DataTypeConverter.js
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/*
** This file is part of JSDataChecker.
**
** JSDataChecker is free software: you can redistribute it and/or modify
** it under the terms of the GNU General Public License as published by
** the Free Software Foundation, either version 3 of the License, or
** (at your option) any later version.
**
** JSDataChecker is distributed in the hope that it will be useful,
** but WITHOUT ANY WARRANTY; without even the implied warranty of
** MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
** GNU General Public License for more details.
**
** You should have received a copy of the GNU General Public License
** along with JSDataChecker. If not, see <http://www.gnu.org/licenses/>.
**
** Copyright (C) 2016 JSDataChecker - Donato Pirozzi (donatopirozzi@gmail.com)
** Distributed under the GNU GPL v3. For full terms see the file LICENSE.
** License: http://www.gnu.org/licenses/gpl.html GPL version 3 or higher
**/
function DataTypeConverter() {
this._fields = [];
this._numOfRows = 0;
};//EndConstructor.
DataTypeConverter.TYPES = {
EMPTY : { value: 0, name: "NULL"},
TEXT : { value: 1, name: "TEXT" },
NUMBER : { value: 2, name: "NUMBER" },
OBJECT : { value: 3, name: "OBJECT" },
DATETIME : { value: 4, name: "DATETIME" }
};
DataTypeConverter.SUBTYPES = {
GEOCOORDINATE : { value: 1000, name: "GEOCOORDINATE" },
GEOJSON : { value: 1001, name: "GEOJSON" },
BOOL : { value: 1002, name: "BOOL"},
CONST : { value: 1003, name: "CONST" },
CATEGORY : { value: 1004, name: "CATEGORY" },
PERCENTAGE : { value: 1100, name: "PERCENTAGE" },
LATITUDE : { value: 1101, name: "LATITUDE" },
LONGITUDE : { value: 1102, name: "LONGITUDE" }
/*CODE : { value: 2000, name: "CODE"},*/
};
DataTypeConverter.LANGS = {
EN : { value: 1000, name: "EN" },
IT : { value: 1001, name: "IT" },
FR : { value: 1100, name: "FR" },
NL : { value: 1101, name: "NL" }
};
DataTypeConverter.GEOJSONTYPES = [ "Point", "MultiPoint", "LineString",
"MultiLineString", "Polygon", "MultiPolygon", "GeometryCollection", "Feature",
"FeatureCollection" ];
DataTypeConverter.prototype = (function () {
/***
* Make an asynchronous call to load the content.
* @param theUrl
* @param callback
* @deprecated
*/
var httpGetAsync = function(theUrl, callbackOnFinish) {
console.warn("Calling deprecated function.");
var xhttp = new XMLHttpRequest();
xhttp.onreadystatechange = function() {
if (xhttp.readyState == 4 && xhttp.status == 200)
_processDataset(xhttp.responseText, callbackOnFinish);
}
xhttp.open("GET", theUrl, true); // true for asynchronous
xhttp.send(null);
};//EndFunction.
/*var _processDataset = function (jsonRows) {
//Check if the jsonRow is an array.
if (Array.isArray(jsonRows) == false) return;
for (var i=0; i<jsonRows.length; i++) {
var jsonRow = jsonRows[i];
_processRow(jsonRow);
}//EndFor.
_analyseDataTypes(this._fields);
return this._fields;
};//EndFunction.*/
/*var _processRow = function(row) {
//Avoid empty rows
if (typeof row === 'undefined') return;
//Get the object keys.
for (var property in row) {
if (row.hasOwnProperty(property)) {
var cellValue = row[property];
//if (property == 'votantspourcentages') debugger;
//if (property == 'va_no_voie') debugger;
var inferredType = _processInferType(cellValue);
if (typeof this._fields[property] === 'undefined')
this._fields[property] = { name: property, _inferredTypes: [], _inferredValues: [] };
_arrUtil.testAndIncrement(this._fields[property]._inferredTypes, inferredType.name);
if (inferredType === DataTypeConverter.TYPES.TEXT)
_arrUtil.testAndIncrement(this._fields[property]._inferredValues, cellValue);
if (inferredType === DataTypeConverter.TYPES.LATITUDE || inferredType === DataTypeConverter.TYPES.LONGITUDE)
_arrUtil.testAndIncrement(this._fields[property]._inferredTypes, DataTypeConverter.TYPES.NUMBER);
}
}
this._numOfRows++;
};//EndFunction.*/
var _analyseDataTypes = function(fields) {
ArrayUtils.IteratorOverKeys(fields, function(field) {
/*
//TODO: removed CODE, I don't know whether it must be inserted
if (field._inferredTypes[DataTypeConverter.TYPES.CODE.name]) {
var confidence = field._inferredTypes[DataTypeConverter.TYPES.CODE.name] / field.numOfItems;
var _numericalInferredType = field._inferredTypes[DataTypeConverter.TYPES.NUMBER.name];
if (typeof _numericalInferredType != 'undefined') confidence += _numericalInferredType / field.numOfItems;
field.type = DataTypeConverter.TYPES.CODE.name;
field.typeConfidence = confidence;
return;
}*/
//Infers the field TYPE.
