Spaces:
Running
Running
File size: 16,208 Bytes
4bb817b |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450 451 452 453 454 455 456 457 458 459 460 461 462 463 |
/*
* 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;
}
|