als-statistics/lib/column/base.js

A powerful and lightweight JavaScript library for descriptive statistics, regression, clustering, outlier detection, and noise analysis using a flexible table/column architecture.

const ColumnFilter = require('../table/filter')
const getType = require('../utils/get-type')
class BaseColumn {
   cache = {};
   constructor(values=[], columnFilter, type) {
      if (!Array.isArray(values)) throw new Error("Input must be a non-empty array");
      this.columnFilter = columnFilter || new ColumnFilter()
      this.type = type || getType(values)
      this._values = values;
   }
   
   count(fn,filtered=true) { return (filtered ? this.values : this._values).filter(fn) }
   
   cached(name, fn) {
      const state = this.columnFilter.filterState;
      if (this.cache[name] && this.cache[name].state === state) return this.cache[name].value;
      this.cache[name] = { state, value: fn() };
      return this.cache[name].value;
   }

   filterRows(indexes) { this.columnFilter.filterRows(indexes) }
   clearRowsFilters(indexes) { this.columnFilter.clearRowsFilters(indexes) }
   clearAllRowsFilters() { this.columnFilter.clearAllRowsFilters() }
   filterRowsBy(fn) {
      const indexes = this._values.map((v, i) => fn(v, i) ? i : false).filter(v => v !== false)
      this.filterRows(indexes) 
   }

   get values() {
      return this.cached('values', () => {
         if (!this.columnFilter.isFiltered) return this._values
         return this._values.filter((v, i) => !this.columnFilter.filtered[i])
      })
   }

   get n() { return this.values.length }
}

module.exports = BaseColumn