var max = ArrayUtils.FindMinMax(field._inferredTypes, function (curval, lastval) {
return curval > lastval;
});
//When the first key is null, it uses the second one.
var tkey = max.first.key;
if (tkey === DataTypeConverter.TYPES.EMPTY.name &&
max.second != null && typeof max.second !== 'undefined')
tkey = max.second.key;
field.type = tkey;
field.typeConfidence = field._inferredTypes[max.first.key] / field.numOfItems;
//##########
//Infers the field SUBTYPE.
var max = ArrayUtils.FindMinMax(field._inferredSubTypes, function (curval, lastval) {
return curval > lastval;
});
field.subtype = null;
if (max != null && max.first != null) {
field.subtype = max.first.key;
field.subtypeConfidence = field._inferredSubTypes[field.subtype] / field.numOfItems;
//TODO: improve this piece of code.
//LAT/LNG.
var fieldName = field.name.toLowerCase();
var isLatType = (field.subtype === DataTypeConverter.SUBTYPES.LATITUDE.name);
var fieldNameContainsLat = fieldName.indexOf('lat') >= 0;
var fieldNameContainsLon = fieldName.indexOf('ng') >= 0; //It could be 'lng'.
if (isLatType == true && fieldNameContainsLat == false && fieldNameContainsLon == true) {
field.subtype = DataTypeConverter.SUBTYPES.LONGITUDE.name;
}
}
///
/// SUBTYPES.
//BOOLEAN.
/*var numOfValues = Object.keys(field._inferredValues).length;
if (field.type === DataTypeConverter.TYPES.TEXT.name) {
//if (numOfValues == 1) field.type = DataTypeConverter.TYPES.CONST.name;
//else if (numOfValues == 2) field.type = DataTypeConverter.TYPES.BOOL.name;
//else
if (numOfValues < field.numOfItems * 0.20) field.type = DataTypeConverter.TYPES.CATEGORY.name;
}*/
});
};//EndFunction.
/**
* Given a dataset value, it tries to recognise the data types.
* This is the central function within the library.
* @param value
* @returns {*}
* @private
*/
var _processInferType = function(value) {
//value = value.toLocaleString();
if (value === null || typeof value === 'undefined')
return DataTypeConverter.TYPES.EMPTY;
if (typeof value === 'object')
return DataTypeConverter.TYPES.OBJECT;
//Try to parse the float.
//var isnumber = DataTypesUtils.FilterFloat(value);
var isnumber = DataTypesUtils.FilterNumber(value);
if (isNaN(isnumber) !== true) {//It is a number.
//If the number ranges from -90.0 to 90.0, the value is marked as Latitude.
//if (-90.0 <= isnumber && isnumber <= 90.0 && _dataTypesUtils.decimalPlaces(isnumber) >= 5)
// return DataTypeConverter.TYPES.LATITUDE;
//It the number ranges from -180.0 to 180.0, the value is marked as Longitude.
//if (-180.0 <= isnumber && isnumber <= 180.0 && _dataTypesUtils.decimalPlaces(isnumber) >= 5)
// return DataTypeConverter.TYPES.LONGITUDE;
/*if (0.0 <= isnumber && isnumber <= 100.0)
if(/^(\+)?((0|([1-9][0-9]*))\.([0-9]+))$/ .test(value))
return DataTypeConverter.TYPES.PERCENTAGE;*/
return DataTypeConverter.TYPES.NUMBER;
}
var _date = DataTypesUtils.FilterDateTime(value);
if (isNaN(_date) == false && _date != null)
return DataTypeConverter.TYPES.DATETIME;
return DataTypeConverter.TYPES.TEXT;
};//EndFunction.
var _processInferSubType = function (value) {
if (value === null || typeof value === 'undefined') return null;
//GEOCOORDINATE
if (Array.isArray(value) && value.length == 2) {//It recognises the LAT LNG as array of two values.
