690 lines
22 KiB
JavaScript
690 lines
22 KiB
JavaScript
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/*
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* Licensed to the Apache Software Foundation (ASF) under one
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* or more contributor license agreements. See the NOTICE file
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* distributed with this work for additional information
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* regarding copyright ownership. The ASF licenses this file
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* to you under the Apache License, Version 2.0 (the
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* "License"); you may not use this file except in compliance
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* with the License. You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing,
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* software distributed under the License is distributed on an
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* "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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* KIND, either express or implied. See the License for the
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* specific language governing permissions and limitations
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* under the License.
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*/
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var _config = require("../../config");
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var __DEV__ = _config.__DEV__;
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var _model = require("../../util/model");
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var makeInner = _model.makeInner;
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var getDataItemValue = _model.getDataItemValue;
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var _util = require("zrender/lib/core/util");
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var createHashMap = _util.createHashMap;
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var each = _util.each;
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var map = _util.map;
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var isArray = _util.isArray;
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var isString = _util.isString;
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var isObject = _util.isObject;
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var isTypedArray = _util.isTypedArray;
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var isArrayLike = _util.isArrayLike;
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var extend = _util.extend;
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var assert = _util.assert;
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var Source = require("../Source");
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var _sourceType = require("./sourceType");
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var SOURCE_FORMAT_ORIGINAL = _sourceType.SOURCE_FORMAT_ORIGINAL;
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var SOURCE_FORMAT_ARRAY_ROWS = _sourceType.SOURCE_FORMAT_ARRAY_ROWS;
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var SOURCE_FORMAT_OBJECT_ROWS = _sourceType.SOURCE_FORMAT_OBJECT_ROWS;
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var SOURCE_FORMAT_KEYED_COLUMNS = _sourceType.SOURCE_FORMAT_KEYED_COLUMNS;
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var SOURCE_FORMAT_UNKNOWN = _sourceType.SOURCE_FORMAT_UNKNOWN;
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var SOURCE_FORMAT_TYPED_ARRAY = _sourceType.SOURCE_FORMAT_TYPED_ARRAY;
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var SERIES_LAYOUT_BY_ROW = _sourceType.SERIES_LAYOUT_BY_ROW;
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/*
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* Licensed to the Apache Software Foundation (ASF) under one
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* or more contributor license agreements. See the NOTICE file
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* distributed with this work for additional information
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* regarding copyright ownership. The ASF licenses this file
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* to you under the Apache License, Version 2.0 (the
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* "License"); you may not use this file except in compliance
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* with the License. You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing,
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* software distributed under the License is distributed on an
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* "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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* KIND, either express or implied. See the License for the
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* specific language governing permissions and limitations
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* under the License.
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*/
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// The result of `guessOrdinal`.
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var BE_ORDINAL = {
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Must: 1,
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// Encounter string but not '-' and not number-like.
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Might: 2,
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// Encounter string but number-like.
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Not: 3 // Other cases
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};
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var inner = makeInner();
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/**
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* @see {module:echarts/data/Source}
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* @param {module:echarts/component/dataset/DatasetModel} datasetModel
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* @return {string} sourceFormat
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*/
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function detectSourceFormat(datasetModel) {
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var data = datasetModel.option.source;
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var sourceFormat = SOURCE_FORMAT_UNKNOWN;
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if (isTypedArray(data)) {
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sourceFormat = SOURCE_FORMAT_TYPED_ARRAY;
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} else if (isArray(data)) {
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// FIXME Whether tolerate null in top level array?
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if (data.length === 0) {
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sourceFormat = SOURCE_FORMAT_ARRAY_ROWS;
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}
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for (var i = 0, len = data.length; i < len; i++) {
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var item = data[i];
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if (item == null) {
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continue;
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} else if (isArray(item)) {
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sourceFormat = SOURCE_FORMAT_ARRAY_ROWS;
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break;
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} else if (isObject(item)) {
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sourceFormat = SOURCE_FORMAT_OBJECT_ROWS;
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break;
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}
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}
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} else if (isObject(data)) {
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for (var key in data) {
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if (data.hasOwnProperty(key) && isArrayLike(data[key])) {
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sourceFormat = SOURCE_FORMAT_KEYED_COLUMNS;
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break;
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}
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}
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} else if (data != null) {
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throw new Error('Invalid data');
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}
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inner(datasetModel).sourceFormat = sourceFormat;
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}
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/**
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* [Scenarios]:
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* (1) Provide source data directly:
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* series: {
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* encode: {...},
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* dimensions: [...]
