| 1 |
- {"ast":null,"code":"import \"core-js/modules/es.array.push.js\";\n/*\n* Licensed to the Apache Software Foundation (ASF) under one\n* or more contributor license agreements. See the NOTICE file\n* distributed with this work for additional information\n* regarding copyright ownership. The ASF licenses this file\n* to you under the Apache License, Version 2.0 (the\n* \"License\"); you may not use this file except in compliance\n* with the License. You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing,\n* software distributed under the License is distributed on an\n* \"AS IS\" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY\n* KIND, either express or implied. See the License for the\n* specific language governing permissions and limitations\n* under the License.\n*/\n\n/**\n * AUTO-GENERATED FILE. DO NOT MODIFY.\n */\n\n/*\r\n* Licensed to the Apache Software Foundation (ASF) under one\r\n* or more contributor license agreements. See the NOTICE file\r\n* distributed with this work for additional information\r\n* regarding copyright ownership. The ASF licenses this file\r\n* to you under the Apache License, Version 2.0 (the\r\n* \"License\"); you may not use this file except in compliance\r\n* with the License. You may obtain a copy of the License at\r\n*\r\n* http://www.apache.org/licenses/LICENSE-2.0\r\n*\r\n* Unless required by applicable law or agreed to in writing,\r\n* software distributed under the License is distributed on an\r\n* \"AS IS\" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY\r\n* KIND, either express or implied. See the License for the\r\n* specific language governing permissions and limitations\r\n* under the License.\r\n*/\nimport { SERIES_LAYOUT_BY_COLUMN, SOURCE_FORMAT_OBJECT_ROWS, SOURCE_FORMAT_ARRAY_ROWS } from '../../util/types.js';\nimport { normalizeToArray } from '../../util/model.js';\nimport { createHashMap, bind, each, hasOwn, map, clone, isObject, extend, isNumber } from 'zrender/lib/core/util.js';\nimport { getRawSourceItemGetter, getRawSourceDataCounter, getRawSourceValueGetter } from './dataProvider.js';\nimport { parseDataValue } from './dataValueHelper.js';\nimport { log, makePrintable, throwError } from '../../util/log.js';\nimport { createSource, detectSourceFormat } from '../Source.js';\n/**\r\n * TODO: disable writable.\r\n * This structure will be exposed to users.\r\n */\nvar ExternalSource = /** @class */function () {\n function ExternalSource() {}\n ExternalSource.prototype.getRawData = function () {\n // Only built-in transform available.\n throw new Error('not supported');\n };\n ExternalSource.prototype.getRawDataItem = function (dataIndex) {\n // Only built-in transform available.\n throw new Error('not supported');\n };\n ExternalSource.prototype.cloneRawData = function () {\n return;\n };\n /**\r\n * @return If dimension not found, return null/undefined.\r\n */\n ExternalSource.prototype.getDimensionInfo = function (dim) {\n return;\n };\n /**\r\n * dimensions defined if and only if either:\r\n * (a) dataset.dimensions are declared.\r\n * (b) dataset data include dimensions definitions in data (detected or via specified `sourceHeader`).\r\n * If dimensions are defined, `dimensionInfoAll` is corresponding to\r\n * the defined dimensions.\r\n * Otherwise, `dimensionInfoAll` is determined by data columns.\r\n * @return Always return an array (even empty array).\r\n */\n ExternalSource.prototype.cloneAllDimensionInfo = function () {\n return;\n };\n ExternalSource.prototype.count = function () {\n return;\n };\n /**\r\n * Only support by dimension index.\r\n * No need to support by dimension name in transform function,\r\n * because transform function is not case-specific, no need to use name literally.