//Checks if the two array's values are numbers.
//if ( DataTypesUtils.FilterFloat(value[0]) != NaN && DataTypesUtils.FilterFloat(value[1]) != NaN )
if ( DataTypesUtils.FilterNumber(value[0]) != NaN && DataTypesUtils.FilterNumber(value[1]) != NaN )
if (DataTypesUtils.DecimalPlaces(value[0]) > 4 && DataTypesUtils.DecimalPlaces(value[1]) > 4 )
return DataTypeConverter.SUBTYPES.GEOCOORDINATE;
}//EndIf.
if (typeof value === 'string') {
var split = value.split(",");
//if (split.length == 2)
if (DataTypesUtils.IsLatLng(split[0]) && DataTypesUtils.IsLatLng(split[1]))
return DataTypeConverter.SUBTYPES.GEOCOORDINATE;
}
//Try to parse the float.
//var isnumber = DataTypesUtils.FilterFloat(value);
var isnumber = DataTypesUtils.FilterNumber(value);
if (isNaN(isnumber) !== true) {//It is a number.
//If the number ranges from -90.0 to 90.0, the value is marked as Latitude.
if (-90.0 <= isnumber && isnumber <= 90.0 && DataTypesUtils.DecimalPlaces(isnumber) >= 5)
return DataTypeConverter.SUBTYPES.GEOCOORDINATE;
//It the number ranges from -180.0 to 180.0, the value is marked as Longitude.
if (-180.0 <= isnumber && isnumber <= 180.0 && DataTypesUtils.DecimalPlaces(isnumber) >= 5)
return DataTypeConverter.SUBTYPES.GEOCOORDINATE;
/*if (0.0 <= isnumber && isnumber <= 100.0)
if(/^(\+)?((0|([1-9][0-9]*))\.([0-9]+))$/ .test(value))
return DataTypeConverter.SUBTYPES.PERCENTAGE;*/
return null;
}
//Try to parse GEOJSON.
if (typeof value === 'object' && value.hasOwnProperty('type')) {
//Check the type variable.
var geotype = value.type;
var isincluded = DataTypeConverter.GEOJSONTYPES.includes(geotype);
if (isincluded) return DataTypeConverter.SUBTYPES.GEOJSON;
}
//If the value starts with a zero and contains all numbers, it is
//inferred as textual content.
/*if (/^0[0-9]+$/.test(value))
return DataTypeConverter.TYPES.CODE;*/
return null;
};//EndFunction.
var _filterBasedOnThreshold = function(metadata, threshold) {
ArrayUtils.IteratorOverKeys(metadata.types, function (fieldType, key) {
if (fieldType.typeConfidence >= threshold) return;
var arrHierarchyTypes = DataTypeHierarchy.HIERARCHY[fieldType.type];
if (arrHierarchyTypes == null)
return metadata;
var lastFieldType = { lastType: arrHierarchyTypes[0],
lastTypeCounter: fieldType._inferredTypes[arrHierarchyTypes[0]],
typeConfidence: 0 };
lastFieldType.typeConfidence = lastFieldType.lastTypeCounter / fieldType.numOfItems;
for (var i= 1, curType; i<arrHierarchyTypes.length, curType = arrHierarchyTypes[i]; i++) {
var numItemsOfCurType = fieldType._inferredTypes.hasOwnProperty(curType) ? fieldType._inferredTypes[curType] : 0 ;
lastFieldType.lastType = curType;
lastFieldType.lastTypeCounter += numItemsOfCurType;
lastFieldType.typeConfidence = lastFieldType.lastTypeCounter / fieldType.numOfItems;
if (lastFieldType.typeConfidence >= threshold) {
fieldType.type = lastFieldType.lastType;
fieldType.typeConfidence = lastFieldType.typeConfidence;
break;
}
}
});
return metadata;
};//EndFunction.
var _capitalizeFirstLetter = function(string) {
return string.charAt(0).toUpperCase() + string.slice(1);
};//EndFunction.