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* seriesLayoutBy: 'row',
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* data: [[...]]
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* }
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* (2) Refer to datasetModel.
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* series: [{
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* encode: {...}
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* // Ignore datasetIndex means `datasetIndex: 0`
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* // and the dimensions defination in dataset is used
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* }, {
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* encode: {...},
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* seriesLayoutBy: 'column',
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* datasetIndex: 1
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* }]
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*
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* Get data from series itself or datset.
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* @return {module:echarts/data/Source} source
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*/
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function getSource(seriesModel) {
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return inner(seriesModel).source;
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}
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/**
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* MUST be called before mergeOption of all series.
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* @param {module:echarts/model/Global} ecModel
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*/
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function resetSourceDefaulter(ecModel) {
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// `datasetMap` is used to make default encode.
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inner(ecModel).datasetMap = createHashMap();
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}
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/**
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* [Caution]:
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* MUST be called after series option merged and
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* before "series.getInitailData()" called.
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*
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* [The rule of making default encode]:
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* Category axis (if exists) alway map to the first dimension.
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* Each other axis occupies a subsequent dimension.
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*
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* [Why make default encode]:
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* Simplify the typing of encode in option, avoiding the case like that:
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* series: [{encode: {x: 0, y: 1}}, {encode: {x: 0, y: 2}}, {encode: {x: 0, y: 3}}],
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* where the "y" have to be manually typed as "1, 2, 3, ...".
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*
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* @param {module:echarts/model/Series} seriesModel
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*/
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function prepareSource(seriesModel) {
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var seriesOption = seriesModel.option;
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var data = seriesOption.data;
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var sourceFormat = isTypedArray(data) ? SOURCE_FORMAT_TYPED_ARRAY : SOURCE_FORMAT_ORIGINAL;
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var fromDataset = false;
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var seriesLayoutBy = seriesOption.seriesLayoutBy;
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var sourceHeader = seriesOption.sourceHeader;
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var dimensionsDefine = seriesOption.dimensions;
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var datasetModel = getDatasetModel(seriesModel);
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if (datasetModel) {
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var datasetOption = datasetModel.option;
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data = datasetOption.source;
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sourceFormat = inner(datasetModel).sourceFormat;
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fromDataset = true; // These settings from series has higher priority.
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seriesLayoutBy = seriesLayoutBy || datasetOption.seriesLayoutBy;
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sourceHeader == null && (sourceHeader = datasetOption.sourceHeader);
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dimensionsDefine = dimensionsDefine || datasetOption.dimensions;
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}
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var completeResult = completeBySourceData(data, sourceFormat, seriesLayoutBy, sourceHeader, dimensionsDefine);
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inner(seriesModel).source = new Source({
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data: data,
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fromDataset: fromDataset,
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seriesLayoutBy: seriesLayoutBy,
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sourceFormat: sourceFormat,
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dimensionsDefine: completeResult.dimensionsDefine,
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startIndex: completeResult.startIndex,
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dimensionsDetectCount: completeResult.dimensionsDetectCount,
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// Note: dataset option does not have `encode`.
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encodeDefine: seriesOption.encode
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});
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} // return {startIndex, dimensionsDefine, dimensionsCount}
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function completeBySourceData(data, sourceFormat, seriesLayoutBy, sourceHeader, dimensionsDefine) {
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if (!data) {
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return {
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dimensionsDefine: normalizeDimensionsDefine(dimensionsDefine)
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};
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}
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var dimensionsDetectCount;
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var startIndex;
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if (sourceFormat === SOURCE_FORMAT_ARRAY_ROWS) {
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// Rule: Most of the first line are string: it is header.
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// Caution: consider a line with 5 string and 1 number,
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// it still can not be sure it is a head, because the
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// 5 string may be 5 values of category columns.
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if (sourceHeader === 'auto' || sourceHeader == null) {
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arrayRowsTravelFirst(function (val) {
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// '-' is regarded as null/undefined.
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if (val != null && val !== '-') {
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if (isString(val)) {
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startIndex == null && (startIndex = 1);
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} else {
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startIndex = 0;
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}
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} // 10 is an experience number, avoid long loop.
