highcharts
Version:
JavaScript charting framework
1,356 lines (1,350 loc) • 78 kB
JavaScript
/* *
*
* Data module
*
* (c) 2012-2021 Torstein Honsi
*
* License: www.highcharts.com/license
*
* !!!!!!! SOURCE GETS TRANSPILED BY TYPESCRIPT. EDIT TS FILE ONLY. !!!!!!!
*
* */
'use strict';
import Ajax from '../Extensions/Ajax.js';
var ajax = Ajax.ajax;
import Chart from '../Core/Chart/Chart.js';
import H from '../Core/Globals.js';
var doc = H.doc;
import Point from '../Core/Series/Point.js';
import SeriesRegistry from '../Core/Series/SeriesRegistry.js';
var seriesTypes = SeriesRegistry.seriesTypes;
import U from '../Core/Utilities.js';
var addEvent = U.addEvent, defined = U.defined, extend = U.extend, fireEvent = U.fireEvent, isNumber = U.isNumber, merge = U.merge, objectEach = U.objectEach, pick = U.pick, splat = U.splat;
/**
* Callback function to modify the CSV before parsing it by the data module.
*
* @callback Highcharts.DataBeforeParseCallbackFunction
*
* @param {string} csv
* The CSV to modify.
*
* @return {string}
* The CSV to parse.
*/
/**
* Callback function that gets called after parsing data.
*
* @callback Highcharts.DataCompleteCallbackFunction
*
* @param {Highcharts.Options} chartOptions
* The chart options that were used.
*/
/**
* Callback function that returns the correspondig Date object to a match.
*
* @callback Highcharts.DataDateFormatCallbackFunction
*
* @param {Array<number>} match
*
* @return {number}
*/
/**
* Structure for alternative date formats to parse.
*
* @interface Highcharts.DataDateFormatObject
*/ /**
* @name Highcharts.DataDateFormatObject#alternative
* @type {string|undefined}
*/ /**
* @name Highcharts.DataDateFormatObject#parser
* @type {Highcharts.DataDateFormatCallbackFunction}
*/ /**
* @name Highcharts.DataDateFormatObject#regex
* @type {global.RegExp}
*/
/**
* Possible types for a data item in a column or row.
*
* @typedef {number|string|null} Highcharts.DataValueType
*/
/**
* Callback function to parse string representations of dates into
* JavaScript timestamps (milliseconds since 1.1.1970).
*
* @callback Highcharts.DataParseDateCallbackFunction
*
* @param {string} dateValue
*
* @return {number}
* Timestamp (milliseconds since 1.1.1970) as integer for Date class.
*/
/**
* Callback function to access the parsed columns, the two-dimentional
* input data array directly, before they are interpreted into series
* data and categories.
*
* @callback Highcharts.DataParsedCallbackFunction
*
* @param {Array<Array<*>>} columns
* The parsed columns by the data module.
*
* @return {boolean|undefined}
* Return `false` to stop completion, or call `this.complete()` to
* continue async.
*/
/**
* The Data module provides a simplified interface for adding data to
* a chart from sources like CVS, HTML tables or grid views. See also
* the [tutorial article on the Data module](
* https://www.highcharts.com/docs/working-with-data/data-module).
*
* It requires the `modules/data.js` file to be loaded.
*
* Please note that the default way of adding data in Highcharts, without
* the need of a module, is through the [series._type_.data](#series.line.data)
* option.
*
* @sample {highcharts} highcharts/demo/column-parsed/
* HTML table
* @sample {highcharts} highcharts/data/csv/
* CSV
*
* @since 4.0
* @requires modules/data
* @apioption data
*/
/**
* A callback function to modify the CSV before parsing it. Return the modified
* string.
*
* @sample {highcharts} highcharts/demo/line-ajax/
* Modify CSV before parse
*
* @type {Highcharts.DataBeforeParseCallbackFunction}
* @since 6.1
* @apioption data.beforeParse
*/
/**
* A two-dimensional array representing the input data on tabular form.
* This input can be used when the data is already parsed, for example
* from a grid view component. Each cell can be a string or number.
* If not switchRowsAndColumns is set, the columns are interpreted as
* series.
*
* @see [data.rows](#data.rows)
*
* @sample {highcharts} highcharts/data/columns/
* Columns
*
* @type {Array<Array<Highcharts.DataValueType>>}
* @since 4.0
* @apioption data.columns
*/
/**
* The callback that is evaluated when the data is finished loading,
* optionally from an external source, and parsed. The first argument
* passed is a finished chart options object, containing the series.
* These options can be extended with additional options and passed
* directly to the chart constructor.
*
* @see [data.parsed](#data.parsed)
*
* @sample {highcharts} highcharts/data/complete/
* Modify data on complete
*
* @type {Highcharts.DataCompleteCallbackFunction}
* @since 4.0
* @apioption data.complete
*/
/**
* A comma delimited string to be parsed. Related options are [startRow](
* #data.startRow), [endRow](#data.endRow), [startColumn](#data.startColumn)
* and [endColumn](#data.endColumn) to delimit what part of the table
* is used. The [lineDelimiter](#data.lineDelimiter) and [itemDelimiter](
* #data.itemDelimiter) options define the CSV delimiter formats.