var _replaceAll = function(search, replacement) {
var target = this;
return target.split(search).join(replacement);
};
var jsonTraverse = function(json, fieldKeys, callback) {
var stack = [];
var numOfRows = 0;
stack.push({ item: json, fieldKeyIndex: 0 });
while (stack.length > 0) {
var stackTask = stack.pop();
var item = stackTask.item;
var fieldKeyIndex = stackTask.fieldKeyIndex;
var fieldKey = fieldKeys[fieldKeyIndex];
//Test fieldKey Value.
if (fieldKey == '*' && ArrayUtils.isArray(item) == false) {
var sProcessedKeys = fieldKeys.slice(0, fieldKeyIndex).toString();
ArrayUtils.IteratorOverKeys(item, function (value, key) {
var curKey = sProcessedKeys + (sProcessedKeys.length > 0 ? "," : "") + key;
var _value = callback(value, key, curKey, numOfRows);
item[key] = _value;
});
numOfRows++;
continue;
}
//It is an array, loops through its cells and pushes items within the stack.
if (fieldKey == '*' && ArrayUtils.isArray(item) == true) {
for (var j= 0, cell; j<item.length && (cell = item[j]); j++) {
stack.push({item: cell, fieldKeyIndex: fieldKeyIndex});
numOfRows++;
}
continue;
}
var jsonSubtree = item[fieldKey];
if (Array.isArray(jsonSubtree)) { //It is an array.
for (var j=0; j<jsonSubtree.length; j++) {
var jsonItem = jsonSubtree[j];
stack.push({ item: jsonItem, fieldKeyIndex: fieldKeyIndex+1 });
}//EndForJ.
} else {
stack.push({ item: jsonSubtree, fieldKeyIndex: fieldKeyIndex+1 });
}
}//EndWhile.
};//EndFunction.
return {
constructor: DataTypeConverter,
/**
*
* @param metadata Previous information on the inferred types.
* @param options Some options to cast the data.
* - castThresholdConfidence: for which threshold the library must perform the cast (default 1)
* - makeChangesToDataset: is a boolean value, to indicate whether the library can do improvement on the storage
* values, for instance, numbers with the comma will be replaced with the dot.
* @returns {*}
*/
cast: function(metadata, options) {
if (typeof options === 'undefined' || options == null)
options = { castThresholdConfidence: 1, castIfNull: false, makeChangesToDataset: false };
return this.convert(metadata, options);
},
/**
* It parses the json in input and converts the content
* in according to the inferred data types.
* @param json
* @param path Format: field1->field2->field3
* @deprecated
*/
convert: function (metadata, options) {
var lastRowIndex = 0;
var isRowInvalid = false;
var numOfRowsInvalid = 0;
var numOfRows = 0;
var numOfValues = 0;
var datasetErrors = 0;
var datasetMissingValues = 0;
if (typeof options === 'undefined' || options == null)
options = { castThresholdConfidence: 1, castIfNull: false, makeChangesToDataset: false };
jsonTraverse(metadata.dataset, metadata.fieldKeys, function(value, key, traversedKeys, rowIndex) {
var inferredType = metadata.types[traversedKeys];
numOfValues++;
if (lastRowIndex != rowIndex) {
lastRowIndex = rowIndex;
numOfRows++;
//if (isRowInvalid) numOfRowsInvalid++;
}
if (value == null || typeof value == 'undefined' || (value + "").length == 0) {
//datasetErrors++;
} //isRowInvalid = true;
//var isCast = !(options.castIfNull == false && inferredType.totalNullValues > 0);
var isCast = inferredType.typeConfidence >= options.castThresholdConfidence;
if (inferredType.type == DataTypeConverter.TYPES.NUMBER.name && isCast) {
if (isNaN(DataTypesUtils.FilterNumber(value)) == false && typeof value === "string")
value = value.replace(',', '.');
var number = parseFloat(value);
if (isNaN(number)) {
datasetErrors++;
return value;
}
return number;
}
return value;
});
metadata.qualityIndex.notNullValues = (numOfValues - datasetMissingValues) / numOfValues;
metadata.qualityIndex.errors = (numOfValues - datasetErrors) / numOfValues;
return metadata;
},//EndFunction.
/**
* It parses the json and infers the data types.
* @param json
* @param path Array of field keys/names.
* @param options Infer Data Type options, in particular the threshold value for the confidence.