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}, seriesLayoutBy, data, 10);
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} else {
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startIndex = sourceHeader ? 1 : 0;
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}
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if (!dimensionsDefine && startIndex === 1) {
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dimensionsDefine = [];
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arrayRowsTravelFirst(function (val, index) {
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dimensionsDefine[index] = val != null ? val : '';
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}, seriesLayoutBy, data);
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}
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dimensionsDetectCount = dimensionsDefine ? dimensionsDefine.length : seriesLayoutBy === SERIES_LAYOUT_BY_ROW ? data.length : data[0] ? data[0].length : null;
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} else if (sourceFormat === SOURCE_FORMAT_OBJECT_ROWS) {
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if (!dimensionsDefine) {
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dimensionsDefine = objectRowsCollectDimensions(data);
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}
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} else if (sourceFormat === SOURCE_FORMAT_KEYED_COLUMNS) {
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if (!dimensionsDefine) {
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dimensionsDefine = [];
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each(data, function (colArr, key) {
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dimensionsDefine.push(key);
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});
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}
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} else if (sourceFormat === SOURCE_FORMAT_ORIGINAL) {
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var value0 = getDataItemValue(data[0]);
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dimensionsDetectCount = isArray(value0) && value0.length || 1;
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} else if (sourceFormat === SOURCE_FORMAT_TYPED_ARRAY) {}
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return {
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startIndex: startIndex,
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dimensionsDefine: normalizeDimensionsDefine(dimensionsDefine),
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dimensionsDetectCount: dimensionsDetectCount
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};
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} // Consider dimensions defined like ['A', 'price', 'B', 'price', 'C', 'price'],
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// which is reasonable. But dimension name is duplicated.
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// Returns undefined or an array contains only object without null/undefiend or string.
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function normalizeDimensionsDefine(dimensionsDefine) {
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if (!dimensionsDefine) {
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// The meaning of null/undefined is different from empty array.
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return;
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}
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var nameMap = createHashMap();
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return map(dimensionsDefine, function (item, index) {
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item = extend({}, isObject(item) ? item : {
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name: item
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}); // User can set null in dimensions.
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// We dont auto specify name, othewise a given name may
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// cause it be refered unexpectedly.
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if (item.name == null) {
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return item;
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} // Also consider number form like 2012.
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item.name += ''; // User may also specify displayName.
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// displayName will always exists except user not
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// specified or dim name is not specified or detected.
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// (A auto generated dim name will not be used as
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// displayName).
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if (item.displayName == null) {
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item.displayName = item.name;
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}
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var exist = nameMap.get(item.name);
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if (!exist) {
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nameMap.set(item.name, {
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count: 1
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});
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} else {
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item.name += '-' + exist.count++;
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}
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return item;
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});
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}
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function arrayRowsTravelFirst(cb, seriesLayoutBy, data, maxLoop) {
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maxLoop == null && (maxLoop = Infinity);
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if (seriesLayoutBy === SERIES_LAYOUT_BY_ROW) {
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for (var i = 0; i < data.length && i < maxLoop; i++) {
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cb(data[i] ? data[i][0] : null, i);
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}
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} else {
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var value0 = data[0] || [];
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for (var i = 0; i < value0.length && i < maxLoop; i++) {
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cb(value0[i], i);
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}
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}
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}
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function objectRowsCollectDimensions(data) {
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var firstIndex = 0;
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var obj;
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while (firstIndex < data.length && !(obj = data[firstIndex++])) {} // jshint ignore: line
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if (obj) {
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var dimensions = [];
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each(obj, function (value, key) {
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dimensions.push(key);
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});
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return dimensions;
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}
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}
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/**
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* [The strategy of the arrengment of data dimensions for dataset]:
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* "value way": all axes are non-category axes. So series one by one take
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* several (the number is coordSysDims.length) dimensions from dataset.
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* The result of data arrengment of data dimensions like:
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* | ser0_x | ser0_y | ser1_x | ser1_y | ser2_x | ser2_y |
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* "category way": at least one axis is category axis. So the the first data
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* dimension is always mapped to the first category axis and shared by
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* all of the series. The other data dimensions are taken by series like
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* "value way" does.
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* The result of data arrengment of data dimensions like:
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* | ser_shared_x | ser0_y | ser1_y | ser2_y |
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*
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* @param {Array.<Object|string>} coordDimensions [{name: <string>, type: <string>, dimsDef: <Array>}, ...]