*
* The built-in CSV parser doesn't support all flavours of CSV, so in
* some cases it may be necessary to use an external CSV parser. See
* [this example](https://jsfiddle.net/highcharts/u59176h4/) of parsing
* CSV through the MIT licensed [Papa Parse](http://papaparse.com/)
* library.
*
* @sample {highcharts} highcharts/data/csv/
* Data from CSV
*
* @type {string}
* @since 4.0
* @apioption data.csv
*/
/**
* Which of the predefined date formats in Date.prototype.dateFormats
* to use to parse date values. Defaults to a best guess based on what
* format gives valid and ordered dates. Valid options include: `YYYY/mm/dd`,
* `dd/mm/YYYY`, `mm/dd/YYYY`, `dd/mm/YY`, `mm/dd/YY`.
*
* @see [data.parseDate](#data.parseDate)
*
* @sample {highcharts} highcharts/data/dateformat-auto/
* Best guess date format
*
* @type {string}
* @since 4.0
* @validvalue ["YYYY/mm/dd", "dd/mm/YYYY", "mm/dd/YYYY", "dd/mm/YYYY",
* "dd/mm/YY", "mm/dd/YY"]
* @apioption data.dateFormat
*/
/**
* The decimal point used for parsing numbers in the CSV.
*
* If both this and data.delimiter is set to `undefined`, the parser will
* attempt to deduce the decimal point automatically.
*
* @sample {highcharts} highcharts/data/delimiters/
* Comma as decimal point
*
* @type {string}
* @default .
* @since 4.1.0
* @apioption data.decimalPoint
*/
/**
* In tabular input data, the last column (indexed by 0) to use. Defaults
* to the last column containing data.
*
* @sample {highcharts} highcharts/data/start-end/
* Limited data
*
* @type {number}
* @since 4.0
* @apioption data.endColumn
*/
/**
* In tabular input data, the last row (indexed by 0) to use. Defaults
* to the last row containing data.
*
* @sample {highcharts} highcharts/data/start-end/
* Limited data
*
* @type {number}
* @since 4.0.4
* @apioption data.endRow
*/
/**
* Whether to use the first row in the data set as series names.
*
* @sample {highcharts} highcharts/data/start-end/
* Don't get series names from the CSV
* @sample {highstock} highcharts/data/start-end/
* Don't get series names from the CSV
*
* @type {boolean}
* @default true
* @since 4.1.0
* @product highcharts highstock gantt
* @apioption data.firstRowAsNames
*/
/**
* The key for a Google Spreadsheet to load. See [general information
* on GS](https://developers.google.com/gdata/samples/spreadsheet_sample).
*
* @sample {highcharts} highcharts/data/google-spreadsheet/
* Load a Google Spreadsheet
*
* @type {string}
* @since 4.0
* @apioption data.googleSpreadsheetKey
*/
/**
* The Google Spreadsheet worksheet to use in combination with
* [googleSpreadsheetKey](#data.googleSpreadsheetKey). The available id's from
* your sheet can be read from `https://spreadsheets.google.com/feeds/worksheets/{key}/public/basic`.
*
* @sample {highcharts} highcharts/data/google-spreadsheet/
* Load a Google Spreadsheet
*
* @type {string}
* @since 4.0
* @apioption data.googleSpreadsheetWorksheet
*/
/**
* Item or cell delimiter for parsing CSV. Defaults to the tab character
* `\t` if a tab character is found in the CSV string, if not it defaults
* to `,`.
*
* If this is set to false or undefined, the parser will attempt to deduce
* the delimiter automatically.
*
* @sample {highcharts} highcharts/data/delimiters/
* Delimiters
*
* @type {string}
* @since 4.0
* @apioption data.itemDelimiter
*/
/**
* Line delimiter for parsing CSV.
*
* @sample {highcharts} highcharts/data/delimiters/
* Delimiters
*
* @type {string}
* @default \n
* @since 4.0
* @apioption data.lineDelimiter
*/
/**
* A callback function to access the parsed columns, the two-dimentional
* input data array directly, before they are interpreted into series
* data and categories. Return `false` to stop completion, or call
* `this.complete()` to continue async.
*
* @see [data.complete](#data.complete)
*
* @sample {highcharts} highcharts/data/parsed/
* Modify data after parse
*
* @type {Highcharts.DataParsedCallbackFunction}
* @since 4.0
* @apioption data.parsed
*/
/**
* A callback function to parse string representations of dates into
* JavaScript timestamps. Should return an integer timestamp on success.
*
* @see [dateFormat](#data.dateFormat)
*
* @type {Highcharts.DataParseDateCallbackFunction}
* @since 4.0
* @apioption data.parseDate
*/
/**
* The same as the columns input option, but defining rows intead of
* columns.
