diff --git a/checklist.txt b/checklist.txt
new file mode 100644
index 0000000..4b9edba
--- /dev/null
+++ b/checklist.txt
@@ -0,0 +1,19 @@
+Checklist to release a new build to NPM:
+  * Clone the repository if needed
+  * Checkout develop branch and make sure develop branch is up-to-date with remote
+  * If git flow is not initialized yet, Run: git flow init
+  * Create a new release branch, Run: git flow release start <new_version_with_v_character>
+  * Delete all existing npm dependencies, Run: rm -rf node_modules package-lock.json
+  * Install dependencies again, Run: npm install
+  * Update package version with new release version in package.json
+  * Update LICENSE file if needed
+  * Update README.md file if needed
+  * Now, create a release-ready build, Run: npm run build
+  * Test the dist/* files if needed
+  * Now commit all the changes with this message: "Make a build and bump version"
+  * Then finish the release, Run: git flow release finish [-s] <new_version_with_v_character> and enter release notes
+  * Push all changes and tags to remote, Run: git push origin master && git push origin develop && git push origin --tags
+  * Edit the title of the released tag in Github
+  * When everything is fine, it's ready to release
+  * Checkout master branch
+  * Now if everything is fine, release it to npm, Run: npm publish
\ No newline at end of file
diff --git a/dist/datamodel.js b/dist/datamodel.js
index e351b81..6d220a4 100644
--- a/dist/datamodel.js
+++ b/dist/datamodel.js
@@ -1,2 +1,2 @@
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a===V?o.select((function(e){return r.every((function(t){return t(e)}))}),{saveChild:!1}):o.select((function(e){return r.some((function(t){return t(e)}))}),{saveChild:!1})},xt=function(e,t,n,r,a){e._rowDiffset=t,e.__calculateFieldspace().calculateFieldsConfig(),Ft(n,e,L.SELECT,{config:r},a)},Lt=function(e,t,n,r){var a=e.clone(n.saveChild),i=t;return n.mode===l.INVERSE&&(i=r.filter((function(e){return-1===t.indexOf(e)}))),a._colIdentifier=i.join(","),a.__calculateFieldspace().calculateFieldsConfig(),Ft(e,a,L.PROJECT,{projField:t,config:n,actualProjField:i},null),a},Ut=function(e,t,n,r){return t.map((function(t){return Lt(e,t,n,r)}))},Vt=function(e){if((e=_({},e)).type||(e.type=f.DIMENSION),!e.subtype)switch(e.type){case f.MEASURE:e.subtype=c.CONTINUOUS;break;default:case f.DIMENSION:e.subtype=u.CATEGORICAL}return e},Bt=function(e){return e.map((function(e){return function(e){var t=[c.CONTINUOUS],n=[u.CATEGORICAL,u.BINNED,u.TEMPORAL,u.GEO],r=e.type,a=e.subtype,i=e.name;switch(r){case f.DIMENSION:if(-1===n.indexOf(a))throw new Error("DataModel doesn't support dimension field subtype "+a+" used for "+i+" field");break;case f.MEASURE:if(-1===t.indexOf(a))throw new Error("DataModel doesn't support measure field subtype "+a+" used for "+i+" field");break;default:throw new Error("DataModel doesn't support field type "+r+" used for "+i+" field")}}(e=Vt(e)),e}))},Yt=function(e,t,n,r){n=Bt(n),r=Object.assign(Object.assign({},nt),r);var i=a[r.dataFormat];if(!i||"function"!=typeof i)throw new Error("No converter function found for "+r.dataFormat+" format");var u=i(t,n,r),c=wt(u,2),f=c[0],l=c[1];!function(e,t){e.forEach((function(e){var n=e.as;if(n){var r=t.indexOf(e.name);t[r]=n,e.name=n,delete e.as}}))}(n,f);var s=tt(l,n,f),d=F.createNamespace(s,r.name);e._partialFieldspace=d,e._rowDiffset=l.length&&l[0].length?"0-"+(l[0].length-1):"";var p=[],h=d.fields,v=h.map((function(e){return e.data()})),m=h.map((function(e){return e.formattedData()}));return T(e._rowDiffset,(function(e){p[e]=Et(h,m,v,e)})),d._cachedValueObjects=p,e._colIdentifier=n.map((function(e){return e.name})).join(),e._dataFormat=r.dataFormat===o.AUTO?D(t):r.dataFormat,e},Ht=function(e,t){for(var n=0;n<e.length;++n)if(t===e[n].name)return{name:t,type:e[n].subtype||e[n].type,index:n};return null},Gt=function(e,t){var n=t.getDerivations(),r=e;return n.forEach((function(e){if(e){var t,n=function(e){var t=[],n=void 0;switch(n=e.op){case L.SELECT:t=[e.criteria];break;case L.PROJECT:t=[e.meta.actualProjField];break;case L.SORT:t=[e.criteria];break;case L.GROUPBY:n="groupBy",t=[e.meta.groupByString.split(","),e.criteria];break;default:n=null}return{operation:n,params:t}}(e),a=n.operation,i=n.params;if(a)r=(t=r)[a].apply(t,_t(i).concat([{saveChild:!1}]))}})),r},Jt=function e(t,n){var r=arguments.length>2&&void 0!==arguments[2]?arguments[2]:{},a=arguments.length>3&&void 0!==arguments[3]?arguments[3]:{},i=a.nonTraversingModel,o=a.excludeModels||[];if(t!==i){var u=!o.length||-1===o.indexOf(t);u&&t.handlePropagation(n,r);var c=t._children;c.forEach((function(t){var i=Gt(n,t);e(t,i,r,a)}))}},zt=function(e){for(;e._parent&&e._derivation.find((function(e){return e.op!==L.GROUPBY}));)e=e._parent;return e},Kt=function(e){for(;e._parent;)e=e._parent;return e},Wt=function(e){for(var t=arguments.length>1&&void 0!==arguments[1]?arguments[1]:[];e._parent;)t.push(e),e=e._parent;return t},Xt=function(e,t,n,r){var a=void 0,i=void 0,o=n.propagationNameSpace,u=n.propagateToSource,c=n.sourceId,f=r.propagateInterpolatedValues,l=[];if(null===e&&!0!==r.persistent)l=[{criteria:[]}],a=[];else{var s,d=Object.values(o.mutableActions);!1!==u&&(d=d.filter((function(e){return e.config.sourceId!==c})));var p=d.filter((function(e){return(r.filterFn||function(){return!0})(e,r)})).map((function(e){return e.config.criteria})),h=[];if(!1!==u){var v=Object.values(o.mutableActions);v.forEach((function(e){var t=e.config;!1===t.applyOnSource&&t.action===r.action&&t.sourceId!==c&&(h.push(e.model),(a=v.filter((function(t){return t!==e})).map((function(e){return e.config.criteria}))).length&&l.push({criteria:a,models:e.model,path:Wt(e.model)}))}))}a=(s=[]).concat.apply(s,[].concat(_t(p),[e])).filter((function(e){return null!==e})),l.push({criteria:a,excludeModels:[].concat(h,_t(r.excludeModels||[]))})}var m=t.model,y=Object.assign({sourceIdentifiers:e,propagationSourceId:c},r),g=t.groupByModel;f&&g&&(i=Pt(g,a,{filterByMeasure:f}),Jt(g,i,y)),l.forEach((function(e){var t=Pt(m,e.criteria),n=e.path;if(n){var r=function(e,t){for(var n=0,r=t.length;n<r;n++){var a=t[n];e=Gt(e,a)}return e}(t,n.reverse());e.models.handlePropagation(r,y)}else Jt(m,t,y,{excludeModels:e.excludeModels,nonTraversingModel:f&&g})}))},qt=function(e,t,n){var r=e.immutableActions;for(var a in r){var i=r[a].config,o=n.config.sourceId,u=!n.propConfig.filterImmutableAction||n.propConfig.filterImmutableAction(i,n.config);if(i.sourceId!==o&&u){var c=i.criteria;Xt(c,t,{propagationNameSpace:e,propagateToSource:!1,sourceId:o},i)}}},Zt=function(e){var t=arguments.length>1&&void 0!==arguments[1]?arguments[1]:{},n=arguments[2],r=void 0,a=t.isMutableAction,i=t.criteria,o=t.action+"-"+t.sourceId;r=a?e.mutableActions:e.immutableActions,null===i?delete r[o]:r[o]={model:n,config:t}},$t=function(e,t,n){var r=e.reduce((function(e,r){return"RegExp"===r.constructor.name?e.push.apply(e,_t(t.filter((function(e){return-1!==e.search(r)})))):r in n&&e.push(r),e}),[]);return Array.from(new Set(r)).map((function(e){return e.trim()}))},Qt=function(e,t){return e.numberFormat?e.numberFormat()(t):t},en=function(){function e(e,t){for(var n=0;n<t.length;n++){var r=t[n];r.enumerable=r.enumerable||!1,r.configurable=!0,"value"in r&&(r.writable=!0),Object.defineProperty(e,r.key,r)}}return function(t,n,r){return n&&e(t.prototype,n),r&&e(t,r),t}}();var tn=function(){function e(){!function(e,t){if(!(e instanceof t))throw new TypeError("Cannot call a class as a function")}(this,e);var t=void 0;this._parent=null,this._derivation=[],this._ancestorDerivation=[],this._children=[];for(var n=arguments.length,r=Array(n),a=0;a<n;a++)r[a]=arguments[a];1===r.length&&(t=r[0])instanceof e?(this._colIdentifier=t._colIdentifier,this._rowDiffset=t._rowDiffset,this._dataFormat=t._dataFormat,this._parent=t,this._partialFieldspace=this._parent._partialFieldspace,this._fieldStoreName=A(),this.__calculateFieldspace().calculateFieldsConfig()):(Yt.apply(void 0,[this].concat(r)),this._fieldStoreName=this._partialFieldspace.name,this.__calculateFieldspace().calculateFieldsConfig(),this._propagationNameSpace={mutableActions:{},immutableActions:{}})}return en(e,[{key:"getSchema",value:function(){return this.getFieldspace().fields.map((function(e){return e.schema()}))}},{key:"getName",value:function(){return this._fieldStoreName}},{key:"getFieldspace",value:function(){return this._fieldspace}},{key:"__calculateFieldspace",value:function(){return this._fieldspace=jt([this._rowDiffset,this._colIdentifier],this.getPartialFieldspace(),this._fieldStoreName),this}},{key:"getPartialFieldspace",value:function(){return this._partialFieldspace}},{key:"join",value:function(e,t){return G(this,e,t)}},{key:"naturalJoin",value:function(e){return G(this,e,je(this,e),!0)}},{key:"union",value:function(e){return Se(this,e)}},{key:"difference",value:function(e){return re(this,e)}},{key:"select",value:function(e,t){var n={mode:l.NORMAL,saveChild:!0};return(t=Object.assign({},n,t)).mode=t.mode||n.mode,function(e,t,n,r){var a={},i=n.mode,o=e.clone(r.saveChild),u=Ct(o,t,n,e,Tt),c=Nt[i].diffIndex;return xt(o,u[c[0]],e,n,t),c.length>1?(a=e.clone(r.saveChild),xt(a,u[c[1]],e,n,t),[o,a]):o}(this,e,t,{saveChild:t.saveChild})}},{key:"isEmpty",value:function(){return!this._rowDiffset.length||!this._colIdentifier.length}},{key:"clone",value:function(){var e=!(arguments.length>0&&void 0!==arguments[0])||arguments[0],t=new this.constructor(this);return e?t.setParent(this):t.setParent(null),t}},{key:"project",value:function(e,t){var n={mode:l.NORMAL,saveChild:!0};t=Object.assign({},n,t);var r=this.getFieldsConfig(),a=Object.keys(r),i=t.mode,o=$t(e,a,r),u=void 0;i===l.ALL?u=[Lt(this,o,{mode:l.NORMAL,saveChild:t.saveChild},a),Lt(this,o,{mode:l.INVERSE,saveChild:t.saveChild},a)]:u=Lt(this,o,t,a);return u}},{key:"getFieldsConfig",value:function(){return this._fieldConfig}},{key:"calculateFieldsConfig",value:function(){return this._fieldConfig=this._fieldspace.fields.reduce((function(e,t,n){return e[t.name()]={index:n,def:t.schema()},e}),{}),this}},{key:"dispose",value:function(){this._parent&&this._parent.removeChild(this),this._parent=null,this._children.forEach((function(e){e._parent=null})),this._children=[]}},{key:"removeChild",value:function(e){var t=this._children.findIndex((function(t){return t===e}));-1===t||this._children.splice(t,1)}},{key:"setParent",value:function(e){this._parent&&this._parent.removeChild(this),this._parent=e,e&&e._children.push(this)}},{key:"getParent",value:function(){return this._parent}},{key:"getChildren",value:function(){return this._children}},{key:"getDerivations",value:function(){return this._derivation}},{key:"getAncestorDerivations",value:function(){return this._ancestorDerivation}}]),e}(),nn=function(e,t){if(Array.isArray(e))return e;if(Symbol.iterator in Object(e))return function(e,t){var n=[],r=!0,a=!1,i=void 0;try{for(var o,u=e[Symbol.iterator]();!(r=(o=u.next()).done)&&(n.push(o.value),!t||n.length!==t);r=!0);}catch(e){a=!0,i=e}finally{try{!r&&u.return&&u.return()}finally{if(a)throw i}}return n}(e,t);throw new TypeError("Invalid attempt to destructure non-iterable instance")},rn=function(){function e(e,t){for(var n=0;n<t.length;n++){var r=t[n];r.enumerable=r.enumerable||!1,r.configurable=!0,"value"in r&&(r.writable=!0),Object.defineProperty(e,r.key,r)}}return function(t,n,r){return n&&e(t.prototype,n),r&&e(t,r),t}}();function an(e){if(Array.isArray(e)){for(var t=0,n=Array(e.length);t<e.length;t++)n[t]=e[t];return n}return Array.from(e)}var on=function(e){function t(){var e;!function(e,t){if(!(e instanceof t))throw new TypeError("Cannot call a class as a function")}(this,t);for(var n=arguments.length,r=Array(n),a=0;a<n;a++)r[a]=arguments[a];var i=function(e,t){if(!e)throw new ReferenceError("this hasn't been initialised - super() hasn't been called");return!t||"object"!=typeof t&&"function"!=typeof t?e:t}(this,(e=t.__proto__||Object.getPrototypeOf(t)).call.apply(e,[this].concat(r)));return i._onPropagation=[],i}return function(e,t){if("function"!=typeof t&&null!==t)throw new TypeError("Super expression must either be null or a function, not "+typeof t);e.prototype=Object.create(t&&t.prototype,{constructor:{value:e,enumerable:!1,writable:!0,configurable:!0}}),t&&(Object.setPrototypeOf?Object.setPrototypeOf(e,t):e.__proto__=t)}(t,e),rn(t,[{key:"getData",value:function(e){e=Object.assign({},{order:"row",formatter:null,withUid:!1,getAllFields:!1,sort:[]},e);var t=this.getPartialFieldspace().fields,n=ne.call(this,this.getPartialFieldspace().fields,this._rowDiffset,e.getAllFields?t.map((function(e){return e.name()})).join():this._colIdentifier,e.sort,{columnWise:"column"===e.order,addUid:!!e.withUid});if(!e.formatter)return n;var r=e.formatter,a=n.data,i=n.schema,o=n.uids,u=i.map((function(e){return e.name})),c=Object.keys(r).reduce((function(e,t){var n=u.indexOf(t);return-1!==n&&e.push([n,r[t]]),e}),[]);return"column"===e.order?c.forEach((function(e){var t=e[0],n=e[1];a[t].forEach((function(e,r){a[t][r]=n.call(void 0,e,o[r],i[t])}))})):a.forEach((function(e,t){c.forEach((function(n){var r=n[0],a=n[1];e[r]=a.call(void 0,e[r],o[t],i[r])}))})),n}},{key:"getUids",value:function(){var e=this._rowDiffset,t=[];e.length&&e.split(",").forEach((function(e){var n=e.split("-").map(Number),r=nn(n,2),a=r[0],i=r[1];i=void 0!==i?i:a,t.push.apply(t,an(Array(i-a+1).fill().map((function(e,t){return a+t}))))}));return t}},{key:"groupBy",value:function(e){var t=arguments.length>1&&void 0!==arguments[1]?arguments[1]:{},n=arguments.length>2&&void 0!==arguments[2]?arguments[2]:{saveChild:!0},r=""+e.join(),a=[this,e,t],i=Ae.apply(void 0,a);return Ft(this,i,L.GROUPBY,{fieldsArr:e,groupByString:r,defaultReducer:_e.defaultReducer()},t),n.saveChild?i.setParent(this):i.setParent(null),i}},{key:"sort",value:function(e){var t=arguments.length>1&&void 0!==arguments[1]?arguments[1]:{saveChild:!1},n=this.getData({order:"row",sort:e}),r=n.schema.map((function(e){return e.name})),a=[r].concat(n.data),i=new this.constructor(a,n.schema,{dataFormat:"DSVArr"});return Ft(this,i,L.SORT,t,e),t.saveChild?i.setParent(this):i.setParent(null),i}},{key:"serialize",value:function(e,t){e=e||this._dataFormat,t=Object.assign({},{fieldSeparator:","},t);var n=this.getFieldspace().fields,r=n.map((function(e){return e.formattedData()})),a=r[0].length,i=void 0,u=void 0,c=void 0;if(e===o.FLAT_JSON)for(i=[],u=0;u<a;u++){var f={};for(c=0;c<n.length;c++)f[n[c].name()]=r[c][u];i.push(f)}else if(e===o.DSV_STR){for(i=[n.map((function(e){return e.name()})).join(t.fieldSeparator)],u=0;u<a;u++){var l=[];for(c=0;c<n.length;c++)l.push(r[c][u]);i.push(l.join(t.fieldSeparator))}i=i.join("\n")}else{if(e!==o.DSV_ARR)throw new Error("Data type "+e+" is not supported");for(i=[n.map((function(e){return e.name()}))],u=0;u<a;u++){var s=[];for(c=0;c<n.length;c++)s.push(r[c][u]);i.push(s)}}return i}},{key:"addField",value:function(e){var t=e.name();this._colIdentifier+=","+t;var n=this._partialFieldspace,r=n._cachedValueObjects,a=e.formattedData(),i=e.partialField.data;if(n.fieldsObj()[e.name()]){var o=n.fields.findIndex((function(e){return e.name()===t}));o>=0&&(n.fields[o]=e)}else n.fields.push(e),r.forEach((function(t,n){t[e.name()]=new k(a[n],i[n],e)}));return n._cachedFieldsObj=null,n._cachedDimension=null,n._cachedMeasure=null,this.__calculateFieldspace().calculateFieldsConfig(),this}},{key:"calculateVariable",value:function(e,t,n){var r=this;e=Vt(e),n=Object.assign({},{saveChild:!0,replaceVar:!1},n);var a=this.getFieldsConfig(),i=t.slice(0,t.length-1),o=t[t.length-1];if(a[e.name]&&!n.replaceVar)throw new Error(e.name+" field already exists in datamodel");var u=i.map((function(e){var t=a[e];if(!t)throw new Error(e+" is not a valid column name.");return t.index})),c=this.clone(n.saveChild),f=c.getFieldspace().fields,l=u.map((function(e){return f[e]})),s={},d=function(){return r.detachedRoot()},p=[];T(c._rowDiffset,(function(e){var t=l.map((function(t){return t.partialField.data[e]}));p[e]=o.apply(void 0,an(t).concat([e,d,s]))}));var h=tt([p],[e],[e.name]),v=nn(h,1)[0];return c.addField(v),Ft(this,c,L.CAL_VAR,{config:e,fields:i},o),c}},{key:"propagate",value:function(e){var t=arguments.length>1&&void 0!==arguments[1]?arguments[1]:{},n=arguments[2],r=arguments.length>3&&void 0!==arguments[3]?arguments[3]:{},a=t.isMutableAction,i=t.sourceId,o=t.payload,u=Kt(this),c=u._propagationNameSpace,f=zt(this),l={groupByModel:f,model:u};return n&&Zt(c,t,this),Xt(e,l,{propagationNameSpace:c,sourceId:i},Object.assign({payload:o},t)),a&&qt(c,l,{config:t,propConfig:r}),this}},{key:"on",value:function(e,t){switch(e){case"propagation":this._onPropagation.push(t)}return 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diff --git a/dist/datamodel.js.map b/dist/datamodel.js.map
index c780cf0..b343b56 100644
--- a/dist/datamodel.js.map
+++ b/dist/datamodel.js.map
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If not found it returns a\n * default no as an index.\n *\n * @param: range {Array} : The list which is to be serached\n * @param: defVal {Number} : Default no if the serach and find does not return anything\n * @return {Function} : An closure function which is to be called by passing an the value which needs to be found\n */\nDateTimeFormatter.defaultRangeParser = function (range, defVal) {\n    return (val) => {\n        let i;\n        let l;\n\n        if (!val) { return defVal; }\n\n        const nVal = val.toLowerCase();\n\n        for (i = 0, l = range.length; i < l; i++) {\n            if (range[i].toLowerCase() === nVal) {\n                return i;\n            }\n        }\n\n        if (i === undefined) {\n            return defVal;\n        }\n        return null;\n    };\n};\n\n/*\n * Defines the tokens which are supporter by the dateformatter. Using this definitation a value gets extracted from\n * the user specifed date string. This also formats the value for display purpose from native JS date.\n * The definition of each token contains the following named properties\n * {\n *     %token_name% : {\n *         name: name of the token, this is used in reverse lookup,\n *         extract: a function that returns the regular expression to extract that piece of information. All the\n *                  regex should be gouped by using ()\n *         parser: a function which receives value extracted by the above regex and parse it to get the date params\n *         formatter: a formatter function that takes milliseconds or JS Date object and format the param\n *                  represented by the token only.\n *     }\n * }\n *\n * @return {Object} : Definition of the all the supported tokens.\n */\nDateTimeFormatter.getTokenDefinitions = function () {\n    const daysDef = {\n        short: [\n            'Sun',\n            'Mon',\n            'Tue',\n            'Wed',\n            'Thu',\n            'Fri',\n            'Sat'\n        ],\n        long: [\n            'Sunday',\n            'Monday',\n            'Tuesday',\n            'Wednesday',\n            'Thursday',\n            'Friday',\n            'Saturday'\n        ]\n    };\n    const monthsDef = {\n        short: [\n            'Jan',\n            'Feb',\n            'Mar',\n            'Apr',\n            'May',\n            'Jun',\n            'Jul',\n            'Aug',\n            'Sep',\n            'Oct',\n            'Nov',\n            'Dec'\n        ],\n        long: [\n            'January',\n            'February',\n            'March',\n            'April',\n            'May',\n            'June',\n            'July',\n            'August',\n            'September',\n            'October',\n            'November',\n            'December'\n        ]\n    };\n\n    const definitions = {\n        H: {\n            // 24 hours format\n            name: 'H',\n            index: 3,\n            extract () { return '(\\\\d+)'; },\n            parser: DateTimeFormatter.defaultNumberParser(),\n            formatter (val) {\n                const d = convertToNativeDate(val);\n\n                return d.getHours().toString();\n            }\n        },\n        l: {\n            // 12 hours format\n            name: 'l',\n            index: 3,\n            extract () { return '(\\\\d+)'; },\n            parser: DateTimeFormatter.defaultNumberParser(),\n            formatter (val) {\n                const d = convertToNativeDate(val);\n                const hours = d.getHours() % 12;\n\n                return (hours === 0 ? 12 : hours).toString();\n            }\n        },\n        p: {\n            // AM or PM\n            name: 'p',\n            index: 3,\n            extract () { return '(AM|PM)'; },\n            parser: (val) => {\n                if (val) {\n                    return val.toLowerCase();\n                }\n                return null;\n            },\n            formatter: (val) => {\n                const d = convertToNativeDate(val);\n                const hours = d.getHours();\n\n                return (hours < 12 ? 'AM' : 'PM');\n            }\n        },\n        P: {\n            // am or pm\n            name: 'P',\n            index: 3,\n            extract () { return '(am|pm)'; },\n            parser: (val) => {\n                if (val) {\n                    return val.toLowerCase();\n                }\n                return null;\n            },\n            formatter: (val) => {\n                const d = convertToNativeDate(val);\n                const hours = d.getHours();\n\n                return (hours < 12 ? 'am' : 'pm');\n            }\n        },\n        M: {\n            // Two digit minutes 00 - 59\n            name: 'M',\n            index: 4,\n            extract () { return '(\\\\d+)'; },\n            parser: DateTimeFormatter.defaultNumberParser(),\n            formatter (val) {\n                const d = convertToNativeDate(val);\n                const mins = d.getMinutes();\n\n                return pad(mins);\n            }\n        },\n        S: {\n            // Two digit seconds 00 - 59\n            name: 'S',\n            index: 5,\n            extract () { return '(\\\\d+)'; },\n            parser: DateTimeFormatter.defaultNumberParser(),\n            formatter (val) {\n                const d = convertToNativeDate(val);\n                const seconds = d.getSeconds();\n\n                return pad(seconds);\n            }\n        },\n        K: {\n            // Milliseconds\n            name: 'K',\n            index: 6,\n            extract () { return '(\\\\d+)'; },\n            parser: DateTimeFormatter.defaultNumberParser(),\n            formatter (val) {\n                const d = convertToNativeDate(val);\n                const ms = d.getMilliseconds();\n\n                return ms.toString();\n            }\n        },\n        a: {\n            // Short name of day, like Mon\n            name: 'a',\n            index: 2,\n            extract () { return `(${daysDef.short.join('|')})`; },\n            parser: DateTimeFormatter.defaultRangeParser(daysDef.short),\n            formatter (val) {\n                const d = convertToNativeDate(val);\n                const day = d.getDay();\n\n                return (daysDef.short[day]).toString();\n            }\n        },\n        A: {\n            // Long name of day, like Monday\n            name: 'A',\n            index: 2,\n            extract () { return `(${daysDef.long.join('|')})`; },\n            parser: DateTimeFormatter.defaultRangeParser(daysDef.long),\n            formatter (val) {\n                const d = convertToNativeDate(val);\n                const day = d.getDay();\n\n                return (daysDef.long[day]).toString();\n            }\n        },\n        e: {\n            // 8 of March, 11 of November\n            name: 'e',\n            index: 2,\n            extract () { return '(\\\\d+)'; },\n            parser: DateTimeFormatter.defaultNumberParser(),\n            formatter (val) {\n                const d = convertToNativeDate(val);\n                const day = d.getDate();\n\n                return day.toString();\n            }\n        },\n        d: {\n            // 08 of March, 11 of November\n            name: 'd',\n            index: 2,\n            extract () { return '(\\\\d+)'; },\n            parser: DateTimeFormatter.defaultNumberParser(),\n            formatter (val) {\n                const d = convertToNativeDate(val);\n                const day = d.getDate();\n\n                return pad(day);\n            }\n        },\n        b: {\n            // Short month, like Jan\n            name: 'b',\n            index: 1,\n            extract () { return `(${monthsDef.short.join('|')})`; },\n            parser: DateTimeFormatter.defaultRangeParser(monthsDef.short),\n            formatter (val) {\n                const d = convertToNativeDate(val);\n                const month = d.getMonth();\n\n                return (monthsDef.short[month]).toString();\n            }\n        },\n        B: {\n            // Long month, like January\n            name: 'B',\n            index: 1,\n            extract () { return `(${monthsDef.long.join('|')})`; },\n            parser: DateTimeFormatter.defaultRangeParser(monthsDef.long),\n            formatter (val) {\n                const d = convertToNativeDate(val);\n                const month = d.getMonth();\n\n                return (monthsDef.long[month]).toString();\n            }\n        },\n        m: {\n            // Two digit month of year like 01 for January\n            name: 'm',\n            index: 1,\n            extract () { return '(\\\\d+)'; },\n            parser (val) { return DateTimeFormatter.defaultNumberParser()(val) - 1; },\n            formatter (val) {\n                const d = convertToNativeDate(val);\n                const month = d.getMonth();\n\n                return pad(month + 1);\n            }\n        },\n        y: {\n            // Short year like 90 for 1990\n            name: 'y',\n            index: 0,\n            extract () { return '(\\\\d{2})'; },\n            parser (val) {\n                let result;\n                if (val) {\n                    const l = val.length;\n                    val = val.substring(l - 2, l);\n                }\n                let parsedVal = DateTimeFormatter.defaultNumberParser()(val);\n                let presentDate = new Date();\n                let presentYear = Math.trunc((presentDate.getFullYear()) / 100);\n\n                result = `${presentYear}${parsedVal}`;\n\n                if (convertToNativeDate(result).getFullYear() > presentDate.getFullYear()) {\n                    result = `${presentYear - 1}${parsedVal}`;\n                }\n                return convertToNativeDate(result).getFullYear();\n            },\n            formatter (val) {\n                const d = convertToNativeDate(val);\n                let year = d.getFullYear().toString();\n                let l;\n\n                if (year) {\n                    l = year.length;\n                    year = year.substring(l - 2, l);\n                }\n\n                return year;\n            }\n        },\n        Y: {\n            // Long year like 1990\n            name: 'Y',\n            index: 0,\n            extract () { return '(\\\\d{4})'; },\n            parser: DateTimeFormatter.defaultNumberParser(),\n            formatter (val) {\n                const d = convertToNativeDate(val);\n                const year = d.getFullYear().toString();\n\n                return year;\n            }\n        }\n    };\n\n    return definitions;\n};\n\n/*\n * The tokens which works internally is not user friendly in terms of memorizing the names. This gives a formal\n * definition to the informal notations.\n *\n * @return {Object} : Formal definition of the tokens\n */\nDateTimeFormatter.getTokenFormalNames = function () {\n    const definitions = DateTimeFormatter.getTokenDefinitions();\n\n    return {\n        HOUR: definitions.H,\n        HOUR_12: definitions.l,\n        AMPM_UPPERCASE: definitions.p,\n        AMPM_LOWERCASE: definitions.P,\n        MINUTE: definitions.M,\n        SECOND: definitions.S,\n        SHORT_DAY: definitions.a,\n        LONG_DAY: definitions.A,\n        DAY_OF_MONTH: definitions.e,\n        DAY_OF_MONTH_CONSTANT_WIDTH: definitions.d,\n        SHORT_MONTH: definitions.b,\n        LONG_MONTH: definitions.B,\n        MONTH_OF_YEAR: definitions.m,\n        SHORT_YEAR: definitions.y,\n        LONG_YEAR: definitions.Y\n    };\n};\n\n/*\n * This defines the rules and declares dependencies that resolves a date parameter (year, month etc) from\n * the date time parameter array.\n *\n * @return {Object} : An object that contains dependencies and a resolver function. The dependencies values are fed\n *                  to the resolver function in that particular sequence only.\n */\nDateTimeFormatter.tokenResolver = function () {\n    const definitions = DateTimeFormatter.getTokenDefinitions();\n    const defaultResolver = (...args) => { // eslint-disable-line require-jsdoc\n        let i = 0;\n        let arg;\n        let targetParam;\n        const l = args.length;\n\n        for (; i < l; i++) {\n            arg = args[i];\n            if (args[i]) {\n                targetParam = arg;\n            }\n        }\n\n        if (!targetParam) { return null; }\n\n        return targetParam[0].parser(targetParam[1]);\n    };\n\n    return {\n        YEAR: [definitions.y, definitions.Y,\n            defaultResolver\n        ],\n        MONTH: [definitions.b, definitions.B, definitions.m,\n            defaultResolver\n        ],\n        DAY: [definitions.a, definitions.A, definitions.e, definitions.d,\n            defaultResolver\n        ],\n        HOUR: [definitions.H, definitions.l, definitions.p, definitions.P,\n            function (hourFormat24, hourFormat12, ampmLower, ampmUpper) {\n                let targetParam;\n                let amOrpm;\n                let isPM;\n                let val;\n\n                if (hourFormat12 && (amOrpm = (ampmLower || ampmUpper))) {\n                    if (amOrpm[0].parser(amOrpm[1]) === 'pm') {\n                        isPM = true;\n                    }\n\n                    targetParam = hourFormat12;\n                } else if (hourFormat12) {\n                    targetParam = hourFormat12;\n                } else {\n                    targetParam = hourFormat24;\n                }\n\n                if (!targetParam) { return null; }\n\n                val = targetParam[0].parser(targetParam[1]);\n                if (isPM) {\n                    val += 12;\n                }\n                return val;\n            }\n        ],\n        MINUTE: [definitions.M,\n            defaultResolver\n        ],\n        SECOND: [definitions.S,\n            defaultResolver\n        ]\n    };\n};\n\n/*\n * Finds token from the format rule specified by a user.\n * @param format {String} : The format of the input date specified by the user\n * @return {Array} : An array of objects which contains the available token and their occurence index in the format\n */\nDateTimeFormatter.findTokens = function (format) {\n    const tokenPrefix = DateTimeFormatter.TOKEN_PREFIX;\n    const definitions = DateTimeFormatter.getTokenDefinitions();\n    const tokenLiterals = Object.keys(definitions);\n    const occurrence = [];\n    let i;\n    let forwardChar;\n\n    while ((i = format.indexOf(tokenPrefix, i + 1)) >= 0) {\n        forwardChar = format[i + 1];\n        if (tokenLiterals.indexOf(forwardChar) === -1) { continue; }\n\n        occurrence.push({\n            index: i,\n            token: forwardChar\n        });\n    }\n\n    return occurrence;\n};\n\n/*\n * Format any JS date to a specified date given by user.\n *\n * @param date {Number | Date} : The date object which is to be formatted\n * @param format {String} : The format using which the date will be formatted for display\n */\nDateTimeFormatter.formatAs = function (date, format) {\n    const nDate = convertToNativeDate(date);\n    const occurrence = DateTimeFormatter.findTokens(format);\n    const definitions = DateTimeFormatter.getTokenDefinitions();\n    let formattedStr = String(format);\n    const tokenPrefix = DateTimeFormatter.TOKEN_PREFIX;\n    let token;\n    let formattedVal;\n    let i;\n    let l;\n\n    for (i = 0, l = occurrence.length; i < l; i++) {\n        token = occurrence[i].token;\n        formattedVal = definitions[token].formatter(nDate);\n        formattedStr = formattedStr.replace(new RegExp(tokenPrefix + token, 'g'), formattedVal);\n    }\n\n    return formattedStr;\n};\n\n/*\n * Parses the user specified date string to extract the date time params.\n *\n * @return {Array} : Value of date time params in an array [year, month, day, hour, minutes, seconds, milli]\n */\nDateTimeFormatter.prototype.parse = function (dateTimeStamp, options) {\n    const tokenResolver = DateTimeFormatter.tokenResolver();\n    const dtParams = this.extractTokenValue(dateTimeStamp);\n    const dtParamSeq = DateTimeFormatter.DATETIME_PARAM_SEQUENCE;\n    const noBreak = options && options.noBreak;\n    const dtParamArr = [];\n    const args = [];\n    let resolverKey;\n    let resolverParams;\n    let resolverFn;\n    let val;\n    let i;\n    let param;\n    let resolvedVal;\n    let l;\n    let result = [];\n\n    for (resolverKey in tokenResolver) {\n        if (!{}.hasOwnProperty.call(tokenResolver, resolverKey)) { continue; }\n\n        args.length = 0;\n        resolverParams = tokenResolver[resolverKey];\n        resolverFn = resolverParams.splice(resolverParams.length - 1, 1)[0];\n\n        for (i = 0, l = resolverParams.length; i < l; i++) {\n            param = resolverParams[i];\n            val = dtParams[param.name];\n\n            if (val === undefined) {\n                args.push(null);\n            } else {\n                args.push([param, val]);\n            }\n        }\n\n        resolvedVal = resolverFn.apply(this, args);\n\n        if ((resolvedVal === undefined || resolvedVal === null) && !noBreak) {\n            break;\n        }\n\n        dtParamArr[dtParamSeq[resolverKey]] = resolvedVal;\n    }\n\n    if (dtParamArr.length && this.checkIfOnlyYear(dtParamArr.length))\n     {\n        result.unshift(dtParamArr[0], 0, 1); }\n    else {\n        result.unshift(...dtParamArr);\n    }\n\n    return result;\n};\n\n/*\n * Extract the value of the token from user specified date time string.\n *\n * @return {Object} : An key value pair which contains the tokens as key and value as pair\n */\nDateTimeFormatter.prototype.extractTokenValue = function (dateTimeStamp) {\n    const format = this.format;\n    const definitions = DateTimeFormatter.getTokenDefinitions();\n    const tokenPrefix = DateTimeFormatter.TOKEN_PREFIX;\n    const occurrence = DateTimeFormatter.findTokens(format);\n    const tokenObj = {};\n\n    let lastOccurrenceIndex;\n    let occObj;\n    let occIndex;\n    let targetText;\n    let regexFormat;\n\n    let l;\n    let i;\n\n    regexFormat = String(format);\n\n    const tokenArr = occurrence.map(obj => obj.token);\n    const occurrenceLength = occurrence.length;\n    for (i = occurrenceLength - 1; i >= 0; i--) {\n        occIndex = occurrence[i].index;\n\n        if (occIndex + 1 === regexFormat.length - 1) {\n            lastOccurrenceIndex = occIndex;\n            continue;\n        }\n\n        if (lastOccurrenceIndex === undefined) {\n            lastOccurrenceIndex = regexFormat.length;\n        }\n\n        targetText = regexFormat.substring(occIndex + 2, lastOccurrenceIndex);\n        regexFormat = regexFormat.substring(0, occIndex + 2) +\n            RegExp.escape(targetText) +\n            regexFormat.substring(lastOccurrenceIndex, regexFormat.length);\n\n        lastOccurrenceIndex = occIndex;\n    }\n\n    for (i = 0; i < occurrenceLength; i++) {\n        occObj = occurrence[i];\n        regexFormat = regexFormat.replace(tokenPrefix + occObj.token, definitions[occObj.token].extract());\n    }\n\n    const extractValues = dateTimeStamp.match(new RegExp(regexFormat)) || [];\n    extractValues.shift();\n\n    for (i = 0, l = tokenArr.length; i < l; i++) {\n        tokenObj[tokenArr[i]] = extractValues[i];\n    }\n    return tokenObj;\n};\n\n/*\n * Give back the JS native date formed from  user specified date string\n *\n * @return {Date} : Native JS Date\n */\nDateTimeFormatter.prototype.getNativeDate = function (dateTimeStamp) {\n    let date = null;\n    if (Number.isFinite(dateTimeStamp)) {\n        date = new Date(dateTimeStamp);\n    } else if (!this.format && Date.parse(dateTimeStamp)) {\n        date = new Date(dateTimeStamp);\n    }\n    else {\n        const dtParams = this.dtParams = this.parse(dateTimeStamp);\n        if (dtParams.length) {\n            this.nativeDate = new Date(...dtParams);\n            date = this.nativeDate;\n        }\n    }\n    return date;\n};\n\nDateTimeFormatter.prototype.checkIfOnlyYear = function(len) {\n    return len === 1 && this.format.match(/y|Y/g).length;\n};\n\n/*\n * Represents JS native date to a user specified format.\n *\n * @param format {String} : The format according to which the date is to be represented\n * @return {String} : The formatted date string\n */\nDateTimeFormatter.prototype.formatAs = function (format, dateTimeStamp) {\n    let nativeDate;\n\n    if (dateTimeStamp) {\n        nativeDate = this.nativeDate = this.getNativeDate(dateTimeStamp);\n    } else if (!(nativeDate = this.nativeDate)) {\n        nativeDate = this.getNativeDate(dateTimeStamp);\n    }\n\n    return DateTimeFormatter.formatAs(nativeDate, format);\n};\n\nexport { DateTimeFormatter as default };\n","/**\n * The utility function to calculate major column.\n *\n * @param {Object} store - The store object.\n * @return {Function} Returns the push function.\n */\nexport default (store) => {\n    let i = 0;\n    return (...fields) => {\n        fields.forEach((val, fieldIndex) => {\n            if (!(store[fieldIndex] instanceof Array)) {\n                store[fieldIndex] = Array.from({ length: i });\n            }\n            store[fieldIndex].push(val);\n        });\n        i++;\n    };\n};\n","/* eslint-disable */\nconst OBJECTSTRING = 'object';\nconst objectToStrFn = Object.prototype.toString;\nconst objectToStr = '[object Object]';\nconst arrayToStr = '[object Array]';\n\nfunction checkCyclicRef(obj, parentArr) {\n    let i = parentArr.length;\n    let bIndex = -1;\n\n    while (i) {\n        if (obj === parentArr[i]) {\n            bIndex = i;\n            return bIndex;\n        }\n        i -= 1;\n    }\n\n    return bIndex;\n}\n\nfunction merge(obj1, obj2, skipUndef, tgtArr, srcArr) {\n    var item,\n        srcVal,\n        tgtVal,\n        str,\n        cRef;\n    // check whether obj2 is an array\n    // if array then iterate through it's index\n    // **** MOOTOOLS precution\n\n    if (!srcArr) {\n        tgtArr = [obj1];\n        srcArr = [obj2];\n    }\n    else {\n        tgtArr.push(obj1);\n        srcArr.push(obj2);\n    }\n\n    if (obj2 instanceof Array) {\n        for (item = 0; item < obj2.length; item += 1) {\n            try {\n                srcVal = obj1[item];\n                tgtVal = obj2[item];\n            }\n            catch (e) {\n                continue;\n            }\n\n            if (typeof tgtVal !== OBJECTSTRING) {\n                if (!(skipUndef && tgtVal === undefined)) {\n                    obj1[item] = tgtVal;\n                }\n            }\n            else {\n                if (srcVal === null || typeof srcVal !== OBJECTSTRING) {\n                    srcVal = obj1[item] = tgtVal instanceof Array ? [] : {};\n                }\n                cRef = checkCyclicRef(tgtVal, srcArr);\n                if (cRef !== -1) {\n                    srcVal = obj1[item] = tgtArr[cRef];\n                }\n                else {\n                    merge(srcVal, tgtVal, skipUndef, tgtArr, srcArr);\n                }\n            }\n        }\n    }\n    else {\n        for (item in obj2) {\n            try {\n                srcVal = obj1[item];\n                tgtVal = obj2[item];\n            }\n            catch (e) {\n                continue;\n            }\n\n            if (tgtVal !== null && typeof tgtVal === OBJECTSTRING) {\n                // Fix for issue BUG: FWXT-602\n                // IE < 9 Object.prototype.toString.call(null) gives\n                // '[object Object]' instead of '[object Null]'\n                // that's why null value becomes Object in IE < 9\n                str = objectToStrFn.call(tgtVal);\n                if (str === objectToStr) {\n                    if (srcVal === null || typeof srcVal !== OBJECTSTRING) {\n                        srcVal = obj1[item] = {};\n                    }\n                    cRef = checkCyclicRef(tgtVal, srcArr);\n                    if (cRef !== -1) {\n                        srcVal = obj1[item] = tgtArr[cRef];\n                    }\n                    else {\n                        merge(srcVal, tgtVal, skipUndef, tgtArr, srcArr);\n                    }\n                }\n                else if (str === arrayToStr) {\n                    if (srcVal === null || !(srcVal instanceof Array)) {\n                        srcVal = obj1[item] = [];\n                    }\n                    cRef = checkCyclicRef(tgtVal, srcArr);\n                    if (cRef !== -1) {\n                        srcVal = obj1[item] = tgtArr[cRef];\n                    }\n                    else {\n                        merge(srcVal, tgtVal, skipUndef, tgtArr, srcArr);\n                    }\n                }\n                else {\n                    obj1[item] = tgtVal;\n                }\n            }\n            else {\n                if (skipUndef && tgtVal === undefined) {\n                    continue;\n                }\n                obj1[item] = tgtVal;\n            }\n        }\n    }\n    return obj1;\n}\n\n\nfunction extend2 (obj1, obj2, skipUndef) {\n    //if none of the arguments are object then return back\n    if (typeof obj1 !== OBJECTSTRING && typeof obj2 !== OBJECTSTRING) {\n        return null;\n    }\n\n    if (typeof obj2 !== OBJECTSTRING || obj2 === null) {\n        return obj1;\n    }\n\n    if (typeof obj1 !== OBJECTSTRING) {\n        obj1 = obj2 instanceof Array ? [] : {};\n    }\n    merge(obj1, obj2, skipUndef);\n    return obj1;\n}\n\nexport { extend2 as default };\n","import { DataFormat } from '../enums';\n\n/**\n * Checks whether the value is an array.\n *\n * @param  {*} val - The value to be checked.\n * @return {boolean} Returns true if the value is an array otherwise returns false.\n */\nexport function isArray (val) {\n    return Array.isArray(val);\n}\n\n/**\n * Checks whether the value is an object.\n *\n * @param  {*} val - The value to be checked.\n * @return {boolean} Returns true if the value is an object otherwise returns false.\n */\nexport function isObject (val) {\n    return val === Object(val);\n}\n\n/**\n * Checks whether the value is a string value.\n *\n * @param  {*} val - The value to be checked.\n * @return {boolean} Returns true if the value is a string value otherwise returns false.\n */\nexport function isString (val) {\n    return typeof val === 'string';\n}\n\n/**\n * Checks whether the value is callable.\n *\n * @param {*} val - The value to be checked.\n * @return {boolean} Returns true if the value is callable otherwise returns false.\n */\nexport function isCallable (val) {\n    return typeof val === 'function';\n}\n\n/**\n * Returns the unique values from the input array.\n *\n * @param {Array} data - The input array.\n * @return {Array} Returns a new array of unique values.\n */\nexport function uniqueValues (data) {\n    return [...new Set(data)];\n}\n\nexport const getUniqueId = () => `id-${new Date().getTime()}${Math.round(Math.random() * 10000)}`;\n\n/**\n * Checks Whether two arrays have same content.\n *\n * @param {Array} arr1 - The first array.\n * @param {Array} arr2 - The 2nd array.\n * @return {boolean} Returns whether two array have same content.\n */\nexport function isArrEqual(arr1, arr2) {\n    if (!isArray(arr1) || !isArray(arr2)) {\n        return arr1 === arr2;\n    }\n\n    if (arr1.length !== arr2.length) {\n        return false;\n    }\n\n    for (let i = 0; i < arr1.length; i++) {\n        if (arr1[i] !== arr2[i]) {\n            return false;\n        }\n    }\n\n    return true;\n}\n\n/**\n * It is the default number format function for the measure field type.\n *\n * @param {any} val - The input value.\n * @return {number} Returns a number value.\n */\nexport function formatNumber(val) {\n    return val;\n}\n\n/**\n * Returns the detected data format.\n *\n * @param {any} data - The input data to be tested.\n * @return {string} Returns the data format name.\n */\nexport const detectDataFormat = (data) => {\n    if (isString(data)) {\n        return DataFormat.DSV_STR;\n    } else if (isArray(data) && isArray(data[0])) {\n        return DataFormat.DSV_ARR;\n    } else if (isArray(data) && (data.length === 0 || isObject(data[0]))) {\n        return DataFormat.FLAT_JSON;\n    }\n    return null;\n};\n","import { FieldType } from './enums';\nimport { getUniqueId } from './utils';\n\nconst fieldStore = {\n    data: {},\n\n    createNamespace (fieldArr, name) {\n        const dataId = name || getUniqueId();\n\n        this.data[dataId] = {\n            name: dataId,\n            fields: fieldArr,\n\n            fieldsObj () {\n                let fieldsObj = this._cachedFieldsObj;\n\n                if (!fieldsObj) {\n                    fieldsObj = this._cachedFieldsObj = {};\n                    this.fields.forEach((field) => {\n                        fieldsObj[field.name()] = field;\n                    });\n                }\n                return fieldsObj;\n            },\n            getMeasure () {\n                let measureFields = this._cachedMeasure;\n\n                if (!measureFields) {\n                    measureFields = this._cachedMeasure = {};\n                    this.fields.forEach((field) => {\n                        if (field.schema().type === FieldType.MEASURE) {\n                            measureFields[field.name()] = field;\n                        }\n                    });\n                }\n                return measureFields;\n            },\n            getDimension () {\n                let dimensionFields = this._cachedDimension;\n\n                if (!this._cachedDimension) {\n                    dimensionFields = this._cachedDimension = {};\n                    this.fields.forEach((field) => {\n                        if (field.schema().type === FieldType.DIMENSION) {\n                            dimensionFields[field.name()] = field;\n                        }\n                    });\n                }\n                return dimensionFields;\n            },\n        };\n        return this.data[dataId];\n    },\n};\n\nexport default fieldStore;\n","import { getNumberFormattedVal } from './helper';\n\n/**\n * The wrapper class on top of the primitive value of a field.\n *\n * @todo Need to have support for StringValue, NumberValue, DateTimeValue\n * and GeoValue. These types should expose predicate API mostly.\n */\nclass Value {\n\n  /**\n   * Creates new Value instance.\n   *\n   * @param {*} val - the primitive value from the field cell.\n   * @param {string | Field} field - The field from which the value belongs.\n   */\n    constructor (value, rawValue, field) {\n        const formattedValue = getNumberFormattedVal(field, value);\n\n        Object.defineProperties(this, {\n            _value: {\n                enumerable: false,\n                configurable: false,\n                writable: false,\n                value\n            },\n            _formattedValue: {\n                enumerable: false,\n                configurable: false,\n                writable: false,\n                value: formattedValue\n            },\n            _internalValue: {\n                enumerable: false,\n                configurable: false,\n                writable: false,\n                value: rawValue\n            }\n        });\n\n        this.field = field;\n    }\n\n  /**\n   * Returns the field value.\n   *\n   * @return {*} Returns the current value.\n   */\n    get value () {\n        return this._value;\n    }\n\n    /**\n     * Returns the parsed value of field\n     */\n    get formattedValue () {\n        return this._formattedValue;\n    }\n\n    /**\n     * Returns the internal value of field\n     */\n    get internalValue () {\n        return this._internalValue;\n    }\n\n  /**\n   * Converts to human readable string.\n   *\n   * @override\n   * @return {string} Returns a human readable string of the field value.\n   *\n   */\n    toString () {\n        return String(this.value);\n    }\n\n  /**\n   * Returns the value of the field.\n   *\n   * @override\n   * @return {*} Returns the field value.\n   */\n    valueOf () {\n        return this.value;\n    }\n}\n\nexport default Value;\n","/**\n * Iterates through the diffSet array and call the callback with the current\n * index.\n *\n * @param {string} rowDiffset - The row diffset string e.g. '0-4,6,10-13'.\n * @param {Function} callback - The callback function to be called with every index.\n */\nexport function rowDiffsetIterator (rowDiffset, callback) {\n    if (rowDiffset.length > 0) {\n        const rowDiffArr = rowDiffset.split(',');\n        rowDiffArr.forEach((diffStr) => {\n            const diffStsArr = diffStr.split('-');\n            const start = +(diffStsArr[0]);\n            const end = +(diffStsArr[1] || diffStsArr[0]);\n            if (end >= start) {\n                for (let i = start; i <= end; i += 1) {\n                    callback(i);\n                }\n            }\n        });\n    }\n}\n","/**\n * A parser to parser null, undefined, invalid and NIL values.\n *\n * @public\n * @class\n */\nclass InvalidAwareTypes {\n    /**\n     * Static method which gets/sets the invalid value registry.\n     *\n     * @public\n     * @param {Object} config - The custom configuration supplied by user.\n     * @return {Object} Returns the invalid values registry.\n     */\n    static invalidAwareVals (config) {\n        if (!config) {\n            return InvalidAwareTypes._invalidAwareValsMap;\n        }\n        return Object.assign(InvalidAwareTypes._invalidAwareValsMap, config);\n    }\n\n    /**\n     * Initialize a new instance.\n     *\n     * @public\n     * @param {string} value - The value of the invalid data type.\n     */\n    constructor (value) {\n        this._value = value;\n    }\n\n    /**\n     * Returns the current value of the instance.\n     *\n     * @public\n     * @return {string} Returns the value of the invalid data type.\n     */\n    value () {\n        return this._value;\n    }\n\n    /**\n     * Returns the current value of the instance in string format.\n     *\n     * @public\n     * @return {string} Returns the value of the invalid data type.\n     */\n    toString () {\n        return String(this._value);\n    }\n\n    static isInvalid(val) {\n        return (val instanceof InvalidAwareTypes) || !!InvalidAwareTypes.invalidAwareVals()[val];\n    }\n\n    static getInvalidType(val) {\n        return val instanceof InvalidAwareTypes ? val : InvalidAwareTypes.invalidAwareVals()[val];\n    }\n}\n\n/**\n * Enums for Invalid types.\n */\nInvalidAwareTypes.NULL = new InvalidAwareTypes('null');\nInvalidAwareTypes.NA = new InvalidAwareTypes('na');\nInvalidAwareTypes.NIL = new InvalidAwareTypes('nil');\n\n/**\n * Default Registry for mapping the invalid values.\n *\n * @private\n */\nInvalidAwareTypes._invalidAwareValsMap = {\n    invalid: InvalidAwareTypes.NA,\n    nil: InvalidAwareTypes.NIL,\n    null: InvalidAwareTypes.NULL,\n    undefined: InvalidAwareTypes.NA\n};\n\nexport default InvalidAwareTypes;\n","import { rowDiffsetIterator } from './row-diffset-iterator';\nimport InvalidAwareTypes from '../invalid-aware-types';\n\nconst generateBuckets = (binSize, start, end) => {\n    const buckets = [];\n    let next = start;\n\n    while (next < end) {\n        buckets.push(next);\n        next += binSize;\n    }\n    buckets.push(next);\n\n    return buckets;\n};\n\nconst findBucketRange = (bucketRanges, value) => {\n    let leftIdx = 0;\n    let rightIdx = bucketRanges.length - 1;\n    let midIdx;\n    let range;\n\n    // Here use binary search as the bucketRanges is a sorted array\n    while (leftIdx <= rightIdx) {\n        midIdx = leftIdx + Math.floor((rightIdx - leftIdx) / 2);\n        range = bucketRanges[midIdx];\n\n        if (value >= range.start && value < range.end) {\n            return range;\n        } else if (value >= range.end) {\n            leftIdx = midIdx + 1;\n        } else if (value < range.start) {\n            rightIdx = midIdx - 1;\n        }\n    }\n\n    return null;\n};\n\n /**\n  * Creates the bin data from input measure field and supplied configs.\n  *\n  * @param {Measure} measureField - The Measure field instance.\n  * @param {string} rowDiffset - The datamodel rowDiffset values.\n  * @param {Object} config - The config object.\n  * @return {Object} Returns the binned data and the corresponding bins.\n  */\nexport function createBinnedFieldData (measureField, rowDiffset, config) {\n    let { buckets, binsCount, binSize, start, end } = config;\n    const [dMin, dMax] = measureField.domain();\n\n    if (!buckets) {\n        start = (start !== 0 && (!start || start > dMin)) ? dMin : start;\n        end = (end !== 0 && (!end || end < dMax)) ? (dMax + 1) : end;\n\n        if (binsCount) {\n            binSize = Math.ceil(Math.abs(end - start) / binsCount);\n        }\n\n        buckets = generateBuckets(binSize, start, end);\n    }\n\n    if (buckets[0] > dMin) {\n        buckets.unshift(dMin);\n    }\n    if (buckets[buckets.length - 1] <= dMax) {\n        buckets.push(dMax + 1);\n    }\n\n    const bucketRanges = [];\n    for (let i = 0; i < buckets.length - 1; i++) {\n        bucketRanges.push({\n            start: buckets[i],\n            end: buckets[i + 1]\n        });\n    }\n\n    const binnedData = [];\n    rowDiffsetIterator(rowDiffset, (i) => {\n        const datum = measureField.partialField.data[i];\n        if (datum instanceof InvalidAwareTypes) {\n            binnedData.push(datum);\n            return;\n        }\n\n        const range = findBucketRange(bucketRanges, datum);\n        binnedData.push(`${range.start}-${range.end}`);\n    });\n\n    return { binnedData, bins: buckets };\n}\n","export { DataFormat, FilteringMode } from '../enums';\n/**\n * The event name for data propagation.\n */\nexport const PROPAGATION = 'propagation';\n\n/**\n * The name of the unique row id column in DataModel.\n */\nexport const ROW_ID = '__id__';\n\n/**\n * The enums for operation names performed on DataModel.\n */\nexport const DM_DERIVATIVES = {\n    SELECT: 'select',\n    PROJECT: 'project',\n    GROUPBY: 'group',\n    COMPOSE: 'compose',\n    CAL_VAR: 'calculatedVariable',\n    BIN: 'bin',\n    SORT: 'sort'\n};\n\nexport const JOINS = {\n    CROSS: 'cross',\n    LEFTOUTER: 'leftOuter',\n    RIGHTOUTER: 'rightOuter',\n    NATURAL: 'natural',\n    FULLOUTER: 'fullOuter'\n};\n\nexport const LOGICAL_OPERATORS = {\n    AND: 'and',\n    OR: 'or'\n};\n","/**\n * The helper function that returns an array of common schema\n * from two fieldStore instances.\n *\n * @param {FieldStore} fs1 - The first FieldStore instance.\n * @param {FieldStore} fs2 - The second FieldStore instance.\n * @return {Array} An array containing the common schema.\n */\nexport function getCommonSchema (fs1, fs2) {\n    const retArr = [];\n    const fs1Arr = [];\n    fs1.fields.forEach((field) => {\n        fs1Arr.push(field.schema().name);\n    });\n    fs2.fields.forEach((field) => {\n        if (fs1Arr.indexOf(field.schema().name) !== -1) {\n            retArr.push(field.schema().name);\n        }\n    });\n    return retArr;\n}\n","import DataModel from '../datamodel';\nimport { extend2 } from '../utils';\nimport { getCommonSchema } from './get-common-schema';\nimport { rowDiffsetIterator } from './row-diffset-iterator';\nimport { JOINS } from '../constants';\nimport { prepareJoinData } from '../helper';\n/**\n * Default filter function for crossProduct.\n *\n * @return {boolean} Always returns true.\n */\nfunction defaultFilterFn() { return true; }\n\n/**\n * Implementation of cross product operation between two DataModel instances.\n * It internally creates the data and schema for the new DataModel.\n *\n * @param {DataModel} dataModel1 - The left DataModel instance.\n * @param {DataModel} dataModel2 - The right DataModel instance.\n * @param {Function} filterFn - The filter function which is used to filter the tuples.\n * @param {boolean} [replaceCommonSchema=false] - The flag if the common name schema should be there.\n * @return {DataModel} Returns The newly created DataModel instance from the crossProduct operation.\n */\nexport function crossProduct (dm1, dm2, filterFn, replaceCommonSchema = false, jointype = JOINS.CROSS) {\n    const schema = [];\n    const data = [];\n    const applicableFilterFn = filterFn || defaultFilterFn;\n    const dm1FieldStore = dm1.getFieldspace();\n    const dm2FieldStore = dm2.getFieldspace();\n    const dm1FieldStoreName = dm1FieldStore.name;\n    const dm2FieldStoreName = dm2FieldStore.name;\n    const name = `${dm1FieldStore.name}.${dm2FieldStore.name}`;\n    const commonSchemaList = getCommonSchema(dm1FieldStore, dm2FieldStore);\n\n    if (dm1FieldStoreName === dm2FieldStoreName) {\n        throw new Error('DataModels must have different alias names');\n    }\n    // Here prepare the schema\n    dm1FieldStore.fields.forEach((field) => {\n        const tmpSchema = extend2({}, field.schema());\n        if (commonSchemaList.indexOf(tmpSchema.name) !== -1 && !replaceCommonSchema) {\n            tmpSchema.name = `${dm1FieldStore.name}.${tmpSchema.name}`;\n        }\n        schema.push(tmpSchema);\n    });\n    dm2FieldStore.fields.forEach((field) => {\n        const tmpSchema = extend2({}, field.schema());\n        if (commonSchemaList.indexOf(tmpSchema.name) !== -1) {\n            if (!replaceCommonSchema) {\n                tmpSchema.name = `${dm2FieldStore.name}.${tmpSchema.name}`;\n                schema.push(tmpSchema);\n            }\n        } else {\n            schema.push(tmpSchema);\n        }\n    });\n\n    // Here prepare Data\n    rowDiffsetIterator(dm1._rowDiffset, (i) => {\n        let rowAdded = false;\n        let rowPosition;\n        rowDiffsetIterator(dm2._rowDiffset, (ii) => {\n            const tuple = [];\n            const userArg = {};\n            userArg[dm1FieldStoreName] = {};\n            userArg[dm2FieldStoreName] = {};\n            dm1FieldStore.fields.forEach((field) => {\n                tuple.push(field.partialField.data[i]);\n                userArg[dm1FieldStoreName][field.name()] = {\n                    rawValue: field.partialField.data[i],\n                    formattedValue: field.formattedData()[i],\n                };\n            });\n            dm2FieldStore.fields.forEach((field) => {\n                if (!(commonSchemaList.indexOf(field.schema().name) !== -1 && replaceCommonSchema)) {\n                    tuple.push(field.partialField.data[ii]);\n                }\n                userArg[dm2FieldStoreName][field.name()] = {\n                    rawValue: field.partialField.data[ii],\n                    formattedValue: field.formattedData()[ii],\n                };\n            });\n\n            let cachedStore = {};\n            let cloneProvider1 = () => dm1.detachedRoot();\n            let cloneProvider2 = () => dm2.detachedRoot();\n\n            const dm1Fields = prepareJoinData(userArg[dm1FieldStoreName]);\n            const dm2Fields = prepareJoinData(userArg[dm2FieldStoreName]);\n            if (applicableFilterFn(dm1Fields, dm2Fields, cloneProvider1, cloneProvider2, cachedStore)) {\n                const tupleObj = {};\n                tuple.forEach((cellVal, iii) => {\n                    tupleObj[schema[iii].name] = cellVal;\n                });\n                if (rowAdded && JOINS.CROSS !== jointype) {\n                    data[rowPosition] = tupleObj;\n                }\n                else {\n                    data.push(tupleObj);\n                    rowAdded = true;\n                    rowPosition = i;\n                }\n            } else if ((jointype === JOINS.LEFTOUTER || jointype === JOINS.RIGHTOUTER) && !rowAdded) {\n                const tupleObj = {};\n                let len = dm1FieldStore.fields.length - 1;\n                tuple.forEach((cellVal, iii) => {\n                    if (iii <= len) {\n                        tupleObj[schema[iii].name] = cellVal;\n                    }\n                    else {\n                        tupleObj[schema[iii].name] = null;\n                    }\n                });\n                rowAdded = true;\n                rowPosition = i;\n                data.push(tupleObj);\n            }\n        });\n    });\n\n    return new DataModel(data, schema, { name });\n}\n","/**\n * The default sort function.\n *\n * @param {*} a - The first value.\n * @param {*} b - The second value.\n * @return {number} Returns the comparison result e.g. 1 or 0 or -1.\n */\nfunction defSortFn (a, b) {\n    const a1 = `${a}`;\n    const b1 = `${b}`;\n    if (a1 < b1) {\n        return -1;\n    }\n    if (a1 > b1) {\n        return 1;\n    }\n    return 0;\n}\n\n/**\n * The helper function for merge sort which creates the sorted array\n * from the two halves of the input array.\n *\n * @param {Array} arr - The target array which needs to be merged.\n * @param {number} lo - The starting index of the first array half.\n * @param {number} mid - The ending index of the first array half.\n * @param {number} hi - The ending index of the second array half.\n * @param {Function} sortFn - The sort function.\n */\nfunction merge (arr, lo, mid, hi, sortFn) {\n    const mainArr = arr;\n    const auxArr = [];\n    for (let i = lo; i <= hi; i += 1) {\n        auxArr[i] = mainArr[i];\n    }\n    let a = lo;\n    let b = mid + 1;\n\n    for (let i = lo; i <= hi; i += 1) {\n        if (a > mid) {\n            mainArr[i] = auxArr[b];\n            b += 1;\n        } else if (b > hi) {\n            mainArr[i] = auxArr[a];\n            a += 1;\n        } else if (sortFn(auxArr[a], auxArr[b]) <= 0) {\n            mainArr[i] = auxArr[a];\n            a += 1;\n        } else {\n            mainArr[i] = auxArr[b];\n            b += 1;\n        }\n    }\n}\n\n/**\n * The helper function for merge sort which would be called\n * recursively for sorting the array halves.\n *\n * @param {Array} arr - The target array which needs to be sorted.\n * @param {number} lo - The starting index of the array half.\n * @param {number} hi - The ending index of the array half.\n * @param {Function} sortFn - The sort function.\n * @return {Array} Returns the target array itself.\n */\nfunction sort (arr, lo, hi, sortFn) {\n    if (hi === lo) { return arr; }\n\n    const mid = lo + Math.floor((hi - lo) / 2);\n    sort(arr, lo, mid, sortFn);\n    sort(arr, mid + 1, hi, sortFn);\n    merge(arr, lo, mid, hi, sortFn);\n\n    return arr;\n}\n\n/**\n * The implementation of merge sort.\n * It is used in DataModel for stable sorting as it is not sure\n * what the sorting algorithm used by browsers is stable or not.\n *\n * @param {Array} arr - The target array which needs to be sorted.\n * @param {Function} [sortFn=defSortFn] - The sort function.\n * @return {Array} Returns the input array itself in sorted order.\n */\nexport function mergeSort (arr, sortFn = defSortFn) {\n    if (arr.length > 1) {\n        sort(arr, 0, arr.length - 1, sortFn);\n    }\n    return arr;\n}\n","import { DimensionSubtype, MeasureSubtype } from '../enums';\nimport { mergeSort } from './merge-sort';\nimport { fieldInSchema } from '../helper';\nimport { isCallable, isArray } from '../utils';\n\n/**\n * Generates the sorting functions to sort the data of a DataModel instance\n * according to the input data type.\n *\n * @param {string} dataType - The data type e.g. 'measure', 'datetime' etc.\n * @param {string} sortType - The sorting order i.e. 'asc' or 'desc'.\n * @return {Function} Returns the the sorting function.\n */\nfunction getSortFn (dataType, sortType) {\n    let retFunc;\n\n    switch (dataType) {\n    case MeasureSubtype.CONTINUOUS:\n    case DimensionSubtype.TEMPORAL:\n        if (sortType === 'asc') {\n            retFunc = (a, b) => a - b;\n        } else {\n            retFunc = (a, b) => b - a;\n        }\n        break;\n    default:\n        if (sortType === 'asc') {\n            retFunc = (a, b) => {\n                a = `${a}`;\n                b = `${b}`;\n                if (a === b) {\n                    return 0;\n                }\n                return a > b ? 1 : -1;\n            };\n        } else {\n            retFunc = (a, b) => {\n                a = `${a}`;\n                b = `${b}`;\n                if (a === b) {\n                    return 0;\n                }\n                return a > b ? -1 : 1;\n            };\n        }\n    }\n\n    return retFunc;\n}\n\n/**\n * Resolves the actual sorting function based on sorting string value.\n *\n * @param {Object} fDetails - The target field info.\n * @param {string} strSortOrder - The sort order value.\n * @return {Function} Returns the sorting function.\n */\nfunction resolveStrSortOrder (fDetails, strSortOrder) {\n    const sortOrder = String(strSortOrder).toLowerCase() === 'desc' ? 'desc' : 'asc';\n    return getSortFn(fDetails.type, sortOrder);\n}\n\n/**\n * Groups the data according to the specified target field.\n *\n * @param {Array} data - The input data array.\n * @param {number} fieldIndex - The target field index within schema array.\n * @return {Array} Returns an array containing the grouped data.\n */\nfunction groupData (data, fieldIndex) {\n    const hashMap = new Map();\n    const groupedData = [];\n\n    data.forEach((datum) => {\n        const fieldVal = datum[fieldIndex];\n        if (hashMap.has(fieldVal)) {\n            groupedData[hashMap.get(fieldVal)][1].push(datum);\n        } else {\n            groupedData.push([fieldVal, [datum]]);\n            hashMap.set(fieldVal, groupedData.length - 1);\n        }\n    });\n\n    return groupedData;\n}\n\n/**\n * Creates the argument value used for sorting function when sort is done\n * with another fields.\n *\n * @param {Array} groupedDatum - The grouped datum for a single dimension field value.\n * @param {Array} targetFields - An array of the sorting fields.\n * @param {Array} targetFieldDetails - An array of the sorting field details in schema.\n * @return {Object} Returns an object containing the value of sorting fields and the target field name.\n */\nfunction createSortingFnArg (groupedDatum, targetFields, targetFieldDetails) {\n    const arg = {\n        label: groupedDatum[0]\n    };\n\n    targetFields.reduce((acc, next, idx) => {\n        acc[next] = groupedDatum[1].map(datum => datum[targetFieldDetails[idx].index]);\n        return acc;\n    }, arg);\n\n    return arg;\n}\n\n/**\n * Sorts the data by applying the standard sorting mechanism.\n *\n * @param {Array} data - The input data array.\n * @param {Array} schema - The data schema.\n * @param {Array} sortingDetails - An array containing the sorting configs.\n */\nfunction applyStandardSort (data, schema, sortingDetails) {\n    let fieldName;\n    let sortMeta;\n    let fDetails;\n    let i = sortingDetails.length - 1;\n\n    for (; i >= 0; i--) {\n        fieldName = sortingDetails[i][0];\n        sortMeta = sortingDetails[i][1];\n        fDetails = fieldInSchema(schema, fieldName);\n\n        if (!fDetails) {\n            // eslint-disable-next-line no-continue\n            continue;\n        }\n\n        if (isCallable(sortMeta)) {\n            // eslint-disable-next-line no-loop-func\n            mergeSort(data, (a, b) => sortMeta(a[fDetails.index], b[fDetails.index]));\n        } else if (isArray(sortMeta)) {\n            const groupedData = groupData(data, fDetails.index);\n            const sortingFn = sortMeta[sortMeta.length - 1];\n            const targetFields = sortMeta.slice(0, sortMeta.length - 1);\n            const targetFieldDetails = targetFields.map(f => fieldInSchema(schema, f));\n\n            groupedData.forEach((groupedDatum) => {\n                groupedDatum.push(createSortingFnArg(groupedDatum, targetFields, targetFieldDetails));\n            });\n\n            mergeSort(groupedData, (a, b) => {\n                const m = a[2];\n                const n = b[2];\n                return sortingFn(m, n);\n            });\n\n            // Empty the array\n            data.length = 0;\n            groupedData.forEach((datum) => {\n                data.push(...datum[1]);\n            });\n        } else {\n            const sortFn = resolveStrSortOrder(fDetails, sortMeta);\n            // eslint-disable-next-line no-loop-func\n            mergeSort(data, (a, b) => sortFn(a[fDetails.index], b[fDetails.index]));\n        }\n    }\n}\n\n/**\n * Creates a map based on grouping.\n *\n * @param {Array} depColumns - The dependency columns' info.\n * @param {Array} data - The input data.\n * @param {Array} schema - The data schema.\n * @param {Array} sortingDetails - The sorting details for standard sorting.\n * @return {Map} Returns a map.\n */\nconst makeGroupMapAndSort = (depColumns, data, schema, sortingDetails) => {\n    if (depColumns.length === 0) { return data; }\n\n    const targetCol = depColumns[0];\n    const map = new Map();\n\n    data.reduce((acc, currRow) => {\n        const fVal = currRow[targetCol.index];\n        if (acc.has(fVal)) {\n            acc.get(fVal).push(currRow);\n        } else {\n            acc.set(fVal, [currRow]);\n        }\n        return acc;\n    }, map);\n\n    for (let [key, val] of map) {\n        const nMap = makeGroupMapAndSort(depColumns.slice(1), val, schema, sortingDetails);\n        map.set(key, nMap);\n        if (Array.isArray(nMap)) {\n            applyStandardSort(nMap, schema, sortingDetails);\n        }\n    }\n\n    return map;\n};\n\n/**\n * Sorts the data by retaining the position/order of a particular field.\n *\n * @param {Array} data - The input data array.\n * @param {Array} schema - The data schema.\n * @param {Array} sortingDetails - An array containing the sorting configs.\n * @param {Array} depColumns - The dependency column list.\n * @return {Array} Returns the sorted data.\n */\nfunction applyGroupSort (data, schema, sortingDetails, depColumns) {\n    sortingDetails = sortingDetails.filter((detail) => {\n        if (detail[1] === null) {\n            depColumns.push(detail[0]);\n            return false;\n        }\n        return true;\n    });\n    if (sortingDetails.length === 0) { return data; }\n\n    depColumns = depColumns.map(c => fieldInSchema(schema, c));\n\n    const sortedGroupMap = makeGroupMapAndSort(depColumns, data, schema, sortingDetails);\n    return data.map((row) => {\n        let i = 0;\n        let nextMap = sortedGroupMap;\n\n        while (!Array.isArray(nextMap)) {\n            nextMap = nextMap.get(row[depColumns[i++].index]);\n        }\n\n        return nextMap.shift();\n    });\n}\n\n/**\n * Sorts the data.\n *\n * @param {Object} dataObj - An object containing the data and schema.\n * @param {Array} sortingDetails - An array containing the sorting configs.\n */\nexport function sortData (dataObj, sortingDetails) {\n    let { schema, data } = dataObj;\n\n    sortingDetails = sortingDetails.filter(sDetial => !!fieldInSchema(schema, sDetial[0]));\n    if (sortingDetails.length === 0) { return; }\n\n    let groupSortingIdx = sortingDetails.findIndex(sDetial => sDetial[1] === null);\n    groupSortingIdx = groupSortingIdx !== -1 ? groupSortingIdx : sortingDetails.length;\n\n    const standardSortingDetails = sortingDetails.slice(0, groupSortingIdx);\n    const groupSortingDetails = sortingDetails.slice(groupSortingIdx);\n\n    applyStandardSort(data, schema, standardSortingDetails);\n    data = applyGroupSort(data, schema, groupSortingDetails, standardSortingDetails.map(detail => detail[0]));\n\n    dataObj.uids = data.map(row => row.pop());\n    dataObj.data = data;\n}\n","import { rowDiffsetIterator } from './row-diffset-iterator';\nimport { sortData } from './sort';\n\n/**\n * Builds the actual data array.\n *\n * @param {Array} fieldStore - An array of field.\n * @param {string} rowDiffset - A string consisting of which rows to be included eg. '0-2,4,6';\n * @param {string} colIdentifier - A string consisting of the details of which column\n * to be included eg 'date,sales,profit';\n * @param {Object} sortingDetails - An object containing the sorting details of the DataModel instance.\n * @param {Object} options - The options required to create the type of the data.\n * @return {Object} Returns an object containing the multidimensional array and the relative schema.\n */\nexport function dataBuilder (fieldStore, rowDiffset, colIdentifier, sortingDetails, options) {\n    const defOptions = {\n        addUid: false,\n        columnWise: false\n    };\n    options = Object.assign({}, defOptions, options);\n\n    const retObj = {\n        schema: [],\n        data: [],\n        uids: []\n    };\n    const addUid = options.addUid;\n    const reqSorting = sortingDetails && sortingDetails.length > 0;\n    // It stores the fields according to the colIdentifier argument\n    const tmpDataArr = [];\n    // Stores the fields according to the colIdentifier argument\n    const colIArr = colIdentifier.split(',');\n\n    colIArr.forEach((colName) => {\n        for (let i = 0; i < fieldStore.length; i += 1) {\n            if (fieldStore[i].name() === colName) {\n                tmpDataArr.push(fieldStore[i]);\n                break;\n            }\n        }\n    });\n\n    // Inserts the schema to the schema object\n    tmpDataArr.forEach((field) => {\n        /** @todo Need to use extend2 here otherwise user can overwrite the schema. */\n        retObj.schema.push(field.schema());\n    });\n\n    if (addUid) {\n        retObj.schema.push({\n            name: 'uid',\n            type: 'identifier'\n        });\n    }\n\n    rowDiffsetIterator(rowDiffset, (i) => {\n        retObj.data.push([]);\n        const insertInd = retObj.data.length - 1;\n        let start = 0;\n        tmpDataArr.forEach((field, ii) => {\n            retObj.data[insertInd][ii + start] = field.partialField.data[i];\n        });\n        if (addUid) {\n            retObj.data[insertInd][tmpDataArr.length] = i;\n        }\n        // Creates an array of unique identifiers for each row\n        retObj.uids.push(i);\n\n        // If sorting needed then there is the need to expose the index\n        // mapping from the old index to its new index\n        if (reqSorting) { retObj.data[insertInd].push(i); }\n    });\n\n    // Handles the sort functionality\n    if (reqSorting) {\n        sortData(retObj, sortingDetails);\n    }\n\n    if (options.columnWise) {\n        const tmpData = Array(...Array(retObj.schema.length)).map(() => []);\n        retObj.data.forEach((tuple) => {\n            tuple.forEach((data, i) => {\n                tmpData[i].push(data);\n            });\n        });\n        retObj.data = tmpData;\n    }\n\n    return retObj;\n}\n","import DataModel from '../datamodel';\nimport { extend2 } from '../utils';\nimport { rowDiffsetIterator } from './row-diffset-iterator';\nimport { isArrEqual } from '../utils/helper';\n\n/**\n * Performs the union operation between two dm instances.\n *\n * @todo Fix the conflicts between union and difference terminology here.\n *\n * @param {dm} dm1 - The first dm instance.\n * @param {dm} dm2 - The second dm instance.\n * @return {dm} Returns the newly created dm after union operation.\n */\nexport function difference (dm1, dm2) {\n    const hashTable = {};\n    const schema = [];\n    const schemaNameArr = [];\n    const data = [];\n    const dm1FieldStore = dm1.getFieldspace();\n    const dm2FieldStore = dm2.getFieldspace();\n    const dm1FieldStoreFieldObj = dm1FieldStore.fieldsObj();\n    const dm2FieldStoreFieldObj = dm2FieldStore.fieldsObj();\n    const name = `${dm1FieldStore.name} union ${dm2FieldStore.name}`;\n\n   // For union the columns should match otherwise return a clone of the dm1\n    if (!isArrEqual(dm1._colIdentifier.split(',').sort(), dm2._colIdentifier.split(',').sort())) {\n        return null;\n    }\n\n    // Prepare the schema\n    (dm1._colIdentifier.split(',')).forEach((fieldName) => {\n        const field = dm1FieldStoreFieldObj[fieldName];\n        schema.push(extend2({}, field.schema()));\n        schemaNameArr.push(field.schema().name);\n    });\n\n    /**\n     * The helper function to create the data.\n     *\n     * @param {dm} dm - The dm instance for which the data is inserted.\n     * @param {Object} fieldsObj - The fieldStore object format.\n     * @param {boolean} addData - If true only tuple will be added to the data.\n     */\n    function prepareDataHelper(dm, fieldsObj, addData) {\n        rowDiffsetIterator(dm._rowDiffset, (i) => {\n            const tuple = {};\n            let hashData = '';\n            schemaNameArr.forEach((schemaName) => {\n                const value = fieldsObj[schemaName].partialField.data[i];\n                hashData += `-${value}`;\n                tuple[schemaName] = value;\n            });\n            if (!hashTable[hashData]) {\n                if (addData) { data.push(tuple); }\n                hashTable[hashData] = true;\n            }\n        });\n    }\n\n    // Prepare the data\n    prepareDataHelper(dm2, dm2FieldStoreFieldObj, false);\n    prepareDataHelper(dm1, dm1FieldStoreFieldObj, true);\n\n    return new DataModel(data, schema, { name });\n}\n\n","import { isArray } from '../utils';\nimport InvalidAwareTypes from '../invalid-aware-types';\nimport { GROUP_BY_FUNCTIONS } from '../enums';\n\nconst { SUM, AVG, FIRST, LAST, COUNT, STD, MIN, MAX } = GROUP_BY_FUNCTIONS;\n\nfunction getFilteredValues(arr) {\n    return arr.filter(item => !(item instanceof InvalidAwareTypes));\n}\n/**\n * Reducer function that returns the sum of all the values.\n *\n * @public\n * @param  {Array.<number>} arr - The input array.\n * @return {number} Returns the sum of the array.\n */\nfunction sum (arr) {\n    if (isArray(arr) && !(arr[0] instanceof Array)) {\n        const filteredNumber = getFilteredValues(arr);\n        const totalSum = filteredNumber.length ?\n                            filteredNumber.reduce((acc, curr) => acc + curr, 0)\n                            : InvalidAwareTypes.NULL;\n        return totalSum;\n    }\n    return InvalidAwareTypes.NULL;\n}\n\n/**\n * Reducer function that returns the average of all the values.\n *\n * @public\n * @param  {Array.<number>} arr - The input array.\n * @return {number} Returns the mean value of the array.\n */\nfunction avg (arr) {\n    if (isArray(arr) && !(arr[0] instanceof Array)) {\n        const totalSum = sum(arr);\n        const len = arr.length || 1;\n        return (Number.isNaN(totalSum) || totalSum instanceof InvalidAwareTypes) ?\n                 InvalidAwareTypes.NULL : totalSum / len;\n    }\n    return InvalidAwareTypes.NULL;\n}\n\n/**\n * Reducer function that gives the min value amongst all the values.\n *\n * @public\n * @param  {Array.<number>} arr - The input array.\n * @return {number} Returns the minimum value of the array.\n */\nfunction min (arr) {\n    if (isArray(arr) && !(arr[0] instanceof Array)) {\n        // Filter out undefined, null and NaN values\n        const filteredValues = getFilteredValues(arr);\n\n        return (filteredValues.length) ? Math.min(...filteredValues) : InvalidAwareTypes.NULL;\n    }\n    return InvalidAwareTypes.NULL;\n}\n\n/**\n * Reducer function that gives the max value amongst all the values.\n *\n * @public\n * @param  {Array.<number>} arr - The input array.\n * @return {number} Returns the maximum value of the array.\n */\nfunction max (arr) {\n    if (isArray(arr) && !(arr[0] instanceof Array)) {\n        // Filter out undefined, null and NaN values\n        const filteredValues = getFilteredValues(arr);\n\n        return (filteredValues.length) ? Math.max(...filteredValues) : InvalidAwareTypes.NULL;\n    }\n    return InvalidAwareTypes.NULL;\n}\n\n/**\n * Reducer function that gives the first value of the array.\n *\n * @public\n * @param  {Array} arr - The input array.\n * @return {number} Returns the first value of the array.\n */\nfunction first (arr) {\n    return arr[0];\n}\n\n/**\n * Reducer function that gives the last value of the array.\n *\n * @public\n * @param  {Array} arr - The input array.\n * @return {number} Returns the last value of the array.\n */\nfunction last (arr) {\n    return arr[arr.length - 1];\n}\n\n/**\n * Reducer function that gives the count value of the array.\n *\n * @public\n * @param  {Array} arr - The input array.\n * @return {number} Returns the length of the array.\n */\nfunction count (arr) {\n    if (isArray(arr)) {\n        return arr.length;\n    }\n    return InvalidAwareTypes.NULL;\n}\n\n/**\n * Calculates the variance of the input array.\n *\n * @param  {Array.<number>} arr - The input array.\n * @return {number} Returns the variance of the input array.\n */\nfunction variance (arr) {\n    let mean = avg(arr);\n    return avg(arr.map(num => (num - mean) ** 2));\n}\n\n/**\n * Calculates the square root of the variance of the input array.\n *\n * @public\n * @param  {Array.<number>} arr - The input array.\n * @return {number} Returns the square root of the variance.\n */\nfunction std (arr) {\n    return Math.sqrt(variance(arr));\n}\n\n\nconst fnList = {\n    [SUM]: sum,\n    [AVG]: avg,\n    [MIN]: min,\n    [MAX]: max,\n    [FIRST]: first,\n    [LAST]: last,\n    [COUNT]: count,\n    [STD]: std\n};\n\nconst defaultReducerName = SUM;\n\nexport {\n    defaultReducerName,\n    sum as defReducer,\n    fnList,\n};\n","import { defReducer, fnList } from '../operator';\n\n/**\n * A page level storage which stores, registers, unregisters reducers for all the datamodel instances. There is only one\n * reducer store available in a page. All the datamodel instances receive same instance of reducer store. DataModel\n * out of the box provides handful of {@link reducer | reducers} which can be used as reducer funciton.\n *\n * @public\n * @namespace DataModel\n */\nclass ReducerStore {\n    constructor () {\n        this.store = new Map();\n        this.store.set('defReducer', defReducer);\n\n        Object.entries(fnList).forEach((key) => {\n            this.store.set(key[0], key[1]);\n        });\n    }\n\n    /**\n     * Changes the `defaultReducer` globally. For all the fields which does not have `defAggFn` mentioned in schema, the\n     * value of `defaultReducer` is used for aggregation.\n     *\n     * @public\n     * @param {string} [reducer='sum'] - The name of the default reducer. It picks up the definition from store by doing\n     * name lookup. If no name is found then it takes `sum` as the default reducer.\n     * @return {ReducerStore} Returns instance of the singleton store in page.\n     */\n    defaultReducer (...params) {\n        if (!params.length) {\n            return this.store.get('defReducer');\n        }\n\n        let reducer = params[0];\n\n        if (typeof reducer === 'function') {\n            this.store.set('defReducer', reducer);\n        } else {\n            reducer = String(reducer);\n            if (Object.keys(fnList).indexOf(reducer) !== -1) {\n                this.store.set('defReducer', fnList[reducer]);\n            } else {\n                throw new Error(`Reducer ${reducer} not found in registry`);\n            }\n        }\n        return this;\n    }\n\n    /**\n     *\n     * Registers a {@link reducer | reducer}.\n     * A {@link reducer | reducer} has to be registered before it is used.\n     *\n     * @example\n     *  // find the mean squared value of a given set\n     *  const reducerStore = DataModel.Reducers();\n     *\n     *  reducers.register('meanSquared', (arr) => {\n     *      const squaredVal = arr.map(item => item * item);\n     *      let sum = 0;\n     *      for (let i = 0, l = squaredVal.length; i < l; i++) {\n     *          sum += squaredVal[i++];\n     *      }\n     *\n     *      return sum;\n     *  })\n     *\n     *  // datamodel (dm) is already prepared with cars.json\n     *  const dm1 = dm.groupBy(['origin'], {\n     *      accleration: 'meanSquared'\n     *  });\n     *\n     * @public\n     *\n     * @param {string} name formal name for a reducer. If the given name already exists in store it is overridden by new\n     *      definition.\n     * @param {Function} reducer definition of {@link reducer} function.\n     *\n     * @return {Function} function for unregistering the reducer.\n     */\n    register (name, reducer) {\n        if (typeof reducer !== 'function') {\n            throw new Error('Reducer should be a function');\n        }\n\n        name = String(name);\n        this.store.set(name, reducer);\n\n        return () => { this.__unregister(name); };\n    }\n\n    __unregister (name) {\n        if (this.store.has(name)) {\n            this.store.delete(name);\n        }\n    }\n\n    resolve (name) {\n        if (name instanceof Function) {\n            return name;\n        }\n        return this.store.get(name);\n    }\n}\n\nconst reducerStore = (function () {\n    let store = null;\n\n    function getStore () {\n        if (store === null) {\n            store = new ReducerStore();\n        }\n        return store;\n    }\n    return getStore();\n}());\n\nexport default reducerStore;\n","import { extend2 } from '../utils';\nimport { rowDiffsetIterator } from './row-diffset-iterator';\nimport DataModel from '../export';\nimport reducerStore from '../utils/reducer-store';\nimport { defaultReducerName } from './group-by-function';\nimport { FieldType } from '../enums';\n\n/**\n * This function sanitize the user given field and return a common Array structure field\n * list\n * @param  {DataModel} dataModel the dataModel operating on\n * @param  {Array} fieldArr  user input of field Array\n * @return {Array}           arrays of field name\n */\nfunction getFieldArr (dataModel, fieldArr) {\n    const retArr = [];\n    const fieldStore = dataModel.getFieldspace();\n    const dimensions = fieldStore.getDimension();\n\n    Object.entries(dimensions).forEach(([key]) => {\n        if (fieldArr && fieldArr.length) {\n            if (fieldArr.indexOf(key) !== -1) {\n                retArr.push(key);\n            }\n        } else {\n            retArr.push(key);\n        }\n    });\n\n    return retArr;\n}\n\n/**\n * This sanitize the reducer provide by the user and create a common type of object.\n * user can give function Also\n * @param  {DataModel} dataModel     dataModel to worked on\n * @param  {Object|function} [reducers={}] reducer provided by the users\n * @return {Object}               object containing reducer function for every measure\n */\nfunction getReducerObj (dataModel, reducers = {}) {\n    const retObj = {};\n    const fieldStore = dataModel.getFieldspace();\n    const measures = fieldStore.getMeasure();\n    const defReducer = reducerStore.defaultReducer();\n\n    Object.keys(measures).forEach((measureName) => {\n        if (typeof reducers[measureName] !