project/node_modules/echarts/lib/data/helper/transform.js

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2024-07-14 15:48:34 +08:00
/*
* 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.
*/
/**
* AUTO-GENERATED FILE. DO NOT MODIFY.
*/
/*
* 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 { SERIES_LAYOUT_BY_COLUMN, SOURCE_FORMAT_OBJECT_ROWS, SOURCE_FORMAT_ARRAY_ROWS } from '../../util/types.js';
import { normalizeToArray } from '../../util/model.js';
import { createHashMap, bind, each, hasOwn, map, clone, isObject, extend, isNumber } from 'zrender/lib/core/util.js';
import { getRawSourceItemGetter, getRawSourceDataCounter, getRawSourceValueGetter } from './dataProvider.js';
import { parseDataValue } from './dataValueHelper.js';
import { log, makePrintable, throwError } from '../../util/log.js';
import { createSource, detectSourceFormat } from '../Source.js';
/**
* TODO: disable writable.
* This structure will be exposed to users.
*/
var ExternalSource = /** @class */function () {
function ExternalSource() {}
ExternalSource.prototype.getRawData = function () {
// Only built-in transform available.
throw new Error('not supported');
};
ExternalSource.prototype.getRawDataItem = function (dataIndex) {
// Only built-in transform available.
throw new Error('not supported');
};
ExternalSource.prototype.cloneRawData = function () {
return;
};
/**
* @return If dimension not found, return null/undefined.
*/
ExternalSource.prototype.getDimensionInfo = function (dim) {
return;
};
/**
* dimensions defined if and only if either:
* (a) dataset.dimensions are declared.
* (b) dataset data include dimensions definitions in data (detected or via specified `sourceHeader`).
* If dimensions are defined, `dimensionInfoAll` is corresponding to
* the defined dimensions.
* Otherwise, `dimensionInfoAll` is determined by data columns.
* @return Always return an array (even empty array).
*/
ExternalSource.prototype.cloneAllDimensionInfo = function () {
return;
};
ExternalSource.prototype.count = function () {
return;
};
/**
* Only support by dimension index.
* No need to support by dimension name in transform function,
* because transform function is not case-specific, no need to use name literally.
*/
ExternalSource.prototype.retrieveValue = function (dataIndex, dimIndex) {
return;
};
ExternalSource.prototype.retrieveValueFromItem = function (dataItem, dimIndex) {
return;
};
ExternalSource.prototype.convertValue = function (rawVal, dimInfo) {
return parseDataValue(rawVal, dimInfo);
};
return ExternalSource;
}();
export { ExternalSource };
function createExternalSource(internalSource, externalTransform) {
var extSource = new ExternalSource();
var data = internalSource.data;
var sourceFormat = extSource.sourceFormat = internalSource.sourceFormat;
var sourceHeaderCount = internalSource.startIndex;
var errMsg = '';
if (internalSource.seriesLayoutBy !== SERIES_LAYOUT_BY_COLUMN) {
// For the logic simplicity in transformer, only 'culumn' is
// supported in data transform. Otherwise, the `dimensionsDefine`
// might be detected by 'row', which probably confuses users.
if (process.env.NODE_ENV !== 'production') {
errMsg = '`seriesLayoutBy` of upstream dataset can only be "column" in data transform.';
}
throwError(errMsg);
}
// [MEMO]
// Create a new dimensions structure for exposing.
// Do not expose all dimension info to users directly.
// Because the dimension is probably auto detected from data and not might reliable.
// Should not lead the transformers to think that is reliable and return it.
// See [DIMENSION_INHERIT_RULE] in `sourceManager.ts`.
var dimensions = [];
var dimsByName = {};
var dimsDef = internalSource.dimensionsDefine;
if (dimsDef) {
each(dimsDef, function (dimDef, idx) {
var name = dimDef.name;
var dimDefExt = {
index: idx,
name: name,
displayName: dimDef.displayName
};
dimensions.push(dimDefExt);
// Users probably do not specify dimension name. For simplicity, data transform
// does not generate dimension name.
if (name != null) {
// Dimension name should not be duplicated.
// For simplicity, data transform forbids name duplication, do not generate
// new name like module `completeDimensions.ts` did, but just tell users.
var errMsg_1 = '';
if (hasOwn(dimsByName, name)) {
if (process.env.NODE_ENV !== 'production') {
errMsg_1 = 'dimension name "' + name + '" duplicated.';
}
throwError(errMsg_1);
}
dimsByName[name] = dimDefExt;
}
});
}
// If dimension definitions are not defined and can not be detected.