*
* @see [data.columns](#data.columns)
*
* @sample {highcharts} highcharts/data/rows/
* Data in rows
*
* @type {Array<Array<Highcharts.DataValueType>>}
* @since 4.0
* @apioption data.rows
*/
/**
* An array containing dictionaries for each series. A dictionary exists of
* Point property names as the key and the CSV column index as the value.
*
* @sample {highcharts} highcharts/data/seriesmapping-label/
* Label from data set
*
* @type {Array<Highcharts.Dictionary<number>>}
* @since 4.0.4
* @apioption data.seriesMapping
*/
/**
* In tabular input data, the first column (indexed by 0) to use.
*
* @sample {highcharts} highcharts/data/start-end/
* Limited data
*
* @type {number}
* @default 0
* @since 4.0
* @apioption data.startColumn
*/
/**
* In tabular input data, the first row (indexed by 0) to use.
*
* @sample {highcharts} highcharts/data/start-end/
* Limited data
*
* @type {number}
* @default 0
* @since 4.0
* @apioption data.startRow
*/
/**
* Switch rows and columns of the input data, so that `this.columns`
* effectively becomes the rows of the data set, and the rows are interpreted
* as series.
*
* @sample {highcharts} highcharts/data/switchrowsandcolumns/
* Switch rows and columns
*
* @type {boolean}
* @default false
* @since 4.0
* @apioption data.switchRowsAndColumns
*/
/**
* An HTML table or the id of such to be parsed as input data. Related
* options are `startRow`, `endRow`, `startColumn` and `endColumn` to
* delimit what part of the table is used.
*
* @sample {highcharts} highcharts/demo/column-parsed/
* Parsed table
*
* @type {string|global.HTMLElement}
* @since 4.0
* @apioption data.table
*/
/**
* An URL to a remote CSV dataset. Will be fetched when the chart is created
* using Ajax.
*
* @sample highcharts/data/livedata-columns
* Categorized bar chart with CSV and live polling
* @sample highcharts/data/livedata-csv
* Time based line chart with CSV and live polling
*
* @type {string}
* @apioption data.csvURL
*/
/**
* A URL to a remote JSON dataset, structured as a row array.
* Will be fetched when the chart is created using Ajax.
*
* @sample highcharts/data/livedata-rows
* Rows with live polling
*
* @type {string}
* @apioption data.rowsURL
*/
/**
* A URL to a remote JSON dataset, structured as a column array.
* Will be fetched when the chart is created using Ajax.
*
* @sample highcharts/data/livedata-columns
* Columns with live polling
*
* @type {string}
* @apioption data.columnsURL
*/
/**
* Sets the refresh rate for data polling when importing remote dataset by
* setting [data.csvURL](data.csvURL), [data.rowsURL](data.rowsURL),
* [data.columnsURL](data.columnsURL), or
* [data.googleSpreadsheetKey](data.googleSpreadsheetKey).
*
* Note that polling must be enabled by setting
* [data.enablePolling](data.enablePolling) to true.
*
* The value is the number of seconds between pollings.
* It cannot be set to less than 1 second.
*
* @sample highcharts/demo/live-data
* Live data with user set refresh rate
*
* @default 1
* @type {number}
* @apioption data.dataRefreshRate
*/
/**
* Enables automatic refetching of remote datasets every _n_ seconds (defined by
* setting [data.dataRefreshRate](data.dataRefreshRate)).
*
* Only works when either [data.csvURL](data.csvURL),
* [data.rowsURL](data.rowsURL), [data.columnsURL](data.columnsURL), or
* [data.googleSpreadsheetKey](data.googleSpreadsheetKey).
*
* @sample highcharts/demo/live-data
* Live data
* @sample highcharts/data/livedata-columns
* Categorized bar chart with CSV and live polling
*
* @type {boolean}
* @default false
* @apioption data.enablePolling
*/
/* eslint-disable valid-jsdoc */
/**
* The Data class
*
* @requires module:modules/data
*
* @class
* @name Highcharts.Data
*
* @param {Highcharts.DataOptions} dataOptions
*
* @param {Highcharts.Options} [chartOptions]
*
* @param {Highcharts.Chart} [chart]
*/
var Data = /** @class */ (function () {
/* *
*
* Constructors
*
* */
function Data(dataOptions, chartOptions, chart) {
this.chart = void 0;
this.chartOptions = void 0;
this.firstRowAsNames = void 0;
this.rawColumns = void 0;
this.options = void 0;
/**
* A collection of available date formats, extendable from the outside to
* support custom date formats.
*
* @name Highcharts.Data#dateFormats
* @type {Highcharts.Dictionary<Highcharts.DataDateFormatObject>}
*/
this.dateFormats = {
'YYYY/mm/dd': {
regex: /^([0-9]{4})[\-\/\.]([0-9]{1,2})[\-\/\.]([0-9]{1,2})$/,
parser: function (match) {
return (match ?