== 'string') {\n            reducers[measureName] = measures[measureName].defAggFn();\n        }\n        const reducerFn = reducerStore.resolve(reducers[measureName]);\n        if (reducerFn) {\n            retObj[measureName] = reducerFn;\n        } else {\n            retObj[measureName] = defReducer;\n            reducers[measureName] = defaultReducerName;\n        }\n    });\n    return retObj;\n}\n\n/**\n * main function which perform the group-by operations which reduce the measures value is the\n * fields are common according to the reducer function provided\n * @param  {DataModel} dataModel the dataModel to worked\n * @param  {Array} fieldArr  fields according to which the groupby should be worked\n * @param  {Object|Function} reducers  reducers function\n * @param {DataModel} existingDataModel Existing datamodel instance\n * @return {DataModel} new dataModel with the group by\n */\nfunction groupBy (dataModel, fieldArr, reducers, existingDataModel) {\n    const sFieldArr = getFieldArr(dataModel, fieldArr);\n    const reducerObj = getReducerObj(dataModel, reducers);\n    const fieldStore = dataModel.getFieldspace();\n    const fieldStoreObj = fieldStore.fieldsObj();\n    const dbName = fieldStore.name;\n    const dimensionArr = [];\n    const measureArr = [];\n    const schema = [];\n    const hashMap = {};\n    const data = [];\n    let newDataModel;\n\n    // Prepare the schema\n    Object.entries(fieldStoreObj).forEach(([key, value]) => {\n        if (sFieldArr.indexOf(key) !== -1 || reducerObj[key]) {\n            schema.push(extend2({}, value.schema()));\n\n            switch (value.schema().type) {\n            case FieldType.MEASURE:\n                measureArr.push(key);\n                break;\n            default:\n            case FieldType.DIMENSION:\n                dimensionArr.push(key);\n            }\n        }\n    });\n    // Prepare the data\n    let rowCount = 0;\n    rowDiffsetIterator(dataModel._rowDiffset, (i) => {\n        let hash = '';\n        dimensionArr.forEach((_) => {\n            hash = `${hash}-${fieldStoreObj[_].partialField.data[i]}`;\n        });\n        if (hashMap[hash] === undefined) {\n            hashMap[hash] = rowCount;\n            data.push({});\n            dimensionArr.forEach((_) => {\n                data[rowCount][_] = fieldStoreObj[_].partialField.data[i];\n            });\n            measureArr.forEach((_) => {\n                data[rowCount][_] = [fieldStoreObj[_].partialField.data[i]];\n            });\n            rowCount += 1;\n        } else {\n            measureArr.forEach((_) => {\n                data[hashMap[hash]][_].push(fieldStoreObj[_].partialField.data[i]);\n            });\n        }\n    });\n\n    // reduction\n    let cachedStore = {};\n    let cloneProvider = () => dataModel.detachedRoot();\n    data.forEach((row) => {\n        const tuple = row;\n        measureArr.forEach((_) => {\n            tuple[_] = reducerObj[_](row[_], cloneProvider, cachedStore);\n        });\n    });\n    if (existingDataModel) {\n        existingDataModel.__calculateFieldspace();\n        newDataModel = existingDataModel;\n    }\n    else {\n        newDataModel = new DataModel(data, schema, { name: dbName });\n    }\n    return newDataModel;\n}\n\nexport { groupBy, getFieldArr, getReducerObj };\n","import { getCommonSchema } from './get-common-schema';\n\n/**\n * The filter function used in natural join.\n * It generates a function that will have the logic to join two\n * DataModel instances by the process of natural join.\n *\n * @param {DataModel} dm1 - The left DataModel instance.\n * @param {DataModel} dm2 - The right DataModel instance.\n * @return {Function} Returns a function that is used in cross-product operation.\n */\nexport function naturalJoinFilter (dm1, dm2) {\n    const dm1FieldStore = dm1.getFieldspace();\n    const dm2FieldStore = dm2.getFieldspace();\n    // const dm1FieldStoreName = dm1FieldStore.name;\n    // const dm2FieldStoreName = dm2FieldStore.name;\n    const commonSchemaArr = getCommonSchema(dm1FieldStore, dm2FieldStore);\n\n    return (dm1Fields, dm2Fields) => {\n        let retainTuple = true;\n        commonSchemaArr.forEach((fieldName) => {\n            if (dm1Fields[fieldName].internalValue ===\n                dm2Fields[fieldName].internalValue && retainTuple) {\n                retainTuple = true;\n            } else {\n                retainTuple = false;\n            }\n        });\n        return retainTuple;\n    };\n}\n","import DataModel from '../export';\nimport { extend2 } from '../utils';\nimport { rowDiffsetIterator } from './row-diffset-iterator';\nimport { isArrEqual } from '../utils/helper';\n/**\n * Performs the union operation between two dm instances.\n *\n * @param {dm} dm1 - The first dm instance.\n * @param {dm} dm2 - The second dm instance.\n * @return {dm} Returns the newly created dm after union operation.\n */\nexport function union (dm1, dm2) {\n    const hashTable = {};\n    const schema = [];\n    const schemaNameArr = [];\n    const data = [];\n    const dm1FieldStore = dm1.getFieldspace();\n    const dm2FieldStore = dm2.getFieldspace();\n    const dm1FieldStoreFieldObj = dm1FieldStore.fieldsObj();\n    const dm2FieldStoreFieldObj = dm2FieldStore.fieldsObj();\n    const name = `${dm1FieldStore.name} union ${dm2FieldStore.name}`;\n\n    // For union the columns should match otherwise return a clone of the dm1\n    if (!isArrEqual(dm1._colIdentifier.split(',').sort(), dm2._colIdentifier.split(',').sort())) {\n        return null;\n    }\n\n    // Prepare the schema\n    (dm1._colIdentifier.split(',')).forEach((fieldName) => {\n        const field = dm1FieldStoreFieldObj[fieldName];\n        schema.push(extend2({}, field.schema()));\n        schemaNameArr.push(field.schema().name);\n    });\n\n    /**\n     * The helper function to create the data.\n     *\n     * @param {dm} dm - The dm instance for which the data is inserted.\n     * @param {Object} fieldsObj - The fieldStore object format.\n     */\n    function prepareDataHelper (dm, fieldsObj) {\n        rowDiffsetIterator(dm._rowDiffset, (i) => {\n            const tuple = {};\n            let hashData = '';\n            schemaNameArr.forEach((schemaName) => {\n                const value = fieldsObj[schemaName].partialField.data[i];\n                hashData += `-${value}`;\n                tuple[schemaName] = value;\n            });\n            if (!hashTable[hashData]) {\n                data.push(tuple);\n                hashTable[hashData] = true;\n            }\n        });\n    }\n\n    // Prepare the data\n    prepareDataHelper(dm1, dm1FieldStoreFieldObj);\n    prepareDataHelper(dm2, dm2FieldStoreFieldObj);\n\n    return new DataModel(data, schema, { name });\n}\n","import { crossProduct } from './cross-product';\nimport { JOINS } from '../constants';\nimport { union } from './union';\n\n\nexport function leftOuterJoin (dataModel1, dataModel2, filterFn) {\n    return crossProduct(dataModel1, dataModel2, filterFn, false, JOINS.LEFTOUTER);\n}\n\nexport function rightOuterJoin (dataModel1, dataModel2, filterFn) {\n    return crossProduct(dataModel2, dataModel1, filterFn, false, JOINS.RIGHTOUTER);\n}\n\nexport function fullOuterJoin (dataModel1, dataModel2, filterFn) {\n    return union(leftOuterJoin(dataModel1, dataModel2, filterFn), rightOuterJoin(dataModel1, dataModel2, filterFn));\n}\n","import { rowDiffsetIterator } from '../../operator/row-diffset-iterator';\n\n/**\n * In {@link DataModel}, every tabular data consists of column, a column is stored as field.\n * Field contains all the data for a given column in an array.\n *\n * Each record consists of several fields; the fields of all records form the columns.\n * Examples of fields: name, gender, sex etc.\n *\n * In DataModel, each field can have multiple attributes which describes its data and behaviour.\n * A field can have two types of data: Measure and Dimension.\n *\n * A Dimension Field is the context on which a data is categorized and the measure is the numerical values that\n * quantify the data set.\n * In short a dimension is the lens through which you are looking at your measure data.\n *\n * Refer to {@link Schema} to get info about possible field attributes.\n *\n * @public\n * @class\n */\nexport default class Field {\n    /**\n     * Initialize a new instance.\n     *\n     * @public\n     * @param {PartialField} partialField - The partialField instance which holds the whole data.\n     * @param {string} rowDiffset - The data subset definition.\n     */\n    constructor (partialField, rowDiffset) {\n        this.partialField = partialField;\n        this.rowDiffset = rowDiffset;\n    }\n\n    /**\n     * Generates the field type specific domain.\n     *\n     * @public\n     * @abstract\n     */\n    domain () {\n        throw new Error('Not yet implemented');\n    }\n\n    /**\n     * Returns the the field schema.\n     *\n     * @public\n     * @return {string} Returns the field schema.\n     */\n    schema () {\n        return this.partialField.schema;\n    }\n\n    /**\n     * Returns the name of the field.\n     *\n     * @public\n     * @return {string} Returns the name of the field.\n     */\n    name () {\n        return this.partialField.name;\n    }\n\n    /**\n     * Returns the type of the field.\n     *\n     * @public\n     * @return {string} Returns the type of the field.\n     */\n    type () {\n        return this.partialField.schema.type;\n    }\n\n    /**\n     * Returns the subtype of the field.\n     *\n     * @public\n     * @return {string} Returns the subtype of the field.\n     */\n    subtype () {\n        return this.partialField.schema.subtype;\n    }\n\n    /**\n     * Returns the description of the field.\n     *\n     * @public\n     * @return {string} Returns the description of the field.\n     */\n    description () {\n        return this.partialField.schema.description;\n    }\n\n    /**\n     * Returns the display name of the field.\n     *\n     * @public\n     * @return {string} Returns the display name of the field.\n     */\n    displayName () {\n        return this.partialField.schema.displayName || this.partialField.schema.name;\n    }\n\n    /**\n     * Returns the data associated with the field.\n     *\n     * @public\n     * @return {Array} Returns the data.\n     */\n    data () {\n        const data = [];\n        rowDiffsetIterator(this.rowDiffset, (i) => {\n            data.push(this.partialField.data[i]);\n        });\n        return data;\n    }\n\n    /**\n     * Returns the formatted version of the underlying field data.\n     *\n     * @public\n     * @abstract\n     */\n    formattedData () {\n        throw new Error('Not yet implemented');\n    }\n}\n","import Field from '../field';\n\n/**\n * Represents dimension field type.\n *\n * @public\n * @class\n * @extends Field\n */\nexport default class Dimension extends Field {\n    /**\n     * Returns the domain for the dimension field.\n     *\n     * @override\n     * @public\n     * @return {any} Returns the calculated domain.\n     */\n    domain () {\n        if (!this._cachedDomain) {\n            this._cachedDomain = this.calculateDataDomain();\n        }\n        return this._cachedDomain;\n    }\n\n    /**\n     * Calculates the corresponding field domain.\n     *\n     * @public\n     * @abstract\n     */\n    calculateDataDomain () {\n        throw new Error('Not yet implemented');\n    }\n\n     /**\n     * Returns the formatted version of the underlying field data.\n     *\n     * @public\n     * @override\n     * @return {Array} Returns the formatted data.\n     */\n    formattedData () {\n        return this.data();\n    }\n}\n","import { rowDiffsetIterator } from '../../operator/row-diffset-iterator';\nimport { DimensionSubtype } from '../../enums';\nimport Dimension from '../dimension';\n/**\n * Represents categorical field subtype.\n *\n * @public\n * @class\n * @extends Dimension\n */\nexport default class Categorical extends Dimension {\n    /**\n     * Returns the subtype of the field.\n     *\n     * @public\n     * @override\n     * @return {string} Returns the subtype of the field.\n     */\n    subtype () {\n        return DimensionSubtype.CATEGORICAL;\n    }\n\n    /**\n     * Calculates the corresponding field domain.\n     *\n     * @public\n     * @override\n     * @return {Array} Returns the unique values.\n     */\n    calculateDataDomain () {\n        const hash = new Set();\n        const domain = [];\n\n        // here don't use this.data() as the iteration will be occurred two times on same data.\n        rowDiffsetIterator(this.rowDiffset, (i) => {\n            const datum = this.partialField.data[i];\n            if (!hash.has(datum)) {\n                hash.add(datum);\n                domain.push(datum);\n            }\n        });\n        return domain;\n    }\n}\n","import { rowDiffsetIterator } from '../../operator/row-diffset-iterator';\nimport Dimension from '../dimension';\nimport { DateTimeFormatter } from '../../utils';\nimport InvalidAwareTypes from '../../invalid-aware-types';\n\n/**\n * Represents temporal field subtype.\n *\n * @public\n * @class\n * @extends Dimension\n */\nexport default class Temporal extends Dimension {\n     /**\n     * Initialize a new instance.\n     *\n     * @public\n     * @param {PartialField} partialField - The partialField instance which holds the whole data.\n     * @param {string} rowDiffset - The data subset definition.\n     */\n    constructor (partialField, rowDiffset) {\n        super(partialField, rowDiffset);\n\n        this._cachedMinDiff = null;\n    }\n\n     /**\n     * Calculates the corresponding field domain.\n     *\n     * @public\n     * @override\n     * @return {Array} Returns the unique values.\n     */\n    calculateDataDomain () {\n        const hash = new Set();\n        const domain = [];\n\n        // here don't use this.data() as the iteration will be\n        // occurred two times on same data.\n        rowDiffsetIterator(this.rowDiffset, (i) => {\n            const datum = this.partialField.data[i];\n            if (!hash.has(datum)) {\n                hash.add(datum);\n                domain.push(datum);\n            }\n        });\n\n        return domain;\n    }\n\n\n    /**\n     * Calculates the minimum consecutive difference from the associated field data.\n     *\n     * @public\n     * @return {number} Returns the minimum consecutive diff in milliseconds.\n     */\n    minimumConsecutiveDifference () {\n        if (this._cachedMinDiff) {\n            return this._cachedMinDiff;\n        }\n\n        const sortedData = this.data().filter(item => !(item instanceof InvalidAwareTypes)).sort((a, b) => a - b);\n        const arrLn = sortedData.length;\n        let minDiff = Number.POSITIVE_INFINITY;\n        let prevDatum;\n        let nextDatum;\n        let processedCount = 0;\n\n        for (let i = 1; i < arrLn; i++) {\n            prevDatum = sortedData[i - 1];\n            nextDatum = sortedData[i];\n\n            if (nextDatum === prevDatum) {\n                continue;\n            }\n\n            minDiff = Math.min(minDiff, nextDatum - sortedData[i - 1]);\n            processedCount++;\n        }\n\n        if (!processedCount) {\n            minDiff = null;\n        }\n        this._cachedMinDiff = minDiff;\n\n        return this._cachedMinDiff;\n    }\n\n    /**\n     * Returns the format specified in the input schema while creating field.\n     *\n     * @public\n     * @return {string} Returns the datetime format.\n     */\n    format () {\n        return this.partialField.schema.format;\n    }\n\n    /**\n     * Returns the formatted version of the underlying field data\n     * If data is of type invalid or has missing format use the raw value\n     * @public\n     * @override\n     * @return {Array} Returns the formatted data.\n     */\n    formattedData () {\n        const data = [];\n        const dataFormat = this.format();\n\n        rowDiffsetIterator(this.rowDiffset, (i) => {\n            const datum = this.partialField.data[i];\n            // If value is of invalid type or format is missing\n            if (InvalidAwareTypes.isInvalid(datum) || (!dataFormat && Number.isFinite(datum))) {\n                // Use the invalid map value or the raw value\n                const parsedDatum = InvalidAwareTypes.getInvalidType(datum) || datum;\n                data.push(parsedDatum);\n            } else {\n                data.push(DateTimeFormatter.formatAs(datum, dataFormat));\n            }\n        });\n        return data;\n    }\n}\n\n","import Dimension from '../dimension';\n\n/**\n * Represents binned field subtype.\n *\n * @public\n * @class\n * @extends Dimension\n */\nexport default class Binned extends Dimension {\n    /**\n     * Calculates the corresponding field domain.\n     *\n     * @public\n     * @override\n     * @return {Array} Returns the last and first values of bins config array.\n     */\n    calculateDataDomain () {\n        const binsArr = this.partialField.schema.bins;\n        return [binsArr[0], binsArr[binsArr.length - 1]];\n    }\n\n    /**\n     * Returns the bins config provided while creating the field instance.\n     *\n     * @public\n     * @return {Array} Returns the bins array config.\n     */\n    bins () {\n        return this.partialField.schema.bins;\n    }\n}\n","import { formatNumber } from '../../utils';\nimport { defaultReducerName } from '../../operator/group-by-function';\nimport Field from '../field';\n\n/**\n * Represents measure field type.\n *\n * @public\n * @class\n * @extends Field\n */\nexport default class Measure extends Field {\n  /**\n   * Returns the domain for the measure field.\n   *\n   * @override\n   * @public\n   * @return {any} Returns the calculated domain.\n   */\n    domain () {\n        if (!this._cachedDomain) {\n            this._cachedDomain = this.calculateDataDomain();\n        }\n        return this._cachedDomain;\n    }\n\n  /**\n   * Returns the unit of the measure field.\n   *\n   * @public\n   * @return {string} Returns unit of the field.\n   */\n    unit () {\n        return this.partialField.schema.unit;\n    }\n\n  /**\n   * Returns the aggregation function name of the measure field.\n   *\n   * @public\n   * @return {string} Returns aggregation function name of the field.\n   */\n    defAggFn () {\n        return this.partialField.schema.defAggFn || defaultReducerName;\n    }\n\n  /**\n   * Returns the number format of the measure field.\n   *\n   * @public\n   * @return {Function} Returns number format of the field.\n   */\n    numberFormat () {\n        const { numberFormat } = this.partialField.schema;\n        return numberFormat instanceof Function ? numberFormat : formatNumber;\n    }\n\n  /**\n   * Calculates the corresponding field domain.\n   *\n   * @public\n   * @abstract\n   */\n    calculateDataDomain () {\n        throw new Error('Not yet implemented');\n    }\n\n    /**\n     * Returns the formatted version of the underlying field data.\n     *\n     * @public\n     * @override\n     * @return {Array} Returns the formatted data.\n     */\n    formattedData () {\n        return this.data();\n    }\n}\n","import { rowDiffsetIterator } from '../../operator/row-diffset-iterator';\nimport { MeasureSubtype } from '../../enums';\nimport Measure from '../measure';\nimport InvalidAwareTypes from '../../invalid-aware-types';\n\n/**\n * Represents continuous field subtype.\n *\n * @public\n * @class\n * @extends Measure\n */\nexport default class Continuous extends Measure {\n    /**\n     * Returns the subtype of the field.\n     *\n     * @public\n     * @override\n     * @return {string} Returns the subtype of the field.\n     */\n    subtype () {\n        return MeasureSubtype.CONTINUOUS;\n    }\n\n    /**\n     * Calculates the corresponding field domain.\n     *\n     * @public\n     * @override\n     * @return {Array} Returns the min and max values.\n     */\n    calculateDataDomain () {\n        let min = Number.POSITIVE_INFINITY;\n        let max = Number.NEGATIVE_INFINITY;\n\n        // here don't use this.data() as the iteration will be occurred two times on same data.\n        rowDiffsetIterator(this.rowDiffset, (i) => {\n            const datum = this.partialField.data[i];\n            if (datum instanceof InvalidAwareTypes) {\n                return;\n            }\n\n            if (datum < min) {\n                min = datum;\n            }\n            if (datum > max) {\n                max = datum;\n            }\n        });\n\n        return [min, max];\n    }\n}\n","/**\n * A interface to represent a parser which is responsible to parse the field.\n *\n * @public\n * @interface\n */\nexport default class FieldParser {\n    /**\n     * Parses a single value of a field and return the sanitized form.\n     *\n     * @public\n     * @abstract\n     */\n    parse () {\n        throw new Error('Not yet implemented');\n    }\n}\n","import FieldParser from '../field-parser';\nimport InvalidAwareTypes from '../../../invalid-aware-types';\n\n/**\n * A FieldParser which parses the categorical values.\n *\n * @public\n * @class\n * @implements {FieldParser}\n */\nexport default class CategoricalParser extends FieldParser {\n  /**\n   * Parses a single value of a field and returns the stringified form.\n   *\n   * @public\n   * @param {string|number} val - The value of the field.\n   * @return {string} Returns the stringified value.\n   */\n    parse (val) {\n        let result;\n        // check if invalid date value\n        if (!InvalidAwareTypes.isInvalid(val)) {\n            result = String(val).trim();\n        } else {\n            result = InvalidAwareTypes.getInvalidType(val);\n        }\n        return result;\n    }\n}\n","import { DateTimeFormatter } from '../../../utils';\nimport FieldParser from '../field-parser';\nimport InvalidAwareTypes from '../../../invalid-aware-types';\n\n/**\n * A FieldParser which parses the temporal values.\n *\n * @public\n * @class\n * @implements {FieldParser}\n */\nexport default class TemporalParser extends FieldParser {\n    /**\n     * Initialize a new instance.\n     *\n     * @public\n     * @param {Object} schema - The schema object for the corresponding field.\n     */\n    constructor (schema) {\n        super();\n        this.schema = schema;\n        this._dtf = new DateTimeFormatter(this.schema.format);\n    }\n\n    /**\n     * Parses a single value of a field and returns the millisecond value.\n     *\n     * @public\n     * @param {string|number} val - The value of the field.\n     * @return {number} Returns the millisecond value.\n     */\n    parse (val) {\n        let result;\n        // check if invalid date value\n        if (!InvalidAwareTypes.isInvalid(val)) {\n            let nativeDate = this._dtf.getNativeDate(val);\n            result = nativeDate ? nativeDate.getTime() : InvalidAwareTypes.NA;\n        } else {\n            result = InvalidAwareTypes.getInvalidType(val);\n        }\n        return result;\n    }\n}\n","import FieldParser from '../field-parser';\nimport InvalidAwareTypes from '../../../invalid-aware-types';\n\n/**\n * A FieldParser which parses the binned values.\n *\n * @public\n * @class\n * @implements {FieldParser}\n */\nexport default class BinnedParser extends FieldParser {\n  /**\n   * Parses a single binned value of a field and returns the sanitized value.\n   *\n   * @public\n   * @param {string} val - The value of the field.\n   * @return {string} Returns the sanitized value.\n   */\n    parse (val) {\n        const regex = /^\\s*([+-]?\\d+(?:\\.\\d+)?)\\s*-\\s*([+-]?\\d+(?:\\.\\d+)?)\\s*$/;\n        val = String(val);\n        let result;\n        // check if invalid date value\n        if (!InvalidAwareTypes.isInvalid(val)) {\n            let matched = val.match(regex);\n            result = matched ? `${Number.parseFloat(matched[1])}-${Number.parseFloat(matched[2])}`\n                             : InvalidAwareTypes.NA;\n        } else {\n            result = InvalidAwareTypes.getInvalidType(val);\n        }\n        return result;\n    }\n}\n","import FieldParser from '../field-parser';\nimport InvalidAwareTypes from '../../../invalid-aware-types';\n\n/**\n * A FieldParser which parses the continuous values.\n *\n * @public\n * @class\n * @implements {FieldParser}\n */\nexport default class ContinuousParser extends FieldParser {\n  /**\n   * Parses a single value of a field and returns the number form.\n   *\n   * @public\n   * @param {string|number} val - The value of the field.\n   * @return {string} Returns the number value.\n   */\n    parse (val) {\n        let result;\n        // check if invalid date value\n        if (!InvalidAwareTypes.isInvalid(val)) {\n            let parsedVal = parseFloat(val, 10);\n            result = Number.isNaN(parsedVal) ? InvalidAwareTypes.NA : parsedVal;\n        } else {\n            result = InvalidAwareTypes.getInvalidType(val);\n        }\n        return result;\n    }\n}\n","/**\n * Stores the full data and the metadata of a field. It provides\n * a single source of data from which the future Field\n * instance can get a subset of it with a rowDiffset config.\n *\n * @class\n * @public\n */\nexport default class PartialField {\n    /**\n     * Initialize a new instance.\n     *\n     * @public\n     * @param {string} name - The name of the field.\n     * @param {Array} data - The data array.\n     * @param {Object} schema - The schema object of the corresponding field.\n     * @param {FieldParser} parser - The parser instance corresponding to that field.\n     */\n    constructor (name, data, schema, parser) {\n        this.name = name;\n        this.schema = schema;\n        this.parser = parser;\n        this.data = this._sanitize(data);\n    }\n\n    /**\n     * Sanitizes the field data.\n     *\n     * @private\n     * @param {Array} data - The actual input data.\n     * @return {Array} Returns the sanitized data.\n     */\n    _sanitize (data) {\n        return data.map(datum => this.parser.parse(datum));\n    }\n}\n","import { FieldType, DimensionSubtype, MeasureSubtype } from './enums';\nimport {\n    Categorical,\n    Temporal,\n    Binned,\n    Continuous,\n    CategoricalParser,\n    TemporalParser,\n    BinnedParser,\n    ContinuousParser,\n    PartialField\n} from './fields';\n\n/**\n * Creates a field instance according to the provided data and schema.\n *\n * @param {Array} data - The field data array.\n * @param {Object} schema - The field schema object.\n * @return {Field} Returns the newly created field instance.\n */\nfunction createUnitField(data, schema) {\n    data = data || [];\n    let partialField;\n\n    switch (schema.type) {\n    case FieldType.MEASURE:\n        switch (schema.subtype) {\n        case MeasureSubtype.CONTINUOUS:\n            partialField = new PartialField(schema.name, data, schema, new ContinuousParser());\n            return new Continuous(partialField, `0-${data.length - 1}`);\n        default:\n            partialField = new PartialField(schema.name, data, schema, new ContinuousParser());\n            return new Continuous(partialField, `0-${data.length - 1}`);\n        }\n    case FieldType.DIMENSION:\n        switch (schema.subtype) {\n        case DimensionSubtype.CATEGORICAL:\n            partialField = new PartialField(schema.name, data, schema, new CategoricalParser());\n            return new Categorical(partialField, `0-${data.length - 1}`);\n        case DimensionSubtype.TEMPORAL:\n            partialField = new PartialField(schema.name, data, schema, new TemporalParser(schema));\n            return new Temporal(partialField, `0-${data.length - 1}`);\n        case DimensionSubtype.BINNED:\n            partialField = new PartialField(schema.name, data, schema, new BinnedParser());\n            return new Binned(partialField, `0-${data.length - 1}`);\n        default:\n            partialField = new PartialField(schema.name, data, schema, new CategoricalParser());\n            return new Categorical(partialField, `0-${data.length - 1}`);\n        }\n    default:\n        partialField = new PartialField(schema.name, data, schema, new CategoricalParser());\n        return new Categorical(partialField, `0-${data.length - 1}`);\n    }\n}\n\n\n/**\n * Creates a field instance from partialField and rowDiffset.\n *\n * @param {PartialField} partialField - The corresponding partial field.\n * @param {string} rowDiffset - The data subset config.\n * @return {Field} Returns the newly created field instance.\n */\nexport function createUnitFieldFromPartial(partialField, rowDiffset) {\n    const { schema } = partialField;\n\n    switch (schema.type) {\n    case FieldType.MEASURE:\n        switch (schema.subtype) {\n        case MeasureSubtype.CONTINUOUS:\n            return new Continuous(partialField, rowDiffset);\n        default:\n            return new Continuous(partialField, rowDiffset);\n        }\n    case FieldType.DIMENSION:\n        switch (schema.subtype) {\n        case DimensionSubtype.CATEGORICAL:\n            return new Categorical(partialField, rowDiffset);\n        case DimensionSubtype.TEMPORAL:\n            return new Temporal(partialField, rowDiffset);\n        case DimensionSubtype.BINNED:\n            return new Binned(partialField, rowDiffset);\n        default:\n            return new Categorical(partialField, rowDiffset);\n        }\n    default:\n        return new Categorical(partialField, rowDiffset);\n    }\n}\n\n/**\n * Creates the field instances with input data and schema.\n *\n * @param {Array} dataColumn - The data array for fields.\n * @param {Array} schema - The schema array for fields.\n * @param {Array} headers - The array of header names.\n * @return {Array.<Field>} Returns an array of newly created field instances.\n */\nexport function createFields(dataColumn, schema, headers) {\n    const headersObj = {};\n\n    if (!(headers && headers.length)) {\n        headers = schema.map(item => item.name);\n    }\n\n    headers.forEach((header, i) => {\n        headersObj[header] = i;\n    });\n\n    return schema.map(item => createUnitField(dataColumn[headersObj[item.name]], item));\n}\n","import { DataFormat } from './enums';\n\nexport default {\n    dataFormat: DataFormat.AUTO\n};\n","import { columnMajor } from '../utils';\n\n/**\n * Parses and converts data formatted in DSV array to a manageable internal format.\n *\n * @param {Array.<Array>} arr - A 2D array containing of the DSV data.\n * @param {Object} options - Option to control the behaviour of the parsing.\n * @param {boolean} [options.firstRowHeader=true] - Whether the first row of the dsv data is header or not.\n * @return {Array} Returns an array of headers and column major data.\n * @example\n *\n * // Sample input data:\n * const data = [\n *    [\"a\", \"b\", \"c\"],\n *    [1, 2, 3],\n *    [4, 5, 6],\n *    [7, 8, 9]\n * ];\n */\nfunction DSVArr(arr, schema, options) {\n    if (!Array.isArray(schema)) {\n        throw new Error('Schema missing or is in an unsupported format');\n    }\n    const defaultOption = {\n        firstRowHeader: true,\n    };\n    const schemaFields = schema.map(unitSchema => unitSchema.name);\n    options = Object.assign({}, defaultOption, options);\n\n    const columns = [];\n    const push = columnMajor(columns);\n\n    let headers = schemaFields;\n    if (options.firstRowHeader) {\n        // If header present then remove the first header row.\n        // Do in-place mutation to save space.\n        headers = arr.splice(0, 1)[0];\n    }\n    // create a map of the headers\n    const headerMap = headers.reduce((acc, h, i) => (\n        Object.assign(acc, { [h]: i })\n    ), {});\n\n    arr.forEach((fields) => {\n        const field = [];\n        schemaFields.forEach((schemaField) => {\n            const headIndex = headerMap[schemaField];\n            field.push(fields[headIndex]);\n        });\n        return push(...field);\n    });\n    return [schemaFields, columns];\n}\n\nexport default DSVArr;\n","var EOL = {},\n    EOF = {},\n    QUOTE = 34,\n    NEWLINE = 10,\n    RETURN = 13;\n\nfunction objectConverter(columns) {\n  return new Function(\"d\", \"return {\" + columns.map(function(name, i) {\n    return JSON.stringify(name) + \": d[\" + i + \"]\";\n  }).join(\",\") + \"}\");\n}\n\nfunction customConverter(columns, f) {\n  var object = objectConverter(columns);\n  return function(row, i) {\n    return f(object(row), i, columns);\n  };\n}\n\n// Compute unique columns in order of discovery.\nfunction inferColumns(rows) {\n  var columnSet = Object.create(null),\n      columns = [];\n\n  rows.forEach(function(row) {\n    for (var column in row) {\n      if (!(column in columnSet)) {\n        columns.push(columnSet[column] = column);\n      }\n    }\n  });\n\n  return columns;\n}\n\nfunction pad(value, width) {\n  var s = value + \"\", length = s.length;\n  return length < width ? new Array(width - length + 1).join(0) + s : s;\n}\n\nfunction formatYear(year) {\n  return year < 0 ? \"-\" + pad(-year, 6)\n    : year > 9999 ? \"+\" + pad(year, 6)\n    : pad(year, 4);\n}\n\nfunction formatDate(date) {\n  var hours = date.getUTCHours(),\n      minutes = date.getUTCMinutes(),\n      seconds = date.getUTCSeconds(),\n      milliseconds = date.getUTCMilliseconds();\n  return isNaN(date) ? \"Invalid Date\"\n      : formatYear(date.getUTCFullYear(), 4) + \"-\" + pad(date.getUTCMonth() + 1, 2) + \"-\" + pad(date.getUTCDate(), 2)\n      + (milliseconds ? \"T\" + pad(hours, 2) + \":\" + pad(minutes, 2) + \":\" + pad(seconds, 2) + \".\" + pad(milliseconds, 3) + \"Z\"\n      : seconds ? \"T\" + pad(hours, 2) + \":\" + pad(minutes, 2) + \":\" + pad(seconds, 2) + \"Z\"\n      : minutes || hours ? \"T\" + pad(hours, 2) + \":\" + pad(minutes, 2) + \"Z\"\n      : \"\");\n}\n\nexport default function(delimiter) {\n  var reFormat = new RegExp(\"[\\\"\" + delimiter + \"\\n\\r]\"),\n      DELIMITER = delimiter.charCodeAt(0);\n\n  function parse(text, f) {\n    var convert, columns, rows = parseRows(text, function(row, i) {\n      if (convert) return convert(row, i - 1);\n      columns = row, convert = f ? customConverter(row, f) : objectConverter(row);\n    });\n    rows.columns = columns || [];\n    return rows;\n  }\n\n  function parseRows(text, f) {\n    var rows = [], // output rows\n        N = text.length,\n        I = 0, // current character index\n        n = 0, // current line number\n        t, // current token\n        eof = N <= 0, // current token followed by EOF?\n        eol = false; // current token followed by EOL?\n\n    // Strip the trailing newline.\n    if (text.charCodeAt(N - 1) === NEWLINE) --N;\n    if (text.charCodeAt(N - 1) === RETURN) --N;\n\n    function token() {\n      if (eof) return EOF;\n      if (eol) return eol = false, EOL;\n\n      // Unescape quotes.\n      var i, j = I, c;\n      if (text.charCodeAt(j) === QUOTE) {\n        while (I++ < N && text.charCodeAt(I) !== QUOTE || text.charCodeAt(++I) === QUOTE);\n        if ((i = I) >= N) eof = true;\n        else if ((c = text.charCodeAt(I++)) === NEWLINE) eol = true;\n        else if (c === RETURN) { eol = true; if (text.charCodeAt(I) === NEWLINE) ++I; }\n        return text.slice(j + 1, i - 1).replace(/\"\"/g, \"\\\"\");\n      }\n\n      // Find next delimiter or newline.\n      while (I < N) {\n        if ((c = text.charCodeAt(i = I++)) === NEWLINE) eol = true;\n        else if (c === RETURN) { eol = true; if (text.charCodeAt(I) === NEWLINE) ++I; }\n        else if (c !== DELIMITER) continue;\n        return text.slice(j, i);\n      }\n\n      // Return last token before EOF.\n      return eof = true, text.slice(j, N);\n    }\n\n    while ((t = token()) !== EOF) {\n      var row = [];\n      while (t !== EOL && t !== EOF) row.push(t), t = token();\n      if (f && (row = f(row, n++)) == null) continue;\n      rows.push(row);\n    }\n\n    return rows;\n  }\n\n  function preformatBody(rows, columns) {\n    return rows.map(function(row) {\n      return columns.map(function(column) {\n        return formatValue(row[column]);\n      }).join(delimiter);\n    });\n  }\n\n  function format(rows, columns) {\n    if (columns == null) columns = inferColumns(rows);\n    return [columns.map(formatValue).join(delimiter)].concat(preformatBody(rows, columns)).join(\"\\n\");\n  }\n\n  function formatBody(rows, columns) {\n    if (columns == null) columns = inferColumns(rows);\n    return preformatBody(rows, columns).join(\"\\n\");\n  }\n\n  function formatRows(rows) {\n    return rows.map(formatRow).join(\"\\n\");\n  }\n\n  function formatRow(row) {\n    return row.map(formatValue).join(delimiter);\n  }\n\n  function formatValue(value) {\n    return value == null ? \"\"\n        : value instanceof Date ? formatDate(value)\n        : reFormat.test(value += \"\") ? \"\\\"\" + value.replace(/\"/g, \"\\\"\\\"\") + \"\\\"\"\n        : value;\n  }\n\n  return {\n    parse: parse,\n    parseRows: parseRows,\n    format: format,\n    formatBody: formatBody,\n    formatRows: formatRows\n  };\n}\n","import dsv from \"./dsv\";\n\nvar csv = dsv(\",\");\n\nexport var csvParse = csv.parse;\nexport var csvParseRows = csv.parseRows;\nexport var csvFormat = csv.format;\nexport var csvFormatBody = csv.formatBody;\nexport var csvFormatRows = csv.formatRows;\n","import dsv from \"./dsv\";\n\nvar tsv = dsv(\"\\t\");\n\nexport var tsvParse = tsv.parse;\nexport var tsvParseRows = tsv.parseRows;\nexport var tsvFormat = tsv.format;\nexport var tsvFormatBody = tsv.formatBody;\nexport var tsvFormatRows = tsv.formatRows;\n","import { dsvFormat as d3Dsv } from 'd3-dsv';\nimport DSVArr from './dsv-arr';\n\n/**\n * Parses and converts data formatted in DSV string to a manageable internal format.\n *\n * @todo Support to be given for https://tools.ietf.org/html/rfc4180.\n * @todo Sample implementation https://github.com/knrz/CSV.js/.\n *\n * @param {string} str - The input DSV string.\n * @param {Object} options - Option to control the behaviour of the parsing.\n * @param {boolean} [options.firstRowHeader=true] - Whether the first row of the dsv string data is header or not.\n * @param {string} [options.fieldSeparator=\",\"] - The separator of two consecutive field.\n * @return {Array} Returns an array of headers and column major data.\n * @example\n *\n * // Sample input data:\n * const data = `\n * a,b,c\n * 1,2,3\n * 4,5,6\n * 7,8,9\n * `\n */\nfunction DSVStr (str, schema, options) {\n    const defaultOption = {\n        firstRowHeader: true,\n        fieldSeparator: ','\n    };\n    options = Object.assign({}, defaultOption, options);\n\n    const dsv = d3Dsv(options.fieldSeparator);\n    return DSVArr(dsv.parseRows(str), schema, options);\n}\n\nexport default DSVStr;\n","import { columnMajor } from '../utils';\n\n/**\n * Parses and converts data formatted in JSON to a manageable internal format.\n *\n * @param {Array.<Object>} arr - The input data formatted in JSON.\n * @return {Array.<Object>} Returns an array of headers and column major data.\n * @example\n *\n * // Sample input data:\n * const data = [\n *    {\n *      \"a\": 1,\n *      \"b\": 2,\n *      \"c\": 3\n *    },\n *    {\n *      \"a\": 4,\n *      \"b\": 5,\n *      \"c\": 6\n *    },\n *    {\n *      \"a\": 7,\n *      \"b\": 8,\n *      \"c\": 9\n *    }\n * ];\n */\nfunction FlatJSON (arr, schema) {\n    if (!Array.isArray(schema)) {\n        throw new Error('Schema missing or is in an unsupported format');\n    }\n\n    const header = {};\n    let i = 0;\n    let insertionIndex;\n    const columns = [];\n    const push = columnMajor(columns);\n    const schemaFieldsName = schema.map(unitSchema => unitSchema.name);\n\n    arr.forEach((item) => {\n        const fields = [];\n        schemaFieldsName.forEach((unitSchema) => {\n            if (unitSchema in header) {\n                insertionIndex = header[unitSchema];\n            } else {\n                header[unitSchema] = i++;\n                insertionIndex = i - 1;\n            }\n            fields[insertionIndex] = item[unitSchema];\n        });\n        push(...fields);\n    });\n\n    return [Object.keys(header), columns];\n}\n\nexport default FlatJSON;\n","import FlatJSON from './flat-json';\nimport DSVArr from './dsv-arr';\nimport DSVStr from './dsv-str';\nimport { detectDataFormat } from '../utils';\n\n/**\n * Parses the input data and detect the format automatically.\n *\n * @param {string|Array} data - The input data.\n * @param {Object} options - An optional config specific to data format.\n * @return {Array.<Object>} Returns an array of headers and column major data.\n */\nfunction Auto (data, schema, options) {\n    const converters = { FlatJSON, DSVStr, DSVArr };\n    const dataFormat = detectDataFormat(data);\n\n    if (!dataFormat) {\n        throw new Error('Couldn\\'t detect the data format');\n    }\n\n    return converters[dataFormat](data, schema, options);\n}\n\nexport default Auto;\n","import { FieldType, FilteringMode, DimensionSubtype, MeasureSubtype, DataFormat } from './enums';\nimport fieldStore from './field-store';\nimport Value from './value';\nimport {\n    rowDiffsetIterator\n} from './operator';\nimport { DM_DERIVATIVES, LOGICAL_OPERATORS } from './constants';\nimport { createFields, createUnitFieldFromPartial } from './field-creator';\nimport defaultConfig from './default-config';\nimport * as converter from './converter';\nimport { extend2, detectDataFormat } from './utils';\n\n/**\n * Prepares the selection data.\n */\nfunction prepareSelectionData (fields, formattedData, rawData, i) {\n    const resp = {};\n\n    for (const [key, field] of fields.entries()) {\n        resp[field.name()] = new Value(formattedData[key][i], rawData[key][i], field);\n    }\n    return resp;\n}\n\nexport function prepareJoinData (fields) {\n    const resp = {};\n\n    for (const key in fields) {\n        resp[key] = new Value(fields[key].formattedValue, fields[key].rawValue, key);\n    }\n    return resp;\n}\n\nexport const updateFields = ([rowDiffset, colIdentifier], partialFieldspace, fieldStoreName) => {\n    let collID = colIdentifier.length ? colIdentifier.split(',') : [];\n    let partialFieldMap = partialFieldspace.fieldsObj();\n    let newFields = collID.map(coll => createUnitFieldFromPartial(partialFieldMap[coll].partialField, rowDiffset));\n    return fieldStore.createNamespace(newFields, fieldStoreName);\n};\n\nexport const persistCurrentDerivation = (model, operation, config = {}, criteriaFn) => {\n    if (operation === DM_DERIVATIVES.COMPOSE) {\n        model._derivation.length = 0;\n        model._derivation.push(...criteriaFn);\n    } else {\n        model._derivation.push({\n            op: operation,\n            meta: config,\n            criteria: criteriaFn\n        });\n    }\n};\nexport const persistAncestorDerivation = (sourceDm, newDm) => {\n    newDm._ancestorDerivation.push(...sourceDm._ancestorDerivation, ...sourceDm._derivation);\n};\n\nexport const persistDerivations = (sourceDm, model, operation, config = {}, criteriaFn) => {\n    persistCurrentDerivation(model, operation, config, criteriaFn);\n    persistAncestorDerivation(sourceDm, model);\n};\n\nconst selectModeMap = {\n    [FilteringMode.NORMAL]: {\n        diffIndex: ['rowDiffset'],\n        calcDiff: [true, false]\n    },\n    [FilteringMode.INVERSE]: {\n        diffIndex: ['rejectRowDiffset'],\n        calcDiff: [false, true]\n    },\n    [FilteringMode.ALL]: {\n        diffIndex: ['rowDiffset', 'rejectRowDiffset'],\n        calcDiff: [true, true]\n    }\n};\n\nconst generateRowDiffset = (rowDiffset, i, lastInsertedValue) => {\n    if (lastInsertedValue !== -1 && i === (lastInsertedValue + 1)) {\n        const li = rowDiffset.length - 1;\n\n        rowDiffset[li] = `${rowDiffset[li].split('-')[0]}-${i}`;\n    } else {\n        rowDiffset.push(`${i}`);\n    }\n};\n\nexport const selectRowDiffsetIterator = (rowDiffset, checker, mode) => {\n    let lastInsertedValueSel = -1;\n    let lastInsertedValueRej = -1;\n    const newRowDiffSet = [];\n    const rejRowDiffSet = [];\n\n    const [shouldSelect, shouldReject] = selectModeMap[mode].calcDiff;\n\n    rowDiffsetIterator(rowDiffset, (i) => {\n        const checkerResult = checker(i);\n        checkerResult && shouldSelect && generateRowDiffset(newRowDiffSet, i, lastInsertedValueSel);\n        !checkerResult && shouldReject && generateRowDiffset(rejRowDiffSet, i, lastInsertedValueRej);\n    });\n    return {\n        rowDiffset: newRowDiffSet.join(','),\n        rejectRowDiffset: rejRowDiffSet.join(',')\n    };\n};\n\n\nexport const rowSplitDiffsetIterator = (rowDiffset, checker, mode, dimensionArr, fieldStoreObj) => {\n    let lastInsertedValue = {};\n    const splitRowDiffset = {};\n    const dimensionMap = {};\n\n    rowDiffsetIterator(rowDiffset, (i) => {\n        if (checker(i)) {\n            let hash = '';\n\n            let dimensionSet = { keys: {} };\n\n            dimensionArr.forEach((_) => {\n                const data = fieldStoreObj[_].partialField.data[i];\n                hash = `${hash}-${data}`;\n                dimensionSet.keys[_] = data;\n            });\n\n            if (splitRowDiffset[hash] === undefined) {\n                splitRowDiffset[hash] = [];\n                lastInsertedValue[hash] = -1;\n                dimensionMap[hash] = dimensionSet;\n            }\n\n            generateRowDiffset(splitRowDiffset[hash], i, lastInsertedValue[hash]);\n            lastInsertedValue[hash] = i;\n        }\n    });\n\n    return {\n        splitRowDiffset,\n        dimensionMap\n    };\n};\n\n\nexport const selectHelper = (clonedDm, selectFn, config, sourceDm, iterator) => {\n    let cachedStore = {};\n    let cloneProvider = () => sourceDm.detachedRoot();\n    const { mode } = config;\n    const rowDiffset = clonedDm._rowDiffset;\n    const fields = clonedDm.getPartialFieldspace().fields;\n    const formattedFieldsData = fields.map(field => field.formattedData());\n    const rawFieldsData = fields.map(field => field.data());\n\n    const selectorHelperFn = index => selectFn(\n        prepareSelectionData(fields, formattedFieldsData, rawFieldsData, index),\n        index,\n        cloneProvider,\n        cachedStore\n    );\n\n    return iterator(rowDiffset, selectorHelperFn, mode);\n};\n\nexport const cloneWithAllFields = (model) => {\n    const clonedDm = model.clone(false);\n    const partialFieldspace = model.getPartialFieldspace();\n    clonedDm._colIdentifier = partialFieldspace.fields.map(f => f.name()).join(',');\n\n    // flush out cached namespace values on addition of new fields\n    partialFieldspace._cachedFieldsObj = null;\n    partialFieldspace._cachedDimension = null;\n    partialFieldspace._cachedMeasure = null;\n    clonedDm.__calculateFieldspace().calculateFieldsConfig();\n\n    return clonedDm;\n};\n\nconst getKey = (arr, data, fn) => {\n    let key = fn(arr, data, 0);\n\n    for (let i = 1, len = arr.length; i < len; i++) {\n        key = `${key},${fn(arr, data, i)}`;\n    }\n    return key;\n};\n\nexport const filterPropagationModel = (model, propModels, config = {}) => {\n    let fns = [];\n    const operation = config.operation || LOGICAL_OPERATORS.AND;\n    const filterByMeasure = config.filterByMeasure || false;\n    const clonedModel = cloneWithAllFields(model);\n    const modelFieldsConfig = clonedModel.getFieldsConfig();\n\n    if (!propModels.length) {\n        fns = [() => false];\n    } else {\n        fns = propModels.map(propModel => ((dataModel) => {\n            let keyFn;\n            const dataObj = dataModel.getData();\n            const fieldsConfig = dataModel.getFieldsConfig();\n            const dimensions = Object.keys(dataModel.getFieldspace().getDimension())\n                .filter(d => d in modelFieldsConfig);\n            const dLen = dimensions.length;\n            const indices = dimensions.map(d =>\n                fieldsConfig[d].index);\n            const measures = Object.keys(dataModel.getFieldspace().getMeasure())\n                .filter(d => d in modelFieldsConfig);\n            const fieldsSpace = dataModel.getFieldspace().fieldsObj();\n            const data = dataObj.data;\n            const domain = measures.reduce((acc, v) => {\n                acc[v] = fieldsSpace[v].domain();\n                return acc;\n            }, {});\n            const valuesMap = {};\n\n            keyFn = (arr, row, idx) => row[arr[idx]];\n            if (dLen) {\n                data.forEach((row) => {\n                    const key = getKey(indices, row, keyFn);\n                    valuesMap[key] = 1;\n                });\n            }\n\n            keyFn = (arr, fields, idx) => fields[arr[idx]].internalValue;\n            return data.length ? (fields) => {\n                const present = dLen ? valuesMap[getKey(dimensions, fields, keyFn)] : true;\n\n                if (filterByMeasure) {\n                    return measures.every(field => fields[field].internalValue >= domain[field][0] &&\n                        fields[field].internalValue <= domain[field][1]) && present;\n                }\n                return present;\n            } : () => false;\n        })(propModel));\n    }\n\n    let filteredModel;\n    if (operation === LOGICAL_OPERATORS.AND) {\n        filteredModel = clonedModel.select(fields => fns.every(fn => fn(fields)), {\n            saveChild: false\n        });\n    } else {\n        filteredModel = clonedModel.select(fields => fns.some(fn => fn(fields)), {\n            saveChild: false\n        });\n    }\n\n    return filteredModel;\n};\n\n\nexport const splitWithSelect = (sourceDm, dimensionArr, reducerFn = val => val, config) => {\n    const {\n        saveChild,\n    } = config;\n    const fieldStoreObj = sourceDm.getFieldspace().fieldsObj();\n\n    const {\n        splitRowDiffset,\n        dimensionMap\n    } = selectHelper(\n        sourceDm.clone(saveChild),\n        reducerFn,\n        config,\n        sourceDm,\n        (...params) => rowSplitDiffsetIterator(...params, dimensionArr, fieldStoreObj)\n        );\n\n    const clonedDMs = [];\n    Object.keys(splitRowDiffset).sort().forEach((e) => {\n        if (splitRowDiffset[e]) {\n            const cloned = sourceDm.clone(saveChild);\n            const derivation = dimensionMap[e];\n            cloned._rowDiffset = splitRowDiffset[e].join(',');\n            cloned.__calculateFieldspace().calculateFieldsConfig();\n\n            const derivationFormula = fields => dimensionArr.every(_ => fields[_].internalValue === derivation.keys[_]);\n            // Store reference to child model and selector function\n            if (saveChild) {\n                persistDerivations(sourceDm, cloned, DM_DERIVATIVES.SELECT, config, derivationFormula);\n            }\n            cloned._derivation[cloned._derivation.length - 1].meta = dimensionMap[e];\n\n            clonedDMs.push(cloned);\n        }\n    });\n\n\n    return clonedDMs;\n};\nexport const addDiffsetToClonedDm = (clonedDm, rowDiffset, sourceDm, selectConfig, selectFn) => {\n    clonedDm._rowDiffset = rowDiffset;\n    clonedDm.__calculateFieldspace().calculateFieldsConfig();\n    persistDerivations(\n        sourceDm,\n        clonedDm,\n        DM_DERIVATIVES.SELECT,\n         { config: selectConfig },\n          selectFn\n    );\n};\n\n\nexport const cloneWithSelect = (sourceDm, selectFn, selectConfig, cloneConfig) => {\n    let extraCloneDm = {};\n\n    let { mode } = selectConfig;\n\n    const cloned = sourceDm.clone(cloneConfig.saveChild);\n    const setOfRowDiffsets = selectHelper(\n        cloned,\n        selectFn,\n        selectConfig,\n        sourceDm,\n        selectRowDiffsetIterator\n    );\n    const diffIndex = selectModeMap[mode].diffIndex;\n\n    addDiffsetToClonedDm(cloned, setOfRowDiffsets[diffIndex[0]], sourceDm, selectConfig, selectFn);\n\n    if (diffIndex.length > 1) {\n        extraCloneDm = sourceDm.clone(cloneConfig.saveChild);\n        addDiffsetToClonedDm(extraCloneDm, setOfRowDiffsets[diffIndex[1]], sourceDm, selectConfig, selectFn);\n        return [cloned, extraCloneDm];\n    }\n\n    return cloned;\n};\n\nexport const cloneWithProject = (sourceDm, projField, config, allFields) => {\n    const cloned = sourceDm.clone(config.saveChild);\n    let projectionSet = projField;\n    if (config.mode === FilteringMode.INVERSE) {\n        projectionSet = allFields.filter(fieldName => projField.indexOf(fieldName) === -1);\n    }\n    // cloned._colIdentifier = sourceDm._colIdentifier.split(',')\n    //                         .filter(coll => projectionSet.indexOf(coll) !== -1).join();\n    cloned._colIdentifier = projectionSet.join(',');\n    cloned.__calculateFieldspace().calculateFieldsConfig();\n\n    persistDerivations(\n        sourceDm,\n        cloned,\n        DM_DERIVATIVES.PROJECT,\n        { projField, config, actualProjField: projectionSet },\n        null\n    );\n\n    return cloned;\n};\n\n\nexport const splitWithProject = (sourceDm, projFieldSet, config, allFields) =>\n    projFieldSet.map(projFields =>\n        cloneWithProject(sourceDm, projFields, config, allFields));\n\nexport const sanitizeUnitSchema = (unitSchema) => {\n    // Do deep clone of the unit schema as the user might change it later.\n    unitSchema = extend2({}, unitSchema);\n    if (!unitSchema.type) {\n        unitSchema.type = FieldType.DIMENSION;\n    }\n\n    if (!unitSchema.subtype) {\n        switch (unitSchema.type) {\n        case FieldType.MEASURE:\n            unitSchema.subtype = MeasureSubtype.CONTINUOUS;\n            break;\n        default:\n        case FieldType.DIMENSION:\n            unitSchema.subtype = DimensionSubtype.CATEGORICAL;\n            break;\n        }\n    }\n\n    return unitSchema;\n};\n\nexport const validateUnitSchema = (unitSchema) => {\n    const supportedMeasureSubTypes = [MeasureSubtype.CONTINUOUS];\n    const supportedDimSubTypes = [\n        DimensionSubtype.CATEGORICAL,\n        DimensionSubtype.BINNED,\n        DimensionSubtype.TEMPORAL,\n        DimensionSubtype.GEO\n    ];\n    const { type, subtype, name } = unitSchema;\n\n    switch (type) {\n    case FieldType.DIMENSION:\n        if (supportedDimSubTypes.indexOf(subtype) === -1) {\n            throw new Error(`DataModel doesn't support dimension field subtype ${subtype} used for ${name} field`);\n        }\n        break;\n    case FieldType.MEASURE:\n        if (supportedMeasureSubTypes.indexOf(subtype) === -1) {\n            throw new Error(`DataModel doesn't support measure field subtype ${subtype} used for ${name} field`);\n        }\n        break;\n    default:\n        throw new Error(`DataModel doesn't support field type ${type} used for ${name} field`);\n    }\n};\n\nexport const sanitizeAndValidateSchema = schema => schema.map((unitSchema) => {\n    unitSchema = sanitizeUnitSchema(unitSchema);\n    validateUnitSchema(unitSchema);\n    return unitSchema;\n});\n\nexport const resolveFieldName = (schema, dataHeader) => {\n    schema.forEach((unitSchema) => {\n        const fieldNameAs = unitSchema.as;\n        if (!fieldNameAs) { return; }\n\n        const idx = dataHeader.indexOf(unitSchema.name);\n        dataHeader[idx] = fieldNameAs;\n        unitSchema.name = fieldNameAs;\n        delete unitSchema.as;\n    });\n};\n\nexport const updateData = (relation, data, schema, options) => {\n    schema = sanitizeAndValidateSchema(schema);\n    options = Object.assign(Object.assign({}, defaultConfig), options);\n    const converterFn = converter[options.dataFormat];\n\n    if (!(converterFn && typeof converterFn === 'function')) {\n        throw new Error(`No converter function found for ${options.dataFormat} format`);\n    }\n\n    const [header, formattedData] = converterFn(data, schema, options);\n    resolveFieldName(schema, header);\n    const fieldArr = createFields(formattedData, schema, header);\n\n    // This will create a new fieldStore with the fields\n    const nameSpace = fieldStore.createNamespace(fieldArr, options.name);\n    relation._partialFieldspace = nameSpace;\n\n    // If data is provided create the default colIdentifier and rowDiffset\n    relation._rowDiffset = formattedData.length && formattedData[0].length ? `0-${formattedData[0].length - 1}` : '';\n\n    // This stores the value objects which is passed to the filter method when selection operation is done.\n    const valueObjects = [];\n    const { fields } = nameSpace;\n    const rawFieldsData = fields.map(field => field.data());\n    const formattedFieldsData = fields.map(field => field.formattedData());\n    rowDiffsetIterator(relation._rowDiffset, (i) => {\n        valueObjects[i] = prepareSelectionData(fields, formattedFieldsData, rawFieldsData, i);\n    });\n    nameSpace._cachedValueObjects = valueObjects;\n\n    relation._colIdentifier = (schema.map(_ => _.name)).join();\n    relation._dataFormat = options.dataFormat === DataFormat.AUTO ? detectDataFormat(data) : options.dataFormat;\n    return relation;\n};\n\nexport const fieldInSchema = (schema, field) => {\n    let i = 0;\n\n    for (; i < schema.length; ++i) {\n        if (field === schema[i].name) {\n            return {\n                name: field,\n                type: schema[i].subtype || schema[i].type,\n                index: i,\n            };\n        }\n    }\n    return null;\n};\n\nexport const getDerivationArguments = (derivation) => {\n    let params = [];\n    let operation;\n    operation = derivation.op;\n    switch (operation) {\n    case DM_DERIVATIVES.SELECT:\n        params = [derivation.criteria];\n        break;\n    case DM_DERIVATIVES.PROJECT:\n        params = [derivation.meta.actualProjField];\n        break;\n    case DM_DERIVATIVES.SORT:\n        params = [derivation.criteria];\n        break;\n    case DM_DERIVATIVES.GROUPBY:\n        operation = 'groupBy';\n        params = [derivation.meta.groupByString.split(','), derivation.criteria];\n        break;\n    default:\n        operation = null;\n    }\n\n    return {\n        operation,\n        params\n    };\n};\n\nconst applyExistingOperationOnModel = (propModel, dataModel) => {\n    const derivations = dataModel.getDerivations();\n    let selectionModel = propModel;\n\n    derivations.forEach((derivation) => {\n        if (!derivation) {\n            return;\n        }\n\n        const { operation, params } = getDerivationArguments(derivation);\n        if (operation) {\n            selectionModel = selectionModel[operation](...params, {\n                saveChild: false\n            });\n        }\n    });\n\n    return selectionModel;\n};\n\nconst getFilteredModel = (propModel, path) => {\n    for (let i = 0, len = path.length; i < len; i++) {\n        const model = path[i];\n        propModel = applyExistingOperationOnModel(propModel, model);\n    }\n    return propModel;\n};\n\nconst propagateIdentifiers = (dataModel, propModel, config = {}, propModelInf = {}) => {\n    const nonTraversingModel = propModelInf.nonTraversingModel;\n    const excludeModels = propModelInf.excludeModels || [];\n\n    if (dataModel === nonTraversingModel) {\n        return;\n    }\n\n    const propagate = excludeModels.length ? excludeModels.indexOf(dataModel) === -1 : true;\n\n    propagate && dataModel.handlePropagation(propModel, config);\n\n    const children = dataModel._children;\n    children.forEach((child) => {\n        const selectionModel = applyExistingOperationOnModel(propModel, child);\n        propagateIdentifiers(child, selectionModel, config, propModelInf);\n    });\n};\n\nexport const getRootGroupByModel = (model) => {\n    while (model._parent && model._derivation.find(d => d.op !== DM_DERIVATIVES.GROUPBY)) {\n        model = model._parent;\n    }\n    return model;\n};\n\nexport const getRootDataModel = (model) => {\n    while (model._parent) {\n        model = model._parent;\n    }\n    return model;\n};\n\nexport const getPathToRootModel = (model, path = []) => {\n    while (model._parent) {\n        path.push(model);\n        model = model._parent;\n    }\n    return path;\n};\n\nexport const propagateToAllDataModels = (identifiers, rootModels, propagationInf, config) => {\n    let criteria;\n    let propModel;\n    const { propagationNameSpace, propagateToSource } = propagationInf;\n    const propagationSourceId = propagationInf.sourceId;\n    const propagateInterpolatedValues = config.propagateInterpolatedValues;\n    const filterFn = (entry) => {\n        const filter = config.filterFn || (() => true);\n        return filter(entry, config);\n    };\n\n    let criterias = [];\n\n    if (identifiers === null && config.persistent !== true) {\n        criterias = [{\n            criteria: []\n        }];\n        criteria = [];\n    } else {\n        let actionCriterias = Object.values(propagationNameSpace.mutableActions);\n        if (propagateToSource !== false) {\n            actionCriterias = actionCriterias.filter(d => d.config.sourceId !== propagationSourceId);\n        }\n\n        const filteredCriteria = actionCriterias.filter(filterFn).map(action => action.config.criteria);\n\n        const excludeModels = [];\n\n        if (propagateToSource !== false) {\n            const sourceActionCriterias = Object.values(propagationNameSpace.mutableActions);\n\n            sourceActionCriterias.forEach((actionInf) => {\n                const actionConf = actionInf.config;\n                if (actionConf.applyOnSource === false && actionConf.action === config.action &&\n                        actionConf.sourceId !== propagationSourceId) {\n                    excludeModels.push(actionInf.model);\n                    criteria = sourceActionCriterias.filter(d => d !== actionInf).map(d => d.config.criteria);\n                    criteria.length && criterias.push({\n                        criteria,\n                        models: actionInf.model,\n                        path: getPathToRootModel(actionInf.model)\n                    });\n                }\n            });\n        }\n\n\n        criteria = [].concat(...[...filteredCriteria, identifiers]).filter(d => d !== null);\n        criterias.push({\n            criteria,\n            excludeModels: [...excludeModels, ...config.excludeModels || []]\n        });\n    }\n\n    const rootModel = rootModels.model;\n\n    const propConfig = Object.assign({\n        sourceIdentifiers: identifiers,\n        propagationSourceId\n    }, config);\n\n    const rootGroupByModel = rootModels.groupByModel;\n    if (propagateInterpolatedValues && rootGroupByModel) {\n        propModel = filterPropagationModel(rootGroupByModel, criteria, {\n            filterByMeasure: propagateInterpolatedValues\n        });\n        propagateIdentifiers(rootGroupByModel, propModel, propConfig);\n    }\n\n    criterias.forEach((inf) => {\n        const propagationModel = filterPropagationModel(rootModel, inf.criteria);\n        const path = inf.path;\n\n        if (path) {\n            const filteredModel = getFilteredModel(propagationModel, path.reverse());\n            inf.models.handlePropagation(filteredModel, propConfig);\n        } else {\n            propagateIdentifiers(rootModel, propagationModel, propConfig, {\n                excludeModels: inf.excludeModels,\n                nonTraversingModel: propagateInterpolatedValues && rootGroupByModel\n            });\n        }\n    });\n};\n\nexport const propagateImmutableActions = (propagationNameSpace, rootModels, propagationInf) => {\n    const immutableActions = propagationNameSpace.immutableActions;\n\n    for (const action in immutableActions) {\n        const actionInf = immutableActions[action];\n        const actionConf = actionInf.config;\n        const propagationSourceId = propagationInf.config.sourceId;\n        const filterImmutableAction = propagationInf.propConfig.filterImmutableAction ?\n            propagationInf.propConfig.filterImmutableAction(actionConf, propagationInf.config) : true;\n        if (actionConf.sourceId !== propagationSourceId && filterImmutableAction) {\n            const criteriaModel = actionConf.criteria;\n            propagateToAllDataModels(criteriaModel, rootModels, {\n                propagationNameSpace,\n                propagateToSource: false,\n                sourceId: propagationSourceId\n            }, actionConf);\n        }\n    }\n};\n\nexport const addToPropNamespace = (propagationNameSpace, config = {}, model) => {\n    let sourceNamespace;\n    const isMutableAction = config.isMutableAction;\n    const criteria = config.criteria;\n    const key = `${config.action}-${config.sourceId}`;\n\n    if (isMutableAction) {\n        sourceNamespace = propagationNameSpace.mutableActions;\n    } else {\n        sourceNamespace = propagationNameSpace.immutableActions;\n    }\n\n    if (criteria === null) {\n        delete sourceNamespace[key];\n    } else {\n        sourceNamespace[key] = {\n            model,\n            config\n        };\n    }\n\n    return this;\n};\n\n\nexport const getNormalizedProFields = (projField, allFields, fieldConfig) => {\n    const normalizedProjField = projField.reduce((acc, field) => {\n        if (field.constructor.name === 'RegExp') {\n            acc.push(...allFields.filter(fieldName => fieldName.search(field) !== -1));\n        } else if (field in fieldConfig) {\n            acc.push(field);\n        }\n        return acc;\n    }, []);\n    return Array.from(new Set(normalizedProjField)).map(field => field.trim());\n};\n\n/**\n * Get the numberFormatted value if numberFormat present,\n * else returns the supplied value.\n * @param {Object} field Field Instance\n * @param {Number|String} value\n * @return {Number|String}\n */\nexport const getNumberFormattedVal = (field, value) => {\n    if (field.numberFormat) {\n        return field.numberFormat()(value);\n    }\n    return value;\n};\n","import { FilteringMode } from './enums';\nimport { getUniqueId } from './utils';\nimport {\n    updateFields,\n    cloneWithSelect,\n    cloneWithProject,\n    updateData,\n    getNormalizedProFields\n} from './helper';\nimport { crossProduct, difference, naturalJoinFilter, union } from './operator';\n\n/**\n * Relation provides the definitions of basic operators of relational algebra like *selection*, *projection*, *union*,\n * *difference* etc.\n *\n * It is extended by {@link DataModel} to inherit the functionalities of relational algebra concept.\n *\n * @class\n * @public\n * @module Relation\n * @namespace DataModel\n */\nclass Relation {\n\n    /**\n     * Creates a new Relation instance by providing underlying data and schema.\n     *\n     * @private\n     *\n     * @param {Object | string | Relation} data - The input tabular data in dsv or json format or\n     * an existing Relation instance object.\n     * @param {Array} schema - An array of data schema.\n     * @param {Object} [options] - The optional options.\n     */\n    constructor (...params) {\n        let source;\n\n        this._parent = null;\n        this._derivation = [];\n        this._ancestorDerivation = [];\n        this._children = [];\n\n        if (params.length === 1 && ((source = params[0]) instanceof Relation)) {\n            // parent datamodel was passed as part of source\n            this._colIdentifier = source._colIdentifier;\n            this._rowDiffset = source._rowDiffset;\n            this._dataFormat = source._dataFormat;\n            this._parent = source;\n            this._partialFieldspace = this._parent._partialFieldspace;\n            this._fieldStoreName = getUniqueId();\n            this.__calculateFieldspace().calculateFieldsConfig();\n        } else {\n            updateData(this, ...params);\n            this._fieldStoreName = this._partialFieldspace.name;\n            this.__calculateFieldspace().calculateFieldsConfig();\n            this._propagationNameSpace = {\n                mutableActions: {},\n                immutableActions: {}\n            };\n        }\n    }\n\n    /**\n     * Retrieves the {@link Schema | schema} details for every {@link Field | field} as an array.\n     *\n     * @public\n     *\n     * @return {Array.<Schema>} Array of fields schema.\n     *      ```\n     *      [\n     *          { name: 'Name', type: 'dimension' },\n     *          { name: 'Miles_per_Gallon', type: 'measure', numberFormat: (val) => `${val} miles / gallon` },\n     *          { name: 'Cylinder', type: 'dimension' },\n     *          { name: 'Displacement', type: 'measure', defAggFn: 'max' },\n     *          { name: 'HorsePower', type: 'measure', defAggFn: 'max' },\n     *          { name: 'Weight_in_lbs', type: 'measure', defAggFn: 'avg',  },\n     *          { name: 'Acceleration', type: 'measure', defAggFn: 'avg' },\n     *          { name: 'Year', type: 'dimension', subtype: 'datetime', format: '%Y' },\n     *          { name: 'Origin' }\n     *      ]\n     *      ```\n     */\n    getSchema () {\n        return this.getFieldspace().fields.map(d => d.schema());\n    }\n\n    /**\n     * Returns the name of the {@link DataModel} instance. If no name was specified during {@link DataModel}\n     * initialization, then it returns a auto-generated name.\n     *\n     * @public\n     *\n     * @return {string} Name of the DataModel instance.\n     */\n    getName() {\n        return this._fieldStoreName;\n    }\n\n    getFieldspace () {\n        return this._fieldspace;\n    }\n\n    __calculateFieldspace () {\n        this._fieldspace = updateFields([this._rowDiffset, this._colIdentifier],\n             this.getPartialFieldspace(), this._fieldStoreName);\n        return this;\n    }\n\n    getPartialFieldspace () {\n        return this._partialFieldspace;\n    }\n\n    /**\n     * Performs {@link link_of_cross_product | cross-product} between two {@link DataModel} instances and returns a\n     * new {@link DataModel} instance containing the results. This operation is also called theta join.\n     *\n     * Cross product takes two set and create one set where each value of one set is paired with each value of another\n     * set.\n     *\n     * This method takes an optional predicate which filters the generated result rows. If the predicate returns true\n     * the combined row is included in the resulatant table.\n     *\n     * @example\n     *  let originDM = dm.project(['Origin','Origin_Formal_Name']);\n     *  let carsDM = dm.project(['Name','Miles_per_Gallon','Origin'])\n     *\n     *  console.log(carsDM.join(originDM)));\n     *\n     *  console.log(carsDM.join(originDM,\n     *      obj => obj.[originDM.getName()].Origin === obj.[carsDM.getName()].Origin));\n     *\n     * @text\n     * This is chained version of `join` operator. `join` can also be used as\n     * {@link link_to_join_op | functional operator}.\n     *\n     * @public\n     *\n     * @param {DataModel} joinWith - The DataModel to be joined with the current instance DataModel.\n     * @param {SelectionPredicate} filterFn - The predicate function that will filter the result of the crossProduct.\n     *\n     * @return {DataModel} New DataModel instance created after joining.\n     */\n    join (joinWith, filterFn) {\n        return crossProduct(this, joinWith, filterFn);\n    }\n\n    /**\n     * {@link natural_join | Natural join} is a special kind of cross-product join where filtering of rows are performed\n     * internally by resolving common fields are from both table and the rows with common value are included.\n     *\n     * @example\n     *  let originDM = dm.project(['Origin','Origin_Formal_Name']);\n     *  let carsDM = dm.project(['Name','Miles_per_Gallon','Origin'])\n     *\n     *  console.log(carsDM.naturalJoin(originDM));\n     *\n     * @text\n     * This is chained version of `naturalJoin` operator. `naturalJoin` can also be used as\n     * {@link link_to_join_op | functional operator}.\n     *\n     * @public\n     *\n     * @param {DataModel} joinWith - The DataModel with which the current instance of DataModel on which the method is\n     *      called will be joined.\n     * @return {DataModel} New DataModel instance created after joining.\n     */\n    naturalJoin (joinWith) {\n        return crossProduct(this, joinWith, naturalJoinFilter(this, joinWith), true);\n    }\n\n    /**\n     * {@link link_to_union | Union} operation can be termed as vertical stacking of all rows from both the DataModel\n     * instances, provided that both of the {@link DataModel} instances should have same column names.\n     *\n     * @example\n     * console.log(EuropeanMakerDM.union(USAMakerDM));\n     *\n     * @text\n     * This is chained version of `naturalJoin` operator. `naturalJoin` can also be used as\n     * {@link link_to_join_op | functional operator}.\n     *\n     * @public\n     *\n     * @param {DataModel} unionWith - DataModel instance for which union has to be applied with the instance on which\n     *      the method is called\n     *\n     * @return {DataModel} New DataModel instance with the result of the operation\n     */\n    union (unionWith) {\n        return union(this, unionWith);\n    }\n\n    /**\n     * {@link link_to_difference | Difference } operation only include rows which are present in the datamodel on which\n     * it was called but not on the one passed as argument.\n     *\n     * @example\n     * console.log(highPowerDM.difference(highExpensiveDM));\n     *\n     * @text\n     * This is chained version of `naturalJoin` operator. `naturalJoin` can also be used as\n     * {@link link_to_join_op | functional operator}.\n     *\n     * @public\n     *\n     * @param {DataModel} differenceWith - DataModel instance for which difference has to be applied with the instance\n     *      on which the method is called\n     * @return {DataModel} New DataModel instance with the result of the operation\n     */\n    difference (differenceWith) {\n        return difference(this, differenceWith);\n    }\n\n    /**\n     * {@link link_to_selection | Selection} is a row filtering operation. It expects a predicate and an optional mode\n     * which control which all rows should be included in the resultant DataModel instance.\n     *\n     * {@link SelectionPredicate} is a function which returns a boolean value. For selection operation the selection\n     * function is called for each row of DataModel instance with the current row passed as argument.\n     *\n     * After executing {@link SelectionPredicate} the rows are labeled as either an entry of selection set or an entry\n     * of rejection set.\n     *\n     * {@link FilteringMode} operates on the selection and rejection set to determine which one would reflect in the\n     * resultant datamodel.\n     *\n     * @warning\n     * Selection and rejection set is only a logical idea for concept explanation purpose.\n     *\n     * @example\n     *  // with selection mode NORMAL:\n     *  const normDt = dt.select(fields => fields.Origin.value === \"USA\")\n     *  console.log(normDt));\n     *\n     * // with selection mode INVERSE:\n     * const inverDt = dt.select(fields => fields.Origin.value === \"USA\", { mode: DataModel.FilteringMode.INVERSE })\n     * console.log(inverDt);\n     *\n     * // with selection mode ALL:\n     * const dtArr = dt.select(fields => fields.Origin.value === \"USA\", { mode: DataModel.FilteringMode.ALL })\n     * // print the selected parts\n     * console.log(dtArr[0]);\n     * // print the inverted parts\n     * console.log(dtArr[1]);\n     *\n     * @text\n     * This is chained version of `select` operator. `select` can also be used as\n     * {@link link_to_join_op | functional operator}.\n     *\n     * @public\n     *\n     * @param {Function} selectFn - The predicate function which is called for each row with the current row.\n     * ```\n     *  function (row, i, cloneProvider, store)  { ... }\n     * ```\n     * @param {Object} config - The configuration object to control the inclusion exclusion of a row in resultant\n     * DataModel instance.\n     * @param {FilteringMode} [config.mode=FilteringMode.NORMAL] - The mode of the selection.\n     * @return {DataModel} Returns the new DataModel instance(s) after operation.\n     */\n    select (selectFn, config) {\n        const defConfig = {\n            mode: FilteringMode.NORMAL,\n            saveChild: true\n        };\n        config = Object.assign({}, defConfig, config);\n        config.mode = config.mode || defConfig.mode;\n\n        const cloneConfig = { saveChild: config.saveChild };\n        return cloneWithSelect(\n            this,\n            selectFn,\n            config,\n            cloneConfig\n        );\n    }\n\n    /**\n     * Retrieves a boolean value if the current {@link DataModel} instance has data.\n     *\n     * @example\n     * const schema = [\n     *    { name: 'CarName', type: 'dimension' },\n     *    { name: 'HorsePower', type: 'measure' },\n     *    { name: \"Origin\", type: 'dimension' }\n     * ];\n     * const data = [];\n     *\n     * const dt = new DataModel(data, schema);\n     * console.log(dt.isEmpty());\n     *\n     * @public\n     *\n     * @return {Boolean} True if the datamodel has no data, otherwise false.\n     */\n    isEmpty () {\n        return !this._rowDiffset.length || !this._colIdentifier.length;\n    }\n\n    /**\n     * Creates a clone from the current DataModel instance with child parent relationship.\n     *\n     * @private\n     * @param {boolean} [saveChild=true] - Whether the cloned instance would be recorded in the parent instance.\n     * @return {DataModel} - Returns the newly cloned DataModel instance.\n     */\n    clone (saveChild = true) {\n        const clonedDm = new this.constructor(this);\n        if (saveChild) {\n            clonedDm.setParent(this);\n        } else {\n            clonedDm.setParent(null);\n        }\n        return clonedDm;\n    }\n\n    /**\n     * {@link Projection} is filter column (field) operation. It expects list of fields' name and either include those\n     * or exclude those based on {@link FilteringMode} on the resultant variable.\n     *\n     * Projection expects array of fields name based on which it creates the selection and rejection set. All the field\n     * whose name is present in array goes in selection set and rest of the fields goes in rejection set.\n     *\n     * {@link FilteringMode} operates on the selection and rejection set to determine which one would reflect in the\n     * resulatant datamodel.\n     *\n     * @warning\n     * Selection and rejection set is only a logical idea for concept explanation purpose.\n     *\n     * @example\n     *  const dm = new DataModel(data, schema);\n     *\n     *  // with projection mode NORMAL:\n     *  const normDt = dt.project([\"Name\", \"HorsePower\"]);\n     *  console.log(normDt.getData());\n     *\n     *  // with projection mode INVERSE:\n     *  const inverDt = dt.project([\"Name\", \"HorsePower\"], { mode: DataModel.FilteringMode.INVERSE })\n     *  console.log(inverDt.getData());\n     *\n     *  // with selection mode ALL:\n     *  const dtArr = dt.project([\"Name\", \"HorsePower\"], { mode: DataModel.FilteringMode.ALL })\n     *  // print the normal parts\n     *  console.log(dtArr[0].getData());\n     *  // print the inverted parts\n     *  console.log(dtArr[1].getData());\n     *\n     * @text\n     * This is chained version of `select` operator. `select` can also be used as\n     * {@link link_to_join_op | functional operator}.\n     *\n     * @public\n     *\n     * @param {Array.<string | Regexp>} projField - An array of column names in string or regular expression.\n     * @param {Object} [config] - An optional config to control the creation of new DataModel\n     * @param {FilteringMode} [config.mode=FilteringMode.NORMAL] - Mode of the projection\n     *\n     * @return {DataModel} Returns the new DataModel instance after operation.\n     */\n    project (projField, config) {\n        const defConfig = {\n            mode: FilteringMode.NORMAL,\n            saveChild: true\n        };\n        config = Object.assign({}, defConfig, config);\n        const fieldConfig = this.getFieldsConfig();\n        const allFields = Object.keys(fieldConfig);\n        const { mode } = config;\n        const normalizedProjField = getNormalizedProFields(projField, allFields, fieldConfig);\n\n        let dataModel;\n\n        if (mode === FilteringMode.ALL) {\n            let projectionClone = cloneWithProject(this, normalizedProjField, {\n                mode: FilteringMode.NORMAL,\n                saveChild: config.saveChild\n            }, allFields);\n            let rejectionClone = cloneWithProject(this, normalizedProjField, {\n                mode: FilteringMode.INVERSE,\n                saveChild: config.saveChild\n            }, allFields);\n            dataModel = [projectionClone, rejectionClone];\n        } else {\n            let projectionClone = cloneWithProject(this, normalizedProjField, config, allFields);\n            dataModel = projectionClone;\n        }\n\n        return dataModel;\n    }\n\n    getFieldsConfig () {\n        return this._fieldConfig;\n    }\n\n    calculateFieldsConfig () {\n        this._fieldConfig = this._fieldspace.fields.reduce((acc, fieldObj, i) => {\n            acc[fieldObj.name()] = {\n                index: i,\n                def: fieldObj.schema(),\n            };\n            return acc;\n        }, {});\n        return this;\n    }\n\n\n    /**\n     * Frees up the resources associated with the current DataModel instance and breaks all the links instance has in\n     * the DAG.\n     *\n     * @public\n     */\n    dispose () {\n        this._parent && this._parent.removeChild(this);\n        this._parent = null;\n        this._children.forEach((child) => {\n            child._parent = null;\n        });\n        this._children = [];\n    }\n\n    /**\n     * Removes the specified child {@link DataModel} from the child list of the current {@link DataModel} instance.\n     *\n     * @example\n     * const schema = [\n     *    { name: 'Name', type: 'dimension' },\n     *    { name: 'HorsePower', type: 'measure' },\n     *    { name: \"Origin\", type: 'dimension' }\n     * ];\n     *\n     * const data = [\n     *    { Name: \"chevrolet chevelle malibu\", Horsepower: 130, Origin: \"USA\" },\n     *    { Name: \"citroen ds-21 pallas\", Horsepower: 115, Origin: \"Europe\" },\n     *    { Name: \"datsun pl510\", Horsepower: 88, Origin: \"Japan\" },\n     *    { Name: \"amc rebel sst\", Horsepower: 150, Origin: \"USA\"},\n     * ]\n     *\n     * const dt = new DataModel(data, schema);\n     *\n     * const dt2 = dt.select(fields => fields.Origin.value === \"USA\")\n     * dt.removeChild(dt2);\n     *\n     * @private\n     *\n     * @param {DataModel} child - Delegates the parent to remove this child.\n     */\n    removeChild (child) {\n        let idx = this._children.findIndex(sibling => sibling === child);\n        idx !== -1 ? this._children.splice(idx, 1) : true;\n    }\n\n    /**\n     * Sets the specified {@link DataModel} as a parent for the current {@link DataModel} instance.\n     *\n     * @param {DataModel} parent - The datamodel instance which will act as parent.\n     */\n    setParent (parent) {\n        this._parent && this._parent.removeChild(this);\n        this._parent = parent;\n        parent && parent._children.push(this);\n    }\n\n    /**\n     * Returns the parent {@link DataModel} instance.\n     *\n     * @example\n     * const schema = [\n     *    { name: 'Name', type: 'dimension' },\n     *    { name: 'HorsePower', type: 'measure' },\n     *    { name: \"Origin\", type: 'dimension' }\n     * ];\n     *\n     * const data = [\n     *    { Name: \"chevrolet chevelle malibu\", Horsepower: 130, Origin: \"USA\" },\n     *    { Name: \"citroen ds-21 pallas\", Horsepower: 115, Origin: \"Europe\" },\n     *    { Name: \"datsun pl510\", Horsepower: 88, Origin: \"Japan\" },\n     *    { Name: \"amc rebel sst\", Horsepower: 150, Origin: \"USA\"},\n     * ]\n     *\n     * const dt = new DataModel(data, schema);\n     *\n     * const dt2 = dt.select(fields => fields.Origin.value === \"USA\");\n     * const parentDm = dt2.getParent();\n     *\n     * @return {DataModel} Returns the parent DataModel instance.\n     */\n    getParent () {\n        return this._parent;\n    }\n\n    /**\n     * Returns the immediate child {@link DataModel} instances.\n     *\n     * @example\n     * const schema = [\n     *    { name: 'Name', type: 'dimension' },\n     *    { name: 'HorsePower', type: 'measure' },\n     *    { name: \"Origin\", type: 'dimension' }\n     * ];\n     *\n     * const data = [\n     *    { Name: \"chevrolet chevelle malibu\", Horsepower: 130, Origin: \"USA\" },\n     *    { Name: \"citroen ds-21 pallas\", Horsepower: 115, Origin: \"Europe\" },\n     *    { Name: \"datsun pl510\", Horsepower: 88, Origin: \"Japan\" },\n     *    { Name: \"amc rebel sst\", Horsepower: 150, Origin: \"USA\"},\n     * ]\n     *\n     * const dt = new DataModel(data, schema);\n     *\n     * const childDm1 = dt.select(fields => fields.Origin.value === \"USA\");\n     * const childDm2 = dt.select(fields => fields.Origin.value === \"Japan\");\n     * const childDm3 = dt.groupBy([\"Origin\"]);\n     *\n     * @return {DataModel[]} Returns the immediate child DataModel instances.\n     */\n    getChildren () {\n        return this._children;\n    }\n\n    /**\n     * Returns the in-between operation meta data while creating the current {@link DataModel} instance.\n     *\n     * @example\n     * const schema = [\n     *   { name: 'Name', type: 'dimension' },\n     *   { name: 'HorsePower', type: 'measure' },\n     *   { name: \"Origin\", type: 'dimension' }\n     * ];\n     *\n     * const data = [\n     *   { Name: \"chevrolet chevelle malibu\", Horsepower: 130, Origin: \"USA\" },\n     *   { Name: \"citroen ds-21 pallas\", Horsepower: 115, Origin: \"Europe\" },\n     *   { Name: \"datsun pl510\", Horsepower: 88, Origin: \"Japan\" },\n     *   { Name: \"amc rebel sst\", Horsepower: 150, Origin: \"USA\"},\n     * ]\n     *\n     * const dt = new DataModel(data, schema);\n     * const dt2 = dt.select(fields => fields.Origin.value === \"USA\");\n     * const dt3 = dt2.groupBy([\"Origin\"]);\n     * const derivations = dt3.getDerivations();\n     *\n     * @return {Any[]} Returns the derivation meta data.\n     */\n    getDerivations () {\n        return this._derivation;\n    }\n\n    /**\n     * Returns the in-between operation meta data happened from root {@link DataModel} to current instance.\n     *\n     * @example\n     * const schema = [\n     *   { name: 'Name', type: 'dimension' },\n     *   { name: 'HorsePower', type: 'measure' },\n     *   { name: \"Origin\", type: 'dimension' }\n     * ];\n     *\n     * const data = [\n     *   { Name: \"chevrolet chevelle malibu\", Horsepower: 130, Origin: \"USA\" },\n     *   { Name: \"citroen ds-21 pallas\", Horsepower: 115, Origin: \"Europe\" },\n     *   { Name: \"datsun pl510\", Horsepower: 88, Origin: \"Japan\" },\n     *   { Name: \"amc rebel sst\", Horsepower: 150, Origin: \"USA\"},\n     * ]\n     *\n     * const dt = new DataModel(data, schema);\n     * const dt2 = dt.select(fields => fields.Origin.value === \"USA\");\n     * const dt3 = dt2.groupBy([\"Origin\"]);\n     * const ancDerivations = dt3.getAncestorDerivations();\n     *\n     * @return {Any[]} Returns the previous derivation meta data.