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/*
* Licensed to the Apache Software Foundation (ASF) under one
* or more contributor license agreements. See the NOTICE file
* distributed with this work for additional information
* regarding copyright ownership. The ASF licenses this file
* to you under the Apache License, Version 2.0 (the
* "License"); you may not use this file except in compliance
* with the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing,
* software distributed under the License is distributed on an
* "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
* KIND, either express or implied. See the License for the
* specific language governing permissions and limitations
* under the License.
*/
import {makeInner, getDataItemValue, queryReferringComponents, SINGLE_REFERRING} from '../../util/model';
import {
createHashMap,
each,
isArray,
isString,
isObject,
isTypedArray,
HashMap
} from 'zrender/src/core/util';
import { Source } from '../Source';
import {
SOURCE_FORMAT_ORIGINAL,
SOURCE_FORMAT_ARRAY_ROWS,
SOURCE_FORMAT_OBJECT_ROWS,
SERIES_LAYOUT_BY_ROW,
SOURCE_FORMAT_KEYED_COLUMNS,
DimensionName,
OptionSourceDataArrayRows,
OptionDataValue,
OptionSourceDataKeyedColumns,
OptionSourceDataOriginal,
OptionSourceDataObjectRows,
OptionEncode,
DimensionIndex,
SeriesEncodableModel
} from '../../util/types';
import { DatasetModel } from '../../component/dataset/install';
import SeriesModel from '../../model/Series';
import GlobalModel from '../../model/Global';
import { CoordDimensionDefinition } from './createDimensions';
// The result of `guessOrdinal`.
export const BE_ORDINAL = {
Must: 1, // Encounter string but not '-' and not number-like.
Might: 2, // Encounter string but number-like.
Not: 3 // Other cases
};
type BeOrdinalValue = (typeof BE_ORDINAL)[keyof typeof BE_ORDINAL];
const innerGlobalModel = makeInner<{
datasetMap: HashMap<DatasetRecord, string>
}, GlobalModel>();
interface DatasetRecord {
categoryWayDim: number;
valueWayDim: number;
}
type SeriesEncodeInternal = {
[key in keyof OptionEncode]: DimensionIndex[];
};
/**
* MUST be called before mergeOption of all series.
*/
export function resetSourceDefaulter(ecModel: GlobalModel): void {
// `datasetMap` is used to make default encode.
innerGlobalModel(ecModel).datasetMap = createHashMap();
}
/**
* [The strategy of the arrengment of data dimensions for dataset]:
* "value way": all axes are non-category axes. So series one by one take
* several (the number is coordSysDims.length) dimensions from dataset.
* The result of data arrengment of data dimensions like:
* | ser0_x | ser0_y | ser1_x | ser1_y | ser2_x | ser2_y |
* "category way": at least one axis is category axis. So the the first data
* dimension is always mapped to the first category axis and shared by
* all of the series. The other data dimensions are taken by series like
* "value way" does.
* The result of data arrengment of data dimensions like:
* | ser_shared_x | ser0_y | ser1_y | ser2_y |
*
* @return encode Never be `null/undefined`.
*/
export function makeSeriesEncodeForAxisCoordSys(
coordDimensions: (DimensionName | CoordDimensionDefinition)[],
seriesModel: SeriesModel,
source: Source
): SeriesEncodeInternal {
const encode: SeriesEncodeInternal = {};
const datasetModel = querySeriesUpstreamDatasetModel(seriesModel);
// Currently only make default when using dataset, util more reqirements occur.
if (!datasetModel || !coordDimensions) {
return encode;
}
const encodeItemName: DimensionIndex[] = [];
const encodeSeriesName: DimensionIndex[] = [];
const ecModel = seriesModel.ecModel;
const datasetMap = innerGlobalModel(ecModel).datasetMap;
const key = datasetModel.uid + '_' + source.seriesLayoutBy;
let baseCategoryDimIndex: number;
let categoryWayValueDimStart;
coordDimensions = coordDimensions.slice();
each(coordDimensions, function (coordDimInfoLoose, coordDimIdx) {
const coordDimInfo: CoordDimensionDefinition = isObject(coordDimInfoLoose)
? coordDimInfoLoose
: (coordDimensions[coordDimIdx] = { name: coordDimInfoLoose as DimensionName });
if (coordDimInfo.type === 'ordinal' && baseCategoryDimIndex == null) {
baseCategoryDimIndex = coordDimIdx;
categoryWayValueDimStart = getDataDimCountOnCoordDim(coordDimInfo);
}
encode[coordDimInfo.name] = [];
});
const datasetRecord = datasetMap.get(key)
|| datasetMap.set(key, {categoryWayDim: categoryWayValueDimStart, valueWayDim: 0});
// TODO
// Auto detect first time axis and do arrangement.
each(coordDimensions, function (coordDimInfo: CoordDimensionDefinition, coordDimIdx) {
const coordDimName = coordDimInfo.name;
const count = getDataDimCountOnCoordDim(coordDimInfo);
// In value way.
if (baseCategoryDimIndex == null) {
const 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 multiple series share one dimension
// category axis, series name should better use
// the other dimension 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 {
const start = datasetRecord.categoryWayDim;
pushDim(encode[coordDimName], start, count);
pushDim(encodeSeriesName, start, count);
datasetRecord.categoryWayDim += count;
}
});
function pushDim(dimIdxArr: DimensionIndex[], idxFrom: number, idxCount: number) {
for (let i = 0; i < idxCount; i++) {
dimIdxArr.push(idxFrom + i);
}
}
function getDataDimCountOnCoordDim(coordDimInfo: CoordDimensionDefinition) {
const 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: ...}, ...].
