Sympy常用函数总结
基础
from sympy import *
数学格式输出:
init_printing()
添加变量:
x, y, z, a, b, c = symbols('x y z a b c')
声明分数:
Rational(1, 3)
\(\displaystyle \frac{1}{3}\)
化简式子:
simplify((x**3 + x**2 - x - 1)/(x**2 + 2*x + 1))
\(\displaystyle x - 1\)
因式分解:
expand((x + 2)*(x - 3))
\(\displaystyle x^{2} - x - 6\)
提取公因式:
factor(x**3 - x**2 + x - 1)
\(\displaystyle \left(x - 1\right) \left(x^{2} + 1\right)\)
约分:
cancel((x**2 + 2*x + 1)/(x**2 + x))
\(\displaystyle \frac{x + 1}{x}\)
裂项:
apart((4*x**3 + 21*x**2 + 10*x + 12)/(x**4 + 5*x**3 + 5*x**2 + 4*x))
\(\displaystyle \frac{2 x - 1}{x^{2} + x + 1} - \frac{1}{x + 4} + \frac{3}{x}\)
变换形式:
tan(x).rewrite(sin)
\(\displaystyle \frac{2 \sin^{2}{\left(x \right)}}{\sin{\left(2 x \right)}}\)
数列求和:
Sum(x ** 2, (x, 1, a)).doit()
\(\displaystyle \frac{a^{3}}{3} + \frac{a^{2}}{2} + \frac{a}{6}\)
数列求积:
Product(x**2,(x, 1, a)).doit()
\(\displaystyle a!^{2}\)
微积分
求导:
diff(cos(x), x)
\(\displaystyle - \sin{\left(x \right)}\)
求高阶导:
diff(x**4, x, 3)
\(\displaystyle 24 x\)
连续求偏导:
diff(exp(x*y*z), x, y, 2, z, 4)
\(\displaystyle x^{3} y^{2} \left(x^{3} y^{3} z^{3} + 14 x^{2} y^{2} z^{2} + 52 x y z + 48\right) e^{x y z}\)
不定积分:
integrate(cos(x), x)
\(\displaystyle \sin{\left(x \right)}\)
定积分:
integrate(exp(-x), (x, 0, oo))
\(\displaystyle 1\)
多重积分:
integrate(exp(-x**2 - y**2), (x, -oo, oo), (y, -oo, oo))
\(\displaystyle \pi\)
极限:
limit(sin(x)/x, x, 0)
\(\displaystyle 1\)
泰勒展开(到第4阶):
sin(x).series(x, 0, 4)
\(\displaystyle x - \frac{x^{3}}{6} + O\left(x^{4}\right)\)
泰勒展开(在x=6处):
exp(x - 6).series(x, 6)
\(\displaystyle -5 + \frac{\left(x - 6\right)^{2}}{2} + \frac{\left(x - 6\right)^{3}}{6} + \frac{\left(x - 6\right)^{4}}{24} + \frac{\left(x - 6\right)^{5}}{120} + x + O\left(\left(x - 6\right)^{6}; x\rightarrow 6\right)\)
矩阵
矩阵求逆:
Matrix([[1, 3], [-2, 3]])**-1
\(\displaystyle \left[\begin{matrix}\frac{1}{3} & - \frac{1}{3}\\\frac{2}{9} & \frac{1}{9}\end{matrix}\right]\)
求转置:
Matrix([[1, 2, 3], [4, 5, 6]]).T
\(\displaystyle \left[\begin{matrix}1 & 4\\2 & 5\\3 & 6\end{matrix}\right]\)
生成单位矩阵:
eye(3)
\(\displaystyle \left[\begin{matrix}1 & 0 & 0\\0 & 1 & 0\\0 & 0 & 1\end{matrix}\right]\)
求行列式:
Matrix([[1, 0, 1], [2, -1, 3], [4, 3, 2]]).det()
\(\displaystyle -1\)
化成行阶梯形矩阵:
Matrix([[1, 0, 1, 3], [2, 3, 4, 7], [-1, -3, -3, -4]]).rref()
\(\displaystyle \left( \left[\begin{matrix}1 & 0 & 1 & 3\\0 & 1 & \frac{2}{3} & \frac{1}{3}\\0 & 0 & 0 & 0\end{matrix}\right], \ \left( 0, \ 1\right)\right)\)
求列向量空间:
Matrix([[1, 1, 2], [2 ,1 , 3], [3 , 1, 4]]).columnspace()
\(\displaystyle \left[ \left[\begin{matrix}1\\2\\3\end{matrix}\right], \ \left[\begin{matrix}1\\1\\1\end{matrix}\right]\right]\)
M = Matrix([[3, -2, 4, -2], [5, 3, -3, -2], [5, -2, 2, -2], [5, -2, -3, 3]])
求特征值:
M.eigenvals()
\(\displaystyle \left\{ -2 : 1, \ 3 : 1, \ 5 : 2\right\}\)
求特征向量:
M.eigenvects()
\(\displaystyle \left[ \left( -2, \ 1, \ \left[ \left[\begin{matrix}0\\1\\1\\1\end{matrix}\right]\right]\right), \ \left( 3, \ 1, \ \left[ \left[\begin{matrix}1\\1\\1\\1\end{matrix}\right]\right]\right), \ \left( 5, \ 2, \ \left[ \left[\begin{matrix}1\\1\\1\\0\end{matrix}\right], \ \left[\begin{matrix}0\\-1\\0\\1\end{matrix}\right]\right]\right)\right]\)
求对角化矩阵,返回两个矩阵P、D满足\(PDP^{-1}=M\):
M.diagonalize()
