python零依赖数学库
Project description
nbmath
一个实用的数学工具包,支持方程求解、几何计算、统计分析等功能。
安装
pip install https://ghproxy.net/https://github.com/tc0512/nbmath/releases/download/v1.0.7/nbmath-1.0.7-py3-none-any.whl
快速开始
from nbmath.equation import solve
from nbmath.const import pi
from nbmath.optimize import newton
from nbmath.utils import is_odd
import os
#解方程
print(solve(1, -3, 2)) #[(2+0j), (1+0j)]
#调用常数
print(pi()) #3.141592653589793
#最小值
TOL = 1e-6
MAX_ITER = 100
print(newton(lambda x: x**2+6*x+9, 1.5, TOL, MAX_ITER)) #x接近-3,y接近0(有浮点误差)
#绘制康托尔阶梯
os.system("python -m nbmath.plots.examples.cantor_stair")
#判断是否为奇数
print(is_odd(99999)) #True
模块介绍
常数模块nbmath.const
pitaue- 数学常数GgkNA- 物理常数
方程模块nbmath.solve
- 一元一次/二次/三次/四次方程求解
- 牛顿迭代法解高次方程
- 不等式
- 统一接口
solve
几何模块nbmath.geo
- 点
Point - 线段
Line - 圆
Circle - 多边形
Polygon
统计模块nbmath.stats
mean平均数percentile百分位数mode众数var方差std标准差
工具模块nbmath.utils
gcd最大公约数lcm最小公倍数floor向下取整trunc截断取整fac阶乘diff多项式求导np.linspace纯python实现polyval多项式代入求值timer计时器is_evenis_odd奇偶数判断
优化算法模块nbmath.optimize
brute咆哮算法golden_section黄金分割法newton牛顿法gradient_descent梯度下降simulated_annealing模拟退火
绘图模块nbmath.plots
point描点scatter散点图line线段fun绘制函数F(x)rect矩形mandelbrotheart等共5个示例图案
示例代码
from nbmath.equation import solve
from nbmath.stats import mode
from nbmath.optimize import simulated_annealing
from nbmath import plots as plt
import math
#求解x^4-10x^2+9=0
roots = solve(1, 0, -10, 0, 9)
print(roots) #接近±1,±3,浮点误差可能存在,请以实际使用为准
print(solve(2, 3, ">")) #x>-1.5
data = [1, 1, 2, 3, 4]
print(mode(data)) #[1]
#求y=x^4-5x^2+4的最小值
def F(x):return x**4-5*x**2+4
TEMP = 100
COOLING = 0.95
STEPS = 1000
TOL = 1e-6
print(simulated_annealing(F, -5, 5, TEMP, COOLING, STEPS, TOL)) #{'x': -1.581998612252256, 'fun': -2.249992603725974}
#绘制y=cos(x)
plt.window(800, 600)
plt.setax(-2*math.pi, -1.5*math.pi, 2*math.pi, 1.5*math.pi)
plt.drawaxhline()
plt.plot_function(lambda x: math.sin(x), -2*math.pi, 2*math.pi)
plt.rect(1, 1, 1.5, 0.5, "red") #绘制一个左下角(1,1),长1.5,宽0.5的红色矩形
plt.keep_window()
许可证
MIT
警告 ·nbmath-1.0.0有bug,请下载nbmath-1.0.4
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