diff --git a/package.json b/package.json index 8cf7548..fe75007 100644 --- a/package.json +++ b/package.json @@ -32,7 +32,6 @@ }, "homepage": "https://github.com/fugle-dev/fugle-backtest-node#readme", "dependencies": { - "danfojs-node": "^1.1.2", "html-minifier": "^4.0.0", "lodash": "^4.17.21", "luxon": "^3.2.1", diff --git a/src/backtest.ts b/src/backtest.ts index 2495643..e136c74 100644 --- a/src/backtest.ts +++ b/src/backtest.ts @@ -1,4 +1,3 @@ -import { DataFrame, Series, toJSON } from 'danfojs-node'; import { intersection, maxBy } from 'lodash'; import { Strategy as BaseStrategy } from './strategy'; import { Broker } from './broker'; @@ -7,6 +6,9 @@ import { Stats } from './stats'; import { HistoricalData, BacktestOptions, Context } from './interfaces'; import { StatsIndex } from './enums'; +import DataFrame from './ndframe/dataframe'; +import Series from './ndframe/series'; + export class Backtest { private _data: DataFrame; private _stats?: Stats; @@ -65,8 +67,7 @@ export class Backtest { }); const strategy = new this.Strategy(data, broker); - // @ts-ignore - if (options?.params) strategy.params = options.params; + if (options?.params) (strategy as any).params = options.params; strategy.init(); @@ -161,7 +162,7 @@ export class Backtest { const data = { date: rows.index[0], - ...(toJSON(rows) as Record[])[0], + ...(rows.toJSON() as Record[])[0], }; const indicators = new Map( diff --git a/src/broker.ts b/src/broker.ts index 8cc2dfb..39ad789 100644 --- a/src/broker.ts +++ b/src/broker.ts @@ -1,11 +1,12 @@ import * as assert from 'assert'; -import { DataFrame } from 'danfojs-node'; import { last, first, sumBy, remove } from 'lodash'; import { Order } from './order'; import { Trade } from './trade'; import { Position } from './position'; import { BrokerOptions, OrderOptions } from './interfaces'; +import DataFrame from './ndframe/dataframe'; + export class Broker { private _i: number; private _cash: number; @@ -135,6 +136,7 @@ export class Broker { const isStopHit = order.isLong ? (high > stopPrice) : (low < stopPrice); /* istanbul ignore if */ if (!isStopHit) continue; + // eslint-disable-next-line @typescript-eslint/ban-ts-comment // @ts-ignore delete order._stopPrice; } diff --git a/src/interfaces/context.interface.ts b/src/interfaces/context.interface.ts index e4360d2..bf0a139 100644 --- a/src/interfaces/context.interface.ts +++ b/src/interfaces/context.interface.ts @@ -1,4 +1,4 @@ -import { DataFrame } from 'danfojs-node'; +import DataFrame from '../ndframe/dataframe'; export interface Context { index: number; diff --git a/src/ndframe/dataframe.ts b/src/ndframe/dataframe.ts new file mode 100644 index 0000000..06faaca --- /dev/null +++ b/src/ndframe/dataframe.ts @@ -0,0 +1,1014 @@ +/** + * @license + * Copyright 2022 JsData. All rights reserved. + * + * This source code is licensed under the MIT license found in the + * LICENSE file in the root directory of this source tree. + + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + * ========================================================================== + */ + +import { ArrayType1D, ArrayType2D } from '../utils/arrays'; +import NDframe from "./ndframe"; +import Series from './series'; + +/** + * Two-dimensional ndarray with axis labels. + * The object supports both integer- and label-based indexing and provides a host of methods for performing operations involving the index. + * Operations between DataFrame (+, -, /, , *) align values based on their associated index values– they need not be the same length. + * @param data 2D Array, JSON, Tensor, Block of data. + * @param options.index Array of numeric or string names for subseting array. If not specified, indices are auto generated. + * @param options.columns Array of column names. If not specified, column names are auto generated. + * @param options.dtypes Array of data types for each the column. If not specified, dtypes are/is inferred. + * @param options.config General configuration object for extending or setting NDframe behavior. + */ +export default class DataFrame extends NDframe { + [key: string]: any + constructor(data: any, options: any = {}) { + const { index, columns, dtypes } = options; + super({ data, index, columns, dtypes, isSeries: false }); + this.$setInternalColumnDataProperty(); + } + + /** + * Access a single value for a row/column label pair. + * Similar to {@link loc}, in that both provide label-based lookups. + * Use at if you only need to get or set a single value in a DataFrame. + * @param row Row index of the value to access. + * @param column Column label of the value to access. + * @example + * ``` + * const df = new DataFrame([[1, 2], [3, 4]], { columns: ['A', 'B']}) + * df.at(0,'A') // 1 + * df.at(1, 'A') // 3 + * df.at(1, 'B') // 4 + * ``` + */ + at(row: string | number, column: string): string | number | boolean | undefined { + if (typeof column !== 'string') { + throw new Error('ParamError: column index must be a string. Use .iat to get a row or column by index.') + } + return (this.values as ArrayType2D)[this.index.indexOf(row)][this.columns.indexOf(column)] + } + + /** + * Access a single value for a row/column pair by integer position. + * Similar to {@link iloc}, in that both provide integer-based lookups. + * Use iat if you only need to get or set a single value in a DataFrame. + * @param row Row index of the value to access. + * @param column Column index of the value to access. + * @example + * ``` + * const df = new DataFrame([[1, 2], [3, 4]], { columns: ['A', 'B']}) + * df.iat(0, 0) // 1 + * df.iat(0, 1) // 2 + * df.iat(1, 0) // 3 + * ``` + */ + iat(row: number, column: number): string | number | boolean | undefined { + if (typeof row === 'string' || typeof column === 'string') { + throw new Error('ParamError: row and column index must be an integer. Use .at to get a row or column by label.') + } + + return (this.values as ArrayType2D)[row][column] + } + + /** + * Returns the first n values in a DataFrame + * @param rows The number of rows to return + * @example + * ``` + * const df = new DataFrame([[1, 2], [3, 4]], { columns: ['A', 'B']}) + * const df2 = df.head(1) + * ``` + */ + head(rows = 5): DataFrame { + + if (rows <= 0) { + throw new Error("ParamError: Number of rows cannot be less than 1") + } + if (this.shape[0] <= rows) { + return this.copy() + } + if (this.shape[0] - rows < 0) { + throw new Error("ParamError: Number of rows cannot be greater than available rows in data") + } + + return this.iloc({ rows: [`0:${rows}`] }) + } + + /** + * Purely integer-location based indexing for selection by position. + * ``.iloc`` is primarily integer position based (from ``0`` to + * ``length-1`` of the axis), but may also be used with a boolean array. + * + * @param rows Array of row indexes + * @param columns Array of column indexes + * + * Allowed inputs are in rows and columns params are: + * + * - An array of single integer, e.g. ``[5]``. + * - A list or array of integers, e.g. ``[4, 3, 0]``. + * - A slice array string with ints, e.g. ``["1:7"]``. + * - A boolean array. + * - A ``callable`` function with one argument (the calling Series or + * DataFrame) and that returns valid output for indexing (one of the above). + * This is useful in method chains, when you don't have a reference to the + * calling object, but would like to base your selection on some value. + * + * ``.iloc`` will raise ``IndexError`` if a requested indexer is + * out-of-bounds. + * + * @example + * ``` + * const df = new DataFrame([[1, 2], [3, 4]], { columns: ['A', 'B'] }) + * const df2 = df.iloc({ rows: [1], columns: ["A"] }) + * ``` + */ + iloc({ rows, columns }: { + rows?: Array | Series, + columns?: Array + }): DataFrame { + /** + * Generates an array of integers between specified range + * @param start The starting number. + * @param end The ending number. + */ + function range(start: number, end: number): Array { + if (end < start) { + throw new Error("ParamError: end must be greater than start") + } + + if (start === end) { + return [start] + } + + const arr = []; + for (let i = start; i <= end; i++) { + arr.push(i); + } + return arr; + } + + let _rowIndexes: Array + let _columnIndexes: Array + + const _data = this.values; + const _index = this.index; + + if (rows instanceof Series) { + rows = rows.values as Array + } + + if (rows !== undefined && !Array.isArray(rows)) { + throw new Error(`rows parameter must be an Array. For example: rows: [1,2] or rows: ["0:10"]`) + } + + if (columns !== undefined && !Array.isArray(columns)) { + throw new Error(`columns parameter must be an Array. For example: columns: [1,2] or columns: ["0:10"]`) + } + + if (!rows) { + _rowIndexes = range(0, this.shape[0] - 1); + + } else if (rows.length == 1 && typeof rows[0] == "string") { + const rowSplit = rows[0].split(":") + + if (rowSplit.length != 2) { + throw new Error(`Invalid row split parameter: If using row split string, it must be of the form; rows: ["start:end"]`); + } + if (isNaN(parseInt(rowSplit[0])) && rowSplit[0] != "") { + throw new Error(`Invalid row split parameter. Split parameter must be a number`); + } + + if (isNaN(parseInt(rowSplit[1])) && rowSplit[1] != "") { + throw new Error(`Invalid row split parameter. Split parameter must be a number`); + } + + const start = rowSplit[0] == "" ? 0 : parseInt(rowSplit[0]) + const end = rowSplit[1] == "" ? this.shape[0] : parseInt(rowSplit[1]) + + if (start < 0) { + throw new Error(`row slice [start] index cannot be less than 0`); + } + + if (end > this.shape[0]) { + throw new Error(`row slice [end] index cannot be bigger than ${this.shape[0]}`); + } + //_rowIndexes = utils.range(start, end - 1) + _rowIndexes = range(start, end - 1) + } else { + const _formatedRows = [] + for (let i = 0; i < rows.length; i++) { + const _indexToUse = rows[i]; + if (_indexToUse > this.shape[0]) { + throw new Error(`Invalid row parameter: Specified index ${_indexToUse} cannot be bigger than index length ${this.shape[0]}`); + } + + if (typeof _indexToUse !== "number" && typeof _indexToUse !== "boolean") { + throw new Error(`Invalid row parameter: row index ${_indexToUse} must be a number or boolean`); + } + + if (typeof _indexToUse === "boolean" && _indexToUse === true) { + _formatedRows.push(_index[i]) + } + + if (typeof _indexToUse === "number") { + _formatedRows.push(_indexToUse) + } + } + + _rowIndexes = _formatedRows as number[] + } + + if (!columns) { + //_columnIndexes = utils.range(0, ndFrame.shape[1] - 1) + _columnIndexes = range(0, this.shape[1] - 1) + + } else if (columns.length == 1 && typeof columns[0] == "string") { + const columnSplit = columns[0].split(":") + + if (columnSplit.length != 2) { + throw new Error(`Invalid column split parameter: If using column split string, it must be of the form; columns: ["start:end"]`); + } + if (isNaN(parseInt(columnSplit[0])) && columnSplit[0] != "") { + throw new Error(`Invalid column split parameter. Split parameter must be a number`); + } + + if (isNaN(parseInt(columnSplit[1])) && columnSplit[1] != "") { + throw new Error(`Invalid column split parameter. Split parameter must be a number`); + } + + const start = columnSplit[0] == "" ? 0 : parseInt(columnSplit[0]) + const end = columnSplit[1] == "" ? this.shape[1] : parseInt(columnSplit[1]) + + if (start < 0) { + throw new Error(`column slice [start] index cannot be less than 0`); + } + + if (end > this.shape[1]) { + throw new Error(`column slice [end] index cannot be bigger than ${this.shape[1]}`); + } + //_columnIndexes = utils.range(start, end - 1) + _columnIndexes = range(start, end - 1) + } else { + + for (let i = 0; i < columns.length; i++) { + const _indexToUse = columns[i]; + if (_indexToUse > this.shape[1]) { + throw new Error(`Invalid column parameter: Specified index ${_indexToUse} cannot be bigger than index length ${this.shape[1]}`); + } + + if (typeof _indexToUse != "number") { + throw new Error(`Invalid column parameter: column index ${_indexToUse} must be a number`); + } + + } + + _columnIndexes = columns as number[] + } + const newData = [] + const newIndex = [] + const newColumnNames: string[] = [] + const newDtypes = [] + + for (let i = 0; i < _rowIndexes.length; i++) { + const rowIndx = _rowIndexes[i] + const rowData: any = _data[rowIndx] + const newRowDataWithRequiredCols = [] + + for (let j = 0; j < _columnIndexes.length; j++) { + const colIndx = _columnIndexes[j] + newRowDataWithRequiredCols.push(rowData[colIndx]) + } + newData.push(newRowDataWithRequiredCols) + newIndex.push(_index[rowIndx]) + } + + for (let i = 0; i < _columnIndexes.length; i++) { + const colIndx = _columnIndexes[i] + newColumnNames.push(this.columns[colIndx]) + newDtypes.push(this.dtypes[colIndx]) + + } + const df = new DataFrame( + newData, + { + index: newIndex, + columns: newColumnNames, + dtypes: newDtypes, + }) + return df + } + + /** + * Makes a deep copy of a DataFrame. + * @example + * ``` + * const df = new DataFrame([[1, 2], [3, 4]], { columns: ['A', 'B']}) + * const df2 = df.copy() + * df2.print() + * ``` + */ + copy(): DataFrame { + const df = new DataFrame([...this.$data], { + columns: [...this.columns], + index: [...this.index], + dtypes: [...this.dtypes], + }); + return df; + } + + /** + * Returns "greater than" of dataframe and other. + * @param other DataFrame, Series, Array or Scalar number to compare with + * @param options.axis 0 or 1. If 0, add column-wise, if 1, add row-wise + * @example + * ``` + * const df = new DataFrame([[1, 2], [3, 4]], { columns: ['A', 'B']}) + * df.gt(2).print() + * ``` + * @example + * ``` + * const df = new DataFrame([[1, 2], [3, 4]], { columns: ['A', 'B']}) + * df.gt([2, 3], { axis: 0 }).print() + * ``` + * @example + * ``` + * const df = new DataFrame([[1, 2], [3, 4]], { columns: ['A', 'B']}) + * const sf = new Series([2, 3]) + * df.gt(sf, { axis: 1 }).print() + * ``` + */ + gt(other: DataFrame | Series | number | Array, options?: { axis?: 0 | 1 }): DataFrame { + const { axis } = { axis: 1, ...options } + + if (this.$frameIsNotCompactibleForArithmeticOperation()) { + throw Error("TypeError: gt operation is not supported for string dtypes"); + } + + if ([0, 1].indexOf(axis) === -1) { + throw Error("ParamError: Axis must be 0 or 1"); + } + + const tensors = this.$getTensorsForArithmeticOperationByAxis(other, axis); + return this.$logicalOps(tensors, "gt") + } + + /** + * Queries the DataFrame for rows that meet the boolean criteria. This is just a wrapper for the `iloc` method. + * @param condition An array of boolean mask, one for each row in the DataFrame. Rows where the value are true will be returned. + * @param options.inplace Boolean indicating whether to perform the operation inplace or not. Defaults to false + * + * @example + * ``` + * const df = new DataFrame([[1, 2], [3, 4], [1, 2], [5, 6]], { columns: ['A', 'B'] }) + * const df2 = df.query([true, false, true, true]) + * df2.print() + * ``` + * + * @example + * ``` + * const df = new DataFrame([[1, 2], [3, 4], [1, 2], [5, 6]], { columns: ['A', 'B'] }) + * const df2 = df.query(df["A"].gt(2)) + * df2.print() + * ``` + * + * @example + * ``` + * const df = new DataFrame([[1, 2], [3, 4], [1, 2], [5, 6]], { columns: ['A', 'B'] }) + * const df2 = df.query(df["A"].gt(2).and(df["B"].lt(5))) + * df2.print() + * ``` + * + * @example + * ``` + * const df = new DataFrame([[1, 2], [3, 4], [1, 2], [5, 6]], { columns: ['A', 'B'] }) + * df.query(df["A"].gt(2), { inplace: true }) + * df.print() + * ``` + **/ + query(condition: Series | Array, options?: { inplace?: boolean }): DataFrame + query(condition: Series | Array, options?: { inplace?: boolean }): DataFrame | void { + const { inplace } = { inplace: false, ...options } + + if (!condition) { + throw new Error("ParamError: condition must be specified"); + } + + const result = this.iloc({ + rows: condition, + }) as DataFrame + + if (inplace) { + this.$setValues(result.values, false, false) + this.$setIndex(result.index) + } else { + return result + } + } + + /** + * Adds a new column to the DataFrame. If column exists, then the column values is replaced. + * @param column The name of the column to add or replace. + * @param values An array of values to be inserted into the DataFrame. Must be the same length as the columns + * @param options.inplace Boolean indicating whether to perform the operation inplace or not. Defaults to false + * @param options.atIndex Column index to insert after. Defaults to the end of the columns. + * @example + * ``` + * const df = new DataFrame([[1, 2], [3, 4]], { columns: ['A', 'B']}) + * const df2 = df.addColumn('C', [5, 6]) + * df2.print() + * ``` + * + * @example + * ``` + * const df = new DataFrame([[1, 2], [3, 4]], { columns: ['A', 'B']}) + * df.addColumn('C', [5, 6], { inplace: true }).print() + * ``` + * + * @example + * ``` + * const df = new DataFrame([[1, 2], [3, 4]], { columns: ['A', 'B']}) + * df.addColumn('C', [5, 6], { inplace: true, atIndex: 0 }).print() + * ``` + */ + addColumn( + column: string, + values: Series | ArrayType1D, + options?: { inplace?: boolean, atIndex?: number | string } + ): DataFrame + addColumn( + column: string, + values: Series | ArrayType1D, + options?: { inplace?: boolean, atIndex?: number | string } + ): DataFrame | void { + // eslint-disable-next-line prefer-const + let { inplace, atIndex } = { inplace: false, atIndex: this.columns.length, ...options }; + if (typeof atIndex === "string") { + if (!(this.columns.includes(atIndex))) { + throw new Error(`${atIndex} not a column`) + } + atIndex = this.columns.indexOf(atIndex) + } + + if (!column) { + throw new Error("ParamError: column must be specified") + } + + if (!values) { + throw new Error("ParamError: values must be specified") + } + + const columnIndex = this.$columns.indexOf(column) + + if (columnIndex === -1) { + let colunmValuesToAdd: ArrayType1D + + if (values instanceof Series) { + colunmValuesToAdd = values.values as ArrayType1D + } else if (Array.isArray(values)) { + colunmValuesToAdd = values; + } else { + throw new Error("ParamError: specified value not supported. It must either be an Array or a Series of the same length") + } + + if (colunmValuesToAdd.length !== this.shape[0]) { + const msg = `ParamError: Column data length mismatch. You provided data with length ${colunmValuesToAdd.length} but Ndframe has column of length ${this.shape[0]}` + throw new Error(msg) + } + + const newData = [] + const oldValues = this.