk=In(Mk,Sk,void 0,{scope:"ListPeoplePickerBase"}),Kk={root:"ms-TagItem",text:"ms-TagItem-text",close:"ms-TagItem-close",isSelected:"is-selected"},Gk=Fn(),Uk=function(e){var t=e.theme,o=e.styles,n=e.selected,r=e.disabled,i=e.enableTagFocusInDisabledPicker,s=e.children,a=e.className,l=e.index,c=e.onRemoveItem,u=e.removeButtonAriaLabel,d=e.title,d=void 0===d?"string"==typeof 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t=e.className,o=e.theme,n=e.selected,r=e.disabled,i=o.palette,s=o.effects,a=o.fonts,l=o.semanticColors,e=zo(Kk,o);return{root:[e.root,a.medium,bo(o),{boxSizing:"content-box",flexShrink:"1",margin:2,height:26,lineHeight:26,cursor:"default",userSelect:"none",display:"flex",flexWrap:"nowrap",maxWidth:300,minWidth:0,borderRadius:s.roundedCorner2,color:l.inputText,background:i.neutralLighter,selectors:((l={":hover":[!r&&!n&&{color:i.neutralDark,background:i.neutralLight,selectors:{".ms-TagItem-close":{color:i.neutralPrimary}}},r&&{background:i.neutralLighter}],":focus-within":[!r&&{background:i.themePrimary,color:i.white}]})[Yt]={border:"1px solid "+(n?"WindowFrame":"WindowText")},l)},r&&{selectors:((l={})[Yt]={borderColor:"GrayText"},l)},n&&!r&&[e.isSelected],t],text:[e.text,{overflow:"hidden",textOverflow:"ellipsis",whiteSpace:"nowrap",minWidth:30,margin:"0 8px"},r&&{selectors:((t={})[Yt]={color:"GrayText"},t)}],close:[e.close,{color:i.neutralSecondary,width:30,height:"100%",flex:"0 0 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n=this,e=this.props.initialScrollPosition;this._events.on(this.contentContainer,"scroll",this._onScroll),this._events.on(window,"resize",this._onWindowResize),this.contentContainer&&e&&(this.contentContainer.scrollTop=e),this.setStickiesDistanceFromTop(),this._stickies.forEach(function(e){n.sortSticky(e)}),this.notifySubscribers(),"MutationObserver"in window&&(this._mutationObserver=new MutationObserver(function(t){var o,e=n._getScrollbarHeight();e!==n.state.scrollbarHeight&&n.setState({scrollbarHeight:e}),n.notifySubscribers(),t.some(function(e){return 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this.props.children!==e.children\|\|this.props.initialScrollPosition!==e.initialScrollPosition\|\|this.props.className!==e.className\|\|this.state.stickyTopHeight!==t.stickyTopHeight\|\|this.state.stickyBottomHeight!==t.stickyBottomHeight\|\|this.state.scrollbarWidth!==t.scrollbarWidth\|\|this.state.scrollbarHeight!==t.scrollbarHeight},Vw.prototype.componentDidUpdate=function(e,t){var o=this.props.initialScrollPosition;this.contentContainer&&"number"==typeof o&&e.initialScrollPosition!==o&&(this.contentContainer.scrollTop=o),t.stickyTopHeight===this.state.stickyTopHeight&&t.stickyBottomHeight===this.state.stickyBottomHeight\|\|this.notifySubscribers(),this._async.setTimeout(this._onWindowResize,0)},Vw.prototype.render=function(){var e=this.props,t=e.className,o=e.scrollContainerFocus,n=e.scrollContainerAriaLabel,r=e.theme,i=e.styles,s=this.state,e=s.stickyTopHeight,s=s.stickyBottomHeight,t=Nw(i,{theme:r,className:t,scrollbarVisibility:this.props.scrollbarVisibility}),n=o?{role:"group",tabIndex:0,"aria-label":n}:{};return gt.createElement("div",ht({},ur(this.props,cr),{ref:this._root,className:t.root}),gt.createElement("div",{ref:this._stickyAboveRef,className:t.stickyAbove,style:this._getStickyContainerStyle(e,!0)}),gt.createElement("div",ht({ref:this._contentContainer},n,{className:t.contentContainer,"data-is-scrollable":!0}),gt.createElement(Mw.Provider,{value:this._getScrollablePaneContext()},this.props.children)),gt.createElement("div",{className:t.stickyBelow,style:this._getStickyContainerStyle(s,!1)},gt.createElement("div",{ref:this._stickyBelowRef,className:t.stickyBelowItems})))},Vw.prototype.setStickiesDistanceFromTop=function(){var t=this;this.contentContainer&&this._stickies.forEach(function(e){e.setDistanceFromTop(t.contentContainer)})},Vw.prototype.forceLayoutUpdate=function(){this._onWindowResize()},Vw.prototype._checkStickyStatus=function(e){this.stickyAbove&&this.stickyBelow&&this.contentContainer&&e.nonStickyContent&&(e.state.isStickyTop\|\|e.state.isStickyBottom?(e.state.isStickyTop&&!this.stickyAbove.contains(e.nonStickyContent)&&e.stickyContentTop&&e.addSticky(e.stickyContentTop),e.state.isStickyBottom&&!this.stickyBelow.contains(e.nonStickyContent)&&e.stickyContentBottom&&e.addSticky(e.stickyContentBottom)):this.contentContainer.contains(e.nonStickyContent)\|\|e.resetSticky())},Vw.prototype._getScrollbarWidth=function(){var e=this.contentContainer;return e?e.offsetWidth-e.clientWidth:0},Vw.prototype._getScrollbarHeight=function(){var e=this.contentContainer;return e?e.offsetHeight-e.clientHeight:0},Vw),Fw=In(Bw,function(e){var t=e.className,o=e.theme,n=zo(Pw,o),r={position:"absolute",pointerEvents:"none"},i={position:"absolute",top:0,right:0,bottom:0,left:0,WebkitOverflowScrolling:"touch"};return{root:[n.root,o.fonts.medium,i,t],contentContainer:[n.contentContainer,{overflowY:"always"===e.scrollbarVisibility?"scroll":"auto"},i],stickyAbove:[{top:0,zIndex:1,selectors:((i={})[Yt]={borderBottom:"1px solid WindowText"},i)},r],stickyBelow:[{bottom:0,selectors:((i={})[Yt]={borderTop:"1px solid WindowText"},i)},r],stickyBelowItems:[{bottom:0},r,{width:"100%"}]}},void 0,{scope:"ScrollablePane"}),Aw="SearchBox",Lw={root:{height:"auto"},icon:{fontSize:"12px"}},Hw={iconName:"Clear"},Ow={ariaLabel:"Clear text"},zw=Fn(),Ww=gt.forwardRef(function(o,e){var t,n,r=o.ariaLabel,i=o.className,s=o.defaultValue,a=void 0===s?"":s,l=o.disabled,c=o.underlined,u=o.styles,d=o.labelText,p=o.placeholder,h=void 0===p?d:p,m=o.theme,g=o.clearButtonProps,f=void 0===g?Ow:g,v=o.disableAnimation,b=void 0!==v&&v,s=o.showIcon,d=void 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d=o.componentRef,t=P,n=s,gt.useImperativeHandle(d,function(){return{focus:function(){var e;return null===(e=t.current)\|\|void 0===e?void 0:e.focus()},hasFocus:function(){return n}}},[t,n]),gt.createElement("div",{role:g,ref:a,className:u.root,onFocusCapture:function(e){var t;I(!0),null===(t=o.onFocus)\|\|void 0===t\|\|t.call(o,e)}},gt.createElement("div",{className:u.iconContainer,onClick:function(){P.current&&(P.current.focus(),P.current.selectionStart=P.current.selectionEnd=0)},"aria-hidden":!0},gt.createElement(Wr,ht({iconName:"Search"},p,{className:u.icon}))),gt.createElement("input",ht({},m,{id:e,className:u.field,placeholder:h,onChange:b,onInput:b,onBlur:c,onKeyDown:function(e){switch(e.which){case En.escape:null==_\|\|_(e),T&&!e.defaultPrevented&&M(e);break;case En.enter:S&&(S(T),e.preventDefault(),e.stopPropagation());break;default:null==x\|\|x(e),e.defaultPrevented&&e.stopPropagation()}},value:T,disabled:l,role:"searchbox","aria-label":r,ref:P})),0<T.length&&gt.createElement("div",{className:u.clearButton},gt.createElement(rd,ht({onBlur:c,styles:Lw,iconProps:Hw},f,{onClick:i}))))});function Vw(e){var u=Ew.call(this,e)\|\|this;return u._root=gt.createRef(),u._stickyAboveRef=gt.createRef(),u._stickyBelowRef=gt.createRef(),u._contentContainer=gt.createRef(),u.subscribe=function(e){u._subscribers.add(e)},u.unsubscribe=function(e){u._subscribers.delete(e)},u.addSticky=function(e){u._stickies.add(e),u.contentContainer&&(e.setDistanceFromTop(u.contentContainer),u.sortSticky(e))},u.removeSticky=function(e){u._stickies.delete(e),u._removeStickyFromContainers(e),u.notifySubscribers()},u.sortSticky=function(e,t){u.stickyAbove&&u.stickyBelow&&(t&&u._removeStickyFromContainers(e),e.canStickyTop&&e.stickyContentTop&&u._addToStickyContainer(e,u.stickyAbove,e.stickyContentTop),e.canStickyBottom&&e.stickyContentBottom&&u._addToStickyContainer(e,u.stickyBelow,e.stickyContentBottom))},u.updateStickyRefHeights=function(){var e=u._stickies,n=0,r=0;e.forEach(function(e){var t=e.state,o=t.isStickyTop,t=t.isStickyBottom;e.nonStickyContent&&(o&&(n+=e.nonStickyContent.offsetHeight),t&&(r+=e.nonStickyContent.offsetHeight),u._checkStickyStatus(e))}),u.setState({stickyTopHeight:n,stickyBottomHeight:r})},u.notifySubscribers=function(){u.contentContainer&&u._subscribers.forEach(function(e){e(u.contentContainer,u.stickyBelow)})},u.getScrollPosition=function(){return u.contentContainer?u.contentContainer.scrollTop:0},u.syncScrollSticky=function(e){e&&u.contentContainer&&e.syncScroll(u.contentContainer)},u._getScrollablePaneContext=function(){return{scrollablePane:{subscribe:u.subscribe,unsubscribe:u.unsubscribe,addSticky:u.addSticky,removeSticky:u.removeSticky,updateStickyRefHeights:u.updateStickyRefHeights,sortSticky:u.sortSticky,notifySubscribers:u.notifySubscribers,syncScrollSticky:u.syncScrollSticky}}},u._addToStickyContainer=function(t,o,e){if(o.children.length){if(!o.contains(e)){var n=[].slice.call(o.children),r=[];u._stickies.forEach(function(e){(o===u.stickyAbove&&t.canStickyTop\|\|t.canStickyBottom)&&r.push(e)});for(var i=void 0,s=0,a=r.sort(function(e,t){return(e.state.distanceFromTop\|\|0)-(t.state.distanceFromTop\|\|0)}).filter(function(e){e=o===u.stickyAbove?e.stickyContentTop:e.stickyContentBottom;return!!e&&-1<n.indexOf(e)});s<a.length;s++){var l=a[s];if((l.state.distanceFromTop\|\|0)>=(t.state.distanceFromTop\|\|0)){i=l;break}}var c=null;i&&(c=o===u.stickyAbove?i.stickyContentTop:i.stickyContentBottom),o.insertBefore(e,c)}}else o.appendChild(e)},u._removeStickyFromContainers=function(e){u.stickyAbove&&e.stickyContentTop&&u.stickyAbove.contains(e.stickyContentTop)&&u.stickyAbove.removeChild(e.stickyContentTop),u.stickyBelow&&e.stickyContentBottom&&u.stickyBelow.contains(e.stickyContentBottom)&&u.stickyBelow.removeChild(e.stickyContentBottom)},u._onWindowResize=function(){var e=u._getScrollbarWidth(),t=u._getScrollbarHeight();u.setState({scrollbarWidth:e,scrollbarHeight:t}),u.notifySubscribers()},u._getStickyContainerStyle=function(e,t){return ht(ht({height:e},Pn(u.props.theme)?{right:"0",left:(u.state.scrollbarWidth\|\|u._getScrollbarWidth()\|\|0)+"px"}:{left:"0",right:(u.state.scrollbarWidth\|\|u._getScrollbarWidth()\|\|0)+"px"}),t?{top:"0"}:{bottom:(u.state.scrollbarHeight\|\|u._getScrollbarHeight()\|\|0)+"px"})},u._onScroll=function(){var t=u.contentContainer;t&&u._stickies.forEach(function(e){e.syncScroll(t)}),u._notifyThrottled()},u._subscribers=new Set,u._stickies=new Set,fi(u),u._async=new Si(u),u._events=new va(u),u.state={stickyTopHeight:0,stickyBottomHeight:0,scrollbarWidth:0,scrollbarHeight:0},u._notifyThrottled=u._async.throttle(u.notifySubscribers,50),u}Ww.displayName=Aw;var Kw,Gw={root:"ms-SearchBox",iconContainer:"ms-SearchBox-iconContainer",icon:"ms-SearchBox-icon",clearButton:"ms-SearchBox-clearButton",field:"ms-SearchBox-field"},Uw=In(Ww,function(e){var t=e.theme,o=e.underlined,n=e.disabled,r=e.hasFocus,i=e.className,s=e.hasInput,a=e.disableAnimation,l=e.showIcon,c=t.palette,u=t.fonts,d=t.semanticColors,p=t.effects,h=zo(Gw,t),m={color:d.inputPlaceholderText,opacity:1},g=c.neutralSecondary,f=c.neutralPrimary,v=c.neutralLighter,b=c.neutralLighter,e=c.neutralLighter;return{root:[h.root,u.medium,Uo,{color:d.inputText,backgroundColor:d.inputBackground,display:"flex",flexDirection:"row",flexWrap:"nowrap",alignItems:"stretch",padding:"1px 0 1px 4px",borderRadius:p.roundedCorner2,border:"1px solid "+d.inputBorder,height:32,selectors:((c={})[Yt]={borderColor:"WindowText"},c[":hover"]={borderColor:d.inputBorderHovered,selectors:((u={})[Yt]={borderColor:"Highlight"},u)},c[":hover ."+h.iconContainer]={color:d.inputIconHovered},c)},!r&&s&&{selectors:((c={})[":hover ."+h.iconContainer]={width:4},c[":hover ."+h.icon]={opacity:0,pointerEvents:"none"},c)},r&&["is-active",{position:"relative"},_o(d.inputFocusBorderAlt,o?0:p.roundedCorner2,o?"borderBottom":"border")],l&&[{selectors:((p={})[":hover ."+h.iconContainer]={width:32},p[":hover ."+h.icon]={opacity:1},p)}],n&&["is-disabled",{borderColor:v,backgroundColor:e,pointerEvents:"none",cursor:"default",selectors:((e={})[Yt]={borderColor:"GrayText"},e)}],o&&["is-underlined",{borderWidth:"0 0 1px 0",borderRadius:0,padding:"1px 0 1px 8px"}],o&&n&&{backgroundColor:"transparent"},s&&"can-clear",i],iconContainer:[h.iconContainer,{display:"flex",flexDirection:"column",justifyContent:"center",flexShrink:0,fontSize:16,width:32,textAlign:"center",color:d.inputIcon,cursor:"text"},r&&{width:4},n&&{color:d.inputIconDisabled},!a&&{transition:"width "+we.durationValue1},l&&r&&{width:32}],icon:[h.icon,{opacity:1},r&&{opacity:0,pointerEvents:"none"},!a&&{transition:"opacity "+we.durationValue1+" 0s"},l&&r&&{opacity:1}],clearButton:[h.clearButton,{display:"flex",flexDirection:"row",alignItems:"stretch",cursor:"pointer",flexBasis:"32px",flexShrink:0,padding:0,margin:"-1px 0px",selectors:{"&:hover .ms-Button":{backgroundColor:b},"&:hover .ms-Button-icon":{color:f},".ms-Button":{borderRadius:Pn(t)?"1px 0 0 1px":"0 1px 1px 0"},".ms-Button-icon":{color:g}}}],field:[h.field,Uo,Zo(m),{backgroundColor:"transparent",border:"none",outline:"none",fontWeight:"inherit",fontFamily:"inherit",fontSize:"inherit",color:d.inputText,flex:"1 1 0px",minWidth:"0px",overflow:"hidden",textOverflow:"ellipsis",paddingBottom:.5,selectors:{"::-ms-clear":{display:"none"}}},n&&{color:d.disabledText}]}},void 0,{scope:"SearchBox"}),jw=(l(qw,Kw=gt.Component),qw.getDerivedStateFromProps=function(e){return e.selectedItems?{items:e.selectedItems}:null},Object.defineProperty(qw.prototype,"items",{get:function(){return this.state.items},enumerable:!1,configurable:!0}),qw.prototype.removeSelectedItems=function(){this.state.items.length&&0<this.selection.getSelectedCount()&&this.removeItems(this.selection.getSelection())},qw.prototype.updateItems=function(e,t){var o=this;this.props.selectedItems?this.onChange(e):this.setState({items:e},function(){o._onSelectedItemsUpdated(e,t)})},qw.prototype.hasSelectedItems=function(){return 0<this.selection.getSelectedCount()},qw.prototype.componentDidUpdate=function(e,t){this.state.items&&this.state.items!==t.items&&this.selection.setItems(this.state.items)},qw.prototype.unselectAll=function(){this.selection.setAllSelected(!1)},qw.prototype.highlightedItems=function(){return this.selection.getSelection()},qw.prototype.componentDidMount=function(){this.selection.setItems(this.state.items)},Object.defineProperty(qw.prototype,"selection",{get:function(){var e;return null!==(e=this.props.selection)&&void 0!==e?e:this._defaultSelection},enumerable:!1,configurable:!0}),qw.prototype.render=function(){return this.renderItems()},qw.prototype.onChange=function(e){this.props.onChange&&this.props.onChange(e)},qw.prototype.copyItems=function(e){if(this.props.onCopyItems){var t=this.props.onCopyItems(e),o=document.createElement("input");document.body.appendChild(o);try{if(o.value=t,o.select(),!document.execCommand("copy"))throw new Error}catch(e){}finally{document.body.removeChild(o)}}},qw.prototype._onSelectedItemsUpdated=function(e,t){this.onChange(e)},qw.prototype._canRemoveItem=function(e){return!this.props.canRemoveItem\|\|this.props.canRemoveItem(e)},qw);function qw(e){var r=Kw.call(this,e)\|\|this;r.addItems=function(e){var t=r.props.onItemSelected?r.props.onItemSelected(e):e,e=t,t=t;t&&t.then?t.then(function(e){e=r.state.items.concat(e);r.updateItems(e)}):(e=r.state.items.concat(e),r.updateItems(e))},r.removeItemAt=function(e){var t=r.state.items;r._canRemoveItem(t[e])&&-1<e&&(r.props.onItemsDeleted&&r.props.onItemsDeleted([t[e]]),e=t.slice(0,e).concat(t.slice(e+1)),r.updateItems(e))},r.removeItem=function(e){e=r.state.items.indexOf(e);r.removeItemAt(e)},r.replaceItem=function(e,t){var o=r.state.items,e=o.indexOf(e);-1<e&&(e=o.slice(0,e).concat(t).concat(o.slice(e+1)),r.updateItems(e))},r.removeItems=function(e){var t=r.state.items,o=e.filter(function(e){return r._canRemoveItem(e)}),n=t.filter(function(e){return-1===o.indexOf(e)}),e=o[0],e=t.indexOf(e);r.props.onItemsDeleted&&r.props.onItemsDeleted(o),r.updateItems(n,e)},r.onCopy=function(e){var t;r.props.onCopyItems&&0<r.selection.getSelectedCount()&&(t=r.selection.getSelection(),r.copyItems(t))},r.renderItems=function(){var o=r.props.removeButtonAriaLabel,n=r.props.onRenderItem;return r.state.items.map(function(e,t){return n({item:e,index:t,key:e.key\|\|t,selected:r.selection.isIndexSelected(t),onRemoveItem:function(){return r.removeItem(e)},onItemChange:r.onItemChange,removeButtonAriaLabel:o,onCopyItem:function(e){return r.copyItems([e])}})})},r.onSelectionChanged=function(){r.forceUpdate()},r.onItemChange=function(e,t){var o=r.state.items;0<=t&&((o=o)[t]=e,r.updateItems(o))},fi(r);e=e.selectedItems\|\|e.defaultSelectedItems\|\|[];return r.state={items:e},r._defaultSelection=new fv({onSelectionChanged:r.onSelectionChanged}),r}Dt([{rawString:".personaContainer_cbad3345{border-radius:15px;display:-webkit-inline-box;display:-ms-inline-flexbox;display:inline-flex;-webkit-box-align:center;-ms-flex-align:center;align-items:center;background:"},{theme:"themeLighterAlt",defaultValue:"#eff6fc"},{rawString:";margin:4px;cursor:default;-webkit-user-select:none;-moz-user-select:none;-ms-user-select:none;user-select:none;vertical-align:middle;position:relative}.personaContainer_cbad3345::-moz-focus-inner{border:0}.personaContainer_cbad3345{outline:transparent}.personaContainer_cbad3345{position:relative}.ms-Fabric--isFocusVisible .personaContainer_cbad3345:focus:after{-webkit-box-sizing:border-box;box-sizing:border-box;content:'';position:absolute;top:-2px;right:-2px;bottom:-2px;left:-2px;pointer-events:none;border:1px solid "},{theme:"focusBorder",defaultValue:"#605e5c"},{rawString:";border-radius:0}.personaContainer_cbad3345 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.itemContent_cbad3345{-webkit-box-flex:0;-ms-flex:0 1 auto;flex:0 1 auto;min-width:0;max-width:100%}.personaContainer_cbad3345 .removeButton_cbad3345{border-radius:15px;-webkit-box-flex:0;-ms-flex:0 0 auto;flex:0 0 auto;width:33px;height:33px;-ms-flex-preferred-size:32px;flex-basis:32px}.personaContainer_cbad3345 .expandButton_cbad3345{border-radius:15px 0 0 15px;height:33px;width:44px;padding-right:16px;position:inherit;display:-webkit-box;display:-ms-flexbox;display:flex;margin-right:-17px}.personaContainer_cbad3345 .personaWrapper_cbad3345{position:relative;display:inherit}.personaContainer_cbad3345 .personaWrapper_cbad3345 .ms-Persona-details{padding:0 8px}.personaContainer_cbad3345 .personaDetails_cbad3345{-webkit-box-flex:0;-ms-flex:0 1 auto;flex:0 1 auto}.itemContainer_cbad3345{display:inline-block;vertical-align:top}"}]);function Yw(e){var t=Wt();if(!t)throw new Error("theme is undefined or null in Editing item getStyles function.");var o=t.semanticColors;return{root:[(t=zo(m1,t)).root,{margin:"4px"}],input:[t.input,{border:"0px",outline:"none",width:"100%",backgroundColor:o.inputBackground,color:o.inputText,selectors:{"::-ms-clear":{display:"none"}}}]}}var Zw,Xw,Qw,Jw,$w,e1="personaContainer_cbad3345",t1="hover_cbad3345",o1="actionButton_cbad3345",n1="personaContainerIsSelected_cbad3345",r1="validationError_cbad3345",i1="itemContent_cbad3345",s1="removeButton_cbad3345",a1="expandButton_cbad3345",l1="personaWrapper_cbad3345",c1="personaDetails_cbad3345",u1="itemContainer_cbad3345",d1=s,p1=(l(w1,$w=gt.Component),w1.prototype.render=function(){var e=this.props,t=e.item,o=e.onExpandItem,n=e.onRemoveItem,r=e.removeButtonAriaLabel,i=e.index,s=e.selected,a=_s();return gt.createElement("div",{ref:this.persona,className:Tr("ms-PickerPersona-container",d1.personaContainer,((e={})["is-selected "+d1.personaContainerIsSelected]=s,e),((e={})["is-invalid "+d1.validationError]=!t.isValid,e)),"data-is-focusable":!0,"data-is-sub-focuszone":!0,"data-selection-index":i,role:"listitem","aria-labelledby":"selectedItemPersona-"+a},gt.createElement("div",{hidden:!t.canExpand\|\|void 0===o},gt.createElement(rd,{onClick:this._onClickIconButton(o),iconProps:{iconName:"Add",style:{fontSize:"14px"}},className:Tr("ms-PickerItem-removeButton",d1.expandButton,d1.actionButton),ariaLabel:r})),gt.createElement("div",{className:Tr(d1.personaWrapper)},gt.createElement("div",{className:Tr("ms-PickerItem-content",d1.itemContent),id:"selectedItemPersona-"+a},gt.createElement(XC,ht({},t,{onRenderCoin:this.props.renderPersonaCoin,onRenderPrimaryText:this.props.renderPrimaryText,size:Pr.size32}))),gt.createElement(rd,{onClick:this._onClickIconButton(n),iconProps:{iconName:"Cancel",style:{fontSize:"14px"}},className:Tr("ms-PickerItem-removeButton",d1.removeButton,d1.actionButton),ariaLabel:r})))},w1.prototype._onClickIconButton=function(t){return function(e){e.stopPropagation(),e.preventDefault(),t&&t()}},w1),h1=(l(k1,Jw=gt.Component),k1.prototype.render=function(){return gt.createElement("div",{ref:this.itemElement,onContextMenu:this._onClick},this.props.renderedItem,this.state.contextualMenuVisible?gt.createElement(Wu,{items:this.props.menuItems,shouldFocusOnMount:!0,target:this.itemElement.current,onDismiss:this._onCloseContextualMenu,directionalHint:Pa.bottomLeftEdge}):null)},k1),m1={root:"ms-EditingItem",input:"ms-EditingItem-input"},g1=(l(x1,Qw=gt.Component),x1.prototype.componentDidMount=function(){var e=(0,this.props.getEditingItemText)(this.props.item);this._editingFloatingPicker.current&&this._editingFloatingPicker.current.onQueryStringChanged(e),this._editingInput.value=e,this._editingInput.focus()},x1.prototype.render=function(){var e=_s(),t=ur(this.props,Zn),o=Fn()(Yw);return gt.createElement("div",{"aria-labelledby":"editingItemPersona-"+e,className:o.root},gt.createElement("input",ht({autoCapitalize:"off",autoComplete:"off"},t,{ref:this._resolveInputRef,onChange:this._onInputChange,onKeyDown:this._onInputKeyDown,onBlur:this._onInputBlur,onClick:this._onInputClick,"data-lpignore":!0,className:o.input,id:e})),this._renderEditingSuggestions())},x1.prototype._onInputKeyDown=function(e){e.which!==En.backspace&&e.which!==En.del\|\|e.stopPropagation()},x1),f1=(l(S1,Xw=jw),S1),v1=(l(_1,Zw=f1),_1.prototype._renderItem=function(e,t){var o=this,n=this.props.removeButtonAriaLabel,r=this.props.onExpandGroup,i={item:e,index:t,key:e.key\|\|t,selected:this.selection.isIndexSelected(t),onRemoveItem:function(){return o.removeItem(e)},onItemChange:this.onItemChange,removeButtonAriaLabel:n,onCopyItem:function(e){return o.copyItems([e])},onExpandItem:r?function(){return r(e)}:void 0,menuItems:this._createMenuItems(e)},t=0<i.menuItems.length;if(e.isEditing&&t)return gt.createElement(g1,ht({},i,{onRenderFloatingPicker:this.props.onRenderFloatingPicker,floatingPickerProps:this.props.floatingPickerProps,onEditingComplete:this._completeEditing,getEditingItemText:this.props.getEditingItemText}));n=(0,this.props.onRenderItem)(i);return t?gt.createElement(h1,{key:i.key,renderedItem:n,beginEditing:this._beginEditing,menuItems:this._createMenuItems(i.item),item:i.item}):n},_1.prototype._createMenuItems=function(e){var o=this,t=[];return this.props.editMenuItemText&&this.props.getEditingItemText&&t.push({key:"Edit",text:this.props.editMenuItemText,onClick:function(e,t){o._beginEditing(t.data)},data:e}),this.props.removeMenuItemText&&t.push({key:"Remove",text:this.props.removeMenuItemText,onClick:function(e,t){o.removeItem(t.data)},data:e}),this.props.copyMenuItemText&&t.push({key:"Copy",text:this.props.copyMenuItemText,onClick:function(e,t){o.props.onCopyItems&&o.copyItems([t.data])},data:e}),t},_1.defaultProps={onRenderItem:function(e){return gt.createElement(p1,ht({},e))}},_1),b1=Fn(),y1=gt.forwardRef(function(e,t){var o=e.styles,n=e.theme,r=e.className,i=e.vertical,s=e.alignContent,e=e.children,s=b1(o,{theme:n,className:r,alignContent:s,vertical:i});return gt.createElement("div",{className:s.root,ref:t},gt.createElement("div",{className:s.content,role:"separator","aria-orientation":i?"vertical":"horizontal"},e))}),C1=In(y1,function(e){var t,o=e.theme,n=e.alignContent,r=e.vertical,e=e.className;return{root:[o.fonts.medium,{position:"relative"},n&&{textAlign:n},!n&&{textAlign:"center"},r&&("center"===n\|\|!n)&&{verticalAlign:"middle"},r&&"start"===n&&{verticalAlign:"top"},r&&"end"===n&&{verticalAlign:"bottom"},r&&{padding:"0 4px",height:"inherit",display:"table-cell",zIndex:1,selectors:{":after":((t={backgroundColor:o.palette.neutralLighter,width:"1px",content:'""',position:"absolute",top:"0",bottom:"0",left:"50%",right:"0",zIndex:-1})[Yt]={backgroundColor:"WindowText"},t)}},!r&&{padding:"4px 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this._placeHolder.current},enumerable:!1,configurable:!0}),Object.defineProperty(AI.prototype,"stickyContentTop",{get:function(){return this._stickyContentTop.current},enumerable:!1,configurable:!0}),Object.defineProperty(AI.prototype,"stickyContentBottom",{get:function(){return this._stickyContentBottom.current},enumerable:!1,configurable:!0}),Object.defineProperty(AI.prototype,"nonStickyContent",{get:function(){return this._nonStickyContent.current},enumerable:!1,configurable:!0}),Object.defineProperty(AI.prototype,"canStickyTop",{get:function(){return this.props.stickyPosition===DI.Both\|\|this.props.stickyPosition===DI.Header},enumerable:!1,configurable:!0}),Object.defineProperty(AI.prototype,"canStickyBottom",{get:function(){return this.props.stickyPosition===DI.Both\|\|this.props.stickyPosition===DI.Footer},enumerable:!1,configurable:!0}),AI.prototype.componentDidMount=function(){var e=this._getContext().scrollablePane;e&&(e.subscribe(this._onScrollEvent),e.addSticky(this))},AI.prototype.componentWillUnmount=function(){var e=this._getContext().scrollablePane;e&&(e.unsubscribe(this._onScrollEvent),e.removeSticky(this))},AI.prototype.componentDidUpdate=function(e,t){var o,n,r,i,s=this._getContext().scrollablePane;s&&(o=(i=this.state).isStickyBottom,n=i.isStickyTop,r=i.distanceFromTop,i=!1,t.distanceFromTop!==r&&(s.sortSticky(this,!0),i=!0),t.isStickyTop===n&&t.isStickyBottom===o\|\|(this._activeElement&&this._activeElement.focus(),s.updateStickyRefHeights(),i=!0),i&&s.syncScrollSticky(this))},AI.prototype.shouldComponentUpdate=function(e,t){if(!this.context.scrollablePane)return!0;var o=this.state,n=o.isStickyTop,r=o.isStickyBottom,o=o.distanceFromTop;return n!==t.isStickyTop\|\|r!==t.isStickyBottom\|\|this.props.stickyPosition!==e.stickyPosition\|\|this.props.children!==e.children\|\|o!==t.distanceFromTop\|\|LI(this._nonStickyContent,this._stickyContentTop)\|\|LI(this._nonStickyContent,this._stickyContentBottom)\|\|LI(this._nonStickyContent,this._placeHolder)},AI.prototype.render=function(){var e=this.state,t=e.isStickyTop,o=e.isStickyBottom,n=this.props,e=n.stickyClassName,n=n.children;return this.context.scrollablePane?gt.createElement("div",{ref:this._root},this.canStickyTop&&gt.createElement("div",{ref:this._stickyContentTop,style:{pointerEvents:t?"auto":"none"}},gt.createElement("div",{style:this._getStickyPlaceholderHeight(t)})),this.canStickyBottom&&gt.createElement("div",{ref:this._stickyContentBottom,style:{pointerEvents:o?"auto":"none"}},gt.createElement("div",{style:this._getStickyPlaceholderHeight(o)})),gt.createElement("div",{style:this._getNonStickyPlaceholderHeightAndWidth(),ref:this._placeHolder},(t\|\|o)&&gt.createElement("span",{style:So},n),gt.createElement("div",{ref:this._nonStickyContent,className:t\|\|o?e:void 0,style:this._getContentStyles(t\|\|o)},n))):gt.createElement("div",null,this.props.children)},AI.prototype.addSticky=function(e){this.nonStickyContent&&e.appendChild(this.nonStickyContent)},AI.prototype.resetSticky=function(){this.nonStickyContent&&this.placeholder&&this.placeholder.appendChild(this.nonStickyContent)},AI.prototype.setDistanceFromTop=function(e){e=this._getNonStickyDistanceFromTop(e);this.setState({distanceFromTop:e})},AI.prototype._getContentStyles=function(e){return{backgroundColor:this.props.stickyBackgroundColor\|\|this._getBackground(),overflow:e?"hidden":""}},AI.prototype._getStickyPlaceholderHeight=function(e){var t=this.nonStickyContent?this.nonStickyContent.offsetHeight:0;return{visibility:e?"hidden":"visible",height:e?0:t}},AI.prototype._getNonStickyPlaceholderHeightAndWidth=function(){var e=this.state,t=e.isStickyTop,e=e.isStickyBottom;if(t\|\|e){t=0,e=0;return this.nonStickyContent&&this.nonStickyContent.firstElementChild&&(t=this.nonStickyContent.offsetHeight,e=this.nonStickyContent.firstElementChild.scrollWidth+(this.nonStickyContent.firstElementChild.offsetWidth-this.nonStickyContent.firstElementChild.clientWidth)),{height:t,width:e}}return{}},AI.prototype._getBackground=function(){if(this.root){for(var e=this.root;"rgba(0, 0, 0, 0)"===window.getComputedStyle(e).getPropertyValue("background-color")\|\|"transparent"===window.getComputedStyle(e).getPropertyValue("background-color");){if("HTML"===e.tagName)return;e.parentElement&&(e=e.parentElement)}return window.getComputedStyle(e).getPropertyValue("background-color")}},AI.defaultProps={stickyPosition:DI.Both,isScrollSynced:!0},AI.contextType=Mw,AI);function AI(e){var i=BI.call(this,e)\|\|this;return i._root=gt.createRef(),i._stickyContentTop=gt.createRef(),i._stickyContentBottom=gt.createRef(),i._nonStickyContent=gt.createRef(),i._placeHolder=gt.createRef(),i.syncScroll=function(e){var t=i.nonStickyContent;t&&i.props.isScrollSynced&&(t.scrollLeft=e.scrollLeft)},i._getContext=function(){return i.context},i._onScrollEvent=function(e,t){var o,n,r;i.root&&i.nonStickyContent&&(o=i._getNonStickyDistanceFromTop(e),r=n=!1,i.canStickyTop&&(n=o-i._getStickyDistanceFromTop()<e.scrollTop),i.canStickyBottom&&e.clientHeight-t.offsetHeight<=o&&(r=o-Math.floor(e.scrollTop)>=i._getStickyDistanceFromTopForFooter(e,t)),document.activeElement&&i.nonStickyContent.contains(document.activeElement)&&(i.state.isStickyTop!==n\|\|i.state.isStickyBottom!==r)?i._activeElement=document.activeElement:i._activeElement=void 0,i.setState({isStickyTop:i.canStickyTop&&n,isStickyBottom:r,distanceFromTop:o}))},i._getStickyDistanceFromTop=function(){var e=0;return e=i.stickyContentTop?i.stickyContentTop.offsetTop:e},i._getStickyDistanceFromTopForFooter=function(e,t){var o=0;return o=i.stickyContentBottom?e.clientHeight-t.offsetHeight+i.stickyContentBottom.offsetTop:o},i._getNonStickyDistanceFromTop=function(e){var t=0,o=i.root;if(o){for(;o&&o.offsetParent!==e;)t+=o.offsetTop,o=o.offsetParent;o&&o.offsetParent===e&&(t+=o.offsetTop)}return t},fi(i),i.state={isStickyTop:!1,isStickyBottom:!1,distanceFromTop:void 0},i._activeElement=void 0,i}function LI(e,t){return e&&t&&e.current&&t.current&&e.current.offsetHeight!==t.current.offsetHeight}var HI=Fn(),OI=Ao(function(e,t,o,n,r,i,s,a,l){e=op(e);return pn({root:["ms-Button",e.root,o,t,s&&["is-checked",e.rootChecked],i&&["is-disabled",e.rootDisabled],!i&&!s&&{selectors:{":hover":e.rootHovered,":focus":e.rootFocused,":active":e.rootPressed}},i&&s&&[e.rootCheckedDisabled],!i&&s&&{selectors:{":hover":e.rootCheckedHovered,":active":e.rootCheckedPressed}}],flexContainer:["ms-Button-flexContainer",e.flexContainer]})}),zI=function(e){var t=e.item,o=e.idPrefix,n=void 0===o?e.id:o,r=e.isRadio,i=e.selected,s=void 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0:e.str},d?gt.createElement("circle",{cx:"50%",cy:"50%",r:"50%"}):gt.createElement("rect",{width:"100%",height:"100%"}))},onClick:h,onHover:m,onFocus:g,label:t.label,className:C.colorCell,getClassNames:OI,index:t.index,onMouseEnter:f,onMouseMove:v,onMouseLeave:b,onWheel:y,onKeyDown:o}))},WI={left:-2,top:-2,bottom:-2,right:-2,border:"none",outlineColor:"ButtonText"},VI=In(zI,function(e){var t,o,n=e.theme,r=e.disabled,i=e.selected,s=e.circle,a=e.isWhite,l=e.height,c=void 0===l?20:l,u=e.width,d=void 0===u?20:u,p=e.borderWidth,h=n.semanticColors,m=n.palette,g=m.neutralLighter,l=m.neutralLight,u=m.neutralSecondary,e=m.neutralTertiary,m=p\|\|(d<24?2:4);return{colorCell:[bo(n,{inset:-1,position:"relative",highContrastStyle:WI}),{backgroundColor:h.bodyBackground,padding:0,position:"relative",boxSizing:"border-box",display:"inline-block",cursor:"pointer",userSelect:"none",borderRadius:0,border:"none",height:c,width:d,verticalAlign:"top"},!s&&{selectors:((t={})["."+go+" &:focus::after"]={outlineOffset:m-1+"px"},t)},s&&{borderRadius:"50%",selectors:((p={})["."+go+" &:focus::after"]={outline:"none",borderColor:h.focusBorder,borderRadius:"50%",left:-m,right:-m,top:-m,bottom:-m,selectors:((t={})[Yt]={outline:"1px solid ButtonText"},t)},p)},i&&{padding:2,border:m+"px solid "+l,selectors:((o={})["&:hover::before"]={content:'""',height:c,width:d,position:"absolute",top:-m,left:-m,borderRadius:s?"50%":"default",boxShadow:"inset 0 0 0 1px "+u},o)},!i&&{selectors:((o={})["&:hover, &:active, &:focus"]={backgroundColor:h.bodyBackground,padding:2,border:m+"px solid "+g},o["&:focus"]={borderColor:h.bodyBackground,padding:0,selectors:{":hover":{borderColor:n.palette.neutralLight,padding:2}}},o)},r&&{color:h.disabledBodyText,pointerEvents:"none",opacity:.3},a&&!i&&{backgroundColor:e,padding:1}],svg:[{width:"100%",height:"100%"},s&&{borderRadius:"50%"}]}},void 0,{scope:"ColorPickerGridCell"},!0),KI=Fn(),GI=gt.forwardRef(function(n,e){var t=iu("swatchColorPicker"),o=n.id\|\|t,r=_l({isNavigationIdle:!0,cellFocused:!1,navigationIdleTimeoutId:void 0,navigationIdleDelay:250}),i=Tm(),s=i.setTimeout,a=i.clearTimeout,l=n.colorCells,c=n.cellShape,u=void 0===c?"circle":c,d=n.columnCount,p=n.shouldFocusCircularNavigate,h=void 0===p\|\|p,m=n.className,g=n.disabled,f=void 0!==g&&g,v=n.doNotContainWithinFocusZone,t=n.styles,i=n.cellMargin,c=void 0===i?10:i,p=n.defaultSelectedId,b=n.focusOnHover,y=n.mouseLeaveParentSelector,C=n.onChange,_=n.onColorChanged,S=n.onCellHovered,x=n.onCellFocused,k=n.getColorGridCellStyles,w=n.cellHeight,I=n.cellWidth,D=n.cellBorderWidth,g=gt.useMemo(function(){return l.map(function(e,t){return ht(ht({},e),{index:t})})},[l]),i=gt.useCallback(function(e,t){var o=null===(o=l.filter(function(e){return e.id===t})[0])\|\|void 0===o?void 0:o.color;null==C\|\|C(e,t,o),null==_\|\|_(t,o)},[C,_,l]),i=Fh(n.selectedId,p,i),E=i[0],T=i[1],m=KI(t,{theme:n.theme,className:m,cellMargin:c}),c={root:m.root,tableCell:m.tableCell,focusedContainer:m.focusedContainer},P=l.length<=d,m=gt.useCallback(function(){x&&(r.cellFocused=!1,x())},[r,x]),R=gt.useCallback(function(e){return b?(r.isNavigationIdle&&!f&&e.currentTarget.focus(),!0):!r.isNavigationIdle\|\|!!f},[b,r,f]),M=gt.useCallback(function(e){if(!b)return!r.isNavigationIdle\|\|!!f;e=e.currentTarget;return!r.isNavigationIdle\|\|document&&e===document.activeElement\|\|e.focus(),!0},[b,r,f]),N=gt.useCallback(function(e){if(b&&y&&r.isNavigationIdle&&!f)for(var t=document.querySelectorAll(y),o=0;o<t.length;o+=1)if(t[o].contains(e.currentTarget)){if(t[o].setActive)try{t[o].setActive()}catch(e){}else t[o].focus();break}},[f,b,r,y]),B=gt.useCallback(function(e){if(S)return e?S(e.id,e.color):S()},[S]),F=gt.useCallback(function(e){if(x)return e?(r.cellFocused=!0,x(e.id,e.color)):(r.cellFocused=!1,x())},[r,x]),A=gt.useCallback(function(e){f\|\|e.id!==E&&(x&&r.cellFocused&&(r.cellFocused=!1,x()),T(e.id))},[f,r,x,E,T]),L=gt.useCallback(function(){r.isNavigationIdle\|\|void 0===r.navigationIdleTimeoutId?r.isNavigationIdle=!1:(a(r.navigationIdleTimeoutId),r.navigationIdleTimeoutId=void 0),r.navigationIdleTimeoutId=s(function(){r.isNavigationIdle=!0},r.navigationIdleDelay)},[a,r,s]),H=gt.useCallback(function(e){e.which!==En.up&&e.which!==En.down&&e.which!==En.left&&e.which!==En.right\|\|L()},[L]),O=function(e){return gt.createElement(VI,{item:e,idPrefix:o,color:e.color,styles:k,disabled:f,onClick:A,onHover:B,onFocus:F,selected:E===e.id,circle:"circle"===u,label:e.label,onMouseEnter:R,onMouseMove:M,onMouseLeave:N,onWheel:L,onKeyDown:H,height:w,width:I,borderWidth:D,isRadio:P})};return l.length<1\|\|d<1?null:gt.createElement(mp,ht({},n,{ref:e,id:o,items:g,columnCount:d,isSemanticRadio:P,onRenderItem:function(e,t){var o=n.onRenderColorCell;return(void 0===o?O:o)(e,O)},shouldFocusCircularNavigate:h,doNotContainWithinFocusZone:v,onBlur:m,theme:n.theme,styles:c}))});GI.displayName="SwatchColorPicker";function UI(e,t){var t=(o=t\|\|{}).calloutWidth,o=o.calloutMaxWidth;return[{display:"block",maxWidth:364,border:0,outline:"transparent",width:t\|\|"calc(100% + 1px)",animationName:""+QI(),animationDuration:"300ms",animationTimingFunction:"linear",animationFillMode:"both"},e&&{maxWidth:o\|\|456}]}var jI={focusedContainer:"ms-swatchColorPickerBodyContainer"},qI=In(GI,function(e){var t=e.className,o=e.theme;return{root:{margin:"8px 0",borderCollapse:"collapse"},tableCell:{padding:e.cellMargin/2},focusedContainer:[zo(jI,o).focusedContainer,{clear:"both",display:"block",minWidth:"180px"},t]}},void 0,{scope:"SwatchColorPicker"}),YI=Fn(),ZI=gt.forwardRef(function(e,t){var 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library(EvalEst) ### Name: MonteCarloSimulations ### Title: Generate simulations ### Aliases: MonteCarloSimulations MonteCarloSimulations.default ### MonteCarloSimulations.TSmodel MonteCarloSimulations.TSestModel ### MonteCarloSimulations.EstEval ### MonteCarloSimulations.MonteCarloSimulations is.MonteCarloSimulations ### Keywords: ts ### ** Examples data("eg1.DSE.data.diff", package="dse") model <- estVARXls(eg1.DSE.data.diff) z <- MonteCarloSimulations(model, simulation.args=list(sampleT=100)) tfplot(z) distribution(z)	/data/genthat_extracted_code/EvalEst/examples/MonteCarloSimulations.Rd.R	no_license	surayaaramli/typeRrh	R	false	false	541	r	library(EvalEst) ### Name: MonteCarloSimulations ### Title: Generate simulations ### Aliases: MonteCarloSimulations MonteCarloSimulations.default ### MonteCarloSimulations.TSmodel MonteCarloSimulations.TSestModel ### MonteCarloSimulations.EstEval ### MonteCarloSimulations.MonteCarloSimulations is.MonteCarloSimulations ### Keywords: ts ### ** Examples data("eg1.DSE.data.diff", package="dse") model <- estVARXls(eg1.DSE.data.diff) z <- MonteCarloSimulations(model, simulation.args=list(sampleT=100)) tfplot(z) distribution(z)
library(tidyverse) library(lubridate) library(httr) library(dplyr) library(xml2) #build the url and GET the result url <- "https://oeis.org/A005408" h <- handle(url) res <- GET(handle = h) a<- read_html(res) htmlCode <- xml_find_all(a, ".//body") # create empty frame df <- data.frame(header = character(0), pText = character(0)) # get all td tags td <- xml_find_all(htmlCode, ".//td") # Iterate through all td tags for (x in td) { if (length(xml_find_first(x, ".//font")) > 0) { section <- xml_text(xml_find_first(x, ".//font")) print(section) } # if there are p tags in this cell if(length(xml_find_all(x, ".//p")) > 0) { pTags <- xml_find_all(x, ".//p") for (p in pTags) { print(paste0("Section to add in DataFrame -->", section)) print(paste0("PTag to add -->", as.character(p))) dataRow <- data.frame( header = section, pText = as.character(p) ) df <- rbind(df, dataRow) } print("END OF ITERATING THROUGH PTAGS") #print(xml_text(pTags)) } } glimpse(df)	/DataPrep/Main.R	no_license	jgab3103/OEIS-Anaytics-Project	R	false	false	1,139	r	library(tidyverse) library(lubridate) library(httr) library(dplyr) library(xml2) #build the url and GET the result url <- "https://oeis.org/A005408" h <- handle(url) res <- GET(handle = h) a<- read_html(res) htmlCode <- xml_find_all(a, ".//body") # create empty frame df <- data.frame(header = character(0), pText = character(0)) # get all td tags td <- xml_find_all(htmlCode, ".//td") # Iterate through all td tags for (x in td) { if (length(xml_find_first(x, ".//font")) > 0) { section <- xml_text(xml_find_first(x, ".//font")) print(section) } # if there are p tags in this cell if(length(xml_find_all(x, ".//p")) > 0) { pTags <- xml_find_all(x, ".//p") for (p in pTags) { print(paste0("Section to add in DataFrame -->", section)) print(paste0("PTag to add -->", as.character(p))) dataRow <- data.frame( header = section, pText = as.character(p) ) df <- rbind(df, dataRow) } print("END OF ITERATING THROUGH PTAGS") #print(xml_text(pTags)) } } glimpse(df)
library(glmnet) mydata = read.table("./TrainingSet/Correlation/pleura.csv",head=T,sep=",") x = as.matrix(mydata[,4:ncol(mydata)]) y = as.matrix(mydata[,1]) set.seed(123) glm = cv.glmnet(x,y,nfolds=10,type.measure="mae",alpha=0.9,family="gaussian",standardize=TRUE) sink('./Model/EN/Correlation/pleura/pleura_091.txt',append=TRUE) print(glm$glmnet.fit) sink()	/Model/EN/Correlation/pleura/pleura_091.R	no_license	leon1003/QSMART	R	false	false	359	r	library(glmnet) mydata = read.table("./TrainingSet/Correlation/pleura.csv",head=T,sep=",") x = as.matrix(mydata[,4:ncol(mydata)]) y = as.matrix(mydata[,1]) set.seed(123) glm = cv.glmnet(x,y,nfolds=10,type.measure="mae",alpha=0.9,family="gaussian",standardize=TRUE) sink('./Model/EN/Correlation/pleura/pleura_091.txt',append=TRUE) print(glm$glmnet.fit) sink()
## Put comments here that give an overall description of what your ## functions do ## Write a short comment describing this function ## The makeCacheMatrix creates a special "matrix", which is really a list containing a function to ## Set the Matrix, Get the Matrix, Set the Inverse of the Matrix, Get the Inverse of the Matrix. makeCacheMatrix <- function(x = matrix()) { i <- NULL set <- function(y) { y <<- x i <<- NULL } get <- function(x) x setinverse <- function(inverse) i <<- inverse getinverse <- function() i list(set = set, get = get, setinverse = setinverse, getinverse = getinverse) } ## Write a short comment describing this function ## The following function calculates the inverse of the Matrix created with the above function. ## However, it first checks to see if the inverse matrix has already been calculated. ## If so, it gets the inverse matrix from the cache and skips the computation. ## Otherwise, it calculates the inverse matrix and sets the value of the inverse in the cache via the setinverse function. cacheSolve <- function(x, ...) { ## Return a matrix that is the inverse of 'x' i <- x$getinverse() if(!is.null(i)) { message("getting cached inverse") return(i) } data <- x$get() i <- solve(data, ...) x$setinverse(i) i }	/cachematrix.R	no_license	PrasanthSatz/ProgrammingAssignment2	R	false	false	1,318	r	## Put comments here that give an overall description of what your ## functions do ## Write a short comment describing this function ## The makeCacheMatrix creates a special "matrix", which is really a list containing a function to ## Set the Matrix, Get the Matrix, Set the Inverse of the Matrix, Get the Inverse of the Matrix. makeCacheMatrix <- function(x = matrix()) { i <- NULL set <- function(y) { y <<- x i <<- NULL } get <- function(x) x setinverse <- function(inverse) i <<- inverse getinverse <- function() i list(set = set, get = get, setinverse = setinverse, getinverse = getinverse) } ## Write a short comment describing this function ## The following function calculates the inverse of the Matrix created with the above function. ## However, it first checks to see if the inverse matrix has already been calculated. ## If so, it gets the inverse matrix from the cache and skips the computation. ## Otherwise, it calculates the inverse matrix and sets the value of the inverse in the cache via the setinverse function. cacheSolve <- function(x, ...) { ## Return a matrix that is the inverse of 'x' i <- x$getinverse() if(!is.null(i)) { message("getting cached inverse") return(i) } data <- x$get() i <- solve(data, ...) x$setinverse(i) i }
#### practice with probability distributions #### # calculating the likelihood requires understanding how to work # with probability distributions. let's start with the binomial # distribution. # the binomial distribution describes the number of "success" in # some number of "trials" given some probability of success. it # is the "coin flipping" distribution. # in R, we can draw a sample from a binomial distribution with rbinom() # this isn't the first time you've seen rbinom, but here it is again, # with the parameters spelled out. you can try changing these to explore # how the function works. number.of.samples <- 2 number.of.trials.per.sample <- 10 probability.of.success <- 0.7 rbinom(number.of.samples, number.of.trials.per.sample, probability.of.success) # below, use rbinom to create sample data for the following scenario. # an experiment tests whether subjects have ESP. 100 subjects are each given # the opportunity to predict whether a randomly generated number is odd or even. # each subject makes 20 guesses. # of course, ESP doesn't exist, so the probability of a successful guess is 0.50. # store the result in a vector called esp.data number.of.samples <- 2 number.of.trials.per.sample <- 20 probability.of.success <- 0.5 esp.data <-replicate(100,rbinom(number.of.samples, number.of.trials.per.sample, probability.of.success))# answer needed here. # a quick way to visualize a distribution is with the hist() function: hist(esp.data) # what if we want to know the probability of someone getting exactly 10 guesses # correct out of 20, if they are randomly guessing? for that we use the density # function of the binomial: dbinom() value.to.check <- 10 number.of.trials <- 20 probability.of.success <- 0.5 dbinom(value.to.check, number.of.trials, probability.of.success) # use dbinom to find out the probability of someone answering 87 out of 100 # questions correctly, if they have a 0.9 probability of giving a correct answer # for each individual question. # answer needed here. value.to.check <- 87 number.of.trials <- 100 probability.of.success <- 0.9 dbinom(value.to.check, number.of.trials, probability.of.success) # with dbinom, you can use a vector as the first argument, to check the probability # of multiple values at the same time: values <- c(3, 4, 5) dbinom(values, 8, 0.5) # using this shortcut, plot the full distribution (probability mass function) # for flipping 16 fair coins, counting the total number of heads. # hint: create one vector for the different possible outcomes # then use dbinom to calculate the probability of all of the elements in the vector # answer needed here. value.to.check <-c(1:16) number.of.trials <- 16 probability.of.success <- 0.5 y<-dbinom(value.to.check, number.of.trials, probability.of.success) x<-value.to.check plot(x,y) # quick detour # # here's a quick tip about plot() or hist() # if you want to change the range on the x-axis, you can use the xlim argument: hist.sample <- rbinom(100, 100, 0.5) hist(hist.sample) hist(hist.sample, xlim=c(0,100)) # compare this plot to the line above. # the normal distribution ## # normal (gaussian) distributions are characterized by two parameters: mean and standard deviation # the mean is the the location of the peak of the distribution, and the sd controls the width. # the smaller the sd, the more peaked the distribution is in the center. # like the binomial, there are rnorm() and dnorm() functions. # generate 100 samples from a normal distribution with mean 0 and standard deviation 10. # then use hist() to create a histogram of these samples. # answer needed here. norm.samples<-replicate(100,rnorm(0,10)) hist(norm.samples) # now plot the probability density function of this distribution. # use the same strategy as you did above with the binomial to find the density of the normal # distribution with mean 0 and sd 10 for values between -50 and 50. the distribution is continuous # so, choose a reasonably small step size between values (remember the seq() function). # answer needed here. x<-seq(from = -50.0, to= 50.0, by= 0.1) norm.dist<-dnorm(x,0,10) plot(x,norm.dist) #### practice calculating likelihoods #### # here's some data from 10 participants in an ESP experiment like the one described # above. each subject had 20 guesses. the number of correct guesses is reported. esp.practice.data <- data.frame(subject=1:10, n.correct=c(11,10,6,10,6,12,10,8,9,11)) # calculate the likelihood (regular, not log) for this data for three different values # of the probability of success parameter: 0.4, 0.5, and 0.6. # hint: prod() will multiple all elements of a vector together. # answer needed here. prod(dbinom(esp.practice.data$n.correct,20,.4)) prod(dbinom(esp.practice.data$n.correct,20,.5)) prod(dbinom(esp.practice.data$n.correct,20,.6)) # which parameter value of those options is most likely? # answer here. # 0.5 has a higher likelihood of selecting the sample data from it's distributions # so we conclude that .5 is more likely prod(dbinom(esp.practice.data$n.correct,20,.5)) # here is a sample of response times for a single subject from a rapid decision making experiment. rt.sample <- c(391.5845, 411.9970, 358.6373, 505.3099, 616.2892, 481.0751, 422.3132, 511.7213, 205.2692, 522.3433, 370.1850, 517.4617, 332.3344, 316.8760, 395.5431, 231.7831, 399.8646, 238.9064, 299.7924, 474.7512, 271.6326, 423.4861, 379.7867, 212.7789, 233.8291, 472.4591, 534.2131, 453.9655, 408.3443, 352.3001) # calculate the log likelihood for this data assuming that it is generated by a normal # distribution for each of the following parameters. # hint: sum() adds the numbers in a vector. log() is the natural log function, or log=T for dnorm(). # 1) mean 350, sd 50 # answer needed here. sum(log(dnorm(rt.sample,350,50))) # 2) mean 400, sd 50 # answer needed here. sum(log(dnorm(rt.sample,400,50))) # 3) mean 450, sd 50 # answer needed here. sum(log(dnorm(rt.sample,450,50))) # 4) mean 350, sd 100 # answer needed here. sum(log(dnorm(rt.sample,350,100))) # 5) mean 400, sd 100 # answer needed here. sum(log(dnorm(rt.sample,400,100))) # 6) mean 450, sd 100 # answer needed here. sum(log(dnorm(rt.sample,450,100))) # which parameter set has the highest likelihood? # answer needed here. #The values with the greatest log likelihood are mean=400, sd=100 # here is a set of data for a subject in a categorization experiment, modeled with GCM. # calculate the log likelihood of the parameters in the model (which i am not showing you). # the point here is to know what to do when the model gives you a predicted probability # of a response, and the data is either that response or not that response. # hint: add a new column indicating the likelihood of each response, using mapply. then convert to log and add. # if you do this correctly, the answer is -10.84249. gcm.practice.data <- data.frame(correct.response = c(T, T, T, T, F, T, T, F, T, T, T, F, F, T, T, F, T, T, T, T), gcm.probability.correct = c(0.84, 0.80, 0.84, 0.80, 0.79, 0.86, 0.89, 0.87, 0.69, 0.85, 0.75, 0.74, 0.82, 0.85, 0.87, 0.69, 0.83, 0.87, 0.80, 0.76)) # answer needed here. gcm.practice.data$likelihood<- mapply(function(x,y){ if(x==TRUE){ return(y)} else{ return(1-y)} },gcm.practice.data$correct.response,gcm.practice.data$gcm.probability.correct) sum(log(gcm.practice.data$likelihood)) #### maximum likelihood estimation #### # the same search strategies we used for parameter fitting with rmse can be used with likelihoods, # including grid search. # here are the number of correct responses each subject gave in an experiment in which they had to # decide if two images were the same or different. there were 40 trials for each subject same.diff.data <- c(32, 29, 31, 34, 26, 29, 31, 34, 29, 31, 30, 29, 31, 34, 33, 27, 32, 29, 29, 27) # we can model this experiment's data as 40 coin flips for each subject. use grid search to plot the likelihood # function for values of theta (probability of a correct response) between 0.5 and 0.9, in steps of 0.01. # start by writing a function that calculates the likelihood (not log) for the entire set of data given a value of theta. # answer needed here. likelihood<-function(th){ prod(sapply(same.diff.data,function(x){dbinom(x,40,th)})) } # then use sapply to run the function for each possible value of theta in the set. use seq() to generate the # set of possible values. plot the set of values on the x axis and the corresponding likelihoods on the y axis. # answer needed here. theta=seq(from = 0.5, to = 0.9, by = .01) likelihood.theta<-sapply(theta,likelihood) install.packages('ggplot2') library(ggplot2) plot.theta.likelihood<-data.frame(theta,likelihood.theta) ggplot(plot.theta.likelihood, aes(x=theta,y=likelihood.theta))+ geom_point() best.theta<-plot.theta.likelihood[which.max(plot.theta.likelihood$likelihood.theta),] # the "true" underlying value i used to generate the data was 0.75. does that match up with the grid search? #Yes, kind of. It got .76 as best.theta ## mle with optim() # in this section, you'll do model recovery for a descriptive model of the linear relationship # between two continuous variables. # let's assume that variable y is a linear function of variable x, such that: # y = 4 + 0.8x # create a vector of x values from 0 to 100, and the corresponding vector of y values, # then plot these with x values on the x axis, and y values on the y axis. # answer needed here. x<-seq(0:100) y<-sapply(x,function(dummy){4+0.8dummy}) plot(x,y) # now let's assume that the relationship between x and y isn't perfect. there's a bit of random # noise. add a random sample from a normal distribution with mean 0 and sd 10 to each y value. # hint: there are 101 y values, so you need 101 samples. # answer needed here. noise<-c(rnorm(101,0,10)) y.noise<- y+noise # plot the data again, with the new noisy y values. # answer needed here. plot(x,y.noise) # there are three parameter values that control this plot, # the intercept of the line: 4 # the slope of the line: 0.8 # the sd of the normal distribution: 10 # say that we observe a point of data, x = 20 and y = 27. # the linear equation, y <- 4 + 0.8x, predicts that when x is 20 y should also be 20. 4 + 0.820 # our model of this data assumes that the relationship is not perfect. # we assume that there is noise so that when x is 20, the most likely value of y should be 4 + 0.8x, # but other values of y are possible. we describe the probability of different values of y with a normal # distribution. when x is 20, then the normal distribution of y values is centered on 20, because the line # says that y is 4 + 0.8x. using the normal distribution is helpful because it gives us a way to quantify # how likely a value of 19 is compared to a value of 16, when x is 20. # here's an example x.observed <- 20 y.predicted <- 4 + 0.8x.observed # to find out the probability of y.observed=20, use dnorm() # the mean of the normal distribution should be y.predicted (the distribution is centered on the line) # and the sd of the normal is a parameter we will estimate, but for the demo below, is set to 10. y.observed <- 20 dnorm(y.observed, y.predicted, 10) # write the code to see how likely it is that y will be 33 when x is 29? (assuming sd = 10) # the correct answer is 0.03371799... # answer needed here. x.observed<-29 y.predicted <- 4 + 0.8x.observed y.observed <- 33 dnorm(y.observed, y.predicted, 10) # now generalize your solution to compute the likelihood of each value of y that you generated above. # in other words, write the code that takes a vector of x and y values, and returns the probability # of each pair given that the relationship between x and y is y <- 4 + 0.8x and the normal distribution has an sd of 10. # answer needed here. likelihood.y.observed<-mapply(function(y.o,y.p){dnorm(y.o,y.p,10)},y.noise,y) # now generalize your solution one step further. write a function that takes in a vector of parameters, # where parameters[1] is the intercept, parameters[2] is the slope, and parameters[3] is the sd of the normal, # and returns the total negative log likelihood. remember, we want the negative log likelihood because # optim() will find the set of parameters that minimizes a function. # answer needed here. negative.log.likelihood<-function(parameters){ intercept<-parameters[1] slope<-parameters[2] sd<-parameters[3] if(sd>0){ x<-seq(0:100) y.pred<-sapply(x,function(x){intercept+(slopex)}) y.obs<-y.noise gg<-data.frame(x,y.obs) likelihood.y.obs<-mapply(function(y.o,y.p){dnorm(y.o,y.p,sd)},y.obs,y.pred) return(sum(-log(likelihood.y.obs))) } else{return(NULL)} } negative.log.likelihood(c(1,2,3)) # use optim() and Nelder-Mead to search for the best fitting parameters. remember to ensure that sd > 0 # and return NA if it is not. # answer needed here. fit <- optim(c(10,.9,15), negative.log.likelihood, method="Nelder-Mead") # finally, plot the best fitting line on your points by using the abline() function, and the parameters that optim() found. # answer needed here. abline(a=fit$par[1], b=fit$par[2], col='blue')	/lab-4.R	no_license	Vassar-COGS282-2016/lab-4-FibonacciGirl	R	false	false	13,289	r	#### practice with probability distributions #### # calculating the likelihood requires understanding how to work # with probability distributions. let's start with the binomial # distribution. # the binomial distribution describes the number of "success" in # some number of "trials" given some probability of success. it # is the "coin flipping" distribution. # in R, we can draw a sample from a binomial distribution with rbinom() # this isn't the first time you've seen rbinom, but here it is again, # with the parameters spelled out. you can try changing these to explore # how the function works. number.of.samples <- 2 number.of.trials.per.sample <- 10 probability.of.success <- 0.7 rbinom(number.of.samples, number.of.trials.per.sample, probability.of.success) # below, use rbinom to create sample data for the following scenario. # an experiment tests whether subjects have ESP. 100 subjects are each given # the opportunity to predict whether a randomly generated number is odd or even. # each subject makes 20 guesses. # of course, ESP doesn't exist, so the probability of a successful guess is 0.50. # store the result in a vector called esp.data number.of.samples <- 2 number.of.trials.per.sample <- 20 probability.of.success <- 0.5 esp.data <-replicate(100,rbinom(number.of.samples, number.of.trials.per.sample, probability.of.success))# answer needed here. # a quick way to visualize a distribution is with the hist() function: hist(esp.data) # what if we want to know the probability of someone getting exactly 10 guesses # correct out of 20, if they are randomly guessing? for that we use the density # function of the binomial: dbinom() value.to.check <- 10 number.of.trials <- 20 probability.of.success <- 0.5 dbinom(value.to.check, number.of.trials, probability.of.success) # use dbinom to find out the probability of someone answering 87 out of 100 # questions correctly, if they have a 0.9 probability of giving a correct answer # for each individual question. # answer needed here. value.to.check <- 87 number.of.trials <- 100 probability.of.success <- 0.9 dbinom(value.to.check, number.of.trials, probability.of.success) # with dbinom, you can use a vector as the first argument, to check the probability # of multiple values at the same time: values <- c(3, 4, 5) dbinom(values, 8, 0.5) # using this shortcut, plot the full distribution (probability mass function) # for flipping 16 fair coins, counting the total number of heads. # hint: create one vector for the different possible outcomes # then use dbinom to calculate the probability of all of the elements in the vector # answer needed here. value.to.check <-c(1:16) number.of.trials <- 16 probability.of.success <- 0.5 y<-dbinom(value.to.check, number.of.trials, probability.of.success) x<-value.to.check plot(x,y) # quick detour # # here's a quick tip about plot() or hist() # if you want to change the range on the x-axis, you can use the xlim argument: hist.sample <- rbinom(100, 100, 0.5) hist(hist.sample) hist(hist.sample, xlim=c(0,100)) # compare this plot to the line above. # the normal distribution ## # normal (gaussian) distributions are characterized by two parameters: mean and standard deviation # the mean is the the location of the peak of the distribution, and the sd controls the width. # the smaller the sd, the more peaked the distribution is in the center. # like the binomial, there are rnorm() and dnorm() functions. # generate 100 samples from a normal distribution with mean 0 and standard deviation 10. # then use hist() to create a histogram of these samples. # answer needed here. norm.samples<-replicate(100,rnorm(0,10)) hist(norm.samples) # now plot the probability density function of this distribution. # use the same strategy as you did above with the binomial to find the density of the normal # distribution with mean 0 and sd 10 for values between -50 and 50. the distribution is continuous # so, choose a reasonably small step size between values (remember the seq() function). # answer needed here. x<-seq(from = -50.0, to= 50.0, by= 0.1) norm.dist<-dnorm(x,0,10) plot(x,norm.dist) #### practice calculating likelihoods #### # here's some data from 10 participants in an ESP experiment like the one described # above. each subject had 20 guesses. the number of correct guesses is reported. esp.practice.data <- data.frame(subject=1:10, n.correct=c(11,10,6,10,6,12,10,8,9,11)) # calculate the likelihood (regular, not log) for this data for three different values # of the probability of success parameter: 0.4, 0.5, and 0.6. # hint: prod() will multiple all elements of a vector together. # answer needed here. prod(dbinom(esp.practice.data$n.correct,20,.4)) prod(dbinom(esp.practice.data$n.correct,20,.5)) prod(dbinom(esp.practice.data$n.correct,20,.6)) # which parameter value of those options is most likely? # answer here. # 0.5 has a higher likelihood of selecting the sample data from it's distributions # so we conclude that .5 is more likely prod(dbinom(esp.practice.data$n.correct,20,.5)) # here is a sample of response times for a single subject from a rapid decision making experiment. rt.sample <- c(391.5845, 411.9970, 358.6373, 505.3099, 616.2892, 481.0751, 422.3132, 511.7213, 205.2692, 522.3433, 370.1850, 517.4617, 332.3344, 316.8760, 395.5431, 231.7831, 399.8646, 238.9064, 299.7924, 474.7512, 271.6326, 423.4861, 379.7867, 212.7789, 233.8291, 472.4591, 534.2131, 453.9655, 408.3443, 352.3001) # calculate the log likelihood for this data assuming that it is generated by a normal # distribution for each of the following parameters. # hint: sum() adds the numbers in a vector. log() is the natural log function, or log=T for dnorm(). # 1) mean 350, sd 50 # answer needed here. sum(log(dnorm(rt.sample,350,50))) # 2) mean 400, sd 50 # answer needed here. sum(log(dnorm(rt.sample,400,50))) # 3) mean 450, sd 50 # answer needed here. sum(log(dnorm(rt.sample,450,50))) # 4) mean 350, sd 100 # answer needed here. sum(log(dnorm(rt.sample,350,100))) # 5) mean 400, sd 100 # answer needed here. sum(log(dnorm(rt.sample,400,100))) # 6) mean 450, sd 100 # answer needed here. sum(log(dnorm(rt.sample,450,100))) # which parameter set has the highest likelihood? # answer needed here. #The values with the greatest log likelihood are mean=400, sd=100 # here is a set of data for a subject in a categorization experiment, modeled with GCM. # calculate the log likelihood of the parameters in the model (which i am not showing you). # the point here is to know what to do when the model gives you a predicted probability # of a response, and the data is either that response or not that response. # hint: add a new column indicating the likelihood of each response, using mapply. then convert to log and add. # if you do this correctly, the answer is -10.84249. gcm.practice.data <- data.frame(correct.response = c(T, T, T, T, F, T, T, F, T, T, T, F, F, T, T, F, T, T, T, T), gcm.probability.correct = c(0.84, 0.80, 0.84, 0.80, 0.79, 0.86, 0.89, 0.87, 0.69, 0.85, 0.75, 0.74, 0.82, 0.85, 0.87, 0.69, 0.83, 0.87, 0.80, 0.76)) # answer needed here. gcm.practice.data$likelihood<- mapply(function(x,y){ if(x==TRUE){ return(y)} else{ return(1-y)} },gcm.practice.data$correct.response,gcm.practice.data$gcm.probability.correct) sum(log(gcm.practice.data$likelihood)) #### maximum likelihood estimation #### # the same search strategies we used for parameter fitting with rmse can be used with likelihoods, # including grid search. # here are the number of correct responses each subject gave in an experiment in which they had to # decide if two images were the same or different. there were 40 trials for each subject same.diff.data <- c(32, 29, 31, 34, 26, 29, 31, 34, 29, 31, 30, 29, 31, 34, 33, 27, 32, 29, 29, 27) # we can model this experiment's data as 40 coin flips for each subject. use grid search to plot the likelihood # function for values of theta (probability of a correct response) between 0.5 and 0.9, in steps of 0.01. # start by writing a function that calculates the likelihood (not log) for the entire set of data given a value of theta. # answer needed here. likelihood<-function(th){ prod(sapply(same.diff.data,function(x){dbinom(x,40,th)})) } # then use sapply to run the function for each possible value of theta in the set. use seq() to generate the # set of possible values. plot the set of values on the x axis and the corresponding likelihoods on the y axis. # answer needed here. theta=seq(from = 0.5, to = 0.9, by = .01) likelihood.theta<-sapply(theta,likelihood) install.packages('ggplot2') library(ggplot2) plot.theta.likelihood<-data.frame(theta,likelihood.theta) ggplot(plot.theta.likelihood, aes(x=theta,y=likelihood.theta))+ geom_point() best.theta<-plot.theta.likelihood[which.max(plot.theta.likelihood$likelihood.theta),] # the "true" underlying value i used to generate the data was 0.75. does that match up with the grid search? #Yes, kind of. It got .76 as best.theta ## mle with optim() # in this section, you'll do model recovery for a descriptive model of the linear relationship # between two continuous variables. # let's assume that variable y is a linear function of variable x, such that: # y = 4 + 0.8x # create a vector of x values from 0 to 100, and the corresponding vector of y values, # then plot these with x values on the x axis, and y values on the y axis. # answer needed here. x<-seq(0:100) y<-sapply(x,function(dummy){4+0.8dummy}) plot(x,y) # now let's assume that the relationship between x and y isn't perfect. there's a bit of random # noise. add a random sample from a normal distribution with mean 0 and sd 10 to each y value. # hint: there are 101 y values, so you need 101 samples. # answer needed here. noise<-c(rnorm(101,0,10)) y.noise<- y+noise # plot the data again, with the new noisy y values. # answer needed here. plot(x,y.noise) # there are three parameter values that control this plot, # the intercept of the line: 4 # the slope of the line: 0.8 # the sd of the normal distribution: 10 # say that we observe a point of data, x = 20 and y = 27. # the linear equation, y <- 4 + 0.8x, predicts that when x is 20 y should also be 20. 4 + 0.820 # our model of this data assumes that the relationship is not perfect. # we assume that there is noise so that when x is 20, the most likely value of y should be 4 + 0.8x, # but other values of y are possible. we describe the probability of different values of y with a normal # distribution. when x is 20, then the normal distribution of y values is centered on 20, because the line # says that y is 4 + 0.8x. using the normal distribution is helpful because it gives us a way to quantify # how likely a value of 19 is compared to a value of 16, when x is 20. # here's an example x.observed <- 20 y.predicted <- 4 + 0.8x.observed # to find out the probability of y.observed=20, use dnorm() # the mean of the normal distribution should be y.predicted (the distribution is centered on the line) # and the sd of the normal is a parameter we will estimate, but for the demo below, is set to 10. y.observed <- 20 dnorm(y.observed, y.predicted, 10) # write the code to see how likely it is that y will be 33 when x is 29? (assuming sd = 10) # the correct answer is 0.03371799... # answer needed here. x.observed<-29 y.predicted <- 4 + 0.8x.observed y.observed <- 33 dnorm(y.observed, y.predicted, 10) # now generalize your solution to compute the likelihood of each value of y that you generated above. # in other words, write the code that takes a vector of x and y values, and returns the probability # of each pair given that the relationship between x and y is y <- 4 + 0.8x and the normal distribution has an sd of 10. # answer needed here. likelihood.y.observed<-mapply(function(y.o,y.p){dnorm(y.o,y.p,10)},y.noise,y) # now generalize your solution one step further. write a function that takes in a vector of parameters, # where parameters[1] is the intercept, parameters[2] is the slope, and parameters[3] is the sd of the normal, # and returns the total negative log likelihood. remember, we want the negative log likelihood because # optim() will find the set of parameters that minimizes a function. # answer needed here. negative.log.likelihood<-function(parameters){ intercept<-parameters[1] slope<-parameters[2] sd<-parameters[3] if(sd>0){ x<-seq(0:100) y.pred<-sapply(x,function(x){intercept+(slopex)}) y.obs<-y.noise gg<-data.frame(x,y.obs) likelihood.y.obs<-mapply(function(y.o,y.p){dnorm(y.o,y.p,sd)},y.obs,y.pred) return(sum(-log(likelihood.y.obs))) } else{return(NULL)} } negative.log.likelihood(c(1,2,3)) # use optim() and Nelder-Mead to search for the best fitting parameters. remember to ensure that sd > 0 # and return NA if it is not. # answer needed here. fit <- optim(c(10,.9,15), negative.log.likelihood, method="Nelder-Mead") # finally, plot the best fitting line on your points by using the abline() function, and the parameters that optim() found. # answer needed here. abline(a=fit$par[1], b=fit$par[2], col='blue')
library(testthat) library(mica) test_check("mica")	/tests/testthat.R	no_license	julia-wrobel/mica	R	false	false	52	r	library(testthat) library(mica) test_check("mica")