\r\n */\n ExternalSource.prototype.retrieveValue = function (dataIndex, dimIndex) {\n return;\n };\n ExternalSource.prototype.retrieveValueFromItem = function (dataItem, dimIndex) {\n return;\n };\n ExternalSource.prototype.convertValue = function (rawVal, dimInfo) {\n return parseDataValue(rawVal, dimInfo);\n };\n return ExternalSource;\n}();\nexport { ExternalSource };\nfunction createExternalSource(internalSource, externalTransform) {\n var extSource = new ExternalSource();\n var data = internalSource.data;\n var sourceFormat = extSource.sourceFormat = internalSource.sourceFormat;\n var sourceHeaderCount = internalSource.startIndex;\n var errMsg = '';\n if (internalSource.seriesLayoutBy !== SERIES_LAYOUT_BY_COLUMN) {\n // For the logic simplicity in transformer, only 'culumn' is\n // supported in data transform. Otherwise, the `dimensionsDefine`\n // might be detected by 'row', which probably confuses users.\n if (process.env.NODE_ENV !== 'production') {\n errMsg = '`seriesLayoutBy` of upstream dataset can only be \"column\" in data transform.';\n }\n throwError(errMsg);\n }\n // [MEMO]\n // Create a new dimensions structure for exposing.\n // Do not expose all dimension info to users directly.\n // Because the dimension is probably auto detected from data and not might reliable.\n // Should not lead the transformers to think that is reliable and return it.\n // See [DIMENSION_INHERIT_RULE] in `sourceManager.ts`.\n var dimensions = [];\n var dimsByName = {};\n var dimsDef = internalSource.dimensionsDefine;\n if (dimsDef) {\n each(dimsDef, function (dimDef, idx) {\n var name = dimDef.name;\n var dimDefExt = {\n index: idx,\n name: name,\n displayName: dimDef.displayName\n };\n dimensions.push(dimDefExt);\n // Users probably do not specify dimension name. For simplicity, data transform\n // does not generate dimension name.\n if (name != null) {\n // Dimension name should not be duplicated.\n // For simplicity, data transform forbids name duplication, do not generate\n // new name like module `completeDimensions.ts` did, but just tell users.\n var errMsg_1 = '';\n if (hasOwn(dimsByName, name)) {\n if (process.env.NODE_ENV !== 'production') {\n errMsg_1 = 'dimension name \"' + name + '\" duplicated.';\n }\n throwError(errMsg_1);\n }\n dimsByName[name] = dimDefExt;\n }\n });\n }\n // If dimension definitions are not defined and can not be detected.\n // e.g., pure data `[[11, 22], ...]`.\n else {\n for (var i = 0; i < internalSource.dimensionsDetectedCount || 0; i++) {\n // Do not generete name or anything others. The consequence process in\n // `transform` or `series` probably have there own name generation strategry.\n dimensions.push({\n index: i\n });\n }\n }\n // Implement public methods:\n var rawItemGetter = getRawSourceItemGetter(sourceFormat, SERIES_LAYOUT_BY_COLUMN);\n if (externalTransform.__isBuiltIn) {\n extSource.getRawDataItem = function (dataIndex) {\n return rawItemGetter(data, sourceHeaderCount, dimensions, dataIndex);\n };\n extSource.getRawData = bind(getRawData, null, internalSource);\n }\n extSource.cloneRawData = bind(cloneRawData, null, internalSource);\n var rawCounter = getRawSourceDataCounter(sourceFormat, SERIES_LAYOUT_BY_COLUMN);\n extSource.count = bind(rawCounter, null, data, sourceHeaderCount, dimensions);\n var rawValueGetter = getRawSourceValueGetter(sourceFormat);\n extSource.retrieveValue = function (dataIndex, dimIndex) {\n var rawItem = rawItemGetter(data, sourceHeaderCount, dimensions, dataIndex);\n return retrieveValueFromItem(rawItem, dimIndex);\n };\n var retrieveValueFromItem = extSource.retrieveValueFromItem = function (dataItem, dimIndex) {\n if (dataItem == null) {\n return;\n }\n var dimDef = dimensions[dimIndex];\n // When `dimIndex` is `null`, `rawValueGetter` return the whole item.