$data + for (let i = 0; i < oldValues.length; i++) { + const innerArr = [...oldValues[i]] as ArrayType1D + innerArr.splice(atIndex, 0, colunmValuesToAdd[i]) + newData.push(innerArr) + } + + if (inplace) { + this.$setValues(newData, true, false) + const columns = [...this.columns] + columns.splice(atIndex, 0, column) + this.$setColumnNames(columns) + this.$setInternalColumnDataProperty(column); + + } else { + const columns = [...this.columns] + columns.splice(atIndex, 0, column) + + const df = new DataFrame(newData, { + index: [...this.index], + columns: columns, + dtypes: [...this.dtypes, NDframe.utils.inferDtype(colunmValuesToAdd)[0]], + }) + return df + } + } else { + this.$setColumnData(column, values); + } + + } + + /** + * Updates the internal column data via column name. + * @param column The name of the column to update. + * @param arr The new column data + */ + private $setColumnData(column: string, arr: ArrayType1D | Series): void { + + const columnIndex = this.$columns.indexOf(column) + + if (columnIndex == -1) { + throw new Error(`ParamError: column ${column} not found in ${this.$columns}. If you need to add a new column, use the df.addColumn method. `) + } + + let colunmValuesToAdd: ArrayType1D + + if (arr instanceof Series) { + colunmValuesToAdd = arr.values as ArrayType1D + } else if (Array.isArray(arr)) { + colunmValuesToAdd = arr; + } else { + throw new Error("ParamError: specified value not supported. It must either be an Array or a Series of the same length") + } + + if (colunmValuesToAdd.length !== this.shape[0]) { + const msg = `ParamError: Column data length mismatch. You provided data with length ${colunmValuesToAdd.length} but Ndframe has column of length ${this.shape[0]}` + throw new Error(msg) + } + + //Update row ($data) array + for (let i = 0; i < this.values.length; i++) { + (this.$data as any)[i][columnIndex] = colunmValuesToAdd[i] + } + //Update column ($dataIncolumnFormat) array since it's available in object + (this.$dataIncolumnFormat as any)[columnIndex] = arr + + //Update the dtypes + this.$dtypes[columnIndex] = NDframe.utils.inferDtype(colunmValuesToAdd)[0] + + } + + /** + * Maps all column names to their corresponding data, and return them as Series objects. + * This makes column subsetting works. E.g this can work ==> `df["col1"]` + * @param column Optional, a single column name to map + */ + private $setInternalColumnDataProperty(column?: string) { + // eslint-disable-next-line @typescript-eslint/no-this-alias + const self = this; + if (column && typeof column === "string") { + if (typeof self[column] === 'function') throw new Error(`${column} is a instance method`); + Object.defineProperty(self, column, { + get() { + return self.$getColumnData(column) + }, + set(arr: ArrayType1D | Series) { + self.$setColumnData(column, arr); + } + }) + } else { + const columns = this.columns; + for (let i = 0; i < columns.length; i++) { + const column = columns[i]; + if (typeof this[column] === 'function') throw new Error(`${column} is an instance method`); + Object.defineProperty(this, column, { + get() { + return self.$getColumnData(column) + }, + set(arr: ArrayType1D | Series) { + self.$setColumnData(column, arr); + } + }) + } + } + + } + + /** + * Returns the column data from the DataFrame by column name. + * @param column column name to get the column data + * @param returnSeries Whether to return the data in series format or not. Defaults to true + */ + private $getColumnData(column: string, returnSeries = true) { + const columnIndex = this.columns.indexOf(column) + + if (columnIndex == -1) { + const msg = `ParamError: Column not found!. Column name must be one of ${this.columns}` + throw new Error(msg) + } + + const dtypes = [this.$dtypes[columnIndex]] + const index = [...this.$index] + const columns = [column] + + const data = this.$dataIncolumnFormat[columnIndex] + if (returnSeries) { + return new Series(data, { + dtypes, + index, + columns, + }) + } else { + return data + } + + } + + /** + * Return data aligned to the specified axis. Transposes the array if needed. + * @param axis 0 or 1. If 0, column-wise, if 1, row-wise + */ + private $getDataArraysByAxis(axis: number): ArrayType2D { + if (axis === 1) { + return this.values as ArrayType2D + } else { + return this.$dataIncolumnFormat as ArrayType2D + } + } + + /** + * Return data with missing values removed from a specified axis + * @param axis 0 or 1. If 0, column-wise, if 1, row-wise + */ + private $getDataByAxisWithMissingValuesRemoved(axis: number): Array { + const oldValues = this.$getDataArraysByAxis(axis); + const cleanValues = []; + for (let i = 0; i < oldValues.length; i++) { + const values = oldValues[i] as number[] + cleanValues.push(NDframe.utils.removeMissingValuesFromArray(values) as number[]); + } + return cleanValues; + } + + /** + * Drop specified columns or rows. + * @param options.columns Array of column names to drop. + * @param options.index Array of index to drop. + * @param options.inplace Boolean indicating whether to perform the operation inplace or not. Defaults to false. + * @example + * ``` + * const df = new DataFrame([[1, 2], [3, 4]], { columns: ['A', 'B']}) + * const df2 = df.drop({ columns: ['A'] }) + * df2.print() + * ``` + * + * @example + * ``` + * const df = new DataFrame([[1, 2], [3, 4]], { columns: ['A', 'B']}) + * df.drop({ index: [0], inplace: true }).print() + * ``` + */ + drop(options?: + { + columns?: string | Array, + index?: Array, + inplace?: boolean + } + ): DataFrame + drop(options?: + { + columns?: string | Array, + index?: Array, + inplace?: boolean + } + ): DataFrame | void { + const { columns, index, inplace } = { inplace: false, ...options } + + if (!columns && !index) { + throw Error('ParamError: Must specify one of columns or index'); + } + + if (columns && index) { + throw Error('ParamError: Can only specify one of columns or index'); + } + + if (columns) { + const columnIndices: Array = [] + + if (typeof columns === "string") { + columnIndices.push(this.columns.indexOf(columns)) + } else if (Array.isArray(columns)) { + for (const column of columns) { + if (this.columns.indexOf(column) === -1) { + throw Error(`ParamError: specified column "${column}" not found in columns`); + } + columnIndices.push(this.columns.indexOf(column)) + } + + } else { + throw Error('ParamError: columns must be an array of column names or a string of column name'); + } + + const newRowData: ArrayType2D = [] + const newColumnNames = [] + const newDtypes = [] + + for (let i = 0; i < this.values.length; i++) { + const tempInnerArr = [] + const innerArr = this.values[i] as ArrayType1D + for (let j = 0; j < innerArr.length; j++) { + if (!(columnIndices.includes(j))) { + tempInnerArr.push(innerArr[j]) + } + } + newRowData.push(tempInnerArr) + } + + for (let i = 0; i < this.columns.length; i++) { + const element = this.columns[i] + if (!(columns.includes(element))) { + newColumnNames.push(element) + newDtypes.push(this.dtypes[i]) + } + } + + if (inplace) { + this.$setValues(newRowData, true, false) + this.$setColumnNames(newColumnNames) + } else { + const df = new DataFrame(newRowData, + { + index: [...this.index], + columns: newColumnNames, + dtypes: newDtypes, + }); + return df; + } + + } + + if (index) { + const rowIndices: Array = [] + + if (typeof index === "string" || typeof index === "number" || typeof index === "boolean") { + rowIndices.push(this.index.indexOf(index)) + } else if (Array.isArray(index)) { + for (const indx of index) { + if (this.index.indexOf(indx) === -1) { + throw Error(`ParamError: specified index "${indx}" not found in indices`); + } + rowIndices.push(this.index.indexOf(indx)); + } + } else { + throw Error('ParamError: index must be an array of indices or a scalar index'); + } + + const newRowData: ArrayType2D = [] + const newIndex = [] + + for (let i = 0; i < this.values.length; i++) { + const innerArr = this.values[i] as ArrayType1D + if (!(rowIndices.includes(i))) { + newRowData.push(innerArr) + } + } + + for (let i = 0; i < this.index.length; i++) { + const indx = this.index[i] + if (!(index.includes(indx))) { + newIndex.push(indx) + } + } + + if (inplace) { + this.$setValues(newRowData, false) + this.$setIndex(newIndex) + } else { + const df = new DataFrame(newRowData, + { + index: newIndex, + columns: [...this.columns], + dtypes: [...this.dtypes], + }); + return df; + } + } + + } + + /** + * Sets the index of the DataFrame to the specified value. + * @param options.index An array of index values to set + * @param options.column A column name whose values set in place of the index + * @param options.drop Whether to drop the column whose index was set. Defaults to false + * @param options.inplace Boolean indicating whether to perform the operation inplace or not. Defaults to false + * @example + * ``` + * const df = new DataFrame([[1, 2], [3, 4]], { columns: ['A', 'B']}) + * const df2 = df.setIndex({ index: ['a', 'b'] }) + * df2.print() + * ``` + * + * @example + * ``` + * const df = new DataFrame([[1, 2], [3, 4]], { columns: ['A', 'B']}) + * df.setIndex({ column: "A", inplace: true }) + * df.print() + * ``` + */ + setIndex( + options: + { + index?: Array, + column?: string, + drop?: boolean, + inplace?: boolean + } + ): DataFrame + setIndex( + options: + { + index?: Array, + column?: string, + drop?: boolean, + inplace?: boolean + } + ): DataFrame | void { + const { index, column, drop, inplace } = { drop: false, inplace: false, ...options } + + if (!index && !column) { + throw new Error("ParamError: must specify either index or column") + } + + let newIndex: Array = []; + + if (index) { + if (!Array.isArray(index)) { + throw Error(`ParamError: index must be an array`); + } + + if (index.length !== this.values.length) { + throw Error(`ParamError: index must be the same length as the number of rows`); + } + newIndex = index; + } + + if (column) { + if (this.columns.indexOf(column) === -1) { + throw Error(`ParamError: column not found in column names`); + } + + newIndex = this.$getColumnData(column, false) as Array + } + + if (drop) { + const dfDropped = this.drop({ columns: [column as string] }) + + const newData = dfDropped?.values as ArrayType2D + const newColumns = dfDropped?.columns + const newDtypes = dfDropped?.dtypes + + if (inplace) { + this.$setValues(newData, true, false) + this.$setIndex(newIndex) + this.$setColumnNames(newColumns) + } else { + const df = new DataFrame(newData, + { + index: newIndex, + columns: newColumns, + dtypes: newDtypes, + }); + return df; + } + } else { + if (inplace) { + this.$setIndex(newIndex) + } else { + const df = new DataFrame(this.values, + { + index: newIndex, + columns: [...this.columns], + dtypes: [...this.dtypes], + }); + return df; + } + } + + } + + /** + * Sorts the Dataframe by the index. + * @param options.inplace Boolean indicating whether to perform the operation inplace or not. Defaults to false + * @param options.ascending Whether to sort values in ascending order or not. Defaults to true + * @example + * ``` + * const df = new DataFrame([[1, 2], [3, 4], [1, 2], [5, 6]], { columns: ['A', 'B'] }) + * const df2 = df.sortIndex() + * df2.print() + * ``` + * + * @example + * ``` + * const df = new DataFrame([[1, 2], [3, 4], [1, 2], [5, 6]], { columns: ['A', 'B'] }) + * df.sortIndex({ inplace: true }) + * df.print() + * ``` + * + * @example + * ``` + * const df = new DataFrame([[1, 2], [3, 4], [1, 2], [5, 6]], { columns: ['A', 'B'] }) + * df.sortIndex({ ascending: false, inplace: true }) + * df.print() + * ``` + */ + sortIndex(options?: + { + inplace?: boolean + ascending?: boolean + } + ): DataFrame + sortIndex(options?: + { + inplace?: boolean + ascending?: boolean + } + ): DataFrame | void { + const { ascending, inplace } = { ascending: true, inplace: false, ...options } + + const indexPosition = NDframe.utils.range(0, this.index.length - 1) + const index = [...this.index] + + const objToSort = index.map((idx, i) => { + return { index: indexPosition[i], value: idx } + }) + + const sortedObjectArr = NDframe.utils.sortObj(objToSort, ascending) + let sortedIndex = sortedObjectArr.map((obj) => obj.index); + const newData = sortedIndex.map(i => (this.values as ArrayType2D)[i as number]) + sortedIndex = sortedIndex.map((i) => index[i as number]); + + if (inplace) { + this.$setValues(newData) + this.$setIndex(sortedIndex) + } else { + return new DataFrame(newData, { + index: sortedIndex, + columns: [...this.columns], + dtypes: [...this.dtypes] + }) + } + + } + + /** + * Apply a function along an axis of the DataFrame. To apply a function element-wise, use `applyMap`. + * Objects passed to the function are Series values whose + * index is either the DataFrame’s index (axis=0) or the DataFrame’s columns (axis=1) + * @param callable Function to apply to each column or row. + * @param options.axis 0 or 1. If 0, apply "callable" column-wise, else apply row-wise + * + * @example + * ``` + * const df = new DataFrame([[1, 2], [3, 4]], { columns: ['A', 'B']}) + * const df2 = df.apply(Math.sqrt, { axis: 0 }) + * df2.print() + * ``` + */ + apply(callable: any, options?: { axis?: 0 | 1 }): DataFrame | Series { + const { axis } = { axis: 1, ...options } + + if ([0, 1].indexOf(axis) === -1) { + throw Error(`ParamError: axis must be 0 or 1`); + } + + const valuesForFunc = this.$getDataByAxisWithMissingValuesRemoved(axis) + + const result = valuesForFunc.map(row => { + return callable(row) + }) + + if (axis === 0) { + if (NDframe.utils.is1DArray(result)) { + return new Series(result, { + index: [...this.columns] + }) + } else { + return new DataFrame(result, { + index: [...this.columns], + columns: [...this.columns], + dtypes: [...this.dtypes] + }) + } + } else { + if (NDframe.utils.is1DArray(result)) { + return new Series(result, { + index: [...this.index] + }) + } else { + return new DataFrame(result, { + index: [...this.index], + columns: [...this.columns], + dtypes: [...this.dtypes] + }) + } + } + } +} diff --git a/src/ndframe/ndframe.ts b/src/ndframe/ndframe.ts new file mode 100644 index 0000000..eade091 --- /dev/null +++ b/src/ndframe/ndframe.ts @@ -0,0 +1,522 @@ +/** + * @license + * Copyright 2022 JsData. All rights reserved. + * + * This source code is licensed under the MIT license found in the + * LICENSE file in the root directory of this source tree. + + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + * ========================================================================== + */ + +import Utils from '../utils/utils'; +import { ArrayType1D, ArrayType2D } from "../utils/arrays"; + +export interface NdframeInputDataType { + data: any + type?: number; + index?: Array + columns?: string[] + dtypes?: Array + isSeries: boolean; +} + +/** + * N-Dimension data structure. Stores multi-dimensional + * data in a size-mutable, labeled data structure. Analogous to the Python Pandas DataFrame. + * + * @param Object + * + * data: 1D or 2D Array, JSON, Tensor, Block of data. + * + * index: Array of numeric or string names for subseting array. If not specified, indexes are auto generated. + * + * columns: Array of column names. If not specified, column names are auto generated. + * + * dtypes: Array of data types for each the column. If not specified, dtypes inferred. + * + * config: General configuration object for NDframe + * + * @returns NDframe + */ +export default class NDframe { + static DATA_TYPES = ["float32", "int32", "string", "boolean", "datetime",'undefined']; + static utils = new Utils(); + $isSeries: boolean; + protected $data: any + protected $dataIncolumnFormat: ArrayType1D | ArrayType2D = [] + protected $index: Array = [] + protected $columns: string[] = [] + protected $dtypes: Array = [] + + constructor({ data, index, columns, dtypes, isSeries }: NdframeInputDataType) { + this.$isSeries = isSeries + + if (data === undefined || (Array.isArray(data) && data.length === 0)) { + if (columns === undefined) columns = []; + if (dtypes === undefined) dtypes = []; + if (columns.length === 0 && dtypes.length !== 0) { + const msg = `DtypeError: columns parameter must be provided when dtypes parameter is provided` + throw new Error(msg) + } + this.loadArrayIntoNdframe({ data: [], index: [], columns: columns, dtypes: dtypes }); + } else if (NDframe.utils.is1DArray(data)) { + this.loadArrayIntoNdframe({ data, index, columns, dtypes }); + } else { + if (Array.isArray(data) && NDframe.utils.isObject(data[0])) { + this.loadObjectIntoNdframe({ data, type: 1, index, columns, dtypes }); + + } else if (NDframe.utils.isObject(data)) { + this.loadObjectIntoNdframe({ data, type: 2, index, columns, dtypes }); + + } else if ( + Array.isArray((data)[0]) || + NDframe.utils.isNumber((data)[0]) || + NDframe.utils.isString((data)[0]) + ) { + this.loadArrayIntoNdframe({ data, index, columns, dtypes }); + } else if (Array.isArray(data) && data.length > 0 && NDframe.utils.isDate(data[0])) { + this.loadArrayIntoNdframe({ data, index, columns, dtypes }); + } else { + throw new Error("File format not supported!"); + } + } + } + + /** + * Internal function to load array of data into NDFrame + * @param data The array of data to load into NDFrame + * @param index Array of numeric or string names for subsetting array. + * @param columns Array of column names. + * @param dtypes Array of data types for each the column. + */ + private loadArrayIntoNdframe({ data, index, columns, dtypes }: any): void { + // this.$data = utils.replaceUndefinedWithNaN(data, this.$isSeries); + this.$data = data + /*if (!this.$config.isLowMemoryMode) {*/ + //In NOT low memory mode, we transpose the array and save in column format. + //This makes column data retrieval run in constant time + this.$dataIncolumnFormat = NDframe.utils.transposeArray(data) + //} + this.$setIndex(index); + this.$setDtypes(dtypes); + this.