Date.UTC(+match[1], match[2] - 1, +match[3]) :
NaN);
}
},
'dd/mm/YYYY': {
regex: /^([0-9]{1,2})[\-\/\.]([0-9]{1,2})[\-\/\.]([0-9]{4})$/,
parser: function (match) {
return (match ?
Date.UTC(+match[3], match[2] - 1, +match[1]) :
NaN);
},
alternative: 'mm/dd/YYYY' // different format with the same regex
},
'mm/dd/YYYY': {
regex: /^([0-9]{1,2})[\-\/\.]([0-9]{1,2})[\-\/\.]([0-9]{4})$/,
parser: function (match) {
return (match ?
Date.UTC(+match[3], match[1] - 1, +match[2]) :
NaN);
}
},
'dd/mm/YY': {
regex: /^([0-9]{1,2})[\-\/\.]([0-9]{1,2})[\-\/\.]([0-9]{2})$/,
parser: function (match) {
if (!match) {
return NaN;
}
var year = +match[3], d = new Date();
if (year > (d.getFullYear() - 2000)) {
year += 1900;
}
else {
year += 2000;
}
return Date.UTC(year, match[2] - 1, +match[1]);
},
alternative: 'mm/dd/YY' // different format with the same regex
},
'mm/dd/YY': {
regex: /^([0-9]{1,2})[\-\/\.]([0-9]{1,2})[\-\/\.]([0-9]{2})$/,
parser: function (match) {
return (match ?
Date.UTC(+match[3] + 2000, match[1] - 1, +match[2]) :
NaN);
}
}
};
this.init(dataOptions, chartOptions, chart);
}
/* *
*
* Functions
*
* */
/**
* Initialize the Data object with the given options
*
* @private
* @function Highcharts.Data#init
* @param {Highcharts.DataOptions} options
* @param {Highcharts.Options} [chartOptions]
* @param {Highcharts.Chart} [chart]
*/
Data.prototype.init = function (options, chartOptions, chart) {
var decimalPoint = options.decimalPoint, hasData;
if (chartOptions) {
this.chartOptions = chartOptions;
}
if (chart) {
this.chart = chart;
}
if (decimalPoint !== '.' && decimalPoint !== ',') {
decimalPoint = void 0;
}
this.options = options;
this.columns = (options.columns ||
this.rowsToColumns(options.rows) ||
[]);
this.firstRowAsNames = pick(options.firstRowAsNames, this.firstRowAsNames, true);
this.decimalRegex = (decimalPoint &&
new RegExp('^(-?[0-9]+)' + decimalPoint + '([0-9]+)$'));
// This is a two-dimensional array holding the raw, trimmed string
// values with the same organisation as the columns array. It makes it
// possible for example to revert from interpreted timestamps to
// string-based categories.
this.rawColumns = [];
// No need to parse or interpret anything
if (this.columns.length) {
this.dataFound();
hasData = true;
}
if (this.hasURLOption(options)) {
clearTimeout(this.liveDataTimeout);
hasData = false;
}
if (!hasData) {
// Fetch live data
hasData = this.fetchLiveData();
}
if (!hasData) {
// Parse a CSV string if options.csv is given. The parseCSV function
// returns a columns array, if it has no length, we have no data
hasData = Boolean(this.parseCSV().length);
}
if (!hasData) {
// Parse a HTML table if options.table is given
hasData = Boolean(this.parseTable().length);
}
if (!hasData) {
// Parse a Google Spreadsheet
hasData = this.parseGoogleSpreadsheet();
}
if (!hasData && options.afterComplete) {
options.afterComplete();
}
};
Data.prototype.hasURLOption = function (options) {
return Boolean(options &&
(options.rowsURL || options.csvURL || options.columnsURL));
};
/**
* Get the column distribution. For example, a line series takes a single
* column for Y values. A range series takes two columns for low and high
* values respectively, and an OHLC series takes four columns.
*
* @function Highcharts.Data#getColumnDistribution
*/
Data.prototype.getColumnDistribution = function () {
var chartOptions = this.chartOptions, options = this.options, xColumns = [], getValueCount = function (type) {
return (seriesTypes[type || 'line'].prototype.pointArrayMap || [0]).length;
}, getPointArrayMap = function (type) {
return seriesTypes[type || 'line'].prototype.pointArrayMap;
}, globalType = (chartOptions &&
chartOptions.chart &&
chartOptions.chart.type), individualCounts = [], seriesBuilders = [], seriesIndex = 0,
// If no series mapping is defined, check if the series array is
// defined with types.
seriesMapping = ((options && options.seriesMapping) ||
(chartOptions &&
chartOptions.series &&
chartOptions.series.map(function () {
return { x: 0 };
})) ||
[]), i;
((chartOptions && chartOptions.series) || []).forEach(function (series) {
individualCounts.push(getValueCount(series.type || globalType));
});
// Collect the x-column indexes from seriesMapping
seriesMapping.forEach(function (mapping) {
xColumns.push(mapping.x || 0);
});
// If there are no defined series with x-columns, use the first column
// as x column
if (xColumns.length === 0) {
xColumns.push(0);
}
// Loop all seriesMappings and constructs SeriesBuilders from
// the mapping options.