\n if (dimDef) {\n return rawValueGetter(dataItem, dimIndex, dimDef.name);\n }\n };\n extSource.getDimensionInfo = bind(getDimensionInfo, null, dimensions, dimsByName);\n extSource.cloneAllDimensionInfo = bind(cloneAllDimensionInfo, null, dimensions);\n return extSource;\n}\nfunction getRawData(upstream) {\n var sourceFormat = upstream.sourceFormat;\n if (!isSupportedSourceFormat(sourceFormat)) {\n var errMsg = '';\n if (process.env.NODE_ENV !== 'production') {\n errMsg = '`getRawData` is not supported in source format ' + sourceFormat;\n }\n throwError(errMsg);\n }\n return upstream.data;\n}\nfunction cloneRawData(upstream) {\n var sourceFormat = upstream.sourceFormat;\n var data = upstream.data;\n if (!isSupportedSourceFormat(sourceFormat)) {\n var errMsg = '';\n if (process.env.NODE_ENV !== 'production') {\n errMsg = '`cloneRawData` is not supported in source format ' + sourceFormat;\n }\n throwError(errMsg);\n }\n if (sourceFormat === SOURCE_FORMAT_ARRAY_ROWS) {\n var result = [];\n for (var i = 0, len = data.length; i < len; i++) {\n // Not strictly clone for performance\n result.push(data[i].slice());\n }\n return result;\n } else if (sourceFormat === SOURCE_FORMAT_OBJECT_ROWS) {\n var result = [];\n for (var i = 0, len = data.length; i < len; i++) {\n // Not strictly clone for performance\n result.push(extend({}, data[i]));\n }\n return result;\n }\n}\nfunction getDimensionInfo(dimensions, dimsByName, dim) {\n if (dim == null) {\n return;\n }\n // Keep the same logic as `List::getDimension` did.\n if (isNumber(dim)\n // If being a number-like string but not being defined a dimension name.\n || !isNaN(dim) && !hasOwn(dimsByName, dim)) {\n return dimensions[dim];\n } else if (hasOwn(dimsByName, dim)) {\n return dimsByName[dim];\n }\n}\nfunction cloneAllDimensionInfo(dimensions) {\n return clone(dimensions);\n}\nvar externalTransformMap = createHashMap();\nexport function registerExternalTransform(externalTransform) {\n externalTransform = clone(externalTransform);\n var type = externalTransform.type;\n var errMsg = '';\n if (!type) {\n if (process.env.NODE_ENV !== 'production') {\n errMsg = 'Must have a `type` when `registerTransform`.';\n }\n throwError(errMsg);\n }\n var typeParsed = type.split(':');\n if (typeParsed.length !== 2) {\n if (process.env.NODE_ENV !== 'production') {\n errMsg = 'Name must include namespace like \"ns:regression\".';\n }\n throwError(errMsg);\n }\n // Namespace 'echarts:xxx' is official namespace, where the transforms should\n // be called directly via 'xxx' rather than 'echarts:xxx'.\n var isBuiltIn = false;\n if (typeParsed[0] === 'echarts') {\n type = typeParsed[1];\n isBuiltIn = true;\n }\n externalTransform.__isBuiltIn = isBuiltIn;\n externalTransformMap.set(type, externalTransform);\n}\nexport function applyDataTransform(rawTransOption, sourceList, infoForPrint) {\n var pipedTransOption = normalizeToArray(rawTransOption);\n var pipeLen = pipedTransOption.length;\n var errMsg = '';\n if (!pipeLen) {\n if (process.env.NODE_ENV !== 'production') {\n errMsg = 'If `transform` declared, it should at least contain one transform.';\n }\n throwError(errMsg);\n }\n for (var i = 0, len = pipeLen; i < len; i++) {\n var transOption = pipedTransOption[i];\n sourceList = applySingleDataTransform(transOption, sourceList, infoForPrint, pipeLen === 1 ? null : i);\n // piped transform only support single input, except the fist one.\n // piped transform only support single output, except the last one.\n if (i !== len - 1) {\n sourceList.length = Math.max(sourceList.length, 1);\n }\n }\n return sourceList;\n}\nfunction applySingleDataTransform(transOption, upSourceList, infoForPrint,\n// If `pipeIndex` is null/undefined, no piped transform.\npipeIndex) {\n var errMsg = '';\n if (!upSourceList.length) {\n if (process.env.NODE_ENV !== 'production') {\n errMsg = 'Must have at least one upstream dataset.';\n }\n throwError(errMsg);\n }\n if (!isObject(transOption)) {\n if (process.env.NODE_ENV !