$setColumnNames(columns); + } + + /** + * Internal function to format and load a Javascript object or object of arrays into NDFrame. + * @param data Object or object of arrays. + * @param type The type of the object. There are two recognized types: + * + * - type 1 object are in JSON format `[{a: 1, b: 2}, {a: 30, b: 20}]`. + * + * - type 2 object are of the form `{a: [1,2,3,4], b: [30,20, 30, 20}]}` + * @param index Array of numeric or string names for subsetting array. + * @param columns Array of column names. + * @param dtypes Array of data types for each the column. + */ + private loadObjectIntoNdframe({ data, type, index, columns, dtypes }: any): void { + if (type === 1 && Array.isArray(data)) { + const _data = (data).map((item) => { + return Object.values(item); + }); + + let _columnNames; + + if (columns) { + _columnNames = columns + } else { + _columnNames = Object.keys((data)[0]); + } + + this.loadArrayIntoNdframe({ data: _data, index, columns: _columnNames, dtypes }); + + } else { + const [_data, _colNames] = NDframe.utils.getRowAndColValues(data); + let _columnNames; + + if (columns) { + _columnNames = columns + } else { + _columnNames = _colNames + } + this.loadArrayIntoNdframe({ data: _data, index, columns: _columnNames, dtypes }); + } + } + + /** + * Returns the dtypes of the columns + */ + get dtypes(): Array { + return this.$dtypes + } + + /** + * Internal function to set the Dtypes of the NDFrame from an array. This function + * performs the necessary checks. + */ + $setDtypes(dtypes: Array | undefined): void { + if (this.$isSeries) { + if (dtypes) { + if (this.$data.length != 0 && dtypes.length != 1) { + const msg = `DtypeError: You provided a dtype array of length ${dtypes.length} but Ndframe columns has length of ${this.shape[1]}` + throw new Error(msg) + } + + if (!(NDframe.DATA_TYPES.includes(`${dtypes[0]}`))) { + const msg = `DtypeError: Dtype "${dtypes[0]}" not supported. dtype must be one of "${NDframe.DATA_TYPES}"` + throw new Error(msg) + } + + this.$dtypes = dtypes + } else { + this.$dtypes = NDframe.utils.inferDtype(this.$data) + } + + } else { + if (dtypes) { + if (this.$data.length != 0 && dtypes.length != this.shape[1]) { + const msg = `DtypeError: You provided a dtype array of length ${dtypes.length} but Ndframe columns has length of ${this.shape[1]}` + throw new Error(msg) + } + + if (this.$data.length == 0 && dtypes.length == 0) { + this.$dtypes = dtypes + } else { + dtypes.forEach((dtype) => { + if (!(NDframe.DATA_TYPES.includes(dtype))) { + const msg = `DtypeError: Dtype "${dtype}" not supported. dtype must be one of "${NDframe.DATA_TYPES}"` + throw new Error(msg) + } + }) + + this.$dtypes = dtypes + + } + + } else { + this.$dtypes = NDframe.utils.inferDtype(this.$data) + } + } + } + + /** + * Returns the dimension of the data. Series have a dimension of 1, + * while DataFrames have a dimension of 2. + */ + /*get ndim(): number { + if (this.$isSeries) { + return 1; + } else { + return 2 + } + }*/ + + /** + * Returns the axis labels of the NDFrame. + *//* + get axis(): AxisType { + return { + index: this.$index, + columns: this.$columns + }; + }*/ + + /** + * Returns the indices of the NDFrame + */ + get index(): Array { + return this.$index + + } + + /** + * Internal function to set the index of the NDFrame with the specified + * array of indices. Performs all necessary checks to ensure that the + * index is valid. + */ + $setIndex(index: Array | undefined): void { + if (index) { + + if (this.$data.length != 0 && index.length != this.shape[0]) { + const msg = `IndexError: You provided an index of length ${index.length} but Ndframe rows has length of ${this.shape[0]}` + throw new Error(msg) + } + if (Array.from(new Set(index)).length !== this.shape[0]) { + const msg = `IndexError: Row index must contain unique values` + throw new Error(msg) + } + + this.$index = index + } else { + this.$index = NDframe.utils.range(0, this.shape[0] - 1) //generate index + } + } + + /** + * Internal function to reset the index of the NDFrame using a range of indices. + */ + $resetIndex(): void { + this.$index = NDframe.utils.range(0, this.shape[0] - 1) + } + + /** + * Returns the column names of the NDFrame + */ + get columns(): string[] { + return this.$columns + } + + /** + * Internal function to set the column names for the NDFrame. This function + * performs a check to ensure that the column names are unique, and same length as the + * number of columns in the data. + */ + $setColumnNames(columns?: string[]) { + + // console.log(columns); + if (this.$isSeries) { + if (columns) { + if (this.$data.length != 0 && columns.length != 1 && typeof columns != 'string') { + const msg = `ParamError: Column names length mismatch. You provided a column of length ${columns.length} but Ndframe columns has length of ${this.shape[1]}` + throw new Error(msg) + } + this.$columns = columns + } else { + this.$columns = ["0"] + } + } else { + if (columns) { + if (this.$data.length != 0 && columns.length != this.shape[1]) { + const msg = `ParamError: Column names length mismatch. You provided a column of length ${columns.length} but Ndframe columns has length of ${this.shape[1]}` + throw new Error(msg) + } + if (Array.from(new Set(columns)).length !== columns.length) { + const msg = `ColumnIndexError: Column index must contain unique values` + throw new Error(msg) + } + + this.$columns = columns + } else { + this.$columns = (NDframe.utils.range(0, this.shape[1] - 1)).map((val) => `${val}`) //generate columns + } + } + } + + /** + * Returns the shape of the NDFrame. Shape is determined by [row length, column length] + */ + get shape(): Array { + if (this.$data.length === 0) { + if (this.$columns.length === 0) return [0, 0]; + else return [0, this.$columns.length]; + } + if (this.$isSeries) { + return [this.$data.length, 1]; + } else { + const rowLen = (this.$data).length + const colLen = (this.$data[0] as []).length + return [rowLen, colLen] + } + } + + /** + * Returns the underlying data in Array format. + */ + get values(): ArrayType1D | ArrayType2D { + return this.$data; + } + + /** + * Updates the internal $data property to the specified value + * @param values An array of values to set + * @param checkLength Whether to check the length of the new values and the existing row length + * @param checkColumnLength Whether to check the length of the new values and the existing column length + * */ + $setValues(values: ArrayType1D | ArrayType2D, checkLength = true, checkColumnLength = true): void { + if (this.$isSeries) { + if (checkLength && values.length != this.shape[0]) { + const msg = `ParamError: Row data length mismatch. You provided data with length ${values.length} but Ndframe has row of length ${this.shape[0]}` + throw new Error(msg) + } + + this.$data = values + this.$dtypes = NDframe.utils.inferDtype(values) //Dtype may change depeneding on the value set + this.$dataIncolumnFormat = values + + } else { + if (checkLength && values.length != this.shape[0]) { + const msg = `ParamError: Row data length mismatch. You provided data with length ${values.length} but Ndframe has row of length ${this.shape[0]}` + throw new Error(msg) + } + + if (checkColumnLength) { + values.forEach(value => { + if ((value as ArrayType1D).length != this.shape[1]) { + const msg = `ParamError: Column data length mismatch. You provided data with length ${values.length} but Ndframe has column of length ${this.shape[0]}` + throw new Error(msg) + } + }) + } + + this.$data = values + this.$dtypes = NDframe.utils.inferDtype(values) + this.$dataIncolumnFormat = NDframe.utils.transposeArray(values) + } + } + + /** + * Returns the underlying data in Array column format. + * Similar to this.values, but in column format. + *//* + get getColumnData() { + if (this.config.isLowMemoryMode) { + return utils.transposeArray(this.values); + } else { + return this.$dataIncolumnFormat; + } + }*/ + + /** + * Returns the size of the NDFrame object + * + */ + get size(): number { + return this.shape[0] * this.shape[1] + } + + /** + * Converts a DataFrame or Series to CSV. + * @deprecated Use `toCSV` function directly instead. + * @example + * ``` + * import * as dfd from "danfojs" + * const df = new dfd.DataFrame([[1, 2, 3], [4, 5, 6]]) + * const csv = dfd.toCSV(df) + * ``` + * @example + * ``` + * import { toCSV } from "danfojs-node" + * const df = new DataFrame([[1, 2, 3], [4, 5, 6]]) + * toCSV(df, { + * filePath: "./data/sample.csv", + * header: true, + * sep: "+" + * }) + *//* + toCSV(options?: any): string | void { + throw new Error("`toCSV` function is deprecated. Use `toCSV` function directly instead. e.g. `dfd.toCSV(df)`") + }*/ + + /** + * Converts a DataFrame or Series to JSON. + * deprecated Use `toJSON` function directly instead. + * @example + * ``` + * import * as dfd from "danfojs-node" + * const df = new dfd.DataFrame([[1, 2, 3], [4, 5, 6]]) + * const json = dfd.toJSON(df) + * ``` + * @example + * ``` + * import { toJSON } from "danfojs-node" + * const df = new DataFrame([[1, 2, 3], [4, 5, 6]]) + * toJSON(df, { + * filePath: "./data/sample.json", + * format: "row" + * }) + * ``` + */ + toJSON(options?: any): object | void { + //let { fileName, format, download } = { fileName: "output.json", download: false, format: "column", ...options } + + if (this.$isSeries) { + const obj: { [key: string]: ArrayType1D } = {}; + obj[this.columns[0]] = this.values as ArrayType1D; + + /*if (download) { + if (!fileName.endsWith(".json")) { + fileName = fileName + ".json" + } + $downloadFileInBrowser(obj, fileName) + } else { + return obj + }*/ + + } else { + /*if (format === "row") { + const obj: { [key: string]: ArrayType1D } = {}; + for (let i = 0; i < df.columns.length; i++) { + obj[df.columns[i]] = (df as DataFrame).column(df.columns[i]).values as ArrayType1D; + } + if (download) { + if (!(fileName.endsWith(".json"))) { + fileName = fileName + ".json" + } + + $downloadFileInBrowser(obj, fileName) + } else { + return obj + } + } else {*/ + const values = this.values as ArrayType2D + const header = this.columns + const jsonArr: any = []; + + values.forEach((val) => { + const obj: any = {}; + header.forEach((h: any, i: any) => { + obj[h] = val[i] + }); + jsonArr.push(obj); + }); + /*if (download) { + if (!fileName.endsWith(".json")) { + fileName = fileName + ".json" + } + $downloadFileInBrowser(jsonArr, fileName) + } else {*/ + return jsonArr + //} + //} + } + } + + /** + * Converts a DataFrame or Series to Excel. + * @deprecated Use `toExcel` function directly instead. + * @example + * ``` + * import * as dfd from "danfojs" + * const df = new dfd.DataFrame([[1, 2, 3], [4, 5, 6]]) + * dfd.toExcel(df, { + * filePath: "./data/sample.xlsx", + * sheetName: "MySheet", + * }) + * ``` + * + * @example + * ``` + * import { toExcel } from "danfojs-node" + * const df = new DataFrame([[1, 2, 3], [4, 5, 6]]) + * toExcel(df, { + * filePath: "./data/sample.xlsx", + * sheetName: "MySheet", + * }) + * ``` + *//* + toExcel(options?: any): void { + throw new Error("Deprecated. Use `toExcel` function directly instead. e.g. `dfd.toExcel(df, {filePath: 'path/to/file.xlsx'})`") + }*/ + + /** + * Pretty prints a DataFrame or Series to the console + */ + print() { + console.log(this + ""); + } +} diff --git a/src/ndframe/series.ts b/src/ndframe/series.ts new file mode 100644 index 0000000..bd17c49 --- /dev/null +++ b/src/ndframe/series.ts @@ -0,0 +1,2448 @@ +/** + * @license + * Copyright 2022 JsData. All rights reserved. + * + * This source code is licensed under the MIT license found in the + * LICENSE file in the root directory of this source tree. + + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + * ========================================================================== + */ + +import { table } from 'table'; +import { ArrayType1D } from '../utils/arrays'; +import NDframe from './ndframe'; + +type mapFunc = (val: any, i: number) => any[] + +type mapParam = object | mapFunc + + +/** + * One-dimensional ndarray with axis labels. + * The object supports both integer- and label-based indexing and provides a host of methods for performing operations involving the index. + * Operations between Series (+, -, /, , *) align values based on their associated index values – they need not be the same length. + * @param data 1D Array, JSON, Tensor, Block of data. + * @param options.index Array of numeric or string index for subseting array. If not specified, indices are auto generated. + * @param options.columns Column name. This is like the name of the Series. If not specified, column name is set to 0. + * @param options.dtypes Data types of the Series data. If not specified, dtypes is inferred. + * @param options.config General configuration object for extending or setting Series behavior. + */ +export default class Series extends NDframe { + maxRow: number + constructor(data: any = [], options: /*BaseDataOptionType*/ any = {}) { + const { index, columns, dtypes, config } = options; + if (Array.isArray(data[0]) || NDframe.utils.isObject(data[0])) { + data = NDframe.utils.convert2DArrayToSeriesArray(data); + super({ + data, + index, + columns, + dtypes, + isSeries: true + }); + } else { + super({ + data, + index, + columns, + dtypes, + isSeries: true + }); + } + this.maxRow = 10; + } + + setMaxRow(maxRow: number) { + this.maxRow = maxRow; + } + + /** + * Purely integer-location based indexing for selection by position. + * ``.iloc`` is primarily integer position based (from ``0`` to + * ``length-1`` of the axis), but may also be used with a boolean array. + * + * @param rows Array of row indexes + * + * Allowed inputs are in rows and columns params are: + * + * - An array of single integer, e.g. ``[5]``. + * - A list or array of integers, e.g. ``[4, 3, 0]``. + * - A slice array string with ints, e.g. ``["1:7"]``. + * - A boolean array. + * - A ``callable`` function with one argument (the calling Series or + * DataFrame) and that returns valid output for indexing (one of the above). + * This is useful in method chains, when you don't have a reference to the + * calling object, but would like to base your selection on some value. + * + * ``.iloc`` will raise ``IndexError`` if a requested indexer is + * out-of-bounds. + * + * @example + * ``` + * const sf = new Series([1, 2, 3, 4, 5, 6], { index: ['a', 'b', 'c', 'd', 'e', 'f'] }); + * const sf2 = sf.iloc([0, 2, 4]); + * sf2.print(); + * ``` + */ + iloc(rows: Array): Series { + /** + * Generates an array of integers between specified range + * @param start The starting number. + * @param end The ending number. + */ + function range(start: number, end: number): Array { + if (end < start) { + throw new Error("ParamError: end must be greater than start") + } + + if (start === end) { + return [start] + } + + const arr = []; + for (let i = start; i <= end; i++) { + arr.push(i); + } + return arr; + } + + let _rowIndexes: Array + + const _data = this.values; + const _index = this.index; + + if (rows instanceof Series) { + rows = rows.values as Array + } + + if (rows !== undefined && !Array.isArray(rows)) { + throw new Error(`rows parameter must be an Array. For example: rows: [1,2] or rows: ["0:10"]`) + } + + if (!rows) { + _rowIndexes = range(0, this.shape[0] - 1); + + } else if (rows.length == 1 && typeof rows[0] == "string") { + const rowSplit = rows[0].split(":") + + if (rowSplit.length != 2) { + throw new Error(`Invalid row split parameter: If using row split string, it must be of the form; rows: ["start:end"]`); + } + if (isNaN(parseInt(rowSplit[0])) && rowSplit[0] != "") { + throw new Error(`Invalid row split parameter. Split parameter must be a number`); + } + + if (isNaN(parseInt(rowSplit[1])) && rowSplit[1] != "") { + throw new Error(`Invalid row split parameter. Split parameter must be a number`); + } + + const start = rowSplit[0] == "" ? 0 : parseInt(rowSplit[0]) + const end = rowSplit[1] == "" ? this.shape[0] : parseInt(rowSplit[1]) + + if (start < 0) { + throw new Error(`row slice [start] index cannot be less than 0`); + } + + if (end > this.shape[0]) { + throw new Error(`row slice [end] index cannot be bigger than ${this.shape[0]}`); + } + //_rowIndexes = utils.range(start, end - 1) + _rowIndexes = range(start, end - 1) + } else { + const _formatedRows = [] + for (let i = 0; i < rows.length; i++) { + const _indexToUse = rows[i]; + if (_indexToUse > this.shape[0]) { + throw new Error(`Invalid row parameter: Specified index ${_indexToUse} cannot be bigger than index length ${this.shape[0]}`); + } + + if (typeof _indexToUse !== "number" && typeof _indexToUse !== "boolean") { + throw new Error(`Invalid row parameter: row index ${_indexToUse} must be a number or boolean`); + } + + if (typeof _indexToUse === "boolean" && _indexToUse === true) { + _formatedRows.push(_index[i]) + } + + if (typeof _indexToUse === "number") { + _formatedRows.push(_indexToUse) + } + } + _rowIndexes = _formatedRows as number[] + } + + //_columnIndexes = utils.range(0, ndFrame.shape[1] - 1) + const _columnIndexes = range(0, this.shape[1] - 1) + const newData = [] + const newIndex = [] + + for (let i = 0; i < _rowIndexes.length; i++) { + const rowIndx = _rowIndexes[i] + newData.push(_data[rowIndx]) + newIndex.push(_index[rowIndx]) + } + const sf = new Series( + newData, + { + index: newIndex, + columns: this.columns, + dtypes: this.dtypes, + }); + return sf + } + + /** + * Access a group of rows by label(s) or a boolean array. + * ``loc`` is primarily label based, but may also be used with a boolean array. + * + * @param rows Array of row indexes + * + * Allowed inputs are: + * + * - A single label, e.g. ``["5"]`` or ``['a']``, (note that ``5`` is interpreted as a + * *label* of the index, and **never** as an integer position along the index). + * + * - A list or array of labels, e.g. ``['a', 'b', 'c']``. + * + * - A slice object with labels, e.g. ``["a:f"]``. Note that start and the stop are included + * + * - A boolean array of the same length as the axis being sliced, + * e.g. ``[True, False, True]``. + * + * - A ``callable`` function with one argument (the calling Series or + * DataFrame) and that returns valid output for indexing (one of the above) + * + * @example + * ``` + * const sf = new Series([1, 2, 3, 4, 5, 6], { index: ['a', 'b', 'c', 'd', 'e', 'f'] }); + * const sf2 = sf.loc(['a', 'c', 'e']); + * sf2.print(); + * ``` + * + * @example + * ``` + * const sf = new Series([1, 2, 3, 4, 5, 6], { index: ['a', 'b', 'c', 'd', 'e', 'f'] }); + * const sf2 = sf.loc(sf.gt(2)); + * sf2.print(); + * ``` + */ + loc(rows: Array): Series { + + let _rowIndexes: Array + + const _data = this.values; + const _index = this.index; + + if (rows instanceof Series) { + rows = rows.values as Array + } + + if (rows !