*
* @return encode Never be `null/undefined`.
*/
export function makeSeriesEncodeForNameBased(
seriesModel: SeriesModel,
source: Source,
dimCount: number
): SeriesEncodeInternal {
const encode: SeriesEncodeInternal = {};
const datasetModel = querySeriesUpstreamDatasetModel(seriesModel);
// Currently only make default when using dataset, util more reqirements occur.
if (!datasetModel) {
return encode;
}
const sourceFormat = source.sourceFormat;
const dimensionsDefine = source.dimensionsDefine;
let 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;
}
});
}
type IdxResult = { v: number, n: number };
const idxResult = (function () {
const idxRes0 = {} as IdxResult;
const idxRes1 = {} as IdxResult;
const guessRecords = [];
// 5 is an experience value.
for (let i = 0, len = Math.min(5, dimCount); i < len; i++) {
const guessResult = doGuessOrdinal(
source.data, sourceFormat, source.seriesLayoutBy,
dimensionsDefine, source.startIndex, i
);
guessRecords.push(guessResult);
const 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: 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.
const nameDimIndex = potentialNameDimIndex != null ? potentialNameDimIndex : idxResult.n;
// By default, label uses itemName in charts.
// So we don't set encodeLabel here.
encode.itemName = [nameDimIndex];
encode.seriesName = [nameDimIndex];
}
return encode;
}
/**
* @return If return null/undefined, indicate that should not use datasetModel.
*/
export function querySeriesUpstreamDatasetModel(
seriesModel: SeriesEncodableModel
): DatasetModel {
// 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.
const thisData = seriesModel.get('data', true);
if (!thisData) {
return queryReferringComponents(
seriesModel.ecModel,
'dataset',
{
index: seriesModel.get('datasetIndex', true),
id: seriesModel.get('datasetId', true)
},
SINGLE_REFERRING
).models[0] as DatasetModel;
}
}
/**
* @return Always return an array event empty.
*/
export function queryDatasetUpstreamDatasetModels(
datasetModel: DatasetModel
): DatasetModel[] {
// Only these attributes declared, we by default reference to `datasetIndex: 0`.
// Otherwise, no reference.
if (!datasetModel.get('transform', true)
&& !datasetModel.get('fromTransformResult', true)
) {
return [];
}
return queryReferringComponents(
datasetModel.ecModel,
'dataset',
{
index: datasetModel.get('fromDatasetIndex', true),
id: datasetModel.get('fromDatasetId', true)
},
SINGLE_REFERRING
).models as DatasetModel[];
}
/**
* 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?
*/
export function guessOrdinal(source: Source, dimIndex: DimensionIndex): BeOrdinalValue {
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: Source['data'],
sourceFormat: Source['sourceFormat'],
seriesLayoutBy: Source['seriesLayoutBy'],
dimensionsDefine: Source['dimensionsDefine'],
startIndex: Source['startIndex'],
dimIndex: DimensionIndex
): BeOrdinalValue {
let result;
// Experience value.
const maxLoop = 5;
if (isTypedArray(data)) {
return BE_ORDINAL.Not;
}
// When sourceType is 'objectRows' or 'keyedColumns', dimensionsDefine
// always exists in source.
let dimName;
let dimType;
if (dimensionsDefine) {
const 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) {
const dataArrayRows = data as OptionSourceDataArrayRows;
if (seriesLayoutBy === SERIES_LAYOUT_BY_ROW) {
const sample = dataArrayRows[dimIndex];
for (let i = 0; i < (sample || []).length && i < maxLoop; i++) {
if ((result = detectValue(sample[startIndex + i])) != null) {
return result;
}
}
}
else {
for (let i = 0; i < dataArrayRows.length && i < maxLoop; i++) {
const row = dataArrayRows[startIndex + i];
if (row && (result = detectValue(row[dimIndex])) != null) {
return result;
}
}
}
}
else if (sourceFormat === SOURCE_FORMAT_OBJECT_ROWS) {
const dataObjectRows = data as OptionSourceDataObjectRows;
if (!dimName) {
return BE_ORDINAL.Not;
}
for (let i = 0; i < dataObjectRows.length && i < maxLoop; i++) {
const item = dataObjectRows[i];
if (item && (result = detectValue(item[dimName])) != null) {
return result;
}
}
}
else if (sourceFormat === SOURCE_FORMAT_KEYED_COLUMNS) {
const dataKeyedColumns = data as OptionSourceDataKeyedColumns;
if (!dimName) {
return BE_ORDINAL.Not;
}
const sample = dataKeyedColumns[dimName];
if (!sample || isTypedArray(sample)) {
return BE_ORDINAL.Not;
}
for (let i = 0; i < sample.length && i < maxLoop; i++) {
if ((result = detectValue(sample[i])) != null) {
return result;
}
}
}
else if (sourceFormat === SOURCE_FORMAT_ORIGINAL) {
const dataOriginal = data as OptionSourceDataOriginal;
for (let i = 0; i < dataOriginal.length && i < maxLoop; i++) {
const item = dataOriginal[i];
const val = getDataItemValue(item);
if (!isArray(val)) {
return BE_ORDINAL.Not;
}
if ((result = detectValue(val[dimIndex])) != null) {
return result;
}
}
}
function detectValue(val: OptionDataValue): BeOrdinalValue {
const beStr = isString(val);
// Consider usage convenience, '1', '2' will be treated as "number".
// `isFinit('')` get `true`.
if (val != null && isFinite(val as number) && val !== '') {
return beStr ? BE_ORDINAL.Might : BE_ORDINAL.Not;
}
else if (beStr && val !== '-') {
return BE_ORDINAL.Must;
}
}
return BE_ORDINAL.Not;
}