cloud.opencode.base.math.OpenMathLib

public final class OpenMathLib extends Object

OpenMathLib - Unified facade for the opencode-base-math module OpenMathLib - opencode-base-math 模块统一门面

Provides convenient static access to the most frequently used mathematical functions from all sub-packages. For advanced or less common operations, use the individual classes directly (e.g., Statistics, Matrix, Combinatorics).

提供对所有子包中最常用数学函数的便捷静态访问。对于高级或不常见的操作，请直接使用各个类（如 Statistics、Matrix、Combinatorics）。

Features | 主要功能:

Statistics: percentile, correlation, regression, streaming - 统计: 百分位数、相关、回归、流式
Linear Algebra: vector/matrix creation - 线性代数: 向量/矩阵创建
Analysis: root finding, differentiation, integration, interpolation - 分析: 求根、微分、积分、插值
Combinatorics: binomial, permutation - 组合数学: 二项式、排列
Distributions: normal, t, chi-squared, etc. - 概率分布: 正态、t、卡方等
Special functions: gamma, beta, erf - 特殊函数: gamma、beta、erf

Usage Examples | 使用示例:

// One-stop import
import cloud.opencode.base.math.OpenMathLib;

// Statistics
double median = OpenMathLib.percentile(data, 50);
double r = OpenMathLib.correlation(x, y);

// Root finding
double sqrt2 = OpenMathLib.findRoot(x -> x * x - 2, 0, 2);

// Integration
double area = OpenMathLib.integrate(Math::sin, 0, Math.PI);

// Combinatorics
long c = OpenMathLib.binomial(20, 10);

// Special functions
double g = OpenMathLib.gamma(5.0);

Security | 安全性:

Thread-safe: Yes (stateless) - 线程安全: 是（无状态）
Null-safe: Yes - 空值安全: 是

Since:

JDK 25, opencode-base-math V1.0.3

Author:

Leon Soo www.LeonSoo.com

See Also:

Method Summary

Modifier and Type

Method

Description

static double

beta(double a, double b)

Computes the beta function.

static long

binomial(int n, int k)

Computes the binomial coefficient C(n, k).

static double

correlation(double[] x, double[] y)

Computes the Pearson correlation coefficient.

static double

covariance(double[] x, double[] y)

Computes the sample covariance.

static double

derivative(DoubleUnaryOperator f, double x)

Computes the numerical derivative of f at x.

static double

erf(double x)

Computes the error function.

static double

findRoot(DoubleUnaryOperator f, double a, double b)

Finds a root of f in [a, b] using Brent's method (recommended).

static double

findRoot(DoubleUnaryOperator f, double a, double b, double tolerance)

Finds a root of f in [a, b] with specified tolerance.

static double

gamma(double x)

Computes the gamma function.

static Matrix

identityMatrix(int n)

Creates an identity matrix of size n.

static double

integrate(DoubleUnaryOperator f, double a, double b)

Numerically integrates f from a to b using Simpson's rule with n=1000.

static double

interpolate(double[] x, double[] y, double xi)

Interpolates using piecewise linear interpolation.

static Regression.LinearModel

linearRegression(double[] x, double[] y)

Performs simple linear regression.

static Matrix

matrix(double[][] data)

Creates a matrix from a 2D array.

static double

percentile(double[] data, double p)

Computes the p-th percentile of the data.

static long

permutation(int n, int k)

Computes the permutation P(n, k).

static double

spearmanCorrelation(double[] x, double[] y)

Computes Spearman's rank correlation coefficient.

static NormalDistribution

standardNormal()

Returns the standard normal distribution N(0, 1).

static StreamingStatistics

streamingStats()

Creates a new streaming statistics accumulator.

static TestResult

tTestOneSample(double[] data, double mu0)

Performs a one-sample t-test.

static TestResult

tTestTwoSample(double[] x, double[] y)

Performs Welch's two-sample t-test.

static Vector

vector(double... components)

Creates a vector from components.

Methods inherited from class Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Method Details
- percentile
  
  public static double percentile(double[] data, double p)
  
  Computes the p-th percentile of the data. 计算数据的第 p 百分位数
  
  Parameters:
  
  data - the data array / 数据数组
  
  p - the percentile in [0, 100] / 百分位数 [0, 100]
  
  Returns:
  
  the percentile value / 百分位数值
- correlation
  
  public static double correlation(double[] x, double[] y)
  
  Computes the Pearson correlation coefficient. 计算 Pearson 相关系数
  
  Parameters:
  
  x - first array / 第一个数组
  
  y - second array / 第二个数组
  
  Returns:
  
  correlation in [-1, 1] / 相关系数 [-1, 1]
- covariance
  
  public static double covariance(double[] x, double[] y)
  
  Computes the sample covariance. 计算样本协方差
  
  Parameters:
  
  x - first array / 第一个数组
  
  y - second array / 第二个数组
  
  Returns:
  
  the covariance / 协方差
- spearmanCorrelation
  
  public static double spearmanCorrelation(double[] x, double[] y)
  
  Computes Spearman's rank correlation coefficient. 计算 Spearman 等级相关系数
  
  Parameters:
  
  x - first array / 第一个数组
  
  y - second array / 第二个数组
  
  Returns:
  
  Spearman's rho in [-1, 1] / Spearman rho [-1, 1]
- linearRegression
  
  public static Regression.LinearModel linearRegression(double[] x, double[] y)
  
  Performs simple linear regression. 执行简单线性回归
  
  Parameters:
  
  x - independent variable / 自变量
  
  y - dependent variable / 因变量
  
  Returns:
  
  the linear model / 线性模型
- streamingStats
  
  public static StreamingStatistics streamingStats()
  