#Data Analysis - WATERHEMP - HPPD - 21 Days 8 cm- Dose Response - 12 UNL CRN TN - 2012/13/14 setwd("C:/Users/NECWEEDS/Documents/DATA/Tarnov/Combined") dir() library(XLConnect) library(drc) library (RODBC) ############Visual Injury Rating (IR) ########### data HPPD 3 in Post=loadWorkbook("Dataa.xlsx") # Read the data on the sheet named "Dose response 3in" Combined = readWorksheet(Post, sheet = "Dose response 3in", header = T) head (Combined) Combined #this will show data #par (mfrow=c(1, 3)) X11() plot (IR~ RateM, data = Combined,las=1, xlab = expression(paste("Herbicide (g ai ha "^"-1",")")), ylab = expression(paste("Waterhemp Control (%)")), type="none", xlim=c(0,850), ylim=c(0,100), cex.lab=1.3, font.axis=2, main="21 DAT - Waterhemp 8 cm ") fm1<-drm(IR~ RateM, fct=l4 (fixed =c(NA,0,85,NA)),data=Combined, subset = Herbicide == "Callisto") fm2<-drm(IR~ RateM, fct=l4 (fixed =c(NA,0,NA,NA)),data=Combined, subset = Herbicide == "Laudis") fm3<-drm(IR~ RateM, fct=l4 (fixed =c(-1.1,0,NA,NA)),data=Combined, subset = Herbicide == "Impact") plot(fm1, add=T,col=1,lty=1, lwd=3,pch=1, bp=0.01, xlim=c(0,850)) plot(fm2, add=T,col=2,lty=1, lwd=3,pch=2, bp=0.01, xlim=c(0,850)) plot(fm3, add=T,col=3,lty=1, lwd=3,pch=3, bp=0.01, xlim=c(0,850)) legend ("bottomright", legend= c ("Mesotrione","Tembotrione","Topramezone"), col=c(1,2,3), lty=c(1,1,1),lwd=3,pch=c(1,2,3)) summary (fm1) summary (fm2) summary (fm3) ED(fm1,c(50, 70, 90)) ED(fm2,c(50, 70, 90)) ED(fm3,c(50, 70, 90)) #################################################################################################################### #Data Analysis - WATERHEMP - HPPD - 21 Days 15 cm- Dose Response - 12 UNL CRN TN - 2012/13/14 setwd("C:/Users/NECWEEDS/Documents/DATA/Tarnov/Combined") dir() library(XLConnect) library(drc) library (RODBC) ############Visual Injury Rating (IR) ########### data HPPD 6 in Post=loadWorkbook("Dataa.xlsx") # Read the data on the sheet named "Dose response 6in" Combined = readWorksheet(Post, sheet = "Dose response 6in", header = T) head (Combined) Combined #this will show data plot (IR~ RateM, data = Combined,las=1, xlab = expression(paste("Herbicide (g ai ha "^"-1",")")), ylab = expression(paste("Waterhemp Control (%)")), type="none", xlim=c(0,850), ylim=c(0,100), cex.lab=1.3, font.axis=2, main="21 DAT - Waterhemp 15 cm ") fm4<-drm(IR~ RateM, fct=l4 (fixed =c(NA,0,95,NA)),data=Combined, subset = Herbicide == "Callisto") fm5<-drm(IR~ RateM, fct=l4 (fixed =c(NA,0,100,NA)),data=Combined, subset = Herbicide == "Laudis") fm6<-drm(IR~ RateM, fct=l4 (fixed =c(-0.9,0,NA,NA)),data=Combined, subset = Herbicide == "Impact") plot(fm4, add=T,col=1,lty=1, lwd=3,pch=1, bp=0.01, xlim=c(0,850)) plot(fm5, add=T,col=2,lty=1, lwd=3,pch=2, bp=0.01, xlim=c(0,850)) plot(fm6, add=T,col=3,lty=1, lwd=3,pch=3, bp=0.01, xlim=c(0,850)) legend ("bottomright", legend= c ("Mesotrione","Tembotrione","Topramezone"),col=c(1,2,3), lty=c(1,1,1),lwd=3,pch=c(1,2,3)) summary (fm1) summary (fm2) summary (fm3) ED(fm4,c(50, 70, 90)) ED(fm5,c(50, 70, 90)) ED(fm6,c(50, 70, 90)) ########################################################################################################################################### x11() #plot first 4 lines on Fig 1 layout(matrix(2:1, ncol = 2), widths = 1, heights = c(1.5,1.5,1), respect = F) par(mar=c(6,7,2,1), mgp=c(4.5,1,0)) plot(fm4, log="", xlim=c(0,850), bp=0.01, cex=2, cex.lab=2.5, font.axis=8, cex.axis=2.1, ylim=c(0,100), ylab=expression("Waterhemp control (%)"), xlab = expression(paste("Herbicide (g ai ha "^"-1",")")), col=1, lwd=6, pch=1) plot(fm5, add=T,col=1,cex=2, lty=2, bp=0.01, lwd=6,pch=2, xlim=c(0,850)) plot(fm6, add=T,col=1, cex=2, lty=3, bp=0.01, lwd=6,pch=3, xlim=c(0,850)) legend ("bottomright", legend=c ("B"), cex=3.0, bty="n") par(mar=c(6,7,2,1), mgp=c(4.5,1,0)) plot(fm1, log="", cex=2, xlim=c(0,850), bp=0.01, cex.lab=2.5, font.axis=8, cex.axis=2.1, ylim=c(0,100), xlab = expression(paste("Herbicide (g ai ha "^"-1",")")), ylab=expression("Waterhemp control (%)"), col=1, lwd=6, pch=1) plot(fm2, add=T,col=1,cex=2,lty=2, bp=0.01, lwd=6,pch=2, xlim=c(0,850)) plot(fm3, add=T,col=1,cex=2,lty=3, bp=0.01, lwd=6,pch=3,xlim=c(0,850)) legend (500,50, legend= c ("Mesotrione","Tembotrione","Topramezone"),col=c(1,1,1), lty=c(1,2,3),cex=2, lwd=6,pch=c(1,2,3)) legend ("bottomright", legend=c ("A"), cex=3.0, bty="n") # Biomass reduction ################################################################################################################################################### #Data Analysis - WATERHEMP - HPPD - 21 Days 15 cm- DWR - 12 UNL CRN TN - 2012/13/14 setwd("C:/Users/NECWEEDS/Documents/DATA/Tarnov/Combined") dir() library(XLConnect) library(drc) library (RODBC) ############Dry weight reduction ########### data HPPD 15 cm Post=loadWorkbook("Dataa.xlsx") # Read the data on the sheet named "Dose response 3in" Combined = readWorksheet(Post, sheet = "Dose response 3in", header = T) head (Combined) Combined #this will show data plot (IR~ RateM, data = Combined,las=1, xlab = expression(paste("Herbicide (g ai ha "^"-1",")")), ylab = expression(paste("Biomass reduction (%)")), type="none", xlim=c(0,850), ylim=c(0,100), cex.lab=1.3, font.axis=2, main="28 DAT - Waterhemp 8 cm ") fm7<-drm(DWR~ RateM, fct=l4 (fixed =c(NA,0,86,NA)),data=Combined, subset = Herbicide == "Callisto") fm8<-drm(DWR~ RateM, fct=l4 (fixed =c(-0.7,0,NA,NA)),data=Combined, subset = Herbicide == "Laudis") fm9<-drm(DWR~ RateM, fct=l4 (fixed =c(-0.9,0,NA,NA)),data=Combined, subset = Herbicide == "Impact") plot(fm7, add=T,col=1,lty=1, lwd=3,pch=1, bp=0.01, xlim=c(0,850)) plot(fm8, add=T,col=2,lty=1, lwd=3,pch=2, bp=0.01, xlim=c(0,850)) plot(fm9, add=T,col=3,lty=1, lwd=3,pch=3, bp=0.01, xlim=c(0,850)) legend ("bottomright", legend= c ("Mesotrione","Tembotrione","Topramezone"),col=c(1,2,3), lty=c(1,1,1),lwd=3,pch=c(1,2,3)) summary (fm1) summary (fm2) summary (fm3) ED(fm1,c(50, 70, 90)) ED(fm2,c(50, 70, 90)) ED(fm3,c(50, 70, 90)) ###################################################################################################################################### ########################################################################################################################################### #Data Analysis - WATERHEMP - HPPD - 21 Days 15 cm- DWR - 12 UNL CRN TN - 2012/13/14 setwd("C:/Users/NECWEEDS/Documents/DATA/Tarnov/Combined") dir() library(XLConnect) library(drc) library (RODBC) ############Dry weight reduction ########### data HPPD 15 cm Post=loadWorkbook("Dataa.xlsx") # Read the data on the sheet named "Dose response 6in" Combined = readWorksheet(Post, sheet = "Dose response 6in", header = T) head (Combined) Combined #this will show data plot (IR~ RateM, data = Combined,las=1, xlab = expression(paste("Herbicide (g ai ha "^"-1",")")), ylab = expression(paste("Biomass reduction (%)")), type="none", xlim=c(0,850), ylim=c(0,100), cex.lab=1.3, font.axis=2, main="28 DAT - Waterhemp 15 cm ") fm10<-drm(DWR~ RateM, fct=l4 (fixed =c(NA,0,100,NA)),data=Combined, subset = Herbicide == "Callisto") fm11<-drm(DWR~ RateM, fct=l4 (fixed =c(-0.6,0,NA,NA)),data=Combined, subset = Herbicide == "Laudis") fm12<-drm(DWR~ RateM, fct=l4 (fixed =c(-0.8,0,NA,NA)),data=Combined, subset = Herbicide == "Impact") plot(fm10, add=T,col=1,lty=1, lwd=3,pch=1, bp=0.01, xlim=c(0,850)) plot(fm11, add=T,col=2,lty=1, lwd=3,pch=2, bp=0.01, xlim=c(0,850)) plot(fm12, add=T,col=3,lty=1, lwd=3,pch=3, bp=0.01, xlim=c(0,850)) legend ("bottomright", legend= c ("Mesotrione","Tembotrione","Topramezone"),col=c(1,2,3), lty=c(1,1,1),lwd=3,pch=c(1,2,3)) summary (fm10) summary (fm11) summary (fm12) ED(fm10,c(50, 70, 90)) ED(fm11,c(50, 70, 90)) ED(fm12,c(50, 70, 90)) ############################################################################################################# #Combining Biomass reduction #plot first 4 lines on Fig 1 layout(matrix(2:1, ncol = 2), widths = 1, heights = c(1.5,1.5,1), respect = F) par(mar=c(6,7,2,1), mgp=c(4.5,1,0)) plot(fm10, log="", xlim=c(0,850), bp=0.01, cex=2, cex.axis=2, cex.lab=2.5, ylim=c(0,100), font.axis=8, ylab=expression("Biomass reduction (%)"), xlab = expression(paste("Herbicide (g ai ha "^"-1",")")), col=1, lwd=6, pch=1) plot(fm11, add=T,col=1,cex=2, lty=2, bp=0.01, lwd=6, pch=2, xlim=c(0,850)) plot(fm12, add=T,col=1, cex=2, lty=3, bp=0.01, lwd=6, pch=3, xlim=c(0,850)) #legend (870,20, legend= c ("Mesotrione","Tembotrione","Topramezone"),col=c(1,1,1), lty=c(1,2,3),lwd=1.5,pch=c(1,2,3)) legend ("bottomright", legend=c ("B"), cex=3, bty="n") par(mar=c(6,7,2,1), mgp=c(4.5,1,0)) plot(fm7, log="", cex=2.0, xlim=c(0,850), bp=0.01, cex.axis=2, cex.lab=2.5, ylim=c(0,100), font.axis=8, ylab="Biomass reduction (%)", xlab = expression(paste("Herbicide (g ai ha "^"-1",")")), col=1, lwd=6, pch=1) plot(fm8, add=T,col=1,cex=2,lty=2, bp=0.01, lwd=6,pch=2, xlim=c(0,850)) plot(fm9, add=T,col=1,cex=2,lty=3, bp=0.01, lwd=6,pch=3,xlim=c(0,850)) legend (500,50, legend= c ("Mesotrione","Tembotrione","Topramezone"),col=c(1,1,1), lty=c(1,2,3),cex=2, lwd=6,pch=c(1,2,3)) legend ("bottomright", legend=c ("A"), cex=3, bty="n") #############COMBINING 3"############################## X11() #plot first 4 lines on Fig 1 layout(matrix(2:1, ncol = 2), widths = 1, heights = c(1.5,1.5,1), respect = F) par(mar=c(6,7,2,1), mgp=c(4.5,1,0)) par(mar=c(6,7,2,1), mgp=c(4.5,1,0)) plot(fm7, log="", cex=2.0, xlim=c(0,850), bp=0.01, cex.axis=2, cex.lab=2.5, ylim=c(0,100), font.axis=8, ylab="Biomass reduction (%)", xlab = expression(paste("Herbicide (g ai ha "^"-1",")")), col=1, lwd=7, pch=1) plot(fm8, add=T,col=1,cex=2,lty=2, bp=0.01, lwd=7,pch=2, xlim=c(0,850)) plot(fm9, add=T,col=1,cex=2,lty=3, bp=0.01, lwd=7,pch=3,xlim=c(0,850)) legend ("bottomright", legend=c ("B"), cex=3, bty="n") par(mar=c(6,7,2,1), mgp=c(4.5,1,0)) plot(fm1, log="", cex=2, xlim=c(0,850), bp=0.01, cex.lab=2.5, font.axis=8, cex.axis=2.1, ylim=c(0,100), xlab = expression(paste("Herbicide (g ai ha "^"-1",")")), ylab=expression("Waterhemp control (%)"), col=1, lwd=7, pch=1) plot(fm2, add=T,col=1,cex=2,lty=2, bp=0.01, lwd=7,pch=2, xlim=c(0,850)) plot(fm3, add=T,col=1,cex=2,lty=3, bp=0.01, lwd=7,pch=3,xlim=c(0,850)) legend (500,50, legend= c ("Mesotrione","Tembotrione","Topramezone"),col=c(1,1,1), lty=c(1,2,3),cex=2, lwd=7,pch=c(1,2,3)) legend ("bottomright", legend=c ("A"), cex=3.0, bty="n") #############COMBINING 6"############################## x11() layout(matrix(2:1, ncol = 2), widths = 1, heights = c(1.5,1.5,1), respect = F) par(mar=c(6,7,2,1), mgp=c(4.5,1,0)) plot(fm10, log="", xlim=c(0,850), bp=0.01, cex=2, cex.axis=2, cex.lab=2.5, ylim=c(0,100), font.axis=8, ylab=expression("Biomass reduction (%)"), xlab = expression(paste("Herbicide (g ai ha "^"-1",")")), col=1, lwd=7, pch=1) plot(fm11, add=T,col=1,cex=2, lty=2, bp=0.01, lwd=7, pch=2, xlim=c(0,850)) plot(fm12, add=T,col=1, cex=2, lty=3, bp=0.01, lwd=7, pch=3, xlim=c(0,850)) legend ("bottomright", legend=c ("B"), cex=3, bty="n") plot(fm4, log="", xlim=c(0,850), bp=0.01, cex=2, cex.lab=2.5, font.axis=8, cex.axis=2.1, ylim=c(0,100), ylab=expression("Waterhemp control (%)"), xlab = expression(paste("Herbicide (g ai ha "^"-1",")")), col=1, lwd=7, pch=1) plot(fm5, add=T,col=1,cex=2, lty=2, bp=0.01, lwd=7,pch=2, xlim=c(0,850)) plot(fm6, add=T,col=1, cex=2, lty=3, bp=0.01, lwd=7,pch=3, xlim=c(0,850)) legend (500,50, legend= c ("Mesotrione","Tembotrione","Topramezone"), cex=2.0, col=c(1,1,1), lty=c(1,2,3),lwd=7,pch=c(1,2,3)) legend ("bottomright", legend=c ("A"), cex=3.0, bty="n")	/Tarnov/Combined/Commbined figures.R	no_license	Phd-data/Waterhemp-confirmation	R	false	false	12,159	r	#Data Analysis - WATERHEMP - HPPD - 21 Days 8 cm- Dose Response - 12 UNL CRN TN - 2012/13/14 setwd("C:/Users/NECWEEDS/Documents/DATA/Tarnov/Combined") dir() library(XLConnect) library(drc) library (RODBC) ############Visual Injury Rating (IR) ########### data HPPD 3 in Post=loadWorkbook("Dataa.xlsx") # Read the data on the sheet named "Dose response 3in" Combined = readWorksheet(Post, sheet = "Dose response 3in", header = T) head (Combined) Combined #this will show data #par (mfrow=c(1, 3)) X11() plot (IR~ RateM, data = Combined,las=1, xlab = expression(paste("Herbicide (g ai ha "^"-1",")")), ylab = expression(paste("Waterhemp Control (%)")), type="none", xlim=c(0,850), ylim=c(0,100), cex.lab=1.3, font.axis=2, main="21 DAT - Waterhemp 8 cm ") fm1<-drm(IR~ RateM, fct=l4 (fixed =c(NA,0,85,NA)),data=Combined, subset = Herbicide == "Callisto") fm2<-drm(IR~ RateM, fct=l4 (fixed =c(NA,0,NA,NA)),data=Combined, subset = Herbicide == "Laudis") fm3<-drm(IR~ RateM, fct=l4 (fixed =c(-1.1,0,NA,NA)),data=Combined, subset = Herbicide == "Impact") plot(fm1, add=T,col=1,lty=1, lwd=3,pch=1, bp=0.01, xlim=c(0,850)) plot(fm2, add=T,col=2,lty=1, lwd=3,pch=2, bp=0.01, xlim=c(0,850)) plot(fm3, add=T,col=3,lty=1, lwd=3,pch=3, bp=0.01, xlim=c(0,850)) legend ("bottomright", legend= c ("Mesotrione","Tembotrione","Topramezone"), col=c(1,2,3), lty=c(1,1,1),lwd=3,pch=c(1,2,3)) summary (fm1) summary (fm2) summary (fm3) ED(fm1,c(50, 70, 90)) ED(fm2,c(50, 70, 90)) ED(fm3,c(50, 70, 90)) #################################################################################################################### #Data Analysis - WATERHEMP - HPPD - 21 Days 15 cm- Dose Response - 12 UNL CRN TN - 2012/13/14 setwd("C:/Users/NECWEEDS/Documents/DATA/Tarnov/Combined") dir() library(XLConnect) library(drc) library (RODBC) ############Visual Injury Rating (IR) ########### data HPPD 6 in Post=loadWorkbook("Dataa.xlsx") # Read the data on the sheet named "Dose response 6in" Combined = readWorksheet(Post, sheet = "Dose response 6in", header = T) head (Combined) Combined #this will show data plot (IR~ RateM, data = Combined,las=1, xlab = expression(paste("Herbicide (g ai ha "^"-1",")")), ylab = expression(paste("Waterhemp Control (%)")), type="none", xlim=c(0,850), ylim=c(0,100), cex.lab=1.3, font.axis=2, main="21 DAT - Waterhemp 15 cm ") fm4<-drm(IR~ RateM, fct=l4 (fixed =c(NA,0,95,NA)),data=Combined, subset = Herbicide == "Callisto") fm5<-drm(IR~ RateM, fct=l4 (fixed =c(NA,0,100,NA)),data=Combined, subset = Herbicide == "Laudis") fm6<-drm(IR~ RateM, fct=l4 (fixed =c(-0.9,0,NA,NA)),data=Combined, subset = Herbicide == "Impact") plot(fm4, add=T,col=1,lty=1, lwd=3,pch=1, bp=0.01, xlim=c(0,850)) plot(fm5, add=T,col=2,lty=1, lwd=3,pch=2, bp=0.01, xlim=c(0,850)) plot(fm6, add=T,col=3,lty=1, lwd=3,pch=3, bp=0.01, xlim=c(0,850)) legend ("bottomright", legend= c ("Mesotrione","Tembotrione","Topramezone"),col=c(1,2,3), lty=c(1,1,1),lwd=3,pch=c(1,2,3)) summary (fm1) summary (fm2) summary (fm3) ED(fm4,c(50, 70, 90)) ED(fm5,c(50, 70, 90)) ED(fm6,c(50, 70, 90)) ########################################################################################################################################### x11() #plot first 4 lines on Fig 1 layout(matrix(2:1, ncol = 2), widths = 1, heights = c(1.5,1.5,1), respect = F) par(mar=c(6,7,2,1), mgp=c(4.5,1,0)) plot(fm4, log="", xlim=c(0,850), bp=0.01, cex=2, cex.lab=2.5, font.axis=8, cex.axis=2.1, ylim=c(0,100), ylab=expression("Waterhemp control (%)"), xlab = expression(paste("Herbicide (g ai ha "^"-1",")")), col=1, lwd=6, pch=1) plot(fm5, add=T,col=1,cex=2, lty=2, bp=0.01, lwd=6,pch=2, xlim=c(0,850)) plot(fm6, add=T,col=1, cex=2, lty=3, bp=0.01, lwd=6,pch=3, xlim=c(0,850)) legend ("bottomright", legend=c ("B"), cex=3.0, bty="n") par(mar=c(6,7,2,1), mgp=c(4.5,1,0)) plot(fm1, log="", cex=2, xlim=c(0,850), bp=0.01, cex.lab=2.5, font.axis=8, cex.axis=2.1, ylim=c(0,100), xlab = expression(paste("Herbicide (g ai ha "^"-1",")")), ylab=expression("Waterhemp control (%)"), col=1, lwd=6, pch=1) plot(fm2, add=T,col=1,cex=2,lty=2, bp=0.01, lwd=6,pch=2, xlim=c(0,850)) plot(fm3, add=T,col=1,cex=2,lty=3, bp=0.01, lwd=6,pch=3,xlim=c(0,850)) legend (500,50, legend= c ("Mesotrione","Tembotrione","Topramezone"),col=c(1,1,1), lty=c(1,2,3),cex=2, lwd=6,pch=c(1,2,3)) legend ("bottomright", legend=c ("A"), cex=3.0, bty="n") # Biomass reduction ################################################################################################################################################### #Data Analysis - WATERHEMP - HPPD - 21 Days 15 cm- DWR - 12 UNL CRN TN - 2012/13/14 setwd("C:/Users/NECWEEDS/Documents/DATA/Tarnov/Combined") dir() library(XLConnect) library(drc) library (RODBC) ############Dry weight reduction ########### data HPPD 15 cm Post=loadWorkbook("Dataa.xlsx") # Read the data on the sheet named "Dose response 3in" Combined = readWorksheet(Post, sheet = "Dose response 3in", header = T) head (Combined) Combined #this will show data plot (IR~ RateM, data = Combined,las=1, xlab = expression(paste("Herbicide (g ai ha "^"-1",")")), ylab = expression(paste("Biomass reduction (%)")), type="none", xlim=c(0,850), ylim=c(0,100), cex.lab=1.3, font.axis=2, main="28 DAT - Waterhemp 8 cm ") fm7<-drm(DWR~ RateM, fct=l4 (fixed =c(NA,0,86,NA)),data=Combined, subset = Herbicide == "Callisto") fm8<-drm(DWR~ RateM, fct=l4 (fixed =c(-0.7,0,NA,NA)),data=Combined, subset = Herbicide == "Laudis") fm9<-drm(DWR~ RateM, fct=l4 (fixed =c(-0.9,0,NA,NA)),data=Combined, subset = Herbicide == "Impact") plot(fm7, add=T,col=1,lty=1, lwd=3,pch=1, bp=0.01, xlim=c(0,850)) plot(fm8, add=T,col=2,lty=1, lwd=3,pch=2, bp=0.01, xlim=c(0,850)) plot(fm9, add=T,col=3,lty=1, lwd=3,pch=3, bp=0.01, xlim=c(0,850)) legend ("bottomright", legend= c ("Mesotrione","Tembotrione","Topramezone"),col=c(1,2,3), lty=c(1,1,1),lwd=3,pch=c(1,2,3)) summary (fm1) summary (fm2) summary (fm3) ED(fm1,c(50, 70, 90)) ED(fm2,c(50, 70, 90)) ED(fm3,c(50, 70, 90)) ###################################################################################################################################### ########################################################################################################################################### #Data Analysis - WATERHEMP - HPPD - 21 Days 15 cm- DWR - 12 UNL CRN TN - 2012/13/14 setwd("C:/Users/NECWEEDS/Documents/DATA/Tarnov/Combined") dir() library(XLConnect) library(drc) library (RODBC) ############Dry weight reduction ########### data HPPD 15 cm Post=loadWorkbook("Dataa.xlsx") # Read the data on the sheet named "Dose response 6in" Combined = readWorksheet(Post, sheet = "Dose response 6in", header = T) head (Combined) Combined #this will show data plot (IR~ RateM, data = Combined,las=1, xlab = expression(paste("Herbicide (g ai ha "^"-1",")")), ylab = expression(paste("Biomass reduction (%)")), type="none", xlim=c(0,850), ylim=c(0,100), cex.lab=1.3, font.axis=2, main="28 DAT - Waterhemp 15 cm ") fm10<-drm(DWR~ RateM, fct=l4 (fixed =c(NA,0,100,NA)),data=Combined, subset = Herbicide == "Callisto") fm11<-drm(DWR~ RateM, fct=l4 (fixed =c(-0.6,0,NA,NA)),data=Combined, subset = Herbicide == "Laudis") fm12<-drm(DWR~ RateM, fct=l4 (fixed =c(-0.8,0,NA,NA)),data=Combined, subset = Herbicide == "Impact") plot(fm10, add=T,col=1,lty=1, lwd=3,pch=1, bp=0.01, xlim=c(0,850)) plot(fm11, add=T,col=2,lty=1, lwd=3,pch=2, bp=0.01, xlim=c(0,850)) plot(fm12, add=T,col=3,lty=1, lwd=3,pch=3, bp=0.01, xlim=c(0,850)) legend ("bottomright", legend= c ("Mesotrione","Tembotrione","Topramezone"),col=c(1,2,3), lty=c(1,1,1),lwd=3,pch=c(1,2,3)) summary (fm10) summary (fm11) summary (fm12) ED(fm10,c(50, 70, 90)) ED(fm11,c(50, 70, 90)) ED(fm12,c(50, 70, 90)) ############################################################################################################# #Combining Biomass reduction #plot first 4 lines on Fig 1 layout(matrix(2:1, ncol = 2), widths = 1, heights = c(1.5,1.5,1), respect = F) par(mar=c(6,7,2,1), mgp=c(4.5,1,0)) plot(fm10, log="", xlim=c(0,850), bp=0.01, cex=2, cex.axis=2, cex.lab=2.5, ylim=c(0,100), font.axis=8, ylab=expression("Biomass reduction (%)"), xlab = expression(paste("Herbicide (g ai ha "^"-1",")")), col=1, lwd=6, pch=1) plot(fm11, add=T,col=1,cex=2, lty=2, bp=0.01, lwd=6, pch=2, xlim=c(0,850)) plot(fm12, add=T,col=1, cex=2, lty=3, bp=0.01, lwd=6, pch=3, xlim=c(0,850)) #legend (870,20, legend= c ("Mesotrione","Tembotrione","Topramezone"),col=c(1,1,1), lty=c(1,2,3),lwd=1.5,pch=c(1,2,3)) legend ("bottomright", legend=c ("B"), cex=3, bty="n") par(mar=c(6,7,2,1), mgp=c(4.5,1,0)) plot(fm7, log="", cex=2.0, xlim=c(0,850), bp=0.01, cex.axis=2, cex.lab=2.5, ylim=c(0,100), font.axis=8, ylab="Biomass reduction (%)", xlab = expression(paste("Herbicide (g ai ha "^"-1",")")), col=1, lwd=6, pch=1) plot(fm8, add=T,col=1,cex=2,lty=2, bp=0.01, lwd=6,pch=2, xlim=c(0,850)) plot(fm9, add=T,col=1,cex=2,lty=3, bp=0.01, lwd=6,pch=3,xlim=c(0,850)) legend (500,50, legend= c ("Mesotrione","Tembotrione","Topramezone"),col=c(1,1,1), lty=c(1,2,3),cex=2, lwd=6,pch=c(1,2,3)) legend ("bottomright", legend=c ("A"), cex=3, bty="n") #############COMBINING 3"############################## X11() #plot first 4 lines on Fig 1 layout(matrix(2:1, ncol = 2), widths = 1, heights = c(1.5,1.5,1), respect = F) par(mar=c(6,7,2,1), mgp=c(4.5,1,0)) par(mar=c(6,7,2,1), mgp=c(4.5,1,0)) plot(fm7, log="", cex=2.0, xlim=c(0,850), bp=0.01, cex.axis=2, cex.lab=2.5, ylim=c(0,100), font.axis=8, ylab="Biomass reduction (%)", xlab = expression(paste("Herbicide (g ai ha "^"-1",")")), col=1, lwd=7, pch=1) plot(fm8, add=T,col=1,cex=2,lty=2, bp=0.01, lwd=7,pch=2, xlim=c(0,850)) plot(fm9, add=T,col=1,cex=2,lty=3, bp=0.01, lwd=7,pch=3,xlim=c(0,850)) legend ("bottomright", legend=c ("B"), cex=3, bty="n") par(mar=c(6,7,2,1), mgp=c(4.5,1,0)) plot(fm1, log="", cex=2, xlim=c(0,850), bp=0.01, cex.lab=2.5, font.axis=8, cex.axis=2.1, ylim=c(0,100), xlab = expression(paste("Herbicide (g ai ha "^"-1",")")), ylab=expression("Waterhemp control (%)"), col=1, lwd=7, pch=1) plot(fm2, add=T,col=1,cex=2,lty=2, bp=0.01, lwd=7,pch=2, xlim=c(0,850)) plot(fm3, add=T,col=1,cex=2,lty=3, bp=0.01, lwd=7,pch=3,xlim=c(0,850)) legend (500,50, legend= c ("Mesotrione","Tembotrione","Topramezone"),col=c(1,1,1), lty=c(1,2,3),cex=2, lwd=7,pch=c(1,2,3)) legend ("bottomright", legend=c ("A"), cex=3.0, bty="n") #############COMBINING 6"############################## x11() layout(matrix(2:1, ncol = 2), widths = 1, heights = c(1.5,1.5,1), respect = F) par(mar=c(6,7,2,1), mgp=c(4.5,1,0)) plot(fm10, log="", xlim=c(0,850), bp=0.01, cex=2, cex.axis=2, cex.lab=2.5, ylim=c(0,100), font.axis=8, ylab=expression("Biomass reduction (%)"), xlab = expression(paste("Herbicide (g ai ha "^"-1",")")), col=1, lwd=7, pch=1) plot(fm11, add=T,col=1,cex=2, lty=2, bp=0.01, lwd=7, pch=2, xlim=c(0,850)) plot(fm12, add=T,col=1, cex=2, lty=3, bp=0.01, lwd=7, pch=3, xlim=c(0,850)) legend ("bottomright", legend=c ("B"), cex=3, bty="n") plot(fm4, log="", xlim=c(0,850), bp=0.01, cex=2, cex.lab=2.5, font.axis=8, cex.axis=2.1, ylim=c(0,100), ylab=expression("Waterhemp control (%)"), xlab = expression(paste("Herbicide (g ai ha "^"-1",")")), col=1, lwd=7, pch=1) plot(fm5, add=T,col=1,cex=2, lty=2, bp=0.01, lwd=7,pch=2, xlim=c(0,850)) plot(fm6, add=T,col=1, cex=2, lty=3, bp=0.01, lwd=7,pch=3, xlim=c(0,850)) legend (500,50, legend= c ("Mesotrione","Tembotrione","Topramezone"), cex=2.0, col=c(1,1,1), lty=c(1,2,3),lwd=7,pch=c(1,2,3)) legend ("bottomright", legend=c ("A"), cex=3.0, bty="n")
#' @rdname plot #' @aliases plot.cj_mm plot.cj_amce plot.cj_freqs #' @title Plot AMCE estimates, MM descriptives, and frequency plots #' @description ggplot2-based plotting of conjoint AMCEs estimates and MMs, and differences #' @param x A data frame returned from \code{\link{cj}} or \code{\link{mm}}. #' @param group Optionally a character string specifying a grouping factor. This is useful when, for example, subgroup analyses or comparing AMCEs for different outcomes. An alternative is to use \code{\link[ggplot2]{facet_wrap}} for faceted graphics. #' @param feature_headers A logical indicating whether to include headers for each feature to visually separate levels for each feature (beyond the color palette). #' @param header_fmt A character string specifying a \code{fmt} argument to \code{\link[base]{sprintf}}, which will be used when generating the feature headers (if \code{feature_headers = TRUE}). #' @param size A numeric value specifying point size in \code{\link[ggplot2]{geom_point}}. #' @param xlab A label for the x-axis #' @param ylab A label for the y-axis #' @param legend_title A character string specifying a label for the legend. #' @param legend_pos An argument forwarded to the \code{legend.position} argument in \code{\link[ggplot2]{theme}}. #' @param xlim A two-element number vector specifying limits for the x-axis. If \code{NULL}, a default value is calculated from the data. #' @param vline Optionally, a numeric value specifying an x-intercept for a vertical line. This can be useful in distinguishing the midpoint of the estimates (e.g., a zero line for AMCEs). #' @param vline_color A character string specifying a color for the \code{vline}. #' @param theme A ggplot2 theme object #' @param \dots Ignored. #' @return A ggplot2 object #' @details These are convenience functions for quickly plotting results from cregg. Because \code{plot} returns ggplot2 objects, these are easily manipulated using standard ggplot2 operations. #' #' Note that ggplot2, by default, sorts factors (like feature names here) in what might be the opposite order of what you would expect and in the opposite order that cregg functions sort their output. #' @examples #' \donttest{ #' require("ggplot2") #' # load data #' data("immigration") #' immigration$contest_no <- factor(immigration$contest_no) #' #' # calculate MMs #' d1 <- mm(immigration, ChosenImmigrant ~ Gender + Education + #' LanguageSkills + CountryOfOrigin + Job + JobExperience + #' JobPlans + ReasonForApplication + PriorEntry, id = ~ CaseID) #' #' # plot MMs #' ## simple plot #' (p <- plot(d1, vline = 0.5)) #' #' ## gridlines to aid interpretation #' p + ggplot2::theme_grey() #' #' ## monochrome bars #' p + scale_color_manual(values = rep("black", 9)) #' #' ## plot with estimates shown as text labels #' p + ggplot2::geom_text( #' aes(label = sprintf("%0.2f (%0.2f)", estimate, std.error)), #' colour = "black", position = position_nudge(y = .5) #' ) #' #' ## plot with facetting by feature #' plot(d1, feature_headers = FALSE) + #' ggplot2::facet_wrap(~feature, ncol = 1L, #' scales = "free_y", strip.position = "right") #' #' # MMs split by profile number #' stacked <- cj(immigration, ChosenImmigrant ~ Gender + #' Education + LanguageSkills + CountryOfOrigin + Job + JobExperience + #' JobPlans + ReasonForApplication + PriorEntry, id = ~ CaseID, #' estimate = "mm", by = ~ contest_no) #' #' ## plot with grouping #' plot(stacked, group = "contest_no", feature_headers = FALSE) #' #' ## plot with facetting #' plot(stacked) + ggplot2::facet_wrap(~contest_no, nrow = 1L) #' #' ## plot with shapes instead of colors for groups #' plot(stacked, group = "contest_no", vline = 0.5) + #' aes(shape = contest_no) + # map group to `shape` aesthetic #' scale_shape_manual(values=c(1, 2, 3, 4, 5)) + #' scale_colour_manual(values=rep("black", 5)) #' #' # estimate AMCEs over different subsets of data #' reasons12 <- subset( #' immigration, ReasonForApplication %in% levels(ReasonForApplication)[1:2] #' ) #' d2_1 <- cj(immigration, ChosenImmigrant ~ CountryOfOrigin, id = ~ CaseID) #' d2_2 <- cj(reasons12, ChosenImmigrant ~ CountryOfOrigin, id = ~ CaseID, #' feature_labels = list(CountryOfOrigin = "Country Of Origin")) #' d2_1$reasons <- "1,2,3" #' d2_2$reasons <- "1,2" #' plot(rbind(d2_1, d2_2), group = "reasons") #' } #' @seealso \code{\link{amce}}, \code{\link{mm}} #' @import ggplot2 #' @importFrom ggstance position_dodgev #' @import scales #' @export plot.cj_amce <- function( x, group = attr(x, "by"), feature_headers = TRUE, header_fmt = "(%s)", size = 1.0, xlab = "Estimated AMCE", ylab = "", legend_title = if (is.null(group)) "Feature" else group, legend_pos = "bottom", xlim = NULL, vline = 0, vline_color = "gray", theme = ggplot2::theme_bw(), ... ) { # optionally, add gaps between features if (isTRUE(feature_headers)) { x$level <- make_feature_headers(x, fmt = header_fmt) to_merge <- data.frame(feature = unique(x$feature), level = sprintf(header_fmt, unique(x$feature))) if ("BY" %in% names(x)) { to_merge <- do.call("rbind", lapply(unique(x[["BY"]]), function(lev) { to_merge[["BY"]] <- lev to_merge })) } else if (!is.null(group)) { to_merge <- do.call("rbind", lapply(unique(x[[group]]), function(lev) { to_merge[[group]] <- lev to_merge })) } x <- merge(x, to_merge, all = TRUE) } if (is.null(group)) { p <- ggplot2::ggplot(data = x, ggplot2::aes_string(x = "estimate", y = "level", colour = "feature")) } else { if (is.null(x[[group]])) { stop(sprintf("`group` variable '%s' not found", group)) } p <- ggplot2::ggplot(data = x, ggplot2::aes_string(x = "estimate", y = "level", colour = group, group = group)) } if (is.null(xlim)) { xmin <- min(x$lower, na.rm = TRUE) xmin <- if (xmin < 0) 1.04xmin else .96xmin xmax <- max(x$upper, na.rm = TRUE) xmax <- if (xmax > 0) 1.04xmax else .96xmax # make symmetric if (abs(xmin) > abs(xmax)) { xmax <- abs(xmin) } else { xmin <- -xmax } xlim <- c(xmin, xmax) } if (!is.null(vline)) { p <- p + ggplot2::geom_vline(xintercept = vline, colour = vline_color) } p <- p + ggplot2::geom_point(position = ggstance::position_dodgev(height = 0.75), size = size, na.rm = TRUE) + ggplot2::geom_errorbarh(ggplot2::aes_string(xmin = "lower", xmax = "upper"), size = 0.2, height = 0, na.rm = TRUE, position = ggstance::position_dodgev(height = 0.75)) if (is.null(group)) { p <- p + ggplot2::scale_colour_discrete(guide = ggplot2::guide_legend(title = legend_title)) } else { p <- p + ggplot2::scale_colour_discrete(breaks = levels(x[[group]]), labels = levels(x[[group]]), guide = ggplot2::guide_legend(title = legend_title)) } p <- p + ggplot2::scale_x_continuous(limits = xlim, oob = scales::rescale_none) + ggplot2::xlab(xlab) + ggplot2::ylab(ylab) + theme + ggplot2::theme( legend.position = legend_pos, panel.grid.major = ggplot2::element_blank(), panel.grid.minor = ggplot2::element_blank() ) + ggplot2::guides(colour = ggplot2::guide_legend(title = legend_title)) return(p) }	/R/plot_cj_amce.R	no_license	tuantx7110/cregg	R	false	false	7,739	r	#' @rdname plot #' @aliases plot.cj_mm plot.cj_amce plot.cj_freqs #' @title Plot AMCE estimates, MM descriptives, and frequency plots #' @description ggplot2-based plotting of conjoint AMCEs estimates and MMs, and differences #' @param x A data frame returned from \code{\link{cj}} or \code{\link{mm}}. #' @param group Optionally a character string specifying a grouping factor. This is useful when, for example, subgroup analyses or comparing AMCEs for different outcomes. An alternative is to use \code{\link[ggplot2]{facet_wrap}} for faceted graphics. #' @param feature_headers A logical indicating whether to include headers for each feature to visually separate levels for each feature (beyond the color palette). #' @param header_fmt A character string specifying a \code{fmt} argument to \code{\link[base]{sprintf}}, which will be used when generating the feature headers (if \code{feature_headers = TRUE}). #' @param size A numeric value specifying point size in \code{\link[ggplot2]{geom_point}}. #' @param xlab A label for the x-axis #' @param ylab A label for the y-axis #' @param legend_title A character string specifying a label for the legend. #' @param legend_pos An argument forwarded to the \code{legend.position} argument in \code{\link[ggplot2]{theme}}. #' @param xlim A two-element number vector specifying limits for the x-axis. If \code{NULL}, a default value is calculated from the data. #' @param vline Optionally, a numeric value specifying an x-intercept for a vertical line. This can be useful in distinguishing the midpoint of the estimates (e.g., a zero line for AMCEs). #' @param vline_color A character string specifying a color for the \code{vline}. #' @param theme A ggplot2 theme object #' @param \dots Ignored. #' @return A ggplot2 object #' @details These are convenience functions for quickly plotting results from cregg. Because \code{plot} returns ggplot2 objects, these are easily manipulated using standard ggplot2 operations. #' #' Note that ggplot2, by default, sorts factors (like feature names here) in what might be the opposite order of what you would expect and in the opposite order that cregg functions sort their output. #' @examples #' \donttest{ #' require("ggplot2") #' # load data #' data("immigration") #' immigration$contest_no <- factor(immigration$contest_no) #' #' # calculate MMs #' d1 <- mm(immigration, ChosenImmigrant ~ Gender + Education + #' LanguageSkills + CountryOfOrigin + Job + JobExperience + #' JobPlans + ReasonForApplication + PriorEntry, id = ~ CaseID) #' #' # plot MMs #' ## simple plot #' (p <- plot(d1, vline = 0.5)) #' #' ## gridlines to aid interpretation #' p + ggplot2::theme_grey() #' #' ## monochrome bars #' p + scale_color_manual(values = rep("black", 9)) #' #' ## plot with estimates shown as text labels #' p + ggplot2::geom_text( #' aes(label = sprintf("%0.2f (%0.2f)", estimate, std.error)), #' colour = "black", position = position_nudge(y = .5) #' ) #' #' ## plot with facetting by feature #' plot(d1, feature_headers = FALSE) + #' ggplot2::facet_wrap(~feature, ncol = 1L, #' scales = "free_y", strip.position = "right") #' #' # MMs split by profile number #' stacked <- cj(immigration, ChosenImmigrant ~ Gender + #' Education + LanguageSkills + CountryOfOrigin + Job + JobExperience + #' JobPlans + ReasonForApplication + PriorEntry, id = ~ CaseID, #' estimate = "mm", by = ~ contest_no) #' #' ## plot with grouping #' plot(stacked, group = "contest_no", feature_headers = FALSE) #' #' ## plot with facetting #' plot(stacked) + ggplot2::facet_wrap(~contest_no, nrow = 1L) #' #' ## plot with shapes instead of colors for groups #' plot(stacked, group = "contest_no", vline = 0.5) + #' aes(shape = contest_no) + # map group to `shape` aesthetic #' scale_shape_manual(values=c(1, 2, 3, 4, 5)) + #' scale_colour_manual(values=rep("black", 5)) #' #' # estimate AMCEs over different subsets of data #' reasons12 <- subset( #' immigration, ReasonForApplication %in% levels(ReasonForApplication)[1:2] #' ) #' d2_1 <- cj(immigration, ChosenImmigrant ~ CountryOfOrigin, id = ~ CaseID) #' d2_2 <- cj(reasons12, ChosenImmigrant ~ CountryOfOrigin, id = ~ CaseID, #' feature_labels = list(CountryOfOrigin = "Country Of Origin")) #' d2_1$reasons <- "1,2,3" #' d2_2$reasons <- "1,2" #' plot(rbind(d2_1, d2_2), group = "reasons") #' } #' @seealso \code{\link{amce}}, \code{\link{mm}} #' @import ggplot2 #' @importFrom ggstance position_dodgev #' @import scales #' @export plot.cj_amce <- function( x, group = attr(x, "by"), feature_headers = TRUE, header_fmt = "(%s)", size = 1.0, xlab = "Estimated AMCE", ylab = "", legend_title = if (is.null(group)) "Feature" else group, legend_pos = "bottom", xlim = NULL, vline = 0, vline_color = "gray", theme = ggplot2::theme_bw(), ... ) { # optionally, add gaps between features if (isTRUE(feature_headers)) { x$level <- make_feature_headers(x, fmt = header_fmt) to_merge <- data.frame(feature = unique(x$feature), level = sprintf(header_fmt, unique(x$feature))) if ("BY" %in% names(x)) { to_merge <- do.call("rbind", lapply(unique(x[["BY"]]), function(lev) { to_merge[["BY"]] <- lev to_merge })) } else if (!is.null(group)) { to_merge <- do.call("rbind", lapply(unique(x[[group]]), function(lev) { to_merge[[group]] <- lev to_merge })) } x <- merge(x, to_merge, all = TRUE) } if (is.null(group)) { p <- ggplot2::ggplot(data = x, ggplot2::aes_string(x = "estimate", y = "level", colour = "feature")) } else { if (is.null(x[[group]])) { stop(sprintf("`group` variable '%s' not found", group)) } p <- ggplot2::ggplot(data = x, ggplot2::aes_string(x = "estimate", y = "level", colour = group, group = group)) } if (is.null(xlim)) { xmin <- min(x$lower, na.rm = TRUE) xmin <- if (xmin < 0) 1.04xmin else .96xmin xmax <- max(x$upper, na.rm = TRUE) xmax <- if (xmax > 0) 1.04xmax else .96xmax # make symmetric if (abs(xmin) > abs(xmax)) { xmax <- abs(xmin) } else { xmin <- -xmax } xlim <- c(xmin, xmax) } if (!is.null(vline)) { p <- p + ggplot2::geom_vline(xintercept = vline, colour = vline_color) } p <- p + ggplot2::geom_point(position = ggstance::position_dodgev(height = 0.75), size = size, na.rm = TRUE) + ggplot2::geom_errorbarh(ggplot2::aes_string(xmin = "lower", xmax = "upper"), size = 0.2, height = 0, na.rm = TRUE, position = ggstance::position_dodgev(height = 0.75)) if (is.null(group)) { p <- p + ggplot2::scale_colour_discrete(guide = ggplot2::guide_legend(title = legend_title)) } else { p <- p + ggplot2::scale_colour_discrete(breaks = levels(x[[group]]), labels = levels(x[[group]]), guide = ggplot2::guide_legend(title = legend_title)) } p <- p + ggplot2::scale_x_continuous(limits = xlim, oob = scales::rescale_none) + ggplot2::xlab(xlab) + ggplot2::ylab(ylab) + theme + ggplot2::theme( legend.position = legend_pos, panel.grid.major = ggplot2::element_blank(), panel.grid.minor = ggplot2::element_blank() ) + ggplot2::guides(colour = ggplot2::guide_legend(title = legend_title)) return(p) }
c DCNF-Autarky [version 0.0.1]. c Copyright (c) 2018-2019 Swansea University. c c Input Clause Count: 16037 c Performing E1-Autarky iteration. c Remaining clauses count after E-Reduction: 16036 c c Performing E1-Autarky iteration. c Remaining clauses count after E-Reduction: 16036 c c Input Parameter (command line, file): c input filename QBFLIB/Basler/terminator/stmt21_258_360.qdimacs c output filename /tmp/dcnfAutarky.dimacs c autarky level 1 c conformity level 0 c encoding type 2 c no.of var 4836 c no.of clauses 16037 c no.of taut cls 0 c c Output Parameters: c remaining no.of clauses 16036 c c QBFLIB/Basler/terminator/stmt21_258_360.qdimacs 4836 16037 E1 [1] 0 260 4575 16036 RED	/code/dcnf-ankit-optimized/Results/QBFLIB-2018/E1/Experiments/Basler/terminator/stmt21_258_360/stmt21_258_360.R	no_license	arey0pushpa/dcnf-autarky	R	false	false	720	r	c DCNF-Autarky [version 0.0.1]. c Copyright (c) 2018-2019 Swansea University. c c Input Clause Count: 16037 c Performing E1-Autarky iteration. c Remaining clauses count after E-Reduction: 16036 c c Performing E1-Autarky iteration. c Remaining clauses count after E-Reduction: 16036 c c Input Parameter (command line, file): c input filename QBFLIB/Basler/terminator/stmt21_258_360.qdimacs c output filename /tmp/dcnfAutarky.dimacs c autarky level 1 c conformity level 0 c encoding type 2 c no.of var 4836 c no.of clauses 16037 c no.of taut cls 0 c c Output Parameters: c remaining no.of clauses 16036 c c QBFLIB/Basler/terminator/stmt21_258_360.qdimacs 4836 16037 E1 [1] 0 260 4575 16036 RED
# Paquetes ---- require(foreign) require(haven) require(ggalt) require(readxl) require(ggthemes) require(lubridate) require(plotly) require(RColorBrewer) require(ggnewscale) require(openxlsx) require(tidyverse) # Desactivar notación científica options(scipen=999) # Directorios ---- inp <- "Github/ppef_2021/01_datos/" out <- "Github/ppef_2021/03_productos/" fiuffi <- "Fuente: elaboración propia con datos de @TPresupuestaria \| @guzmart_" # Datos ---- cp_2019 <- readRDS(paste0(inp, "2019_cp_sindefl.rds")) pef_2020 <- readRDS(paste0(inp, "2020_pef_sindefl.rds")) ppef_2021 <-readRDS(paste0(inp, "2021_ppef_sindefl.rds")) tribble( ~variable_1, ~variable2, ~variable_3, ~variable_n, "margarita", "yaris", 2020, "méxico", "girasoles", "vocho", 2020, "méxico", "rosas", "tsuru", 2020, "méxico", "lavanda", "jetta", 2020, "méxico" ) deflactor_2021 <- tribble( ~año, ~def, "2000", 264.3805/100, "2001", 254.5415/100, "2002", 238.3775/100, "2003", 231.0361/100, "2004", 210.5657/100, "2005", 201.2366/100, "2006", 189.3730/100, "2007", 176.4373/100, "2008", 170.7035/100, "2009", 162.3738/100, "2010", 154.6858/100, "2011", 143.8631/100, "2012", 142.5077/100, "2013", 139.4495/100, "2014", 133.5881/100, "2015", 129.7219/100, "2016", 120.7418/100, "2017", 114.8619/100, "2018", 109.4587/100, "2019", 107.1113/100, "2020", 103.4333/100, "2021", 100.0000/100 ) deflactor_2021$def[deflactor_2021$año=="2012"] # DEFLACTAR A MANO ---- data_cp_2019 <- cp_2019 %>% # deshacerse de columnas X select(-starts_with("X")) %>% # volver minúsculas las variables rename_all(tolower) %>% # deflactar los montos mutate_at( # ¿Qué variables? vars(starts_with("monto")), # ¿Qué les hago? funs(.deflactor_2021$def[deflactor_2021$año==unique(cp_2019$CICLO)]) ) %>% mutate( # width = cuánto quieres que mida, side = de qué lado, pad = relleno id_ramo = str_pad(id_ramo, width = 2, side = "left", pad = "0") ) data_pef_2020 <- pef_2020 %>% rename_all(tolower) %>% mutate_at( vars(starts_with("monto")), funs( (.deflactor_2021$def[deflactor_2021$año=="2020"]) ) ) %>% mutate( id_ramo = str_pad(id_ramo, 2, "l", "0") ) data_ppef_2021 <- ppef_2021 %>% rename_all(tolower) %>% mutate( id_ramo = str_pad(id_ramo, 2, "l", "0") ) %>% mutate_at( vars(starts_with("monto")), funs( (as.numeric(str_remove_all(., ","))deflactor_2021$def[deflactor_2021$año=="2021"]) ) ) # DEFLACTAR CON FUNCIÓN ---- # ¿Cómo hacer más sencillo el proceso para deflactar? # ¡Con una función! nombre_de_la_función <- function(argumento_de_la_función){ "¿qué le voy a hacer al argumento?" } mi_función <- function(argumento){ print(argumento) } mi_función("Katia") mi_función_2 <- function(argumento, argumento_2){ print(paste(argumento, argumento_2)) } mi_función_2("hola", "sof") deflacta_2021 <- function(monto, ciclo){ (montodeflactor_2021$def[deflactor_2021$año==ciclo]) } deflacta_2021(monto = 500000000000, ciclo = 2013) data_cp_2019 <- cp_2019 %>% # deshacerse de columnas X select(-starts_with("X")) %>% # volver minúsculas las variables rename_all(tolower) %>% # deflactar los montos mutate_at( # ¿Qué variables? vars(starts_with("monto")), # ¿Qué les hago? funs(deflacta_2021(monto = ., ciclo = unique(cp_2019$CICLO))) ) %>% mutate( # width = cuánto quieres que mida, side = de qué lado, pad = relleno id_ramo = str_pad(id_ramo, width = 2, side = "left", pad = "0") ) data_pef_2020 <- pef_2020 %>% rename_all(tolower) %>% mutate_at( vars(starts_with("monto")), funs( deflacta_2021(monto = ., ciclo = unique(pef_2020$CICLO)) ) ) %>% mutate( id_ramo = str_pad(id_ramo, 2, "l", "0") ) data_ppef_2021 <- ppef_2021 %>% rename_all(tolower) %>% mutate( id_ramo = str_pad(id_ramo, 2, "l", "0") ) %>% mutate_at( vars(starts_with("monto")), funs( deflacta_2021(monto = as.numeric(str_remove_all(., ",")), ciclo = unique(ppef_2021$CICLO)) ) )	/20200912_02_script_ppef_2021.R	no_license	guzmart/ppef_2021	R	false	false	4,260	r	# Paquetes ---- require(foreign) require(haven) require(ggalt) require(readxl) require(ggthemes) require(lubridate) require(plotly) require(RColorBrewer) require(ggnewscale) require(openxlsx) require(tidyverse) # Desactivar notación científica options(scipen=999) # Directorios ---- inp <- "Github/ppef_2021/01_datos/" out <- "Github/ppef_2021/03_productos/" fiuffi <- "Fuente: elaboración propia con datos de @TPresupuestaria \| @guzmart_" # Datos ---- cp_2019 <- readRDS(paste0(inp, "2019_cp_sindefl.rds")) pef_2020 <- readRDS(paste0(inp, "2020_pef_sindefl.rds")) ppef_2021 <-readRDS(paste0(inp, "2021_ppef_sindefl.rds")) tribble( ~variable_1, ~variable2, ~variable_3, ~variable_n, "margarita", "yaris", 2020, "méxico", "girasoles", "vocho", 2020, "méxico", "rosas", "tsuru", 2020, "méxico", "lavanda", "jetta", 2020, "méxico" ) deflactor_2021 <- tribble( ~año, ~def, "2000", 264.3805/100, "2001", 254.5415/100, "2002", 238.3775/100, "2003", 231.0361/100, "2004", 210.5657/100, "2005", 201.2366/100, "2006", 189.3730/100, "2007", 176.4373/100, "2008", 170.7035/100, "2009", 162.3738/100, "2010", 154.6858/100, "2011", 143.8631/100, "2012", 142.5077/100, "2013", 139.4495/100, "2014", 133.5881/100, "2015", 129.7219/100, "2016", 120.7418/100, "2017", 114.8619/100, "2018", 109.4587/100, "2019", 107.1113/100, "2020", 103.4333/100, "2021", 100.0000/100 ) deflactor_2021$def[deflactor_2021$año=="2012"] # DEFLACTAR A MANO ---- data_cp_2019 <- cp_2019 %>% # deshacerse de columnas X select(-starts_with("X")) %>% # volver minúsculas las variables rename_all(tolower) %>% # deflactar los montos mutate_at( # ¿Qué variables? vars(starts_with("monto")), # ¿Qué les hago? funs(.deflactor_2021$def[deflactor_2021$año==unique(cp_2019$CICLO)]) ) %>% mutate( # width = cuánto quieres que mida, side = de qué lado, pad = relleno id_ramo = str_pad(id_ramo, width = 2, side = "left", pad = "0") ) data_pef_2020 <- pef_2020 %>% rename_all(tolower) %>% mutate_at( vars(starts_with("monto")), funs( (.deflactor_2021$def[deflactor_2021$año=="2020"]) ) ) %>% mutate( id_ramo = str_pad(id_ramo, 2, "l", "0") ) data_ppef_2021 <- ppef_2021 %>% rename_all(tolower) %>% mutate( id_ramo = str_pad(id_ramo, 2, "l", "0") ) %>% mutate_at( vars(starts_with("monto")), funs( (as.numeric(str_remove_all(., ","))deflactor_2021$def[deflactor_2021$año=="2021"]) ) ) # DEFLACTAR CON FUNCIÓN ---- # ¿Cómo hacer más sencillo el proceso para deflactar? # ¡Con una función! nombre_de_la_función <- function(argumento_de_la_función){ "¿qué le voy a hacer al argumento?" } mi_función <- function(argumento){ print(argumento) } mi_función("Katia") mi_función_2 <- function(argumento, argumento_2){ print(paste(argumento, argumento_2)) } mi_función_2("hola", "sof") deflacta_2021 <- function(monto, ciclo){ (montodeflactor_2021$def[deflactor_2021$año==ciclo]) } deflacta_2021(monto = 500000000000, ciclo = 2013) data_cp_2019 <- cp_2019 %>% # deshacerse de columnas X select(-starts_with("X")) %>% # volver minúsculas las variables rename_all(tolower) %>% # deflactar los montos mutate_at( # ¿Qué variables? vars(starts_with("monto")), # ¿Qué les hago? funs(deflacta_2021(monto = ., ciclo = unique(cp_2019$CICLO))) ) %>% mutate( # width = cuánto quieres que mida, side = de qué lado, pad = relleno id_ramo = str_pad(id_ramo, width = 2, side = "left", pad = "0") ) data_pef_2020 <- pef_2020 %>% rename_all(tolower) %>% mutate_at( vars(starts_with("monto")), funs( deflacta_2021(monto = ., ciclo = unique(pef_2020$CICLO)) ) ) %>% mutate( id_ramo = str_pad(id_ramo, 2, "l", "0") ) data_ppef_2021 <- ppef_2021 %>% rename_all(tolower) %>% mutate( id_ramo = str_pad(id_ramo, 2, "l", "0") ) %>% mutate_at( vars(starts_with("monto")), funs( deflacta_2021(monto = as.numeric(str_remove_all(., ",")), ciclo = unique(ppef_2021$CICLO)) ) )
#### Kruskal-Wallis & boxplot of fished vs. unfished Quahog Lengths #### # load packages library(plyr) library(car) # Read in data quahog_lengths <- read.csv("lengths_for_hist.csv") # subset only quonnie data quon <- subset(quahog_lengths, Pond.x == "QUON") # subset only suction quahogs quon <- subset(quon, Species == "Suction_Quahaug") # clean up quon_quahog <- quon[ rep( seq(dim(quon)[1]), quon$CountOfLength),] quon_quahog <- quon_quahog[,c(2,5,7)] colnames(quon_quahog)[3] <- "Harvest" # add legal/sub-legal column quon_quahog$Size <- "" for (i in 1:nrow(quon_quahog)) { ifelse(quon_quahog$Length[i] > 25.4, quon_quahog$Size[i] <- "Legal", quon_quahog$Size[i] <- "Sub-legal") } # Count number of legal and sublegal per station quon_count <- count(quon_quahog, vars = c("Station","Harvest","Size")) quon_count <- dcast(quon_count, Station+Harvest~Size, value.var = "freq") for (i in 3:4){quon_count[,i][is.na(quon_count[,i])] <- 0} #### LENGTH -- Statistical Analysis #### boxplot(Length ~ Harvest, data = quon_quahog) # Levene's Test leveneTest(Length ~ Harvest, data = quon_quahog) ## Not significant (p = .3381) --> K-W # Kruskal-Wallis kruskal.test(Length ~ Harvest, data = quon_quahog) # means are significant (p < 0.0001) ################################################################################## #### Fished vs. Unfished Quahog Densities #### lengths2 <- read.csv("C:/clam_suck/data/lengths_2015and2016.csv") stations <- read.csv("C:/clam_suck/data/clamsuck_dat_2015and2016.csv") a <- subset(lengths2, Species == "Suction_Quahaug") a <- a[,c(1,2,4,5,6,8,19,20)] a <- a[ rep( seq(dim(a)[1]), a$CountOfLength),] a <- count(a, vars = c("S_Date","Year","Time","Pond","Station","OLD.GridStatSample")) b <- stations[,c(6,10,28)] b <- unique(b) c <- merge(a,b, by.x = "Station", by.y = "Station", all = F) d <- merge(a,b, by.x = "OLD.GridStatSample", by.y = "OLD_StatGr", all = F) c <- c[,-c(6,8)] d <- d[,-c(6,8)] colnames(d)[1] <- "Station" c$Station <- as.character(c$Station) c <- rbind(c,d) quon_dens <- subset(c, Pond == "QUON") colnames(quon_dens)[c(6,7)] <- c("Density","Harvest") #### DENSITY -- Statistical Analysis #### boxplot(Density ~ Harvest, data = quon_dens) # Levene's Test leveneTest(Density ~ Harvest, data = quon_dens) ## Not significant (p = .5258) --> K-W # Kruskal-Wallis kruskal.test(Density ~ Harvest, data = quon_dens) ## Not Significant (p = 0.1592)	/KW_boxplot.R	no_license	whelt911/Quahog_Suction_Survey	R	false	false	2,534	r	#### Kruskal-Wallis & boxplot of fished vs. unfished Quahog Lengths #### # load packages library(plyr) library(car) # Read in data quahog_lengths <- read.csv("lengths_for_hist.csv") # subset only quonnie data quon <- subset(quahog_lengths, Pond.x == "QUON") # subset only suction quahogs quon <- subset(quon, Species == "Suction_Quahaug") # clean up quon_quahog <- quon[ rep( seq(dim(quon)[1]), quon$CountOfLength),] quon_quahog <- quon_quahog[,c(2,5,7)] colnames(quon_quahog)[3] <- "Harvest" # add legal/sub-legal column quon_quahog$Size <- "" for (i in 1:nrow(quon_quahog)) { ifelse(quon_quahog$Length[i] > 25.4, quon_quahog$Size[i] <- "Legal", quon_quahog$Size[i] <- "Sub-legal") } # Count number of legal and sublegal per station quon_count <- count(quon_quahog, vars = c("Station","Harvest","Size")) quon_count <- dcast(quon_count, Station+Harvest~Size, value.var = "freq") for (i in 3:4){quon_count[,i][is.na(quon_count[,i])] <- 0} #### LENGTH -- Statistical Analysis #### boxplot(Length ~ Harvest, data = quon_quahog) # Levene's Test leveneTest(Length ~ Harvest, data = quon_quahog) ## Not significant (p = .3381) --> K-W # Kruskal-Wallis kruskal.test(Length ~ Harvest, data = quon_quahog) # means are significant (p < 0.0001) ################################################################################## #### Fished vs. Unfished Quahog Densities #### lengths2 <- read.csv("C:/clam_suck/data/lengths_2015and2016.csv") stations <- read.csv("C:/clam_suck/data/clamsuck_dat_2015and2016.csv") a <- subset(lengths2, Species == "Suction_Quahaug") a <- a[,c(1,2,4,5,6,8,19,20)] a <- a[ rep( seq(dim(a)[1]), a$CountOfLength),] a <- count(a, vars = c("S_Date","Year","Time","Pond","Station","OLD.GridStatSample")) b <- stations[,c(6,10,28)] b <- unique(b) c <- merge(a,b, by.x = "Station", by.y = "Station", all = F) d <- merge(a,b, by.x = "OLD.GridStatSample", by.y = "OLD_StatGr", all = F) c <- c[,-c(6,8)] d <- d[,-c(6,8)] colnames(d)[1] <- "Station" c$Station <- as.character(c$Station) c <- rbind(c,d) quon_dens <- subset(c, Pond == "QUON") colnames(quon_dens)[c(6,7)] <- c("Density","Harvest") #### DENSITY -- Statistical Analysis #### boxplot(Density ~ Harvest, data = quon_dens) # Levene's Test leveneTest(Density ~ Harvest, data = quon_dens) ## Not significant (p = .5258) --> K-W # Kruskal-Wallis kruskal.test(Density ~ Harvest, data = quon_dens) ## Not Significant (p = 0.1592)
% Generated by roxygen2: do not edit by hand % Please edit documentation in R/mod_database_setup_module.R \name{db_setup_ui} \alias{db_setup_ui} \alias{db_select_logic} \alias{db_connect_logic} \title{Database Setup Module} \usage{ db_setup_ui(id) db_select_logic(input, output, session) db_connect_logic(input, output, session, db_type, db_disconnect) } \arguments{ \item{id}{The namespace id for the UI output} \item{input}{internal} \item{output}{internal} \item{session}{internal} \item{db_type}{Database type selection} \item{db_disconnect}{An Action button press} } \description{ A Shiny module to step a user through the process of selecting a database and calling the appropriate module based on selection. } \keyword{internal}	/man/mod_database_setup_module.Rd	permissive	Mwilso4/ReviewR	R	false	true	743	rd	% Generated by roxygen2: do not edit by hand % Please edit documentation in R/mod_database_setup_module.R \name{db_setup_ui} \alias{db_setup_ui} \alias{db_select_logic} \alias{db_connect_logic} \title{Database Setup Module} \usage{ db_setup_ui(id) db_select_logic(input, output, session) db_connect_logic(input, output, session, db_type, db_disconnect) } \arguments{ \item{id}{The namespace id for the UI output} \item{input}{internal} \item{output}{internal} \item{session}{internal} \item{db_type}{Database type selection} \item{db_disconnect}{An Action button press} } \description{ A Shiny module to step a user through the process of selecting a database and calling the appropriate module based on selection. } \keyword{internal}
% Generated by roxygen2: do not edit by hand % Please edit documentation in R/compute_functions.R \name{subnetworks.list} \alias{subnetworks.list} \title{Retrieves a list of subnetworks available to the specified project.} \usage{ subnetworks.list(project, region, filter = NULL, maxResults = NULL, orderBy = NULL, pageToken = NULL) } \arguments{ \item{project}{Project ID for this request} \item{region}{Name of the region scoping this request} \item{filter}{Sets a filter expression for filtering listed resources, in the form filter={expression}} \item{maxResults}{The maximum number of results per page that should be returned} \item{orderBy}{Sorts list results by a certain order} \item{pageToken}{Specifies a page token to use} } \description{ Autogenerated via \code{\link[googleAuthR]{gar_create_api_skeleton}} } \details{ Authentication scopes used by this function are: \itemize{ \item https://www.googleapis.com/auth/cloud-platform \item https://www.googleapis.com/auth/compute \item https://www.googleapis.com/auth/compute.readonly } Set \code{options(googleAuthR.scopes.selected = c(https://www.googleapis.com/auth/cloud-platform, https://www.googleapis.com/auth/compute, https://www.googleapis.com/auth/compute.readonly)} Then run \code{googleAuthR::gar_auth()} to authenticate. See \code{\link[googleAuthR]{gar_auth}} for details. } \seealso{ \href{https://developers.google.com/compute/docs/reference/latest/}{Google Documentation} }	/googlecomputealpha.auto/man/subnetworks.list.Rd	permissive	GVersteeg/autoGoogleAPI	R	false	true	1,460	rd	% Generated by roxygen2: do not edit by hand % Please edit documentation in R/compute_functions.R \name{subnetworks.list} \alias{subnetworks.list} \title{Retrieves a list of subnetworks available to the specified project.} \usage{ subnetworks.list(project, region, filter = NULL, maxResults = NULL, orderBy = NULL, pageToken = NULL) } \arguments{ \item{project}{Project ID for this request} \item{region}{Name of the region scoping this request} \item{filter}{Sets a filter expression for filtering listed resources, in the form filter={expression}} \item{maxResults}{The maximum number of results per page that should be returned} \item{orderBy}{Sorts list results by a certain order} \item{pageToken}{Specifies a page token to use} } \description{ Autogenerated via \code{\link[googleAuthR]{gar_create_api_skeleton}} } \details{ Authentication scopes used by this function are: \itemize{ \item https://www.googleapis.com/auth/cloud-platform \item https://www.googleapis.com/auth/compute \item https://www.googleapis.com/auth/compute.readonly } Set \code{options(googleAuthR.scopes.selected = c(https://www.googleapis.com/auth/cloud-platform, https://www.googleapis.com/auth/compute, https://www.googleapis.com/auth/compute.readonly)} Then run \code{googleAuthR::gar_auth()} to authenticate. See \code{\link[googleAuthR]{gar_auth}} for details. } \seealso{ \href{https://developers.google.com/compute/docs/reference/latest/}{Google Documentation} }
# random visualization test # 2021-06-14 n = 0:99 x = n %% 10 # x position on grid y = floor(n/10) # y position on grid # make 4 plots pdf(file = "~/git/misc-analyses/visualizing_randomness/block_test_various_percent.pdf", width = 8, height = 8) par(mar=c(2,2,4,2), mfrow=c(2,2)) colorset = rep("#d3c597ff",100) is_blue = sample(n,2) colorset[is_blue] = "#2aa074ff" plot(x,y, cex=3, pch=15, col=colorset, frame.plot=FALSE, axes=FALSE, main = "2 random out of 100", xlab = "", ylab = "", cex.main=2) colorset = rep("#d3c597ff",100) is_blue = sample(n,10) colorset[is_blue] = "#2aa074ff" plot(x,y, cex=3, pch=15, col=colorset, frame.plot=FALSE, axes=FALSE, main = "10 random out of 100", xlab = "", ylab = "", cex.main=2) colorset = rep("#d3c597ff",100) is_blue = sample(n,51) colorset[is_blue] = "#2aa074ff" plot(x,y, cex=3, pch=15, col=colorset, frame.plot=FALSE, axes=FALSE, main = "51 random out of 100", xlab = "", ylab = "", cex.main=2) colorset = rep("#d3c597ff",100) is_blue = sample(n,66) colorset[is_blue] = "#2aa074ff" plot(x,y, cex=3, pch=15, col=colorset, frame.plot=FALSE, axes=FALSE, main = "66 random out of 100", xlab = "", ylab = "", cex.main=2) dev.off()	/visualizing_randomness/random_visualization_test.R	no_license	wrf/misc-analyses	R	false	false	1,198	r	# random visualization test # 2021-06-14 n = 0:99 x = n %% 10 # x position on grid y = floor(n/10) # y position on grid # make 4 plots pdf(file = "~/git/misc-analyses/visualizing_randomness/block_test_various_percent.pdf", width = 8, height = 8) par(mar=c(2,2,4,2), mfrow=c(2,2)) colorset = rep("#d3c597ff",100) is_blue = sample(n,2) colorset[is_blue] = "#2aa074ff" plot(x,y, cex=3, pch=15, col=colorset, frame.plot=FALSE, axes=FALSE, main = "2 random out of 100", xlab = "", ylab = "", cex.main=2) colorset = rep("#d3c597ff",100) is_blue = sample(n,10) colorset[is_blue] = "#2aa074ff" plot(x,y, cex=3, pch=15, col=colorset, frame.plot=FALSE, axes=FALSE, main = "10 random out of 100", xlab = "", ylab = "", cex.main=2) colorset = rep("#d3c597ff",100) is_blue = sample(n,51) colorset[is_blue] = "#2aa074ff" plot(x,y, cex=3, pch=15, col=colorset, frame.plot=FALSE, axes=FALSE, main = "51 random out of 100", xlab = "", ylab = "", cex.main=2) colorset = rep("#d3c597ff",100) is_blue = sample(n,66) colorset[is_blue] = "#2aa074ff" plot(x,y, cex=3, pch=15, col=colorset, frame.plot=FALSE, axes=FALSE, main = "66 random out of 100", xlab = "", ylab = "", cex.main=2) dev.off()
# Set this path to the one that you are using #setwd("/home/student/java-eim/java-eim-parent/src/site/resources/R/dataproc/demography/") if (!"Unicode" %in% installed.packages()) install.packages("Unicode") if (!"RCurl" %in% installed.packages()) install.packages("RCurl") library("Unicode") library("RCurl") library("rstudioapi") setwd(dirname(rstudioapi::getActiveDocumentContext()$path)) # urlPrefix = "https://docs.google.com/spreadsheet/pub?key=0Asrw_" # urlKey = "eAzHG5ydGp5X014eG5LbWVyVnBocW5jUU1yZ0E" # urlSuffix = "&single=true&gid=0&output=csv" # # csvUrl <- paste0(urlPrefix,urlKey,urlSuffix) # print(paste0("Downloading from URL ", csvUrl)) # csvFile <- getURL(csvUrl, ssl.verifypeer=FALSE) # df <- read.csv(textConnection(csvFile), encoding="UTF-8") # print(paste0("Total rows read: ",nrow(df))) df <- read.table("Taut-VPd-2013-07-01.csv", header=TRUE, sep=",") zdf <- df[ order(-df[,3]/(df[,2] + df[,3]),df[,1]), ] zzdf <- zdf[ zdf[2] + zdf[3] >= 100, ] firstData <- zzdf[,3]/(zzdf[,2] + zzdf[,3]) firstLabels <- u_to_lower_case(as.vector(zzdf[,1])) png("noncit-dotplot-2013-07-01.png", width=600, height=450) dotchart(firstData,labels=firstLabels,cex=0.8, main="Nepilso\u0146u \u012Bpatsvari taut\u012Bb\u0101s", xlab="Nepilso\u0146u \u012Bpatsvars") grid() dev.off()	/age-distribution/noncit-dotplot.R	permissive	kapsitis/demografija-lv	R	false	false	1,315	r	# Set this path to the one that you are using #setwd("/home/student/java-eim/java-eim-parent/src/site/resources/R/dataproc/demography/") if (!"Unicode" %in% installed.packages()) install.packages("Unicode") if (!"RCurl" %in% installed.packages()) install.packages("RCurl") library("Unicode") library("RCurl") library("rstudioapi") setwd(dirname(rstudioapi::getActiveDocumentContext()$path)) # urlPrefix = "https://docs.google.com/spreadsheet/pub?key=0Asrw_" # urlKey = "eAzHG5ydGp5X014eG5LbWVyVnBocW5jUU1yZ0E" # urlSuffix = "&single=true&gid=0&output=csv" # # csvUrl <- paste0(urlPrefix,urlKey,urlSuffix) # print(paste0("Downloading from URL ", csvUrl)) # csvFile <- getURL(csvUrl, ssl.verifypeer=FALSE) # df <- read.csv(textConnection(csvFile), encoding="UTF-8") # print(paste0("Total rows read: ",nrow(df))) df <- read.table("Taut-VPd-2013-07-01.csv", header=TRUE, sep=",") zdf <- df[ order(-df[,3]/(df[,2] + df[,3]),df[,1]), ] zzdf <- zdf[ zdf[2] + zdf[3] >= 100, ] firstData <- zzdf[,3]/(zzdf[,2] + zzdf[,3]) firstLabels <- u_to_lower_case(as.vector(zzdf[,1])) png("noncit-dotplot-2013-07-01.png", width=600, height=450) dotchart(firstData,labels=firstLabels,cex=0.8, main="Nepilso\u0146u \u012Bpatsvari taut\u012Bb\u0101s", xlab="Nepilso\u0146u \u012Bpatsvars") grid() dev.off()
model{ for(k in 1:max(year_no)){ for(j in 1:max(season_weeks)){ #this fits the blended model to your observed data. y[k,j] ~ dnorm(mu[k,j],tau_obs) } #### Process Model for(j in 2:max(season_weeks)){ mu[k,j]~dnorm(x[k,j],tau_proc) x[k,j] <- mu[k,j-1] + yr[year_no[k]] } #Loops through number of years and defines prior for each year yr[k] ~ dnorm(0,tau_yr) mu[k,1] ~ dnorm(x_ic,tau_ic) #keep in mind you'll need to index like a matrix } #### Priors tau_proc ~ dgamma(a_proc,r_proc) tau_obs ~ dgamma(a_obs, r_obs) tau_yr ~ dgamma(0.01,0.01) }	/RCode/Jags_Models/Seasonal_for_loop/Seasonal_RandomWalk_RandomYear.R	no_license	GLEON/Bayes_forecast_WG	R	false	false	624	r	model{ for(k in 1:max(year_no)){ for(j in 1:max(season_weeks)){ #this fits the blended model to your observed data. y[k,j] ~ dnorm(mu[k,j],tau_obs) } #### Process Model for(j in 2:max(season_weeks)){ mu[k,j]~dnorm(x[k,j],tau_proc) x[k,j] <- mu[k,j-1] + yr[year_no[k]] } #Loops through number of years and defines prior for each year yr[k] ~ dnorm(0,tau_yr) mu[k,1] ~ dnorm(x_ic,tau_ic) #keep in mind you'll need to index like a matrix } #### Priors tau_proc ~ dgamma(a_proc,r_proc) tau_obs ~ dgamma(a_obs, r_obs) tau_yr ~ dgamma(0.01,0.01) }
% Generated by roxygen2: do not edit by hand % Please edit documentation in R/paws.medialive_operations.R \name{create_tags} \alias{create_tags} \title{Create tags for a resource} \usage{ create_tags(ResourceArn, Tags = NULL) } \arguments{ \item{ResourceArn}{[required]} \item{Tags}{} } \description{ Create tags for a resource } \section{Accepted Parameters}{ \preformatted{create_tags( ResourceArn = "string", Tags = list( "string" ) ) } }	/service/paws.medialive/man/create_tags.Rd	permissive	CR-Mercado/paws	R	false	true	454	rd	% Generated by roxygen2: do not edit by hand % Please edit documentation in R/paws.medialive_operations.R \name{create_tags} \alias{create_tags} \title{Create tags for a resource} \usage{ create_tags(ResourceArn, Tags = NULL) } \arguments{ \item{ResourceArn}{[required]} \item{Tags}{} } \description{ Create tags for a resource } \section{Accepted Parameters}{ \preformatted{create_tags( ResourceArn = "string", Tags = list( "string" ) ) } }
library(withr) library(magrittr) library(MASS) library(dplyr) library(ggplot2) library(latex2exp) text <- data.frame( x = rep(c(1, -1, -1, 1), 2), y = c(1.2, 1.2, -0.7, -0.7, 0.7, 0.7, -1.2, -1.2), text = c("A", "B", "C", "D", TeX("$(x > \\bar{x}) \\bigcap (y > \\bar{y})$", output = "character"), TeX("$(x < \\bar{x}) \\bigcap (y > \\bar{y})$", output = "character"), TeX("$(x < \\bar{x}) \\bigcap (y < \\bar{y})$", output = "character"), TeX("$(x > \\bar{x}) \\bigcap (y < \\bar{y})$", output = "character")), colour = rep(c("red", "blue"),4) ) with_seed(721, MASS::mvrnorm(n = 30, mu = c(0, 0), Sigma = matrix(c(1, 0.9, 0.9, 1), ncol = 2), empirical = TRUE)) %>% as.data.frame() %>% rename(x = 1, y = 2) %$% { ggplot(data = NULL) + aes(x = x, y = y) + geom_point(alpha = 0.5) + geom_vline(xintercept = mean(x), linetype = 2) + geom_hline(yintercept = mean(y), linetype = 2) + scale_x_continuous(breaks = c(-1, 0, 1), labels = c("-", expression(bar(x)), "+")) + scale_y_continuous(breaks = c(-1, 0, 1), labels = c("-", expression(bar(y)), "+")) + geom_text(data = text, aes(x = x, y = y, label = text, colour = colour), size = 10, parse = TRUE, show.legend = FALSE) + theme_classic(base_size = 20) }	/Lecture-11/figure/fig-11-03.R	no_license	jirou7800/Statistics_YNU2020_exercise	R	false	false	1,540	r	library(withr) library(magrittr) library(MASS) library(dplyr) library(ggplot2) library(latex2exp) text <- data.frame( x = rep(c(1, -1, -1, 1), 2), y = c(1.2, 1.2, -0.7, -0.7, 0.7, 0.7, -1.2, -1.2), text = c("A", "B", "C", "D", TeX("$(x > \\bar{x}) \\bigcap (y > \\bar{y})$", output = "character"), TeX("$(x < \\bar{x}) \\bigcap (y > \\bar{y})$", output = "character"), TeX("$(x < \\bar{x}) \\bigcap (y < \\bar{y})$", output = "character"), TeX("$(x > \\bar{x}) \\bigcap (y < \\bar{y})$", output = "character")), colour = rep(c("red", "blue"),4) ) with_seed(721, MASS::mvrnorm(n = 30, mu = c(0, 0), Sigma = matrix(c(1, 0.9, 0.9, 1), ncol = 2), empirical = TRUE)) %>% as.data.frame() %>% rename(x = 1, y = 2) %$% { ggplot(data = NULL) + aes(x = x, y = y) + geom_point(alpha = 0.5) + geom_vline(xintercept = mean(x), linetype = 2) + geom_hline(yintercept = mean(y), linetype = 2) + scale_x_continuous(breaks = c(-1, 0, 1), labels = c("-", expression(bar(x)), "+")) + scale_y_continuous(breaks = c(-1, 0, 1), labels = c("-", expression(bar(y)), "+")) + geom_text(data = text, aes(x = x, y = y, label = text, colour = colour), size = 10, parse = TRUE, show.legend = FALSE) + theme_classic(base_size = 20) }
% Generated by roxygen2: do not edit by hand % Please edit documentation in R/latest_quarter.R \name{latest_quarter} \alias{latest_quarter} \title{Returns name of latest quarter, for within the bulletin.} \usage{ latest_quarter() } \description{ Returns name of latest quarter, for within the bulletin. }	/man/latest_quarter.Rd	no_license	moj-analytical-services/kpow	R	false	true	305	rd	% Generated by roxygen2: do not edit by hand % Please edit documentation in R/latest_quarter.R \name{latest_quarter} \alias{latest_quarter} \title{Returns name of latest quarter, for within the bulletin.} \usage{ latest_quarter() } \description{ Returns name of latest quarter, for within the bulletin. }