== undefined && !Array.isArray(rows)) { + throw new Error(`rows parameter must be an Array. For example: rows: [1,2] or rows: ["0:10"]`) + } + + if (!rows) { + _rowIndexes = _index.map(indexValue => _index.indexOf(indexValue)) // Return all row index + + } else if (rows.length == 1 && typeof rows[0] == "string") { + + if (rows[0].indexOf(":") === -1) { // Input type ==> ["1"] or [`"1"`] + let temp; + if (rows[0].startsWith(`"`) || rows[0].startsWith(`'`) || rows[0].startsWith("`")) { + temp = _index.indexOf(rows[0].replace(/['"`]/g, '')) + } else { + temp = _index.indexOf(Number(rows[0])) + } + + if (temp === -1) { + throw new Error(`IndexError: Specified index (${rows[0]}) not found`); + } + + _rowIndexes = [temp] + + } else { + // Input type ==> ["1:2"] or [`"1":"4"`] + const rowSplit = rows[0].split(":") + + if (rowSplit.length != 2) { + throw new Error(`Invalid row split parameter: If using row split string, it must be of the form; rows: ["start:end"]`); + } + + let start: number + let end: number + + if (rowSplit[0] === "") { + start = _index.indexOf(_index[0]) + } else { + if (rowSplit[0].startsWith(`"`) || rowSplit[0].startsWith(`'`) || rowSplit[0].startsWith("`")) { + start = _index.indexOf(rowSplit[0].replace(/['"`]/g, '')) + } else { + start = _index.indexOf(Number(rowSplit[0])) + } + + } + + if (rowSplit[1] === "") { + end = _index.indexOf(_index[_index.length - 1]) + 1 + } else { + if (rowSplit[0].startsWith(`"`) || rowSplit[0].startsWith(`'`) || rowSplit[0].startsWith("`")) { + end = _index.indexOf(rowSplit[1].replace(/['"`]/g, '')) + } else { + end = _index.indexOf(Number(rowSplit[1])) + } + + } + + if (start === -1) { + throw new Error(`IndexError: Specified start index not found`); + } + + if (end === -1) { + throw new Error(`IndexError: Specified end index not found`); + } + + _rowIndexes = _index.slice(start, end).map(indexValue => _index.indexOf(indexValue)) + } + + } else { + // Input type ==> ["1", "2"] or [1, 5] or [true, false] + const rowsIndexToUse = [] + for (let i = 0; i < rows.length; i++) { + const isBoolean = typeof rows[i] === "boolean" + if (isBoolean && rows[i]) { + rowsIndexToUse.push(_index.indexOf(_index[i])) + } + + if (!isBoolean) { + const rowIndex = _index.indexOf(rows[i] as number | string) + if (rowIndex === -1) { + throw new Error(`IndexError: Specified index (${rows[i]}) not found`); + } + rowsIndexToUse.push(rowIndex) + } + } + + _rowIndexes = rowsIndexToUse + } + + const _columnNames = this.columns + + const _columnIndexes = _columnNames.map(columnName => _columnNames.indexOf(columnName))// Return all column index + + const newData = [] + const newIndex = [] + + for (let i = 0; i < _rowIndexes.length; i++) { + const rowIndx = _rowIndexes[i] + newData.push(_data[rowIndx]) + newIndex.push(_index[rowIndx]) + } + const sf = new Series( + newData, + { + index: newIndex, + columns: this.columns, + dtypes: this.dtypes, + }); + return sf + } + + /** + * Returns the first n values in a Series + * @param rows The number of rows to return + * @example + * ``` + * const sf = new Series([1, 2, 3, 4, 5, 6], { index: ['a', 'b', 'c', 'd', 'e', 'f'] }); + * const sf2 = sf.head(3); + * sf2.print(); + * ``` + */ + head(rows = 5): Series { + if (rows <= 0) { + throw new Error("ParamError: Number of rows cannot be less than 1") + } + if (this.shape[0] <= rows) { + return this.copy() + } + if (this.shape[0] - rows < 0) { + throw new Error("ParamError: Number of rows cannot be greater than available rows in data") + } + return this.iloc([`0:${rows}`]) + } + + /** + * Returns the last n values in a Series + * @param rows The number of rows to return + * @example + * ``` + * const sf = new Series([1, 2, 3, 4, 5, 6], { index: ['a', 'b', 'c', 'd', 'e', 'f'] }); + * const sf2 = sf.tail(3); + * sf2.print(); + * ``` + */ + tail(rows = 5): Series { + if (rows <= 0) { + throw new Error("ParamError: Number of rows cannot be less than 1") + } + if (this.shape[0] <= rows) { + return this.copy() + } + if (this.shape[0] - rows < 0) { + throw new Error("ParamError: Number of rows cannot be greater than available rows in data") + } + + const startIdx = this.shape[0] - rows + return this.iloc([`${startIdx}:`]) + } + + /** + * Returns specified number of random rows in a Series + * @param num The number of rows to return + * @param options.seed An integer specifying the random seed that will be used to create the distribution. + * @example + * ``` + * const df = new Series([1, 2, 3, 4]) + * const df2 = await df.sample(2) + * df2.print() + * ``` + * @example + * ``` + * const df = new Series([1, 2, 3, 4]) + * const df2 = await df.sample(1, { seed: 1 }) + * df2.print() + * ``` + *//* + async sample(num = 5, options?: { seed?: number }): Promise { + const { seed } = { seed: 1, ...options } + + if (num > this.shape[0]) { + throw new Error("Sample size n cannot be bigger than size of dataset"); + } + if (num < -1 || num == 0) { + throw new Error("Sample size cannot be less than -1 or be equal to 0"); + } + num = num === -1 ? this.shape[0] : num; + + const shuffledIndex = await tensorflow.data.array(this.index).shuffle(num, `${seed}`).take(num).toArray(); + const sf = this.iloc(shuffledIndex); + return sf; + }*/ + + /** + * Return Addition of series and other, element-wise (binary operator add). + * Equivalent to series + other + * @param other Series, Array of same length or scalar number to add + * @param options.inplace Boolean indicating whether to perform the operation inplace or not. Defaults to false + * + * @example + * ``` + * const sf = new Series([1, 2, 3, 4, 5, 6], { index: ['a', 'b', 'c', 'd', 'e', 'f'] }); + * const sf2 = sf.add(2); + * console.log(sf2.values); + * //output [3, 4, 5, 6, 7, 8] + * ``` + * + * @example + * ``` + * const sf = new Series([1, 2, 3, 4, 5, 6], { index: ['a', 'b', 'c', 'd', 'e', 'f'] }); + * const sf2 = sf.add([2, 3, 4, 5, 6, 7]); + * console.log(sf2.values); + * //output [3, 5, 7, 9, 11, 13] + * ``` + * + * @example + * ``` + * const sf = new Series([1, 2, 3, 4, 5, 6], { index: ['a', 'b', 'c', 'd', 'e', 'f'] }); + * sf.add(2, { inplace: true }); + * console.log(sf.values); + * //output [3, 4, 5, 6, 7, 8] + * ``` + */ + add(other: Series | Array | number, options?: { inplace?: boolean }): Series + add(other: Series | Array | number, options?: { inplace?: boolean }): Series | void { + const { inplace } = { inplace: false, ...options } + + if (this.dtypes[0] == "string") { + throw new Error(`DtypeError: String data type does not support add operation`); + } + let newData; + if (typeof other === "number") { + newData = (this.values as number[]).map((ele => ele + other)) + } else if (other instanceof Series) { + this.checkSeriesOpCompatibility(other, 'add'); + newData = (this.values as number[]).map((ele, index) => { return ele + (other.values as number[])[index] }) + } else if (Array.isArray(other)) { + newData = (this.values as number[]).map((ele, index) => { return ele + (other as number[])[index] }) + } else { + throw new Error("ParamError: value for other not supported. It must be either a scalar, Array or Series"); + } + if (inplace) { + this.$setValues(newData as ArrayType1D) + } else { + return this.createNdframeFromNewDataWithOldProps({ newData }) + } + } + + /** + * Returns the subtraction between a series and other, element-wise (binary operator subtraction). + * Equivalent to series - other + * @param other Number to subtract + * @param options.inplace Boolean indicating whether to perform the operation inplace or not. Defaults to false + * @example + * ``` + * const sf = new Series([1, 2, 3, 4, 5, 6], { index: ['a', 'b', 'c', 'd', 'e', 'f'] }); + * const sf2 = sf.sub(2); + * console.log(sf2.values); + * //output [-1, 0, 1, 2, 3, 4] + * ``` + * + * @example + * ``` + * const sf = new Series([1, 2, 3, 4, 5, 6], { index: ['a', 'b', 'c', 'd', 'e', 'f'] }); + * const sf2 = sf.sub([2, 3, 4, 5, 6, 7]); + * console.log(sf2.values); + * //output [-1, -1, -1, -1, -1, -1] + * ``` + * + * @example + * ``` + * const sf = new Series([1, 2, 3, 4, 5, 6], { index: ['a', 'b', 'c', 'd', 'e', 'f'] }); + * sf.sub(2, { inplace: true }); + * console.log(sf.values); + * //output [-1, 0, 1, 2, 3, 4] + * ``` + */ + sub(other: Series | number | Array, options?: { inplace?: boolean }): Series + sub(other: Series | number | Array, options?: { inplace?: boolean }): Series | void { + const { inplace } = { inplace: false, ...options } + + if (this.dtypes[0] == "string") { + throw new Error(`DtypeError: String data type does not support sub operation`); + } + + let newData; + if (typeof other === "number") { + newData = (this.values as number[]).map((ele => ele - other)) + } else if (other instanceof Series) { + this.checkSeriesOpCompatibility(other, 'sub'); + newData = (this.values as number[]).map((ele, index) => { return ele - (other.values as number[])[index] }) + } else if (Array.isArray(other)) { + newData = (this.values as number[]).map((ele, index) => { return ele - (other as number[])[index] }) + } else { + throw new Error("ParamError: value for other not supported. It must be either a scalar, Array or Series"); + } + if (inplace) { + this.$setValues(newData as ArrayType1D) + } else { + return this.createNdframeFromNewDataWithOldProps({ newData }) + } + } + + /** + * Return Multiplication of series and other, element-wise (binary operator mul). + * Equivalent to series * other + * @param other Number to multiply with. + * @param options.inplace Boolean indicating whether to perform the operation inplace or not. Defaults to false + * @example + * ``` + * const sf = new Series([1, 2, 3, 4, 5, 6], { index: ['a', 'b', 'c', 'd', 'e', 'f'] }); + * const sf2 = sf.mul(2); + * console.log(sf2.values); + * //output [2, 4, 6, 8, 10, 12] + * ``` + * + * @example + * ``` + * const sf = new Series([1, 2, 3, 4, 5, 6], { index: ['a', 'b', 'c', 'd', 'e', 'f'] }); + * const sf2 = sf.mul([2, 3, 4, 5, 6, 7]); + * console.log(sf2.values); + * //output [2, 6, 12, 20, 30, 42] + * ``` + * + * @example + * ``` + * const sf = new Series([1, 2, 3, 4, 5, 6], { index: ['a', 'b', 'c', 'd', 'e', 'f'] }); + * sf.mul(2, { inplace: true }); + * console.log(sf.values); + * //output [2, 4, 6, 8, 10, 12] + * ``` + */ + mul(other: Series | number | Array, options?: { inplace?: boolean }): Series + mul(other: Series | number | Array, options?: { inplace?: boolean }): Series | void { + const { inplace } = { inplace: false, ...options } + + if (this.dtypes[0] == "string") { + throw new Error(`DtypeError: String data type does not support mul operation`); + } + + let newData; + if (typeof other === "number") { + newData = (this.values as number[]).map((ele => ele * other)) + } else if (other instanceof Series) { + this.checkSeriesOpCompatibility(other, 'mul'); + newData = (this.values as number[]).map((ele, index) => { return ele * (other.values as number[])[index] }) + } else if (Array.isArray(other)) { + newData = (this.values as number[]).map((ele, index) => { return ele * (other as number[])[index] }) + } else { + throw new Error("ParamError: value for other not supported. It must be either a scalar, Array or Series"); + } + if (inplace) { + this.$setValues(newData as ArrayType1D) + } else { + return this.createNdframeFromNewDataWithOldProps({ newData }) + } + } + + /** + * Return division of series and other, element-wise (binary operator div). + * Equivalent to series / other + * @param other Series or number to divide with. + * @param options.inplace Boolean indicating whether to perform the operation inplace or not. Defaults to false + * @example + * ``` + * const sf = new Series([1, 2, 3, 4, 5, 6], { index: ['a', 'b', 'c', 'd', 'e', 'f'] }); + * const sf2 = sf.div(2); + * console.log(sf2.values); + * //output [0.5, 1, 1.5, 2, 2.5, 3] + * ``` + * + * @example + * ``` + * const sf = new Series([1, 2, 3, 4, 5, 6], { index: ['a', 'b', 'c', 'd', 'e', 'f'] }); + * const sf2 = sf.div([2, 3, 4, 5, 6, 7]); + * console.log(sf2.values); + * ``` + * + * @example + * ``` + * const sf = new Series([1, 2, 3, 4, 5, 6], { index: ['a', 'b', 'c', 'd', 'e', 'f'] }); + * sf.div(2, { inplace: true }); + * console.log(sf.values); + * //output [0.5, 1, 1.5, 2, 2.5, 3] + * ``` + */ + div(other: Series | number | Array, options?: { inplace?: boolean }): Series + div(other: Series | number | Array, options?: { inplace?: boolean }): Series | void { + const { inplace } = { inplace: false, ...options } + + if (this.dtypes[0] == "string") { + throw new Error(`DtypeError: String data type does not support div operation`); + } + + let newData; + if (typeof other === "number") { + newData = (this.values as number[]).map((ele => ele / other)) + } else if (other instanceof Series) { + this.checkSeriesOpCompatibility(other, 'div'); + newData = (this.values as number[]).map((ele, index) => { return ele / (other.values as number[])[index] }) + } else if (Array.isArray(other)) { + newData = (this.values as number[]).map((ele, index) => { return ele / (other as number[])[index] }) + } else { + throw new Error("ParamError: value for other not supported. It must be either a scalar, Array or Series"); + } + if (inplace) { + this.$setValues(newData as ArrayType1D) + } else { + return this.createNdframeFromNewDataWithOldProps({ newData }) + } + } + + /** + * Return Exponential power of series and other, element-wise (binary operator pow). + * Equivalent to series ** other + * @param other Number to raise to power. + * @param options.inplace Boolean indicating whether to perform the operation inplace or not. Defaults to false + * @example + * ``` + * const sf = new Series([1, 2, 3, 4, 5, 6], { index: ['a', 'b', 'c', 'd', 'e', 'f'] }); + * const sf2 = sf.pow(2); + * console.log(sf2.values); + * //output [1, 4, 9, 16, 25, 36] + * ``` + * + * @example + * ``` + * const sf = new Series([1, 2, 3, 4, 5, 6], { index: ['a', 'b', 'c', 'd', 'e', 'f'] }); + * const sf2 = sf.pow(new Series([2, 3, 4, 5, 6, 7])); + * console.log(sf2.values); + * //output [ 1, 8, 81, 1024, 15625, 279936 ] + * ``` + * + */ + pow(other: Series | number | Array, options?: { inplace?: boolean }): Series + pow(other: Series | number | Array, options?: { inplace?: boolean }): Series | void { + const { inplace } = { inplace: false, ...options } + + if (this.dtypes[0] == "string") { + throw new Error(`DtypeError: String data type does not support pow operation`); + } + + let newData; + if (typeof other === "number") { + newData = (this.values as number[]).map((ele => ele ** other)) + } else if (other instanceof Series) { + this.checkSeriesOpCompatibility(other, 'pow'); + newData = (this.values as number[]).map((ele, index) => { return ele ** (other.values as number[])[index] }) + } else if (Array.isArray(other)) { + newData = (this.values as number[]).map((ele, index) => { return ele ** (other as number[])[index] }) + } else { + throw new Error("ParamError: value for other not supported. It must be either a scalar, Array or Series"); + } + if (inplace) { + this.$setValues(newData as ArrayType1D) + } else { + return this.createNdframeFromNewDataWithOldProps({ newData }) + } + } + + /** + * Return Modulo of series and other, element-wise (binary operator mod). + * Equivalent to series % other + * @param other Number to modulo with + * @param options.inplace Boolean indicating whether to perform the operation inplace or not. Defaults to false + * @example + * ``` + * const sf = new Series([1, 2, 3, 4, 5, 6], { index: ['a', 'b', 'c', 'd', 'e', 'f'] }); + * const sf2 = sf.mod(2); + * console.log(sf2.values); + * //output [1, 0, 1, 0, 1, 0] + * ``` + */ + mod(other: Series | number | Array, options?: { inplace?: boolean }): Series + mod(other: Series | number | Array, options?: { inplace?: boolean }): Series | void { + const { inplace } = { inplace: false, ...options } + + if (this.dtypes[0] == "string") { + throw new Error(`DtypeError: String data type does not support mod operation`); + } + + let newData; + if (typeof other === "number") { + newData = (this.values as number[]).map((ele => ele % other)) + } else if (other instanceof Series) { + this.checkSeriesOpCompatibility(other, 'mod'); + newData = (this.values as number[]).map((ele, index) => { return ele % (other.values as number[])[index] }) + } else if (Array.isArray(other)) { + newData = (this.values as number[]).map((ele, index) => { return ele % (other as number[])[index] }) + } else { + throw new Error("ParamError: value for other not supported. It must be either a scalar, Array or Series"); + } + if (inplace) { + this.$setValues(newData as ArrayType1D) + } else { + return this.createNdframeFromNewDataWithOldProps({ newData }) + } + } + + /** + * Checks if the array value passed has a compatible dtype, removes NaN values, and if + * boolean values are present, converts them to integer values. + */ + private $checkAndCleanValues(values: ArrayType1D, operation: string): number[] { + if (this.dtypes[0] == "string") { + throw new Error(`DtypeError: String data type does not support ${operation} operation`); + } + values = NDframe.utils.removeMissingValuesFromArray(values); + + if (this.dtypes[0] == "boolean") { + values = (NDframe.utils.mapBooleansToIntegers(values as boolean[], 1) as ArrayType1D); + } + return values as number[] + } + + /** + * Returns the mean of elements in Series. + * @example + * ``` + * const sf = new Series([1, 2, 3, 4, 5, 6]); + * console.log(sf.mean()); + * //output 3.5 + * ``` + */ + mean(): number { + const values = this.$checkAndCleanValues(this.values as ArrayType1D, "mean") + return (values.reduce((a, b) => a + b) / values.length) as number + } + + /** + * Returns the minimum value in a Series + * @example + * ``` + * const sf = new Series([1, 2, 3, 4, 5, 6]); + * console.log(sf.min()); + * //output 1 + * ``` + * + */ + min(): number { + const values = this.$checkAndCleanValues(this.values as ArrayType1D, "min") + let smallestValue = values[0] + for (let i = 0; i < values.length; i++) { + smallestValue = smallestValue < values[i] ? smallestValue : values[i] + } + return smallestValue + } + + /** + * Returns the maximum value in a Series + * @example + * ``` + * const sf = new Series([1, 2, 3, 4, 5, 6]); + * console.log(sf.max()); + * //output 6 + * ``` + */ + max(): number { + const values = this.$checkAndCleanValues(this.values as ArrayType1D, "max") + let biggestValue = values[0] + for (let i = 0; i < values.length; i++) { + biggestValue = biggestValue > values[i] ? biggestValue : values[i] + } + return biggestValue + } + + /** + * Return sample standard deviation of elements in Series + * @example + * ``` + * const sf = new Series([1, 2, 3, 4, 5, 6]); + * console.log(sf.std()); + * //output 1.8708286933869707 + * ``` + */ + std(): number { + const values = this.