\(\displaystyle \left( \left[\begin{matrix}0 & 1 & 1 & 0\\1 & 1 & 1 & -1\\1 & 1 & 1 & 0\\1 & 1 & 0 & 1\end{matrix}\right], \ \left[\begin{matrix}-2 & 0 & 0 & 0\\0 & 3 & 0 & 0\\0 & 0 & 5 & 0\\0 & 0 & 0 & 5\end{matrix}\right]\right)\)
解方程
求解集:
solveset(x**2 - x, x)
\(\displaystyle \left\{0, 1\right\}\)
求解集(显示多少个重根):
roots(x**3 - 6*x**2 + 9*x, x)
\(\displaystyle \left\{ 0 : 1, \ 3 : 2\right\}\)
求解集(用Eq构造等式):
solveset(Eq(sin(x), 1), x, domain=S.Reals)
\(\displaystyle \left\{2 n \pi + \frac{\pi}{2}\; |\; n \in \mathbb{Z}\right\}\)
解线性方程组:
linsolve([x + y + z - 1, x + y + 2*z - 3 ], (x, y, z))
\(\displaystyle \left\{\left( - y - 1, \ y, \ 2\right)\right\}\)
解线性方程组(矩阵表示):
linsolve(Matrix(([1, 1, 1, 1], [1, 1, 2, 3])), (x, y, z))
\(\displaystyle \left\{\left( - y - 1, \ y, \ 2\right)\right\}\)
解非线性方程组:
nonlinsolve([exp(x) - sin(y), 1/y - 3], [x, y])
\(\displaystyle \left\{\left( \log{\left(\sin{\left(\frac{1}{3} \right)} \right)}, \ \frac{1}{3}\right), \left( \left\{2 n i \pi + \left(\log{\left(\sin{\left(\frac{1}{3} \right)} \right)}\bmod{2 i \pi}\right)\; |\; n \in \mathbb{Z}\right\}, \ \frac{1}{3}\right)\right\}\)
解微分方程:
f, g = symbols('f g', cls=Function)
dsolve(Eq(f(x).diff(x, x) - 2*f(x).diff(x) + f(x), sin(x)), f(x))
\(\displaystyle f{\left(x \right)} = \left(C_{1} + C_{2} x\right) e^{x} + \frac{\cos{\left(x \right)}}{2}\)
解不等式组:
from sympy.solvers.inequalities import *
reduce_inequalities([x <= x ** 2], [x])
\(\displaystyle \left(1 \leq x \wedge x < \infty\right) \vee \left(x \leq 0 \wedge -\infty < x\right)\)
逻辑代数
from sympy.logic.boolalg import *
合取范式:
to_cnf(~(x | y) | z)
\(\displaystyle \left(z \vee \neg x\right) \wedge \left(z \vee \neg y\right)\)
析取范式:
to_dnf(x & (y | z))
\(\displaystyle \left(x \wedge y\right) \vee \left(x \wedge z\right)\)
化简逻辑函数:
simplify_logic((~x & ~y & ~z) | ( ~x & ~y & z))
\(\displaystyle \neg x \wedge \neg y\)
from sympy.logic import *
化简最小项之和为析取范式
minterms = [0, 7]
SOPform([x, y, z], minterms)
\(\displaystyle \left(x \wedge y \wedge z\right) \vee \left(\neg x \wedge \neg y \wedge \neg z\right)\)
化简最小项之和为合取范式
minterms = [[1, 0, 1], [1, 1, 0], [1, 1, 1]]
POSform([x, y, z], minterms)
\(\displaystyle x \wedge \left(y \vee z\right)\)
化简最小项之和为析取范式(第7项任取)
minterms = [[1, 0, 1], [1, 1, 0]]
dontcares = [7]
SOPform([x, y, z], minterms, dontcares)
\(\displaystyle \left(x \wedge y\right) \vee \left(x \wedge z\right)\)
数论
from sympy.ntheory import *
阶乘:
factorial(10)
\(\displaystyle 3628800\)
分解质因数:
factorint(300)
\(\displaystyle \left\{ 2 : 2, \ 3 : 1, \ 5 : 2\right\}\)
factorint(300, visual=True)
\(\displaystyle 2^{2} \cdot 3^{1} \cdot 5^{2}\)
求欧拉函数:
totient(25)
\(\displaystyle 20\)
判断质数:
isprime(101)
True
莫比乌斯函数:
mobius(13 * 17 * 5)
\(\displaystyle -1\)
乘法逆元(模后者意义):
mod_inverse(3, 5)
\(\displaystyle 2\)
from sympy.ntheory.factor_ import *
求因子:
divisors(36)
\(\displaystyle \left[ 1, \ 2, \ 3, \ 4, \ 6, \ 9, \ 12, \ 18, \ 36\right]\)
from sympy.ntheory.modular import *
中国剩余定理解同余方程(模数需互质,前三个数为模数,后三个数为余数,返回第一个数为结果):
crt([99, 97, 95], [49, 76, 65])
\(\displaystyle \left( 639985, \ 912285\right)\)
解同余方程(模数不需互质但比中国剩余定理慢,每个元组第一个数为余数,第二个数为模数,返回第一个数为结果):
solve_congruence((2, 3), (3, 5), (2, 7))
\(\displaystyle \left( 23, \ 105\right)\)
from sympy.ntheory.residue_ntheory import *
求原根(如下2在模19意义下的所有幂占满了0到18):
primitive_root(19)
\(\displaystyle 2\)
求离散对数(如下\(7^3 mod 15 = 41\)):
discrete_log(41, 15, 7)
\(\displaystyle 3\)