library(tidyverse) library(zoo) library(purrr) source("Rscripts/baseRscript.R") HCVFiles3<-list.files("Output1A/Overview3/",pattern="overview3.csv") # #### read the filtered MF files from 10.1.2 TsMutFreq <-read.csv("Output1A/MutFreq.filtered/Filtered.Ts.Q35.csv",stringsAsFactors = F,row.names=1) Tv1.MutFreq<-read.csv("Output1A/MutFreq.filtered/Filtered.Tv1.MutFreq.Q35.csv",stringsAsFactors = F,row.names=1) Tv2.MutFreq<-read.csv("Output1A/MutFreq.filtered/Filtered.Tv2.MutFreq.Q35.csv",stringsAsFactors = F,row.names=1) Tvs.MutFreq<-read.csv("Output1A/MutFreq.filtered/Filtered.Tvs.MutFreq.Q35.csv",stringsAsFactors = F,row.names=1) AllMutFreq <-read.csv("Output1A/MutFreq.filtered/Filtered.AllMutFreq.Q35.csv", stringsAsFactors = F,row.names=1) mf.files<-list() mf.files[[1]]<-TsMutFreq mf.files[[2]]<-Tv1.MutFreq mf.files[[3]]<-Tv2.MutFreq mf.files[[4]]<-Tvs.MutFreq mf.files[[5]]<-AllMutFreq names(mf.files)[1]<-"TransMutFreq" names(mf.files)[2]<-"Tv1.MutFreq" names(mf.files)[3]<-"Tv2.MutFreq" names(mf.files)[4]<-"Tvs.MutFreq" names(mf.files)[5]<-"AllMutFreq" s<-length(HCVFiles3) #### 1) Transition Mutations (mean) # 1.1) Summary Ts<-mf.files[[1]] Ts<-Ts[Ts$pos>=342, ] mean(Ts$mean[Ts$Type=="syn"]) #0.008093379 mean(Ts$mean[Ts$Type=="nonsyn"]) #0.003348242 mean(Ts$mean[Ts$Type=="stop"]) #0.002022381 table(Ts$Type) #nonsyn stop syn # 5193 220 2545 std.error(Ts$mean[Ts$Type=="syn"]) #9.066418e-05 std.error(Ts$mean[Ts$Type=="nonsyn"]) # 2.768315e-05 std.error(Ts$mean[Ts$Type=="stop"]) # 9.204526e-05 r1<-wilcox.test(Ts$mean[Ts$Type=="syn"], Ts$mean[Ts$Type=="nonsyn"], alternative = "greater", paired = FALSE) r2<-wilcox.test(Ts$mean[Ts$Type=="nonsyn"], Ts$mean[Ts$Type=="stop"], alternative = "greater", paired = FALSE) r1[[3]] #P=0 r2[[3]] #P= 1.933446e-41 #CpG creating vs Non-CpG creating T2<-Ts[Ts$ref=="a"\|Ts$ref=="t",] r3<-wilcox.test(T2$mean[T2$Type=="syn"&T2$makesCpG==0], T2$mean[T2$Type=="syn"&T2$makesCpG==1], alternative = "greater", paired = FALSE) r4<-wilcox.test(T2$mean[T2$Type=="nonsyn"&T2$makesCpG==0], T2$mean[T2$Type=="nonsyn"&T2$makesCpG==1], alternative = "greater", paired = FALSE) r3[[3]] #P=0.005231179 r4[[3]] #P=3.893716e-12 ################## # 1.2) run Wilcoxin Test on means based on mutation types WilcoxTest.results.nt<-data.frame(matrix(ncol=3,nrow=6)) colnames(WilcoxTest.results.nt)<-c("nt","test","P.value") # 1) transition Mutations, using 'mean' dat<-mf_files[[1]] #dat<-TransMutFreq_filtered dat<-dat[dat$pos>=342, ] which(is.na(dat$freq.Ts)) dat<-dat[1:8236, ]#7895 ty<-which(colnames(dat)=="Type");fname="Transition" m<-data.frame() se<-data.frame() m_CpG<-data.frame() se_CpG<-data.frame() m_nonCpG<-data.frame() se_nonCpG<-data.frame() table(dat$ref) #a c g t #1556 2431 2310 1661 for (typeofsite in c("syn", "nonsyn","stop")){ for (wtnt in c("a", "t", "c", "g")){ mutrate<- dat$mean[dat[,ty]==typeofsite & dat$ref==wtnt] m[typeofsite,wtnt]<-mean(mutrate[!is.na(mutrate)]) se[typeofsite,wtnt]<-std.error(mutrate[!is.na(mutrate)]) m_NonCpG<-dat$mean[dat$Type==typeofsite & dat$ref==wtnt & dat$makesCpG==0] m_nonCpG[typeofsite,wtnt]<-mean(m_NonCpG[!is.na(m_NonCpG)]) se_nonCpG[typeofsite,wtnt]<-std.error(m_NonCpG[!is.na(m_NonCpG)]) mu_CpG<-dat$mean[dat$Type==typeofsite & dat$ref==wtnt & dat$makesCpG==1] m_CpG[typeofsite,wtnt]<-mean(mu_CpG[!is.na(mu_CpG)]) se_CpG[typeofsite,wtnt]<-std.error(mu_CpG[!is.na(mu_CpG)]) vectorname<-paste0(typeofsite,"_",wtnt) assign(vectorname, mutrate) vname1<<-paste0(typeofsite,"_",wtnt,"_noncpg") assign(vname1, m_NonCpG) vname2<<-paste0(typeofsite,"_",wtnt,"_cpg") assign(vname2, mu_CpG) } } #rownames(m)<-c("syn","nonsyn","stop") rownames(se)<-c("syn_se","nonsyn_se","stop_se") rownames(m_nonCpG)<-c("syn_noncpg","nonsyn_noncpg","stop_noncpg") rownames(se_nonCpG)<-c("syn_noncpg_se","nonsyn_noncpg_se","stop_noncpg_se") rownames(m_CpG)<-c("syn_cpg","nonsyn_cpg","stop_cpg") rownames(se_CpG)<-c("syn_cpg_se","nonsyn_cpg_se","stop_cpg_se") MFbyType<-rbind(m,se,m_nonCpG,se_nonCpG,m_CpG,se_CpG) MFbyType2<-t(MFbyType) MFbyType2<-data.frame(MFbyType2) write.csv(MFbyType2,"Output1A/SummaryStats/TransitionMF_byNt_byType_mean.csv") #run Wilcoxin Test for (i in c("a","t","c","g")) { if (i=="a"\|i=="t"){ syncpg<-get(paste0("syn_",i,"_cpg")) synnoncpg<-get(paste0("syn_",i,"_noncpg")) nonsyncpg<-get(paste0("nonsyn_",i,"_cpg")) nonsynnoncpg<-get(paste0("nonsyn_",i,"_noncpg")) if (i=="a"){ result1<-wilcox.test(syncpg, synnoncpg, alternative = "less", paired = FALSE) result2<-wilcox.test(nonsyncpg,nonsynnoncpg,alternative = "less", paired = FALSE) for (r in 1:2){ result<-get(paste0('result',r)) WilcoxTest.results.nt$nt[r]<-i WilcoxTest.results.nt$test[r]<-result[[7]] WilcoxTest.results.nt$P.value[r]<-result[[3]]} } if (i=="t"){ result3<-wilcox.test(syncpg, synnoncpg, alternative = "less", paired = FALSE) result4<-wilcox.test(nonsyncpg,nonsynnoncpg,alternative = "less", paired = FALSE) for (r in 3:4){ result<-get(paste0('result',r)) WilcoxTest.results.nt$nt[r]<-i WilcoxTest.results.nt$test[r]<-result[[7]] WilcoxTest.results.nt$P.value[r]<-result[[3]]} } } else { synnoncpg<-get(paste0("syn_",i,"_noncpg")) nonsynnoncpg<-get(paste0("nonsyn_",i,"_noncpg")) if (i =="c") { result5<-wilcox.test(synnoncpg,nonsynnoncpg, alternative = "greater", paired = FALSE) WilcoxTest.results.nt$nt[5]<-i WilcoxTest.results.nt$test[5]<-result5[[7]] WilcoxTest.results.nt$P.value[5]<-result5[[3]] } if (i =="g") { result6<-wilcox.test(synnoncpg,nonsynnoncpg, alternative = "greater", paired = FALSE) WilcoxTest.results.nt$nt[6]<-i WilcoxTest.results.nt$test[6]<-result6[[7]] WilcoxTest.results.nt$P.value[6]<-result6[[3]] } } } write.csv(WilcoxTest.results.nt,paste0("Output1A/SummaryStats/WilcoxTestResults_Ts_eachNT_mean.csv")) al<-mf.files[[5]] mean(al$mean) #0.005771959 tvs<-mf.files[[4]] tvs<-tvs[tvs$pos>=342,] mean(tvs$mean) #0.0009650088 # 2) Transversion with mean ### ## 2.1) Summary Stats Tv1<-mf.files[[2]] Tv1<-Tv1[Tv1$pos>=342, ] Tv2<-mf.files[[3]] Tv2<-Tv2[Tv2$pos>=342, ] All<-c(Tv1$mean,Tv2$mean) #0.0004825044 Syn<-c(Tv1$mean[Tv1$Type.tv1=="syn"],Tv2$mean[Tv2$Type.tv2=="syn"]) Nonsyn <- c(Tv1$mean[Tv1$Type.tv1=="nonsyn"],Tv2$mean[Tv2$Type.tv2=="nonsyn"]) Stop <- c(Tv1$mean[Tv1$Type.tv1=="stop"],Tv2$mean[Tv2$Type.tv2=="stop"]) mean(All) #0.0004825044 mean(Syn) #0.0007535948 mean(Nonsyn) #0.0004099817 mean(Stop) #0.0005612278 c(length(Nonsyn),length(Stop),length(Syn)) #nonsyn stop syn # 12184 625 3107 std.error(Syn) # 1.508687e-05 std.error(Nonsyn) # 4.921358e-06 std.error(Stop) # 1.833373e-05 r1<-wilcox.test(Syn, Nonsyn, alternative = "greater", paired = FALSE) r2<-wilcox.test(Nonsyn, Stop, alternative = "greater", paired = FALSE) wilcox.test(Nonsyn, Stop, alternative = "less", paired = FALSE) r1[[3]] #2.811567e-175 r2[[3]] #1 Syncpg<-c(Tv1$mean[Tv1$Type.tv1=="syn"&Tv1$makesCpG.tv1==1],Tv2$mean[Tv2$Type.tv2=="syn"&Tv2$makesCpG.tv2==1]) SynNoncpg<-c(Tv1$mean[Tv1$Type.tv1=="syn"&Tv1$makesCpG.tv1==0],Tv2$mean[Tv2$Type.tv2=="syn"&Tv2$makesCpG.tv2==0]) Nonsyncpg <- c(Tv1$mean[Tv1$Type.tv1=="nonsyn"&Tv1$makesCpG.tv1==1],Tv2$mean[Tv2$Type.tv2=="nonsyn"&Tv2$makesCpG.tv2==1]) NNcpg <- c(Tv1$mean[Tv1$Type.tv1=="nonsyn"&Tv1$makesCpG.tv1==0],Tv2$mean[Tv2$Type.tv2=="nonsyn"&Tv2$makesCpG.tv2==0]) r3<-wilcox.test(SynNoncpg,Syncpg, alternative = "greater", paired = FALSE) r4<-wilcox.test(NNcpg,Nonsyncpg, alternative = "greater", paired = FALSE) r3[[3]] #[1] 5.038601e-143 r4[[3]] #[1] 1.390009e-237 ## 2.2) Run Wilcoxon test on each NT, transversion dat1<-mf_filtered[[2]] dat1<-dat1[dat1$pos>=342, ] dat2<-mf_filtered[[3]] dat2<-dat2[dat2$pos>=342, ] m<-data.frame() se<-data.frame() m_nonCpG<-data.frame() se_nonCpG<-data.frame() mr_CpG<-data.frame() se_CpG<-data.frame() for (typeofsite in c("syn", "nonsyn","stop")){ for (wtnt in c("a", "t", "c", "g")){ mr1<- dat1$mean[dat1$Type.tv1==typeofsite & dat1$ref==wtnt] mr2<- dat2$mean[dat2$Type.tv2==typeofsite & dat1$ref==wtnt] m_NonCpG1<-dat1$mean[dat1$Type.tv1==typeofsite & dat1$ref==wtnt & dat1$makesCpG.tv1==0] m_NonCpG2<-dat2$mean[dat2$Type.tv2==typeofsite & dat2$ref==wtnt & dat2$makesCpG.tv2==0] m_CpG1<-dat1$mean[dat1$Type.tv1==typeofsite & dat1$ref==wtnt & dat1$makesCpG.tv1==1] m_CpG2<-dat2$mean[dat2$Type.tv2==typeofsite & dat2$ref==wtnt & dat2$makesCpG.tv2==1] mr<-c(mr1,mr2) m_NonCpG<-c(m_NonCpG1,m_NonCpG2) m_CpG<-c(m_CpG1,m_CpG2) m[typeofsite,wtnt]<-mean(mr[!is.na(mr)]) se[typeofsite,wtnt]<-std.error(mr[!is.na(mr)]) m_nonCpG[typeofsite,wtnt]<-mean(m_NonCpG[!is.na(m_NonCpG)]) se_nonCpG[typeofsite,wtnt]<-std.error(m_NonCpG[!is.na(m_NonCpG)]) mr_CpG[typeofsite,wtnt]<-mean(m_CpG[!is.na(m_CpG)]) se_CpG[typeofsite,wtnt]<-std.error(m_CpG[!is.na(m_CpG)]) vectorname<-paste0(typeofsite,"_",wtnt) assign(vectorname, mr) vname1<<-paste0(typeofsite,"_",wtnt,"_noncpg") assign(vname1, m_NonCpG) vname2<<-paste0(typeofsite,"_",wtnt,"_cpg") assign(vname2, m_CpG) } } rownames(se)<-c("syn_se","nonsyn_se","stop_se") rownames(m_nonCpG)<-c("syn_noncpg","nonsyn_noncpg","stop_noncpg") rownames(se_nonCpG)<-c("syn_noncpg_se","nonsyn_noncpg_se","stop_noncpg_se") rownames(mr_CpG)<-c("syn_cpg","nonsyn_cpg","stop_cpg") rownames(se_CpG)<-c("syn_cpg_se","nonsyn_cpg_se","stop_cpg_se") MFbyType.tv<-rbind(m,se,mr_CpG,se_CpG,m_nonCpG,se_nonCpG) MFbyType.tv2<-t(MFbyType.tv) write.csv(MFbyType.tv2,paste0("Output1A/SummaryStats/Transversion_MF_byNt_byType_mean.csv")) # CpG vs nonCpG WilcoxTest.results.nt.tv<-data.frame(matrix(ncol=3,nrow=8)) colnames(WilcoxTest.results.nt.tv)<-c("nt","test","P.value") for (i in c("a","t","c","g")) { syncpg<-get(paste0("syn_",i,"_cpg")) synnoncpg<-get(paste0("syn_",i,"_noncpg")) nonsyncpg<-get(paste0("nonsyn_",i,"_cpg")) nonsynnoncpg<-get(paste0("nonsyn_",i,"_noncpg")) if (i=="a"){ if (length(syncpg)==0) next else{result1<-wilcox.test(syncpg, synnoncpg, alternative = "less", paired = FALSE) result2<-wilcox.test(nonsyncpg,nonsynnoncpg,alternative = "less", paired = FALSE) for (r in 1:2){ result<-get(paste0('result',r)) WilcoxTest.results.nt.tv$nt[r]<-i WilcoxTest.results.nt.tv$test[r]<-result[[7]] WilcoxTest.results.nt.tv$P.value[r]<-result[[3]]} }} if (i=="t"){ if (length(syncpg)==0) next else{ result3<-wilcox.test(syncpg, synnoncpg, alternative = "less", paired = FALSE) result4<-wilcox.test(nonsyncpg,nonsynnoncpg,alternative = "less", paired = FALSE) for (r in 3:4){ result<-get(paste0('result',r)) WilcoxTest.results.nt.tv$nt[r]<-i WilcoxTest.results.nt.tv$test[r]<-result[[7]] WilcoxTest.results.nt.tv$P.value[r]<-result[[3]]} }} if (i=="c"){ if (length(syncpg)==0) next else{ result5<-wilcox.test(syncpg, synnoncpg, alternative = "less", paired = FALSE) result6<-wilcox.test(nonsyncpg,nonsynnoncpg,alternative = "less", paired = FALSE) for (r in 5:6){ result<-get(paste0('result',r)) WilcoxTest.results.nt.tv$nt[r]<-i WilcoxTest.results.nt.tv$test[r]<-result[[7]] WilcoxTest.results.nt.tv$P.value[r]<-result[[3]]} }} if (i=="g"){ if (length(syncpg)==0) next else{ result7<-wilcox.test(syncpg, synnoncpg, alternative = "less", paired = FALSE) result8<-wilcox.test(nonsyncpg,nonsynnoncpg,alternative = "less", paired = FALSE) for (r in 7:8){ result<-get(paste0('result',r)) WilcoxTest.results.nt.tv$nt[r]<-i WilcoxTest.results.nt.tv$test[r]<-result[[7]] WilcoxTest.results.nt.tv$P.value[r]<-result[[3]]} }} } write.csv(WilcoxTest.results.nt.tv,paste0("Output1A/SummaryStats/WilcoxTestResults_TV_eachNT_mean.csv")) ##################### ## Not sure if we need to run these: # 3) use all data to create summary / run Wilcoxon Test (using all values,not just the mean of 195 files) on Transition source("Rscripts/MutationFreqSum.filtered.R") ##3.1 Transition nuc.mf2<-data.frame("s.cpg"=matrix(nrow=4)) rownames(nuc.mf2)<-c("a","t","c","g") WilcoxTest.nt.mf2<-data.frame(matrix(ncol=3,nrow=6)) colnames(WilcoxTest.nt.mf2)<-c("nt","test","P.value") k=1 for (i in c("A","T","C","G")) { if (i=="A"\|i=="T"){ syncpg1<-get(paste0(i,"_syn_cpg")) synnoncpg1<-get(paste0(i,"_syn_noncpg")) nonsyncpg1<-get(paste0(i,"_nonsyn_cpg")) nonsynnoncpg1<-get(paste0(i,"_nonsyn_noncpg")) nuc.mf2$s.cpg[k]<-mean(syncpg1, na.rm=T) nuc.mf2$s.cpg.se[k]<-std.error(syncpg1, na.rm=T) nuc.mf2$s.ncpg[k]<-mean(synnoncpg1, na.rm=T) nuc.mf2$s.ncpg.se[k]<-std.error(synnoncpg1, na.rm=T) nuc.mf2$ns.cpg[k]<-mean(nonsyncpg1, na.rm=T) nuc.mf2$ns.cpg.se[k]<-std.error(nonsyncpg1, na.rm=T) nuc.mf2$ns.ncpg[k]<-mean(nonsynnoncpg1, na.rm=T) nuc.mf2$ns.ncpg.se[k]<-std.error(nonsynnoncpg1, na.rm=T) #nuc.mf2$stop.ncpg[k]<-NA #nuc.mf2$stop.ncpg.se[k]<-NA if (i=="A"){ result1<-wilcox.test(syncpg1, synnoncpg1, alternative = "less", paired = FALSE) result2<-wilcox.test(nonsyncpg1,nonsynnoncpg1,alternative = "less", paired = FALSE) for (r in 1:2){ result<-get(paste0('result',r)) WilcoxTest.nt.mf2$nt[r]<-i WilcoxTest.nt.mf2$test[r]<-result[[7]] WilcoxTest.nt.mf2$P.value[r]<-result[[3]]} } if (i=="T"){ result3<-wilcox.test(syncpg1, synnoncpg1, alternative = "less", paired = FALSE) result4<-wilcox.test(nonsyncpg1,nonsynnoncpg1,alternative = "less", paired = FALSE) for (r in 3:4){ result<-get(paste0('result',r)) WilcoxTest.nt.mf2$nt[r]<-i WilcoxTest.nt.mf2$test[r]<-result[[7]] WilcoxTest.nt.mf2$P.value[r]<-result[[3]]} } } else { synnoncpg1<-get(paste0(i,"_syn_noncpg")) nonsynnoncpg1<-get(paste0(i,"_nonsyn_noncpg")) nuc.mf2$s.cpg[k]<-NA nuc.mf2$s.cpg.se[k]<-NA nuc.mf2$s.ncpg[k]<-mean(synnoncpg1, na.rm=T) nuc.mf2$s.ncpg.se[k]<-std.error(synnoncpg1, na.rm=T) nuc.mf2$ns.cpg[k]<-NA nuc.mf2$ns.cpg.se[k]<-NA nuc.mf2$ns.ncpg[k]<-mean(nonsynnoncpg1, na.rm=T) nuc.mf2$ns.ncpg.se[k]<-std.error(nonsynnoncpg1, na.rm=T) if (i =="C") { result5<-wilcox.test(synnoncpg1,nonsynnoncpg1, alternative = "greater", paired = FALSE) WilcoxTest.nt.mf2$nt[5]<-i WilcoxTest.nt.mf2$test[5]<-result5[[7]] WilcoxTest.nt.mf2$P.value[5]<-result5[[3]] } if (i =="G") { result6<-wilcox.test(synnoncpg1,nonsynnoncpg1, alternative = "greater", paired = FALSE) WilcoxTest.nt.mf2$nt[6]<-i WilcoxTest.nt.mf2$test[6]<-result6[[7]] WilcoxTest.nt.mf2$P.value[6]<-result6[[3]] } } k=k+1 } write.csv(WilcoxTest.nt.mf2,paste0("Output/SummaryStats/WilcoxTestResults_Transition_eachNT_all.csv")) write.csv(nuc.mf2,paste0("Output/SummaryStats/TransitionMF_byNT_byType_all.csv")) wilcoxtest2<-data.frame("test"=matrix(nrow=4)) Typelist2<-list() syn_all<-c(A_syn,T_syn,C_syn,G_syn) Typelist2[[1]]<-syn_all; names(Typelist2)[1]<-"syn_all" nonsyn_all<-c(A_nonsyn,T_nonsyn,C_nonsyn,G_nonsyn) Typelist2[[2]]<-nonsyn_all; names(Typelist2)[2]<-"nonsyn_all" stop_all<-c(A_stop,T_stop,C_stop,G_stop) Typelist2[[3]]<-stop_all; names(Typelist2)[3]<-"stop_all" syn_allCpG<-c(A_syn_cpg,T_syn_cpg) Typelist2[[4]]<-syn_allCpG; names(Typelist2)[4]<-"syn_allCpG" syn_allnonCpG<-c(A_syn_noncpg,T_syn_noncpg) Typelist2[[5]]<-syn_allnonCpG; names(Typelist2)[5]<-"syn_allnonCpG" nonsyn_allCpG<-c(A_nonsyn_cpg,T_nonsyn_cpg) Typelist2[[6]]<-nonsyn_allCpG; names(Typelist2)[6]<-"nonsyn_allCpG" nonsyn_allnonCpG<-c(A_nonsyn_noncpg,T_nonsyn_noncpg) Typelist2[[7]]<-nonsyn_allnonCpG; names(Typelist2)[7]<-"nonsyn_allnonCpG" re1<-wilcox.test(syn_all,nonsyn_all, alternative = "greater", paired = FALSE) wilcoxtest2$test[1]<-re1[[7]] wilcoxtest2$P.value[1]<-re1[[3]] re2<-wilcox.test(nonsyn_all,stop_all, alternative = "greater", paired = FALSE) wilcoxtest2$test[2]<-re2[[7]] wilcoxtest2$P.value[2]<-re2[[3]] re3<-wilcox.test(syn_allCpG,syn_allnonCpG, alternative = "less", paired = FALSE) wilcoxtest2$test[3]<-re3[[7]] wilcoxtest2$P.value[3]<-re3[[3]] re4<-wilcox.test(nonsyn_allCpG,nonsyn_allnonCpG, alternative = "less", paired = FALSE) wilcoxtest2$test[4]<-re4[[7]] wilcoxtest2$P.value[4]<-re4[[3]] write.csv(wilcoxtest2,"Output/SummaryStats/WilcoxTestResults_by_Type_MF_Ts_all.csv") Type.mf1<-data.frame("mean"=matrix(nrow=7)) for (i in 1:7){ rownames(Type.mf1)[i]<-names(Typelist2)[i] Type.mf1$mean[i]<-mean(Typelist2[[i]],na.rm=T) Type.mf1$se[i]<-std.error(Typelist2[[i]], na.rm=T) } write.csv(Type.mf1,paste0("Output/SummaryStats/MutFreq_byType_Summary_all.csv")) ################################## ##3.2 Transversion (all) nuc.mft<-data.frame("s.cpg"=matrix(nrow=4)) rownames(nuc.mft)<-c("a","t","c","g") WilcoxTest.nt.mft<-data.frame(matrix(ncol=3,nrow=8)) colnames(WilcoxTest.nt.mft)<-c("nt","test","P.value") k=1 for (i in c("A","T","C","G")) { if (i=="A"\|i=="G"){ syncpg1<-get(paste0(i,"_tv1_syn_cpg")) #syncpg2<-get(paste0(i,"_tv2_syn_cpg")) synnoncpg1<-get(paste0(i,"_tv1_syn_noncpg")) synnoncpg2<-get(paste0(i,"_tv2_syn_noncpg")) nonsyncpg1<-get(paste0(i,"_tv1_nonsyn_cpg")) #nonsyncpg2<-get(paste0(i,"_tv2_nonsyn_cpg")) nonsynnoncpg1<-get(paste0(i,"_tv1_nonsyn_noncpg")) nonsynnoncpg2<-get(paste0(i,"_tv2_nonsyn_noncpg")) synnoncpg<-c(synnoncpg1,synnoncpg2) nonsynnoncpg<-c(nonsynnoncpg1,nonsynnoncpg2) nuc.mft$s.cpg[k]<-mean(syncpg1, na.rm=T) nuc.mft$s.cpg.se[k]<-std.error(syncpg1, na.rm=T) nuc.mft$s.ncpg[k]<-mean(synnoncpg, na.rm=T) nuc.mft$s.ncpg.se[k]<-std.error(synnoncpg, na.rm=T) nuc.mft$ns.cpg[k]<-mean(nonsyncpg1, na.rm=T) nuc.mft$ns.cpg.se[k]<-std.error(nonsyncpg1, na.rm=T) nuc.mft$ns.ncpg[k]<-mean(nonsynnoncpg, na.rm=T) nuc.mft$ns.ncpg.se[k]<-std.error(nonsynnoncpg, na.rm=T) #nuc.mft$stop.ncpg[k]<-NA #nuc.mft$stop.ncpg.se[k]<-NA if (i=="A"){ result1<-wilcox.test(syncpg1, synnoncpg, alternative = "less", paired = FALSE) result2<-wilcox.test(nonsyncpg1,nonsynnoncpg,alternative = "less", paired = FALSE) for (r in 1:2){ result<-get(paste0('result',r)) WilcoxTest.nt.mft$nt[r]<-i WilcoxTest.nt.mft$test[r]<-result[[7]] WilcoxTest.nt.mft$P.value[r]<-result[[3]]} } if (i=="G"){ result7<-wilcox.test(syncpg1, synnoncpg, alternative = "less", paired = FALSE) result8<-wilcox.test(nonsyncpg1,nonsynnoncpg,alternative = "less", paired = FALSE) for (r in 7:8){ result<-get(paste0('result',r)) WilcoxTest.nt.mft$nt[r]<-i WilcoxTest.nt.mft$test[r]<-result[[7]] WilcoxTest.nt.mft$P.value[r]<-result[[3]]} } } if (i=="T"\|i=="C") { syncpg2<-get(paste0(i,"_tv2_syn_cpg")) synnoncpg1<-get(paste0(i,"_tv1_syn_noncpg")) synnoncpg2<-get(paste0(i,"_tv2_syn_noncpg")) nonsyncpg2<-get(paste0(i,"_tv2_nonsyn_cpg")) nonsynnoncpg1<-get(paste0(i,"_tv1_nonsyn_noncpg")) nonsynnoncpg2<-get(paste0(i,"_tv2_nonsyn_noncpg")) synnoncpg<-c(synnoncpg1,synnoncpg2) nonsynnoncpg<-c(nonsynnoncpg1,nonsynnoncpg2) nuc.mft$s.cpg[k]<-mean(syncpg2, na.rm=T) nuc.mft$s.cpg.se[k]<-std.error(syncpg2, na.rm=T) nuc.mft$s.ncpg[k]<-mean(synnoncpg, na.rm=T) nuc.mft$s.ncpg.se[k]<-std.error(synnoncpg, na.rm=T) nuc.mft$ns.cpg[k]<-mean(nonsyncpg2, na.rm=T) nuc.mft$ns.cpg.se[k]<-std.error(nonsyncpg2, na.rm=T) nuc.mft$ns.ncpg[k]<-mean(nonsynnoncpg, na.rm=T) nuc.mft$ns.ncpg.se[k]<-std.error(nonsynnoncpg, na.rm=T) if (i =="T") { result3<-wilcox.test(syncpg2, synnoncpg, alternative = "less", paired = FALSE) result4<-wilcox.test(nonsyncpg2,nonsynnoncpg,alternative = "less", paired = FALSE) for (r in 3:4){ result<-get(paste0('result',r)) WilcoxTest.nt.mft$nt[r]<-i WilcoxTest.nt.mft$test[r]<-result[[7]] WilcoxTest.nt.mft$P.value[r]<-result[[3]]} } if (i =="C") { result5<-wilcox.test(syncpg2, synnoncpg, alternative = "less", paired = FALSE) result6<-wilcox.test(nonsyncpg2,nonsynnoncpg,alternative = "less", paired = FALSE) for (r in 5:6){ result<-get(paste0('result',r)) WilcoxTest.nt.mft$nt[r]<-i WilcoxTest.nt.mft$test[r]<-result[[7]] WilcoxTest.nt.mft$P.value[r]<-result[[3]]} } } k=k+1 } write.csv(WilcoxTest.nt.mft,paste0("Output/SummaryStats/WilcoxTestResults_TV_eachNT_all.csv")) write.csv(nuc.mft,paste0("Output/SummaryStats/TransversionMF_byNT_byType_all.csv")) wilcoxtest3<-data.frame("test"=matrix(nrow=4)) Typelist3<-list() syn_all<-c(A_tv1_syn,T_tv1_syn,C_tv1_syn,G_tv1_syn,A_tv2_syn,T_tv2_syn,C_tv2_syn,G_tv2_syn) Typelist3[[1]]<-syn_all; names(Typelist3)[1]<-"syn_all" nonsyn_all<-c(A_tv1_nonsyn,T_tv1_nonsyn,C_tv1_nonsyn,G_tv1_nonsyn,A_tv2_nonsyn,T_tv2_nonsyn,C_tv2_nonsyn,G_tv2_nonsyn) Typelist3[[2]]<-nonsyn_all; names(Typelist3)[2]<-"nonsyn_all" syn_allCpG<-c(A_tv1_syn_cpg,T_tv2_syn_cpg,G_tv1_syn_cpg,C_tv2_syn_cpg ) Typelist3[[3]]<-syn_allCpG; names(Typelist3)[3]<-"syn_allCpG" syn_allnonCpG<-c(A_tv1_syn_noncpg,T_tv1_syn_noncpg,G_tv1_syn_noncpg,C_tv1_syn_noncpg,A_tv2_syn_noncpg,T_tv2_syn_noncpg,G_tv2_syn_noncpg,C_tv2_syn_noncpg) Typelist3[[4]]<-syn_allnonCpG; names(Typelist3)[4]<-"syn_allnonCpG" nonsyn_allCpG<-c(A_tv1_nonsyn_cpg,T_tv2_nonsyn_cpg,G_tv1_nonsyn_cpg,C_tv2_nonsyn_cpg) Typelist3[[5]]<-nonsyn_allCpG; names(Typelist3)[5]<-"nonsyn_allCpG" nonsyn_allnonCpG<-c(A_tv1_nonsyn_noncpg,T_tv1_nonsyn_noncpg,G_tv1_nonsyn_noncpg,C_tv1_nonsyn_noncpg,A_tv2_nonsyn_noncpg,T_tv2_nonsyn_noncpg,G_tv2_nonsyn_noncpg,C_tv2_nonsyn_noncpg) Typelist3[[6]]<-nonsyn_allnonCpG; names(Typelist3)[6]<-"nonsyn_allnonCpG" stop_all<-c(A_tv1_stop,T_tv1_stop,C_tv1_stop,G_tv1_stop,A_tv2_stop,T_tv2_stop,C_tv2_stop,G_tv2_stop) Typelist3[[7]]<-stop_all; names(Typelist3)[7]<-"stop_all" re1<-wilcox.test(syn_all,nonsyn_all, alternative = "greater", paired = FALSE) wilcoxtest3$test[1]<-re1[[7]] wilcoxtest3$P.value[1]<-re1[[3]] re2<-wilcox.test(nonsyn_all,stop_all, alternative = "greater", paired = FALSE) wilcoxtest3$test[2]<-re2[[7]] wilcoxtest3$P.value[2]<-re2[[3]] re3<-wilcox.test(syn_allCpG,syn_allnonCpG, alternative = "less", paired = FALSE) wilcoxtest3$test[3]<-re3[[7]] wilcoxtest3$P.value[3]<-re3[[3]] re4<-wilcox.test(nonsyn_allCpG,nonsyn_allnonCpG, alternative = "less", paired = FALSE) wilcoxtest3$test[4]<-re4[[7]] wilcoxtest3$P.value[4]<-re4[[3]] write.csv(wilcoxtest3,"Output/SummaryStats/WilcoxTestResults_by_Type_MF_Transversion_all.csv") Type.mf2<-data.frame("mean"=matrix(nrow=7)) for (i in 1:7){ rownames(Type.mf2)[i]<-names(Typelist3)[i] Type.mf2$mean[i]<-mean(Typelist3[[i]],na.rm=T) Type.mf2$se[i]<-std.error(Typelist3[[i]], na.rm=T) } write.csv(Type.mf2,paste0("Output/SummaryStats/MutFreq_byType_Summary_Transversion_all.csv")) ####### plot to visually assure ### Type.mf2$names<-c("Syn","Nonsyn","Syn_CpG", "Syn_nonCpG","Nonsyn_CpG","Nonsyn_nonCpG","Stop") x=seq(1,7, by=1) plot(x, Type.mf2$mean, xaxt="n",main="", xlab ="",ylim=c(0,0.0012),pch=".") #axis(1, at=1:7, labels=Type.mf2$names, las = 1, cex.axis = 0.8) text(cex=1,x=x, y=-0.0001, labels=Type.mf2$names, xpd=TRUE, srt=35,adj= 1) bar<-0.02 segments(x,(Type.mf2$mean-Type.mf2$se),x,(Type.mf2$mean+Type.mf2$se)) segments(x-bar,(Type.mf2$mean-Type.mf2$se),x+bar,(Type.mf2$mean-Type.mf2$se)) segments(x-bar,(Type.mf2$mean+Type.mf2$se),x+bar,(Type.mf2$mean+Type.mf2$se)) ##################################	/Rscripts/10.5.WilcoxinTest_FilteredData.R	no_license	kahot/HCV_project	R	false	false	27,846	r	library(tidyverse) library(zoo) library(purrr) source("Rscripts/baseRscript.R") HCVFiles3<-list.files("Output1A/Overview3/",pattern="overview3.csv") # #### read the filtered MF files from 10.1.2 TsMutFreq <-read.csv("Output1A/MutFreq.filtered/Filtered.Ts.Q35.csv",stringsAsFactors = F,row.names=1) Tv1.MutFreq<-read.csv("Output1A/MutFreq.filtered/Filtered.Tv1.MutFreq.Q35.csv",stringsAsFactors = F,row.names=1) Tv2.MutFreq<-read.csv("Output1A/MutFreq.filtered/Filtered.Tv2.MutFreq.Q35.csv",stringsAsFactors = F,row.names=1) Tvs.MutFreq<-read.csv("Output1A/MutFreq.filtered/Filtered.Tvs.MutFreq.Q35.csv",stringsAsFactors = F,row.names=1) AllMutFreq <-read.csv("Output1A/MutFreq.filtered/Filtered.AllMutFreq.Q35.csv", stringsAsFactors = F,row.names=1) mf.files<-list() mf.files[[1]]<-TsMutFreq mf.files[[2]]<-Tv1.MutFreq mf.files[[3]]<-Tv2.MutFreq mf.files[[4]]<-Tvs.MutFreq mf.files[[5]]<-AllMutFreq names(mf.files)[1]<-"TransMutFreq" names(mf.files)[2]<-"Tv1.MutFreq" names(mf.files)[3]<-"Tv2.MutFreq" names(mf.files)[4]<-"Tvs.MutFreq" names(mf.files)[5]<-"AllMutFreq" s<-length(HCVFiles3) #### 1) Transition Mutations (mean) # 1.1) Summary Ts<-mf.files[[1]] Ts<-Ts[Ts$pos>=342, ] mean(Ts$mean[Ts$Type=="syn"]) #0.008093379 mean(Ts$mean[Ts$Type=="nonsyn"]) #0.003348242 mean(Ts$mean[Ts$Type=="stop"]) #0.002022381 table(Ts$Type) #nonsyn stop syn # 5193 220 2545 std.error(Ts$mean[Ts$Type=="syn"]) #9.066418e-05 std.error(Ts$mean[Ts$Type=="nonsyn"]) # 2.768315e-05 std.error(Ts$mean[Ts$Type=="stop"]) # 9.204526e-05 r1<-wilcox.test(Ts$mean[Ts$Type=="syn"], Ts$mean[Ts$Type=="nonsyn"], alternative = "greater", paired = FALSE) r2<-wilcox.test(Ts$mean[Ts$Type=="nonsyn"], Ts$mean[Ts$Type=="stop"], alternative = "greater", paired = FALSE) r1[[3]] #P=0 r2[[3]] #P= 1.933446e-41 #CpG creating vs Non-CpG creating T2<-Ts[Ts$ref=="a"\|Ts$ref=="t",] r3<-wilcox.test(T2$mean[T2$Type=="syn"&T2$makesCpG==0], T2$mean[T2$Type=="syn"&T2$makesCpG==1], alternative = "greater", paired = FALSE) r4<-wilcox.test(T2$mean[T2$Type=="nonsyn"&T2$makesCpG==0], T2$mean[T2$Type=="nonsyn"&T2$makesCpG==1], alternative = "greater", paired = FALSE) r3[[3]] #P=0.005231179 r4[[3]] #P=3.893716e-12 ################## # 1.2) run Wilcoxin Test on means based on mutation types WilcoxTest.results.nt<-data.frame(matrix(ncol=3,nrow=6)) colnames(WilcoxTest.results.nt)<-c("nt","test","P.value") # 1) transition Mutations, using 'mean' dat<-mf_files[[1]] #dat<-TransMutFreq_filtered dat<-dat[dat$pos>=342, ] which(is.na(dat$freq.Ts)) dat<-dat[1:8236, ]#7895 ty<-which(colnames(dat)=="Type");fname="Transition" m<-data.frame() se<-data.frame() m_CpG<-data.frame() se_CpG<-data.frame() m_nonCpG<-data.frame() se_nonCpG<-data.frame() table(dat$ref) #a c g t #1556 2431 2310 1661 for (typeofsite in c("syn", "nonsyn","stop")){ for (wtnt in c("a", "t", "c", "g")){ mutrate<- dat$mean[dat[,ty]==typeofsite & dat$ref==wtnt] m[typeofsite,wtnt]<-mean(mutrate[!is.na(mutrate)]) se[typeofsite,wtnt]<-std.error(mutrate[!is.na(mutrate)]) m_NonCpG<-dat$mean[dat$Type==typeofsite & dat$ref==wtnt & dat$makesCpG==0] m_nonCpG[typeofsite,wtnt]<-mean(m_NonCpG[!is.na(m_NonCpG)]) se_nonCpG[typeofsite,wtnt]<-std.error(m_NonCpG[!is.na(m_NonCpG)]) mu_CpG<-dat$mean[dat$Type==typeofsite & dat$ref==wtnt & dat$makesCpG==1] m_CpG[typeofsite,wtnt]<-mean(mu_CpG[!is.na(mu_CpG)]) se_CpG[typeofsite,wtnt]<-std.error(mu_CpG[!is.na(mu_CpG)]) vectorname<-paste0(typeofsite,"_",wtnt) assign(vectorname, mutrate) vname1<<-paste0(typeofsite,"_",wtnt,"_noncpg") assign(vname1, m_NonCpG) vname2<<-paste0(typeofsite,"_",wtnt,"_cpg") assign(vname2, mu_CpG) } } #rownames(m)<-c("syn","nonsyn","stop") rownames(se)<-c("syn_se","nonsyn_se","stop_se") rownames(m_nonCpG)<-c("syn_noncpg","nonsyn_noncpg","stop_noncpg") rownames(se_nonCpG)<-c("syn_noncpg_se","nonsyn_noncpg_se","stop_noncpg_se") rownames(m_CpG)<-c("syn_cpg","nonsyn_cpg","stop_cpg") rownames(se_CpG)<-c("syn_cpg_se","nonsyn_cpg_se","stop_cpg_se") MFbyType<-rbind(m,se,m_nonCpG,se_nonCpG,m_CpG,se_CpG) MFbyType2<-t(MFbyType) MFbyType2<-data.frame(MFbyType2) write.csv(MFbyType2,"Output1A/SummaryStats/TransitionMF_byNt_byType_mean.csv") #run Wilcoxin Test for (i in c("a","t","c","g")) { if (i=="a"\|i=="t"){ syncpg<-get(paste0("syn_",i,"_cpg")) synnoncpg<-get(paste0("syn_",i,"_noncpg")) nonsyncpg<-get(paste0("nonsyn_",i,"_cpg")) nonsynnoncpg<-get(paste0("nonsyn_",i,"_noncpg")) if (i=="a"){ result1<-wilcox.test(syncpg, synnoncpg, alternative = "less", paired = FALSE) result2<-wilcox.test(nonsyncpg,nonsynnoncpg,alternative = "less", paired = FALSE) for (r in 1:2){ result<-get(paste0('result',r)) WilcoxTest.results.nt$nt[r]<-i WilcoxTest.results.nt$test[r]<-result[[7]] WilcoxTest.results.nt$P.value[r]<-result[[3]]} } if (i=="t"){ result3<-wilcox.test(syncpg, synnoncpg, alternative = "less", paired = FALSE) result4<-wilcox.test(nonsyncpg,nonsynnoncpg,alternative = "less", paired = FALSE) for (r in 3:4){ result<-get(paste0('result',r)) WilcoxTest.results.nt$nt[r]<-i WilcoxTest.results.nt$test[r]<-result[[7]] WilcoxTest.results.nt$P.value[r]<-result[[3]]} } } else { synnoncpg<-get(paste0("syn_",i,"_noncpg")) nonsynnoncpg<-get(paste0("nonsyn_",i,"_noncpg")) if (i =="c") { result5<-wilcox.test(synnoncpg,nonsynnoncpg, alternative = "greater", paired = FALSE) WilcoxTest.results.nt$nt[5]<-i WilcoxTest.results.nt$test[5]<-result5[[7]] WilcoxTest.results.nt$P.value[5]<-result5[[3]] } if (i =="g") { result6<-wilcox.test(synnoncpg,nonsynnoncpg, alternative = "greater", paired = FALSE) WilcoxTest.results.nt$nt[6]<-i WilcoxTest.results.nt$test[6]<-result6[[7]] WilcoxTest.results.nt$P.value[6]<-result6[[3]] } } } write.csv(WilcoxTest.results.nt,paste0("Output1A/SummaryStats/WilcoxTestResults_Ts_eachNT_mean.csv")) al<-mf.files[[5]] mean(al$mean) #0.005771959 tvs<-mf.files[[4]] tvs<-tvs[tvs$pos>=342,] mean(tvs$mean) #0.0009650088 # 2) Transversion with mean ### ## 2.1) Summary Stats Tv1<-mf.files[[2]] Tv1<-Tv1[Tv1$pos>=342, ] Tv2<-mf.files[[3]] Tv2<-Tv2[Tv2$pos>=342, ] All<-c(Tv1$mean,Tv2$mean) #0.0004825044 Syn<-c(Tv1$mean[Tv1$Type.tv1=="syn"],Tv2$mean[Tv2$Type.tv2=="syn"]) Nonsyn <- c(Tv1$mean[Tv1$Type.tv1=="nonsyn"],Tv2$mean[Tv2$Type.tv2=="nonsyn"]) Stop <- c(Tv1$mean[Tv1$Type.tv1=="stop"],Tv2$mean[Tv2$Type.tv2=="stop"]) mean(All) #0.0004825044 mean(Syn) #0.0007535948 mean(Nonsyn) #0.0004099817 mean(Stop) #0.0005612278 c(length(Nonsyn),length(Stop),length(Syn)) #nonsyn stop syn # 12184 625 3107 std.error(Syn) # 1.508687e-05 std.error(Nonsyn) # 4.921358e-06 std.error(Stop) # 1.833373e-05 r1<-wilcox.test(Syn, Nonsyn, alternative = "greater", paired = FALSE) r2<-wilcox.test(Nonsyn, Stop, alternative = "greater", paired = FALSE) wilcox.test(Nonsyn, Stop, alternative = "less", paired = FALSE) r1[[3]] #2.811567e-175 r2[[3]] #1 Syncpg<-c(Tv1$mean[Tv1$Type.tv1=="syn"&Tv1$makesCpG.tv1==1],Tv2$mean[Tv2$Type.tv2=="syn"&Tv2$makesCpG.tv2==1]) SynNoncpg<-c(Tv1$mean[Tv1$Type.tv1=="syn"&Tv1$makesCpG.tv1==0],Tv2$mean[Tv2$Type.tv2=="syn"&Tv2$makesCpG.tv2==0]) Nonsyncpg <- c(Tv1$mean[Tv1$Type.tv1=="nonsyn"&Tv1$makesCpG.tv1==1],Tv2$mean[Tv2$Type.tv2=="nonsyn"&Tv2$makesCpG.tv2==1]) NNcpg <- c(Tv1$mean[Tv1$Type.tv1=="nonsyn"&Tv1$makesCpG.tv1==0],Tv2$mean[Tv2$Type.tv2=="nonsyn"&Tv2$makesCpG.tv2==0]) r3<-wilcox.test(SynNoncpg,Syncpg, alternative = "greater", paired = FALSE) r4<-wilcox.test(NNcpg,Nonsyncpg, alternative = "greater", paired = FALSE) r3[[3]] #[1] 5.038601e-143 r4[[3]] #[1] 1.390009e-237 ## 2.2) Run Wilcoxon test on each NT, transversion dat1<-mf_filtered[[2]] dat1<-dat1[dat1$pos>=342, ] dat2<-mf_filtered[[3]] dat2<-dat2[dat2$pos>=342, ] m<-data.frame() se<-data.frame() m_nonCpG<-data.frame() se_nonCpG<-data.frame() mr_CpG<-data.frame() se_CpG<-data.frame() for (typeofsite in c("syn", "nonsyn","stop")){ for (wtnt in c("a", "t", "c", "g")){ mr1<- dat1$mean[dat1$Type.tv1==typeofsite & dat1$ref==wtnt] mr2<- dat2$mean[dat2$Type.tv2==typeofsite & dat1$ref==wtnt] m_NonCpG1<-dat1$mean[dat1$Type.tv1==typeofsite & dat1$ref==wtnt & dat1$makesCpG.tv1==0] m_NonCpG2<-dat2$mean[dat2$Type.tv2==typeofsite & dat2$ref==wtnt & dat2$makesCpG.tv2==0] m_CpG1<-dat1$mean[dat1$Type.tv1==typeofsite & dat1$ref==wtnt & dat1$makesCpG.tv1==1] m_CpG2<-dat2$mean[dat2$Type.tv2==typeofsite & dat2$ref==wtnt & dat2$makesCpG.tv2==1] mr<-c(mr1,mr2) m_NonCpG<-c(m_NonCpG1,m_NonCpG2) m_CpG<-c(m_CpG1,m_CpG2) m[typeofsite,wtnt]<-mean(mr[!is.na(mr)]) se[typeofsite,wtnt]<-std.error(mr[!is.na(mr)]) m_nonCpG[typeofsite,wtnt]<-mean(m_NonCpG[!is.na(m_NonCpG)]) se_nonCpG[typeofsite,wtnt]<-std.error(m_NonCpG[!is.na(m_NonCpG)]) mr_CpG[typeofsite,wtnt]<-mean(m_CpG[!is.na(m_CpG)]) se_CpG[typeofsite,wtnt]<-std.error(m_CpG[!is.na(m_CpG)]) vectorname<-paste0(typeofsite,"_",wtnt) assign(vectorname, mr) vname1<<-paste0(typeofsite,"_",wtnt,"_noncpg") assign(vname1, m_NonCpG) vname2<<-paste0(typeofsite,"_",wtnt,"_cpg") assign(vname2, m_CpG) } } rownames(se)<-c("syn_se","nonsyn_se","stop_se") rownames(m_nonCpG)<-c("syn_noncpg","nonsyn_noncpg","stop_noncpg") rownames(se_nonCpG)<-c("syn_noncpg_se","nonsyn_noncpg_se","stop_noncpg_se") rownames(mr_CpG)<-c("syn_cpg","nonsyn_cpg","stop_cpg") rownames(se_CpG)<-c("syn_cpg_se","nonsyn_cpg_se","stop_cpg_se") MFbyType.tv<-rbind(m,se,mr_CpG,se_CpG,m_nonCpG,se_nonCpG) MFbyType.tv2<-t(MFbyType.tv) write.csv(MFbyType.tv2,paste0("Output1A/SummaryStats/Transversion_MF_byNt_byType_mean.csv")) # CpG vs nonCpG WilcoxTest.results.nt.tv<-data.frame(matrix(ncol=3,nrow=8)) colnames(WilcoxTest.results.nt.tv)<-c("nt","test","P.value") for (i in c("a","t","c","g")) { syncpg<-get(paste0("syn_",i,"_cpg")) synnoncpg<-get(paste0("syn_",i,"_noncpg")) nonsyncpg<-get(paste0("nonsyn_",i,"_cpg")) nonsynnoncpg<-get(paste0("nonsyn_",i,"_noncpg")) if (i=="a"){ if (length(syncpg)==0) next else{result1<-wilcox.test(syncpg, synnoncpg, alternative = "less", paired = FALSE) result2<-wilcox.test(nonsyncpg,nonsynnoncpg,alternative = "less", paired = FALSE) for (r in 1:2){ result<-get(paste0('result',r)) WilcoxTest.results.nt.tv$nt[r]<-i WilcoxTest.results.nt.tv$test[r]<-result[[7]] WilcoxTest.results.nt.tv$P.value[r]<-result[[3]]} }} if (i=="t"){ if (length(syncpg)==0) next else{ result3<-wilcox.test(syncpg, synnoncpg, alternative = "less", paired = FALSE) result4<-wilcox.test(nonsyncpg,nonsynnoncpg,alternative = "less", paired = FALSE) for (r in 3:4){ result<-get(paste0('result',r)) WilcoxTest.results.nt.tv$nt[r]<-i WilcoxTest.results.nt.tv$test[r]<-result[[7]] WilcoxTest.results.nt.tv$P.value[r]<-result[[3]]} }} if (i=="c"){ if (length(syncpg)==0) next else{ result5<-wilcox.test(syncpg, synnoncpg, alternative = "less", paired = FALSE) result6<-wilcox.test(nonsyncpg,nonsynnoncpg,alternative = "less", paired = FALSE) for (r in 5:6){ result<-get(paste0('result',r)) WilcoxTest.results.nt.tv$nt[r]<-i WilcoxTest.results.nt.tv$test[r]<-result[[7]] WilcoxTest.results.nt.tv$P.value[r]<-result[[3]]} }} if (i=="g"){ if (length(syncpg)==0) next else{ result7<-wilcox.test(syncpg, synnoncpg, alternative = "less", paired = FALSE) result8<-wilcox.test(nonsyncpg,nonsynnoncpg,alternative = "less", paired = FALSE) for (r in 7:8){ result<-get(paste0('result',r)) WilcoxTest.results.nt.tv$nt[r]<-i WilcoxTest.results.nt.tv$test[r]<-result[[7]] WilcoxTest.results.nt.tv$P.value[r]<-result[[3]]} }} } write.csv(WilcoxTest.results.nt.tv,paste0("Output1A/SummaryStats/WilcoxTestResults_TV_eachNT_mean.csv")) ##################### ## Not sure if we need to run these: # 3) use all data to create summary / run Wilcoxon Test (using all values,not just the mean of 195 files) on Transition source("Rscripts/MutationFreqSum.filtered.R") ##3.1 Transition nuc.mf2<-data.frame("s.cpg"=matrix(nrow=4)) rownames(nuc.mf2)<-c("a","t","c","g") WilcoxTest.nt.mf2<-data.frame(matrix(ncol=3,nrow=6)) colnames(WilcoxTest.nt.mf2)<-c("nt","test","P.value") k=1 for (i in c("A","T","C","G")) { if (i=="A"\|i=="T"){ syncpg1<-get(paste0(i,"_syn_cpg")) synnoncpg1<-get(paste0(i,"_syn_noncpg")) nonsyncpg1<-get(paste0(i,"_nonsyn_cpg")) nonsynnoncpg1<-get(paste0(i,"_nonsyn_noncpg")) nuc.mf2$s.cpg[k]<-mean(syncpg1, na.rm=T) nuc.mf2$s.cpg.se[k]<-std.error(syncpg1, na.rm=T) nuc.mf2$s.ncpg[k]<-mean(synnoncpg1, na.rm=T) nuc.mf2$s.ncpg.se[k]<-std.error(synnoncpg1, na.rm=T) nuc.mf2$ns.cpg[k]<-mean(nonsyncpg1, na.rm=T) nuc.mf2$ns.cpg.se[k]<-std.error(nonsyncpg1, na.rm=T) nuc.mf2$ns.ncpg[k]<-mean(nonsynnoncpg1, na.rm=T) nuc.mf2$ns.ncpg.se[k]<-std.error(nonsynnoncpg1, na.rm=T) #nuc.mf2$stop.ncpg[k]<-NA #nuc.mf2$stop.ncpg.se[k]<-NA if (i=="A"){ result1<-wilcox.test(syncpg1, synnoncpg1, alternative = "less", paired = FALSE) result2<-wilcox.test(nonsyncpg1,nonsynnoncpg1,alternative = "less", paired = FALSE) for (r in 1:2){ result<-get(paste0('result',r)) WilcoxTest.nt.mf2$nt[r]<-i WilcoxTest.nt.mf2$test[r]<-result[[7]] WilcoxTest.nt.mf2$P.value[r]<-result[[3]]} } if (i=="T"){ result3<-wilcox.test(syncpg1, synnoncpg1, alternative = "less", paired = FALSE) result4<-wilcox.test(nonsyncpg1,nonsynnoncpg1,alternative = "less", paired = FALSE) for (r in 3:4){ result<-get(paste0('result',r)) WilcoxTest.nt.mf2$nt[r]<-i WilcoxTest.nt.mf2$test[r]<-result[[7]] WilcoxTest.nt.mf2$P.value[r]<-result[[3]]} } } else { synnoncpg1<-get(paste0(i,"_syn_noncpg")) nonsynnoncpg1<-get(paste0(i,"_nonsyn_noncpg")) nuc.mf2$s.cpg[k]<-NA nuc.mf2$s.cpg.se[k]<-NA nuc.mf2$s.ncpg[k]<-mean(synnoncpg1, na.rm=T) nuc.mf2$s.ncpg.se[k]<-std.error(synnoncpg1, na.rm=T) nuc.mf2$ns.cpg[k]<-NA nuc.mf2$ns.cpg.se[k]<-NA nuc.mf2$ns.ncpg[k]<-mean(nonsynnoncpg1, na.rm=T) nuc.mf2$ns.ncpg.se[k]<-std.error(nonsynnoncpg1, na.rm=T) if (i =="C") { result5<-wilcox.test(synnoncpg1,nonsynnoncpg1, alternative = "greater", paired = FALSE) WilcoxTest.nt.mf2$nt[5]<-i WilcoxTest.nt.mf2$test[5]<-result5[[7]] WilcoxTest.nt.mf2$P.value[5]<-result5[[3]] } if (i =="G") { result6<-wilcox.test(synnoncpg1,nonsynnoncpg1, alternative = "greater", paired = FALSE) WilcoxTest.nt.mf2$nt[6]<-i WilcoxTest.nt.mf2$test[6]<-result6[[7]] WilcoxTest.nt.mf2$P.value[6]<-result6[[3]] } } k=k+1 } write.csv(WilcoxTest.nt.mf2,paste0("Output/SummaryStats/WilcoxTestResults_Transition_eachNT_all.csv")) write.csv(nuc.mf2,paste0("Output/SummaryStats/TransitionMF_byNT_byType_all.csv")) wilcoxtest2<-data.frame("test"=matrix(nrow=4)) Typelist2<-list() syn_all<-c(A_syn,T_syn,C_syn,G_syn) Typelist2[[1]]<-syn_all; names(Typelist2)[1]<-"syn_all" nonsyn_all<-c(A_nonsyn,T_nonsyn,C_nonsyn,G_nonsyn) Typelist2[[2]]<-nonsyn_all; names(Typelist2)[2]<-"nonsyn_all" stop_all<-c(A_stop,T_stop,C_stop,G_stop) Typelist2[[3]]<-stop_all; names(Typelist2)[3]<-"stop_all" syn_allCpG<-c(A_syn_cpg,T_syn_cpg) Typelist2[[4]]<-syn_allCpG; names(Typelist2)[4]<-"syn_allCpG" syn_allnonCpG<-c(A_syn_noncpg,T_syn_noncpg) Typelist2[[5]]<-syn_allnonCpG; names(Typelist2)[5]<-"syn_allnonCpG" nonsyn_allCpG<-c(A_nonsyn_cpg,T_nonsyn_cpg) Typelist2[[6]]<-nonsyn_allCpG; names(Typelist2)[6]<-"nonsyn_allCpG" nonsyn_allnonCpG<-c(A_nonsyn_noncpg,T_nonsyn_noncpg) Typelist2[[7]]<-nonsyn_allnonCpG; names(Typelist2)[7]<-"nonsyn_allnonCpG" re1<-wilcox.test(syn_all,nonsyn_all, alternative = "greater", paired = FALSE) wilcoxtest2$test[1]<-re1[[7]] wilcoxtest2$P.value[1]<-re1[[3]] re2<-wilcox.test(nonsyn_all,stop_all, alternative = "greater", paired = FALSE) wilcoxtest2$test[2]<-re2[[7]] wilcoxtest2$P.value[2]<-re2[[3]] re3<-wilcox.test(syn_allCpG,syn_allnonCpG, alternative = "less", paired = FALSE) wilcoxtest2$test[3]<-re3[[7]] wilcoxtest2$P.value[3]<-re3[[3]] re4<-wilcox.test(nonsyn_allCpG,nonsyn_allnonCpG, alternative = "less", paired = FALSE) wilcoxtest2$test[4]<-re4[[7]] wilcoxtest2$P.value[4]<-re4[[3]] write.csv(wilcoxtest2,"Output/SummaryStats/WilcoxTestResults_by_Type_MF_Ts_all.csv") Type.mf1<-data.frame("mean"=matrix(nrow=7)) for (i in 1:7){ rownames(Type.mf1)[i]<-names(Typelist2)[i] Type.mf1$mean[i]<-mean(Typelist2[[i]],na.rm=T) Type.mf1$se[i]<-std.error(Typelist2[[i]], na.rm=T) } write.csv(Type.mf1,paste0("Output/SummaryStats/MutFreq_byType_Summary_all.csv")) ################################## ##3.2 Transversion (all) nuc.mft<-data.frame("s.cpg"=matrix(nrow=4)) rownames(nuc.mft)<-c("a","t","c","g") WilcoxTest.nt.mft<-data.frame(matrix(ncol=3,nrow=8)) colnames(WilcoxTest.nt.mft)<-c("nt","test","P.value") k=1 for (i in c("A","T","C","G")) { if (i=="A"\|i=="G"){ syncpg1<-get(paste0(i,"_tv1_syn_cpg")) #syncpg2<-get(paste0(i,"_tv2_syn_cpg")) synnoncpg1<-get(paste0(i,"_tv1_syn_noncpg")) synnoncpg2<-get(paste0(i,"_tv2_syn_noncpg")) nonsyncpg1<-get(paste0(i,"_tv1_nonsyn_cpg")) #nonsyncpg2<-get(paste0(i,"_tv2_nonsyn_cpg")) nonsynnoncpg1<-get(paste0(i,"_tv1_nonsyn_noncpg")) nonsynnoncpg2<-get(paste0(i,"_tv2_nonsyn_noncpg")) synnoncpg<-c(synnoncpg1,synnoncpg2) nonsynnoncpg<-c(nonsynnoncpg1,nonsynnoncpg2) nuc.mft$s.cpg[k]<-mean(syncpg1, na.rm=T) nuc.mft$s.cpg.se[k]<-std.error(syncpg1, na.rm=T) nuc.mft$s.ncpg[k]<-mean(synnoncpg, na.rm=T) nuc.mft$s.ncpg.se[k]<-std.error(synnoncpg, na.rm=T) nuc.mft$ns.cpg[k]<-mean(nonsyncpg1, na.rm=T) nuc.mft$ns.cpg.se[k]<-std.error(nonsyncpg1, na.rm=T) nuc.mft$ns.ncpg[k]<-mean(nonsynnoncpg, na.rm=T) nuc.mft$ns.ncpg.se[k]<-std.error(nonsynnoncpg, na.rm=T) #nuc.mft$stop.ncpg[k]<-NA #nuc.mft$stop.ncpg.se[k]<-NA if (i=="A"){ result1<-wilcox.test(syncpg1, synnoncpg, alternative = "less", paired = FALSE) result2<-wilcox.test(nonsyncpg1,nonsynnoncpg,alternative = "less", paired = FALSE) for (r in 1:2){ result<-get(paste0('result',r)) WilcoxTest.nt.mft$nt[r]<-i WilcoxTest.nt.mft$test[r]<-result[[7]] WilcoxTest.nt.mft$P.value[r]<-result[[3]]} } if (i=="G"){ result7<-wilcox.test(syncpg1, synnoncpg, alternative = "less", paired = FALSE) result8<-wilcox.test(nonsyncpg1,nonsynnoncpg,alternative = "less", paired = FALSE) for (r in 7:8){ result<-get(paste0('result',r)) WilcoxTest.nt.mft$nt[r]<-i WilcoxTest.nt.mft$test[r]<-result[[7]] WilcoxTest.nt.mft$P.value[r]<-result[[3]]} } } if (i=="T"\|i=="C") { syncpg2<-get(paste0(i,"_tv2_syn_cpg")) synnoncpg1<-get(paste0(i,"_tv1_syn_noncpg")) synnoncpg2<-get(paste0(i,"_tv2_syn_noncpg")) nonsyncpg2<-get(paste0(i,"_tv2_nonsyn_cpg")) nonsynnoncpg1<-get(paste0(i,"_tv1_nonsyn_noncpg")) nonsynnoncpg2<-get(paste0(i,"_tv2_nonsyn_noncpg")) synnoncpg<-c(synnoncpg1,synnoncpg2) nonsynnoncpg<-c(nonsynnoncpg1,nonsynnoncpg2) nuc.mft$s.cpg[k]<-mean(syncpg2, na.rm=T) nuc.mft$s.cpg.se[k]<-std.error(syncpg2, na.rm=T) nuc.mft$s.ncpg[k]<-mean(synnoncpg, na.rm=T) nuc.mft$s.ncpg.se[k]<-std.error(synnoncpg, na.rm=T) nuc.mft$ns.cpg[k]<-mean(nonsyncpg2, na.rm=T) nuc.mft$ns.cpg.se[k]<-std.error(nonsyncpg2, na.rm=T) nuc.mft$ns.ncpg[k]<-mean(nonsynnoncpg, na.rm=T) nuc.mft$ns.ncpg.se[k]<-std.error(nonsynnoncpg, na.rm=T) if (i =="T") { result3<-wilcox.test(syncpg2, synnoncpg, alternative = "less", paired = FALSE) result4<-wilcox.test(nonsyncpg2,nonsynnoncpg,alternative = "less", paired = FALSE) for (r in 3:4){ result<-get(paste0('result',r)) WilcoxTest.nt.mft$nt[r]<-i WilcoxTest.nt.mft$test[r]<-result[[7]] WilcoxTest.nt.mft$P.value[r]<-result[[3]]} } if (i =="C") { result5<-wilcox.test(syncpg2, synnoncpg, alternative = "less", paired = FALSE) result6<-wilcox.test(nonsyncpg2,nonsynnoncpg,alternative = "less", paired = FALSE) for (r in 5:6){ result<-get(paste0('result',r)) WilcoxTest.nt.mft$nt[r]<-i WilcoxTest.nt.mft$test[r]<-result[[7]] WilcoxTest.nt.mft$P.value[r]<-result[[3]]} } } k=k+1 } write.csv(WilcoxTest.nt.mft,paste0("Output/SummaryStats/WilcoxTestResults_TV_eachNT_all.csv")) write.csv(nuc.mft,paste0("Output/SummaryStats/TransversionMF_byNT_byType_all.csv")) wilcoxtest3<-data.frame("test"=matrix(nrow=4)) Typelist3<-list() syn_all<-c(A_tv1_syn,T_tv1_syn,C_tv1_syn,G_tv1_syn,A_tv2_syn,T_tv2_syn,C_tv2_syn,G_tv2_syn) Typelist3[[1]]<-syn_all; names(Typelist3)[1]<-"syn_all" nonsyn_all<-c(A_tv1_nonsyn,T_tv1_nonsyn,C_tv1_nonsyn,G_tv1_nonsyn,A_tv2_nonsyn,T_tv2_nonsyn,C_tv2_nonsyn,G_tv2_nonsyn) Typelist3[[2]]<-nonsyn_all; names(Typelist3)[2]<-"nonsyn_all" syn_allCpG<-c(A_tv1_syn_cpg,T_tv2_syn_cpg,G_tv1_syn_cpg,C_tv2_syn_cpg ) Typelist3[[3]]<-syn_allCpG; names(Typelist3)[3]<-"syn_allCpG" syn_allnonCpG<-c(A_tv1_syn_noncpg,T_tv1_syn_noncpg,G_tv1_syn_noncpg,C_tv1_syn_noncpg,A_tv2_syn_noncpg,T_tv2_syn_noncpg,G_tv2_syn_noncpg,C_tv2_syn_noncpg) Typelist3[[4]]<-syn_allnonCpG; names(Typelist3)[4]<-"syn_allnonCpG" nonsyn_allCpG<-c(A_tv1_nonsyn_cpg,T_tv2_nonsyn_cpg,G_tv1_nonsyn_cpg,C_tv2_nonsyn_cpg) Typelist3[[5]]<-nonsyn_allCpG; names(Typelist3)[5]<-"nonsyn_allCpG" nonsyn_allnonCpG<-c(A_tv1_nonsyn_noncpg,T_tv1_nonsyn_noncpg,G_tv1_nonsyn_noncpg,C_tv1_nonsyn_noncpg,A_tv2_nonsyn_noncpg,T_tv2_nonsyn_noncpg,G_tv2_nonsyn_noncpg,C_tv2_nonsyn_noncpg) Typelist3[[6]]<-nonsyn_allnonCpG; names(Typelist3)[6]<-"nonsyn_allnonCpG" stop_all<-c(A_tv1_stop,T_tv1_stop,C_tv1_stop,G_tv1_stop,A_tv2_stop,T_tv2_stop,C_tv2_stop,G_tv2_stop) Typelist3[[7]]<-stop_all; names(Typelist3)[7]<-"stop_all" re1<-wilcox.test(syn_all,nonsyn_all, alternative = "greater", paired = FALSE) wilcoxtest3$test[1]<-re1[[7]] wilcoxtest3$P.value[1]<-re1[[3]] re2<-wilcox.test(nonsyn_all,stop_all, alternative = "greater", paired = FALSE) wilcoxtest3$test[2]<-re2[[7]] wilcoxtest3$P.value[2]<-re2[[3]] re3<-wilcox.test(syn_allCpG,syn_allnonCpG, alternative = "less", paired = FALSE) wilcoxtest3$test[3]<-re3[[7]] wilcoxtest3$P.value[3]<-re3[[3]] re4<-wilcox.test(nonsyn_allCpG,nonsyn_allnonCpG, alternative = "less", paired = FALSE) wilcoxtest3$test[4]<-re4[[7]] wilcoxtest3$P.value[4]<-re4[[3]] write.csv(wilcoxtest3,"Output/SummaryStats/WilcoxTestResults_by_Type_MF_Transversion_all.csv") Type.mf2<-data.frame("mean"=matrix(nrow=7)) for (i in 1:7){ rownames(Type.mf2)[i]<-names(Typelist3)[i] Type.mf2$mean[i]<-mean(Typelist3[[i]],na.rm=T) Type.mf2$se[i]<-std.error(Typelist3[[i]], na.rm=T) } write.csv(Type.mf2,paste0("Output/SummaryStats/MutFreq_byType_Summary_Transversion_all.csv")) ####### plot to visually assure ### Type.mf2$names<-c("Syn","Nonsyn","Syn_CpG", "Syn_nonCpG","Nonsyn_CpG","Nonsyn_nonCpG","Stop") x=seq(1,7, by=1) plot(x, Type.mf2$mean, xaxt="n",main="", xlab ="",ylim=c(0,0.0012),pch=".") #axis(1, at=1:7, labels=Type.mf2$names, las = 1, cex.axis = 0.8) text(cex=1,x=x, y=-0.0001, labels=Type.mf2$names, xpd=TRUE, srt=35,adj= 1) bar<-0.02 segments(x,(Type.mf2$mean-Type.mf2$se),x,(Type.mf2$mean+Type.mf2$se)) segments(x-bar,(Type.mf2$mean-Type.mf2$se),x+bar,(Type.mf2$mean-Type.mf2$se)) segments(x-bar,(Type.mf2$mean+Type.mf2$se),x+bar,(Type.mf2$mean+Type.mf2$se)) ##################################
setwd("/Users/kelly/Desktop/2019_Summer/Ve572/hw/hw4") var <-read.csv("result/variance.csv",header=TRUE) avg <-read.csv("result/average.csv",header=TRUE) # load("RData/ycache.RData") # save(data, file="RData/ycache.RData") library(ggplot2) ggplot() + geom_point(data = avg, aes(x = cont, y = tavg), color="royalblue2", size = 2) + labs(y="average temperature (\u00B0C)", # ASCII code for celcius x="continent", caption = "temperature variation of each continent") ggplot(data = var, aes(x = cont, y = tvar)) + geom_point(color="orange", size = 2) + labs(y=expression("temperature variance (\u00B0C)"^2), # ASCII code for celcius x="continent", caption = "temperature variation of each continent")	/hw4/plot.R	no_license	YunyyYY/Methods-and-tools-for-big-data	R	false	false	742	r	setwd("/Users/kelly/Desktop/2019_Summer/Ve572/hw/hw4") var <-read.csv("result/variance.csv",header=TRUE) avg <-read.csv("result/average.csv",header=TRUE) # load("RData/ycache.RData") # save(data, file="RData/ycache.RData") library(ggplot2) ggplot() + geom_point(data = avg, aes(x = cont, y = tavg), color="royalblue2", size = 2) + labs(y="average temperature (\u00B0C)", # ASCII code for celcius x="continent", caption = "temperature variation of each continent") ggplot(data = var, aes(x = cont, y = tvar)) + geom_point(color="orange", size = 2) + labs(y=expression("temperature variance (\u00B0C)"^2), # ASCII code for celcius x="continent", caption = "temperature variation of each continent")
#! /usr/bin/env Rscript library(argparser) library(magrittr) argp <- arg_parser("Run KING-robust") %>% add_argument("gds_file", help = "GDS file") %>% add_argument("--out_prefix", help = "Prefix for output files", default = "") %>% add_argument("--variant_id", help = "File with vector of variant IDs") %>% add_argument("--sample_id", help = "File with vector of sample IDs") %>% add_argument("--num_core", help = "num.thread argument for snpgdsIBDKING (if NA, detect the number of cores automatically)") argv <- parse_args(argp) sessionInfo() print(argv) library(SNPRelate) library(SeqArray) if (!is.na(argv$variant_id)) { variant_id <- readRDS(argv$variant_id) } else { variant_id <- NULL } if (!is.na(argv$sample_id)) { sample_id <- readRDS(argv$sample_id) } else { sample_id <- NULL } gds <- seqOpen(argv$gds_file) king <- snpgdsIBDKING(gds, snp.id = variant_id, sample.id = sample_id, type = "KING-robust", num.thread = as.numeric(argv$num_core)) rownames(king$kinship) <- king$sample.id colnames(king$kinship) <- king$sample.id saveRDS(king, paste0(argv$out_prefix, "king_out.rds")) saveRDS(king$kinship, paste0(argv$out_prefix, "king_grm.rds"))	/king_grm.R	permissive	HanleyKingston/assoc_pipeline	R	false	false	1,238	r	#! /usr/bin/env Rscript library(argparser) library(magrittr) argp <- arg_parser("Run KING-robust") %>% add_argument("gds_file", help = "GDS file") %>% add_argument("--out_prefix", help = "Prefix for output files", default = "") %>% add_argument("--variant_id", help = "File with vector of variant IDs") %>% add_argument("--sample_id", help = "File with vector of sample IDs") %>% add_argument("--num_core", help = "num.thread argument for snpgdsIBDKING (if NA, detect the number of cores automatically)") argv <- parse_args(argp) sessionInfo() print(argv) library(SNPRelate) library(SeqArray) if (!is.na(argv$variant_id)) { variant_id <- readRDS(argv$variant_id) } else { variant_id <- NULL } if (!is.na(argv$sample_id)) { sample_id <- readRDS(argv$sample_id) } else { sample_id <- NULL } gds <- seqOpen(argv$gds_file) king <- snpgdsIBDKING(gds, snp.id = variant_id, sample.id = sample_id, type = "KING-robust", num.thread = as.numeric(argv$num_core)) rownames(king$kinship) <- king$sample.id colnames(king$kinship) <- king$sample.id saveRDS(king, paste0(argv$out_prefix, "king_out.rds")) saveRDS(king$kinship, paste0(argv$out_prefix, "king_grm.rds"))
library(sp) library(spacetime) m = 3# nr of trajectories n = 100 # length of each l = vector("list", m) t0 = as.POSIXct("2013-05-05",tz="GMT") set.seed(1331) for (i in 1:m) { x = cumsum(rnorm(n)) y = cumsum(rnorm(n)) sp = SpatialPoints(cbind(x,y)) #t = t0 + (0:(n-1) + (i-1)n) 60 t = t0 + (0:(n-1) + (i-1)n/2) 60 l[[i]] = STI(sp, t) } stt= STT(l) sttdf = STTDF(stt, data.frame(attr = rnorm(n*m), id = paste("ID", rep(1:m, each=n)))) x = as(stt, "STI") stplot(sttdf, col=1:m, scales=list(draw=TRUE)) stplot(sttdf, by = "id") stplot(sttdf[1]) stplot(sttdf[1]) p = Polygon(cbind(x=c(-20,-15,-15,-20,-20),y=c(10,10,15,15,10))) pol=SpatialPolygons(list(Polygons(list(p), "ID"))) stplot(sttdf[pol]) names(sttdf[pol]@traj) stplot(sttdf[1:2],col=1:2) stplot(sttdf[,t0]) stplot(sttdf[,"2013"]) stplot(sttdf[pol,"2013"]) is.null(sttdf[pol,t0])	/tests/rw.R	no_license	mages/spacetime	R	false	false	866	r	library(sp) library(spacetime) m = 3# nr of trajectories n = 100 # length of each l = vector("list", m) t0 = as.POSIXct("2013-05-05",tz="GMT") set.seed(1331) for (i in 1:m) { x = cumsum(rnorm(n)) y = cumsum(rnorm(n)) sp = SpatialPoints(cbind(x,y)) #t = t0 + (0:(n-1) + (i-1)n) 60 t = t0 + (0:(n-1) + (i-1)n/2) 60 l[[i]] = STI(sp, t) } stt= STT(l) sttdf = STTDF(stt, data.frame(attr = rnorm(n*m), id = paste("ID", rep(1:m, each=n)))) x = as(stt, "STI") stplot(sttdf, col=1:m, scales=list(draw=TRUE)) stplot(sttdf, by = "id") stplot(sttdf[1]) stplot(sttdf[1]) p = Polygon(cbind(x=c(-20,-15,-15,-20,-20),y=c(10,10,15,15,10))) pol=SpatialPolygons(list(Polygons(list(p), "ID"))) stplot(sttdf[pol]) names(sttdf[pol]@traj) stplot(sttdf[1:2],col=1:2) stplot(sttdf[,t0]) stplot(sttdf[,"2013"]) stplot(sttdf[pol,"2013"]) is.null(sttdf[pol,t0])
library(dplyr) # Unzipping raw data setwd("C:/Users/carla/OneDrive/Coursera/CleaningData/Week4/Project") UnZip <- unzip("data.zip") setwd("C:/Users/carla/OneDrive/Coursera/CleaningData/Week4/Project//UCI HAR Dataset") # Reading raw data x_train <- read.table("train/X_train.txt") y_train <- read.table("train/y_train.txt") subject_train <- read.table("train/subject_train.txt") x_test <- read.table("test/X_test.txt") y_test <- read.table("test/y_test.txt") subject_test <- read.table("test/subject_test.txt") features <- read.table("features.txt") # Merge the training and the test sets in one dataset X <- rbind(x_train, x_test) Y <- rbind(y_train, y_test) subject <- rbind(subject_train, subject_test) # Extracts from 561 features the mean and standard deviation mean_std_features <- grep("-(mean\|std)\$\$", features[, 2]) # Use descriptive activity names to name the activities in the data set X <- X %>% select(mean_std_features) names(X) <- features[mean_std_features, 2] # Labels the data set with descriptive variable names activities <- read.table("activity_labels.txt") Y[,1] = activities[Y[,1], 2] names(Y) = c("activity") names(subject) = c("subject") # Binding data data <- cbind(subject, Y, X) groupedBy_subject_activity <- data %>% group_by(subject, activity) %>% summarise_each(funs(mean)) write.table(groupedBy_subject_activity, "grouped_data.txt", row.name=FALSE)	/run_analysis.R	no_license	littlelightshining/GettingCleaningDataPeerGradedAssignment	R	false	false	1,404	r	library(dplyr) # Unzipping raw data setwd("C:/Users/carla/OneDrive/Coursera/CleaningData/Week4/Project") UnZip <- unzip("data.zip") setwd("C:/Users/carla/OneDrive/Coursera/CleaningData/Week4/Project//UCI HAR Dataset") # Reading raw data x_train <- read.table("train/X_train.txt") y_train <- read.table("train/y_train.txt") subject_train <- read.table("train/subject_train.txt") x_test <- read.table("test/X_test.txt") y_test <- read.table("test/y_test.txt") subject_test <- read.table("test/subject_test.txt") features <- read.table("features.txt") # Merge the training and the test sets in one dataset X <- rbind(x_train, x_test) Y <- rbind(y_train, y_test) subject <- rbind(subject_train, subject_test) # Extracts from 561 features the mean and standard deviation mean_std_features <- grep("-(mean\|std)\$\$", features[, 2]) # Use descriptive activity names to name the activities in the data set X <- X %>% select(mean_std_features) names(X) <- features[mean_std_features, 2] # Labels the data set with descriptive variable names activities <- read.table("activity_labels.txt") Y[,1] = activities[Y[,1], 2] names(Y) = c("activity") names(subject) = c("subject") # Binding data data <- cbind(subject, Y, X) groupedBy_subject_activity <- data %>% group_by(subject, activity) %>% summarise_each(funs(mean)) write.table(groupedBy_subject_activity, "grouped_data.txt", row.name=FALSE)
library(glmnet) mydata = read.table("./TrainingSet/Correlation/ovary.csv",head=T,sep=",") x = as.matrix(mydata[,4:ncol(mydata)]) y = as.matrix(mydata[,1]) set.seed(123) glm = cv.glmnet(x,y,nfolds=10,type.measure="mse",alpha=0.6,family="gaussian",standardize=TRUE) sink('./Model/EN/Correlation/ovary/ovary_065.txt',append=TRUE) print(glm$glmnet.fit) sink()	/Model/EN/Correlation/ovary/ovary_065.R	no_license	leon1003/QSMART	R	false	false	356	r	library(glmnet) mydata = read.table("./TrainingSet/Correlation/ovary.csv",head=T,sep=",") x = as.matrix(mydata[,4:ncol(mydata)]) y = as.matrix(mydata[,1]) set.seed(123) glm = cv.glmnet(x,y,nfolds=10,type.measure="mse",alpha=0.6,family="gaussian",standardize=TRUE) sink('./Model/EN/Correlation/ovary/ovary_065.txt',append=TRUE) print(glm$glmnet.fit) sink()
% Generated by roxygen2: do not edit by hand % Please edit documentation in R/genomeChartSV.R \name{genomeChartSV} \alias{genomeChartSV} \title{genomeChartSV} \usage{ genomeChartSV( outfilename, SV_bedpe_file, SNV_vcf_file = NULL, SNV_tab_file = NULL, PEAK.FACTOR = 10, kmin = 10, plot_title = NULL, genome.v = "hg19" ) } \arguments{ \item{outfilename}{file where the figure should be plotted. This also determines the file type of the output, use either pdf (recommended) or png} \item{SV_bedpe_file}{name of the tab separated bedpe file containing the SVs. The file should contain a rearrangement for each row (two breakpoint positions should be on one row as determined by a pair of mates of paired-end sequencing) and should already be filtered according to the user preference, as all rearrangements in the file will be used and no filter will be applied. The files should contain a header in the first line with the following columns: "chrom1", "start1", "end1", "chrom2", "start2", "end2" and "sample" (sample name). In addition, either two columns indicating the strands of the mates, "strand1" (+ or -) and "strand2" (+ or -), or one column indicating the structural variant class, "svclass": translocation, inversion, deletion, tandem-duplication. The column "svclass" should correspond to (Sanger BRASS convention): inversion (strands +/- or -/+ and mates on the same chromosome), deletion (strands +/+ and mates on the same chromosome), tandem-duplication (strands -/- and mates on the same chromosome), translocation (mates are on different chromosomes). In addition, columns 'non-template' and 'micro-homology' can be specified, including the non-templated insertion or micro-homology deletion sequence, which will be used to build an SV junctions catalogue.} \item{SNV_vcf_file}{name of the vcf file containing the SNVs} \item{SNV_tab_file}{name of the tab separated file containing the SNVs. Column names should be: chr, position, REF and ALT. If SNV_vcf_file is also specified, these variants will be ignored and the variants in the vcf file will be used instead.} \item{plot_title}{title of the plot. If NULL, then the sample_name will be used as title. Use "", the empty string, to have no title.} \item{genome.v}{genome version to use, either hg19 or hg38} } \value{ all computed results, like catalogues and clustering regions, will be returned } \description{ Plotting of somatic variants using the circlize R package. This plot focuses on structural variants (SVs or rearrangements). Clusters of SVs, if any, are shown on the plot using a different colour for each cluster. If SNVs are available, SNVs within the SV clusters are identified and used to build an SNV mutational catalogue of these localised variants. Moreover, if the bedpe file of the SVs contains data about non-templated insertions and micro-homology deletions at breakpoint junctions then the SV junction catalogue is also built and shown. }	/man/genomeChartSV.Rd	permissive	Nik-Zainal-Group/signature.tools.lib	R	false	true	2,957	rd	% Generated by roxygen2: do not edit by hand % Please edit documentation in R/genomeChartSV.R \name{genomeChartSV} \alias{genomeChartSV} \title{genomeChartSV} \usage{ genomeChartSV( outfilename, SV_bedpe_file, SNV_vcf_file = NULL, SNV_tab_file = NULL, PEAK.FACTOR = 10, kmin = 10, plot_title = NULL, genome.v = "hg19" ) } \arguments{ \item{outfilename}{file where the figure should be plotted. This also determines the file type of the output, use either pdf (recommended) or png} \item{SV_bedpe_file}{name of the tab separated bedpe file containing the SVs. The file should contain a rearrangement for each row (two breakpoint positions should be on one row as determined by a pair of mates of paired-end sequencing) and should already be filtered according to the user preference, as all rearrangements in the file will be used and no filter will be applied. The files should contain a header in the first line with the following columns: "chrom1", "start1", "end1", "chrom2", "start2", "end2" and "sample" (sample name). In addition, either two columns indicating the strands of the mates, "strand1" (+ or -) and "strand2" (+ or -), or one column indicating the structural variant class, "svclass": translocation, inversion, deletion, tandem-duplication. The column "svclass" should correspond to (Sanger BRASS convention): inversion (strands +/- or -/+ and mates on the same chromosome), deletion (strands +/+ and mates on the same chromosome), tandem-duplication (strands -/- and mates on the same chromosome), translocation (mates are on different chromosomes). In addition, columns 'non-template' and 'micro-homology' can be specified, including the non-templated insertion or micro-homology deletion sequence, which will be used to build an SV junctions catalogue.} \item{SNV_vcf_file}{name of the vcf file containing the SNVs} \item{SNV_tab_file}{name of the tab separated file containing the SNVs. Column names should be: chr, position, REF and ALT. If SNV_vcf_file is also specified, these variants will be ignored and the variants in the vcf file will be used instead.} \item{plot_title}{title of the plot. If NULL, then the sample_name will be used as title. Use "", the empty string, to have no title.} \item{genome.v}{genome version to use, either hg19 or hg38} } \value{ all computed results, like catalogues and clustering regions, will be returned } \description{ Plotting of somatic variants using the circlize R package. This plot focuses on structural variants (SVs or rearrangements). Clusters of SVs, if any, are shown on the plot using a different colour for each cluster. If SNVs are available, SNVs within the SV clusters are identified and used to build an SNV mutational catalogue of these localised variants. Moreover, if the bedpe file of the SVs contains data about non-templated insertions and micro-homology deletions at breakpoint junctions then the SV junction catalogue is also built and shown. }
# clear the workspace rm(list=ls()) # Load the required libraries library(ggplot2) library(GGally) # for the ggpairs() library(corrplot) library(plyr) library(mice) library(car) library(rpart) library(randomForest) library(gbm) library(moments) # for skewness function library(tidyr) # for the gather() library(VIM) # for missing data visualization # Data source # Department of Statistics, Malaysia: http://www.dosm.gov.my/v1/index.php?r=column3/accordion&menu_id=aHhRYUpWS3B4VXlYaVBOeUF0WFpWUT09 # load the rubber estate data df1<- read.csv("data/rubberestate/rubber-paidemployee.csv", header = TRUE, sep = ",", stringsAsFactors = FALSE) df2<- read.csv("data/rubberestate/rubber-plantedarea.csv", header = TRUE, sep = ",", stringsAsFactors = FALSE) df3<- read.csv("data/rubberestate/rubber-production.csv", header = TRUE, sep = ",", stringsAsFactors = FALSE) df4<- read.csv("data/rubberestate/rubber-taparea.csv", header = TRUE, sep = ",", stringsAsFactors = FALSE) df5<- read.csv("data/rubberestate/rubber-yield.csv", header = TRUE, sep = ",", stringsAsFactors = FALSE) # Exploratory Data Analysis dim(df1) dim(df2) dim(df3) dim(df4) dim(df5) names(df1) # observation: column name too long. rename them names(df2) # additional space after column names. do formatting names(df3) names(df4) names(df5) head(df1) # You cannot have employees in decimals. Round this variable names(df.master) # Basic Data Management # Renaming the column name # Reference: http://stackoverflow.com/questions/9283171/named-columns-renaming df1<- rename(df1, c("Total.Number.of.Paid.Employee.During.the.Last.Pay.Period..Estate." = "TotalPaidEmployee")) df2<-rename(df2, c("Planted.Area..Estate....000..Hectare" = "AreaPlantedHect")) df3<-rename(df3, c("Production..Estate....000..Tonne" = "ProduceTonne")) df4<-rename(df4, c("Tapped.Area..Estate....000..Hectare" = "TapAreaHect")) df5<-rename(df5, c("Yeild.per.Hectare..Estate...Kg." = "YieldperHectKg")) # Rounding the column value for TotalPaidEmployee because there cant be for example 2.5 employees df1$TotalPaidEmployee<- round(df1$TotalPaidEmployee) # Inner Join the data frames on common column df.m1<- merge(df1,df2, by="Year") df.m2<- merge(df3,df4, by="Year") df.m3<- merge(df.m2, df5, by="Year") df.master<- merge(df.m1, df.m3, by="Year") summary(df.master) # Missing data treatment aggr_plot <- aggr(df.master, col=c('navyblue','red'), numbers=TRUE, sortVars=TRUE, labels=names(df.master), cex.axis=.7, gap=3, ylab=c("Histogram of missing data","Pattern")) colSums(is.na(df.master)) # There is only 1 missing row tempData <- mice(df.master,m=5,maxit=50,meth='pmm',seed=1234) df.master<- mice::complete(tempData,1) colSums(is.na(df.master)) # Describe the data library(Hmisc) describe(df.master) library(psych) describe(df.master) ######### Data Visualization # Univariate visualization- Histogram (Continuous data- use density plot, histogram) ggplot(df.master) + geom_histogram(aes(x=AreaPlantedHect), fill="gray", binwidth = 250, stat = "bin", position = "stack") # density plot d<- density(df.master$AreaPlantedHect) plot(d, main = "Kernel Density of Area Planted per Hectare") polygon(d, col="red", border = "blue") rug(df.master$AreaPlantedHect, col = "brown") ggplot(df.master) + geom_density(aes(x=TotalPaidEmployee, colour="red")) ggplot(df.master) + geom_density(aes(x=AreaPlantedHect)) ggplot(df.master) + geom_density(aes(x=ProduceTonne)) ggplot(df.master) + geom_density(aes(x=TapAreaHect)) ggplot(df.master) + geom_density(aes(x=YieldperHectKg)) # boxplots for continuous variables library(magrittr) # for the pipe operator library(dplyr) # for select() # Method 1: selecting individual predictor name boxplot(df.master %>% # Note that the ‘%>%’ (pipe) passes data from the command before to the one after. select(AreaPlantedHect,YieldperHectKg,ProduceTonne,TapAreaHect,TotalPaidEmployee)) # Method 2: Use the minus sign before the predictor you dont want to plot such that the remaining predictors are plotted boxplot(df.master %>% select(-Year), col = c("red","sienna","palevioletred1","royalblue2","brown"), ylab="Count", xlab="Predictors" ) # Line plots- visualizing relationship between two variables ggplot(df.master)+ geom_line(aes(x=AreaPlantedHect, y=YieldperHectKg, color="red")) # interesting: the yield per hectare decline (after 600 hectares) as planted area size increases ggplot(df.master)+ geom_line(aes(x=AreaPlantedHect, y=ProduceTonne, color="red")) # produce increases with area but then it begins to decline after 600 hectares ggplot(df.master)+ geom_line(aes(x=AreaPlantedHect, y=TapAreaHect, color="red")) # there is a positive linear relationship between area planted and tap area ggplot(df.master)+ geom_line(aes(x=AreaPlantedHect, y=TotalPaidEmployee, color="red")) # Again, a positive linear realtionship between area planted and paid employees but there is a sharp decline at 600 hectares ## Checking for High correlation cor(df.master$AreaPlantedHect, df.master$YieldperHectKg) # negative correlation, proving the point above that the yield per hectare decreases as plantation size increases cor(df.master$AreaPlantedHect, df.master$TapAreaHect) # very strong positive correlation cor(df.master$AreaPlantedHect, df.master$ProduceTonne) # very strong positive correlation cor(df.master$AreaPlantedHect, df.master$TotalPaidEmployee) # very strong positive correlation, as land size increases more labour is required correlations<- cor(df.master) # Visualizing the high correlations corrplot(correlations, method="number") # we can see that vars 'TotalPaidEmployee','AreaPlantedHect','ProduceTonee' and 'TapAreaHect' are high positive correlated. # Year and YieldPerHect have low positive correlation; TotalPaidEmployee and YieldHect have semi-strong negative correlation; # AreaPlantedHect and YieldPerHect has strong netaive correlation # ProduceTonne and YieldperhectKg has low negative correlation # YieldperHect and TapAreaHect has low negative correlation highCor<- c("TotalPaidEmployee","AreaPlantedHect","ProduceTonne","TapAreaHect") # Scatterplot for variables that have high correlations attach(df.master) plot(TotalPaidEmployee,AreaPlantedHect) # strong positive correlation plot(TapAreaHect,ProduceTonne) # strong positive correlation plot(TotalPaidEmployee, YieldperHectKg) #semi-strong negative correlation plot(ProduceTonne,YieldperHectKg) # low negative correlation plot(TapAreaHect,YieldperHectKg) # low negative correlation plot(Year,AreaPlantedHect) # strong negative correlation plot(Year,TotalPaidEmployee)# strong negative correlation # Basic scatterplot matrix pairs(~., data = df.master, lower.panel=panel.smooth,pch=20, main="Rubber production Scatterplot Matrix") # where panel.smooth can be used to plot a loess curve for each plot in a scatterplot matrix ggpairs(~., data=df.master) pm= ggpairs(data = df.master, columns = 1:ncol(df.master), upper = list(continuous="density"), title = "Correlations among predictors" ) print(pm) ## Checking relationship between TotalPaidEmployee, AreaPlantedHect, ProduceTonne, TapAreaHect plot1<-ggpairs(data=Training, columns=2:5, mapping = aes(color = "dark green"), axisLabels="show") plot1 boxplot1=boxplot(YieldperHectKg~TapAreaHect, data = Training, col=(c("gold","darkgreen")), main="Yield (Hectare) vs. Rubber tapped area (Hectare)", xlab="Rubber tapped area (Hectare)", ylab="Yield (Hectare)") library(RColorBrewer) #we will select the first 4 colors in the Set1 palette cols<-brewer.pal(n=4,name="Set1") #cols contain the names of four different colors plot(Training$AreaPlantedHect, Training$YieldperHectKg, pch=16, col=cols, main=" Does larger plantation area yield more rubber?", xlab = "Area planted (in hectare)", ylab = "Yield in Kg (per hectare)" ) ### Data Transformation: skewed variable treatment # A variable is considered ‘highly skewed’ if its absolute value is greater than 1. # A variable is considered ‘moderately skewed’ if its absolute value is greater than 0.5. skewedVars <- NA for(i in names(df.master)){ if(is.numeric(df.master[,i])){ if(i != "YieldperHectKg"){ # Enters this block if variable is non-categorical skewVal <- skewness(df.master[,i]) print(paste(i, skewVal, sep = ": ")) if(abs(skewVal) > 0.5){ skewedVars <- c(skewedVars, i) } } } } # None of the predictors are skewed ### Feature Importance library(Boruta) # run boruta analysis set.seed(1234) # pull out the response variable response <- df.master$YieldperHectKg bor.results <- Boruta(df.master,response, maxRuns=101, doTrace=0) bor.results # basically, all the variables are considered important for response variable prediction cat("\n\nRelevant Attributes:\n") getSelectedAttributes(bor.results) plot(bor.results) ######## Splitting the dataset into train and test##### ratio = sample(1:nrow(df.master), size = 0.25*nrow(df.master)) Test = df.master[ratio,] #Test dataset 25% of total Training = df.master[-ratio,] #Train dataset 75% of total dim(Training) dim(Test) # Evaluation metric function RMSE <- function(x,y){ a <- sqrt(sum((log(x)-log(y))^2)/length(y)) return(a) } # Multiple Linear regression linear.mod<- lm(YieldperHectKg~., data = Training) summary(linear.mod) plot(linear.mod, pch=16, which = 1) predict<- predict(linear.mod, Test) RMSE0<- RMSE(predict, Test$YieldperHectKg) RMSE0 # Calculate prediction accuracy and error rates actuals_preds <- data.frame(cbind(actuals=Test$YieldperHectKg, predicteds=predict)) # make actuals_predicteds dataframe. correlation_accuracy <- cor(actuals_preds) correlation_accuracy min_max_accuracy <- mean (apply(actuals_preds, 1, min) / apply(actuals_preds, 1, max)) min_max_accuracy mape <- mean(abs((actuals_preds$predicteds - actuals_preds$actuals))/actuals_preds$actuals) mape # Model Diagnostics # Check the AIC and BIC AIC(linear.mod) BIC(linear.mod) ## creating another model to compare the AIC and BIC linear.mod1<- lm(YieldperHectKg~ProduceTonne+TapAreaHect, data = Training) AIC(linear.mod1) BIC(linear.mod1) # Regression model with significant predictors only linear.mod.1<- lm(YieldperHectKg~ TotalPaidEmployee+AreaPlantedHect+Year, data = train) summary(linear.mod.1) predict<- predict(linear.mod, Test) RMSE0<- RMSE(predict, Test$YieldperHectKg) RMSE0 #### R, Regression Trees, function rpart(), method "anova" #### model <- rpart(YieldperHectKg ~., data = Training, method = "anova") predict <- predict(model, Test) # RMSE RMSE1 <- RMSE(predict, Test$YieldperHectKg) RMSE1 <- round(RMSE1, digits = 3) RMSE1 #0.098 plot1 <- predict-Test$YieldperHectKg ### R, Random Forests, function randomForest(), method "anova" #### help("randomForest") model.forest <- randomForest(YieldperHectKg ~., data = Training, method = "anova", ntree = 300, mtry = 2, #mtry is sqrt(6) replace = F, nodesize = 1, importance = T) varImpPlot(model.forest) # Look at the IncNodePurity plot. From this plot we see that important vars are `TotalPaidEmployee`, `ProduceTonne` and `TapAreaHect` prediction <- predict(model.forest,Test) rmse <- sqrt(mean((log(prediction)-log(Test$YieldperHectKg))^2)) round(rmse, digits = 3) # 0.049 # Alternative way to caluclaute RMSE RMSE2 <- RMSE(predict, Test$YieldperHectKg) RMSE2 <- round(RMSE2, digits = 3) #.098 plot2 <- predict-Test$YieldperHectKg #### CONCLUSION: TO PREDICT Yield per Hectare in Kg # Linear Regression: 0.04533296 #Regression Tree RMSE: 0.098 #Random Forest RMSE: 0.049 #Regression Tree gives the most accutate result in predicting	/scripts/CaseStudy-MY-RubberPlantation.R	permissive	ewillyliew/LearningR	R	false	false	11,907	r	# clear the workspace rm(list=ls()) # Load the required libraries library(ggplot2) library(GGally) # for the ggpairs() library(corrplot) library(plyr) library(mice) library(car) library(rpart) library(randomForest) library(gbm) library(moments) # for skewness function library(tidyr) # for the gather() library(VIM) # for missing data visualization # Data source # Department of Statistics, Malaysia: http://www.dosm.gov.my/v1/index.php?r=column3/accordion&menu_id=aHhRYUpWS3B4VXlYaVBOeUF0WFpWUT09 # load the rubber estate data df1<- read.csv("data/rubberestate/rubber-paidemployee.csv", header = TRUE, sep = ",", stringsAsFactors = FALSE) df2<- read.csv("data/rubberestate/rubber-plantedarea.csv", header = TRUE, sep = ",", stringsAsFactors = FALSE) df3<- read.csv("data/rubberestate/rubber-production.csv", header = TRUE, sep = ",", stringsAsFactors = FALSE) df4<- read.csv("data/rubberestate/rubber-taparea.csv", header = TRUE, sep = ",", stringsAsFactors = FALSE) df5<- read.csv("data/rubberestate/rubber-yield.csv", header = TRUE, sep = ",", stringsAsFactors = FALSE) # Exploratory Data Analysis dim(df1) dim(df2) dim(df3) dim(df4) dim(df5) names(df1) # observation: column name too long. rename them names(df2) # additional space after column names. do formatting names(df3) names(df4) names(df5) head(df1) # You cannot have employees in decimals. Round this variable names(df.master) # Basic Data Management # Renaming the column name # Reference: http://stackoverflow.com/questions/9283171/named-columns-renaming df1<- rename(df1, c("Total.Number.of.Paid.Employee.During.the.Last.Pay.Period..Estate." = "TotalPaidEmployee")) df2<-rename(df2, c("Planted.Area..Estate....000..Hectare" = "AreaPlantedHect")) df3<-rename(df3, c("Production..Estate....000..Tonne" = "ProduceTonne")) df4<-rename(df4, c("Tapped.Area..Estate....000..Hectare" = "TapAreaHect")) df5<-rename(df5, c("Yeild.per.Hectare..Estate...Kg." = "YieldperHectKg")) # Rounding the column value for TotalPaidEmployee because there cant be for example 2.5 employees df1$TotalPaidEmployee<- round(df1$TotalPaidEmployee) # Inner Join the data frames on common column df.m1<- merge(df1,df2, by="Year") df.m2<- merge(df3,df4, by="Year") df.m3<- merge(df.m2, df5, by="Year") df.master<- merge(df.m1, df.m3, by="Year") summary(df.master) # Missing data treatment aggr_plot <- aggr(df.master, col=c('navyblue','red'), numbers=TRUE, sortVars=TRUE, labels=names(df.master), cex.axis=.7, gap=3, ylab=c("Histogram of missing data","Pattern")) colSums(is.na(df.master)) # There is only 1 missing row tempData <- mice(df.master,m=5,maxit=50,meth='pmm',seed=1234) df.master<- mice::complete(tempData,1) colSums(is.na(df.master)) # Describe the data library(Hmisc) describe(df.master) library(psych) describe(df.master) ######### Data Visualization # Univariate visualization- Histogram (Continuous data- use density plot, histogram) ggplot(df.master) + geom_histogram(aes(x=AreaPlantedHect), fill="gray", binwidth = 250, stat = "bin", position = "stack") # density plot d<- density(df.master$AreaPlantedHect) plot(d, main = "Kernel Density of Area Planted per Hectare") polygon(d, col="red", border = "blue") rug(df.master$AreaPlantedHect, col = "brown") ggplot(df.master) + geom_density(aes(x=TotalPaidEmployee, colour="red")) ggplot(df.master) + geom_density(aes(x=AreaPlantedHect)) ggplot(df.master) + geom_density(aes(x=ProduceTonne)) ggplot(df.master) + geom_density(aes(x=TapAreaHect)) ggplot(df.master) + geom_density(aes(x=YieldperHectKg)) # boxplots for continuous variables library(magrittr) # for the pipe operator library(dplyr) # for select() # Method 1: selecting individual predictor name boxplot(df.master %>% # Note that the ‘%>%’ (pipe) passes data from the command before to the one after. select(AreaPlantedHect,YieldperHectKg,ProduceTonne,TapAreaHect,TotalPaidEmployee)) # Method 2: Use the minus sign before the predictor you dont want to plot such that the remaining predictors are plotted boxplot(df.master %>% select(-Year), col = c("red","sienna","palevioletred1","royalblue2","brown"), ylab="Count", xlab="Predictors" ) # Line plots- visualizing relationship between two variables ggplot(df.master)+ geom_line(aes(x=AreaPlantedHect, y=YieldperHectKg, color="red")) # interesting: the yield per hectare decline (after 600 hectares) as planted area size increases ggplot(df.master)+ geom_line(aes(x=AreaPlantedHect, y=ProduceTonne, color="red")) # produce increases with area but then it begins to decline after 600 hectares ggplot(df.master)+ geom_line(aes(x=AreaPlantedHect, y=TapAreaHect, color="red")) # there is a positive linear relationship between area planted and tap area ggplot(df.master)+ geom_line(aes(x=AreaPlantedHect, y=TotalPaidEmployee, color="red")) # Again, a positive linear realtionship between area planted and paid employees but there is a sharp decline at 600 hectares ## Checking for High correlation cor(df.master$AreaPlantedHect, df.master$YieldperHectKg) # negative correlation, proving the point above that the yield per hectare decreases as plantation size increases cor(df.master$AreaPlantedHect, df.master$TapAreaHect) # very strong positive correlation cor(df.master$AreaPlantedHect, df.master$ProduceTonne) # very strong positive correlation cor(df.master$AreaPlantedHect, df.master$TotalPaidEmployee) # very strong positive correlation, as land size increases more labour is required correlations<- cor(df.master) # Visualizing the high correlations corrplot(correlations, method="number") # we can see that vars 'TotalPaidEmployee','AreaPlantedHect','ProduceTonee' and 'TapAreaHect' are high positive correlated. # Year and YieldPerHect have low positive correlation; TotalPaidEmployee and YieldHect have semi-strong negative correlation; # AreaPlantedHect and YieldPerHect has strong netaive correlation # ProduceTonne and YieldperhectKg has low negative correlation # YieldperHect and TapAreaHect has low negative correlation highCor<- c("TotalPaidEmployee","AreaPlantedHect","ProduceTonne","TapAreaHect") # Scatterplot for variables that have high correlations attach(df.master) plot(TotalPaidEmployee,AreaPlantedHect) # strong positive correlation plot(TapAreaHect,ProduceTonne) # strong positive correlation plot(TotalPaidEmployee, YieldperHectKg) #semi-strong negative correlation plot(ProduceTonne,YieldperHectKg) # low negative correlation plot(TapAreaHect,YieldperHectKg) # low negative correlation plot(Year,AreaPlantedHect) # strong negative correlation plot(Year,TotalPaidEmployee)# strong negative correlation # Basic scatterplot matrix pairs(~., data = df.master, lower.panel=panel.smooth,pch=20, main="Rubber production Scatterplot Matrix") # where panel.smooth can be used to plot a loess curve for each plot in a scatterplot matrix ggpairs(~., data=df.master) pm= ggpairs(data = df.master, columns = 1:ncol(df.master), upper = list(continuous="density"), title = "Correlations among predictors" ) print(pm) ## Checking relationship between TotalPaidEmployee, AreaPlantedHect, ProduceTonne, TapAreaHect plot1<-ggpairs(data=Training, columns=2:5, mapping = aes(color = "dark green"), axisLabels="show") plot1 boxplot1=boxplot(YieldperHectKg~TapAreaHect, data = Training, col=(c("gold","darkgreen")), main="Yield (Hectare) vs. Rubber tapped area (Hectare)", xlab="Rubber tapped area (Hectare)", ylab="Yield (Hectare)") library(RColorBrewer) #we will select the first 4 colors in the Set1 palette cols<-brewer.pal(n=4,name="Set1") #cols contain the names of four different colors plot(Training$AreaPlantedHect, Training$YieldperHectKg, pch=16, col=cols, main=" Does larger plantation area yield more rubber?", xlab = "Area planted (in hectare)", ylab = "Yield in Kg (per hectare)" ) ### Data Transformation: skewed variable treatment # A variable is considered ‘highly skewed’ if its absolute value is greater than 1. # A variable is considered ‘moderately skewed’ if its absolute value is greater than 0.5. skewedVars <- NA for(i in names(df.master)){ if(is.numeric(df.master[,i])){ if(i != "YieldperHectKg"){ # Enters this block if variable is non-categorical skewVal <- skewness(df.master[,i]) print(paste(i, skewVal, sep = ": ")) if(abs(skewVal) > 0.5){ skewedVars <- c(skewedVars, i) } } } } # None of the predictors are skewed ### Feature Importance library(Boruta) # run boruta analysis set.seed(1234) # pull out the response variable response <- df.master$YieldperHectKg bor.results <- Boruta(df.master,response, maxRuns=101, doTrace=0) bor.results # basically, all the variables are considered important for response variable prediction cat("\n\nRelevant Attributes:\n") getSelectedAttributes(bor.results) plot(bor.results) ######## Splitting the dataset into train and test##### ratio = sample(1:nrow(df.master), size = 0.25*nrow(df.master)) Test = df.master[ratio,] #Test dataset 25% of total Training = df.master[-ratio,] #Train dataset 75% of total dim(Training) dim(Test) # Evaluation metric function RMSE <- function(x,y){ a <- sqrt(sum((log(x)-log(y))^2)/length(y)) return(a) } # Multiple Linear regression linear.mod<- lm(YieldperHectKg~., data = Training) summary(linear.mod) plot(linear.mod, pch=16, which = 1) predict<- predict(linear.mod, Test) RMSE0<- RMSE(predict, Test$YieldperHectKg) RMSE0 # Calculate prediction accuracy and error rates actuals_preds <- data.frame(cbind(actuals=Test$YieldperHectKg, predicteds=predict)) # make actuals_predicteds dataframe. correlation_accuracy <- cor(actuals_preds) correlation_accuracy min_max_accuracy <- mean (apply(actuals_preds, 1, min) / apply(actuals_preds, 1, max)) min_max_accuracy mape <- mean(abs((actuals_preds$predicteds - actuals_preds$actuals))/actuals_preds$actuals) mape # Model Diagnostics # Check the AIC and BIC AIC(linear.mod) BIC(linear.mod) ## creating another model to compare the AIC and BIC linear.mod1<- lm(YieldperHectKg~ProduceTonne+TapAreaHect, data = Training) AIC(linear.mod1) BIC(linear.mod1) # Regression model with significant predictors only linear.mod.1<- lm(YieldperHectKg~ TotalPaidEmployee+AreaPlantedHect+Year, data = train) summary(linear.mod.1) predict<- predict(linear.mod, Test) RMSE0<- RMSE(predict, Test$YieldperHectKg) RMSE0 #### R, Regression Trees, function rpart(), method "anova" #### model <- rpart(YieldperHectKg ~., data = Training, method = "anova") predict <- predict(model, Test) # RMSE RMSE1 <- RMSE(predict, Test$YieldperHectKg) RMSE1 <- round(RMSE1, digits = 3) RMSE1 #0.098 plot1 <- predict-Test$YieldperHectKg ### R, Random Forests, function randomForest(), method "anova" #### help("randomForest") model.forest <- randomForest(YieldperHectKg ~., data = Training, method = "anova", ntree = 300, mtry = 2, #mtry is sqrt(6) replace = F, nodesize = 1, importance = T) varImpPlot(model.forest) # Look at the IncNodePurity plot. From this plot we see that important vars are `TotalPaidEmployee`, `ProduceTonne` and `TapAreaHect` prediction <- predict(model.forest,Test) rmse <- sqrt(mean((log(prediction)-log(Test$YieldperHectKg))^2)) round(rmse, digits = 3) # 0.049 # Alternative way to caluclaute RMSE RMSE2 <- RMSE(predict, Test$YieldperHectKg) RMSE2 <- round(RMSE2, digits = 3) #.098 plot2 <- predict-Test$YieldperHectKg #### CONCLUSION: TO PREDICT Yield per Hectare in Kg # Linear Regression: 0.04533296 #Regression Tree RMSE: 0.098 #Random Forest RMSE: 0.049 #Regression Tree gives the most accutate result in predicting
input.data.x <- iris[,-5] cluster <- function(k,input.data.x) { #input.data.x <- input.data.x[sample(nrow(input.data.x)),] #table randomization cluster.lengths <- c(0,sample(1:nrow(input.data.x),k-1) , nrow(input.data.x)) cluster.list <- list() for (i in 1:k) { cluster.list[[length(cluster.list)+1]] <- input.data.x[(cluster.lengths[i] + 1):cluster.lengths[i+1], ] } return(cluster.list) }	/clustering.r	no_license	atishdixit16/k-means-algorithm-minimum-computational-complexity-	R	false	false	401	r	input.data.x <- iris[,-5] cluster <- function(k,input.data.x) { #input.data.x <- input.data.x[sample(nrow(input.data.x)),] #table randomization cluster.lengths <- c(0,sample(1:nrow(input.data.x),k-1) , nrow(input.data.x)) cluster.list <- list() for (i in 1:k) { cluster.list[[length(cluster.list)+1]] <- input.data.x[(cluster.lengths[i] + 1):cluster.lengths[i+1], ] } return(cluster.list) }
