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Introducing the Socket Python SDK
The initial version of the Socket Python SDK is now on PyPI, enabling developers to more easily interact with the Socket REST API in Python projects.
BitMatrix 以
ArrayBuffer
为基础, 以bit
为单元的矩阵类实现;
特性:
base64
导入导出, 打通存储问题;适用场景:
任何需要存储点阵信息的场景;
类说明:
除了
ArrayBuffer
做存储的矩阵, 还提供AnyMatrix
,AnyMatrixUseObject
两个类;
这两个类主要用于做为参照物; 也可以做为可以存储任意值的矩阵来使用; API相同
class | base DataView | value range |
---|---|---|
BitMatrix | 0 / 1 | |
Int8Matrix | Int8Array | Int8 |
Uint8Matrix | Uint8Array | Uint8 |
Uint8ClampedMatrix | Uint8ClampedArray | Uint8 |
Int16Matrix | Int16Array | Int16 |
Uint16Matrix | Uint16Array | Uint16 |
Int32Matrix | Int32Array | Int32 |
Uint32Matrix | Uint32Array | Uint32 |
Float32Matrix | Float32Array | Float32 |
Float64Matrix | Float64Array | Float64 |
AnyMatrix | Array | any |
AnyMatrixUseObject | Object | any |
npm i bitmatrix
nodejs
const BitMatrix = require('bitmatrix').BitMatrix;
//使用其它的矩阵类
//const {BitMatrix, Uint8Matrix, AnyMatrix} = require('bitmatrix');
let bm = new BitMatrix(2,2,0); //初始化一个以 0 填充的 2*2 矩阵
console.log(bm.showView());
ES2015
// 默认导出 BitMatrix 类
import BitMatrix from 'bitmatrix';
//使用其它的矩阵类
//import {BitMatrix, Uint8Matrix, AnyMatrix} from 'bitmatrix'
console.log(bm.showView());
浏览器
浏览器使用时可选择 己打包依赖的文件 ./dist/BitMatrix.umd.js
<script src="//unpkg.com/@cnwhy/base64/dist/BitMatrix.umd.js"></script>
API 可能还会有变化, 欢迎提意见.
class Matrix {
constructor(width: number, height: number, defaultValue?: any);
//宽(只读)
width: number;
//高(只读)
height: number;
//单元格总数(只读)
total: number;
// 填充矩阵
fill(value: any);
// 填充一行
fillRow(row: number, value: any);
// 填充一列
fillColumn(column: number, value: any);
// 读取指定单元格
get(x: number, y: number): any;
// 设置指定单元格
set(x: number, y: number, value: any);
// 读取一行 返回 Array
getRow(y: number): any[];
// 设置一行 返回 Array
setRow(y: number, row:any[]);
// 读取一列 返回 Array
getColumn(x: number): any[];
// 设置一列 返回 Array
setColumn(x: number, column: any[]);
// 暴露矩阵原型数据对像, 如果你不清楚是什么, 请勿使用
getPrototypeData():Object;
// 遍历矩阵
cellForEach(fn: (value: any, x: number, y: number) => void);
// 以','分隔列, '\n'分隔行, 返回当前矩阵数据
showView(): string;
// 创建一个副本
clone(): Matrix;
// 用现有数据创建矩阵
static from(arr:[][]): Matrix;
static from(arr:[],width:number): Matrix;
// 用现有矩阵对像 创建一个此类型的矩阵对象 注意区别clone(); from可以创建不能类型的矩阵
static from(matrix:Matrix,callback:(value: any, x: number, y: number)=>any,thisArg): Matrix;
// 通过base64导出矩阵,便于存储
static output(matrix:Matrix): string;
// 通过导入base64,创建矩阵
static input(base64:string): Matrix;
}
推荐使用矩阵对像的 clone()
方法;
为获取最大兼容,选用
base64
为媒介进行导入(input()
), 导出(output()
);
导入/导出的数据结构:
前9个字节为描述字节, 后面为数据;
0 | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | ||
Uint32LE(width) | Uint32LE(height) | Uint8(typeMark) | ...(data) |
import BitMatrix from 'bitmatrix';
let bm = new BitMatrix(7,7,0);
bm.fillColumn(3,1);
bm.fillRow(3,1);
let b64 = BitMatrix.output(bm);
console.log(b64);
let bm1 = BitMatrix.input(b64);
console.log(bm1.showView())
/*
AAAABwAAAAcDCATij0AgAA==
0,0,0,1,0,0,0
0,0,0,1,0,0,0
0,0,0,1,0,0,0
1,1,1,1,1,1,1
0,0,0,1,0,0,0
0,0,0,1,0,0,0
0,0,0,1,0,0,0
*/
基于
BufferArray
只能运行于支持ES2015
的环境;
node v10.13.0
从以下的表格看, 是符合预期的.