$checkAndCleanValues(this.values as ArrayType1D, "std") + const n = values.length; + const mean = values.reduce((a, b) => a + b) / n; + return Math.sqrt( + values.map((x) => Math.pow(x - mean, 2)).reduce((a, b) => a + b) / (n - 1), + ); + } + + /** + * Return the sum of the values in a series. + * @example + * ``` + * const sf = new Series([1, 2, 3, 4, 5, 6]); + * console.log(sf.sum()); + * //output 21 + * ``` + */ + sum(): number { + const values = this.$checkAndCleanValues(this.values as ArrayType1D, "sum") + return values.reduce((sum, value) => sum + value, 0) + } + + /** + * Return number of non-null elements in a Series + * @example + * ``` + * const sf = new Series([1, 2, 3, 4, 5, 6]); + * console.log(sf.count()); + * //output 6 + * ``` + * + * @example + * ``` + * const sf = new Series([1, 2, 3, 4, 5, 6, NaN]); + * console.log(sf.count()); + * //output 6 + * ``` + */ + count(): number { + const values = NDframe.utils.removeMissingValuesFromArray(this.values as ArrayType1D) + return values.length + } + + /** + * Return maximum of series and other. + * @param other Series, number or Array of numbers to check against + * @example + * ``` + * const sf = new Series([1, 2, 3, 4, 5, 6]); + * const sf2 = sf.maximum(3); + * console.log(sf2.values); + * //output [ 3, 3, 3, 4, 5, 6 ] + * ``` + * + * @example + * ``` + * const sf = new Series([1, 2, 3, 4, 5, 6]); + * const sf2 = new Series([4, 1, 3, 40, 5, 3]); + * const sf3 = sf.maximum(sf2); + * console.log(sf3.values); + * //output [ 4, 2, 3, 40, 5, 6 ] + * ``` + */ + maximum(other: Series | number | Array): Series { + if (this.dtypes[0] == "string") { + throw new Error(`DtypeError: String data type does not support maximum operation`); + } + + let newData; + if (typeof other === "number") { + newData = (this.values as number[]).map((ele => Math.max(ele, other))) + } else if (other instanceof Series) { + this.checkSeriesOpCompatibility(other, 'maximum'); + newData = (this.values as number[]).map((ele, index) => { return Math.max(ele, (other.values as number[])[index]) }) + } else if (Array.isArray(other)) { + newData = (this.values as number[]).map((ele, index) => { return Math.max(ele, (other as number[])[index]) }) + } else { + throw new Error("ParamError: value for other not supported. It must be either a scalar, Array or Series"); + } + return new Series(newData, { + columns: this.columns, + index: this.index + }); + } + + /** + * Return minimum of series and other. + * @param other Series, number of Array of numbers to check against + * @example + * ``` + * const sf = new Series([1, 2, 3, 4, 5, 6]); + * const sf2 = sf.minimum(3); + * console.log(sf2.values); + * //output [ 1, 2, 3, 3, 3, 3 ] + * ``` + * + * @example + * ``` + * const sf = new Series([1, 2, 3, 4, 5, 6]); + * const sf2 = new Series([4, 1, 3, 40, 5, 3]); + * const sf3 = sf.minimum(sf2); + * console.log(sf3.values); + * //output [ 1, 1, 3, 4, 5, 3 ] + * ``` + * + */ + minimum(other: Series | number | Array): Series { + if (this.dtypes[0] == "string") { + throw new Error(`DtypeError: String data type does not support minimum operation`); + } + + let newData; + if (typeof other === "number") { + newData = (this.values as number[]).map((ele => Math.min(ele, other))) + } else if (other instanceof Series) { + this.checkSeriesOpCompatibility(other, 'maximum'); + newData = (this.values as number[]).map((ele, index) => { return Math.min(ele, (other.values as number[])[index]) }) + } else if (Array.isArray(other)) { + newData = (this.values as number[]).map((ele, index) => { return Math.min(ele, (other as number[])[index]) }) + } else { + throw new Error("ParamError: value for other not supported. It must be either a scalar, Array or Series"); + } + return new Series(newData, { + columns: this.columns, + index: this.index + }); + } + + /** + * Round each value in a Series to the specified number of decimals. + * @param dp Number of Decimal places to round to + * @param options.inplace Boolean indicating whether to perform the operation inplace or not. Defaults to false + * + * @example + * ``` + * const sf = new Series([1.23, 2.4, 3.123, 4.1234, 5.12345]); + * const sf2 = sf.round(2); + * console.log(sf2.values); + * //output [ 1.23, 2.4, 3.12, 4.12, 5.12 ] + * ``` + * + * @example + * ``` + * const sf = new Series([1.23, 2.4, 3.123, 4.1234, 5.12345]); + * sf.round(2, { inplace: true }); + * console.log(sf.values); + * //output [ 1.23, 2.4, 3.12, 4.12, 5.12 ] + * ``` + */ + round(dp?: number, options?: { inplace?: boolean }): Series + round(dp = 1, options?: { inplace?: boolean }): Series | void { + const { inplace } = { inplace: false, ...options } + if (dp === undefined) dp = 1; + const newValues = NDframe.utils.round(this.values as number[], dp, true); + + if (inplace) { + this.$setValues(newValues) + } else { + return this.createNdframeFromNewDataWithOldProps({ newData: newValues }) + } + } + + /** + * Return unbiased variance of elements in a Series. + * @example + * ``` + * const sf = new Series([1, 2, 3, 4, 5, 6]); + * console.log(sf.var()); + * //output 3.5 + * ``` + */ + var(): number { + const values = this.$checkAndCleanValues(this.values as ArrayType1D, "max") + return this.variance(values); + } + + /** + * Return a boolean same-sized object indicating where elements are NaN. + * NaN and undefined values gets mapped to true, and everything else gets mapped to false. + * @example + * ``` + * const sf = new Series([1, 2, 3, 4, NaN, 6]); + * console.log(sf.isNaN()); + * //output [ false, false, false, false, true, false ] + * ``` + * + */ + isNa(): Series { + const newData = this.values.map((value) => { + + if (NDframe.utils.isEmpty(value)) { + return true; + } else { + return false; + } + }) + const sf = new Series(newData, + { + index: this.index, + dtypes: ["boolean"] + }); + return sf; + } + + /** + * Replace all missing values with a specified value + * @param value The value to replace NaN with + * @param options.inplace Boolean indicating whether to perform the operation inplace or not. Defaults to false + * + * @example + * ``` + * const sf = new Series([1, 2, 3, 4, NaN, 6]); + * const sf2 = sf.fillNa(-99); + * console.log(sf2.values); + * //output [ 1, 2, 3, 4, -99, 6 ] + * ``` + * + * @example + * ``` + * const sf = new Series([1, 2, 3, 4, NaN, 6]); + * sf.fillNa(-99, { inplace: true }); + * console.log(sf.values); + * //output [ 1, 2, 3, 4, -99, 6 ] + * ``` + */ + fillNa(value: number | string | boolean, options?: { inplace?: boolean }): Series + fillNa(value: number | string | boolean, options?: { inplace?: boolean }): Series | void { + const { inplace } = { inplace: false, ...options } + + if (!value && typeof value !== "boolean" && typeof value !== "number") { + throw Error('ParamError: value must be specified'); + } + + const newValues: ArrayType1D = []; + (this.values as ArrayType1D).forEach((val) => { + if (NDframe.utils.isEmpty(val)) { + newValues.push(value); + } else { + newValues.push(val); + } + }); + + if (inplace) { + this.$setValues(newValues) + } else { + return this.createNdframeFromNewDataWithOldProps({ newData: newValues }); + } + } + + + /** + * Sort a Series in ascending or descending order by some criterion. + * @param options Method options + * @param ascending Whether to return sorted values in ascending order or not. Defaults to true + * @param options.inplace Boolean indicating whether to perform the operation inplace or not. Defaults to false + * @example + * ``` + * const sf = new Series([2, 1, 3, 4, 6, 5]); + * const sf2 = sf.sortValues(); + * console.log(sf2.values); + * //output [ 1, 2, 3, 4, 5, 6 ] + * ``` + */ + sortValues(options?: { ascending?: boolean, inplace?: boolean }): Series + sortValues(options?: { ascending?: boolean, inplace?: boolean }): Series | void { + const { ascending, inplace, } = { ascending: true, inplace: false, ...options } + + let sortedValues = []; + let sortedIndex = [] + const rangeIdx = NDframe.utils.range(0, this.index.length - 1); + const sortedIdx = NDframe.utils.sortArrayByIndex(rangeIdx, this.values, this.dtypes[0]); + + for (const indx of sortedIdx) { + sortedValues.push(this.values[indx]) + sortedIndex.push(this.index[indx]) + } + + if (ascending) { + sortedValues = sortedValues.reverse(); + sortedIndex = sortedIndex.reverse(); + } + + if (inplace) { + this.$setValues(sortedValues as ArrayType1D) + this.$setIndex(sortedIndex); + } else { + const sf = new Series(sortedValues, { + index: sortedIndex, + dtypes: this.dtypes, + }); + return sf; + + } + } + + + /** + * Makes a deep copy of a Series + * @example + * ``` + * const sf = new Series([1, 2, 3, 4, 5, 6]); + * const sf2 = sf.copy(); + * ``` + * + */ + copy(): Series { + const sf = new Series([...this.values], { + columns: [...this.columns], + index: [...this.index], + dtypes: [...this.dtypes], + }); + return sf; + } + + /** + * Resets the index of the Series to default values. + * @example + * ``` + * const sf = new Series([1, 2, 3, 4, 5, 6], { index: ['a', 'b', 'c', 'd', 'e', 'f'] }); + * const sf2 = sf.resetIndex(); + * console.log(sf2.index); + * //output [ 0, 1, 2, 3, 4, 5 ] + * ``` + * + * @example + * ``` + * const sf = new Series([1, 2, 3, 4, 5, 6], { index: ['a', 'b', 'c', 'd', 'e', 'f'] }); + * sf.resetIndex({ inplace: true }); + * console.log(sf.index); + * //output [ 0, 1, 2, 3, 4, 5 ] + * ``` + */ + resetIndex(options?: { inplace?: boolean }): Series + resetIndex(options?: { inplace?: boolean }): Series | void { + const { inplace } = { inplace: false, ...options } + + if (inplace) { + this.$resetIndex(); + } else { + const sf = this.copy(); + sf.$resetIndex(); + return sf; + } + } + + /** + * Set the Series index (row labels) using an array of the same length. + * @param index Array of new index values, + * @param options.inplace Boolean indicating whether to perform the operation inplace or not. Defaults to false + * @example + * ``` + * const sf = new Series([1, 2, 3, 4, 5, 6], { index: ['a', 'b', 'c', 'd', 'e', 'f'] }); + * const sf2 = sf.setIndex(['g', 'h', 'i', 'j', 'k', 'l']); + * console.log(sf2.index); + * //output [ 'g', 'h', 'i', 'j', 'k', 'l' ] + * ``` + */ + setIndex(index: Array, options?: { inplace?: boolean }): Series + setIndex(index: Array, options?: { inplace?: boolean }): Series | void { + const { inplace } = { inplace: false, ...options } + + if (!index) { + throw Error('Param Error: Must specify index array'); + } + + if (inplace) { + this.$setIndex(index) + } else { + const sf = this.copy(); + sf.$setIndex(index) + return sf; + } + } + + + /** + * map all the element in a Series to a function or object. + * @param callable callable can either be a funtion or an object. If function, then each value and the corresponding index is passed. + * @param options.inplace Boolean indicating whether to perform the operation inplace or not. Defaults to false + * @example + * ``` + * const sf = new Series([1, 2, 3, 4, 5, 6]); + * const sf2 = sf.map((x) => x * 2); + * console.log(sf2.values); + * //output [ 2, 4, 6, 8, 10, 12 ] + * ``` + * + * @example + * ``` + * const sf = new Series([1, 2, 3, 4, 5, 6]); + * const sf2 = sf.map({ + * 1: -99, + * 3: -99 + * }); + * console.log(sf2.values); + * //output [ -99, 2, -99, 4, -99, 6 ] + * ``` + */ + map(callable: mapParam, options?: { inplace?: boolean }): Series + map(callable: mapParam, options?: { inplace?: boolean }): Series | void { + const { inplace } = { inplace: false, ...options } + + const isCallable = NDframe.utils.isFunction(callable); + + const data = (this.values as ArrayType1D).map((val: any, i: number) => { + if (isCallable) { + return (callable as Function)(val, i); + } else if (NDframe.utils.isObject(callable)) { + if (val in callable) { + // eslint-disable-next-line @typescript-eslint/ban-ts-comment + //@ts-ignore + return callable[val]; + } else { + return val + } + } else { + throw new Error("Param Error: callable must either be a function or an object"); + } + }); + + if (inplace) { + this.$setValues(data) + } else { + const sf = this.copy(); + sf.$setValues(data) + return sf; + } + } + + /** + * Applies a function to each element of a Series + * @param callable Function to apply to each element of the series + * @param options.inplace Boolean indicating whether to perform the operation inplace or not. Defaults to false + * @example + * ``` + * const sf = new Series([1, 2, 3, 4, 5, 6]); + * const sf2 = sf.apply((x) => x * 2); + * console.log(sf2.values); + * //output [ 2, 4, 6, 8, 10, 12 ] + * ``` + * + * @example + * ``` + * const sf = new Series([1, 2, 3, 4, 5, 6]); + * sf.apply((x) => x * 2, { inplace: true }); + * console.log(sf.values); + * //output [ 2, 4, 6, 8, 10, 12 ] + * ``` + * + */ + apply(callable: (value: any) => any, options?: { inplace?: boolean }): Series + apply(callable: (value: any) => any, options?: { inplace?: boolean }): Series | void { + const { inplace } = { inplace: false, ...options } + + const isCallable = NDframe.utils.isFunction(callable); + if (!isCallable) { + throw new Error("Param Error: callable must be a function"); + } + + const data = this.values.map((val) => { + return callable(val); + }); + + if (inplace) { + this.$setValues(data) + } else { + const sf = this.copy(); + sf.$setValues(data) + return sf; + } + } + + /** + * Returns a Series with only the unique value(s) in the original Series + * @example + * ``` + * const sf = new Series([1, 2, 3, 4, 5, 6, 1, 2, 3, 4, 5, 6]); + * const sf2 = sf.unique(); + * console.log(sf2.values); + * //output [ 1, 2, 3, 4, 5, 6 ] + * ``` + */ + unique(): Series { + const newValues = new Set(this.values as ArrayType1D); + const series = new Series(Array.from(newValues)); + return series; + } + + /** + * Return the number of unique elements in a Series + * @example + * ``` + * const sf = new Series([1, 2, 3, 4, 5, 6, 1, 2, 3, 4, 5, 6]); + * console.log(sf.nUnique()); + * //output 6 + * ``` + * + */ + nUnique(): number { + return (new Set(this.values as ArrayType1D)).size; + } + + /** + * Returns unique values and their counts in a Series + * @example + * ``` + * const sf = new Series([1, 2, 3, 4, 5, 6, 1, 2, 3, 4, 5, 6]); + * const sf2 = sf.valueCounts(); + * sf2.print(); + * ``` + */ + valueCounts(): Series { + const sData = this.values; + const dataDict: any = {}; + for (let i = 0; i < sData.length; i++) { + const val = sData[i]; + if (`${val}` in dataDict) { + dataDict[`${val}`] = dataDict[`${val}`] + 1; + } else { + dataDict[`${val}`] = 1; + } + } + + const index = Object.keys(dataDict).map((x) => { + return parseInt(x) ? parseInt(x) : x; + }); + const data = Object.values(dataDict); + + const series = new Series(data, { index: index }); + return series; + + } + + /** + * Returns the absolute of values in Series + * @param options.inplace Boolean indicating whether to perform the operation inplace or not. Defaults to false + * @example + * ``` + * const sf = new Series([1, -2, 3, -4, 5, -6]); + * const sf2 = sf.abs(); + * console.log(sf2.values); + * //output [ 1, 2, 3, 4, 5, 6 ] + * ``` + * + * @example + * ``` + * const sf = new Series([1, -2, 3, -4, 5, -6]); + * sf.abs({ inplace: true }); + * console.log(sf.values); + * //output [ 1, 2, 3, 4, 5, 6 ] + * ``` + */ + abs(options?: { inplace?: boolean }): Series + abs(options?: { inplace?: boolean }): Series | void { + const { inplace } = { inplace: false, ...options } + + if (this.dtypes[0] == "string") { + throw new Error(`DtypeError: String data type does not support abs operation`); + } + + const newValues = this.values.map(val => Math.abs(val as number)); + + if (inplace) { + this.$setValues(newValues as ArrayType1D) + } else { + const sf = this.copy(); + sf.$setValues(newValues as ArrayType1D) + return sf; + } + } + + /** + * Returns the cumulative sum over a Series + * @param options.inplace Boolean indicating whether to perform the operation inplace or not. Defaults to false + * @example + * ``` + * const sf = new Series([1, 2, 3, 4, 5, 6]); + * const sf2 = sf.cumsum(); + * console.log(sf2.values); + * //output [ 1, 3, 6, 10, 15, 21 ] + * ``` + * + * @example + * ``` + * const sf = new Series([1, 2, 3, 4, 5, 6]); + * sf.cumSum({ inplace: true }); + * console.log(sf.values); + * //output [ 1, 3, 6, 10, 15, 21 ] + * ``` + */ + cumSum(options?: { inplace?: boolean }): Series + cumSum(options?: { inplace?: boolean }): Series | void { + const ops = { inplace: false, ...options } + return this.cumOps("sum", ops); + } + + /** + * Returns cumulative minimum over a Series + * @param options.inplace Boolean indicating whether to perform the operation inplace or not. Defaults to false + * @example + * ``` + * const sf = new Series([1, 2, 3, 4, 5, 6]); + * const sf2 = sf.cumMin(); + * console.log(sf2.values); + * //output [ 1, 1, 1, 1, 1, 1 ] + * ``` + * + */ + cumMin(options?: { inplace?: boolean }): Series + cumMin(options?: { inplace?: boolean }): Series | void { + const ops = { inplace: false, ...options } + return this.cumOps("min", ops); + } + + + /** + * Returns cumulative maximum over a Series + * @param options.inplace Boolean indicating whether to perform the operation inplace or not. Defaults to false + * @example + * ``` + * const sf = new Series([1, 2, 3, 4, 5, 6]); + * const sf2 = sf.cumMax(); + * console.log(sf2.values); + * //output [ 1, 2, 3, 4, 5, 6 ] + * ``` + */ + cumMax(options?: { inplace?: boolean }): Series + cumMax(options?: { inplace?: boolean }): Series | void { + const ops = { inplace: false, ...options } + return this.cumOps("max", ops); + } + + /** + * Returns cumulative product over a Series + * @param options.inplace Boolean indicating whether to perform the operation inplace or not. Defaults to false + * @example + * ``` + * const sf = new Series([1, 2, 3, 4, 5, 6]); + * const sf2 = sf.cumProd(); + * console.log(sf2.values); + * //output [ 1, 2, 6, 24, 120, 720 ] + * ``` + */ + cumProd(options?: { inplace?: boolean }): Series + cumProd(options?: { inplace?: boolean }): Series | void { + const ops = { inplace: false, ...options } + return this.cumOps("prod", ops); + } + + /** + * Internal helper function to calculate cumulative operations on series data + */ + private cumOps(ops: string, options: { inplace: boolean }): Series | void { + if (this.dtypes[0] == "string") { + throw new Error(`DtypeError: String data type does not support ${ops} operation`); + } + const { inplace } = options; + + const sData = this.values; + let tempval = sData[0]; + const data = [tempval]; + + for (let i = 1; i < sData.length; i++) { + const currVal = sData[i]; + switch (ops) { + case "max": + if (currVal > tempval) { + data.push(currVal); + tempval = currVal; + } else { + data.push(tempval); + } + break; + case "min": + if (currVal < tempval) { + data.push(currVal); + tempval = currVal; + } else { + data.push(tempval); + } + break; + case "sum": + tempval = (tempval as number) + (currVal as number) + data.push(tempval); + break; + case "prod": + tempval = (tempval as number) * (currVal as number) + data.push(tempval); + break; + + } + } + + if (inplace) { + this.