# All of these models are (loosely) derived from assignments in my Dynamics of # Infectious Disease (EPI 501) course at HSPH. There is a nonzero probability # errors are contained within. ## Load packages we'll need. library(shiny); library(deSolve); library(ggplot2); library(quantmod) ## Define various comparmental models we will use later. All models are in an ## open population, but that changes by simply setting births and deaths to 0. # 1) N is total population. S is susceptible. E is exposed (but not # infectious). I is infectious. R is recovered. # 2) b is the probability of transmission from one infected to a susceptible # at one point in time (i.e., one contact). # 3) k is the contact rate. # 4) Models that incorporate seasonal variation decompose k such that: # k = k0 * (1 + k1 * cos(2 * pi * t)) # where k0 is the overall average contact rate, k1 is the amplitude # (fluctuation about k0) and t is time. For simplicity, this can only # be added when the time scale is yearly. # 5) Together, bk = beta in our models. # 6) r is the rate of recovery--also the reciprocal of disease duration. # 7) L is the latent period where a person is neither infectious nor # susceptible. ### Basic SIR open population SIR.open <- function(t, x, parms) { with(as.list(c(parms, x)), { N <- S + I + R dS <- birthN - betaSI/N - deathS - pvbirthN dI <- betaSI/N - rI - deathI dR <- rI - deathR + pvbirthN result <- c(dS, dI, dR) list(result) }) } ### Basic SEIR open population SEIR.open <- function(t, x, parms) { with(as.list(c(parms, x)), { N <- S + E + I + R dS <- birthN - betaSI/N - deathS - pvbirthN dE <- betaSI/N - LE - deathE dI <- LE - rI - deathI dR <- rI - deathR + pvbirthN result <- c(dS, dE, dI, dR) list(result) }) } ### SEIR with seasonal variation SIR.kt <- function(t, x, parms) { with(as.list(c(parms, x)), { k <- k0 (1 + k1 * cos(2 * pi * (t/t.adj))) beta <- b * k N <- S + I + R dS <- -betaSI/N + birthN - deathS - pvbirthN dI <- betaSI/N - rI - deathI dR <- rI - deathR + pvbirthN result <- c(dS, dI, dR) list(result) }) } ### SEIR with seasonal variation SEIR.kt <- function(t, x, parms) { with(as.list(c(parms, x)), { k <- k0 * (1 + k1 * cos(2 * pi * (t/t.adj))) beta <- b * k N <- S + E + I + R dS <- -betaSI/N + birthN - deathS - pvbirthN dE <- betaSI/N - kE - deathE dI <- kE - rI - deathI dR <- rI - deathR + pvbirthN result <- c(dS, dE, dI, dR) list(result) }) } ## Define a function to find max infections to put on plots later. max.inf <- function(x) { infectious <- round(max(x$people[x$compartments=="I"])) timestep <- which.max(x$people[x$compartments=="I"]) info <- cbind(infectious, timestep) return(info) } ## Index of second highest infection value. sec.index <- function(x) { index <- round(findPeaks(x$people[x$compartments=="I"], thresh=.1)[2]) if (is.na(index)) { return(0) } else return(as.integer(index)) } ## Makes the data in a more ggplot-friendly format stacker <- function(df){ df.stack <- stack(df[, -1]) df.stack$time <- rep(seq_len(nrow(df)), length(table(df.stack$ind))) names(df.stack)[1:2] <- c("people", "compartments") df.stack$compartments <- factor(df.stack$compartments, levels=c("S","E","I","R"), ordered=TRUE) return(df.stack) } ## Start the Shiny stuff shinyServer(function(input, output) { output$guessPlot <- renderPlot(function() { if (input$timex=="days") { r.adj <- 1; k.adj <- 1/7; bd.adj <- 365; L.adj <- 1; t.adj <- 365; pv.adj<-1 timemax <- input$tmaxday } else { r.adj<-365; k.adj<-52; bd.adj<-1; L.adj<-365; t.adj<-1; pv.adj<-1 timemax <- input$tmaxyear } dt <- seq(0, timemax, by=.01) if (input$norecov==TRUE) r.adj <- 0 # First, making sure we use the right model. ## SIR without seasonal effects if(input$L==0 & input$seasonal==0) { r <- (1/input$D) r.adj b <- input$b k <- input$k * k.adj birth <- death <- input$bdrate/bd.adj pv <- (input$vaccinput$vacceff)/pv.adj inits <- c(S=1e6-1, I=1, R=0) guess_pars <- c(r=r, beta=bk, birth=birth, death=death, pv=pv) guess <- stacker(as.data.frame(ode(inits, dt, SIR.open, parms=guess_pars))) } else if (input$L!=0 & input$seasonal==0) { ## SEIR without seasonal effects r <- (1/input$D) * r.adj b <- input$b k <- input$k * k.adj L <- (1/input$L) * L.adj birth <- death <- input$bdrate/bd.adj pv <- (input$vaccinput$vacceff)/pv.adj inits <- c(S=1e6-1, E=0, I=1, R=0) guess_pars <- c(r=r, beta=bk, birth=birth, death=death, L=L, pv=pv) guess <- stacker(as.data.frame(ode(inits, dt, SEIR.open, parms=guess_pars))) } else if (input$L==0 & input$seasonal!=0) { ## SIR with seasonal effects r <- (1/input$D) * r.adj b <- input$b k0 <- input$k * k.adj k1 <- input$seasonal birth <- death <- input$bdrate/bd.adj pv <- (input$vaccinput$vacceff)/pv.adj inits <- c(S=1e6-1, I=1, R=0) guess_pars <- c(r=r, b=b, birth=birth, death=death, k0=k0, k1=k1, t.adj=t.adj, pv=pv) guess <- stacker(as.data.frame(ode(inits, dt, SIR.kt, parms=guess_pars))) } else if (input$L!=0 & input$seasonal!=0) { ## SEIR with seasonal effects r <- (1/input$D) r.adj b <- input$b k0 <- input$k * k.adj k1 <- input$seasonal L <- (1/input$L) * L.adj birth <- death <- input$bdrate/bd.adj pv <- (input$vaccinput$vacceff)/pv.adj inits <- c(S=1e6-1, E=0, I=1, R=0) guess_pars <- c(r=r, b=b, birth=birth, death=death, k0=k0, k1=k1, t.adj=t.adj, L=L, pv=pv) guess <- stacker(as.data.frame(ode(inits, dt, SEIR.kt, parms=guess_pars))) } if (input$second.inf==TRUE) { guess <- subset(guess, time > (.95 sec.index(guess))) } # Max infections max.guess <- as.data.frame(max.inf(guess)) max.guess$compartments <- "I" max.guess$adj.timestep <- max.guess$timestep / 100 max.guess$maxtime <- max(guess$time) # Base plots if (input$inf.only==FALSE) { base.plot <- ggplot(guess, aes(x=time, y=people, group=compartments, color=compartments)) + xlab("Time") + ylab("Number of People") } else { base.plot <- ggplot(guess[guess$compartments=="I",], aes(x=time, y=people, group=compartments, color=compartments)) + xlab("Time") + ylab("Number of Infected") } label.plot <- base.plot + geom_line(alpha=.8) + theme_bw() + theme(legend.position="bottom") + theme(legend.title=element_blank()) # # Conditioning plots # if (input$maxinfect==TRUE) { # # } else { # rescaledx.plot <- label.plot + # scale_x_continuous(labels=function(x) x/100) + # geom_text(data=max.guess, # aes(x=.95*maxtime, y=infectious, # label=paste(infectious, "infections\nat", adj.timestep)), # hjust=1, vjust=1, show_guide=FALSE, size=5, # alpha=.5, color="black") # } rescaledx.plot <- label.plot + scale_x_continuous(labels=function(x) x/100) final.plot <- rescaledx.plot print(final.plot) }) # closes reactivePlot }) # Closes shinyServer	/server.R	permissive	proto4426/DiseaseDynamics	R	false	false	8,774	r	# All of these models are (loosely) derived from assignments in my Dynamics of # Infectious Disease (EPI 501) course at HSPH. There is a nonzero probability # errors are contained within. ## Load packages we'll need. library(shiny); library(deSolve); library(ggplot2); library(quantmod) ## Define various comparmental models we will use later. All models are in an ## open population, but that changes by simply setting births and deaths to 0. # 1) N is total population. S is susceptible. E is exposed (but not # infectious). I is infectious. R is recovered. # 2) b is the probability of transmission from one infected to a susceptible # at one point in time (i.e., one contact). # 3) k is the contact rate. # 4) Models that incorporate seasonal variation decompose k such that: # k = k0 * (1 + k1 * cos(2 * pi * t)) # where k0 is the overall average contact rate, k1 is the amplitude # (fluctuation about k0) and t is time. For simplicity, this can only # be added when the time scale is yearly. # 5) Together, bk = beta in our models. # 6) r is the rate of recovery--also the reciprocal of disease duration. # 7) L is the latent period where a person is neither infectious nor # susceptible. ### Basic SIR open population SIR.open <- function(t, x, parms) { with(as.list(c(parms, x)), { N <- S + I + R dS <- birthN - betaSI/N - deathS - pvbirthN dI <- betaSI/N - rI - deathI dR <- rI - deathR + pvbirthN result <- c(dS, dI, dR) list(result) }) } ### Basic SEIR open population SEIR.open <- function(t, x, parms) { with(as.list(c(parms, x)), { N <- S + E + I + R dS <- birthN - betaSI/N - deathS - pvbirthN dE <- betaSI/N - LE - deathE dI <- LE - rI - deathI dR <- rI - deathR + pvbirthN result <- c(dS, dE, dI, dR) list(result) }) } ### SEIR with seasonal variation SIR.kt <- function(t, x, parms) { with(as.list(c(parms, x)), { k <- k0 (1 + k1 * cos(2 * pi * (t/t.adj))) beta <- b * k N <- S + I + R dS <- -betaSI/N + birthN - deathS - pvbirthN dI <- betaSI/N - rI - deathI dR <- rI - deathR + pvbirthN result <- c(dS, dI, dR) list(result) }) } ### SEIR with seasonal variation SEIR.kt <- function(t, x, parms) { with(as.list(c(parms, x)), { k <- k0 * (1 + k1 * cos(2 * pi * (t/t.adj))) beta <- b * k N <- S + E + I + R dS <- -betaSI/N + birthN - deathS - pvbirthN dE <- betaSI/N - kE - deathE dI <- kE - rI - deathI dR <- rI - deathR + pvbirthN result <- c(dS, dE, dI, dR) list(result) }) } ## Define a function to find max infections to put on plots later. max.inf <- function(x) { infectious <- round(max(x$people[x$compartments=="I"])) timestep <- which.max(x$people[x$compartments=="I"]) info <- cbind(infectious, timestep) return(info) } ## Index of second highest infection value. sec.index <- function(x) { index <- round(findPeaks(x$people[x$compartments=="I"], thresh=.1)[2]) if (is.na(index)) { return(0) } else return(as.integer(index)) } ## Makes the data in a more ggplot-friendly format stacker <- function(df){ df.stack <- stack(df[, -1]) df.stack$time <- rep(seq_len(nrow(df)), length(table(df.stack$ind))) names(df.stack)[1:2] <- c("people", "compartments") df.stack$compartments <- factor(df.stack$compartments, levels=c("S","E","I","R"), ordered=TRUE) return(df.stack) } ## Start the Shiny stuff shinyServer(function(input, output) { output$guessPlot <- renderPlot(function() { if (input$timex=="days") { r.adj <- 1; k.adj <- 1/7; bd.adj <- 365; L.adj <- 1; t.adj <- 365; pv.adj<-1 timemax <- input$tmaxday } else { r.adj<-365; k.adj<-52; bd.adj<-1; L.adj<-365; t.adj<-1; pv.adj<-1 timemax <- input$tmaxyear } dt <- seq(0, timemax, by=.01) if (input$norecov==TRUE) r.adj <- 0 # First, making sure we use the right model. ## SIR without seasonal effects if(input$L==0 & input$seasonal==0) { r <- (1/input$D) r.adj b <- input$b k <- input$k * k.adj birth <- death <- input$bdrate/bd.adj pv <- (input$vaccinput$vacceff)/pv.adj inits <- c(S=1e6-1, I=1, R=0) guess_pars <- c(r=r, beta=bk, birth=birth, death=death, pv=pv) guess <- stacker(as.data.frame(ode(inits, dt, SIR.open, parms=guess_pars))) } else if (input$L!=0 & input$seasonal==0) { ## SEIR without seasonal effects r <- (1/input$D) * r.adj b <- input$b k <- input$k * k.adj L <- (1/input$L) * L.adj birth <- death <- input$bdrate/bd.adj pv <- (input$vaccinput$vacceff)/pv.adj inits <- c(S=1e6-1, E=0, I=1, R=0) guess_pars <- c(r=r, beta=bk, birth=birth, death=death, L=L, pv=pv) guess <- stacker(as.data.frame(ode(inits, dt, SEIR.open, parms=guess_pars))) } else if (input$L==0 & input$seasonal!=0) { ## SIR with seasonal effects r <- (1/input$D) * r.adj b <- input$b k0 <- input$k * k.adj k1 <- input$seasonal birth <- death <- input$bdrate/bd.adj pv <- (input$vaccinput$vacceff)/pv.adj inits <- c(S=1e6-1, I=1, R=0) guess_pars <- c(r=r, b=b, birth=birth, death=death, k0=k0, k1=k1, t.adj=t.adj, pv=pv) guess <- stacker(as.data.frame(ode(inits, dt, SIR.kt, parms=guess_pars))) } else if (input$L!=0 & input$seasonal!=0) { ## SEIR with seasonal effects r <- (1/input$D) r.adj b <- input$b k0 <- input$k * k.adj k1 <- input$seasonal L <- (1/input$L) * L.adj birth <- death <- input$bdrate/bd.adj pv <- (input$vaccinput$vacceff)/pv.adj inits <- c(S=1e6-1, E=0, I=1, R=0) guess_pars <- c(r=r, b=b, birth=birth, death=death, k0=k0, k1=k1, t.adj=t.adj, L=L, pv=pv) guess <- stacker(as.data.frame(ode(inits, dt, SEIR.kt, parms=guess_pars))) } if (input$second.inf==TRUE) { guess <- subset(guess, time > (.95 sec.index(guess))) } # Max infections max.guess <- as.data.frame(max.inf(guess)) max.guess$compartments <- "I" max.guess$adj.timestep <- max.guess$timestep / 100 max.guess$maxtime <- max(guess$time) # Base plots if (input$inf.only==FALSE) { base.plot <- ggplot(guess, aes(x=time, y=people, group=compartments, color=compartments)) + xlab("Time") + ylab("Number of People") } else { base.plot <- ggplot(guess[guess$compartments=="I",], aes(x=time, y=people, group=compartments, color=compartments)) + xlab("Time") + ylab("Number of Infected") } label.plot <- base.plot + geom_line(alpha=.8) + theme_bw() + theme(legend.position="bottom") + theme(legend.title=element_blank()) # # Conditioning plots # if (input$maxinfect==TRUE) { # # } else { # rescaledx.plot <- label.plot + # scale_x_continuous(labels=function(x) x/100) + # geom_text(data=max.guess, # aes(x=.95*maxtime, y=infectious, # label=paste(infectious, "infections\nat", adj.timestep)), # hjust=1, vjust=1, show_guide=FALSE, size=5, # alpha=.5, color="black") # } rescaledx.plot <- label.plot + scale_x_continuous(labels=function(x) x/100) final.plot <- rescaledx.plot print(final.plot) }) # closes reactivePlot }) # Closes shinyServer
library(PresenceAbsence) ### Name: roc.plot.calculate ### Title: ROC Plot Calculations ### Aliases: roc.plot.calculate ### Keywords: models ### ** Examples data(SIM3DATA) roc.plot.calculate(SIM3DATA,which.model=2)	/data/genthat_extracted_code/PresenceAbsence/examples/roc.plot.calculate.Rd.R	no_license	surayaaramli/typeRrh	R	false	false	222	r	library(PresenceAbsence) ### Name: roc.plot.calculate ### Title: ROC Plot Calculations ### Aliases: roc.plot.calculate ### Keywords: models ### ** Examples data(SIM3DATA) roc.plot.calculate(SIM3DATA,which.model=2)
#' match assembled transcripts to annotated transcripts #' #' @param assembled \code{GRangesList} object representing assembled transcripts #' @param annotated \code{GRangesList} object representing annotated transcripts #' #' @details If \code{gown} is a \code{ballgown} object, \code{assembled} can be #' \code{structure(gown)$trans} (or any subset). You can generate a #' \code{GRangesList} object #' containing annotated transcripts from a gtf file using the #' \code{\link{gffReadGR}} function and #' setting \code{splitByTranscripts=TRUE}. #' #' @return data frame, where each row contains \code{assembledInd} and #' \code{annotatedInd} (indexes of overlapping transcripts in \code{assembled} #' and \code{annotated}), and the percent overlap between the two transcripts. #' #' @author Alyssa Frazee #' #' @export #' @examples #' data(bg) #' gtfPath = system.file('extdata', 'annot.gtf.gz', package='ballgown') #' annot = gffReadGR(gtfPath, splitByTranscript=TRUE) #' info = annotate_assembly(assembled=structure(bg)$trans, annotated=annot) annotate_assembly = function(assembled, annotated){ stopifnot(class(annotated) == 'GRangesList' & class(assembled) == 'GRangesList') # things will get out of order: keep track names_annot = names(annotated) names_assmb = names(assembled) # get rid of metadata: annotatedUL = unlist(annotated) mcols(annotatedUL) = NULL annotated = split(annotatedUL, names(annotatedUL)) annotated = annotated[match(names_annot, names(annotated))] # for assembly: get rid of metadata assembledUL = unlist(assembled) mcols(assembledUL) = NULL assembled = split(assembledUL, names(assembledUL)) assembled = assembled[match(names_assmb, names(assembled))] # find the overlaps: ol = findOverlaps(assembled, annotated) # get lists of corresponding assembled/annotated transcripts: assembled_sort = assembled[queryHits(ol)] annotated_sort = annotated[subjectHits(ol)] # concatenate the appropriate GRanges objects (for overlapping transcripts) assembled_overlapIDs = rep(1:length(ol), times=elementLengths(assembled_sort)) annotated_overlapIDs = rep(1:length(ol), times=elementLengths(annotated_sort)) all_transcripts = c(unlist(assembled_sort), unlist(annotated_sort)) overlapping = split(all_transcripts, c(assembled_overlapIDs, annotated_overlapIDs)) # calculate percentage overlap: coverages = coverage(ranges(overlapping)) runvals = runValue(coverages) runlengths = runLength(coverages) pct = sum(runlengths[runvals==2]) / sum(runlengths[runvals==1 \| runvals==2]) return(data.frame(assembledInd=queryHits(ol), annotatedInd=subjectHits(ol), percent=pct)) }	/R/annotate_assembly.R	no_license	alyssafrazee/ballgown-release	R	false	false	2,788	r	#' match assembled transcripts to annotated transcripts #' #' @param assembled \code{GRangesList} object representing assembled transcripts #' @param annotated \code{GRangesList} object representing annotated transcripts #' #' @details If \code{gown} is a \code{ballgown} object, \code{assembled} can be #' \code{structure(gown)$trans} (or any subset). You can generate a #' \code{GRangesList} object #' containing annotated transcripts from a gtf file using the #' \code{\link{gffReadGR}} function and #' setting \code{splitByTranscripts=TRUE}. #' #' @return data frame, where each row contains \code{assembledInd} and #' \code{annotatedInd} (indexes of overlapping transcripts in \code{assembled} #' and \code{annotated}), and the percent overlap between the two transcripts. #' #' @author Alyssa Frazee #' #' @export #' @examples #' data(bg) #' gtfPath = system.file('extdata', 'annot.gtf.gz', package='ballgown') #' annot = gffReadGR(gtfPath, splitByTranscript=TRUE) #' info = annotate_assembly(assembled=structure(bg)$trans, annotated=annot) annotate_assembly = function(assembled, annotated){ stopifnot(class(annotated) == 'GRangesList' & class(assembled) == 'GRangesList') # things will get out of order: keep track names_annot = names(annotated) names_assmb = names(assembled) # get rid of metadata: annotatedUL = unlist(annotated) mcols(annotatedUL) = NULL annotated = split(annotatedUL, names(annotatedUL)) annotated = annotated[match(names_annot, names(annotated))] # for assembly: get rid of metadata assembledUL = unlist(assembled) mcols(assembledUL) = NULL assembled = split(assembledUL, names(assembledUL)) assembled = assembled[match(names_assmb, names(assembled))] # find the overlaps: ol = findOverlaps(assembled, annotated) # get lists of corresponding assembled/annotated transcripts: assembled_sort = assembled[queryHits(ol)] annotated_sort = annotated[subjectHits(ol)] # concatenate the appropriate GRanges objects (for overlapping transcripts) assembled_overlapIDs = rep(1:length(ol), times=elementLengths(assembled_sort)) annotated_overlapIDs = rep(1:length(ol), times=elementLengths(annotated_sort)) all_transcripts = c(unlist(assembled_sort), unlist(annotated_sort)) overlapping = split(all_transcripts, c(assembled_overlapIDs, annotated_overlapIDs)) # calculate percentage overlap: coverages = coverage(ranges(overlapping)) runvals = runValue(coverages) runlengths = runLength(coverages) pct = sum(runlengths[runvals==2]) / sum(runlengths[runvals==1 \| runvals==2]) return(data.frame(assembledInd=queryHits(ol), annotatedInd=subjectHits(ol), percent=pct)) }
library(rvest) library(dplyr) library(tidyverse) library(stringr) library(tibble) install.packages("RSQLite") library(RSQLite) install.packages("sentimentr") library(sentimentr) #Reviews data function product<-function(keyword,page) { url<-"https://www.amazon.com/product-reviews/%s/ref=cm_cr_arp_d_paging_btm_%i?ie=UTF8&reviewerType=all_reviews&pageNumber=%i" amazon<-sprintf(url,URLencode(keyword),page,page) reviewpage<-read_html(amazon) profile_name <- reviewpage%>% html_nodes(".review-byline .author")%>% html_text(trim=T)%>% gsub("By","",.) personal_rating <- reviewpage%>% html_nodes("#cm_cr-review_list .review-rating")%>% html_text()%>% str_extract("\\d")%>% as.numeric() description <- reviewpage%>% html_nodes("#cm_cr-review_list .a-color-base")%>% html_text(trim=T) review <- reviewpage%>% html_nodes(".review-text")%>% html_text(trim=T) verification <- reviewpage%>% html_nodes(".review-data.a-spacing-mini")%>% html_text(trim=T)%>% grepl("Verified Purchase",.) product_id<-keyword df <- data.frame(profile_name,personal_rating,description,review,verification,product_id) } ma<-dbConnect(SQLite(),dbname="x.sqlite") dbSendQuery(conn=ma,"create table maintable( product_id1 text primary key, name1 text, price1 num, ratings1 num, no_of_reviews1 num) without rowid") dbSendQuery(conn=ma,"create table reviewtable( profile_name text, personal_rating num, description text, review text, verification logical, product_id1 text, foreign key(product_id1) references maintable(product_id1))") multiple_page <- function(keyword,page) { x <- map(1:page,function(n) { product(keyword,n) })%>% bind_rows() dbWriteTable(conn=ma,name="reviewtable",value=x,row.names=F,header=T,overwrite=T) } multiple_page("B0756CYWWD",4) #main page function main_page <- function(keyword) { main <- "https://www.amazon.com/gp/product/%s" item <- sprintf(main,URLencode(keyword)) items <- read_html(item) name <- items%>% html_node("#productTitle")%>% html_text(trim=T) ratings <- items%>% html_node(".arp-rating-out-of-text")%>% html_text()%>% str_extract("\\d{1}.\\d{1}")%>% as.numeric() price <- items%>% html_node("#priceblock_ourprice")%>% html_text(trim=T)%>% gsub("\\$","",.)%>% as.numeric() no_of_reviews <- items%>% html_node("#acrCustomerReviewText")%>% html_text(trim=T)%>% gsub("[A-z]","",.)%>% gsub(",","",.)%>% as.numeric() product_id <- keyword df <- data_frame(product_id,name,price,ratings,no_of_reviews) dbWriteTable(conn=ma,name="maintable",value=df,row.names=F,header=T,overwrite=T) } main_page("B0756CYWWD") a<-dbGetQuery(conn=ma,"select * from maintable m join reviewtable r on m.product_id=r.product_id") head(a) dbGetQuery(conn=ma,"select * from maintable") sent_agg <- with(a, sentiment_by(review)) head(sent_agg) par(mfrow=c(1,2)) with(a, hist(personal_rating)) with(sent_agg, hist(ave_sentiment)) mean(a$personal_rating) mean(sent_agg$ave_sentiment) best_reviews <- slice(a, top_n(sent_agg, 10, ave_sentiment)$element_id) with(best_reviews, sentiment_by(review)) %>% highlight() worst_reviews <- slice(a, top_n(sent_agg, 10, -ave_sentiment)$element_id) with(worst_reviews, sentiment_by(review)) %>% highlight() library(dplyr) library(stringr) library(tidytext) get_sentiments("afinn") get_sentiments("bing") get_sentiments("nrc") b<-a$review text_tb <- tibble(c = seq_along(b), text = b) head(text_tb) x<-text_tb %>% unnest_tokens(word, text) x x%>% count(word,sort=T) x %>% anti_join(stop_words) %>% count(word, sort = TRUE) x %>% right_join(get_sentiments("nrc")) %>% filter(!is.na(sentiment)) %>% count(sentiment, sort = TRUE) bing_word_counts <- x %>% inner_join(get_sentiments("bing")) %>% count(word, sentiment, sort = TRUE) %>% ungroup() bing_word_counts %>% group_by(sentiment) %>% top_n(10) %>% ggplot(aes(reorder(word, n), n, fill = sentiment)) + geom_bar(alpha = 0.8, stat = "identity", show.legend = FALSE) + facet_wrap(~sentiment, scales = "free_y") + labs(y = "Contribution to sentiment", x = NULL) + coord_flip() install.packages("wordcloud") library(wordcloud) x %>% anti_join(stop_words) %>% count(word) %>% with(wordcloud(word, n, max.words = 100)) library(reshape2) x %>% inner_join(get_sentiments("bing")) %>% count(word, sentiment, sort = TRUE) %>% acast(word ~ sentiment, value.var = "n", fill = 0) %>% comparison.cloud(colors = c("#F8766D", "#00BFC4"), max.words = 100) afinn <- x %>% mutate(word_count = 1:n(), index = word_count %/% 500 + 1) %>% inner_join(get_sentiments("afinn")) %>% group_by(index) %>% summarise(sentiment = sum(score)) %>% mutate(method = "AFINN") afinn	/amazon sen reviews.R	no_license	meiarul11/Amazon-Sentiment-Analysis	R	false	false	5,272	r	library(rvest) library(dplyr) library(tidyverse) library(stringr) library(tibble) install.packages("RSQLite") library(RSQLite) install.packages("sentimentr") library(sentimentr) #Reviews data function product<-function(keyword,page) { url<-"https://www.amazon.com/product-reviews/%s/ref=cm_cr_arp_d_paging_btm_%i?ie=UTF8&reviewerType=all_reviews&pageNumber=%i" amazon<-sprintf(url,URLencode(keyword),page,page) reviewpage<-read_html(amazon) profile_name <- reviewpage%>% html_nodes(".review-byline .author")%>% html_text(trim=T)%>% gsub("By","",.) personal_rating <- reviewpage%>% html_nodes("#cm_cr-review_list .review-rating")%>% html_text()%>% str_extract("\\d")%>% as.numeric() description <- reviewpage%>% html_nodes("#cm_cr-review_list .a-color-base")%>% html_text(trim=T) review <- reviewpage%>% html_nodes(".review-text")%>% html_text(trim=T) verification <- reviewpage%>% html_nodes(".review-data.a-spacing-mini")%>% html_text(trim=T)%>% grepl("Verified Purchase",.) product_id<-keyword df <- data.frame(profile_name,personal_rating,description,review,verification,product_id) } ma<-dbConnect(SQLite(),dbname="x.sqlite") dbSendQuery(conn=ma,"create table maintable( product_id1 text primary key, name1 text, price1 num, ratings1 num, no_of_reviews1 num) without rowid") dbSendQuery(conn=ma,"create table reviewtable( profile_name text, personal_rating num, description text, review text, verification logical, product_id1 text, foreign key(product_id1) references maintable(product_id1))") multiple_page <- function(keyword,page) { x <- map(1:page,function(n) { product(keyword,n) })%>% bind_rows() dbWriteTable(conn=ma,name="reviewtable",value=x,row.names=F,header=T,overwrite=T) } multiple_page("B0756CYWWD",4) #main page function main_page <- function(keyword) { main <- "https://www.amazon.com/gp/product/%s" item <- sprintf(main,URLencode(keyword)) items <- read_html(item) name <- items%>% html_node("#productTitle")%>% html_text(trim=T) ratings <- items%>% html_node(".arp-rating-out-of-text")%>% html_text()%>% str_extract("\\d{1}.\\d{1}")%>% as.numeric() price <- items%>% html_node("#priceblock_ourprice")%>% html_text(trim=T)%>% gsub("\\$","",.)%>% as.numeric() no_of_reviews <- items%>% html_node("#acrCustomerReviewText")%>% html_text(trim=T)%>% gsub("[A-z]","",.)%>% gsub(",","",.)%>% as.numeric() product_id <- keyword df <- data_frame(product_id,name,price,ratings,no_of_reviews) dbWriteTable(conn=ma,name="maintable",value=df,row.names=F,header=T,overwrite=T) } main_page("B0756CYWWD") a<-dbGetQuery(conn=ma,"select * from maintable m join reviewtable r on m.product_id=r.product_id") head(a) dbGetQuery(conn=ma,"select * from maintable") sent_agg <- with(a, sentiment_by(review)) head(sent_agg) par(mfrow=c(1,2)) with(a, hist(personal_rating)) with(sent_agg, hist(ave_sentiment)) mean(a$personal_rating) mean(sent_agg$ave_sentiment) best_reviews <- slice(a, top_n(sent_agg, 10, ave_sentiment)$element_id) with(best_reviews, sentiment_by(review)) %>% highlight() worst_reviews <- slice(a, top_n(sent_agg, 10, -ave_sentiment)$element_id) with(worst_reviews, sentiment_by(review)) %>% highlight() library(dplyr) library(stringr) library(tidytext) get_sentiments("afinn") get_sentiments("bing") get_sentiments("nrc") b<-a$review text_tb <- tibble(c = seq_along(b), text = b) head(text_tb) x<-text_tb %>% unnest_tokens(word, text) x x%>% count(word,sort=T) x %>% anti_join(stop_words) %>% count(word, sort = TRUE) x %>% right_join(get_sentiments("nrc")) %>% filter(!is.na(sentiment)) %>% count(sentiment, sort = TRUE) bing_word_counts <- x %>% inner_join(get_sentiments("bing")) %>% count(word, sentiment, sort = TRUE) %>% ungroup() bing_word_counts %>% group_by(sentiment) %>% top_n(10) %>% ggplot(aes(reorder(word, n), n, fill = sentiment)) + geom_bar(alpha = 0.8, stat = "identity", show.legend = FALSE) + facet_wrap(~sentiment, scales = "free_y") + labs(y = "Contribution to sentiment", x = NULL) + coord_flip() install.packages("wordcloud") library(wordcloud) x %>% anti_join(stop_words) %>% count(word) %>% with(wordcloud(word, n, max.words = 100)) library(reshape2) x %>% inner_join(get_sentiments("bing")) %>% count(word, sentiment, sort = TRUE) %>% acast(word ~ sentiment, value.var = "n", fill = 0) %>% comparison.cloud(colors = c("#F8766D", "#00BFC4"), max.words = 100) afinn <- x %>% mutate(word_count = 1:n(), index = word_count %/% 500 + 1) %>% inner_join(get_sentiments("afinn")) %>% group_by(index) %>% summarise(sentiment = sum(score)) %>% mutate(method = "AFINN") afinn
# run_analysis.R does the following: # 1. Merges the training and the test sets to create one data set. tmp1 <- read.table("train/X_train.txt") tmp2 <- read.table("test/X_test.txt") X <- rbind(tmp1, tmp2) tmp1 <- read.table("train/subject_train.txt") tmp2 <- read.table("test/subject_test.txt") S <- rbind(tmp1, tmp2) tmp1 <- read.table("train/y_train.txt") tmp2 <- read.table("test/y_test.txt") Y <- rbind(tmp1, tmp2) # 2. Extracts only the measurements on the mean and standard deviation for each measurement. features <- read.table("features.txt") indices_of_good_features <- grep("-mean\$\$\|-std\$\$", features[, 2]) X <- X[, indices_of_good_features] names(X) <- features[indices_of_good_features, 2] names(X) <- gsub("\$\|\$", "", names(X)) names(X) <- tolower(names(X)) # 3. Uses descriptive activity names to name the activities in the data set. activities <- read.table("activity_labels.txt") activities[, 2] = gsub("_", "", tolower(as.character(activities[, 2]))) Y[,1] = activities[Y[,1], 2] names(Y) <- "activity" # 4. Appropriately labels the data set with descriptive activity names. names(S) <- "subject" cleaned <- cbind(S, Y, X) write.table(cleaned, "merged_clean_data.txt") # 5. Creates a 2nd, independent tidy data set with the average of each variable for each activity and each subject. uniqueSubjects = unique(S)[,1] numSubjects = length(unique(S)[,1]) numActivities = length(activities[,1]) numCols = dim(cleaned)[2] result = cleaned[1:(numSubjects*numActivities), ] row = 1 for (s in 1:numSubjects) { for (a in 1:numActivities) { result[row, 1] = uniqueSubjects[s] result[row, 2] = activities[a, 2] tmp <- cleaned[cleaned$subject==s & cleaned$activity==activities[a, 2], ] result[row, 3:numCols] <- colMeans(tmp[, 3:numCols]) row = row+1 } } write.table(result, "data_set_with_the_averages.txt")	/run_analysis.R	no_license	ElisaPdM/Getting-and-Cleaning-Data	R	false	false	1,886	r	# run_analysis.R does the following: # 1. Merges the training and the test sets to create one data set. tmp1 <- read.table("train/X_train.txt") tmp2 <- read.table("test/X_test.txt") X <- rbind(tmp1, tmp2) tmp1 <- read.table("train/subject_train.txt") tmp2 <- read.table("test/subject_test.txt") S <- rbind(tmp1, tmp2) tmp1 <- read.table("train/y_train.txt") tmp2 <- read.table("test/y_test.txt") Y <- rbind(tmp1, tmp2) # 2. Extracts only the measurements on the mean and standard deviation for each measurement. features <- read.table("features.txt") indices_of_good_features <- grep("-mean\$\$\|-std\$\$", features[, 2]) X <- X[, indices_of_good_features] names(X) <- features[indices_of_good_features, 2] names(X) <- gsub("\$\|\$", "", names(X)) names(X) <- tolower(names(X)) # 3. Uses descriptive activity names to name the activities in the data set. activities <- read.table("activity_labels.txt") activities[, 2] = gsub("_", "", tolower(as.character(activities[, 2]))) Y[,1] = activities[Y[,1], 2] names(Y) <- "activity" # 4. Appropriately labels the data set with descriptive activity names. names(S) <- "subject" cleaned <- cbind(S, Y, X) write.table(cleaned, "merged_clean_data.txt") # 5. Creates a 2nd, independent tidy data set with the average of each variable for each activity and each subject. uniqueSubjects = unique(S)[,1] numSubjects = length(unique(S)[,1]) numActivities = length(activities[,1]) numCols = dim(cleaned)[2] result = cleaned[1:(numSubjects*numActivities), ] row = 1 for (s in 1:numSubjects) { for (a in 1:numActivities) { result[row, 1] = uniqueSubjects[s] result[row, 2] = activities[a, 2] tmp <- cleaned[cleaned$subject==s & cleaned$activity==activities[a, 2], ] result[row, 3:numCols] <- colMeans(tmp[, 3:numCols]) row = row+1 } } write.table(result, "data_set_with_the_averages.txt")
## The functions in this file find the inverse of a matrix. Since this is ## an expensive operation, they provide a caching mechanism, so that the ## inverse is only computed when necessary ## This function creates a matrix-like structure that can cache its inverse. ## The structure has methods set(x) and get() that provide access to the ## underlying matrix. It also has the method getinverse(), which returns the ## multiplicative inverse of the matrix. If getinverse() returns null, it is ## the caller's responsibility to set the inverse first using setinverse(). ## See cacheSolve() for an example of proper usage makeCacheMatrix <- function(x = matrix()) { inv <- NULL set <- function(y) { x <<- y inv <<- NULL } get <- function() x setinverse <- function(inverse) inv <<- inverse getinverse <- function() inv list(set = set, get = get, setinverse = setinverse, getinverse = getinverse) } ## This function returns the inverse of a matrix built with makeCacheMatrix(). ## It first looks to see if the inverse has already been computed. If not, it ## computes the inverse and stores the value in a cache. cacheSolve <- function(x, ...) { ## Return a matrix that is the inverse of 'x' inv <- x$getinverse() if(!is.null(inv)) { message("getting cached data") return(inv) } data <- x$get() inv <- solve(data, ...) x$setinverse(inv) inv }	/cachematrix.R	no_license	rubengamboa/ProgrammingAssignment2	R	false	false	1,472	r	## The functions in this file find the inverse of a matrix. Since this is ## an expensive operation, they provide a caching mechanism, so that the ## inverse is only computed when necessary ## This function creates a matrix-like structure that can cache its inverse. ## The structure has methods set(x) and get() that provide access to the ## underlying matrix. It also has the method getinverse(), which returns the ## multiplicative inverse of the matrix. If getinverse() returns null, it is ## the caller's responsibility to set the inverse first using setinverse(). ## See cacheSolve() for an example of proper usage makeCacheMatrix <- function(x = matrix()) { inv <- NULL set <- function(y) { x <<- y inv <<- NULL } get <- function() x setinverse <- function(inverse) inv <<- inverse getinverse <- function() inv list(set = set, get = get, setinverse = setinverse, getinverse = getinverse) } ## This function returns the inverse of a matrix built with makeCacheMatrix(). ## It first looks to see if the inverse has already been computed. If not, it ## computes the inverse and stores the value in a cache. cacheSolve <- function(x, ...) { ## Return a matrix that is the inverse of 'x' inv <- x$getinverse() if(!is.null(inv)) { message("getting cached data") return(inv) } data <- x$get() inv <- solve(data, ...) x$setinverse(inv) inv }
#' Global EnKPF #' #' @description #' Special cases: #' setting gam.fix=1: EnKF #' setting gam.fix=0: PF #' setting gam.fix=1 and kloc=TRUE recovers the LEnKF #' #' Otherwise gamma is chosen adaptively (then pass e.0 and e.1 as arguments) #' see also utils_enkpf for the exact procedure. #' #' @param xb the background ensemble #' @param y the observations #' @param H the observation linear operator #' @param R the observations error covariance #' @param taper the tapering correlation matrix applied to P #' @param P the background covariance #' @param gam.fix fixed gamma value #' @param d,K,q dimension of observation, ensemble and state space #' @param R2 matrix square-root of R #' @param eps1,eps2 random perturbations N(0,R) #' @param unif used for balanced sampling #' @param ... additional parameters passed to adaptive_gamma, typically e.0 and e.1 #' @return a list with xa, gam and ess EnKPF <- function(xb, y, H, R, taper=1, P=cov(t(xb))taper, ## background covariance gam.fix=NA, ## if passed then gamma not chosen adaptively d=length(y),K=ncol(xb),q=nrow(xb), ## dimensions R2=msqrt(R), ## random perturbations (typically passed as argument for local algorithms) eps1=R2%%matrix(rnorm(dK),d,K), eps2=R2%%matrix(rnorm(dK),d,K), unif=runif(1), ## uniform used for balanced sampling ... ## extra arguments passed to adaptive_gamma ){ ## innovations: y.resx <- y - H%%xb ## adaptive gamma (or not): if (is.na(gam.fix)){ gam.an <- adaptive_gamma(xb=xb,y=y, P=P, H=H, R=R, y.resx=y.resx, ...) } else{ gam.an <- enkf_step(y, xb, gam.fix,P, H, R, y.resx,...) } ## unpack optimal results: gam <- gam.an$gam w <- gam.an$w ess <- gam.an$ess Kal <- gam.an$K Q <- gam.an$Q nu <- gam.an$nux y.resnu <- gam.an$y.resnu ## special case if gam=1, pure EnKF if (gam == 1) { eps <- Kal %% eps1 xa <- nu + eps ess <- 1 gam <- 1 index <- 1:ncol(xb) } else{ ## resampling # index <- bal.sample(w, R=ncol(xb), unif=unif)$index # index <- leftmatch(1:ncol(xb), index) index <- bal_sample_ordered(w, unif=unif)$index ## update: matq <- chol(H %% Q %% t(H) + R/(1-gam)) matq.inv <- chol2inv(matq) KQ <- Q %% t(H) %% matq.inv mu <- nu + KQ %% y.resnu ## noisy increments: if (gam!=0){ xinc <- Kal %% eps1/sqrt(gam) - KQ %% H %% Kal %% eps1/sqrt(gam) + KQ %*% eps2/sqrt(1-gam) } else{ xinc <- 0 } xa <- mu[,index] + xinc } return(list(xa= xa, gam=gam, ess=ess, index=index)) }	/R/update_EnKPF.R	no_license	robertsy/assimilr	R	false	false	2,989	r	#' Global EnKPF #' #' @description #' Special cases: #' setting gam.fix=1: EnKF #' setting gam.fix=0: PF #' setting gam.fix=1 and kloc=TRUE recovers the LEnKF #' #' Otherwise gamma is chosen adaptively (then pass e.0 and e.1 as arguments) #' see also utils_enkpf for the exact procedure. #' #' @param xb the background ensemble #' @param y the observations #' @param H the observation linear operator #' @param R the observations error covariance #' @param taper the tapering correlation matrix applied to P #' @param P the background covariance #' @param gam.fix fixed gamma value #' @param d,K,q dimension of observation, ensemble and state space #' @param R2 matrix square-root of R #' @param eps1,eps2 random perturbations N(0,R) #' @param unif used for balanced sampling #' @param ... additional parameters passed to adaptive_gamma, typically e.0 and e.1 #' @return a list with xa, gam and ess EnKPF <- function(xb, y, H, R, taper=1, P=cov(t(xb))taper, ## background covariance gam.fix=NA, ## if passed then gamma not chosen adaptively d=length(y),K=ncol(xb),q=nrow(xb), ## dimensions R2=msqrt(R), ## random perturbations (typically passed as argument for local algorithms) eps1=R2%%matrix(rnorm(dK),d,K), eps2=R2%%matrix(rnorm(dK),d,K), unif=runif(1), ## uniform used for balanced sampling ... ## extra arguments passed to adaptive_gamma ){ ## innovations: y.resx <- y - H%%xb ## adaptive gamma (or not): if (is.na(gam.fix)){ gam.an <- adaptive_gamma(xb=xb,y=y, P=P, H=H, R=R, y.resx=y.resx, ...) } else{ gam.an <- enkf_step(y, xb, gam.fix,P, H, R, y.resx,...) } ## unpack optimal results: gam <- gam.an$gam w <- gam.an$w ess <- gam.an$ess Kal <- gam.an$K Q <- gam.an$Q nu <- gam.an$nux y.resnu <- gam.an$y.resnu ## special case if gam=1, pure EnKF if (gam == 1) { eps <- Kal %% eps1 xa <- nu + eps ess <- 1 gam <- 1 index <- 1:ncol(xb) } else{ ## resampling # index <- bal.sample(w, R=ncol(xb), unif=unif)$index # index <- leftmatch(1:ncol(xb), index) index <- bal_sample_ordered(w, unif=unif)$index ## update: matq <- chol(H %% Q %% t(H) + R/(1-gam)) matq.inv <- chol2inv(matq) KQ <- Q %% t(H) %% matq.inv mu <- nu + KQ %% y.resnu ## noisy increments: if (gam!=0){ xinc <- Kal %% eps1/sqrt(gam) - KQ %% H %% Kal %% eps1/sqrt(gam) + KQ %*% eps2/sqrt(1-gam) } else{ xinc <- 0 } xa <- mu[,index] + xinc } return(list(xa= xa, gam=gam, ess=ess, index=index)) }
% Generated by roxygen2: do not edit by hand % Please edit documentation in R/1DGPfunctions.R \name{DGP_bin_complex_min} \alias{DGP_bin_complex_min} \title{Simulate with AL bin DGP} \usage{ DGP_bin_complex_min(n, dA = NULL, a = NULL) } \arguments{ \item{n}{n} \item{dA}{rule type} \item{a}{static txt} } \value{ data for DGP_bin_complex_min } \description{ Generate data according to AL bin DGP - want lower outcomes }	/man/DGP_bin_complex_min.Rd	no_license	lmmontoya/SL.ODTR	R	false	true	421	rd	% Generated by roxygen2: do not edit by hand % Please edit documentation in R/1DGPfunctions.R \name{DGP_bin_complex_min} \alias{DGP_bin_complex_min} \title{Simulate with AL bin DGP} \usage{ DGP_bin_complex_min(n, dA = NULL, a = NULL) } \arguments{ \item{n}{n} \item{dA}{rule type} \item{a}{static txt} } \value{ data for DGP_bin_complex_min } \description{ Generate data according to AL bin DGP - want lower outcomes }
pooled_tibble_all_posteriors = function( recovery_rma, # Output from rma() with only RECOVER& multiple_priors_object # Output from normal_approximation_multiple_priors() ) { set.seed = 123 # set seed for reproducibility (rnorm()) n = 10e4 # sampling size tibble( # This is an output from rbeta() in noninformative_posterior() "Non-informative" = rnorm(n, mean = recovery_rma$beta, sd = recovery_rma$se ), "Evidence-based" = multiple_priors_object %>% filter(type == "evidence-based") %>% summarise(a = rnorm(n, mean = post.mean, sd = post.sd )) %>% pull(), "Skeptical" = multiple_priors_object %>% filter(type == "skeptical") %>% summarise(a = rnorm(n, mean = post.mean, sd = post.sd )) %>% pull(), "Optimistic" = multiple_priors_object %>% filter(type == "optimistic") %>% summarise(a = rnorm(n, mean = post.mean, sd = post.sd )) %>% pull(), "Pessimistic" = multiple_priors_object %>% filter(type == "pessimistic") %>% summarise(a = rnorm(n, mean = post.mean, sd = post.sd )) %>% pull(), ) }	/final_analyses/script/functions/pooled/pooled_tibble_all_posteriors.R	no_license	brophyj/tocilizumab_reanalysis	R	false	false	1,367	r	pooled_tibble_all_posteriors = function( recovery_rma, # Output from rma() with only RECOVER& multiple_priors_object # Output from normal_approximation_multiple_priors() ) { set.seed = 123 # set seed for reproducibility (rnorm()) n = 10e4 # sampling size tibble( # This is an output from rbeta() in noninformative_posterior() "Non-informative" = rnorm(n, mean = recovery_rma$beta, sd = recovery_rma$se ), "Evidence-based" = multiple_priors_object %>% filter(type == "evidence-based") %>% summarise(a = rnorm(n, mean = post.mean, sd = post.sd )) %>% pull(), "Skeptical" = multiple_priors_object %>% filter(type == "skeptical") %>% summarise(a = rnorm(n, mean = post.mean, sd = post.sd )) %>% pull(), "Optimistic" = multiple_priors_object %>% filter(type == "optimistic") %>% summarise(a = rnorm(n, mean = post.mean, sd = post.sd )) %>% pull(), "Pessimistic" = multiple_priors_object %>% filter(type == "pessimistic") %>% summarise(a = rnorm(n, mean = post.mean, sd = post.sd )) %>% pull(), ) }
# NOTE - Most parameters not in formals, all listed here: # https://github.com/microsoft/LightGBM/blob/master/docs/Parameters.rst library(mlr3extralearners) install_learners("regr.lightgbm") test_that("regr.lightgbm train", { learner = lrn("regr.lightgbm") fun = lightgbm::lgb.train exclude = c( "params", # handled internally "data", # handled internally "obj", # uses 'objective' alias "eval", # uses 'metric' alias "valids", # handled internally "colnames" # handled internally ) ParamTest = run_paramtest(learner, fun, exclude) expect_true(ParamTest, info = paste0( "Missing parameters:", paste0("- '", ParamTest$missing, "'", collapse = " "))) }) test_that("regr.lightgbm predict", { learner = lrn("regr.lightgbm") fun = lightgbm:::predict.lgb.Booster exclude = c( "object", # handled internally "data", # handled internally "rawscore", # always FALSE "predleaf", # always FALSE "predcontrib", # always FALSE "reshape" # always FALSE ) ParamTest = run_paramtest(learner, fun, exclude) expect_true(ParamTest, info = paste0( "Missing parameters:", paste0("- '", ParamTest$missing, "'", collapse = " "))) })	/inst/paramtest/test_paramtest_lightgbm_regr_lightgbm.R	no_license	Mrlirhan/mlr3extralearners	R	false	false	1,221	r	# NOTE - Most parameters not in formals, all listed here: # https://github.com/microsoft/LightGBM/blob/master/docs/Parameters.rst library(mlr3extralearners) install_learners("regr.lightgbm") test_that("regr.lightgbm train", { learner = lrn("regr.lightgbm") fun = lightgbm::lgb.train exclude = c( "params", # handled internally "data", # handled internally "obj", # uses 'objective' alias "eval", # uses 'metric' alias "valids", # handled internally "colnames" # handled internally ) ParamTest = run_paramtest(learner, fun, exclude) expect_true(ParamTest, info = paste0( "Missing parameters:", paste0("- '", ParamTest$missing, "'", collapse = " "))) }) test_that("regr.lightgbm predict", { learner = lrn("regr.lightgbm") fun = lightgbm:::predict.lgb.Booster exclude = c( "object", # handled internally "data", # handled internally "rawscore", # always FALSE "predleaf", # always FALSE "predcontrib", # always FALSE "reshape" # always FALSE ) ParamTest = run_paramtest(learner, fun, exclude) expect_true(ParamTest, info = paste0( "Missing parameters:", paste0("- '", ParamTest$missing, "'", collapse = " "))) })
data(airquality) N <- 10^4 ## make a function to be used in all three instances boot.func <- function(i) { set.seed(1985) train.set <- sample(1:153, size = 153, replace = T) fit <- lm(Ozone ~ .^2, data = airquality[train.set, ]) coef.mse <- summary(fit)$coef[, 2] return(coef.mse) } ## for version ~ 41 seconds coef.mse.for <- NULL system.time( for (i in 1:N) { coef.mse.for <- cbind(coef.mse.for, boot.func(i)) } ) ## mean.coef.mse.for <- apply(coef.mse.for, 1, mean) ## apply version ~ 30 seconds system.time( coef.mse.sapply <- sapply(X = 1:N, FUN = boot.func) ) ## mean.coef.mse.sapply <- apply(coef.mse.sapply, 1, mean) ## foreach version ~ 18 seconds library(foreach) library(doParallel) library(doRNG) registerDoParallel(cores = 4) ## multi-threading issues with cores = 2 system.time( coef.mse.foreach <- foreach(i = 1:N, .inorder = FALSE, .combine = 'cbind', .options.RNG = 1985) %dopar% boot.func(i) ) ## mean.coef.mse.foreach <- apply(coef.mse.foreach, 1, mean) ## ## iterators ## registerDoParallel(cores = 4) ## multi-threading issues with cores = 2 ## system.time( ## coef.mse.foreach <- foreach(i = icount(N), ## .inorder = FALSE, ## .combine = 'cbind') %dopar% boot.func(i) ## ) ## ## they really all do the same thing ## sum(mean.coef.mse.for == mean.coef.mse.sapply) ## sum(mean.coef.mse.for == mean.coef.mse.foreach) ## ## this is a terrible motivation here... ## ## error calculations without bootstrap ## full.fit <- lm(Ozone ~ .^2, data = airquality) ## full.fit.coef.mse <- summary(full.fit)$coef[, 2] ## ## plot ## par(mfrow = c(4, 4)) ## for (i in 1:16) { ## hist(mse[i, ], breaks = 30, main = rownames(mse)[i]) ## abline(v = full.fit.coef.mse[i], col = "red") ## }	/foreach/old_R_code/boot_code.R	no_license	henryrscharf/fixschewitt	R	false	false	1,930	r	data(airquality) N <- 10^4 ## make a function to be used in all three instances boot.func <- function(i) { set.seed(1985) train.set <- sample(1:153, size = 153, replace = T) fit <- lm(Ozone ~ .^2, data = airquality[train.set, ]) coef.mse <- summary(fit)$coef[, 2] return(coef.mse) } ## for version ~ 41 seconds coef.mse.for <- NULL system.time( for (i in 1:N) { coef.mse.for <- cbind(coef.mse.for, boot.func(i)) } ) ## mean.coef.mse.for <- apply(coef.mse.for, 1, mean) ## apply version ~ 30 seconds system.time( coef.mse.sapply <- sapply(X = 1:N, FUN = boot.func) ) ## mean.coef.mse.sapply <- apply(coef.mse.sapply, 1, mean) ## foreach version ~ 18 seconds library(foreach) library(doParallel) library(doRNG) registerDoParallel(cores = 4) ## multi-threading issues with cores = 2 system.time( coef.mse.foreach <- foreach(i = 1:N, .inorder = FALSE, .combine = 'cbind', .options.RNG = 1985) %dopar% boot.func(i) ) ## mean.coef.mse.foreach <- apply(coef.mse.foreach, 1, mean) ## ## iterators ## registerDoParallel(cores = 4) ## multi-threading issues with cores = 2 ## system.time( ## coef.mse.foreach <- foreach(i = icount(N), ## .inorder = FALSE, ## .combine = 'cbind') %dopar% boot.func(i) ## ) ## ## they really all do the same thing ## sum(mean.coef.mse.for == mean.coef.mse.sapply) ## sum(mean.coef.mse.for == mean.coef.mse.foreach) ## ## this is a terrible motivation here... ## ## error calculations without bootstrap ## full.fit <- lm(Ozone ~ .^2, data = airquality) ## full.fit.coef.mse <- summary(full.fit)$coef[, 2] ## ## plot ## par(mfrow = c(4, 4)) ## for (i in 1:16) { ## hist(mse[i, ], breaks = 30, main = rownames(mse)[i]) ## abline(v = full.fit.coef.mse[i], col = "red") ## }
# Import the dataset data_full <- read.csv("./Coursera_DS/4/Week1/hpc.txt", header=T, sep=';', na.strings="?", nrows=2075259, check.names=F, stringsAsFactors=F, comment.char="", quote='\"') data_full$Date <- as.Date(data_full$Date, format="%d/%m/%Y") # Subset the dataset data <- subset(data_full, subset=(Date >= "2007-02-01" & Date <= "2007-02-02")) rm(data_full) # Convert the dates datetime <- paste(as.Date(data$Date), data$Time) data$Datetime <- as.POSIXct(datetime) # Plot 1 hist(data$Global_active_power, main="Global Active Power", xlab="Global Active Power (kilowatts)", ylab="Frequency", col="Red") # Export the pic dev.copy(png, file="plot1.png", height=480, width=480) dev.off()	/plot1.R	no_license	warmperfume/ExData_Plotting1	R	false	false	724	r	# Import the dataset data_full <- read.csv("./Coursera_DS/4/Week1/hpc.txt", header=T, sep=';', na.strings="?", nrows=2075259, check.names=F, stringsAsFactors=F, comment.char="", quote='\"') data_full$Date <- as.Date(data_full$Date, format="%d/%m/%Y") # Subset the dataset data <- subset(data_full, subset=(Date >= "2007-02-01" & Date <= "2007-02-02")) rm(data_full) # Convert the dates datetime <- paste(as.Date(data$Date), data$Time) data$Datetime <- as.POSIXct(datetime) # Plot 1 hist(data$Global_active_power, main="Global Active Power", xlab="Global Active Power (kilowatts)", ylab="Frequency", col="Red") # Export the pic dev.copy(png, file="plot1.png", height=480, width=480) dev.off()
complete <- function(directory, id = 1:332) { ## 'directory' is a character vector of length 1 indicating ## the location of the csv files ## 'id' is an integer vector indicating the monitor ID numbers ## to be used ## Return a data frame of the form: ## id nobs ## 1 117 ## 2 1041 ## ... ## where 'id" is the monitor ID number and 'nobs" is the ## number of complete cases # Get a list of full file names files_full <- list.files(directory, full.names=TRUE) # Read all the files by given id target_files <- lapply(files_full[id], read.csv) # compute the complete cases for each target file nobs <- sapply(target_files, function(x) sum(complete.cases(x))) # return the required format data.frame('id' = id, 'nobs' = nobs) }	/Chapter2.R_Programming/PgmAsm1/complete.R	no_license	lxwvictor/DataScienceCoursera	R	false	false	929	r	complete <- function(directory, id = 1:332) { ## 'directory' is a character vector of length 1 indicating ## the location of the csv files ## 'id' is an integer vector indicating the monitor ID numbers ## to be used ## Return a data frame of the form: ## id nobs ## 1 117 ## 2 1041 ## ... ## where 'id" is the monitor ID number and 'nobs" is the ## number of complete cases # Get a list of full file names files_full <- list.files(directory, full.names=TRUE) # Read all the files by given id target_files <- lapply(files_full[id], read.csv) # compute the complete cases for each target file nobs <- sapply(target_files, function(x) sum(complete.cases(x))) # return the required format data.frame('id' = id, 'nobs' = nobs) }
#You roll a fair 6 sided die N times, the sum of those N rolls is M. #Find the expected value for the product of those N rolls. #What is the standard deviation of the result #traverse all possible rolls by moving one over each time # findRolls <-function(arr, pos, N, M, probs){ n <- arr[pos] s <- 0 for (i in 1:n){ for (j in 1:6){ s <- s + arr[j]j } #s <- M if (s == M){ #print(i) #print(pos) #print(arr) p <- 1 for (j in 1:6){ if (arr[j] > 0){ p <- p j^arr[j] } } prodArray <<- c(prodArray, p) probArray <<- c(probArray, dmultinom(arr,prob = probs)) numberArray <<- c(numberArray, dmultinom(arr,prob = probs)6^N) } if (pos != 6){ arr[pos] <- arr[pos] - 1 arr[pos+1] <- arr[pos+1] + 1 findRolls(arr, pos+1, N, M, probs) } } } N = 50 M = 150 #sum of N rolls #start with all N rolls a 1 and itterate through all combos with findRolls startArr <-c(N,0,0,0,0,0) probs <- c(1/6,1/6,1/6,1/6,1/6,1/6) prodArray <- vector() #store product of roll probArray <- vector() #store the prob of each roll numberArray <- vector() #store number of rolls that end up with sum = M findRolls(arr = startArr, pos = 1, N = N, M = M, probs = probs) probArray <- probArray/(sum(numberArray)/6^N) #bayes theorm to find actual probabilities probArray sum(probArray) expectedProd <- sum(prodArrayprobArray) numberArray expectedProd sprintf("%.10f",expectedProd) stdDev <- sqrt(sum(probArray*(prodArray-expectedProd)^2)) sprintf("%.10f",stdDev)	/DataIncProb1.R	no_license	keithdlandry/dataIncubatorChallenge	R	false	false	1,518	r	#You roll a fair 6 sided die N times, the sum of those N rolls is M. #Find the expected value for the product of those N rolls. #What is the standard deviation of the result #traverse all possible rolls by moving one over each time # findRolls <-function(arr, pos, N, M, probs){ n <- arr[pos] s <- 0 for (i in 1:n){ for (j in 1:6){ s <- s + arr[j]j } #s <- M if (s == M){ #print(i) #print(pos) #print(arr) p <- 1 for (j in 1:6){ if (arr[j] > 0){ p <- p j^arr[j] } } prodArray <<- c(prodArray, p) probArray <<- c(probArray, dmultinom(arr,prob = probs)) numberArray <<- c(numberArray, dmultinom(arr,prob = probs)6^N) } if (pos != 6){ arr[pos] <- arr[pos] - 1 arr[pos+1] <- arr[pos+1] + 1 findRolls(arr, pos+1, N, M, probs) } } } N = 50 M = 150 #sum of N rolls #start with all N rolls a 1 and itterate through all combos with findRolls startArr <-c(N,0,0,0,0,0) probs <- c(1/6,1/6,1/6,1/6,1/6,1/6) prodArray <- vector() #store product of roll probArray <- vector() #store the prob of each roll numberArray <- vector() #store number of rolls that end up with sum = M findRolls(arr = startArr, pos = 1, N = N, M = M, probs = probs) probArray <- probArray/(sum(numberArray)/6^N) #bayes theorm to find actual probabilities probArray sum(probArray) expectedProd <- sum(prodArrayprobArray) numberArray expectedProd sprintf("%.10f",expectedProd) stdDev <- sqrt(sum(probArray*(prodArray-expectedProd)^2)) sprintf("%.10f",stdDev)
### Let's add in climate data for forcing # 24 January 2019 - Cat # Load from calc_mergeall.R (including libraries) if(is.data.frame(d)){ ## Now it's time to bring in climate data from Weld Hill... # Clean up the dataframe cc.arb<-read.csv("input/weldhill.csv", header=TRUE) cc.arb<-cc.arb%>% rename(date.time=Eastern.daylight.time) cc.arb$date<-gsub("\\s* .$", '', cc.arb$date.time) cc.arb$date<- as.Date(cc.arb$date, "%m/%d/%Y") cc.arb$date<-as.Date(gsub("001", "201", cc.arb$date)) cc.arb$year<-substr(cc.arb$date, 0, 4) cc.arb$doy<-yday(cc.arb$date) cc.arb$hour<-gsub("^. \\s\|\\s:.*$", '', cc.arb$date.time) # Find data for the day and by hour cc.arb<-dplyr::select(cc.arb, Temp..F, Rain.in, date, year, doy, hour) cc.arb$tmin<-ave(cc.arb$Temp..F, cc.arb$date, FUN=min) cc.arb$tmin<-fahrenheit.to.celsius(cc.arb$tmin) cc.arb$tmax<-ave(cc.arb$Temp..F, cc.arb$date, FUN=max) cc.arb$tmax<-fahrenheit.to.celsius(cc.arb$tmax) cc.arb$tmean<-ave(cc.arb$Temp..F, cc.arb$date, cc.arb$hour) cc.arb$tmean<-fahrenheit.to.celsius(cc.arb$tmean) cc.arb$Temp..F <- NULL cc.arb<-cc.arb[!duplicated(cc.arb),] ## If we deem necessary later on in analysis we can add precip back in if(TRUE){ cc.arb$Rain.in<-ave(cc.arb$Rain.in, cc.arb$date, FUN=sum) cc.arb$precip<-conv_unit(cc.arb$Rain.in, "inch", "mm") } cc.arb$year<-as.integer(cc.arb$year) yearlim <- 2015 cc.arb$climatetype <- "weldhill" cc.arb <- cc.arb[(cc.arb$year>yearlim),] #### And now time for climate data from Harvard Forest.... cc.hf <- read.csv("input/hf001-10-15min-m.csv", header=TRUE) cc.hf$date <- as.Date(substr(cc.hf$datetime, 0, 10)) cc.hf$hour <- substr(cc.hf$datetime, 12, 13) cc.hf$year<-substr(cc.hf$date, 0, 4) cc.hf$doy<-yday(cc.hf$date) cc.hf<-dplyr::select(cc.hf, airt, prec, date, year, doy, hour) cc.hf$tmin<-ave(cc.hf$airt, cc.hf$date, FUN=min) cc.hf$tmax<-ave(cc.hf$airt, cc.hf$date, FUN=max) cc.hf$tmean<-ave(cc.hf$airt, cc.hf$date, cc.hf$hour) cc.hf<-cc.hf[!duplicated(cc.hf),] cc.hf$climatetype <- "harvardforest" ## If we deem necessary later on in analysis we can add precip back in if(TRUE){ cc.hf$precip<-ave(cc.hf$prec, cc.hf$date, FUN=sum) } cc.hf$year<-as.integer(cc.hf$year) cc.hf <- cc.hf[(cc.hf$year>yearlim),] commoncols <- c("date", "year", "doy", "hour", "tmin", "tmax", "tmean", "climatetype", "precip") cc.arb <- subset(cc.arb, select=commoncols) cc.hf <- subset(cc.hf, select=commoncols) cc <- full_join(cc.arb, cc.hf) cc <- cc[!duplicated(cc),] d$climatetype <- NA d$climatetype <- ifelse(d$type=="Treespotters" \| d$type=="Common Garden", "weldhill", d$climatetype) d$climatetype <- ifelse(d$type=="Harvard Forest", "harvardforest", d$climatetype) d$id_year_type <- paste(d$id, d$year, d$climatetype, sep=";") } else { print("Error: d not a data.frame") } print(file.info("input/weldhill.csv")$ctime) print(file.info("input/hf001-10-15min-m.csv")$ctime) stop("Not an error, climate is now added to dataframe. If these dates are too old, please follow the directions above to download more recent weather data.")	/analyses/calculating/clean_addinclimate.R	no_license	cchambe12/microclimates	R	false	false	3,234	r	### Let's add in climate data for forcing # 24 January 2019 - Cat # Load from calc_mergeall.R (including libraries) if(is.data.frame(d)){ ## Now it's time to bring in climate data from Weld Hill... # Clean up the dataframe cc.arb<-read.csv("input/weldhill.csv", header=TRUE) cc.arb<-cc.arb%>% rename(date.time=Eastern.daylight.time) cc.arb$date<-gsub("\\s* .$", '', cc.arb$date.time) cc.arb$date<- as.Date(cc.arb$date, "%m/%d/%Y") cc.arb$date<-as.Date(gsub("001", "201", cc.arb$date)) cc.arb$year<-substr(cc.arb$date, 0, 4) cc.arb$doy<-yday(cc.arb$date) cc.arb$hour<-gsub("^. \\s\|\\s:.*$", '', cc.arb$date.time) # Find data for the day and by hour cc.arb<-dplyr::select(cc.arb, Temp..F, Rain.in, date, year, doy, hour) cc.arb$tmin<-ave(cc.arb$Temp..F, cc.arb$date, FUN=min) cc.arb$tmin<-fahrenheit.to.celsius(cc.arb$tmin) cc.arb$tmax<-ave(cc.arb$Temp..F, cc.arb$date, FUN=max) cc.arb$tmax<-fahrenheit.to.celsius(cc.arb$tmax) cc.arb$tmean<-ave(cc.arb$Temp..F, cc.arb$date, cc.arb$hour) cc.arb$tmean<-fahrenheit.to.celsius(cc.arb$tmean) cc.arb$Temp..F <- NULL cc.arb<-cc.arb[!duplicated(cc.arb),] ## If we deem necessary later on in analysis we can add precip back in if(TRUE){ cc.arb$Rain.in<-ave(cc.arb$Rain.in, cc.arb$date, FUN=sum) cc.arb$precip<-conv_unit(cc.arb$Rain.in, "inch", "mm") } cc.arb$year<-as.integer(cc.arb$year) yearlim <- 2015 cc.arb$climatetype <- "weldhill" cc.arb <- cc.arb[(cc.arb$year>yearlim),] #### And now time for climate data from Harvard Forest.... cc.hf <- read.csv("input/hf001-10-15min-m.csv", header=TRUE) cc.hf$date <- as.Date(substr(cc.hf$datetime, 0, 10)) cc.hf$hour <- substr(cc.hf$datetime, 12, 13) cc.hf$year<-substr(cc.hf$date, 0, 4) cc.hf$doy<-yday(cc.hf$date) cc.hf<-dplyr::select(cc.hf, airt, prec, date, year, doy, hour) cc.hf$tmin<-ave(cc.hf$airt, cc.hf$date, FUN=min) cc.hf$tmax<-ave(cc.hf$airt, cc.hf$date, FUN=max) cc.hf$tmean<-ave(cc.hf$airt, cc.hf$date, cc.hf$hour) cc.hf<-cc.hf[!duplicated(cc.hf),] cc.hf$climatetype <- "harvardforest" ## If we deem necessary later on in analysis we can add precip back in if(TRUE){ cc.hf$precip<-ave(cc.hf$prec, cc.hf$date, FUN=sum) } cc.hf$year<-as.integer(cc.hf$year) cc.hf <- cc.hf[(cc.hf$year>yearlim),] commoncols <- c("date", "year", "doy", "hour", "tmin", "tmax", "tmean", "climatetype", "precip") cc.arb <- subset(cc.arb, select=commoncols) cc.hf <- subset(cc.hf, select=commoncols) cc <- full_join(cc.arb, cc.hf) cc <- cc[!duplicated(cc),] d$climatetype <- NA d$climatetype <- ifelse(d$type=="Treespotters" \| d$type=="Common Garden", "weldhill", d$climatetype) d$climatetype <- ifelse(d$type=="Harvard Forest", "harvardforest", d$climatetype) d$id_year_type <- paste(d$id, d$year, d$climatetype, sep=";") } else { print("Error: d not a data.frame") } print(file.info("input/weldhill.csv")$ctime) print(file.info("input/hf001-10-15min-m.csv")$ctime) stop("Not an error, climate is now added to dataframe. If these dates are too old, please follow the directions above to download more recent weather data.")