seriesMapping.forEach(function (mapping) {
var builder = new SeriesBuilder(), numberOfValueColumnsNeeded = individualCounts[seriesIndex] ||
getValueCount(globalType), seriesArr = (chartOptions && chartOptions.series) || [], series = seriesArr[seriesIndex] || {}, defaultPointArrayMap = getPointArrayMap(series.type || globalType), pointArrayMap = defaultPointArrayMap || ['y'];
if (
// User-defined x.mapping
defined(mapping.x) ||
// All non cartesian don't need 'x'
series.isCartesian ||
// Except pie series:
!defaultPointArrayMap) {
// Add an x reader from the x property or from an undefined
// column if the property is not set. It will then be auto
// populated later.
builder.addColumnReader(mapping.x, 'x');
}
// Add all column mappings
objectEach(mapping, function (val, name) {
if (name !== 'x') {
builder.addColumnReader(val, name);
}
});
// Add missing columns
for (i = 0; i < numberOfValueColumnsNeeded; i++) {
if (!builder.hasReader(pointArrayMap[i])) {
// Create and add a column reader for the next free column
// index
builder.addColumnReader(void 0, pointArrayMap[i]);
}
}
seriesBuilders.push(builder);
seriesIndex++;
});
var globalPointArrayMap = getPointArrayMap(globalType);
if (typeof globalPointArrayMap === 'undefined') {
globalPointArrayMap = ['y'];
}
this.valueCount = {
global: getValueCount(globalType),
xColumns: xColumns,
individual: individualCounts,
seriesBuilders: seriesBuilders,
globalPointArrayMap: globalPointArrayMap
};
};
/**
* When the data is parsed into columns, either by CSV, table, GS or direct
* input, continue with other operations.
*
* @private
* @function Highcharts.Data#dataFound
*/
Data.prototype.dataFound = function () {
if (this.options.switchRowsAndColumns) {
this.columns = this.rowsToColumns(this.columns);
}
// Interpret the info about series and columns
this.getColumnDistribution();
// Interpret the values into right types
this.parseTypes();
// Handle columns if a handleColumns callback is given
if (this.parsed() !== false) {
// Complete if a complete callback is given
this.complete();
}
};
/**
* Parse a CSV input string
*
* @function Highcharts.Data#parseCSV
*
* @param {Highcharts.DataOptions} [inOptions]
*
* @return {Array<Array<Highcharts.DataValueType>>}
*/
Data.prototype.parseCSV = function (inOptions) {
var self = this, options = inOptions || this.options, csv = options.csv, columns, startRow = (typeof options.startRow !== 'undefined' && options.startRow ?
options.startRow :
0), endRow = options.endRow || Number.MAX_VALUE, startColumn = (typeof options.startColumn !== 'undefined' &&
options.startColumn) ? options.startColumn : 0, endColumn = options.endColumn || Number.MAX_VALUE, itemDelimiter, lines, rowIt = 0,
// activeRowNo = 0,
dataTypes = [],
// We count potential delimiters in the prepass, and use the
// result as the basis of half-intelligent guesses.
potDelimiters = {
',': 0,
';': 0,
'\t': 0
};
columns = this.columns = [];
/*
This implementation is quite verbose. It will be shortened once
it's stable and passes all the test.
It's also not written with speed in mind, instead everything is
very seggregated, and there a several redundant loops.
This is to make it easier to stabilize the code initially.
We do a pre-pass on the first 4 rows to make some intelligent
guesses on the set. Guessed delimiters are in this pass counted.
Auto detecting delimiters
- If we meet a quoted string, the next symbol afterwards
(that's not \s, \t) is the delimiter
- If we meet a date, the next symbol afterwards is the delimiter
Date formats
- If we meet a column with date formats, check all of them to
see if one of the potential months crossing 12. If it does,
we now know the format
It would make things easier to guess the delimiter before
doing the actual parsing.
General rules:
- Quoting is allowed, e.g: "Col 1",123,321
- Quoting is optional, e.g.: Col1,123,321
- Doubble quoting is escaping, e.g. "Col ""Hello world""",123
- Spaces are considered part of the data: Col1 ,123
- New line is always the row delimiter
- Potential column delimiters are , ; \t
- First row may optionally contain headers
- The last row may or may not have a row delimiter
- Comments are optionally supported, in which case the comment
must start at the first column, and the rest of the line will
be ignored
*/
/**
* Parse a single row.