$setValues(data as ArrayType1D) + } else { + return new Series(data, { + index: this.index, + }); + } + } + + + /** + * Returns less than of series and other. Supports element wise operations + * @param other Series, number, or Array of numbers to compare against + * @example + * ``` + * const sf = new Series([1, 2, 3, 4, 5, 6]); + * const sf2 = sf.lt(3); + * console.log(sf2.values); + * //output [ true, true, false, false, false, false ] + * ``` + * + * @example + * ``` + * const sf = new Series([1, 2, 3, 4, 5, 6]); + * const sf2 = sf.lt([3, 4, 5, 6, 7, 8]); + * console.log(sf2.values); + * //output [ true, true, false, false, false, false ] + * ``` + */ + lt(other: Series | number | Array | boolean[]): Series { + return this.boolOps(other, "lt"); + } + + /** + * Returns Greater than of series and other. Supports element wise operations + * @param other Series, number or Array of numbers to compare against + * @example + * ``` + * const sf = new Series([1, 2, 3, 4, 5, 6]); + * const sf2 = sf.gt(3); + * console.log(sf2.values); + * //output [ false, false, true, true, true, true ] + * ``` + * + * @example + * ``` + * const sf = new Series([1, 2, 3, 4, 5, 6]); + * const sf2 = sf.gt([3, 4, 5, 6, 7, 8]); + * console.log(sf2.values); + * //output [ false, false, true, true, true, true ] + * ``` + */ + gt(other: Series | number | Array | boolean[]): Series { + return this.boolOps(other, "gt"); + } + + /** + * Returns Less than or Equal to of series and other. Supports element wise operations + * @param other Series, number or Array of numbers to compare against + * @example + * ``` + * const sf = new Series([1, 2, 3, 4, 5, 6]); + * const sf2 = sf.le(3); + * console.log(sf2.values); + * //output [ true, true, true, true, false, false ] + * ``` + * + * @example + * ``` + * const sf = new Series([1, 2, 3, 4, 5, 6]); + * const sf2 = sf.le([3, 4, 5, 6, 7, 8]); + * console.log(sf2.values); + * //output [ true, true, true, true, false, false ] + * ``` + * + */ + le(other: Series | number | Array | boolean[]): Series { + return this.boolOps(other, "le"); + } + + /** + * Returns Greater than or Equal to of series and other. Supports element wise operations + * @param other Series, number or Array of numbers to compare against + * @example + * ``` + * const sf = new Series([1, 2, 3, 4, 5, 6]); + * const sf2 = sf.ge(3); + * console.log(sf2.values); + * //output [ false, false, true, true, true, true ] + * ``` + * + * @example + * ``` + * const sf = new Series([1, 2, 3, 4, 5, 6]); + * const sf2 = sf.ge([3, 4, 5, 6, 7, 8]); + * console.log(sf2.values); + * //output [ false, false, true, true, true, true ] + * ``` + */ + ge(other: Series | number | Array | boolean[]): Series { + return this.boolOps(other, "ge"); + } + + /** + * Returns Not Equal to of series and other. Supports element wise operations + * @param other Series, number or Array of numbers to compare against + * @example + * ``` + * const sf = new Series([1, 2, 3, 4, 5, 6]); + * const sf2 = sf.ne(3); + * console.log(sf2.values); + * //output [ true, true, false, true, true, true ] + * ``` + * + * @example + * ``` + * const sf = new Series([1, 2, 3, 4, 5, 6]); + * const sf2 = sf.ne([3, 2, 5, 6, 7, 8]); + * console.log(sf2.values); + * //output [ true, false, true, true, true, true ] + * ``` + * + */ + ne(other: Series | number | Array | boolean[]): Series { + return this.boolOps(other, "ne"); + } + + /** + * Returns Equal to of series and other. Supports element wise operations + * @param other Series, number or Array of numbers to compare against + * @example + * ``` + * const sf = new Series([1, 2, 3, 4, 5, 6]); + * const sf2 = sf.eq(3); + * console.log(sf2.values); + * //output [ false, false, true, false, false, false ] + * ``` + * + * @example + * ``` + * const sf = new Series([1, 2, 3, 4, 5, 6]); + * const sf2 = sf.eq(new Series([3, 2, 5, 6, 7, 8])); + * console.log(sf2.values); + * //output [ false, true, false, false, false, false ] + * ``` + */ + eq(other: Series | number | Array | boolean[]): Series { + return this.boolOps(other, "eq"); + } + + /** + * Internal function to perform boolean operations + * @param other Other Series or number to compare with + * @param bOps Name of operation to perform [ne, ge, le, gt, lt, eq] + */ + private boolOps(other: Series | number | Array | boolean[], bOps: string) { + const data = []; + const lSeries = this.values; + let rSeries; + + if (typeof other == "number") { + rSeries = Array(this.values.length).fill(other); //create array of repeated value for broadcasting + } else if (typeof other == "string" && ["eq", "ne"].includes(bOps)) { + rSeries = Array(this.values.length).fill(other); + } else if (other instanceof Series) { + rSeries = other.values; + } else if (Array.isArray(other)) { + rSeries = other; + } else { + throw new Error("ParamError: value for other not supported. It must be either a scalar, Array or Series"); + } + + if (!(lSeries.length === rSeries.length)) { + throw new Error("LengthError: length of other must be equal to length of Series"); + } + + + for (let i = 0; i < lSeries.length; i++) { + const lVal = lSeries[i]; + const rVal = rSeries[i]; + let bool = null; + switch (bOps) { + case "lt": + bool = lVal < rVal ? true : false; + data.push(bool); + break; + case "gt": + bool = lVal > rVal ? true : false; + data.push(bool); + break; + case "le": + bool = lVal <= rVal ? true : false; + data.push(bool); + break; + case "ge": + bool = lVal >= rVal ? true : false; + data.push(bool); + break; + case "ne": + bool = lVal !== rVal ? true : false; + data.push(bool); + break; + case "eq": + bool = lVal === rVal ? true : false; + data.push(bool); + break; + } + } + return new Series(data, { + index: this.index, + }); + } + + /** + * Replace all occurence of a value with a new value + * @param oldValue The value you want to replace + * @param newValue The new value you want to replace the old value with + * @param options.inplace Boolean indicating whether to perform the operation inplace or not. Defaults to false + * + * @example + * ``` + * const sf = new Series([1, 2, 3, 4, 5, 6]); + * const sf2 = sf.replace(3, 10); + * console.log(sf2.values); + * //output [ 1, 2, 10, 4, 5, 6 ] + * ``` + * + * @example + * ``` + * const sf = new Series([1, 2, 3, 4, 5, 6]); + * sf.replace(3, 10, { inplace: true }); + * console.log(sf.values); + * //output [ 1, 2, 10, 4, 5, 6 ] + * ``` + */ + replace( + oldValue: string | number | boolean, + newValue: string | number | boolean, + options?: { inplace?: boolean } + ): Series + replace( + oldValue: string | number | boolean, + newValue: string | number | boolean, + options?: { inplace?: boolean } + ): Series | void { + const { inplace } = { inplace: false, ...options } + + if (!oldValue && typeof oldValue !== 'boolean') { + throw Error(`Params Error: Must specify param 'oldValue' to replace`); + } + + if (!newValue && typeof newValue !== 'boolean') { + throw Error(`Params Error: Must specify param 'newValue' to replace with`); + } + + const newArr = [...this.values].map((val) => { + if (val === oldValue) { + return newValue + } else { + return val + } + }); + + if (inplace) { + this.$setValues(newArr as ArrayType1D) + } else { + const sf = this.copy(); + sf.$setValues(newArr as ArrayType1D) + return sf; + } + + } + + /** + * Drops all missing values (NaN, null, undefined) from a Series. + * @param options.inplace Boolean indicating whether to perform the operation inplace or not. Defaults to false + * + * @example + * ``` + * const sf = new Series([1, 2, NaN, 4, 5, NaN]); + * const sf2 = sf.dropNa(); + * console.log(sf2.values); + * //output [ 1, 2, 4, 5 ] + * ``` + * + * @example + * ``` + * const sf = new Series([1, 2, NaN, 4, 5, null]); + * sf.dropNa({ inplace: true }); + * console.log(sf.values); + * //output [ 1, 2, 4, 5 ] + * ``` + */ + dropNa(options?: { inplace?: boolean }): Series + dropNa(options?: { inplace?: boolean }): Series | void { + const { inplace } = { inplace: false, ...options } + + const oldValues = this.values; + const oldIndex = this.index; + const newValues: ArrayType1D = []; + const newIndex: Array = []; + const isNaVals = this.isNa().values; + + isNaVals.forEach((val, i) => { + if (!val) { + newValues.push((oldValues as ArrayType1D)[i]); + newIndex.push(oldIndex[i]) + } + }); + + if (inplace) { + this.$setValues(newValues, false) + this.$setIndex(newIndex) + } else { + const sf = this.copy(); + sf.$setValues(newValues, false) + sf.$setIndex(newIndex) + return sf; + } + + } + + /** + * Returns the integer indices that would sort the Series. + * @param ascending Boolean indicating whether to sort in ascending order or not. Defaults to true + * @example + * ``` + * const sf = new Series([3, 1, 2]); + * const sf2 = sf.argSort(); + * console.log(sf2.values); + * //output [ 1, 2, 0 ] + * ``` + * + * @example + * ``` + * const sf = new Series([3, 1, 2]); + * const sf2 = sf.argSort({ascending: false}); + * console.log(sf2.values); + * //output [ 0, 2, 1 ] + * + */ + argSort(options?: { ascending: boolean }): Series { + const { ascending } = { ascending: true, ...options } + const sortedIndex = this.sortValues({ ascending }); + const sf = new Series(sortedIndex.index); + return sf; + } + + /** + * Returns integer position of the largest value in the Series. + * @example + * ``` + * const sf = new Series([3, 1, 2]); + * const sf2 = sf.argMax(); + * console.log(sf2); + * //output 0 + * ``` + * + *//* + argMax(): number { + return this.tensor.argMax().arraySync() as number + }*/ + + + /** + * Returns integer position of the smallest value in the Series. + * @example + * ``` + * const sf = new Series([3, 1, 2]); + * const sf2 = sf.argMin(); + * console.log(sf2); + * //output 1 + * ``` + * + *//* + argMin(): number { + return this.tensor.argMin().arraySync() as number + }*/ + + /** + * Remove duplicate values from a Series + * @param keep "first" | "last", which dupliate value to keep. Defaults to "first". + * @param options.inplace Boolean indicating whether to perform the operation inplace or not. Defaults to false + * @example + * ``` + * const sf = new Series([1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10]); + * const sf2 = sf.dropDuplicates(); + * console.log(sf2.values); + * //output [ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 ] + * ``` + * + * @example + * ``` + * const sf = new Series([1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10]); + * sf.dropDuplicates({ keep: "last", inplace: true }); + * console.log(sf.values); + * //output [ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 ] + * ``` + * + */ + dropDuplicates(options?: { keep?: "first" | "last", inplace?: boolean }): Series + dropDuplicates(options?: { keep?: "first" | "last", inplace?: boolean }): Series | void { + const { keep, inplace } = { keep: "first", inplace: false, ...options } + + if (!(["first", "last"].includes(keep))) { + throw Error(`Params Error: Keep must be one of 'first' or 'last'`); + } + + let dataArr: ArrayType1D + let newArr: ArrayType1D = []; + let oldIndex: Array + let newIndex: Array = []; + + if (keep === "last") { + dataArr = (this.values as ArrayType1D).reverse(); + oldIndex = this.index.reverse(); + } else { + dataArr = (this.values as ArrayType1D) + oldIndex = this.index; + } + + dataArr.forEach((val, i) => { + if (!newArr.includes(val)) { + newIndex.push(oldIndex[i]); + newArr.push(val); + } + }); + + if (keep === "last") { + //re-reversed the array and index to its true order + newArr = newArr.reverse(); + newIndex = newIndex.reverse(); + } + + if (inplace) { + this.$setValues(newArr, false) + this.$setIndex(newIndex) + } else { + const sf = this.copy(); + sf.$setValues(newArr, false) + sf.$setIndex(newIndex) + return sf; + } + + } + + /** + * Cast Series to specified data type + * @param dtype Data type to cast to. One of [float32, int32, string, boolean, undefined] + * @param options.inplace Boolean indicating whether to perform the operation inplace or not. Defaults to false + * + * @example + * ``` + * const sf = new Series([1, 2, 3, 4, 5, 6, 7, 8, 9, 10]); + * const sf2 = sf.asType("float32"); + * console.log(sf2.dtype); + * //output "float32" + * ``` + * + * @example + * ``` + * const sf = new Series([1, 2, 3, 4, 5, 6, 7, 8, 9, 10]); + * sf.asType("float32", {inplace: true}); + * console.log(sf.dtype); + * //output "float32" + * ``` + */ + asType(dtype: "float32" | "int32" | "string" | "boolean" | "undefined", options?: { inplace?: boolean }): Series + asType(dtype: "float32" | "int32" | "string" | "boolean" | "undefined", options?: { inplace?: boolean }): Series | void { + const { inplace } = { inplace: false, ...options } + + if (!dtype) { + throw Error("Param Error: Please specify dtype to cast to"); + } + + if (!(NDframe.DATA_TYPES.includes(dtype))) { + throw Error(`dtype ${dtype} not supported. dtype must be one of ${NDframe.DATA_TYPES}`); + } + + const oldValues = [...this.values]; + const newValues: ArrayType1D = []; + + switch (dtype) { + case "float32": + oldValues.forEach((val) => { + newValues.push(Number(val)); + }); + break; + case "int32": + oldValues.forEach((val) => { + newValues.push(parseInt(val as any)); + }); + break; + case "string": + oldValues.forEach((val) => { + newValues.push(String(val)); + }); + break; + case "boolean": + oldValues.forEach((val) => { + newValues.push(Boolean(val)); + }); + break; + case "undefined": + oldValues.forEach((_) => { + newValues.push(NaN); + }); + break; + default: + break; + } + + if (inplace) { + this.$setValues(newValues, false) + this.$setDtypes([dtype]) + } else { + const sf = this.copy(); + sf.$setValues(newValues, false) + sf.$setDtypes([dtype]) + return sf; + } + + } + + /** + * Appends a new value or values to the end of the Series + * @param newValue Single value | Array | Series to append to the Series + * @param index The new index value(s) to append to the Series. Must contain the same number of values as `newValues` + * as they map `1 - 1`. + * @param options.inplace Boolean indicating whether to perform the operation inplace or not. Defaults to false + * @example + * ``` + * const sf = new Series([1, 2, 3, 4, 5, 6, 7, 8, 9, 10]); + * sf.append(11); + * console.log(sf.values); + * //output [ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 ] + * ``` + * + * @example + * ``` + * const sf = new Series([1, 2, 3, 4, 5, 6, 7, 8, 9, 10]); + * sf.append([11, 12, 13]); + * console.log(sf.values); + * //output [ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13 ] + * ``` + * + * @example + * ``` + * const sf = new Series([1, 2, 3, 4, 5, 6, 7, 8, 9, 10]); + * sf.append(new Series([11, 12, 13]), { inplace: true}); + * console.log(sf.values); + * //output [ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13 ] + * ``` + */ + append( + newValue: string | number | boolean | Series | ArrayType1D, + index: Array | number | string, + options?: { inplace?: boolean } + ): Series + append( + newValue: string | number | boolean | Series | ArrayType1D, + index: Array | number | string, + options?: { inplace?: boolean } + ): Series | void { + const { inplace } = { inplace: false, ...options } + + if (!newValue && typeof newValue !== "boolean" && typeof newValue !== "number") { + throw Error("Param Error: newValue cannot be null or undefined"); + } + + if (!index) { + throw Error("Param Error: index cannot be null or undefined"); + } + + const newData = [...this.values] + const newIndx = [...this.index] + + if (Array.isArray(newValue) && Array.isArray(index)) { + + if (newValue.length !== index.length) { + throw Error("Param Error: Length of new values and index must be the same"); + } + + newValue.forEach((el, i) => { + newData.push(el); + newIndx.push(index[i]); + }); + + } else if (newValue instanceof Series) { + const _value = newValue.values; + + if (!Array.isArray(index)) { + throw Error("Param Error: index must be an array"); + } + + if (index.length !== _value.length) { + throw Error("Param Error: Length of new values and index must be the same"); + } + + _value.forEach((el, i) => { + newData.push(el); + newIndx.push(index[i]); + }); + } else { + newData.push(newValue); + newIndx.push(index as string | number); + } + + if (inplace) { + this.$setValues(newData as ArrayType1D, false) + this.