  Creates a new streaming statistics accumulator. 创建新的流式统计累加器
  
  Returns:
  
  a new empty accumulator / 新的空累加器
- tTestOneSample
  
  public static TestResult tTestOneSample(double[] data, double mu0)
  
  Performs a one-sample t-test. 执行单样本 t 检验
  
  Parameters:
  
  data - the sample data / 样本数据
  
  mu0 - the hypothesized mean / 假设均值
  
  Returns:
  
  the test result / 检验结果
- tTestTwoSample
  
  public static TestResult tTestTwoSample(double[] x, double[] y)
  
  Performs Welch's two-sample t-test. 执行 Welch 双样本 t 检验
  
  Parameters:
  
  x - first sample / 第一个样本
  
  y - second sample / 第二个样本
  
  Returns:
  
  the test result / 检验结果
- vector
  
  public static Vector vector(double... components)
  
  Creates a vector from components. 从分量创建向量
  
  Parameters:
  
  components - the components / 分量
  
  Returns:
  
  a new vector / 新向量
- matrix
  
  public static Matrix matrix(double[][] data)
  
  Creates a matrix from a 2D array. 从二维数组创建矩阵
  
  Parameters:
  
  data - the matrix data / 矩阵数据
  
  Returns:
  
  a new matrix / 新矩阵
- identityMatrix
  
  public static Matrix identityMatrix(int n)
  
  Creates an identity matrix of size n. 创建 n 阶单位矩阵
  
  Parameters:
  
  n - the size / 阶数
  
  Returns:
  
  the identity matrix / 单位矩阵
- findRoot
  
  public static double findRoot(DoubleUnaryOperator f, double a, double b)
  
  Finds a root of f in [a, b] using Brent's method (recommended). 使用 Brent 法在 [a, b] 内求 f 的根（推荐）
  
  Parameters:
  
  f - the function / 函数
  
  a - left endpoint / 左端点
  
  b - right endpoint / 右端点
  
  Returns:
  
  the root / 根
- findRoot
  
  public static double findRoot(DoubleUnaryOperator f, double a, double b, double tolerance)
  
  Finds a root of f in [a, b] with specified tolerance. 使用指定容差在 [a, b] 内求 f 的根
  
  Parameters:
  
  f - the function / 函数
  
  a - left endpoint / 左端点
  
  b - right endpoint / 右端点
  
  tolerance - convergence tolerance / 收敛容差
  
  Returns:
  
  the root / 根
- derivative
  
  public static double derivative(DoubleUnaryOperator f, double x)
  
  Computes the numerical derivative of f at x. 计算 f 在 x 处的数值导数
  
  Parameters:
  
  f - the function / 函数
  
  x - the point / 点
  
  Returns:
  
  the approximate derivative / 近似导数
- integrate
  
  public static double integrate(DoubleUnaryOperator f, double a, double b)
  
  Numerically integrates f from a to b using Simpson's rule with n=1000. 使用 Simpson 法则对 f 从 a 到 b 数值积分（n=1000）
  
  Parameters:
  
  f - the integrand / 被积函数
  
  a - lower bound / 下限
  
  b - upper bound / 上限
  
  Returns:
  
  the approximate integral / 近似积分值
- interpolate
  
  public static double interpolate(double[] x, double[] y, double xi)
  
  Interpolates using piecewise linear interpolation. 分段线性插值
  
  Parameters:
  
  x - the x data points (sorted ascending) / x 数据点（升序）
  
  y - the y data points / y 数据点
  
  xi - the query point / 查询点
  
  Returns:
  
  the interpolated value / 插值结果
- binomial
  
  public static long binomial(int n, int k)
  
  Computes the binomial coefficient C(n, k). 计算二项式系数 C(n, k)
  
  Parameters:
  
  n - total items / 总数
  
  k - items to choose / 选取数
  
  Returns:
  
  C(n, k) / 二项式系数
- permutation
  
  public static long permutation(int n, int k)
  
  Computes the permutation P(n, k). 计算排列数 P(n, k)
  
  Parameters:
  
  n - total items / 总数
  
  k - items to arrange / 排列数
  
  Returns:
  
  P(n, k) / 排列数
- standardNormal
  
  public static NormalDistribution standardNormal()
  
  Returns the standard normal distribution N(0, 1). 返回标准正态分布 N(0, 1)
  
  Returns:
  
  the standard normal / 标准正态分布
- gamma
  
  public static double gamma(double x)
  
  Computes the gamma function. 计算 Gamma 函数
  
  Parameters:
  
  x - the input / 输入值
  
  Returns:
  
  Gamma(x) / Gamma 函数值
- erf
  
  public static double erf(double x)
  
  Computes the error function. 计算误差函数
  
  Parameters:
  
  x - the input / 输入值
  
  Returns:
  
  erf(x) / 误差函数值
- beta
  
  public static double beta(double a, double b)
  
  Computes the beta function. 计算 Beta 函数
  
  Parameters:
  
  a - first parameter / 第一个参数
  
  b - second parameter / 第二个参数
  
  Returns:
  
  Beta(a, b) / Beta 函数值

Class OpenMathLib

Method Summary

Methods inherited from class Object

Method Details

percentile

correlation

covariance

spearmanCorrelation

linearRegression

streamingStats

tTestOneSample

tTestTwoSample

vector

matrix

identityMatrix

findRoot

findRoot

derivative

integrate

interpolate

binomial

permutation

standardNormal

gamma

erf

beta