// e.g., pure data `[[11, 22], ...]`.
else {
for (var i = 0; i < internalSource.dimensionsDetectedCount || 0; i++) {
// Do not generete name or anything others. The consequence process in
// `transform` or `series` probably have there own name generation strategry.
dimensions.push({
index: i
});
}
}
// Implement public methods:
var rawItemGetter = getRawSourceItemGetter(sourceFormat, SERIES_LAYOUT_BY_COLUMN);
if (externalTransform.__isBuiltIn) {
extSource.getRawDataItem = function (dataIndex) {
return rawItemGetter(data, sourceHeaderCount, dimensions, dataIndex);
};
extSource.getRawData = bind(getRawData, null, internalSource);
}
extSource.cloneRawData = bind(cloneRawData, null, internalSource);
var rawCounter = getRawSourceDataCounter(sourceFormat, SERIES_LAYOUT_BY_COLUMN);
extSource.count = bind(rawCounter, null, data, sourceHeaderCount, dimensions);
var rawValueGetter = getRawSourceValueGetter(sourceFormat);
extSource.retrieveValue = function (dataIndex, dimIndex) {
var rawItem = rawItemGetter(data, sourceHeaderCount, dimensions, dataIndex);
return retrieveValueFromItem(rawItem, dimIndex);
};
var retrieveValueFromItem = extSource.retrieveValueFromItem = function (dataItem, dimIndex) {
if (dataItem == null) {
return;
}
var dimDef = dimensions[dimIndex];
// When `dimIndex` is `null`, `rawValueGetter` return the whole item.
if (dimDef) {
return rawValueGetter(dataItem, dimIndex, dimDef.name);
}
};
extSource.getDimensionInfo = bind(getDimensionInfo, null, dimensions, dimsByName);
extSource.cloneAllDimensionInfo = bind(cloneAllDimensionInfo, null, dimensions);
return extSource;
}
function getRawData(upstream) {
var sourceFormat = upstream.sourceFormat;
if (!isSupportedSourceFormat(sourceFormat)) {
var errMsg = '';
if (process.env.NODE_ENV !== 'production') {
errMsg = '`getRawData` is not supported in source format ' + sourceFormat;
}
throwError(errMsg);
}
return upstream.data;
}
function cloneRawData(upstream) {
var sourceFormat = upstream.sourceFormat;
var data = upstream.data;
if (!isSupportedSourceFormat(sourceFormat)) {
var errMsg = '';
if (process.env.NODE_ENV !== 'production') {
errMsg = '`cloneRawData` is not supported in source format ' + sourceFormat;
}
throwError(errMsg);
}
if (sourceFormat === SOURCE_FORMAT_ARRAY_ROWS) {
var result = [];
for (var i = 0, len = data.length; i < len; i++) {
// Not strictly clone for performance
result.push(data[i].slice());
}
return result;
} else if (sourceFormat === SOURCE_FORMAT_OBJECT_ROWS) {
var result = [];
for (var i = 0, len = data.length; i < len; i++) {
// Not strictly clone for performance
result.push(extend({}, data[i]));
}
return result;
}
}
function getDimensionInfo(dimensions, dimsByName, dim) {
if (dim == null) {
return;
}
// Keep the same logic as `List::getDimension` did.
if (isNumber(dim)
// If being a number-like string but not being defined a dimension name.
|| !isNaN(dim) && !hasOwn(dimsByName, dim)) {
return dimensions[dim];
} else if (hasOwn(dimsByName, dim)) {
return dimsByName[dim];
}
}
function cloneAllDimensionInfo(dimensions) {
return clone(dimensions);
}
var externalTransformMap = createHashMap();
export function registerExternalTransform(externalTransform) {
externalTransform = clone(externalTransform);
var type = externalTransform.type;
var errMsg = '';
if (!type) {
if (process.env.NODE_ENV !== 'production') {
errMsg = 'Must have a `type` when `registerTransform`.';
}
throwError(errMsg);
}
var typeParsed = type.split(':');
if (typeParsed.length !== 2) {
if (process.env.NODE_ENV !== 'production') {
errMsg = 'Name must include namespace like "ns:regression".';
}
throwError(errMsg);
}
// Namespace 'echarts:xxx' is official namespace, where the transforms should
// be called directly via 'xxx' rather than 'echarts:xxx'.
var isBuiltIn = false;
if (typeParsed[0] === 'echarts') {
type = typeParsed[1];
isBuiltIn = true;
}
externalTransform.__isBuiltIn = isBuiltIn;
externalTransformMap.set(type, externalTransform);
}
export function applyDataTransform(rawTransOption, sourceList, infoForPrint) {
var pipedTransOption = normalizeToArray(rawTransOption);
var pipeLen = pipedTransOption.length;
var errMsg = '';
if (!pipeLen) {
if (process.env.NODE_ENV !== 'production') {
errMsg = 'If `transform` declared, it should at least contain one transform.';
}
throwError(errMsg);
}
for (var i = 0, len = pipeLen; i < len; i++) {
var transOption = pipedTransOption[i];
sourceList = applySingleDataTransform(transOption, sourceList, infoForPrint, pipeLen === 1 ? null : i);
// piped transform only support single input, except the fist one.