$setIndex(newIndx) + } else { + const sf = new Series( + newData, + { + index: newIndx, + columns: this.columns, + dtypes: this.dtypes, + }) + + return sf + } + } + + /** + * Returns dtype of Series + * @example + * ``` + * const sf = new Series([1, 2, 3, 4, 5, 6, 7, 8, 9, 10]); + * console.log(sf.dtype); + * //output "int32" + * ``` + */ + get dtype(): string { + return this.dtypes[0]; + } + + /** + * Exposes numerous string methods to manipulate Series of string dtype + * @example + * ``` + * const sf = new Series(["a", "b", "c", "d", "e", "f", "g", "h", "i", "j"]); + * const sfs = sf.str.join("HelloWorld", ""); + * console.log(sfs.values); + * //output ["aHelloWorld", "bHelloWorld", "cHelloWorld", "dHelloWorld", "eHelloWorld", "fHelloWorld", "gHelloWorld", "hHelloWorld", "iHelloWorld", "jHelloWorld"] + * ``` + *//* + get str() { + if (this.dtypes[0] == "string") { + return new Str(this); + } else { + throw new Error("Cannot call accessor str on non-string type"); + } + }*/ + + /** + * Returns time class that exposes different date time method + * @example + * ``` + * const sf = new Series([ + * "2020-01-01", + * "2020-01-02", + * "2020-01-03", + * "2020-01-04", + * "2020-01-05", + * ]); + * const sfd = sf.dt.dayOfWeekName(); + * console.log(sfd.values); + * //output [ 'Wednesday', 'Thursday', 'Friday', 'Saturday', 'Sunday' ] + * ``` + *//* + get dt() { + if (["string", "datetime"].includes(this.dtypes[0])) { + return new Dt(this) + } else { + throw new Error("Cannot call accessor dt on non-string type"); + } + }*/ + + /** + * Overrides default toString implementation. This essentially makes `print()` works. + */ + toString(): string { + const maxRow = 10; + let indx: (string | number)[] + let values = [] + + if (this.shape[0] > maxRow) { + //slice rows to show [max_rows] rows + const sfSlice = this.iloc([`0:${maxRow}`]); + + indx = sfSlice.index + values = sfSlice.values; + + } else { + indx = this.index + values = this.values; + } + + const tabledata = values.map((x, i) => [indx[i], x]) + return table(tabledata as any); + } + + /** + * Returns the logical AND between Series and other. Supports element wise operations and broadcasting. + * @param other Series, Scalar, Array of Scalars + * @example + * ``` + * const sf = new Series([true, true, false, false, true]); + * const sf2 = new Series([true, false, true, false, true]); + * const sf3 = sf.and(sf2); + * console.log(sf3.values); + * //output [ true, false, false, false, false ] + * ``` + */ + and(other: any): Series { + + if (other === undefined) { + throw new Error("Param Error: other cannot be undefined"); + } + const newValues: ArrayType1D = []; + + if (other instanceof Series) { + if (this.dtypes[0] !== other.dtypes[0]) { + throw new Error("Param Error: Series must be of same dtype"); + } + + if (this.shape[0] !== other.shape[0]) { + throw new Error("Param Error: Series must be of same shape"); + } + + this.values.forEach((val, i) => { + newValues.push(Boolean(val) && Boolean(other.values[i])); + }); + + } else if (typeof other === "boolean") { + + this.values.forEach((val) => { + newValues.push(Boolean(val) && Boolean(other)); + }); + + } else if (Array.isArray(other)) { + + this.values.forEach((val, i) => { + newValues.push(Boolean(val) && Boolean(other[i])); + }); + + } else { + throw new Error("Param Error: other must be a Series, Scalar, or Array of Scalars"); + } + return new Series(newValues, { + index: this.index, + }); + } + + /** + * Returns the logical OR between Series and other. Supports element wise operations and broadcasting. + * @param other Series, Scalar, Array of Scalars + * @example + * ``` + * const sf = new Series([true, true, false, false, true]); + * const sf2 = new Series([true, false, true, false, true]); + * const sf3 = sf.or(sf2); + * console.log(sf3.values); + * //output [ true, true, true, false, true ] + * ``` + * + */ + or(other: any): Series { + + if (other === undefined) { + throw new Error("Param Error: other cannot be undefined"); + } + const newValues: ArrayType1D = []; + + if (other instanceof Series) { + if (this.dtypes[0] !== other.dtypes[0]) { + throw new Error("Param Error: Series must be of same dtype"); + } + + if (this.shape[0] !== other.shape[0]) { + throw new Error("Param Error: Series must be of same shape"); + } + + this.values.forEach((val, i) => { + newValues.push(Boolean(val) || Boolean(other.values[i])); + }); + + } else if (typeof other === "boolean") { + + this.values.forEach((val) => { + newValues.push(Boolean(val) || Boolean(other)); + }); + + } else if (Array.isArray(other)) { + + this.values.forEach((val, i) => { + newValues.push(Boolean(val) || Boolean(other[i])); + }); + + } else { + throw new Error("Param Error: other must be a Series, Scalar, or Array of Scalars"); + } + + return new Series(newValues, { + index: this.index + }); + } + + /** + * One-hot encode values in the Series. + * @param options Options for the operation. The following options are available: + * - `prefix`: Prefix to add to the new column. Defaults to unique labels. + * - `prefixSeparator`: Separator to use for the prefix. Defaults to '_'. + * @example + * ``` + * const sf = new Series(["a", "b", "c", "a"]); + * const sf2 = sf.getDummies({ prefix: "category" }); + * console.log(sf2.values); + * //output [ [ 1, 0, 0 ], [ 0, 1, 0 ], [ 0, 0, 1 ], [ 1, 0, 0 ] ] + * ``` + * + * @example + * ``` + * const sf = new Series(["a", "b", "c", "a"]); + * const sf2 = sf.getDummies({ prefix: "category", prefixSeparator: "-" }); + * console.log(sf2.values); + * //output [ [ 1, 0, 0 ], [ 0, 1, 0 ], [ 0, 0, 1 ], [ 1, 0, 0 ] ] + * ``` + *//* + getDummies(options?: { + columns?: string | Array, + prefix?: string | Array, + prefixSeparator?: string, + }): DataFrame { + return dummyEncode(this, options) + }*/ + + /** + * Access a single value for a row index. + * Similar to iloc, in that both provide index-based lookups. + * Use iat if you only need to get or set a single value in a Series. + * @param row Row index of the value to access. + * @example + * ``` + * const sf = new Series([1, 2, 3, 4, 5]) + * sf.iat(0) //returns 1 + * sf.iat(1) //returns 2 + * sf.iat(2) //returns 3 + * ``` + */ + iat(row: number): number | string | boolean | undefined { + if (typeof row === 'string') { + throw new Error('ParamError: row index must be an integer. Use .at to get a row by label.') + } + return (this.values as ArrayType1D)[row]; + } + + /** + * Access a single value for a row label. + * Similar to loc, in that both provide label-based lookups. + * Use at if you only need to get or set a single value in a Series. + * @param row Row label of the value to access. + * @example + * ``` + * const sf = new Series([1, 2, 3, 4, 5, 6], { index: ['A', 'B', 'C', 'D', 'E', 'F'] }) + * sf.at('A') //returns 1 + * sf.at('B') //returns 2 + * sf.at('C') //returns 3 + * ``` + */ + at(row: string): number | string | boolean | undefined { + if (typeof row !== 'string') { + throw new Error('ParamError: row index must be a string. Use .iat to get a row by index.') + } + return (this.values as ArrayType1D)[this.index.indexOf(row)]; + } + + /** + * Exposes functions for creating charts from a DataFrame. + * Charts are created using the Plotly.js library, so all Plotly's configuration parameters are available. + * @param divId name of the HTML Div to render the chart in. + *//* + plot(divId: string): IPlotlyLib { + //TODO: Add support for check plot library to use. So we can support other plot library like d3, vega, etc + if (utils.isBrowserEnv()) { + const plt = new PlotlyLib(this, divId); + return plt; + } else { + throw new Error("Not supported in NodeJS"); + } + }*/ + + variance(arr: number[]) { + if (arr.length === 0) { + return 0; + } + + // Calculate the mean + const sum = arr.reduce((acc, val) => acc + val, 0); + const mean = sum / arr.length; + + // Calculate the squared differences from the mean + const squaredDiffs = arr.map((val) => Math.pow(val - mean, 2)); + + // Calculate the variance + const variance = squaredDiffs.reduce((acc, val) => acc + val, 0) / arr.length; + + return variance; + } + + /** + * Returns a new series with properties of the old series + * + * @param series The series to copy + */ + createNdframeFromNewDataWithOldProps({ newData }: { newData: any }) { + return new Series( + newData, + { + index: [...this.index], + columns: [...this.columns], + dtypes: [...this.dtypes], + }); + } + + checkSeriesOpCompatibility(other: Series, operation: string): void { + if (this.shape[0] != other.shape[0]) { + const msg = `ParamError: Row length mismatch. Length of other (${other.shape[0]}), must be the same as Ndframe (${this.shape[0]})` + throw new Error(msg) + } + if (this.dtypes[0] == 'string' || other.dtypes[0] == 'string') { + const msg = `DtypeError: String data type does not support ${operation} operation` + throw new Error(msg) + } + } +} diff --git a/src/plotting.ts b/src/plotting.ts index 60dc024..55168ce 100644 --- a/src/plotting.ts +++ b/src/plotting.ts @@ -1,10 +1,11 @@ import * as fs from 'fs'; import * as assert from 'assert'; import * as open from 'open'; -import { DataFrame, toJSON } from 'danfojs-node'; import { minify } from 'html-minifier'; import { Stats } from './stats'; -import { PlottingOptions } from './interfaces' +import { PlottingOptions } from './interfaces'; + +import DataFrame from './ndframe/dataframe'; export class Plotting { private readonly openBrowser: boolean; @@ -37,8 +38,8 @@ export class Plotting { assert(this.stats.tradeLog); const df = this.stats.equityCurve.addColumn('Date', this.stats.equityCurve.index) as DataFrame; - const equityCurve = JSON.stringify(toJSON(df)); - const tradesTable = JSON.stringify(toJSON(this.stats.tradeLog as DataFrame)); + const equityCurve = JSON.stringify(df.toJSON()); + const tradesTable = JSON.stringify(this.stats.tradeLog.toJSON() as DataFrame); return ` diff --git a/src/stats.ts b/src/stats.ts index cc9b455..18b189c 100644 --- a/src/stats.ts +++ b/src/stats.ts @@ -1,5 +1,5 @@ import * as assert from 'assert'; -import { DataFrame, Series } from 'danfojs-node'; +import Series from './ndframe/series'; import { uniq, first, last } from 'lodash'; import { DateTime } from 'luxon'; import { StatsOptions } from './interfaces'; @@ -8,6 +8,8 @@ import { Strategy } from './strategy'; import { Trade } from './trade'; import { Plotting } from './plotting'; +import DataFrame from './ndframe/dataframe'; + export class Stats { private _equityCurve?: DataFrame; private _tradeLog?: DataFrame; @@ -67,7 +69,9 @@ export class Stats { ); const pl = tradeLog[TradeLogColumn.PnL] as Series; + const returns = tradeLog[TradeLogColumn.ReturnPct] as Series; + const durations = tradeLog[TradeLogColumn.Duration] as Series; const start = DateTime.fromISO(first(index) as string); @@ -82,6 +86,7 @@ export class Stats { const equityFinal = this.equity.iat(index.length - 1) as number; const equityPeak = this.equity.max(); const returnPct = this.computeReturnPct(this.equity); + const buyAndHoldReturn = this.computeReturnPct(this.data['close']); results.append( @@ -151,7 +156,7 @@ export class Stats { ); results.apply(v => (typeof v === 'number') ? this.foramt(v) : v, { inplace: true }); - results.config.setMaxRow(results.index.length); + results.setMaxRow(results.index.length); this._equityCurve = equityCurve; this._tradeLog = tradeLog; @@ -199,16 +204,19 @@ export class Stats { } private computeDrawdownDurationPeaks(drawdown: Series) { + // eslint-disable-next-line @typescript-eslint/ban-ts-comment // @ts-ignore - const iloc = uniq([ ...drawdown.eq(0).values.reduce((arr, v, i) => v ? [ ...arr, i ] : arr, []), drawdown.index.length - 1]); - const prev = [ NaN, ...iloc.slice(0, -1) ]; - const df = new DataFrame({ iloc, prev }); + const ilocs = uniq([ ...drawdown.eq(0).values.reduce((arr, v, i) => v ? [ ...arr, i ] : arr, []), drawdown.index.length - 1]); + const prev = [ NaN, ...ilocs.slice(0, -1) ]; + const df = new DataFrame({ ilocs, prev }); + // eslint-disable-next-line @typescript-eslint/ban-ts-comment // @ts-ignore - df.query(df['iloc'].gt(df['prev'].add(1)), { inplace: true }); + df.query(df['ilocs'].gt(df['prev'].add(1)), { inplace: true }); + // eslint-disable-next-line @typescript-eslint/ban-ts-comment // @ts-ignore - df.setIndex({ index: df['iloc'].values.map(i => drawdown.index[i]), inplace: true }) + df.setIndex({ index: df['ilocs'].values.map(i => drawdown.index[i]), inplace: true }) if (!df.size) { const nan = new Series(Array(drawdown.count()).fill(NaN)) @@ -222,9 +230,10 @@ export class Stats { return end.diff(start, 'days').get('days'); }), { inplace: true }); + // eslint-disable-next-line @typescript-eslint/ban-ts-comment // @ts-ignore - df.addColumn('peaks', df.apply(([iloc, prev, duration]) => - drawdown.iloc(Array.from({ length: (iloc - prev) + 1 }, (v, k) => k + prev)).max(), { axis: 1 }, + df.addColumn('peaks', df.apply(([ilocs, prev, duration]) => + drawdown.iloc(Array.from({ length: (ilocs - prev) + 1 }, (v, k) => k + prev)).max(), { axis: 1 }, ), { inplace: true }); const ddDur = new Series(drawdown.index.map(i => df.index.includes(i) ? df.at(i, 'duration') : NaN)); diff --git a/src/strategy.ts b/src/strategy.ts index dcea937..b2b1d40 100644 --- a/src/strategy.ts +++ b/src/strategy.ts @@ -1,8 +1,9 @@ import * as assert from 'assert'; -import { DataFrame } from 'danfojs-node'; import { Broker } from './broker'; import { Context, OrderOptions } from './interfaces'; +import DataFrame from './ndframe/dataframe'; + export abstract class Strategy { private _indicators: Record[]> = {}; private _signals: Record = {}; @@ -108,8 +109,10 @@ export abstract class Strategy { * Get the strategy name. */ public toString() { + // eslint-disable-next-line @typescript-eslint/ban-ts-comment // @ts-ignore if (this.params && Object.keys(this.params).length) { + // eslint-disable-next-line @typescript-eslint/ban-ts-comment // @ts-ignore const params = Object.entries(this.params) .map(([key, value]) => `${key}=${value}`); diff --git a/src/trade.ts b/src/trade.ts index 1fd3df9..517fc83 100644 --- a/src/trade.ts +++ b/src/trade.ts @@ -173,7 +173,7 @@ export class Trade { /** * Place new `Order` to close `portion` of the trade at next market price. */ - public close(portion: number = 1) { + public close(portion = 1) { assert(portion > 0 && portion <= 1, 'portion must be a fraction between 0 and 1'); const size = Math.max(1, Math.round(Math.abs(this._size) * portion)) * Math.sign(-this._size); const order = new Order(this.broker, { size, parentTrade: this, tag: this.tag }); diff --git a/src/utils/arrays.ts b/src/utils/arrays.ts new file mode 100644 index 0000000..ffabd33 --- /dev/null +++ b/src/utils/arrays.ts @@ -0,0 +1,2 @@ +export declare type ArrayType1D = Array; +export declare type ArrayType2D = Array; diff --git a/src/utils/utils.ts b/src/utils/utils.ts new file mode 100644 index 0000000..985816f --- /dev/null +++ b/src/utils/utils.ts @@ -0,0 +1,481 @@ +/** + * @license + * Copyright 2022 JsData. All rights reserved. + * + * This source code is licensed under the MIT license found in the + * LICENSE file in the root directory of this source tree. + + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + * ========================================================================== + */ + +import { ArrayType1D, ArrayType2D } from './arrays'; + +/** + * General Utility class + */ +export default class Utils { + + /** + * Checks if array is 1D + * @param arr The array + */ + is1DArray(arr: ArrayType1D | ArrayType2D): boolean { + if ( + typeof arr[0] == "number" || + typeof arr[0] == "string" || + typeof arr[0] == "boolean" || + arr[0] === null + ) { + return true; + } else { + return false; + } + } + + /** + * Checks if a value is a date object + * @param value A date object + * @returns boolean + */ + isDate(value: any): boolean { + return value instanceof Date; + } + + /** + * Check if value is a string. + * @param value The value to check. + * @returns + */ + isString(value: T): boolean { + return typeof value === "string"; + } + + /** + * Checks if value is a number. + * @param value The value to check. + * @returns + */ + isNumber(value: T): boolean { + return typeof value === "number" && isFinite(value); + } + + /** + * Checks if value is an object. + * @param value The value to check. + * @returns + */ + isObject(value: any): boolean { + return value && typeof value === "object" && value.constructor && value.constructor.name === "Object"; + } + + /** + * Checks if a value is empty. Empty means it's either null, undefined or NaN + * @param value The value to check. + * @returns + */ + isEmpty(value: T): boolean { + return value === undefined || value === null || (isNaN(value as any) && typeof value !== "string"); + } + + /** + * Retrieve row array and column names from an object of the form {a: [1,2,3,4], b: [30,20, 30, 20]} + * @param obj The object to retrieve rows and column names from. + */ + getRowAndColValues(obj: object): [ArrayType1D | ArrayType2D, string[]] { + const colNames = Object.keys(obj); + const colData = Object.values(obj); + const firstColLen = colData[0].length; + + colData.forEach((cdata) => { + if (cdata.length != firstColLen) { + throw Error("Length Error: Length of columns must be the same!"); + } + }); + + const rowsArr = this.transposeArray(colData) + return [rowsArr, colNames]; + } + + /** + * Generates an array of integers between specified range + * @param start The starting number. + * @param end The ending number. + */ + range(start: number, end: number): Array { + if (end < start) { + throw new Error("ParamError: end must be greater than start") + } + + if (start === end) { + return [start] + } + + const arr = []; + for (let i = start; i <= end; i++) { + arr.push(i); + } + return arr; + } + + /** + * Infer data type from an array or array of arrays + * @param arr An array or array of arrays + */ + inferDtype(arr: ArrayType1D | ArrayType2D) { + // eslint-disable-next-line @typescript-eslint/no-this-alias + const self = this; + if (this.is1DArray(arr)) { + return [this.$typeChecker(arr)]; + } else { + const arrSlice = this.transposeArray(arr.slice(0, 500)) + const dtypes = arrSlice.map((innerArr) => { + return self.$typeChecker(innerArr as any); + }); + return dtypes; + } + } + + /** + * Private type checker used by inferDtype function + * @param arr The array + */ + private $typeChecker(arr: ArrayType1D | ArrayType2D) { + let dtypes: string; + let lim: number; + const intTracker: Array = []; + const floatTracker: Array = []; + const stringTracker: Array = []; + const boolTracker: Array = []; + const dateTracker: Array = []; + + if (arr.length < 500) { + lim = arr.length; + } else { + lim = 500; + } + + const arrSlice = arr.slice(0, lim); + + for (let i = 0; i < lim; i++) { + const ele = arrSlice[i]; + if (typeof ele == "boolean") { + floatTracker.push(false); + intTracker.push(false); + stringTracker.push(false); + boolTracker.push(true); + dateTracker.push(false); + } else if (this.isEmpty(ele)) { + floatTracker.push(true); + intTracker.push(false); + stringTracker.push(false); + boolTracker.push(false); + dateTracker.push(false); + } else if (this.isDate(ele)) { + floatTracker.push(false); + intTracker.push(false); + stringTracker.push(false); + boolTracker.push(false); + dateTracker.push(true); + } else if (!isNaN(Number(ele))) { + if ((ele as unknown as string).toString().includes(".")) { + floatTracker.push(true); + intTracker.push(false); + stringTracker.push(false); + boolTracker.push(false); + dateTracker.push(false); + } else { + floatTracker.push(false); + intTracker.push(true); + stringTracker.push(false); + boolTracker.push(false); + dateTracker.push(false); + } + } else { + floatTracker.push(false); + intTracker.push(false); + stringTracker.push(true); + boolTracker.push(false); + dateTracker.push(false); + } + } + + const even = (ele: number | string | boolean) => ele == true; + + if (stringTracker.some(even)) { + dtypes = "string"; + } else if (floatTracker.some(even)) { + dtypes = "float32"; + } else if (intTracker.some(even)) { + dtypes = "int32"; + } else if (boolTracker.some(even)) { + dtypes = "boolean"; + } else if (dateTracker.some(even)) { + dtypes = "datetime"; + } else { + dtypes = "undefined"; + } + + return dtypes; + } + + + /** + * Transposes an array of array + * @param obj The object to check. + * @param key The key to find. + */ + transposeArray(arr: ArrayType1D | ArrayType2D): ArrayType1D | ArrayType2D { //old name: __get_col_values + if (arr.length === 0) return arr + + const rowLen: number = arr.length; + if (Array.isArray(arr[0])) { + const colLen: number = arr[0].length; + const newArr = []; + + for (let i = 0; i <= colLen - 1; i++) { + const temp = []; + for (let j = 0; j < rowLen; j++) { + const _elem = (arr as any)[j][i] + temp.push(_elem); + } + newArr.push(temp); + } + return newArr; + } else { + return arr; + } + } + + /** + * Remove NaN values from 1D array + * @param arr + */ + removeMissingValuesFromArray(arr: Array | ArrayType1D) { + const values = arr.filter((val) => { + return !