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27 KiB
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1 line
27 KiB
JSON
{"ast":null,"code":"/*\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/*\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*/\nimport { assert, isArray, eqNaN, isFunction } from 'zrender/lib/core/util.js';\nimport { parsePercent } from 'zrender/lib/contain/text.js';\n\nvar ScaleRawExtentInfo =\n/** @class */\nfunction () {\n function ScaleRawExtentInfo(scale, model, // Usually: data extent from all series on this axis.\n originalExtent) {\n this._prepareParams(scale, model, originalExtent);\n }\n /**\n * Parameters depending on outside (like model, user callback)\n * are prepared and fixed here.\n */\n\n\n ScaleRawExtentInfo.prototype._prepareParams = function (scale, model, // Usually: data extent from all series on this axis.\n dataExtent) {\n if (dataExtent[1] < dataExtent[0]) {\n dataExtent = [NaN, NaN];\n }\n\n this._dataMin = dataExtent[0];\n this._dataMax = dataExtent[1];\n var isOrdinal = this._isOrdinal = scale.type === 'ordinal';\n this._needCrossZero = scale.type === 'interval' && model.getNeedCrossZero && model.getNeedCrossZero();\n var modelMinRaw = this._modelMinRaw = model.get('min', true);\n\n if (isFunction(modelMinRaw)) {\n // This callback always provides users the full data extent (before data is filtered).\n this._modelMinNum = parseAxisModelMinMax(scale, modelMinRaw({\n min: dataExtent[0],\n max: dataExtent[1]\n }));\n } else if (modelMinRaw !== 'dataMin') {\n this._modelMinNum = parseAxisModelMinMax(scale, modelMinRaw);\n }\n\n var modelMaxRaw = this._modelMaxRaw = model.get('max', true);\n\n if (isFunction(modelMaxRaw)) {\n // This callback always provides users the full data extent (before data is filtered).\n this._modelMaxNum = parseAxisModelMinMax(scale, modelMaxRaw({\n min: dataExtent[0],\n max: dataExtent[1]\n }));\n } else if (modelMaxRaw !== 'dataMax') {\n this._modelMaxNum = parseAxisModelMinMax(scale, modelMaxRaw);\n }\n\n if (isOrdinal) {\n // FIXME: there is a flaw here: if there is no \"block\" data processor like `dataZoom`,\n // and progressive rendering is using, here the category result might just only contain\n // the processed chunk rather than the entire result.\n this._axisDataLen = model.getCategories().length;\n } else {\n var boundaryGap = model.get('boundaryGap');\n var boundaryGapArr = isArray(boundaryGap) ? boundaryGap : [boundaryGap || 0, boundaryGap || 0];\n\n if (typeof boundaryGapArr[0] === 'boolean' || typeof boundaryGapArr[1] === 'boolean') {\n if (process.env.NODE_ENV !== 'production') {\n console.warn('Boolean type for boundaryGap is only ' + 'allowed for ordinal axis. Please use string in ' + 'percentage instead, e.g., \"20%\". Currently, ' + 'boundaryGap is set to be 0.');\n }\n\n this._boundaryGapInner = [0, 0];\n } else {\n this._boundaryGapInner = [parsePercent(boundaryGapArr[0], 1), parsePercent(boundaryGapArr[1], 1)];\n }\n }\n };\n /**\n * Calculate extent by prepared parameters.\n * This method has no external dependency and can be called duplicatedly,\n * getting the same result.\n * If parameters changed, should call this method to recalcuate.\n */\n\n\n ScaleRawExtentInfo.prototype.calculate = function () {\n // Notice: When min/max is not set (that is, when there are null/undefined,\n // which is the most common case), these cases should be ensured:\n // (1) For 'ordinal', show all axis.data.\n // (2) For others:\n // + `boundaryGap` is applied (if min/max set, boundaryGap is\n // disabled).\n // + If `needCrossZero`, min/max should be zero, otherwise, min/max should\n // be the result that originalExtent enlarged by boundaryGap.\n // (3) If no data, it should be ensured that `scale.setBlank` is set.\n var isOrdinal = this._isOrdinal;\n var dataMin = this._dataMin;\n var dataMax = this._dataMax;\n var axisDataLen = this._axisDataLen;\n var boundaryGapInner = this._boundaryGapInner;\n var span = !isOrdinal ? dataMax - dataMin || Math.abs(dataMin) : null; // Currently if a `'value'` axis model min is specified as 'dataMin'/'dataMax',\n // `boundaryGap` will not be used. It's the different from specifying as `null`/`undefined`.