// piped transform only support single output, except the last one.
if (i !== len - 1) {
sourceList.length = Math.max(sourceList.length, 1);
}
}
return sourceList;
}
function applySingleDataTransform(transOption, upSourceList, infoForPrint,
// If `pipeIndex` is null/undefined, no piped transform.
pipeIndex) {
var errMsg = '';
if (!upSourceList.length) {
if (process.env.NODE_ENV !== 'production') {
errMsg = 'Must have at least one upstream dataset.';
}
throwError(errMsg);
}
if (!isObject(transOption)) {
if (process.env.NODE_ENV !== 'production') {
errMsg = 'transform declaration must be an object rather than ' + typeof transOption + '.';
}
throwError(errMsg);
}
var transType = transOption.type;
var externalTransform = externalTransformMap.get(transType);
if (!externalTransform) {
if (process.env.NODE_ENV !== 'production') {
errMsg = 'Can not find transform on type "' + transType + '".';
}
throwError(errMsg);
}
// Prepare source
var extUpSourceList = map(upSourceList, function (upSource) {
return createExternalSource(upSource, externalTransform);
});
var resultList = normalizeToArray(externalTransform.transform({
upstream: extUpSourceList[0],
upstreamList: extUpSourceList,
config: clone(transOption.config)
}));
if (process.env.NODE_ENV !== 'production') {
if (transOption.print) {
var printStrArr = map(resultList, function (extSource) {
var pipeIndexStr = pipeIndex != null ? ' === pipe index: ' + pipeIndex : '';
return ['=== dataset index: ' + infoForPrint.datasetIndex + pipeIndexStr + ' ===', '- transform result data:', makePrintable(extSource.data), '- transform result dimensions:', makePrintable(extSource.dimensions)].join('\n');
}).join('\n');
log(printStrArr);
}
}
return map(resultList, function (result, resultIndex) {
var errMsg = '';
if (!isObject(result)) {
if (process.env.NODE_ENV !== 'production') {
errMsg = 'A transform should not return some empty results.';
}
throwError(errMsg);
}
if (!result.data) {
if (process.env.NODE_ENV !== 'production') {
errMsg = 'Transform result data should be not be null or undefined';
}
throwError(errMsg);
}
var sourceFormat = detectSourceFormat(result.data);
if (!isSupportedSourceFormat(sourceFormat)) {
if (process.env.NODE_ENV !== 'production') {
errMsg = 'Transform result data should be array rows or object rows.';
}
throwError(errMsg);
}
var resultMetaRawOption;
var firstUpSource = upSourceList[0];
/**
* Intuitively, the end users known the content of the original `dataset.source`,
* calucating the transform result in mind.
* Suppose the original `dataset.source` is:
* ```js
* [
* ['product', '2012', '2013', '2014', '2015'],
* ['AAA', 41.1, 30.4, 65.1, 53.3],
* ['BBB', 86.5, 92.1, 85.7, 83.1],
* ['CCC', 24.1, 67.2, 79.5, 86.4]
* ]
* ```
* The dimension info have to be detected from the source data.
* Some of the transformers (like filter, sort) will follow the dimension info
* of upstream, while others use new dimensions (like aggregate).
* Transformer can output a field `dimensions` to define the its own output dimensions.
* We also allow transformers to ignore the output `dimensions` field, and
* inherit the upstream dimensions definition. It can reduce the burden of handling
* dimensions in transformers.
*
* See also [DIMENSION_INHERIT_RULE] in `sourceManager.ts`.
*/
if (firstUpSource && resultIndex === 0
// If transformer returns `dimensions`, it means that the transformer has different
// dimensions definitions. We do not inherit anything from upstream.
&& !result.dimensions) {
var startIndex = firstUpSource.startIndex;
// We copy the header of upstream to the result, because:
// (1) The returned data always does not contain header line and can not be used
// as dimension-detection. In this case we can not use "detected dimensions" of
// upstream directly, because it might be detected based on different `seriesLayoutBy`.
// (2) We should support that the series read the upstream source in `seriesLayoutBy: 'row'`.
// So the original detected header should be add to the result, otherwise they can not be read.
if (startIndex) {
result.data = firstUpSource.data.slice(0, startIndex).concat(result.data);
}
resultMetaRawOption = {
seriesLayoutBy: SERIES_LAYOUT_BY_COLUMN,
sourceHeader: startIndex,
dimensions: firstUpSource.metaRawOption.dimensions
};
} else {
resultMetaRawOption = {
seriesLayoutBy: SERIES_LAYOUT_BY_COLUMN,
sourceHeader: 0,
dimensions: result.dimensions
};
}
return createSource(result.data, resultMetaRawOption, null);
});
}
function isSupportedSourceFormat(sourceFormat) {
return sourceFormat === SOURCE_FORMAT_ARRAY_ROWS || sourceFormat === SOURCE_FORMAT_OBJECT_ROWS;
}