\n     */\n    getAncestorDerivations () {\n        return this._ancestorDerivation;\n    }\n}\n\nexport default Relation;\n","/* eslint-disable default-case */\n\nimport { FieldType, DimensionSubtype, DataFormat, FilteringMode } from './enums';\nimport {\n    persistDerivations,\n    getRootGroupByModel,\n    propagateToAllDataModels,\n    getRootDataModel,\n    propagateImmutableActions,\n    addToPropNamespace,\n    sanitizeUnitSchema,\n    splitWithSelect,\n    splitWithProject,\n    getNormalizedProFields\n} from './helper';\nimport { DM_DERIVATIVES, PROPAGATION } from './constants';\nimport {\n    dataBuilder,\n    rowDiffsetIterator,\n    groupBy\n} from './operator';\nimport { createBinnedFieldData } from './operator/bucket-creator';\nimport Relation from './relation';\nimport reducerStore from './utils/reducer-store';\nimport { createFields } from './field-creator';\nimport InvalidAwareTypes from './invalid-aware-types';\nimport Value from './value';\n\n/**\n * DataModel is an in-browser representation of tabular data. It supports\n * {@link https://en.wikipedia.org/wiki/Relational_algebra | relational algebra} operators as well as generic data\n * processing opearators.\n * DataModel extends {@link Relation} class which defines all the relational algebra opreators. DataModel gives\n * definition of generic data processing operators which are not relational algebra complient.\n *\n * @public\n * @class\n * @extends Relation\n * @memberof Datamodel\n */\nclass DataModel extends Relation {\n    /**\n     * Creates a new DataModel instance by providing data and schema. Data could be in the form of\n     * - Flat JSON\n     * - DSV String\n     * - 2D Array\n     *\n     * By default DataModel finds suitable adapter to serialize the data. DataModel also expects a\n     * {@link Schema | schema} for identifying the variables present in data.\n     *\n     * @constructor\n     * @example\n     * const data = loadData('cars.csv');\n     * const schema = [\n     *      { name: 'Name', type: 'dimension' },\n     *      { name: 'Miles_per_Gallon', type: 'measure', unit : 'cm', scale: '1000', numberformat: val => `${val}G`},\n     *      { name: 'Cylinders', type: 'dimension' },\n     *      { name: 'Displacement', type: 'measure' },\n     *      { name: 'Horsepower', type: 'measure' },\n     *      { name: 'Weight_in_lbs', type: 'measure' },\n     *      { name: 'Acceleration', type: 'measure' },\n     *      { name: 'Year', type: 'dimension', subtype: 'datetime', format: '%Y' },\n     *      { name: 'Origin', type: 'dimension' }\n     * ];\n     * const dm = new DataModel(data, schema, { name: 'Cars' });\n     * table(dm);\n     *\n     * @public\n     *\n     * @param {Array.<Object> | string | Array.<Array>} data Input data in any of the mentioned formats\n     * @param {Array.<Schema>} schema Defination of the variables. Order of the variables in data and order of the\n     *      variables in schema has to be same.\n     * @param {object} [options] Optional arguments to specify more settings regarding the creation part\n     * @param {string} [options.name] Name of the datamodel instance. If no name is given an auto generated name is\n     *      assigned to the instance.\n     * @param {string} [options.fieldSeparator=','] specify field separator type if the data is of type dsv string.\n     */\n    constructor (...args) {\n        super(...args);\n\n        this._onPropagation = [];\n    }\n\n    /**\n     * Reducers are simple functions which reduces an array of numbers to a representative number of the set.\n     * Like an array of numbers `[10, 20, 5, 15]` can be reduced to `12.5` if average / mean reducer function is\n     * applied. All the measure fields in datamodel (variables in data) needs a reducer to handle aggregation.\n     *\n     * @public\n     *\n     * @return {ReducerStore} Singleton instance of {@link ReducerStore}.\n     */\n    static get Reducers () {\n        return reducerStore;\n    }\n\n    /**\n     * Configure null, undefined, invalid values in the source data\n     *\n     * @public\n     *\n     * @param {Object} [config] - Configuration to control how null, undefined and non-parsable values are\n     * represented in DataModel.\n     * @param {string} [config.undefined] - Define how an undefined value will be represented.\n     * @param {string} [config.null] - Define how a null value will be represented.\n     * @param {string} [config.invalid] - Define how a non-parsable value will be represented.\n     */\n    static configureInvalidAwareTypes (config) {\n        return InvalidAwareTypes.invalidAwareVals(config);\n    }\n\n    /**\n     * Retrieve the data attached to an instance in JSON format.\n     *\n     * @example\n     * // DataModel instance is already prepared and assigned to dm variable\n     *  const data = dm.getData({\n     *      order: 'column',\n     *      formatter: {\n     *          origin: (val) => val === 'European Union' ? 'EU' : val;\n     *      }\n     *  });\n     *  console.log(data);\n     *\n     * @public\n     *\n     * @param {Object} [options] Options to control how the raw data is to be returned.\n     * @param {string} [options.order='row'] Defines if data is retieved in row order or column order. Possible values\n     *      are `'rows'` and `'columns'`\n     * @param {Function} [options.formatter=null] Formats the output data. This expects an object, where the keys are\n     *      the name of the variable needs to be formatted. The formatter function is called for each row passing the\n     *      value of the cell for a particular row as arguments. The formatter is a function in the form of\n     *      `function (value, rowId, schema) => { ... }`\n     *      Know more about {@link Fomatter}.\n     *\n     * @return {Array} Returns a multidimensional array of the data with schema. The return format looks like\n     *      ```\n     *          {\n     *              data,\n     *              schema\n     *          }\n     *      ```\n     */\n    getData (options) {\n        const defOptions = {\n            order: 'row',\n            formatter: null,\n            withUid: false,\n            getAllFields: false,\n            sort: []\n        };\n        options = Object.assign({}, defOptions, options);\n        const fields = this.getPartialFieldspace().fields;\n\n        const dataGenerated = dataBuilder.call(\n            this,\n            this.getPartialFieldspace().fields,\n            this._rowDiffset,\n            options.getAllFields ? fields.map(d => d.name()).join() : this._colIdentifier,\n            options.sort,\n            {\n                columnWise: options.order === 'column',\n                addUid: !!options.withUid\n            }\n        );\n\n        if (!options.formatter) {\n            return dataGenerated;\n        }\n\n        const { formatter } = options;\n        const { data, schema, uids } = dataGenerated;\n        const fieldNames = schema.map((e => e.name));\n        const fmtFieldNames = Object.keys(formatter);\n        const fmtFieldIdx = fmtFieldNames.reduce((acc, next) => {\n            const idx = fieldNames.indexOf(next);\n            if (idx !== -1) {\n                acc.push([idx, formatter[next]]);\n            }\n            return acc;\n        }, []);\n\n        if (options.order === 'column') {\n            fmtFieldIdx.forEach((elem) => {\n                const fIdx = elem[0];\n                const fmtFn = elem[1];\n\n                data[fIdx].forEach((datum, datumIdx) => {\n                    data[fIdx][datumIdx] = fmtFn.call(\n                        undefined,\n                        datum,\n                        uids[datumIdx],\n                        schema[fIdx]\n                    );\n                });\n            });\n        } else {\n            data.forEach((datum, datumIdx) => {\n                fmtFieldIdx.forEach((elem) => {\n                    const fIdx = elem[0];\n                    const fmtFn = elem[1];\n\n                    datum[fIdx] = fmtFn.call(\n                        undefined,\n                        datum[fIdx],\n                        uids[datumIdx],\n                        schema[fIdx]\n                    );\n                });\n            });\n        }\n\n        return dataGenerated;\n    }\n\n    /**\n     * Returns the unique ids in an array.\n     *\n     * @return {Array} Returns an array of ids.\n     */\n    getUids () {\n        const rowDiffset = this._rowDiffset;\n        const ids = [];\n\n        if (rowDiffset.length) {\n            const diffSets = rowDiffset.split(',');\n\n            diffSets.forEach((set) => {\n                let [start, end] = set.split('-').map(Number);\n\n                end = end !== undefined ? end : start;\n                ids.push(...Array(end - start + 1).fill().map((_, idx) => start + idx));\n            });\n        }\n\n        return ids;\n    }\n    /**\n     * Groups the data using particular dimensions and by reducing measures. It expects a list of dimensions using which\n     * it projects the datamodel and perform aggregations to reduce the duplicate tuples. Refer this\n     * {@link link_to_one_example_with_group_by | document} to know the intuition behind groupBy.\n     *\n     * DataModel by default provides definition of few {@link reducer | Reducers}.\n     * {@link ReducerStore | User defined reducers} can also be registered.\n     *\n     * This is the chained implementation of `groupBy`.\n     * `groupBy` also supports {@link link_to_compose_groupBy | composability}\n     *\n     * @example\n     * const groupedDM = dm.groupBy(['Year'], { horsepower: 'max' } );\n     * console.log(groupedDm);\n     *\n     * @public\n     *\n     * @param {Array.<string>} fieldsArr - Array containing the name of dimensions\n     * @param {Object} [reducers={}] - A map whose key is the variable name and value is the name of the reducer. If its\n     *      not passed, or any variable is ommitted from the object, default aggregation function is used from the\n     *      schema of the variable.\n     *\n     * @return {DataModel} Returns a new DataModel instance after performing the groupby.\n     */\n    groupBy (fieldsArr, reducers = {}, config = { saveChild: true }) {\n        const groupByString = `${fieldsArr.join()}`;\n        let params = [this, fieldsArr, reducers];\n        const newDataModel = groupBy(...params);\n\n        persistDerivations(\n            this,\n            newDataModel,\n            DM_DERIVATIVES.GROUPBY,\n            { fieldsArr, groupByString, defaultReducer: reducerStore.defaultReducer() },\n            reducers\n        );\n\n        if (config.saveChild) {\n            newDataModel.setParent(this);\n        } else {\n            newDataModel.setParent(null);\n        }\n\n        return newDataModel;\n    }\n\n    /**\n     * Performs sorting operation on the current {@link DataModel} instance according to the specified sorting details.\n     * Like every other operator it doesn't mutate the current DataModel instance on which it was called, instead\n     * returns a new DataModel instance containing the sorted data.\n     *\n     * DataModel support multi level sorting by listing the variables using which sorting needs to be performed and\n     * the type of sorting `ASC` or `DESC`.\n     *\n     * In the following example, data is sorted by `Origin` field in `DESC` order in first level followed by another\n     * level of sorting by `Acceleration` in `ASC` order.\n     *\n     * @example\n     * // here dm is the pre-declared DataModel instance containing the data of 'cars.json' file\n     * let sortedDm = dm.sort([\n     *    [\"Origin\", \"DESC\"]\n     *    [\"Acceleration\"] // Default value is ASC\n     * ]);\n     *\n     * console.log(dm.getData());\n     * console.log(sortedDm.getData());\n     *\n     * // Sort with a custom sorting function\n     * sortedDm = dm.sort([\n     *    [\"Origin\", \"DESC\"]\n     *    [\"Acceleration\", (a, b) => a - b] // Custom sorting function\n     * ]);\n     *\n     * console.log(dm.getData());\n     * console.log(sortedDm.getData());\n     *\n     * @text\n     * DataModel also provides another sorting mechanism out of the box where sort is applied to a variable using\n     * another variable which determines the order.\n     * Like the above DataModel contains three fields `Origin`, `Name` and `Acceleration`. Now, the data in this\n     * model can be sorted by `Origin` field according to the average value of all `Acceleration` for a\n     * particular `Origin` value.\n     *\n     * @example\n     * // here dm is the pre-declared DataModel instance containing the data of 'cars.json' file\n     * const sortedDm = dm.sort([\n     *     ['Origin', ['Acceleration', (a, b) => avg(...a.Acceleration) - avg(...b.Acceleration)]]\n     * ]);\n     *\n     * console.log(dm.getData());\n     * console.log(sortedDm.getData());\n     *\n     * @public\n     *\n     * @param {Array.<Array>} sortingDetails - Sorting details based on which the sorting will be performed.\n     * @return {DataModel} Returns a new instance of DataModel with sorted data.\n     */\n    sort (sortingDetails, config = { saveChild: false }) {\n        const rawData = this.getData({\n            order: 'row',\n            sort: sortingDetails\n        });\n        const header = rawData.schema.map(field => field.name);\n        const dataInCSVArr = [header].concat(rawData.data);\n\n        const sortedDm = new this.constructor(dataInCSVArr, rawData.schema, { dataFormat: 'DSVArr' });\n\n        persistDerivations(\n            this,\n            sortedDm,\n            DM_DERIVATIVES.SORT,\n            config,\n            sortingDetails\n        );\n\n        if (config.saveChild) {\n            sortedDm.setParent(this);\n        } else {\n            sortedDm.setParent(null);\n        }\n\n        return sortedDm;\n    }\n\n    /**\n     * Performs the serialization operation on the current {@link DataModel} instance according to the specified data\n     * type. When an {@link DataModel} instance is created, it de-serializes the input data into its internal format,\n     * and during its serialization process, it converts its internal data format to the specified data type and returns\n     * that data regardless what type of data is used during the {@link DataModel} initialization.\n     *\n     * @example\n     * // here dm is the pre-declared DataModel instance.\n     * const csvData = dm.serialize(DataModel.DataFormat.DSV_STR, { fieldSeparator: \",\" });\n     * console.log(csvData); // The csv formatted data.\n     *\n     * const jsonData = dm.serialize(DataModel.DataFormat.FLAT_JSON);\n     * console.log(jsonData); // The json data.\n     *\n     * @public\n     *\n     * @param {string} type - The data type name for serialization.\n     * @param {Object} options - The optional option object.\n     * @param {string} options.fieldSeparator - The field separator character for DSV data type.\n     * @return {Array|string} Returns the serialized data.\n     */\n    serialize (type, options) {\n        type = type || this._dataFormat;\n        options = Object.assign({}, { fieldSeparator: ',' }, options);\n\n        const fields = this.getFieldspace().fields;\n        const colData = fields.map(f => f.formattedData());\n        const rowsCount = colData[0].length;\n        let serializedData;\n        let rowIdx;\n        let colIdx;\n\n        if (type === DataFormat.FLAT_JSON) {\n            serializedData = [];\n            for (rowIdx = 0; rowIdx < rowsCount; rowIdx++) {\n                const row = {};\n                for (colIdx = 0; colIdx < fields.length; colIdx++) {\n                    row[fields[colIdx].name()] = colData[colIdx][rowIdx];\n                }\n                serializedData.push(row);\n            }\n        } else if (type === DataFormat.DSV_STR) {\n            serializedData = [fields.map(f => f.name()).join(options.fieldSeparator)];\n            for (rowIdx = 0; rowIdx < rowsCount; rowIdx++) {\n                const row = [];\n                for (colIdx = 0; colIdx < fields.length; colIdx++) {\n                    row.push(colData[colIdx][rowIdx]);\n                }\n                serializedData.push(row.join(options.fieldSeparator));\n            }\n            serializedData = serializedData.join('\\n');\n        } else if (type === DataFormat.DSV_ARR) {\n            serializedData = [fields.map(f => f.name())];\n            for (rowIdx = 0; rowIdx < rowsCount; rowIdx++) {\n                const row = [];\n                for (colIdx = 0; colIdx < fields.length; colIdx++) {\n                    row.push(colData[colIdx][rowIdx]);\n                }\n                serializedData.push(row);\n            }\n        } else {\n            throw new Error(`Data type ${type} is not supported`);\n        }\n\n        return serializedData;\n    }\n\n    addField (field) {\n        const fieldName = field.name();\n        this._colIdentifier += `,${fieldName}`;\n        const partialFieldspace = this._partialFieldspace;\n        const cachedValueObjects = partialFieldspace._cachedValueObjects;\n        const formattedData = field.formattedData();\n        const rawData = field.partialField.data;\n\n        if (!partialFieldspace.fieldsObj()[field.name()]) {\n            partialFieldspace.fields.push(field);\n            cachedValueObjects.forEach((obj, i) => {\n                obj[field.name()] = new Value(formattedData[i], rawData[i], field);\n            });\n        } else {\n            const fieldIndex = partialFieldspace.fields.findIndex(fieldinst => fieldinst.name() === fieldName);\n            fieldIndex >= 0 && (partialFieldspace.fields[fieldIndex] = field);\n        }\n\n        // flush out cached namespace values on addition of new fields\n        partialFieldspace._cachedFieldsObj = null;\n        partialFieldspace._cachedDimension = null;\n        partialFieldspace._cachedMeasure = null;\n\n        this.__calculateFieldspace().calculateFieldsConfig();\n        return this;\n    }\n\n    /**\n    * Creates a new variable calculated from existing variables. This method expects the definition of the newly created\n    * variable and a function which resolves the value of the new variable from existing variables.\n    *\n    * Can create a new measure based on existing variables:\n    * @example\n    *  // DataModel already prepared and assigned to dm variable;\n    *  const newDm = dataModel.calculateVariable({\n    *      name: 'powerToWeight',\n    *      type: 'measure'\n    *  }, ['horsepower', 'weight_in_lbs', (hp, weight) => hp / weight ]);\n    *\n    *\n    * Can create a new dimension based on existing variables:\n    * @example\n    *  // DataModel already prepared and assigned to dm variable;\n    *  const child = dataModel.calculateVariable(\n    *     {\n    *       name: 'Efficiency',\n    *       type: 'dimension'\n    *     }, ['horsepower', (hp) => {\n    *      if (hp < 80) { return 'low'; },\n    *      else if (hp < 120) { return 'moderate'; }\n    *      else { return 'high' }\n    *  }]);\n    *\n    * @public\n    *\n    * @param {Object} schema - The schema of newly defined variable.\n    * @param {Array.<string|function>} dependency - An array containing the dependency variable names and a resolver\n    * function as the last element.\n    * @param {Object} config - An optional config object.\n    * @param {boolean} [config.saveChild] - Whether the newly created DataModel will be a child.\n    * @param {boolean} [config.replaceVar] - Whether the newly created variable will replace the existing variable.\n    * @return {DataModel} Returns an instance of DataModel with the new field.\n    */\n    calculateVariable (schema, dependency, config) {\n        schema = sanitizeUnitSchema(schema);\n        config = Object.assign({}, { saveChild: true, replaceVar: false }, config);\n\n        const fieldsConfig = this.getFieldsConfig();\n        const depVars = dependency.slice(0, dependency.length - 1);\n        const retrieveFn = dependency[dependency.length - 1];\n\n        if (fieldsConfig[schema.name] && !config.replaceVar) {\n            throw new Error(`${schema.name} field already exists in datamodel`);\n        }\n\n        const depFieldIndices = depVars.map((field) => {\n            const fieldSpec = fieldsConfig[field];\n            if (!fieldSpec) {\n                // @todo dont throw error here, use warning in production mode\n                throw new Error(`${field} is not a valid column name.`);\n            }\n            return fieldSpec.index;\n        });\n\n        const clone = this.clone(config.saveChild);\n\n        const fs = clone.getFieldspace().fields;\n        const suppliedFields = depFieldIndices.map(idx => fs[idx]);\n\n        let cachedStore = {};\n        let cloneProvider = () => this.detachedRoot();\n\n        const computedValues = [];\n        rowDiffsetIterator(clone._rowDiffset, (i) => {\n            const fieldsData = suppliedFields.map(field => field.partialField.data[i]);\n            computedValues[i] = retrieveFn(...fieldsData, i, cloneProvider, cachedStore);\n        });\n        const [field] = createFields([computedValues], [schema], [schema.name]);\n        clone.addField(field);\n\n        persistDerivations(\n            this,\n            clone,\n            DM_DERIVATIVES.CAL_VAR,\n            { config: schema, fields: depVars },\n            retrieveFn\n        );\n\n        return clone;\n    }\n\n    /**\n     * Propagates changes across all the connected DataModel instances.\n     *\n     * @param {Array} identifiers - A list of identifiers that were interacted with.\n     * @param {Object} payload - The interaction specific details.\n     *\n     * @return {DataModel} DataModel instance.\n     */\n    propagate (identifiers, config = {}, addToNameSpace, propConfig = {}) {\n        const isMutableAction = config.isMutableAction;\n        const propagationSourceId = config.sourceId;\n        const payload = config.payload;\n        const rootModel = getRootDataModel(this);\n        const propagationNameSpace = rootModel._propagationNameSpace;\n        const rootGroupByModel = getRootGroupByModel(this);\n        const rootModels = {\n            groupByModel: rootGroupByModel,\n            model: rootModel\n        };\n\n        addToNameSpace && addToPropNamespace(propagationNameSpace, config, this);\n        propagateToAllDataModels(identifiers, rootModels, { propagationNameSpace, sourceId: propagationSourceId },\n            Object.assign({\n                payload\n            }, config));\n\n        if (isMutableAction) {\n            propagateImmutableActions(propagationNameSpace, rootModels, {\n                config,\n                propConfig\n            }, this);\n        }\n\n        return this;\n    }\n\n    /**\n     * Associates a callback with an event name.\n     *\n     * @param {string} eventName - The name of the event.\n     * @param {Function} callback - The callback to invoke.\n     * @return {DataModel} Returns this current DataModel instance itself.\n     */\n    on (eventName, callback) {\n        switch (eventName) {\n        case PROPAGATION:\n            this._onPropagation.push(callback);\n            break;\n        }\n        return this;\n    }\n\n    /**\n     * Unsubscribes the callbacks for the provided event name.\n     *\n     * @param {string} eventName - The name of the event to unsubscribe.\n     * @return {DataModel} Returns the current DataModel instance itself.\n     */\n    unsubscribe (eventName) {\n        switch (eventName) {\n        case PROPAGATION:\n            this._onPropagation = [];\n            break;\n\n        }\n        return this;\n    }\n\n    /**\n     * This method is used to invoke the method associated with propagation.\n     *\n     * @param {Object} payload The interaction payload.\n     * @param {DataModel} identifiers The propagated DataModel.\n     * @memberof DataModel\n     */\n    handlePropagation (propModel, payload) {\n        let propListeners = this._onPropagation;\n        propListeners.forEach(fn => fn.call(this, propModel, payload));\n    }\n\n    /**\n     * Performs the binning operation on a measure field based on the binning configuration. Binning means discretizing\n     * values of a measure. Binning configuration contains an array; subsequent values from the array marks the boundary\n     * of buckets in [inclusive, exclusive) range format. This operation does not mutate the subject measure field,\n     * instead, it creates a new field (variable) of type dimension and subtype binned.\n     *\n     * Binning can be configured by\n     * - providing custom bin configuration with non-uniform buckets,\n     * - providing bins count,\n     * - providing each bin size,\n     *\n     * When custom `buckets` are provided as part of binning configuration:\n     * @example\n     *  // DataModel already prepared and assigned to dm variable\n     *  const config = { name: 'binnedHP', buckets: [30, 80, 100, 110] }\n     *  const binnedDM = dataModel.bin('horsepower', config);\n     *\n     * @text\n     * When `binsCount` is defined as part of binning configuration:\n     * @example\n     *  // DataModel already prepared and assigned to dm variable\n     *  const config = { name: 'binnedHP', binsCount: 5, start: 0, end: 100 }\n     *  const binDM = dataModel.bin('horsepower', config);\n     *\n     * @text\n     * When `binSize` is defined as part of binning configuration:\n     * @example\n     *  // DataModel already prepared and assigned to dm variable\n     *  const config = { name: 'binnedHorsepower', binSize: 20, start: 5}\n     *  const binDM = dataModel.bin('horsepower', config);\n     *\n     * @public\n     *\n     * @param {string} measureFieldName - The name of the target measure field.\n     * @param {Object} config - The config object.\n     * @param {string} [config.name] - The name of the new field which will be created.\n     * @param {string} [config.buckets] - An array containing the bucket ranges.\n     * @param {string} [config.binSize] - The size of each bin. It is ignored when buckets are given.\n     * @param {string} [config.binsCount] - The total number of bins to generate. It is ignored when buckets are given.\n     * @param {string} [config.start] - The start value of the bucket ranges. It is ignored when buckets are given.\n     * @param {string} [config.end] - The end value of the bucket ranges. It is ignored when buckets are given.\n     * @return {DataModel} Returns a new {@link DataModel} instance with the new field.\n     */\n    bin (measureFieldName, config) {\n        const fieldsConfig = this.getFieldsConfig();\n\n        if (!fieldsConfig[measureFieldName]) {\n            throw new Error(`Field ${measureFieldName} doesn't exist`);\n        }\n\n        const binFieldName = config.name || `${measureFieldName}_binned`;\n\n        if (fieldsConfig[binFieldName]) {\n            throw new Error(`Field ${binFieldName} already exists`);\n        }\n\n        const measureField = this.getFieldspace().fieldsObj()[measureFieldName];\n        const { binnedData, bins } = createBinnedFieldData(measureField, this._rowDiffset, config);\n\n        const binField = createFields([binnedData], [\n            {\n                name: binFieldName,\n                type: FieldType.DIMENSION,\n                subtype: DimensionSubtype.BINNED,\n                bins\n            }], [binFieldName])[0];\n\n        const clone = this.clone(config.saveChild);\n        clone.addField(binField);\n\n        persistDerivations(\n            this,\n            clone,\n            DM_DERIVATIVES.BIN,\n             { measureFieldName, config, binFieldName },\n             null\n        );\n\n        return clone;\n    }\n\n    /**\n     * Creates a new {@link DataModel} instance with completely detached root from current {@link DataModel} instance,\n     * the new {@link DataModel} instance has no parent-children relationship with the current one, but has same data as\n     * the current one.\n     * This API is useful when a completely different {@link DataModel} but with same data as the current instance is\n     * needed.\n     *\n     * @example\n     *  const dm = new DataModel(data, schema);\n     *  const detachedDm = dm.detachedRoot();\n     *\n     * // has different namespace\n     * console.log(dm.getPartialFieldspace().name);\n     * console.log(detachedDm.getPartialFieldspace().name);\n     *\n     * // has same data\n     * console.log(dm.getData());\n     * console.log(detachedDm.getData());\n     *\n     * @public\n     *\n     * @return {DataModel} Returns a detached {@link DataModel} instance.\n     */\n    detachedRoot () {\n        const data = this.serialize(DataFormat.FLAT_JSON);\n        const schema = this.getSchema();\n\n        return new DataModel(data, schema);\n    }\n\n    /**\n     * Creates a set of new {@link DataModel} instances by splitting the set of rows in the source {@link DataModel}\n     * instance based on a set of dimensions.\n     *\n     * For each unique dimensional value, a new split is created which creates a unique {@link DataModel} instance for\n     *  that split\n     *\n     * If multiple dimensions are provided, it splits the source {@link DataModel} instance with all possible\n     * combinations of the dimensional values for all the dimensions provided\n     *\n     * Additionally, it also accepts a predicate function to reduce the set of rows provided. A\n     * {@link link_to_selection | Selection} is performed on all the split {@link DataModel} instances based on\n     * the predicate function\n     *\n     * @example\n     *  // without predicate function:\n     *  const splitDt = dt.splitByRow(['Origin'])\n     *  console.log(splitDt));\n     * // This should give three unique DataModel instances, one each having rows only for 'USA',\n     * // 'Europe' and 'Japan' respectively\n     *\n     * @example\n     *  // without predicate function:\n     *  const splitDtMulti = dt.splitByRow(['Origin', 'Cylinders'])\n     *  console.log(splitDtMulti));\n     * // This should give DataModel instances for all unique combinations of Origin and Cylinder values\n     *\n     * @example\n     * // with predicate function:\n     * const splitWithPredDt = dt.select(['Origin'], fields => fields.Origin.value === \"USA\")\n     * console.log(splitWithPredDt);\n     * // This should not include the DataModel for the Origin : 'USA'\n     *\n     *\n     * @public\n     *\n     * @param {Array} dimensionArr - Set of dimensions based on which the split should occur\n     * @param {Object} config - The configuration object\n     * @param {string} [config.saveChild] - Configuration to save child or not\n     * @param {string}[config.mode=FilteringMode.NORMAL] -The mode of the selection.\n     * @return {Array}  Returns the new DataModel instances after operation.\n     */\n    splitByRow (dimensionArr, reducerFn, config) {\n        const fieldsConfig = this.getFieldsConfig();\n\n        dimensionArr.forEach((fieldName) => {\n            if (!fieldsConfig[fieldName]) {\n                throw new Error(`Field ${fieldName} doesn't exist in the schema`);\n            }\n        });\n\n        const defConfig = {\n            mode: FilteringMode.NORMAL,\n            saveChild: true\n        };\n\n        config = Object.assign({}, defConfig, config);\n\n        return splitWithSelect(this, dimensionArr, reducerFn, config);\n    }\n\n    /**\n     * Creates a set of new {@link DataModel} instances by splitting the set of fields in the source {@link DataModel}\n     * instance based on a set of common and unique field names provided.\n     *\n     * Each DataModel created contains a set of fields which are common to all and a set of unique fields.\n     * It also accepts configurations such as saveChild and mode(inverse or normal) to include/exclude the respective\n     * fields\n     *\n     * @example\n     *  // without predicate function:\n     *  const splitDt = dt.splitByColumn( [['Acceleration'], ['Horsepower']], ['Origin'])\n     *  console.log(splitDt));\n     * // This should give two unique DataModel instances, both having the field 'Origin' and\n     * // one each having 'Acceleration' and 'Horsepower' fields respectively\n     *\n     * @example\n     *  // without predicate function:\n     *  const splitDtInv = dt.splitByColumn( [['Acceleration'], ['Horsepower'],['Origin', 'Cylinders'],\n     *                           {mode: 'inverse'})\n     *  console.log(splitDtInv));\n     * // This should give DataModel instances in the following way:\n     * // All DataModel Instances do not have the fields 'Origin' and 'Cylinders'\n     * // One DataModel Instance has rest of the fields except 'Acceleration' and the other DataModel instance\n     * // has rest of the fields except 'Horsepower'\n     *\n     *\n     *\n     * @public\n     *\n     * @param {Array} uniqueFields - Set of unique fields included in each datamModel instance\n     * @param {Array} commonFields - Set of common fields included in all datamModel instances\n     * @param {Object} config - The configuration object\n     * @param {string} [config.saveChild] - Configuration to save child or not\n     * @param {string}[config.mode=FilteringMode.NORMAL] -The mode of the selection.\n     * @return {Array}  Returns the new DataModel instances after operation.\n     */\n    splitByColumn (uniqueFields = [], commonFields = [], config) {\n        const defConfig = {\n            mode: FilteringMode.NORMAL,\n            saveChild: true\n        };\n        const fieldConfig = this.getFieldsConfig();\n        const allFields = Object.keys(fieldConfig);\n        const normalizedProjFieldSets = [[commonFields]];\n\n        config = Object.assign({}, defConfig, config);\n        uniqueFields = uniqueFields.length ? uniqueFields : [[]];\n\n\n        uniqueFields.forEach((fieldSet, i) => {\n            normalizedProjFieldSets[i] = getNormalizedProFields(\n                [...fieldSet, ...commonFields],\n                allFields,\n                fieldConfig);\n        });\n\n        return splitWithProject(this, normalizedProjFieldSets, config, allFields);\n    }\n\n\n}\n\nexport default DataModel;\n","import { fnList } from '../operator/group-by-function';\n\nexport const { sum, avg, min, max, first, last, count, std: sd } = fnList;\n","import DataModel from './datamodel';\nimport {\n  compose,\n  bin,\n  select,\n  project,\n  groupby as groupBy,\n  calculateVariable,\n  sort,\n  crossProduct,\n  difference,\n  naturalJoin,\n  leftOuterJoin,\n  rightOuterJoin,\n  fullOuterJoin,\n  union\n} from './operator';\nimport * as Stats from './stats';\nimport * as enums from './enums';\nimport { DateTimeFormatter } from './utils';\nimport { DataFormat, FilteringMode, DM_DERIVATIVES } from './constants';\nimport InvalidAwareTypes from './invalid-aware-types';\nimport pkg from '../package.json';\n\nconst Operators = {\n    compose,\n    bin,\n    select,\n    project,\n    groupBy,\n    calculateVariable,\n    sort,\n    crossProduct,\n    difference,\n    naturalJoin,\n    leftOuterJoin,\n    rightOuterJoin,\n    fullOuterJoin,\n    union\n};\n\nconst version = pkg.version;\nObject.assign(DataModel, {\n    Operators,\n    Stats,\n    DM_DERIVATIVES,\n    DateTimeFormatter,\n    DataFormat,\n    FilteringMode,\n    InvalidAwareTypes,\n    version\n}, enums);\n\nexport default DataModel;\n","import { persistDerivations } from '../helper';\nimport { DM_DERIVATIVES } from '../constants';\n\n/**\n * DataModel's opearators are exposed as composable functional operators as well as chainable operators. Chainable\n * operators are called on the instances of {@link Datamodel} and {@link Relation} class.\n *\n * Those same operators can be used as composable operators from `DataModel.Operators` namespace.\n *\n * All these operators have similar behaviour. All these operators when called with the argument returns a function\n * which expects a DataModel instance.\n *\n * @public\n * @module Operators\n * @namespace DataModel\n */\n\n/**\n * This is functional version of selection operator. {@link link_to_selection | Selection} is a row filtering operation.\n * It takes {@link SelectionPredicate | predicate} for filtering criteria and returns a function.\n * The returned function is called with the DataModel instance on which the action needs to be performed.\n *\n * {@link SelectionPredicate} is a function which returns a boolean value. For selection opearation the selection\n * function is called for each row of DataModel instance with the current row passed as argument.\n *\n * After executing {@link SelectionPredicate} the rows are labeled as either an entry of selection set or an entry\n * of rejection set.\n *\n * {@link FilteringMode} operates on the selection and rejection set to determine which one would reflect in the\n * resulatant datamodel.\n *\n * @warning\n * [Warn] Selection and rejection set is only a logical idea for concept explanation purpose.\n *\n * @error\n * [Error] `FilteringMode.ALL` is not a valid working mode for functional version of `select`. Its only avialable on the\n * chained version.\n *\n * @example\n * const select = DataModel.Operators.select;\n * usaCarsFn = select(fields => fields.Origin.value === 'USA');\n * usaCarsDm = usaCarsFn(dm);\n * console.log(usaCarsDm);\n *\n * @public\n * @namespace DataModel\n * @module Operators\n *\n * @param {SelectionPredicate} selectFn - Predicate funciton which is called for each row with the current row\n *      ```\n *          function (row, i)  { ... }\n *      ```\n * @param {Object} [config] - The configuration object to control the inclusion exclusion of a row in resultant\n *      DataModel instance\n * @param {FilteringMode} [config.mode=FilteringMode.NORMAL] - The mode of the selection\n *\n * @return {PreparatorFunction} Function which expects an instance of DataModel on which the operator needs to be\n *      applied.\n */\nexport const select = (...args) => dm => dm.select(...args);\n\n/**\n * This is functional version of projection operator. {@link link_to_projection | Projection} is a column filtering\n * operation.It expects list of fields name and either include those or exclude those based on {@link FilteringMode} on\n * the  resultant variable.It returns a function which is called with the DataModel instance on which the action needs\n * to be performed.\n *\n * Projection expects array of fields name based on which it creates the selection and rejection set. All the field\n * whose name is present in array goes in selection set and rest of the fields goes in rejection set.\n *\n * {@link FilteringMode} operates on the selection and rejection set to determine which one would reflect in the\n * resulatant datamodel.\n *\n * @warning\n * Selection and rejection set is only a logical idea for concept explanation purpose.\n *\n * @error\n * `FilteringMode.ALL` is not a valid working mode for functional version of `select`. Its only avialable on the\n * chained version.\n *\n * @public\n * @namespace DataModel\n * @module Operators\n *\n * @param {Array.<string | Regexp>} projField - An array of column names in string or regular expression.\n * @param {Object} [config] - An optional config to control the creation of new DataModel\n * @param {FilteringMode} [config.mode=FilteringMode.NORMAL] - Mode of the projection\n *\n * @return {PreparatorFunction} Function which expects an instance of DataModel on which the operator needs to be\n *      applied.\n */\nexport const project = (...args) => dm => dm.project(...args);\n\n/**\n * This is functional version of binnig operator. Binning happens on a measure field based on a binning configuration.\n * Binning in DataModel does not aggregate the number of rows present in DataModel instance after binning, it just adds\n * a new field with the binned value. Refer binning {@link example_of_binning | example} to have a intuition of what\n * binning is and the use case.\n *\n * Binning can be configured by\n * - providing custom bin configuration with non uniform buckets\n * - providing bin count\n * - providing each bin size\n *\n * When custom buckets are provided as part of binning configuration\n * @example\n *  // DataModel already prepared and assigned to dm vairable\n *  const buckets = {\n *      start: 30\n *      stops: [80, 100, 110]\n *  };\n *  const config = { buckets, name: 'binnedHP' }\n *  const binFn = bin('horsepower', config);\n *  const binnedDm = binFn(dm);\n *\n * @text\n * When `binCount` is defined as part of binning configuration\n * @example\n *  // DataModel already prepared and assigned to dm vairable\n *  const config = { binCount: 5, name: 'binnedHP' }\n *  const binFn = bin('horsepower', config);\n *  const binnedDm = binFn(Dm);\n *\n * @text\n * When `binSize` is defined as part of binning configuration\n * @example\n *  // DataModel already prepared and assigned to dm vairable\n *  const config = { binSize: 200, name: 'binnedHorsepower' }\n *  const binnedDm = dataModel.bin('horsepower', config);\n *  const binnedDm = binFn(Dm);\n *\n * @public\n * @namespace DataModel\n * @module Operators\n *\n * @param {String} name Name of measure which will be used to create bin\n * @param {Object} config Config required for bin creation\n * @param {Array.<Number>} config.bucketObj.stops Defination of bucket ranges. Two subsequent number from arrays\n *      are picked and a range is created. The first number from range is inclusive and the second number from range\n *      is exclusive.\n * @param {Number} [config.bucketObj.startAt] Force the start of the bin from a particular number.\n *      If not mentioned, the start of the bin or the lower domain of the data if stops is not mentioned, else its\n *      the first value of the stop.\n * @param {Number} config.binSize Bucket size for each bin\n * @param {Number} config.binCount Number of bins which will be created\n * @param {String} config.name Name of the new binned field to be created\n *\n * @return {PreparatorFunction} Function which expects an instance of DataModel on which the operator needs to be\n *      applied.\n */\nexport const bin = (...args) => dm => dm.bin(...args);\n\n/**\n * This is functional version of `groupBy` operator.Groups the data using particular dimensions and by reducing\n * measures. It expects a list of dimensions using which it projects the datamodel and perform aggregations to reduce\n * the duplicate tuples. Refer this {@link link_to_one_example_with_group_by | document} to know the intuition behind\n * groupBy.\n *\n * DataModel by default provides definition of few {@link reducer | Reducers}.\n * {@link ReducerStore | User defined reducers} can also be registered.\n *\n * This is the chained implementation of `groupBy`.\n * `groupBy` also supports {@link link_to_compose_groupBy | composability}\n *\n * @example\n * const groupBy = DataModel.Operators.groupBy;\n * const groupedFn = groupBy(['Year'], { horsepower: 'max' } );\n * groupedDM = groupByFn(dm);\n *\n * @public\n *\n * @param {Array.<string>} fieldsArr - Array containing the name of dimensions\n * @param {Object} [reducers={}] - A map whose key is the variable name and value is the name of the reducer. If its\n *      not passed, or any variable is ommitted from the object, default aggregation function is used from the\n *      schema of the variable.\n *\n * @return {PreparatorFunction} Function which expects an instance of DataModel on which the operator needs to be\n *      applied.\n */\nexport const groupBy = (...args) => dm => dm.groupBy(...args);\n\n/**\n * Enables composing operators to run multiple operations and save group of operataion as named opration on a DataModel.\n * The resulting DataModel will be the result of all the operation provided. The operations provided will be executed in\n * a serial manner ie. result of one operation will be the input for the next operations (like pipe operator in unix).\n *\n * Suported operations in compose are\n * - `select`\n * - `project`\n * - `groupBy`\n * - `bin`\n * - `compose`\n *\n * @example\n * const compose = DataModel.Operators.compose;\n * const select = DataModel.Operators.select;\n * const project = DataModel.Operators.project;\n *\n * let composedFn = compose(\n *    select(fields => fields.netprofit.value <= 15),\n *    project(['netprofit', 'netsales']));\n *\n * const dataModel = new DataModel(data1, schema1);\n *\n * let composedDm = composedFn(dataModel);\n *\n * @public\n * @namespace DataModel\n * @module Operators\n *\n * @param {Array.<Operators>} operators: An array of operation that will be applied on the\n * datatable.\n *\n * @returns {DataModel} Instance of resultant DataModel\n */\nexport const compose = (...operations) =>\n    (dm, config = { saveChild: true }) => {\n        let currentDM = dm;\n        let firstChild;\n        const derivations = [];\n\n        operations.forEach((operation) => {\n            currentDM = operation(currentDM);\n            derivations.push(...currentDM._derivation);\n            if (!firstChild) {\n                firstChild = currentDM;\n            }\n        });\n\n        if (firstChild && firstChild !== currentDM) {\n            firstChild.dispose();\n        }\n\n        // reset all ancestorDerivation saved in-between compose\n        currentDM._ancestorDerivation = [];\n        persistDerivations(\n            dm,\n            currentDM,\n            DM_DERIVATIVES.COMPOSE,\n            null,\n            derivations\n        );\n\n        if (config.saveChild) {\n            currentDM.setParent(dm);\n        } else {\n            currentDM.setParent(null);\n        }\n\n        return currentDM;\n    };\n","/**\n * Wrapper on calculateVariable() method of DataModel to behave\n * the pure-function functionality.\n *\n * @param {Array} args - The argument list.\n * @return {any} Returns the returned value of calling function.\n */\nexport const calculateVariable = (...args) => dm => dm.calculateVariable(...args);\n\n/**\n * Wrapper on sort() method of DataModel to behave\n * the pure-function functionality.\n *\n * @param {Array} args - The argument list.\n * @return {any} Returns the returned value of calling function.\n */\nexport const sort = (...args) => dm => dm.sort(...args);\n","import { crossProduct } from './cross-product';\nimport { naturalJoinFilter } from './natural-join-filter-function';\n\nexport function naturalJoin (dataModel1, dataModel2) {\n    return crossProduct(dataModel1, dataModel2, naturalJoinFilter(dataModel1, dataModel2), true);\n}\n"],"sourceRoot":""}
\ No newline at end of file
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'a', getter);\n \t\treturn getter;\n \t};\n\n \t// Object.prototype.hasOwnProperty.call\n \t__webpack_require__.o = function(object, property) { return Object.prototype.hasOwnProperty.call(object, property); };\n\n \t// __webpack_public_path__\n \t__webpack_require__.p = \"\";\n\n\n \t// Load entry module and return exports\n \treturn __webpack_require__(__webpack_require__.s = 1);\n","const DataModel = require('./export');\n\nmodule.exports = DataModel.default ? DataModel.default : DataModel;\n","/**\n * DataFormat Enum defines the format of the input data.\n * Based on the format of the data the respective adapter is loaded.\n *\n * @readonly\n * @enum {string}\n */\nconst DataFormat = {\n    FLAT_JSON: 'FlatJSON',\n    DSV_STR: 'DSVStr',\n    DSV_ARR: 'DSVArr',\n    AUTO: 'Auto'\n};\n\nexport default DataFormat;\n","/**\n * DimensionSubtype enum defines the sub types of the Dimensional Field.\n *\n * @readonly\n * @enum {string}\n */\nconst DimensionSubtype = {\n    CATEGORICAL: 'categorical',\n    TEMPORAL: 'temporal',\n    BINNED: 'binned'\n};\n\nexport default DimensionSubtype;\n","/**\n * MeasureSubtype enum defines the sub types of the Measure Field.\n *\n * @readonly\n * @enum {string}\n */\nconst MeasureSubtype = {\n    CONTINUOUS: 'continuous'\n};\n\nexport default MeasureSubtype;\n","/**\n * FieldType enum defines the high level field based on which visuals are controlled.\n * Measure in a high level is numeric field and Dimension in a high level is string field.\n *\n * @readonly\n * @enum {string}\n */\nconst FieldType = {\n    MEASURE: 'measure',\n    DIMENSION: 'dimension'\n};\n\nexport default FieldType;\n","/**\n * Filtering mode enum defines the filering modes of DataModel.\n *\n * @readonly\n * @enum {string}\n */\nconst FilteringMode = {\n    NORMAL: 'normal',\n    INVERSE: 'inverse',\n    ALL: 'all'\n};\n\nexport default FilteringMode;\n","/**\n * Group by function names\n *\n * @readonly\n * @enum {string}\n */\nconst GROUP_BY_FUNCTIONS = {\n    SUM: 'sum',\n    AVG: 'avg',\n    MIN: 'min',\n    MAX: 'max',\n    FIRST: 'first',\n    LAST: 'last',\n    COUNT: 'count',\n    STD: 'std'\n};\n\nexport default GROUP_BY_FUNCTIONS;\n","/**\n * Creates a JS native date object from input\n *\n * @param {string | number | Date} date Input using which date object to be created\n * @return {Date} : JS native date object\n */\nfunction convertToNativeDate (date) {\n    if (date instanceof Date) {\n        return date;\n    }\n\n    return new Date(date);\n}\n/**\n * Apply padding before a number if its less than 1o. This is used when constant digit's number to be returned\n * between 0 - 99\n *\n * @param {number} n Input to be padded\n * @return {string} Padded number\n */\nfunction pad (n) {\n    return (n < 10) ? (`0${n}`) : n;\n}\n/*\n * DateFormatter utility to convert any date format to any other date format\n * DateFormatter parse a date time stamp specified by a user abiding by rules which are defined\n * by user in terms of token. It creates JS native date object from the user specified format.\n * That native date can also be displayed\n * in any specified format.\n * This utility class only takes care of format conversion only\n */\n\n/*\n * Escapes all the special character that are used in regular expression.\n * Like\n * RegExp.escape('sgfd-$') // Output: sgfd\\-\\$\n *\n * @param text {String} : text which is to be escaped\n */\nRegExp.escape = function (text) {\n    return text.replace(/[-[\\]{}()*+?.,\\\\^$|#\\s]/g, '\\\\$&');\n};\n\n/**\n * DateTimeFormatter class to convert any user format of date time stamp to any other format\n * of date time stamp.\n *\n * @param {string} format Format of the date given. For the above date,\n * 'year: %Y, month: %b, day: %d'.\n * @class\n */\n/* istanbul ignore next */ function DateTimeFormatter (format) {\n    this.format = format;\n    this.dtParams = undefined;\n    this.nativeDate = undefined;\n}\n\n// The identifier of the tokens\nDateTimeFormatter.TOKEN_PREFIX = '%';\n\n// JS native Date constructor takes the date params (year, month, etc) in a certail sequence.\n// This defines the sequence of the date parameters in the constructor.\nDateTimeFormatter.DATETIME_PARAM_SEQUENCE = {\n    YEAR: 0,\n    MONTH: 1,\n    DAY: 2,\n    HOUR: 3,\n    MINUTE: 4,\n    SECOND: 5,\n    MILLISECOND: 6\n};\n\n/*\n * This is a default number parsing utility. It tries to parse a number in integer, if parsing is unsuccessful, it\n * gives back a default value.\n *\n * @param: defVal {Number} : Default no if the parsing to integer is not successful\n * @return {Function} : An closure function which is to be called by passing an the value which needs to be parsed.\n */\nDateTimeFormatter.defaultNumberParser = function (defVal) {\n    return function (val) {\n        let parsedVal;\n        if (isFinite(parsedVal = parseInt(val, 10))) {\n            return parsedVal;\n        }\n\n        return defVal;\n    };\n};\n\n/*\n * This is a default number range utility. It tries to find an element in the range. If not found it returns a\n * default no as an index.\n *\n * @param: range {Array} : The list which is to be serached\n * @param: defVal {Number} : Default no if the serach and find does not return anything\n * @return {Function} : An closure function which is to be called by passing an the value which needs to be found\n */\nDateTimeFormatter.defaultRangeParser = function (range, defVal) {\n    return (val) => {\n        let i;\n        let l;\n\n        if (!val) { return defVal; }\n\n        const nVal = val.toLowerCase();\n\n        for (i = 0, l = range.length; i < l; i++) {\n            if (range[i].toLowerCase() === nVal) {\n                return i;\n            }\n        }\n\n        if (i === undefined) {\n            return defVal;\n        }\n        return null;\n    };\n};\n\n/*\n * Defines the tokens which are supporter by the dateformatter. Using this definitation a value gets extracted from\n * the user specifed date string. This also formats the value for display purpose from native JS date.\n * The definition of each token contains the following named properties\n * {\n *     %token_name% : {\n *         name: name of the token, this is used in reverse lookup,\n *         extract: a function that returns the regular expression to extract that piece of information. All the\n *                  regex should be gouped by using ()\n *         parser: a function which receives value extracted by the above regex and parse it to get the date params\n *         formatter: a formatter function that takes milliseconds or JS Date object and format the param\n *                  represented by the token only.\n *     }\n * }\n *\n * @return {Object} : Definition of the all the supported tokens.\n */\nDateTimeFormatter.getTokenDefinitions = function () {\n    const daysDef = {\n        short: [\n            'Sun',\n            'Mon',\n            'Tue',\n            'Wed',\n            'Thu',\n            'Fri',\n            'Sat'\n        ],\n        long: [\n            'Sunday',\n            'Monday',\n            'Tuesday',\n            'Wednesday',\n            'Thursday',\n            'Friday',\n            'Saturday'\n        ]\n    };\n    const monthsDef = {\n        short: [\n            'Jan',\n            'Feb',\n            'Mar',\n            'Apr',\n            'May',\n            'Jun',\n            'Jul',\n            'Aug',\n            'Sep',\n            'Oct',\n            'Nov',\n            'Dec'\n        ],\n        long: [\n            'January',\n            'February',\n            'March',\n            'April',\n            'May',\n            'June',\n            'July',\n            'August',\n            'September',\n            'October',\n            'November',\n            'December'\n        ]\n    };\n\n    const definitions = {\n        H: {\n            // 24 hours format\n            name: 'H',\n            index: 3,\n            extract () { return '(\\\\d+)'; },\n            parser: DateTimeFormatter.defaultNumberParser(),\n            formatter (val) {\n                const d = convertToNativeDate(val);\n\n                return d.getHours().toString();\n            }\n        },\n        l: {\n            // 12 hours format\n            name: 'l',\n            index: 3,\n            extract () { return '(\\\\d+)'; },\n            parser: DateTimeFormatter.defaultNumberParser(),\n            formatter (val) {\n                const d = convertToNativeDate(val);\n                const hours = d.getHours() % 12;\n\n                return (hours === 0 ? 12 : hours).toString();\n            }\n        },\n        p: {\n            // AM or PM\n            name: 'p',\n            index: 3,\n            extract () { return '(AM|PM)'; },\n            parser: (val) => {\n                if (val) {\n                    return val.toLowerCase();\n                }\n                return null;\n            },\n            formatter: (val) => {\n                const d = convertToNativeDate(val);\n                const hours = d.getHours();\n\n                return (hours < 12 ? 'AM' : 'PM');\n            }\n        },\n        P: {\n            // am or pm\n            name: 'P',\n            index: 3,\n            extract () { return '(am|pm)'; },\n            parser: (val) => {\n                if (val) {\n                    return val.toLowerCase();\n                }\n                return null;\n            },\n            formatter: (val) => {\n                const d = convertToNativeDate(val);\n                const hours = d.getHours();\n\n                return (hours < 12 ? 'am' : 'pm');\n            }\n        },\n        M: {\n            // Two digit minutes 00 - 59\n            name: 'M',\n            index: 4,\n            extract () { return '(\\\\d+)'; },\n            parser: DateTimeFormatter.defaultNumberParser(),\n            formatter (val) {\n                const d = convertToNativeDate(val);\n                const mins = d.getMinutes();\n\n                return pad(mins);\n            }\n        },\n        S: {\n            // Two digit seconds 00 - 59\n            name: 'S',\n            index: 5,\n            extract () { return '(\\\\d+)'; },\n            parser: DateTimeFormatter.defaultNumberParser(),\n            formatter (val) {\n                const d = convertToNativeDate(val);\n                const seconds = d.getSeconds();\n\n                return pad(seconds);\n            }\n        },\n        K: {\n            // Milliseconds\n            name: 'K',\n            index: 6,\n            extract () { return '(\\\\d+)'; },\n            parser: DateTimeFormatter.defaultNumberParser(),\n            formatter (val) {\n                const d = convertToNativeDate(val);\n                const ms = d.getMilliseconds();\n\n                return ms.toString();\n            }\n        },\n        a: {\n            // Short name of day, like Mon\n            name: 'a',\n            index: 2,\n            extract () { return `(${daysDef.short.join('|')})`; },\n            parser: DateTimeFormatter.defaultRangeParser(daysDef.short),\n            formatter (val) {\n                const d = convertToNativeDate(val);\n                const day = d.getDay();\n\n                return (daysDef.short[day]).toString();\n            }\n        },\n        A: {\n            // Long name of day, like Monday\n            name: 'A',\n            index: 2,\n            extract () { return `(${daysDef.long.join('|')})`; },\n            parser: DateTimeFormatter.defaultRangeParser(daysDef.long),\n            formatter (val) {\n                const d = convertToNativeDate(val);\n                const day = d.getDay();\n\n                return (daysDef.long[day]).toString();\n            }\n        },\n        e: {\n            // 8 of March, 11 of November\n            name: 'e',\n            index: 2,\n            extract () { return '(\\\\d+)'; },\n            parser: DateTimeFormatter.defaultNumberParser(),\n            formatter (val) {\n                const d = convertToNativeDate(val);\n                const day = d.getDate();\n\n                return day.toString();\n            }\n        },\n        d: {\n            // 08 of March, 11 of November\n            name: 'd',\n            index: 2,\n            extract () { return '(\\\\d+)'; },\n            parser: DateTimeFormatter.defaultNumberParser(),\n            formatter (val) {\n                const d = convertToNativeDate(val);\n                const day = d.getDate();\n\n                return pad(day);\n            }\n        },\n        b: {\n            // Short month, like Jan\n            name: 'b',\n            index: 1,\n            extract () { return `(${monthsDef.short.join('|')})`; },\n            parser: DateTimeFormatter.defaultRangeParser(monthsDef.short),\n            formatter (val) {\n                const d = convertToNativeDate(val);\n                const month = d.getMonth();\n\n                return (monthsDef.short[month]).toString();\n            }\n        },\n        B: {\n            // Long month, like January\n            name: 'B',\n            index: 1,\n            extract () { return `(${monthsDef.long.join('|')})`; },\n            parser: DateTimeFormatter.defaultRangeParser(monthsDef.long),\n            formatter (val) {\n                const d = convertToNativeDate(val);\n                const month = d.getMonth();\n\n                return (monthsDef.long[month]).toString();\n            }\n        },\n        m: {\n            // Two digit month of year like 01 for January\n            name: 'm',\n            index: 1,\n            extract () { return '(\\\\d+)'; },\n            parser (val) { return DateTimeFormatter.defaultNumberParser()(val) - 1; },\n            formatter (val) {\n                const d = convertToNativeDate(val);\n                const month = d.getMonth();\n\n                return pad(month + 1);\n            }\n        },\n        y: {\n            // Short year like 90 for 1990\n            name: 'y',\n            index: 0,\n            extract () { return '(\\\\d{2})'; },\n            parser (val) {\n                let result;\n                if (val) {\n                    const l = val.length;\n                    val = val.substring(l - 2, l);\n                }\n                let parsedVal = DateTimeFormatter.defaultNumberParser()(val);\n                let presentDate = new Date();\n                let presentYear = Math.trunc((presentDate.getFullYear()) / 100);\n\n                result = `${presentYear}${parsedVal}`;\n\n                if (convertToNativeDate(result).getFullYear() > presentDate.getFullYear()) {\n                    result = `${presentYear - 1}${parsedVal}`;\n                }\n                return convertToNativeDate(result).getFullYear();\n            },\n            formatter (val) {\n                const d = convertToNativeDate(val);\n                let year = d.getFullYear().toString();\n                let l;\n\n                if (year) {\n                    l = year.length;\n                    year = year.substring(l - 2, l);\n                }\n\n                return year;\n            }\n        },\n        Y: {\n            // Long year like 1990\n            name: 'Y',\n            index: 0,\n            extract () { return '(\\\\d{4})'; },\n            parser: DateTimeFormatter.defaultNumberParser(),\n            formatter (val) {\n                const d = convertToNativeDate(val);\n                const year = d.getFullYear().toString();\n\n                return year;\n            }\n        }\n    };\n\n    return definitions;\n};\n\n/*\n * The tokens which works internally is not user friendly in terms of memorizing the names. This gives a formal\n * definition to the informal notations.\n *\n * @return {Object} : Formal definition of the tokens\n */\nDateTimeFormatter.getTokenFormalNames = function () {\n    const definitions = DateTimeFormatter.getTokenDefinitions();\n\n    return {\n        HOUR: definitions.H,\n        HOUR_12: definitions.l,\n        AMPM_UPPERCASE: definitions.p,\n        AMPM_LOWERCASE: definitions.P,\n        MINUTE: definitions.M,\n        SECOND: definitions.S,\n        SHORT_DAY: definitions.a,\n        LONG_DAY: definitions.A,\n        DAY_OF_MONTH: definitions.e,\n        DAY_OF_MONTH_CONSTANT_WIDTH: definitions.d,\n        SHORT_MONTH: definitions.b,\n        LONG_MONTH: definitions.B,\n        MONTH_OF_YEAR: definitions.m,\n        SHORT_YEAR: definitions.y,\n        LONG_YEAR: definitions.Y\n    };\n};\n\n/*\n * This defines the rules and declares dependencies that resolves a date parameter (year, month etc) from\n * the date time parameter array.\n *\n * @return {Object} : An object that contains dependencies and a resolver function. The dependencies values are fed\n *                  to the resolver function in that particular sequence only.\n */\nDateTimeFormatter.tokenResolver = function () {\n    const definitions = DateTimeFormatter.getTokenDefinitions();\n    const defaultResolver = (...args) => { // eslint-disable-line require-jsdoc\n        let i = 0;\n        let arg;\n        let targetParam;\n        const l = args.length;\n\n        for (; i < l; i++) {\n            arg = args[i];\n            if (args[i]) {\n                targetParam = arg;\n            }\n        }\n\n        if (!targetParam) { return null; }\n\n        return targetParam[0].parser(targetParam[1]);\n    };\n\n    return {\n        YEAR: [definitions.y, definitions.Y,\n            defaultResolver\n        ],\n        MONTH: [definitions.b, definitions.B, definitions.m,\n            defaultResolver\n        ],\n        DAY: [definitions.a, definitions.A, definitions.e, definitions.d,\n            defaultResolver\n        ],\n        HOUR: [definitions.H, definitions.l, definitions.p, definitions.P,\n            function (hourFormat24, hourFormat12, ampmLower, ampmUpper) {\n                let targetParam;\n                let amOrpm;\n                let isPM;\n                let val;\n\n                if (hourFormat12 && (amOrpm = (ampmLower || ampmUpper))) {\n                    if (amOrpm[0].parser(amOrpm[1]) === 'pm') {\n                        isPM = true;\n                    }\n\n                    targetParam = hourFormat12;\n                } else if (hourFormat12) {\n                    targetParam = hourFormat12;\n                } else {\n                    targetParam = hourFormat24;\n                }\n\n                if (!targetParam) { return null; }\n\n                val = targetParam[0].parser(targetParam[1]);\n                if (isPM) {\n                    val += 12;\n                }\n                return val;\n            }\n        ],\n        MINUTE: [definitions.M,\n            defaultResolver\n        ],\n        SECOND: [definitions.S,\n            defaultResolver\n        ]\n    };\n};\n\n/*\n * Finds token from the format rule specified by a user.\n * @param format {String} : The format of the input date specified by the user\n * @return {Array} : An array of objects which contains the available token and their occurence index in the format\n */\nDateTimeFormatter.findTokens = function (format) {\n    const tokenPrefix = DateTimeFormatter.TOKEN_PREFIX;\n    const definitions = DateTimeFormatter.getTokenDefinitions();\n    const tokenLiterals = Object.keys(definitions);\n    const occurrence = [];\n    let i;\n    let forwardChar;\n\n    while ((i = format.indexOf(tokenPrefix, i + 1)) >= 0) {\n        forwardChar = format[i + 1];\n        if (tokenLiterals.indexOf(forwardChar) === -1) { continue; }\n\n        occurrence.push({\n            index: i,\n            token: forwardChar\n        });\n    }\n\n    return occurrence;\n};\n\n/*\n * Format any JS date to a specified date given by user.\n *\n * @param date {Number | Date} : The date object which is to be formatted\n * @param format {String} : The format using which the date will be formatted for display\n */\nDateTimeFormatter.formatAs = function (date, format) {\n    const nDate = convertToNativeDate(date);\n    const occurrence = DateTimeFormatter.findTokens(format);\n    const definitions = DateTimeFormatter.getTokenDefinitions();\n    let formattedStr = String(format);\n    const tokenPrefix = DateTimeFormatter.TOKEN_PREFIX;\n    let token;\n    let formattedVal;\n    let i;\n    let l;\n\n    for (i = 0, l = occurrence.length; i < l; i++) {\n        token = occurrence[i].token;\n        formattedVal = definitions[token].formatter(nDate);\n        formattedStr = formattedStr.replace(new RegExp(tokenPrefix + token, 'g'), formattedVal);\n    }\n\n    return formattedStr;\n};\n\n/*\n * Parses the user specified date string to extract the date time params.\n *\n * @return {Array} : Value of date time params in an array [year, month, day, hour, minutes, seconds, milli]\n */\nDateTimeFormatter.prototype.parse = function (dateTimeStamp, options) {\n    const tokenResolver = DateTimeFormatter.tokenResolver();\n    const dtParams = this.extractTokenValue(dateTimeStamp);\n    const dtParamSeq = DateTimeFormatter.DATETIME_PARAM_SEQUENCE;\n    const noBreak = options && options.noBreak;\n    const dtParamArr = [];\n    const args = [];\n    let resolverKey;\n    let resolverParams;\n    let resolverFn;\n    let val;\n    let i;\n    let param;\n    let resolvedVal;\n    let l;\n    let result = [];\n\n    for (resolverKey in tokenResolver) {\n        if (!{}.hasOwnProperty.call(tokenResolver, resolverKey)) { continue; }\n\n        args.length = 0;\n        resolverParams = tokenResolver[resolverKey];\n        resolverFn = resolverParams.splice(resolverParams.length - 1, 1)[0];\n\n        for (i = 0, l = resolverParams.length; i < l; i++) {\n            param = resolverParams[i];\n            val = dtParams[param.name];\n\n            if (val === undefined) {\n                args.push(null);\n            } else {\n                args.push([param, val]);\n            }\n        }\n\n        resolvedVal = resolverFn.apply(this, args);\n\n        if ((resolvedVal === undefined || resolvedVal === null) && !noBreak) {\n            break;\n        }\n\n        dtParamArr[dtParamSeq[resolverKey]] = resolvedVal;\n    }\n\n    if (dtParamArr.length && this.checkIfOnlyYear(dtParamArr.length))\n     {\n        result.unshift(dtParamArr[0], 0, 1); }\n    else {\n        result.unshift(...dtParamArr);\n    }\n\n    return result;\n};\n\n/*\n * Extract the value of the token from user specified date time string.\n *\n * @return {Object} : An key value pair which contains the tokens as key and value as pair\n */\nDateTimeFormatter.prototype.extractTokenValue = function (dateTimeStamp) {\n    const format = this.format;\n    const definitions = DateTimeFormatter.getTokenDefinitions();\n    const tokenPrefix = DateTimeFormatter.TOKEN_PREFIX;\n    const occurrence = DateTimeFormatter.findTokens(format);\n    const tokenObj = {};\n\n    let lastOccurrenceIndex;\n    let occObj;\n    let occIndex;\n    let targetText;\n    let regexFormat;\n\n    let l;\n    let i;\n\n    regexFormat = String(format);\n\n    const tokenArr = occurrence.map(obj => obj.token);\n    const occurrenceLength = occurrence.length;\n    for (i = occurrenceLength - 1; i >= 0; i--) {\n        occIndex = occurrence[i].index;\n\n        if (occIndex + 1 === regexFormat.length - 1) {\n            lastOccurrenceIndex = occIndex;\n            continue;\n        }\n\n        if (lastOccurrenceIndex === undefined) {\n            lastOccurrenceIndex = regexFormat.length;\n        }\n\n        targetText = regexFormat.substring(occIndex + 2, lastOccurrenceIndex);\n        regexFormat = regexFormat.substring(0, occIndex + 2) +\n            RegExp.escape(targetText) +\n            regexFormat.substring(lastOccurrenceIndex, regexFormat.length);\n\n        lastOccurrenceIndex = occIndex;\n    }\n\n    for (i = 0; i < occurrenceLength; i++) {\n        occObj = occurrence[i];\n        regexFormat = regexFormat.replace(tokenPrefix + occObj.token, definitions[occObj.token].extract());\n    }\n\n    const extractValues = dateTimeStamp.match(new RegExp(regexFormat)) || [];\n    extractValues.shift();\n\n    for (i = 0, l = tokenArr.length; i < l; i++) {\n        tokenObj[tokenArr[i]] = extractValues[i];\n    }\n    return tokenObj;\n};\n\n/*\n * Give back the JS native date formed from  user specified date string\n *\n * @return {Date} : Native JS Date\n */\nDateTimeFormatter.prototype.getNativeDate = function (dateTimeStamp) {\n    let date = null;\n    if (Number.isFinite(dateTimeStamp)) {\n        date = new Date(dateTimeStamp);\n    } else if (!this.format && Date.parse(dateTimeStamp)) {\n        date = new Date(dateTimeStamp);\n    }\n    else {\n        const dtParams = this.dtParams = this.parse(dateTimeStamp);\n        if (dtParams.length) {\n            this.nativeDate = new Date(...dtParams);\n            date = this.nativeDate;\n        }\n    }\n    return date;\n};\n\nDateTimeFormatter.prototype.checkIfOnlyYear = function(len) {\n    return len === 1 && this.format.match(/y|Y/g).length;\n};\n\n/*\n * Represents JS native date to a user specified format.\n *\n * @param format {String} : The format according to which the date is to be represented\n * @return {String} : The formatted date string\n */\nDateTimeFormatter.prototype.formatAs = function (format, dateTimeStamp) {\n    let nativeDate;\n\n    if (dateTimeStamp) {\n        nativeDate = this.nativeDate = this.getNativeDate(dateTimeStamp);\n    } else if (!(nativeDate = this.nativeDate)) {\n        nativeDate = this.getNativeDate(dateTimeStamp);\n    }\n\n    return DateTimeFormatter.formatAs(nativeDate, format);\n};\n\nexport { DateTimeFormatter as default };\n","/**\n * The utility function to calculate major column.\n *\n * @param {Object} store - The store object.\n * @return {Function} Returns the push function.\n */\nexport default (store) => {\n    let i = 0;\n    return (...fields) => {\n        fields.forEach((val, fieldIndex) => {\n            if (!(store[fieldIndex] instanceof Array)) {\n                store[fieldIndex] = Array.from({ length: i });\n            }\n            store[fieldIndex].push(val);\n        });\n        i++;\n    };\n};\n","/* eslint-disable */\nconst OBJECTSTRING = 'object';\nconst objectToStrFn = Object.prototype.toString;\nconst objectToStr = '[object Object]';\nconst arrayToStr = '[object Array]';\n\nfunction checkCyclicRef(obj, parentArr) {\n    let i = parentArr.length;\n    let bIndex = -1;\n\n    while (i) {\n        if (obj === parentArr[i]) {\n            bIndex = i;\n            return bIndex;\n        }\n        i -= 1;\n    }\n\n    return bIndex;\n}\n\nfunction merge(obj1, obj2, skipUndef, tgtArr, srcArr) {\n    var item,\n        srcVal,\n        tgtVal,\n        str,\n        cRef;\n    // check whether obj2 is an array\n    // if array then iterate through it's index\n    // **** MOOTOOLS precution\n\n    if (!srcArr) {\n        tgtArr = [obj1];\n        srcArr = [obj2];\n    }\n    else {\n        tgtArr.push(obj1);\n        srcArr.push(obj2);\n    }\n\n    if (obj2 instanceof Array) {\n        for (item = 0; item < obj2.length; item += 1) {\n            try {\n                srcVal = obj1[item];\n                tgtVal = obj2[item];\n            }\n            catch (e) {\n                continue;\n            }\n\n            if (typeof tgtVal !== OBJECTSTRING) {\n                if (!(skipUndef && tgtVal === undefined)) {\n                    obj1[item] = tgtVal;\n                }\n            }\n            else {\n                if (srcVal === null || typeof srcVal !== OBJECTSTRING) {\n                    srcVal = obj1[item] = tgtVal instanceof Array ? [] : {};\n                }\n                cRef = checkCyclicRef(tgtVal, srcArr);\n                if (cRef !== -1) {\n                    srcVal = obj1[item] = tgtArr[cRef];\n                }\n                else {\n                    merge(srcVal, tgtVal, skipUndef, tgtArr, srcArr);\n                }\n            }\n        }\n    }\n    else {\n        for (item in obj2) {\n            try {\n                srcVal = obj1[item];\n                tgtVal = obj2[item];\n            }\n            catch (e) {\n                continue;\n            }\n\n            if (tgtVal !== null && typeof tgtVal === OBJECTSTRING) {\n                // Fix for issue BUG: FWXT-602\n                // IE < 9 Object.prototype.toString.call(null) gives\n                // '[object Object]' instead of '[object Null]'\n                // that's why null value becomes Object in IE < 9\n                str = objectToStrFn.call(tgtVal);\n                if (str === objectToStr) {\n                    if (srcVal === null || typeof srcVal !== OBJECTSTRING) {\n                        srcVal = obj1[item] = {};\n                    }\n                    cRef = checkCyclicRef(tgtVal, srcArr);\n                    if (cRef !== -1) {\n                        srcVal = obj1[item] = tgtArr[cRef];\n                    }\n                    else {\n                        merge(srcVal, tgtVal, skipUndef, tgtArr, srcArr);\n                    }\n                }\n                else if (str === arrayToStr) {\n                    if (srcVal === null || !(srcVal instanceof Array)) {\n                        srcVal = obj1[item] = [];\n                    }\n                    cRef = checkCyclicRef(tgtVal, srcArr);\n                    if (cRef !== -1) {\n                        srcVal = obj1[item] = tgtArr[cRef];\n                    }\n                    else {\n                        merge(srcVal, tgtVal, skipUndef, tgtArr, srcArr);\n                    }\n                }\n                else {\n                    obj1[item] = tgtVal;\n                }\n            }\n            else {\n                if (skipUndef && tgtVal === undefined) {\n                    continue;\n                }\n                obj1[item] = tgtVal;\n            }\n        }\n    }\n    return obj1;\n}\n\n\nfunction extend2 (obj1, obj2, skipUndef) {\n    //if none of the arguments are object then return back\n    if (typeof obj1 !== OBJECTSTRING && typeof obj2 !== OBJECTSTRING) {\n        return null;\n    }\n\n    if (typeof obj2 !== OBJECTSTRING || obj2 === null) {\n        return obj1;\n    }\n\n    if (typeof obj1 !== OBJECTSTRING) {\n        obj1 = obj2 instanceof Array ? [] : {};\n    }\n    merge(obj1, obj2, skipUndef);\n    return obj1;\n}\n\nexport { extend2 as default };\n","import { DataFormat } from '../enums';\n\n/**\n * Checks whether the value is an array.\n *\n * @param  {*} val - The value to be checked.\n * @return {boolean} Returns true if the value is an array otherwise returns false.\n */\nexport function isArray (val) {\n    return Array.isArray(val);\n}\n\n/**\n * Checks whether the value is an object.\n *\n * @param  {*} val - The value to be checked.\n * @return {boolean} Returns true if the value is an object otherwise returns false.\n */\nexport function isObject (val) {\n    return val === Object(val);\n}\n\n/**\n * Checks whether the value is a string value.\n *\n * @param  {*} val - The value to be checked.\n * @return {boolean} Returns true if the value is a string value otherwise returns false.\n */\nexport function isString (val) {\n    return typeof val === 'string';\n}\n\n/**\n * Checks whether the value is callable.\n *\n * @param {*} val - The value to be checked.\n * @return {boolean} Returns true if the value is callable otherwise returns false.\n */\nexport function isCallable (val) {\n    return typeof val === 'function';\n}\n\n/**\n * Returns the unique values from the input array.\n *\n * @param {Array} data - The input array.\n * @return {Array} Returns a new array of unique values.\n */\nexport function uniqueValues (data) {\n    return [...new Set(data)];\n}\n\nexport const getUniqueId = () => `id-${new Date().getTime()}${Math.round(Math.random() * 10000)}`;\n\n/**\n * Checks Whether two arrays have same content.\n *\n * @param {Array} arr1 - The first array.\n * @param {Array} arr2 - The 2nd array.\n * @return {boolean} Returns whether two array have same content.\n */\nexport function isArrEqual(arr1, arr2) {\n    if (!isArray(arr1) || !isArray(arr2)) {\n        return arr1 === arr2;\n    }\n\n    if (arr1.length !== arr2.length) {\n        return false;\n    }\n\n    for (let i = 0; i < arr1.length; i++) {\n        if (arr1[i] !== arr2[i]) {\n            return false;\n        }\n    }\n\n    return true;\n}\n\n/**\n * It is the default number format function for the measure field type.\n *\n * @param {any} val - The input value.\n * @return {number} Returns a number value.\n */\nexport function formatNumber(val) {\n    return val;\n}\n\n/**\n * Returns the detected data format.\n *\n * @param {any} data - The input data to be tested.\n * @return {string} Returns the data format name.\n */\nexport const detectDataFormat = (data) => {\n    if (isString(data)) {\n        return DataFormat.DSV_STR;\n    } else if (isArray(data) && isArray(data[0])) {\n        return DataFormat.DSV_ARR;\n    } else if (isArray(data) && (data.length === 0 || isObject(data[0]))) {\n        return DataFormat.FLAT_JSON;\n    }\n    return null;\n};\n","import { FieldType } from './enums';\nimport { getUniqueId } from './utils';\n\nconst fieldStore = {\n    data: {},\n\n    createNamespace (fieldArr, name) {\n        const dataId = name || getUniqueId();\n\n        this.data[dataId] = {\n            name: dataId,\n            fields: fieldArr,\n\n            fieldsObj () {\n                let fieldsObj = this._cachedFieldsObj;\n\n                if (!fieldsObj) {\n                    fieldsObj = this._cachedFieldsObj = {};\n                    this.fields.forEach((field) => {\n                        fieldsObj[field.name()] = field;\n                    });\n                }\n                return fieldsObj;\n            },\n            getMeasure () {\n                let measureFields = this._cachedMeasure;\n\n                if (!measureFields) {\n                    measureFields = this._cachedMeasure = {};\n                    this.fields.forEach((field) => {\n                        if (field.schema().type === FieldType.MEASURE) {\n                            measureFields[field.name()] = field;\n                        }\n                    });\n                }\n                return measureFields;\n            },\n            getDimension () {\n                let dimensionFields = this._cachedDimension;\n\n                if (!this._cachedDimension) {\n                    dimensionFields = this._cachedDimension = {};\n                    this.fields.forEach((field) => {\n                        if (field.schema().type === FieldType.DIMENSION) {\n                            dimensionFields[field.name()] = field;\n                        }\n                    });\n                }\n                return dimensionFields;\n            },\n        };\n        return this.data[dataId];\n    },\n};\n\nexport default fieldStore;\n","import { getNumberFormattedVal } from './helper';\n\n/**\n * The wrapper class on top of the primitive value of a field.\n *\n * @todo Need to have support for StringValue, NumberValue, DateTimeValue\n * and GeoValue. These types should expose predicate API mostly.\n */\nclass Value {\n\n  /**\n   * Creates new Value instance.\n   *\n   * @param {*} val - the primitive value from the field cell.\n   * @param {string | Field} field - The field from which the value belongs.\n   */\n    constructor (value, rawValue, field) {\n        const formattedValue = getNumberFormattedVal(field, value);\n\n        Object.defineProperties(this, {\n            _value: {\n                enumerable: false,\n                configurable: false,\n                writable: false,\n                value\n            },\n            _formattedValue: {\n                enumerable: false,\n                configurable: false,\n                writable: false,\n                value: formattedValue\n            },\n            _internalValue: {\n                enumerable: false,\n                configurable: false,\n                writable: false,\n                value: rawValue\n            }\n        });\n\n        this.field = field;\n    }\n\n  /**\n   * Returns the field value.\n   *\n   * @return {*} Returns the current value.\n   */\n    get value () {\n        return this._value;\n    }\n\n    /**\n     * Returns the parsed value of field\n     */\n    get formattedValue () {\n        return this._formattedValue;\n    }\n\n    /**\n     * Returns the internal value of field\n     */\n    get internalValue () {\n        return this._internalValue;\n    }\n\n  /**\n   * Converts to human readable string.\n   *\n   * @override\n   * @return {string} Returns a human readable string of the field value.\n   *\n   */\n    toString () {\n        return String(this.value);\n    }\n\n  /**\n   * Returns the value of the field.\n   *\n   * @override\n   * @return {*} Returns the field value.\n   */\n    valueOf () {\n        return this.value;\n    }\n}\n\nexport default Value;\n","/**\n * Iterates through the diffSet array and call the callback with the current\n * index.\n *\n * @param {string} rowDiffset - The row diffset string e.g. '0-4,6,10-13'.\n * @param {Function} callback - The callback function to be called with every index.\n */\nexport function rowDiffsetIterator (rowDiffset, callback) {\n    if (rowDiffset.length > 0) {\n        const rowDiffArr = rowDiffset.split(',');\n        rowDiffArr.forEach((diffStr) => {\n            const diffStsArr = diffStr.split('-');\n            const start = +(diffStsArr[0]);\n            const end = +(diffStsArr[1] || diffStsArr[0]);\n            if (end >= start) {\n                for (let i = start; i <= end; i += 1) {\n                    callback(i);\n                }\n            }\n        });\n    }\n}\n","/**\n * A parser to parser null, undefined, invalid and NIL values.\n *\n * @public\n * @class\n */\nclass InvalidAwareTypes {\n    /**\n     * Static method which gets/sets the invalid value registry.\n     *\n     * @public\n     * @param {Object} config - The custom configuration supplied by user.\n     * @return {Object} Returns the invalid values registry.\n     */\n    static invalidAwareVals (config) {\n        if (!config) {\n            return InvalidAwareTypes._invalidAwareValsMap;\n        }\n        return Object.assign(InvalidAwareTypes._invalidAwareValsMap, config);\n    }\n\n    /**\n     * Initialize a new instance.\n     *\n     * @public\n     * @param {string} value - The value of the invalid data type.\n     */\n    constructor (value) {\n        this._value = value;\n    }\n\n    /**\n     * Returns the current value of the instance.\n     *\n     * @public\n     * @return {string} Returns the value of the invalid data type.\n     */\n    value () {\n        return this._value;\n    }\n\n    /**\n     * Returns the current value of the instance in string format.\n     *\n     * @public\n     * @return {string} Returns the value of the invalid data type.\n     */\n    toString () {\n        return String(this._value);\n    }\n\n    static isInvalid(val) {\n        return (val instanceof InvalidAwareTypes) || !!InvalidAwareTypes.invalidAwareVals()[val];\n    }\n\n    static getInvalidType(val) {\n        return val instanceof InvalidAwareTypes ? val : InvalidAwareTypes.invalidAwareVals()[val];\n    }\n}\n\n/**\n * Enums for Invalid types.\n */\nInvalidAwareTypes.NULL = new InvalidAwareTypes('null');\nInvalidAwareTypes.NA = new InvalidAwareTypes('na');\nInvalidAwareTypes.NIL = new InvalidAwareTypes('nil');\n\n/**\n * Default Registry for mapping the invalid values.\n *\n * @private\n */\nInvalidAwareTypes._invalidAwareValsMap = {\n    invalid: InvalidAwareTypes.NA,\n    nil: InvalidAwareTypes.NIL,\n    null: InvalidAwareTypes.NULL,\n    undefined: InvalidAwareTypes.NA\n};\n\nexport default InvalidAwareTypes;\n","import { rowDiffsetIterator } from './row-diffset-iterator';\nimport InvalidAwareTypes from '../invalid-aware-types';\n\nconst generateBuckets = (binSize, start, end) => {\n    const buckets = [];\n    let next = start;\n\n    while (next < end) {\n        buckets.push(next);\n        next += binSize;\n    }\n    buckets.push(next);\n\n    return buckets;\n};\n\nconst findBucketRange = (bucketRanges, value) => {\n    let leftIdx = 0;\n    let rightIdx = bucketRanges.length - 1;\n    let midIdx;\n    let range;\n\n    // Here use binary search as the bucketRanges is a sorted array\n    while (leftIdx <= rightIdx) {\n        midIdx = leftIdx + Math.floor((rightIdx - leftIdx) / 2);\n        range = bucketRanges[midIdx];\n\n        if (value >= range.start && value < range.end) {\n            return range;\n        } else if (value >= range.end) {\n            leftIdx = midIdx + 1;\n        } else if (value < range.start) {\n            rightIdx = midIdx - 1;\n        }\n    }\n\n    return null;\n};\n\n /**\n  * Creates the bin data from input measure field and supplied configs.\n  *\n  * @param {Measure} measureField - The Measure field instance.\n  * @param {string} rowDiffset - The datamodel rowDiffset values.\n  * @param {Object} config - The config object.