== 'production') {\n errMsg = 'transform declaration must be an object rather than ' + typeof transOption + '.';\n }\n throwError(errMsg);\n }\n var transType = transOption.type;\n var externalTransform = externalTransformMap.get(transType);\n if (!externalTransform) {\n if (process.env.NODE_ENV !== 'production') {\n errMsg = 'Can not find transform on type \"' + transType + '\".';\n }\n throwError(errMsg);\n }\n // Prepare source\n var extUpSourceList = map(upSourceList, function (upSource) {\n return createExternalSource(upSource, externalTransform);\n });\n var resultList = normalizeToArray(externalTransform.transform({\n upstream: extUpSourceList[0],\n upstreamList: extUpSourceList,\n config: clone(transOption.config)\n }));\n if (process.env.NODE_ENV !== 'production') {\n if (transOption.print) {\n var printStrArr = map(resultList, function (extSource) {\n var pipeIndexStr = pipeIndex != null ? ' === pipe index: ' + pipeIndex : '';\n return ['=== dataset index: ' + infoForPrint.datasetIndex + pipeIndexStr + ' ===', '- transform result data:', makePrintable(extSource.data), '- transform result dimensions:', makePrintable(extSource.dimensions)].join('\\n');\n }).join('\\n');\n log(printStrArr);\n }\n }\n return map(resultList, function (result, resultIndex) {\n var errMsg = '';\n if (!isObject(result)) {\n if (process.env.NODE_ENV !== 'production') {\n errMsg = 'A transform should not return some empty results.';\n }\n throwError(errMsg);\n }\n if (!result.data) {\n if (process.env.NODE_ENV !== 'production') {\n errMsg = 'Transform result data should be not be null or undefined';\n }\n throwError(errMsg);\n }\n var sourceFormat = detectSourceFormat(result.data);\n if (!isSupportedSourceFormat(sourceFormat)) {\n if (process.env.NODE_ENV !== 'production') {\n errMsg = 'Transform result data should be array rows or object rows.';\n }\n throwError(errMsg);\n }\n var resultMetaRawOption;\n var firstUpSource = upSourceList[0];\n /**\r\n * Intuitively, the end users known the content of the original `dataset.source`,\r\n * calucating the transform result in mind.\r\n * Suppose the original `dataset.source` is:\r\n * ```js\r\n * [\r\n * ['product', '2012', '2013', '2014', '2015'],\r\n * ['AAA', 41.1, 30.4, 65.1, 53.3],\r\n * ['BBB', 86.5, 92.1, 85.7, 83.1],\r\n * ['CCC', 24.1, 67.2, 79.5, 86.4]\r\n * ]\r\n * ```\r\n * The dimension info have to be detected from the source data.\r\n * Some of the transformers (like filter, sort) will follow the dimension info\r\n * of upstream, while others use new dimensions (like aggregate).\r\n * Transformer can output a field `dimensions` to define the its own output dimensions.\r\n * We also allow transformers to ignore the output `dimensions` field, and\r\n * inherit the upstream dimensions definition. It can reduce the burden of handling\r\n * dimensions in transformers.\r\n *\r\n * See also [DIMENSION_INHERIT_RULE] in `sourceManager.ts`.\r\n */\n if (firstUpSource && resultIndex === 0\n // If transformer returns `dimensions`, it means that the transformer has different\n // dimensions definitions. We do not inherit anything from upstream.\n && !result.dimensions) {\n var startIndex = firstUpSource.startIndex;\n // We copy the header of upstream to the result, because:\n // (1) The returned data always does not contain header line and can not be used\n // as dimension-detection. In this case we can not use \"detected dimensions\" of\n // upstream directly, because it might be detected based on different `seriesLayoutBy`.\n // (2) We should support that the series read the upstream source in `seriesLayoutBy: 'row'`.\n // So the original detected header should be add to the result, otherwise they can not be read.