library(dplyr) Sys.setenv(LANG = "en_US.UTF-8") data <- read.csv("household_power_consumption.txt", header = T, sep = ";", na.strings = c("?"), blank.lines.skip = T) data <- mutate(data, DateTime = as.POSIXct(paste(data$Date, data$Time), format = "%d/%m/%Y %H:%M:%S", tz = "GMT")) data.relevant <- data[data$DateTime >= as.POSIXct("2007-02-01", tz = "GMT") & data$DateTime < as.POSIXct("2007-02-03", tz = "GMT"), ] plot(data.relevant$DateTime, data.relevant$Global_active_power, type = "l", xlab = "", xaxt = "n", ylab = "Global Active Power (kilowatts)") # Use english abbreviations for days as ticks on the x axis axis(1, at = c(as.POSIXct("2007-02-01", tz = "GMT"), as.POSIXct("2007-02-02", tz = "GMT"), as.POSIXct("2007-02-03", tz = "GMT")), labels = c("Thu", "Fri", "Sat")) dev.copy(png, "plot2.png") dev.off()	/plot2.R	no_license	croesnick/ExData_Plotting1	R	false	false	1,065	r	library(dplyr) Sys.setenv(LANG = "en_US.UTF-8") data <- read.csv("household_power_consumption.txt", header = T, sep = ";", na.strings = c("?"), blank.lines.skip = T) data <- mutate(data, DateTime = as.POSIXct(paste(data$Date, data$Time), format = "%d/%m/%Y %H:%M:%S", tz = "GMT")) data.relevant <- data[data$DateTime >= as.POSIXct("2007-02-01", tz = "GMT") & data$DateTime < as.POSIXct("2007-02-03", tz = "GMT"), ] plot(data.relevant$DateTime, data.relevant$Global_active_power, type = "l", xlab = "", xaxt = "n", ylab = "Global Active Power (kilowatts)") # Use english abbreviations for days as ticks on the x axis axis(1, at = c(as.POSIXct("2007-02-01", tz = "GMT"), as.POSIXct("2007-02-02", tz = "GMT"), as.POSIXct("2007-02-03", tz = "GMT")), labels = c("Thu", "Fri", "Sat")) dev.copy(png, "plot2.png") dev.off()
setwd("H:\\Dateneingangskontrolle\\") library(foreign) file1 <- read.spss("file1.sav", to.data.frame = TRUE) file2 <- read.spss("file2.sav", to.data.frame = TRUE) a1 <- names(file1) a2 <- names(file2) which(!a1 %in% a2) a1[which(!a1 %in% a2)] which(!a2 %in% a1) a2[which(!a2 %in% a1)]	/Compare_names_of_datasets.R	no_license	conseal/Library	R	false	false	290	r	setwd("H:\\Dateneingangskontrolle\\") library(foreign) file1 <- read.spss("file1.sav", to.data.frame = TRUE) file2 <- read.spss("file2.sav", to.data.frame = TRUE) a1 <- names(file1) a2 <- names(file2) which(!a1 %in% a2) a1[which(!a1 %in% a2)] which(!a2 %in% a1) a2[which(!a2 %in% a1)]
\name{BRISC_estimation} \alias{BRISC_estimation} \title{Function for estimation with BRISC} \description{ The function \code{BRISC_estimation} fits univariate spatial regression models for large spatial data using Vecchia's approximate likelihood (Vecchia, 1988). \code{BRISC_estimation} uses the sparse Cholesky representation of Vecchia’s likelihood developed in Datta et al., 2016. The Maximum Likelihood Estimates (MLE) of the parameters are used later for calculating the confidence interval via the \code{BRISC_bootstrap} (BRISC, Saha & Datta, 2018). \cr We recommend using \code{BRISC_estimation} followed by \code{BRISC_bootstrap} to obtain the cofidence intervals for the model parameters. The optimization is performed with C library of limited-memory BFGS libLBFGS: a library of Limited-memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS), \cr http://www.chokkan.org/software/liblbfgs/ (Naoaki Okazaki). For user convenience the soure codes of the package libLBFGS are provided in the package. The code for the coordinate ordering method, approximate Maximum Minimum Distance (Guinness, 2018) is available in \cr https://github.com/joeguinness/gp_reorder/tree/master/R and is adopted with minor modification. Some code blocks are borrowed from the R package: spNNGP: Spatial Regression Models for Large Datasets using Nearest Neighbor Gaussian Processes https://CRAN.R-project.org/package=spNNGP . } \usage{ BRISC_estimation(coords, y, x = NULL, sigma.sq = 1, tau.sq = 0.1, phi = 1, nu = 1.5, n.neighbors = 15, n_omp = 1, order = "Sum_coords", cov.model = "exponential", search.type = "tree", stabilization = NULL, pred.stabilization = 1e-8, verbose = TRUE, eps = 2e-05, nugget_status = 1, tol = 12) } \arguments{ \item{coords}{an \eqn{n \times 2}{n x 2} matrix of the observation coordinates in \eqn{R^2}{R^2} (e.g., easting and northing). } \item{y}{an \eqn{n}{n} length vector of response at the observed coordinates. } \item{x}{an \eqn{n \times p}{n x p} matrix of the covariates in the observation coordinates. Default value is \eqn{n \times 1}{n x 1} matrix of \eqn{1} to adjust for the mean(intercept). } \item{sigma.sq}{starting value of sigma square. Default value is 1. } \item{tau.sq}{starting value of tau square. Default value is 0.1. } \item{phi}{starting value of phi. Default value is 1. } \item{nu}{starting value of nu, only required for matern covariance model. Default value is 1.5. } \item{n.neighbors}{number of neighbors used in the NNGP. Default value is 15. } \item{n_omp}{number of threads to be used, value can be more than 1 if source code is compiled with OpenMP support. Default is 1. } \item{order}{keyword that specifies the ordering scheme to be used in ordering the observations. Supported keywords are: \code{"AMMD"} and \code{"Sum_coords"} for approximate Maximum Minimum Distance and sum of coordinate based ordering, respectively. Default value is \code{"Sum_coords"}. \eqn{n > 65} is required for \code{"AMMD"}.} \item{cov.model}{keyword that specifies the covariance function to be used in modelling the spatial dependence structure among the observations. Supported keywords are: \code{"exponential"}, \code{"matern"}, \code{"spherical"}, and \code{"gaussian"} for exponential, Matern, spherical and Gaussian covariance function respectively. Default value is "exponential". } \item{search.type}{keyword that specifies type of nearest neighbor search algorithm to be used. Supported keywords are: \code{"brute"}, \code{"tree"} and \code{"cb"}. \cr \code{"brute"} and \code{"tree"} provide the same result, though \code{"tree"} should be faster. \code{"cb"} implements fast code book search described in Ra and Kim (1993) modified for NNGP. If locations do not have identical coordinate values on the axis used for the nearest neighbor ordering (see \code{order} argument) then \code{"cb"} and \code{"brute"} should produce identical neighbor sets. However, if there are identical coordinate values on the axis used for nearest neighbor ordering, then \code{"cb"} and \code{"brute"} might produce different, but equally valid, neighbor sets, e.g., if data are on a grid. Default value is \code{"tree"}. } \item{stabilization}{when the spatial errors are generated from a very smooth covarince model (lower values of phi for spherical and Gaussian covariance and low phi and high nu for Matern covarinace), the estimation process may fail due to computational instability. If \code{stabilization = TRUE}, performs stabilization by adding a white noise to the reordered data with nugget \code{tau.sq = } \code{sigma.sq} * 1e-06. Estimation is performed on this new data with \code{nugget_status = 1} (see \code{nugget_status} argument below). Default value is \code{TRUE} for \code{cov.model = "expoenential"} and \code{FALSE} otherwise. } \item{pred.stabilization}{if not \code{NULL}, will truncate the estimated tau square to \code{pred.stabilization} * estimated sigma square. This provides additional stability in \cr \code{BRISC_prediction}. Default value is \eqn{1e-8}. } \item{verbose}{if \code{TRUE}, model specifications along with information regarding OpenMP support and progress of the algorithm is printed to the screen. Otherwise, nothing is printed to the screen. Default value is \code{TRUE}. } \item{eps}{tolerance to be used in centred finite difference approximation of derivatives. Default value is 2e-05. } \item{nugget_status}{if \code{nugget_status = 0}, \code{tau.sq} is fixed to 0, if \code{nugget_status = 1} \code{tau.sq} is estimated. Default value is 1. } \item{tol}{the input observation coordinates, response and the covariates are rounded to this many places after the decimal. The default value is 12. } } \value{ An object of class \code{BRISC_Out}, which is a list comprising: \item{ord}{the vector of indices used to order data necessary for fitting the NNGP model.} \item{coords}{the matrix \code{coords[ord,]}. } \item{y}{If \code{stabilization = FALSE}, returns the vector \code{y[ord]}. \cr If \code{stabilization = TRUE}, returns \code{y[ord]} + used white noise in stabilization process. } \item{X}{the matrix \code{x[ord,,drop=FALSE]}. } \item{n.neighbors}{the used value of \code{n.neighbors}. } \item{cov.model}{the used covariance model. } \item{eps}{value of used \code{eps} for approximate derivation. Default value is 2e-05. } \item{init}{initial values of the parameters of the covariance model; \cr accounts for \code{stabilization}. } \item{Beta}{estimate of beta. } \item{Theta}{estimate of parameters of covarinace model. } \item{estimation.time}{time (in seconds) required to perform the model fitting after ordering and preprocessing data in \code{R}, reported using \code{proc.time()}. } \item{BRISC_Object}{object required for bootstrap and prediction. } } \references{ Saha, A., & Datta, A. (2018). BRISC: bootstrap for rapid inference on spatial covariances. Stat, e184, DOI: 10.1002/sta4.184. Datta, A., S. Banerjee, A.O. Finley, and A.E. Gelfand. (2016) Hierarchical Nearest-Neighbor Gaussian process models for large geostatistical datasets. Journal of the American Statistical Association, 111:800-812. Guinness, J. (2018) Permutation and Grouping Methods for Sharpening Gaussian Process Approximations, Technometrics, DOI: 10.1080/00401706.2018.1437476, \cr https://github.com/joeguinness/gp_reorder/tree/master/R . Vecchia, A. V. (1988) Estimation and model identification for continuous spatial processes. Journal of the Royal Statistical Society. Series B (Methodological), 297-312. Okazaki N. libLBFGS: a library of Limited-memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS), \cr http://www.chokkan.org/software/liblbfgs/ . Andrew Finley, Abhirup Datta and Sudipto Banerjee (2020). spNNGP: Spatial Regression Models for Large Datasets using Nearest Neighbor Gaussian Processes. R package version 0.1.4. https://CRAN.R-project.org/package=spNNGP Ra, S. W., & Kim, J. K. (1993). A fast mean-distance-ordered partial codebook search algorithm for image vector quantization. IEEE Transactions on Circuits and Systems II: Analog and Digital Signal Processing, 40(9), 576-579. } \author{ Arkajyoti Saha \email{arkajyotisaha93@gmail.com}, \cr Abhirup Datta \email{abhidatta@jhu.edu} } \examples{ rmvn <- function(n, mu = 0, V = matrix(1)){ p <- length(mu) if(any(is.na(match(dim(V),p)))) stop("Dimension not right!") D <- chol(V) t(matrix(rnorm(np), ncol=p)\%\%D + rep(mu,rep(n,p))) } set.seed(1) n <- 1000 coords <- cbind(runif(n,0,1), runif(n,0,1)) beta <- c(1,5) x <- cbind(rnorm(n), rnorm(n)) sigma.sq = 1 phi = 1 tau.sq = 0.1 B <- as.matrix(beta) D <- as.matrix(dist(coords)) R <- exp(-phiD) w <- rmvn(1, rep(0,n), sigma.sqR) y <- rnorm(n, x\%*\%B + w, sqrt(tau.sq)) estimation_result <- BRISC_estimation(coords, y, x) estimation_result$Theta ##Estimates of covariance model parameters. estimation_result$Beta ##Estimates of Beta } \keyword{model}	/man/BRISC_estimation.Rd	no_license	ArkajyotiSaha/BRISC	R	false	false	9,624	rd	\name{BRISC_estimation} \alias{BRISC_estimation} \title{Function for estimation with BRISC} \description{ The function \code{BRISC_estimation} fits univariate spatial regression models for large spatial data using Vecchia's approximate likelihood (Vecchia, 1988). \code{BRISC_estimation} uses the sparse Cholesky representation of Vecchia’s likelihood developed in Datta et al., 2016. The Maximum Likelihood Estimates (MLE) of the parameters are used later for calculating the confidence interval via the \code{BRISC_bootstrap} (BRISC, Saha & Datta, 2018). \cr We recommend using \code{BRISC_estimation} followed by \code{BRISC_bootstrap} to obtain the cofidence intervals for the model parameters. The optimization is performed with C library of limited-memory BFGS libLBFGS: a library of Limited-memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS), \cr http://www.chokkan.org/software/liblbfgs/ (Naoaki Okazaki). For user convenience the soure codes of the package libLBFGS are provided in the package. The code for the coordinate ordering method, approximate Maximum Minimum Distance (Guinness, 2018) is available in \cr https://github.com/joeguinness/gp_reorder/tree/master/R and is adopted with minor modification. Some code blocks are borrowed from the R package: spNNGP: Spatial Regression Models for Large Datasets using Nearest Neighbor Gaussian Processes https://CRAN.R-project.org/package=spNNGP . } \usage{ BRISC_estimation(coords, y, x = NULL, sigma.sq = 1, tau.sq = 0.1, phi = 1, nu = 1.5, n.neighbors = 15, n_omp = 1, order = "Sum_coords", cov.model = "exponential", search.type = "tree", stabilization = NULL, pred.stabilization = 1e-8, verbose = TRUE, eps = 2e-05, nugget_status = 1, tol = 12) } \arguments{ \item{coords}{an \eqn{n \times 2}{n x 2} matrix of the observation coordinates in \eqn{R^2}{R^2} (e.g., easting and northing). } \item{y}{an \eqn{n}{n} length vector of response at the observed coordinates. } \item{x}{an \eqn{n \times p}{n x p} matrix of the covariates in the observation coordinates. Default value is \eqn{n \times 1}{n x 1} matrix of \eqn{1} to adjust for the mean(intercept). } \item{sigma.sq}{starting value of sigma square. Default value is 1. } \item{tau.sq}{starting value of tau square. Default value is 0.1. } \item{phi}{starting value of phi. Default value is 1. } \item{nu}{starting value of nu, only required for matern covariance model. Default value is 1.5. } \item{n.neighbors}{number of neighbors used in the NNGP. Default value is 15. } \item{n_omp}{number of threads to be used, value can be more than 1 if source code is compiled with OpenMP support. Default is 1. } \item{order}{keyword that specifies the ordering scheme to be used in ordering the observations. Supported keywords are: \code{"AMMD"} and \code{"Sum_coords"} for approximate Maximum Minimum Distance and sum of coordinate based ordering, respectively. Default value is \code{"Sum_coords"}. \eqn{n > 65} is required for \code{"AMMD"}.} \item{cov.model}{keyword that specifies the covariance function to be used in modelling the spatial dependence structure among the observations. Supported keywords are: \code{"exponential"}, \code{"matern"}, \code{"spherical"}, and \code{"gaussian"} for exponential, Matern, spherical and Gaussian covariance function respectively. Default value is "exponential". } \item{search.type}{keyword that specifies type of nearest neighbor search algorithm to be used. Supported keywords are: \code{"brute"}, \code{"tree"} and \code{"cb"}. \cr \code{"brute"} and \code{"tree"} provide the same result, though \code{"tree"} should be faster. \code{"cb"} implements fast code book search described in Ra and Kim (1993) modified for NNGP. If locations do not have identical coordinate values on the axis used for the nearest neighbor ordering (see \code{order} argument) then \code{"cb"} and \code{"brute"} should produce identical neighbor sets. However, if there are identical coordinate values on the axis used for nearest neighbor ordering, then \code{"cb"} and \code{"brute"} might produce different, but equally valid, neighbor sets, e.g., if data are on a grid. Default value is \code{"tree"}. } \item{stabilization}{when the spatial errors are generated from a very smooth covarince model (lower values of phi for spherical and Gaussian covariance and low phi and high nu for Matern covarinace), the estimation process may fail due to computational instability. If \code{stabilization = TRUE}, performs stabilization by adding a white noise to the reordered data with nugget \code{tau.sq = } \code{sigma.sq} * 1e-06. Estimation is performed on this new data with \code{nugget_status = 1} (see \code{nugget_status} argument below). Default value is \code{TRUE} for \code{cov.model = "expoenential"} and \code{FALSE} otherwise. } \item{pred.stabilization}{if not \code{NULL}, will truncate the estimated tau square to \code{pred.stabilization} * estimated sigma square. This provides additional stability in \cr \code{BRISC_prediction}. Default value is \eqn{1e-8}. } \item{verbose}{if \code{TRUE}, model specifications along with information regarding OpenMP support and progress of the algorithm is printed to the screen. Otherwise, nothing is printed to the screen. Default value is \code{TRUE}. } \item{eps}{tolerance to be used in centred finite difference approximation of derivatives. Default value is 2e-05. } \item{nugget_status}{if \code{nugget_status = 0}, \code{tau.sq} is fixed to 0, if \code{nugget_status = 1} \code{tau.sq} is estimated. Default value is 1. } \item{tol}{the input observation coordinates, response and the covariates are rounded to this many places after the decimal. The default value is 12. } } \value{ An object of class \code{BRISC_Out}, which is a list comprising: \item{ord}{the vector of indices used to order data necessary for fitting the NNGP model.} \item{coords}{the matrix \code{coords[ord,]}. } \item{y}{If \code{stabilization = FALSE}, returns the vector \code{y[ord]}. \cr If \code{stabilization = TRUE}, returns \code{y[ord]} + used white noise in stabilization process. } \item{X}{the matrix \code{x[ord,,drop=FALSE]}. } \item{n.neighbors}{the used value of \code{n.neighbors}. } \item{cov.model}{the used covariance model. } \item{eps}{value of used \code{eps} for approximate derivation. Default value is 2e-05. } \item{init}{initial values of the parameters of the covariance model; \cr accounts for \code{stabilization}. } \item{Beta}{estimate of beta. } \item{Theta}{estimate of parameters of covarinace model. } \item{estimation.time}{time (in seconds) required to perform the model fitting after ordering and preprocessing data in \code{R}, reported using \code{proc.time()}. } \item{BRISC_Object}{object required for bootstrap and prediction. } } \references{ Saha, A., & Datta, A. (2018). BRISC: bootstrap for rapid inference on spatial covariances. Stat, e184, DOI: 10.1002/sta4.184. Datta, A., S. Banerjee, A.O. Finley, and A.E. Gelfand. (2016) Hierarchical Nearest-Neighbor Gaussian process models for large geostatistical datasets. Journal of the American Statistical Association, 111:800-812. Guinness, J. (2018) Permutation and Grouping Methods for Sharpening Gaussian Process Approximations, Technometrics, DOI: 10.1080/00401706.2018.1437476, \cr https://github.com/joeguinness/gp_reorder/tree/master/R . Vecchia, A. V. (1988) Estimation and model identification for continuous spatial processes. Journal of the Royal Statistical Society. Series B (Methodological), 297-312. Okazaki N. libLBFGS: a library of Limited-memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS), \cr http://www.chokkan.org/software/liblbfgs/ . Andrew Finley, Abhirup Datta and Sudipto Banerjee (2020). spNNGP: Spatial Regression Models for Large Datasets using Nearest Neighbor Gaussian Processes. R package version 0.1.4. https://CRAN.R-project.org/package=spNNGP Ra, S. W., & Kim, J. K. (1993). A fast mean-distance-ordered partial codebook search algorithm for image vector quantization. IEEE Transactions on Circuits and Systems II: Analog and Digital Signal Processing, 40(9), 576-579. } \author{ Arkajyoti Saha \email{arkajyotisaha93@gmail.com}, \cr Abhirup Datta \email{abhidatta@jhu.edu} } \examples{ rmvn <- function(n, mu = 0, V = matrix(1)){ p <- length(mu) if(any(is.na(match(dim(V),p)))) stop("Dimension not right!") D <- chol(V) t(matrix(rnorm(np), ncol=p)\%\%D + rep(mu,rep(n,p))) } set.seed(1) n <- 1000 coords <- cbind(runif(n,0,1), runif(n,0,1)) beta <- c(1,5) x <- cbind(rnorm(n), rnorm(n)) sigma.sq = 1 phi = 1 tau.sq = 0.1 B <- as.matrix(beta) D <- as.matrix(dist(coords)) R <- exp(-phiD) w <- rmvn(1, rep(0,n), sigma.sqR) y <- rnorm(n, x\%*\%B + w, sqrt(tau.sq)) estimation_result <- BRISC_estimation(coords, y, x) estimation_result$Theta ##Estimates of covariance model parameters. estimation_result$Beta ##Estimates of Beta } \keyword{model}
library(MESS) ### Name: round_percent ### Title: Round vector of number to percentages ### Aliases: round_percent ### Keywords: manip ### ** Examples f <- c(1,2,1,3,2,1,2,3,1) round_percent(f)	/data/genthat_extracted_code/MESS/examples/round_percent.Rd.R	no_license	surayaaramli/typeRrh	R	false	false	203	r	library(MESS) ### Name: round_percent ### Title: Round vector of number to percentages ### Aliases: round_percent ### Keywords: manip ### ** Examples f <- c(1,2,1,3,2,1,2,3,1) round_percent(f)
#' Create initial profile for GOTM #' #' Extract and format the initial profile for GOTM from the observation file used in ACPy. #' #' @param obs_file filepath; Path to observation file #' @param date character; Date in "YYYY-mm-dd HH:MM:SS" format to extract the initial profile. If using month, the date to which to set the start date #' @param tprof_file filepath; For the new initial temperature profile file. #' @param month numeric;select a month if you want to use an 'average profile from a particular month. Defaults to NULL. #' @param ndeps numeric; number of depths to extract from the monthly average profile. Defaults to 2 (surface and bottom) #' @param btm_depth numeric; Depth to extract the bottom temperature from, must be negative. If none provided uses the max depth in the observed file. Defaults to NULL #' @param print logical; Prints the temperature profile to the console #' @param ... arguments to be passed to read.delim() for reading in observed file e.g "header = TRUE, sep = ','" #' @return Message stating if the file has been created #' @import utils #' @importFrom lubridate month #' @export init_prof <- function(obs_file, date, tprof_file, month = NULL, ndeps = 2, btm_depth = NULL, print = TRUE, ...){ obs <- read.delim(obs_file, stringsAsFactors = F, ...) if(!is.null(month)){ obs[,1] <- as.POSIXct(obs[,1], tz = 'UTC') obs$month <- month(obs[,1]) sub = obs[(obs$month == month),] if(nrow(sub) == 0){ stop('No measurements for that month. Select a different month') } sub$fdepth <- factor(sub[,2]) library(plyr) sub2 <- ddply(sub, 2, function(df) { mn = mean(df[,3], na.rm = T) return(mn) }) sub2[,1] <- as.numeric(as.character(sub2[,1])) if(is.null(btm_depth)){ btm = min(sub2[,1]) }else{ btm = btm_depth } top = max(sub2[,1]) deps = seq(btm, top, length.out = ndeps) avg_prof = approx(x = sub2[,1], y = sub2[,2], xout = deps) deps = avg_prof$x tmp = avg_prof$y }else{ #obs[,1] <- as.POSIXct(obs[,1], tz = 'UTC') dat = which(obs[,1] == date) ndeps = length(dat) deps = obs[dat,2] tmp = obs[dat,3] } tmp = tmp[order(-deps)] deps = deps[order(-deps)] df <- matrix(NA, nrow =1+ndeps, ncol =2) df[1,1] <- date df[1,2] <- paste0(ndeps,' ',2) df[(2):(1+ndeps),1] = as.numeric(deps) df[(2):(1+ndeps),2] = as.numeric(tmp) write.table(df, tprof_file, quote = F, row.names = F, col.names = F, sep = "\t") message('New inital temperature file ', tprof_file, ' has been created.') if(print == TRUE){ print(df) } }	/MtBold/R_scripts/modelling/functions/init_prof.R	no_license	icra/WATExR	R	false	false	2,609	r	#' Create initial profile for GOTM #' #' Extract and format the initial profile for GOTM from the observation file used in ACPy. #' #' @param obs_file filepath; Path to observation file #' @param date character; Date in "YYYY-mm-dd HH:MM:SS" format to extract the initial profile. If using month, the date to which to set the start date #' @param tprof_file filepath; For the new initial temperature profile file. #' @param month numeric;select a month if you want to use an 'average profile from a particular month. Defaults to NULL. #' @param ndeps numeric; number of depths to extract from the monthly average profile. Defaults to 2 (surface and bottom) #' @param btm_depth numeric; Depth to extract the bottom temperature from, must be negative. If none provided uses the max depth in the observed file. Defaults to NULL #' @param print logical; Prints the temperature profile to the console #' @param ... arguments to be passed to read.delim() for reading in observed file e.g "header = TRUE, sep = ','" #' @return Message stating if the file has been created #' @import utils #' @importFrom lubridate month #' @export init_prof <- function(obs_file, date, tprof_file, month = NULL, ndeps = 2, btm_depth = NULL, print = TRUE, ...){ obs <- read.delim(obs_file, stringsAsFactors = F, ...) if(!is.null(month)){ obs[,1] <- as.POSIXct(obs[,1], tz = 'UTC') obs$month <- month(obs[,1]) sub = obs[(obs$month == month),] if(nrow(sub) == 0){ stop('No measurements for that month. Select a different month') } sub$fdepth <- factor(sub[,2]) library(plyr) sub2 <- ddply(sub, 2, function(df) { mn = mean(df[,3], na.rm = T) return(mn) }) sub2[,1] <- as.numeric(as.character(sub2[,1])) if(is.null(btm_depth)){ btm = min(sub2[,1]) }else{ btm = btm_depth } top = max(sub2[,1]) deps = seq(btm, top, length.out = ndeps) avg_prof = approx(x = sub2[,1], y = sub2[,2], xout = deps) deps = avg_prof$x tmp = avg_prof$y }else{ #obs[,1] <- as.POSIXct(obs[,1], tz = 'UTC') dat = which(obs[,1] == date) ndeps = length(dat) deps = obs[dat,2] tmp = obs[dat,3] } tmp = tmp[order(-deps)] deps = deps[order(-deps)] df <- matrix(NA, nrow =1+ndeps, ncol =2) df[1,1] <- date df[1,2] <- paste0(ndeps,' ',2) df[(2):(1+ndeps),1] = as.numeric(deps) df[(2):(1+ndeps),2] = as.numeric(tmp) write.table(df, tprof_file, quote = F, row.names = F, col.names = F, sep = "\t") message('New inital temperature file ', tprof_file, ' has been created.') if(print == TRUE){ print(df) } }
##################################################################### # 20190922 EJ # # Running stock assessments for WGMG 2018 projects ##################################################################### library(FLa4a) source('../../helper_code/a4a_funs.R') #==================================================================== # read data #==================================================================== setwd('../ices_data/') idxs <- readFLIndices('survey.dat') idxs <- window(idxs, end=2016) stk <- readFLStock('index.low', no.discards = TRUE) stk <- setPlusGroup(stk, 11) range(stk)[c('minfbar','maxfbar')] <- c(5,10) setwd('../a4asca_constantFSelectivity') #==================================================================== # replace 0 with half of the minimum #==================================================================== catch.n(stk)[catch.n(stk)==0] <- min(catch.n(stk)[catch.n(stk)!=0])/2 idxs <- lapply(idxs, function(x){ index(x)[index(x)==0] <- min(index(x)[index(x)!=0])/2 x }) #==================================================================== # Use only years with surveys #==================================================================== my <- min(unlist(lapply(lapply(idxs, range), '[', 'minyear'))) stk <- window(stk, start=my) #==================================================================== # run model #==================================================================== qmod <- list(~s(age, k=3)) fmod <- ~s(age, k=5) + s(year, k=15) srmod <- ~geomean(CV=0.2) fit <- sca(stk, idxs, qmodel=qmod, fmodel=fmod, srmodel=srmod) fits <- simulate(fit, 500) #==================================================================== # run retro and predictions #==================================================================== stk.retro <- retro(stk, idxs, retro=7, k=c(age=4, year=15), ftype="sep", qmodel=qmod, srmodel=srmod) fit.rm <- mohn(stk.retro) fit.pi <- predIdxs(stk, idxs, qmodel=qmod, fmodel=fmod, srmodel=srmod) #==================================================================== # save #==================================================================== dumpTabs(stk, idxs, fits, preds=fit.pi, mohnRho=fit.rm) dumpDiags(stk, idxs, fit, stk.retro, fit.pi)	/state-space/ICEherring/a4asca_constantFSelectivity/algorithm.R	no_license	Claudio-Castillo/wg_MGWG	R	false	false	2,230	r	##################################################################### # 20190922 EJ # # Running stock assessments for WGMG 2018 projects ##################################################################### library(FLa4a) source('../../helper_code/a4a_funs.R') #==================================================================== # read data #==================================================================== setwd('../ices_data/') idxs <- readFLIndices('survey.dat') idxs <- window(idxs, end=2016) stk <- readFLStock('index.low', no.discards = TRUE) stk <- setPlusGroup(stk, 11) range(stk)[c('minfbar','maxfbar')] <- c(5,10) setwd('../a4asca_constantFSelectivity') #==================================================================== # replace 0 with half of the minimum #==================================================================== catch.n(stk)[catch.n(stk)==0] <- min(catch.n(stk)[catch.n(stk)!=0])/2 idxs <- lapply(idxs, function(x){ index(x)[index(x)==0] <- min(index(x)[index(x)!=0])/2 x }) #==================================================================== # Use only years with surveys #==================================================================== my <- min(unlist(lapply(lapply(idxs, range), '[', 'minyear'))) stk <- window(stk, start=my) #==================================================================== # run model #==================================================================== qmod <- list(~s(age, k=3)) fmod <- ~s(age, k=5) + s(year, k=15) srmod <- ~geomean(CV=0.2) fit <- sca(stk, idxs, qmodel=qmod, fmodel=fmod, srmodel=srmod) fits <- simulate(fit, 500) #==================================================================== # run retro and predictions #==================================================================== stk.retro <- retro(stk, idxs, retro=7, k=c(age=4, year=15), ftype="sep", qmodel=qmod, srmodel=srmod) fit.rm <- mohn(stk.retro) fit.pi <- predIdxs(stk, idxs, qmodel=qmod, fmodel=fmod, srmodel=srmod) #==================================================================== # save #==================================================================== dumpTabs(stk, idxs, fits, preds=fit.pi, mohnRho=fit.rm) dumpDiags(stk, idxs, fit, stk.retro, fit.pi)
#' compress a dfm or fcm by combining identical dimension elements #' #' "Compresses" a \link{dfm} or \link{fcm} whose dimension names are the same, #' for either documents or features. This may happen, for instance, if features #' are made equivalent through application of a thesaurus. It may also occur #' after lower-casing or stemming the features of a dfm, but this should only be #' done in very rare cases (approaching never: it's better to do this #' \emph{before} constructing the dfm.) It could also be needed after a #' \code{\link{cbind.dfm}} or \code{\link{rbind.dfm}} operation. #' #' @param x input object, a \link{dfm} or \link{fcm} #' @param margin character indicating on which margin to compress a dfm, either #' \code{"documents"}, \code{"features"}, or \code{"both"} (default). For fcm #' objects, \code{"documents"} has no effect. #' @param ... additional arguments passed from generic to specific methods #' @export #' @examples #' mat <- rbind(dfm(c("b A A", "C C a b B"), tolower = FALSE, verbose = FALSE), #' dfm("A C C C C C", tolower = FALSE, verbose = FALSE)) #' colnames(mat) <- char_tolower(featnames(mat)) #' mat #' dfm_compress(mat, margin = "documents") #' dfm_compress(mat, margin = "features") #' dfm_compress(mat) #' #' # no effect if no compression needed #' compactdfm <- dfm(data_char_inaugural[1:5], verbose = FALSE) #' dim(compactdfm) #' dim(dfm_compress(compactdfm)) #' dfm_compress <- function(x, margin = c("both", "documents", "features")) { UseMethod("dfm_compress") } #' @noRd #' @export dfm_compress.dfmSparse <- function(x, margin = c("both", "documents", "features")) { margin <- match.arg(margin) uniquednames <- unique(rownames(x)) uniquefnames <- unique(colnames(x)) if (length(uniquednames) == nrow(x) & length(uniquefnames) == ncol(x)) return(x) # add 1 since stored from 0, but constructor requires indexing from 1 new_i <- x@i + 1 new_j <- as(x, "dgTMatrix")@j + 1 allZeroFeatures <- match(names(which(colSums(x)==0)), uniquefnames) allZeroDocs <- match(names(which(rowSums(x)==0)), uniquednames) # combine documents if (margin %in% c("both", "documents") & length(uniquednames) < nrow(x)) new_i <- match(rownames(x), uniquednames)[new_i] else uniquednames <- rownames(x) # combine features if (margin %in% c("both", "features") & length(uniquefnames) < ncol(x)) new_j <- match(colnames(x), uniquefnames)[new_j] else uniquefnames <- colnames(x) if (nf <- length(allZeroFeatures)) { new_i <- c(new_i, rep(1, nf)) new_j <- c(new_j, allZeroFeatures) } if (nd <- length(allZeroDocs)) { new_i <- c(new_i, allZeroDocs) new_j <- c(new_j, rep(1, nd)) } new("dfmSparse", sparseMatrix(i = new_i, j = new_j, x = c(x@x, rep(0, length(allZeroFeatures)), rep(0, length(allZeroDocs))), dimnames = list(docs = uniquednames, features = uniquefnames)), settings = x@settings, weightTf = x@weightTf, weightDf = x@weightDf, smooth = x@smooth, ngrams = x@ngrams, concatenator = x@concatenator) } #' @noRd #' @export #' @examples #' # for dfmDense #' mat <- rbind(dfm(c("b A A", "C C a b B"), tolower = FALSE, verbose = FALSE), #' dfm("A C C C C C", tolower = FALSE, verbose = FALSE)) #' matd <- dfm_smooth(mat) #' colnames(matd) <- char_tolower(featnames(mat)) #' matd #' dfm_compress(matd, margin = "documents") #' dfm_compress(matd, margin = "features") #' dfm_compress(matd) dfm_compress.dfmDense <- function(x, ...) { dfm_compress(new("dfmSparse", Matrix::Matrix(as.matrix(x), sparse = TRUE), settings = x@settings, weightTf = x@weightTf, weightDf = x@weightDf, smooth = x@smooth, ngrams = x@ngrams, concatenator = x@concatenator), ...) } #' convert the case of the features of a dfm and combine #' #' \code{dfm_tolower} and \code{dfm_toupper} convert the features of the dfm to #' lower and upper case, respectively, and then recombine the counts. #' @param x the \link{dfm} or \link{fcm} object #' @importFrom stringi stri_trans_tolower #' @export #' @examples #' # for a document-feature matrix #' mydfm <- dfm(c("b A A", "C C a b B"), #' toLower = FALSE, verbose = FALSE) #' mydfm #' dfm_tolower(mydfm) #' dfm_toupper(mydfm) #' dfm_tolower <- function(x) { if (!is.dfm(x)) stop("dfm_tolower requires x to be a dfm object") colnames(x) <- stringi::stri_trans_tolower(colnames(x)) dfm_compress(x) } #' @rdname dfm_tolower #' @importFrom stringi stri_trans_toupper #' @export dfm_toupper <- function(x) { if (!is.dfm(x)) stop("dfm_toupper requires x to be a dfm object") colnames(x) <- stringi::stri_trans_toupper(colnames(x)) dfm_compress(x) } #' sort a dfm by frequency of one or more margins #' #' Sorts a \link{dfm} by descending frequency of total features, total features #' in documents, or both. #' #' @param x Document-feature matrix created by \code{\link{dfm}} #' @param margin which margin to sort on \code{features} to sort by frequency of #' features, \code{documents} to sort by total feature counts in documents, #' and \code{both} to sort by both #' @param decreasing TRUE (default) if sort will be in descending order, #' otherwise sort in increasing order #' @return A sorted \link{dfm} matrix object #' @export #' @author Ken Benoit #' @examples #' dtm <- dfm(data_corpus_inaugural) #' dtm[1:10, 1:5] #' dfm_sort(dtm)[1:10, 1:5] #' dfm_sort(dtm, decreasing = FALSE, "both")[1:10, 1:5] dfm_sort <- function(x, decreasing = TRUE, margin = c("features", "documents", "both")) { if (!is.dfm(x)) stop("dfm_sort requires x to be a dfm object") margin <- match.arg(margin) class_xorig <- class(x) if (margin=="features") { x <- x[, order(colSums(x), decreasing=decreasing)] } else if (margin=="documents") { x <- x[order(rowSums(x), decreasing=decreasing), ] } else if (margin=="both") { x <- x[order(rowSums(x), decreasing=decreasing), order(colSums(x), decreasing=decreasing)] } class(x) <- class_xorig return(x) }	/R/dfm_compress.R	no_license	strategist922/quanteda	R	false	false	6,479	r	#' compress a dfm or fcm by combining identical dimension elements #' #' "Compresses" a \link{dfm} or \link{fcm} whose dimension names are the same, #' for either documents or features. This may happen, for instance, if features #' are made equivalent through application of a thesaurus. It may also occur #' after lower-casing or stemming the features of a dfm, but this should only be #' done in very rare cases (approaching never: it's better to do this #' \emph{before} constructing the dfm.) It could also be needed after a #' \code{\link{cbind.dfm}} or \code{\link{rbind.dfm}} operation. #' #' @param x input object, a \link{dfm} or \link{fcm} #' @param margin character indicating on which margin to compress a dfm, either #' \code{"documents"}, \code{"features"}, or \code{"both"} (default). For fcm #' objects, \code{"documents"} has no effect. #' @param ... additional arguments passed from generic to specific methods #' @export #' @examples #' mat <- rbind(dfm(c("b A A", "C C a b B"), tolower = FALSE, verbose = FALSE), #' dfm("A C C C C C", tolower = FALSE, verbose = FALSE)) #' colnames(mat) <- char_tolower(featnames(mat)) #' mat #' dfm_compress(mat, margin = "documents") #' dfm_compress(mat, margin = "features") #' dfm_compress(mat) #' #' # no effect if no compression needed #' compactdfm <- dfm(data_char_inaugural[1:5], verbose = FALSE) #' dim(compactdfm) #' dim(dfm_compress(compactdfm)) #' dfm_compress <- function(x, margin = c("both", "documents", "features")) { UseMethod("dfm_compress") } #' @noRd #' @export dfm_compress.dfmSparse <- function(x, margin = c("both", "documents", "features")) { margin <- match.arg(margin) uniquednames <- unique(rownames(x)) uniquefnames <- unique(colnames(x)) if (length(uniquednames) == nrow(x) & length(uniquefnames) == ncol(x)) return(x) # add 1 since stored from 0, but constructor requires indexing from 1 new_i <- x@i + 1 new_j <- as(x, "dgTMatrix")@j + 1 allZeroFeatures <- match(names(which(colSums(x)==0)), uniquefnames) allZeroDocs <- match(names(which(rowSums(x)==0)), uniquednames) # combine documents if (margin %in% c("both", "documents") & length(uniquednames) < nrow(x)) new_i <- match(rownames(x), uniquednames)[new_i] else uniquednames <- rownames(x) # combine features if (margin %in% c("both", "features") & length(uniquefnames) < ncol(x)) new_j <- match(colnames(x), uniquefnames)[new_j] else uniquefnames <- colnames(x) if (nf <- length(allZeroFeatures)) { new_i <- c(new_i, rep(1, nf)) new_j <- c(new_j, allZeroFeatures) } if (nd <- length(allZeroDocs)) { new_i <- c(new_i, allZeroDocs) new_j <- c(new_j, rep(1, nd)) } new("dfmSparse", sparseMatrix(i = new_i, j = new_j, x = c(x@x, rep(0, length(allZeroFeatures)), rep(0, length(allZeroDocs))), dimnames = list(docs = uniquednames, features = uniquefnames)), settings = x@settings, weightTf = x@weightTf, weightDf = x@weightDf, smooth = x@smooth, ngrams = x@ngrams, concatenator = x@concatenator) } #' @noRd #' @export #' @examples #' # for dfmDense #' mat <- rbind(dfm(c("b A A", "C C a b B"), tolower = FALSE, verbose = FALSE), #' dfm("A C C C C C", tolower = FALSE, verbose = FALSE)) #' matd <- dfm_smooth(mat) #' colnames(matd) <- char_tolower(featnames(mat)) #' matd #' dfm_compress(matd, margin = "documents") #' dfm_compress(matd, margin = "features") #' dfm_compress(matd) dfm_compress.dfmDense <- function(x, ...) { dfm_compress(new("dfmSparse", Matrix::Matrix(as.matrix(x), sparse = TRUE), settings = x@settings, weightTf = x@weightTf, weightDf = x@weightDf, smooth = x@smooth, ngrams = x@ngrams, concatenator = x@concatenator), ...) } #' convert the case of the features of a dfm and combine #' #' \code{dfm_tolower} and \code{dfm_toupper} convert the features of the dfm to #' lower and upper case, respectively, and then recombine the counts. #' @param x the \link{dfm} or \link{fcm} object #' @importFrom stringi stri_trans_tolower #' @export #' @examples #' # for a document-feature matrix #' mydfm <- dfm(c("b A A", "C C a b B"), #' toLower = FALSE, verbose = FALSE) #' mydfm #' dfm_tolower(mydfm) #' dfm_toupper(mydfm) #' dfm_tolower <- function(x) { if (!is.dfm(x)) stop("dfm_tolower requires x to be a dfm object") colnames(x) <- stringi::stri_trans_tolower(colnames(x)) dfm_compress(x) } #' @rdname dfm_tolower #' @importFrom stringi stri_trans_toupper #' @export dfm_toupper <- function(x) { if (!is.dfm(x)) stop("dfm_toupper requires x to be a dfm object") colnames(x) <- stringi::stri_trans_toupper(colnames(x)) dfm_compress(x) } #' sort a dfm by frequency of one or more margins #' #' Sorts a \link{dfm} by descending frequency of total features, total features #' in documents, or both. #' #' @param x Document-feature matrix created by \code{\link{dfm}} #' @param margin which margin to sort on \code{features} to sort by frequency of #' features, \code{documents} to sort by total feature counts in documents, #' and \code{both} to sort by both #' @param decreasing TRUE (default) if sort will be in descending order, #' otherwise sort in increasing order #' @return A sorted \link{dfm} matrix object #' @export #' @author Ken Benoit #' @examples #' dtm <- dfm(data_corpus_inaugural) #' dtm[1:10, 1:5] #' dfm_sort(dtm)[1:10, 1:5] #' dfm_sort(dtm, decreasing = FALSE, "both")[1:10, 1:5] dfm_sort <- function(x, decreasing = TRUE, margin = c("features", "documents", "both")) { if (!is.dfm(x)) stop("dfm_sort requires x to be a dfm object") margin <- match.arg(margin) class_xorig <- class(x) if (margin=="features") { x <- x[, order(colSums(x), decreasing=decreasing)] } else if (margin=="documents") { x <- x[order(rowSums(x), decreasing=decreasing), ] } else if (margin=="both") { x <- x[order(rowSums(x), decreasing=decreasing), order(colSums(x), decreasing=decreasing)] } class(x) <- class_xorig return(x) }
## # Test: colnames<- # Description: Select a dataset, display column names, assign new colum names ## setwd(normalizePath(dirname(R.utils::commandArgs(asValues=TRUE)$"f"))) source('../findNSourceUtils.R') test.basic.colname.assignment <- function(conn) { Log.info("Uploading iris data...") hex <- h2o.uploadFile.FV(conn, locate("smalldata/iris/iris.csv"), "iris.hex") hex_name <- h2o.uploadFile.FV(conn, locate("smalldata/iris/iris_header.csv"), "iris_header.hex") print(colnames(hex)) print(colnames(hex_name)) colnames(hex) <- hex_name expect_that(colnames(hex), equals(colnames(hex_name))) testEnd() } doTest("EQ2 Tests: colnames<-", test.basic.colname.assignment)	/R/tests/testdir_misc/runit_colnameSet_basic.R	permissive	vkuznet/h2o	R	false	false	692	r	## # Test: colnames<- # Description: Select a dataset, display column names, assign new colum names ## setwd(normalizePath(dirname(R.utils::commandArgs(asValues=TRUE)$"f"))) source('../findNSourceUtils.R') test.basic.colname.assignment <- function(conn) { Log.info("Uploading iris data...") hex <- h2o.uploadFile.FV(conn, locate("smalldata/iris/iris.csv"), "iris.hex") hex_name <- h2o.uploadFile.FV(conn, locate("smalldata/iris/iris_header.csv"), "iris_header.hex") print(colnames(hex)) print(colnames(hex_name)) colnames(hex) <- hex_name expect_that(colnames(hex), equals(colnames(hex_name))) testEnd() } doTest("EQ2 Tests: colnames<-", test.basic.colname.assignment)
#' Custom devtools release checks. #' #' This function performs additional checks prior to release. It is called #' automatically by [release()]. #' #' @template devtools #' @keywords internal #' @export release_checks <- function(pkg = ".", built_path = NULL) { pkg <- as.package(pkg) cat_rule(paste0("Running additional devtools checks for ", pkg$package)) check_version(pkg) check_dev_versions(pkg) check_vignette_titles(pkg) check_news_md(pkg) check_remotes(pkg) cat_rule() } check_dev_versions <- function(pkg = ".") { pkg <- as.package(pkg) dep_list <- pkg[tolower(remotes::standardise_dep(TRUE))] deps <- do.call("rbind", unname(compact(lapply(dep_list, parse_deps)))) deps <- deps[!is.na(deps$version), , drop = FALSE] parsed <- lapply(deps$version, function(x) unlist(numeric_version(x))) lengths <- vapply(parsed, length, integer(1)) last_ver <- vapply(parsed, function(x) x[[length(x)]], integer(1)) is_dev <- lengths == 4 & last_ver >= 9000 check_status( !any(is_dev), "dependencies don't rely on dev versions", paste( "depends on devel versions of: ", paste0(deps$name[is_dev], collapse = ", ") ) ) return(invisible(FALSE)) } check_version <- function(pkg = ".") { pkg <- as.package(pkg) ver <- unlist(numeric_version(pkg$version)) check_status( length(ver) == 3, "version number has three components", paste0("version (", pkg$version, ") should have exactly three components") ) } check_vignette_titles <- function(pkg = ".") { pkg <- as.package(pkg) vigns <- tools::pkgVignettes(dir = pkg$path) if (length(vigns$docs) == 0) return() has_vignette_title <- function(v, n) { h <- readLines(v, n = n) any(grepl("Vignette Title", h)) } v <- stats::setNames(vigns$docs, basename(vigns$docs)) has_vt <- vapply(v, has_vignette_title, logical(1), n = 30) check_status( !any(has_vt), "vignette titles are not placeholders", paste0( "placeholder 'Vignette Title' detected in 'title' field and/or ", "'VignetteIndexEntry' for: ", paste(names(has_vt)[has_vt], collapse = ",") ) ) } check_news_md <- function(pkg) { pkg <- as.package(pkg) news_path <- file.path(pkg$path, "NEWS.md") if (!file.exists(news_path)) { return() } ignore_path <- file.path(pkg$path, ".Rbuildignore") if (!file.exists(ignore_path)) { ignore_lines <- character() } else { ignore_lines <- readLines(ignore_path) } has_news <- grepl("NEWS\\.md", ignore_lines, fixed = TRUE) \| grepl("NEWS.md", ignore_lines, fixed = TRUE) check_status( !any(has_news), "NEWS.md is not ignored", "NEWS.md now supported by CRAN and doesn't need to be ignored." ) news_rd_path <- file.path(pkg$path, "inst/NEWS.Rd") check_status( !file.exists(news_rd_path), "NEWS.Rd does not exist", "NEWS.md now supported by CRAN, NEWS.Rd can be removed." ) } check_remotes <- function(pkg) { check_status( !has_dev_remotes(pkg), "DESCRIPTION doesn't have Remotes field", "Remotes field should be removed before CRAN submission." ) } has_dev_remotes <- function(pkg) { !is.null(pkg[["remotes"]]) } check_status <- function(status, name, warning) { cat("Checking ", name, "...", sep = "") status <- tryCatch( if (status) { cat(" OK\n") } else { cat("\n") message("WARNING: ", warning) }, error = function(e) { cat("\n") message("ERROR: ", conditionMessage(e)) FALSE } ) invisible(status) }	/R/check-devtools.R	no_license	insightdataintel/devtools	R	false	false	3,548	r	#' Custom devtools release checks. #' #' This function performs additional checks prior to release. It is called #' automatically by [release()]. #' #' @template devtools #' @keywords internal #' @export release_checks <- function(pkg = ".", built_path = NULL) { pkg <- as.package(pkg) cat_rule(paste0("Running additional devtools checks for ", pkg$package)) check_version(pkg) check_dev_versions(pkg) check_vignette_titles(pkg) check_news_md(pkg) check_remotes(pkg) cat_rule() } check_dev_versions <- function(pkg = ".") { pkg <- as.package(pkg) dep_list <- pkg[tolower(remotes::standardise_dep(TRUE))] deps <- do.call("rbind", unname(compact(lapply(dep_list, parse_deps)))) deps <- deps[!is.na(deps$version), , drop = FALSE] parsed <- lapply(deps$version, function(x) unlist(numeric_version(x))) lengths <- vapply(parsed, length, integer(1)) last_ver <- vapply(parsed, function(x) x[[length(x)]], integer(1)) is_dev <- lengths == 4 & last_ver >= 9000 check_status( !any(is_dev), "dependencies don't rely on dev versions", paste( "depends on devel versions of: ", paste0(deps$name[is_dev], collapse = ", ") ) ) return(invisible(FALSE)) } check_version <- function(pkg = ".") { pkg <- as.package(pkg) ver <- unlist(numeric_version(pkg$version)) check_status( length(ver) == 3, "version number has three components", paste0("version (", pkg$version, ") should have exactly three components") ) } check_vignette_titles <- function(pkg = ".") { pkg <- as.package(pkg) vigns <- tools::pkgVignettes(dir = pkg$path) if (length(vigns$docs) == 0) return() has_vignette_title <- function(v, n) { h <- readLines(v, n = n) any(grepl("Vignette Title", h)) } v <- stats::setNames(vigns$docs, basename(vigns$docs)) has_vt <- vapply(v, has_vignette_title, logical(1), n = 30) check_status( !any(has_vt), "vignette titles are not placeholders", paste0( "placeholder 'Vignette Title' detected in 'title' field and/or ", "'VignetteIndexEntry' for: ", paste(names(has_vt)[has_vt], collapse = ",") ) ) } check_news_md <- function(pkg) { pkg <- as.package(pkg) news_path <- file.path(pkg$path, "NEWS.md") if (!file.exists(news_path)) { return() } ignore_path <- file.path(pkg$path, ".Rbuildignore") if (!file.exists(ignore_path)) { ignore_lines <- character() } else { ignore_lines <- readLines(ignore_path) } has_news <- grepl("NEWS\\.md", ignore_lines, fixed = TRUE) \| grepl("NEWS.md", ignore_lines, fixed = TRUE) check_status( !any(has_news), "NEWS.md is not ignored", "NEWS.md now supported by CRAN and doesn't need to be ignored." ) news_rd_path <- file.path(pkg$path, "inst/NEWS.Rd") check_status( !file.exists(news_rd_path), "NEWS.Rd does not exist", "NEWS.md now supported by CRAN, NEWS.Rd can be removed." ) } check_remotes <- function(pkg) { check_status( !has_dev_remotes(pkg), "DESCRIPTION doesn't have Remotes field", "Remotes field should be removed before CRAN submission." ) } has_dev_remotes <- function(pkg) { !is.null(pkg[["remotes"]]) } check_status <- function(status, name, warning) { cat("Checking ", name, "...", sep = "") status <- tryCatch( if (status) { cat(" OK\n") } else { cat("\n") message("WARNING: ", warning) }, error = function(e) { cat("\n") message("ERROR: ", conditionMessage(e)) FALSE } ) invisible(status) }
library(HardyWeinberg) ### Name: HWD ### Title: Compute disequilibrium statistic D ### Aliases: HWD ### Keywords: misc ### ** Examples x <- c(MM=298,MN=489,NN=213) D <- HWD(x) cat("Disequilibrium coefficient: ",D,"\n")	/data/genthat_extracted_code/HardyWeinberg/examples/HWD.Rd.R	no_license	surayaaramli/typeRrh	R	false	false	226	r	library(HardyWeinberg) ### Name: HWD ### Title: Compute disequilibrium statistic D ### Aliases: HWD ### Keywords: misc ### ** Examples x <- c(MM=298,MN=489,NN=213) D <- HWD(x) cat("Disequilibrium coefficient: ",D,"\n")
# Generate SALUS Experiment Files (.xdb.xml) # Jill Deines # June 15, 2018 # Goal: make SALUS experiment files based on: # - physical characteristics (soil/climate/crop/irrigation) from 02.20....Rmd # - management parameters (planting densities, irrigation thresholds) # Output: # 1 experiment .xdb.xml file for every 1000 experiments # the HPCC shell script (.sh) # the HPCC batch script (.bat) # To Use: # This is designed to run on the HPCC to quickly create the .xdb.xml's # Each parameter run shall have a saved 03.XX script and parameter file matched # to the run name to preserve parameters # Parameters set and csv exported from 02.90_salusParameters.Rmd # .xdb.xml's are created in a temp folder on HPCC and not auto-saved # Notes # most functions bundled into a salustools package # End Top Matter --------------------------------------------------------------- # R Packages Needed library(dplyr) library(stringr) library(readr) #library(devtools) #install_github("jdeines/salustools") library(salustools) # from Jill's github library(lubridate) #------------------------------------------------------------------------------- # User Parameters #------------------------------------------------------------------------------- # run name (this should also be parameter set name) runName <- '0074_thetaC' # shouldn't need to change below? # hpcc directory containing static salus files salusBaseDir <- '/mnt/home/deinesji/salus/' # hpcc run directory runBaseDir <- paste0(salusBaseDir,runName,'/') parameterDir <- runBaseDir parameterFileNoExt <- runName # make scratch directories # create output directories scratchSalus <- '/mnt/scratch/deinesji/salus/' runFolder <- paste0(scratchSalus,runName) # scratch run folder dir.create(runFolder, showWarnings = FALSE) dir.create(paste0(runFolder,'/results'), showWarnings = FALSE) # hpcc scratch output directory to hold xdb.xml's outDir <- paste0(scratchSalus,parameterFileNoExt,'/') # salus crop database cdb.xml cropfile <- 'cropsn29Dec2016_SGttMatrFixed_whIB1099_sd6.cdb.xml' cropfileNoExt <- 'cropsn29Dec2016_SGttMatrFixed_whIB1099_sd6' # cdb.xml file, no extension # experiment dir and unique combos experimentDir <- salusBaseDir exptCombos <- '1_Experiments_SD6_top7_aimhpa_20180618.rds' ## RUN NAME AND TIME SPECS runTitle <- runName startDOY <- 1 startYear <- 2006 # winter wheat will be adjusted to be planted in late 2005 endYear <- 2017 ## HPCC Folders and SH info xdbDir <- outDir # find xdb's in the output dir xdbOut <- xdbDir # write the Sh scripts to same directory # hpcc directory containing salus static files hpcHomeDir <- salusBaseDir # hpcc directory containing created xdb.xml's and .sh scripts for this run hpcXdbDir <- xdbDir # hpcc directory for salus results files (stored in scratch for future processing) hpcOutDir <- paste0(xdbDir, '/results/') # arguments for shell script writers: be mindful of extensions sdb <- "KS" # sdb.xml, no extension wdbZip <- 'gridmet_4kgrid_20050101_20171231.tar.gz' # tarballed weather xdb.xml's #------------------------------------------------------------------------------- # Process Vars / END USER INPUT #------------------------------------------------------------------------------- # adjust start year for winter wheat planting wheatStart <- startYear -1 # calculate number of years in run (including wheat pre-planting) Nyrs <- endYear - startYear + 2 # load parameters parameters <- read_csv(paste0(parameterDir,parameterFileNoExt,'_parameters.csv')) # define crop key to link exp codes with management cropkey <- data.frame(cropCode = c('001','004','005','024','036','061','176'), crop = c('CORN','SORGHUM','SOYBEANS','WHEAT','ALFALFA', 'FALLOW','GRASS')) # Extract Unique Combo Experiments --------------------------------------------- # load experiments and split into sets of 1000 per .xdb.xml # load experiments expts <- readRDS(paste0(experimentDir,exptCombos)) # split out pieces expts2 <- expts %>% mutate(weather = str_sub(ExpCode, start = 10, end = 13), state = str_sub(ExpCode, start = 1, end = 2), mukey = str_sub(ExpCode, start = 3, end = 9), static = str_sub(ExpCode, start = 1, end = 13), ExpCode = as.character(ExpCode)) # make a grouping vector ngroup <- ceiling(nrow(expts)/1000) groups <- sort(rep(1:ngroup, 1000))[1:nrow(expts2)] # Assign into groups of 1000, sequentially lemaExps3 <- expts2 %>% mutate(xdbGroup = groups, xdbCode = paste0('X_',xdbGroup)) ## # write experiment files! ------------------------------------------------------ # writes an experiment file for each 1000-expt group by looping through groups # and individual rotational components of each expt # g<-1 # i<-1 # m<-1 # write an experiment file for each xdb group for(g in 1:ngroup){ expt_set <- lemaExps3 %>% filter(xdbGroup == g) # translate variables in parameters needed to specify experiment tag exp_master <- salustools::makeExperimentTable(runTitle, expt_set$ExpID, expt_set$mukey, expt_set$weather, expt_set$ExpCode, wheatStart, Nyrs, startDOY, cropfp = cropfile, state = 'KS') ### Write the file! ------------------------------- outFile2 <- paste0(outDir,expt_set$xdbCode[1], '.xdb.xml') # initialize the file write_xdb_topMatter(outFile2) # for each experiment: for(i in 1:nrow(exp_master)){ # write each set of experiment parameters write_xdb_experiment(outFile2, exp_master$ExpID[i], exp_master$runTitle[i], exp_master$startYear[i], exp_master$Nyrs[i], exp_master$startDOY[i], exp_master$weather[i], exp_master$weatherfp[i], exp_master$soilId[i], exp_master$soilfp[i], exp_master$cropfp[i]) # parse experiment rotations rotations <- salustools::parseRotationStrings(as.character(exp_master$ExpCode[i]), startyear = exp_master$startYear[i]+1, cropkey) # combine with management table annualSpecs <- rotations %>% left_join(parameters,by = c("year", "crop")) # write rotation and management parameters for each year for(m in 1:nrow(annualSpecs)){ # reset irrigation method based on null irrigation status if (annualSpecs$irrStatus[m] == 0){ annualSpecs$IIrrI[m] <- 'N' } # set density column names based on irrigation status if (annualSpecs$IIrrI[m] == 'N') { ppopCol <- 'Ppop_rain' rowsCol <- 'RowSpc' cultivarCol <- 'cult_R' } if (annualSpecs$IIrrI[m] %in% c('F','A','R','D','Y')){ ppopCol <- 'Ppop_irr' rowsCol <- 'RowSp_irr' cultivarCol <- 'cult_I' } # rotation parameters write_xdb_rotation(outFile2, m, annualSpecs$crop[m], annualSpecs$IIrrI[m], annualSpecs$IferI[m], annualSpecs$ITilI[m], annualSpecs$IHarI[m], annualSpecs$IResI[m]) # management: planting ## adjust KS state median for by planting date adjust param for nw region adjPlantDOY <- annualSpecs$plantingDOY_50[m] + annualSpecs$plantDOY_adj[m] write_xdb_mPlanting(outFile2, annualSpecs$CropMod[m], annualSpecs$SpeciesID[m], annualSpecs[m,cultivarCol], annualSpecs$plantYear[m], adjPlantDOY, annualSpecs[m,ppopCol], annualSpecs[m,rowsCol], annualSpecs$Sdepth[m]) # management: fertilize if(annualSpecs$IferI[m] == 'R'){ # specified fert # figure out how many events for(p in 1:annualSpecs[m,'numFertEvents']){ # set first fert date based on planting fert1Day <- adjPlantDOY # but not for wheat if(annualSpecs$crop[m] == 'WHEAT') fert1Day <- 75 if(p==1){ write_xdb_mFertilize(outFile2, annualSpecs$harvYear[m], fert1Day, annualSpecs$ANFer1[m]) } if(p==2){ fert2DOY <- adjPlantDOY + 30 write_xdb_mFertilize(outFile2, annualSpecs$harvYear[m], fert2DOY, annualSpecs$ANFer2[m]) } } } if(annualSpecs$IferI[m] == 'A'){ # auto fertilization write_xdb_mFertilize_Auto(outFile2, annualSpecs$SoilNC[m], annualSpecs$ANFer1[m]) } # management: tillage if(annualSpecs$ITilI[m] == 'R'){ write_xdb_mTillage(outFile2, annualSpecs$harvYear[m], adjPlantDOY-annualSpecs$T_DaysBeforePlanting[m], TDep = annualSpecs$TDep[m]) } # management: irrigation if(annualSpecs$IIrrI[m] == 'F'){ write_xdb_mIrrigate_Auto(outFile2, AIrAm = annualSpecs$AIrAm[m], DSoil = annualSpecs$DSoil[m], ThetaC = annualSpecs$ThetaC[m], IAMe = annualSpecs$IAMe[m]) } # management: harvest if(annualSpecs$IHarI[m] == 'M'){ write_xdb_mHarvest_maturity(outFile2, closeComponent = 'Y') } if(annualSpecs$IHarI[m] == 'R'){ write_xdb_mHarvest_reported(outFile2, annualSpecs$harvYear[m], annualSpecs$harvestedDOY_50[m], closeComponent = 'Y') } } # close rotations and experiment write_xdb_bottomMatter(outFile2, closeRotation = 'Y', closeExperiment = 'Y') } # close out write_xdb_bottomMatter(outFile2, writeVersion = 'Y', closeXDB = 'Y') } ## Make the HPCC scripts ------------------------------------------------------- # Shell script: make 1 sh file for each experiment # extract xdb name from xmls xdb <- sapply(strsplit(list.files(xdbDir, pattern='*.xdb.xml'),'.', fixed=TRUE), head, 1) DayVars <- 'ExpID,Title,SpeciesID,GWAD,IRRC,DRNC,PREC,ETAC,ESAC,EPAC,ROFC' SeaVars <- 'ExpID,Title,SpeciesID,GWAD' walltime <- '01:30:00' memory <- '2000mb' SALUS_bat_Nflag <- '-w' # loop over xdbs for (i in 1:length(xdb)){ salustools::write_HPC_shell(xdbOut, hpcHomeDir, hpcXdbDir, hpcOutDir, Nflag = SALUS_bat_Nflag, xdb[i], sdb, wdbZip, DayVars, SeaVars, walltime, memory, cdb = cropfileNoExt) } ### HPC bash bat script # sends the sh files to queue shNames <- paste0(xdb,'.sh') fileOut <- paste0(xdbOut, parameterFileNoExt, '.bat') # write out .bat file write_HPC_bat(shNames, fileOut)	/data/SALUS_output/0030_waterSA/0074_thetaC/03.00_salusXdb_experimentWriter_HPCC.R	permissive	jdeines/Deines_etal_LEMA_SALUS	R	false	false	11,106	r	# Generate SALUS Experiment Files (.xdb.xml) # Jill Deines # June 15, 2018 # Goal: make SALUS experiment files based on: # - physical characteristics (soil/climate/crop/irrigation) from 02.20....Rmd # - management parameters (planting densities, irrigation thresholds) # Output: # 1 experiment .xdb.xml file for every 1000 experiments # the HPCC shell script (.sh) # the HPCC batch script (.bat) # To Use: # This is designed to run on the HPCC to quickly create the .xdb.xml's # Each parameter run shall have a saved 03.XX script and parameter file matched # to the run name to preserve parameters # Parameters set and csv exported from 02.90_salusParameters.Rmd # .xdb.xml's are created in a temp folder on HPCC and not auto-saved # Notes # most functions bundled into a salustools package # End Top Matter --------------------------------------------------------------- # R Packages Needed library(dplyr) library(stringr) library(readr) #library(devtools) #install_github("jdeines/salustools") library(salustools) # from Jill's github library(lubridate) #------------------------------------------------------------------------------- # User Parameters #------------------------------------------------------------------------------- # run name (this should also be parameter set name) runName <- '0074_thetaC' # shouldn't need to change below? # hpcc directory containing static salus files salusBaseDir <- '/mnt/home/deinesji/salus/' # hpcc run directory runBaseDir <- paste0(salusBaseDir,runName,'/') parameterDir <- runBaseDir parameterFileNoExt <- runName # make scratch directories # create output directories scratchSalus <- '/mnt/scratch/deinesji/salus/' runFolder <- paste0(scratchSalus,runName) # scratch run folder dir.create(runFolder, showWarnings = FALSE) dir.create(paste0(runFolder,'/results'), showWarnings = FALSE) # hpcc scratch output directory to hold xdb.xml's outDir <- paste0(scratchSalus,parameterFileNoExt,'/') # salus crop database cdb.xml cropfile <- 'cropsn29Dec2016_SGttMatrFixed_whIB1099_sd6.cdb.xml' cropfileNoExt <- 'cropsn29Dec2016_SGttMatrFixed_whIB1099_sd6' # cdb.xml file, no extension # experiment dir and unique combos experimentDir <- salusBaseDir exptCombos <- '1_Experiments_SD6_top7_aimhpa_20180618.rds' ## RUN NAME AND TIME SPECS runTitle <- runName startDOY <- 1 startYear <- 2006 # winter wheat will be adjusted to be planted in late 2005 endYear <- 2017 ## HPCC Folders and SH info xdbDir <- outDir # find xdb's in the output dir xdbOut <- xdbDir # write the Sh scripts to same directory # hpcc directory containing salus static files hpcHomeDir <- salusBaseDir # hpcc directory containing created xdb.xml's and .sh scripts for this run hpcXdbDir <- xdbDir # hpcc directory for salus results files (stored in scratch for future processing) hpcOutDir <- paste0(xdbDir, '/results/') # arguments for shell script writers: be mindful of extensions sdb <- "KS" # sdb.xml, no extension wdbZip <- 'gridmet_4kgrid_20050101_20171231.tar.gz' # tarballed weather xdb.xml's #------------------------------------------------------------------------------- # Process Vars / END USER INPUT #------------------------------------------------------------------------------- # adjust start year for winter wheat planting wheatStart <- startYear -1 # calculate number of years in run (including wheat pre-planting) Nyrs <- endYear - startYear + 2 # load parameters parameters <- read_csv(paste0(parameterDir,parameterFileNoExt,'_parameters.csv')) # define crop key to link exp codes with management cropkey <- data.frame(cropCode = c('001','004','005','024','036','061','176'), crop = c('CORN','SORGHUM','SOYBEANS','WHEAT','ALFALFA', 'FALLOW','GRASS')) # Extract Unique Combo Experiments --------------------------------------------- # load experiments and split into sets of 1000 per .xdb.xml # load experiments expts <- readRDS(paste0(experimentDir,exptCombos)) # split out pieces expts2 <- expts %>% mutate(weather = str_sub(ExpCode, start = 10, end = 13), state = str_sub(ExpCode, start = 1, end = 2), mukey = str_sub(ExpCode, start = 3, end = 9), static = str_sub(ExpCode, start = 1, end = 13), ExpCode = as.character(ExpCode)) # make a grouping vector ngroup <- ceiling(nrow(expts)/1000) groups <- sort(rep(1:ngroup, 1000))[1:nrow(expts2)] # Assign into groups of 1000, sequentially lemaExps3 <- expts2 %>% mutate(xdbGroup = groups, xdbCode = paste0('X_',xdbGroup)) ## # write experiment files! ------------------------------------------------------ # writes an experiment file for each 1000-expt group by looping through groups # and individual rotational components of each expt # g<-1 # i<-1 # m<-1 # write an experiment file for each xdb group for(g in 1:ngroup){ expt_set <- lemaExps3 %>% filter(xdbGroup == g) # translate variables in parameters needed to specify experiment tag exp_master <- salustools::makeExperimentTable(runTitle, expt_set$ExpID, expt_set$mukey, expt_set$weather, expt_set$ExpCode, wheatStart, Nyrs, startDOY, cropfp = cropfile, state = 'KS') ### Write the file! ------------------------------- outFile2 <- paste0(outDir,expt_set$xdbCode[1], '.xdb.xml') # initialize the file write_xdb_topMatter(outFile2) # for each experiment: for(i in 1:nrow(exp_master)){ # write each set of experiment parameters write_xdb_experiment(outFile2, exp_master$ExpID[i], exp_master$runTitle[i], exp_master$startYear[i], exp_master$Nyrs[i], exp_master$startDOY[i], exp_master$weather[i], exp_master$weatherfp[i], exp_master$soilId[i], exp_master$soilfp[i], exp_master$cropfp[i]) # parse experiment rotations rotations <- salustools::parseRotationStrings(as.character(exp_master$ExpCode[i]), startyear = exp_master$startYear[i]+1, cropkey) # combine with management table annualSpecs <- rotations %>% left_join(parameters,by = c("year", "crop")) # write rotation and management parameters for each year for(m in 1:nrow(annualSpecs)){ # reset irrigation method based on null irrigation status if (annualSpecs$irrStatus[m] == 0){ annualSpecs$IIrrI[m] <- 'N' } # set density column names based on irrigation status if (annualSpecs$IIrrI[m] == 'N') { ppopCol <- 'Ppop_rain' rowsCol <- 'RowSpc' cultivarCol <- 'cult_R' } if (annualSpecs$IIrrI[m] %in% c('F','A','R','D','Y')){ ppopCol <- 'Ppop_irr' rowsCol <- 'RowSp_irr' cultivarCol <- 'cult_I' } # rotation parameters write_xdb_rotation(outFile2, m, annualSpecs$crop[m], annualSpecs$IIrrI[m], annualSpecs$IferI[m], annualSpecs$ITilI[m], annualSpecs$IHarI[m], annualSpecs$IResI[m]) # management: planting ## adjust KS state median for by planting date adjust param for nw region adjPlantDOY <- annualSpecs$plantingDOY_50[m] + annualSpecs$plantDOY_adj[m] write_xdb_mPlanting(outFile2, annualSpecs$CropMod[m], annualSpecs$SpeciesID[m], annualSpecs[m,cultivarCol], annualSpecs$plantYear[m], adjPlantDOY, annualSpecs[m,ppopCol], annualSpecs[m,rowsCol], annualSpecs$Sdepth[m]) # management: fertilize if(annualSpecs$IferI[m] == 'R'){ # specified fert # figure out how many events for(p in 1:annualSpecs[m,'numFertEvents']){ # set first fert date based on planting fert1Day <- adjPlantDOY # but not for wheat if(annualSpecs$crop[m] == 'WHEAT') fert1Day <- 75 if(p==1){ write_xdb_mFertilize(outFile2, annualSpecs$harvYear[m], fert1Day, annualSpecs$ANFer1[m]) } if(p==2){ fert2DOY <- adjPlantDOY + 30 write_xdb_mFertilize(outFile2, annualSpecs$harvYear[m], fert2DOY, annualSpecs$ANFer2[m]) } } } if(annualSpecs$IferI[m] == 'A'){ # auto fertilization write_xdb_mFertilize_Auto(outFile2, annualSpecs$SoilNC[m], annualSpecs$ANFer1[m]) } # management: tillage if(annualSpecs$ITilI[m] == 'R'){ write_xdb_mTillage(outFile2, annualSpecs$harvYear[m], adjPlantDOY-annualSpecs$T_DaysBeforePlanting[m], TDep = annualSpecs$TDep[m]) } # management: irrigation if(annualSpecs$IIrrI[m] == 'F'){ write_xdb_mIrrigate_Auto(outFile2, AIrAm = annualSpecs$AIrAm[m], DSoil = annualSpecs$DSoil[m], ThetaC = annualSpecs$ThetaC[m], IAMe = annualSpecs$IAMe[m]) } # management: harvest if(annualSpecs$IHarI[m] == 'M'){ write_xdb_mHarvest_maturity(outFile2, closeComponent = 'Y') } if(annualSpecs$IHarI[m] == 'R'){ write_xdb_mHarvest_reported(outFile2, annualSpecs$harvYear[m], annualSpecs$harvestedDOY_50[m], closeComponent = 'Y') } } # close rotations and experiment write_xdb_bottomMatter(outFile2, closeRotation = 'Y', closeExperiment = 'Y') } # close out write_xdb_bottomMatter(outFile2, writeVersion = 'Y', closeXDB = 'Y') } ## Make the HPCC scripts ------------------------------------------------------- # Shell script: make 1 sh file for each experiment # extract xdb name from xmls xdb <- sapply(strsplit(list.files(xdbDir, pattern='*.xdb.xml'),'.', fixed=TRUE), head, 1) DayVars <- 'ExpID,Title,SpeciesID,GWAD,IRRC,DRNC,PREC,ETAC,ESAC,EPAC,ROFC' SeaVars <- 'ExpID,Title,SpeciesID,GWAD' walltime <- '01:30:00' memory <- '2000mb' SALUS_bat_Nflag <- '-w' # loop over xdbs for (i in 1:length(xdb)){ salustools::write_HPC_shell(xdbOut, hpcHomeDir, hpcXdbDir, hpcOutDir, Nflag = SALUS_bat_Nflag, xdb[i], sdb, wdbZip, DayVars, SeaVars, walltime, memory, cdb = cropfileNoExt) } ### HPC bash bat script # sends the sh files to queue shNames <- paste0(xdb,'.sh') fileOut <- paste0(xdbOut, parameterFileNoExt, '.bat') # write out .bat file write_HPC_bat(shNames, fileOut)
fortify.zoo <- function(model, data, names = c("Index", "Series", "Value"), melt = FALSE, sep = NULL, ...) { if (!is.null(sep) && !melt) stop("Cannot specify sep if melt = FALSE") ## dimensions n <- NROW(model) k <- NCOL(model) ## dots only named data.frame arguments dots <- list(...) dots <- dots[names(dots) %in% c("row.names", "check.rows", "check.names", "fix.empty.names", "stringsAsFactors")] ## series labels lab <- colnames(model) if(is.null(lab)) lab <- rep.int(deparse(substitute(model)), k) lab <- make.unique(lab) ## return data names nm <- c("Index", "Series", "Value") if(!is.null(names(names))) names <- names[nm] if(is.list(names)) { names(names) <- nm for(i in 1L:3L) if(is.null(names[[i]]) \|\| is.na(names[[i]])) names[[i]] <- nm[i] nm <- unlist(names) } else { names <- rep_len(names, 3L) nm[!is.na(names)] <- names[!is.na(names)] } ## either long format (melt = TRUE) or wide format (melt = FALSE) if(melt) { df <- if(k == 1L) { do.call("data.frame", c( list(index(model), factor(rep.int(1, n), labels = lab), coredata(model)), dots)) } else { do.call("data.frame", c( list(index(model)[rep.int(1:n, k)], factor(rep(1:k, each = n), levels = 1:k, labels = lab), as.vector(coredata(model))), dots)) } if (!is.null(sep)) { df <- data.frame(df[1L], do.call("rbind", strsplit(as.character(df[[2L]]), ".", fixed = TRUE)), df[3L]) } nl <- length(nm) names(df) <- c(nm[1L], make.unique(rep_len(nm[-c(1L, nl)], ncol(df) - 2L)), nm[nl]) } else { df <- cbind( do.call("data.frame", c(list(index(model)), dots)), coredata(model)) names(df) <- c(nm[1L], lab) } return(df) } autoplot.zoo <- function(object, geom = "line", facets, ...) { ## convert to data.frame (and assure correct label ## processing by fortify.zoo) lab <- deparse(substitute(object)) if(NCOL(object) == 1L) { if(is.null(dim(object))) dim(object) <- c(NROW(object), 1L) if(is.null(colnames(object))) colnames(object) <- lab } if(is.null(colnames(object))) colnames(object) <- paste(lab, 1:NCOL(object), sep = ".") df <- fortify.zoo(object, melt = TRUE) ## default for facets single <- nlevels(df$Series) == 1L if(missing(facets)) { auto <- TRUE facets <- if(single) NULL else Series ~ . } else { auto <- FALSE } ## "fake" variables for nonstandard evaluation Index <- Value <- Series <- NULL ## call qplot gg <- if(single \| (!is.null(facets) & auto)) { ggplot2::qplot(Index, Value, data = df, geom = geom, facets = facets, ...) + ggplot2::ylab(if(single) levels(df$Series) else "") + ggplot2::xlab("Index") } else { ggplot2::qplot(Index, Value, data = df, group = Series, geom = geom, facets = facets, colour = Series, ...) + ggplot2::ylab("") + ggplot2::xlab("Index") } return(gg) } facet_free <- function (facets = Series ~ ., margins = FALSE, scales = "free_y", ...) { ggplot2::facet_grid(facets, margins = margins, scales = scales, ...) } yearmon_trans <- function(format = "%b %Y", n = 5) { breaks. <- function(x) as.yearmon(scales::pretty_breaks(n)(x)) format. <- function(x) format(x, format = format) scales::trans_new("yearmon", transform = as.numeric, inverse = as.yearmon, breaks = breaks., format = format.) } scale_x_yearmon <- function(..., format = "%b %Y", n = 5) { ggplot2::scale_x_continuous(..., trans = yearmon_trans(format, n)) } scale_y_yearmon <- function(..., format = "%b %Y", n = 5) { ggplot2::scale_y_continuous(..., trans = yearmon_trans(format, n)) } yearqtr_trans <- function(format = "%Y-%q", n = 5) { breaks. <- function(x) as.yearqtr(scales::pretty_breaks(n)(x)) format. <- function(x) zoo::format.yearqtr(x, format = format) scales::trans_new("yearqtr", transform = as.numeric, inverse = as.yearqtr, breaks = breaks., format = format.) } scale_x_yearqtr <- function(..., format = "%Y-%q", n = 5) { ggplot2::scale_x_continuous(..., trans = yearqtr_trans(format, n)) } scale_y_yearqtr <- function(..., format = "%Y-%q", n = 5) { ggplot2::scale_y_continuous(..., trans = yearqtr_trans(format, n)) }	/R/ggplot2.zoo.R	no_license	FieldberryGruppe/zoo	R	false	false	4,214	r	fortify.zoo <- function(model, data, names = c("Index", "Series", "Value"), melt = FALSE, sep = NULL, ...) { if (!is.null(sep) && !melt) stop("Cannot specify sep if melt = FALSE") ## dimensions n <- NROW(model) k <- NCOL(model) ## dots only named data.frame arguments dots <- list(...) dots <- dots[names(dots) %in% c("row.names", "check.rows", "check.names", "fix.empty.names", "stringsAsFactors")] ## series labels lab <- colnames(model) if(is.null(lab)) lab <- rep.int(deparse(substitute(model)), k) lab <- make.unique(lab) ## return data names nm <- c("Index", "Series", "Value") if(!is.null(names(names))) names <- names[nm] if(is.list(names)) { names(names) <- nm for(i in 1L:3L) if(is.null(names[[i]]) \|\| is.na(names[[i]])) names[[i]] <- nm[i] nm <- unlist(names) } else { names <- rep_len(names, 3L) nm[!is.na(names)] <- names[!is.na(names)] } ## either long format (melt = TRUE) or wide format (melt = FALSE) if(melt) { df <- if(k == 1L) { do.call("data.frame", c( list(index(model), factor(rep.int(1, n), labels = lab), coredata(model)), dots)) } else { do.call("data.frame", c( list(index(model)[rep.int(1:n, k)], factor(rep(1:k, each = n), levels = 1:k, labels = lab), as.vector(coredata(model))), dots)) } if (!is.null(sep)) { df <- data.frame(df[1L], do.call("rbind", strsplit(as.character(df[[2L]]), ".", fixed = TRUE)), df[3L]) } nl <- length(nm) names(df) <- c(nm[1L], make.unique(rep_len(nm[-c(1L, nl)], ncol(df) - 2L)), nm[nl]) } else { df <- cbind( do.call("data.frame", c(list(index(model)), dots)), coredata(model)) names(df) <- c(nm[1L], lab) } return(df) } autoplot.zoo <- function(object, geom = "line", facets, ...) { ## convert to data.frame (and assure correct label ## processing by fortify.zoo) lab <- deparse(substitute(object)) if(NCOL(object) == 1L) { if(is.null(dim(object))) dim(object) <- c(NROW(object), 1L) if(is.null(colnames(object))) colnames(object) <- lab } if(is.null(colnames(object))) colnames(object) <- paste(lab, 1:NCOL(object), sep = ".") df <- fortify.zoo(object, melt = TRUE) ## default for facets single <- nlevels(df$Series) == 1L if(missing(facets)) { auto <- TRUE facets <- if(single) NULL else Series ~ . } else { auto <- FALSE } ## "fake" variables for nonstandard evaluation Index <- Value <- Series <- NULL ## call qplot gg <- if(single \| (!is.null(facets) & auto)) { ggplot2::qplot(Index, Value, data = df, geom = geom, facets = facets, ...) + ggplot2::ylab(if(single) levels(df$Series) else "") + ggplot2::xlab("Index") } else { ggplot2::qplot(Index, Value, data = df, group = Series, geom = geom, facets = facets, colour = Series, ...) + ggplot2::ylab("") + ggplot2::xlab("Index") } return(gg) } facet_free <- function (facets = Series ~ ., margins = FALSE, scales = "free_y", ...) { ggplot2::facet_grid(facets, margins = margins, scales = scales, ...) } yearmon_trans <- function(format = "%b %Y", n = 5) { breaks. <- function(x) as.yearmon(scales::pretty_breaks(n)(x)) format. <- function(x) format(x, format = format) scales::trans_new("yearmon", transform = as.numeric, inverse = as.yearmon, breaks = breaks., format = format.) } scale_x_yearmon <- function(..., format = "%b %Y", n = 5) { ggplot2::scale_x_continuous(..., trans = yearmon_trans(format, n)) } scale_y_yearmon <- function(..., format = "%b %Y", n = 5) { ggplot2::scale_y_continuous(..., trans = yearmon_trans(format, n)) } yearqtr_trans <- function(format = "%Y-%q", n = 5) { breaks. <- function(x) as.yearqtr(scales::pretty_breaks(n)(x)) format. <- function(x) zoo::format.yearqtr(x, format = format) scales::trans_new("yearqtr", transform = as.numeric, inverse = as.yearqtr, breaks = breaks., format = format.) } scale_x_yearqtr <- function(..., format = "%Y-%q", n = 5) { ggplot2::scale_x_continuous(..., trans = yearqtr_trans(format, n)) } scale_y_yearqtr <- function(..., format = "%Y-%q", n = 5) { ggplot2::scale_y_continuous(..., trans = yearqtr_trans(format, n)) }
rm(list=ls()) library(data.table) load("D:/HEIS/DataProcessed/Y96HHBase.rda") load("D:/HEIS/DataProcessed/Y96HHI.rda") load("D:/GitHub/IRHEIS/Data/SamplingWeights/HHWeights96.rda") DT <- merge(HHBase[ProvinceCode==23],HHI,by="HHID") DT <- merge(DT,HHWeights) names(DT) DT[,sum(NElementaryWeight)] DT[,sum(NMiddleWeight)] DT[,sum((NHigh+NPre)Weight)] DT[,sum(Weight)] DT[,sum(SizeWeight)] DT[CountyCode==2301 & Region=="Urban", sum(NElementaryWeight)] DT[CountyCode==2301 & Region=="Urban", sum(NMiddleWeight)] DT[CountyCode==2301 & Region=="Urban", sum((NHigh+NPre)Weight)] DT[CountyCode==2301 & Region=="Urban", sum(Weight)] DT[CountyCode==2301 & Region=="Urban", sum(SizeWeight)]	/R/Archive/Test-Tehran-Students-Count.R	no_license	IPRCIRI/IRHEIS	R	false	false	698	r	rm(list=ls()) library(data.table) load("D:/HEIS/DataProcessed/Y96HHBase.rda") load("D:/HEIS/DataProcessed/Y96HHI.rda") load("D:/GitHub/IRHEIS/Data/SamplingWeights/HHWeights96.rda") DT <- merge(HHBase[ProvinceCode==23],HHI,by="HHID") DT <- merge(DT,HHWeights) names(DT) DT[,sum(NElementaryWeight)] DT[,sum(NMiddleWeight)] DT[,sum((NHigh+NPre)Weight)] DT[,sum(Weight)] DT[,sum(SizeWeight)] DT[CountyCode==2301 & Region=="Urban", sum(NElementaryWeight)] DT[CountyCode==2301 & Region=="Urban", sum(NMiddleWeight)] DT[CountyCode==2301 & Region=="Urban", sum((NHigh+NPre)Weight)] DT[CountyCode==2301 & Region=="Urban", sum(Weight)] DT[CountyCode==2301 & Region=="Urban", sum(SizeWeight)]