\n  * @return {Object} Returns the binned data and the corresponding bins.\n  */\nexport function createBinnedFieldData (measureField, rowDiffset, config) {\n    let { buckets, binsCount, binSize, start, end } = config;\n    const [dMin, dMax] = measureField.domain();\n\n    if (!buckets) {\n        start = (start !== 0 && (!start || start > dMin)) ? dMin : start;\n        end = (end !== 0 && (!end || end < dMax)) ? (dMax + 1) : end;\n\n        if (binsCount) {\n            binSize = Math.ceil(Math.abs(end - start) / binsCount);\n        }\n\n        buckets = generateBuckets(binSize, start, end);\n    }\n\n    if (buckets[0] > dMin) {\n        buckets.unshift(dMin);\n    }\n    if (buckets[buckets.length - 1] <= dMax) {\n        buckets.push(dMax + 1);\n    }\n\n    const bucketRanges = [];\n    for (let i = 0; i < buckets.length - 1; i++) {\n        bucketRanges.push({\n            start: buckets[i],\n            end: buckets[i + 1]\n        });\n    }\n\n    const binnedData = [];\n    rowDiffsetIterator(rowDiffset, (i) => {\n        const datum = measureField.partialField.data[i];\n        if (datum instanceof InvalidAwareTypes) {\n            binnedData.push(datum);\n            return;\n        }\n\n        const range = findBucketRange(bucketRanges, datum);\n        binnedData.push(`${range.start}-${range.end}`);\n    });\n\n    return { binnedData, bins: buckets };\n}\n","export { DataFormat, FilteringMode } from '../enums';\n/**\n * The event name for data propagation.\n */\nexport const PROPAGATION = 'propagation';\n\n/**\n * The name of the unique row id column in DataModel.\n */\nexport const ROW_ID = '__id__';\n\n/**\n * The enums for operation names performed on DataModel.\n */\nexport const DM_DERIVATIVES = {\n    SELECT: 'select',\n    PROJECT: 'project',\n    GROUPBY: 'group',\n    COMPOSE: 'compose',\n    CAL_VAR: 'calculatedVariable',\n    BIN: 'bin',\n    SORT: 'sort'\n};\n\nexport const JOINS = {\n    CROSS: 'cross',\n    LEFTOUTER: 'leftOuter',\n    RIGHTOUTER: 'rightOuter',\n    NATURAL: 'natural',\n    FULLOUTER: 'fullOuter'\n};\n\nexport const LOGICAL_OPERATORS = {\n    AND: 'and',\n    OR: 'or'\n};\n","/**\n * The helper function that returns an array of common schema\n * from two fieldStore instances.\n *\n * @param {FieldStore} fs1 - The first FieldStore instance.\n * @param {FieldStore} fs2 - The second FieldStore instance.\n * @return {Array} An array containing the common schema.\n */\nexport function getCommonSchema (fs1, fs2) {\n    const retArr = [];\n    const fs1Arr = [];\n    fs1.fields.forEach((field) => {\n        fs1Arr.push(field.schema().name);\n    });\n    fs2.fields.forEach((field) => {\n        if (fs1Arr.indexOf(field.schema().name) !== -1) {\n            retArr.push(field.schema().name);\n        }\n    });\n    return retArr;\n}\n","import DataModel from '../datamodel';\nimport { extend2 } from '../utils';\nimport { getCommonSchema } from './get-common-schema';\nimport { rowDiffsetIterator } from './row-diffset-iterator';\nimport { JOINS } from '../constants';\nimport { prepareJoinData } from '../helper';\n/**\n * Default filter function for crossProduct.\n *\n * @return {boolean} Always returns true.\n */\nfunction defaultFilterFn() { return true; }\n\n/**\n * Implementation of cross product operation between two DataModel instances.\n * It internally creates the data and schema for the new DataModel.\n *\n * @param {DataModel} dataModel1 - The left DataModel instance.\n * @param {DataModel} dataModel2 - The right DataModel instance.\n * @param {Function} filterFn - The filter function which is used to filter the tuples.\n * @param {boolean} [replaceCommonSchema=false] - The flag if the common name schema should be there.\n * @return {DataModel} Returns The newly created DataModel instance from the crossProduct operation.\n */\nexport function crossProduct (dm1, dm2, filterFn, replaceCommonSchema = false, jointype = JOINS.CROSS) {\n    const schema = [];\n    const data = [];\n    const applicableFilterFn = filterFn || defaultFilterFn;\n    const dm1FieldStore = dm1.getFieldspace();\n    const dm2FieldStore = dm2.getFieldspace();\n    const dm1FieldStoreName = dm1FieldStore.name;\n    const dm2FieldStoreName = dm2FieldStore.name;\n    const name = `${dm1FieldStore.name}.${dm2FieldStore.name}`;\n    const commonSchemaList = getCommonSchema(dm1FieldStore, dm2FieldStore);\n\n    if (dm1FieldStoreName === dm2FieldStoreName) {\n        throw new Error('DataModels must have different alias names');\n    }\n    // Here prepare the schema\n    dm1FieldStore.fields.forEach((field) => {\n        const tmpSchema = extend2({}, field.schema());\n        if (commonSchemaList.indexOf(tmpSchema.name) !== -1 && !replaceCommonSchema) {\n            tmpSchema.name = `${dm1FieldStore.name}.${tmpSchema.name}`;\n        }\n        schema.push(tmpSchema);\n    });\n    dm2FieldStore.fields.forEach((field) => {\n        const tmpSchema = extend2({}, field.schema());\n        if (commonSchemaList.indexOf(tmpSchema.name) !== -1) {\n            if (!replaceCommonSchema) {\n                tmpSchema.name = `${dm2FieldStore.name}.${tmpSchema.name}`;\n                schema.push(tmpSchema);\n            }\n        } else {\n            schema.push(tmpSchema);\n        }\n    });\n\n    // Here prepare Data\n    rowDiffsetIterator(dm1._rowDiffset, (i) => {\n        let rowAdded = false;\n        let rowPosition;\n        rowDiffsetIterator(dm2._rowDiffset, (ii) => {\n            const tuple = [];\n            const userArg = {};\n            userArg[dm1FieldStoreName] = {};\n            userArg[dm2FieldStoreName] = {};\n            dm1FieldStore.fields.forEach((field) => {\n                tuple.push(field.partialField.data[i]);\n                userArg[dm1FieldStoreName][field.name()] = {\n                    rawValue: field.partialField.data[i],\n                    formattedValue: field.formattedData()[i],\n                };\n            });\n            dm2FieldStore.fields.forEach((field) => {\n                if (!(commonSchemaList.indexOf(field.schema().name) !== -1 && replaceCommonSchema)) {\n                    tuple.push(field.partialField.data[ii]);\n                }\n                userArg[dm2FieldStoreName][field.name()] = {\n                    rawValue: field.partialField.data[ii],\n                    formattedValue: field.formattedData()[ii],\n                };\n            });\n\n            let cachedStore = {};\n            let cloneProvider1 = () => dm1.detachedRoot();\n            let cloneProvider2 = () => dm2.detachedRoot();\n\n            const dm1Fields = prepareJoinData(userArg[dm1FieldStoreName]);\n            const dm2Fields = prepareJoinData(userArg[dm2FieldStoreName]);\n            if (applicableFilterFn(dm1Fields, dm2Fields, cloneProvider1, cloneProvider2, cachedStore)) {\n                const tupleObj = {};\n                tuple.forEach((cellVal, iii) => {\n                    tupleObj[schema[iii].name] = cellVal;\n                });\n                if (rowAdded && JOINS.CROSS !== jointype) {\n                    data[rowPosition] = tupleObj;\n                }\n                else {\n                    data.push(tupleObj);\n                    rowAdded = true;\n                    rowPosition = i;\n                }\n            } else if ((jointype === JOINS.LEFTOUTER || jointype === JOINS.RIGHTOUTER) && !rowAdded) {\n                const tupleObj = {};\n                let len = dm1FieldStore.fields.length - 1;\n                tuple.forEach((cellVal, iii) => {\n                    if (iii <= len) {\n                        tupleObj[schema[iii].name] = cellVal;\n                    }\n                    else {\n                        tupleObj[schema[iii].name] = null;\n                    }\n                });\n                rowAdded = true;\n                rowPosition = i;\n                data.push(tupleObj);\n            }\n        });\n    });\n\n    return new DataModel(data, schema, { name });\n}\n","/**\n * The default sort function.\n *\n * @param {*} a - The first value.\n * @param {*} b - The second value.\n * @return {number} Returns the comparison result e.g. 1 or 0 or -1.\n */\nfunction defSortFn (a, b) {\n    const a1 = `${a}`;\n    const b1 = `${b}`;\n    if (a1 < b1) {\n        return -1;\n    }\n    if (a1 > b1) {\n        return 1;\n    }\n    return 0;\n}\n\n/**\n * The helper function for merge sort which creates the sorted array\n * from the two halves of the input array.\n *\n * @param {Array} arr - The target array which needs to be merged.\n * @param {number} lo - The starting index of the first array half.\n * @param {number} mid - The ending index of the first array half.\n * @param {number} hi - The ending index of the second array half.\n * @param {Function} sortFn - The sort function.\n */\nfunction merge (arr, lo, mid, hi, sortFn) {\n    const mainArr = arr;\n    const auxArr = [];\n    for (let i = lo; i <= hi; i += 1) {\n        auxArr[i] = mainArr[i];\n    }\n    let a = lo;\n    let b = mid + 1;\n\n    for (let i = lo; i <= hi; i += 1) {\n        if (a > mid) {\n            mainArr[i] = auxArr[b];\n            b += 1;\n        } else if (b > hi) {\n            mainArr[i] = auxArr[a];\n            a += 1;\n        } else if (sortFn(auxArr[a], auxArr[b]) <= 0) {\n            mainArr[i] = auxArr[a];\n            a += 1;\n        } else {\n            mainArr[i] = auxArr[b];\n            b += 1;\n        }\n    }\n}\n\n/**\n * The helper function for merge sort which would be called\n * recursively for sorting the array halves.\n *\n * @param {Array} arr - The target array which needs to be sorted.\n * @param {number} lo - The starting index of the array half.\n * @param {number} hi - The ending index of the array half.\n * @param {Function} sortFn - The sort function.\n * @return {Array} Returns the target array itself.\n */\nfunction sort (arr, lo, hi, sortFn) {\n    if (hi === lo) { return arr; }\n\n    const mid = lo + Math.floor((hi - lo) / 2);\n    sort(arr, lo, mid, sortFn);\n    sort(arr, mid + 1, hi, sortFn);\n    merge(arr, lo, mid, hi, sortFn);\n\n    return arr;\n}\n\n/**\n * The implementation of merge sort.\n * It is used in DataModel for stable sorting as it is not sure\n * what the sorting algorithm used by browsers is stable or not.\n *\n * @param {Array} arr - The target array which needs to be sorted.\n * @param {Function} [sortFn=defSortFn] - The sort function.\n * @return {Array} Returns the input array itself in sorted order.\n */\nexport function mergeSort (arr, sortFn = defSortFn) {\n    if (arr.length > 1) {\n        sort(arr, 0, arr.length - 1, sortFn);\n    }\n    return arr;\n}\n","import { DimensionSubtype, MeasureSubtype } from '../enums';\nimport { mergeSort } from './merge-sort';\nimport { fieldInSchema } from '../helper';\nimport { isCallable, isArray } from '../utils';\n\n/**\n * Generates the sorting functions to sort the data of a DataModel instance\n * according to the input data type.\n *\n * @param {string} dataType - The data type e.g. 'measure', 'datetime' etc.\n * @param {string} sortType - The sorting order i.e. 'asc' or 'desc'.\n * @return {Function} Returns the the sorting function.\n */\nfunction getSortFn (dataType, sortType) {\n    let retFunc;\n\n    switch (dataType) {\n    case MeasureSubtype.CONTINUOUS:\n    case DimensionSubtype.TEMPORAL:\n        if (sortType === 'asc') {\n            retFunc = (a, b) => a - b;\n        } else {\n            retFunc = (a, b) => b - a;\n        }\n        break;\n    default:\n        if (sortType === 'asc') {\n            retFunc = (a, b) => {\n                a = `${a}`;\n                b = `${b}`;\n                if (a === b) {\n                    return 0;\n                }\n                return a > b ? 1 : -1;\n            };\n        } else {\n            retFunc = (a, b) => {\n                a = `${a}`;\n                b = `${b}`;\n                if (a === b) {\n                    return 0;\n                }\n                return a > b ? -1 : 1;\n            };\n        }\n    }\n\n    return retFunc;\n}\n\n/**\n * Resolves the actual sorting function based on sorting string value.\n *\n * @param {Object} fDetails - The target field info.\n * @param {string} strSortOrder - The sort order value.\n * @return {Function} Returns the sorting function.\n */\nfunction resolveStrSortOrder (fDetails, strSortOrder) {\n    const sortOrder = String(strSortOrder).toLowerCase() === 'desc' ? 'desc' : 'asc';\n    return getSortFn(fDetails.type, sortOrder);\n}\n\n/**\n * Groups the data according to the specified target field.\n *\n * @param {Array} data - The input data array.\n * @param {number} fieldIndex - The target field index within schema array.\n * @return {Array} Returns an array containing the grouped data.\n */\nfunction groupData (data, fieldIndex) {\n    const hashMap = new Map();\n    const groupedData = [];\n\n    data.forEach((datum) => {\n        const fieldVal = datum[fieldIndex];\n        if (hashMap.has(fieldVal)) {\n            groupedData[hashMap.get(fieldVal)][1].push(datum);\n        } else {\n            groupedData.push([fieldVal, [datum]]);\n            hashMap.set(fieldVal, groupedData.length - 1);\n        }\n    });\n\n    return groupedData;\n}\n\n/**\n * Creates the argument value used for sorting function when sort is done\n * with another fields.\n *\n * @param {Array} groupedDatum - The grouped datum for a single dimension field value.\n * @param {Array} targetFields - An array of the sorting fields.\n * @param {Array} targetFieldDetails - An array of the sorting field details in schema.\n * @return {Object} Returns an object containing the value of sorting fields and the target field name.\n */\nfunction createSortingFnArg (groupedDatum, targetFields, targetFieldDetails) {\n    const arg = {\n        label: groupedDatum[0]\n    };\n\n    targetFields.reduce((acc, next, idx) => {\n        acc[next] = groupedDatum[1].map(datum => datum[targetFieldDetails[idx].index]);\n        return acc;\n    }, arg);\n\n    return arg;\n}\n\n/**\n * Sorts the data by applying the standard sorting mechanism.\n *\n * @param {Array} data - The input data array.\n * @param {Array} schema - The data schema.\n * @param {Array} sortingDetails - An array containing the sorting configs.\n */\nfunction applyStandardSort (data, schema, sortingDetails) {\n    let fieldName;\n    let sortMeta;\n    let fDetails;\n    let i = sortingDetails.length - 1;\n\n    for (; i >= 0; i--) {\n        fieldName = sortingDetails[i][0];\n        sortMeta = sortingDetails[i][1];\n        fDetails = fieldInSchema(schema, fieldName);\n\n        if (!fDetails) {\n            // eslint-disable-next-line no-continue\n            continue;\n        }\n\n        if (isCallable(sortMeta)) {\n            // eslint-disable-next-line no-loop-func\n            mergeSort(data, (a, b) => sortMeta(a[fDetails.index], b[fDetails.index]));\n        } else if (isArray(sortMeta)) {\n            const groupedData = groupData(data, fDetails.index);\n            const sortingFn = sortMeta[sortMeta.length - 1];\n            const targetFields = sortMeta.slice(0, sortMeta.length - 1);\n            const targetFieldDetails = targetFields.map(f => fieldInSchema(schema, f));\n\n            groupedData.forEach((groupedDatum) => {\n                groupedDatum.push(createSortingFnArg(groupedDatum, targetFields, targetFieldDetails));\n            });\n\n            mergeSort(groupedData, (a, b) => {\n                const m = a[2];\n                const n = b[2];\n                return sortingFn(m, n);\n            });\n\n            // Empty the array\n            data.length = 0;\n            groupedData.forEach((datum) => {\n                data.push(...datum[1]);\n            });\n        } else {\n            const sortFn = resolveStrSortOrder(fDetails, sortMeta);\n            // eslint-disable-next-line no-loop-func\n            mergeSort(data, (a, b) => sortFn(a[fDetails.index], b[fDetails.index]));\n        }\n    }\n}\n\n/**\n * Creates a map based on grouping.\n *\n * @param {Array} depColumns - The dependency columns' info.\n * @param {Array} data - The input data.\n * @param {Array} schema - The data schema.\n * @param {Array} sortingDetails - The sorting details for standard sorting.\n * @return {Map} Returns a map.\n */\nconst makeGroupMapAndSort = (depColumns, data, schema, sortingDetails) => {\n    if (depColumns.length === 0) { return data; }\n\n    const targetCol = depColumns[0];\n    const map = new Map();\n\n    data.reduce((acc, currRow) => {\n        const fVal = currRow[targetCol.index];\n        if (acc.has(fVal)) {\n            acc.get(fVal).push(currRow);\n        } else {\n            acc.set(fVal, [currRow]);\n        }\n        return acc;\n    }, map);\n\n    for (let [key, val] of map) {\n        const nMap = makeGroupMapAndSort(depColumns.slice(1), val, schema, sortingDetails);\n        map.set(key, nMap);\n        if (Array.isArray(nMap)) {\n            applyStandardSort(nMap, schema, sortingDetails);\n        }\n    }\n\n    return map;\n};\n\n/**\n * Sorts the data by retaining the position/order of a particular field.\n *\n * @param {Array} data - The input data array.\n * @param {Array} schema - The data schema.\n * @param {Array} sortingDetails - An array containing the sorting configs.\n * @param {Array} depColumns - The dependency column list.\n * @return {Array} Returns the sorted data.\n */\nfunction applyGroupSort (data, schema, sortingDetails, depColumns) {\n    sortingDetails = sortingDetails.filter((detail) => {\n        if (detail[1] === null) {\n            depColumns.push(detail[0]);\n            return false;\n        }\n        return true;\n    });\n    if (sortingDetails.length === 0) { return data; }\n\n    depColumns = depColumns.map(c => fieldInSchema(schema, c));\n\n    const sortedGroupMap = makeGroupMapAndSort(depColumns, data, schema, sortingDetails);\n    return data.map((row) => {\n        let i = 0;\n        let nextMap = sortedGroupMap;\n\n        while (!Array.isArray(nextMap)) {\n            nextMap = nextMap.get(row[depColumns[i++].index]);\n        }\n\n        return nextMap.shift();\n    });\n}\n\n/**\n * Sorts the data.\n *\n * @param {Object} dataObj - An object containing the data and schema.\n * @param {Array} sortingDetails - An array containing the sorting configs.\n */\nexport function sortData (dataObj, sortingDetails) {\n    let { schema, data } = dataObj;\n\n    sortingDetails = sortingDetails.filter(sDetial => !!fieldInSchema(schema, sDetial[0]));\n    if (sortingDetails.length === 0) { return; }\n\n    let groupSortingIdx = sortingDetails.findIndex(sDetial => sDetial[1] === null);\n    groupSortingIdx = groupSortingIdx !== -1 ? groupSortingIdx : sortingDetails.length;\n\n    const standardSortingDetails = sortingDetails.slice(0, groupSortingIdx);\n    const groupSortingDetails = sortingDetails.slice(groupSortingIdx);\n\n    applyStandardSort(data, schema, standardSortingDetails);\n    data = applyGroupSort(data, schema, groupSortingDetails, standardSortingDetails.map(detail => detail[0]));\n\n    dataObj.uids = data.map(row => row.pop());\n    dataObj.data = data;\n}\n","import { rowDiffsetIterator } from './row-diffset-iterator';\nimport { sortData } from './sort';\nimport { FieldType } from '../enums';\nimport { ROW_ID } from '../constants';\n\n/**\n * Builds the actual data array.\n *\n * @param {Array} fieldStore - An array of field.\n * @param {string} rowDiffset - A string consisting of which rows to be included eg. '0-2,4,6';\n * @param {string} colIdentifier - A string consisting of the details of which column\n * to be included eg 'date,sales,profit';\n * @param {Object} sortingDetails - An object containing the sorting details of the DataModel instance.\n * @param {Object} options - The options required to create the type of the data.\n * @return {Object} Returns an object containing the multidimensional array and the relative schema.\n */\nexport function dataBuilder (fieldStore, rowDiffset, colIdentifier, sortingDetails, options) {\n    const defOptions = {\n        addUid: false,\n        columnWise: false\n    };\n    options = Object.assign({}, defOptions, options);\n\n    const retObj = {\n        schema: [],\n        data: [],\n        uids: []\n    };\n    const addUid = options.addUid;\n    const reqSorting = sortingDetails && sortingDetails.length > 0;\n    // It stores the fields according to the colIdentifier argument\n    const tmpDataArr = [];\n    // Stores the fields according to the colIdentifier argument\n    const colIArr = colIdentifier.split(',');\n\n    colIArr.forEach((colName) => {\n        for (let i = 0; i < fieldStore.length; i += 1) {\n            if (fieldStore[i].name() === colName) {\n                tmpDataArr.push(fieldStore[i]);\n                break;\n            }\n        }\n    });\n\n    // Inserts the schema to the schema object\n    tmpDataArr.forEach((field) => {\n        /** @todo Need to use extend2 here otherwise user can overwrite the schema. */\n        retObj.schema.push(field.schema());\n    });\n\n    if (addUid) {\n        retObj.schema.push({\n            name: ROW_ID,\n            type: FieldType.DIMENSION\n        });\n    }\n\n    rowDiffsetIterator(rowDiffset, (i) => {\n        retObj.data.push([]);\n        const insertInd = retObj.data.length - 1;\n        let start = 0;\n        tmpDataArr.forEach((field, ii) => {\n            retObj.data[insertInd][ii + start] = field.partialField.data[i];\n        });\n        if (addUid) {\n            retObj.data[insertInd][tmpDataArr.length] = i;\n        }\n        // Creates an array of unique identifiers for each row\n        retObj.uids.push(i);\n\n        // If sorting needed then there is the need to expose the index\n        // mapping from the old index to its new index\n        if (reqSorting) { retObj.data[insertInd].push(i); }\n    });\n\n    // Handles the sort functionality\n    if (reqSorting) {\n        sortData(retObj, sortingDetails);\n    }\n\n    if (options.columnWise) {\n        const tmpData = Array(...Array(retObj.schema.length)).map(() => []);\n        retObj.data.forEach((tuple) => {\n            tuple.forEach((data, i) => {\n                tmpData[i].push(data);\n            });\n        });\n        retObj.data = tmpData;\n    }\n\n    return retObj;\n}\n","import DataModel from '../datamodel';\nimport { extend2 } from '../utils';\nimport { rowDiffsetIterator } from './row-diffset-iterator';\nimport { isArrEqual } from '../utils/helper';\n\n/**\n * Performs the union operation between two dm instances.\n *\n * @todo Fix the conflicts between union and difference terminology here.\n *\n * @param {dm} dm1 - The first dm instance.\n * @param {dm} dm2 - The second dm instance.\n * @return {dm} Returns the newly created dm after union operation.\n */\nexport function difference (dm1, dm2) {\n    const hashTable = {};\n    const schema = [];\n    const schemaNameArr = [];\n    const data = [];\n    const dm1FieldStore = dm1.getFieldspace();\n    const dm2FieldStore = dm2.getFieldspace();\n    const dm1FieldStoreFieldObj = dm1FieldStore.fieldsObj();\n    const dm2FieldStoreFieldObj = dm2FieldStore.fieldsObj();\n    const name = `${dm1FieldStore.name} union ${dm2FieldStore.name}`;\n\n   // For union the columns should match otherwise return a clone of the dm1\n    if (!isArrEqual(dm1._colIdentifier.split(',').sort(), dm2._colIdentifier.split(',').sort())) {\n        return null;\n    }\n\n    // Prepare the schema\n    (dm1._colIdentifier.split(',')).forEach((fieldName) => {\n        const field = dm1FieldStoreFieldObj[fieldName];\n        schema.push(extend2({}, field.schema()));\n        schemaNameArr.push(field.schema().name);\n    });\n\n    /**\n     * The helper function to create the data.\n     *\n     * @param {dm} dm - The dm instance for which the data is inserted.\n     * @param {Object} fieldsObj - The fieldStore object format.\n     * @param {boolean} addData - If true only tuple will be added to the data.\n     */\n    function prepareDataHelper(dm, fieldsObj, addData) {\n        rowDiffsetIterator(dm._rowDiffset, (i) => {\n            const tuple = {};\n            let hashData = '';\n            schemaNameArr.forEach((schemaName) => {\n                const value = fieldsObj[schemaName].partialField.data[i];\n                hashData += `-${value}`;\n                tuple[schemaName] = value;\n            });\n            if (!hashTable[hashData]) {\n                if (addData) { data.push(tuple); }\n                hashTable[hashData] = true;\n            }\n        });\n    }\n\n    // Prepare the data\n    prepareDataHelper(dm2, dm2FieldStoreFieldObj, false);\n    prepareDataHelper(dm1, dm1FieldStoreFieldObj, true);\n\n    return new DataModel(data, schema, { name });\n}\n\n","import { isArray } from '../utils';\nimport InvalidAwareTypes from '../invalid-aware-types';\nimport { GROUP_BY_FUNCTIONS } from '../enums';\n\nconst { SUM, AVG, FIRST, LAST, COUNT, STD, MIN, MAX } = GROUP_BY_FUNCTIONS;\n\nfunction getFilteredValues(arr) {\n    return arr.filter(item => !(item instanceof InvalidAwareTypes));\n}\n/**\n * Reducer function that returns the sum of all the values.\n *\n * @public\n * @param  {Array.<number>} arr - The input array.\n * @return {number} Returns the sum of the array.\n */\nfunction sum (arr) {\n    if (isArray(arr) && !(arr[0] instanceof Array)) {\n        const filteredNumber = getFilteredValues(arr);\n        const totalSum = filteredNumber.length ?\n                            filteredNumber.reduce((acc, curr) => acc + curr, 0)\n                            : InvalidAwareTypes.NULL;\n        return totalSum;\n    }\n    return InvalidAwareTypes.NULL;\n}\n\n/**\n * Reducer function that returns the average of all the values.\n *\n * @public\n * @param  {Array.<number>} arr - The input array.\n * @return {number} Returns the mean value of the array.\n */\nfunction avg (arr) {\n    if (isArray(arr) && !(arr[0] instanceof Array)) {\n        const totalSum = sum(arr);\n        const len = arr.length || 1;\n        return (Number.isNaN(totalSum) || totalSum instanceof InvalidAwareTypes) ?\n                 InvalidAwareTypes.NULL : totalSum / len;\n    }\n    return InvalidAwareTypes.NULL;\n}\n\n/**\n * Reducer function that gives the min value amongst all the values.\n *\n * @public\n * @param  {Array.<number>} arr - The input array.\n * @return {number} Returns the minimum value of the array.\n */\nfunction min (arr) {\n    if (isArray(arr) && !(arr[0] instanceof Array)) {\n        // Filter out undefined, null and NaN values\n        const filteredValues = getFilteredValues(arr);\n\n        return (filteredValues.length) ? Math.min(...filteredValues) : InvalidAwareTypes.NULL;\n    }\n    return InvalidAwareTypes.NULL;\n}\n\n/**\n * Reducer function that gives the max value amongst all the values.\n *\n * @public\n * @param  {Array.<number>} arr - The input array.\n * @return {number} Returns the maximum value of the array.\n */\nfunction max (arr) {\n    if (isArray(arr) && !(arr[0] instanceof Array)) {\n        // Filter out undefined, null and NaN values\n        const filteredValues = getFilteredValues(arr);\n\n        return (filteredValues.length) ? Math.max(...filteredValues) : InvalidAwareTypes.NULL;\n    }\n    return InvalidAwareTypes.NULL;\n}\n\n/**\n * Reducer function that gives the first value of the array.\n *\n * @public\n * @param  {Array} arr - The input array.\n * @return {number} Returns the first value of the array.\n */\nfunction first (arr) {\n    return arr[0];\n}\n\n/**\n * Reducer function that gives the last value of the array.\n *\n * @public\n * @param  {Array} arr - The input array.\n * @return {number} Returns the last value of the array.\n */\nfunction last (arr) {\n    return arr[arr.length - 1];\n}\n\n/**\n * Reducer function that gives the count value of the array.\n *\n * @public\n * @param  {Array} arr - The input array.\n * @return {number} Returns the length of the array.\n */\nfunction count (arr) {\n    if (isArray(arr)) {\n        return arr.length;\n    }\n    return InvalidAwareTypes.NULL;\n}\n\n/**\n * Calculates the variance of the input array.\n *\n * @param  {Array.<number>} arr - The input array.\n * @return {number} Returns the variance of the input array.\n */\nfunction variance (arr) {\n    let mean = avg(arr);\n    return avg(arr.map(num => (num - mean) ** 2));\n}\n\n/**\n * Calculates the square root of the variance of the input array.\n *\n * @public\n * @param  {Array.<number>} arr - The input array.\n * @return {number} Returns the square root of the variance.\n */\nfunction std (arr) {\n    return Math.sqrt(variance(arr));\n}\n\n\nconst fnList = {\n    [SUM]: sum,\n    [AVG]: avg,\n    [MIN]: min,\n    [MAX]: max,\n    [FIRST]: first,\n    [LAST]: last,\n    [COUNT]: count,\n    [STD]: std\n};\n\nconst defaultReducerName = SUM;\n\nexport {\n    defaultReducerName,\n    sum as defReducer,\n    fnList,\n};\n","import { defReducer, fnList } from '../operator';\n\n/**\n * A page level storage which stores, registers, unregisters reducers for all the datamodel instances. There is only one\n * reducer store available in a page. All the datamodel instances receive same instance of reducer store. DataModel\n * out of the box provides handful of {@link reducer | reducers} which can be used as reducer funciton.\n *\n * @public\n * @namespace DataModel\n */\nclass ReducerStore {\n    constructor () {\n        this.store = new Map();\n        this.store.set('defReducer', defReducer);\n\n        Object.entries(fnList).forEach((key) => {\n            this.store.set(key[0], key[1]);\n        });\n    }\n\n    /**\n     * Changes the `defaultReducer` globally. For all the fields which does not have `defAggFn` mentioned in schema, the\n     * value of `defaultReducer` is used for aggregation.\n     *\n     * @public\n     * @param {string} [reducer='sum'] - The name of the default reducer. It picks up the definition from store by doing\n     * name lookup. If no name is found then it takes `sum` as the default reducer.\n     * @return {ReducerStore} Returns instance of the singleton store in page.\n     */\n    defaultReducer (...params) {\n        if (!params.length) {\n            return this.store.get('defReducer');\n        }\n\n        let reducer = params[0];\n\n        if (typeof reducer === 'function') {\n            this.store.set('defReducer', reducer);\n        } else {\n            reducer = String(reducer);\n            if (Object.keys(fnList).indexOf(reducer) !== -1) {\n                this.store.set('defReducer', fnList[reducer]);\n            } else {\n                throw new Error(`Reducer ${reducer} not found in registry`);\n            }\n        }\n        return this;\n    }\n\n    /**\n     *\n     * Registers a {@link reducer | reducer}.\n     * A {@link reducer | reducer} has to be registered before it is used.\n     *\n     * @example\n     *  // find the mean squared value of a given set\n     *  const reducerStore = DataModel.Reducers();\n     *\n     *  reducers.register('meanSquared', (arr) => {\n     *      const squaredVal = arr.map(item => item * item);\n     *      let sum = 0;\n     *      for (let i = 0, l = squaredVal.length; i < l; i++) {\n     *          sum += squaredVal[i++];\n     *      }\n     *\n     *      return sum;\n     *  })\n     *\n     *  // datamodel (dm) is already prepared with cars.json\n     *  const dm1 = dm.groupBy(['origin'], {\n     *      accleration: 'meanSquared'\n     *  });\n     *\n     * @public\n     *\n     * @param {string} name formal name for a reducer. If the given name already exists in store it is overridden by new\n     *      definition.\n     * @param {Function} reducer definition of {@link reducer} function.\n     *\n     * @return {Function} function for unregistering the reducer.\n     */\n    register (name, reducer) {\n        if (typeof reducer !== 'function') {\n            throw new Error('Reducer should be a function');\n        }\n\n        name = String(name);\n        this.store.set(name, reducer);\n\n        return () => { this.__unregister(name); };\n    }\n\n    __unregister (name) {\n        if (this.store.has(name)) {\n            this.store.delete(name);\n        }\n    }\n\n    resolve (name) {\n        if (name instanceof Function) {\n            return name;\n        }\n        return this.store.get(name);\n    }\n}\n\nconst reducerStore = (function () {\n    let store = null;\n\n    function getStore () {\n        if (store === null) {\n            store = new ReducerStore();\n        }\n        return store;\n    }\n    return getStore();\n}());\n\nexport default reducerStore;\n","import { extend2 } from '../utils';\nimport { rowDiffsetIterator } from './row-diffset-iterator';\nimport DataModel from '../export';\nimport reducerStore from '../utils/reducer-store';\nimport { defaultReducerName } from './group-by-function';\nimport { FieldType } from '../enums';\n\n/**\n * This function sanitize the user given field and return a common Array structure field\n * list\n * @param  {DataModel} dataModel the dataModel operating on\n * @param  {Array} fieldArr  user input of field Array\n * @return {Array}           arrays of field name\n */\nfunction getFieldArr (dataModel, fieldArr) {\n    const retArr = [];\n    const fieldStore = dataModel.getFieldspace();\n    const dimensions = fieldStore.getDimension();\n\n    Object.entries(dimensions).forEach(([key]) => {\n        if (fieldArr && fieldArr.length) {\n            if (fieldArr.indexOf(key) !== -1) {\n                retArr.push(key);\n            }\n        } else {\n            retArr.push(key);\n        }\n    });\n\n    return retArr;\n}\n\n/**\n * This sanitize the reducer provide by the user and create a common type of object.\n * user can give function Also\n * @param  {DataModel} dataModel     dataModel to worked on\n * @param  {Object|function} [reducers={}] reducer provided by the users\n * @return {Object}               object containing reducer function for every measure\n */\nfunction getReducerObj (dataModel, reducers = {}) {\n    const retObj = {};\n    const fieldStore = dataModel.getFieldspace();\n    const measures = fieldStore.getMeasure();\n    const defReducer = reducerStore.defaultReducer();\n\n    Object.keys(measures).forEach((measureName) => {\n        if (typeof reducers[measureName] !== 'string') {\n            reducers[measureName] = measures[measureName].defAggFn();\n        }\n        const reducerFn = reducerStore.resolve(reducers[measureName]);\n        if (reducerFn) {\n            retObj[measureName] = reducerFn;\n        } else {\n            retObj[measureName] = defReducer;\n            reducers[measureName] = defaultReducerName;\n        }\n    });\n    return retObj;\n}\n\n/**\n * main function which perform the group-by operations which reduce the measures value is the\n * fields are common according to the reducer function provided\n * @param  {DataModel} dataModel the dataModel to worked\n * @param  {Array} fieldArr  fields according to which the groupby should be worked\n * @param  {Object|Function} reducers  reducers function\n * @param {DataModel} existingDataModel Existing datamodel instance\n * @return {DataModel} new dataModel with the group by\n */\nfunction groupBy (dataModel, fieldArr, reducers, existingDataModel) {\n    const sFieldArr = getFieldArr(dataModel, fieldArr);\n    const reducerObj = getReducerObj(dataModel, reducers);\n    const fieldStore = dataModel.getFieldspace();\n    const fieldStoreObj = fieldStore.fieldsObj();\n    const dbName = fieldStore.name;\n    const dimensionArr = [];\n    const measureArr = [];\n    const schema = [];\n    const hashMap = {};\n    const data = [];\n    let newDataModel;\n\n    // Prepare the schema\n    Object.entries(fieldStoreObj).forEach(([key, value]) => {\n        if (sFieldArr.indexOf(key) !== -1 || reducerObj[key]) {\n            schema.push(extend2({}, value.schema()));\n\n            switch (value.schema().type) {\n            case FieldType.MEASURE:\n                measureArr.push(key);\n                break;\n            default:\n            case FieldType.DIMENSION:\n                dimensionArr.push(key);\n            }\n        }\n    });\n    // Prepare the data\n    let rowCount = 0;\n    rowDiffsetIterator(dataModel._rowDiffset, (i) => {\n        let hash = '';\n        dimensionArr.forEach((_) => {\n            hash = `${hash}-${fieldStoreObj[_].partialField.data[i]}`;\n        });\n        if (hashMap[hash] === undefined) {\n            hashMap[hash] = rowCount;\n            data.push({});\n            dimensionArr.forEach((_) => {\n                data[rowCount][_] = fieldStoreObj[_].partialField.data[i];\n            });\n            measureArr.forEach((_) => {\n                data[rowCount][_] = [fieldStoreObj[_].partialField.data[i]];\n            });\n            rowCount += 1;\n        } else {\n            measureArr.forEach((_) => {\n                data[hashMap[hash]][_].push(fieldStoreObj[_].partialField.data[i]);\n            });\n        }\n    });\n\n    // reduction\n    let cachedStore = {};\n    let cloneProvider = () => dataModel.detachedRoot();\n    data.forEach((row) => {\n        const tuple = row;\n        measureArr.forEach((_) => {\n            tuple[_] = reducerObj[_](row[_], cloneProvider, cachedStore);\n        });\n    });\n    if (existingDataModel) {\n        existingDataModel.__calculateFieldspace();\n        newDataModel = existingDataModel;\n    }\n    else {\n        newDataModel = new DataModel(data, schema, { name: dbName });\n    }\n    return newDataModel;\n}\n\nexport { groupBy, getFieldArr, getReducerObj };\n","import { getCommonSchema } from './get-common-schema';\n\n/**\n * The filter function used in natural join.\n * It generates a function that will have the logic to join two\n * DataModel instances by the process of natural join.\n *\n * @param {DataModel} dm1 - The left DataModel instance.\n * @param {DataModel} dm2 - The right DataModel instance.\n * @return {Function} Returns a function that is used in cross-product operation.\n */\nexport function naturalJoinFilter (dm1, dm2) {\n    const dm1FieldStore = dm1.getFieldspace();\n    const dm2FieldStore = dm2.getFieldspace();\n    // const dm1FieldStoreName = dm1FieldStore.name;\n    // const dm2FieldStoreName = dm2FieldStore.name;\n    const commonSchemaArr = getCommonSchema(dm1FieldStore, dm2FieldStore);\n\n    return (dm1Fields, dm2Fields) => {\n        let retainTuple = true;\n        commonSchemaArr.forEach((fieldName) => {\n            if (dm1Fields[fieldName].internalValue ===\n                dm2Fields[fieldName].internalValue && retainTuple) {\n                retainTuple = true;\n            } else {\n                retainTuple = false;\n            }\n        });\n        return retainTuple;\n    };\n}\n","import DataModel from '../export';\nimport { extend2 } from '../utils';\nimport { rowDiffsetIterator } from './row-diffset-iterator';\nimport { isArrEqual } from '../utils/helper';\n/**\n * Performs the union operation between two dm instances.\n *\n * @param {dm} dm1 - The first dm instance.\n * @param {dm} dm2 - The second dm instance.\n * @return {dm} Returns the newly created dm after union operation.\n */\nexport function union (dm1, dm2) {\n    const hashTable = {};\n    const schema = [];\n    const schemaNameArr = [];\n    const data = [];\n    const dm1FieldStore = dm1.getFieldspace();\n    const dm2FieldStore = dm2.getFieldspace();\n    const dm1FieldStoreFieldObj = dm1FieldStore.fieldsObj();\n    const dm2FieldStoreFieldObj = dm2FieldStore.fieldsObj();\n    const name = `${dm1FieldStore.name} union ${dm2FieldStore.name}`;\n\n    // For union the columns should match otherwise return a clone of the dm1\n    if (!isArrEqual(dm1._colIdentifier.split(',').sort(), dm2._colIdentifier.split(',').sort())) {\n        return null;\n    }\n\n    // Prepare the schema\n    (dm1._colIdentifier.split(',')).forEach((fieldName) => {\n        const field = dm1FieldStoreFieldObj[fieldName];\n        schema.push(extend2({}, field.schema()));\n        schemaNameArr.push(field.schema().name);\n    });\n\n    /**\n     * The helper function to create the data.\n     *\n     * @param {dm} dm - The dm instance for which the data is inserted.\n     * @param {Object} fieldsObj - The fieldStore object format.\n     */\n    function prepareDataHelper (dm, fieldsObj) {\n        rowDiffsetIterator(dm._rowDiffset, (i) => {\n            const tuple = {};\n            let hashData = '';\n            schemaNameArr.forEach((schemaName) => {\n                const value = fieldsObj[schemaName].partialField.data[i];\n                hashData += `-${value}`;\n                tuple[schemaName] = value;\n            });\n            if (!hashTable[hashData]) {\n                data.push(tuple);\n                hashTable[hashData] = true;\n            }\n        });\n    }\n\n    // Prepare the data\n    prepareDataHelper(dm1, dm1FieldStoreFieldObj);\n    prepareDataHelper(dm2, dm2FieldStoreFieldObj);\n\n    return new DataModel(data, schema, { name });\n}\n","import { crossProduct } from './cross-product';\nimport { JOINS } from '../constants';\nimport { union } from './union';\n\n\nexport function leftOuterJoin (dataModel1, dataModel2, filterFn) {\n    return crossProduct(dataModel1, dataModel2, filterFn, false, JOINS.LEFTOUTER);\n}\n\nexport function rightOuterJoin (dataModel1, dataModel2, filterFn) {\n    return crossProduct(dataModel2, dataModel1, filterFn, false, JOINS.RIGHTOUTER);\n}\n\nexport function fullOuterJoin (dataModel1, dataModel2, filterFn) {\n    return union(leftOuterJoin(dataModel1, dataModel2, filterFn), rightOuterJoin(dataModel1, dataModel2, filterFn));\n}\n","/**\n * Stores the full data and the metadata of a field. It provides\n * a single source of data from which the future Field\n * instance can get a subset of it with a rowDiffset config.\n *\n * @class\n * @public\n */\nexport default class PartialField {\n    /**\n     * Initialize a new instance.\n     *\n     * @public\n     * @param {string} name - The name of the field.\n     * @param {Array} data - The data array.\n     * @param {Object} schema - The schema object of the corresponding field.\n     * @param {FieldParser} parser - The parser instance corresponding to that field.\n     */\n    constructor (name, data, schema, parser) {\n        this.name = name;\n        this.schema = schema;\n        this.parser = parser;\n        this.data = this._sanitize(data);\n    }\n\n    /**\n     * Sanitizes the field data.\n     *\n     * @private\n     * @param {Array} data - The actual input data.\n     * @return {Array} Returns the sanitized data.\n     */\n    _sanitize (data) {\n        return data.map(datum => this.parser.parse(datum, { format: this.schema.format }));\n    }\n}\n","import { rowDiffsetIterator } from '../../operator/row-diffset-iterator';\nimport PartialField from '../partial-field';\n\n/**\n * In {@link DataModel}, every tabular data consists of column, a column is stored as field.\n * Field contains all the data for a given column in an array.\n *\n * Each record consists of several fields; the fields of all records form the columns.\n * Examples of fields: name, gender, sex etc.\n *\n * In DataModel, each field can have multiple attributes which describes its data and behaviour.\n * A field can have two types of data: Measure and Dimension.\n *\n * A Dimension Field is the context on which a data is categorized and the measure is the numerical values that\n * quantify the data set.\n * In short a dimension is the lens through which you are looking at your measure data.\n *\n * Refer to {@link Schema} to get info about possible field attributes.\n *\n * @public\n * @class\n */\nexport default class Field {\n    /**\n     * Initialize a new instance.\n     *\n     * @public\n     * @param {PartialField} partialField - The partialField instance which holds the whole data.\n     * @param {string} rowDiffset - The data subset definition.\n     */\n    constructor (partialField, rowDiffset) {\n        this.partialField = partialField;\n        this.rowDiffset = rowDiffset;\n    }\n\n    static parser() {\n        throw new Error('Not yet implemented');\n    }\n\n    /**\n     * Generates the field type specific domain.\n     *\n     * @public\n     * @abstract\n     */\n    domain () {\n        throw new Error('Not yet implemented');\n    }\n\n    /**\n     * Returns the the field schema.\n     *\n     * @public\n     * @return {string} Returns the field schema.\n     */\n    schema () {\n        return this.partialField.schema;\n    }\n\n    /**\n     * Returns the name of the field.\n     *\n     * @public\n     * @return {string} Returns the name of the field.\n     */\n    name () {\n        return this.partialField.name;\n    }\n\n    /**\n     * Returns the type of the field.\n     *\n     * @public\n     * @return {string} Returns the type of the field.\n     */\n    type () {\n        return this.partialField.schema.type;\n    }\n\n    /**\n     * Returns the subtype of the field.\n     *\n     * @public\n     * @return {string} Returns the subtype of the field.\n     */\n    subtype () {\n        return this.partialField.schema.subtype;\n    }\n\n    /**\n     * Returns the description of the field.\n     *\n     * @public\n     * @return {string} Returns the description of the field.\n     */\n    description () {\n        return this.partialField.schema.description;\n    }\n\n    /**\n     * Returns the display name of the field.\n     *\n     * @public\n     * @return {string} Returns the display name of the field.\n     */\n    displayName () {\n        return this.partialField.schema.displayName || this.partialField.schema.name;\n    }\n\n    /**\n     * Returns the data associated with the field.\n     *\n     * @public\n     * @return {Array} Returns the data.\n     */\n    data () {\n        const data = [];\n        rowDiffsetIterator(this.rowDiffset, (i) => {\n            data.push(this.partialField.data[i]);\n        });\n        return data;\n    }\n\n    /**\n     * Returns the formatted version of the underlying field data.\n     *\n     * @public\n     * @abstract\n     */\n    formattedData () {\n        throw new Error('Not yet implemented');\n    }\n\n    static get BUILDER() {\n        const builder = {\n            _params: {},\n            _context: this,\n            fieldName(name) {\n                this._params.name = name;\n                return this;\n            },\n            schema(schema) {\n                this._params.schema = schema;\n                return this;\n            },\n            data(data) {\n                this._params.data = data;\n                return this;\n            },\n            partialField(partialField) {\n                this._params.partialField = partialField;\n                return this;\n            },\n            rowDiffset(rowDiffset) {\n                this._params.rowDiffset = rowDiffset;\n                return this;\n            },\n            build() {\n                let partialField = null;\n                if (this._params.partialField instanceof PartialField) {\n                    partialField = this._params.partialField;\n                } else if (this._params.schema && this._params.data) {\n                    partialField = new PartialField(this._params.name,\n                                        this._params.data,\n                                        this._params.schema,\n                                        this._context.parser());\n                }\n                else {\n                    throw new Error('Invalid Field parameters');\n                }\n                return new this._context(partialField, this._params.rowDiffset);\n            }\n        };\n        return builder;\n    }\n}\n","import Field from '../field';\n\n/**\n * Represents dimension field type.\n *\n * @public\n * @class\n * @extends Field\n */\nexport default class Dimension extends Field {\n    /**\n     * Returns the domain for the dimension field.\n     *\n     * @override\n     * @public\n     * @return {any} Returns the calculated domain.\n     */\n    domain () {\n        if (!this._cachedDomain) {\n            this._cachedDomain = this.calculateDataDomain();\n        }\n        return this._cachedDomain;\n    }\n\n    /**\n     * Calculates the corresponding field domain.\n     *\n     * @public\n     * @abstract\n     */\n    calculateDataDomain () {\n        throw new Error('Not yet implemented');\n    }\n\n     /**\n     * Returns the formatted version of the underlying field data.\n     *\n     * @public\n     * @override\n     * @return {Array} Returns the formatted data.\n     */\n    formattedData () {\n        return this.data();\n    }\n}\n","import { formatNumber } from '../../utils';\nimport { defaultReducerName } from '../../operator/group-by-function';\nimport Field from '../field';\n\n/**\n * Represents measure field type.\n *\n * @public\n * @class\n * @extends Field\n */\nexport default class Measure extends Field {\n  /**\n   * Returns the domain for the measure field.\n   *\n   * @override\n   * @public\n   * @return {any} Returns the calculated domain.\n   */\n    domain () {\n        if (!this._cachedDomain) {\n            this._cachedDomain = this.calculateDataDomain();\n        }\n        return this._cachedDomain;\n    }\n\n  /**\n   * Returns the unit of the measure field.\n   *\n   * @public\n   * @return {string} Returns unit of the field.\n   */\n    unit () {\n        return this.partialField.schema.unit;\n    }\n\n  /**\n   * Returns the aggregation function name of the measure field.\n   *\n   * @public\n   * @return {string} Returns aggregation function name of the field.\n   */\n    defAggFn () {\n        return this.partialField.schema.defAggFn || defaultReducerName;\n    }\n\n  /**\n   * Returns the number format of the measure field.\n   *\n   * @public\n   * @return {Function} Returns number format of the field.\n   */\n    numberFormat () {\n        const { numberFormat } = this.partialField.schema;\n        return numberFormat instanceof Function ? numberFormat : formatNumber;\n    }\n\n  /**\n   * Calculates the corresponding field domain.\n   *\n   * @public\n   * @abstract\n   */\n    calculateDataDomain () {\n        throw new Error('Not yet implemented');\n    }\n\n    /**\n     * Returns the formatted version of the underlying field data.\n     *\n     * @public\n     * @override\n     * @return {Array} Returns the formatted data.\n     */\n    formattedData () {\n        return this.data();\n    }\n}\n","/**\n * A interface to represent a parser which is responsible to parse the field.\n *\n * @public\n * @interface\n */\nexport default class FieldParser {\n    /**\n     * Parses a single value of a field and return the sanitized form.\n     *\n     * @public\n     * @abstract\n     */\n    parse () {\n        throw new Error('Not yet implemented');\n    }\n}\n","import FieldParser from '../field-parser';\nimport InvalidAwareTypes from '../../../invalid-aware-types';\n\n/**\n * A FieldParser which parses the categorical values.\n *\n * @public\n * @class\n * @implements {FieldParser}\n */\nexport default class CategoricalParser extends FieldParser {\n  /**\n   * Parses a single value of a field and returns the stringified form.\n   *\n   * @public\n   * @param {string|number} val - The value of the field.\n   * @return {string} Returns the stringified value.\n   */\n    parse (val) {\n        let result;\n        // check if invalid date value\n        if (!InvalidAwareTypes.isInvalid(val)) {\n            result = String(val).trim();\n        } else {\n            result = InvalidAwareTypes.getInvalidType(val);\n        }\n        return result;\n    }\n}\n","import { rowDiffsetIterator } from '../../operator/row-diffset-iterator';\nimport { DimensionSubtype } from '../../enums';\nimport Dimension from '../dimension';\nimport CategoricalParser from '../parsers/categorical-parser';\n/**\n * Represents categorical field subtype.\n *\n * @public\n * @class\n * @extends Dimension\n */\nexport default class Categorical extends Dimension {\n    /**\n     * Returns the subtype of the field.\n     *\n     * @public\n     * @override\n     * @return {string} Returns the subtype of the field.\n     */\n    subtype () {\n        return DimensionSubtype.CATEGORICAL;\n    }\n\n    /**\n     * Calculates the corresponding field domain.\n     *\n     * @public\n     * @override\n     * @return {Array} Returns the unique values.\n     */\n    calculateDataDomain () {\n        const hash = new Set();\n        const domain = [];\n\n        // here don't use this.data() as the iteration will be occurred two times on same data.\n        rowDiffsetIterator(this.rowDiffset, (i) => {\n            const datum = this.partialField.data[i];\n            if (!hash.has(datum)) {\n                hash.add(datum);\n                domain.push(datum);\n            }\n        });\n        return domain;\n    }\n\n    static parser() {\n        return new CategoricalParser();\n    }\n}\n","import { DateTimeFormatter } from '../../../utils';\nimport FieldParser from '../field-parser';\nimport InvalidAwareTypes from '../../../invalid-aware-types';\n\n/**\n * A FieldParser which parses the temporal values.\n *\n * @public\n * @class\n * @implements {FieldParser}\n */\nexport default class TemporalParser extends FieldParser {\n\n    /**\n     * Parses a single value of a field and returns the millisecond value.\n     *\n     * @public\n     * @param {string|number} val - The value of the field.\n     * @return {number} Returns the millisecond value.\n     */\n    parse (val, { format }) {\n        let result;\n        // check if invalid date value\n        if (!this._dtf) {\n            this._dtf = new DateTimeFormatter(format);\n        }\n        if (!InvalidAwareTypes.isInvalid(val)) {\n            let nativeDate = this._dtf.getNativeDate(val);\n            result = nativeDate ? nativeDate.getTime() : InvalidAwareTypes.NA;\n        } else {\n            result = InvalidAwareTypes.getInvalidType(val);\n        }\n        return result;\n    }\n}\n","import { rowDiffsetIterator } from '../operator/row-diffset-iterator';\nimport InvalidAwareTypes from '../invalid-aware-types';\n\nexport const calculateContinuousDomain = (data, rowDiffset) => {\n    let min = Number.POSITIVE_INFINITY;\n    let max = Number.NEGATIVE_INFINITY;\n\n    // here don't use this.data() as the iteration will be occurred two times on same data.\n    rowDiffsetIterator(rowDiffset, (i) => {\n        const datum = data[i];\n        if (datum instanceof InvalidAwareTypes) {\n            return;\n        }\n\n        if (datum < min) {\n            min = datum;\n        }\n        if (datum > max) {\n            max = datum;\n        }\n    });\n\n    return [min, max];\n};\n","import { rowDiffsetIterator } from '../../operator/row-diffset-iterator';\nimport Dimension from '../dimension';\nimport { DateTimeFormatter } from '../../utils';\nimport InvalidAwareTypes from '../../invalid-aware-types';\nimport TemporalParser from '../parsers/temporal-parser';\nimport { calculateContinuousDomain } from '../helper';\n\n/**\n * Represents temporal field subtype.\n *\n * @public\n * @class\n * @extends Dimension\n */\nexport default class Temporal extends Dimension {\n     /**\n     * Initialize a new instance.\n     *\n     * @public\n     * @param {PartialField} partialField - The partialField instance which holds the whole data.\n     * @param {string} rowDiffset - The data subset definition.\n     */\n    constructor (partialField, rowDiffset) {\n        super(partialField, rowDiffset);\n\n        this._cachedMinDiff = null;\n    }\n\n     /**\n     * Calculates the corresponding field domain.\n     *\n     * @public\n     * @override\n     * @return {Array} Returns the unique values.\n     */\n    calculateDataDomain () {\n        return calculateContinuousDomain(this.partialField.data, this.rowDiffset);\n    }\n\n\n    /**\n     * Calculates the minimum consecutive difference from the associated field data.\n     *\n     * @public\n     * @return {number} Returns the minimum consecutive diff in milliseconds.\n     */\n    minimumConsecutiveDifference () {\n        if (this._cachedMinDiff) {\n            return this._cachedMinDiff;\n        }\n\n        const sortedData = this.data().filter(item => !(item instanceof InvalidAwareTypes)).sort((a, b) => a - b);\n        const arrLn = sortedData.length;\n        let minDiff = Number.POSITIVE_INFINITY;\n        let prevDatum;\n        let nextDatum;\n        let processedCount = 0;\n\n        for (let i = 1; i < arrLn; i++) {\n            prevDatum = sortedData[i - 1];\n            nextDatum = sortedData[i];\n\n            if (nextDatum === prevDatum) {\n                continue;\n            }\n\n            minDiff = Math.min(minDiff, nextDatum - sortedData[i - 1]);\n            processedCount++;\n        }\n\n        if (!processedCount) {\n            minDiff = null;\n        }\n        this._cachedMinDiff = minDiff;\n\n        return this._cachedMinDiff;\n    }\n\n    /**\n     * Returns the format specified in the input schema while creating field.\n     *\n     * @public\n     * @return {string} Returns the datetime format.\n     */\n    format () {\n        return this.partialField.schema.format;\n    }\n\n    /**\n     * Returns the formatted version of the underlying field data\n     * If data is of type invalid or has missing format use the raw value\n     * @public\n     * @override\n     * @return {Array} Returns the formatted data.\n     */\n    formattedData () {\n        const data = [];\n        const dataFormat = this.format();\n\n        rowDiffsetIterator(this.rowDiffset, (i) => {\n            const datum = this.partialField.data[i];\n            // If value is of invalid type or format is missing\n            if (InvalidAwareTypes.isInvalid(datum) || (!dataFormat && Number.isFinite(datum))) {\n                // Use the invalid map value or the raw value\n                const parsedDatum = InvalidAwareTypes.getInvalidType(datum) || datum;\n                data.push(parsedDatum);\n            } else {\n                data.push(DateTimeFormatter.formatAs(datum, dataFormat));\n            }\n        });\n        return data;\n    }\n\n    static parser() {\n        return new TemporalParser();\n    }\n}\n\n","import FieldParser from '../field-parser';\nimport InvalidAwareTypes from '../../../invalid-aware-types';\n\n/**\n * A FieldParser which parses the binned values.\n *\n * @public\n * @class\n * @implements {FieldParser}\n */\nexport default class BinnedParser extends FieldParser {\n  /**\n   * Parses a single binned value of a field and returns the sanitized value.\n   *\n   * @public\n   * @param {string} val - The value of the field.\n   * @return {string} Returns the sanitized value.\n   */\n    parse (val) {\n        const regex = /^\\s*([+-]?\\d+(?:\\.\\d+)?)\\s*-\\s*([+-]?\\d+(?:\\.\\d+)?)\\s*$/;\n        val = String(val);\n        let result;\n        // check if invalid date value\n        if (!InvalidAwareTypes.isInvalid(val)) {\n            let matched = val.match(regex);\n            result = matched ? `${Number.parseFloat(matched[1])}-${Number.parseFloat(matched[2])}`\n                             : InvalidAwareTypes.NA;\n        } else {\n            result = InvalidAwareTypes.getInvalidType(val);\n        }\n        return result;\n    }\n}\n","import Dimension from '../dimension';\nimport BinnedParser from '../parsers/binned-parser';\n\n/**\n * Represents binned field subtype.\n *\n * @public\n * @class\n * @extends Dimension\n */\nexport default class Binned extends Dimension {\n    /**\n     * Calculates the corresponding field domain.\n     *\n     * @public\n     * @override\n     * @return {Array} Returns the last and first values of bins config array.\n     */\n    calculateDataDomain () {\n        const binsArr = this.partialField.schema.bins;\n        return [binsArr[0], binsArr[binsArr.length - 1]];\n    }\n\n    /**\n     * Returns the bins config provided while creating the field instance.\n     *\n     * @public\n     * @return {Array} Returns the bins array config.\n     */\n    bins () {\n        return this.partialField.schema.bins;\n    }\n\n    static parser() {\n        return new BinnedParser();\n    }\n}\n","import FieldParser from '../field-parser';\nimport InvalidAwareTypes from '../../../invalid-aware-types';\n\n/**\n * A FieldParser which parses the continuous values.\n *\n * @public\n * @class\n * @implements {FieldParser}\n */\nexport default class ContinuousParser extends FieldParser {\n  /**\n   * Parses a single value of a field and returns the number form.\n   *\n   * @public\n   * @param {string|number} val - The value of the field.\n   * @return {string} Returns the number value.\n   */\n    parse (val) {\n        let result;\n        // check if invalid date value\n        if (!InvalidAwareTypes.isInvalid(val)) {\n            let parsedVal = parseFloat(val, 10);\n            result = Number.isNaN(parsedVal) ? InvalidAwareTypes.NA : parsedVal;\n        } else {\n            result = InvalidAwareTypes.getInvalidType(val);\n        }\n        return result;\n    }\n}\n","import { MeasureSubtype } from '../../enums';\nimport Measure from '../measure';\nimport ContinuousParser from '../parsers/continuous-parser';\nimport { calculateContinuousDomain } from '../helper';\n\n/**\n * Represents continuous field subtype.\n *\n * @public\n * @class\n * @extends Measure\n */\nexport default class Continuous extends Measure {\n    /**\n     * Returns the subtype of the field.\n     *\n     * @public\n     * @override\n     * @return {string} Returns the subtype of the field.\n     */\n    subtype () {\n        return MeasureSubtype.CONTINUOUS;\n    }\n\n    /**\n     * Calculates the corresponding field domain.\n     *\n     * @public\n     * @override\n     * @return {Array} Returns the min and max values.\n     */\n    calculateDataDomain () {\n        return calculateContinuousDomain(this.partialField.data, this.rowDiffset);\n    }\n\n    static parser() {\n        return new ContinuousParser();\n    }\n}\n","import Categorical from './categorical';\nimport Temporal from './temporal';\nimport Binned from './binned';\nimport Continuous from './continuous';\nimport { DimensionSubtype, MeasureSubtype } from '../enums';\n\n\nclass FieldTypeRegistry {\n    constructor() {\n        this._fieldType = new Map();\n    }\n\n    registerFieldType(subtype, dimension) {\n        this._fieldType.set(subtype, dimension);\n        return this;\n    }\n\n    has(type) {\n        return this._fieldType.has(type);\n    }\n\n    get(type) {\n        return this._fieldType.get(type);\n    }\n}\n\nconst registerDefaultFields = (store) => {\n    store\n                    .registerFieldType(DimensionSubtype.CATEGORICAL, Categorical)\n                    .registerFieldType(DimensionSubtype.TEMPORAL, Temporal)\n                    .registerFieldType(DimensionSubtype.BINNED, Binned)\n                    .registerFieldType(MeasureSubtype.CONTINUOUS, Continuous);\n};\n\nconst fieldRegistry = (function () {\n    let store = null;\n    function getStore () {\n        store = new FieldTypeRegistry();\n        registerDefaultFields(store);\n        return store;\n    }\n    return store || getStore();\n}());\n\nexport default fieldRegistry;\n\n","import { FieldType, DimensionSubtype, MeasureSubtype } from './enums';\nimport { fieldRegistry } from './fields';\n\n/**\n * Creates a field instance according to the provided data and schema.\n *\n * @param {Array} data - The field data array.\n * @param {Object} schema - The field schema object.\n * @return {Field} Returns the newly created field instance.\n */\nfunction createUnitField(data, schema) {\n    data = data || [];\n\n    if (fieldRegistry.has(schema.subtype)) {\n        return fieldRegistry.get(schema.subtype)\n                        .BUILDER\n                        .fieldName(schema.name)\n                        .schema(schema)\n                        .data(data)\n                        .rowDiffset(`0-${data.length - 1}`)\n                        .build();\n    }\n    return fieldRegistry\n                    .get(schema.type === FieldType.MEASURE ? MeasureSubtype.CONTINUOUS : DimensionSubtype.CATEGORICAL)\n                    .BUILDER\n                    .fieldName(schema.name)\n                    .schema(schema)\n                    .data(data)\n                    .rowDiffset(`0-${data.length - 1}`)\n                    .build();\n}\n\n\n/**\n * Creates a field instance from partialField and rowDiffset.\n *\n * @param {PartialField} partialField - The corresponding partial field.\n * @param {string} rowDiffset - The data subset config.\n * @return {Field} Returns the newly created field instance.\n */\nexport function createUnitFieldFromPartial(partialField, rowDiffset) {\n    const { schema } = partialField;\n\n    if (fieldRegistry.has(schema.subtype)) {\n        return fieldRegistry.get(schema.subtype)\n                        .BUILDER\n                        .partialField(partialField)\n                        .rowDiffset(rowDiffset)\n                        .build();\n    }\n    return fieldRegistry\n                    .get(schema.type === FieldType.MEASURE ? MeasureSubtype.CONTINUOUS : DimensionSubtype.CATEGORICAL)\n                    .BUILDER\n                    .partialField(partialField)\n                    .rowDiffset(rowDiffset)\n                    .build();\n}\n\n/**\n * Creates the field instances with input data and schema.\n *\n * @param {Array} dataColumn - The data array for fields.\n * @param {Array} schema - The schema array for fields.\n * @param {Array} headers - The array of header names.\n * @return {Array.<Field>} Returns an array of newly created field instances.\n */\nexport function createFields(dataColumn, schema, headers) {\n    const headersObj = {};\n\n    if (!(headers && headers.length)) {\n        headers = schema.map(item => item.name);\n    }\n\n    headers.forEach((header, i) => {\n        headersObj[header] = i;\n    });\n\n    return schema.map(item => createUnitField(dataColumn[headersObj[item.name]], item));\n}\n","import { DataFormat } from './enums';\n\nexport default {\n    dataFormat: DataFormat.AUTO\n};\n","/**\n * Interface for all data converters\n */\nexport default class DataConverter {\n    constructor(type) {\n        this._type = type;\n    }\n\n    get type() {\n        return this._type;\n    }\n\n    convert() {\n        throw new Error('Convert method not implemented.');\n    }\n\n}\n","var EOL = {},\n    EOF = {},\n    QUOTE = 34,\n    NEWLINE = 10,\n    RETURN = 13;\n\nfunction objectConverter(columns) {\n  return new Function(\"d\", \"return {\" + columns.map(function(name, i) {\n    return JSON.stringify(name) + \": d[\" + i + \"] || \\\"\\\"\";\n  }).join(\",\") + \"}\");\n}\n\nfunction customConverter(columns, f) {\n  var object = objectConverter(columns);\n  return function(row, i) {\n    return f(object(row), i, columns);\n  };\n}\n\n// Compute unique columns in order of discovery.\nfunction inferColumns(rows) {\n  var columnSet = Object.create(null),\n      columns = [];\n\n  rows.forEach(function(row) {\n    for (var column in row) {\n      if (!(column in columnSet)) {\n        columns.push(columnSet[column] = column);\n      }\n    }\n  });\n\n  return columns;\n}\n\nfunction pad(value, width) {\n  var s = value + \"\", length = s.length;\n  return length < width ? new Array(width - length + 1).join(0) + s : s;\n}\n\nfunction formatYear(year) {\n  return year < 0 ? \"-\" + pad(-year, 6)\n    : year > 9999 ? \"+\" + pad(year, 6)\n    : pad(year, 4);\n}\n\nfunction formatDate(date) {\n  var hours = date.getUTCHours(),\n      minutes = date.getUTCMinutes(),\n      seconds = date.getUTCSeconds(),\n      milliseconds = date.getUTCMilliseconds();\n  return isNaN(date) ? \"Invalid Date\"\n      : formatYear(date.getUTCFullYear(), 4) + \"-\" + pad(date.getUTCMonth() + 1, 2) + \"-\" + pad(date.getUTCDate(), 2)\n      + (milliseconds ? \"T\" + pad(hours, 2) + \":\" + pad(minutes, 2) + \":\" + pad(seconds, 2) + \".\" + pad(milliseconds, 3) + \"Z\"\n      : seconds ? \"T\" + pad(hours, 2) + \":\" + pad(minutes, 2) + \":\" + pad(seconds, 2) + \"Z\"\n      : minutes || hours ? \"T\" + pad(hours, 2) + \":\" + pad(minutes, 2) + \"Z\"\n      : \"\");\n}\n\nexport default function(delimiter) {\n  var reFormat = new RegExp(\"[\\\"\" + delimiter + \"\\n\\r]\"),\n      DELIMITER = delimiter.charCodeAt(0);\n\n  function parse(text, f) {\n    var convert, columns, rows = parseRows(text, function(row, i) {\n      if (convert) return convert(row, i - 1);\n      columns = row, convert = f ? customConverter(row, f) : objectConverter(row);\n    });\n    rows.columns = columns || [];\n    return rows;\n  }\n\n  function parseRows(text, f) {\n    var rows = [], // output rows\n        N = text.length,\n        I = 0, // current character index\n        n = 0, // current line number\n        t, // current token\n        eof = N <= 0, // current token followed by EOF?\n        eol = false; // current token followed by EOL?\n\n    // Strip the trailing newline.\n    if (text.charCodeAt(N - 1) === NEWLINE) --N;\n    if (text.charCodeAt(N - 1) === RETURN) --N;\n\n    function token() {\n      if (eof) return EOF;\n      if (eol) return eol = false, EOL;\n\n      // Unescape quotes.\n      var i, j = I, c;\n      if (text.charCodeAt(j) === QUOTE) {\n        while (I++ < N && text.charCodeAt(I) !== QUOTE || text.charCodeAt(++I) === QUOTE);\n        if ((i = I) >= N) eof = true;\n        else if ((c = text.charCodeAt(I++)) === NEWLINE) eol = true;\n        else if (c === RETURN) { eol = true; if (text.charCodeAt(I) === NEWLINE) ++I; }\n        return text.slice(j + 1, i - 1).replace(/\"\"/g, \"\\\"\");\n      }\n\n      // Find next delimiter or newline.\n      while (I < N) {\n        if ((c = text.charCodeAt(i = I++)) === NEWLINE) eol = true;\n        else if (c === RETURN) { eol = true; if (text.charCodeAt(I) === NEWLINE) ++I; }\n        else if (c !== DELIMITER) continue;\n        return text.slice(j, i);\n      }\n\n      // Return last token before EOF.\n      return eof = true, text.slice(j, N);\n    }\n\n    while ((t = token()) !== EOF) {\n      var row = [];\n      while (t !== EOL && t !== EOF) row.push(t), t = token();\n      if (f && (row = f(row, n++)) == null) continue;\n      rows.push(row);\n    }\n\n    return rows;\n  }\n\n  function preformatBody(rows, columns) {\n    return rows.map(function(row) {\n      return columns.map(function(column) {\n        return formatValue(row[column]);\n      }).join(delimiter);\n    });\n  }\n\n  function format(rows, columns) {\n    if (columns == null) columns = inferColumns(rows);\n    return [columns.map(formatValue).join(delimiter)].concat(preformatBody(rows, columns)).join(\"\\n\");\n  }\n\n  function formatBody(rows, columns) {\n    if (columns == null) columns = inferColumns(rows);\n    return preformatBody(rows, columns).join(\"\\n\");\n  }\n\n  function formatRows(rows) {\n    return rows.map(formatRow).join(\"\\n\");\n  }\n\n  function formatRow(row) {\n    return row.map(formatValue).join(delimiter);\n  }\n\n  function formatValue(value) {\n    return value == null ? \"\"\n        : value instanceof Date ? formatDate(value)\n        : reFormat.test(value += \"\") ? \"\\\"\" + value.replace(/\"/g, \"\\\"\\\"\") + \"\\\"\"\n        : value;\n  }\n\n  return {\n    parse: parse,\n    parseRows: parseRows,\n    format: format,\n    formatBody: formatBody,\n    formatRows: formatRows,\n    formatRow: formatRow,\n    formatValue: formatValue\n  };\n}\n","import { columnMajor } from '../../utils';\n\n/**\n * Parses and converts data formatted in DSV array to a manageable internal format.\n *\n * @param {Array.<Array>} arr - A 2D array containing of the DSV data.\n * @param {Object} options - Option to control the behaviour of the parsing.\n * @param {boolean} [options.firstRowHeader=true] - Whether the first row of the dsv data is header or not.\n * @return {Array} Returns an array of headers and column major data.\n * @example\n *\n * // Sample input data:\n * const data = [\n *    [\"a\", \"b\", \"c\"],\n *    [1, 2, 3],\n *    [4, 5, 6],\n *    [7, 8, 9]\n * ];\n */\nfunction DSVArr(arr, schema, options) {\n    if (!Array.isArray(schema)) {\n        throw new Error('Schema missing or is in an unsupported format');\n    }\n    const defaultOption = {\n        firstRowHeader: true,\n    };\n    const schemaFields = schema.map(unitSchema => unitSchema.name);\n    options = Object.assign({}, defaultOption, options);\n\n    const columns = [];\n    const push = columnMajor(columns);\n\n    let headers = schemaFields;\n    if (options.firstRowHeader) {\n        // If header present then remove the first header row.\n        // Do in-place mutation to save space.\n        headers = arr.splice(0, 1)[0];\n    }\n    // create a map of the headers\n    const headerMap = headers.reduce((acc, h, i) => (\n        Object.assign(acc, { [h]: i })\n    ), {});\n\n    arr.forEach((fields) => {\n        const field = [];\n        schemaFields.forEach((schemaField) => {\n            const headIndex = headerMap[schemaField];\n            field.push(fields[headIndex]);\n        });\n        return push(...field);\n    });\n    return [schemaFields, columns];\n}\n\nexport default DSVArr;\n","import { dsvFormat as d3Dsv } from 'd3-dsv';\nimport DSVArr from './dsv-arr';\n\n/**\n * Parses and converts data formatted in DSV string to a manageable internal format.\n *\n * @todo Support to be given for https://tools.ietf.org/html/rfc4180.\n * @todo Sample implementation https://github.com/knrz/CSV.js/.\n *\n * @param {string} str - The input DSV string.\n * @param {Object} options - Option to control the behaviour of the parsing.\n * @param {boolean} [options.firstRowHeader=true] - Whether the first row of the dsv string data is header or not.\n * @param {string} [options.fieldSeparator=\",\"] - The separator of two consecutive field.\n * @return {Array} Returns an array of headers and column major data.\n * @example\n *\n * // Sample input data:\n * const data = `\n * a,b,c\n * 1,2,3\n * 4,5,6\n * 7,8,9\n * `\n */\nfunction DSVStr (str, schema, options) {\n    const defaultOption = {\n        firstRowHeader: true,\n        fieldSeparator: ','\n    };\n    options = Object.assign({}, defaultOption, options);\n\n    const dsv = d3Dsv(options.fieldSeparator);\n    return DSVArr(dsv.parseRows(str), schema, options);\n}\n\nexport default DSVStr;\n","import DataConverter from '../model/dataConverter';\nimport DSVStr from '../utils/dsv-str';\nimport DataFormat from '../../enums/data-format';\n\nexport default class DSVStringConverter extends DataConverter {\n    constructor() {\n        super(DataFormat.DSV_STR);\n    }\n\n    convert(data, schema, options) {\n        return DSVStr(data, schema, options);\n    }\n}\n","import { columnMajor } from '../../utils';\n\n/**\n * Parses and converts data formatted in JSON to a manageable internal format.\n *\n * @param {Array.<Object>} arr - The input data formatted in JSON.\n * @return {Array.<Object>} Returns an array of headers and column major data.\n * @example\n *\n * // Sample input data:\n * const data = [\n *    {\n *      \"a\": 1,\n *      \"b\": 2,\n *      \"c\": 3\n *    },\n *    {\n *      \"a\": 4,\n *      \"b\": 5,\n *      \"c\": 6\n *    },\n *    {\n *      \"a\": 7,\n *      \"b\": 8,\n *      \"c\": 9\n *    }\n * ];\n */\nfunction FlatJSON (arr, schema) {\n    if (!Array.isArray(schema)) {\n        throw new Error('Schema missing or is in an unsupported format');\n    }\n\n    const header = {};\n    let i = 0;\n    let insertionIndex;\n    const columns = [];\n    const push = columnMajor(columns);\n    const schemaFieldsName = schema.map(unitSchema => unitSchema.name);\n\n    arr.forEach((item) => {\n        const fields = [];\n        schemaFieldsName.forEach((unitSchema) => {\n            if (unitSchema in header) {\n                insertionIndex = header[unitSchema];\n            } else {\n                header[unitSchema] = i++;\n                insertionIndex = i - 1;\n            }\n            fields[insertionIndex] = item[unitSchema];\n        });\n        push(...fields);\n    });\n\n    return [Object.keys(header), columns];\n}\n\nexport default FlatJSON;\n","import DataConverter from '../model/dataConverter';\nimport FlatJSON from '../utils/flat-json';\nimport DataFormat from '../../enums/data-format';\n\nexport default class JSONConverter extends DataConverter {\n    constructor() {\n        super(DataFormat.FLAT_JSON);\n    }\n\n    convert(data, schema, options) {\n        return FlatJSON(data, schema, options);\n    }\n}\n","import DataConverter from '../model/dataConverter';\nimport DSVArr from '../utils/dsv-arr';\nimport DataFormat from '../../enums/data-format';\n\nexport default class DSVArrayConverter extends DataConverter {\n    constructor() {\n        super(DataFormat.DSV_ARR);\n    }\n\n    convert(data, schema, options) {\n        return DSVArr(data, schema, options);\n    }\n}\n","import FlatJSON from './flat-json';\nimport DSVArr from './dsv-arr';\nimport DSVStr from './dsv-str';\nimport { detectDataFormat } from '../../utils';\n\n/**\n * Parses the input data and detect the format automatically.\n *\n * @param {string|Array} data - The input data.\n * @param {Object} options - An optional config specific to data format.\n * @return {Array.<Object>} Returns an array of headers and column major data.\n */\nfunction Auto (data, schema, options) {\n    const converters = { FlatJSON, DSVStr, DSVArr };\n    const dataFormat = detectDataFormat(data);\n\n    if (!dataFormat) {\n        throw new Error('Couldn\\'t detect the data format');\n    }\n\n    return converters[dataFormat](data, schema, options);\n}\n\nexport default Auto;\n","import DataConverter from '../model/dataConverter';\nimport AUTO from '../utils/auto-resolver';\nimport DataFormat from '../../enums/data-format';\n\nexport default class AutoDataConverter extends DataConverter {\n    constructor() {\n        super(DataFormat.AUTO);\n    }\n\n    convert(data, schema, options) {\n        return AUTO(data, schema, options);\n    }\n}\n","import DataConverter from './model/dataConverter';\nimport { DSVStringConverter, DSVArrayConverter, JSONConverter, AutoDataConverter } from './defaultConverters';\n\nclass DataConverterStore {\n    constructor() {\n        this.store = new Map();\n        this.converters(this._getDefaultConverters());\n    }\n\n    _getDefaultConverters() {\n        return [\n            new DSVStringConverter(),\n            new DSVArrayConverter(),\n            new JSONConverter(),\n            new AutoDataConverter()\n        ];\n    }\n\n    /**\n     * Sets the given converters in the store and returns the store\n     * @param  {Array<DataConverter>} converters : contains array of converter instance\n     * @return { Map<String,DataConverter> }\n     */\n    converters(converters = []) {\n        converters.forEach(converter => this.store.set(converter.type, converter));\n        return this.store;\n    }\n\n    /**\n     * Registers a Converter of type DataConverter\n     * @param {DataConverter} converter : converter Instance\n     * @returns self\n     */\n    register(converter) {\n        if (converter instanceof DataConverter) {\n            this.store.set(converter.type, converter);\n            return this;\n        }\n        return null;\n    }\n\n    /**\n     * Rempves a converter from store\n     * @param {DataConverter} converter : converter Instance\n     * @returns self\n     */\n\n    unregister(converter) {\n        this.store.delete(converter.type);\n        return this;\n    }\n\n    get(name) {\n        if (this.store.has(name)) {\n            return this.store.get(name);\n        }\n        return null;\n    }\n\n}\n\nconst converterStore = (function () {\n    let store = null;\n\n    function getStore () {\n        store = new DataConverterStore();\n        return store;\n    }\n    return store || getStore();\n}());\n\nexport default converterStore;\n","import { FieldType, FilteringMode, DimensionSubtype, MeasureSubtype, DataFormat } from './enums';\nimport fieldStore from './field-store';\nimport Value from './value';\nimport {\n    rowDiffsetIterator\n} from './operator';\nimport { DM_DERIVATIVES, LOGICAL_OPERATORS, ROW_ID } from './constants';\nimport { createFields, createUnitFieldFromPartial } from './field-creator';\nimport defaultConfig from './default-config';\nimport { converterStore } from './converter';\nimport { fieldRegistry } from './fields';\nimport { extend2, detectDataFormat } from './utils';\n\n/**\n * Prepares the selection data.\n */\nfunction prepareSelectionData (fields, formattedData, rawData, i) {\n    const resp = {};\n\n    for (const [key, field] of fields.entries()) {\n        resp[field.name()] = new Value(formattedData[key][i], rawData[key][i], field);\n    }\n    return resp;\n}\n\nexport function prepareJoinData (fields) {\n    const resp = {};\n\n    for (const key in fields) {\n        resp[key] = new Value(fields[key].formattedValue, fields[key].rawValue, key);\n    }\n    return resp;\n}\n\nexport const updateFields = ([rowDiffset, colIdentifier], partialFieldspace, fieldStoreName) => {\n    let collID = colIdentifier.length ? colIdentifier.split(',') : [];\n    let partialFieldMap = partialFieldspace.fieldsObj();\n    let newFields = collID.map(coll => createUnitFieldFromPartial(partialFieldMap[coll].partialField, rowDiffset));\n    return fieldStore.createNamespace(newFields, fieldStoreName);\n};\n\nexport const persistCurrentDerivation = (model, operation, config = {}, criteriaFn) => {\n    if (operation === DM_DERIVATIVES.COMPOSE) {\n        model._derivation.length = 0;\n        model._derivation.push(...criteriaFn);\n    } else {\n        model._derivation.push({\n            op: operation,\n            meta: config,\n            criteria: criteriaFn\n        });\n    }\n};\nexport const persistAncestorDerivation = (sourceDm, newDm) => {\n    newDm._ancestorDerivation.push(...sourceDm._ancestorDerivation, ...sourceDm._derivation);\n};\n\nexport const persistDerivations = (sourceDm, model, operation, config = {}, criteriaFn) => {\n    persistCurrentDerivation(model, operation, config, criteriaFn);\n    persistAncestorDerivation(sourceDm, model);\n};\n\nconst selectModeMap = {\n    [FilteringMode.NORMAL]: {\n        diffIndex: ['rowDiffset'],\n        calcDiff: [true, false]\n    },\n    [FilteringMode.INVERSE]: {\n        diffIndex: ['rejectRowDiffset'],\n        calcDiff: [false, true]\n    },\n    [FilteringMode.ALL]: {\n        diffIndex: ['rowDiffset', 'rejectRowDiffset'],\n        calcDiff: [true, true]\n    }\n};\n\nconst generateRowDiffset = (rowDiffset, i, lastInsertedValue) => {\n    if (lastInsertedValue !== -1 && i === (lastInsertedValue + 1)) {\n        const li = rowDiffset.length - 1;\n\n        rowDiffset[li] = `${rowDiffset[li].split('-')[0]}-${i}`;\n    } else {\n        rowDiffset.push(`${i}`);\n    }\n};\n\nexport const selectRowDiffsetIterator = (rowDiffset, checker, mode) => {\n    let lastInsertedValueSel = -1;\n    let lastInsertedValueRej = -1;\n    const newRowDiffSet = [];\n    const rejRowDiffSet = [];\n\n    const [shouldSelect, shouldReject] = selectModeMap[mode].calcDiff;\n\n    rowDiffsetIterator(rowDiffset, (i) => {\n        const checkerResult = checker(i);\n        checkerResult && shouldSelect && generateRowDiffset(newRowDiffSet, i, lastInsertedValueSel);\n        !checkerResult && shouldReject && generateRowDiffset(rejRowDiffSet, i, lastInsertedValueRej);\n    });\n    return {\n        rowDiffset: newRowDiffSet.join(','),\n        rejectRowDiffset: rejRowDiffSet.join(',')\n    };\n};\n\n\nexport const rowSplitDiffsetIterator = (rowDiffset, checker, mode, dimensionArr, fieldStoreObj) => {\n    let lastInsertedValue = {};\n    const splitRowDiffset = {};\n    const dimensionMap = {};\n\n    rowDiffsetIterator(rowDiffset, (i) => {\n        if (checker(i)) {\n            let hash = '';\n\n            let dimensionSet = { keys: {} };\n\n            dimensionArr.forEach((_) => {\n                const data = fieldStoreObj[_].partialField.data[i];\n                hash = `${hash}-${data}`;\n                dimensionSet.keys[_] = data;\n            });\n\n            if (splitRowDiffset[hash] === undefined) {\n                splitRowDiffset[hash] = [];\n                lastInsertedValue[hash] = -1;\n                dimensionMap[hash] = dimensionSet;\n            }\n\n            generateRowDiffset(splitRowDiffset[hash], i, lastInsertedValue[hash]);\n            lastInsertedValue[hash] = i;\n        }\n    });\n\n    return {\n        splitRowDiffset,\n        dimensionMap\n    };\n};\n\n\nexport const selectHelper = (clonedDm, selectFn, config, sourceDm, iterator) => {\n    let cachedStore = {};\n    let cloneProvider = () => sourceDm.detachedRoot();\n    const { mode } = config;\n    const rowDiffset = clonedDm._rowDiffset;\n    const cachedValueObjects = clonedDm._partialFieldspace._cachedValueObjects;\n\n    const selectorHelperFn = index => selectFn(\n        cachedValueObjects[index],\n        index,\n        cloneProvider,\n        cachedStore\n    );\n\n    return iterator(rowDiffset, selectorHelperFn, mode);\n};\n\nexport const cloneWithAllFields = (model) => {\n    const clonedDm = model.clone(false);\n    const partialFieldspace = model.getPartialFieldspace();\n    clonedDm._colIdentifier = partialFieldspace.fields.map(f => f.name()).join(',');\n\n    // flush out cached namespace values on addition of new fields\n    partialFieldspace._cachedFieldsObj = null;\n    partialFieldspace._cachedDimension = null;\n    partialFieldspace._cachedMeasure = null;\n    clonedDm.__calculateFieldspace().calculateFieldsConfig();\n\n    return clonedDm;\n};\n\nconst getKey = (arr, data, fn, rowId) => {\n    let key = fn(arr, data, 0, rowId);\n\n    for (let i = 1, len = arr.length; i < len; i++) {\n        key = `${key},${fn(arr, data, i, rowId)}`;\n    }\n    return key;\n};\n\nconst keyFn = (arr, fields, idx, rowId) => {\n    const field = arr[idx];\n    const val = field === ROW_ID ? rowId : fields[field].internalValue;\n    return val;\n};\n\nconst domainChecker = (val, domain) => {\n    const domainArr = domain[0] instanceof Array ? domain : [domain];\n    return domainArr.some(dom => val >= dom[0] && val <= dom[1]);\n};\n\nconst boundsChecker = {\n    [MeasureSubtype.CONTINUOUS]: domainChecker,\n    [DimensionSubtype.TEMPORAL]: domainChecker\n};\n\nconst isWithinDomain = (value, domain, fieldType) => boundsChecker[fieldType](value, domain);\n\nexport const filterPropagationModel = (model, propModels, config = {}) => {\n    let fns = [];\n    const operation = config.operation || LOGICAL_OPERATORS.AND;\n    const { filterByDim = true, filterByMeasure = false, clone = true } = config;\n    const clonedModel = clone ? cloneWithAllFields(model) : model;\n    const modelFieldsConfig = clonedModel.getFieldsConfig();\n\n    if (!propModels.length) {\n        fns = [() => false];\n    } else {\n        fns = propModels.map(propModel => (({ criteria = {} }) => {\n            const { identifiers = [[], []], range } = criteria;\n            let [fieldNames = [], values = []] = identifiers;\n            const indices = fieldNames.reduce((map, name, i) => {\n                map[name] = i;\n                return map;\n            }, {});\n            fieldNames = fieldNames.filter(field => (field in modelFieldsConfig &&\n                modelFieldsConfig[field].def.type === FieldType.DIMENSION) || field === ROW_ID);\n            const dLen = fieldNames.length;\n            const valuesMap = {};\n\n            if (dLen) {\n                for (let i = 1, len = identifiers.length; i < len; i++) {\n                    const row = identifiers[i];\n                    const key = `${fieldNames.map((field) => {\n                        const idx = indices[field];\n                        return row[idx];\n                    })}`;\n                    valuesMap[key] = 1;\n                }\n            }\n            let rangeKeys = Object.keys(range || {}).filter(field => field in modelFieldsConfig);\n            const hasData = values.length || rangeKeys.length;\n\n            if (!filterByMeasure) {\n                rangeKeys = rangeKeys.filter(field => modelFieldsConfig[field].def.type !