(this.isEmpty(val)) + }) + return values; + } + + /** + * Custom sort for an array of index and values + * @param arr The array of objects to sort + * @param ascending Whether to sort in ascending order or not + */ + sortObj( + arr: Array<{ index: number | string, value: number | string | boolean }>, + ascending: boolean + ) { + const sortedValues = arr.sort((obj1, obj2) => { + let a = obj2.value; + let b = obj1.value; + + if (!ascending) { + if (typeof a === "string" && typeof b === "string") { + a = a.toUpperCase(); + b = b.toUpperCase(); + + if (a < b) { + return -1; + } + + if (a > b) { + return 1; + } + + return 0; + + } else { + return Number(a) - Number(b); + } + } else { + if (typeof a === "string" && typeof b === "string") { + a = a.toUpperCase(); + b = b.toUpperCase(); + + if (a > b) { + return -1; + } + + if (a < b) { + return 1; + } + + return 0; + } else { + return Number(b) - Number(a); + } + } + }); + + return sortedValues; + } + + /** + * Converts a 2D array of array to 1D array for Series Class + * @param arr The array to convert. + */ + convert2DArrayToSeriesArray(arr: ArrayType2D): Array { + const newArr = arr.map((val) => { + if (this.isObject(val)) { + return JSON.stringify(val) + } else { + return `${val}` + } + }); + return newArr; + } + + /** + * Checks if two series are compatible for a mathematical operation + * @param object + * + * firstSeries ==> First Series object + * + * secondSeries ==> Second Series object to comapre with + * + * operation ==> The mathematical operation + *//* + checkSeriesOpCompactibility({ firstSeries, secondSeries, operation }: { + firstSeries: Series, secondSeries: Series, operation: string + }): void { + + if (firstSeries.shape[0] != secondSeries.shape[0]) { + const msg = `ParamError: Row length mismatch. Length of other (${secondSeries.shape[0]}), must be the same as Ndframe (${firstSeries.shape[0]})` + throw new Error(msg) + } + if (firstSeries.dtypes[0] == 'string' || secondSeries.dtypes[0] == 'string') { + const msg = `DtypeError: String data type does not support ${operation} operation` + throw new Error(msg) + } + }*/ + + /** + * Returns a new series with properties of the old series + * + * @param series The series to copy + *//* + createNdframeFromNewDataWithOldProps({ ndFrame, newData, isSeries }: { ndFrame: Series, newData: any, isSeries: boolean }) { + if (isSeries) { + return new Series( + newData, + { + index: [...ndFrame.index], + columns: [...ndFrame.columns], + dtypes: [...ndFrame.dtypes], + }) + } else { + return new DataFrame(newData, + { + index: [...ndFrame.index], + columns: [...ndFrame.columns], + dtypes: [...ndFrame.dtypes], + }) + } + }*/ + + /** + * Maps boolean values (false, true) to integer equivalent (0, 1) + * @param arr The array of booleans + * @param dim The dimension of the array + */ + mapBooleansToIntegers(arr: Array, dim: number): Array { + if (dim == 2) { + const newArr: Array = []; + arr.map((innerArr) => { + const temp: Array = []; + (innerArr as Array).map((val) => temp.push(val ? 1 : 0)); + newArr.push(temp); + }); + return newArr; + } else { + const newArr: Array = []; + arr.map((val) => newArr.push(val ? 1 : 0)); + return newArr; + } + } + + /** + * Round elements of an array or array of arrays to specified dp + * @param arr The Array to round + * @param dp The number of dp to round to + * @param isSeries Whether the array is of type Series or not + */ + round(arr: Array, dp = 1, isSeries: boolean): ArrayType1D | ArrayType2D { + if (dp < 0) { + dp = 1; + } + + if (isSeries) { + const newArr = []; + for (let i = 0; i < arr.length; i++) { + const ele = arr[i]; + if (typeof ele == "number" && !isNaN(ele) && ele !== undefined && ele !== null) { + newArr.push(Number((ele).toFixed(dp))); + } else { + newArr.push(ele) + } + } + return newArr as ArrayType1D + } else { + const resultArr = []; + for (let i = 0; i < arr.length; i++) { + const innerVal = arr[i]; + const newArr: Array = []; + if (Array.isArray(innerVal)) { + for (let i = 0; i < innerVal.length; i++) { + const ele = innerVal[i]; + if (typeof ele == "number" && !isNaN(ele) && ele !== undefined && ele !== null) { + newArr.push(Number((ele).toFixed(dp))); + } else { + newArr.push(ele) + } + } + resultArr.push(newArr); + } else { + if (typeof innerVal == "number" && !isNaN(innerVal) && innerVal !== undefined && innerVal !== null) { + newArr.push(Number((innerVal).toFixed(dp))); + } else { + newArr.push(innerVal) + } + } + + } + return resultArr; + } + } + + /** + * Returns the index of a sorted array + * @param arr1 The first array + * @param arr2 The second array + * @param dtype The data type of the arrays + * + * @returns sorted index + */ + sortArrayByIndex(arr1: ArrayType1D | ArrayType2D, arr2: ArrayType1D | ArrayType2D, dtype: string) { + const sortedIdx = arr1.map((item, index) => { + return [arr2[index], item]; + }); + if (dtype == "string") { + sortedIdx.sort(); + } else { + sortedIdx.sort(([arg1], [arg2]) => (arg2 as unknown as number) - (arg1 as unknown as number)); + } + + return sortedIdx.map(([, item]) => item) as number[] + } + + /** + * Checks if a func is a function + * @param func + */ + isFunction(func: object): boolean { + return typeof func == "function"; + } +} diff --git a/test/backtest.spec.ts b/test/backtest.spec.ts index 2bd1bc1..bb0667c 100644 --- a/test/backtest.spec.ts +++ b/test/backtest.spec.ts @@ -3,10 +3,12 @@ import { Stats } from '../src/stats'; import { SmaCross } from './sma-cross.strategy'; describe('Backtest', () => { + // eslint-disable-next-line @typescript-eslint/no-var-requires const data = require('./fixtures/2330.json'); describe('constructor()', () => { beforeEach(() => { + // eslint-disable-next-line @typescript-eslint/no-empty-function jest.spyOn(console, 'warn').mockImplementation(() => {}); }); @@ -32,6 +34,7 @@ describe('Backtest', () => { it('should throw error when Strategy is invalid', () => { expect(() => { + // eslint-disable-next-line @typescript-eslint/ban-ts-comment // @ts-ignore new Backtest(data, {}); }).toThrow(TypeError); @@ -45,6 +48,7 @@ describe('Backtest', () => { it('should throw error when some data fields are missing', () => { expect(() => { + // eslint-disable-next-line @typescript-eslint/ban-ts-comment // @ts-ignore new Backtest([{ date: '2023-01-03' }], SmaCross); }).toThrow(TypeError); @@ -73,6 +77,7 @@ describe('Backtest', () => { it('should throw error when no parameters provided', async () => { const backtest = new Backtest(data, SmaCross); + // eslint-disable-next-line @typescript-eslint/ban-ts-comment // @ts-ignore await expect(() => backtest.optimize({})).rejects.toThrow(); }); diff --git a/test/broker.spec.ts b/test/broker.spec.ts index 99446bb..a6a1ad9 100644 --- a/test/broker.spec.ts +++ b/test/broker.spec.ts @@ -1,13 +1,15 @@ -import { DataFrame } from 'danfojs-node'; import { sumBy } from 'lodash'; import { Broker } from '../src/broker'; import { Order } from '../src/order'; import { Trade } from '../src/trade'; +import DataFrame from '../src/ndframe/dataframe'; + describe('Broker', () => { let data: DataFrame; beforeEach(() => { + // eslint-disable-next-line @typescript-eslint/no-var-requires data = new DataFrame(require('./fixtures/2330.json')); data.setIndex({ index: data['date'].values, column: 'date', drop: true, inplace: true }); }); diff --git a/test/order.spec.ts b/test/order.spec.ts index 2f719a8..7d16745 100644 --- a/test/order.spec.ts +++ b/test/order.spec.ts @@ -1,13 +1,15 @@ -import { DataFrame } from 'danfojs-node'; import { Broker } from '../src/broker'; import { Order } from '../src/order'; import { Trade } from '../src/trade'; +import DataFrame from '../src/ndframe/dataframe'; + describe('Order', () => { let data: DataFrame; let broker: Broker; beforeEach(() => { + // eslint-disable-next-line @typescript-eslint/no-var-requires data = new DataFrame(require('./fixtures/2330.json')); broker = new Broker(data, { cash: 10000, diff --git a/test/position.spec.ts b/test/position.spec.ts index 9881d3f..5bf9acc 100644 --- a/test/position.spec.ts +++ b/test/position.spec.ts @@ -1,14 +1,16 @@ import { sum, sumBy } from 'lodash'; -import { DataFrame } from 'danfojs-node'; import { Broker } from '../src/broker'; import { Position } from '../src/position'; import { Trade } from '../src/trade'; +import DataFrame from '../src/ndframe/dataframe'; + describe('Position', () => { let data: DataFrame; let broker: Broker; beforeEach(() => { + // eslint-disable-next-line @typescript-eslint/no-var-requires data = new DataFrame(require('./fixtures/2330.json')); broker = new Broker(data, { cash: 10000, diff --git a/test/stats.spec.ts b/test/stats.spec.ts index 2dff03e..ea779d0 100644 --- a/test/stats.spec.ts +++ b/test/stats.spec.ts @@ -1,11 +1,13 @@ -import { DataFrame, Series } from 'danfojs-node'; import { Broker } from '../src/broker'; -import { Strategy } from '../src/strategy'; +import { Strategy } from '../src'; import { Stats } from '../src/stats'; import { Plotting } from '../src/plotting'; import { Trade } from '../src/trade'; import { SmaCross } from './sma-cross.strategy'; +import DataFrame from '../src/ndframe/dataframe'; +import Series from '../src/ndframe/series'; + describe('Stats', () => { let data: DataFrame; let broker: Broker; @@ -14,7 +16,10 @@ describe('Stats', () => { let trades: Trade[]; beforeEach(() => { + // eslint-disable-next-line @typescript-eslint/no-var-requires data = new DataFrame(require('./fixtures/2330.json')); + // eslint-disable-next-line @typescript-eslint/ban-ts-comment + // @ts-ignore data.setIndex({ index: data['date'].values, column: 'date', drop: true, inplace: true }); strategy = new SmaCross(data, broker); broker = new Broker(data, { @@ -54,7 +59,7 @@ describe('Stats', () => { it('should print the results', () => { const stats = new Stats(data, strategy, equity, trades, { riskFreeRate: 0 }); stats.compute(); - Series.prototype.print = jest.fn();; + Series.prototype.print = jest.fn(); stats.print(); expect(stats.results?.print).toBeCalled(); }); diff --git a/test/strategy.spec.ts b/test/strategy.spec.ts index eb8927d..f20281d 100644 --- a/test/strategy.spec.ts +++ b/test/strategy.spec.ts @@ -1,14 +1,16 @@ -import { DataFrame } from 'danfojs-node'; -import { Strategy } from '../src/strategy'; +import { Strategy } from '../src'; import { Broker } from '../src/broker'; import { SmaCross } from './sma-cross.strategy'; +import DataFrame from '../src/ndframe/dataframe'; + describe('Strategy', () => { let strategy: Strategy; let data: DataFrame; let broker: Broker; beforeEach(() => { + // eslint-disable-next-line @typescript-eslint/no-var-requires data = new DataFrame(require('./fixtures/2330.json')); data.setIndex({ index: data['date'].values, column: 'date', drop: true, inplace: true }); broker = new Broker(data, { @@ -182,6 +184,7 @@ describe('Strategy', () => { }); it('should return the name of the constructor if params are empty', () => { + // eslint-disable-next-line @typescript-eslint/ban-ts-comment // @ts-ignore strategy['params'] = {}; expect(strategy.toString()).toBe(strategy.constructor.name); diff --git a/test/trade.spec.ts b/test/trade.spec.ts index 7899b5e..7635035 100644 --- a/test/trade.spec.ts +++ b/test/trade.spec.ts @@ -1,13 +1,15 @@ -import { DataFrame } from 'danfojs-node'; import { Broker } from '../src/broker'; import { Order } from '../src/order'; import { Trade } from '../src/trade'; +import DataFrame from '../src/ndframe/dataframe'; + describe('Trade', () => { let data: DataFrame; let broker: Broker; beforeEach(() => { + // eslint-disable-next-line @typescript-eslint/no-var-requires data = new DataFrame(require('./fixtures/2330.json')); broker = new Broker(data, { cash: 10000, diff --git a/yarn.lock b/yarn.lock index 2f5bb9e..daae184 100644 --- a/yarn.lock +++ b/yarn.lock @@ -4,34 +4,41 @@ "@ampproject/remapping@^2.2.0": version "2.2.0" - resolved "https://registry.yarnpkg.com/@ampproject/remapping/-/remapping-2.2.0.tgz#56c133824780de3174aed5ab6834f3026790154d" + resolved "https://registry.npmjs.org/@ampproject/remapping/-/remapping-2.2.0.tgz" integrity sha512-qRmjj8nj9qmLTQXXmaR1cck3UXSRMPrbsLJAasZpF+t3riI71BXed5ebIOYwQntykeZuhjsdweEc9BxH5Jc26w== dependencies: "@jridgewell/gen-mapping" "^0.1.0" "@jridgewell/trace-mapping" "^0.3.9" -"@babel/code-frame@7.12.11": +"@babel/code-frame@^7.0.0", "@babel/code-frame@7.12.11": version "7.12.11" - resolved "https://registry.yarnpkg.com/@babel/code-frame/-/code-frame-7.12.11.tgz#f4ad435aa263db935b8f10f2c552d23fb716a63f" + resolved "https://registry.npmjs.org/@babel/code-frame/-/code-frame-7.12.11.tgz" integrity sha512-Zt1yodBx1UcyiePMSkWnU4hPqhwq7hGi2nFL1LeA3EUl+q2LQx16MISgJ0+z7dnmgvP9QtIleuETGOiOH1RcIw== dependencies: "@babel/highlight" "^7.10.4" -"@babel/code-frame@^7.0.0", "@babel/code-frame@^7.12.13", "@babel/code-frame@^7.18.6": +"@babel/code-frame@^7.12.13": version "7.18.6" - resolved "https://registry.yarnpkg.com/@babel/code-frame/-/code-frame-7.18.6.tgz#3b25d38c89600baa2dcc219edfa88a74eb2c427a" + resolved "https://registry.npmjs.org/@babel/code-frame/-/code-frame-7.18.6.tgz" + integrity sha512-TDCmlK5eOvH+eH7cdAFlNXeVJqWIQ7gW9tY1GJIpUtFb6CmjVyq2VM3u71bOyR8CRihcCgMUYoDNyLXao3+70Q== + dependencies: + "@babel/highlight" "^7.18.6" + +"@babel/code-frame@^7.18.6": + version "7.18.6" + resolved "https://registry.npmjs.org/@babel/code-frame/-/code-frame-7.18.6.tgz" integrity sha512-TDCmlK5eOvH+eH7cdAFlNXeVJqWIQ7gW9tY1GJIpUtFb6CmjVyq2VM3u71bOyR8CRihcCgMUYoDNyLXao3+70Q== dependencies: "@babel/highlight" "^7.18.6" "@babel/compat-data@^7.20.5": version "7.21.0" - resolved "https://registry.yarnpkg.com/@babel/compat-data/-/compat-data-7.21.0.tgz#c241dc454e5b5917e40d37e525e2f4530c399298" + resolved "https://registry.npmjs.org/@babel/compat-data/-/compat-data-7.21.0.tgz" integrity sha512-gMuZsmsgxk/ENC3O/fRw5QY8A9/uxQbbCEypnLIiYYc/qVJtEV7ouxC3EllIIwNzMqAQee5tanFabWsUOutS7g== -"@babel/core@^7.1.0", "@babel/core@^7.12.3", "@babel/core@^7.7.2", "@babel/core@^7.8.0": +"@babel/core@^7.0.0", "@babel/core@^7.0.0-0", "@babel/core@^7.1.0", "@babel/core@^7.12.3", "@babel/core@^7.7.2", "@babel/core@^7.8.0", "@babel/core@>=7.0.0-beta.0 <8": version "7.21.0" - resolved "https://registry.yarnpkg.com/@babel/core/-/core-7.21.0.tgz#1341aefdcc14ccc7553fcc688dd8986a2daffc13" + resolved "https://registry.npmjs.org/@babel/core/-/core-7.21.0.tgz" integrity sha512-PuxUbxcW6ZYe656yL3EAhpy7qXKq0DmYsrJLpbB8XrsCP9Nm+XCg9XFMb5vIDliPD7+U/+M+QJlH17XOcB7eXA== dependencies: "@ampproject/remapping" "^2.2.0" @@ -52,7 +59,7 @@ "@babel/generator@^7.21.0", "@babel/generator@^7.21.1", "@babel/generator@^7.7.2": version "7.21.1" - resolved "https://registry.yarnpkg.com/@babel/generator/-/generator-7.21.1.tgz#951cc626057bc0af2c35cd23e9c64d384dea83dd" + resolved "https://registry.npmjs.org/@babel/generator/-/generator-7.21.1.tgz" integrity sha512-1lT45bAYlQhFn/BHivJs43AiW2rg3/UbLyShGfF3C0KmHvO5fSghWd5kBJy30kpRRucGzXStvnnCFniCR2kXAA== dependencies: "@babel/types" "^7.21.0" @@ -62,7 +69,7 @@ "@babel/helper-compilation-targets@^7.20.7": version "7.20.7" - resolved "https://registry.yarnpkg.com/@babel/helper-compilation-targets/-/helper-compilation-targets-7.20.7.tgz#a6cd33e93629f5eb473b021aac05df62c4cd09bb" + resolved "https://registry.npmjs.org/@babel/helper-compilation-targets/-/helper-compilation-targets-7.20.7.tgz" integrity sha512-4tGORmfQcrc+bvrjb5y3dG9Mx1IOZjsHqQVUz7XCNHO+iTmqxWnVg3KRygjGmpRLJGdQSKuvFinbIb0CnZwHAQ== dependencies: "@babel/compat-data" "^7.20.5" @@ -73,12 +80,12 @@ "@babel/helper-environment-visitor@^7.18.9": version "7.18.9" - resolved "https://registry.yarnpkg.com/@babel/helper-environment-visitor/-/helper-environment-visitor-7.18.9.tgz#0c0cee9b35d2ca190478756865bb3528422f51be" + resolved "https://registry.npmjs.org/@babel/helper-environment-visitor/-/helper-environment-visitor-7.18.9.tgz" integrity sha512-3r/aACDJ3fhQ/EVgFy0hpj8oHyHpQc+LPtJoY9SzTThAsStm4Ptegq92vqKoE3vD706ZVFWITnMnxucw+S9Ipg== "@babel/helper-function-name@^7.21.0": version "7.21.0" - resolved "https://registry.yarnpkg.com/@babel/helper-function-name/-/helper-function-name-7.21.0.tgz#d552829b10ea9f120969304023cd0645fa00b1b4" + resolved "https://registry.npmjs.org/@babel/helper-function-name/-/helper-function-name-7.21.0.tgz" integrity sha512-HfK1aMRanKHpxemaY2gqBmL04iAPOPRj7DxtNbiDOrJK+gdwkiNRVpCpUJYbUT+aZyemKN8brqTOxzCaG6ExRg== dependencies: "@babel/template" "^7.20.7" @@ -86,21 +93,21 @@ "@babel/helper-hoist-variables@^7.18.6": version "7.18.6" - resolved "https://registry.yarnpkg.com/@babel/helper-hoist-variables/-/helper-hoist-variables-7.18.6.tgz#d4d2c8fb4baeaa5c68b99cc8245c56554f926678" + resolved "https://registry.npmjs.org/@babel/helper-hoist-variables/-/helper-hoist-variables-7.18.6.tgz" integrity sha512-UlJQPkFqFULIcyW5sbzgbkxn2FKRgwWiRexcuaR8RNJRy8+LLveqPjwZV/bwrLZCN0eUHD/x8D0heK1ozuoo6Q== dependencies: "@babel/types" "^7.18.6" "@babel/helper-module-imports@^7.18.6": version "7.18.6" - 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