\n if (startIndex) {\n result.data = firstUpSource.data.slice(0, startIndex).concat(result.data);\n }\n resultMetaRawOption = {\n seriesLayoutBy: SERIES_LAYOUT_BY_COLUMN,\n sourceHeader: startIndex,\n dimensions: firstUpSource.metaRawOption.dimensions\n };\n } else {\n resultMetaRawOption = {\n seriesLayoutBy: SERIES_LAYOUT_BY_COLUMN,\n sourceHeader: 0,\n dimensions: result.dimensions\n };\n }\n return createSource(result.data, resultMetaRawOption, null);\n });\n}\nfunction isSupportedSourceFormat(sourceFormat) {\n return sourceFormat === SOURCE_FORMAT_ARRAY_ROWS || sourceFormat === SOURCE_FORMAT_OBJECT_ROWS;\n}","map":{"version":3,"names":["SERIES_LAYOUT_BY_COLUMN","SOURCE_FORMAT_OBJECT_ROWS","SOURCE_FORMAT_ARRAY_ROWS","normalizeToArray","createHashMap","bind","each","hasOwn","map","clone","isObject","extend","isNumber","getRawSourceItemGetter","getRawSourceDataCounter","getRawSourceValueGetter","parseDataValue","log","makePrintable","throwError","createSource","detectSourceFormat","ExternalSource","prototype","getRawData","Error","getRawDataItem","dataIndex","cloneRawData","getDimensionInfo","dim","cloneAllDimensionInfo","count","retrieveValue","dimIndex","retrieveValueFromItem","dataItem","convertValue","rawVal","dimInfo","createExternalSource","internalSource","externalTransform","extSource","data","sourceFormat","sourceHeaderCount","startIndex","errMsg","seriesLayoutBy","process","env","NODE_ENV","dimensions","dimsByName","dimsDef","dimensionsDefine","dimDef","idx","name","dimDefExt","index","displayName","push","errMsg_1","i","dimensionsDetectedCount","rawItemGetter","__isBuiltIn","rawCounter","rawValueGetter","rawItem","upstream","isSupportedSourceFormat","result","len","length","slice","isNaN","externalTransformMap","registerExternalTransform","type","typeParsed","split","isBuiltIn","set","applyDataTransform","rawTransOption","sourceList","infoForPrint","pipedTransOption","pipeLen","transOption","applySingleDataTransform","Math","max","upSourceList","pipeIndex","transType","get","extUpSourceList","upSource","resultList","transform","upstreamList","config","print","printStrArr","pipeIndexStr","datasetIndex","join","resultIndex","resultMetaRawOption","firstUpSource","concat","sourceHeader","metaRawOption"],"sources":["E:/git/2021项目/安科院大屏/node_modules/echarts/lib/data/helper/transform.js"],"sourcesContent":["\n/*\n* Licensed to the Apache Software Foundation (ASF) under one\n* or more contributor license agreements. See the NOTICE file\n* distributed with this work for additional information\n* regarding copyright ownership. The ASF licenses this file\n* to you under the Apache License, Version 2.0 (the\n* \"License\"); you may not use this file except in compliance\n* with the License. You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing,\n* software distributed under the License is distributed on an\n* \"AS IS\" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY\n* KIND, either express or implied. See the License for the\n* specific language governing permissions and limitations\n* under the License.\n*/\n\n\n/**\n * AUTO-GENERATED FILE. DO NOT MODIFY.\n */\n\n/*\r\n* Licensed to the Apache Software Foundation (ASF) under one\r\n* or more contributor license agreements. See the NOTICE file\r\n* distributed with this work for additional information\r\n* regarding copyright ownership. The ASF licenses this file\r\n* to you under the Apache License, Version 2.0 (the\r\n* \"License\"); you may not use this file except in compliance\r\n* with the License. You may obtain a copy of the License at\r\n*\r\n* http://www.apache.org/licenses/LICENSE-2.0\r\n*\r\n* Unless required by applicable law or agreed to in writing,\r\n* software distributed under the License is distributed on an\r\n* \"AS IS\" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY\r\n* KIND, either express or implied. See the License for the\r\n* specific language governing permissions and limitations\r\n* under the License.