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* @param {module:model/Series} seriesModel
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|
* @param {module:data/Source} source
|
||
|
|
* @return {Object} encode Never be `null/undefined`.
|
||
|
|
*/
|
||
|
|
|
||
|
|
|
||
|
|
function makeSeriesEncodeForAxisCoordSys(coordDimensions, seriesModel, source) {
|
||
|
|
var encode = {};
|
||
|
|
var datasetModel = getDatasetModel(seriesModel); // Currently only make default when using dataset, util more reqirements occur.
|
||
|
|
|
||
|
|
if (!datasetModel || !coordDimensions) {
|
||
|
|
return encode;
|
||
|
|
}
|
||
|
|
|
||
|
|
var encodeItemName = [];
|
||
|
|
var encodeSeriesName = [];
|
||
|
|
var ecModel = seriesModel.ecModel;
|
||
|
|
var datasetMap = inner(ecModel).datasetMap;
|
||
|
|
var key = datasetModel.uid + '_' + source.seriesLayoutBy;
|
||
|
|
var baseCategoryDimIndex;
|
||
|
|
var categoryWayValueDimStart;
|
||
|
|
coordDimensions = coordDimensions.slice();
|
||
|
|
each(coordDimensions, function (coordDimInfo, coordDimIdx) {
|
||
|
|
!isObject(coordDimInfo) && (coordDimensions[coordDimIdx] = {
|
||
|
|
name: coordDimInfo
|
||
|
|
});
|
||
|
|
|
||
|
|
if (coordDimInfo.type === 'ordinal' && baseCategoryDimIndex == null) {
|
||
|
|
baseCategoryDimIndex = coordDimIdx;
|
||
|
|
categoryWayValueDimStart = getDataDimCountOnCoordDim(coordDimensions[coordDimIdx]);
|
||
|
|
}
|
||
|
|
|
||
|
|
encode[coordDimInfo.name] = [];
|
||
|
|
});
|
||
|
|
var datasetRecord = datasetMap.get(key) || datasetMap.set(key, {
|
||
|
|
categoryWayDim: categoryWayValueDimStart,
|
||
|
|
valueWayDim: 0
|
||
|
|
}); // TODO
|
||
|
|
// Auto detect first time axis and do arrangement.
|
||
|
|
|
||
|
|
each(coordDimensions, function (coordDimInfo, coordDimIdx) {
|
||
|
|
var coordDimName = coordDimInfo.name;
|
||
|
|
var count = getDataDimCountOnCoordDim(coordDimInfo); // In value way.
|
||
|
|
|
||
|
|
if (baseCategoryDimIndex == null) {
|
||
|
|
var start = datasetRecord.valueWayDim;
|
||
|
|
pushDim(encode[coordDimName], start, count);
|
||
|
|
pushDim(encodeSeriesName, start, count);
|
||
|
|
datasetRecord.valueWayDim += count; // ??? TODO give a better default series name rule?
|
||
|
|
// especially when encode x y specified.
|
||
|
|
// consider: when mutiple series share one dimension
|
||
|
|
// category axis, series name should better use
|
||
|
|
// the other dimsion name. On the other hand, use
|
||
|
|
// both dimensions name.
|
||
|
|
} // In category way, the first category axis.
|
||
|
|
else if (baseCategoryDimIndex === coordDimIdx) {
|
||
|
|
pushDim(encode[coordDimName], 0, count);
|
||
|
|
pushDim(encodeItemName, 0, count);
|
||
|
|
} // In category way, the other axis.
|
||
|
|
else {
|
||
|
|
var start = datasetRecord.categoryWayDim;
|
||
|
|
pushDim(encode[coordDimName], start, count);
|
||
|
|
pushDim(encodeSeriesName, start, count);
|
||
|
|
datasetRecord.categoryWayDim += count;
|
||
|
|
}
|
||
|
|
});
|
||
|
|
|
||
|
|
function pushDim(dimIdxArr, idxFrom, idxCount) {
|
||
|
|
for (var i = 0; i < idxCount; i++) {
|
||
|
|
dimIdxArr.push(idxFrom + i);
|
||
|
|
}
|
||
|
|
}
|
||
|
|
|
||
|
|
function getDataDimCountOnCoordDim(coordDimInfo) {
|
||
|
|
var dimsDef = coordDimInfo.dimsDef;
|
||
|
|
return dimsDef ? dimsDef.length : 1;
|
||
|
|
}
|
||
|
|
|
||
|
|
encodeItemName.length && (encode.itemName = encodeItemName);
|
||
|
|
encodeSeriesName.length && (encode.seriesName = encodeSeriesName);
|
||
|
|
return encode;
|
||
|
|
}
|
||
|
|
/**
|
||
|
|
* Work for data like [{name: ..., value: ...}, ...].