# general parser functions library(data.table) library(stringr) # get the text of a filing from a link get_filing <- function(filing_text_link) { tmp <- tempfile() httr::GET(filing_text_link, httr::add_headers(.headers=headers), httr::write_disk(tmp, overwrite = T)) filing <- readLines(tmp) %>% tolower unlink(tmp) do.call(paste0("collapse_", guess_text_html(filing)), args = list(filing = filing)) } get_filing_tables <- function(filing_url) { filing <- get_filing(filing_url) do.call(paste0("get_", guess_text_html(filing), "_filing_tables"), args = list(filing = filing)) } # collapse lines of an html document # line structure is irrelevant and breaks things # in the existing code collapse_html <- function(filing) { paste0(filing, collapse = "") } # critical to preserve line breaks # otherwise we can't parse the tables at all collapse_text <- function(filing) { paste0(filing, collapse = "\r\n") } # list of all filings in a given year list_filings <- function(year) { list.files(paste0("data/processed/", year), full.names = T, recursive = T, pattern = "crawler.csv") } # guess whether it is text or html format guess_text_html <- function(filing) { if(any(str_detect(string = tolower(filing), fixed("<tr>")))) { "html" } else { "text" } } # check the format for each column # e.g. is is comma-separated numbers, # dollar denominated, etc. check_col_format <- function(df) { sapply(df, check_format) } # parse the tables within a filing # using the functions above parse_single_table <- function(x) { data <- fix_dollar_placement(x) %>% fix_percent_placement %>% fix_extra_spaces_in_parens %>% strange_characters_to_spaces %>% fix_dollar_placement %>% # again, for some reason read_char_table %>% replace_empty %>% remove_na_cols() %>% unique # grab just the complete data data[complete.cases(data)] } parse_multiple_tables <- function(x) { parsed_tbls <- list() for(i in 1:length(x)) { parsed_tbls[[i]] <- parse_single_table(x[[i]]) } parsed_tbls } # get the format of most of the tables in the list # often disclosures get embedded in tables # so do things like the name of the fund # we don't want that mucking up the format get_majority_format <- function(df_list) { lapply(df_list, check_col_format) %>% sapply(paste0, collapse = ", ") %>% table %>% # get counts sort(decreasing = T) %>% head(1) %>% names } # filter tables based on the majority format get_relevant_tables <- function(df_list) { format <- get_majority_format(df_list) Filter(function(x) paste0(check_col_format(x), collapse = ", ") == format, df_list) } combine_all_tables_from_filing <- function(filing_html_tables) { filing_html_tables %>% get_relevant_tables %>% rbindlist } unlist_until_table <- function(table_list) { # while table_list is a list of length > 0 # unlist until there is at least one element a level down # that is a table while(is.list(table_list) & !any(sapply(table_list, function(x) "data.frame" %in% class(x))) & length(table_list) > 0) { table_list <- unlist(table_list, recursive = F) } table_list }	/parsers/general-parsers.R	no_license	be-green/sec-filings	R	false	false	3,295	r	# general parser functions library(data.table) library(stringr) # get the text of a filing from a link get_filing <- function(filing_text_link) { tmp <- tempfile() httr::GET(filing_text_link, httr::add_headers(.headers=headers), httr::write_disk(tmp, overwrite = T)) filing <- readLines(tmp) %>% tolower unlink(tmp) do.call(paste0("collapse_", guess_text_html(filing)), args = list(filing = filing)) } get_filing_tables <- function(filing_url) { filing <- get_filing(filing_url) do.call(paste0("get_", guess_text_html(filing), "_filing_tables"), args = list(filing = filing)) } # collapse lines of an html document # line structure is irrelevant and breaks things # in the existing code collapse_html <- function(filing) { paste0(filing, collapse = "") } # critical to preserve line breaks # otherwise we can't parse the tables at all collapse_text <- function(filing) { paste0(filing, collapse = "\r\n") } # list of all filings in a given year list_filings <- function(year) { list.files(paste0("data/processed/", year), full.names = T, recursive = T, pattern = "crawler.csv") } # guess whether it is text or html format guess_text_html <- function(filing) { if(any(str_detect(string = tolower(filing), fixed("<tr>")))) { "html" } else { "text" } } # check the format for each column # e.g. is is comma-separated numbers, # dollar denominated, etc. check_col_format <- function(df) { sapply(df, check_format) } # parse the tables within a filing # using the functions above parse_single_table <- function(x) { data <- fix_dollar_placement(x) %>% fix_percent_placement %>% fix_extra_spaces_in_parens %>% strange_characters_to_spaces %>% fix_dollar_placement %>% # again, for some reason read_char_table %>% replace_empty %>% remove_na_cols() %>% unique # grab just the complete data data[complete.cases(data)] } parse_multiple_tables <- function(x) { parsed_tbls <- list() for(i in 1:length(x)) { parsed_tbls[[i]] <- parse_single_table(x[[i]]) } parsed_tbls } # get the format of most of the tables in the list # often disclosures get embedded in tables # so do things like the name of the fund # we don't want that mucking up the format get_majority_format <- function(df_list) { lapply(df_list, check_col_format) %>% sapply(paste0, collapse = ", ") %>% table %>% # get counts sort(decreasing = T) %>% head(1) %>% names } # filter tables based on the majority format get_relevant_tables <- function(df_list) { format <- get_majority_format(df_list) Filter(function(x) paste0(check_col_format(x), collapse = ", ") == format, df_list) } combine_all_tables_from_filing <- function(filing_html_tables) { filing_html_tables %>% get_relevant_tables %>% rbindlist } unlist_until_table <- function(table_list) { # while table_list is a list of length > 0 # unlist until there is at least one element a level down # that is a table while(is.list(table_list) & !any(sapply(table_list, function(x) "data.frame" %in% class(x))) & length(table_list) > 0) { table_list <- unlist(table_list, recursive = F) } table_list }
#BF528_Project_2_Biologist #Rachel Thomas #clear all variables & start fresh rm(list=ls(all.names=TRUE)) #load in libraries library(dplyr) library(ggplot2) library(tidyr) library(RColorBrewer) #Load and read data from SCC -- files generated by programmer fpkm_0 <- read.table('/projectnb/bf528/users/swiss_cheese2/project_2/P0_1_cufflinks/genes.fpkm_tracking', header = TRUE) fpkm_0 <- fpkm_0 %>% select(FPKM, tracking_id, gene_short_name) #changed column name from FPKM to P0_1 colnames(fpkm_0) = gsub("FPKM", "P0_1", colnames(fpkm_0)) #relocate P0_1 column to last column fpkm_0 <- fpkm_0 %>% relocate(P0_1, .after = gene_short_name) #load fpkm csv pre-generated sample file from SCC fpkm_matrix <- read.csv('/project/bf528/project_2/data/fpkm_matrix.csv', sep = "\t") #removes the "FPKM" from each header column colnames(fpkm_matrix) = gsub("_FPKM", "", colnames(fpkm_matrix)) #combine fpkm p0_1 into fpkm matrix fpkm_combined <- merge(fpkm_0, fpkm_matrix) fpkm_combined <- fpkm_combined %>% relocate(P0_1, .after = Ad_2) fpkm_combined #create new matrix for Line plot 1 fpkm_1 <- fpkm_combined %>% select(gene_short_name, P0_1, P4_1, P7_1, Ad_1) fpkm_2 <- fpkm_combined %>% select(gene_short_name, P0_2, P4_2, P7_2, Ad_2) #7.1 Line plots of Sarcomere gene_names = c('Csrp3', 'Tcap', 'Cryab', 'Pdlim5', 'Pygm', 'Myoz2', 'Des') f <- fpkm_1[fpkm_1$gene_short_name %in% gene_names, ] e <- f[-1] row.names(e) <- f$gene_short_name e <- as.data.frame(t(e)) e$Samples <- row.names(e) row.names(e) <- NULL line_plot <- e %>% mutate(Samples = factor(Samples, levels = unique(Samples))) %>% gather(Genes, FPKM, -Samples) %>% ggplot(aes(Samples, FPKM)) + geom_line(aes(color = Genes, group = Genes)) + geom_point() + scale_y_log10() + ggtitle("Sarcomere") + scale_color_brewer(palette = "Set1") + theme_bw() + theme(panel.grid = element_blank()) + theme(plot.title = element_text(hjust = 0.5)) png("sarcomere_line_plot.png") line_plot dev.off() #7.1 Mitochondria plot gene_names_2 = c('Mpc1', 'Prdx3', 'Acat1', 'Echs1', 'Slc25a11', 'Phyh') h <- fpkm_2[fpkm_2$gene_short_name %in% gene_names_2, ] g <- h[-1] row.names(g) <- h$gene_short_name g <- as.data.frame(t(g)) g$Samples <- row.names(g) row.names(g) <- NULL line_plot <- g %>% mutate(Samples = factor(Samples, levels = unique(Samples))) %>% gather(Genes, FPKM, -Samples) %>% ggplot(aes(Samples, FPKM)) + geom_line(aes(color = Genes, group = Genes)) + geom_point() + scale_y_log10() + ggtitle("Mitochondria") + scale_color_brewer(palette = "Set1") + theme_bw() + theme(panel.grid = element_blank()) + theme(plot.title = element_text(hjust = 0.5)) png("Mitochondria_line_plot.png") line_plot dev.off() #7.1 Cell Cycle plot gene_names_3 = c('Cdc7', 'Cdk7', 'Cdc26', 'Bora', 'Cdc27', 'Cdc23','Cdc45', 'Aurkb', 'Rad51') i <- fpkm_1[fpkm_1$gene_short_name %in% gene_names_3, ] j <- i[-1] row.names(j) <- i$gene_short_name j <- as.data.frame(t(j)) j$Samples <- row.names(j) row.names(j) <- NULL line_plot <- j %>% mutate(Samples = factor(Samples, levels = unique(Samples))) %>% gather(Genes, FPKM, -Samples) %>% ggplot(aes(Samples, FPKM)) + geom_line(aes(color = Genes, group = Genes)) + geom_point() + scale_y_log10() + ggtitle("Cell Cycle") + scale_color_brewer(palette = "Dark2") + theme_bw() + theme(panel.grid = element_blank()) + theme(plot.title = element_text(hjust = 0.5)) png("CellCycle_line_plot.png") line_plot dev.off()	/project_2/FPKM_plots.R	permissive	MogicianEik/BF528_team_swiss_cheese	R	false	false	3,495	r	#BF528_Project_2_Biologist #Rachel Thomas #clear all variables & start fresh rm(list=ls(all.names=TRUE)) #load in libraries library(dplyr) library(ggplot2) library(tidyr) library(RColorBrewer) #Load and read data from SCC -- files generated by programmer fpkm_0 <- read.table('/projectnb/bf528/users/swiss_cheese2/project_2/P0_1_cufflinks/genes.fpkm_tracking', header = TRUE) fpkm_0 <- fpkm_0 %>% select(FPKM, tracking_id, gene_short_name) #changed column name from FPKM to P0_1 colnames(fpkm_0) = gsub("FPKM", "P0_1", colnames(fpkm_0)) #relocate P0_1 column to last column fpkm_0 <- fpkm_0 %>% relocate(P0_1, .after = gene_short_name) #load fpkm csv pre-generated sample file from SCC fpkm_matrix <- read.csv('/project/bf528/project_2/data/fpkm_matrix.csv', sep = "\t") #removes the "FPKM" from each header column colnames(fpkm_matrix) = gsub("_FPKM", "", colnames(fpkm_matrix)) #combine fpkm p0_1 into fpkm matrix fpkm_combined <- merge(fpkm_0, fpkm_matrix) fpkm_combined <- fpkm_combined %>% relocate(P0_1, .after = Ad_2) fpkm_combined #create new matrix for Line plot 1 fpkm_1 <- fpkm_combined %>% select(gene_short_name, P0_1, P4_1, P7_1, Ad_1) fpkm_2 <- fpkm_combined %>% select(gene_short_name, P0_2, P4_2, P7_2, Ad_2) #7.1 Line plots of Sarcomere gene_names = c('Csrp3', 'Tcap', 'Cryab', 'Pdlim5', 'Pygm', 'Myoz2', 'Des') f <- fpkm_1[fpkm_1$gene_short_name %in% gene_names, ] e <- f[-1] row.names(e) <- f$gene_short_name e <- as.data.frame(t(e)) e$Samples <- row.names(e) row.names(e) <- NULL line_plot <- e %>% mutate(Samples = factor(Samples, levels = unique(Samples))) %>% gather(Genes, FPKM, -Samples) %>% ggplot(aes(Samples, FPKM)) + geom_line(aes(color = Genes, group = Genes)) + geom_point() + scale_y_log10() + ggtitle("Sarcomere") + scale_color_brewer(palette = "Set1") + theme_bw() + theme(panel.grid = element_blank()) + theme(plot.title = element_text(hjust = 0.5)) png("sarcomere_line_plot.png") line_plot dev.off() #7.1 Mitochondria plot gene_names_2 = c('Mpc1', 'Prdx3', 'Acat1', 'Echs1', 'Slc25a11', 'Phyh') h <- fpkm_2[fpkm_2$gene_short_name %in% gene_names_2, ] g <- h[-1] row.names(g) <- h$gene_short_name g <- as.data.frame(t(g)) g$Samples <- row.names(g) row.names(g) <- NULL line_plot <- g %>% mutate(Samples = factor(Samples, levels = unique(Samples))) %>% gather(Genes, FPKM, -Samples) %>% ggplot(aes(Samples, FPKM)) + geom_line(aes(color = Genes, group = Genes)) + geom_point() + scale_y_log10() + ggtitle("Mitochondria") + scale_color_brewer(palette = "Set1") + theme_bw() + theme(panel.grid = element_blank()) + theme(plot.title = element_text(hjust = 0.5)) png("Mitochondria_line_plot.png") line_plot dev.off() #7.1 Cell Cycle plot gene_names_3 = c('Cdc7', 'Cdk7', 'Cdc26', 'Bora', 'Cdc27', 'Cdc23','Cdc45', 'Aurkb', 'Rad51') i <- fpkm_1[fpkm_1$gene_short_name %in% gene_names_3, ] j <- i[-1] row.names(j) <- i$gene_short_name j <- as.data.frame(t(j)) j$Samples <- row.names(j) row.names(j) <- NULL line_plot <- j %>% mutate(Samples = factor(Samples, levels = unique(Samples))) %>% gather(Genes, FPKM, -Samples) %>% ggplot(aes(Samples, FPKM)) + geom_line(aes(color = Genes, group = Genes)) + geom_point() + scale_y_log10() + ggtitle("Cell Cycle") + scale_color_brewer(palette = "Dark2") + theme_bw() + theme(panel.grid = element_blank()) + theme(plot.title = element_text(hjust = 0.5)) png("CellCycle_line_plot.png") line_plot dev.off()
% Generated by roxygen2: do not edit by hand % Please edit documentation in R/perform_mutation.R \name{perform_mutation} \alias{perform_mutation} \title{Perform mutation} \usage{ perform_mutation(L) } \arguments{ \item{L}{list with all parameters for ExpDE framework} } \value{ List \code{L} containing all updated parameters, including the mutated population \code{M} } \description{ Implements the control of mutation functions for the ExpDE framework } \section{Mutation Parameters}{ The \code{mutpars} parameter contains all parameters required to define the mutation. } \author{ Bruna Queiroz (\email{bsqueiroz98@gmail.com}) }	/man/perform_mutation.Rd	no_license	brunasqz/ExpDE	R	false	true	635	rd	% Generated by roxygen2: do not edit by hand % Please edit documentation in R/perform_mutation.R \name{perform_mutation} \alias{perform_mutation} \title{Perform mutation} \usage{ perform_mutation(L) } \arguments{ \item{L}{list with all parameters for ExpDE framework} } \value{ List \code{L} containing all updated parameters, including the mutated population \code{M} } \description{ Implements the control of mutation functions for the ExpDE framework } \section{Mutation Parameters}{ The \code{mutpars} parameter contains all parameters required to define the mutation. } \author{ Bruna Queiroz (\email{bsqueiroz98@gmail.com}) }
> install.packages(“RImpala”) > library(RImpala) > rimpala.init(libs="/opt/jars/impala-jdbc-0.5-2") > rimpala.connect("192.168.122.189", "21050") > rimpala.showdatabases() > rimpala.usedatabase("weblog") > ds = rimpala.query("select substr(requesttime, 2, 11) as dayofmonth, count(*) as hits from weblog group by dayofmonth order by dayofmonth limit 31") > traffic<-ds$hits > webts <- ts(traffic, frequency=1) > plot(webts)	/ch06/Rimpala.R	permissive	jiadebin/impala-in-action	R	false	false	594	r	> install.packages(“RImpala”) > library(RImpala) > rimpala.init(libs="/opt/jars/impala-jdbc-0.5-2") > rimpala.connect("192.168.122.189", "21050") > rimpala.showdatabases() > rimpala.usedatabase("weblog") > ds = rimpala.query("select substr(requesttime, 2, 11) as dayofmonth, count(*) as hits from weblog group by dayofmonth order by dayofmonth limit 31") > traffic<-ds$hits > webts <- ts(traffic, frequency=1) > plot(webts)
rm(list = ls()) library(Daniel) library(dplyr) library(nnet) CalcCImultinom <- function(fit) { s <- summary(fit) coef <- s$coefficients ses <- s$standard.errors ci.1 <- coef[1,2] + c(-1, 1)1.96ses[1, 2] ci.2 <- coef[2,2] + c(-1, 1)1.96ses[2, 2] return(rbind(ci.1,ci.2)) } #key # A, B,C,D,E,F - betaE[2] = 1.25, 1.5, 1.75, 2, 2.25, 2.5 # A,B,C, D, E,F - betaU = 2,3,4,5,6,7 patt <- "BD" beta0 <- c(-6, -5) betaE <- c(log(1.5), log(1.5)) betaU <- c(log(5), log(0.4)) sigmaU <- 1 n.sample <- 50000 n.sim <- 1000 AllY <- matrix(nr = n.sim, nc = 3) sace.diff1 <- sace.diff2 <- ace.diff1 <- ace.diff2 <- sace.or1 <- sace.or2 <- ace.or1 <- ace.or2 <- or.approx1 <- or.approx2 <- or.approx.true1 <- or.approx.true2 <- pop.never.s1 <- pop.never.s2 <- vector(length = n.sim) ci1 <- ci2 <- matrix(nr = n.sim, nc = 2) for (j in 1:n.sim) { CatIndex(j) # Simulate genetic score U <- rnorm(n.sample, 0, sd = sigmaU) #### Calcualte probabilites for each subtype with and without the exposure #### e1E0 <- exp(beta0[1] + betaU[1]U) e1E1 <- exp(beta0[1] + betaE[1] + betaU[1]U) e2E0 <- exp(beta0[2] + betaU[2]U) e2E1 <- exp(beta0[2] + betaE[2] + betaU[2]U) prE0Y1 <- e1E0/(1 + e1E0 + e2E0) prE0Y2 <- e2E0/(1 + e1E0 + e2E0) prE1Y1 <- e1E1/(1 + e1E1 + e2E1) prE1Y2 <- e2E1/(1 + e1E1 + e2E1) probsE0 <- cbind(prE0Y1, prE0Y2, 1 - prE0Y1 - prE0Y2) probsE1 <- cbind(prE1Y1, prE1Y2, 1 - prE1Y1 - prE1Y2) # Simulate subtypes # Yctrl <- Ytrt <- vector(length = n.sample) X <- rbinom(n = n.sample, 1, 0.5) for (i in 1:n.sample) { Yctrl[i] <- sample(c(1,2,0), 1, replace = T, prob = probsE0[i, ]) Ytrt[i] <- sample(c(1,2,0), 1, replace = T, prob = probsE1[i, ]) } Y <- (1-X)Yctrl + XYtrt AllY[j, ] <- table(Y) Y1ctrl <- Yctrl==1 Y1trt <- Ytrt==1 Y2ctrl <- Yctrl==2 Y2trt <- Ytrt==2 pop.never.s1[j] <- mean(Y1ctrl==0 & Y1trt==0) pop.never.s2[j] <- mean(Y2ctrl==0 & Y2trt==0) # estimate causal parameters sace.diff1[j] <- mean((Y1trt - Y1ctrl)[Y2ctrl==0 & Y2trt==0]) sace.diff2[j]<- mean((Y2trt - Y2ctrl)[Y1ctrl==0 & Y1trt==0]) ace.diff1[j] <- mean((Y1trt[Y2trt==0 & X==1]) - mean(Y1ctrl[Y2ctrl==0 & X==0])) ace.diff2[j] <- mean((Y2trt[Y1trt==0 & X==1]) - mean(Y2ctrl[Y1ctrl==0 & X==0])) # Ypo <- c(Yctrl, Ytrt) # Upo <- rep(U,2) # Xpo <- rep(x = c(0,1), each = n.sample) # fit.full.po <- multinom(Ypo~ Xpo + Upo) # fit.po <- multinom(Ypo~ Xpo) fit <- multinom(Y~ X) cis <- CalcCImultinom(fit) ci1[j, ] <- cis[1, ] ci2[j, ] <- cis[2, ] Y1only <- Y[Y<2] X1only <- X[Y<2] U1only <-U[Y<2] Y2only <- Y[Y!=1] X2only <- X[Y!=1] U2only <-U[Y!=1] Y2only[Y2only>0] <- 1 vec.for.or.1only <- c(sum((1 - Y1only) * (1 - X1only)) , sum(Y1only * (1 - X1only)), sum((1 - Y1only) * X1only), sum(Y1onlyX1only)) vec.for.or.2only <- c(sum((1 - Y2only) (1 - X2only)) , sum(Y2only * (1 - X2only)), sum((1 - Y2only) * X2only), sum(Y2onlyX2only)) ace.or1[j] <- CalcOR(vec.for.or.1only) ace.or2[j] <- CalcOR(vec.for.or.2only) Y1only.sace <- Y[Ytrt <2 & Yctrl < 2] X1only.sace <- X[Ytrt <2 & Yctrl < 2] U1only.sace <-U[Ytrt <2 & Yctrl < 2] Y2only.sace <- Y[Ytrt!=1 & Y1ctrl!=1] X2only.sace <- X[Ytrt!=1 & Y1ctrl!=1] U2only.sace <-U[Ytrt!=1 & Y1ctrl!=1] Y2only.sace[Y2only.sace>0] <- 1 vec.for.or.sace1 <- c(sum((1 - Y1only.sace) (1 - X1only.sace)) , sum(Y1only.sace * (1 - X1only.sace)), sum((1 - Y1only.sace) * X1only.sace), sum(Y1only.saceX1only.sace)) vec.for.or.sace2 <- c(sum((1 - Y2only.sace) (1 - X2only.sace)) , sum(Y2only.sace * (1 - X2only.sace)), sum((1 - Y2only.sace) * X2only.sace), sum(Y2only.sace*X2only.sace)) sace.or1[j] <- CalcOR(vec.for.or.sace1) sace.or2[j] <- CalcOR(vec.for.or.sace2) Y1 <- Y==1 Y2 <- Y==2 fit.logistic.Y1 <- glm(Y1 ~ X, family = "binomial") fit.logistic.true.Y1 <- glm(Y1 ~ X + U, family = "binomial") fit.logistic.Y2 <- glm(Y2 ~ X, family = "binomial") fit.logistic.true.Y2 <- glm(Y2 ~ X + U, family = "binomial") or.approx1[j] <- exp(coef(fit.logistic.Y1)[2]) or.approx.true1[j] <- exp(coef(fit.logistic.true.Y1)[2]) or.approx2[j] <- exp(coef(fit.logistic.Y2)[2]) or.approx.true2[j] <- exp(coef(fit.logistic.true.Y2)[2]) } save.image(paste0("CMPEn50krareScen25",patt,".RData"))	/Simulations/Scripts/R/Rare/Scenario 25/CMPEn50KrareScen25BD.R	no_license	yadevi/CausalMPE	R	false	false	4,220	r	rm(list = ls()) library(Daniel) library(dplyr) library(nnet) CalcCImultinom <- function(fit) { s <- summary(fit) coef <- s$coefficients ses <- s$standard.errors ci.1 <- coef[1,2] + c(-1, 1)1.96ses[1, 2] ci.2 <- coef[2,2] + c(-1, 1)1.96ses[2, 2] return(rbind(ci.1,ci.2)) } #key # A, B,C,D,E,F - betaE[2] = 1.25, 1.5, 1.75, 2, 2.25, 2.5 # A,B,C, D, E,F - betaU = 2,3,4,5,6,7 patt <- "BD" beta0 <- c(-6, -5) betaE <- c(log(1.5), log(1.5)) betaU <- c(log(5), log(0.4)) sigmaU <- 1 n.sample <- 50000 n.sim <- 1000 AllY <- matrix(nr = n.sim, nc = 3) sace.diff1 <- sace.diff2 <- ace.diff1 <- ace.diff2 <- sace.or1 <- sace.or2 <- ace.or1 <- ace.or2 <- or.approx1 <- or.approx2 <- or.approx.true1 <- or.approx.true2 <- pop.never.s1 <- pop.never.s2 <- vector(length = n.sim) ci1 <- ci2 <- matrix(nr = n.sim, nc = 2) for (j in 1:n.sim) { CatIndex(j) # Simulate genetic score U <- rnorm(n.sample, 0, sd = sigmaU) #### Calcualte probabilites for each subtype with and without the exposure #### e1E0 <- exp(beta0[1] + betaU[1]U) e1E1 <- exp(beta0[1] + betaE[1] + betaU[1]U) e2E0 <- exp(beta0[2] + betaU[2]U) e2E1 <- exp(beta0[2] + betaE[2] + betaU[2]U) prE0Y1 <- e1E0/(1 + e1E0 + e2E0) prE0Y2 <- e2E0/(1 + e1E0 + e2E0) prE1Y1 <- e1E1/(1 + e1E1 + e2E1) prE1Y2 <- e2E1/(1 + e1E1 + e2E1) probsE0 <- cbind(prE0Y1, prE0Y2, 1 - prE0Y1 - prE0Y2) probsE1 <- cbind(prE1Y1, prE1Y2, 1 - prE1Y1 - prE1Y2) # Simulate subtypes # Yctrl <- Ytrt <- vector(length = n.sample) X <- rbinom(n = n.sample, 1, 0.5) for (i in 1:n.sample) { Yctrl[i] <- sample(c(1,2,0), 1, replace = T, prob = probsE0[i, ]) Ytrt[i] <- sample(c(1,2,0), 1, replace = T, prob = probsE1[i, ]) } Y <- (1-X)Yctrl + XYtrt AllY[j, ] <- table(Y) Y1ctrl <- Yctrl==1 Y1trt <- Ytrt==1 Y2ctrl <- Yctrl==2 Y2trt <- Ytrt==2 pop.never.s1[j] <- mean(Y1ctrl==0 & Y1trt==0) pop.never.s2[j] <- mean(Y2ctrl==0 & Y2trt==0) # estimate causal parameters sace.diff1[j] <- mean((Y1trt - Y1ctrl)[Y2ctrl==0 & Y2trt==0]) sace.diff2[j]<- mean((Y2trt - Y2ctrl)[Y1ctrl==0 & Y1trt==0]) ace.diff1[j] <- mean((Y1trt[Y2trt==0 & X==1]) - mean(Y1ctrl[Y2ctrl==0 & X==0])) ace.diff2[j] <- mean((Y2trt[Y1trt==0 & X==1]) - mean(Y2ctrl[Y1ctrl==0 & X==0])) # Ypo <- c(Yctrl, Ytrt) # Upo <- rep(U,2) # Xpo <- rep(x = c(0,1), each = n.sample) # fit.full.po <- multinom(Ypo~ Xpo + Upo) # fit.po <- multinom(Ypo~ Xpo) fit <- multinom(Y~ X) cis <- CalcCImultinom(fit) ci1[j, ] <- cis[1, ] ci2[j, ] <- cis[2, ] Y1only <- Y[Y<2] X1only <- X[Y<2] U1only <-U[Y<2] Y2only <- Y[Y!=1] X2only <- X[Y!=1] U2only <-U[Y!=1] Y2only[Y2only>0] <- 1 vec.for.or.1only <- c(sum((1 - Y1only) * (1 - X1only)) , sum(Y1only * (1 - X1only)), sum((1 - Y1only) * X1only), sum(Y1onlyX1only)) vec.for.or.2only <- c(sum((1 - Y2only) (1 - X2only)) , sum(Y2only * (1 - X2only)), sum((1 - Y2only) * X2only), sum(Y2onlyX2only)) ace.or1[j] <- CalcOR(vec.for.or.1only) ace.or2[j] <- CalcOR(vec.for.or.2only) Y1only.sace <- Y[Ytrt <2 & Yctrl < 2] X1only.sace <- X[Ytrt <2 & Yctrl < 2] U1only.sace <-U[Ytrt <2 & Yctrl < 2] Y2only.sace <- Y[Ytrt!=1 & Y1ctrl!=1] X2only.sace <- X[Ytrt!=1 & Y1ctrl!=1] U2only.sace <-U[Ytrt!=1 & Y1ctrl!=1] Y2only.sace[Y2only.sace>0] <- 1 vec.for.or.sace1 <- c(sum((1 - Y1only.sace) (1 - X1only.sace)) , sum(Y1only.sace * (1 - X1only.sace)), sum((1 - Y1only.sace) * X1only.sace), sum(Y1only.saceX1only.sace)) vec.for.or.sace2 <- c(sum((1 - Y2only.sace) (1 - X2only.sace)) , sum(Y2only.sace * (1 - X2only.sace)), sum((1 - Y2only.sace) * X2only.sace), sum(Y2only.sace*X2only.sace)) sace.or1[j] <- CalcOR(vec.for.or.sace1) sace.or2[j] <- CalcOR(vec.for.or.sace2) Y1 <- Y==1 Y2 <- Y==2 fit.logistic.Y1 <- glm(Y1 ~ X, family = "binomial") fit.logistic.true.Y1 <- glm(Y1 ~ X + U, family = "binomial") fit.logistic.Y2 <- glm(Y2 ~ X, family = "binomial") fit.logistic.true.Y2 <- glm(Y2 ~ X + U, family = "binomial") or.approx1[j] <- exp(coef(fit.logistic.Y1)[2]) or.approx.true1[j] <- exp(coef(fit.logistic.true.Y1)[2]) or.approx2[j] <- exp(coef(fit.logistic.Y2)[2]) or.approx.true2[j] <- exp(coef(fit.logistic.true.Y2)[2]) } save.image(paste0("CMPEn50krareScen25",patt,".RData"))
	/data/fromWeb/proposiciones/getPweb.r	permissive	emagar/dipMex	R	false	false	101,683	r
# Makeover Monday Week 32 2020 # Benefits of Remote Work # Data Source: State of Remote Work 2020 #library("httr") #library("readxl") #GET("https://query.data.world/s/524igbtttdrn3gfibs2eqfmd7iiqwg", write_disk(tf <- tempfile(fileext = ".xlsx"))) # df <- read_excel(tf) # Load libraries library(ggplot2) library(reshape2) library("httr") library("readxl") # GET data GET("https://query.data.world/s/524igbtttdrn3gfibs2eqfmd7iiqwg", write_disk(tf <- tempfile(fileext = ".xlsx"))) df <- read_excel(tf) data <- data.frame( name=df$`Benefit of remote work`, value=df$Percentage) barplot <- ggplot(data, aes(x=reorder(name, value), y=value)) + # enter data frame geom_bar(stat = "identity" ,fill = "#7f7fff") + # colour bars coord_flip() + # flip vertical bars into horizontal bar geom_text(aes(label = paste0(value,'%') # data labels ,y = value + max(value)0.01) # positioned just outside bar ,hjust = 0 # left align text ,size = (5/14)8 # sizing in line with theme text ,colour = "#323232") + # colour text theme( panel.grid.major = element_blank() # Remove gridlines (major) ,panel.grid.minor = element_blank() # Remove gridlines (minor) ,panel.background = element_blank() # Remove grey background ,plot.title = element_text(hjust = 0, size = 16, colour = "#323232") # Title size and colour ,plot.title.position = "plot" ,plot.subtitle = element_text(hjust = 0, size = 8, colour = "#323232") # Subtitle size and colour ,plot.caption = element_text(vjust = 0.3, size = 8, colour = "#323232") # Caption size and colour ,axis.ticks.y = element_blank() # Remove tick marks (Y-Axis) ,axis.text.y = element_text(hjust = 1, colour = "#323232", size = 8) # Axis size and colour (Y-Axis) ,axis.ticks.x = element_blank() # Remove tick marks (X-Axis) ,axis.text.x = element_blank() # Remove axis scale (X-Axis) ,axis.title.x = element_text(size = 8, colour = "#323232" ) # Axis label size and colour (X-Axis) ) + geom_hline(yintercept=0, color = "#7f7fff", size=1) + # Axis line size and colour (Y-Axis) labs(title = 'The Flex Life' # Title text ,subtitle = lapply(strwrap("Data from Buffer shows flexibility (in schedule & location) as the top benefit to remote working.", simplify = FALSE), paste, collapse="\n") # Subtitle text ,x = element_blank() # Removed Y-Axis text (flipped co-ordinates) ,y = element_blank() # 'Response (%)' # X-Axis text (flipped co-ordinates) ,caption = "Author: Will Sutton, Source: Buffer - State of Remote Work 2020") + # Caption text scale_y_continuous(limits = c( ifelse(min(data$value)>=0,0,min(data$value)1.05) # Minimum X-Axis scale (flipped co-ordinates) ,max(data$value)1.25) # Maximum X-Axis scale (flipped co-ordinates) ,expand = c(0,0) # Removing blank space around plot (X-Axis (flipped co-ordinates)) ) # Save the plot ggsave("2020w32/the_flex_life_bar_chart.png" # filename ,plot = barplot # variable for file ,width = 5, height = 4, dpi = 300, units = "in") # dimensions and image quality	/2020w32/build_bar_chart.R	permissive	wjsutton/Makeover-Monday	R	false	false	3,169	r	# Makeover Monday Week 32 2020 # Benefits of Remote Work # Data Source: State of Remote Work 2020 #library("httr") #library("readxl") #GET("https://query.data.world/s/524igbtttdrn3gfibs2eqfmd7iiqwg", write_disk(tf <- tempfile(fileext = ".xlsx"))) # df <- read_excel(tf) # Load libraries library(ggplot2) library(reshape2) library("httr") library("readxl") # GET data GET("https://query.data.world/s/524igbtttdrn3gfibs2eqfmd7iiqwg", write_disk(tf <- tempfile(fileext = ".xlsx"))) df <- read_excel(tf) data <- data.frame( name=df$`Benefit of remote work`, value=df$Percentage) barplot <- ggplot(data, aes(x=reorder(name, value), y=value)) + # enter data frame geom_bar(stat = "identity" ,fill = "#7f7fff") + # colour bars coord_flip() + # flip vertical bars into horizontal bar geom_text(aes(label = paste0(value,'%') # data labels ,y = value + max(value)0.01) # positioned just outside bar ,hjust = 0 # left align text ,size = (5/14)8 # sizing in line with theme text ,colour = "#323232") + # colour text theme( panel.grid.major = element_blank() # Remove gridlines (major) ,panel.grid.minor = element_blank() # Remove gridlines (minor) ,panel.background = element_blank() # Remove grey background ,plot.title = element_text(hjust = 0, size = 16, colour = "#323232") # Title size and colour ,plot.title.position = "plot" ,plot.subtitle = element_text(hjust = 0, size = 8, colour = "#323232") # Subtitle size and colour ,plot.caption = element_text(vjust = 0.3, size = 8, colour = "#323232") # Caption size and colour ,axis.ticks.y = element_blank() # Remove tick marks (Y-Axis) ,axis.text.y = element_text(hjust = 1, colour = "#323232", size = 8) # Axis size and colour (Y-Axis) ,axis.ticks.x = element_blank() # Remove tick marks (X-Axis) ,axis.text.x = element_blank() # Remove axis scale (X-Axis) ,axis.title.x = element_text(size = 8, colour = "#323232" ) # Axis label size and colour (X-Axis) ) + geom_hline(yintercept=0, color = "#7f7fff", size=1) + # Axis line size and colour (Y-Axis) labs(title = 'The Flex Life' # Title text ,subtitle = lapply(strwrap("Data from Buffer shows flexibility (in schedule & location) as the top benefit to remote working.", simplify = FALSE), paste, collapse="\n") # Subtitle text ,x = element_blank() # Removed Y-Axis text (flipped co-ordinates) ,y = element_blank() # 'Response (%)' # X-Axis text (flipped co-ordinates) ,caption = "Author: Will Sutton, Source: Buffer - State of Remote Work 2020") + # Caption text scale_y_continuous(limits = c( ifelse(min(data$value)>=0,0,min(data$value)1.05) # Minimum X-Axis scale (flipped co-ordinates) ,max(data$value)1.25) # Maximum X-Axis scale (flipped co-ordinates) ,expand = c(0,0) # Removing blank space around plot (X-Axis (flipped co-ordinates)) ) # Save the plot ggsave("2020w32/the_flex_life_bar_chart.png" # filename ,plot = barplot # variable for file ,width = 5, height = 4, dpi = 300, units = "in") # dimensions and image quality
hit3_function = function(dummy_list, log_row) { #三壘安打 # 展開 dummy_list 的值 rem_type <- dummy_list$rem_type base1 <- dummy_list$base1 base2 <- dummy_list$base2 base3 <- dummy_list$base3 player <- dummy_list$player if (grepl("三壘安打", log_row)) { # hit_function start work # catch player name player <- substr (log_row, regexpr("：",log_row)-3, regexpr("：",log_row)-1 ) # 依得分矩陣24種情境辦事 # 三壘安打 if (rem_type %in% c(1,2,3)) { # empty to 3B base3 <- player rem_type <- rem_type + 9 } else if (rem_type %in% c(4,5,6)) { # 1B to 3B # 得一分 base3 <- player base1 <- "NA" rem_type <- rem_type + 6 } else if (rem_type %in% c(7,8,9)) { # 2B to 3B #得一分 base2 <- "NA" base3 <- player rem_type <- rem_type + 3 } else if (rem_type %in% c(10,11,12)) { # 3B to 3B # 得一分 base3 <- player rem_type <- rem_type } else if (rem_type %in% c(13,14,15)) { # 1B_2B to 3B #得兩分 base3 <- player base2 <- "NA" base1 <- "NA" rem_type <- rem_type - 3 } else if (rem_type %in% c(16,17,18)) { # 1B_3B to 3B # 得兩分 base3 <- player base1 <- "NA" rem_type <- rem_type - 6 } else if (rem_type %in% c(19,20,21)) { # 2B_3B to 3B #得兩分 base3 <- player base2 <- "NA" rem_type <- rem_type - 9 } else if (rem_type %in% c(22,23,24)) { # 1B_2B_3B to 3B base3 <- player base2 <- "NA" base1 <- "NA" rem_type <- rem_type - 12 } } else { # dummy_list 不變 } # 將區域變數復原為 dummy_list 傳出 dummy_list$rem_type <- rem_type dummy_list$base1 <- base1 dummy_list$base2 <- base2 dummy_list$base3 <- base3 dummy_list$player <- player return(dummy_list) }	/offensive_db/functions/hit3_function.R	no_license	Shih-Po/cpbl_project	R	false	false	2,003	r	hit3_function = function(dummy_list, log_row) { #三壘安打 # 展開 dummy_list 的值 rem_type <- dummy_list$rem_type base1 <- dummy_list$base1 base2 <- dummy_list$base2 base3 <- dummy_list$base3 player <- dummy_list$player if (grepl("三壘安打", log_row)) { # hit_function start work # catch player name player <- substr (log_row, regexpr("：",log_row)-3, regexpr("：",log_row)-1 ) # 依得分矩陣24種情境辦事 # 三壘安打 if (rem_type %in% c(1,2,3)) { # empty to 3B base3 <- player rem_type <- rem_type + 9 } else if (rem_type %in% c(4,5,6)) { # 1B to 3B # 得一分 base3 <- player base1 <- "NA" rem_type <- rem_type + 6 } else if (rem_type %in% c(7,8,9)) { # 2B to 3B #得一分 base2 <- "NA" base3 <- player rem_type <- rem_type + 3 } else if (rem_type %in% c(10,11,12)) { # 3B to 3B # 得一分 base3 <- player rem_type <- rem_type } else if (rem_type %in% c(13,14,15)) { # 1B_2B to 3B #得兩分 base3 <- player base2 <- "NA" base1 <- "NA" rem_type <- rem_type - 3 } else if (rem_type %in% c(16,17,18)) { # 1B_3B to 3B # 得兩分 base3 <- player base1 <- "NA" rem_type <- rem_type - 6 } else if (rem_type %in% c(19,20,21)) { # 2B_3B to 3B #得兩分 base3 <- player base2 <- "NA" rem_type <- rem_type - 9 } else if (rem_type %in% c(22,23,24)) { # 1B_2B_3B to 3B base3 <- player base2 <- "NA" base1 <- "NA" rem_type <- rem_type - 12 } } else { # dummy_list 不變 } # 將區域變數復原為 dummy_list 傳出 dummy_list$rem_type <- rem_type dummy_list$base1 <- base1 dummy_list$base2 <- base2 dummy_list$base3 <- base3 dummy_list$player <- player return(dummy_list) }
# Install and load packages package_names <- c("survey","dplyr","foreign","devtools") lapply(package_names, function(x) if(!x %in% installed.packages()) install.packages(x)) lapply(package_names, require, character.only=T) install_github("e-mitchell/meps_r_pkg/MEPS") library(MEPS) options(survey.lonely.psu="adjust") # Load FYC file FYC <- read.xport('C:/MEPS/.FYC..ssp'); year <- .year. if(year <= 2001) FYC <- FYC %>% mutate(VARPSU = VARPSU.yy., VARSTR=VARSTR.yy.) if(year <= 1998) FYC <- FYC %>% rename(PERWT.yy.F = WTDPER.yy.) if(year == 1996) FYC <- FYC %>% mutate(AGE42X = AGE2X, AGE31X = AGE1X) FYC <- FYC %>% mutate_at(vars(starts_with("AGE")),funs(replace(., .< 0, NA))) %>% mutate(AGELAST = coalesce(AGE.yy.X, AGE42X, AGE31X)) FYC$ind = 1 # Education if(year <= 1998){ FYC <- FYC %>% mutate(EDUCYR = EDUCYR.yy.) }else if(year <= 2004){ FYC <- FYC %>% mutate(EDUCYR = EDUCYEAR) } if(year >= 2012 & year < 2016){ FYC <- FYC %>% mutate( less_than_hs = (0 <= EDRECODE & EDRECODE < 13), high_school = (EDRECODE == 13), some_college = (EDRECODE > 13)) }else{ FYC <- FYC %>% mutate( less_than_hs = (0 <= EDUCYR & EDUCYR < 12), high_school = (EDUCYR == 12), some_college = (EDUCYR > 12)) } FYC <- FYC %>% mutate( education = 1less_than_hs + 2high_school + 3*some_college, education = replace(education, AGELAST < 18, 9), education = recode_factor(education, .default = "Missing", .missing = "Missing", "1" = "Less than high school", "2" = "High school", "3" = "Some college", "9" = "Inapplicable (age < 18)", "0" = "Missing")) # Perceived health status if(year == 1996) FYC <- FYC %>% mutate(RTHLTH53 = RTEHLTH2, RTHLTH42 = RTEHLTH2, RTHLTH31 = RTEHLTH1) FYC <- FYC %>% mutate_at(vars(starts_with("RTHLTH")), funs(replace(., .< 0, NA))) %>% mutate( health = coalesce(RTHLTH53, RTHLTH42, RTHLTH31), health = recode_factor(health, .default = "Missing", .missing = "Missing", "1" = "Excellent", "2" = "Very good", "3" = "Good", "4" = "Fair", "5" = "Poor")) FYCdsgn <- svydesign( id = ~VARPSU, strata = ~VARSTR, weights = ~PERWT.yy.F, data = FYC, nest = TRUE) results <- svyby(~(PERWT.yy.F > 0), FUN = svytotal, by = ~health + education, design = FYCdsgn) print(results)	/mepstrends/hc_use/json/code/r/totPOP__health__education__.r	permissive	RandomCriticalAnalysis/MEPS-summary-tables	R	false	false	2,435	r	# Install and load packages package_names <- c("survey","dplyr","foreign","devtools") lapply(package_names, function(x) if(!x %in% installed.packages()) install.packages(x)) lapply(package_names, require, character.only=T) install_github("e-mitchell/meps_r_pkg/MEPS") library(MEPS) options(survey.lonely.psu="adjust") # Load FYC file FYC <- read.xport('C:/MEPS/.FYC..ssp'); year <- .year. if(year <= 2001) FYC <- FYC %>% mutate(VARPSU = VARPSU.yy., VARSTR=VARSTR.yy.) if(year <= 1998) FYC <- FYC %>% rename(PERWT.yy.F = WTDPER.yy.) if(year == 1996) FYC <- FYC %>% mutate(AGE42X = AGE2X, AGE31X = AGE1X) FYC <- FYC %>% mutate_at(vars(starts_with("AGE")),funs(replace(., .< 0, NA))) %>% mutate(AGELAST = coalesce(AGE.yy.X, AGE42X, AGE31X)) FYC$ind = 1 # Education if(year <= 1998){ FYC <- FYC %>% mutate(EDUCYR = EDUCYR.yy.) }else if(year <= 2004){ FYC <- FYC %>% mutate(EDUCYR = EDUCYEAR) } if(year >= 2012 & year < 2016){ FYC <- FYC %>% mutate( less_than_hs = (0 <= EDRECODE & EDRECODE < 13), high_school = (EDRECODE == 13), some_college = (EDRECODE > 13)) }else{ FYC <- FYC %>% mutate( less_than_hs = (0 <= EDUCYR & EDUCYR < 12), high_school = (EDUCYR == 12), some_college = (EDUCYR > 12)) } FYC <- FYC %>% mutate( education = 1less_than_hs + 2high_school + 3*some_college, education = replace(education, AGELAST < 18, 9), education = recode_factor(education, .default = "Missing", .missing = "Missing", "1" = "Less than high school", "2" = "High school", "3" = "Some college", "9" = "Inapplicable (age < 18)", "0" = "Missing")) # Perceived health status if(year == 1996) FYC <- FYC %>% mutate(RTHLTH53 = RTEHLTH2, RTHLTH42 = RTEHLTH2, RTHLTH31 = RTEHLTH1) FYC <- FYC %>% mutate_at(vars(starts_with("RTHLTH")), funs(replace(., .< 0, NA))) %>% mutate( health = coalesce(RTHLTH53, RTHLTH42, RTHLTH31), health = recode_factor(health, .default = "Missing", .missing = "Missing", "1" = "Excellent", "2" = "Very good", "3" = "Good", "4" = "Fair", "5" = "Poor")) FYCdsgn <- svydesign( id = ~VARPSU, strata = ~VARSTR, weights = ~PERWT.yy.F, data = FYC, nest = TRUE) results <- svyby(~(PERWT.yy.F > 0), FUN = svytotal, by = ~health + education, design = FYCdsgn) print(results)
#' Generate \code{\link[ggplot2]{ggplot}} object. #' #' @param x [\code{smoof_function}]\cr #' Objective function. #' @param show.optimum [\code{logical(1)}]\cr #' If the function has a known global optimum, should its location be #' plotted by a point or multiple points in case of multiple global optima? #' Default is \code{FALSE}. #' @param render.levels [\code{logical(1)}]\cr #' For 2D numeric functions only: Should an image map be plotted? Default is #' \code{FALSE}. #' @param render.contours [\code{logical(1)}]\cr #' For 2D numeric functions only: Should contour lines be plotted? Default is #' \code{TRUE}. #' @param use.facets [\code{logical(1)}]\cr #' For mixed functions only: Should the plot be splitted by the discrete values #' or should the different values be distinguished by colour in a single plot? #' Default is \code{FALSE}. #' @param ... [any]\cr #' Not used. #' @return [\code{\link[ggplot2]{ggplot}}] #' @examples #' library(ggplot2) #' fn = makeHimmelblauFunction() #' print(autoplot(fn)) #' print(autoplot(fn, render.levels = TRUE, render.contours = FALSE)) #' print(autoplot(fn, show.optimum = TRUE)) #' @export autoplot.smoof_function = function(x, show.optimum = FALSE, render.levels = FALSE, render.contours = TRUE, use.facets = FALSE, ...) { checkPlotFunParams(x) assertFlag(show.optimum, na.ok = FALSE) assertFlag(render.levels, na.ok = FALSE) assertFlag(render.contours, na.ok = FALSE) assertFlag(use.facets, na.ok = FALSE) mapping = list("1Dnumeric" = autoplot1DNumeric, "2Dnumeric" = autoplot2DNumeric, "2DMixed" = autoplot2DMixed) autoPlotFun = getInternalPlotFunction(x, mapping = mapping) autoPlotFun(x, show.optimum = show.optimum, render.levels = render.levels, render.contours = render.contours, use.facets = use.facets, ... ) } autoplot1DNumeric = function(x, show.optimum, render.contours, render.levels, use.facets, ...) { # extract data par.set = getParamSet(x) par.name = getParamIds(par.set) # get lower and upper bounds lower = getBounds(bound = getLower(par.set), default = -10L) upper = getBounds(bound = getUpper(par.set), default = 10L) data = generateDataframeForGGPlot(fn = x, sequences = list(seq(lower, upper, by = 0.01)), par.set = par.set) # finally draw data pl = ggplot(data = data, mapping = aes_string(x = par.name, y = "y")) if (isNoisy(x)) { pl = pl + geom_point() } else { pl = pl + geom_line() if (show.optimum && hasGlobalOptimum(x)) { global.optimum = getGlobalOptimum(x) pl = pl + geom_vline(xintercept = as.numeric(global.optimum$param), linetype = "dashed", colour = "grey") point.data = data.frame(x = unlist(global.optimum$param), y = global.optimum$value) colnames(point.data) = c(par.name, "y") pl = pl + geom_point(data = point.data, colour = "tomato") } } pl = pl + ggtitle(getName(x)) pl = pl + xlab(par.name) return(pl) } autoplot2DNumeric = function(x, show.optimum, render.contours, render.levels, use.facets, ...) { if (!render.levels & !render.contours) { stopf("At learst render.contours or render.levels needs to be TRUE. Otherwise we have no data to plot.") } # extract data par.set = getParamSet(x) par.names = getParamIds(par.set, with.nr = TRUE, repeated = TRUE) # get bounds lower = getBounds(getLower(par.set), default = -10L) upper = getBounds(getUpper(par.set), default = 10L) # build up data frame #FIXME: setting the stepsize (for example b = 0.05) is very evil! #For example double_sum with x_i in [-65.5, 65.5] takes about 20 minutes to produce the plot sequence.x1 = seq(lower[1], upper[1], length.out = 150) sequence.x2 = seq(lower[2], upper[2], length.out = 150) sequences = list(sequence.x1, sequence.x2) data = generateDataframeForGGPlot(x, sequences, par.set) # nice color palette for render.levels # see http://learnr.wordpress.com/2009/07/20/ggplot2-version-of-figures-in-lattice-multivariate-data-visualization-with-r-part-6/ brewer.div = colorRampPalette(brewer.pal(11, "Spectral"), interpolate = "spline") # plot pl = ggplot(data = data, mapping = aes_string(x = par.names[1], y = par.names[2])) if (render.levels) { pl = pl + geom_tile(aes_string(fill = "y")) pl = pl + scale_fill_gradientn(colours = brewer.div(200)) pl = pl + theme(legend.position = "top") } if (render.contours) { pl = pl + stat_contour(aes_string(z = "y", fill = NULL), colour = "gray", alpha = 0.8) } # show global optimum points if (show.optimum && hasGlobalOptimum(x)) { df.opt = getGlobalOptimum(x)$param df.colnames = colnames(df.opt) pl = pl + geom_point(data = df.opt, mapping = aes_string(x = df.colnames[1], y = df.colnames[2]), colour = "tomato") } # prettify pl = pl + xlab(expression(x[1])) + ylab(expression(x[2])) pl = pl + ggtitle(getName(x)) # pl = pl + scale_x_continuous(expand = c(0,0)) # pl = pl + scale_y_continuous(expand = c(0,0)) return(pl) } autoplot2DMixed = function(x, show.optimum, render.contours, render.levels, use.facets, ...) { # extract data par.set = getParamSet(x) par.types = getParamTypes(par.set) par.names = getParamIds(par.set) # which parameter is discrete/logical? idx.factor = which(par.types %in% c("discrete", "logical")) idx.numeric = setdiff(1:2, idx.factor) # get names of factors respectively numeric parameters name.factor = par.names[idx.factor] name.numeric = par.names[idx.numeric] # get bounds lower = getBounds(bound = getLower(par.set), default = -10L) upper = getBounds(bound = getUpper(par.set), default = 10L) numeric.seq = seq(lower, upper, by = 0.01) #FIXME: 'getValues' for Params? factor.seq = unlist(par.set$pars[[idx.factor]]$values) sequences = list(numeric.seq, factor.seq) if (idx.factor == 1L) { sequences = list(factor.seq, numeric.seq) } # build up data frame data = generateDataframeForGGPlot(fn = x, sequences = sequences, par.set = par.set) pl = ggplot(data = data, mapping = aes_string(x = name.numeric, y = "y")) if (use.facets) { pl = pl + geom_line() pl = pl + facet_grid(reformulate(".", name.factor)) } else { pl = pl + geom_line(aes_string(linetype = name.factor)) } pl = pl + ggtitle(getName(x)) pl = pl + theme(legend.position = "top") return(pl) }	/R/plot.autoplot.R	no_license	mllg/smoof	R	false	false	6,358	r	#' Generate \code{\link[ggplot2]{ggplot}} object. #' #' @param x [\code{smoof_function}]\cr #' Objective function. #' @param show.optimum [\code{logical(1)}]\cr #' If the function has a known global optimum, should its location be #' plotted by a point or multiple points in case of multiple global optima? #' Default is \code{FALSE}. #' @param render.levels [\code{logical(1)}]\cr #' For 2D numeric functions only: Should an image map be plotted? Default is #' \code{FALSE}. #' @param render.contours [\code{logical(1)}]\cr #' For 2D numeric functions only: Should contour lines be plotted? Default is #' \code{TRUE}. #' @param use.facets [\code{logical(1)}]\cr #' For mixed functions only: Should the plot be splitted by the discrete values #' or should the different values be distinguished by colour in a single plot? #' Default is \code{FALSE}. #' @param ... [any]\cr #' Not used. #' @return [\code{\link[ggplot2]{ggplot}}] #' @examples #' library(ggplot2) #' fn = makeHimmelblauFunction() #' print(autoplot(fn)) #' print(autoplot(fn, render.levels = TRUE, render.contours = FALSE)) #' print(autoplot(fn, show.optimum = TRUE)) #' @export autoplot.smoof_function = function(x, show.optimum = FALSE, render.levels = FALSE, render.contours = TRUE, use.facets = FALSE, ...) { checkPlotFunParams(x) assertFlag(show.optimum, na.ok = FALSE) assertFlag(render.levels, na.ok = FALSE) assertFlag(render.contours, na.ok = FALSE) assertFlag(use.facets, na.ok = FALSE) mapping = list("1Dnumeric" = autoplot1DNumeric, "2Dnumeric" = autoplot2DNumeric, "2DMixed" = autoplot2DMixed) autoPlotFun = getInternalPlotFunction(x, mapping = mapping) autoPlotFun(x, show.optimum = show.optimum, render.levels = render.levels, render.contours = render.contours, use.facets = use.facets, ... ) } autoplot1DNumeric = function(x, show.optimum, render.contours, render.levels, use.facets, ...) { # extract data par.set = getParamSet(x) par.name = getParamIds(par.set) # get lower and upper bounds lower = getBounds(bound = getLower(par.set), default = -10L) upper = getBounds(bound = getUpper(par.set), default = 10L) data = generateDataframeForGGPlot(fn = x, sequences = list(seq(lower, upper, by = 0.01)), par.set = par.set) # finally draw data pl = ggplot(data = data, mapping = aes_string(x = par.name, y = "y")) if (isNoisy(x)) { pl = pl + geom_point() } else { pl = pl + geom_line() if (show.optimum && hasGlobalOptimum(x)) { global.optimum = getGlobalOptimum(x) pl = pl + geom_vline(xintercept = as.numeric(global.optimum$param), linetype = "dashed", colour = "grey") point.data = data.frame(x = unlist(global.optimum$param), y = global.optimum$value) colnames(point.data) = c(par.name, "y") pl = pl + geom_point(data = point.data, colour = "tomato") } } pl = pl + ggtitle(getName(x)) pl = pl + xlab(par.name) return(pl) } autoplot2DNumeric = function(x, show.optimum, render.contours, render.levels, use.facets, ...) { if (!render.levels & !render.contours) { stopf("At learst render.contours or render.levels needs to be TRUE. Otherwise we have no data to plot.") } # extract data par.set = getParamSet(x) par.names = getParamIds(par.set, with.nr = TRUE, repeated = TRUE) # get bounds lower = getBounds(getLower(par.set), default = -10L) upper = getBounds(getUpper(par.set), default = 10L) # build up data frame #FIXME: setting the stepsize (for example b = 0.05) is very evil! #For example double_sum with x_i in [-65.5, 65.5] takes about 20 minutes to produce the plot sequence.x1 = seq(lower[1], upper[1], length.out = 150) sequence.x2 = seq(lower[2], upper[2], length.out = 150) sequences = list(sequence.x1, sequence.x2) data = generateDataframeForGGPlot(x, sequences, par.set) # nice color palette for render.levels # see http://learnr.wordpress.com/2009/07/20/ggplot2-version-of-figures-in-lattice-multivariate-data-visualization-with-r-part-6/ brewer.div = colorRampPalette(brewer.pal(11, "Spectral"), interpolate = "spline") # plot pl = ggplot(data = data, mapping = aes_string(x = par.names[1], y = par.names[2])) if (render.levels) { pl = pl + geom_tile(aes_string(fill = "y")) pl = pl + scale_fill_gradientn(colours = brewer.div(200)) pl = pl + theme(legend.position = "top") } if (render.contours) { pl = pl + stat_contour(aes_string(z = "y", fill = NULL), colour = "gray", alpha = 0.8) } # show global optimum points if (show.optimum && hasGlobalOptimum(x)) { df.opt = getGlobalOptimum(x)$param df.colnames = colnames(df.opt) pl = pl + geom_point(data = df.opt, mapping = aes_string(x = df.colnames[1], y = df.colnames[2]), colour = "tomato") } # prettify pl = pl + xlab(expression(x[1])) + ylab(expression(x[2])) pl = pl + ggtitle(getName(x)) # pl = pl + scale_x_continuous(expand = c(0,0)) # pl = pl + scale_y_continuous(expand = c(0,0)) return(pl) } autoplot2DMixed = function(x, show.optimum, render.contours, render.levels, use.facets, ...) { # extract data par.set = getParamSet(x) par.types = getParamTypes(par.set) par.names = getParamIds(par.set) # which parameter is discrete/logical? idx.factor = which(par.types %in% c("discrete", "logical")) idx.numeric = setdiff(1:2, idx.factor) # get names of factors respectively numeric parameters name.factor = par.names[idx.factor] name.numeric = par.names[idx.numeric] # get bounds lower = getBounds(bound = getLower(par.set), default = -10L) upper = getBounds(bound = getUpper(par.set), default = 10L) numeric.seq = seq(lower, upper, by = 0.01) #FIXME: 'getValues' for Params? factor.seq = unlist(par.set$pars[[idx.factor]]$values) sequences = list(numeric.seq, factor.seq) if (idx.factor == 1L) { sequences = list(factor.seq, numeric.seq) } # build up data frame data = generateDataframeForGGPlot(fn = x, sequences = sequences, par.set = par.set) pl = ggplot(data = data, mapping = aes_string(x = name.numeric, y = "y")) if (use.facets) { pl = pl + geom_line() pl = pl + facet_grid(reformulate(".", name.factor)) } else { pl = pl + geom_line(aes_string(linetype = name.factor)) } pl = pl + ggtitle(getName(x)) pl = pl + theme(legend.position = "top") return(pl) }
#' # Invert results - Figures & Tables #' #' Description: Model comparison tables #' #' ### Preamble #' #' Load libraries #+ libraries, message = F, warning = F library(knitr) # documentation-related library(ezknitr) # documentation-related library(devtools) # documentation-related library(unmarked) # analysis-related library(ggplot2) library(ggthemes) library(gridExtra) #' Clear environment and set seed #' #' Note: for reproducibility, it is important to include these. Clearing the #' environment ensures that you have specified all pertinent files that need #' to be loaded, and setting the seed ensures that your analysis is #' repeatable remove(list = ls()) set.seed(2583722) #' Unmarked models #' #' HELE load(file = "data/output_data/hele_occ_d_NB.Rdata") #disturbance hele.occ.d.NB <- occ.d.NB load(file = "data/output_data/hele_occ_null_NB.Rdata") #null hele.occ.null.NB <- occ.null.NB load(file = "data/output_data/hele_occ_t_NB.Rdata") #liatris hele.occ.t.NB <- occ.t.NB load(file = "data/output_data/hele_occ_nb_NB.Rdata")#nonbunchgrass hele.occ.nb.NB <- occ.nb.NB load(file = "data/output_data/hele_occ_b_NB.Rdata") #bunchgrass hele.occ.b.NB <- occ.b.NB load(file = "data/output_data/hele_occ_l_NB.Rdata")#litter hele.occ.l.NB <- occ.l.NB load(file = "data/output_data/hele_occ_c_NB.Rdata") #canopy hele.occ.c.NB <- occ.c.NB #' CIPA load(file = "data/output_data/cipa_occ_e_NB.Rdata") #elevCV cipa.occ.e.NB <- occ.e.NB load(file = "data/output_data/cipa_occ_null_NB.Rdata") #null cipa.occ.null.NB <- occ.null.NB load(file = "data/output_data/cipa_occ_l_NB.Rdata")#litter cipa.occ.l.NB <- occ.l.NB load(file = "data/output_data/cipa_occ_c_NB.Rdata") #canopy cipa.occ.c.NB <- occ.c.NB #' ____________________________________________________________________________ #' ### Unmarked results #' #' CIPA #' #' Fit list dfms.cipa <- fitList("lam(.)p(.)gamma(.)omega(.)-NB" = cipa.occ.null.NB, "lam(canopy)p(.)gamma(.)omega(.)-NB" = cipa.occ.c.NB, "lam(litter)p(.)gamma(.)omega(.)-NB" = cipa.occ.l.NB, "lam(elev.CV)p(.)gamma(.)omega(.)-NB" = cipa.occ.e.NB ) (dms <- modSel(dfms.cipa)) #' Model 1 (elevation) coef(cipa.occ.e.NB, type="psi") confint(cipa.occ.e.NB, type="psi", level=0.85) coef(cipa.occ.e.NB, type="det") confint(cipa.occ.e.NB, type="det", level=0.85) coef(cipa.occ.e.NB, type="col") confint(cipa.occ.e.NB, type="col", level=0.85) coef(cipa.occ.e.NB, type="ext") confint(cipa.occ.e.NB, type="ext", level=0.85) cipa.occ.e.NB #' Model 2 (canopy) coef(cipa.occ.c.NB, type="psi") confint(cipa.occ.c.NB, type="psi", level=0.85) coef(cipa.occ.c.NB, type="det") confint(cipa.occ.c.NB, type="det", level=0.85) coef(cipa.occ.c.NB, type="col") confint(cipa.occ.c.NB, type="col", level=0.85) coef(cipa.occ.c.NB, type="ext") confint(cipa.occ.c.NB, type="ext", level=0.85) cipa.occ.c.NB #' Model 3 (null) coef(cipa.occ.null.NB, type="psi") confint(cipa.occ.null.NB, type="psi", level=0.85) coef(cipa.occ.null.NB, type="det") confint(cipa.occ.null.NB, type="det", level=0.85) coef(cipa.occ.null.NB, type="col") confint(cipa.occ.null.NB, type="col", level=0.85) coef(cipa.occ.null.NB, type="ext") confint(cipa.occ.null.NB, type="ext", level=0.85) cipa.occ.null.NB #' Model 4 (litter) coef(cipa.occ.l.NB, type="psi") confint(cipa.occ.l.NB, type="psi", level=0.85) coef(cipa.occ.l.NB, type="det") confint(cipa.occ.l.NB, type="det", level=0.85) coef(cipa.occ.l.NB, type="col") confint(cipa.occ.l.NB, type="col", level=0.85) coef(cipa.occ.l.NB, type="ext") confint(cipa.occ.l.NB, type="ext", level=0.85) cipa.occ.l.NB #' #' HELE #' #' Fit list dfms.hele <- fitList("lam(.)p(.)gamma(.)omega(.)-NB" = hele.occ.null.NB, "lam(canopy)p(.)gamma(.)omega(.)-NB" = hele.occ.c.NB, "lam(bunchgrass)p(.)gamma(.)omega(.)-NB" = hele.occ.b.NB, "lam(nonbunchgrass)p(.)gamma(.)omega(.)-NB" = hele.occ.nb.NB, "lam(liatris)p(.)gamma(.)omega(.)-NB" = hele.occ.t.NB, "lam(litter)p(.)gamma(.)omega(.)-NB" = hele.occ.l.NB, "lam(dy_pre2015)p(.)gamma(.)omega(.)-NB" = hele.occ.d.NB) (dms <- modSel(dfms.hele)) #' Model 1 (liatris) coef(hele.occ.t.NB, type="psi") confint(hele.occ.t.NB, type="psi", level=0.85) coef(hele.occ.t.NB, type="det") confint(hele.occ.t.NB, type="det", level=0.85) coef(hele.occ.t.NB, type="col") confint(hele.occ.t.NB, type="col", level=0.85) coef(hele.occ.t.NB, type="ext") confint(hele.occ.t.NB, type="ext", level=0.85) hele.occ.t.NB #' Model 2 (null) coef(hele.occ.null.NB, type="psi") confint(hele.occ.null.NB, type="psi", level=0.85) coef(hele.occ.null.NB, type="det") confint(hele.occ.null.NB, type="det", level=0.85) coef(hele.occ.null.NB, type="col") confint(hele.occ.null.NB, type="col", level=0.85) coef(hele.occ.null.NB, type="ext") confint(hele.occ.null.NB, type="ext", level=0.85) hele.occ.null.NB #' Model 3 (nonbunchgrass) coef(hele.occ.nb.NB, type="psi") confint(hele.occ.nb.NB, type="psi", level=0.85) coef(hele.occ.nb.NB, type="det") confint(hele.occ.nb.NB, type="det", level=0.85) coef(hele.occ.nb.NB, type="col") confint(hele.occ.nb.NB, type="col", level=0.85) coef(hele.occ.nb.NB, type="ext") confint(hele.occ.nb.NB, type="ext", level=0.85) hele.occ.nb.NB #' Model 4 (litter) coef(hele.occ.l.NB, type="psi") confint(hele.occ.l.NB, type="psi", level=0.85) coef(hele.occ.l.NB, type="det") confint(hele.occ.l.NB, type="det", level=0.85) coef(hele.occ.l.NB, type="col") confint(hele.occ.l.NB, type="col", level=0.85) coef(hele.occ.l.NB, type="ext") confint(hele.occ.l.NB, type="ext", level=0.85) hele.occ.l.NB #' Model 5 (bunchgrass) coef(hele.occ.b.NB, type="psi") confint(hele.occ.b.NB, type="psi", level=0.85) coef(hele.occ.b.NB, type="det") confint(hele.occ.b.NB, type="det", level=0.85) coef(hele.occ.b.NB, type="col") confint(hele.occ.b.NB, type="col", level=0.85) coef(hele.occ.b.NB, type="ext") confint(hele.occ.b.NB, type="ext", level=0.85) hele.occ.b.NB #' Model 6 (canopy) coef(hele.occ.c.NB, type="psi") confint(hele.occ.c.NB, type="psi", level=0.85) coef(hele.occ.c.NB, type="det") confint(hele.occ.c.NB, type="det", level=0.85) coef(hele.occ.c.NB, type="col") confint(hele.occ.c.NB, type="col", level=0.85) coef(hele.occ.c.NB, type="ext") confint(hele.occ.c.NB, type="ext", level=0.85) hele.occ.c.NB #' Model 7 (disturbance) coef(hele.occ.d.NB, type="psi") confint(hele.occ.d.NB, type="psi", level=0.85) coef(hele.occ.d.NB, type="det") confint(hele.occ.d.NB, type="det", level=0.85) coef(hele.occ.d.NB, type="col") confint(hele.occ.d.NB, type="col", level=0.85) coef(hele.occ.d.NB, type="ext") confint(hele.occ.d.NB, type="ext", level=0.85) hele.occ.d.NB #' _____________________________________________________________________________ #' ### Footer #' #' Session Info devtools::session_info() #' This document was "spun" with: #' #' ezspin(file = "programs/00_thesis_programs/10b_occupancy_results_inverts.R", out_dir = "output/thesis_results_spun", fig_dir = "figures", keep_md = F) #' #' You can run the ezspin() code above to create an html in the "output" folder #' and any associated figures will get put into the "figures" folder.	/programs/10b_occupancy_results_inverts.R	no_license	Magswell/thesis	R	false	false	7,235	r	#' # Invert results - Figures & Tables #' #' Description: Model comparison tables #' #' ### Preamble #' #' Load libraries #+ libraries, message = F, warning = F library(knitr) # documentation-related library(ezknitr) # documentation-related library(devtools) # documentation-related library(unmarked) # analysis-related library(ggplot2) library(ggthemes) library(gridExtra) #' Clear environment and set seed #' #' Note: for reproducibility, it is important to include these. Clearing the #' environment ensures that you have specified all pertinent files that need #' to be loaded, and setting the seed ensures that your analysis is #' repeatable remove(list = ls()) set.seed(2583722) #' Unmarked models #' #' HELE load(file = "data/output_data/hele_occ_d_NB.Rdata") #disturbance hele.occ.d.NB <- occ.d.NB load(file = "data/output_data/hele_occ_null_NB.Rdata") #null hele.occ.null.NB <- occ.null.NB load(file = "data/output_data/hele_occ_t_NB.Rdata") #liatris hele.occ.t.NB <- occ.t.NB load(file = "data/output_data/hele_occ_nb_NB.Rdata")#nonbunchgrass hele.occ.nb.NB <- occ.nb.NB load(file = "data/output_data/hele_occ_b_NB.Rdata") #bunchgrass hele.occ.b.NB <- occ.b.NB load(file = "data/output_data/hele_occ_l_NB.Rdata")#litter hele.occ.l.NB <- occ.l.NB load(file = "data/output_data/hele_occ_c_NB.Rdata") #canopy hele.occ.c.NB <- occ.c.NB #' CIPA load(file = "data/output_data/cipa_occ_e_NB.Rdata") #elevCV cipa.occ.e.NB <- occ.e.NB load(file = "data/output_data/cipa_occ_null_NB.Rdata") #null cipa.occ.null.NB <- occ.null.NB load(file = "data/output_data/cipa_occ_l_NB.Rdata")#litter cipa.occ.l.NB <- occ.l.NB load(file = "data/output_data/cipa_occ_c_NB.Rdata") #canopy cipa.occ.c.NB <- occ.c.NB #' ____________________________________________________________________________ #' ### Unmarked results #' #' CIPA #' #' Fit list dfms.cipa <- fitList("lam(.)p(.)gamma(.)omega(.)-NB" = cipa.occ.null.NB, "lam(canopy)p(.)gamma(.)omega(.)-NB" = cipa.occ.c.NB, "lam(litter)p(.)gamma(.)omega(.)-NB" = cipa.occ.l.NB, "lam(elev.CV)p(.)gamma(.)omega(.)-NB" = cipa.occ.e.NB ) (dms <- modSel(dfms.cipa)) #' Model 1 (elevation) coef(cipa.occ.e.NB, type="psi") confint(cipa.occ.e.NB, type="psi", level=0.85) coef(cipa.occ.e.NB, type="det") confint(cipa.occ.e.NB, type="det", level=0.85) coef(cipa.occ.e.NB, type="col") confint(cipa.occ.e.NB, type="col", level=0.85) coef(cipa.occ.e.NB, type="ext") confint(cipa.occ.e.NB, type="ext", level=0.85) cipa.occ.e.NB #' Model 2 (canopy) coef(cipa.occ.c.NB, type="psi") confint(cipa.occ.c.NB, type="psi", level=0.85) coef(cipa.occ.c.NB, type="det") confint(cipa.occ.c.NB, type="det", level=0.85) coef(cipa.occ.c.NB, type="col") confint(cipa.occ.c.NB, type="col", level=0.85) coef(cipa.occ.c.NB, type="ext") confint(cipa.occ.c.NB, type="ext", level=0.85) cipa.occ.c.NB #' Model 3 (null) coef(cipa.occ.null.NB, type="psi") confint(cipa.occ.null.NB, type="psi", level=0.85) coef(cipa.occ.null.NB, type="det") confint(cipa.occ.null.NB, type="det", level=0.85) coef(cipa.occ.null.NB, type="col") confint(cipa.occ.null.NB, type="col", level=0.85) coef(cipa.occ.null.NB, type="ext") confint(cipa.occ.null.NB, type="ext", level=0.85) cipa.occ.null.NB #' Model 4 (litter) coef(cipa.occ.l.NB, type="psi") confint(cipa.occ.l.NB, type="psi", level=0.85) coef(cipa.occ.l.NB, type="det") confint(cipa.occ.l.NB, type="det", level=0.85) coef(cipa.occ.l.NB, type="col") confint(cipa.occ.l.NB, type="col", level=0.85) coef(cipa.occ.l.NB, type="ext") confint(cipa.occ.l.NB, type="ext", level=0.85) cipa.occ.l.NB #' #' HELE #' #' Fit list dfms.hele <- fitList("lam(.)p(.)gamma(.)omega(.)-NB" = hele.occ.null.NB, "lam(canopy)p(.)gamma(.)omega(.)-NB" = hele.occ.c.NB, "lam(bunchgrass)p(.)gamma(.)omega(.)-NB" = hele.occ.b.NB, "lam(nonbunchgrass)p(.)gamma(.)omega(.)-NB" = hele.occ.nb.NB, "lam(liatris)p(.)gamma(.)omega(.)-NB" = hele.occ.t.NB, "lam(litter)p(.)gamma(.)omega(.)-NB" = hele.occ.l.NB, "lam(dy_pre2015)p(.)gamma(.)omega(.)-NB" = hele.occ.d.NB) (dms <- modSel(dfms.hele)) #' Model 1 (liatris) coef(hele.occ.t.NB, type="psi") confint(hele.occ.t.NB, type="psi", level=0.85) coef(hele.occ.t.NB, type="det") confint(hele.occ.t.NB, type="det", level=0.85) coef(hele.occ.t.NB, type="col") confint(hele.occ.t.NB, type="col", level=0.85) coef(hele.occ.t.NB, type="ext") confint(hele.occ.t.NB, type="ext", level=0.85) hele.occ.t.NB #' Model 2 (null) coef(hele.occ.null.NB, type="psi") confint(hele.occ.null.NB, type="psi", level=0.85) coef(hele.occ.null.NB, type="det") confint(hele.occ.null.NB, type="det", level=0.85) coef(hele.occ.null.NB, type="col") confint(hele.occ.null.NB, type="col", level=0.85) coef(hele.occ.null.NB, type="ext") confint(hele.occ.null.NB, type="ext", level=0.85) hele.occ.null.NB #' Model 3 (nonbunchgrass) coef(hele.occ.nb.NB, type="psi") confint(hele.occ.nb.NB, type="psi", level=0.85) coef(hele.occ.nb.NB, type="det") confint(hele.occ.nb.NB, type="det", level=0.85) coef(hele.occ.nb.NB, type="col") confint(hele.occ.nb.NB, type="col", level=0.85) coef(hele.occ.nb.NB, type="ext") confint(hele.occ.nb.NB, type="ext", level=0.85) hele.occ.nb.NB #' Model 4 (litter) coef(hele.occ.l.NB, type="psi") confint(hele.occ.l.NB, type="psi", level=0.85) coef(hele.occ.l.NB, type="det") confint(hele.occ.l.NB, type="det", level=0.85) coef(hele.occ.l.NB, type="col") confint(hele.occ.l.NB, type="col", level=0.85) coef(hele.occ.l.NB, type="ext") confint(hele.occ.l.NB, type="ext", level=0.85) hele.occ.l.NB #' Model 5 (bunchgrass) coef(hele.occ.b.NB, type="psi") confint(hele.occ.b.NB, type="psi", level=0.85) coef(hele.occ.b.NB, type="det") confint(hele.occ.b.NB, type="det", level=0.85) coef(hele.occ.b.NB, type="col") confint(hele.occ.b.NB, type="col", level=0.85) coef(hele.occ.b.NB, type="ext") confint(hele.occ.b.NB, type="ext", level=0.85) hele.occ.b.NB #' Model 6 (canopy) coef(hele.occ.c.NB, type="psi") confint(hele.occ.c.NB, type="psi", level=0.85) coef(hele.occ.c.NB, type="det") confint(hele.occ.c.NB, type="det", level=0.85) coef(hele.occ.c.NB, type="col") confint(hele.occ.c.NB, type="col", level=0.85) coef(hele.occ.c.NB, type="ext") confint(hele.occ.c.NB, type="ext", level=0.85) hele.occ.c.NB #' Model 7 (disturbance) coef(hele.occ.d.NB, type="psi") confint(hele.occ.d.NB, type="psi", level=0.85) coef(hele.occ.d.NB, type="det") confint(hele.occ.d.NB, type="det", level=0.85) coef(hele.occ.d.NB, type="col") confint(hele.occ.d.NB, type="col", level=0.85) coef(hele.occ.d.NB, type="ext") confint(hele.occ.d.NB, type="ext", level=0.85) hele.occ.d.NB #' _____________________________________________________________________________ #' ### Footer #' #' Session Info devtools::session_info() #' This document was "spun" with: #' #' ezspin(file = "programs/00_thesis_programs/10b_occupancy_results_inverts.R", out_dir = "output/thesis_results_spun", fig_dir = "figures", keep_md = F) #' #' You can run the ezspin() code above to create an html in the "output" folder #' and any associated figures will get put into the "figures" folder.
# Uvoz potrebnih knjižnic library(rgdal) library(rgeos) library(dplyr) library(readr) library(ggplot2) library(digest) library(mosaic) library(maptools) library(digest) # Funkcija uvozi.zemljevid(url, ime.zemljevida, pot.zemljevida="", # mapa="../zemljevidi", encoding=NULL, force=FALSE) # # Funkcija najprej preveri, ali zemljevid na podani lokaciji že obstaja. Če # ne obstaja ali če je parameter force nastavljen na TRUE, pobere arhiv z # navedenega naslova in ga razširi. Nato uvozi zemljevid in ga vrne. # # Parametri: # * url Naslov URL, iz katerega naj dobimo arhiv z zemljevidom. # * ime.zemljevida Ime datoteke SHP brez končnice # * pot.zemljevida Pot do mape z datoteko SHP, kakršna je v pobranem arhivu # (privzeto prazna - vrhnja mapa arhiva). # * mapa Pot do mape, kamor naj se shrani zemljevid (privzeto # mapa "../zemljevid") # * encoding Kodiranje znakov v zemljevidu (privzeta vrednost # NULL, da se pretvorba ne opravi). # * force Ali naj se zemljevid v vsakem primeru pobere z navedenega # naslova (privzeta vrednost FALSE). # # Vrača: # * zemljevid (SpatialPolygonsDataFrame) iz pobranega arhiva uvozi.zemljevid <- function(url, ime.zemljevida, pot.zemljevida="", mapa="../zemljevidi", encoding=NULL, force=FALSE) { zgostitev <- digest(url, algo="sha1") map <- paste0(mapa, "/", zgostitev) pot <- paste0(map, "/", pot.zemljevida) shp <- paste0(pot, "/", ime.zemljevida, ".shp") zip <- paste0(map, "/", zgostitev, ".zip") if (force \|\| !file.exists(shp)) { if (!file.exists(map)) { dir.create(map, recursive=TRUE) } download.file(url, zip) unzip(zip, exdir=map) } re <- paste0("^", gsub("\\.", "\\.", ime.zemljevida), "\\.") files <- grep(paste0(re, "[a-z0-9.]$"), grep(paste0(re, ".$"), dir(pot), value=TRUE), value=TRUE, invert=TRUE) file.rename(paste0(map, "/", files), paste0(map, "/", sapply(strsplit(files, "\\."), function(x) paste(c(x[1:(length(x)-1)], tolower(x[length(x)])), collapse=".")))) zemljevid <- readOGR(shp, ime.zemljevida) if (!is.null(encoding)) { loc <- locale(encoding=encoding) for (col in names(zemljevid)) { if (is.factor(zemljevid[[col]])) { zemljevid[[col]] <- zemljevid[[col]] %>% as.character() %>% parse_character(locale=loc) %>% factor() } } } return(zemljevid) } # Primer uvoza zemljevida (slovenske občine) # obcine <- uvozi.zemljevid("http://baza.fmf.uni-lj.si/OB.zip", "OB", # pot.zemljevida="OB", encoding="Windows-1250")	/lib/uvozi.zemljevid.r	permissive	zanmikola/APPR-2019-20	R	false	false	2,871	r	# Uvoz potrebnih knjižnic library(rgdal) library(rgeos) library(dplyr) library(readr) library(ggplot2) library(digest) library(mosaic) library(maptools) library(digest) # Funkcija uvozi.zemljevid(url, ime.zemljevida, pot.zemljevida="", # mapa="../zemljevidi", encoding=NULL, force=FALSE) # # Funkcija najprej preveri, ali zemljevid na podani lokaciji že obstaja. Če # ne obstaja ali če je parameter force nastavljen na TRUE, pobere arhiv z # navedenega naslova in ga razširi. Nato uvozi zemljevid in ga vrne. # # Parametri: # * url Naslov URL, iz katerega naj dobimo arhiv z zemljevidom. # * ime.zemljevida Ime datoteke SHP brez končnice # * pot.zemljevida Pot do mape z datoteko SHP, kakršna je v pobranem arhivu # (privzeto prazna - vrhnja mapa arhiva). # * mapa Pot do mape, kamor naj se shrani zemljevid (privzeto # mapa "../zemljevid") # * encoding Kodiranje znakov v zemljevidu (privzeta vrednost # NULL, da se pretvorba ne opravi). # * force Ali naj se zemljevid v vsakem primeru pobere z navedenega # naslova (privzeta vrednost FALSE). # # Vrača: # * zemljevid (SpatialPolygonsDataFrame) iz pobranega arhiva uvozi.zemljevid <- function(url, ime.zemljevida, pot.zemljevida="", mapa="../zemljevidi", encoding=NULL, force=FALSE) { zgostitev <- digest(url, algo="sha1") map <- paste0(mapa, "/", zgostitev) pot <- paste0(map, "/", pot.zemljevida) shp <- paste0(pot, "/", ime.zemljevida, ".shp") zip <- paste0(map, "/", zgostitev, ".zip") if (force \|\| !file.exists(shp)) { if (!file.exists(map)) { dir.create(map, recursive=TRUE) } download.file(url, zip) unzip(zip, exdir=map) } re <- paste0("^", gsub("\\.", "\\.", ime.zemljevida), "\\.") files <- grep(paste0(re, "[a-z0-9.]$"), grep(paste0(re, ".$"), dir(pot), value=TRUE), value=TRUE, invert=TRUE) file.rename(paste0(map, "/", files), paste0(map, "/", sapply(strsplit(files, "\\."), function(x) paste(c(x[1:(length(x)-1)], tolower(x[length(x)])), collapse=".")))) zemljevid <- readOGR(shp, ime.zemljevida) if (!is.null(encoding)) { loc <- locale(encoding=encoding) for (col in names(zemljevid)) { if (is.factor(zemljevid[[col]])) { zemljevid[[col]] <- zemljevid[[col]] %>% as.character() %>% parse_character(locale=loc) %>% factor() } } } return(zemljevid) } # Primer uvoza zemljevida (slovenske občine) # obcine <- uvozi.zemljevid("http://baza.fmf.uni-lj.si/OB.zip", "OB", # pot.zemljevida="OB", encoding="Windows-1250")
% Generated by roxygen2: do not edit by hand % Please edit documentation in R/metadata.R \name{has_label} \alias{has_label} \title{Has label} \usage{ has_label(x) } \arguments{ \item{x}{a vector} } \description{ Has label } \examples{ example("labelled", "haven") has_label(x) }	/man/has_label.Rd	no_license	cran/codebook	R	false	true	297	rd	% Generated by roxygen2: do not edit by hand % Please edit documentation in R/metadata.R \name{has_label} \alias{has_label} \title{Has label} \usage{ has_label(x) } \arguments{ \item{x}{a vector} } \description{ Has label } \examples{ example("labelled", "haven") has_label(x) }
\name{install.tract} \alias{install.tract} %- Also NEED an '\alias' for EACH other topic documented here. \title{ Installer for the UScensus2010tract package. } \description{ Convenient installer for the UScensus2010 package. Warning this installs from the source file for OS X and Linux and can take several minutes. Windows install only available for 2.11+ at this time.%Only 32 bit windows build available at this time. } \usage{ install.tract(x) } %- maybe also 'usage' for other objects documented here. \arguments{ \item{x}{a character string, must be either "osx:, "linux" or "windows"} } %\details{ %% ~~ If necessary, more details than the description above ~~ %} \references{ Zack W. Almquist (2010). US Census Spatial and Demographic Data in R: The UScensus2000 Suite of Packages. Journal of Statistical Software, 37(6), 1-31. \url{https://www.jstatsoft.org/v37/i06/}. } \author{ Zack W Almquist } \section{Warning }{ This is an extremely large file (around 180 megabytes) and should only be installed if you have a very good connection. Also it is worth noting that for all systems the install is from source and can take quite a bit of time to install. } \examples{ \dontrun{ install.tract("osx") } } % Add one or more standard keywords, see file 'KEYWORDS' in the % R documentation directory. \keyword{install}	/man/install.tract.Rd	no_license	cran/UScensus2010	R	false	false	1,333	rd	\name{install.tract} \alias{install.tract} %- Also NEED an '\alias' for EACH other topic documented here. \title{ Installer for the UScensus2010tract package. } \description{ Convenient installer for the UScensus2010 package. Warning this installs from the source file for OS X and Linux and can take several minutes. Windows install only available for 2.11+ at this time.%Only 32 bit windows build available at this time. } \usage{ install.tract(x) } %- maybe also 'usage' for other objects documented here. \arguments{ \item{x}{a character string, must be either "osx:, "linux" or "windows"} } %\details{ %% ~~ If necessary, more details than the description above ~~ %} \references{ Zack W. Almquist (2010). US Census Spatial and Demographic Data in R: The UScensus2000 Suite of Packages. Journal of Statistical Software, 37(6), 1-31. \url{https://www.jstatsoft.org/v37/i06/}. } \author{ Zack W Almquist } \section{Warning }{ This is an extremely large file (around 180 megabytes) and should only be installed if you have a very good connection. Also it is worth noting that for all systems the install is from source and can take quite a bit of time to install. } \examples{ \dontrun{ install.tract("osx") } } % Add one or more standard keywords, see file 'KEYWORDS' in the % R documentation directory. \keyword{install}
testlist <- list(Rext = numeric(0), Rs = numeric(0), Z = numeric(0), alpha = numeric(0), atmp = numeric(0), relh = numeric(0), temp = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), u = numeric(0)) result <- do.call(meteor:::E_Penman,testlist) str(result)	/meteor/inst/testfiles/E_Penman/AFL_E_Penman/E_Penman_valgrind_files/1615917733-test.R	no_license	akhikolla/updatedatatype-list3	R	false	false	498	r	testlist <- list(Rext = numeric(0), Rs = numeric(0), Z = numeric(0), alpha = numeric(0), atmp = numeric(0), relh = numeric(0), temp = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), u = numeric(0)) result <- do.call(meteor:::E_Penman,testlist) str(result)
#scoring.R #' @get /scoring getCustScoring <- function(cus_id) { library(DBI) library(devtools) library(RMySQL) library(party) library(stringi) library(stringr) mydb <- dbConnect(MySQL(), user='helpr', password='Q#2dT9C&xapk', dbname='helpr', host='52.66.125.0') querylp<-sprintf("select * from customer_scoring;") datacheck=dbGetQuery(mydb, querylp) dbDisconnect(mydb) for( i in length(datacheck$customer_id)) { if(datacheck$customer_id[i]==cus_id) { mydb <- dbConnect(MySQL(), user='helpr', password='Q#2dT9C&xapk', dbname='helpr', host='52.66.123.49') querycs<-sprintf("select * from customer_scoring where customer_id not in ('CUSTOMER');") querycs <- sub("CUSTOMER",as.numeric(cus_id),querycs); datacs=dbGetQuery(mydb, querycs) train<-datacs train[is.na(train)]<-0 train$get<-2 query5<-sprintf("select * from customer_scoring where customer_id='CUSTOMER';") query5 <- sub("CUSTOMER",as.numeric(cus_id),query5) test<-dbGetQuery(mydb, query5) test$get<-1 data=rbind(test,train) test<-subset(data,data$get==1) output.fit<-ctree(as.factor(customer_score)~cancelled_count+completed_count+amount_spend_task+amount_spend_subscription,data=train) p<-predict(output.fit,test) test$customer_score<-p #dbWriteTable(mydb, value = test, name = "customer_scoring", overwrite=TRUE ) queryd<-sprintf("DELETE FROM customer_scoring where customer_id = 'CUSTOMER'") queryd <- sub("CUSTOMER",as.numeric(cus_id),queryd); dbSendQuery(mydb,queryd) querys<- sprintf("INSERT IGNORE INTO customer_scoring (customer_id,cancelled_count,completed_count,amount_spend_subscription,amount_spend_task, customer_score ) VALUES ('CUSTOMER','CANCELLED','COMPLETED','AMOUNT_S','AMOUNT_T','SCORE');") querys <- sub("CUSTOMER",as.numeric(test$customer_id),querys);querys <- sub("CANCELLED",as.numeric(test$cancelled_count),querys);querys <- sub("COMPLETED",as.numeric(test$completed_count),querys);querys <- sub("AMOUNT_S",as.numeric(test$amount_spend_subscription),querys);querys <- sub("AMOUNT_T",as.numeric(test$amount_spend_task),querys);querys <- sub("SCORE",as.numeric(test$customer_score),querys); dbSendQuery(mydb,querys) #queryv<- sprintf("UPDATE customer_scoring set customer_score='SCORE' where customer_scoring_id= 'CUS_SC_ID' AND customer_id='CUSTOMER';") #queryv <- sub("CUS_SC_ID",as.numeric(test$customer_scoring_id),queryv);queryv <- sub("CUSTOMER",as.numeric(cus_id),queryv);queryv <- sub("SCORE",as.numeric(test$customer_score),queryv) #dbSendQuery(mydb,queryv) queryu<- sprintf("UPDATE customer_scoring set last_modified_date=now() where customer_id='CUSTOMER'") queryu <- sub("CUSTOMER",as.numeric(cus_id),queryu) dbSendQuery(mydb,queryu) dbDisconnect(mydb) cus_id<-test$customer_score[test$customer_id==cus_id] } else if(datacheck$customer_id[i]!=cus_id) { mydb <- dbConnect(MySQL(), user='helpr', password='Q#2dT9C&xapk', dbname='helpr', host='52.66.123.49') train<-datacheck train[is.na(train)]<-0 train$customer_scoring_id<-NULL train$last_modified_date<-NULL train$created_date<-NULL train$get<-2 query1 <- sprintf("select DISTINCT i.customer_id,SUM(i.gross_amount) as amount_spend_task,c.created_date AS created_date from invoice i INNER JOIN customer c on c.customer_id=i.customer_id INNER JOIN task t ON i.task_id=t.task_id WHERE t.STATUS= 'COMPLETED' AND c.customer_id = 'CUSTOMER' GROUP BY i.customer_id;") query1 <- sub("CUSTOMER",as.numeric(cus_id),query1) query2 <- sprintf(" select DISTINCT c.customer_id,SUM(su.gross_amount) as amount_spend_subscription from customer c INNER JOIN subscription_user_plan su ON su.customer_id=c.customer_id WHERE su.subscription_invoice_number IS NOT NULL AND c.customer_id = 'CUSTOMER' GROUP BY c.customer_id; ") query2 <- sub("CUSTOMER",as.numeric(cus_id),query2) query3 <- sprintf("select c.customer_id,count(t.task_id) AS cancelled_count from customer c inner join task t on c.customer_id=t.customer_id where t.status='cancelled' AND c.customer_id = 'CUSTOMER' GROUP BY c.customer_id ;") query3 <- sub("CUSTOMER",as.numeric(cus_id),query3) query4 <- sprintf("select c.customer_id,count(t.task_id) AS completed_count from customer c inner join task t on c.customer_id=t.customer_id where t.status='completed' AND c.customer_id = 'CUSTOMER' GROUP BY c.customer_id ; ") query4 <- sub("CUSTOMER",as.numeric(cus_id),query4) data1 = dbGetQuery(mydb, query1) data2 = dbGetQuery(mydb, query2) data3 = dbGetQuery(mydb, query3) data4 = dbGetQuery(mydb, query4) b=merge(data3,data4,by="customer_id",all=TRUE) c=merge(b,data2,by="customer_id",all=TRUE) test=merge(c,data1,by="customer_id",all=TRUE) test[is.na(test)]<-0 test$customer_score<-3 test$get<-1 test$created_date<-NULL train<-rbind(train,test) test<-subset(train,train$get==1) output.fit<-ctree(as.factor(customer_score)~cancelled_count+completed_count+amount_spend_task+amount_spend_subscription,data=train) p<-predict(output.fit,test) test$customer_score<-p queryd<-sprintf("DELETE FROM customer_scoring where customer_id = 'CUSTOMER'") queryd <- sub("CUSTOMER",as.numeric(cus_id),queryd); dbSendQuery(mydb,queryd) querys<- sprintf("INSERT IGNORE INTO customer_scoring (customer_id,cancelled_count,completed_count,amount_spend_subscription,amount_spend_task, customer_score ) VALUES ('CUSTOMER','CANCELLED','COMPLETED','AMOUNT_S','AMOUNT_T','SCORE');") querys <- sub("CUSTOMER",as.numeric(test$customer_id),querys);querys <- sub("CANCELLED",as.numeric(test$cancelled_count),querys);querys <- sub("COMPLETED",as.numeric(test$completed_count),querys);querys <- sub("AMOUNT_S",as.numeric(test$amount_spend_subscription),querys);querys <- sub("AMOUNT_T",as.numeric(test$amount_spend_task),querys);querys <- sub("SCORE",as.numeric(test$customer_score),querys); dbSendQuery(mydb,querys) queryu<- sprintf("UPDATE customer_scoring set last_modified_date=now() where customer_id='CUSTOMER'") queryu <- sub("CUSTOMER",as.numeric(cus_id),queryu) dbSendQuery(mydb,queryu) dbDisconnect(mydb) cus_id<-test$customer_score[test$customer_id==cus_id] } } return(cus_id) }	/custscore.R	no_license	svivek1786/Helpr	R	false	false	6,798	r	#scoring.R #' @get /scoring getCustScoring <- function(cus_id) { library(DBI) library(devtools) library(RMySQL) library(party) library(stringi) library(stringr) mydb <- dbConnect(MySQL(), user='helpr', password='Q#2dT9C&xapk', dbname='helpr', host='52.66.125.0') querylp<-sprintf("select * from customer_scoring;") datacheck=dbGetQuery(mydb, querylp) dbDisconnect(mydb) for( i in length(datacheck$customer_id)) { if(datacheck$customer_id[i]==cus_id) { mydb <- dbConnect(MySQL(), user='helpr', password='Q#2dT9C&xapk', dbname='helpr', host='52.66.123.49') querycs<-sprintf("select * from customer_scoring where customer_id not in ('CUSTOMER');") querycs <- sub("CUSTOMER",as.numeric(cus_id),querycs); datacs=dbGetQuery(mydb, querycs) train<-datacs train[is.na(train)]<-0 train$get<-2 query5<-sprintf("select * from customer_scoring where customer_id='CUSTOMER';") query5 <- sub("CUSTOMER",as.numeric(cus_id),query5) test<-dbGetQuery(mydb, query5) test$get<-1 data=rbind(test,train) test<-subset(data,data$get==1) output.fit<-ctree(as.factor(customer_score)~cancelled_count+completed_count+amount_spend_task+amount_spend_subscription,data=train) p<-predict(output.fit,test) test$customer_score<-p #dbWriteTable(mydb, value = test, name = "customer_scoring", overwrite=TRUE ) queryd<-sprintf("DELETE FROM customer_scoring where customer_id = 'CUSTOMER'") queryd <- sub("CUSTOMER",as.numeric(cus_id),queryd); dbSendQuery(mydb,queryd) querys<- sprintf("INSERT IGNORE INTO customer_scoring (customer_id,cancelled_count,completed_count,amount_spend_subscription,amount_spend_task, customer_score ) VALUES ('CUSTOMER','CANCELLED','COMPLETED','AMOUNT_S','AMOUNT_T','SCORE');") querys <- sub("CUSTOMER",as.numeric(test$customer_id),querys);querys <- sub("CANCELLED",as.numeric(test$cancelled_count),querys);querys <- sub("COMPLETED",as.numeric(test$completed_count),querys);querys <- sub("AMOUNT_S",as.numeric(test$amount_spend_subscription),querys);querys <- sub("AMOUNT_T",as.numeric(test$amount_spend_task),querys);querys <- sub("SCORE",as.numeric(test$customer_score),querys); dbSendQuery(mydb,querys) #queryv<- sprintf("UPDATE customer_scoring set customer_score='SCORE' where customer_scoring_id= 'CUS_SC_ID' AND customer_id='CUSTOMER';") #queryv <- sub("CUS_SC_ID",as.numeric(test$customer_scoring_id),queryv);queryv <- sub("CUSTOMER",as.numeric(cus_id),queryv);queryv <- sub("SCORE",as.numeric(test$customer_score),queryv) #dbSendQuery(mydb,queryv) queryu<- sprintf("UPDATE customer_scoring set last_modified_date=now() where customer_id='CUSTOMER'") queryu <- sub("CUSTOMER",as.numeric(cus_id),queryu) dbSendQuery(mydb,queryu) dbDisconnect(mydb) cus_id<-test$customer_score[test$customer_id==cus_id] } else if(datacheck$customer_id[i]!=cus_id) { mydb <- dbConnect(MySQL(), user='helpr', password='Q#2dT9C&xapk', dbname='helpr', host='52.66.123.49') train<-datacheck train[is.na(train)]<-0 train$customer_scoring_id<-NULL train$last_modified_date<-NULL train$created_date<-NULL train$get<-2 query1 <- sprintf("select DISTINCT i.customer_id,SUM(i.gross_amount) as amount_spend_task,c.created_date AS created_date from invoice i INNER JOIN customer c on c.customer_id=i.customer_id INNER JOIN task t ON i.task_id=t.task_id WHERE t.STATUS= 'COMPLETED' AND c.customer_id = 'CUSTOMER' GROUP BY i.customer_id;") query1 <- sub("CUSTOMER",as.numeric(cus_id),query1) query2 <- sprintf(" select DISTINCT c.customer_id,SUM(su.gross_amount) as amount_spend_subscription from customer c INNER JOIN subscription_user_plan su ON su.customer_id=c.customer_id WHERE su.subscription_invoice_number IS NOT NULL AND c.customer_id = 'CUSTOMER' GROUP BY c.customer_id; ") query2 <- sub("CUSTOMER",as.numeric(cus_id),query2) query3 <- sprintf("select c.customer_id,count(t.task_id) AS cancelled_count from customer c inner join task t on c.customer_id=t.customer_id where t.status='cancelled' AND c.customer_id = 'CUSTOMER' GROUP BY c.customer_id ;") query3 <- sub("CUSTOMER",as.numeric(cus_id),query3) query4 <- sprintf("select c.customer_id,count(t.task_id) AS completed_count from customer c inner join task t on c.customer_id=t.customer_id where t.status='completed' AND c.customer_id = 'CUSTOMER' GROUP BY c.customer_id ; ") query4 <- sub("CUSTOMER",as.numeric(cus_id),query4) data1 = dbGetQuery(mydb, query1) data2 = dbGetQuery(mydb, query2) data3 = dbGetQuery(mydb, query3) data4 = dbGetQuery(mydb, query4) b=merge(data3,data4,by="customer_id",all=TRUE) c=merge(b,data2,by="customer_id",all=TRUE) test=merge(c,data1,by="customer_id",all=TRUE) test[is.na(test)]<-0 test$customer_score<-3 test$get<-1 test$created_date<-NULL train<-rbind(train,test) test<-subset(train,train$get==1) output.fit<-ctree(as.factor(customer_score)~cancelled_count+completed_count+amount_spend_task+amount_spend_subscription,data=train) p<-predict(output.fit,test) test$customer_score<-p queryd<-sprintf("DELETE FROM customer_scoring where customer_id = 'CUSTOMER'") queryd <- sub("CUSTOMER",as.numeric(cus_id),queryd); dbSendQuery(mydb,queryd) querys<- sprintf("INSERT IGNORE INTO customer_scoring (customer_id,cancelled_count,completed_count,amount_spend_subscription,amount_spend_task, customer_score ) VALUES ('CUSTOMER','CANCELLED','COMPLETED','AMOUNT_S','AMOUNT_T','SCORE');") querys <- sub("CUSTOMER",as.numeric(test$customer_id),querys);querys <- sub("CANCELLED",as.numeric(test$cancelled_count),querys);querys <- sub("COMPLETED",as.numeric(test$completed_count),querys);querys <- sub("AMOUNT_S",as.numeric(test$amount_spend_subscription),querys);querys <- sub("AMOUNT_T",as.numeric(test$amount_spend_task),querys);querys <- sub("SCORE",as.numeric(test$customer_score),querys); dbSendQuery(mydb,querys) queryu<- sprintf("UPDATE customer_scoring set last_modified_date=now() where customer_id='CUSTOMER'") queryu <- sub("CUSTOMER",as.numeric(cus_id),queryu) dbSendQuery(mydb,queryu) dbDisconnect(mydb) cus_id<-test$customer_score[test$customer_id==cus_id] } } return(cus_id) }