\r\n*/\nimport { SERIES_LAYOUT_BY_COLUMN, SOURCE_FORMAT_OBJECT_ROWS, SOURCE_FORMAT_ARRAY_ROWS } from '../../util/types.js';\nimport { normalizeToArray } from '../../util/model.js';\nimport { createHashMap, bind, each, hasOwn, map, clone, isObject, extend, isNumber } from 'zrender/lib/core/util.js';\nimport { getRawSourceItemGetter, getRawSourceDataCounter, getRawSourceValueGetter } from './dataProvider.js';\nimport { parseDataValue } from './dataValueHelper.js';\nimport { log, makePrintable, throwError } from '../../util/log.js';\nimport { createSource, detectSourceFormat } from '../Source.js';\n/**\r\n * TODO: disable writable.\r\n * This structure will be exposed to users.\r\n */\nvar ExternalSource = /** @class */function () {\n function ExternalSource() {}\n ExternalSource.prototype.getRawData = function () {\n // Only built-in transform available.\n throw new Error('not supported');\n };\n ExternalSource.prototype.getRawDataItem = function (dataIndex) {\n // Only built-in transform available.\n throw new Error('not supported');\n };\n ExternalSource.prototype.cloneRawData = function () {\n return;\n };\n /**\r\n * @return If dimension not found, return null/undefined.\r\n */\n ExternalSource.prototype.getDimensionInfo = function (dim) {\n return;\n };\n /**\r\n * dimensions defined if and only if either:\r\n * (a) dataset.dimensions are declared.\r\n * (b) dataset data include dimensions definitions in data (detected or via specified `sourceHeader`).\r\n * If dimensions are defined, `dimensionInfoAll` is corresponding to\r\n * the defined dimensions.\r\n * Otherwise, `dimensionInfoAll` is determined by data columns.\r\n * @return Always return an array (even empty array).\r\n */\n ExternalSource.prototype.cloneAllDimensionInfo = function () {\n return;\n };\n ExternalSource.prototype.count = function () {\n return;\n };\n /**\r\n * Only support by dimension index.\r\n * No need to support by dimension name in transform function,\r\n * because transform function is not case-specific, no need to use name literally.\r\n */\n ExternalSource.prototype.retrieveValue = function (dataIndex, dimIndex) {\n return;\n };\n ExternalSource.prototype.retrieveValueFromItem = function (dataItem, dimIndex) {\n return;\n };\n ExternalSource.prototype.convertValue = function (rawVal, dimInfo) {\n return parseDataValue(rawVal, dimInfo);\n };\n return ExternalSource;\n}();\nexport { ExternalSource };\nfunction createExternalSource(internalSource, externalTransform) {\n var extSource = new ExternalSource();\n var data = internalSource.data;\n var sourceFormat = extSource.sourceFormat = internalSource.sourceFormat;\n var sourceHeaderCount = internalSource.startIndex;\n var errMsg = '';\n if (internalSource.seriesLayoutBy !== SERIES_LAYOUT_BY_COLUMN) {\n // For the logic simplicity in transformer, only 'culumn' is\n // supported in data transform. Otherwise, the `dimensionsDefine`\n // might be detected by 'row', which probably confuses users.\n if (process.env.NODE_ENV !== 'production') {\n errMsg = '`seriesLayoutBy` of upstream dataset can only be \"column\" in data transform.';\n }\n throwError(errMsg);\n }\n // [MEMO]\n // Create a new dimensions structure for exposing.\n // Do not expose all dimension info to users directly.\n // Because the dimension is probably auto detected from data and not might reliable.\n // Should not lead the transformers to think that is reliable and return it.\n // See [DIMENSION_INHERIT_RULE] in `sourceManager.ts`.\n var dimensions = [];\n var dimsByName = {};\n var dimsDef = internalSource.dimensionsDefine;\n if (dimsDef) {\n each(dimsDef, function (dimDef, idx) {\n var name = dimDef.name;\n var dimDefExt = {\n index: idx,\n name: name,\n displayName: dimDef.displayName\n };\n dimensions.push(dimDefExt);\n // Users probably do not specify dimension name. For simplicity, data transform\n // does not generate dimension name.\n if (name != null) {\n // Dimension name should not be duplicated.