|
||
|
|
*
|
||
|
|
* @param {module:model/Series} seriesModel
|
||
|
|
* @param {module:data/Source} source
|
||
|
|
* @return {Object} encode Never be `null/undefined`.
|
||
|
|
*/
|
||
|
|
|
||
|
|
|
||
|
|
function makeSeriesEncodeForNameBased(seriesModel, source, dimCount) {
|
||
|
|
var encode = {};
|
||
|
|
var datasetModel = getDatasetModel(seriesModel); // Currently only make default when using dataset, util more reqirements occur.
|
||
|
|
|
||
|
|
if (!datasetModel) {
|
||
|
|
return encode;
|
||
|
|
}
|
||
|
|
|
||
|
|
var sourceFormat = source.sourceFormat;
|
||
|
|
var dimensionsDefine = source.dimensionsDefine;
|
||
|
|
var potentialNameDimIndex;
|
||
|
|
|
||
|
|
if (sourceFormat === SOURCE_FORMAT_OBJECT_ROWS || sourceFormat === SOURCE_FORMAT_KEYED_COLUMNS) {
|
||
|
|
each(dimensionsDefine, function (dim, idx) {
|
||
|
|
if ((isObject(dim) ? dim.name : dim) === 'name') {
|
||
|
|
potentialNameDimIndex = idx;
|
||
|
|
}
|
||
|
|
});
|
||
|
|
} // idxResult: {v, n}.
|
||
|
|
|
||
|
|
|
||
|
|
var idxResult = function () {
|
||
|
|
var idxRes0 = {};
|
||
|
|
var idxRes1 = {};
|
||
|
|
var guessRecords = []; // 5 is an experience value.
|
||
|
|
|
||
|
|
for (var i = 0, len = Math.min(5, dimCount); i < len; i++) {
|
||
|
|
var guessResult = doGuessOrdinal(source.data, sourceFormat, source.seriesLayoutBy, dimensionsDefine, source.startIndex, i);
|
||
|
|
guessRecords.push(guessResult);
|
||
|
|
var isPureNumber = guessResult === BE_ORDINAL.Not; // [Strategy of idxRes0]: find the first BE_ORDINAL.Not as the value dim,
|
||
|
|
// and then find a name dim with the priority:
|
||
|
|
// "BE_ORDINAL.Might|BE_ORDINAL.Must" > "other dim" > "the value dim itself".
|
||
|
|
|
||
|
|
if (isPureNumber && idxRes0.v == null && i !== potentialNameDimIndex) {
|
||
|
|
idxRes0.v = i;
|
||
|
|
}
|
||
|
|
|
||
|
|
if (idxRes0.n == null || idxRes0.n === idxRes0.v || !isPureNumber && guessRecords[idxRes0.n] === BE_ORDINAL.Not) {
|
||
|
|
idxRes0.n = i;
|
||
|
|
}
|
||
|
|
|
||
|
|
if (fulfilled(idxRes0) && guessRecords[idxRes0.n] !== BE_ORDINAL.Not) {
|
||
|
|
return idxRes0;
|
||
|
|
} // [Strategy of idxRes1]: if idxRes0 not satisfied (that is, no BE_ORDINAL.Not),
|
||
|
|
// find the first BE_ORDINAL.Might as the value dim,
|
||
|
|
// and then find a name dim with the priority:
|
||
|
|
// "other dim" > "the value dim itself".
|
||
|
|
// That is for backward compat: number-like (e.g., `'3'`, `'55'`) can be
|
||
|
|
// treated as number.