生成 2000 个 100*100 矩阵, 并用 1 填充, 内存及耗时占用情况:
┌─────────┬──────────────────────┬────────────┬────────────┬──────────────────────┬───────────────────┐
│ (index) │ className │ heapUsed │ external │ sum │ time │
├─────────┼──────────────────────┼────────────┼────────────┼──────────────────────┼───────────────────┤
│ 0 │ 'BitMatrix' │ '0.77MB' │ '2.38MB' │ '3.16MB | 1.91%' │ '7 | 1.46%' │
│ 1 │ 'Int8Matrix' │ '0.87MB' │ '19.07MB' │ '19.94MB | 12.07%' │ '16 | 3.33%' │
│ 2 │ 'Uint8Matrix' │ '0.82MB' │ '19.07MB' │ '19.90MB | 12.04%' │ '14 | 2.92%' │
│ 3 │ 'Uint8ClampedMatrix' │ '0.82MB' │ '19.07MB' │ '19.89MB | 12.04%' │ '15 | 3.13%' │
│ 4 │ 'Int16Matrix' │ '0.80MB' │ '38.15MB' │ '38.95MB | 23.57%' │ '17 | 3.54%' │
│ 5 │ 'Uint16Matrix' │ '0.68MB' │ '38.15MB' │ '38.83MB | 23.50%' │ '19 | 3.96%' │
│ 6 │ 'Int32Matrix' │ '0.53MB' │ '76.29MB' │ '76.82MB | 46.49%' │ '147 | 30.63%' │
│ 7 │ 'Uint32Matrix' │ '0.53MB' │ '76.29MB' │ '76.82MB | 46.49%' │ '139 | 28.96%' │
│ 8 │ 'Float32Matrix' │ '0.53MB' │ '76.29MB' │ '76.82MB | 46.49%' │ '140 | 29.17%' │
│ 9 │ 'Float64Matrix' │ '0.49MB' │ '152.59MB' │ '153.08MB | 92.64%' │ '286 | 59.58%' │
│ 10 │ 'AnyMatrix' │ '153.61MB' │ '0.00MB' │ '153.61MB | 92.96%' │ '2445 | 509.38%' │
│ 11 │ 'AnyMatrixUseObject' │ '153.75MB' │ '0.00MB' │ '153.75MB | 93.05%' │ '6056 | 1261.67%' │
│ 12 │ 'number[]' │ '153.13MB' │ '0.00MB' │ '153.13MB | 92.67%' │ '2808 | 585.00%' │
│ 13 │ 'number[][]' │ '165.24MB' │ '0.00MB' │ '165.24MB | 100.00%' │ '480 | 100.00%' │
└─────────┴──────────────────────┴────────────┴────────────┴──────────────────────┴───────────────────┘
可执行
npm run test-memory
命令测试, 获取本结果;
node v10.13.0
操作同为 1000*1000 矩阵, 基础方法的QPS比较:
┌─────────┬─────────────────┬───────────┬─────────────┬─────────────┬─────────────┐
│ (index) │ name │ fill │ get │ set │ cellForEach │
├─────────┼─────────────────┼───────────┼─────────────┼─────────────┼─────────────┤
│ 0 │ 'BitMatrix' │ '210.31K' │ '8194.21K' │ '6275.51K' │ '700.17' │
│ 1 │ 'Uint8Matrix' │ '25.63K' │ '10969.26K' │ '9658.56K' │ '991.44' │
│ 2 │ 'Uint32Matrix' │ '2.66K' │ '11844.04K' │ '10304.60K' │ '992.45' │
│ 3 │ 'Float64Matrix' │ '1.19K' │ '11845.38K' │ '10639.79K' │ '988.99' │
│ 4 │ 'AnyMatrix' │ '1.23K' │ '11453.06K' │ '10560.18K' │ '987.83' │
│ 5 │ 'number[]' │ '1.15K' │ '15009.22K' │ '14345.48K' │ '960.72' │
│ 6 │ 'number[][]' │ '752.19' │ '12196.47K' │ '11029.79K' │ '1.48K' │
└─────────┴─────────────────┴───────────┴─────────────┴─────────────┴─────────────┘
get
与set
测试都使用了9个点, 所以真实值应该再乘上9;
可执行npm run test-benchmark
命令, 获取本结果;
FAQs
Low-cost dot matrix Class
We found that bitmatrix demonstrated a not healthy version release cadence and project activity because the last version was released a year ago. It has 1 open source maintainer collaborating on the project.
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