\n // For simplicity, data transform forbids name duplication, do not generate\n // new name like module `completeDimensions.ts` did, but just tell users.\n var errMsg_1 = '';\n if (hasOwn(dimsByName, name)) {\n if (process.env.NODE_ENV !== 'production') {\n errMsg_1 = 'dimension name \"' + name + '\" duplicated.';\n }\n throwError(errMsg_1);\n }\n dimsByName[name] = dimDefExt;\n }\n });\n }\n // If dimension definitions are not defined and can not be detected.\n // e.g., pure data `[[11, 22], ...]`.\n else {\n for (var i = 0; i < internalSource.dimensionsDetectedCount || 0; i++) {\n // Do not generete name or anything others. The consequence process in\n // `transform` or `series` probably have there own name generation strategry.\n dimensions.push({\n index: i\n });\n }\n }\n // Implement public methods:\n var rawItemGetter = getRawSourceItemGetter(sourceFormat, SERIES_LAYOUT_BY_COLUMN);\n if (externalTransform.__isBuiltIn) {\n extSource.getRawDataItem = function (dataIndex) {\n return rawItemGetter(data, sourceHeaderCount, dimensions, dataIndex);\n };\n extSource.getRawData = bind(getRawData, null, internalSource);\n }\n extSource.cloneRawData = bind(cloneRawData, null, internalSource);\n var rawCounter = getRawSourceDataCounter(sourceFormat, SERIES_LAYOUT_BY_COLUMN);\n extSource.count = bind(rawCounter, null, data, sourceHeaderCount, dimensions);\n var rawValueGetter = getRawSourceValueGetter(sourceFormat);\n extSource.retrieveValue = function (dataIndex, dimIndex) {\n var rawItem = rawItemGetter(data, sourceHeaderCount, dimensions, dataIndex);\n return retrieveValueFromItem(rawItem, dimIndex);\n };\n var retrieveValueFromItem = extSource.retrieveValueFromItem = function (dataItem, dimIndex) {\n if (dataItem == null) {\n return;\n }\n var dimDef = dimensions[dimIndex];\n // When `dimIndex` is `null`, `rawValueGetter` return the whole item.\n if (dimDef) {\n return rawValueGetter(dataItem, dimIndex, dimDef.name);\n }\n };\n extSource.getDimensionInfo = bind(getDimensionInfo, null, dimensions, dimsByName);\n extSource.cloneAllDimensionInfo = bind(cloneAllDimensionInfo, null, dimensions);\n return extSource;\n}\nfunction getRawData(upstream) {\n var sourceFormat = upstream.sourceFormat;\n if (!isSupportedSourceFormat(sourceFormat)) {\n var errMsg = '';\n if (process.env.NODE_ENV !== 'production') {\n errMsg = '`getRawData` is not supported in source format ' + sourceFormat;\n }\n throwError(errMsg);\n }\n return upstream.data;\n}\nfunction cloneRawData(upstream) {\n var sourceFormat = upstream.sourceFormat;\n var data = upstream.data;\n if (!isSupportedSourceFormat(sourceFormat)) {\n var errMsg = '';\n if (process.env.NODE_ENV !== 'production') {\n errMsg = '`cloneRawData` is not supported in source format ' + sourceFormat;\n }\n throwError(errMsg);\n }\n if (sourceFormat === SOURCE_FORMAT_ARRAY_ROWS) {\n var result = [];\n for (var i = 0, len = data.length; i < len; i++) {\n // Not strictly clone for performance\n result.push(data[i].slice());\n }\n return result;\n } else if (sourceFormat === SOURCE_FORMAT_OBJECT_ROWS) {\n var result = [];\n for (var i = 0, len = data.length; i < len; i++) {\n // Not strictly clone for performance\n result.push(extend({}, data[i]));\n }\n return result;\n }\n}\nfunction getDimensionInfo(dimensions, dimsByName, dim) {\n if (dim == null) {\n return;\n }\n // Keep the same logic as `List::getDimension` did.\n if (isNumber(dim)\n // If being a number-like string but not being defined a dimension name.\n || !isNaN(dim) && !hasOwn(dimsByName, dim)) {\n return dimensions[dim];\n } else if (hasOwn(dimsByName, dim)) {\n return dimsByName[dim];\n }\n}\nfunction cloneAllDimensionInfo(dimensions) {\n return clone(dimensions);\n}\nvar externalTransformMap = createHashMap();\nexport function registerExternalTransform(externalTransform) {\n externalTransform = clone(externalTransform);\n var type = externalTransform.type;\n var errMsg = '';\n if (!type) {\n if (process.env.NODE_ENV !