== FieldType.MEASURE);\n            }\n\n            if (!filterByDim) {\n                rangeKeys = rangeKeys.filter(field => modelFieldsConfig[field].def.type !== FieldType.DIMENSION);\n            }\n\n            return hasData ? (fields, i) => {\n                let present = true;\n                if (filterByDim) {\n                    present = dLen ? valuesMap[getKey(fieldNames, fields, keyFn, i)] : true;\n                }\n\n                return rangeKeys.every((field) => {\n                    const val = fields[field].internalValue;\n                    return isWithinDomain(val, range[field], modelFieldsConfig[field].def.subtype);\n                }) && present;\n            } : () => false;\n        })(propModel));\n    }\n\n    let filteredModel;\n    if (operation === LOGICAL_OPERATORS.AND) {\n        filteredModel = clonedModel.select((fields, i) => fns.every(fn => fn(fields, i)), {\n            saveChild: false\n        });\n    } else {\n        filteredModel = clonedModel.select((fields, i) => fns.some(fn => fn(fields, i)), {\n            saveChild: false\n        });\n    }\n\n    return filteredModel;\n};\n\n\nexport const splitWithSelect = (sourceDm, dimensionArr, reducerFn = val => val, config) => {\n    const {\n        saveChild,\n    } = config;\n    const fieldStoreObj = sourceDm.getFieldspace().fieldsObj();\n\n    const {\n        splitRowDiffset,\n        dimensionMap\n    } = selectHelper(\n        sourceDm.clone(saveChild),\n        reducerFn,\n        config,\n        sourceDm,\n        (...params) => rowSplitDiffsetIterator(...params, dimensionArr, fieldStoreObj)\n        );\n\n    const clonedDMs = [];\n    Object.keys(splitRowDiffset).sort().forEach((e) => {\n        if (splitRowDiffset[e]) {\n            const cloned = sourceDm.clone(saveChild);\n            const derivation = dimensionMap[e];\n            cloned._rowDiffset = splitRowDiffset[e].join(',');\n            cloned.__calculateFieldspace().calculateFieldsConfig();\n\n            const derivationFormula = fields => dimensionArr.every(_ => fields[_].internalValue === derivation.keys[_]);\n            // Store reference to child model and selector function\n            if (saveChild) {\n                persistDerivations(sourceDm, cloned, DM_DERIVATIVES.SELECT, config, derivationFormula);\n            }\n            cloned._derivation[cloned._derivation.length - 1].meta = dimensionMap[e];\n\n            clonedDMs.push(cloned);\n        }\n    });\n\n\n    return clonedDMs;\n};\nexport const addDiffsetToClonedDm = (clonedDm, rowDiffset, sourceDm, selectConfig, selectFn) => {\n    clonedDm._rowDiffset = rowDiffset;\n    clonedDm.__calculateFieldspace().calculateFieldsConfig();\n    persistDerivations(\n        sourceDm,\n        clonedDm,\n        DM_DERIVATIVES.SELECT,\n         { config: selectConfig },\n          selectFn\n    );\n};\n\n\nexport const cloneWithSelect = (sourceDm, selectFn, selectConfig, cloneConfig) => {\n    let extraCloneDm = {};\n\n    let { mode } = selectConfig;\n\n    const cloned = sourceDm.clone(cloneConfig.saveChild);\n    const setOfRowDiffsets = selectHelper(\n        cloned,\n        selectFn,\n        selectConfig,\n        sourceDm,\n        selectRowDiffsetIterator\n    );\n    const diffIndex = selectModeMap[mode].diffIndex;\n\n    addDiffsetToClonedDm(cloned, setOfRowDiffsets[diffIndex[0]], sourceDm, selectConfig, selectFn);\n\n    if (diffIndex.length > 1) {\n        extraCloneDm = sourceDm.clone(cloneConfig.saveChild);\n        addDiffsetToClonedDm(extraCloneDm, setOfRowDiffsets[diffIndex[1]], sourceDm, selectConfig, selectFn);\n        return [cloned, extraCloneDm];\n    }\n\n    return cloned;\n};\n\nexport const cloneWithProject = (sourceDm, projField, config, allFields) => {\n    const cloned = sourceDm.clone(config.saveChild);\n    let projectionSet = projField;\n    if (config.mode === FilteringMode.INVERSE) {\n        projectionSet = allFields.filter(fieldName => projField.indexOf(fieldName) === -1);\n    }\n    // cloned._colIdentifier = sourceDm._colIdentifier.split(',')\n    //                         .filter(coll => projectionSet.indexOf(coll) !== -1).join();\n    cloned._colIdentifier = projectionSet.join(',');\n    cloned.__calculateFieldspace().calculateFieldsConfig();\n\n    persistDerivations(\n        sourceDm,\n        cloned,\n        DM_DERIVATIVES.PROJECT,\n        { projField, config, actualProjField: projectionSet },\n        null\n    );\n\n    return cloned;\n};\n\n\nexport const splitWithProject = (sourceDm, projFieldSet, config, allFields) =>\n    projFieldSet.map(projFields =>\n        cloneWithProject(sourceDm, projFields, config, allFields));\n\nexport const sanitizeUnitSchema = (unitSchema) => {\n    // Do deep clone of the unit schema as the user might change it later.\n    unitSchema = extend2({}, unitSchema);\n    if (!unitSchema.type) {\n        unitSchema.type = FieldType.DIMENSION;\n    }\n\n    if (!unitSchema.subtype) {\n        switch (unitSchema.type) {\n        case FieldType.MEASURE:\n            unitSchema.subtype = MeasureSubtype.CONTINUOUS;\n            break;\n        default:\n        case FieldType.DIMENSION:\n            unitSchema.subtype = DimensionSubtype.CATEGORICAL;\n            break;\n        }\n    }\n\n    return unitSchema;\n};\n\nexport const validateUnitSchema = (unitSchema) => {\n    const { type, subtype, name } = unitSchema;\n    if (type === FieldType.DIMENSION || type === FieldType.MEASURE) {\n        if (!fieldRegistry.has(subtype)) {\n            throw new Error(`DataModel doesn't support measure field subtype ${subtype} used for ${name} field`);\n        }\n    } else {\n        throw new Error(`DataModel doesn't support field type ${type} used for ${name} field`);\n    }\n};\n\nexport const sanitizeAndValidateSchema = schema => schema.map((unitSchema) => {\n    unitSchema = sanitizeUnitSchema(unitSchema);\n    validateUnitSchema(unitSchema);\n    return unitSchema;\n});\n\nexport const resolveFieldName = (schema, dataHeader) => {\n    schema.forEach((unitSchema) => {\n        const fieldNameAs = unitSchema.as;\n        if (!fieldNameAs) { return; }\n\n        const idx = dataHeader.indexOf(unitSchema.name);\n        dataHeader[idx] = fieldNameAs;\n        unitSchema.name = fieldNameAs;\n        delete unitSchema.as;\n    });\n};\n\nexport const updateData = (relation, data, schema, options) => {\n    schema = sanitizeAndValidateSchema(schema);\n    options = Object.assign(Object.assign({}, defaultConfig), options);\n    const converter = converterStore.get(options.dataFormat);\n\n\n    if (!converter) {\n        throw new Error(`No converter function found for ${options.dataFormat} format`);\n    }\n\n    const [header, formattedData] = converter.convert(data, schema, options);\n    resolveFieldName(schema, header);\n    const fieldArr = createFields(formattedData, schema, header);\n\n    // This will create a new fieldStore with the fields\n    const nameSpace = fieldStore.createNamespace(fieldArr, options.name);\n    relation._partialFieldspace = nameSpace;\n\n    // If data is provided create the default colIdentifier and rowDiffset\n    relation._rowDiffset = formattedData.length && formattedData[0].length ? `0-${formattedData[0].length - 1}` : '';\n\n    // This stores the value objects which is passed to the filter method when selection operation is done.\n    const valueObjects = [];\n    const { fields } = nameSpace;\n    const rawFieldsData = fields.map(field => field.data());\n    const formattedFieldsData = fields.map(field => field.formattedData());\n    rowDiffsetIterator(relation._rowDiffset, (i) => {\n        valueObjects[i] = prepareSelectionData(fields, formattedFieldsData, rawFieldsData, i);\n    });\n    nameSpace._cachedValueObjects = valueObjects;\n\n    relation._colIdentifier = (schema.map(_ => _.name)).join();\n    relation._dataFormat = options.dataFormat === DataFormat.AUTO ? detectDataFormat(data) : options.dataFormat;\n    return relation;\n};\n\nexport const fieldInSchema = (schema, field) => {\n    let i = 0;\n\n    for (; i < schema.length; ++i) {\n        if (field === schema[i].name) {\n            return {\n                name: field,\n                type: schema[i].subtype || schema[i].type,\n                index: i,\n            };\n        }\n    }\n    return null;\n};\n\nexport const getDerivationArguments = (derivation) => {\n    let params = [];\n    let operation;\n    operation = derivation.op;\n    switch (operation) {\n    case DM_DERIVATIVES.SELECT:\n        params = [derivation.criteria];\n        break;\n    case DM_DERIVATIVES.PROJECT:\n        params = [derivation.meta.actualProjField];\n        break;\n    case DM_DERIVATIVES.SORT:\n        params = [derivation.criteria];\n        break;\n    case DM_DERIVATIVES.GROUPBY:\n        operation = 'groupBy';\n        params = [derivation.meta.groupByString.split(','), derivation.criteria];\n        break;\n    default:\n        operation = null;\n    }\n\n    return {\n        operation,\n        params\n    };\n};\n\nconst applyExistingOperationOnModel = (propModel, dataModel) => {\n    const derivations = dataModel.getDerivations();\n    let selectionModel = propModel;\n\n    derivations.forEach((derivation) => {\n        if (!derivation) {\n            return;\n        }\n\n        const { operation, params } = getDerivationArguments(derivation);\n        if (operation) {\n            selectionModel = selectionModel[operation](...params, {\n                saveChild: false\n            });\n        }\n    });\n\n    return selectionModel;\n};\n\nconst getFilteredModel = (propModel, path) => {\n    for (let i = 0, len = path.length; i < len; i++) {\n        const model = path[i];\n        propModel = applyExistingOperationOnModel(propModel, model);\n    }\n    return propModel;\n};\n\nconst propagateIdentifiers = (dataModel, propModel, config = {}, propModelInf = {}) => {\n    const excludeModels = propModelInf.excludeModels || [];\n    const criterias = propModelInf.criteria;\n\n    const propagate = excludeModels.length ? excludeModels.indexOf(dataModel) === -1 : true;\n\n    propagate && dataModel.handlePropagation(propModel, config);\n\n    const children = dataModel._children;\n    children.forEach((child) => {\n        const matchingCriteria = criterias.filter(val => val.groupedModel === child);\n        let selectionModel = applyExistingOperationOnModel(propModel, child);\n\n        if (matchingCriteria.length) {\n            selectionModel = filterPropagationModel(selectionModel, matchingCriteria, {\n                filterByDim: false,\n                filterByMeasure: true,\n                clone: false\n            });\n        }\n        propagateIdentifiers(child, selectionModel, config, propModelInf);\n    });\n};\n\nexport const getRootGroupByModel = (model) => {\n    while (model._parent && model._derivation.find(d => d.op !== DM_DERIVATIVES.GROUPBY)) {\n        model = model._parent;\n    }\n    return model;\n};\n\nexport const getRootDataModel = (model) => {\n    while (model._parent) {\n        model = model._parent;\n    }\n    return model;\n};\n\nexport const getPathToRootModel = (model, path = []) => {\n    while (model._parent) {\n        path.push(model);\n        model = model._parent;\n    }\n    return path;\n};\n\nexport const propagateToAllDataModels = (identifiers, rootModels, propagationInf, config) => {\n    let criteria;\n    const { propagationNameSpace, propagateToSource } = propagationInf;\n    const propagationSourceId = propagationInf.sourceId;\n    const filterFn = (entry) => {\n        const filter = config.filterFn || (() => true);\n        return filter(entry, config);\n    };\n\n    const addGroupedModel = ({ config: conf, model }) => {\n        const { criteria: crit } = conf;\n        let groupedModel;\n\n        if (crit !== null && crit.fields.some(d => d.type === FieldType.MEASURE)) {\n            groupedModel = getRootGroupByModel(model);\n        }\n        return Object.assign({}, conf, {\n            groupedModel\n        });\n    };\n\n    let criterias = [];\n\n    if (identifiers === null) {\n        criterias = [{\n            criteria: []\n        }];\n        criteria = [];\n    } else {\n        let actionCriterias = Object.values(propagationNameSpace.mutableActions);\n        if (propagateToSource !== false) {\n            actionCriterias = actionCriterias.filter(d => d.config.sourceId !== propagationSourceId);\n        }\n\n        const filteredCriteria = actionCriterias.filter(filterFn);\n\n        const excludeModels = [];\n\n        if (propagateToSource !== false) {\n            const sourceActionCriterias = Object.values(propagationNameSpace.mutableActions);\n\n            sourceActionCriterias.forEach((actionInf) => {\n                const actionConf = actionInf.config;\n                if (actionConf.applyOnSource === false && actionConf.action === config.action &&\n                        actionConf.sourceId !== propagationSourceId) {\n                    excludeModels.push(actionInf.model);\n                    criteria = sourceActionCriterias.filter(d => d !== actionInf).map(addGroupedModel);\n                    criteria.length && criterias.push({\n                        criteria,\n                        models: actionInf.model,\n                        path: getPathToRootModel(actionInf.model)\n                    });\n                }\n            });\n        }\n\n\n        criteria = [].concat(...[...filteredCriteria.map(addGroupedModel), {\n            criteria: identifiers,\n            groupedModel: identifiers !== null && identifiers.fields.some(d => d.type === FieldType.MEASURE) ?\n                getRootGroupByModel(propagationInf.propagationSource) : null\n        }]).filter(d => d !== null);\n        criterias.push({\n            criteria,\n            excludeModels: [...excludeModels, ...config.excludeModels || []]\n        });\n    }\n\n    const rootModel = rootModels.model;\n\n    const propConfig = Object.assign({\n        sourceIdentifiers: identifiers,\n        propagationSourceId\n    }, config);\n\n    criterias.forEach((inf) => {\n        const { criteria: crit } = inf;\n        const propagationModel = filterPropagationModel(rootModel, crit, {\n            filterByMeasure: !!crit.find(d => d.groupedModel === rootModel)\n        });\n        const path = inf.path;\n\n        if (path) {\n            const filteredModel = getFilteredModel(propagationModel, path.reverse());\n            inf.models.handlePropagation(filteredModel, propConfig);\n        } else {\n            propagateIdentifiers(rootModel, propagationModel, propConfig, {\n                excludeModels: inf.excludeModels,\n                criteria: crit\n            });\n        }\n    });\n};\n\nexport const propagateImmutableActions = (propagationNameSpace, rootModel, propagationInf) => {\n    const immutableActions = propagationNameSpace.immutableActions;\n\n    for (const action in immutableActions) {\n        const actionInf = immutableActions[action];\n        const actionConf = actionInf.config;\n        const propagationSourceId = propagationInf.config.sourceId;\n        const filterImmutableAction = propagationInf.propConfig.filterImmutableAction ?\n            propagationInf.propConfig.filterImmutableAction(actionConf, propagationInf.config) : true;\n        if (actionConf.sourceId !== propagationSourceId && filterImmutableAction) {\n            const criteriaModel = actionConf.criteria;\n            propagateToAllDataModels(criteriaModel, {\n                model: rootModel,\n                groupByModel: getRootGroupByModel(actionInf.model)\n            }, {\n                propagationNameSpace,\n                propagateToSource: false,\n                sourceId: propagationSourceId,\n                propagationSource: actionInf.model\n            }, actionConf);\n        }\n    }\n};\n\nexport const addToPropNamespace = (propagationNameSpace, config = {}, model) => {\n    let sourceNamespace;\n    const isMutableAction = config.isMutableAction;\n    const criteria = config.criteria;\n    const key = `${config.action}-${config.sourceId}`;\n\n    if (isMutableAction) {\n        sourceNamespace = propagationNameSpace.mutableActions;\n    } else {\n        sourceNamespace = propagationNameSpace.immutableActions;\n    }\n\n    if (criteria === null) {\n        delete sourceNamespace[key];\n    } else {\n        sourceNamespace[key] = {\n            model,\n            config\n        };\n    }\n\n    return this;\n};\n\n\nexport const getNormalizedProFields = (projField, allFields, fieldConfig) => {\n    const normalizedProjField = projField.reduce((acc, field) => {\n        if (field.constructor.name === 'RegExp') {\n            acc.push(...allFields.filter(fieldName => fieldName.search(field) !== -1));\n        } else if (field in fieldConfig) {\n            acc.push(field);\n        }\n        return acc;\n    }, []);\n    return Array.from(new Set(normalizedProjField)).map(field => field.trim());\n};\n\n/**\n * Get the numberFormatted value if numberFormat present,\n * else returns the supplied value.\n * @param {Object} field Field Instance\n * @param {Number|String} value\n * @return {Number|String}\n */\nexport const getNumberFormattedVal = (field, value) => {\n    if (field.numberFormat) {\n        return field.numberFormat()(value);\n    }\n    return value;\n};\n","import { FilteringMode } from './enums';\nimport { getUniqueId } from './utils';\nimport {\n    updateFields,\n    cloneWithSelect,\n    cloneWithProject,\n    updateData,\n    getNormalizedProFields\n} from './helper';\nimport { crossProduct, difference, naturalJoinFilter, union } from './operator';\n\n/**\n * Relation provides the definitions of basic operators of relational algebra like *selection*, *projection*, *union*,\n * *difference* etc.\n *\n * It is extended by {@link DataModel} to inherit the functionalities of relational algebra concept.\n *\n * @class\n * @public\n * @module Relation\n * @namespace DataModel\n */\nclass Relation {\n\n    /**\n     * Creates a new Relation instance by providing underlying data and schema.\n     *\n     * @private\n     *\n     * @param {Object | string | Relation} data - The input tabular data in dsv or json format or\n     * an existing Relation instance object.\n     * @param {Array} schema - An array of data schema.\n     * @param {Object} [options] - The optional options.\n     */\n    constructor (...params) {\n        let source;\n\n        this._parent = null;\n        this._derivation = [];\n        this._ancestorDerivation = [];\n        this._children = [];\n\n        if (params.length === 1 && ((source = params[0]) instanceof Relation)) {\n            // parent datamodel was passed as part of source\n            this._colIdentifier = source._colIdentifier;\n            this._rowDiffset = source._rowDiffset;\n            this._dataFormat = source._dataFormat;\n            this._parent = source;\n            this._partialFieldspace = this._parent._partialFieldspace;\n            this._fieldStoreName = getUniqueId();\n            this.__calculateFieldspace().calculateFieldsConfig();\n        } else {\n            updateData(this, ...params);\n            this._fieldStoreName = this._partialFieldspace.name;\n            this.__calculateFieldspace().calculateFieldsConfig();\n            this._propagationNameSpace = {\n                mutableActions: {},\n                immutableActions: {}\n            };\n        }\n    }\n\n    /**\n     * Retrieves the {@link Schema | schema} details for every {@link Field | field} as an array.\n     *\n     * @public\n     *\n     * @return {Array.<Schema>} Array of fields schema.\n     *      ```\n     *      [\n     *          { name: 'Name', type: 'dimension' },\n     *          { name: 'Miles_per_Gallon', type: 'measure', numberFormat: (val) => `${val} miles / gallon` },\n     *          { name: 'Cylinder', type: 'dimension' },\n     *          { name: 'Displacement', type: 'measure', defAggFn: 'max' },\n     *          { name: 'HorsePower', type: 'measure', defAggFn: 'max' },\n     *          { name: 'Weight_in_lbs', type: 'measure', defAggFn: 'avg',  },\n     *          { name: 'Acceleration', type: 'measure', defAggFn: 'avg' },\n     *          { name: 'Year', type: 'dimension', subtype: 'datetime', format: '%Y' },\n     *          { name: 'Origin' }\n     *      ]\n     *      ```\n     */\n    getSchema () {\n        return this.getFieldspace().fields.map(d => d.schema());\n    }\n\n    /**\n     * Returns the name of the {@link DataModel} instance. If no name was specified during {@link DataModel}\n     * initialization, then it returns a auto-generated name.\n     *\n     * @public\n     *\n     * @return {string} Name of the DataModel instance.\n     */\n    getName() {\n        return this._fieldStoreName;\n    }\n\n    getFieldspace () {\n        return this._fieldspace;\n    }\n\n    __calculateFieldspace () {\n        this._fieldspace = updateFields([this._rowDiffset, this._colIdentifier],\n             this.getPartialFieldspace(), this._fieldStoreName);\n        return this;\n    }\n\n    getPartialFieldspace () {\n        return this._partialFieldspace;\n    }\n\n    /**\n     * Performs {@link link_of_cross_product | cross-product} between two {@link DataModel} instances and returns a\n     * new {@link DataModel} instance containing the results. This operation is also called theta join.\n     *\n     * Cross product takes two set and create one set where each value of one set is paired with each value of another\n     * set.\n     *\n     * This method takes an optional predicate which filters the generated result rows. If the predicate returns true\n     * the combined row is included in the resulatant table.\n     *\n     * @example\n     *  let originDM = dm.project(['Origin','Origin_Formal_Name']);\n     *  let carsDM = dm.project(['Name','Miles_per_Gallon','Origin'])\n     *\n     *  console.log(carsDM.join(originDM)));\n     *\n     *  console.log(carsDM.join(originDM,\n     *      obj => obj.[originDM.getName()].Origin === obj.[carsDM.getName()].Origin));\n     *\n     * @text\n     * This is chained version of `join` operator. `join` can also be used as\n     * {@link link_to_join_op | functional operator}.\n     *\n     * @public\n     *\n     * @param {DataModel} joinWith - The DataModel to be joined with the current instance DataModel.\n     * @param {SelectionPredicate} filterFn - The predicate function that will filter the result of the crossProduct.\n     *\n     * @return {DataModel} New DataModel instance created after joining.\n     */\n    join (joinWith, filterFn) {\n        return crossProduct(this, joinWith, filterFn);\n    }\n\n    /**\n     * {@link natural_join | Natural join} is a special kind of cross-product join where filtering of rows are performed\n     * internally by resolving common fields are from both table and the rows with common value are included.\n     *\n     * @example\n     *  let originDM = dm.project(['Origin','Origin_Formal_Name']);\n     *  let carsDM = dm.project(['Name','Miles_per_Gallon','Origin'])\n     *\n     *  console.log(carsDM.naturalJoin(originDM));\n     *\n     * @text\n     * This is chained version of `naturalJoin` operator. `naturalJoin` can also be used as\n     * {@link link_to_join_op | functional operator}.\n     *\n     * @public\n     *\n     * @param {DataModel} joinWith - The DataModel with which the current instance of DataModel on which the method is\n     *      called will be joined.\n     * @return {DataModel} New DataModel instance created after joining.\n     */\n    naturalJoin (joinWith) {\n        return crossProduct(this, joinWith, naturalJoinFilter(this, joinWith), true);\n    }\n\n    /**\n     * {@link link_to_union | Union} operation can be termed as vertical stacking of all rows from both the DataModel\n     * instances, provided that both of the {@link DataModel} instances should have same column names.\n     *\n     * @example\n     * console.log(EuropeanMakerDM.union(USAMakerDM));\n     *\n     * @text\n     * This is chained version of `naturalJoin` operator. `naturalJoin` can also be used as\n     * {@link link_to_join_op | functional operator}.\n     *\n     * @public\n     *\n     * @param {DataModel} unionWith - DataModel instance for which union has to be applied with the instance on which\n     *      the method is called\n     *\n     * @return {DataModel} New DataModel instance with the result of the operation\n     */\n    union (unionWith) {\n        return union(this, unionWith);\n    }\n\n    /**\n     * {@link link_to_difference | Difference } operation only include rows which are present in the datamodel on which\n     * it was called but not on the one passed as argument.\n     *\n     * @example\n     * console.log(highPowerDM.difference(highExpensiveDM));\n     *\n     * @text\n     * This is chained version of `naturalJoin` operator. `naturalJoin` can also be used as\n     * {@link link_to_join_op | functional operator}.\n     *\n     * @public\n     *\n     * @param {DataModel} differenceWith - DataModel instance for which difference has to be applied with the instance\n     *      on which the method is called\n     * @return {DataModel} New DataModel instance with the result of the operation\n     */\n    difference (differenceWith) {\n        return difference(this, differenceWith);\n    }\n\n    /**\n     * {@link link_to_selection | Selection} is a row filtering operation. It expects a predicate and an optional mode\n     * which control which all rows should be included in the resultant DataModel instance.\n     *\n     * {@link SelectionPredicate} is a function which returns a boolean value. For selection operation the selection\n     * function is called for each row of DataModel instance with the current row passed as argument.\n     *\n     * After executing {@link SelectionPredicate} the rows are labeled as either an entry of selection set or an entry\n     * of rejection set.\n     *\n     * {@link FilteringMode} operates on the selection and rejection set to determine which one would reflect in the\n     * resultant datamodel.\n     *\n     * @warning\n     * Selection and rejection set is only a logical idea for concept explanation purpose.\n     *\n     * @example\n     *  // with selection mode NORMAL:\n     *  const normDt = dt.select(fields => fields.Origin.value === \"USA\")\n     *  console.log(normDt));\n     *\n     * // with selection mode INVERSE:\n     * const inverDt = dt.select(fields => fields.Origin.value === \"USA\", { mode: DataModel.FilteringMode.INVERSE })\n     * console.log(inverDt);\n     *\n     * // with selection mode ALL:\n     * const dtArr = dt.select(fields => fields.Origin.value === \"USA\", { mode: DataModel.FilteringMode.ALL })\n     * // print the selected parts\n     * console.log(dtArr[0]);\n     * // print the inverted parts\n     * console.log(dtArr[1]);\n     *\n     * @text\n     * This is chained version of `select` operator. `select` can also be used as\n     * {@link link_to_join_op | functional operator}.\n     *\n     * @public\n     *\n     * @param {Function} selectFn - The predicate function which is called for each row with the current row.\n     * ```\n     *  function (row, i, cloneProvider, store)  { ... }\n     * ```\n     * @param {Object} config - The configuration object to control the inclusion exclusion of a row in resultant\n     * DataModel instance.\n     * @param {FilteringMode} [config.mode=FilteringMode.NORMAL] - The mode of the selection.\n     * @return {DataModel} Returns the new DataModel instance(s) after operation.\n     */\n    select (selectFn, config) {\n        const defConfig = {\n            mode: FilteringMode.NORMAL,\n            saveChild: true\n        };\n        config = Object.assign({}, defConfig, config);\n        config.mode = config.mode || defConfig.mode;\n\n        const cloneConfig = { saveChild: config.saveChild };\n        return cloneWithSelect(\n            this,\n            selectFn,\n            config,\n            cloneConfig\n        );\n    }\n\n    /**\n     * Retrieves a boolean value if the current {@link DataModel} instance has data.\n     *\n     * @example\n     * const schema = [\n     *    { name: 'CarName', type: 'dimension' },\n     *    { name: 'HorsePower', type: 'measure' },\n     *    { name: \"Origin\", type: 'dimension' }\n     * ];\n     * const data = [];\n     *\n     * const dt = new DataModel(data, schema);\n     * console.log(dt.isEmpty());\n     *\n     * @public\n     *\n     * @return {Boolean} True if the datamodel has no data, otherwise false.\n     */\n    isEmpty () {\n        return !this._rowDiffset.length || !this._colIdentifier.length;\n    }\n\n    /**\n     * Creates a clone from the current DataModel instance with child parent relationship.\n     *\n     * @private\n     * @param {boolean} [saveChild=true] - Whether the cloned instance would be recorded in the parent instance.\n     * @return {DataModel} - Returns the newly cloned DataModel instance.\n     */\n    clone (saveChild = true) {\n        const clonedDm = new this.constructor(this);\n        if (saveChild) {\n            clonedDm.setParent(this);\n        } else {\n            clonedDm.setParent(null);\n        }\n        return clonedDm;\n    }\n\n    /**\n     * {@link Projection} is filter column (field) operation. It expects list of fields' name and either include those\n     * or exclude those based on {@link FilteringMode} on the resultant variable.\n     *\n     * Projection expects array of fields name based on which it creates the selection and rejection set. All the field\n     * whose name is present in array goes in selection set and rest of the fields goes in rejection set.\n     *\n     * {@link FilteringMode} operates on the selection and rejection set to determine which one would reflect in the\n     * resulatant datamodel.\n     *\n     * @warning\n     * Selection and rejection set is only a logical idea for concept explanation purpose.\n     *\n     * @example\n     *  const dm = new DataModel(data, schema);\n     *\n     *  // with projection mode NORMAL:\n     *  const normDt = dt.project([\"Name\", \"HorsePower\"]);\n     *  console.log(normDt.getData());\n     *\n     *  // with projection mode INVERSE:\n     *  const inverDt = dt.project([\"Name\", \"HorsePower\"], { mode: DataModel.FilteringMode.INVERSE })\n     *  console.log(inverDt.getData());\n     *\n     *  // with selection mode ALL:\n     *  const dtArr = dt.project([\"Name\", \"HorsePower\"], { mode: DataModel.FilteringMode.ALL })\n     *  // print the normal parts\n     *  console.log(dtArr[0].getData());\n     *  // print the inverted parts\n     *  console.log(dtArr[1].getData());\n     *\n     * @text\n     * This is chained version of `select` operator. `select` can also be used as\n     * {@link link_to_join_op | functional operator}.\n     *\n     * @public\n     *\n     * @param {Array.<string | Regexp>} projField - An array of column names in string or regular expression.\n     * @param {Object} [config] - An optional config to control the creation of new DataModel\n     * @param {FilteringMode} [config.mode=FilteringMode.NORMAL] - Mode of the projection\n     *\n     * @return {DataModel} Returns the new DataModel instance after operation.\n     */\n    project (projField, config) {\n        const defConfig = {\n            mode: FilteringMode.NORMAL,\n            saveChild: true\n        };\n        config = Object.assign({}, defConfig, config);\n        const fieldConfig = this.getFieldsConfig();\n        const allFields = Object.keys(fieldConfig);\n        const { mode } = config;\n        const normalizedProjField = getNormalizedProFields(projField, allFields, fieldConfig);\n\n        let dataModel;\n\n        if (mode === FilteringMode.ALL) {\n            let projectionClone = cloneWithProject(this, normalizedProjField, {\n                mode: FilteringMode.NORMAL,\n                saveChild: config.saveChild\n            }, allFields);\n            let rejectionClone = cloneWithProject(this, normalizedProjField, {\n                mode: FilteringMode.INVERSE,\n                saveChild: config.saveChild\n            }, allFields);\n            dataModel = [projectionClone, rejectionClone];\n        } else {\n            let projectionClone = cloneWithProject(this, normalizedProjField, config, allFields);\n            dataModel = projectionClone;\n        }\n\n        return dataModel;\n    }\n\n    getFieldsConfig () {\n        return this._fieldConfig;\n    }\n\n    calculateFieldsConfig () {\n        this._fieldConfig = this._fieldspace.fields.reduce((acc, fieldObj, i) => {\n            acc[fieldObj.name()] = {\n                index: i,\n                def: fieldObj.schema(),\n            };\n            return acc;\n        }, {});\n        return this;\n    }\n\n\n    /**\n     * Frees up the resources associated with the current DataModel instance and breaks all the links instance has in\n     * the DAG.\n     *\n     * @public\n     */\n    dispose () {\n        this._parent && this._parent.removeChild(this);\n        this._parent = null;\n        this._children.forEach((child) => {\n            child._parent = null;\n        });\n        this._children = [];\n    }\n\n    /**\n     * Removes the specified child {@link DataModel} from the child list of the current {@link DataModel} instance.\n     *\n     * @example\n     * const schema = [\n     *    { name: 'Name', type: 'dimension' },\n     *    { name: 'HorsePower', type: 'measure' },\n     *    { name: \"Origin\", type: 'dimension' }\n     * ];\n     *\n     * const data = [\n     *    { Name: \"chevrolet chevelle malibu\", Horsepower: 130, Origin: \"USA\" },\n     *    { Name: \"citroen ds-21 pallas\", Horsepower: 115, Origin: \"Europe\" },\n     *    { Name: \"datsun pl510\", Horsepower: 88, Origin: \"Japan\" },\n     *    { Name: \"amc rebel sst\", Horsepower: 150, Origin: \"USA\"},\n     * ]\n     *\n     * const dt = new DataModel(data, schema);\n     *\n     * const dt2 = dt.select(fields => fields.Origin.value === \"USA\")\n     * dt.removeChild(dt2);\n     *\n     * @private\n     *\n     * @param {DataModel} child - Delegates the parent to remove this child.\n     */\n    removeChild (child) {\n        let idx = this._children.findIndex(sibling => sibling === child);\n        idx !== -1 ? this._children.splice(idx, 1) : true;\n    }\n\n    /**\n     * Sets the specified {@link DataModel} as a parent for the current {@link DataModel} instance.\n     *\n     * @param {DataModel} parent - The datamodel instance which will act as parent.\n     */\n    setParent (parent) {\n        this._parent && this._parent.removeChild(this);\n        this._parent = parent;\n        parent && parent._children.push(this);\n    }\n\n    /**\n     * Returns the parent {@link DataModel} instance.\n     *\n     * @example\n     * const schema = [\n     *    { name: 'Name', type: 'dimension' },\n     *    { name: 'HorsePower', type: 'measure' },\n     *    { name: \"Origin\", type: 'dimension' }\n     * ];\n     *\n     * const data = [\n     *    { Name: \"chevrolet chevelle malibu\", Horsepower: 130, Origin: \"USA\" },\n     *    { Name: \"citroen ds-21 pallas\", Horsepower: 115, Origin: \"Europe\" },\n     *    { Name: \"datsun pl510\", Horsepower: 88, Origin: \"Japan\" },\n     *    { Name: \"amc rebel sst\", Horsepower: 150, Origin: \"USA\"},\n     * ]\n     *\n     * const dt = new DataModel(data, schema);\n     *\n     * const dt2 = dt.select(fields => fields.Origin.value === \"USA\");\n     * const parentDm = dt2.getParent();\n     *\n     * @return {DataModel} Returns the parent DataModel instance.\n     */\n    getParent () {\n        return this._parent;\n    }\n\n    /**\n     * Returns the immediate child {@link DataModel} instances.\n     *\n     * @example\n     * const schema = [\n     *    { name: 'Name', type: 'dimension' },\n     *    { name: 'HorsePower', type: 'measure' },\n     *    { name: \"Origin\", type: 'dimension' }\n     * ];\n     *\n     * const data = [\n     *    { Name: \"chevrolet chevelle malibu\", Horsepower: 130, Origin: \"USA\" },\n     *    { Name: \"citroen ds-21 pallas\", Horsepower: 115, Origin: \"Europe\" },\n     *    { Name: \"datsun pl510\", Horsepower: 88, Origin: \"Japan\" },\n     *    { Name: \"amc rebel sst\", Horsepower: 150, Origin: \"USA\"},\n     * ]\n     *\n     * const dt = new DataModel(data, schema);\n     *\n     * const childDm1 = dt.select(fields => fields.Origin.value === \"USA\");\n     * const childDm2 = dt.select(fields => fields.Origin.value === \"Japan\");\n     * const childDm3 = dt.groupBy([\"Origin\"]);\n     *\n     * @return {DataModel[]} Returns the immediate child DataModel instances.\n     */\n    getChildren () {\n        return this._children;\n    }\n\n    /**\n     * Returns the in-between operation meta data while creating the current {@link DataModel} instance.\n     *\n     * @example\n     * const schema = [\n     *   { name: 'Name', type: 'dimension' },\n     *   { name: 'HorsePower', type: 'measure' },\n     *   { name: \"Origin\", type: 'dimension' }\n     * ];\n     *\n     * const data = [\n     *   { Name: \"chevrolet chevelle malibu\", Horsepower: 130, Origin: \"USA\" },\n     *   { Name: \"citroen ds-21 pallas\", Horsepower: 115, Origin: \"Europe\" },\n     *   { Name: \"datsun pl510\", Horsepower: 88, Origin: \"Japan\" },\n     *   { Name: \"amc rebel sst\", Horsepower: 150, Origin: \"USA\"},\n     * ]\n     *\n     * const dt = new DataModel(data, schema);\n     * const dt2 = dt.select(fields => fields.Origin.value === \"USA\");\n     * const dt3 = dt2.groupBy([\"Origin\"]);\n     * const derivations = dt3.getDerivations();\n     *\n     * @return {Any[]} Returns the derivation meta data.\n     */\n    getDerivations () {\n        return this._derivation;\n    }\n\n    /**\n     * Returns the in-between operation meta data happened from root {@link DataModel} to current instance.\n     *\n     * @example\n     * const schema = [\n     *   { name: 'Name', type: 'dimension' },\n     *   { name: 'HorsePower', type: 'measure' },\n     *   { name: \"Origin\", type: 'dimension' }\n     * ];\n     *\n     * const data = [\n     *   { Name: \"chevrolet chevelle malibu\", Horsepower: 130, Origin: \"USA\" },\n     *   { Name: \"citroen ds-21 pallas\", Horsepower: 115, Origin: \"Europe\" },\n     *   { Name: \"datsun pl510\", Horsepower: 88, Origin: \"Japan\" },\n     *   { Name: \"amc rebel sst\", Horsepower: 150, Origin: \"USA\"},\n     * ]\n     *\n     * const dt = new DataModel(data, schema);\n     * const dt2 = dt.select(fields => fields.Origin.value === \"USA\");\n     * const dt3 = dt2.groupBy([\"Origin\"]);\n     * const ancDerivations = dt3.getAncestorDerivations();\n     *\n     * @return {Any[]} Returns the previous derivation meta data.\n     */\n    getAncestorDerivations () {\n        return this._ancestorDerivation;\n    }\n}\n\nexport default Relation;\n","/* eslint-disable default-case */\n\nimport { FieldType, DimensionSubtype, DataFormat, FilteringMode } from './enums';\nimport {\n    persistDerivations,\n    getRootGroupByModel,\n    propagateToAllDataModels,\n    getRootDataModel,\n    propagateImmutableActions,\n    addToPropNamespace,\n    sanitizeUnitSchema,\n    splitWithSelect,\n    splitWithProject,\n    getNormalizedProFields\n} from './helper';\nimport { DM_DERIVATIVES, PROPAGATION } from './constants';\nimport {\n    dataBuilder,\n    rowDiffsetIterator,\n    groupBy\n} from './operator';\nimport { createBinnedFieldData } from './operator/bucket-creator';\nimport Relation from './relation';\nimport reducerStore from './utils/reducer-store';\nimport { createFields } from './field-creator';\nimport InvalidAwareTypes from './invalid-aware-types';\nimport Value from './value';\nimport { converterStore } from './converter';\nimport { fieldRegistry } from './fields';\n\n/**\n * DataModel is an in-browser representation of tabular data. It supports\n * {@link https://en.wikipedia.org/wiki/Relational_algebra | relational algebra} operators as well as generic data\n * processing opearators.\n * DataModel extends {@link Relation} class which defines all the relational algebra opreators. DataModel gives\n * definition of generic data processing operators which are not relational algebra complient.\n *\n * @public\n * @class\n * @extends Relation\n * @memberof Datamodel\n */\nclass DataModel extends Relation {\n    /**\n     * Creates a new DataModel instance by providing data and schema. Data could be in the form of\n     * - Flat JSON\n     * - DSV String\n     * - 2D Array\n     *\n     * By default DataModel finds suitable adapter to serialize the data. DataModel also expects a\n     * {@link Schema | schema} for identifying the variables present in data.\n     *\n     * @constructor\n     * @example\n     * const data = loadData('cars.csv');\n     * const schema = [\n     *      { name: 'Name', type: 'dimension' },\n     *      { name: 'Miles_per_Gallon', type: 'measure', unit : 'cm', scale: '1000', numberformat: val => `${val}G`},\n     *      { name: 'Cylinders', type: 'dimension' },\n     *      { name: 'Displacement', type: 'measure' },\n     *      { name: 'Horsepower', type: 'measure' },\n     *      { name: 'Weight_in_lbs', type: 'measure' },\n     *      { name: 'Acceleration', type: 'measure' },\n     *      { name: 'Year', type: 'dimension', subtype: 'datetime', format: '%Y' },\n     *      { name: 'Origin', type: 'dimension' }\n     * ];\n     * const dm = new DataModel(data, schema, { name: 'Cars' });\n     * table(dm);\n     *\n     * @public\n     *\n     * @param {Array.<Object> | string | Array.<Array>} data Input data in any of the mentioned formats\n     * @param {Array.<Schema>} schema Defination of the variables. Order of the variables in data and order of the\n     *      variables in schema has to be same.\n     * @param {object} [options] Optional arguments to specify more settings regarding the creation part\n     * @param {string} [options.name] Name of the datamodel instance. If no name is given an auto generated name is\n     *      assigned to the instance.\n     * @param {string} [options.fieldSeparator=','] specify field separator type if the data is of type dsv string.\n     */\n    constructor (...args) {\n        super(...args);\n\n        this._onPropagation = [];\n    }\n\n    /**\n     * Reducers are simple functions which reduces an array of numbers to a representative number of the set.\n     * Like an array of numbers `[10, 20, 5, 15]` can be reduced to `12.5` if average / mean reducer function is\n     * applied. All the measure fields in datamodel (variables in data) needs a reducer to handle aggregation.\n     *\n     * @public\n     *\n     * @return {ReducerStore} Singleton instance of {@link ReducerStore}.\n     */\n    static get Reducers () {\n        return reducerStore;\n    }\n\n    /**\n     * Converters are functions that transforms data in various format tpo datamodel consumabe format.\n     */\n    static get Converters() {\n        return converterStore;\n    }\n\n    /**\n     * Register new type of fields\n     */\n    static get FieldTypes() {\n        return fieldRegistry;\n    }\n\n    /**\n     * Configure null, undefined, invalid values in the source data\n     *\n     * @public\n     *\n     * @param {Object} [config] - Configuration to control how null, undefined and non-parsable values are\n     * represented in DataModel.\n     * @param {string} [config.undefined] - Define how an undefined value will be represented.\n     * @param {string} [config.null] - Define how a null value will be represented.\n     * @param {string} [config.invalid] - Define how a non-parsable value will be represented.\n     */\n    static configureInvalidAwareTypes (config) {\n        return InvalidAwareTypes.invalidAwareVals(config);\n    }\n\n    /**\n     * Retrieve the data attached to an instance in JSON format.\n     *\n     * @example\n     * // DataModel instance is already prepared and assigned to dm variable\n     *  const data = dm.getData({\n     *      order: 'column',\n     *      formatter: {\n     *          origin: (val) => val === 'European Union' ? 'EU' : val;\n     *      }\n     *  });\n     *  console.log(data);\n     *\n     * @public\n     *\n     * @param {Object} [options] Options to control how the raw data is to be returned.\n     * @param {string} [options.order='row'] Defines if data is retieved in row order or column order. Possible values\n     *      are `'rows'` and `'columns'`\n     * @param {Function} [options.formatter=null] Formats the output data. This expects an object, where the keys are\n     *      the name of the variable needs to be formatted. The formatter function is called for each row passing the\n     *      value of the cell for a particular row as arguments. The formatter is a function in the form of\n     *      `function (value, rowId, schema) => { ... }`\n     *      Know more about {@link Fomatter}.\n     *\n     * @return {Array} Returns a multidimensional array of the data with schema. The return format looks like\n     *      ```\n     *          {\n     *              data,\n     *              schema\n     *          }\n     *      ```\n     */\n    getData (options) {\n        const defOptions = {\n            order: 'row',\n            formatter: null,\n            withUid: false,\n            getAllFields: false,\n            sort: []\n        };\n        options = Object.assign({}, defOptions, options);\n        const fields = this.getPartialFieldspace().fields;\n\n        const dataGenerated = dataBuilder.call(\n            this,\n            this.getPartialFieldspace().fields,\n            this._rowDiffset,\n            options.getAllFields ? fields.map(d => d.name()).join() : this._colIdentifier,\n            options.sort,\n            {\n                columnWise: options.order === 'column',\n                addUid: !!options.withUid\n            }\n        );\n\n        if (!options.formatter) {\n            return dataGenerated;\n        }\n\n        const { formatter } = options;\n        const { data, schema, uids } = dataGenerated;\n        const fieldNames = schema.map((e => e.name));\n        const fmtFieldNames = Object.keys(formatter);\n        const fmtFieldIdx = fmtFieldNames.reduce((acc, next) => {\n            const idx = fieldNames.indexOf(next);\n            if (idx !== -1) {\n                acc.push([idx, formatter[next]]);\n            }\n            return acc;\n        }, []);\n\n        if (options.order === 'column') {\n            fmtFieldIdx.forEach((elem) => {\n                const fIdx = elem[0];\n                const fmtFn = elem[1];\n\n                data[fIdx].forEach((datum, datumIdx) => {\n                    data[fIdx][datumIdx] = fmtFn.call(\n                        undefined,\n                        datum,\n                        uids[datumIdx],\n                        schema[fIdx]\n                    );\n                });\n            });\n        } else {\n            data.forEach((datum, datumIdx) => {\n                fmtFieldIdx.forEach((elem) => {\n                    const fIdx = elem[0];\n                    const fmtFn = elem[1];\n\n                    datum[fIdx] = fmtFn.call(\n                        undefined,\n                        datum[fIdx],\n                        uids[datumIdx],\n                        schema[fIdx]\n                    );\n                });\n            });\n        }\n\n        return dataGenerated;\n    }\n\n    /**\n     * Returns the unique ids in an array.\n     *\n     * @return {Array} Returns an array of ids.\n     */\n    getUids () {\n        const rowDiffset = this._rowDiffset;\n        const ids = [];\n\n        if (rowDiffset.length) {\n            const diffSets = rowDiffset.split(',');\n\n            diffSets.forEach((set) => {\n                let [start, end] = set.split('-').map(Number);\n\n                end = end !== undefined ? end : start;\n                ids.push(...Array(end - start + 1).fill().map((_, idx) => start + idx));\n            });\n        }\n\n        return ids;\n    }\n    /**\n     * Groups the data using particular dimensions and by reducing measures. It expects a list of dimensions using which\n     * it projects the datamodel and perform aggregations to reduce the duplicate tuples. Refer this\n     * {@link link_to_one_example_with_group_by | document} to know the intuition behind groupBy.\n     *\n     * DataModel by default provides definition of few {@link reducer | Reducers}.\n     * {@link ReducerStore | User defined reducers} can also be registered.\n     *\n     * This is the chained implementation of `groupBy`.\n     * `groupBy` also supports {@link link_to_compose_groupBy | composability}\n     *\n     * @example\n     * const groupedDM = dm.groupBy(['Year'], { horsepower: 'max' } );\n     * console.log(groupedDm);\n     *\n     * @public\n     *\n     * @param {Array.<string>} fieldsArr - Array containing the name of dimensions\n     * @param {Object} [reducers={}] - A map whose key is the variable name and value is the name of the reducer. If its\n     *      not passed, or any variable is ommitted from the object, default aggregation function is used from the\n     *      schema of the variable.\n     *\n     * @return {DataModel} Returns a new DataModel instance after performing the groupby.\n     */\n    groupBy (fieldsArr, reducers = {}, config = { saveChild: true }) {\n        const groupByString = `${fieldsArr.join()}`;\n        let params = [this, fieldsArr, reducers];\n        const newDataModel = groupBy(...params);\n\n        persistDerivations(\n            this,\n            newDataModel,\n            DM_DERIVATIVES.GROUPBY,\n            { fieldsArr, groupByString, defaultReducer: reducerStore.defaultReducer() },\n            reducers\n        );\n\n        if (config.saveChild) {\n            newDataModel.setParent(this);\n        } else {\n            newDataModel.setParent(null);\n        }\n\n        return newDataModel;\n    }\n\n    /**\n     * Performs sorting operation on the current {@link DataModel} instance according to the specified sorting details.\n     * Like every other operator it doesn't mutate the current DataModel instance on which it was called, instead\n     * returns a new DataModel instance containing the sorted data.\n     *\n     * DataModel support multi level sorting by listing the variables using which sorting needs to be performed and\n     * the type of sorting `ASC` or `DESC`.\n     *\n     * In the following example, data is sorted by `Origin` field in `DESC` order in first level followed by another\n     * level of sorting by `Acceleration` in `ASC` order.\n     *\n     * @example\n     * // here dm is the pre-declared DataModel instance containing the data of 'cars.json' file\n     * let sortedDm = dm.sort([\n     *    [\"Origin\", \"DESC\"]\n     *    [\"Acceleration\"] // Default value is ASC\n     * ]);\n     *\n     * console.log(dm.getData());\n     * console.log(sortedDm.getData());\n     *\n     * // Sort with a custom sorting function\n     * sortedDm = dm.sort([\n     *    [\"Origin\", \"DESC\"]\n     *    [\"Acceleration\", (a, b) => a - b] // Custom sorting function\n     * ]);\n     *\n     * console.log(dm.getData());\n     * console.log(sortedDm.getData());\n     *\n     * @text\n     * DataModel also provides another sorting mechanism out of the box where sort is applied to a variable using\n     * another variable which determines the order.\n     * Like the above DataModel contains three fields `Origin`, `Name` and `Acceleration`. Now, the data in this\n     * model can be sorted by `Origin` field according to the average value of all `Acceleration` for a\n     * particular `Origin` value.\n     *\n     * @example\n     * // here dm is the pre-declared DataModel instance containing the data of 'cars.json' file\n     * const sortedDm = dm.sort([\n     *     ['Origin', ['Acceleration', (a, b) => avg(...a.Acceleration) - avg(...b.Acceleration)]]\n     * ]);\n     *\n     * console.log(dm.getData());\n     * console.log(sortedDm.getData());\n     *\n     * @public\n     *\n     * @param {Array.<Array>} sortingDetails - Sorting details based on which the sorting will be performed.\n     * @return {DataModel} Returns a new instance of DataModel with sorted data.\n     */\n    sort (sortingDetails, config = { saveChild: false }) {\n        const rawData = this.getData({\n            order: 'row',\n            sort: sortingDetails\n        });\n        const header = rawData.schema.map(field => field.name);\n        const dataInCSVArr = [header].concat(rawData.data);\n\n        const sortedDm = new this.constructor(dataInCSVArr, rawData.schema, { dataFormat: 'DSVArr' });\n\n        persistDerivations(\n            this,\n            sortedDm,\n            DM_DERIVATIVES.SORT,\n            config,\n            sortingDetails\n        );\n\n        if (config.saveChild) {\n            sortedDm.setParent(this);\n        } else {\n            sortedDm.setParent(null);\n        }\n\n        return sortedDm;\n    }\n\n    /**\n     * Performs the serialization operation on the current {@link DataModel} instance according to the specified data\n     * type. When an {@link DataModel} instance is created, it de-serializes the input data into its internal format,\n     * and during its serialization process, it converts its internal data format to the specified data type and returns\n     * that data regardless what type of data is used during the {@link DataModel} initialization.\n     *\n     * @example\n     * // here dm is the pre-declared DataModel instance.\n     * const csvData = dm.serialize(DataModel.DataFormat.DSV_STR, { fieldSeparator: \",\" });\n     * console.log(csvData); // The csv formatted data.\n     *\n     * const jsonData = dm.serialize(DataModel.DataFormat.FLAT_JSON);\n     * console.log(jsonData); // The json data.\n     *\n     * @public\n     *\n     * @param {string} type - The data type name for serialization.\n     * @param {Object} options - The optional option object.\n     * @param {string} options.fieldSeparator - The field separator character for DSV data type.\n     * @return {Array|string} Returns the serialized data.\n     */\n    serialize (type, options) {\n        type = type || this._dataFormat;\n        options = Object.assign({}, { fieldSeparator: ',' }, options);\n\n        const fields = this.getFieldspace().fields;\n        const colData = fields.map(f => f.formattedData());\n        const rowsCount = colData[0].length;\n        let serializedData;\n        let rowIdx;\n        let colIdx;\n\n        if (type === DataFormat.FLAT_JSON) {\n            serializedData = [];\n            for (rowIdx = 0; rowIdx < rowsCount; rowIdx++) {\n                const row = {};\n                for (colIdx = 0; colIdx < fields.length; colIdx++) {\n                    row[fields[colIdx].name()] = colData[colIdx][rowIdx];\n                }\n                serializedData.push(row);\n            }\n        } else if (type === DataFormat.DSV_STR) {\n            serializedData = [fields.map(f => f.name()).join(options.fieldSeparator)];\n            for (rowIdx = 0; rowIdx < rowsCount; rowIdx++) {\n                const row = [];\n                for (colIdx = 0; colIdx < fields.length; colIdx++) {\n                    row.push(colData[colIdx][rowIdx]);\n                }\n                serializedData.push(row.join(options.fieldSeparator));\n            }\n            serializedData = serializedData.join('\\n');\n        } else if (type === DataFormat.DSV_ARR) {\n            serializedData = [fields.map(f => f.name())];\n            for (rowIdx = 0; rowIdx < rowsCount; rowIdx++) {\n                const row = [];\n                for (colIdx = 0; colIdx < fields.length; colIdx++) {\n                    row.push(colData[colIdx][rowIdx]);\n                }\n                serializedData.push(row);\n            }\n        } else {\n            throw new Error(`Data type ${type} is not supported`);\n        }\n\n        return serializedData;\n    }\n\n    addField (field) {\n        const fieldName = field.name();\n        this._colIdentifier += `,${fieldName}`;\n        const partialFieldspace = this._partialFieldspace;\n        const cachedValueObjects = partialFieldspace._cachedValueObjects;\n        const formattedData = field.formattedData();\n        const rawData = field.partialField.data;\n\n        if (!partialFieldspace.fieldsObj()[field.name()]) {\n            partialFieldspace.fields.push(field);\n            cachedValueObjects.forEach((obj, i) => {\n                obj[field.name()] = new Value(formattedData[i], rawData[i], field);\n            });\n        } else {\n            const fieldIndex = partialFieldspace.fields.findIndex(fieldinst => fieldinst.name() === fieldName);\n            fieldIndex >= 0 && (partialFieldspace.fields[fieldIndex] = field);\n        }\n\n        // flush out cached namespace values on addition of new fields\n        partialFieldspace._cachedFieldsObj = null;\n        partialFieldspace._cachedDimension = null;\n        partialFieldspace._cachedMeasure = null;\n\n        this.__calculateFieldspace().calculateFieldsConfig();\n        return this;\n    }\n\n    /**\n    * Creates a new variable calculated from existing variables. This method expects the definition of the newly created\n    * variable and a function which resolves the value of the new variable from existing variables.\n    *\n    * Can create a new measure based on existing variables:\n    * @example\n    *  // DataModel already prepared and assigned to dm variable;\n    *  const newDm = dataModel.calculateVariable({\n    *      name: 'powerToWeight',\n    *      type: 'measure'\n    *  }, ['horsepower', 'weight_in_lbs', (hp, weight) => hp / weight ]);\n    *\n    *\n    * Can create a new dimension based on existing variables:\n    * @example\n    *  // DataModel already prepared and assigned to dm variable;\n    *  const child = dataModel.calculateVariable(\n    *     {\n    *       name: 'Efficiency',\n    *       type: 'dimension'\n    *     }, ['horsepower', (hp) => {\n    *      if (hp < 80) { return 'low'; },\n    *      else if (hp < 120) { return 'moderate'; }\n    *      else { return 'high' }\n    *  }]);\n    *\n    * @public\n    *\n    * @param {Object} schema - The schema of newly defined variable.\n    * @param {Array.<string|function>} dependency - An array containing the dependency variable names and a resolver\n    * function as the last element.\n    * @param {Object} config - An optional config object.\n    * @param {boolean} [config.saveChild] - Whether the newly created DataModel will be a child.\n    * @param {boolean} [config.replaceVar] - Whether the newly created variable will replace the existing variable.\n    * @return {DataModel} Returns an instance of DataModel with the new field.\n    */\n    calculateVariable (schema, dependency, config) {\n        schema = sanitizeUnitSchema(schema);\n        config = Object.assign({}, { saveChild: true, replaceVar: false }, config);\n\n        const fieldsConfig = this.getFieldsConfig();\n        const depVars = dependency.slice(0, dependency.length - 1);\n        const retrieveFn = dependency[dependency.length - 1];\n\n        if (fieldsConfig[schema.name] && !config.replaceVar) {\n            throw new Error(`${schema.name} field already exists in datamodel`);\n        }\n\n        const depFieldIndices = depVars.map((field) => {\n            const fieldSpec = fieldsConfig[field];\n            if (!fieldSpec) {\n                // @todo dont throw error here, use warning in production mode\n                throw new Error(`${field} is not a valid column name.`);\n            }\n            return fieldSpec.index;\n        });\n\n        const clone = this.clone(config.saveChild);\n\n        const fs = clone.getFieldspace().fields;\n        const suppliedFields = depFieldIndices.map(idx => fs[idx]);\n\n        let cachedStore = {};\n        let cloneProvider = () => this.detachedRoot();\n\n        const computedValues = [];\n        rowDiffsetIterator(clone._rowDiffset, (i) => {\n            const fieldsData = suppliedFields.map(field => field.partialField.data[i]);\n            computedValues[i] = retrieveFn(...fieldsData, i, cloneProvider, cachedStore);\n        });\n        const [field] = createFields([computedValues], [schema], [schema.name]);\n        clone.addField(field);\n\n        persistDerivations(\n            this,\n            clone,\n            DM_DERIVATIVES.CAL_VAR,\n            { config: schema, fields: depVars },\n            retrieveFn\n        );\n\n        return clone;\n    }\n\n    /**\n     * Propagates changes across all the connected DataModel instances.\n     *\n     * @param {Array} identifiers - A list of identifiers that were interacted with.\n     * @param {Object} payload - The interaction specific details.\n     *\n     * @return {DataModel} DataModel instance.\n     */\n    propagate (identifiers, config = {}, addToNameSpace, propConfig = {}) {\n        const isMutableAction = config.isMutableAction;\n        const propagationSourceId = config.sourceId;\n        const payload = config.payload;\n        const rootModel = getRootDataModel(this);\n        const propagationNameSpace = rootModel._propagationNameSpace;\n        const rootGroupByModel = getRootGroupByModel(this);\n        const rootModels = {\n            groupByModel: rootGroupByModel,\n            model: rootModel\n        };\n\n        addToNameSpace && addToPropNamespace(propagationNameSpace, config, this);\n        propagateToAllDataModels(identifiers, rootModels, { propagationNameSpace,\n            sourceId: propagationSourceId,\n            propagationSource: this },\n            Object.assign({\n                payload\n            }, config));\n\n        if (isMutableAction) {\n            propagateImmutableActions(propagationNameSpace, rootModel, {\n                config,\n                propConfig\n            }, this);\n        }\n\n        return this;\n    }\n\n    /**\n     * Associates a callback with an event name.\n     *\n     * @param {string} eventName - The name of the event.\n     * @param {Function} callback - The callback to invoke.\n     * @return {DataModel} Returns this current DataModel instance itself.\n     */\n    on (eventName, callback) {\n        switch (eventName) {\n        case PROPAGATION:\n            this._onPropagation.push(callback);\n            break;\n        }\n        return this;\n    }\n\n    /**\n     * Unsubscribes the callbacks for the provided event name.\n     *\n     * @param {string} eventName - The name of the event to unsubscribe.\n     * @return {DataModel} Returns the current DataModel instance itself.\n     */\n    unsubscribe (eventName) {\n        switch (eventName) {\n        case PROPAGATION:\n            this._onPropagation = [];\n            break;\n\n        }\n        return this;\n    }\n\n    /**\n     * This method is used to invoke the method associated with propagation.\n     *\n     * @param {Object} payload The interaction payload.\n     * @param {DataModel} identifiers The propagated DataModel.\n     * @memberof DataModel\n     */\n    handlePropagation (propModel, payload) {\n        let propListeners = this._onPropagation;\n        propListeners.forEach(fn => fn.call(this, propModel, payload));\n    }\n\n    /**\n     * Performs the binning operation on a measure field based on the binning configuration. Binning means discretizing\n     * values of a measure. Binning configuration contains an array; subsequent values from the array marks the boundary\n     * of buckets in [inclusive, exclusive) range format. This operation does not mutate the subject measure field,\n     * instead, it creates a new field (variable) of type dimension and subtype binned.\n     *\n     * Binning can be configured by\n     * - providing custom bin configuration with non-uniform buckets,\n     * - providing bins count,\n     * - providing each bin size,\n     *\n     * When custom `buckets` are provided as part of binning configuration:\n     * @example\n     *  // DataModel already prepared and assigned to dm variable\n     *  const config = { name: 'binnedHP', buckets: [30, 80, 100, 110] }\n     *  const binnedDM = dataModel.bin('horsepower', config);\n     *\n     * @text\n     * When `binsCount` is defined as part of binning configuration:\n     * @example\n     *  // DataModel already prepared and assigned to dm variable\n     *  const config = { name: 'binnedHP', binsCount: 5, start: 0, end: 100 }\n     *  const binDM = dataModel.bin('horsepower', config);\n     *\n     * @text\n     * When `binSize` is defined as part of binning configuration:\n     * @example\n     *  // DataModel already prepared and assigned to dm variable\n     *  const config = { name: 'binnedHorsepower', binSize: 20, start: 5}\n     *  const binDM = dataModel.bin('horsepower', config);\n     *\n     * @public\n     *\n     * @param {string} measureFieldName - The name of the target measure field.\n     * @param {Object} config - The config object.\n     * @param {string} [config.name] - The name of the new field which will be created.\n     * @param {string} [config.buckets] - An array containing the bucket ranges.\n     * @param {string} [config.binSize] - The size of each bin. It is ignored when buckets are given.\n     * @param {string} [config.binsCount] - The total number of bins to generate. It is ignored when buckets are given.\n     * @param {string} [config.start] - The start value of the bucket ranges. It is ignored when buckets are given.\n     * @param {string} [config.end] - The end value of the bucket ranges. It is ignored when buckets are given.\n     * @return {DataModel} Returns a new {@link DataModel} instance with the new field.\n     */\n    bin (measureFieldName, config) {\n        const fieldsConfig = this.getFieldsConfig();\n\n        if (!fieldsConfig[measureFieldName]) {\n            throw new Error(`Field ${measureFieldName} doesn't exist`);\n        }\n\n        const binFieldName = config.name || `${measureFieldName}_binned`;\n\n        if (fieldsConfig[binFieldName]) {\n            throw new Error(`Field ${binFieldName} already exists`);\n        }\n\n        const measureField = this.getFieldspace().fieldsObj()[measureFieldName];\n        const { binnedData, bins } = createBinnedFieldData(measureField, this._rowDiffset, config);\n\n        const binField = createFields([binnedData], [\n            {\n                name: binFieldName,\n                type: FieldType.DIMENSION,\n                subtype: DimensionSubtype.BINNED,\n                bins\n            }], [binFieldName])[0];\n\n        const clone = this.clone(config.saveChild);\n        clone.addField(binField);\n\n        persistDerivations(\n            this,\n            clone,\n            DM_DERIVATIVES.BIN,\n             { measureFieldName, config, binFieldName },\n             null\n        );\n\n        return clone;\n    }\n\n    /**\n     * Creates a new {@link DataModel} instance with completely detached root from current {@link DataModel} instance,\n     * the new {@link DataModel} instance has no parent-children relationship with the current one, but has same data as\n     * the current one.\n     * This API is useful when a completely different {@link DataModel} but with same data as the current instance is\n     * needed.\n     *\n     * @example\n     *  const dm = new DataModel(data, schema);\n     *  const detachedDm = dm.detachedRoot();\n     *\n     * // has different namespace\n     * console.log(dm.getPartialFieldspace().name);\n     * console.log(detachedDm.getPartialFieldspace().name);\n     *\n     * // has same data\n     * console.log(dm.getData());\n     * console.log(detachedDm.getData());\n     *\n     * @public\n     *\n     * @return {DataModel} Returns a detached {@link DataModel} instance.\n     */\n    detachedRoot () {\n        const data = this.serialize(DataFormat.FLAT_JSON);\n        const schema = this.getSchema();\n\n        return new DataModel(data, schema);\n    }\n\n    /**\n     * Creates a set of new {@link DataModel} instances by splitting the set of rows in the source {@link DataModel}\n     * instance based on a set of dimensions.\n     *\n     * For each unique dimensional value, a new split is created which creates a unique {@link DataModel} instance for\n     *  that split\n     *\n     * If multiple dimensions are provided, it splits the source {@link DataModel} instance with all possible\n     * combinations of the dimensional values for all the dimensions provided\n     *\n     * Additionally, it also accepts a predicate function to reduce the set of rows provided. A\n     * {@link link_to_selection | Selection} is performed on all the split {@link DataModel} instances based on\n     * the predicate function\n     *\n     * @example\n     *  // without predicate function:\n     *  const splitDt = dt.splitByRow(['Origin'])\n     *  console.log(splitDt));\n     * // This should give three unique DataModel instances, one each having rows only for 'USA',\n     * // 'Europe' and 'Japan' respectively\n     *\n     * @example\n     *  // without predicate function:\n     *  const splitDtMulti = dt.splitByRow(['Origin', 'Cylinders'])\n     *  console.log(splitDtMulti));\n     * // This should give DataModel instances for all unique combinations of Origin and Cylinder values\n     *\n     * @example\n     * // with predicate function:\n     * const splitWithPredDt = dt.select(['Origin'], fields => fields.Origin.value === \"USA\")\n     * console.log(splitWithPredDt);\n     * // This should not include the DataModel for the Origin : 'USA'\n     *\n     *\n     * @public\n     *\n     * @param {Array} dimensionArr - Set of dimensions based on which the split should occur\n     * @param {Object} config - The configuration object\n     * @param {string} [config.saveChild] - Configuration to save child or not\n     * @param {string}[config.mode=FilteringMode.NORMAL] -The mode of the selection.\n     * @return {Array}  Returns the new DataModel instances after operation.\n     */\n    splitByRow (dimensionArr, reducerFn, config) {\n        const fieldsConfig = this.getFieldsConfig();\n\n        dimensionArr.forEach((fieldName) => {\n            if (!fieldsConfig[fieldName]) {\n                throw new Error(`Field ${fieldName} doesn't exist in the schema`);\n            }\n        });\n\n        const defConfig = {\n            mode: FilteringMode.NORMAL,\n            saveChild: true\n        };\n\n        config = Object.assign({}, defConfig, config);\n\n        return splitWithSelect(this, dimensionArr, reducerFn, config);\n    }\n\n    /**\n     * Creates a set of new {@link DataModel} instances by splitting the set of fields in the source {@link DataModel}\n     * instance based on a set of common and unique field names provided.\n     *\n     * Each DataModel created contains a set of fields which are common to all and a set of unique fields.\n     * It also accepts configurations such as saveChild and mode(inverse or normal) to include/exclude the respective\n     * fields\n     *\n     * @example\n     *  // without predicate function:\n     *  const splitDt = dt.splitByColumn( [['Acceleration'], ['Horsepower']], ['Origin'])\n     *  console.log(splitDt));\n     * // This should give two unique DataModel instances, both having the field 'Origin' and\n     * // one each having 'Acceleration' and 'Horsepower' fields respectively\n     *\n     * @example\n     *  // without predicate function:\n     *  const splitDtInv = dt.splitByColumn( [['Acceleration'], ['Horsepower'],['Origin', 'Cylinders'],\n     *                           {mode: 'inverse'})\n     *  console.log(splitDtInv));\n     * // This should give DataModel instances in the following way:\n     * // All DataModel Instances do not have the fields 'Origin' and 'Cylinders'\n     * // One DataModel Instance has rest of the fields except 'Acceleration' and the other DataModel instance\n     * // has rest of the fields except 'Horsepower'\n     *\n     *\n     *\n     * @public\n     *\n     * @param {Array} uniqueFields - Set of unique fields included in each datamModel instance\n     * @param {Array} commonFields - Set of common fields included in all datamModel instances\n     * @param {Object} config - The configuration object\n     * @param {string} [config.saveChild] - Configuration to save child or not\n     * @param {string}[config.mode=FilteringMode.NORMAL] -The mode of the selection.\n     * @return {Array}  Returns the new DataModel instances after operation.\n     */\n    splitByColumn (uniqueFields = [], commonFields = [], config) {\n        const defConfig = {\n            mode: FilteringMode.NORMAL,\n            saveChild: true\n        };\n        const fieldConfig = this.getFieldsConfig();\n        const allFields = Object.keys(fieldConfig);\n        const normalizedProjFieldSets = [[commonFields]];\n\n        config = Object.assign({}, defConfig, config);\n        uniqueFields = uniqueFields.length ? uniqueFields : [[]];\n\n\n        uniqueFields.forEach((fieldSet, i) => {\n            normalizedProjFieldSets[i] = getNormalizedProFields(\n                [...fieldSet, ...commonFields],\n                allFields,\n                fieldConfig);\n        });\n\n        return splitWithProject(this, normalizedProjFieldSets, config, allFields);\n    }\n\n\n}\n\nexport default DataModel;\n","import { fnList } from '../operator/group-by-function';\n\nexport const { sum, avg, min, max, first, last, count, std: sd } = fnList;\n","import DataModel from './datamodel';\nimport {\n  compose,\n  bin,\n  select,\n  project,\n  groupby as groupBy,\n  calculateVariable,\n  sort,\n  crossProduct,\n  difference,\n  naturalJoin,\n  leftOuterJoin,\n  rightOuterJoin,\n  fullOuterJoin,\n  union,\n  rowDiffsetIterator\n} from './operator';\nimport * as Stats from './stats';\nimport * as enums from './enums';\nimport { DataConverter } from './converter';\nimport { DateTimeFormatter } from './utils';\nimport { DataFormat, FilteringMode, DM_DERIVATIVES } from './constants';\nimport InvalidAwareTypes from './invalid-aware-types';\nimport pkg from '../package.json';\nimport * as FieldsUtility from './fields';\n\nconst Operators = {\n    compose,\n    bin,\n    select,\n    project,\n    groupBy,\n    calculateVariable,\n    sort,\n    crossProduct,\n    difference,\n    naturalJoin,\n    leftOuterJoin,\n    rightOuterJoin,\n    fullOuterJoin,\n    union,\n    rowDiffsetIterator\n};\n\nconst version = pkg.version;\nObject.assign(DataModel, {\n    Operators,\n    Stats,\n    DM_DERIVATIVES,\n    DateTimeFormatter,\n    DataFormat,\n    FilteringMode,\n    InvalidAwareTypes,\n    version,\n    DataConverter,\n    FieldsUtility\n}, enums);\n\nexport default DataModel;\n","import { persistDerivations } from '../helper';\nimport { DM_DERIVATIVES } from '../constants';\n\n/**\n * DataModel's opearators are exposed as composable functional operators as well as chainable operators. Chainable\n * operators are called on the instances of {@link Datamodel} and {@link Relation} class.\n *\n * Those same operators can be used as composable operators from `DataModel.Operators` namespace.\n *\n * All these operators have similar behaviour. All these operators when called with the argument returns a function\n * which expects a DataModel instance.\n *\n * @public\n * @module Operators\n * @namespace DataModel\n */\n\n/**\n * This is functional version of selection operator. {@link link_to_selection | Selection} is a row filtering operation.\n * It takes {@link SelectionPredicate | predicate} for filtering criteria and returns a function.\n * The returned function is called with the DataModel instance on which the action needs to be performed.\n *\n * {@link SelectionPredicate} is a function which returns a boolean value. For selection opearation the selection\n * function is called for each row of DataModel instance with the current row passed as argument.\n *\n * After executing {@link SelectionPredicate} the rows are labeled as either an entry of selection set or an entry\n * of rejection set.\n *\n * {@link FilteringMode} operates on the selection and rejection set to determine which one would reflect in the\n * resulatant datamodel.\n *\n * @warning\n * [Warn] Selection and rejection set is only a logical idea for concept explanation purpose.\n *\n * @error\n * [Error] `FilteringMode.ALL` is not a valid working mode for functional version of `select`. Its only avialable on the\n * chained version.\n *\n * @example\n * const select = DataModel.Operators.select;\n * usaCarsFn = select(fields => fields.Origin.value === 'USA');\n * usaCarsDm = usaCarsFn(dm);\n * console.log(usaCarsDm);\n *\n * @public\n * @namespace DataModel\n * @module Operators\n *\n * @param {SelectionPredicate} selectFn - Predicate funciton which is called for each row with the current row\n *      ```\n *          function (row, i)  { ... }\n *      ```\n * @param {Object} [config] - The configuration object to control the inclusion exclusion of a row in resultant\n *      DataModel instance\n * @param {FilteringMode} [config.mode=FilteringMode.NORMAL] - The mode of the selection\n *\n * @return {PreparatorFunction} Function which expects an instance of DataModel on which the operator needs to be\n *      applied.\n */\nexport const select = (...args) => dm => dm.select(...args);\n\n/**\n * This is functional version of projection operator. {@link link_to_projection | Projection} is a column filtering\n * operation.It expects list of fields name and either include those or exclude those based on {@link FilteringMode} on\n * the  resultant variable.It returns a function which is called with the DataModel instance on which the action needs\n * to be performed.\n *\n * Projection expects array of fields name based on which it creates the selection and rejection set. All the field\n * whose name is present in array goes in selection set and rest of the fields goes in rejection set.\n *\n * {@link FilteringMode} operates on the selection and rejection set to determine which one would reflect in the\n * resulatant datamodel.\n *\n * @warning\n * Selection and rejection set is only a logical idea for concept explanation purpose.\n *\n * @error\n * `FilteringMode.ALL` is not a valid working mode for functional version of `select`. Its only avialable on the\n * chained version.\n *\n * @public\n * @namespace DataModel\n * @module Operators\n *\n * @param {Array.<string | Regexp>} projField - An array of column names in string or regular expression.\n * @param {Object} [config] - An optional config to control the creation of new DataModel\n * @param {FilteringMode} [config.mode=FilteringMode.NORMAL] - Mode of the projection\n *\n * @return {PreparatorFunction} Function which expects an instance of DataModel on which the operator needs to be\n *      applied.\n */\nexport const project = (...args) => dm => dm.project(...args);\n\n/**\n * This is functional version of binnig operator. Binning happens on a measure field based on a binning configuration.\n * Binning in DataModel does not aggregate the number of rows present in DataModel instance after binning, it just adds\n * a new field with the binned value. Refer binning {@link example_of_binning | example} to have a intuition of what\n * binning is and the use case.\n *\n * Binning can be configured by\n * - providing custom bin configuration with non uniform buckets\n * - providing bin count\n * - providing each bin size\n *\n * When custom buckets are provided as part of binning configuration\n * @example\n *  // DataModel already prepared and assigned to dm vairable\n *  const buckets = {\n *      start: 30\n *      stops: [80, 100, 110]\n *  };\n *  const config = { buckets, name: 'binnedHP' }\n *  const binFn = bin('horsepower', config);\n *  const binnedDm = binFn(dm);\n *\n * @text\n * When `binCount` is defined as part of binning configuration\n * @example\n *  // DataModel already prepared and assigned to dm vairable\n *  const config = { binCount: 5, name: 'binnedHP' }\n *  const binFn = bin('horsepower', config);\n *  const binnedDm = binFn(Dm);\n *\n * @text\n * When `binSize` is defined as part of binning configuration\n * @example\n *  // DataModel already prepared and assigned to dm vairable\n *  const config = { binSize: 200, name: 'binnedHorsepower' }\n *  const binnedDm = dataModel.bin('horsepower', config);\n *  const binnedDm = binFn(Dm);\n *\n * @public\n * @namespace DataModel\n * @module Operators\n *\n * @param {String} name Name of measure which will be used to create bin\n * @param {Object} config Config required for bin creation\n * @param {Array.<Number>} config.bucketObj.stops Defination of bucket ranges. Two subsequent number from arrays\n *      are picked and a range is created. The first number from range is inclusive and the second number from range\n *      is exclusive.\n * @param {Number} [config.bucketObj.startAt] Force the start of the bin from a particular number.\n *      If not mentioned, the start of the bin or the lower domain of the data if stops is not mentioned, else its\n *      the first value of the stop.\n * @param {Number} config.binSize Bucket size for each bin\n * @param {Number} config.binCount Number of bins which will be created\n * @param {String} config.name Name of the new binned field to be created\n *\n * @return {PreparatorFunction} Function which expects an instance of DataModel on which the operator needs to be\n *      applied.\n */\nexport const bin = (...args) => dm => dm.bin(...args);\n\n/**\n * This is functional version of `groupBy` operator.Groups the data using particular dimensions and by reducing\n * measures. It expects a list of dimensions using which it projects the datamodel and perform aggregations to reduce\n * the duplicate tuples. Refer this {@link link_to_one_example_with_group_by | document} to know the intuition behind\n * groupBy.\n *\n * DataModel by default provides definition of few {@link reducer | Reducers}.\n * {@link ReducerStore | User defined reducers} can also be registered.\n *\n * This is the chained implementation of `groupBy`.\n * `groupBy` also supports {@link link_to_compose_groupBy | composability}\n *\n * @example\n * const groupBy = DataModel.Operators.groupBy;\n * const groupedFn = groupBy(['Year'], { horsepower: 'max' } );\n * groupedDM = groupByFn(dm);\n *\n * @public\n *\n * @param {Array.<string>} fieldsArr - Array containing the name of dimensions\n * @param {Object} [reducers={}] - A map whose key is the variable name and value is the name of the reducer. If its\n *      not passed, or any variable is ommitted from the object, default aggregation function is used from the\n *      schema of the variable.\n *\n * @return {PreparatorFunction} Function which expects an instance of DataModel on which the operator needs to be\n *      applied.\n */\nexport const groupBy = (...args) => dm => dm.groupBy(...args);\n\n/**\n * Enables composing operators to run multiple operations and save group of operataion as named opration on a DataModel.\n * The resulting DataModel will be the result of all the operation provided. The operations provided will be executed in\n * a serial manner ie. result of one operation will be the input for the next operations (like pipe operator in unix).\n *\n * Suported operations in compose are\n * - `select`\n * - `project`\n * - `groupBy`\n * - `bin`\n * - `compose`\n *\n * @example\n * const compose = DataModel.Operators.compose;\n * const select = DataModel.Operators.select;\n * const project = DataModel.Operators.project;\n *\n * let composedFn = compose(\n *    select(fields => fields.netprofit.value <= 15),\n *    project(['netprofit', 'netsales']));\n *\n * const dataModel = new DataModel(data1, schema1);\n *\n * let composedDm = composedFn(dataModel);\n *\n * @public\n * @namespace DataModel\n * @module Operators\n *\n * @param {Array.<Operators>} operators: An array of operation that will be applied on the\n * datatable.\n *\n * @returns {DataModel} Instance of resultant DataModel\n */\nexport const compose = (...operations) =>\n    (dm, config = { saveChild: true }) => {\n        let currentDM = dm;\n        let firstChild;\n        const derivations = [];\n\n        operations.forEach((operation) => {\n            currentDM = operation(currentDM);\n            derivations.push(...currentDM._derivation);\n            if (!firstChild) {\n                firstChild = currentDM;\n            }\n        });\n\n        if (firstChild && firstChild !== currentDM) {\n            firstChild.dispose();\n        }\n\n        // reset all ancestorDerivation saved in-between compose\n        currentDM._ancestorDerivation = [];\n        persistDerivations(\n            dm,\n            currentDM,\n            DM_DERIVATIVES.COMPOSE,\n            null,\n            derivations\n        );\n\n        if (config.saveChild) {\n            currentDM.setParent(dm);\n        } else {\n            currentDM.setParent(null);\n        }\n\n        return currentDM;\n    };\n","/**\n * Wrapper on calculateVariable() method of DataModel to behave\n * the pure-function functionality.\n *\n * @param {Array} args - The argument list.\n * @return {any} Returns the returned value of calling function.\n */\nexport const calculateVariable = (...args) => dm => dm.calculateVariable(...args);\n\n/**\n * Wrapper on sort() method of DataModel to behave\n * the pure-function functionality.\n *\n * @param {Array} args - The argument list.\n * @return {any} Returns the returned value of calling function.\n */\nexport const sort = (...args) => dm => dm.sort(...args);\n","import { crossProduct } from './cross-product';\nimport { naturalJoinFilter } from './natural-join-filter-function';\n\nexport function naturalJoin (dataModel1, dataModel2) {\n    return crossProduct(dataModel1, dataModel2, naturalJoinFilter(dataModel1, dataModel2), true);\n}\n"],"sourceRoot":""}
\ No newline at end of file
diff --git a/example/index.html b/example/index.html
index d2d791d..2b4d5ae 100644
--- a/example/index.html
+++ b/example/index.html
@@ -13,7 +13,7 @@
 