\n\n var min = this._modelMinRaw === 'dataMin' ? dataMin : this._modelMinNum;\n var max = this._modelMaxRaw === 'dataMax' ? dataMax : this._modelMaxNum; // If `_modelMinNum`/`_modelMaxNum` is `null`/`undefined`, should not be fixed.\n\n var minFixed = min != null;\n var maxFixed = max != null;\n\n if (min == null) {\n min = isOrdinal ? axisDataLen ? 0 : NaN : dataMin - boundaryGapInner[0] * span;\n }\n\n if (max == null) {\n max = isOrdinal ? axisDataLen ? axisDataLen - 1 : NaN : dataMax + boundaryGapInner[1] * span;\n }\n\n (min == null || !isFinite(min)) && (min = NaN);\n (max == null || !isFinite(max)) && (max = NaN);\n var isBlank = eqNaN(min) || eqNaN(max) || isOrdinal && !axisDataLen; // If data extent modified, need to recalculated to ensure cross zero.\n\n if (this._needCrossZero) {\n // Axis is over zero and min is not set\n if (min > 0 && max > 0 && !minFixed) {\n min = 0; // minFixed = true;\n } // Axis is under zero and max is not set\n\n\n if (min < 0 && max < 0 && !maxFixed) {\n max = 0; // maxFixed = true;\n } // PENDING:\n // When `needCrossZero` and all data is positive/negative, should it be ensured\n // that the results processed by boundaryGap are positive/negative?\n // If so, here `minFixed`/`maxFixed` need to be set.\n\n }\n\n var determinedMin = this._determinedMin;\n var determinedMax = this._determinedMax;\n\n if (determinedMin != null) {\n min = determinedMin;\n minFixed = true;\n }\n\n if (determinedMax != null) {\n max = determinedMax;\n maxFixed = true;\n } // Ensure min/max be finite number or NaN here. (not to be null/undefined)\n // `NaN` means min/max axis is blank.\n\n\n return {\n min: min,\n max: max,\n minFixed: minFixed,\n maxFixed: maxFixed,\n isBlank: isBlank\n };\n };\n\n ScaleRawExtentInfo.prototype.modifyDataMinMax = function (minMaxName, val) {\n if (process.env.NODE_ENV !== 'production') {\n assert(!this.frozen);\n }\n\n this[DATA_MIN_MAX_ATTR[minMaxName]] = val;\n };\n\n ScaleRawExtentInfo.prototype.setDeterminedMinMax = function (minMaxName, val) {\n var attr = DETERMINED_MIN_MAX_ATTR[minMaxName];\n\n if (process.env.NODE_ENV !== 'production') {\n assert(!this.frozen // Earse them usually means logic flaw.\n && this[attr] == null);\n }\n\n this[attr] = val;\n };\n\n ScaleRawExtentInfo.prototype.freeze = function () {\n // @ts-ignore\n this.frozen = true;\n };\n\n return ScaleRawExtentInfo;\n}();\n\nexport { ScaleRawExtentInfo };\nvar DETERMINED_MIN_MAX_ATTR = {\n min: '_determinedMin',\n max: '_determinedMax'\n};\nvar DATA_MIN_MAX_ATTR = {\n min: '_dataMin',\n max: '_dataMax'\n};\n/**\n * Get scale min max and related info only depends on model settings.\n * This method can be called after coordinate system created.\n * For example, in data processing stage.\n *\n * Scale extent info probably be required multiple times during a workflow.\n * For example:\n * (1) `dataZoom` depends it to get the axis extent in \"100%\" state.\n * (2) `processor/extentCalculator` depends it to make sure whether axis extent is specified.\n * (3) `coordSys.update` use it to finally decide the scale extent.\n * But the callback of `min`/`max` should not be called multiple times.\n * The code below should not be implemented repeatedly either.\n * So we cache the result in the scale instance, which will be recreated at the beginning\n * of the workflow (because `scale` instance will be recreated each round of the workflow).\n */\n\nexport function ensureScaleRawExtentInfo(scale, model, // Usually: data extent from all series on this axis.\noriginalExtent) {\n // Do not permit to recreate.\n var rawExtentInfo = scale.rawExtentInfo;\n\n if (rawExtentInfo) {\n return rawExtentInfo;\n }\n\n rawExtentInfo = new ScaleRawExtentInfo(scale, model, originalExtent); // @ts-ignore\n\n scale.rawExtentInfo = rawExtentInfo;\n return rawExtentInfo;\n}\nexport function parseAxisModelMinMax(scale, minMax) {\n return minMax == null ? null : eqNaN(minMax) ? 