== 'production') {\n errMsg = 'Must have a `type` when `registerTransform`.';\n }\n throwError(errMsg);\n }\n var typeParsed = type.split(':');\n if (typeParsed.length !== 2) {\n if (process.env.NODE_ENV !== 'production') {\n errMsg = 'Name must include namespace like \"ns:regression\".';\n }\n throwError(errMsg);\n }\n // Namespace 'echarts:xxx' is official namespace, where the transforms should\n // be called directly via 'xxx' rather than 'echarts:xxx'.\n var isBuiltIn = false;\n if (typeParsed[0] === 'echarts') {\n type = typeParsed[1];\n isBuiltIn = true;\n }\n externalTransform.__isBuiltIn = isBuiltIn;\n externalTransformMap.set(type, externalTransform);\n}\nexport function applyDataTransform(rawTransOption, sourceList, infoForPrint) {\n var pipedTransOption = normalizeToArray(rawTransOption);\n var pipeLen = pipedTransOption.length;\n var errMsg = '';\n if (!pipeLen) {\n if (process.env.NODE_ENV !== 'production') {\n errMsg = 'If `transform` declared, it should at least contain one transform.';\n }\n throwError(errMsg);\n }\n for (var i = 0, len = pipeLen; i < len; i++) {\n var transOption = pipedTransOption[i];\n sourceList = applySingleDataTransform(transOption, sourceList, infoForPrint, pipeLen === 1 ? 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' === pipe index: ' + pipeIndex : '';\n return ['=== dataset index: ' + infoForPrint.datasetIndex + pipeIndexStr + ' ===', '- transform result data:', makePrintable(extSource.data), '- transform result dimensions:', makePrintable(extSource.dimensions)].join('\\n');\n }).join('\\n');\n log(printStrArr);\n }\n }\n return map(resultList, function (result, resultIndex) {\n var errMsg = '';\n if (!isObject(result)) {\n if (process.env.NODE_ENV !== 'production') {\n errMsg = 'A transform should not return some empty results.';\n }\n throwError(errMsg);\n }\n if (!result.data) {\n if (process.env.NODE_ENV !== 'production') {\n errMsg = 'Transform result data should be not be null or undefined';\n }\n throwError(errMsg);\n }\n var sourceFormat = detectSourceFormat(result.data);\n if (!isSupportedSourceFormat(sourceFormat)) {\n if (process.env.NODE_ENV !== 'production') {\n errMsg = 'Transform result data should be array rows or object rows.';\n }\n throwError(errMsg);\n }\n var resultMetaRawOption;\n var firstUpSource = upSourceList[0];\n /**\r\n * Intuitively, the end users known the content of the original `dataset.source`,\r\n * calucating the transform result in mind.\r\n * Suppose the original `dataset.source` is:\r\n * ```js\r\n * [\r\n * ['product', '2012', '2013', '2014', '2015'],\r\n * ['AAA', 41.1, 30.4, 65.1, 53.3],\r\n * ['BBB', 86.5, 92.1, 85.7, 83.1],\r\n * ['CCC', 24.1, 67.2, 79.5, 86.4]\r\n * ]\r\n * ```\r\n * The dimension info have to be detected from the source data.\r\n * Some of the transformers (like filter, sort) will follow the dimension info\r\n * of upstream, while others use new dimensions (like aggregate).\r\n * Transformer can output a field `dimensions` to define the its own output dimensions.\r\n * We also allow transformers to ignore the output `dimensions` field, and\r\n * inherit the upstream dimensions definition. It can reduce the burden of handling\r\n * dimensions in transformers.\r\n *\r\n * See also [DIMENSION_INHERIT_RULE] in `sourceManager.ts`.\r\n */\n if (firstUpSource && resultIndex === 0\n // If transformer returns `dimensions`, it means that the transformer has different\n // dimensions definitions. We do not inherit anything from upstream.\n && !result.dimensions) {\n var startIndex = firstUpSource.startIndex;\n // We copy the header of upstream to the result, because:\n // (1) The returned data always does not contain header line and can not be used\n // as dimension-detection. 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