 <body>
   <!-- <script src="./samples/sample-with-split.js"></script> -->
-  <script src="./samples/example3.js"></script>
+  <script src="./samples/example2.js"></script>
 </body>
 
 </html>
\ No newline at end of file
diff --git a/example/samples/example2.js b/example/samples/example2.js
index 0fd3bd2..fd84ae6 100644
--- a/example/samples/example2.js
+++ b/example/samples/example2.js
@@ -1,4 +1,59 @@
-const DataModel = window.DataModel.default;
+// const DataModel = window.DataModel.default;
+const columnMajor = (store) => {
+    let i = 0;
+    return (...fields) => {
+        fields.forEach((val, fieldIndex) => {
+            if (!(store[fieldIndex] instanceof Array)) {
+                store[fieldIndex] = Array.from({ length: i });
+            }
+            store[fieldIndex].push(val);
+        });
+        i++;
+    };
+};
+
+
+function FlatJSON222 (arr, schema) {
+    if (!Array.isArray(schema)) {
+        throw new Error('Schema missing or is in an unsupported format');
+    }
+
+    const header = {};
+    let i = 0;
+    let insertionIndex;
+    const columns = [];
+    const push = columnMajor(columns);
+    const schemaFieldsName = schema.map(unitSchema => unitSchema.name);
+
+    arr.forEach((item) => {
+        const fields = [];
+        schemaFieldsName.forEach((unitSchema) => {
+            if (unitSchema in header) {
+                insertionIndex = header[unitSchema];
+            } else {
+                header[unitSchema] = i++;
+                insertionIndex = i - 1;
+            }
+            fields[insertionIndex] = item[unitSchema];
+        });
+        push(...fields);
+    });
+
+    return [Object.keys(header), columns];
+}
+
+class JSONConverter2 extends DataModel.DataConverter{
+    constructor(){
+        super("json2")
+    }
+
+    convert(data , schema , options){
+        console.log("this is json2")
+        return FlatJSON222(data,schema,options);
+    }
+} 
+
+DataModel.Converters.register(new JSONConverter2());
 