* @private
*/
function parseRow(columnStr, rowNumber, noAdd, callbacks) {
var i = 0, c = '', cl = '', cn = '', token = '', actualColumn = 0, column = 0;
/**
* @private
*/
function read(j) {
c = columnStr[j];
cl = columnStr[j - 1];
cn = columnStr[j + 1];
}
/**
* @private
*/
function pushType(type) {
if (dataTypes.length < column + 1) {
dataTypes.push([type]);
}
if (dataTypes[column][dataTypes[column].length - 1] !== type) {
dataTypes[column].push(type);
}
}
/**
* @private
*/
function push() {
if (startColumn > actualColumn || actualColumn > endColumn) {
// Skip this column, but increment the column count (#7272)
++actualColumn;
token = '';
return;
}
if (!isNaN(parseFloat(token)) && isFinite(token)) {
token = parseFloat(token);
pushType('number');
}
else if (!isNaN(Date.parse(token))) {
token = token.replace(/\//g, '-');
pushType('date');
}
else {
pushType('string');
}
if (columns.length < column + 1) {
columns.push([]);
}
if (!noAdd) {
// Don't push - if there's a varrying amount of columns
// for each row, pushing will skew everything down n slots
columns[column][rowNumber] = token;
}
token = '';
++column;
++actualColumn;
}
if (!columnStr.trim().length) {
return;
}
if (columnStr.trim()[0] === '#') {
return;
}
for (; i < columnStr.length; i++) {
read(i);
if (c === '"') {
read(++i);
while (i < columnStr.length) {
if (c === '"' && cl !== '"' && cn !== '"') {
break;
}
if (c !== '"' || (c === '"' && cl !== '"')) {
token += c;
}
read(++i);
}
// Perform "plugin" handling
}
else if (callbacks && callbacks[c]) {
if (callbacks[c](c, token)) {
push();
}
// Delimiter - push current token
}
else if (c === itemDelimiter) {
push();
// Actual column data
}
else {
token += c;
}
}
push();
}
/**
* Attempt to guess the delimiter. We do a separate parse pass here
* because we need to count potential delimiters softly without making
* any assumptions.
* @private
*/
function guessDelimiter(lines) {
var points = 0, commas = 0, guessed = false;
lines.some(function (columnStr, i) {
var inStr = false, c, cn, cl, token = '';
// We should be able to detect dateformats within 13 rows
if (i > 13) {
return true;
}
for (var j = 0; j < columnStr.length; j++) {
c = columnStr[j];
cn = columnStr[j + 1];
cl = columnStr[j - 1];
if (c === '#') {
// Skip the rest of the line - it's a comment
return;
}
if (c === '"') {
if (inStr) {
if (cl !== '"' && cn !== '"') {
while (cn === ' ' && j < columnStr.length) {
cn = columnStr[++j];
}
// After parsing a string, the next non-blank
// should be a delimiter if the CSV is properly
// formed.
if (typeof potDelimiters[cn] !== 'undefined') {
potDelimiters[cn]++;
}
inStr = false;
}
}
else {
inStr = true;
}
}
else if (typeof potDelimiters[c] !== 'undefined') {
token = token.trim();
if (!isNaN(Date.parse(token))) {
potDelimiters[c]++;
}
else if (isNaN(token) ||
!isFinite(token)) {
potDelimiters[c]++;
}
token = '';
}
else {
token += c;
}
if (c === ',') {
commas++;
}
if (c === '.') {
points++;
}
}
});
// Count the potential delimiters.
// This could be improved by checking if the number of delimiters
// equals the number of columns - 1
if (potDelimiters[';'] > potDelimiters[',']) {
guessed = ';';
}
else if (potDelimiters[','] > potDelimiters[';']) {
guessed = ',';
}
else {
// No good guess could be made..
guessed = ',';
}
// Try to deduce the decimal point if it's not explicitly set.
// If both commas or points is > 0 there is likely an issue
if (!options.decimalPoint) {
if (points > commas) {
options.decimalPoint = '.';
}
else {
options.decimalPoint = ',';
}
// Apply a new decimal regex based on the presumed decimal sep.
self.decimalRegex = new RegExp('^(-?[0-9]+)' +
options.decimalPoint +
'([0-9]+)$');
}
return guessed;
}
/**
* Tries to guess the date format
* - Check if either month candidate exceeds 12
* - Check if year is missing (use current year)
* - Check if a shortened year format is used (e.g. 1/1/99)
* - If no guess can be made, the user must be prompted
* data is the data to deduce a format based on
* @private
*/
function deduceDateFormat(data, limit) {
var format = 'YYYY/mm/dd', thing, guessedFormat = [], calculatedFormat, i = 0, madeDeduction = false,
// candidates = {},
stable = [], max = [], j;
if (!limit || limit > data.length) {
limit = data.length;
}
for (; i < limit; i++) {
if (typeof data[i] !== 'undefined' &&
data[i] && data[i].length) {
thing = data[i]
.trim()
.replace(/\//g, ' ')
.replace(/\-/g, ' ')
.replace(/\./g, ' ')
.split(' ');
guessedFormat = [
'',
'',
''
];
for (j = 0; j < thing.length; j++) {
if (j < guessedFormat.length) {
thing[j] = parseInt(thing[j], 10);
if (thing[j]) {
max[j] = (!max[j] || max[j] < thing[j]) ?