|
||
|
|
|
||
|
|
|
||
|
|
if (!isPureNumber) {
|
||
|
|
if (guessResult === BE_ORDINAL.Might && idxRes1.v == null && i !== potentialNameDimIndex) {
|
||
|
|
idxRes1.v = i;
|
||
|
|
}
|
||
|
|
|
||
|
|
if (idxRes1.n == null || idxRes1.n === idxRes1.v) {
|
||
|
|
idxRes1.n = i;
|
||
|
|
}
|
||
|
|
}
|
||
|
|
}
|
||
|
|
|
||
|
|
function fulfilled(idxResult) {
|
||
|
|
return idxResult.v != null && idxResult.n != null;
|
||
|
|
}
|
||
|
|
|
||
|
|
return fulfilled(idxRes0) ? idxRes0 : fulfilled(idxRes1) ? idxRes1 : null;
|
||
|
|
}();
|
||
|
|
|
||
|
|
if (idxResult) {
|
||
|
|
encode.value = idxResult.v; // `potentialNameDimIndex` has highest priority.
|
||
|
|
|
||
|
|
var nameDimIndex = potentialNameDimIndex != null ? potentialNameDimIndex : idxResult.n; // By default, label use itemName in charts.
|
||
|
|
// So we dont set encodeLabel here.
|
||
|
|
|
||
|
|
encode.itemName = [nameDimIndex];
|
||
|
|
encode.seriesName = [nameDimIndex];
|
||
|
|
}
|
||
|
|
|
||
|
|
return encode;
|
||
|
|
}
|
||
|
|
/**
|
||
|
|
* If return null/undefined, indicate that should not use datasetModel.
|
||
|
|
*/
|
||
|
|
|
||
|
|
|
||
|
|
function getDatasetModel(seriesModel) {
|
||
|
|
var option = seriesModel.option; // Caution: consider the scenario:
|
||
|
|
// A dataset is declared and a series is not expected to use the dataset,
|
||
|
|
// and at the beginning `setOption({series: { noData })` (just prepare other
|
||
|
|
// option but no data), then `setOption({series: {data: [...]}); In this case,
|
||
|
|
// the user should set an empty array to avoid that dataset is used by default.
|
||
|
|
|
||
|
|
var thisData = option.data;
|
||
|
|
|
||
|
|
if (!thisData) {
|
||
|
|
return seriesModel.ecModel.getComponent('dataset', option.datasetIndex || 0);
|
||
|
|
}
|
||
|
|
}
|
||
|
|
/**
|
||
|
|
* The rule should not be complex, otherwise user might not
|
||
|
|
* be able to known where the data is wrong.
|
||
|
|
* The code is ugly, but how to make it neat?
|
||
|
|
*
|
||
|
|
* @param {module:echars/data/Source} source
|
||
|
|
* @param {number} dimIndex
|
||
|
|
* @return {BE_ORDINAL} guess result.
|
||
|
|
*/
|
||
|
|
|
||
|
|
|
||
|
|
function guessOrdinal(source, dimIndex) {
|
||
|
|
return doGuessOrdinal(source.data, source.sourceFormat, source.seriesLayoutBy, source.dimensionsDefine, source.startIndex, dimIndex);
|
||
|
|
} // dimIndex may be overflow source data.
|
||
|
|
// return {BE_ORDINAL}
|
||
|
|
|
||
|
|
|
||
|
|
function doGuessOrdinal(data, sourceFormat, seriesLayoutBy, dimensionsDefine, startIndex, dimIndex) {
|
||
|
|
var result; // Experience value.
|
||
|
|
|
||
|
|
var maxLoop = 5;
|
||
|
|
|
||
|
|
if (isTypedArray(data)) {
|
||
|
|
return BE_ORDINAL.Not;
|
||
|
|
} // When sourceType is 'objectRows' or 'keyedColumns', dimensionsDefine
|
||
|
|
// always exists in source.
