'use strict';

var model = require('../../util/model.js');
var util = require('../../../../../../zrender@6.0.0/node_modules/zrender/lib/core/util.js');
var types = require('../../util/types.js');

// The result of `guessOrdinal`.
var BE_ORDINAL = {
  Must: 1,
  Might: 2,
  Not: 3 // Other cases
};
var innerGlobalModel = model.makeInner();
/**
 * MUST be called before mergeOption of all series.
 */
function resetSourceDefaulter(ecModel) {
  // `datasetMap` is used to make default encode.
  innerGlobalModel(ecModel).datasetMap = util.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`.
 */
function makeSeriesEncodeForAxisCoordSys(coordDimensions, seriesModel, source) {
  var encode = {};
  var datasetModel = querySeriesUpstreamDatasetModel(seriesModel);
  // Currently only make default when using dataset, util more reqirements occur.
  if (!datasetModel || !coordDimensions) {
    return encode;
  }
  var encodeItemName = [];
  var encodeSeriesName = [];
  var ecModel = seriesModel.ecModel;
  var datasetMap = innerGlobalModel(ecModel).datasetMap;
  var key = datasetModel.uid + '_' + source.seriesLayoutBy;
  var baseCategoryDimIndex;
  var categoryWayValueDimStart;
  coordDimensions = coordDimensions.slice();
  util.each(coordDimensions, function (coordDimInfoLoose, coordDimIdx) {
    var coordDimInfo = util.isObject(coordDimInfoLoose) ? coordDimInfoLoose : coordDimensions[coordDimIdx] = {
      name: coordDimInfoLoose
    };
    if (coordDimInfo.type === 'ordinal' && baseCategoryDimIndex == null) {
      baseCategoryDimIndex = coordDimIdx;
      categoryWayValueDimStart = getDataDimCountOnCoordDim(coordDimInfo);
    }
    encode[coordDimInfo.name] = [];
  });
  var datasetRecord = datasetMap.get(key) || datasetMap.set(key, {
    categoryWayDim: categoryWayValueDimStart,
    valueWayDim: 0
  });
  // TODO
  // Auto detect first time axis and do arrangement.
  util.each(coordDimensions, function (coordDimInfo, coordDimIdx) {
    var coordDimName = coordDimInfo.name;
    var count = getDataDimCountOnCoordDim(coordDimInfo);
    // In value way.
    if (baseCategoryDimIndex == null) {
      var 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 {
      var start = datasetRecord.categoryWayDim;
      pushDim(encode[coordDimName], start, count);
      pushDim(encodeSeriesName, start, count);
      datasetRecord.categoryWayDim += count;
    }
  });
  function pushDim(dimIdxArr, idxFrom, idxCount) {
    for (var i = 0; i < idxCount; i++) {
      dimIdxArr.push(idxFrom + i);
    }
  }
  function getDataDimCountOnCoordDim(coordDimInfo) {
    var 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`.
 */
function makeSeriesEncodeForNameBased(seriesModel, source, dimCount) {
  var encode = {};
  var datasetModel = querySeriesUpstreamDatasetModel(seriesModel);
  // Currently only make default when using dataset, util more reqirements occur.
  if (!datasetModel) {
    return encode;
  }
  var sourceFormat = source.sourceFormat;
  var dimensionsDefine = source.dimensionsDefine;
  var potentialNameDimIndex;
  if (sourceFormat === types.SOURCE_FORMAT_OBJECT_ROWS || sourceFormat === types.SOURCE_FORMAT_KEYED_COLUMNS) {
    util.each(dimensionsDefine, function (dim, idx) {
      if ((util.isObject(dim) ? dim.name : dim) === 'name') {
        potentialNameDimIndex = idx;
      }
    });
  }
  var idxResult = function () {
    var idxRes0 = {};
    var idxRes1 = {};
    var guessRecords = [];
    // 5 is an experience value.
    for (var i = 0, len = Math.min(5, dimCount); i < len; i++) {
      var guessResult = doGuessOrdinal(source.data, sourceFormat, source.seriesLayoutBy, dimensionsDefine, source.startIndex, i);
      guessRecords.push(guessResult);
      var 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) {
      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.
    var 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.
 */
function querySeriesUpstreamDatasetModel(seriesModel) {
  // 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.
  var thisData = seriesModel.get('data', true);
  if (!thisData) {