thing[j] :
max[j];
if (typeof stable[j] !== 'undefined') {
if (stable[j] !== thing[j]) {
stable[j] = false;
}
}
else {
stable[j] = thing[j];
}
if (thing[j] > 31) {
if (thing[j] < 100) {
guessedFormat[j] = 'YY';
}
else {
guessedFormat[j] = 'YYYY';
}
// madeDeduction = true;
}
else if (thing[j] > 12 &&
thing[j] <= 31) {
guessedFormat[j] = 'dd';
madeDeduction = true;
}
else if (!guessedFormat[j].length) {
guessedFormat[j] = 'mm';
}
}
}
}
}
}
if (madeDeduction) {
// This handles a few edge cases with hard to guess dates
for (j = 0; j < stable.length; j++) {
if (stable[j] !== false) {
if (max[j] > 12 &&
guessedFormat[j] !== 'YY' &&
guessedFormat[j] !== 'YYYY') {
guessedFormat[j] = 'YY';
}
}
else if (max[j] > 12 && guessedFormat[j] === 'mm') {
guessedFormat[j] = 'dd';
}
}
// If the middle one is dd, and the last one is dd,
// the last should likely be year.
if (guessedFormat.length === 3 &&
guessedFormat[1] === 'dd' &&
guessedFormat[2] === 'dd') {
guessedFormat[2] = 'YY';
}
calculatedFormat = guessedFormat.join('/');
// If the caculated format is not valid, we need to present an
// error.
if (!(options.dateFormats || self.dateFormats)[calculatedFormat]) {
// This should emit an event instead
fireEvent('deduceDateFailed');
return format;
}
return calculatedFormat;
}
return format;
}
/**
* @todo
* Figure out the best axis types for the data
* - If the first column is a number, we're good
* - If the first column is a date, set to date/time
* - If the first column is a string, set to categories
* @private
*/
function deduceAxisTypes() {
}
if (csv && options.beforeParse) {
csv = options.beforeParse.call(this, csv);
}
if (csv) {
lines = csv
.replace(/\r\n/g, '\n') // Unix
.replace(/\r/g, '\n') // Mac
.split(options.lineDelimiter || '\n');
if (!startRow || startRow < 0) {
startRow = 0;
}
if (!endRow || endRow >= lines.length) {
endRow = lines.length - 1;
}
if (options.itemDelimiter) {
itemDelimiter = options.itemDelimiter;
}
else {
itemDelimiter = null;
itemDelimiter = guessDelimiter(lines);
}
var offset = 0;
for (rowIt = startRow; rowIt <= endRow; rowIt++) {
if (lines[rowIt][0] === '#') {
offset++;
}
else {
parseRow(lines[rowIt], rowIt - startRow - offset);
}
}
// //Make sure that there's header columns for everything
// columns.forEach(function (col) {
// });
deduceAxisTypes();
if ((!options.columnTypes || options.columnTypes.length === 0) &&
dataTypes.length &&
dataTypes[0].length &&
dataTypes[0][1] === 'date' &&
!options.dateFormat) {
options.dateFormat = deduceDateFormat(columns[0]);
}
// lines.forEach(function (line, rowNo) {
// var trimmed = self.trim(line),
// isComment = trimmed.indexOf('#') === 0,
// isBlank = trimmed === '',
// items;
// if (
// rowNo >= startRow &&
// rowNo <= endRow &&
// !isComment && !isBlank
// ) {
// items = line.split(itemDelimiter);
// items.forEach(function (item, colNo) {
// if (colNo >= startColumn && colNo <= endColumn) {
// if (!columns[colNo - startColumn]) {
// columns[colNo - startColumn] = [];
// }
// columns[colNo - startColumn][activeRowNo] = item;
// }
// });
// activeRowNo += 1;
// }
// });
//
this.dataFound();
}
return columns;
};
/**
* Parse a HTML table
*
* @function Highcharts.Data#parseTable
*
* @return {Array<Array<Highcharts.DataValueType>>}
*/
Data.prototype.parseTable = function () {
var options = this.options, table = options.table, columns = this.columns || [], startRow = options.startRow || 0, endRow = options.endRow || Number.MAX_VALUE, startColumn = options.startColumn || 0, endColumn = options.endColumn || Number.MAX_VALUE;
if (table) {
if (typeof table === 'string') {
table = doc.getElementById(table);
}
[].forEach.call(table.getElementsByTagName('tr'), function (tr, rowNo) {
if (rowNo >= startRow && rowNo <= endRow) {
[].forEach.call(tr.children, function (item, colNo) {
var row = columns[colNo - startColumn];
var i = 1;
if ((item.tagName === 'TD' ||
item.tagName === 'TH') &&
colNo >= startColumn &&
colNo <= endColumn) {
if (!columns[colNo - startColumn]) {
columns[colNo - startColumn] = [];
}
columns[colNo - startColumn][rowNo - startRow] = item.innerHTML;
// Loop over all previous indices and make sure
// they are nulls, not undefined.