*/
inferJsonDataType: function (json, fieldKeys, options) {
//Default options initialisation.
if (typeof options === 'undefined' || options == null) options = { };
if (options.hasOwnProperty("thresholdConfidence") == false)
options.thresholdConfidence = 1;
if (options.hasOwnProperty("language") == false)
options.language = DataTypeConverter.LANGS.EN.name;
else
options.language = options.language.toUpperCase();
var stack = [];
var fieldsType = {};
var fieldsSubType = {};
var numOfRows = 0;
if (typeof fieldKeys == 'undefined')
throw "IllegalArgumentException: undefined json path to analyse.";
//Insert the first item (json root) within the stack.
stack.push({ item: json, fieldKeyIndex: 0 });
while (stack.length > 0) {
var stackTask = stack.pop();
var item = stackTask.item;
var fieldKeyIndex = stackTask.fieldKeyIndex;
var fieldKey = fieldKeys[fieldKeyIndex];
//Test fieldKey Value.
//This if is executed when the fieldKey is * and the dataset it is NOT an ARRAY.
//Thus, it loops through the javascript object KEYs.
if (fieldKey == '*' && ArrayUtils.isArray(item) == false) {
var sProcessedKeys = fieldKeys.slice(0, fieldKeyIndex).toString();
ArrayUtils.IteratorOverKeys(item, function (item, key) {
var curKey = sProcessedKeys + ((sProcessedKeys.length == 0) ? "" : ",") + key;
var fieldType = ArrayUtils.TestAndInitializeKey(fieldsType, curKey, { name: curKey, _inferredTypes: [], _inferredSubTypes: [], _inferredValues: [], numOfItems: 0 });
fieldType.numOfItems++;
///TYPE
var inferredType = _processInferType(item);
ArrayUtils.TestAndIncrement(fieldType._inferredTypes, inferredType.name);
if (inferredType === DataTypeConverter.TYPES.TEXT)
ArrayUtils.TestAndIncrement(fieldType._inferredValues, item);
///SUBTYPE
var inferredSubType = _processInferSubType(item);
if (inferredSubType != null && typeof inferredSubType !== 'undefined') {
ArrayUtils.TestAndIncrement(fieldType._inferredSubTypes, inferredSubType.name);
/*if (inferredSubType === DataTypeConverter.TYPES.LATITUDE)
ArrayUtils.TestAndIncrement(fieldType._inferredSubTypes, DataTypeConverter.TYPES.LATITUDE);
if (inferredSubType === DataTypeConverter.TYPES.LONGITUDE)
ArrayUtils.TestAndIncrement(fieldType._inferredSubTypes, DataTypeConverter.TYPES.LONGITUDE);*/
}//EndSubtype.
});
numOfRows++;
continue;
}
//Loops through the array cells.
if (fieldKey == '*' && ArrayUtils.isArray(item)) {
for (var j= 0, cell; j<item.length && (cell = item[j]); j++) {
stack.push({item: cell, fieldKeyIndex: fieldKeyIndex});
numOfRows++;
}
continue;
}
//This is executed when the fieldKey is not *
var jsonSubtree = item[fieldKey];
if (Array.isArray(jsonSubtree)) { //It is an array.
for (var j=0; j<jsonSubtree.length; j++) {
var jsonItem = jsonSubtree[j];
stack.push({ item: jsonItem, fieldKeyIndex: fieldKeyIndex+1 });
}//EndForJ.
} else {
stack.push({ item: jsonSubtree, fieldKeyIndex: fieldKeyIndex+1 });
}
}//EndWhile.
//Calculates the number of rows in the dataset.
var _numOfRows = 0;
ArrayUtils.IteratorOverKeys(fieldsType, function(fieldType) {
if (fieldType.numOfItems > _numOfRows)
_numOfRows = fieldType.numOfItems;
});
//Computes the number of null values.
ArrayUtils.IteratorOverKeys(fieldsType, function(fieldType) {
if (!fieldType._inferredTypes.hasOwnProperty(DataTypeConverter.TYPES.EMPTY.name)) {
//Initialises the field.
fieldType._inferredTypes[DataTypeConverter.TYPES.EMPTY.name] = 0;
}
fieldType._inferredTypes[DataTypeConverter.TYPES.EMPTY.name] = fieldType._inferredTypes[DataTypeConverter.TYPES.EMPTY.name] + (_numOfRows - fieldType.numOfItems);
});
//Infers the data type.