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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/*\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*/\nimport { assert, isArray, eqNaN, isFunction } from 'zrender/lib/core/util.js';\nimport { parsePercent } from 'zrender/lib/contain/text.js';\n\nvar ScaleRawExtentInfo =\n/** @class */\nfunction () {\n function ScaleRawExtentInfo(scale, model, // Usually: data extent from all series on this axis.\n originalExtent) {\n this._prepareParams(scale, model, originalExtent);\n }\n /**\n * Parameters depending on outside (like model, user callback)\n * are prepared and fixed here.\n */\n\n\n ScaleRawExtentInfo.prototype._prepareParams = function (scale, model, // Usually: data extent from all series on this axis.\n dataExtent) {\n if (dataExtent[1] < dataExtent[0]) {\n dataExtent = [NaN, NaN];\n }\n\n this._dataMin = dataExtent[0];\n this._dataMax = dataExtent[1];\n var isOrdinal = this._isOrdinal = scale.type === 'ordinal';\n this._needCrossZero = scale.type === 'interval' && model.getNeedCrossZero && model.getNeedCrossZero();\n var modelMinRaw = this._modelMinRaw = model.get('min', true);\n\n if (isFunction(modelMinRaw)) {\n // This callback always provides users the full data extent (before data is filtered).\n this._modelMinNum = parseAxisModelMinMax(scale, modelMinRaw({\n min: dataExtent[0],\n max: dataExtent[1]\n }));\n } else if (modelMinRaw !== 'dataMin') {\n this._modelMinNum = parseAxisModelMinMax(scale, modelMinRaw);\n }\n\n var modelMaxRaw = this._modelMaxRaw = model.get('max', true);\n\n if (isFunction(modelMaxRaw)) {\n // This callback always provides users the full data extent (before data is filtered).\n this._modelMaxNum = parseAxisModelMinMax(scale, modelMaxRaw({\n min: dataExtent[0],\n max: dataExtent[1]\n }));\n } else if (modelMaxRaw !== 'dataMax') {\n this._modelMaxNum = parseAxisModelMinMax(scale, modelMaxRaw);\n }\n\n if (isOrdinal) {\n // FIXME: there is a flaw here: if there is no \"block\" data processor like `dataZoom`,\n // and progressive rendering is using, here the category result might just only contain\n // the processed chunk rather than the entire result.\n this._axisDataLen = model.getCategories().length;\n } else {\n var boundaryGap = model.get('boundaryGap');\n var boundaryGapArr = isArray(boundaryGap) ? boundaryGap : [boundaryGap || 0, boundaryGap || 0];\n\n if (typeof boundaryGapArr[0] === 'boolean' || typeof boundaryGapArr[1] === 'boolean') {\n if (process.env.NODE_ENV !== 'production') {\n console.warn('Boolean type for boundaryGap is only ' + 'allowed for ordinal axis. Please use string in ' + 'percentage instead, e.g., \"20%\". Currently, ' + 'boundaryGap is set to be 0.');\n }\n\n this._boundaryGapInner = [0, 0];\n } else {\n this._boundaryGapInner = [parsePercent(boundaryGapArr[0], 1), parsePercent(boundaryGapArr[1], 1)];\n }\n }\n };\n /**\n * Calculate extent by prepared parameters.\n * This method has no external dependency and can be called duplicatedly,\n * getting the same result.\n * If parameters changed, should call this method to recalcuate.\n */\n\n\n ScaleRawExtentInfo.prototype.calculate = function () {\n // Notice: When min/max is not set (that is, when there are null/undefined,\n // which is the most common case), these cases should be ensured:\n // (1) For 'ordinal', show all axis.data.\n // (2) For others:\n // + `boundaryGap` is applied (if min/max set, boundaryGap is\n // disabled).\n // + If `needCrossZero`, min/max should be zero, otherwise, min/max should\n // be the result that originalExtent enlarged by boundaryGap.\n // (3) If no data, it should be ensured that `scale.setBlank` is set.\n var isOrdinal = this._isOrdinal;\n var dataMin = this._dataMin;\n var dataMax = this._dataMax;\n var axisDataLen = this._axisDataLen;\n var boundaryGapInner = this._boundaryGapInner;\n var span = !isOrdinal ? dataMax - dataMin || Math.abs(dataMin) : null; // Currently if a `'value'` axis model min is specified as 'dataMin'/'dataMax',\n // `boundaryGap` will not be used. It's the different from specifying as `null`/`undefined`.