while (rowNo - startRow >= i &&
row[rowNo - startRow - i] === void 0) {
row[rowNo - startRow - i] = null;
i++;
}
}
});
}
});
this.dataFound(); // continue
}
return columns;
};
/**
* Fetch or refetch live data
*
* @function Highcharts.Data#fetchLiveData
*
* @return {boolean}
* The URLs that were tried can be found in the options
*/
Data.prototype.fetchLiveData = function () {
var data = this, chart = this.chart, options = this.options, maxRetries = 3, currentRetries = 0, pollingEnabled = options.enablePolling, updateIntervalMs = (options.dataRefreshRate || 2) * 1000, originalOptions = merge(options);
if (!this.hasURLOption(options)) {
return false;
}
// Do not allow polling more than once a second
if (updateIntervalMs < 1000) {
updateIntervalMs = 1000;
}
delete options.csvURL;
delete options.rowsURL;
delete options.columnsURL;
/**
* @private
*/
function performFetch(initialFetch) {
/**
* Helper function for doing the data fetch + polling.
* @private
*/
function request(url, done, tp) {
if (!url || url.indexOf('http') !== 0) {
if (url && options.error) {
options.error('Invalid URL');
}
return false;
}
if (initialFetch) {
clearTimeout(data.liveDataTimeout);
chart.liveDataURL = url;
}
/**
* @private
*/
function poll() {
// Poll
if (pollingEnabled && chart.liveDataURL === url) {
// We need to stop doing this if the URL has changed
data.liveDataTimeout =
setTimeout(performFetch, updateIntervalMs);
}
}
ajax({
url: url,
dataType: tp || 'json',
success: function (res) {
if (chart && chart.series) {
done(res);
}
poll();
},
error: function (xhr, text) {
if (++currentRetries < maxRetries) {
poll();
}
return options.error && options.error(text, xhr);
}
});
return true;
}
if (!request(originalOptions.csvURL, function (res) {
chart.update({
data: {
csv: res
}
});
}, 'text')) {
if (!request(originalOptions.rowsURL, function (res) {
chart.update({
data: {
rows: res
}
});
})) {
request(originalOptions.columnsURL, function (res) {
chart.update({
data: {
columns: res
}
});
});
}
}
}
performFetch(true);
return this.hasURLOption(options);
};
/**
* Parse a Google spreadsheet.
*
* @function Highcharts.Data#parseGoogleSpreadsheet
*
* @return {boolean}
* Always returns false, because it is an intermediate fetch.
*/
Data.prototype.parseGoogleSpreadsheet = function () {
var data = this, options = this.options, googleSpreadsheetKey = options.googleSpreadsheetKey, chart = this.chart,
// use sheet 1 as the default rather than od6
// as the latter sometimes cause issues (it looks like it can
// be renamed in some cases, ref. a fogbugz case).
worksheet = options.googleSpreadsheetWorksheet || 1, startRow = options.startRow || 0, endRow = options.endRow || Number.MAX_VALUE, startColumn = options.startColumn || 0, endColumn = options.endColumn || Number.MAX_VALUE, refreshRate = (options.dataRefreshRate || 2) * 1000;
if (refreshRate < 4000) {
refreshRate = 4000;
}
/**
* Fetch the actual spreadsheet using XMLHttpRequest.
* @private
*/
function fetchSheet(fn) {
var url = [
'https://spreadsheets.google.com/feeds/cells',
googleSpreadsheetKey,
worksheet,
'public/values?alt=json'
].join('/');
ajax({
url: url,
dataType: 'json',
success: function (json) {
fn(json);
if (options.enablePolling) {
setTimeout(function () {
fetchSheet(fn);
}, (options.dataRefreshRate || 2) * 1000);
}
},
error: function (xhr, text) {
return options.error && options.error(text, xhr);
}
});
}
if (googleSpreadsheetKey) {
delete options.googleSpreadsheetKey;
fetchSheet(function (json) {
// Prepare the data from the spreadsheat
var columns = [], cells = json.feed.entry, cell, cellCount = (cells || []).length, colCount = 0, rowCount = 0, val, gr, gc, cellInner, i;
if (!cells || cells.length === 0) {
return false;
}
// First, find the total number of columns and rows that
// are actually filled with data
for (i = 0; i < cellCount; i++) {
cell = cells[i];
colCount = Math.max(colCount, cell.gs$cell.col);
rowCount = Math.max(rowCount, cell.gs$cell.row);
}
// Set up arrays containing the column data
for (i = 0; i < colCount; i++) {
if (i >= startColumn && i <= endColumn) {
// Create new columns with the length of either
// end-start or rowCount
columns[i - startColumn] = [];
}
}
// Loop over the cells and assign the value to the right
// place in the column arrays
for (i = 0; i < cellCount; i++) {
cell = cells[i];
gr = cell.gs$cell.row - 1; // rows start at 1
gc = cell.gs$cell.col - 1; // columns start at 1
// If both row and col falls