_analyseDataTypes(fieldsType);
//Data quality.
var quality = { homogeneity: 1, completeness: 1, totalNullValues: 0, totalValues: 0 };
ArrayUtils.IteratorOverKeys(fieldsType, function(fieldType) {
quality.totalValues += fieldType.numOfItems;
quality.homogeneity *= fieldType.typeConfidence;
fieldType.totalNullValues = 0;
if (fieldType._inferredTypes.hasOwnProperty(DataTypeConverter.TYPES.EMPTY.name)) {
fieldType.totalNullValues = fieldType._inferredTypes[DataTypeConverter.TYPES.EMPTY.name];
quality.totalNullValues += fieldType.totalNullValues;
}
});
quality.homogeneity = Math.round(quality.homogeneity * 100) / 100;
var totFullValues = quality.totalValues - quality.totalNullValues;
quality.completeness = Math.round(totFullValues / quality.totalValues * 100) / 100;
//Converts confidence to description.
var warningsTextual = "";
ArrayUtils.IteratorOverKeys(fieldsType, function(fieldType) {
fieldType.errorsDescription = "";
var description = "";
//if (fieldType.typeConfidence < 1 || fieldType.totalNullValues > 0)
// description = "The field <" + fieldType.name + "> is a <" + fieldType.type + ">, ";
if (fieldType.typeConfidence < 1) {
/*if (fieldType._inferredTypes.hasOwnProperty(DataTypeConverter.TYPES.EMPTY.name)) {
var numNulls = fieldType._inferredTypes[DataTypeConverter.TYPES.EMPTY.name];
if (typeof numNulls !== 'undefined' && numNulls > 0)
description += " and has " + numNulls + " EMPTY values, ";
}*/
var incorrect = fieldType.numOfItems - fieldType.totalNullValues - fieldType._inferredTypes[fieldType.type];
if (incorrect > 0) {
var _descr1 = _capitalizeFirstLetter(JDC_LNG['key_declaretype'][options.language]) + ".";
var _descr2 = _capitalizeFirstLetter(JDC_LNG['key_notoftype_singular'][options.language]) + ".";
if (incorrect > 1)
_descr2 = _capitalizeFirstLetter(JDC_LNG['key_notoftype_plural'][options.language]) + ".";
var descr = _descr1 + " " + _descr2;
descr = descr.replace(/%COL_NAME/g, fieldType.name);
descr = descr.replace(/%COL_TYPE/g, fieldType.type);
descr = descr.replace(/%COL_ERRORS/g, incorrect);
description += descr;
/*description += "The column <" + fieldType.name + "> has the type <" + fieldType.type + ">";
var verb = (incorrect == 1) ? " value is" : " values are";
description += ", but " + incorrect + verb + " not a " + fieldType.type;*/
}
}
var descr = "";
if (fieldType.totalNullValues == 1)
descr = _capitalizeFirstLetter(JDC_LNG['key_emptyvalue_singolar'][options.language]) + ".";
else if (fieldType.totalNullValues > 1 )
descr = _capitalizeFirstLetter(JDC_LNG['key_emptyvalue_plural'][options.language]) + ".";
descr = descr.replace(/%COL_NAME/g, fieldType.name);
descr = descr.replace(/%COL_TYPE/g, fieldType.type);
descr = descr.replace(/%COL_NULLVALUES/g, fieldType.totalNullValues);
description = description + " " + descr;
/*if (fieldType.totalNullValues > 0) {
var descr = _capitalizeFirstLetter(JDC_LNG['key_declaretype'][options.language]) + ".";
description += "The column <" + fieldType.name + "> has " + fieldType.totalNullValues + " EMPTY value";
if (fieldType.totalNullValues > 1) description += "s";
}
if (description.length > 0)
description += ".";*/
fieldType.errorsDescription = description.trim();
warningsTextual += description.trim();
});
var metadata = { dataset: json, fieldKeys: fieldKeys, types: fieldsType, qualityIndex: quality, warningsTextual: warningsTextual };
_filterBasedOnThreshold(metadata, options.thresholdConfidence);
return metadata;
},//EndFunction.
/*inferDataTypes: function (jsonRows) {
this._fields = [];
this._numOfRows = 0;
_processDataset(jsonRows);
return this._fields;
},//EndFunction.*/
/**
* Given in input a value, the function infers the data type.
* @param value
* @returns {*}
*/
inferDataTypeOfValue: function (value) {
return _processInferType(value);
},//EndFunction.
/**
* Given in input a value, the function infers the data type.
* @param value
* @returns {*}
*/
inferDataSubTypeOfValue: function (value) {
return _processInferSubType(value);
}//EndFunction.
};
})();