    return model.queryReferringComponents(seriesModel.ecModel, 'dataset', {
      index: seriesModel.get('datasetIndex', true),
      id: seriesModel.get('datasetId', true)
    }, model.SINGLE_REFERRING).models[0];
  }
}
/**
 * @return Always return an array event empty.
 */
function queryDatasetUpstreamDatasetModels(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 model.queryReferringComponents(datasetModel.ecModel, 'dataset', {
    index: datasetModel.get('fromDatasetIndex', true),
    id: datasetModel.get('fromDatasetId', true)
  }, model.SINGLE_REFERRING).models;
}
/**
 * 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?
 */
function guessOrdinal(source, dimIndex) {
  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, sourceFormat, seriesLayoutBy, dimensionsDefine, startIndex, dimIndex) {
  var result;
  // Experience value.
  var maxLoop = 5;
  if (util.isTypedArray(data)) {
    return BE_ORDINAL.Not;
  }
  // When sourceType is 'objectRows' or 'keyedColumns', dimensionsDefine
  // always exists in source.
  var dimName;
  var dimType;
  if (dimensionsDefine) {
    var dimDefItem = dimensionsDefine[dimIndex];
    if (util.isObject(dimDefItem)) {
      dimName = dimDefItem.name;
      dimType = dimDefItem.type;
    } else if (util.isString(dimDefItem)) {
      dimName = dimDefItem;
    }
  }
  if (dimType != null) {
    return dimType === 'ordinal' ? BE_ORDINAL.Must : BE_ORDINAL.Not;
  }
  if (sourceFormat === types.SOURCE_FORMAT_ARRAY_ROWS) {
    var dataArrayRows = data;
    if (seriesLayoutBy === types.SERIES_LAYOUT_BY_ROW) {
      var sample = dataArrayRows[dimIndex];
      for (var i = 0; i < (sample || []).length && i < maxLoop; i++) {
        if ((result = detectValue(sample[startIndex + i])) != null) {
          return result;
        }
      }
    } else {
      for (var i = 0; i < dataArrayRows.length && i < maxLoop; i++) {
        var row = dataArrayRows[startIndex + i];
        if (row && (result = detectValue(row[dimIndex])) != null) {
          return result;
        }
      }
    }
  } else if (sourceFormat === types.SOURCE_FORMAT_OBJECT_ROWS) {
    var dataObjectRows = data;
    if (!dimName) {
      return BE_ORDINAL.Not;
    }
    for (var i = 0; i < dataObjectRows.length && i < maxLoop; i++) {
      var item = dataObjectRows[i];
      if (item && (result = detectValue(item[dimName])) != null) {
        return result;
      }
    }
  } else if (sourceFormat === types.SOURCE_FORMAT_KEYED_COLUMNS) {
    var dataKeyedColumns = data;
    if (!dimName) {
      return BE_ORDINAL.Not;
    }
    var sample = dataKeyedColumns[dimName];
    if (!sample || util.isTypedArray(sample)) {
      return BE_ORDINAL.Not;
    }
    for (var i = 0; i < sample.length && i < maxLoop; i++) {
      if ((result = detectValue(sample[i])) != null) {
        return result;
      }
    }
  } else if (sourceFormat === types.SOURCE_FORMAT_ORIGINAL) {
    var dataOriginal = data;
    for (var i = 0; i < dataOriginal.length && i < maxLoop; i++) {
      var item = dataOriginal[i];
      var val = model.getDataItemValue(item);
      if (!util.isArray(val)) {
        return BE_ORDINAL.Not;
      }
      if ((result = detectValue(val[dimIndex])) != null) {
        return result;
      }
    }
  }
  function detectValue(val) {
    var beStr = util.isString(val);
    // Consider usage convenience, '1', '2' will be treated as "number".
    // `Number('')` (or any whitespace) is `0`.
    if (val != null && Number.isFinite(Number(val)) && val !== '') {
      return beStr ? BE_ORDINAL.Might : BE_ORDINAL.Not;
    } else if (beStr && val !== '-') {
      return BE_ORDINAL.Must;
    }
  }
  return BE_ORDINAL.Not;
}

exports.BE_ORDINAL = BE_ORDINAL;
exports.guessOrdinal = guessOrdinal;
exports.makeSeriesEncodeForAxisCoordSys = makeSeriesEncodeForAxisCoordSys;
exports.makeSeriesEncodeForNameBased = makeSeriesEncodeForNameBased;
exports.queryDatasetUpstreamDatasetModels = queryDatasetUpstreamDatasetModels;
exports.querySeriesUpstreamDatasetModel = querySeriesUpstreamDatasetModel;
exports.resetSourceDefaulter = resetSourceDefaulter;