 const schema = [
     {
@@ -50,13 +105,6 @@ const data = [
     }
 ];
 
-const dm = new DataModel(data, schema);
-const dataGenerated = dm.getData({
-    order: 'column',
-    formatter: {
-        birthday: val => new Date(val),
-        name: val => `Name: ${val}`
-    }
-});
+const dm = new DataModel(data, schema,{ dataFormat:"json2" });
 
-console.log(dataGenerated);
+console.log(dm.getData());
diff --git a/package.json b/package.json
index 39a1036..f16e55f 100644
--- a/package.json
+++ b/package.json
@@ -2,7 +2,7 @@
   "name": "datamodel",
   "description": "Relational algebra compliant in-memory tabular data store",
   "homepage": "https://github.com/chartshq/datamodel",
-  "version": "2.2.3",
+  "version": "2.3.0",
   "license": "MIT",
   "main": "dist/datamodel.js",
   "keywords": [
diff --git a/src/converter/dataConverterStore.js b/src/converter/dataConverterStore.js
new file mode 100644
index 0000000..96de471
--- /dev/null
+++ b/src/converter/dataConverterStore.js
@@ -0,0 +1,72 @@
+import DataConverter from './model/dataConverter';
+import { DSVStringConverter, DSVArrayConverter, JSONConverter, AutoDataConverter } from './defaultConverters';
+
+class DataConverterStore {
+    constructor() {
+        this.store = new Map();
+        this.converters(this._getDefaultConverters());
+    }
+
+    _getDefaultConverters() {
+        return [
+            new DSVStringConverter(),
+            new DSVArrayConverter(),
+            new JSONConverter(),
+            new AutoDataConverter()
+        ];
+    }
+
+    /**
+     * Sets the given converters in the store and returns the store
+     * @param  {Array<DataConverter>} converters : contains array of converter instance
+     * @return { Map<String,DataConverter> }
+     */
+    converters(converters = []) {
+        converters.forEach(converter => this.store.set(converter.type, converter));
+        return this.store;
+    }
+
+    /**
+     * Registers a Converter of type DataConverter
+     * @param {DataConverter} converter : converter Instance
+     * @returns self
+     */
+    register(converter) {
+        if (converter instanceof DataConverter) {
+            this.store.set(converter.type, converter);
+            return this;
+        }
+        return null;
+    }
+
+    /**
+     * Rempves a converter from store
+     * @param {DataConverter} converter : converter Instance
+     * @returns self
+     */
+
+    unregister(converter) {
+        this.store.delete(converter.type);
+        return this;
+    }
+
+    get(name) {
+        if (this.store.has(name)) {
+            return this.store.get(name);
+        }
+        return null;
+    }
+
+}
+
+const converterStore = (function () {
+    let store = null;
+
+    function getStore () {
+        store = new DataConverterStore();
+        return store;
+    }
+    return store || getStore();
+}());
+
+export default converterStore;
diff --git a/src/converter/dataConverterStore.spec.js b/src/converter/dataConverterStore.spec.js
new file mode 100644
index 0000000..89966fa
--- /dev/null
+++ b/src/converter/dataConverterStore.spec.js
@@ -0,0 +1,31 @@
+/* global describe, it */
+/* eslint-disable no-unused-expressions */
+
+import { expect } from 'chai';
+import converterStore from './dataConverterStore';
+import DataConverter from '../converter/model/dataConverter';
+
+describe('#DataConverterStore', () => {
+    it('should register and unregister converter', () => {
+        class JSONConverter2 extends DataConverter {
+            constructor() {
+                super('json2');
+            }
+
+            convert() {
+                return '';
+            }
+        }
+
+        const converter = new JSONConverter2();
+        converterStore.register(converter);
+        expect(converterStore.get('json2')).to.not.null;
+
+        converterStore.unregister(converter);
+        expect(converterStore.get('json2')).to.null;
+    });
+
+    it('should not register invalid Coverter', () => {
+        expect(converterStore.register(() => {})).to.null;
+    });
+});
diff --git a/src/converter/defaultConverters/autoConverter.js b/src/converter/defaultConverters/autoConverter.js
new file mode 100644
index 0000000..1777377
--- /dev/null
+++ b/src/converter/defaultConverters/autoConverter.js
@@ -0,0 +1,13 @@
+import DataConverter from '../model/dataConverter';
+import AUTO from '../utils/auto-resolver';
+import DataFormat from '../../enums/data-format';
+
+export default class AutoDataConverter extends DataConverter {
+    constructor() {
+        super(DataFormat.AUTO);
+    }
+
+    convert(data, schema, options) {
+        return AUTO(data, schema, options);
+    }
+}
diff --git a/src/converter/defaultConverters/dsvArrayConverter.js b/src/converter/defaultConverters/dsvArrayConverter.js
new file mode 100644
index 0000000..9dd2db1
--- /dev/null
+++ b/src/converter/defaultConverters/dsvArrayConverter.js
@@ -0,0 +1,13 @@
+import DataConverter from '../model/dataConverter';
+import DSVArr from '../utils/dsv-arr';
+import DataFormat from '../../enums/data-format';
+
+export default class DSVArrayConverter extends DataConverter {
+    constructor() {
+        super(DataFormat.DSV_ARR);
+    }
+
+    convert(data, schema, options) {
+        return DSVArr(data, schema, options);
+    }
+}
diff --git a/src/converter/defaultConverters/dsvStringConverter.js b/src/converter/defaultConverters/dsvStringConverter.js
new file mode 100644
index 0000000..fa052a2
--- /dev/null
+++ b/src/converter/defaultConverters/dsvStringConverter.js
@@ -0,0 +1,13 @@
+import DataConverter from '../model/dataConverter';
+import DSVStr from '../utils/dsv-str';
+import DataFormat from '../../enums/data-format';
+
+export default class DSVStringConverter extends DataConverter {
+    constructor() {
+        super(DataFormat.DSV_STR);
+    }
+
+    convert(data, schema, options) {
+        return DSVStr(data, schema, options);
+    }
+}
diff --git a/src/converter/defaultConverters/index.js b/src/converter/defaultConverters/index.js
new file mode 100644
index 0000000..fdcf21f
--- /dev/null
+++ b/src/converter/defaultConverters/index.js
@@ -0,0 +1,4 @@
+export { default as DSVStringConverter } from './dsvStringConverter';
+export { default as JSONConverter } from './jsonConverter';
+export { default as DSVArrayConverter } from './dsvArrayConverter';
+export { default as AutoDataConverter } from './autoConverter';
diff --git a/src/converter/defaultConverters/jsonConverter.js b/src/converter/defaultConverters/jsonConverter.js
new file mode 100644
index 0000000..e4b1d2e
--- /dev/null
+++ b/src/converter/defaultConverters/jsonConverter.js
@@ -0,0 +1,13 @@
+import DataConverter from '../model/dataConverter';
+import FlatJSON from '../utils/flat-json';
+import DataFormat from '../../enums/data-format';
+
+export default class JSONConverter extends DataConverter {
+    constructor() {
+        super(DataFormat.FLAT_JSON);
+    }
+
+    convert(data, schema, options) {
+        return FlatJSON(data, schema, options);
+    }
+}
diff --git a/src/converter/defaultConverters/jsonConverter.spec.js b/src/converter/defaultConverters/jsonConverter.spec.js
new file mode 100644
index 0000000..c398456
--- /dev/null
+++ b/src/converter/defaultConverters/jsonConverter.spec.js
@@ -0,0 +1,56 @@
+/* global describe, it ,beforeEach */
+/* eslint-disable no-unused-expressions */
+
+import { expect } from 'chai';
+import JSONConverter from './jsonConverter';
+
+describe('JSON Converter', () => {
+    let data;
+    let converter = new JSONConverter();
+    beforeEach(() => {
+        data = [
+            {
+                a: 1,
+                b: 2,
+                c: 3
+            },
+            {
+                a: 4,
+                b: 5,
+                c: 6
+            },
+            {
+                a: 7,
+                b: 8,
+                c: 9
+            }
+        ];
+    });
+
+    describe('#JSON', () => {
+        it('should convert to JSON data', () => {
+            const schema = [
+                {
+                    name: 'a',
+                    type: 'measure',
+                    subtype: 'continuous'
+                },
+                {
+                    name: 'b',
+                    type: 'measure',
+                    subtype: 'continuous'
+                },
+                {
+                    name: 'c',
+                    type: 'measure',
+                    subtype: 'continuous'
+                }
+            ];
+
+            const parsedData = converter.convert(data, schema);
+            const expected = [['a', 'b', 'c'], [[1, 4, 7], [2, 5, 8], [3, 6, 9]]];
+
+            expect(parsedData).to.deep.equal(expected);
+        });
+    });
+});
diff --git a/src/converter/index.js b/src/converter/index.js
index c5cc212..135b30a 100644
--- a/src/converter/index.js
+++ b/src/converter/index.js
@@ -1,4 +1,4 @@
-export { default as DSVArr } from './dsv-arr';
-export { default as DSVStr } from './dsv-str';
-export { default as FlatJSON } from './flat-json';
-export { default as Auto } from './auto-resolver';
+import converterStore from './dataConverterStore';
+import DataConverter from './model/dataConverter';
+
+export { DataConverter, converterStore };
diff --git a/src/converter/model/dataConverter.js b/src/converter/model/dataConverter.js
new file mode 100644
index 0000000..0aa9385
--- /dev/null
+++ b/src/converter/model/dataConverter.js
@@ -0,0 +1,17 @@
+/**
+ * Interface for all data converters
+ */
+export default class DataConverter {
+    constructor(type) {
+        this._type = type;
+    }
+
+    get type() {
+        return this._type;
+    }
+
+    convert() {
+        throw new Error('Convert method not implemented.');
+    }
+
+}
diff --git a/src/converter/model/dataConverter.spec.js b/src/converter/model/dataConverter.spec.js
new file mode 100644
index 0000000..cabd996
--- /dev/null
+++ b/src/converter/model/dataConverter.spec.js
@@ -0,0 +1,11 @@
+/* global describe, it */
+/* eslint-disable no-unused-expressions */
+
+import { expect } from 'chai';
+import DataConverter from './dataConverter';
+
+describe('#DataConverterModel', () => {
+    it('should throw error', () => {
+        expect(new DataConverter().convert).to.throw(Error, 'Convert method not implemented');
+    });
+});
diff --git a/src/converter/auto-resolver.js b/src/converter/utils/auto-resolver.js
similarity index 93%
rename from src/converter/auto-resolver.js
rename to src/converter/utils/auto-resolver.js
index 2dc6ee2..7453858 100644
--- a/src/converter/auto-resolver.js
+++ b/src/converter/utils/auto-resolver.js
@@ -1,7 +1,7 @@
 import FlatJSON from './flat-json';
 import DSVArr from './dsv-arr';
 import DSVStr from './dsv-str';
-import { detectDataFormat } from '../utils';
+import { detectDataFormat } from '../../utils';
 