fnReadNamedValue <- function( sName, vsLines ) { #XXXX_SOFT_TAB_PROBLEM sRegExp <- paste0("^",sName,"\\t") sRegExp <- paste0("^",sName,"( \|\\t)") iLine <- grep( sRegExp, vsLines, ignore.case=T ) if(!length(iLine)) return() # name not found if( length(iLine)>1 ) stop( paste0("Multiple name value pairs for - '",sName,"'") ) # read value from line #XXXX_SOFT_TAB_PROBLEM vsParsed <- strsplit(vsLines[iLine], split="\t")[[1]] vsParsed <- strsplit(vsLines[iLine], split=c("( \|\t)+"))[[1]] if(length(vsParsed)==2) return(vsParsed[2]) else if(length(vsParsed)==1) return("") else stop("Unexpected number of items in parsed line") } fnReadHeading <- function( sHeading, vsLines ) { sRegExp <- paste0("^",sHeading,"$") iLine <- grep( sRegExp, vsLines, ignore.case=T ) if(!length(iLine)) return() # heading not found iLine } fnGetLinesAfterHeading <- function( sHeading, vsLines ) { iLine <- fnReadHeading( sHeading, vsLines ) if(is.null(iLine)) return() # heading not found if( length(iLine)>1 ) stop( paste0("Multiple headings - '",sHeading,"'") ) # calc line number of first line of block iLineStart <- iLine + 1 nofLines <- length(vsLines) if(iLineStart > nofLines) stop( paste0("No block following heading - '",sHeading,"'") ) # calc line number of last line of block vixBlankLines <- which(grepl( "^( \|\\t)$", vsLines )) vbx <- iLine < vixBlankLines iLineEnd <- (vixBlankLines[vbx]-1)[1] if(is.na(iLineEnd)) iLineEnd <- nofLines # return block extent c(iLineStart,iLineEnd) } fnReadLines <- function( vsLines, vsTokenNameValuePair, vsTokenLinesAfter, vsTokenTableAfter ) { #vsLines <- sub( pattern="#.$", "", vsLines ) # remove comments vsLines <- sub( pattern="[\t ]+$", "", vsLines ) # remove trailing spaces lOut <- list() # init object that will represent the information gleaned from the file for( sToken in vsTokenLinesAfter ){ viLineStartEnd <- fnGetLinesAfterHeading( sToken, vsLines ) if( !is.null(viLineStartEnd) ) lOut[[sToken]] <- vsLines[viLineStartEnd[1]:viLineStartEnd[2]] } for( sToken in vsTokenNameValuePair ){ value <- fnReadNamedValue( sToken, vsLines ) if( !is.null(value) ) lOut[[sToken]] <- value } for( sToken in vsTokenTableAfter ){ viLineStartEnd <- fnGetLinesAfterHeading( sToken, vsLines ) if( !is.null(viLineStartEnd) ) { txtCon <- textConnection(vsLines[viLineStartEnd[1]:viLineStartEnd[2]]) dfTbl <- NA; dfTbl <- tryCatch( { #XXXX_SOFT_TAB_PROBLEM lOut[[sToken]] <- utils::read.table( file=txtCon, sep="\t", header=T, stringsAsFactors=F, colClasses="character", skip=viLineStartEnd[1]-1, nrows=viLineStartEnd[2]-viLineStartEnd[1] ) #lOut[[sToken]] <- utils::read.table( file=txtCon, sep="", header=T, stringsAsFactors=F, colClasses="character", skip=viLineStartEnd[1]-1, nrows=viLineStartEnd[2]-viLineStartEnd[1] ) lOut[[sToken]] <- utils::read.table( file=txtCon, sep="", header=T, stringsAsFactors=F, colClasses="character" ) } , warning=function(w) w$message , error=function(e) e$message ) # end of tryCatch close(txtCon) if( is.character(dfTbl)) stop( "Problem with ", sToken, " table : ", dfTbl ) } } lOut } #' XXXX #' #' XXXX #' @param sFile XXXX #' @param vsTokenNameValuePair XXXX #' @param vsTokenLinesAfter XXXX #' @param vsTokenTableAfter XXXX #' @return XXXX #' @export fnReadFile <- function( sFile, vsTokenNameValuePair, vsTokenLinesAfter, vsTokenTableAfter ) { # read file into a vector of lines vsLines <- readLines(sFile, n = -1) # convert into read object lOut <- fnReadLines( vsLines, vsTokenNameValuePair, vsTokenLinesAfter, vsTokenTableAfter ) lOut } fnTypeConvertAndValidateVector <- function( vParamValue, sType ) { switch( sType , character = { vParamValue <- suppressWarnings( as.character(vParamValue) ) if( any( is.na(vParamValue) \| is.null(vParamValue) ) ) stop( "Not text") } , characterVector = { if( "character" != typeof(vParamValue) ) stop( "Not text") } , table = { if( "data.frame" != class(vParamValue) ) stop( "Not table") } , numeric = { vParamValue <- suppressWarnings( as.numeric(vParamValue) ) if( any( is.na(vParamValue) \| is.null(vParamValue) ) ) stop( "Not a number") } , proportion = { vParamValue <- suppressWarnings( as.numeric(vParamValue) ) if( any( is.na(vParamValue) \| is.null(vParamValue) \| vParamValue < 0 \| vParamValue > 1 ) ) stop( "Not a number between 0 and 1") } , positive = { vParamValue <- suppressWarnings( as.numeric(vParamValue) ) if( any( is.na(vParamValue) \| is.null(vParamValue) \| vParamValue < 0 ) ) stop( "Not a positive number") } , stop( paste( "Unhandled type encountered - ", sType) ) ) vParamValue } fnTypeConvertRangeCheck <- function( dfDisDef, lDisFile ) { # global parameters for( rr in 1:nrow(dfDisDef) ) { if( dfDisDef$category[rr] != "global" ) next sParam <- dfDisDef$parameter[rr] # validate required parameters defined if( ! sParam %in% names(lDisFile) ){ if(dfDisDef$required[rr]) stop( paste0("Required parameter not defined - '", sParam, "'")) next # nothing more to check as parameter is absent } # convert value to correct type and validate paramValue <- NULL; paramValue <- tryCatch( fnTypeConvertAndValidateVector( lDisFile[[sParam]], dfDisDef$type[rr] ) ,error=function(e){ return(e) } ) if( "error" %in% class(paramValue) ) { oError <- paramValue; paramValue <- NULL stop( paste0( "Problem value found for '", sParam, "' parameter : ", oError$message ) ) } lDisFile[[sParam]] <- paramValue } # table parameters for( rr in 1:nrow(dfDisDef) ) { if( dfDisDef$category[rr] == "global" ) next sParam <- dfDisDef$parameter[rr] sTable <- dfDisDef$category[rr] # if current table not specified in Dis file then ignore this parameter check if( !sTable %in% names(lDisFile) ) next # validate required parameters defined if( ! sParam %in% colnames(lDisFile[[sTable]]) ){ if(dfDisDef$required[rr]) stop( paste0("Required parameter not defined - table '", sTable, "', column'", sParam, "'")) next # nothing more to check as parameter is absent } # convert value to correct type and validate vParamValue <- NULL; vParamValue <- tryCatch( fnTypeConvertAndValidateVector( lDisFile[[sTable]][,sParam], dfDisDef$type[rr] ) ,error=function(e){ return(e) } ) if( "error" %in% class(vParamValue) ) { oError <- vParamValue; vParamValue <- NULL stop( paste0( "Problem in '", sTable, "' table, '", sParam, "' column : ", oError$message) ) } lDisFile[[sTable]][,sParam] <- vParamValue } lDisFile }	/R/FileReaderSrc.R	no_license	DesmondCampbell/diseaseRiskPredictor	R	false	false	6,968	r	fnReadNamedValue <- function( sName, vsLines ) { #XXXX_SOFT_TAB_PROBLEM sRegExp <- paste0("^",sName,"\\t") sRegExp <- paste0("^",sName,"( \|\\t)") iLine <- grep( sRegExp, vsLines, ignore.case=T ) if(!length(iLine)) return() # name not found if( length(iLine)>1 ) stop( paste0("Multiple name value pairs for - '",sName,"'") ) # read value from line #XXXX_SOFT_TAB_PROBLEM vsParsed <- strsplit(vsLines[iLine], split="\t")[[1]] vsParsed <- strsplit(vsLines[iLine], split=c("( \|\t)+"))[[1]] if(length(vsParsed)==2) return(vsParsed[2]) else if(length(vsParsed)==1) return("") else stop("Unexpected number of items in parsed line") } fnReadHeading <- function( sHeading, vsLines ) { sRegExp <- paste0("^",sHeading,"$") iLine <- grep( sRegExp, vsLines, ignore.case=T ) if(!length(iLine)) return() # heading not found iLine } fnGetLinesAfterHeading <- function( sHeading, vsLines ) { iLine <- fnReadHeading( sHeading, vsLines ) if(is.null(iLine)) return() # heading not found if( length(iLine)>1 ) stop( paste0("Multiple headings - '",sHeading,"'") ) # calc line number of first line of block iLineStart <- iLine + 1 nofLines <- length(vsLines) if(iLineStart > nofLines) stop( paste0("No block following heading - '",sHeading,"'") ) # calc line number of last line of block vixBlankLines <- which(grepl( "^( \|\\t)$", vsLines )) vbx <- iLine < vixBlankLines iLineEnd <- (vixBlankLines[vbx]-1)[1] if(is.na(iLineEnd)) iLineEnd <- nofLines # return block extent c(iLineStart,iLineEnd) } fnReadLines <- function( vsLines, vsTokenNameValuePair, vsTokenLinesAfter, vsTokenTableAfter ) { #vsLines <- sub( pattern="#.$", "", vsLines ) # remove comments vsLines <- sub( pattern="[\t ]+$", "", vsLines ) # remove trailing spaces lOut <- list() # init object that will represent the information gleaned from the file for( sToken in vsTokenLinesAfter ){ viLineStartEnd <- fnGetLinesAfterHeading( sToken, vsLines ) if( !is.null(viLineStartEnd) ) lOut[[sToken]] <- vsLines[viLineStartEnd[1]:viLineStartEnd[2]] } for( sToken in vsTokenNameValuePair ){ value <- fnReadNamedValue( sToken, vsLines ) if( !is.null(value) ) lOut[[sToken]] <- value } for( sToken in vsTokenTableAfter ){ viLineStartEnd <- fnGetLinesAfterHeading( sToken, vsLines ) if( !is.null(viLineStartEnd) ) { txtCon <- textConnection(vsLines[viLineStartEnd[1]:viLineStartEnd[2]]) dfTbl <- NA; dfTbl <- tryCatch( { #XXXX_SOFT_TAB_PROBLEM lOut[[sToken]] <- utils::read.table( file=txtCon, sep="\t", header=T, stringsAsFactors=F, colClasses="character", skip=viLineStartEnd[1]-1, nrows=viLineStartEnd[2]-viLineStartEnd[1] ) #lOut[[sToken]] <- utils::read.table( file=txtCon, sep="", header=T, stringsAsFactors=F, colClasses="character", skip=viLineStartEnd[1]-1, nrows=viLineStartEnd[2]-viLineStartEnd[1] ) lOut[[sToken]] <- utils::read.table( file=txtCon, sep="", header=T, stringsAsFactors=F, colClasses="character" ) } , warning=function(w) w$message , error=function(e) e$message ) # end of tryCatch close(txtCon) if( is.character(dfTbl)) stop( "Problem with ", sToken, " table : ", dfTbl ) } } lOut } #' XXXX #' #' XXXX #' @param sFile XXXX #' @param vsTokenNameValuePair XXXX #' @param vsTokenLinesAfter XXXX #' @param vsTokenTableAfter XXXX #' @return XXXX #' @export fnReadFile <- function( sFile, vsTokenNameValuePair, vsTokenLinesAfter, vsTokenTableAfter ) { # read file into a vector of lines vsLines <- readLines(sFile, n = -1) # convert into read object lOut <- fnReadLines( vsLines, vsTokenNameValuePair, vsTokenLinesAfter, vsTokenTableAfter ) lOut } fnTypeConvertAndValidateVector <- function( vParamValue, sType ) { switch( sType , character = { vParamValue <- suppressWarnings( as.character(vParamValue) ) if( any( is.na(vParamValue) \| is.null(vParamValue) ) ) stop( "Not text") } , characterVector = { if( "character" != typeof(vParamValue) ) stop( "Not text") } , table = { if( "data.frame" != class(vParamValue) ) stop( "Not table") } , numeric = { vParamValue <- suppressWarnings( as.numeric(vParamValue) ) if( any( is.na(vParamValue) \| is.null(vParamValue) ) ) stop( "Not a number") } , proportion = { vParamValue <- suppressWarnings( as.numeric(vParamValue) ) if( any( is.na(vParamValue) \| is.null(vParamValue) \| vParamValue < 0 \| vParamValue > 1 ) ) stop( "Not a number between 0 and 1") } , positive = { vParamValue <- suppressWarnings( as.numeric(vParamValue) ) if( any( is.na(vParamValue) \| is.null(vParamValue) \| vParamValue < 0 ) ) stop( "Not a positive number") } , stop( paste( "Unhandled type encountered - ", sType) ) ) vParamValue } fnTypeConvertRangeCheck <- function( dfDisDef, lDisFile ) { # global parameters for( rr in 1:nrow(dfDisDef) ) { if( dfDisDef$category[rr] != "global" ) next sParam <- dfDisDef$parameter[rr] # validate required parameters defined if( ! sParam %in% names(lDisFile) ){ if(dfDisDef$required[rr]) stop( paste0("Required parameter not defined - '", sParam, "'")) next # nothing more to check as parameter is absent } # convert value to correct type and validate paramValue <- NULL; paramValue <- tryCatch( fnTypeConvertAndValidateVector( lDisFile[[sParam]], dfDisDef$type[rr] ) ,error=function(e){ return(e) } ) if( "error" %in% class(paramValue) ) { oError <- paramValue; paramValue <- NULL stop( paste0( "Problem value found for '", sParam, "' parameter : ", oError$message ) ) } lDisFile[[sParam]] <- paramValue } # table parameters for( rr in 1:nrow(dfDisDef) ) { if( dfDisDef$category[rr] == "global" ) next sParam <- dfDisDef$parameter[rr] sTable <- dfDisDef$category[rr] # if current table not specified in Dis file then ignore this parameter check if( !sTable %in% names(lDisFile) ) next # validate required parameters defined if( ! sParam %in% colnames(lDisFile[[sTable]]) ){ if(dfDisDef$required[rr]) stop( paste0("Required parameter not defined - table '", sTable, "', column'", sParam, "'")) next # nothing more to check as parameter is absent } # convert value to correct type and validate vParamValue <- NULL; vParamValue <- tryCatch( fnTypeConvertAndValidateVector( lDisFile[[sTable]][,sParam], dfDisDef$type[rr] ) ,error=function(e){ return(e) } ) if( "error" %in% class(vParamValue) ) { oError <- vParamValue; vParamValue <- NULL stop( paste0( "Problem in '", sTable, "' table, '", sParam, "' column : ", oError$message) ) } lDisFile[[sTable]][,sParam] <- vParamValue } lDisFile }
#' A4CreateSettlement(region_id,dirs,filename,title,outfile,m2data_new) #' Create data frames for new settlement and predict prices #' #' @param region_id id number for region #' @param dirs list of directories #' @param filename .csv file containing details of settlement #' @param m2data_new input base dataframe for new settlement #' @param travelmodelbasis c("cheb","glp","tensor") #' @param title title of table of summary stats #' @param outfile output file #' @return newdata list containing (m1data_new,m2data_new) #' @keywords new settlement #' @export #' @examples #' newdata <- A4CreateSettlement(region_id = 1,dirs,filename = "Bedford.csv",title,outfile) #' newdata <- A4CreateSettlement(region_id = 1,dirs,m2data_new = m2data_base) A4CreateSettlement<-function(region_id,dirs,filename,m2data_new,travelmodelbasis="cheb", title="none",outfile="none") { default_warn<-getOption("warn") options(warn=-1) # proj_4string for spatial objects wgs.84 <- '+proj=longlat +datum=WGS84 +no_defs +ellps=WGS84 +towgs84=0,0,0' if (!missing(filename)) { # Load New settlement data # example: filename<-"Bedford.csv" m2data_new<-read.csv(paste0(dirs$newdatadir,"/",filename), header=TRUE) } else if (missing(filename) & missing(m2data_new)) { stop("Error in A4CreateSettlement. Must input either 'filename' or 'm2data_new'.") } DestinationFile <- paste0(dirs$datadir,"/destinations",region_id,"B.csv") dest <- read.csv(DestinationFile) load(paste0(dirs$newdatadir,"/m1data_template.RData")) load(paste0(dirs$datadir,"/m2data2.RData")) load(paste0(dirs$datadir,"/convexhull.RData")) # used for A2Model2_newvariables levels(m2data_new$tenure)<-c("F","L") # create dataset to estimate model 1 if (nrow(m1data_template)>nrow(m2data_new)) { m1data_new<-m1data_template[1:nrow(m2data_new),] } else { m1data_new<-m1data_template[sample(c(1:nrow(m1data_template)),nrow(m2data_new),replace=TRUE),] } m1data_new$date <- as.Date("2017-12-31") m1data_new$year <- factor("2017",levels=levels(m1data_new$year)) m1data_new$propertytype <- m2data_new$propertytype m1data_new$newbuild <- factor("Y",levels=levels(m1data_template$newbuild)) m1data_new$tenure <- m2data_new$tenure m1data_new$total_floor_area <- m2data_new$total_floor_area m1data_new$latitude <- m2data_new$latitude m1data_new$longitude <- m2data_new$longitude # create interaction (lat_long) m1data_new <- cbind(m1data_new,m1data_new$latitudem1data_new$longitude) i1 <- grep("m1data",colnames(m1data_new)) colnames(m1data_new)[i1] <- "lat_long" # predict location_value for new settlement # iold = indexes of points in m2data that are in the region defined by envelope of m2data_new p1<-SpatialPoints(m2data_new[,c("longitude","latitude")],CRS(wgs.84)) p2<-SpatialPoints(m2data[,c("longitude","latitude")],CRS(wgs.84)) poly1<-gEnvelope(p1) poly2<-gBuffer(poly1,width=0.1) iold<-gIntersects(poly1,p2,byid=TRUE) if (sum(iold)<100) { iold<-gIntersects(poly2,p2,byid=TRUE) } if (sum(iold)<100) { laname<-droplevels(m2data_new$laname) iold <- rep(FALSE,length=nrow(m2data)) for (i1 in levels(laname)) { itemp <- levels(m2data$laname)[m2data$laname]==i1 iold[itemp]<-TRUE } } tempdata<-m2data[iold[,1],] if (nrow(tempdata)>1000) { isample<-sample(c(1:nrow(tempdata)),size=1000,replace=F) }else { isample<-c(1:nrow(tempdata)) } np_location_value <-npreg(location_value~latitude+longitude,data=tempdata[isample,]) m2data_new$location_value <-predict(np_location_value,newdata=m2data_new) # Restricted land percentage m2data_new$restrictedland_pct<-mean(tempdata$restrictedland_pct) # 1) imdrank # 2) imddecile # 3) prob_4band # 4) noiseclass # 5) roadnoise # 6) greenbelt i1<-sample(c(1:sum(iold)),size=nrow(m2data_new),replace=TRUE) m2data_new$imdrank<-tempdata$imdrank[i1] m2data_new$imddecile<-tempdata$imddecile[i1] m2data_new$prob_4band<-tempdata$prob_4band[i1] m2data_new$noiseclass<-tempdata$noiseclass[i1] m2data_new$roadnoise<-tempdata$roadnoise[i1] m2data_new$greenbelt<-tempdata$greenbelt[i1] # Impute postal_town and (town_lon,town_lat) using tempdata postal_town<-knn(tempdata[,c("longitude","latitude")],m2data_new[,c("longitude","latitude")], tempdata[,"postal_town"],k=1) postal_town<-data.frame(postal_town) names(postal_town)<-"postal_town" postal_town<-join(postal_town,tempdata[,c("postal_town","town_lon","town_lat")], by="postal_town",type="left",match="first") m2data_new[,c("postal_town","town_lon","town_lat")]<-postal_town # Compute # 1) travel times to destinations # 2) travel time to postal_town # 3) distance to destinations # 4) distance to coast # 5) distance to AONB # 6) distance to national park # 7) distance to motorways # 8) distance to A road # 9) distance to nearest rail station m2data_new<-A2Model2_newvariables(m2data_new,dest,convexhull,region_id,dirs, drop_outlier=FALSE,basis=travelmodelbasis) # load spline details and compute splines load(file=paste0(dirs$outdir,"/m2dataspline.RData")) for (i1 in 1:length(m2dataspline$varlist)) { i2<-grep(m2dataspline$varlist[i1],colnames(m2data_new)) tempknots<-m2dataspline$knots[[i1]] m2data_new$tempB<-bSpline(m2data_new[,m2dataspline$varlist[i1]], knots=tempknots, degree=m2dataspline$degree[i1],intercept=FALSE) iTempB<-grep("tempB",colnames(m2data_new)) names(m2data_new)[iTempB]<-paste0("spline_",m2dataspline$varlist[i1]) } # summary statistics if (title!="none") { stargazer(tempdata[,m2ols0$varlist], m2data_new[,m2ols0$varlist],title=title, align=TRUE, out.header=TRUE,digits=4, out=paste0(dirs$outdir,"/",outfile)) } load(file=paste0(dirs$datadir,"/m1data.RData")) if (nrow(m1data)>nrow(m1data_new)) { # Extract subset of m1data same size as m1data_new n1<-nrow(m1data) n2<-nrow(m1data_new) set.seed(569472) i1<-sample(c(1:n1),size=n2) m1data<-m1data[i1,] } else if (nrow(m1data_new)>nrow(m1data)) { # m1data_new has more rows than m1data # create sample (with replacement) from m1data and # set size equal to size of m1data_new n1<=nrow(m1data_new) n2<-nrow(m1data) set.seed(569471) i1<-sample(c(1:n2),size=n1,replace=TRUE) m1data<-m1data[i1,] } outdata<-list(m1data_new,m2data_new,m1data) names(outdata)<-c("m1data_new","m2data_new","m1data_old") options(warn=default_warn) return(outdata) }	/code/oldversions/v3_20180424/model/A4CreateSettlement.R	no_license	UCL/provis	R	false	false	6,903	r	#' A4CreateSettlement(region_id,dirs,filename,title,outfile,m2data_new) #' Create data frames for new settlement and predict prices #' #' @param region_id id number for region #' @param dirs list of directories #' @param filename .csv file containing details of settlement #' @param m2data_new input base dataframe for new settlement #' @param travelmodelbasis c("cheb","glp","tensor") #' @param title title of table of summary stats #' @param outfile output file #' @return newdata list containing (m1data_new,m2data_new) #' @keywords new settlement #' @export #' @examples #' newdata <- A4CreateSettlement(region_id = 1,dirs,filename = "Bedford.csv",title,outfile) #' newdata <- A4CreateSettlement(region_id = 1,dirs,m2data_new = m2data_base) A4CreateSettlement<-function(region_id,dirs,filename,m2data_new,travelmodelbasis="cheb", title="none",outfile="none") { default_warn<-getOption("warn") options(warn=-1) # proj_4string for spatial objects wgs.84 <- '+proj=longlat +datum=WGS84 +no_defs +ellps=WGS84 +towgs84=0,0,0' if (!missing(filename)) { # Load New settlement data # example: filename<-"Bedford.csv" m2data_new<-read.csv(paste0(dirs$newdatadir,"/",filename), header=TRUE) } else if (missing(filename) & missing(m2data_new)) { stop("Error in A4CreateSettlement. Must input either 'filename' or 'm2data_new'.") } DestinationFile <- paste0(dirs$datadir,"/destinations",region_id,"B.csv") dest <- read.csv(DestinationFile) load(paste0(dirs$newdatadir,"/m1data_template.RData")) load(paste0(dirs$datadir,"/m2data2.RData")) load(paste0(dirs$datadir,"/convexhull.RData")) # used for A2Model2_newvariables levels(m2data_new$tenure)<-c("F","L") # create dataset to estimate model 1 if (nrow(m1data_template)>nrow(m2data_new)) { m1data_new<-m1data_template[1:nrow(m2data_new),] } else { m1data_new<-m1data_template[sample(c(1:nrow(m1data_template)),nrow(m2data_new),replace=TRUE),] } m1data_new$date <- as.Date("2017-12-31") m1data_new$year <- factor("2017",levels=levels(m1data_new$year)) m1data_new$propertytype <- m2data_new$propertytype m1data_new$newbuild <- factor("Y",levels=levels(m1data_template$newbuild)) m1data_new$tenure <- m2data_new$tenure m1data_new$total_floor_area <- m2data_new$total_floor_area m1data_new$latitude <- m2data_new$latitude m1data_new$longitude <- m2data_new$longitude # create interaction (lat_long) m1data_new <- cbind(m1data_new,m1data_new$latitudem1data_new$longitude) i1 <- grep("m1data",colnames(m1data_new)) colnames(m1data_new)[i1] <- "lat_long" # predict location_value for new settlement # iold = indexes of points in m2data that are in the region defined by envelope of m2data_new p1<-SpatialPoints(m2data_new[,c("longitude","latitude")],CRS(wgs.84)) p2<-SpatialPoints(m2data[,c("longitude","latitude")],CRS(wgs.84)) poly1<-gEnvelope(p1) poly2<-gBuffer(poly1,width=0.1) iold<-gIntersects(poly1,p2,byid=TRUE) if (sum(iold)<100) { iold<-gIntersects(poly2,p2,byid=TRUE) } if (sum(iold)<100) { laname<-droplevels(m2data_new$laname) iold <- rep(FALSE,length=nrow(m2data)) for (i1 in levels(laname)) { itemp <- levels(m2data$laname)[m2data$laname]==i1 iold[itemp]<-TRUE } } tempdata<-m2data[iold[,1],] if (nrow(tempdata)>1000) { isample<-sample(c(1:nrow(tempdata)),size=1000,replace=F) }else { isample<-c(1:nrow(tempdata)) } np_location_value <-npreg(location_value~latitude+longitude,data=tempdata[isample,]) m2data_new$location_value <-predict(np_location_value,newdata=m2data_new) # Restricted land percentage m2data_new$restrictedland_pct<-mean(tempdata$restrictedland_pct) # 1) imdrank # 2) imddecile # 3) prob_4band # 4) noiseclass # 5) roadnoise # 6) greenbelt i1<-sample(c(1:sum(iold)),size=nrow(m2data_new),replace=TRUE) m2data_new$imdrank<-tempdata$imdrank[i1] m2data_new$imddecile<-tempdata$imddecile[i1] m2data_new$prob_4band<-tempdata$prob_4band[i1] m2data_new$noiseclass<-tempdata$noiseclass[i1] m2data_new$roadnoise<-tempdata$roadnoise[i1] m2data_new$greenbelt<-tempdata$greenbelt[i1] # Impute postal_town and (town_lon,town_lat) using tempdata postal_town<-knn(tempdata[,c("longitude","latitude")],m2data_new[,c("longitude","latitude")], tempdata[,"postal_town"],k=1) postal_town<-data.frame(postal_town) names(postal_town)<-"postal_town" postal_town<-join(postal_town,tempdata[,c("postal_town","town_lon","town_lat")], by="postal_town",type="left",match="first") m2data_new[,c("postal_town","town_lon","town_lat")]<-postal_town # Compute # 1) travel times to destinations # 2) travel time to postal_town # 3) distance to destinations # 4) distance to coast # 5) distance to AONB # 6) distance to national park # 7) distance to motorways # 8) distance to A road # 9) distance to nearest rail station m2data_new<-A2Model2_newvariables(m2data_new,dest,convexhull,region_id,dirs, drop_outlier=FALSE,basis=travelmodelbasis) # load spline details and compute splines load(file=paste0(dirs$outdir,"/m2dataspline.RData")) for (i1 in 1:length(m2dataspline$varlist)) { i2<-grep(m2dataspline$varlist[i1],colnames(m2data_new)) tempknots<-m2dataspline$knots[[i1]] m2data_new$tempB<-bSpline(m2data_new[,m2dataspline$varlist[i1]], knots=tempknots, degree=m2dataspline$degree[i1],intercept=FALSE) iTempB<-grep("tempB",colnames(m2data_new)) names(m2data_new)[iTempB]<-paste0("spline_",m2dataspline$varlist[i1]) } # summary statistics if (title!="none") { stargazer(tempdata[,m2ols0$varlist], m2data_new[,m2ols0$varlist],title=title, align=TRUE, out.header=TRUE,digits=4, out=paste0(dirs$outdir,"/",outfile)) } load(file=paste0(dirs$datadir,"/m1data.RData")) if (nrow(m1data)>nrow(m1data_new)) { # Extract subset of m1data same size as m1data_new n1<-nrow(m1data) n2<-nrow(m1data_new) set.seed(569472) i1<-sample(c(1:n1),size=n2) m1data<-m1data[i1,] } else if (nrow(m1data_new)>nrow(m1data)) { # m1data_new has more rows than m1data # create sample (with replacement) from m1data and # set size equal to size of m1data_new n1<=nrow(m1data_new) n2<-nrow(m1data) set.seed(569471) i1<-sample(c(1:n2),size=n1,replace=TRUE) m1data<-m1data[i1,] } outdata<-list(m1data_new,m2data_new,m1data) names(outdata)<-c("m1data_new","m2data_new","m1data_old") options(warn=default_warn) return(outdata) }
#!/usr/bin/env Rscript # Read me ---- # Modified version of # "GBM Model IUCN Region prob expansion outcome Two-step 24.August.R" plus # "GBM 22.Sept Crop_MC.R" and "GBM 22.Sept Pasture_MC.R" # I have changed some of the variable names to make them slightly more # intelligible when it comes to the land-clearance loop # Some of this comes from "ProbabilitiesOfLandClearance_Current.R" # # This version (16 October) fits the pasture GBM after the cropland one # AND fits a trimmed-down version of the GBM: # - Does not include ISO Numeric but does include overall land demand # - Fits a global model (not separate models to countries that have had cropland expansion, # compared to contraction) # Packages ----- library(plyr) library(tidyverse) library(reshape2) library(caret) library(pROC) library(gbm) library(e1071) library(glmnet) library(raster) library(rgdal) library(gridExtra) library(doMC) library(dplyr) library(plyr) library(nnet) library(DHARMa) library(SuppDists) registerDoMC(cores = 4) # Clean up ----- rm(list = ls()) # change cutoff for where we denote if a cell has experienced a change in crop extent cutoff <- .025 # getting list of GBM file names setwd("/Users/maclark/Desktop/Mike's Files/GBM Data Files") file.list <- list.files(path = ".") ### Prep: creating lists used to assign model outputs # creating list used to assign values to model output if cells experienced a change in cropland extent region_list <- gsub("GBM.Data.22.Feb.","",file.list) region_list <- gsub(".csv","",region_list) region_list <- as.character(region_list) region_list_model_change <- paste(gsub(" ","",region_list),"model_change",sep = "_") # list used to assign values to model output for model that estimates the change in cropland extent by cell region_list_model_extentchange_increase <- paste(gsub(" ","",region_list),"model_extentchange_increase",sep = "_") region_list_model_extentchange_decrease <- paste(gsub(" ","",region_list),"model_extentchange_decrease",sep = "_") # Data prep: Set predictor names ---- # I am selecting the columns by name not index to account for possible changes # This is currently only used to test for scaled predictors predictor_vars_pasture <- c("dist_50k", "ag_suitability", "PA_binary", "prop_adj_to_predict_from_pasture", "prop_to_predict_from_pasture", "prop_to_predict_from_cell_delta_pasture", "prop_to_predict_from_crop") # And plot variables to test residuals plot_vars_crop <- c('dist_50k_log' , 'dist_50k_log_sq' , 'ag_suitability' , 'PA_binary', 'prop_to_predict_from_crop' , 'prop_crop_sq' , 'prop_to_predict_from_pasture' , 'prop_pasture_sq' , 'prop_to_predict_from_cell_delta_pasture' , 'prop_cell_delta_pasture_sq', "prop_adj_to_predict_from_pasture", "prop_adj_pasture_sq", 'ISO_numeric') # creating lists to savemodels change_list_crop <- list() # first model step proportion_list_crop_increase <- list() # second model step proportion_list_crop_decrease <- list() # second model step # Creating list of names used to save files file.names.save <- paste(region_list, "_7March_Cutoff_025_Crop.rda", sep = "") mods.prob <- list() mods.increase <- list() mods.decrease <- list() coef.prob <- list() coef.increase <- list() coef.decrease <- list() t1 = Sys.time() ### big loop to cycle through each file in file.list for (k in 8:9) { print(region_list[k]) # importing files dat_orig <- read.csv(file.list[k], header = TRUE, stringsAsFactors = FALSE) # All non PA areas have value of 0 dat_orig$PA.Binary[-which(dat_orig$PA.Binary == 1)] <- 0 # creating columns for for change in crop between 2002 and 2007 and 2007 and 2012 dat_orig$pasture_extent_change_2007.2002 <- dat_orig$Prop.Pasture.2007 - dat_orig$Prop.Pasture.2002 dat_orig$pasture_extent_change_2012.2007 <- dat_orig$Prop.Pasture.2012 - dat_orig$Prop.Pasture.2007 # creating column for has_changed_crop between 2007 and 2012 dat_orig$has_changed_pasture_2012.2007 <- NA dat_orig$has_changed_pasture_2012.2007[dat_orig$pasture_extent_change_2012.2007 >= cutoff] <- "Increase" dat_orig$has_changed_pasture_2012.2007[dat_orig$pasture_extent_change_2012.2007 <= -cutoff] <- "Decrease" dat_orig$has_changed_pasture_2012.2007[abs(dat_orig$pasture_extent_change_2012.2007) < cutoff] <- "aNoChange" # Data prep: Remove unnecessary columns, rename predictor_vars ---- # I am renaming a) for consistency b) so that we can more easily understand dat_orig <- dplyr::select(dat_orig, row_index = Row.Index, ISO_numeric = ISO.Numeric, IUCN_region = IUCN.Region, dist_50k = Dist.50k, ag_suitability = Ag.suitability, PA_binary = PA.Binary, change_demand_crop = CountryIncrease.Crop.2002.2007, prop_adj_to_predict_from_pasture = Prop.AdjacentPasture.2007, prop_to_predict_from_crop = Prop.Crop.2007, prop_to_predict_from_cell_delta_pasture = pasture_extent_change_2007.2002, pasture_extent_change_2012.2007 = pasture_extent_change_2012.2007, prop_to_predict_from_pasture = Prop.Pasture.2007, prop_pasture_2002 = Prop.Pasture.2002, prop_pasture_2012 = Prop.Pasture.2012, prop_change_cell_pasture_2007.2012 = pasture_extent_change_2012.2007, has_changed_pasture = has_changed_pasture_2012.2007, GDD_10c = GDD_10c) # Data prep: Getting model data # Limiting to specific variables and complete cases dat_mod <- dat_orig[,c(predictor_vars_pasture, "has_changed_pasture", "prop_change_cell_pasture_2007.2012","ISO_numeric")] dat_mod <- dat_mod[complete.cases(dat_mod),] # Removing original dat rm(dat_orig) # Adding columns for square transformations dat_mod$prop_crop_sq <- dat_mod$prop_to_predict_from_crop^2 dat_mod$prop_pasture_sq <- dat_mod$prop_to_predict_from_pasture^2 dat_mod$prop_cell_delta_pasture_sq <- dat_mod$prop_to_predict_from_cell_delta_pasture^2 dat_mod$prop_adj_pasture_sq <- dat_mod$prop_adj_to_predict_from_pasture^2 # Adding columns for log transformations dat_mod$dist_50k_log <- log(dat_mod$dist_50k + .001) dat_mod$dist_50k_log_sq <- dat_mod$dist_50k_log^2 # dat_mod$ISO_numeric <- as.character(dat_mod$ISO_numeric) # Getting multinomial model outcomeName <- "has_changed_pasture" # outcome factor variable # Attaching data set # Getting multinomial regression model # Getting multinomial regression model objModel <- multinom(has_changed_pasture ~ dist_50k_log + dist_50k_log_sq + ag_suitability + PA_binary + prop_to_predict_from_crop + prop_crop_sq + prop_to_predict_from_pasture + prop_pasture_sq + prop_to_predict_from_cell_delta_pasture + prop_cell_delta_pasture_sq + prop_adj_to_predict_from_pasture + prop_adj_pasture_sq + factor(ISO_numeric, ordered = FALSE), dat = dat_mod, model = FALSE, maxit = 250) coef.multinom <- coef(objModel) # # coef.prob[[region_list[k]]] <- as.data.frame(exp(coef(objModel))) # mods.prob[[region_list[k]]] <- objModel # # # Changing outcome name for extent models # outcomeName <- "prop_change_cell_crop_2007.2012" # Processing: Creating data frames that only contains cells which have increased or decreasd in extent dat_region_increase <- dat_mod[dat_mod$prop_change_cell_pasture >= cutoff,] dat_region_decrease <- dat_mod[dat_mod$prop_change_cell_pasture <= -cutoff,] # removing data rm(dat_mod) # Dropping rows with values <0 for increaes and > 0 for decrease dat_region_increase <- dat_region_increase[dat_region_increase$prop_change_cell_pasture_2007.2012 >= 0,] dat_region_decrease <- dat_region_decrease[dat_region_decrease$prop_change_cell_pasture_2007.2012 <= 0,] # arcsining response variable # dat_region_increase$prop_change_cell_crop_2007.2012 <- asin(sqrt(dat_region_increase$prop_change_cell_crop_2007.2012)) # dat_region_decrease$prop_change_cell_crop_2007.2012 <- asin(sqrt(abs(dat_region_decrease$prop_change_cell_crop_2007.2012))) # Getting model for extent increase objModel_increase <- glm(prop_change_cell_pasture_2007.2012 ~ dist_50k_log + dist_50k_log_sq + ag_suitability + PA_binary + prop_to_predict_from_crop + prop_crop_sq + prop_to_predict_from_pasture + prop_pasture_sq + prop_to_predict_from_cell_delta_pasture + prop_cell_delta_pasture_sq + prop_adj_to_predict_from_pasture + prop_adj_pasture_sq + factor(ISO_numeric, ordered = FALSE), family = Gamma(link = 'log'), dat = dat_region_increase, model = FALSE, control = list(maxit = 250)) coef.increase <- as.data.frame(coef(objModel_increase)) # # # # plot(objModel_increase, # # main = paste(region_list[k], # # "Increase")) # # And getting model for extent decrease # # # Getting absolute of decrease in crop extent # dat_region_decrease$prop_change_cell_pasture_2007.2012 <- abs(dat_region_decrease$prop_change_cell_pasture_2007.2012) # objModel_decrease <- glm(prop_change_cell_pasture_2007.2012 ~ # dist_50k_log + # dist_50k_log_sq + # ag_suitability + # PA_binary + # prop_to_predict_from_crop + # prop_crop_sq + # prop_to_predict_from_pasture + # prop_pasture_sq + # prop_to_predict_from_cell_delta_pasture + # prop_cell_delta_pasture_sq + # prop_adj_to_predict_from_pasture + # prop_adj_pasture_sq + # factor(ISO_numeric, ordered = FALSE), # family = Gamma(link = 'log'), # dat = dat_region_decrease, # model = FALSE, # control = list(maxit = 250)) # # coef.decrease <- as.data.frame(coef(objModel_decrease)) # plot(objModel_decrease, # main = paste(region_list[k], # "Decrease")) # Simulating results and plotting # simincrease <- simulateResiduals(objModel_increase, n=250) # # # And plotting simulated residuals # graphics.off() # removing plots # par(mfrow = c(1,2)) # updating graphical parameters # # And plotting # png(file = paste("/Users/maclark/Desktop/Mike's Files/GBM Model Outputs/8_March/Plots/", # region_list[k], # "Sim_Increase_Gamma.png", # sep = ""), # height = 10, width = 20, units = 'cm', res = 300) # plotSimulatedResiduals(simincrease) # dev.off() # # # And plotting simulated residuals for each predictor variable # graphics.off() # removing plots # # And plotting individual coefficients # for(var.names in 1:length(plot_vars_crop)) { # png(file = paste("/Users/maclark/Desktop/Mike's Files/GBM Model Outputs/8_March/Plots/", # region_list[k], # plot_vars_crop[var.names], # "Sim_Increase_Gamma.png", # sep = ""), # height = 10, width = 20, units = 'cm', res = 300) # plotResiduals(dat_region_increase[[plot_vars_crop[var.names]]], # simincrease$scaledResiduals, # main = plot_vars_crop[var.names]) # dev.off() # Saving plots # } # removing from memory # rm(simincrease, dat_region_increase) # # # For decreasing files # simdecrease <- simulateResiduals(objModel_decrease, n=250) # # And removing plots from R stuido # graphics.off() # par(mfrow = c(1,2)) # updating graphical parameters # # # png(file = paste("/Users/maclark/Desktop/Mike's Files/GBM Model Outputs/8_March/Plots/", # region_list[k], # "Sim_Decrease_Gamma.png", # sep = ""), # height = 10, width = 20, units = 'cm', res = 300) # plotSimulatedResiduals(simdecrease) # dev.off() # # # And plotting simulated residuals for each predictor variable # graphics.off() # removing plots # # for(var.names in 1:length(plot_vars_crop)) { # # png(file = paste("/Users/maclark/Desktop/Mike's Files/GBM Model Outputs/8_March/Plots/", # # region_list[k], # # plot_vars_crop[var.names], # # "Sim_Decrease_Gamma.png", # # sep = ""), # # height = 10, width = 20, units = 'cm', res = 300) # # plotResiduals(dat_region_decrease[[plot_vars_crop[var.names]]], # # simdecrease$scaledResiduals, # # main = plot_vars_crop[var.names]) # # dev.off() # Saving plots # # } # # And removing plots to (hopefully) increase speed # graphics.off() # Removing from memory # rm(simdecrease, dat_region_decrease) save(objModel_increase, objModel, file = paste("/Users/maclark/Desktop/Mike's Files/GBM Model Outputs/8_March/Gamma_Log/", region_list[k], "_Gamma_Link_Log_Multinom_Pasture_Model.rda", sep = "")) rm(objModel_increase) # save(simincrease, simdecrease, # file = paste("/Users/maclark/Desktop/Mike's Files/GBM Model Outputs/8_March/", # region_list[k], # "_Gamma_Link_Identity_Simulations.rda", # sep = "")) save(coef.increase, coef.multinom, file = paste("/Users/maclark/Desktop/Mike's Files/GBM Model Outputs/8_March/Gamma_Log/", region_list[k], "_Gamma_Link_Log_Multinom_Pasture_Coefs.rda", sep = "")) } Sys.time() - t1 quit(save = 'no')	/Scripts/AnalysisScripts/2_Scripts/Gamma_Oceania_SAs_Pasture.R	no_license	hommedesmuffins/LandExpansionBiodiversity	R	false	false	15,503	r	#!/usr/bin/env Rscript # Read me ---- # Modified version of # "GBM Model IUCN Region prob expansion outcome Two-step 24.August.R" plus # "GBM 22.Sept Crop_MC.R" and "GBM 22.Sept Pasture_MC.R" # I have changed some of the variable names to make them slightly more # intelligible when it comes to the land-clearance loop # Some of this comes from "ProbabilitiesOfLandClearance_Current.R" # # This version (16 October) fits the pasture GBM after the cropland one # AND fits a trimmed-down version of the GBM: # - Does not include ISO Numeric but does include overall land demand # - Fits a global model (not separate models to countries that have had cropland expansion, # compared to contraction) # Packages ----- library(plyr) library(tidyverse) library(reshape2) library(caret) library(pROC) library(gbm) library(e1071) library(glmnet) library(raster) library(rgdal) library(gridExtra) library(doMC) library(dplyr) library(plyr) library(nnet) library(DHARMa) library(SuppDists) registerDoMC(cores = 4) # Clean up ----- rm(list = ls()) # change cutoff for where we denote if a cell has experienced a change in crop extent cutoff <- .025 # getting list of GBM file names setwd("/Users/maclark/Desktop/Mike's Files/GBM Data Files") file.list <- list.files(path = ".") ### Prep: creating lists used to assign model outputs # creating list used to assign values to model output if cells experienced a change in cropland extent region_list <- gsub("GBM.Data.22.Feb.","",file.list) region_list <- gsub(".csv","",region_list) region_list <- as.character(region_list) region_list_model_change <- paste(gsub(" ","",region_list),"model_change",sep = "_") # list used to assign values to model output for model that estimates the change in cropland extent by cell region_list_model_extentchange_increase <- paste(gsub(" ","",region_list),"model_extentchange_increase",sep = "_") region_list_model_extentchange_decrease <- paste(gsub(" ","",region_list),"model_extentchange_decrease",sep = "_") # Data prep: Set predictor names ---- # I am selecting the columns by name not index to account for possible changes # This is currently only used to test for scaled predictors predictor_vars_pasture <- c("dist_50k", "ag_suitability", "PA_binary", "prop_adj_to_predict_from_pasture", "prop_to_predict_from_pasture", "prop_to_predict_from_cell_delta_pasture", "prop_to_predict_from_crop") # And plot variables to test residuals plot_vars_crop <- c('dist_50k_log' , 'dist_50k_log_sq' , 'ag_suitability' , 'PA_binary', 'prop_to_predict_from_crop' , 'prop_crop_sq' , 'prop_to_predict_from_pasture' , 'prop_pasture_sq' , 'prop_to_predict_from_cell_delta_pasture' , 'prop_cell_delta_pasture_sq', "prop_adj_to_predict_from_pasture", "prop_adj_pasture_sq", 'ISO_numeric') # creating lists to savemodels change_list_crop <- list() # first model step proportion_list_crop_increase <- list() # second model step proportion_list_crop_decrease <- list() # second model step # Creating list of names used to save files file.names.save <- paste(region_list, "_7March_Cutoff_025_Crop.rda", sep = "") mods.prob <- list() mods.increase <- list() mods.decrease <- list() coef.prob <- list() coef.increase <- list() coef.decrease <- list() t1 = Sys.time() ### big loop to cycle through each file in file.list for (k in 8:9) { print(region_list[k]) # importing files dat_orig <- read.csv(file.list[k], header = TRUE, stringsAsFactors = FALSE) # All non PA areas have value of 0 dat_orig$PA.Binary[-which(dat_orig$PA.Binary == 1)] <- 0 # creating columns for for change in crop between 2002 and 2007 and 2007 and 2012 dat_orig$pasture_extent_change_2007.2002 <- dat_orig$Prop.Pasture.2007 - dat_orig$Prop.Pasture.2002 dat_orig$pasture_extent_change_2012.2007 <- dat_orig$Prop.Pasture.2012 - dat_orig$Prop.Pasture.2007 # creating column for has_changed_crop between 2007 and 2012 dat_orig$has_changed_pasture_2012.2007 <- NA dat_orig$has_changed_pasture_2012.2007[dat_orig$pasture_extent_change_2012.2007 >= cutoff] <- "Increase" dat_orig$has_changed_pasture_2012.2007[dat_orig$pasture_extent_change_2012.2007 <= -cutoff] <- "Decrease" dat_orig$has_changed_pasture_2012.2007[abs(dat_orig$pasture_extent_change_2012.2007) < cutoff] <- "aNoChange" # Data prep: Remove unnecessary columns, rename predictor_vars ---- # I am renaming a) for consistency b) so that we can more easily understand dat_orig <- dplyr::select(dat_orig, row_index = Row.Index, ISO_numeric = ISO.Numeric, IUCN_region = IUCN.Region, dist_50k = Dist.50k, ag_suitability = Ag.suitability, PA_binary = PA.Binary, change_demand_crop = CountryIncrease.Crop.2002.2007, prop_adj_to_predict_from_pasture = Prop.AdjacentPasture.2007, prop_to_predict_from_crop = Prop.Crop.2007, prop_to_predict_from_cell_delta_pasture = pasture_extent_change_2007.2002, pasture_extent_change_2012.2007 = pasture_extent_change_2012.2007, prop_to_predict_from_pasture = Prop.Pasture.2007, prop_pasture_2002 = Prop.Pasture.2002, prop_pasture_2012 = Prop.Pasture.2012, prop_change_cell_pasture_2007.2012 = pasture_extent_change_2012.2007, has_changed_pasture = has_changed_pasture_2012.2007, GDD_10c = GDD_10c) # Data prep: Getting model data # Limiting to specific variables and complete cases dat_mod <- dat_orig[,c(predictor_vars_pasture, "has_changed_pasture", "prop_change_cell_pasture_2007.2012","ISO_numeric")] dat_mod <- dat_mod[complete.cases(dat_mod),] # Removing original dat rm(dat_orig) # Adding columns for square transformations dat_mod$prop_crop_sq <- dat_mod$prop_to_predict_from_crop^2 dat_mod$prop_pasture_sq <- dat_mod$prop_to_predict_from_pasture^2 dat_mod$prop_cell_delta_pasture_sq <- dat_mod$prop_to_predict_from_cell_delta_pasture^2 dat_mod$prop_adj_pasture_sq <- dat_mod$prop_adj_to_predict_from_pasture^2 # Adding columns for log transformations dat_mod$dist_50k_log <- log(dat_mod$dist_50k + .001) dat_mod$dist_50k_log_sq <- dat_mod$dist_50k_log^2 # dat_mod$ISO_numeric <- as.character(dat_mod$ISO_numeric) # Getting multinomial model outcomeName <- "has_changed_pasture" # outcome factor variable # Attaching data set # Getting multinomial regression model # Getting multinomial regression model objModel <- multinom(has_changed_pasture ~ dist_50k_log + dist_50k_log_sq + ag_suitability + PA_binary + prop_to_predict_from_crop + prop_crop_sq + prop_to_predict_from_pasture + prop_pasture_sq + prop_to_predict_from_cell_delta_pasture + prop_cell_delta_pasture_sq + prop_adj_to_predict_from_pasture + prop_adj_pasture_sq + factor(ISO_numeric, ordered = FALSE), dat = dat_mod, model = FALSE, maxit = 250) coef.multinom <- coef(objModel) # # coef.prob[[region_list[k]]] <- as.data.frame(exp(coef(objModel))) # mods.prob[[region_list[k]]] <- objModel # # # Changing outcome name for extent models # outcomeName <- "prop_change_cell_crop_2007.2012" # Processing: Creating data frames that only contains cells which have increased or decreasd in extent dat_region_increase <- dat_mod[dat_mod$prop_change_cell_pasture >= cutoff,] dat_region_decrease <- dat_mod[dat_mod$prop_change_cell_pasture <= -cutoff,] # removing data rm(dat_mod) # Dropping rows with values <0 for increaes and > 0 for decrease dat_region_increase <- dat_region_increase[dat_region_increase$prop_change_cell_pasture_2007.2012 >= 0,] dat_region_decrease <- dat_region_decrease[dat_region_decrease$prop_change_cell_pasture_2007.2012 <= 0,] # arcsining response variable # dat_region_increase$prop_change_cell_crop_2007.2012 <- asin(sqrt(dat_region_increase$prop_change_cell_crop_2007.2012)) # dat_region_decrease$prop_change_cell_crop_2007.2012 <- asin(sqrt(abs(dat_region_decrease$prop_change_cell_crop_2007.2012))) # Getting model for extent increase objModel_increase <- glm(prop_change_cell_pasture_2007.2012 ~ dist_50k_log + dist_50k_log_sq + ag_suitability + PA_binary + prop_to_predict_from_crop + prop_crop_sq + prop_to_predict_from_pasture + prop_pasture_sq + prop_to_predict_from_cell_delta_pasture + prop_cell_delta_pasture_sq + prop_adj_to_predict_from_pasture + prop_adj_pasture_sq + factor(ISO_numeric, ordered = FALSE), family = Gamma(link = 'log'), dat = dat_region_increase, model = FALSE, control = list(maxit = 250)) coef.increase <- as.data.frame(coef(objModel_increase)) # # # # plot(objModel_increase, # # main = paste(region_list[k], # # "Increase")) # # And getting model for extent decrease # # # Getting absolute of decrease in crop extent # dat_region_decrease$prop_change_cell_pasture_2007.2012 <- abs(dat_region_decrease$prop_change_cell_pasture_2007.2012) # objModel_decrease <- glm(prop_change_cell_pasture_2007.2012 ~ # dist_50k_log + # dist_50k_log_sq + # ag_suitability + # PA_binary + # prop_to_predict_from_crop + # prop_crop_sq + # prop_to_predict_from_pasture + # prop_pasture_sq + # prop_to_predict_from_cell_delta_pasture + # prop_cell_delta_pasture_sq + # prop_adj_to_predict_from_pasture + # prop_adj_pasture_sq + # factor(ISO_numeric, ordered = FALSE), # family = Gamma(link = 'log'), # dat = dat_region_decrease, # model = FALSE, # control = list(maxit = 250)) # # coef.decrease <- as.data.frame(coef(objModel_decrease)) # plot(objModel_decrease, # main = paste(region_list[k], # "Decrease")) # Simulating results and plotting # simincrease <- simulateResiduals(objModel_increase, n=250) # # # And plotting simulated residuals # graphics.off() # removing plots # par(mfrow = c(1,2)) # updating graphical parameters # # And plotting # png(file = paste("/Users/maclark/Desktop/Mike's Files/GBM Model Outputs/8_March/Plots/", # region_list[k], # "Sim_Increase_Gamma.png", # sep = ""), # height = 10, width = 20, units = 'cm', res = 300) # plotSimulatedResiduals(simincrease) # dev.off() # # # And plotting simulated residuals for each predictor variable # graphics.off() # removing plots # # And plotting individual coefficients # for(var.names in 1:length(plot_vars_crop)) { # png(file = paste("/Users/maclark/Desktop/Mike's Files/GBM Model Outputs/8_March/Plots/", # region_list[k], # plot_vars_crop[var.names], # "Sim_Increase_Gamma.png", # sep = ""), # height = 10, width = 20, units = 'cm', res = 300) # plotResiduals(dat_region_increase[[plot_vars_crop[var.names]]], # simincrease$scaledResiduals, # main = plot_vars_crop[var.names]) # dev.off() # Saving plots # } # removing from memory # rm(simincrease, dat_region_increase) # # # For decreasing files # simdecrease <- simulateResiduals(objModel_decrease, n=250) # # And removing plots from R stuido # graphics.off() # par(mfrow = c(1,2)) # updating graphical parameters # # # png(file = paste("/Users/maclark/Desktop/Mike's Files/GBM Model Outputs/8_March/Plots/", # region_list[k], # "Sim_Decrease_Gamma.png", # sep = ""), # height = 10, width = 20, units = 'cm', res = 300) # plotSimulatedResiduals(simdecrease) # dev.off() # # # And plotting simulated residuals for each predictor variable # graphics.off() # removing plots # # for(var.names in 1:length(plot_vars_crop)) { # # png(file = paste("/Users/maclark/Desktop/Mike's Files/GBM Model Outputs/8_March/Plots/", # # region_list[k], # # plot_vars_crop[var.names], # # "Sim_Decrease_Gamma.png", # # sep = ""), # # height = 10, width = 20, units = 'cm', res = 300) # # plotResiduals(dat_region_decrease[[plot_vars_crop[var.names]]], # # simdecrease$scaledResiduals, # # main = plot_vars_crop[var.names]) # # dev.off() # Saving plots # # } # # And removing plots to (hopefully) increase speed # graphics.off() # Removing from memory # rm(simdecrease, dat_region_decrease) save(objModel_increase, objModel, file = paste("/Users/maclark/Desktop/Mike's Files/GBM Model Outputs/8_March/Gamma_Log/", region_list[k], "_Gamma_Link_Log_Multinom_Pasture_Model.rda", sep = "")) rm(objModel_increase) # save(simincrease, simdecrease, # file = paste("/Users/maclark/Desktop/Mike's Files/GBM Model Outputs/8_March/", # region_list[k], # "_Gamma_Link_Identity_Simulations.rda", # sep = "")) save(coef.increase, coef.multinom, file = paste("/Users/maclark/Desktop/Mike's Files/GBM Model Outputs/8_March/Gamma_Log/", region_list[k], "_Gamma_Link_Log_Multinom_Pasture_Coefs.rda", sep = "")) } Sys.time() - t1 quit(save = 'no')
View(spain) library(dplyr) library(tidyr) library(devtools) come_back_tb <- spain%>% separate(HT, c('ht_h','ht_v'),sep='-')%>% separate(FT, c('ft_h','ft_v'),sep='-')%>% filter(abs(as.numeric(ht_h) - as.numeric(ht_v)) == 2 ) View(come_back_tb) come_back_tb <- come_back_tb%>% mutate( won = case_when(((as.numeric(ht_h) - as.numeric(ht_v)) * (as.numeric(ft_h)-as.numeric(ft_v)) > 0) ~ 'T', TRUE ~ 'F')) View(come_back_tb) come_back_tb <- come_back_tb%>% mutate( num = n() )%>% filter(won == 'T')%>% summarise( win_rate = n() / num )%>% distinct() View(come_back_tb) # احتمال برنده شدن تیمی که در نیمه اول دو گل جلو افتاده است	/Learn_Working_With_Data/q8.R	no_license	kian79/data_science_with_R	R	false	false	703	r	View(spain) library(dplyr) library(tidyr) library(devtools) come_back_tb <- spain%>% separate(HT, c('ht_h','ht_v'),sep='-')%>% separate(FT, c('ft_h','ft_v'),sep='-')%>% filter(abs(as.numeric(ht_h) - as.numeric(ht_v)) == 2 ) View(come_back_tb) come_back_tb <- come_back_tb%>% mutate( won = case_when(((as.numeric(ht_h) - as.numeric(ht_v)) * (as.numeric(ft_h)-as.numeric(ft_v)) > 0) ~ 'T', TRUE ~ 'F')) View(come_back_tb) come_back_tb <- come_back_tb%>% mutate( num = n() )%>% filter(won == 'T')%>% summarise( win_rate = n() / num )%>% distinct() View(come_back_tb) # احتمال برنده شدن تیمی که در نیمه اول دو گل جلو افتاده است
% Generated by roxygen2: do not edit by hand % Please edit documentation in R/securityhub_operations.R \name{securityhub_create_members} \alias{securityhub_create_members} \title{Creates a member association in Security Hub between the specified accounts and the account used to make the request, which is the master account} \usage{ securityhub_create_members(AccountDetails) } \arguments{ \item{AccountDetails}{[required] The list of accounts to associate with the Security Hub master account. For each account, the list includes the account ID and optionally the email address.} } \value{ A list with the following syntax:\preformatted{list( UnprocessedAccounts = list( list( AccountId = "string", ProcessingResult = "string" ) ) ) } } \description{ Creates a member association in Security Hub between the specified accounts and the account used to make the request, which is the master account. If you are integrated with Organizations, then the master account is the Security Hub administrator account that is designated by the organization management account. \code{\link[=securityhub_create_members]{create_members}} is always used to add accounts that are not organization members. For accounts that are part of an organization, \code{\link[=securityhub_create_members]{create_members}} is only used in the following cases: \itemize{ \item Security Hub is not configured to automatically add new accounts in an organization. \item The account was disassociated or deleted in Security Hub. } This action can only be used by an account that has Security Hub enabled. To enable Security Hub, you can use the \code{\link[=securityhub_enable_security_hub]{enable_security_hub}} operation. For accounts that are not organization members, you create the account association and then send an invitation to the member account. To send the invitation, you use the \code{\link[=securityhub_invite_members]{invite_members}} operation. If the account owner accepts the invitation, the account becomes a member account in Security Hub. Accounts that are part of an organization do not receive an invitation. They automatically become a member account in Security Hub. A permissions policy is added that permits the master account to view the findings generated in the member account. When Security Hub is enabled in a member account, findings are sent to both the member and master accounts. To remove the association between the master and member accounts, use the \code{\link[=securityhub_disassociate_from_master_account]{disassociate_from_master_account}} or \code{\link[=securityhub_disassociate_members]{disassociate_members}} operation. } \section{Request syntax}{ \preformatted{svc$create_members( AccountDetails = list( list( AccountId = "string", Email = "string" ) ) ) } } \keyword{internal}	/cran/paws.security.identity/man/securityhub_create_members.Rd	permissive	TWarczak/paws	R	false	true	2,854	rd	% Generated by roxygen2: do not edit by hand % Please edit documentation in R/securityhub_operations.R \name{securityhub_create_members} \alias{securityhub_create_members} \title{Creates a member association in Security Hub between the specified accounts and the account used to make the request, which is the master account} \usage{ securityhub_create_members(AccountDetails) } \arguments{ \item{AccountDetails}{[required] The list of accounts to associate with the Security Hub master account. For each account, the list includes the account ID and optionally the email address.} } \value{ A list with the following syntax:\preformatted{list( UnprocessedAccounts = list( list( AccountId = "string", ProcessingResult = "string" ) ) ) } } \description{ Creates a member association in Security Hub between the specified accounts and the account used to make the request, which is the master account. If you are integrated with Organizations, then the master account is the Security Hub administrator account that is designated by the organization management account. \code{\link[=securityhub_create_members]{create_members}} is always used to add accounts that are not organization members. For accounts that are part of an organization, \code{\link[=securityhub_create_members]{create_members}} is only used in the following cases: \itemize{ \item Security Hub is not configured to automatically add new accounts in an organization. \item The account was disassociated or deleted in Security Hub. } This action can only be used by an account that has Security Hub enabled. To enable Security Hub, you can use the \code{\link[=securityhub_enable_security_hub]{enable_security_hub}} operation. For accounts that are not organization members, you create the account association and then send an invitation to the member account. To send the invitation, you use the \code{\link[=securityhub_invite_members]{invite_members}} operation. If the account owner accepts the invitation, the account becomes a member account in Security Hub. Accounts that are part of an organization do not receive an invitation. They automatically become a member account in Security Hub. A permissions policy is added that permits the master account to view the findings generated in the member account. When Security Hub is enabled in a member account, findings are sent to both the member and master accounts. To remove the association between the master and member accounts, use the \code{\link[=securityhub_disassociate_from_master_account]{disassociate_from_master_account}} or \code{\link[=securityhub_disassociate_members]{disassociate_members}} operation. } \section{Request syntax}{ \preformatted{svc$create_members( AccountDetails = list( list( AccountId = "string", Email = "string" ) ) ) } } \keyword{internal}
#' An R6 Class to represent one or more Personal Weather Stations. #' @description An R6 Class to represent one or more Personal Weather Stations #' #' @docType class #' @field id A character vector containing 1 or more PWS ids. REQUIRED. #' @field lat A numeric vector containing lat coordiantes for PWS ids. REQUIRED. #' @field lon A numeric vector containing lat coordiantes for PWS ids. REQUIRED. #' @field neighborhood A character vector containing the neighborhoods of the PWSs (1 per PWS) #' @field city A character vector containing the cities of the PWSs (1 per PWS) #' @field state A character vector containing state codes of the PWSs (1 per PWS) #' @field country A character vector containing country codes of the PWSs (1 per PWS) #' @field distance_km An integer vector of the distance in km for each PWS from city. REQUIRED, but has a 0 default. #' @field distance_mi An integer vector of the distance in miles for each PWS from city #' @section Methods: #' \describe{ #' \item{\code{getId(pwsId)}}{This method uses \code{pwsId} to determine if to get some or all (if NA) of the ids in the class instance} #' \item{\code{getLat(pwsId)}}{This method uses \code{pwsId} to determine if to get some or all (if NA) of the latitudes in the class instance} #' \item{\code{getLon(pwsId)}}{This method uses \code{pwsId} to determine if to get some or all (if NA) of the longitudes in the class instance} #' \item{\code{getCity(pwsId)}}{This method uses \code{pwsId} to determine if to get some or all (if NA) of the cities in the class instance} #' \item{\code{getNeighborhood(pwsId)}}{This method uses \code{pwsId} to determine if to get some or all (if NA) of the neighborhoods in the class instance} #' \item{\code{getState(pwsId)}}{This method uses \code{pwsId} to determine if to get some or all (if NA) of the states in the class instance} #' \item{\code{getCountry(pwsId)}}{This method uses \code{pwsId} to determine if to get some or all (if NA) of the countries in the class instance} #' \item{\code{getDistance_km(pwsId)}}{This method uses \code{pwsId} to determine if to get some or all (if NA) of the distances in kms in the class instance} #' \item{\code{getDistance_mi(pwsId)}}{This method uses \code{pwsId} to determine if to get some or all (if NA) of the distances in miles in the class instance} #' \item{\code{getTibble(pwsId,pwsCity,pwsState,pwsDistanceLte)}}{This method uses \code{pwsId} as priority 1 by itself/only, \code{state} priority 2 (assumed in US) and/or \code{country} priority 3, then \code{city}, and \code{pwsDistanceLte} in km to return a tibble containing pws data} #' \item{\code{print()}}{This method prints the class in the manner or a tibble} #' \item{\code{plot(plottype)}}{This method \code{plottype} to determine whether p/pins or t/text (ids) to produce a plot of weather stations on a map using RgoogleMaps package} #' } #' @importFrom R6 R6Class #' @importFrom RgoogleMaps qbbox GetMap.bbox PlotOnStaticMap TextOnStaticMap MaxZoom #' @importFrom tibble tibble #' @examples #' data(pwsData) #' testr6 <- Pws$new( #' id = pwsData$id #' ,lat = pwsData$lat #' ,lon = pwsData$lon #' ,neighborhood = pwsData$neighborhood #' ,city = pwsData$city #' ,state = pwsData$state #' ,country = pwsData$country #' ,distance_km = pwsData$distance_km #' ,distance_mi = pwsData$distance_mi #' ) #' testr6$print() #' testr6$plot() #' @export ## ## begin mcaldwel code ## ##note - examples from https://github.com/wch/R6/issues/3 were used to document the class ##3 required elements - id, lat, lon, and distance_km (for later subsetting, but will default to 0) Pws <- R6::R6Class( "Pws" ,private = list( id = character(0) ,lat = numeric(0) ,lon = numeric(0) ,neighborhood = character(0) ,city = character(0) ,state = character(0) ,country = character(0) ,distance_km = integer(0) ,distance_mi = integer(0) ,valid = function( id ,lat ,lon ,neighborhood ,city ,state ,country ,distance_km ,distance_mi ) { #check required fields first #>0 if( length( id ) == 0 \| length( lat ) == 0 \| length( lon ) == 0 \| length( distance_km ) == 0 ) { return(FALSE) } #cannot be na anywhere if( any( is.na( id ) ) \| any( is.na( lat ) ) \| any( is.na( lon ) ) \| any( is.na( distance_km ) ) ) { return(FALSE) } #for type if( !is.character( id ) \| !is.numeric( lat ) \| !is.numeric( lon ) \| !is.numeric( distance_km ) ) { return(FALSE) } #now check the others if not all nas if( ( !all( is.na(neighborhood) ) & !is.character( neighborhood ) ) \| ( !all( is.na(city ) ) & !is.character( city ) ) \| ( !all( is.na(state ) ) & !is.character( state ) ) \| ( !all( is.na(country ) ) & !is.character( country ) ) \| ( !all( is.na(distance_mi ) ) & !is.numeric( distance_mi ) ) ){ return(FALSE) } #everything needs to match the length of id if( length( lat ) != length( id ) \| length( lon ) != length( id ) \| length( distance_km ) != length( id ) ) { return(FALSE) } if( ( !all( is.na(neighborhood) ) & length( neighborhood ) != length( id ) ) \| ( !all( is.na(city ) ) & length( city ) != length( id ) ) \| ( !all( is.na(state ) ) & length( state ) != length( id ) ) \| ( !all( is.na(country ) ) & length( country ) != length( id ) ) \| ( !all( is.na(distance_mi ) ) & length( distance_mi ) != length( id ) ) ){ return(FALSE) } #if made it to here, cleared checks TRUE } ) #end private list ,public = list( initialize = function( id ,lat = NA ,lon = NA ,neighborhood = NA ,city = NA ,state = NA ,country = NA ,distance_km = 0 ,distance_mi = 0 ) { if( !private$valid( id ,lat ,lon ,neighborhood ,city ,state ,country ,distance_km ,distance_mi )) { stop("BAD INPUT VALUES") } private$id <- id private$lat <- lat private$lon <- lon private$neighborhood <- neighborhood private$city <- city private$state <- state private$country <- country private$distance_km <- distance_km private$distance_mi <- distance_mi } #removed setters, will need to just create at instantiation by combining tibbles #either gets the entire vector specified, or only retrieves those with the id passed ,getId = function(pwsId = NA) { if( all(is.na(pwsId)) ){ private$id } else{ private$id[private$id %in% pwsId] } } ,getLat = function(pwsId = NA) { if( all(is.na(pwsId)) ){ private$lat } else{ private$lat[private$id %in% pwsId] } } ,getLon = function(pwsId = NA) { if( all(is.na(pwsId)) ){ private$lon } else{ private$lon[private$id %in% pwsId] } } ,getNeighborhood= function(pwsId = NA) { if( all(is.na(pwsId)) ){ private$neighborhood } else{ private$neighborhood[private$id %in% pwsId] } } ,getCity= function(pwsId = NA) { if( all(is.na(pwsId)) ){ private$city } else{ private$city[private$id %in% pwsId] } } ,getState= function(pwsId = NA) { if( all(is.na(pwsId)) ){ private$state } else{ private$state[private$id %in% pwsId] } } ,getCountry = function(pwsId = NA) { if( all(is.na(pwsId)) ){ private$country } else{ private$country[private$id %in% pwsId] } } ,getDistance_km= function(pwsId = NA) { if( all(is.na(pwsId)) ){ private$distance_km } else{ private$distance_km[private$id %in% pwsId] } } ,getDistance_mi= function(pwsId = NA) { if( all(is.na(pwsId)) ){ private$distance_mi } else{ private$distance_mi[private$id %in% pwsId] } } ,getTibble = function( pwsId = NA ,pwsCity = NA ,pwsState = NA ,pwsCountry = NA ,pwsDistanceLte = NA #assuming km - needs to be a single value ) { #only do for no pwsId, as that trumps everything else if( all(is.na(pwsId) ) ){ #first capture it as the entire vector, then reduce if needed pwsId = private$id #state trumps country and is assumed to be US if( !all( is.na( pwsState) ) & is.character( pwsState ) ){ pwsId <- pwsId[ pwsId %in% private$id[private$state %in% pwsState] ] } else if( !all( is.na( pwsCountry) ) & is.character( pwsCountry ) ){ pwsId <- pwsId[ pwsId %in% private$id[private$country %in% pwsCountry] ] } #now if a city, further narrow if( !all( is.na( pwsCity) ) & is.character( pwsCity ) ){ pwsId <- pwsId[ pwsId %in% private$id[private$city %in% pwsCity] ] } #now if distance was provided, narrow again, assume km if( !all( is.na(pwsDistanceLte) ) ){ if( length(pwsDistanceLte) != 1 \| !is.numeric(pwsDistanceLte) ){ stop("IF NOT NA, pwsDistanceLte MUST BE OF LENGTH 1 NUMERIC SCALAR") } pwsId <- pwsId[ pwsId %in% private$id[private$distance_km <= pwsDistanceLte] ] } } # end if all is.na(pwsId) else{ if( !is.character( pwsId ) ){ stop("IF NOT NA, pwsId MUST BE A CHARACTER TYPE") } } tibble::tibble( id = self$getId(pwsId) ,lat = self$getLat(pwsId) ,lon = self$getLon(pwsId) ,neighborhood = self$getNeighborhood(pwsId) ,city = self$getCity(pwsId) ,state = self$getState(pwsId) ,country = self$getCountry(pwsId) ,distance_km = self$getDistance_km(pwsId) ,distance_mi = self$getDistance_mi(pwsId) ) } ,print = function() { print( self$getTibble() ) } ,plot = function(plottype="t") { if( !( plottype %in% c("t","p") ) ){ stop("INVALID PLOT TYPE PASSED TO Pws class plot function") } #can only plot with a lat and long if( !any( is.na(private$lat) ) & !any( is.na(private$lon) ) ){ if( length(unique(private$id)) > 10){ message("Note: Plot can become cluttered with over 10 PWS ids") } bb <- RgoogleMaps::qbbox(lat = private$lat, lon = private$lon) #satellite, terrain, hybrid, and mobile are maptypes #zooming did not seem to be doing anything good, so took it out if(plottype=="t"){ pwsMap <- RgoogleMaps::GetMap.bbox( bb$lonR ,bb$latR ,destfile = "pwsMap.png" ,maptype="terrain" ,size=c(640,640) ) tmpMap <- RgoogleMaps::PlotOnStaticMap( pwsMap ,lat = private$lat ,lon = private$lon #,zoom=min(MaxZoom(latrange=bb$latR,lonrange=bb$lonR)) ,cex=0 ,pch=20 ,col=c("black") ) RgoogleMaps::TextOnStaticMap( pwsMap ,lat = private$lat ,lon = private$lon ,labels=private$id ,add=TRUE ,cex=0.8 ,col=c("red") ) } #end if plottype == t else if(plottype == "p"){ pwsMap <- RgoogleMaps::GetMap.bbox( bb$lonR ,bb$latR ,destfile = "pwsMap.png" ,maptype="terrain" ,markers = self$getTibble() ,size=c(640,640) ) RgoogleMaps::PlotOnStaticMap( pwsMap ,lat = private$lat ,lon = private$lon #,zoom=min(MaxZoom(latrange=bb$latR,lonrange=bb$lonR)) ,cex=0 ,pch=20 ,col=c("red") ) } #end if plottype == p } #end if have lat and lon for plotting } #end plot function ) # end public list ) #end class declaration ## ## end mcaldwel code ##	/weatherProject/R/Pws.R	no_license	DrRoad/Wunderground-Weather-Project	R	false	false	12,646	r	#' An R6 Class to represent one or more Personal Weather Stations. #' @description An R6 Class to represent one or more Personal Weather Stations #' #' @docType class #' @field id A character vector containing 1 or more PWS ids. REQUIRED. #' @field lat A numeric vector containing lat coordiantes for PWS ids. REQUIRED. #' @field lon A numeric vector containing lat coordiantes for PWS ids. REQUIRED. #' @field neighborhood A character vector containing the neighborhoods of the PWSs (1 per PWS) #' @field city A character vector containing the cities of the PWSs (1 per PWS) #' @field state A character vector containing state codes of the PWSs (1 per PWS) #' @field country A character vector containing country codes of the PWSs (1 per PWS) #' @field distance_km An integer vector of the distance in km for each PWS from city. REQUIRED, but has a 0 default. #' @field distance_mi An integer vector of the distance in miles for each PWS from city #' @section Methods: #' \describe{ #' \item{\code{getId(pwsId)}}{This method uses \code{pwsId} to determine if to get some or all (if NA) of the ids in the class instance} #' \item{\code{getLat(pwsId)}}{This method uses \code{pwsId} to determine if to get some or all (if NA) of the latitudes in the class instance} #' \item{\code{getLon(pwsId)}}{This method uses \code{pwsId} to determine if to get some or all (if NA) of the longitudes in the class instance} #' \item{\code{getCity(pwsId)}}{This method uses \code{pwsId} to determine if to get some or all (if NA) of the cities in the class instance} #' \item{\code{getNeighborhood(pwsId)}}{This method uses \code{pwsId} to determine if to get some or all (if NA) of the neighborhoods in the class instance} #' \item{\code{getState(pwsId)}}{This method uses \code{pwsId} to determine if to get some or all (if NA) of the states in the class instance} #' \item{\code{getCountry(pwsId)}}{This method uses \code{pwsId} to determine if to get some or all (if NA) of the countries in the class instance} #' \item{\code{getDistance_km(pwsId)}}{This method uses \code{pwsId} to determine if to get some or all (if NA) of the distances in kms in the class instance} #' \item{\code{getDistance_mi(pwsId)}}{This method uses \code{pwsId} to determine if to get some or all (if NA) of the distances in miles in the class instance} #' \item{\code{getTibble(pwsId,pwsCity,pwsState,pwsDistanceLte)}}{This method uses \code{pwsId} as priority 1 by itself/only, \code{state} priority 2 (assumed in US) and/or \code{country} priority 3, then \code{city}, and \code{pwsDistanceLte} in km to return a tibble containing pws data} #' \item{\code{print()}}{This method prints the class in the manner or a tibble} #' \item{\code{plot(plottype)}}{This method \code{plottype} to determine whether p/pins or t/text (ids) to produce a plot of weather stations on a map using RgoogleMaps package} #' } #' @importFrom R6 R6Class #' @importFrom RgoogleMaps qbbox GetMap.bbox PlotOnStaticMap TextOnStaticMap MaxZoom #' @importFrom tibble tibble #' @examples #' data(pwsData) #' testr6 <- Pws$new( #' id = pwsData$id #' ,lat = pwsData$lat #' ,lon = pwsData$lon #' ,neighborhood = pwsData$neighborhood #' ,city = pwsData$city #' ,state = pwsData$state #' ,country = pwsData$country #' ,distance_km = pwsData$distance_km #' ,distance_mi = pwsData$distance_mi #' ) #' testr6$print() #' testr6$plot() #' @export ## ## begin mcaldwel code ## ##note - examples from https://github.com/wch/R6/issues/3 were used to document the class ##3 required elements - id, lat, lon, and distance_km (for later subsetting, but will default to 0) Pws <- R6::R6Class( "Pws" ,private = list( id = character(0) ,lat = numeric(0) ,lon = numeric(0) ,neighborhood = character(0) ,city = character(0) ,state = character(0) ,country = character(0) ,distance_km = integer(0) ,distance_mi = integer(0) ,valid = function( id ,lat ,lon ,neighborhood ,city ,state ,country ,distance_km ,distance_mi ) { #check required fields first #>0 if( length( id ) == 0 \| length( lat ) == 0 \| length( lon ) == 0 \| length( distance_km ) == 0 ) { return(FALSE) } #cannot be na anywhere if( any( is.na( id ) ) \| any( is.na( lat ) ) \| any( is.na( lon ) ) \| any( is.na( distance_km ) ) ) { return(FALSE) } #for type if( !is.character( id ) \| !is.numeric( lat ) \| !is.numeric( lon ) \| !is.numeric( distance_km ) ) { return(FALSE) } #now check the others if not all nas if( ( !all( is.na(neighborhood) ) & !is.character( neighborhood ) ) \| ( !all( is.na(city ) ) & !is.character( city ) ) \| ( !all( is.na(state ) ) & !is.character( state ) ) \| ( !all( is.na(country ) ) & !is.character( country ) ) \| ( !all( is.na(distance_mi ) ) & !is.numeric( distance_mi ) ) ){ return(FALSE) } #everything needs to match the length of id if( length( lat ) != length( id ) \| length( lon ) != length( id ) \| length( distance_km ) != length( id ) ) { return(FALSE) } if( ( !all( is.na(neighborhood) ) & length( neighborhood ) != length( id ) ) \| ( !all( is.na(city ) ) & length( city ) != length( id ) ) \| ( !all( is.na(state ) ) & length( state ) != length( id ) ) \| ( !all( is.na(country ) ) & length( country ) != length( id ) ) \| ( !all( is.na(distance_mi ) ) & length( distance_mi ) != length( id ) ) ){ return(FALSE) } #if made it to here, cleared checks TRUE } ) #end private list ,public = list( initialize = function( id ,lat = NA ,lon = NA ,neighborhood = NA ,city = NA ,state = NA ,country = NA ,distance_km = 0 ,distance_mi = 0 ) { if( !private$valid( id ,lat ,lon ,neighborhood ,city ,state ,country ,distance_km ,distance_mi )) { stop("BAD INPUT VALUES") } private$id <- id private$lat <- lat private$lon <- lon private$neighborhood <- neighborhood private$city <- city private$state <- state private$country <- country private$distance_km <- distance_km private$distance_mi <- distance_mi } #removed setters, will need to just create at instantiation by combining tibbles #either gets the entire vector specified, or only retrieves those with the id passed ,getId = function(pwsId = NA) { if( all(is.na(pwsId)) ){ private$id } else{ private$id[private$id %in% pwsId] } } ,getLat = function(pwsId = NA) { if( all(is.na(pwsId)) ){ private$lat } else{ private$lat[private$id %in% pwsId] } } ,getLon = function(pwsId = NA) { if( all(is.na(pwsId)) ){ private$lon } else{ private$lon[private$id %in% pwsId] } } ,getNeighborhood= function(pwsId = NA) { if( all(is.na(pwsId)) ){ private$neighborhood } else{ private$neighborhood[private$id %in% pwsId] } } ,getCity= function(pwsId = NA) { if( all(is.na(pwsId)) ){ private$city } else{ private$city[private$id %in% pwsId] } } ,getState= function(pwsId = NA) { if( all(is.na(pwsId)) ){ private$state } else{ private$state[private$id %in% pwsId] } } ,getCountry = function(pwsId = NA) { if( all(is.na(pwsId)) ){ private$country } else{ private$country[private$id %in% pwsId] } } ,getDistance_km= function(pwsId = NA) { if( all(is.na(pwsId)) ){ private$distance_km } else{ private$distance_km[private$id %in% pwsId] } } ,getDistance_mi= function(pwsId = NA) { if( all(is.na(pwsId)) ){ private$distance_mi } else{ private$distance_mi[private$id %in% pwsId] } } ,getTibble = function( pwsId = NA ,pwsCity = NA ,pwsState = NA ,pwsCountry = NA ,pwsDistanceLte = NA #assuming km - needs to be a single value ) { #only do for no pwsId, as that trumps everything else if( all(is.na(pwsId) ) ){ #first capture it as the entire vector, then reduce if needed pwsId = private$id #state trumps country and is assumed to be US if( !all( is.na( pwsState) ) & is.character( pwsState ) ){ pwsId <- pwsId[ pwsId %in% private$id[private$state %in% pwsState] ] } else if( !all( is.na( pwsCountry) ) & is.character( pwsCountry ) ){ pwsId <- pwsId[ pwsId %in% private$id[private$country %in% pwsCountry] ] } #now if a city, further narrow if( !all( is.na( pwsCity) ) & is.character( pwsCity ) ){ pwsId <- pwsId[ pwsId %in% private$id[private$city %in% pwsCity] ] } #now if distance was provided, narrow again, assume km if( !all( is.na(pwsDistanceLte) ) ){ if( length(pwsDistanceLte) != 1 \| !is.numeric(pwsDistanceLte) ){ stop("IF NOT NA, pwsDistanceLte MUST BE OF LENGTH 1 NUMERIC SCALAR") } pwsId <- pwsId[ pwsId %in% private$id[private$distance_km <= pwsDistanceLte] ] } } # end if all is.na(pwsId) else{ if( !is.character( pwsId ) ){ stop("IF NOT NA, pwsId MUST BE A CHARACTER TYPE") } } tibble::tibble( id = self$getId(pwsId) ,lat = self$getLat(pwsId) ,lon = self$getLon(pwsId) ,neighborhood = self$getNeighborhood(pwsId) ,city = self$getCity(pwsId) ,state = self$getState(pwsId) ,country = self$getCountry(pwsId) ,distance_km = self$getDistance_km(pwsId) ,distance_mi = self$getDistance_mi(pwsId) ) } ,print = function() { print( self$getTibble() ) } ,plot = function(plottype="t") { if( !( plottype %in% c("t","p") ) ){ stop("INVALID PLOT TYPE PASSED TO Pws class plot function") } #can only plot with a lat and long if( !any( is.na(private$lat) ) & !any( is.na(private$lon) ) ){ if( length(unique(private$id)) > 10){ message("Note: Plot can become cluttered with over 10 PWS ids") } bb <- RgoogleMaps::qbbox(lat = private$lat, lon = private$lon) #satellite, terrain, hybrid, and mobile are maptypes #zooming did not seem to be doing anything good, so took it out if(plottype=="t"){ pwsMap <- RgoogleMaps::GetMap.bbox( bb$lonR ,bb$latR ,destfile = "pwsMap.png" ,maptype="terrain" ,size=c(640,640) ) tmpMap <- RgoogleMaps::PlotOnStaticMap( pwsMap ,lat = private$lat ,lon = private$lon #,zoom=min(MaxZoom(latrange=bb$latR,lonrange=bb$lonR)) ,cex=0 ,pch=20 ,col=c("black") ) RgoogleMaps::TextOnStaticMap( pwsMap ,lat = private$lat ,lon = private$lon ,labels=private$id ,add=TRUE ,cex=0.8 ,col=c("red") ) } #end if plottype == t else if(plottype == "p"){ pwsMap <- RgoogleMaps::GetMap.bbox( bb$lonR ,bb$latR ,destfile = "pwsMap.png" ,maptype="terrain" ,markers = self$getTibble() ,size=c(640,640) ) RgoogleMaps::PlotOnStaticMap( pwsMap ,lat = private$lat ,lon = private$lon #,zoom=min(MaxZoom(latrange=bb$latR,lonrange=bb$lonR)) ,cex=0 ,pch=20 ,col=c("red") ) } #end if plottype == p } #end if have lat and lon for plotting } #end plot function ) # end public list ) #end class declaration ## ## end mcaldwel code ##
% Generated by roxygen2: do not edit by hand % Please edit documentation in R/glasso_CV.R \name{robglasso} \alias{robglasso} \title{glasso with robust covariance estimations} \usage{ robglasso( data, covest = cov, rho = 0.1, CV = FALSE, k = 10, grids = 15, evaluation = negLLrobOmega, ... ) } \arguments{ \item{data}{raw data, should be a matrix or a data.frame, row as sample} \item{covest}{a function or name of a function (string) that takes a matrix to estimate covariance} \item{rho}{a scalar or vector of tuning parameters to be chosen, if CV=FALSE, should be a scalar, if CV=TRUE scalar input will be override and tuning parameter will be chosen based on CV} \item{CV}{bool, whether doing cross validation for tuning parameter, if set to TRUE and rho is a scalar, the candidate will be chosen automatically by log spacing between 0.01 max covariance and max covariance with number of grids} \item{k}{fold for cross validation if applicable} \item{grids}{number of candidate tuning parameters in cross validation} \item{evaluation}{a function or name of a function (string) that takes only two arguments, the estimated covariance and the test covariace, when NULL, we use negative log likelihood on test sets} \item{...}{extra argument sent to glasso::glasso} } \value{ a glasso return (see ?glasso::glasso), most important one is $X the estimated sparse precision,with an extra entry of tuning parameter lambda } \description{ This routine fits glasso using a robust covariance matrix } \examples{ robglasso(matrix(rnorm(100),20,5)) }	/man/robglasso.Rd	no_license	cran/robustcov	R	false	true	1,573	rd	% Generated by roxygen2: do not edit by hand % Please edit documentation in R/glasso_CV.R \name{robglasso} \alias{robglasso} \title{glasso with robust covariance estimations} \usage{ robglasso( data, covest = cov, rho = 0.1, CV = FALSE, k = 10, grids = 15, evaluation = negLLrobOmega, ... ) } \arguments{ \item{data}{raw data, should be a matrix or a data.frame, row as sample} \item{covest}{a function or name of a function (string) that takes a matrix to estimate covariance} \item{rho}{a scalar or vector of tuning parameters to be chosen, if CV=FALSE, should be a scalar, if CV=TRUE scalar input will be override and tuning parameter will be chosen based on CV} \item{CV}{bool, whether doing cross validation for tuning parameter, if set to TRUE and rho is a scalar, the candidate will be chosen automatically by log spacing between 0.01 max covariance and max covariance with number of grids} \item{k}{fold for cross validation if applicable} \item{grids}{number of candidate tuning parameters in cross validation} \item{evaluation}{a function or name of a function (string) that takes only two arguments, the estimated covariance and the test covariace, when NULL, we use negative log likelihood on test sets} \item{...}{extra argument sent to glasso::glasso} } \value{ a glasso return (see ?glasso::glasso), most important one is $X the estimated sparse precision,with an extra entry of tuning parameter lambda } \description{ This routine fits glasso using a robust covariance matrix } \examples{ robglasso(matrix(rnorm(100),20,5)) }
################################################################################ # plot1.R #--------------------------downloading and extracting the file------------------ if(!file.exists("./data")){ dir.create("./data") } download.file("https://d396qusza40orc.cloudfront.net/exdata%2Fdata%2Fhousehold_power_consumption.zip", destfile = "./data/extdata_data_household_power_consumption.zip") unzip("./data/extdata_data_household_power_consumption.zip",exdir = "./data") #------------------------Reading the file-------------------------------------- library(data.table) library(dplyr) library(lubridate) data <- fread(input = "./data/household_power_consumption.txt",sep = ";") #------------------------------------------------------------------------------ # Taking subset over date from 1/2/2017 - 2/2/2017 and casting the required columns subset <- data %>%filter(Date=="1/2/2007"\|Date=="2/2/2007" ) subset$Global_active_power<- as.numeric(subset$Global_active_power) #----------------------------------------------------------------------------- #Plot 1 png(filename = "./plot1.png",height = 480,width = 480) hist(subset$Global_active_power,xlab = "Global Active Power (kilowatts)", ylab = "Frquency",main = "Global Active Power",col="red") dev.off()	/plot1.R	no_license	muhammadnaqeebasif/ExData_Plotting1	R	false	false	1,285	r	################################################################################ # plot1.R #--------------------------downloading and extracting the file------------------ if(!file.exists("./data")){ dir.create("./data") } download.file("https://d396qusza40orc.cloudfront.net/exdata%2Fdata%2Fhousehold_power_consumption.zip", destfile = "./data/extdata_data_household_power_consumption.zip") unzip("./data/extdata_data_household_power_consumption.zip",exdir = "./data") #------------------------Reading the file-------------------------------------- library(data.table) library(dplyr) library(lubridate) data <- fread(input = "./data/household_power_consumption.txt",sep = ";") #------------------------------------------------------------------------------ # Taking subset over date from 1/2/2017 - 2/2/2017 and casting the required columns subset <- data %>%filter(Date=="1/2/2007"\|Date=="2/2/2007" ) subset$Global_active_power<- as.numeric(subset$Global_active_power) #----------------------------------------------------------------------------- #Plot 1 png(filename = "./plot1.png",height = 480,width = 480) hist(subset$Global_active_power,xlab = "Global Active Power (kilowatts)", ylab = "Frquency",main = "Global Active Power",col="red") dev.off()
% Generated by roxygen2: do not edit by hand % Please edit documentation in R/Read_IMU_Utils.R \name{imu_collapse} \alias{imu_collapse} \title{Collapse raw IMU data to a specified epoch} \usage{ imu_collapse(AG, block_size, verbose = FALSE) } \arguments{ \item{AG}{dataframe containing raw IMU data} \item{block_size}{number of samples per epoch} \item{verbose}{A logical scalar: Print processing updates?} } \value{ dataframe of IMU data averaged over the specified epoch length } \description{ Collapse raw IMU data to a specified epoch } \examples{ data(imu_to_collapse) collapsed <- imu_collapse(imu_to_collapse, 100) head(collapsed) }	/man/imu_collapse.Rd	permissive	paulhibbing/AGread	R	false	true	643	rd	% Generated by roxygen2: do not edit by hand % Please edit documentation in R/Read_IMU_Utils.R \name{imu_collapse} \alias{imu_collapse} \title{Collapse raw IMU data to a specified epoch} \usage{ imu_collapse(AG, block_size, verbose = FALSE) } \arguments{ \item{AG}{dataframe containing raw IMU data} \item{block_size}{number of samples per epoch} \item{verbose}{A logical scalar: Print processing updates?} } \value{ dataframe of IMU data averaged over the specified epoch length } \description{ Collapse raw IMU data to a specified epoch } \examples{ data(imu_to_collapse) collapsed <- imu_collapse(imu_to_collapse, 100) head(collapsed) }