|
||
|
|
|
||
|
|
|
||
|
|
var dimName;
|
||
|
|
var dimType;
|
||
|
|
|
||
|
|
if (dimensionsDefine) {
|
||
|
|
var dimDefItem = dimensionsDefine[dimIndex];
|
||
|
|
|
||
|
|
if (isObject(dimDefItem)) {
|
||
|
|
dimName = dimDefItem.name;
|
||
|
|
dimType = dimDefItem.type;
|
||
|
|
} else if (isString(dimDefItem)) {
|
||
|
|
dimName = dimDefItem;
|
||
|
|
}
|
||
|
|
}
|
||
|
|
|
||
|
|
if (dimType != null) {
|
||
|
|
return dimType === 'ordinal' ? BE_ORDINAL.Must : BE_ORDINAL.Not;
|
||
|
|
}
|
||
|
|
|
||
|
|
if (sourceFormat === SOURCE_FORMAT_ARRAY_ROWS) {
|
||
|
|
if (seriesLayoutBy === SERIES_LAYOUT_BY_ROW) {
|
||
|
|
var sample = data[dimIndex];
|
||
|
|
|
||
|
|
for (var i = 0; i < (sample || []).length && i < maxLoop; i++) {
|
||
|
|
if ((result = detectValue(sample[startIndex + i])) != null) {
|
||
|
|
return result;
|
||
|
|
}
|
||
|
|
}
|
||
|
|
} else {
|
||
|
|
for (var i = 0; i < data.length && i < maxLoop; i++) {
|
||
|
|
var row = data[startIndex + i];
|
||
|
|
|
||
|
|
if (row && (result = detectValue(row[dimIndex])) != null) {
|
||
|
|
return result;
|
||
|
|
}
|
||
|
|
}
|
||
|
|
}
|
||
|
|
} else if (sourceFormat === SOURCE_FORMAT_OBJECT_ROWS) {
|
||
|
|
if (!dimName) {
|
||
|
|
return BE_ORDINAL.Not;
|
||
|
|
}
|
||
|
|
|
||
|
|
for (var i = 0; i < data.length && i < maxLoop; i++) {
|
||
|
|
var item = data[i];
|
||
|
|
|
||
|
|
if (item && (result = detectValue(item[dimName])) != null) {
|
||
|
|
return result;
|
||
|
|
}
|
||
|
|
}
|
||
|
|
} else if (sourceFormat === SOURCE_FORMAT_KEYED_COLUMNS) {
|
||
|
|
if (!dimName) {
|
||
|
|
return BE_ORDINAL.Not;
|
||
|
|
}
|
||
|
|
|
||
|
|
var sample = data[dimName];
|
||
|
|
|
||
|
|
if (!sample || isTypedArray(sample)) {
|
||
|
|
return BE_ORDINAL.Not;
|
||
|
|
}
|
||
|
|
|
||
|
|
for (var i = 0; i < sample.length && i < maxLoop; i++) {
|
||
|
|
if ((result = detectValue(sample[i])) != null) {
|
||
|
|
return result;
|
||
|
|
}
|
||
|
|
}
|
||
|
|
} else if (sourceFormat === SOURCE_FORMAT_ORIGINAL) {
|
||
|
|
for (var i = 0; i < data.length && i < maxLoop; i++) {
|
||
|
|
var item = data[i];
|
||
|
|
var val = getDataItemValue(item);
|
||
|
|
|
||
|
|
if (!isArray(val)) {
|
||
|
|
return BE_ORDINAL.Not;
|
||
|
|
}
|
||
|
|
|
||
|
|
if ((result = detectValue(val[dimIndex])) != null) {
|
||
|
|
return result;
|
||
|
|
}
|
||
|
|
}
|
||
|
|
}
|
||
|
|
|
||
|
|
function detectValue(val) {
|
||
|
|
var beStr = isString(val); // Consider usage convenience, '1', '2' will be treated as "number".
|
||
|
|
// `isFinit('')` get `true`.
|
||
|
|
|
||
|
|
if (val != null && isFinite(val) && val !== '') {
|
||
|
|
return beStr ? BE_ORDINAL.Might : BE_ORDINAL.Not;
|
||
|
|
} else if (beStr && val !== '-') {
|
||
|
|
return BE_ORDINAL.Must;
|
||
|
|
}
|
||
|
|
}
|
||
|
|
|
||
|
|
return BE_ORDINAL.Not;
|
||
|
|
}
|
||
|
|
|
||
|
|
exports.BE_ORDINAL = BE_ORDINAL;
|
||
|
|
exports.detectSourceFormat = detectSourceFormat;
|
||
|
|
exports.getSource = getSource;
|
||
|
|
exports.resetSourceDefaulter = resetSourceDefaulter;
|
||
|
|
exports.prepareSource = prepareSource;
|
||
|
|
exports.makeSeriesEncodeForAxisCoordSys = makeSeriesEncodeForAxisCoordSys;
|
||
|
|
exports.makeSeriesEncodeForNameBased = makeSeriesEncodeForNameBased;
|
||
|
|
exports.guessOrdinal = guessOrdinal;
|