 /**
  * Parses the input data and detect the format automatically.
diff --git a/src/converter/auto-resolver.spec.js b/src/converter/utils/auto-resolver.spec.js
similarity index 100%
rename from src/converter/auto-resolver.spec.js
rename to src/converter/utils/auto-resolver.spec.js
diff --git a/src/converter/dsv-arr.js b/src/converter/utils/dsv-arr.js
similarity index 97%
rename from src/converter/dsv-arr.js
rename to src/converter/utils/dsv-arr.js
index 9366fa5..130096a 100644
--- a/src/converter/dsv-arr.js
+++ b/src/converter/utils/dsv-arr.js
@@ -1,4 +1,4 @@
-import { columnMajor } from '../utils';
+import { columnMajor } from '../../utils';
 
 /**
  * Parses and converts data formatted in DSV array to a manageable internal format.
diff --git a/src/converter/dsv-arr.spec.js b/src/converter/utils/dsv-arr.spec.js
similarity index 100%
rename from src/converter/dsv-arr.spec.js
rename to src/converter/utils/dsv-arr.spec.js
diff --git a/src/converter/dsv-str.js b/src/converter/utils/dsv-str.js
similarity index 100%
rename from src/converter/dsv-str.js
rename to src/converter/utils/dsv-str.js
diff --git a/src/converter/dsv-str.spec.js b/src/converter/utils/dsv-str.spec.js
similarity index 100%
rename from src/converter/dsv-str.spec.js
rename to src/converter/utils/dsv-str.spec.js
diff --git a/src/converter/flat-json.js b/src/converter/utils/flat-json.js
similarity index 96%
rename from src/converter/flat-json.js
rename to src/converter/utils/flat-json.js
index 14f0bc8..c76ef9d 100644
--- a/src/converter/flat-json.js
+++ b/src/converter/utils/flat-json.js
@@ -1,4 +1,4 @@
-import { columnMajor } from '../utils';
+import { columnMajor } from '../../utils';
 
 /**
  * Parses and converts data formatted in JSON to a manageable internal format.
diff --git a/src/converter/flat-json.spec.js b/src/converter/utils/flat-json.spec.js
similarity index 100%
rename from src/converter/flat-json.spec.js
rename to src/converter/utils/flat-json.spec.js
diff --git a/src/create-fields.spec.js b/src/create-fields.spec.js
index b0ea799..c7a4fbd 100644
--- a/src/create-fields.spec.js
+++ b/src/create-fields.spec.js
@@ -2,16 +2,19 @@
 /* eslint-disable no-unused-expressions */
 
 import { expect } from 'chai';
-import { Categorical, Temporal, Binned, Continuous } from './fields';
+import Categorical from './fields/categorical';
+import Temporal from './fields/temporal';
+import Binned from './fields/binned';
+import Continuous from './fields/continuous';
 import { createFields, createUnitFieldFromPartial } from './field-creator';
 import { MeasureSubtype, DimensionSubtype } from './enums';
+import PartialField from './fields/partial-field';
 
 describe('Creating Field', () => {
     describe('#createUnitFieldFromPartial', () => {
         it('should return an array of correct field instances', () => {
-            let mockedPartialField = {
-                schema: { name: 'Country' }
-            };
+            let mockedPartialField = new PartialField('Country', [], { name: 'Country' }, null);
+            // mockedPartialField.schema = { name: 'Country' }
             let mockedRowDiffset = '1-2';
             expect(createUnitFieldFromPartial(mockedPartialField, mockedRowDiffset) instanceof Categorical).to.be.true;
 
diff --git a/src/datamodel.js b/src/datamodel.js
index 31e986e..e362e0b 100644
--- a/src/datamodel.js
+++ b/src/datamodel.js
@@ -25,6 +25,8 @@ import reducerStore from './utils/reducer-store';
 import { createFields } from './field-creator';
 import InvalidAwareTypes from './invalid-aware-types';
 import Value from './value';
+import { converterStore } from './converter';
+import { fieldRegistry } from './fields';
 
 /**
  * DataModel is an in-browser representation of tabular data. It supports
@@ -94,6 +96,20 @@ class DataModel extends Relation {
         return reducerStore;
     }
 
+    /**
+     * Converters are functions that transforms data in various format tpo datamodel consumabe format.
+     */
+    static get Converters() {
+        return converterStore;
+    }
+
+    /**
+     * Register new type of fields
+     */
+    static get FieldTypes() {
+        return fieldRegistry;
+    }
+
     /**
      * Configure null, undefined, invalid values in the source data
      *
@@ -558,13 +574,15 @@ class DataModel extends Relation {
         };
 
         addToNameSpace && addToPropNamespace(propagationNameSpace, config, this);
-        propagateToAllDataModels(identifiers, rootModels, { propagationNameSpace, sourceId: propagationSourceId },
+        propagateToAllDataModels(identifiers, rootModels, { propagationNameSpace,
+            sourceId: propagationSourceId,
+            propagationSource: this },
             Object.assign({
                 payload
             }, config));
 
         if (isMutableAction) {
-            propagateImmutableActions(propagationNameSpace, rootModels, {
+            propagateImmutableActions(propagationNameSpace, rootModel, {
                 config,
                 propConfig
             }, this);
diff --git a/src/enums/dimension-subtype.js b/src/enums/dimension-subtype.js
index 70c4da3..9a9f17b 100644
--- a/src/enums/dimension-subtype.js
+++ b/src/enums/dimension-subtype.js
@@ -7,7 +7,6 @@
 const DimensionSubtype = {
     CATEGORICAL: 'categorical',
     TEMPORAL: 'temporal',
-    GEO: 'geo',
     BINNED: 'binned'
 };
 
diff --git a/src/export.js b/src/export.js
index ed7d7c6..7767443 100644
--- a/src/export.js
+++ b/src/export.js
@@ -13,14 +13,17 @@ import {
   leftOuterJoin,
   rightOuterJoin,
   fullOuterJoin,
-  union
+  union,
+  rowDiffsetIterator
 } from './operator';
 import * as Stats from './stats';
 import * as enums from './enums';
+import { DataConverter } from './converter';
 import { DateTimeFormatter } from './utils';
 import { DataFormat, FilteringMode, DM_DERIVATIVES } from './constants';
 import InvalidAwareTypes from './invalid-aware-types';
 import pkg from '../package.json';
+import * as FieldsUtility from './fields';
 
 const Operators = {
     compose,
@@ -36,7 +39,8 @@ const Operators = {
     leftOuterJoin,
     rightOuterJoin,
     fullOuterJoin,
-    union
+    union,
+    rowDiffsetIterator
 };
 
 const version = pkg.version;
@@ -48,7 +52,9 @@ Object.assign(DataModel, {
     DataFormat,
     FilteringMode,
     InvalidAwareTypes,
-    version
+    version,
+    DataConverter,
+    FieldsUtility
 }, enums);
 
 export default DataModel;
diff --git a/src/field-creator.js b/src/field-creator.js
index 6d69eac..06f6fa6 100644
--- a/src/field-creator.js
+++ b/src/field-creator.js
@@ -1,15 +1,5 @@
 import { FieldType, DimensionSubtype, MeasureSubtype } from './enums';
-import {
-    Categorical,
-    Temporal,
-    Binned,
-    Continuous,
-    CategoricalParser,
-    TemporalParser,
-    BinnedParser,
-    ContinuousParser,
-    PartialField
-} from './fields';
+import { fieldRegistry } from './fields';
 
 /**
  * Creates a field instance according to the provided data and schema.
@@ -20,37 +10,24 @@ import {
  */
 function createUnitField(data, schema) {
     data = data || [];
-    let partialField;
 
-    switch (schema.type) {
-    case FieldType.MEASURE:
-        switch (schema.subtype) {
-        case MeasureSubtype.CONTINUOUS:
-            partialField = new PartialField(schema.name, data, schema, new ContinuousParser());
-            return new Continuous(partialField, `0-${data.length - 1}`);
-        default:
-            partialField = new PartialField(schema.name, data, schema, new ContinuousParser());
-            return new Continuous(partialField, `0-${data.length - 1}`);
-        }
-    case FieldType.DIMENSION:
-        switch (schema.subtype) {
-        case DimensionSubtype.CATEGORICAL:
-            partialField = new PartialField(schema.name, data, schema, new CategoricalParser());
-            return new Categorical(partialField, `0-${data.length - 1}`);
-        case DimensionSubtype.TEMPORAL:
-            partialField = new PartialField(schema.name, data, schema, new TemporalParser(schema));
-            return new Temporal(partialField, `0-${data.length - 1}`);
-        case DimensionSubtype.BINNED:
-            partialField = new PartialField(schema.name, data, schema, new BinnedParser());
-            return new Binned(partialField, `0-${data.length - 1}`);
-        default:
-            partialField = new PartialField(schema.name, data, schema, new CategoricalParser());
-            return new Categorical(partialField, `0-${data.length - 1}`);
-        }
-    default:
-        partialField = new PartialField(schema.name, data, schema, new CategoricalParser());
-        return new Categorical(partialField, `0-${data.length - 1}`);
+    if (fieldRegistry.has(schema.subtype)) {
+        return fieldRegistry.get(schema.subtype)
+                        .BUILDER
+                        .fieldName(schema.name)
+                        .schema(schema)
+                        .data(data)
+                        .rowDiffset(`0-${data.length - 1}`)
+                        .build();
     }
+    return fieldRegistry
+                    .get(schema.type === FieldType.MEASURE ? MeasureSubtype.CONTINUOUS : DimensionSubtype.CATEGORICAL)
+                    .BUILDER
+                    .fieldName(schema.name)
+                    .schema(schema)
+                    .data(data)
+                    .rowDiffset(`0-${data.length - 1}`)
+                    .build();
 }
 
 
@@ -64,28 +41,19 @@ function createUnitField(data, schema) {
 export function createUnitFieldFromPartial(partialField, rowDiffset) {
     const { schema } = partialField;
 
-    switch (schema.type) {
-    case FieldType.MEASURE:
-        switch (schema.subtype) {
-        case MeasureSubtype.CONTINUOUS:
-            return new Continuous(partialField, rowDiffset);
-        default:
-            return new Continuous(partialField, rowDiffset);
-        }
-    case FieldType.DIMENSION:
-        switch (schema.subtype) {
-        case DimensionSubtype.CATEGORICAL:
-            return new Categorical(partialField, rowDiffset);
-        case DimensionSubtype.TEMPORAL:
-            return new Temporal(partialField, rowDiffset);
-        case DimensionSubtype.BINNED:
-            return new Binned(partialField, rowDiffset);
-        default:
-            return new Categorical(partialField, rowDiffset);
-        }
-    default:
-        return new Categorical(partialField, rowDiffset);
+    if (fieldRegistry.has(schema.subtype)) {
+        return fieldRegistry.get(schema.subtype)
+                        .BUILDER
+                        .partialField(partialField)
+                        .rowDiffset(rowDiffset)
+                        .build();
     }
+    return fieldRegistry
+                    .get(schema.type === FieldType.MEASURE ? MeasureSubtype.CONTINUOUS : DimensionSubtype.CATEGORICAL)
+                    .BUILDER
+                    .partialField(partialField)
+                    .rowDiffset(rowDiffset)
+                    .build();
 }
 
 /**
diff --git a/src/fields/binned/index.js b/src/fields/binned/index.js
index 04d1fbf..8438416 100644
--- a/src/fields/binned/index.js
+++ b/src/fields/binned/index.js
@@ -1,4 +1,5 @@
 import Dimension from '../dimension';
+import BinnedParser from '../parsers/binned-parser';
 
 /**
  * Represents binned field subtype.
@@ -29,4 +30,8 @@ export default class Binned extends Dimension {
     bins () {
         return this.partialField.schema.bins;
     }
+
+    static parser() {
+        return new BinnedParser();
+    }
 }
diff --git a/src/fields/categorical/index.js b/src/fields/categorical/index.js
index 267cbfc..e62f50d 100644
--- a/src/fields/categorical/index.js
+++ b/src/fields/categorical/index.js
@@ -1,6 +1,7 @@
 import { rowDiffsetIterator } from '../../operator/row-diffset-iterator';
 import { DimensionSubtype } from '../../enums';
 import Dimension from '../dimension';
+import CategoricalParser from '../parsers/categorical-parser';
 /**
  * Represents categorical field subtype.
  *
@@ -41,4 +42,8 @@ export default class Categorical extends Dimension {
         });
         return domain;
     }
+
+    static parser() {
+        return new CategoricalParser();
+    }
 }
diff --git a/src/fields/continuous/index.js b/src/fields/continuous/index.js
index d0f68b3..d83ca6d 100644
--- a/src/fields/continuous/index.js
+++ b/src/fields/continuous/index.js
@@ -1,7 +1,7 @@
-import { rowDiffsetIterator } from '../../operator/row-diffset-iterator';
 import { MeasureSubtype } from '../../enums';
 import Measure from '../measure';
-import InvalidAwareTypes from '../../invalid-aware-types';
+import ContinuousParser from '../parsers/continuous-parser';
+import { calculateContinuousDomain } from '../helper';
 
 /**
  * Represents continuous field subtype.
@@ -30,24 +30,10 @@ export default class Continuous extends Measure {
      * @return {Array} Returns the min and max values.
      */
     calculateDataDomain () {
-        let min = Number.POSITIVE_INFINITY;
-        let max = Number.NEGATIVE_INFINITY;
-
-        // here don't use this.data() as the iteration will be occurred two times on same data.
-        rowDiffsetIterator(this.rowDiffset, (i) => {
-            const datum = this.partialField.data[i];
-            if (datum instanceof InvalidAwareTypes) {
-                return;
-            }
-
-            if (datum < min) {
-                min = datum;
-            }
-            if (datum > max) {
-                max = datum;
-            }
-        });
+        return calculateContinuousDomain(this.partialField.data, this.rowDiffset);
+    }
 
-        return [min, max];
+    static parser() {
+        return new ContinuousParser();
     }
 }
diff --git a/src/fields/field-registry.js b/src/fields/field-registry.js
new file mode 100644
index 0000000..984f492
--- /dev/null
+++ b/src/fields/field-registry.js
@@ -0,0 +1,46 @@
+import Categorical from './categorical';
+import Temporal from './temporal';
+import Binned from './binned';
+import Continuous from './continuous';
+import { DimensionSubtype, MeasureSubtype } from '../enums';
+
+
+class FieldTypeRegistry {
+    constructor() {
+        this._fieldType = new Map();
+    }
+
+    registerFieldType(subtype, dimension) {
+        this._fieldType.set(subtype, dimension);
+        return this;
+    }
+
+    has(type) {
+        return this._fieldType.has(type);
+    }
+
+    get(type) {
+        return this._fieldType.get(type);
+    }
+}
+
+const registerDefaultFields = (store) => {
+    store
+                    .registerFieldType(DimensionSubtype.CATEGORICAL, Categorical)
+                    .registerFieldType(DimensionSubtype.TEMPORAL, Temporal)
+                    .registerFieldType(DimensionSubtype.BINNED, Binned)
+                    .registerFieldType(MeasureSubtype.CONTINUOUS, Continuous);
+};
+
+const fieldRegistry = (function () {
+    let store = null;
+    function getStore () {
+        store = new FieldTypeRegistry();
+        registerDefaultFields(store);
+        return store;
+    }
+    return store || getStore();
+}());
+
+export default fieldRegistry;
+
diff --git a/src/fields/field-registry.spec.js b/src/fields/field-registry.spec.js
new file mode 100644
index 0000000..e69de29
diff --git a/src/fields/field/index.js b/src/fields/field/index.js
index 267afb0..beb7294 100644
--- a/src/fields/field/index.js
+++ b/src/fields/field/index.js
@@ -1,4 +1,5 @@
 import { rowDiffsetIterator } from '../../operator/row-diffset-iterator';
+import PartialField from '../partial-field';
 
 /**
  * In {@link DataModel}, every tabular data consists of column, a column is stored as field.
@@ -32,6 +33,10 @@ export default class Field {
         this.rowDiffset = rowDiffset;
     }
 
+    static parser() {
+        throw new Error('Not yet implemented');
+    }
+
     /**
      * Generates the field type specific domain.
      *
@@ -125,4 +130,47 @@ export default class Field {
     formattedData () {
         throw new Error('Not yet implemented');
     }
+
+    static get BUILDER() {
+        const builder = {
+            _params: {},
+            _context: this,
+            fieldName(name) {
+                this._params.name = name;
+                return this;
+            },
+            schema(schema) {
+                this._params.schema = schema;
+                return this;
+            },
+            data(data) {
+                this._params.data = data;
+                return this;
+            },
+            partialField(partialField) {
+                this._params.partialField = partialField;
+                return this;
+            },
+            rowDiffset(rowDiffset) {
+                this._params.rowDiffset = rowDiffset;
+                return this;
+            },
+            build() {
+                let partialField = null;
+                if (this._params.partialField instanceof PartialField) {
+                    partialField = this._params.partialField;
+                } else if (this._params.schema && this._params.data) {
+                    partialField = new PartialField(this._params.name,
+                                        this._params.data,
+                                        this._params.schema,
+                                        this._context.parser());
+                }
+                else {
+                    throw new Error('Invalid Field parameters');
+                }
+                return new this._context(partialField, this._params.rowDiffset);
+            }
+        };
+        return builder;
+    }
 }
diff --git a/src/fields/helper.js b/src/fields/helper.js
new file mode 100644
index 0000000..9ed11eb
--- /dev/null
+++ b/src/fields/helper.js
@@ -0,0 +1,24 @@
+import { rowDiffsetIterator } from '../operator/row-diffset-iterator';
+import InvalidAwareTypes from '../invalid-aware-types';
+
+export const calculateContinuousDomain = (data, rowDiffset) => {
+    let min = Number.POSITIVE_INFINITY;
+    let max = Number.NEGATIVE_INFINITY;
+
+    // here don't use this.data() as the iteration will be occurred two times on same data.
+    rowDiffsetIterator(rowDiffset, (i) => {
+        const datum = data[i];
+        if (datum instanceof InvalidAwareTypes) {
+            return;
+        }
+
+        if (datum < min) {
+            min = datum;
+        }
+        if (datum > max) {
+            max = datum;
+        }
+    });
+
+    return [min, max];
+};
diff --git a/src/fields/index.js b/src/fields/index.js
index fbe76bf..c62b24f 100644
--- a/src/fields/index.js
+++ b/src/fields/index.js
@@ -1,13 +1,5 @@
-export { default as Field } from './field';
 export { default as Dimension } from './dimension';
-export { default as Categorical } from './categorical';
-export { default as Temporal } from './temporal';
-export { default as Binned } from './binned';
 export { default as Measure } from './measure';
-export { default as Continuous } from './continuous';
 export { default as FieldParser } from './parsers/field-parser';
-export { default as CategoricalParser } from './parsers/categorical-parser';
-export { default as TemporalParser } from './parsers/temporal-parser';
-export { default as BinnedParser } from './parsers/binned-parser';
-export { default as ContinuousParser } from './parsers/continuous-parser';
-export { default as PartialField } from './partial-field';
+export { default as fieldRegistry } from './field-registry';
+export { columnMajor } from '../utils';
diff --git a/src/fields/parsers/temporal-parser/index.js b/src/fields/parsers/temporal-parser/index.js
index 0c02894..81fef24 100644
--- a/src/fields/parsers/temporal-parser/index.js
+++ b/src/fields/parsers/temporal-parser/index.js
@@ -10,17 +10,6 @@ import InvalidAwareTypes from '../../../invalid-aware-types';
  * @implements {FieldParser}
  */
 export default class TemporalParser extends FieldParser {
-    /**
-     * Initialize a new instance.
-     *
-     * @public
-     * @param {Object} schema - The schema object for the corresponding field.
-     */
-    constructor (schema) {
-        super();
-        this.schema = schema;
-        this._dtf = new DateTimeFormatter(this.schema.format);
-    }
 
     /**
      * Parses a single value of a field and returns the millisecond value.
@@ -29,9 +18,12 @@ export default class TemporalParser extends FieldParser {
      * @param {string|number} val - The value of the field.
      * @return {number} Returns the millisecond value.
      */
-    parse (val) {
+    parse (val, { format }) {
         let result;
         // check if invalid date value
+        if (!this._dtf) {
+            this._dtf = new DateTimeFormatter(format);
+        }
         if (!InvalidAwareTypes.isInvalid(val)) {
             let nativeDate = this._dtf.getNativeDate(val);
             result = nativeDate ? nativeDate.getTime() : InvalidAwareTypes.NA;
diff --git a/src/fields/parsers/temporal-parser/index.spec.js b/src/fields/parsers/temporal-parser/index.spec.js
index 5805cf6..728eeaf 100644
--- a/src/fields/parsers/temporal-parser/index.spec.js
+++ b/src/fields/parsers/temporal-parser/index.spec.js
@@ -17,37 +17,37 @@ describe('TemporalParser', () => {
     let temParser;
 
     beforeEach(() => {
-        temParser = new TemporalParser(schema);
+        temParser = new TemporalParser();
     });
 
     describe('#parse', () => {
         it('should return milliseconds for the formatted value', () => {
             const dateStr = '2017-03-01';
             const expectedTs = new DateTimeFormatter(schema.format).getNativeDate(dateStr).getTime();
-            expect(temParser.parse(dateStr)).to.equal(expectedTs);
+            expect(temParser.parse(dateStr, { format: schema.format })).to.equal(expectedTs);
         });
 
         it('should bypass to Date API when format is not present', () => {
             const val = 1540629018697;
-            temParser = new TemporalParser(Object.assign({}, schema, { format: undefined }));
-            expect(temParser.parse(val)).to.equal(+new Date(val));
+            temParser = new TemporalParser();
+            expect(temParser.parse(val, { format: undefined })).to.equal(+new Date(val));
         });
 
         it('should return default invalid type for invalid value', () => {
-            expect(temParser.parse(null)).to.eql(DataModel.InvalidAwareTypes.NULL);
-            expect(temParser.parse(undefined)).to.equal(DataModel.InvalidAwareTypes.NA);
-            expect(temParser.parse('abcd')).to.equal(DataModel.InvalidAwareTypes.NA);
+            expect(temParser.parse(null, { format: schema.format })).to.eql(DataModel.InvalidAwareTypes.NULL);
+            expect(temParser.parse(undefined, { format: schema.format })).to.equal(DataModel.InvalidAwareTypes.NA);
+            expect(temParser.parse('abcd', { format: schema.format })).to.equal(DataModel.InvalidAwareTypes.NA);
         });
         it('should return valid date for edge case', () => {
-            expect(temParser.parse('')).to.equal(DataModel.InvalidAwareTypes.NA);
+            expect(temParser.parse('', { format: schema.format })).to.equal(DataModel.InvalidAwareTypes.NA);
 
-            temParser = new TemporalParser(Object.assign({}, schema, { format: '%Y' }));
-            expect(temParser.parse('1998')).to.equal(new Date(1998, 0, 1).getTime());
+            temParser = new TemporalParser();
+            expect(temParser.parse('1998', { format: '%Y' })).to.equal(new Date(1998, 0, 1).getTime());
 
-            temParser = new TemporalParser(Object.assign({}, schema, { format: '%y' }));
-            expect(temParser.parse('98')).to.equal(new Date(1998, 0, 1).getTime());
+            temParser = new TemporalParser();
+            expect(temParser.parse('98', { format: '%y' })).to.equal(new Date(1998, 0, 1).getTime());
 
-            expect(temParser.parse('abcd')).to.equal(DataModel.InvalidAwareTypes.NA);
+            expect(temParser.parse('abcd', { format: '%y' })).to.equal(DataModel.InvalidAwareTypes.NA);
         });
     });
 });
diff --git a/src/fields/partial-field/index.js b/src/fields/partial-field/index.js
index 2795f92..a31457c 100644
--- a/src/fields/partial-field/index.js
+++ b/src/fields/partial-field/index.js
@@ -31,6 +31,6 @@ export default class PartialField {
      * @return {Array} Returns the sanitized data.
      */
     _sanitize (data) {
-        return data.map(datum => this.parser.parse(datum));
+        return data.map(datum => this.parser.parse(datum, { format: this.schema.format }));
     }
 }
diff --git a/src/fields/partial-field/index.spec.js b/src/fields/partial-field/index.spec.js
index 7f286d7..49edf06 100644
--- a/src/fields/partial-field/index.spec.js
+++ b/src/fields/partial-field/index.spec.js
@@ -19,7 +19,7 @@ describe('PartialField', () => {
     let temParser;
 
     beforeEach(() => {
-        temParser = new TemporalParser(schema);
+        temParser = new TemporalParser();
         partField = new PartialField(schema.name, data, schema, temParser);
     });
 
@@ -31,7 +31,7 @@ describe('PartialField', () => {
         });
 
         it('should sanitize the input data before use', () => {
-            const expected = data.map(d => temParser.parse(d));
+            const expected = data.map(d => temParser.parse(d, { format: schema.format }));
             expect(partField.data).to.eql(expected);
         });
     });
diff --git a/src/fields/temporal/index.js b/src/fields/temporal/index.js
index 0b3c540..4fcdd2b 100644
--- a/src/fields/temporal/index.js
+++ b/src/fields/temporal/index.js
@@ -2,6 +2,8 @@ import { rowDiffsetIterator } from '../../operator/row-diffset-iterator';
 import Dimension from '../dimension';
 import { DateTimeFormatter } from '../../utils';
 import InvalidAwareTypes from '../../invalid-aware-types';
+import TemporalParser from '../parsers/temporal-parser';
+import { calculateContinuousDomain } from '../helper';
 
 /**
  * Represents temporal field subtype.
@@ -32,20 +34,7 @@ export default class Temporal extends Dimension {
      * @return {Array} Returns the unique values.
      */
     calculateDataDomain () {
-        const hash = new Set();
-        const domain = [];
-
-        // here don't use this.data() as the iteration will be
-        // occurred two times on same data.
-        rowDiffsetIterator(this.rowDiffset, (i) => {
-            const datum = this.partialField.data[i];
-            if (!hash.has(datum)) {
-                hash.add(datum);
-                domain.push(datum);
-            }
-        });
-
-        return domain;
+        return calculateContinuousDomain(this.partialField.data, this.rowDiffset);
     }
 
 
@@ -121,5 +110,9 @@ export default class Temporal extends Dimension {
         });
         return data;
     }
+
+    static parser() {
+        return new TemporalParser();
+    }
 }
 
diff --git a/src/fields/temporal/index.spec.js b/src/fields/temporal/index.spec.js
index 86afd4d..f66bf80 100644
--- a/src/fields/temporal/index.spec.js
+++ b/src/fields/temporal/index.spec.js
@@ -34,7 +34,6 @@ describe('Temporal', () => {
         it('should return the field domain', () => {
             const expected = [
                 new Date(2017, 3 - 1, 1).getTime(),
-                new Date(2017, 3 - 1, 2).getTime(),
                 new Date(2017, 3 - 1, 3).getTime()
             ];
             expect(tempField.calculateDataDomain()).to.eql(expected);
@@ -49,9 +48,7 @@ describe('Temporal', () => {
 
             const expected = [
                 new Date(2017, 3 - 1, 2).getTime(),
-                new Date(2017, 3 - 1, 3).getTime(),
-                new Date(2019, 11 - 1, 7).getTime(),
-                DataModel.InvalidAwareTypes.NULL
+                new Date(2019, 11 - 1, 7).getTime()
             ];
             expect(tempField.calculateDataDomain()).to.eql(expected);
         });
diff --git a/src/helper.js b/src/helper.js
index 2da2f26..ef85a76 100644
--- a/src/helper.js
+++ b/src/helper.js
@@ -4,10 +4,11 @@ import Value from './value';
 import {
     rowDiffsetIterator
 } from './operator';
-import { DM_DERIVATIVES, LOGICAL_OPERATORS } from './constants';
+import { DM_DERIVATIVES, LOGICAL_OPERATORS, ROW_ID } from './constants';
 import { createFields, createUnitFieldFromPartial } from './field-creator';
 import defaultConfig from './default-config';
-import * as converter from './converter';
+import { converterStore } from './converter';
+import { fieldRegistry } from './fields';
 import { extend2, detectDataFormat } from './utils';
 
 /**
@@ -144,12 +145,10 @@ export const selectHelper = (clonedDm, selectFn, config, sourceDm, iterator) =>
     let cloneProvider = () => sourceDm.detachedRoot();
     const { mode } = config;
     const rowDiffset = clonedDm._rowDiffset;
-    const fields = clonedDm.getPartialFieldspace().fields;
-    const formattedFieldsData = fields.map(field => field.formattedData());
-    const rawFieldsData = fields.map(field => field.data());
+    const cachedValueObjects = clonedDm._partialFieldspace._cachedValueObjects;
 
     const selectorHelperFn = index => selectFn(
-        prepareSelectionData(fields, formattedFieldsData, rawFieldsData, index),
+        cachedValueObjects[index],
         index,
         cloneProvider,
         cachedStore
@@ -172,72 +171,97 @@ export const cloneWithAllFields = (model) => {
     return clonedDm;
 };
 
-const getKey = (arr, data, fn) => {
-    let key = fn(arr, data, 0);
+const getKey = (arr, data, fn, rowId) => {
+    let key = fn(arr, data, 0, rowId);
 
     for (let i = 1, len = arr.length; i < len; i++) {
-        key = `${key},${fn(arr, data, i)}`;
+        key = `${key},${fn(arr, data, i, rowId)}`;
     }
     return key;
 };
 
+const keyFn = (arr, fields, idx, rowId) => {
+    const field = arr[idx];
+    const val = field === ROW_ID ? rowId : fields[field].internalValue;
+    return val;
+};
+
+const domainChecker = (val, domain) => {
+    const domainArr = domain[0] instanceof Array ? domain : [domain];
+    return domainArr.some(dom => val >= dom[0] && val <= dom[1]);
+};
+
+const boundsChecker = {
+    [MeasureSubtype.CONTINUOUS]: domainChecker,
+    [DimensionSubtype.TEMPORAL]: domainChecker
+};
+
+const isWithinDomain = (value, domain, fieldType) => boundsChecker[fieldType](value, domain);
+
 export const filterPropagationModel = (model, propModels, config = {}) => {
     let fns = [];
     const operation = config.operation || LOGICAL_OPERATORS.AND;
-    const filterByMeasure = config.filterByMeasure || false;
-    const clonedModel = cloneWithAllFields(model);
+    const { filterByDim = true, filterByMeasure = false, clone = true } = config;
+    const clonedModel = clone ? cloneWithAllFields(model) : model;
     const modelFieldsConfig = clonedModel.getFieldsConfig();
 
     if (!propModels.length) {
         fns = [() => false];
     } else {
-        fns = propModels.map(propModel => ((dataModel) => {
-            let keyFn;
-            const dataObj = dataModel.getData();
-            const fieldsConfig = dataModel.getFieldsConfig();
-            const dimensions = Object.keys(dataModel.getFieldspace().getDimension())
-                .filter(d => d in modelFieldsConfig);
-            const dLen = dimensions.length;
-            const indices = dimensions.map(d =>
-                fieldsConfig[d].index);
-            const measures = Object.keys(dataModel.getFieldspace().getMeasure())
-                .filter(d => d in modelFieldsConfig);
-            const fieldsSpace = dataModel.getFieldspace().fieldsObj();
-            const data = dataObj.data;
-            const domain = measures.reduce((acc, v) => {
-                acc[v] = fieldsSpace[v].domain();
-                return acc;
+        fns = propModels.map(propModel => (({ criteria = {} }) => {
+            const { identifiers = [[], []], range } = criteria;
+            let [fieldNames = [], values = []] = identifiers;
+            const indices = fieldNames.reduce((map, name, i) => {
+                map[name] = i;
+                return map;
             }, {});
+            fieldNames = fieldNames.filter(field => (field in modelFieldsConfig &&
+                modelFieldsConfig[field].def.type === FieldType.DIMENSION) || field === ROW_ID);
+            const dLen = fieldNames.length;
             const valuesMap = {};
 
-            keyFn = (arr, row, idx) => row[arr[idx]];
             if (dLen) {
-                data.forEach((row) => {
-                    const key = getKey(indices, row, keyFn);
+                for (let i = 1, len = identifiers.length; i < len; i++) {
+                    const row = identifiers[i];
+                    const key = `${fieldNames.map((field) => {
+                        const idx = indices[field];
+                        return row[idx];
+                    })}`;
                     valuesMap[key] = 1;
-                });
+                }
+            }
+            let rangeKeys = Object.keys(range || {}).filter(field => field in modelFieldsConfig);
+            const hasData = values.length || rangeKeys.length;
+
+            if (!filterByMeasure) {
+                rangeKeys = rangeKeys.filter(field => modelFieldsConfig[field].def.type !== FieldType.MEASURE);
             }
 
-            keyFn = (arr, fields, idx) => fields[arr[idx]].internalValue;
-            return data.length ? (fields) => {
-                const present = dLen ? valuesMap[getKey(dimensions, fields, keyFn)] : true;
+            if (!filterByDim) {
+                rangeKeys = rangeKeys.filter(field => modelFieldsConfig[field].def.type !== FieldType.DIMENSION);
+            }
 
-                if (filterByMeasure) {
-                    return measures.every(field => fields[field].internalValue >= domain[field][0] &&
-                        fields[field].internalValue <= domain[field][1]) && present;
+            return hasData ? (fields, i) => {
+                let present = true;
+                if (filterByDim) {
+                    present = dLen ? valuesMap[getKey(fieldNames, fields, keyFn, i)] : true;
                 }
-                return present;
+
+                return rangeKeys.every((field) => {
+                    const val = fields[field].internalValue;
+                    return isWithinDomain(val, range[field], modelFieldsConfig[field].def.subtype);
+                }) && present;
             } : () => false;
         })(propModel));
     }
 
     let filteredModel;
     if (operation === LOGICAL_OPERATORS.AND) {
-        filteredModel = clonedModel.select(fields => fns.every(fn => fn(fields)), {
+        filteredModel = clonedModel.select((fields, i) => fns.every(fn => fn(fields, i)), {
             saveChild: false
         });
     } else {
-        filteredModel = clonedModel.select(fields => fns.some(fn => fn(fields)), {
+        filteredModel = clonedModel.select((fields, i) => fns.some(fn => fn(fields, i)), {
             saveChild: false
         });
     }
@@ -374,27 +398,12 @@ export const sanitizeUnitSchema = (unitSchema) => {
 };
 
 export const validateUnitSchema = (unitSchema) => {
-    const supportedMeasureSubTypes = [MeasureSubtype.CONTINUOUS];
-    const supportedDimSubTypes = [
-        DimensionSubtype.CATEGORICAL,
-        DimensionSubtype.BINNED,
-        DimensionSubtype.TEMPORAL,
-        DimensionSubtype.GEO
-    ];
     const { type, subtype, name } = unitSchema;
-
-    switch (type) {
-    case FieldType.DIMENSION:
-        if (supportedDimSubTypes.indexOf(subtype) === -1) {
-            throw new Error(`DataModel doesn't support dimension field subtype ${subtype} used for ${name} field`);
-        }
-        break;
-    case FieldType.MEASURE:
-        if (supportedMeasureSubTypes.indexOf(subtype) === -1) {
+    if (type === FieldType.DIMENSION || type === FieldType.MEASURE) {
+        if (!fieldRegistry.has(subtype)) {
             throw new Error(`DataModel doesn't support measure field subtype ${subtype} used for ${name} field`);
         }
-        break;
-    default:
+    } else {
         throw new Error(`DataModel doesn't support field type ${type} used for ${name} field`);
     }
 };
@@ -420,13 +429,14 @@ export const resolveFieldName = (schema, dataHeader) => {
 export const updateData = (relation, data, schema, options) => {
     schema = sanitizeAndValidateSchema(schema);
     options = Object.assign(Object.assign({}, defaultConfig), options);
-    const converterFn = converter[options.dataFormat];
+    const converter = converterStore.get(options.dataFormat);
 
-    if (!(converterFn && typeof converterFn === 'function')) {
+
+    if (!converter) {
         throw new Error(`No converter function found for ${options.dataFormat} format`);
     }
 
-    const [header, formattedData] = converterFn(data, schema, options);
+    const [header, formattedData] = converter.convert(data, schema, options);
     resolveFieldName(schema, header);
     const fieldArr = createFields(formattedData, schema, header);
 
@@ -524,12 +534,8 @@ const getFilteredModel = (propModel, path) => {
 };
 
 const propagateIdentifiers = (dataModel, propModel, config = {}, propModelInf = {}) => {
-    const nonTraversingModel = propModelInf.nonTraversingModel;
     const excludeModels = propModelInf.excludeModels || [];
-
-    if (dataModel === nonTraversingModel) {
-        return;
-    }
+    const criterias = propModelInf.criteria;
 
     const propagate = excludeModels.length ? excludeModels.indexOf(dataModel) === -1 : true;
 
@@ -537,7 +543,16 @@ const propagateIdentifiers = (dataModel, propModel, config = {}, propModelInf =
 
     const children = dataModel._children;
     children.forEach((child) => {
-        const selectionModel = applyExistingOperationOnModel(propModel, child);
+        const matchingCriteria = criterias.filter(val => val.groupedModel === child);
+        let selectionModel = applyExistingOperationOnModel(propModel, child);
+
+        if (matchingCriteria.length) {
+            selectionModel = filterPropagationModel(selectionModel, matchingCriteria, {
+                filterByDim: false,
+                filterByMeasure: true,
+                clone: false
+            });
+        }
         propagateIdentifiers(child, selectionModel, config, propModelInf);
     });
 };
@@ -566,18 +581,28 @@ export const getPathToRootModel = (model, path = []) => {
 
 export const propagateToAllDataModels = (identifiers, rootModels, propagationInf, config) => {
     let criteria;
-    let propModel;
     const { propagationNameSpace, propagateToSource } = propagationInf;
     const propagationSourceId = propagationInf.sourceId;
-    const propagateInterpolatedValues = config.propagateInterpolatedValues;
     const filterFn = (entry) => {
         const filter = config.filterFn || (() => true);
         return filter(entry, config);
     };
 
+    const addGroupedModel = ({ config: conf, model }) => {
+        const { criteria: crit } = conf;
+        let groupedModel;
+
+        if (crit !== null && crit.fields.some(d => d.type === FieldType.MEASURE)) {
+            groupedModel = getRootGroupByModel(model);
+        }
+        return Object.assign({}, conf, {
+            groupedModel
+        });
+    };
+
     let criterias = [];
 
-    if (identifiers === null && config.persistent !== true) {
+    if (identifiers === null) {
         criterias = [{
             criteria: []
         }];
@@ -588,7 +613,7 @@ export const propagateToAllDataModels = (identifiers, rootModels, propagationInf
             actionCriterias = actionCriterias.filter(d => d.config.sourceId !== propagationSourceId);
         }
 
-        const filteredCriteria = actionCriterias.filter(filterFn).map(action => action.config.criteria);
+        const filteredCriteria = actionCriterias.filter(filterFn);
 
         const excludeModels = [];
 
@@ -600,7 +625,7 @@ export const propagateToAllDataModels = (identifiers, rootModels, propagationInf
                 if (actionConf.applyOnSource === false && actionConf.action === config.action &&
                         actionConf.sourceId !== propagationSourceId) {
                     excludeModels.push(actionInf.model);
-                    criteria = sourceActionCriterias.filter(d => d !== actionInf).map(d => d.config.criteria);
+                    criteria = sourceActionCriterias.filter(d => d !== actionInf).map(addGroupedModel);
                     criteria.length && criterias.push({
                         criteria,
                         models: actionInf.model,
@@ -611,7 +636,11 @@ export const propagateToAllDataModels = (identifiers, rootModels, propagationInf
         }
 
 
-        criteria = [].concat(...[...filteredCriteria, identifiers]).filter(d => d !== null);
+        criteria = [].concat(...[...filteredCriteria.map(addGroupedModel), {
+            criteria: identifiers,
+            groupedModel: identifiers !== null && identifiers.fields.some(d => d.type === FieldType.MEASURE) ?
+                getRootGroupByModel(propagationInf.propagationSource) : null
+        }]).filter(d => d !== null);
         criterias.push({
             criteria,
             excludeModels: [...excludeModels, ...config.excludeModels || []]
@@ -625,16 +654,11 @@ export const propagateToAllDataModels = (identifiers, rootModels, propagationInf
         propagationSourceId
     }, config);
 
-    const rootGroupByModel = rootModels.groupByModel;
-    if (propagateInterpolatedValues && rootGroupByModel) {
-        propModel = filterPropagationModel(rootGroupByModel, criteria, {
-            filterByMeasure: propagateInterpolatedValues
-        });
-        propagateIdentifiers(rootGroupByModel, propModel, propConfig);
-    }
-
     criterias.forEach((inf) => {
-        const propagationModel = filterPropagationModel(rootModel, inf.criteria);
+        const { criteria: crit } = inf;
+        const propagationModel = filterPropagationModel(rootModel, crit, {
+            filterByMeasure: !!crit.find(d => d.groupedModel === rootModel)
+        });
         const path = inf.path;
 
         if (path) {
@@ -643,13 +667,13 @@ export const propagateToAllDataModels = (identifiers, rootModels, propagationInf
         } else {
             propagateIdentifiers(rootModel, propagationModel, propConfig, {
                 excludeModels: inf.excludeModels,
-                nonTraversingModel: propagateInterpolatedValues && rootGroupByModel
+                criteria: crit
             });
         }
     });
 };
 
-export const propagateImmutableActions = (propagationNameSpace, rootModels, propagationInf) => {
+export const propagateImmutableActions = (propagationNameSpace, rootModel, propagationInf) => {
     const immutableActions = propagationNameSpace.immutableActions;
 
     for (const action in immutableActions) {
@@ -660,10 +684,14 @@ export const propagateImmutableActions = (propagationNameSpace, rootModels, prop
             propagationInf.propConfig.filterImmutableAction(actionConf, propagationInf.config) : true;
         if (actionConf.sourceId !== propagationSourceId && filterImmutableAction) {
             const criteriaModel = actionConf.criteria;
-            propagateToAllDataModels(criteriaModel, rootModels, {
+            propagateToAllDataModels(criteriaModel, {
+                model: rootModel,
+                groupByModel: getRootGroupByModel(actionInf.model)
+            }, {
                 propagationNameSpace,
                 propagateToSource: false,
-                sourceId: propagationSourceId
+                sourceId: propagationSourceId,
+                propagationSource: actionInf.model
             }, actionConf);
         }
     }
diff --git a/src/index.spec.js b/src/index.spec.js
index 127ab33..55ccc7f 100644
--- a/src/index.spec.js
+++ b/src/index.spec.js
@@ -3,7 +3,7 @@
 
 import { expect } from 'chai';
 import { FilteringMode, DataFormat } from './enums';
-import { DM_DERIVATIVES } from './constants';
+import { DM_DERIVATIVES, ROW_ID } from './constants';
 import DataModel from './index';
 import pkg from '../package.json';
 import InvalidAwareTypes from './invalid-aware-types';
@@ -407,7 +407,7 @@ describe('DataModel', () => {
                 schema: [
                     { name: 'name', type: 'dimension', subtype: 'categorical' },
                     { name: 'birthday', type: 'dimension', subtype: 'temporal', format: '%Y-%m-%d' },
-                    { name: 'uid', type: 'identifier' }
+                    { name: ROW_ID, type: 'dimension' }
                 ],
                 uids: [0, 1, 2]
             };
@@ -1903,30 +1903,30 @@ describe('DataModel', () => {
             { name: 'first', type: 'dimension' },
             { name: 'second', type: 'dimension' },
         ];
-        const propModel = new DataModel([{
-            first: 'Hey',
-            second: 'Jude'
-        }], [{
-            name: 'first',
-            type: 'dimension'
-        }, {
-            name: 'second',
-            type: 'dimension'
-        }]);
-        const propModel1 = new DataModel([{
-            first: 'Hey',
-            second: 'Jude',
-            count: 100
-        }], [{
-            name: 'first',
-            type: 'dimension'
-        }, {
-            name: 'second',
-            type: 'dimension'
-        }, {
-            name: 'count',
-            type: 'measure'
-        }]);
+
+        const propModel = {
+            fields: [{
+                name: 'first',
+                type: 'dimension'
+            }, {
+                name: 'second',
+                type: 'dimension'
+            }],
+            data: [
+                ['first', 'second'],
+                ['Hey', 'Jude']
+            ]
+        };
+
+        const propModel1 = {
+            fields: [{
+                name: 'sales',
+                type: 'measure'
+            }],
+            range: {
+                sales: [20, 25]
+            }
+        };
 
         let dataModel;
         let projectionFlag = false;
@@ -1935,12 +1935,14 @@ describe('DataModel', () => {
         let projected;
         let selected;
         let grouped;
+        let groupedChild;
 
         beforeEach(() => {
             dataModel = new DataModel(data1, schema1);
             projected = dataModel.project(['profit']);
             selected = dataModel.select(fields => fields.profit.valueOf() > 10);
             grouped = dataModel.groupBy(['first']);
+            groupedChild = grouped.select(() => true);
             // setup listeners
             projected.on('propagation', () => {
                 projectionFlag = true;
@@ -2042,6 +2044,27 @@ describe('DataModel', () => {
                 projectionFlag && selectionFlag && groupByFlag
             ).to.be.true;
         });
+
+        it('Should propagate when measures are present in criteria', () => {
+            groupedChild.propagate(propModel1, {
+                action: 'highlight',
+                isMutableAction: true,
+                sourceId: 'canvas-1',
+                applyOnSource: false,
+                propagateToSource: true,
+                criteria: propModel1
+            }, true);
+
+            groupedChild.propagate(propModel1, {
+                action: 'highlight',
+                isMutableAction: true,
+                sourceId: 'canvas-2',
+                applyOnSource: false,
+                propagateToSource: true,
+                criteria: propModel1
+            }, true);
+            expect(projectionFlag && selectionFlag && groupByFlag).to.be.true;
+        });
     });
 
     describe('#getUIDs', () => {
diff --git a/src/operator/data-builder.js b/src/operator/data-builder.js
index 4e4b84d..d2238fa 100644
--- a/src/operator/data-builder.js
+++ b/src/operator/data-builder.js
@@ -1,5 +1,7 @@
 import { rowDiffsetIterator } from './row-diffset-iterator';
 import { sortData } from './sort';
+import { FieldType } from '../enums';
+import { ROW_ID } from '../constants';
 
 /**
  * Builds the actual data array.
@@ -48,8 +50,8 @@ export function dataBuilder (fieldStore, rowDiffset, colIdentifier, sortingDetai
 
     if (addUid) {
         retObj.schema.push({
-            name: 'uid',
-            type: 'identifier'
+            name: ROW_ID,
+            type: FieldType.DIMENSION
         });
     }