\n\n var min = this._modelMinRaw === 'dataMin' ? dataMin : this._modelMinNum;\n var max = this._modelMaxRaw === 'dataMax' ? dataMax : this._modelMaxNum; // If `_modelMinNum`/`_modelMaxNum` is `null`/`undefined`, should not be fixed.\n\n var minFixed = min != null;\n var maxFixed = max != null;\n\n if (min == null) {\n min = isOrdinal ? axisDataLen ? 0 : NaN : dataMin - boundaryGapInner[0] * span;\n }\n\n if (max == null) {\n max = isOrdinal ? axisDataLen ? axisDataLen - 1 : NaN : dataMax + boundaryGapInner[1] * span;\n }\n\n (min == null || !isFinite(min)) && (min = NaN);\n (max == null || !isFinite(max)) && (max = NaN);\n var isBlank = eqNaN(min) || eqNaN(max) || isOrdinal && !axisDataLen; // If data extent modified, need to recalculated to ensure cross zero.\n\n if (this._needCrossZero) {\n // Axis is over zero and min is not set\n if (min > 0 && max > 0 && !minFixed) {\n min = 0; // minFixed = true;\n } // Axis is under zero and max is not set\n\n\n if (min < 0 && max < 0 && !maxFixed) {\n max = 0; // maxFixed = true;\n } // PENDING:\n // When `needCrossZero` and all data is positive/negative, should it be ensured\n // that the results processed by boundaryGap are positive/negative?\n // If so, here `minFixed`/`maxFixed` need to be set.\n\n }\n\n var determinedMin = this._determinedMin;\n var determinedMax = this._determinedMax;\n\n if (determinedMin != null) {\n min = determinedMin;\n minFixed = true;\n }\n\n if (determinedMax != null) {\n max = determinedMax;\n maxFixed = true;\n } // Ensure min/max be finite number or NaN here. (not to be null/undefined)\n // `NaN` means min/max axis is blank.\n\n\n return {\n min: min,\n max: max,\n minFixed: minFixed,\n maxFixed: maxFixed,\n isBlank: isBlank\n };\n };\n\n ScaleRawExtentInfo.prototype.modifyDataMinMax = function (minMaxName, val) {\n if (process.env.NODE_ENV !== 'production') {\n assert(!this.frozen);\n }\n\n this[DATA_MIN_MAX_ATTR[minMaxName]] = val;\n };\n\n ScaleRawExtentInfo.prototype.setDeterminedMinMax = function (minMaxName, val) {\n var attr = DETERMINED_MIN_MAX_ATTR[minMaxName];\n\n if (process.env.NODE_ENV !== 'production') {\n assert(!this.frozen // Earse them usually means logic flaw.\n && this[attr] == null);\n }\n\n this[attr] = val;\n };\n\n ScaleRawExtentInfo.prototype.freeze = function () {\n // @ts-ignore\n this.frozen = true;\n };\n\n return ScaleRawExtentInfo;\n}();\n\nexport { ScaleRawExtentInfo };\nvar DETERMINED_MIN_MAX_ATTR = {\n min: '_determinedMin',\n max: '_determinedMax'\n};\nvar DATA_MIN_MAX_ATTR = {\n min: '_dataMin',\n max: '_dataMax'\n};\n/**\n * Get scale min max and related info only depends on model settings.\n * This method can be called after coordinate system created.\n * For example, in data processing stage.\n *\n * Scale extent info probably be required multiple times during a workflow.\n * For example:\n * (1) `dataZoom` depends it to get the axis extent in \"100%\" state.\n * (2) `processor/extentCalculator` depends it to make sure whether axis extent is specified.\n * (3) `coordSys.update` use it to finally decide the scale extent.\n * But the callback of `min`/`max` should not be called multiple times.\n * The code below should not be implemented repeatedly either.\n * So we cache the result in the scale instance, which will be recreated at the beginning\n * of the workflow (because `scale` instance will be recreated each round of the workflow).\n */\n\nexport function ensureScaleRawExtentInfo(scale, model, // Usually: data extent from all series on this axis.\noriginalExtent) {\n // Do not permit to recreate.\n var rawExtentInfo = scale.rawExtentInfo;\n\n if (rawExtentInfo) {\n return rawExtentInfo;\n }\n\n rawExtentInfo = new ScaleRawExtentInfo(scale, model, originalExtent); // @ts-ignore\n\n scale.rawExtentInfo = rawExtentInfo;\n return rawExtentInfo;\n}\nexport function parseAxisModelMinMax(scale, minMax) {\n return minMax == null ? null : eqNaN(minMax) ? NaN : scale.parse(minMax);\n}"]},"metadata":{},"sourceType":"module"} |