const currentScores = {};

const rescore = (target, { name, jab, rgb }) => {
  currentScores[name] = {
    jab: {
      total: applyMetrics(jab.total, target.jab),
      clusters: jab.clusters.map(c => applyMetrics(c, target.jab)),
    },
    rgb: {
      total: applyMetrics(rgb.total, target.rgb),
      clusters: rgb.clusters.map(c => applyMetrics(c, target.rgb)),
    },
  };
};

const rescoreAll = target => pokemonData.forEach(pkmn => rescore(target, pkmn));

const getBestClusterIndex = (pkmn, space, { sortMetric, scaleOption, sortOrder }) => {
  // get the scales
  const scales = scaleOption(pkmn);
  // and multiply with the intended metric, and find the best value
  return argComp(sortOrder)(
    currentScores[pkmn.name][space].map((c, i) => c[sortMetric] * scales[i])
  );
}

const getBest = (number, space, clusterSettings, { sortMetric, scaleOption, sortOrder }) => {
  let valueExtractor;
  if (clusterSettings) {
    valueExtractor = pkmn => {
      const index = getBestClusterIndex(pkmn, space, clusterSettings);
      // and then get the *actual* score according to the sort metric
      return scaleOption(pkmn)[index] * clusters[index][sortMetric];      
    };
  } else {
    // ignore scaleOption if not using clusters
    valueExtractor = pkmn => currentScores[pkmn.name][space].total[sortMetric];
  }
  
  return pokemonData
    .slice()
    .sort((a, b) => sortOrder(valueExtractor(a), valueExtractor(b)))
    .slice(0, number);
};