% Generated by roxygen2: do not edit by hand % Please edit documentation in R/oin.R \name{oin_ctrl} \alias{oin_ctrl} \title{Check the control numbers for \code{oin}} \usage{ oin_ctrl(oin) } \arguments{ \item{oin}{Vector with swedish organization identity numbers (oin) in \code{NNNNNN-NNNN} format.} } \value{ Logical vector indicating if a oin is correct (\code{TRUE}) or not (\code{FALSE}) } \description{ Calculates the control number using the Luhn algorithm and compare it with the control number in the organization identity number (oin). } \examples{ ex_oin <- c("556000-4615", "232100-0156", "802002-4280", "232100-0157", "802002-4281") oin_ctrl(ex_oin) } \references{ \href{http://www.skatteverket.se/download/18.70ac421612e2a997f85800040284/1302507382017/70909.pdf}{SKV 709} }	/man/oin_ctrl.Rd	no_license	YohanRobinson/sweidnumbr	R	false	true	789	rd	% Generated by roxygen2: do not edit by hand % Please edit documentation in R/oin.R \name{oin_ctrl} \alias{oin_ctrl} \title{Check the control numbers for \code{oin}} \usage{ oin_ctrl(oin) } \arguments{ \item{oin}{Vector with swedish organization identity numbers (oin) in \code{NNNNNN-NNNN} format.} } \value{ Logical vector indicating if a oin is correct (\code{TRUE}) or not (\code{FALSE}) } \description{ Calculates the control number using the Luhn algorithm and compare it with the control number in the organization identity number (oin). } \examples{ ex_oin <- c("556000-4615", "232100-0156", "802002-4280", "232100-0157", "802002-4281") oin_ctrl(ex_oin) } \references{ \href{http://www.skatteverket.se/download/18.70ac421612e2a997f85800040284/1302507382017/70909.pdf}{SKV 709} }
#' @export tierFunction tierFunction <- function(player_id, points, srcpoints, pos, d.threshold){ cohens_d <- function(x, y, na.rm = TRUE) { if(na.rm){ x <- x[!is.na(x)] y <- y[!is.na(y)] } n.x <- length(x)- 1 n.y <- length(y)- 1 mean.diff <- abs(mean(x) - mean(y)) common.sd <- sqrt((n.x * var(x) + n.y * var(y))/(n.x + n.y)) return(mean.diff/common.sd) } tier <- rep(NA, length(points)) tierNum <- 1 dValue <- rep(NA, length(points)) playerObs <- srcpoints[ , .(numObs = .N), by = c("playerId", "position")] singleObs <- playerObs[numObs <=1] # Finding top player and assigning first tier top_player <- player_id[which.max(points)] tier[player_id == top_player] <- tierNum dValue[player_id == top_player] <- -1 repeat { # Finding the player with the lowest player in the current tier comp_player <- player_id[tier == tierNum][which.max(points[tier == tierNum])] # Finding the player with the highest points that is not in a tier max_player <- player_id[is.na(tier)][which.max(points[is.na(tier)])] if(length(max_player) == 0) break if(max_player %in% singleObs){ dValue[player_id == max_player] <- NA tier[player_id == max_player] <- 0 next } dval <- with(srcpoints, cohens_d(points[playerId == comp_player], points[playerId == max_player])) if(!is.finite(dval)){ dValue[player_id == max_player] <- NA tier[player_id == max_player] <- 0 next } dValue[player_id == max_player] <- dval if(dval > d.threshold){ tierNum <- tierNum + 1 } tier[player_id == max_player] <- tierNum # If all players have assigned tiers then quit. if(length(tier[is.na(tier)]) == 0) break } no_tier <- player_id[tier == 0] for(pl in no_tier){ pl_pts <- points[player_id == pl] pl_over <- player_id[points > pl_pts][which.min(points[points > pl_pts])] pl_under <- player_id[points < pl_pts][which.max(points[points < pl_pts])] tier[player_id == pl] <- max(tier[player_id == pl_over], tier[player_id == pl_under]) } return(list("tier" = tier, d.value =dValue)) }	/R/tierFunction.R	no_license	isaactpetersen/ffanalytics	R	false	false	2,235	r	#' @export tierFunction tierFunction <- function(player_id, points, srcpoints, pos, d.threshold){ cohens_d <- function(x, y, na.rm = TRUE) { if(na.rm){ x <- x[!is.na(x)] y <- y[!is.na(y)] } n.x <- length(x)- 1 n.y <- length(y)- 1 mean.diff <- abs(mean(x) - mean(y)) common.sd <- sqrt((n.x * var(x) + n.y * var(y))/(n.x + n.y)) return(mean.diff/common.sd) } tier <- rep(NA, length(points)) tierNum <- 1 dValue <- rep(NA, length(points)) playerObs <- srcpoints[ , .(numObs = .N), by = c("playerId", "position")] singleObs <- playerObs[numObs <=1] # Finding top player and assigning first tier top_player <- player_id[which.max(points)] tier[player_id == top_player] <- tierNum dValue[player_id == top_player] <- -1 repeat { # Finding the player with the lowest player in the current tier comp_player <- player_id[tier == tierNum][which.max(points[tier == tierNum])] # Finding the player with the highest points that is not in a tier max_player <- player_id[is.na(tier)][which.max(points[is.na(tier)])] if(length(max_player) == 0) break if(max_player %in% singleObs){ dValue[player_id == max_player] <- NA tier[player_id == max_player] <- 0 next } dval <- with(srcpoints, cohens_d(points[playerId == comp_player], points[playerId == max_player])) if(!is.finite(dval)){ dValue[player_id == max_player] <- NA tier[player_id == max_player] <- 0 next } dValue[player_id == max_player] <- dval if(dval > d.threshold){ tierNum <- tierNum + 1 } tier[player_id == max_player] <- tierNum # If all players have assigned tiers then quit. if(length(tier[is.na(tier)]) == 0) break } no_tier <- player_id[tier == 0] for(pl in no_tier){ pl_pts <- points[player_id == pl] pl_over <- player_id[points > pl_pts][which.min(points[points > pl_pts])] pl_under <- player_id[points < pl_pts][which.max(points[points < pl_pts])] tier[player_id == pl] <- max(tier[player_id == pl_over], tier[player_id == pl_under]) } return(list("tier" = tier, d.value =dValue)) }
get_pval <- function(i,j,true_dag,names,k=c()){ e <- bnlearn::empty.graph(names) bnlearn::amat(e) <- true_dag if (length(k)==0){ pval <- as.numeric(bnlearn::dsep(e,names[i+1],names[j+1])) } else { pval <- as.numeric(bnlearn::dsep(e,names[i+1],names[j+1],names[k+1])) } return(pval) }	/R/get_pval.R	no_license	stephenvsmith/Local-PC	R	false	false	306	r	get_pval <- function(i,j,true_dag,names,k=c()){ e <- bnlearn::empty.graph(names) bnlearn::amat(e) <- true_dag if (length(k)==0){ pval <- as.numeric(bnlearn::dsep(e,names[i+1],names[j+1])) } else { pval <- as.numeric(bnlearn::dsep(e,names[i+1],names[j+1],names[k+1])) } return(pval) }
\name{data_correction} \alias{data_correction} %- Also NEED an '\alias' for EACH other topic documented here. \title{ Data correction } \description{ Perform spectra corrections with 3 different methods. } \usage{ data_correction(dataset, type = "background", method = "modpolyfit", ...) } %- maybe also 'usage' for other objects documented here. \arguments{ \item{dataset}{ list representing the dataset from a metabolomics experiment. } \item{type}{ string that represents the type of correction that will be applied to the spectra. The three possible types are: "background", to perform background correction; "offset", to perform offset correction; and "baseline", to perform baseline correction. } \item{method}{ string parameter of baseline correction indicating the correction method. } \item{\dots}{ additional parameters of baseline correction. } } \value{ Returns the dataset with the spectra corrected. } \examples{ ## Example of data correction using background correction data(cassavaPPD) dataset.corrected = data_correction(cassavaPPD, type = "background") } % Add one or more standard keywords, see file 'KEYWORDS' in the % R documentation directory. \keyword{ correction } \keyword{ dataset }% __ONLY ONE__ keyword per line	/man/data_correction.Rd	no_license	Neal050617/specmine	R	false	false	1,277	rd	\name{data_correction} \alias{data_correction} %- Also NEED an '\alias' for EACH other topic documented here. \title{ Data correction } \description{ Perform spectra corrections with 3 different methods. } \usage{ data_correction(dataset, type = "background", method = "modpolyfit", ...) } %- maybe also 'usage' for other objects documented here. \arguments{ \item{dataset}{ list representing the dataset from a metabolomics experiment. } \item{type}{ string that represents the type of correction that will be applied to the spectra. The three possible types are: "background", to perform background correction; "offset", to perform offset correction; and "baseline", to perform baseline correction. } \item{method}{ string parameter of baseline correction indicating the correction method. } \item{\dots}{ additional parameters of baseline correction. } } \value{ Returns the dataset with the spectra corrected. } \examples{ ## Example of data correction using background correction data(cassavaPPD) dataset.corrected = data_correction(cassavaPPD, type = "background") } % Add one or more standard keywords, see file 'KEYWORDS' in the % R documentation directory. \keyword{ correction } \keyword{ dataset }% __ONLY ONE__ keyword per line
########################### # Export rds to json data # ########################### # pre rm(list=ls()) graphics.off() #libraries import library(M4comp2018) library(jsonlite) library(tidyverse) library(parallel) library(anytime) library(purrr) library(xts) library(zoo) source("src/ts_to_json.R") #m4_info_df <- read_csv("M4-info.txt") ## Filter by period and frequency data(M4) #df <- Filter(function(df) df$period=="Daily" & df$type=="Daily", M4) df <- Filter(function(df) df$period=="Yearly", M4) rm(M4) as.character(df[[1]]$period); as.character(df[[1]]$type);length(df) # draw random sample #my_df <- give_sam(df, size=10, seed=16) # train file json1 <- map(1:length(df), ts_to_json, df, test_data=FALSE, true_dates=FALSE, domain_cat=TRUE) sink("data/json/m4_yearly_domain_train.json") json1 <- lapply(json1, cat) sink() # test file json2 <- map(1:length(df), ts_to_json, df, test_data=TRUE, true_dates=FALSE, domain_cat=TRUE) sink("data/json/m4_yearly_domain_test.json") json2 <- lapply(json2, cat) sink()	/src/data/export_json_data_v2.R	no_license	tm1611/M4-Statistical-Methods	R	false	false	1,027	r	########################### # Export rds to json data # ########################### # pre rm(list=ls()) graphics.off() #libraries import library(M4comp2018) library(jsonlite) library(tidyverse) library(parallel) library(anytime) library(purrr) library(xts) library(zoo) source("src/ts_to_json.R") #m4_info_df <- read_csv("M4-info.txt") ## Filter by period and frequency data(M4) #df <- Filter(function(df) df$period=="Daily" & df$type=="Daily", M4) df <- Filter(function(df) df$period=="Yearly", M4) rm(M4) as.character(df[[1]]$period); as.character(df[[1]]$type);length(df) # draw random sample #my_df <- give_sam(df, size=10, seed=16) # train file json1 <- map(1:length(df), ts_to_json, df, test_data=FALSE, true_dates=FALSE, domain_cat=TRUE) sink("data/json/m4_yearly_domain_train.json") json1 <- lapply(json1, cat) sink() # test file json2 <- map(1:length(df), ts_to_json, df, test_data=TRUE, true_dates=FALSE, domain_cat=TRUE) sink("data/json/m4_yearly_domain_test.json") json2 <- lapply(json2, cat) sink()
# makeCacheMatrix is meant to create a function that makes a cache of the inverse of a matrix # 1. creating the first parameters of the function # 2. set is meant to make changes in the vector stored in the main function # 3. get is meant to return the vector stored in the main function # 4. setinverse sets the value as the inverse of the matrix # 5. getinverse is meant to get the value of the inverse of the matrix makeCacheMatrix <- function(x = matrix()) {> makeCacheMatrix <- function(x = matrix()) { i <- NULL set <- function(y) { x <<- y i <<- NULL } get <- function() x setinverse <- function(solve) i <<- solve getinverse <- function() i list(set = set, get = get, setinverse = setinverse, getinverse = getinverse) } # cacheSolve is meant to compute the inverse of the matrix. It first sees if # the inverse has already computed, and if this is true it gets the result # and skips the rest of the function. If the inverse is not yet computed, # it computes the inverse and sets the value via the setinverse function cacheSolve <- function(x, ...) { i <- x$getinverse() if(!is.null(i)) { message("getting cached data") return(i) } data <- x$get() i <- solve(data) x$setinverse(i) i } ## Test Run ## generate matrix ##> g <- matrix(rnorm(15),3,3) ##> g ## [,1] [,2] [,3] ##[1,] -0.7372368 0.4692986 0.02518957 ##[2,] 0.2082417 0.6971028 -1.68635151 ##[3,] -1.3971880 0.6572188 0.67417206 ## apply first function ##> x <- makeCacheMatrix(g) ##> x$get() ## [,1] [,2] [,3] ##[1,] -0.7372368 0.4692986 0.02518957 ##[2,] 0.2082417 0.6971028 -1.68635151 ##[3,] -1.3971880 0.6572188 0.6741720 ## inverse not calculated so proceed to solve ##> cacheSolve(x) ## [,1] [,2] [,3] ##[1,] -16.48778 3.132279 8.451024 ##[2,] -23.14748 4.824621 12.933021 ##[3,] -11.60471 1.788196 6.389831 }	/cachematrix.R	no_license	mylauron/ProgrammingAssignment2	R	false	false	2,100	r	# makeCacheMatrix is meant to create a function that makes a cache of the inverse of a matrix # 1. creating the first parameters of the function # 2. set is meant to make changes in the vector stored in the main function # 3. get is meant to return the vector stored in the main function # 4. setinverse sets the value as the inverse of the matrix # 5. getinverse is meant to get the value of the inverse of the matrix makeCacheMatrix <- function(x = matrix()) {> makeCacheMatrix <- function(x = matrix()) { i <- NULL set <- function(y) { x <<- y i <<- NULL } get <- function() x setinverse <- function(solve) i <<- solve getinverse <- function() i list(set = set, get = get, setinverse = setinverse, getinverse = getinverse) } # cacheSolve is meant to compute the inverse of the matrix. It first sees if # the inverse has already computed, and if this is true it gets the result # and skips the rest of the function. If the inverse is not yet computed, # it computes the inverse and sets the value via the setinverse function cacheSolve <- function(x, ...) { i <- x$getinverse() if(!is.null(i)) { message("getting cached data") return(i) } data <- x$get() i <- solve(data) x$setinverse(i) i } ## Test Run ## generate matrix ##> g <- matrix(rnorm(15),3,3) ##> g ## [,1] [,2] [,3] ##[1,] -0.7372368 0.4692986 0.02518957 ##[2,] 0.2082417 0.6971028 -1.68635151 ##[3,] -1.3971880 0.6572188 0.67417206 ## apply first function ##> x <- makeCacheMatrix(g) ##> x$get() ## [,1] [,2] [,3] ##[1,] -0.7372368 0.4692986 0.02518957 ##[2,] 0.2082417 0.6971028 -1.68635151 ##[3,] -1.3971880 0.6572188 0.6741720 ## inverse not calculated so proceed to solve ##> cacheSolve(x) ## [,1] [,2] [,3] ##[1,] -16.48778 3.132279 8.451024 ##[2,] -23.14748 4.824621 12.933021 ##[3,] -11.60471 1.788196 6.389831 }
install.packages("randomForest") library(randomForest) credito = read.csv(file.choose(), sep=",", header=T) modelo = randomForest(class ~ ., data = credito, ntree=500 ) #previsao baseado nos dados out of bag modelo$predicted #importancia dos atributos no modelo modelo$importance #proporção de votos na classificação de cada instancia modelo$votes #arvores induzidas modelo$forest #matriz de confusão baseado nos dados out of bag modelo$confusion plot(modelo) #fazendo previsões com um registro predict(modelo, newdata = credito[154,])	/Random Forest.r	no_license	FelipeLelis/MachineLearning	R	false	false	591	r	install.packages("randomForest") library(randomForest) credito = read.csv(file.choose(), sep=",", header=T) modelo = randomForest(class ~ ., data = credito, ntree=500 ) #previsao baseado nos dados out of bag modelo$predicted #importancia dos atributos no modelo modelo$importance #proporção de votos na classificação de cada instancia modelo$votes #arvores induzidas modelo$forest #matriz de confusão baseado nos dados out of bag modelo$confusion plot(modelo) #fazendo previsões com um registro predict(modelo, newdata = credito[154,])
library(shiny) library(shinydashboard) ui = dashboardPage( dashboardHeader(title="Estancias Infantiles"), dashboardSidebar( sidebarMenu( menuItem("Histogramas del Programa", tabName = "Dashboard", icon = icon("dashboard")), menuItem("Aseguradoras y Capacidad", tabName = "graph", icon = icon("area-chart")), menuItem("Tablas de datos", tabName = "data_table", icon = icon("table")), menuItem("Imagen", tabName = "img", icon = icon("file-picture-o")) ) ), dashboardBody( tags$head( tags$img(src='logo.png',height='80',width='230')) ) ) server = function(input, output) {} shinyApp(ui, server)	/proyecto_final/app.R	permissive	leotrujillo86/proyecto	R	false	false	709	r	library(shiny) library(shinydashboard) ui = dashboardPage( dashboardHeader(title="Estancias Infantiles"), dashboardSidebar( sidebarMenu( menuItem("Histogramas del Programa", tabName = "Dashboard", icon = icon("dashboard")), menuItem("Aseguradoras y Capacidad", tabName = "graph", icon = icon("area-chart")), menuItem("Tablas de datos", tabName = "data_table", icon = icon("table")), menuItem("Imagen", tabName = "img", icon = icon("file-picture-o")) ) ), dashboardBody( tags$head( tags$img(src='logo.png',height='80',width='230')) ) ) server = function(input, output) {} shinyApp(ui, server)
#Biometry Logistic Regression #Auriel Fournier library(reshape) library(Hmisc) library(ggplot2) library(AICcmodavg)#for AIC ranking library(rms) library(ds) setwd("~/Downloads") #diving beetle h = read.csv("h_sulphuria.csv", header=T) hsub = subset(x=h, select=c("shed_urban", "riparian_forest","h_sulphuria","shed_area")) hmelt = melt(hsub, id.vars="h_sulphuria") ggplot() + geom_point(data=hmelt, aes(x=h_sulphuria, y=value, group=variable, colour=variable)) #pearson's correlation cor = rcorr(as.matrix(hsub), type="pearson") cor #lrm() is the logisitc regression model cand.mod = list() cand.mod[[1]] = glm(h_sulphuria ~ shed_urban+shed_area, data=hsub, family=binomial) cand.mod[[2]] = glm(h_sulphuria ~ shed_urban+riparian_forest+shed_area, data=hsub, family=binomial) cand.mod[[3]] = glm(h_sulphuria ~ riparian_forestshed_urbanshed_area, data=hsub, family=binomial) #list of the names for the models names = c("model 1", "model 2", "model 3") #generates AIC table aictab(cand.mod, names, sort=T) model = lrm(h_sulphuria ~ shed_area, data=hsub, x=T, y=T) model1 = lrm(h_sulphuria ~ shed_urban+shed_area, data=hsub, x=T, y=T) model2 = lrm(h_sulphuria ~ shed_urban+riparian_forest+shed_area, data=hsub, x=T, y=T) model3 = lrm(h_sulphuria ~ riparian_forestshed_urbanshed_area, data=hsub, x=T, y=T) #burying beetle n = read.csv("n_americanus.csv", header=T) cand.modn = list() cand.modn[[1]] = glm(americanus ~ forest, data=n, family=binomial) cand.modn[[2]] = glm(americanus ~ grassland, data=n, family=binomial) cand.modn[[3]] = glm(americanus ~ soil_dom, data=n, family=binomial) cand.modn[[4]] = glm(americanus ~ deltachilu + tomentosus, data=n, family=binomial) cand.modn[[5]] = glm(americanus ~ forest + as.factor(soil_dom), data=n, family=binomial) cand.modn[[6]] = glm(americanus ~ forest + as.factor(soil_dom)+ deltachilu,data=n, family=binomial) #list of the names for the models names = c("model 1", "model 2", "model 3", "model 4", "model 5", "model 6") #generates AIC table aictab(cand.modn, names, sort=T)	/biometry_spring_2014/Biometry_Logistic_Regression/Biometry_Logistic_Regression.R	no_license	aurielfournier/courses	R	false	false	2,047	r	#Biometry Logistic Regression #Auriel Fournier library(reshape) library(Hmisc) library(ggplot2) library(AICcmodavg)#for AIC ranking library(rms) library(ds) setwd("~/Downloads") #diving beetle h = read.csv("h_sulphuria.csv", header=T) hsub = subset(x=h, select=c("shed_urban", "riparian_forest","h_sulphuria","shed_area")) hmelt = melt(hsub, id.vars="h_sulphuria") ggplot() + geom_point(data=hmelt, aes(x=h_sulphuria, y=value, group=variable, colour=variable)) #pearson's correlation cor = rcorr(as.matrix(hsub), type="pearson") cor #lrm() is the logisitc regression model cand.mod = list() cand.mod[[1]] = glm(h_sulphuria ~ shed_urban+shed_area, data=hsub, family=binomial) cand.mod[[2]] = glm(h_sulphuria ~ shed_urban+riparian_forest+shed_area, data=hsub, family=binomial) cand.mod[[3]] = glm(h_sulphuria ~ riparian_forestshed_urbanshed_area, data=hsub, family=binomial) #list of the names for the models names = c("model 1", "model 2", "model 3") #generates AIC table aictab(cand.mod, names, sort=T) model = lrm(h_sulphuria ~ shed_area, data=hsub, x=T, y=T) model1 = lrm(h_sulphuria ~ shed_urban+shed_area, data=hsub, x=T, y=T) model2 = lrm(h_sulphuria ~ shed_urban+riparian_forest+shed_area, data=hsub, x=T, y=T) model3 = lrm(h_sulphuria ~ riparian_forestshed_urbanshed_area, data=hsub, x=T, y=T) #burying beetle n = read.csv("n_americanus.csv", header=T) cand.modn = list() cand.modn[[1]] = glm(americanus ~ forest, data=n, family=binomial) cand.modn[[2]] = glm(americanus ~ grassland, data=n, family=binomial) cand.modn[[3]] = glm(americanus ~ soil_dom, data=n, family=binomial) cand.modn[[4]] = glm(americanus ~ deltachilu + tomentosus, data=n, family=binomial) cand.modn[[5]] = glm(americanus ~ forest + as.factor(soil_dom), data=n, family=binomial) cand.modn[[6]] = glm(americanus ~ forest + as.factor(soil_dom)+ deltachilu,data=n, family=binomial) #list of the names for the models names = c("model 1", "model 2", "model 3", "model 4", "model 5", "model 6") #generates AIC table aictab(cand.modn, names, sort=T)
manageparam <- function(start.arg, fix.arg, obs, distname) { #if clause with 3 different cases: #start.arg : NULL \| named list \| a function if (is.null(start.arg)) { trystart <- try(start.arg.default(obs, distname), silent = TRUE) if (class(trystart) == "try-error") { cat("Error in computing default starting values.\n") stop(trystart) } lstart <- trystart #lstart should be a named list but check it hasnoname <- is.null(names(lstart)) \|\| !is.list(lstart) if (hasnoname) stop("Starting values must be a named list, error in default starting value.") } else if (is.list(start.arg)) { hasnoname <- is.null(names(start.arg)) if (hasnoname) stop("Starting values must be a named list (or a function returning a named list).") lstart <- start.arg } else if (is.function(start.arg)) { trystart <- try(start.arg(obs), silent = TRUE) if (class(trystart) == "try-error") { cat("Error in computing starting values with your function.\n") stop(trystart) } lstart <- trystart hasnoname <- is.null(names(lstart)) \|\| !is.list(lstart) if (hasnoname) stop("Starting values must be a named list, your function does not return that.") } else stop("Wrong type of argument for start") #if clause with 3 different cases: #fix.arg : NULL \| named list \| a function if (is.null(fix.arg)) { lfix <- NULL } else if (is.list(fix.arg)) { hasnoname <- is.null(names(fix.arg)) if (hasnoname) stop("Fixed parameter values must be a named list (or a function returning a named list).") lfix <- fix.arg } else if (is.function(fix.arg)) { tryfix <- try(fix.arg(obs), silent = TRUE) if (class(tryfix) == "try-error") { cat("Error in computing fixed parameter values with your function.\n") stop(tryfix) } lfix <- tryfix hasnoname <- is.null(names(lfix)) \|\| !is.list(lfix) if (hasnoname) stop("Fixed parameter values must be a named list, your function does not return that.") } else stop("Wrong type of argument for fix.arg") #eliminate arguments both in lstart and lfix (when start.arg was NULL) if (is.null(start.arg) && !is.null(lfix)) { lstart <- lstart[!names(lstart) %in% names(lfix)] if (length(lstart) == 0) stop("Don't need to use fitdist() if all parameters have fixed values") } list("start.arg" = lstart, "fix.arg" = lfix) } checkparamlist <- function(start.arg, fix.arg, argdistname, hasnodefaultval) { errtxt <- list(t3 = "'start' must specify names which are arguments to 'distr'.", t4 = "'fix.arg' must specify names which are arguments to 'distr'.", t5 = "A distribution parameter cannot be specified both in 'start' and 'fix.arg'.", t6 = "'start' should not have NA or NaN values.", t7 = "'fix.arg' should not have NA or NaN values.", t8 = "Some parameter names have no starting/fixed value: ", t9 = "Some parameter names have no starting/fixed value but have a default value: ") vstart <- unlist(start.arg) #check unexpected names m <- match(names(vstart), argdistname) if (any(is.na(m))) stop(errtxt$t3) #check NA/NaN values if (any(is.na(vstart)) \|\| any(is.nan(vstart))) stop(errtxt$t6) if (!is.null(fix.arg)) { vfix <- unlist(fix.arg) #check unexpected names mfix <- match(names(vfix), argdistname) if (any(is.na(mfix))) stop(errtxt$t4) # check that some parameters are not both in fix.arg and start minter <- match(names(vstart), names(vfix)) if (any(!is.na(minter))) stop(errtxt$t5) #check NA/NaN values if (any(is.na(vfix)) \|\| any(is.nan(vfix))) stop(errtxt$t7) allparname <- names(c(vstart, vfix)) } else allparname <- names(vstart) theoparam <- computegetparam(argdistname) #special case where both scale and rate are allowed, see ?dgamma if ("scale" %in% theoparam && "rate" %in% theoparam) { errt8 <- any(!allparname %in% theoparam) \|\| length(allparname) != length(theoparam) - 1 #special case where both prob and mu are allowed, see ?dnbinom } else if (length(theoparam) == 3 && all(c("size", "prob", "mu") %in% theoparam)) { errt8 <- any(!allparname %in% theoparam) \|\| length(allparname) != length(theoparam) - 1 } else errt8 <- any(!theoparam %in% allparname) #only make a warning if unset arguments have a default value if (errt8) { unsetarg <- theoparam[!theoparam %in% allparname] if (any(hasnodefaultval[unsetarg])) stop(paste0(errtxt$t8, unsetarg, ".")) else warning(paste0(errtxt$t9, unsetarg, ".")) } list("start.arg" = start.arg, "fix.arg" = fix.arg) } computegetparam <- function(argdistname) { #remove first argument, that should be "x", "p", "q", or "n", see ?dgamma, pgamma, qgamma argdistname <- argdistname[-1] nonparaminR <- c("x", "p", "q", "n") #defensive programming #remove other arguments, see ?dgamma, pgamma, qgamma, dbeta nonparaminR <- c(nonparaminR, "log", "log.p", "lower.tail", "ncp") nonparaminActuar <- c("limit", "order", "t") nonparaminGamlssdist <- "fast" nonparamspecial <- c("...", "..1", "..2") #see ?dnig, dhyperb, dskewlap, dgig,... nonparaminGenHyperbolic <- c("param", "KOmega", "ibfTol", "nmax", "method", "intTol", "valueOnly", "nInterpol", "uniTol", "subdivisions", "logPars") #see ?dsn nonparamsn <- "dp" plist <- setdiff(argdistname, nonparaminR) plist <- setdiff(plist, nonparaminActuar) plist <- setdiff(plist, nonparaminGamlssdist) plist <- setdiff(plist, nonparamspecial) plist <- setdiff(plist, nonparaminGenHyperbolic) plist <- setdiff(plist, nonparamsn) plist } trace= function(data, distr, start = NULL, fix.arg = NULL, optim.method = "default", lower = -Inf, upper = Inf, custom.optim = NULL, weights = NULL, silent = TRUE, gradient = NULL, checkstartfix = FALSE, ...) { if (!is.character(distr)) stop("distr must be a character string naming a distribution") else distname <- distr ddistname <- paste("d", distname, sep = "") argddistname <- names(formals(ddistname)) if (!exists(ddistname, mode = "function")) stop(paste("The ", ddistname, " function must be defined")) if (is.null(custom.optim)) optim.method <- match.arg(optim.method, c("default", "Nelder-Mead", "BFGS", "CG", "L-BFGS-B", "SANN", "Brent")) start.arg <- start if (is.vector(start.arg)) start.arg <- as.list(start.arg) txt1 <- "data must be a numeric vector of length greater than 1 for non censored data" txt2 <- "or a dataframe with two columns named left and right and more than one line for censored data" if (!is.null(weights)) { if (any(weights < 0)) stop("weights should be a vector of integers greater than 0") if (!is.allint.w(weights)) stop("weights should be a vector of (strictly) positive integers") if (length(weights) != NROW(data)) stop("weights should be a vector with a length equal to the observation number") warning("weights are not taken into account in the default initial values") } if (is.vector(data)) { cens <- FALSE if (!(is.numeric(data) & length(data) > 1)) stop(paste(txt1, txt2)) } else { cens <- TRUE censdata <- data if (!(is.vector(censdata$left) & is.vector(censdata$right) & length(censdata[, 1]) > 1)) stop(paste(txt1, txt2)) pdistname <- paste("p", distname, sep = "") if (!exists(pdistname, mode = "function")) stop(paste("The ", pdistname, " function must be defined to apply maximum likelihood to censored data")) } if (cens) { dataformat <- cens2pseudo(censdata) data <- dataformat$pseudo rcens <- dataformat$rcens lcens <- dataformat$lcens icens <- dataformat$icens ncens <- dataformat$ncens irow <- cens2idxrow(censdata) irow.rcens <- irow$rcens irow.lcens <- irow$lcens irow.icens <- irow$icens irow.ncens <- irow$ncens } if (!checkstartfix) { arg_startfix <- manageparam(start.arg = start, fix.arg = fix.arg, obs = data, distname = distname) hasnodefaultval <- sapply(formals(ddistname), is.name) arg_startfix <- checkparamlist(arg_startfix$start.arg, arg_startfix$fix.arg, argddistname, hasnodefaultval) if (is.function(fix.arg)) fix.arg.fun <- fix.arg else fix.arg.fun <- NULL } else { arg_startfix <- list(start.arg = start, fix.arg = fix.arg) fix.arg.fun <- NULL } vstart <- unlist(arg_startfix$start.arg) if (is.null(vstart)) stop("Starting values could not be NULL with checkstartfix=TRUE") fix.arg <- arg_startfix$fix.arg if (distname == "unif") { par <- c(min = min(data), max = max(data)) res <- list(estimate = par[!names(par) %in% names(fix.arg)], convergence = 0, loglik = NA, hessian = NA, optim.function = NA, fix.arg = fix.arg) return(res) } if (!cens && is.null(weights)) { if ("log" %in% argddistname) { fnobj <- function(par, fix.arg, obs, ddistnam) { -sum(do.call(ddistnam, c(list(obs), as.list(par), as.list(fix.arg), log = TRUE))) } } else { fnobj <- function(par, fix.arg, obs, ddistnam) { -sum(log(do.call(ddistnam, c(list(obs), as.list(par), as.list(fix.arg))))) } } } else if (cens && is.null(weights)) { argpdistname <- names(formals(pdistname)) if (("log" %in% argddistname) & ("log.p" %in% argpdistname)) fnobjcens <- function(par, fix.arg, rcens, lcens, icens, ncens, ddistnam, pdistnam) - sum(do.call(ddistnam, c(list(ncens), as.list(par), as.list(fix.arg), list(log = TRUE)))) - sum(do.call(pdistnam, c(list(lcens), as.list(par), as.list(fix.arg), list(log = TRUE)))) - sum(do.call(pdistnam, c(list(rcens), as.list(par), as.list(fix.arg), list(lower.tail = FALSE), list(log = TRUE)))) - sum(log(do.call(pdistnam, c(list(icens$right), as.list(par), as.list(fix.arg))) - do.call(pdistnam, c(list(icens$left), as.list(par), as.list(fix.arg))))) else fnobjcens <- function(par, fix.arg, rcens, lcens, icens, ncens, ddistnam, pdistnam) - sum(log(do.call(ddistnam, c(list(ncens), as.list(par), as.list(fix.arg))))) - sum(log(do.call(pdistnam, c(list(lcens), as.list(par), as.list(fix.arg))))) - sum(log(1 - do.call(pdistnam, c(list(rcens), as.list(par), as.list(fix.arg))))) - sum(log(do.call(pdistnam, c(list(icens$right), as.list(par), as.list(fix.arg))) - do.call(pdistnam, c(list(icens$left), as.list(par), as.list(fix.arg))))) } else if (!cens && !is.null(weights)) { fnobj <- function(par, fix.arg, obs, ddistnam) { -sum(weights * log(do.call(ddistnam, c(list(obs), as.list(par), as.list(fix.arg))))) } } else if (cens && !is.null(weights)) { fnobjcens <- function(par, fix.arg, rcens, lcens, icens, ncens, ddistnam, pdistnam) { p1 <- log(do.call(ddistnam, c(list(ncens), as.list(par), as.list(fix.arg)))) p2 <- log(do.call(pdistnam, c(list(lcens), as.list(par), as.list(fix.arg)))) p3 <- log(1 - do.call(pdistnam, c(list(rcens), as.list(par), as.list(fix.arg)))) p4 <- log(do.call(pdistnam, c(list(icens$right), as.list(par), as.list(fix.arg))) - do.call(pdistnam, c(list(icens$left), as.list(par), as.list(fix.arg)))) - sum(weights[irow.ncens] * p1) - sum(weights[irow.lcens] * p2) - sum(weights[irow.rcens] * p3) - sum(weights[irow.icens] * p4) } } owarn <- getOption("warn") if (is.null(custom.optim)) { hasbound <- any(is.finite(lower) \| is.finite(upper)) if (optim.method == "default") { meth <- ifelse(length(vstart) > 1, "Nelder-Mead", "BFGS") } else meth <- optim.method if (meth == "BFGS" && hasbound && is.null(gradient)) { meth <- "L-BFGS-B" txt1 <- "The BFGS method cannot be used with bounds without provided the gradient." txt2 <- "The method is changed to L-BFGS-B." warning(paste(txt1, txt2)) } options(warn = ifelse(silent, -1, 0)) if (hasbound) { if (!is.null(gradient)) { opt.fun <- "constrOptim" } else { if (meth == "Nelder-Mead") opt.fun <- "constrOptim" else if (meth %in% c("L-BFGS-B", "Brent")) opt.fun <- "optim" else { txt1 <- paste("The method", meth, "cannot be used by constrOptim() nor optim() without gradient and bounds.") txt2 <- "Only optimization methods L-BFGS-B, Brent and Nelder-Mead can be used in such case." stop(paste(txt1, txt2)) } } if (opt.fun == "constrOptim") { npar <- length(vstart) lower <- as.double(rep_len(lower, npar)) upper <- as.double(rep_len(upper, npar)) haslow <- is.finite(lower) Mat <- diag(npar)[haslow,] hasupp <- is.finite(upper) Mat <- rbind(Mat, - diag(npar)[hasupp,]) colnames(Mat) <- names(vstart) rownames(Mat) <- paste0("constr", 1:NROW(Mat)) Bnd <- c(lower[is.finite(lower)], - upper[is.finite(upper)]) names(Bnd) <- paste0("constr", 1:length(Bnd)) initconstr <- Mat %*% vstart - Bnd if (any(initconstr < 0)) stop("Starting values must be in the feasible region.") if (!cens) { opttryerror <- try(opt <- constrOptim(theta = vstart, f = fnobj, ui = Mat, ci = Bnd, grad = gradient, fix.arg = fix.arg, obs = data, ddistnam = ddistname, hessian = !is.null(gradient), method = meth, ...), silent = TRUE) } else opttryerror <- try(opt <- constrOptim(theta = vstart, f = fnobjcens, ui = Mat, ci = Bnd, grad = gradient, ddistnam = ddistname, rcens = rcens, lcens = lcens, icens = icens, ncens = ncens, pdistnam = pdistname, fix.arg = fix.arg, hessian = !is.null(gradient), method = meth, ...), silent = TRUE) if (!inherits(opttryerror, "try-error")) if (length(opt$counts) == 1) opt$counts <- c(opt$counts, NA) } else { if (!cens) opttryerror <- try(opt <- optim(par = vstart, fn = fnobj, fix.arg = fix.arg, obs = data, gr = gradient, ddistnam = ddistname, hessian = TRUE, method = meth, lower = lower, upper = upper, ...), silent = TRUE) else opttryerror <- try(opt <- optim(par = vstart, fn = fnobjcens, fix.arg = fix.arg, gr = gradient, rcens = rcens, lcens = lcens, icens = icens, ncens = ncens, ddistnam = ddistname, pdistnam = pdistname, hessian = TRUE, method = meth, lower = lower, upper = upper, ...), silent = TRUE) } } else { opt.fun <- "optim" if (!cens) opttryerror <- try(opt <- optim(par = vstart, fn = fnobj, fix.arg = fix.arg, obs = data, gr = gradient, ddistnam = ddistname, hessian = TRUE, method = method, lower = lower, upper = upper, control=list(trace=6), ...), silent = TRUE) else opttryerror <- try(opt <- optim(par = vstart, fn = fnobjcens, fix.arg = fix.arg, gr = gradient, rcens = rcens, lcens = lcens, icens = icens, ncens = ncens, ddistnam = ddistname, pdistnam = pdistname, hessian = TRUE, method = meth, lower = lower, upper = upper, ...), silent = TRUE) } options(warn = owarn) if (inherits(opttryerror, "try-error")) { warnings("The function optim encountered an error and stopped.") if (getOption("show.error.messages")) print(attr(opttryerror, "condition")) return(list(estimate = rep(NA, length(vstart)), convergence = 100, loglik = NA, hessian = NA, optim.function = opt.fun, fix.arg = fix.arg, optim.method = meth, fix.arg.fun = fix.arg.fun, counts = c(NA, NA))) } if (opt$convergence > 0) { warnings("The function optim failed to converge, with the error code ", opt$convergence) } if (is.null(names(opt$par))) names(opt$par) <- names(vstart) res <- list(estimate = opt$par, convergence = opt$convergence, value = opt$value, hessian = opt$hessian, optim.function = opt.fun, optim.method = meth, fix.arg = fix.arg, fix.arg.fun = fix.arg.fun, weights = weights, counts = opt$counts, optim.message = opt$message, loglik = -opt$value) } else { options(warn = ifelse(silent, -1, 0)) if (!cens) opttryerror <- try(opt <- custom.optim(fn = fnobj, fix.arg = fix.arg, obs = data, ddistnam = ddistname, par = vstart, ...), silent = TRUE) else opttryerror <- try(opt <- custom.optim(fn = fnobjcens, fix.arg = fix.arg, rcens = rcens, lcens = lcens, icens = icens, ncens = ncens, ddistnam = ddistname, pdistnam = pdistname, par = vstart, ...), silent = TRUE) options(warn = owarn) if (inherits(opttryerror, "try-error")) { warnings("The customized optimization function encountered an error and stopped.") if (getOption("show.error.messages")) print(attr(opttryerror, "condition")) return(list(estimate = rep(NA, length(vstart)), convergence = 100, loglik = NA, hessian = NA, optim.function = custom.optim, fix.arg = fix.arg, fix.arg.fun = fix.arg.fun, counts = c(NA, NA))) } if (opt$convergence > 0) { warnings("The customized optimization function failed to converge, with the error code ", opt$convergence) } if (is.null(names(opt$par))) names(opt$par) <- names(vstart) argdot <- list(...) method.cust <- argdot$method res <- list(estimate = opt$par, convergence = opt$convergence, value = opt$value, hessian = opt$hessian, optim.function = custom.optim, optim.method = method.cust, fix.arg = fix.arg, fix.arg.fun = fix.arg.fun, weights = weights, counts = opt$counts, optim.message = opt$message, loglik = -opt$value) } return(res) } z= trace(x.1972, 'gb2', start = list(shape1 = 1, shape2 = 1, shape3 = 1, scale = 1), lower = c(0, 0, 0, 0), optim.method = 'Nelder-Mead')	/trace.R	no_license	eastnile/proj_005_incinq	R	false	false	20,419	r	manageparam <- function(start.arg, fix.arg, obs, distname) { #if clause with 3 different cases: #start.arg : NULL \| named list \| a function if (is.null(start.arg)) { trystart <- try(start.arg.default(obs, distname), silent = TRUE) if (class(trystart) == "try-error") { cat("Error in computing default starting values.\n") stop(trystart) } lstart <- trystart #lstart should be a named list but check it hasnoname <- is.null(names(lstart)) \|\| !is.list(lstart) if (hasnoname) stop("Starting values must be a named list, error in default starting value.") } else if (is.list(start.arg)) { hasnoname <- is.null(names(start.arg)) if (hasnoname) stop("Starting values must be a named list (or a function returning a named list).") lstart <- start.arg } else if (is.function(start.arg)) { trystart <- try(start.arg(obs), silent = TRUE) if (class(trystart) == "try-error") { cat("Error in computing starting values with your function.\n") stop(trystart) } lstart <- trystart hasnoname <- is.null(names(lstart)) \|\| !is.list(lstart) if (hasnoname) stop("Starting values must be a named list, your function does not return that.") } else stop("Wrong type of argument for start") #if clause with 3 different cases: #fix.arg : NULL \| named list \| a function if (is.null(fix.arg)) { lfix <- NULL } else if (is.list(fix.arg)) { hasnoname <- is.null(names(fix.arg)) if (hasnoname) stop("Fixed parameter values must be a named list (or a function returning a named list).") lfix <- fix.arg } else if (is.function(fix.arg)) { tryfix <- try(fix.arg(obs), silent = TRUE) if (class(tryfix) == "try-error") { cat("Error in computing fixed parameter values with your function.\n") stop(tryfix) } lfix <- tryfix hasnoname <- is.null(names(lfix)) \|\| !is.list(lfix) if (hasnoname) stop("Fixed parameter values must be a named list, your function does not return that.") } else stop("Wrong type of argument for fix.arg") #eliminate arguments both in lstart and lfix (when start.arg was NULL) if (is.null(start.arg) && !is.null(lfix)) { lstart <- lstart[!names(lstart) %in% names(lfix)] if (length(lstart) == 0) stop("Don't need to use fitdist() if all parameters have fixed values") } list("start.arg" = lstart, "fix.arg" = lfix) } checkparamlist <- function(start.arg, fix.arg, argdistname, hasnodefaultval) { errtxt <- list(t3 = "'start' must specify names which are arguments to 'distr'.", t4 = "'fix.arg' must specify names which are arguments to 'distr'.", t5 = "A distribution parameter cannot be specified both in 'start' and 'fix.arg'.", t6 = "'start' should not have NA or NaN values.", t7 = "'fix.arg' should not have NA or NaN values.", t8 = "Some parameter names have no starting/fixed value: ", t9 = "Some parameter names have no starting/fixed value but have a default value: ") vstart <- unlist(start.arg) #check unexpected names m <- match(names(vstart), argdistname) if (any(is.na(m))) stop(errtxt$t3) #check NA/NaN values if (any(is.na(vstart)) \|\| any(is.nan(vstart))) stop(errtxt$t6) if (!is.null(fix.arg)) { vfix <- unlist(fix.arg) #check unexpected names mfix <- match(names(vfix), argdistname) if (any(is.na(mfix))) stop(errtxt$t4) # check that some parameters are not both in fix.arg and start minter <- match(names(vstart), names(vfix)) if (any(!is.na(minter))) stop(errtxt$t5) #check NA/NaN values if (any(is.na(vfix)) \|\| any(is.nan(vfix))) stop(errtxt$t7) allparname <- names(c(vstart, vfix)) } else allparname <- names(vstart) theoparam <- computegetparam(argdistname) #special case where both scale and rate are allowed, see ?dgamma if ("scale" %in% theoparam && "rate" %in% theoparam) { errt8 <- any(!allparname %in% theoparam) \|\| length(allparname) != length(theoparam) - 1 #special case where both prob and mu are allowed, see ?dnbinom } else if (length(theoparam) == 3 && all(c("size", "prob", "mu") %in% theoparam)) { errt8 <- any(!allparname %in% theoparam) \|\| length(allparname) != length(theoparam) - 1 } else errt8 <- any(!theoparam %in% allparname) #only make a warning if unset arguments have a default value if (errt8) { unsetarg <- theoparam[!theoparam %in% allparname] if (any(hasnodefaultval[unsetarg])) stop(paste0(errtxt$t8, unsetarg, ".")) else warning(paste0(errtxt$t9, unsetarg, ".")) } list("start.arg" = start.arg, "fix.arg" = fix.arg) } computegetparam <- function(argdistname) { #remove first argument, that should be "x", "p", "q", or "n", see ?dgamma, pgamma, qgamma argdistname <- argdistname[-1] nonparaminR <- c("x", "p", "q", "n") #defensive programming #remove other arguments, see ?dgamma, pgamma, qgamma, dbeta nonparaminR <- c(nonparaminR, "log", "log.p", "lower.tail", "ncp") nonparaminActuar <- c("limit", "order", "t") nonparaminGamlssdist <- "fast" nonparamspecial <- c("...", "..1", "..2") #see ?dnig, dhyperb, dskewlap, dgig,... nonparaminGenHyperbolic <- c("param", "KOmega", "ibfTol", "nmax", "method", "intTol", "valueOnly", "nInterpol", "uniTol", "subdivisions", "logPars") #see ?dsn nonparamsn <- "dp" plist <- setdiff(argdistname, nonparaminR) plist <- setdiff(plist, nonparaminActuar) plist <- setdiff(plist, nonparaminGamlssdist) plist <- setdiff(plist, nonparamspecial) plist <- setdiff(plist, nonparaminGenHyperbolic) plist <- setdiff(plist, nonparamsn) plist } trace= function(data, distr, start = NULL, fix.arg = NULL, optim.method = "default", lower = -Inf, upper = Inf, custom.optim = NULL, weights = NULL, silent = TRUE, gradient = NULL, checkstartfix = FALSE, ...) { if (!is.character(distr)) stop("distr must be a character string naming a distribution") else distname <- distr ddistname <- paste("d", distname, sep = "") argddistname <- names(formals(ddistname)) if (!exists(ddistname, mode = "function")) stop(paste("The ", ddistname, " function must be defined")) if (is.null(custom.optim)) optim.method <- match.arg(optim.method, c("default", "Nelder-Mead", "BFGS", "CG", "L-BFGS-B", "SANN", "Brent")) start.arg <- start if (is.vector(start.arg)) start.arg <- as.list(start.arg) txt1 <- "data must be a numeric vector of length greater than 1 for non censored data" txt2 <- "or a dataframe with two columns named left and right and more than one line for censored data" if (!is.null(weights)) { if (any(weights < 0)) stop("weights should be a vector of integers greater than 0") if (!is.allint.w(weights)) stop("weights should be a vector of (strictly) positive integers") if (length(weights) != NROW(data)) stop("weights should be a vector with a length equal to the observation number") warning("weights are not taken into account in the default initial values") } if (is.vector(data)) { cens <- FALSE if (!(is.numeric(data) & length(data) > 1)) stop(paste(txt1, txt2)) } else { cens <- TRUE censdata <- data if (!(is.vector(censdata$left) & is.vector(censdata$right) & length(censdata[, 1]) > 1)) stop(paste(txt1, txt2)) pdistname <- paste("p", distname, sep = "") if (!exists(pdistname, mode = "function")) stop(paste("The ", pdistname, " function must be defined to apply maximum likelihood to censored data")) } if (cens) { dataformat <- cens2pseudo(censdata) data <- dataformat$pseudo rcens <- dataformat$rcens lcens <- dataformat$lcens icens <- dataformat$icens ncens <- dataformat$ncens irow <- cens2idxrow(censdata) irow.rcens <- irow$rcens irow.lcens <- irow$lcens irow.icens <- irow$icens irow.ncens <- irow$ncens } if (!checkstartfix) { arg_startfix <- manageparam(start.arg = start, fix.arg = fix.arg, obs = data, distname = distname) hasnodefaultval <- sapply(formals(ddistname), is.name) arg_startfix <- checkparamlist(arg_startfix$start.arg, arg_startfix$fix.arg, argddistname, hasnodefaultval) if (is.function(fix.arg)) fix.arg.fun <- fix.arg else fix.arg.fun <- NULL } else { arg_startfix <- list(start.arg = start, fix.arg = fix.arg) fix.arg.fun <- NULL } vstart <- unlist(arg_startfix$start.arg) if (is.null(vstart)) stop("Starting values could not be NULL with checkstartfix=TRUE") fix.arg <- arg_startfix$fix.arg if (distname == "unif") { par <- c(min = min(data), max = max(data)) res <- list(estimate = par[!names(par) %in% names(fix.arg)], convergence = 0, loglik = NA, hessian = NA, optim.function = NA, fix.arg = fix.arg) return(res) } if (!cens && is.null(weights)) { if ("log" %in% argddistname) { fnobj <- function(par, fix.arg, obs, ddistnam) { -sum(do.call(ddistnam, c(list(obs), as.list(par), as.list(fix.arg), log = TRUE))) } } else { fnobj <- function(par, fix.arg, obs, ddistnam) { -sum(log(do.call(ddistnam, c(list(obs), as.list(par), as.list(fix.arg))))) } } } else if (cens && is.null(weights)) { argpdistname <- names(formals(pdistname)) if (("log" %in% argddistname) & ("log.p" %in% argpdistname)) fnobjcens <- function(par, fix.arg, rcens, lcens, icens, ncens, ddistnam, pdistnam) - sum(do.call(ddistnam, c(list(ncens), as.list(par), as.list(fix.arg), list(log = TRUE)))) - sum(do.call(pdistnam, c(list(lcens), as.list(par), as.list(fix.arg), list(log = TRUE)))) - sum(do.call(pdistnam, c(list(rcens), as.list(par), as.list(fix.arg), list(lower.tail = FALSE), list(log = TRUE)))) - sum(log(do.call(pdistnam, c(list(icens$right), as.list(par), as.list(fix.arg))) - do.call(pdistnam, c(list(icens$left), as.list(par), as.list(fix.arg))))) else fnobjcens <- function(par, fix.arg, rcens, lcens, icens, ncens, ddistnam, pdistnam) - sum(log(do.call(ddistnam, c(list(ncens), as.list(par), as.list(fix.arg))))) - sum(log(do.call(pdistnam, c(list(lcens), as.list(par), as.list(fix.arg))))) - sum(log(1 - do.call(pdistnam, c(list(rcens), as.list(par), as.list(fix.arg))))) - sum(log(do.call(pdistnam, c(list(icens$right), as.list(par), as.list(fix.arg))) - do.call(pdistnam, c(list(icens$left), as.list(par), as.list(fix.arg))))) } else if (!cens && !is.null(weights)) { fnobj <- function(par, fix.arg, obs, ddistnam) { -sum(weights * log(do.call(ddistnam, c(list(obs), as.list(par), as.list(fix.arg))))) } } else if (cens && !is.null(weights)) { fnobjcens <- function(par, fix.arg, rcens, lcens, icens, ncens, ddistnam, pdistnam) { p1 <- log(do.call(ddistnam, c(list(ncens), as.list(par), as.list(fix.arg)))) p2 <- log(do.call(pdistnam, c(list(lcens), as.list(par), as.list(fix.arg)))) p3 <- log(1 - do.call(pdistnam, c(list(rcens), as.list(par), as.list(fix.arg)))) p4 <- log(do.call(pdistnam, c(list(icens$right), as.list(par), as.list(fix.arg))) - do.call(pdistnam, c(list(icens$left), as.list(par), as.list(fix.arg)))) - sum(weights[irow.ncens] * p1) - sum(weights[irow.lcens] * p2) - sum(weights[irow.rcens] * p3) - sum(weights[irow.icens] * p4) } } owarn <- getOption("warn") if (is.null(custom.optim)) { hasbound <- any(is.finite(lower) \| is.finite(upper)) if (optim.method == "default") { meth <- ifelse(length(vstart) > 1, "Nelder-Mead", "BFGS") } else meth <- optim.method if (meth == "BFGS" && hasbound && is.null(gradient)) { meth <- "L-BFGS-B" txt1 <- "The BFGS method cannot be used with bounds without provided the gradient." txt2 <- "The method is changed to L-BFGS-B." warning(paste(txt1, txt2)) } options(warn = ifelse(silent, -1, 0)) if (hasbound) { if (!is.null(gradient)) { opt.fun <- "constrOptim" } else { if (meth == "Nelder-Mead") opt.fun <- "constrOptim" else if (meth %in% c("L-BFGS-B", "Brent")) opt.fun <- "optim" else { txt1 <- paste("The method", meth, "cannot be used by constrOptim() nor optim() without gradient and bounds.") txt2 <- "Only optimization methods L-BFGS-B, Brent and Nelder-Mead can be used in such case." stop(paste(txt1, txt2)) } } if (opt.fun == "constrOptim") { npar <- length(vstart) lower <- as.double(rep_len(lower, npar)) upper <- as.double(rep_len(upper, npar)) haslow <- is.finite(lower) Mat <- diag(npar)[haslow,] hasupp <- is.finite(upper) Mat <- rbind(Mat, - diag(npar)[hasupp,]) colnames(Mat) <- names(vstart) rownames(Mat) <- paste0("constr", 1:NROW(Mat)) Bnd <- c(lower[is.finite(lower)], - upper[is.finite(upper)]) names(Bnd) <- paste0("constr", 1:length(Bnd)) initconstr <- Mat %*% vstart - Bnd if (any(initconstr < 0)) stop("Starting values must be in the feasible region.") if (!cens) { opttryerror <- try(opt <- constrOptim(theta = vstart, f = fnobj, ui = Mat, ci = Bnd, grad = gradient, fix.arg = fix.arg, obs = data, ddistnam = ddistname, hessian = !is.null(gradient), method = meth, ...), silent = TRUE) } else opttryerror <- try(opt <- constrOptim(theta = vstart, f = fnobjcens, ui = Mat, ci = Bnd, grad = gradient, ddistnam = ddistname, rcens = rcens, lcens = lcens, icens = icens, ncens = ncens, pdistnam = pdistname, fix.arg = fix.arg, hessian = !is.null(gradient), method = meth, ...), silent = TRUE) if (!inherits(opttryerror, "try-error")) if (length(opt$counts) == 1) opt$counts <- c(opt$counts, NA) } else { if (!cens) opttryerror <- try(opt <- optim(par = vstart, fn = fnobj, fix.arg = fix.arg, obs = data, gr = gradient, ddistnam = ddistname, hessian = TRUE, method = meth, lower = lower, upper = upper, ...), silent = TRUE) else opttryerror <- try(opt <- optim(par = vstart, fn = fnobjcens, fix.arg = fix.arg, gr = gradient, rcens = rcens, lcens = lcens, icens = icens, ncens = ncens, ddistnam = ddistname, pdistnam = pdistname, hessian = TRUE, method = meth, lower = lower, upper = upper, ...), silent = TRUE) } } else { opt.fun <- "optim" if (!cens) opttryerror <- try(opt <- optim(par = vstart, fn = fnobj, fix.arg = fix.arg, obs = data, gr = gradient, ddistnam = ddistname, hessian = TRUE, method = method, lower = lower, upper = upper, control=list(trace=6), ...), silent = TRUE) else opttryerror <- try(opt <- optim(par = vstart, fn = fnobjcens, fix.arg = fix.arg, gr = gradient, rcens = rcens, lcens = lcens, icens = icens, ncens = ncens, ddistnam = ddistname, pdistnam = pdistname, hessian = TRUE, method = meth, lower = lower, upper = upper, ...), silent = TRUE) } options(warn = owarn) if (inherits(opttryerror, "try-error")) { warnings("The function optim encountered an error and stopped.") if (getOption("show.error.messages")) print(attr(opttryerror, "condition")) return(list(estimate = rep(NA, length(vstart)), convergence = 100, loglik = NA, hessian = NA, optim.function = opt.fun, fix.arg = fix.arg, optim.method = meth, fix.arg.fun = fix.arg.fun, counts = c(NA, NA))) } if (opt$convergence > 0) { warnings("The function optim failed to converge, with the error code ", opt$convergence) } if (is.null(names(opt$par))) names(opt$par) <- names(vstart) res <- list(estimate = opt$par, convergence = opt$convergence, value = opt$value, hessian = opt$hessian, optim.function = opt.fun, optim.method = meth, fix.arg = fix.arg, fix.arg.fun = fix.arg.fun, weights = weights, counts = opt$counts, optim.message = opt$message, loglik = -opt$value) } else { options(warn = ifelse(silent, -1, 0)) if (!cens) opttryerror <- try(opt <- custom.optim(fn = fnobj, fix.arg = fix.arg, obs = data, ddistnam = ddistname, par = vstart, ...), silent = TRUE) else opttryerror <- try(opt <- custom.optim(fn = fnobjcens, fix.arg = fix.arg, rcens = rcens, lcens = lcens, icens = icens, ncens = ncens, ddistnam = ddistname, pdistnam = pdistname, par = vstart, ...), silent = TRUE) options(warn = owarn) if (inherits(opttryerror, "try-error")) { warnings("The customized optimization function encountered an error and stopped.") if (getOption("show.error.messages")) print(attr(opttryerror, "condition")) return(list(estimate = rep(NA, length(vstart)), convergence = 100, loglik = NA, hessian = NA, optim.function = custom.optim, fix.arg = fix.arg, fix.arg.fun = fix.arg.fun, counts = c(NA, NA))) } if (opt$convergence > 0) { warnings("The customized optimization function failed to converge, with the error code ", opt$convergence) } if (is.null(names(opt$par))) names(opt$par) <- names(vstart) argdot <- list(...) method.cust <- argdot$method res <- list(estimate = opt$par, convergence = opt$convergence, value = opt$value, hessian = opt$hessian, optim.function = custom.optim, optim.method = method.cust, fix.arg = fix.arg, fix.arg.fun = fix.arg.fun, weights = weights, counts = opt$counts, optim.message = opt$message, loglik = -opt$value) } return(res) } z= trace(x.1972, 'gb2', start = list(shape1 = 1, shape2 = 1, shape3 = 1, scale = 1), lower = c(0, 0, 0, 0), optim.method = 'Nelder-Mead')
# PREAMBLE #### if(!require(tidyverse)) { install.packages("tidyverse") library(tidyverse) } # Get SIC codes #### codes <- read.csv("data/SIC_codes.csv", stringsAsFactors = F) # Source SIC codes from ONS # url <- "http://resources.companieshouse.gov.uk/sic/" # t <- htmltab(doc = url) # cats <- ifelse(!grepl("[0-9]+", t$Code), t$Description, NA) # t$cat <- zoo::na.locf(cats) # codes <- t[grepl("[0-9]+", t$Code),] # write.csv(t, "SIC_codes.csv") # Get dap data #### gap <- read.csv("data/gap_data.csv", stringsAsFactors = F) # Assign sector data gap$sector <- codes$cat[match(gap$SicCodes,codes$Code)] # NOTE THAT ~ CODES WERE NOT MATCHED! # Plot #### sec_keep <- c("Manufacturing", "Administrative and support service activities", "Wholesale and retail trade; repair of motor vehicles and motorcycles", "Professional, scientific and technical activities", "Financial and insurance activities" ) xlabs2 <- c("Manufacturing", "Admin & services", "Wholesale and retail", "Professional & scientific", "Financial & insurance" ) gap %>% dplyr::mutate( # EmployerSize = factor( # ifelse(EmployerSize == "Not Provided", NA, EmployerSize), # levels = c("Less than 250","250 to 499","500 to 999","1000 to 4999", "5000 to 19,999", "20,000 or more") # ) sector = factor(sector, levels = sec_keep) ) %>% dplyr::filter(sector %in% sec_keep) %>% dplyr::rename(var = sector) %>% dplyr::group_by(var) %>% dplyr::summarise( `Hourly rate (mean)` = mean(DiffMeanHourlyPercent), # median = median(DiffMeanHourlyPercent), `Bonus payment (mean)` = mean(DiffMeanBonusPercent) # median_bonus = median(DiffMedianBonusPercent) ) %>% reshape2::melt(id="var") %>% ggplot(aes(x = var, y = value, fill = var)) + geom_col(position = "dodge") + scale_fill_discrete("Sector",labels = xlabs2) + scale_y_continuous("% by which women are paid less than men") + scale_x_discrete("") + facet_grid(~variable) + # theme_bw() + labs(title = "Gender pay gap in the UK (2017-18)", caption = "Source: @d_alburez with data from https://gender-pay-gap.service.gov.uk/") + theme_bw() + theme(axis.text.x=element_blank(), axis.ticks.x=element_blank(), text = element_text(size=14))	/gap.r	no_license	alburezg/pay_gap_UK	R	false	false	2,393	r	# PREAMBLE #### if(!require(tidyverse)) { install.packages("tidyverse") library(tidyverse) } # Get SIC codes #### codes <- read.csv("data/SIC_codes.csv", stringsAsFactors = F) # Source SIC codes from ONS # url <- "http://resources.companieshouse.gov.uk/sic/" # t <- htmltab(doc = url) # cats <- ifelse(!grepl("[0-9]+", t$Code), t$Description, NA) # t$cat <- zoo::na.locf(cats) # codes <- t[grepl("[0-9]+", t$Code),] # write.csv(t, "SIC_codes.csv") # Get dap data #### gap <- read.csv("data/gap_data.csv", stringsAsFactors = F) # Assign sector data gap$sector <- codes$cat[match(gap$SicCodes,codes$Code)] # NOTE THAT ~ CODES WERE NOT MATCHED! # Plot #### sec_keep <- c("Manufacturing", "Administrative and support service activities", "Wholesale and retail trade; repair of motor vehicles and motorcycles", "Professional, scientific and technical activities", "Financial and insurance activities" ) xlabs2 <- c("Manufacturing", "Admin & services", "Wholesale and retail", "Professional & scientific", "Financial & insurance" ) gap %>% dplyr::mutate( # EmployerSize = factor( # ifelse(EmployerSize == "Not Provided", NA, EmployerSize), # levels = c("Less than 250","250 to 499","500 to 999","1000 to 4999", "5000 to 19,999", "20,000 or more") # ) sector = factor(sector, levels = sec_keep) ) %>% dplyr::filter(sector %in% sec_keep) %>% dplyr::rename(var = sector) %>% dplyr::group_by(var) %>% dplyr::summarise( `Hourly rate (mean)` = mean(DiffMeanHourlyPercent), # median = median(DiffMeanHourlyPercent), `Bonus payment (mean)` = mean(DiffMeanBonusPercent) # median_bonus = median(DiffMedianBonusPercent) ) %>% reshape2::melt(id="var") %>% ggplot(aes(x = var, y = value, fill = var)) + geom_col(position = "dodge") + scale_fill_discrete("Sector",labels = xlabs2) + scale_y_continuous("% by which women are paid less than men") + scale_x_discrete("") + facet_grid(~variable) + # theme_bw() + labs(title = "Gender pay gap in the UK (2017-18)", caption = "Source: @d_alburez with data from https://gender-pay-gap.service.gov.uk/") + theme_bw() + theme(axis.text.x=element_blank(), axis.ticks.x=element_blank(), text = element_text(size=14))
Tapkee <- function(data, method="pca", td=2, verbose=FALSE, add="", prefix="Dim", rm=TRUE) { tmp <- tempfile(c("tapkee_in", "tapkee_out")) data <- as.matrix(data) if (!is.numeric(data)) stop("All columns must be numeric") write.table(data, file=tmp[1], sep=",", row.names=FALSE, col.names=FALSE, quote=FALSE) arg <- paste("tapkee", "-i", tmp[1], "-o", tmp[2], "-m", method, "-td", td, ifelse(verbose, "--verbose", ""), add) system(arg) if (file.exists(tmp[2]) && file.size(tmp[2]) > 0) { res <- read.table(tmp[2], sep=",", comment.char="", colClasses="numeric", nrows=nrow(data)) names(res) <- paste0(prefix, 1:length(names(res))) } else { warning("No 'tapkee' output, I return your input back. Did you install 'tapkee' properly?") res <- data } if(rm) unlink(tmp) return(res) }	/R/tapkee.r	no_license	cran/tapkee	R	false	false	797	r	Tapkee <- function(data, method="pca", td=2, verbose=FALSE, add="", prefix="Dim", rm=TRUE) { tmp <- tempfile(c("tapkee_in", "tapkee_out")) data <- as.matrix(data) if (!is.numeric(data)) stop("All columns must be numeric") write.table(data, file=tmp[1], sep=",", row.names=FALSE, col.names=FALSE, quote=FALSE) arg <- paste("tapkee", "-i", tmp[1], "-o", tmp[2], "-m", method, "-td", td, ifelse(verbose, "--verbose", ""), add) system(arg) if (file.exists(tmp[2]) && file.size(tmp[2]) > 0) { res <- read.table(tmp[2], sep=",", comment.char="", colClasses="numeric", nrows=nrow(data)) names(res) <- paste0(prefix, 1:length(names(res))) } else { warning("No 'tapkee' output, I return your input back. Did you install 'tapkee' properly?") res <- data } if(rm) unlink(tmp) return(res) }
context("ngraph class") library(igraph, warn.conflicts = FALSE) # make a very simple neuron # 1 2 3b 4 5 # 6 testd=data.frame(PointNo=1:6,Label=2, X=c(1:5,3),Y=c(rep(1,5),2),Z=0,W=NA, Parent=c(-1,1:4,3)) test_that("as.ngraph can convert swc data into an ngraph object",{ g1=as.ngraph(testd) expect_is(g1,'ngraph') # check we keep ngraph class when modifying ngraph expect_is(set.graph.attribute(g1,'origin',1),'ngraph') # same neuron with PointNo 2 greater testd2=data.frame(PointNo=3:8,Label=2, X=c(1:5,3),Y=c(rep(1,5),2),Z=0,W=NA, Parent=c(-1,2+c(1:4,3))) g2=as.ngraph(testd2) expect_true(graph.isomorphic(g1,g2)) }) test_that("equivalence of seglist and swc methods for as.ngraph.neuron",{ testn=as.neuron(testd) # isomorphic # 1 2 3b 5 6 # 4 testn2=as.neuron(data.frame( PointNo=1:6,Label=2, X=c(1:3,3,4,5),Y=c(rep(1,3),2,1,1),Z=0,W=NA, Parent=c(-1,1:3,3,5))) # different by vertex position (isomorphic to 1 by connectivity) # 1 2 3b 4 # 5 # 6 testn3=as.neuron(data.frame( PointNo=1:6,Label=2, X=c(1:4,3,3),Y=c(rep(1,4),2,3),Z=0,W=NA, Parent=c(-1,1:3,3,5))) g1=as.ngraph(testn) g2=as.ngraph(testn2) g3=as.ngraph(testn3) #expect_equal(g2,g3) g1s=as.ngraph(testn,method='seglist') g2s=as.ngraph(testn2,method='seglist') g3s=as.ngraph(testn3,method='seglist') #expect_equal(g2s,g3s) expect_true(graph.isomorphic(g1,g2)) expect_true(graph.isomorphic(g1s,g1)) expect_true(graph.isomorphic(g2s,g2)) expect_true(graph.isomorphic(g1,g3)) expect_true(graph.isomorphic(g1s,g3s)) myidentical_graph<-function(target, current, ...){ old_igraph = package_version(igraph::igraph.version())<'1.0' if(old_igraph) isTRUE(all.equal(target, current, ...)) else igraph::identical_graphs(target, current) } expect_true(myidentical_graph(g1,g1s)) expect_true(myidentical_graph(g2,g2s)) expect_true(myidentical_graph(g3,g3s)) }) test_that("we can construct an empty ngraph",{ expect_is(ngraph(matrix(nrow=0,ncol=2),vertexlabels = 1, xyz=cbind(0,0,0,0)), 'ngraph') }) test_that("as.ngraph/as.neuron",{ n <- Cell07PNs[[1]] expect_is(g<-as.ngraph(n), 'ngraph') expect_equal(g, as.ngraph(g)) # as.neuron.igraph class(g)='igraph' expect_equal(n, as.neuron(g)) g2=igraph::delete_edges(g, 1:3) expect_is(as.neuron(g2), 'neuron') }) test_that("we can find the length of the spine of a neuron", { n <- Cell07PNs[[1]] spine.length <- spine(n, rval='length') spine.length.expected <- 186.085903694106 expect_equal(spine.length, spine.length.expected, tolerance=1e-4) }) test_that("we can find the path of the spine of a neuron", { n <- Cell07PNs[[1]] expect_is(spine <- spine(n), 'neuron') spine.expected <- readRDS('testdata/neuron/testCell07PNs1_spine.rds') expect_equal(spine, spine.expected) expect_equal(spine(n, rval='length'), 186.0859, tol=1e-4) expect_equal(spine(n, rval='ids'), spine.expected$d$PointNo) # check that we get the same result when using start point, # since that is part of result expect_equal(spine(n, UseStartPoint = T), spine.expected) expect_equal(spine(n, UseStartPoint = T, rval='length'), 186.0859, tol=1e-4) # check that can cope with point labels other than 1:n n$d$PointNo=n$d$PointNo+1 spine.expected$PointNo=spine.expected$PointNo+1 expect_equal(spine, spine.expected) }) test_that("we can find the inverse of the spine", { n <- Cell07PNs[[1]] neuron.length=sum(seglengths(n)) expect_is(antispine<-spine(n, invert = TRUE), 'neuron') expect_equal(sum(seglengths(antispine, all = TRUE)), neuron.length-spine(n, rval='length'), tolerance=1e-4) expect_equal(spine(n, invert = TRUE, rval = 'ids'), match(antispine$d$PointNo, n$d$PointNo)) }) test_that("prune_edges (and therefore spine) can cope with paths with reversed edges", { # see https://github.com/jefferis/nat/issues/320 baseline=prune_edges(Cell07PNs[[1]], cbind(1:3, 2:4), invert=TRUE) expect_equal(prune_edges(Cell07PNs[[1]], cbind(c(2,3,3), c(1,2,4)), invert=TRUE), baseline) }) test_that("setting of graph attributes",{ gatts=list(name='testneuron',nclass="PN") expect_is(testg <- as.ngraph(testd, graph.attributes = gatts, vertex.attributes=list(X=testd$X)), 'ngraph') expect_equal(get.graph.attribute(testg, name = 'nclass'), gatts$nclass) expect_equal(get.graph.attribute(testg, name = 'name'), gatts$name) # null attributes expect_equal(get.graph.attribute(testg, name = 'rhubarb'), gatts$rhubarb) # vertex attributes expect_equal(get.vertex.attribute(testg, name = 'X'), testd$X) expect_warning(testg <- as.ngraph(testd, graph.attributes = gatts, vertex.attributes=list(X=testd$X[-1]))) }) test_that("graph weights can be calculated and set",{ # weights for a neuron with unit length segments g1=as.ngraph(testd, weights=TRUE) expect_is(g2 <- as.ngraph(testd, weights=FALSE), 'ngraph') expect_equal(igraph::E(g1)$weight, rep(1, 5)) expect_equal(igraph::diameter(g1), igraph::diameter(g2)) g1=as.ngraph(testd, weights=rep(2,5)) expect_equal(igraph::E(g1)$weight, rep(2, 5)) g3=as.ngraph(Cell07PNs[[1]], weights=TRUE) expect_equal(sum(igraph::E(g3)$weight), 297.1763, tolerance=1e-4) }) test_that("we can find the segmentgraph of a neuron",{ testn=as.neuron(testd) expect_is(sg<-segmentgraph(testn), 'igraph') baseline=graph(c(1,2,2,3,2,4), directed=TRUE) expect_true(graph.isomorphic(sg, baseline)) expect_equal(E(sg)$weight, c(2, 2, 1)) expect_true(graph.isomorphic(segmentgraph(testn, weights=FALSE), sg)) # check that we can make a segment graph where each edge direction is # reversed expect_is(sgr<-segmentgraph(testn, reverse.edges = TRUE), 'igraph') expect_equal(get.edges(sgr,E(sgr)), get.edges(sg,E(sg))[,2:1]) # and with segment ids included expect_is(sgs<-segmentgraph(testn, segids = TRUE), 'igraph') expect_equal(E(sgs)$segid, 1:3) }) test_that("as.ngraph can convert undirected graph into an ngraph object",{ g1=as.ngraph(testd) expect_is(g2<-as.ngraph(as.undirected(g1), root = rootpoints(g1)), 'ngraph') expect_true(graph.isomorphic(g1,g2)) }) test_that("Strahler order", { n = as.neuron(testd) expect_equal(strahler_order(n), list(points = c(2L, 2L, 2L, 1L, 1L, 1L), segments = c(2L, 1L, 1L))) ns=structure(list(NumPoints = 3L, StartPoint = 1L, BranchPoints = integer(0), EndPoints = c(1L, 3L), nTrees = 1, NumSegs = 1L, SegList = structure(list(1:3), class = c("seglist", "list")), d = structure(list(PointNo = 1:3, Label = c(2, 2, 2), X = c(1, 2, 3), Y = c(1, 1, 1), Z = c(0, 0, 0), W = c(NA, NA, NA), Parent = c(-1L, 1L, 2L)), .Names = c("PointNo", "Label", "X", "Y", "Z", "W", "Parent"), class = "data.frame", row.names = c(NA, -3L))), .Names = c("NumPoints", "StartPoint", "BranchPoints", "EndPoints", "nTrees", "NumSegs", "SegList", "d"), class = c("neuron", "list")) expect_equal(prune_strahler(n, orderstoprune = 1L), ns) })	/tests/testthat/test-ngraph.R	no_license	strategist922/nat	R	false	false	7,239	r	context("ngraph class") library(igraph, warn.conflicts = FALSE) # make a very simple neuron # 1 2 3b 4 5 # 6 testd=data.frame(PointNo=1:6,Label=2, X=c(1:5,3),Y=c(rep(1,5),2),Z=0,W=NA, Parent=c(-1,1:4,3)) test_that("as.ngraph can convert swc data into an ngraph object",{ g1=as.ngraph(testd) expect_is(g1,'ngraph') # check we keep ngraph class when modifying ngraph expect_is(set.graph.attribute(g1,'origin',1),'ngraph') # same neuron with PointNo 2 greater testd2=data.frame(PointNo=3:8,Label=2, X=c(1:5,3),Y=c(rep(1,5),2),Z=0,W=NA, Parent=c(-1,2+c(1:4,3))) g2=as.ngraph(testd2) expect_true(graph.isomorphic(g1,g2)) }) test_that("equivalence of seglist and swc methods for as.ngraph.neuron",{ testn=as.neuron(testd) # isomorphic # 1 2 3b 5 6 # 4 testn2=as.neuron(data.frame( PointNo=1:6,Label=2, X=c(1:3,3,4,5),Y=c(rep(1,3),2,1,1),Z=0,W=NA, Parent=c(-1,1:3,3,5))) # different by vertex position (isomorphic to 1 by connectivity) # 1 2 3b 4 # 5 # 6 testn3=as.neuron(data.frame( PointNo=1:6,Label=2, X=c(1:4,3,3),Y=c(rep(1,4),2,3),Z=0,W=NA, Parent=c(-1,1:3,3,5))) g1=as.ngraph(testn) g2=as.ngraph(testn2) g3=as.ngraph(testn3) #expect_equal(g2,g3) g1s=as.ngraph(testn,method='seglist') g2s=as.ngraph(testn2,method='seglist') g3s=as.ngraph(testn3,method='seglist') #expect_equal(g2s,g3s) expect_true(graph.isomorphic(g1,g2)) expect_true(graph.isomorphic(g1s,g1)) expect_true(graph.isomorphic(g2s,g2)) expect_true(graph.isomorphic(g1,g3)) expect_true(graph.isomorphic(g1s,g3s)) myidentical_graph<-function(target, current, ...){ old_igraph = package_version(igraph::igraph.version())<'1.0' if(old_igraph) isTRUE(all.equal(target, current, ...)) else igraph::identical_graphs(target, current) } expect_true(myidentical_graph(g1,g1s)) expect_true(myidentical_graph(g2,g2s)) expect_true(myidentical_graph(g3,g3s)) }) test_that("we can construct an empty ngraph",{ expect_is(ngraph(matrix(nrow=0,ncol=2),vertexlabels = 1, xyz=cbind(0,0,0,0)), 'ngraph') }) test_that("as.ngraph/as.neuron",{ n <- Cell07PNs[[1]] expect_is(g<-as.ngraph(n), 'ngraph') expect_equal(g, as.ngraph(g)) # as.neuron.igraph class(g)='igraph' expect_equal(n, as.neuron(g)) g2=igraph::delete_edges(g, 1:3) expect_is(as.neuron(g2), 'neuron') }) test_that("we can find the length of the spine of a neuron", { n <- Cell07PNs[[1]] spine.length <- spine(n, rval='length') spine.length.expected <- 186.085903694106 expect_equal(spine.length, spine.length.expected, tolerance=1e-4) }) test_that("we can find the path of the spine of a neuron", { n <- Cell07PNs[[1]] expect_is(spine <- spine(n), 'neuron') spine.expected <- readRDS('testdata/neuron/testCell07PNs1_spine.rds') expect_equal(spine, spine.expected) expect_equal(spine(n, rval='length'), 186.0859, tol=1e-4) expect_equal(spine(n, rval='ids'), spine.expected$d$PointNo) # check that we get the same result when using start point, # since that is part of result expect_equal(spine(n, UseStartPoint = T), spine.expected) expect_equal(spine(n, UseStartPoint = T, rval='length'), 186.0859, tol=1e-4) # check that can cope with point labels other than 1:n n$d$PointNo=n$d$PointNo+1 spine.expected$PointNo=spine.expected$PointNo+1 expect_equal(spine, spine.expected) }) test_that("we can find the inverse of the spine", { n <- Cell07PNs[[1]] neuron.length=sum(seglengths(n)) expect_is(antispine<-spine(n, invert = TRUE), 'neuron') expect_equal(sum(seglengths(antispine, all = TRUE)), neuron.length-spine(n, rval='length'), tolerance=1e-4) expect_equal(spine(n, invert = TRUE, rval = 'ids'), match(antispine$d$PointNo, n$d$PointNo)) }) test_that("prune_edges (and therefore spine) can cope with paths with reversed edges", { # see https://github.com/jefferis/nat/issues/320 baseline=prune_edges(Cell07PNs[[1]], cbind(1:3, 2:4), invert=TRUE) expect_equal(prune_edges(Cell07PNs[[1]], cbind(c(2,3,3), c(1,2,4)), invert=TRUE), baseline) }) test_that("setting of graph attributes",{ gatts=list(name='testneuron',nclass="PN") expect_is(testg <- as.ngraph(testd, graph.attributes = gatts, vertex.attributes=list(X=testd$X)), 'ngraph') expect_equal(get.graph.attribute(testg, name = 'nclass'), gatts$nclass) expect_equal(get.graph.attribute(testg, name = 'name'), gatts$name) # null attributes expect_equal(get.graph.attribute(testg, name = 'rhubarb'), gatts$rhubarb) # vertex attributes expect_equal(get.vertex.attribute(testg, name = 'X'), testd$X) expect_warning(testg <- as.ngraph(testd, graph.attributes = gatts, vertex.attributes=list(X=testd$X[-1]))) }) test_that("graph weights can be calculated and set",{ # weights for a neuron with unit length segments g1=as.ngraph(testd, weights=TRUE) expect_is(g2 <- as.ngraph(testd, weights=FALSE), 'ngraph') expect_equal(igraph::E(g1)$weight, rep(1, 5)) expect_equal(igraph::diameter(g1), igraph::diameter(g2)) g1=as.ngraph(testd, weights=rep(2,5)) expect_equal(igraph::E(g1)$weight, rep(2, 5)) g3=as.ngraph(Cell07PNs[[1]], weights=TRUE) expect_equal(sum(igraph::E(g3)$weight), 297.1763, tolerance=1e-4) }) test_that("we can find the segmentgraph of a neuron",{ testn=as.neuron(testd) expect_is(sg<-segmentgraph(testn), 'igraph') baseline=graph(c(1,2,2,3,2,4), directed=TRUE) expect_true(graph.isomorphic(sg, baseline)) expect_equal(E(sg)$weight, c(2, 2, 1)) expect_true(graph.isomorphic(segmentgraph(testn, weights=FALSE), sg)) # check that we can make a segment graph where each edge direction is # reversed expect_is(sgr<-segmentgraph(testn, reverse.edges = TRUE), 'igraph') expect_equal(get.edges(sgr,E(sgr)), get.edges(sg,E(sg))[,2:1]) # and with segment ids included expect_is(sgs<-segmentgraph(testn, segids = TRUE), 'igraph') expect_equal(E(sgs)$segid, 1:3) }) test_that("as.ngraph can convert undirected graph into an ngraph object",{ g1=as.ngraph(testd) expect_is(g2<-as.ngraph(as.undirected(g1), root = rootpoints(g1)), 'ngraph') expect_true(graph.isomorphic(g1,g2)) }) test_that("Strahler order", { n = as.neuron(testd) expect_equal(strahler_order(n), list(points = c(2L, 2L, 2L, 1L, 1L, 1L), segments = c(2L, 1L, 1L))) ns=structure(list(NumPoints = 3L, StartPoint = 1L, BranchPoints = integer(0), EndPoints = c(1L, 3L), nTrees = 1, NumSegs = 1L, SegList = structure(list(1:3), class = c("seglist", "list")), d = structure(list(PointNo = 1:3, Label = c(2, 2, 2), X = c(1, 2, 3), Y = c(1, 1, 1), Z = c(0, 0, 0), W = c(NA, NA, NA), Parent = c(-1L, 1L, 2L)), .Names = c("PointNo", "Label", "X", "Y", "Z", "W", "Parent"), class = "data.frame", row.names = c(NA, -3L))), .Names = c("NumPoints", "StartPoint", "BranchPoints", "EndPoints", "nTrees", "NumSegs", "SegList", "d"), class = c("neuron", "list")) expect_equal(prune_strahler(n, orderstoprune = 1L), ns) })
	/combine_data.R	no_license	wuweizte/jijin_modelAnalysis	R	false	false	4,516	r
% Generated by roxygen2: do not edit by hand % Please edit documentation in R/utils.R \name{Paste} \alias{Paste} \title{noNApaste} \usage{ Paste(x) } \description{ noNApaste } \examples{ \donttest{ x = c(NA, 1) } }	/man/Paste.Rd	no_license	mpio-be/bib2	R	false	true	215	rd	% Generated by roxygen2: do not edit by hand % Please edit documentation in R/utils.R \name{Paste} \alias{Paste} \title{noNApaste} \usage{ Paste(x) } \description{ noNApaste } \examples{ \donttest{ x = c(NA, 1) } }
% Generated by roxygen2: do not edit by hand % Please edit documentation in R/get_request.R \name{get_requests_lim} \alias{get_requests_lim} \title{Execute multiple get_request calls with rate limiting} \usage{ get_requests_lim(urls, table, user, key, ...) } \description{ Execute multiple get_request calls with rate limiting }	/man/get_requests_lim.Rd	permissive	propellerpdx/harvestR	R	false	true	329	rd	% Generated by roxygen2: do not edit by hand % Please edit documentation in R/get_request.R \name{get_requests_lim} \alias{get_requests_lim} \title{Execute multiple get_request calls with rate limiting} \usage{ get_requests_lim(urls, table, user, key, ...) } \description{ Execute multiple get_request calls with rate limiting }
\name{wrap_get_density} \alias{wrap_get_density} \title{ A function to get the number of markers along consecutive genomic bins from input files for TIGER } \description{ %% ~~ A concise (1-5 lines) description of what the function does. ~~ } \usage{ wrap_get_density(inputfile,binsize,cut=T,chr.match,cutoff=10) } %- maybe also 'usage' for other objects documented here. \arguments{ \item{inputfile}{ A txt input file for TIGER pipeline, usually strat with chr and pos followed by Alleles from one line, allele call,and alleles from another line,and corresponding allele call} \item{binsize}{The size of the genomic bins} \item{cut}{ If the bins with too few markers should be discarded} \item{chr.match}{ a file matching Contig names to chromsome,} \item{cutoff}{ if the number of markers in a bin is smaller than cutoff, this bin would be discarded} } \details{ %% ~~ If necessary, more details than the description above ~~ } \value{ return a vector with number of markers for this input file. %% ~Describe the value returned %% If it is a LIST, use %% \item{comp1 }{Description of 'comp1'} %% \item{comp2 }{Description of 'comp2'} %% ... } \references{ Yanjun Zan, Thibaut Payen, Mette Lillie Leif Andersson, Paul B. Siegel and Örjan Carlborg;Whole-genome QTL mapping in experimental pedigrees from outbred founders utilizing low coverage individual based sequencing 2018 } \author{ Yanjun Zan, Thibaut Payen } \note{ %% ~~further notes~~ } %% ~Make other sections like Warning with \section{Warning }{....} ~ \seealso{ %% ~~objects to See Also as \code{\link{help}}, ~~~ } \examples{ } % Add one or more standard keywords, see file 'KEYWORDS' in the % R documentation directory. \keyword{ ~kwd1 } \keyword{ ~kwd2 }% __ONLY ONE__ keyword per line	/man/wrap_get_density.Rd	no_license	CarlborgGenomics/Stripes_downstream	R	false	false	1,774	rd	\name{wrap_get_density} \alias{wrap_get_density} \title{ A function to get the number of markers along consecutive genomic bins from input files for TIGER } \description{ %% ~~ A concise (1-5 lines) description of what the function does. ~~ } \usage{ wrap_get_density(inputfile,binsize,cut=T,chr.match,cutoff=10) } %- maybe also 'usage' for other objects documented here. \arguments{ \item{inputfile}{ A txt input file for TIGER pipeline, usually strat with chr and pos followed by Alleles from one line, allele call,and alleles from another line,and corresponding allele call} \item{binsize}{The size of the genomic bins} \item{cut}{ If the bins with too few markers should be discarded} \item{chr.match}{ a file matching Contig names to chromsome,} \item{cutoff}{ if the number of markers in a bin is smaller than cutoff, this bin would be discarded} } \details{ %% ~~ If necessary, more details than the description above ~~ } \value{ return a vector with number of markers for this input file. %% ~Describe the value returned %% If it is a LIST, use %% \item{comp1 }{Description of 'comp1'} %% \item{comp2 }{Description of 'comp2'} %% ... } \references{ Yanjun Zan, Thibaut Payen, Mette Lillie Leif Andersson, Paul B. Siegel and Örjan Carlborg;Whole-genome QTL mapping in experimental pedigrees from outbred founders utilizing low coverage individual based sequencing 2018 } \author{ Yanjun Zan, Thibaut Payen } \note{ %% ~~further notes~~ } %% ~Make other sections like Warning with \section{Warning }{....} ~ \seealso{ %% ~~objects to See Also as \code{\link{help}}, ~~~ } \examples{ } % Add one or more standard keywords, see file 'KEYWORDS' in the % R documentation directory. \keyword{ ~kwd1 } \keyword{ ~kwd2 }% __ONLY ONE__ keyword per line
% Generated by roxygen2: do not edit by hand % Please edit documentation in R/rgcForest.R \docType{package} \name{gcForest-package} \alias{gcForest-package} \title{gcForest-package} \description{ R application programming interface (API) for Deep Forest which based on Zhi-hua Zhou and Ji Feng. Deep Forest: Towards an Alternative to Deep Neural Networks. In IJCAI-2017. (\url{https://arxiv.org/abs/1702.08835v2}) or Zhi-hua Zhou and Ji Feng. Deep Forest. In IJCAI-2017.(<https://arxiv.org/abs/1702.08835>), and the Python application programming interface (API) (\url{https://github.com/pylablanche/gcForest}) } \examples{ # ========= Model train======= have_numpy <- reticulate::py_module_available("numpy") have_sklearn <- reticulate::py_module_available("sklearn") if(have_numpy && have_sklearn){ library(gcForest) # req_py() sk <- NULL .onLoad <- function(libname, pkgname) { sk <<- reticulate::import("sklearn", delay_load = TRUE) } sk <<- reticulate::import("sklearn", delay_load = TRUE) train_test_split <- sk$model_selection$train_test_split data <- sk$datasets$load_iris iris <- data() X = iris$data y = iris$target data_split = train_test_split(X, y, test_size=0.33) X_tr <- data_split[[1]] X_te <- data_split[[2]] y_tr <- data_split[[3]] y_te <- data_split[[4]] gcforest_m <- gcforest(shape_1X=4L, window=2L, tolerance=0.0) gcforest_m$fit(X_tr, y_tr) gcf_model <- model_save(gcforest_m,'gcforest_model.model') gcf <- model_load('gcforest_model.model') gcf$predict(X_te) # learn more from gcForest package tutorial utils::vignette('gcForest-docs') }else{ print('You should have the Python testing environment!') } } \seealso{ [1] Zhi-hua Zhou and Ji Feng. Deep Forest: Towards an Alternative to Deep Neural Networks.In IJCAI-2017. (\url{https://arxiv.org/abs/1702.08835v2}) [2] Zhi-hua Zhou and Ji Feng. Deep Forest. In IJCAI-2017.(\url{https://arxiv.org/abs/1702.08835}) [3] \url{https://github.com/pylablanche/gcForest} } \author{ Xu Jing }	/man/gcForest-package.Rd	no_license	cran/gcForest	R	false	true	2,116	rd	% Generated by roxygen2: do not edit by hand % Please edit documentation in R/rgcForest.R \docType{package} \name{gcForest-package} \alias{gcForest-package} \title{gcForest-package} \description{ R application programming interface (API) for Deep Forest which based on Zhi-hua Zhou and Ji Feng. Deep Forest: Towards an Alternative to Deep Neural Networks. In IJCAI-2017. (\url{https://arxiv.org/abs/1702.08835v2}) or Zhi-hua Zhou and Ji Feng. Deep Forest. In IJCAI-2017.(<https://arxiv.org/abs/1702.08835>), and the Python application programming interface (API) (\url{https://github.com/pylablanche/gcForest}) } \examples{ # ========= Model train======= have_numpy <- reticulate::py_module_available("numpy") have_sklearn <- reticulate::py_module_available("sklearn") if(have_numpy && have_sklearn){ library(gcForest) # req_py() sk <- NULL .onLoad <- function(libname, pkgname) { sk <<- reticulate::import("sklearn", delay_load = TRUE) } sk <<- reticulate::import("sklearn", delay_load = TRUE) train_test_split <- sk$model_selection$train_test_split data <- sk$datasets$load_iris iris <- data() X = iris$data y = iris$target data_split = train_test_split(X, y, test_size=0.33) X_tr <- data_split[[1]] X_te <- data_split[[2]] y_tr <- data_split[[3]] y_te <- data_split[[4]] gcforest_m <- gcforest(shape_1X=4L, window=2L, tolerance=0.0) gcforest_m$fit(X_tr, y_tr) gcf_model <- model_save(gcforest_m,'gcforest_model.model') gcf <- model_load('gcforest_model.model') gcf$predict(X_te) # learn more from gcForest package tutorial utils::vignette('gcForest-docs') }else{ print('You should have the Python testing environment!') } } \seealso{ [1] Zhi-hua Zhou and Ji Feng. Deep Forest: Towards an Alternative to Deep Neural Networks.In IJCAI-2017. (\url{https://arxiv.org/abs/1702.08835v2}) [2] Zhi-hua Zhou and Ji Feng. Deep Forest. In IJCAI-2017.(\url{https://arxiv.org/abs/1702.08835}) [3] \url{https://github.com/pylablanche/gcForest} } \author{ Xu Jing }

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