微积分

这里有一些使用 Sage 进行微积分符号计算的例子。

微分

微分:

sage: var('x k w')
(x, k, w)
sage: f = x^3 * e^(k*x) * sin(w*x); f
x^3*e^(k*x)*sin(w*x)
sage: f.diff(x)
w*x^3*cos(w*x)*e^(k*x) + k*x^3*e^(k*x)*sin(w*x) + 3*x^2*e^(k*x)*sin(w*x)
sage: latex(f.diff(x))
w x^{3} \cos\left(w x\right) e^{\left(k x\right)} + k x^{3} e^{\left(k x\right)} \sin\left(w x\right) + 3 \, x^{2} e^{\left(k x\right)} \sin\left(w x\right)
>>> from sage.all import *
>>> var('x k w')
(x, k, w)
>>> f = x**Integer(3) * e**(k*x) * sin(w*x); f
x^3*e^(k*x)*sin(w*x)
>>> f.diff(x)
w*x^3*cos(w*x)*e^(k*x) + k*x^3*e^(k*x)*sin(w*x) + 3*x^2*e^(k*x)*sin(w*x)
>>> latex(f.diff(x))
w x^{3} \cos\left(w x\right) e^{\left(k x\right)} + k x^{3} e^{\left(k x\right)} \sin\left(w x\right) + 3 \, x^{2} e^{\left(k x\right)} \sin\left(w x\right)

如果你输入 view(f.diff(x)),将会打开一个新的窗口显示编译后的输出。在 notebook 中,你可以在单元格中输入

var('x k w')
f = x^3 * e^(k*x) * sin(w*x)
show(f)
show(f.diff(x))

然后按 shift-enter 来获得类似的结果。

你还可以在 notebook 单元格中,使用以下命令进行微分和积分

R = PolynomialRing(QQ,"x")
x = R.gen()
p = x^2 + 1
show(p.derivative())
show(p.integral())

或者在命令行中,使用以下命令进行微分和积分

sage: R = PolynomialRing(QQ,"x")
sage: x = R.gen()
sage: p = x^2 + 1
sage: p.derivative()
2*x
sage: p.integral()
1/3*x^3 + x
>>> from sage.all import *
>>> R = PolynomialRing(QQ,"x")
>>> x = R.gen()
>>> p = x**Integer(2) + Integer(1)
>>> p.derivative()
2*x
>>> p.integral()
1/3*x^3 + x

此时你也可以输入 view(p.derivative())view(p.integral()) 以打开一个新窗口, 并由 LaTeX 对输出进行排版。

临界点

你可以找到分段定义函数的临界点:

sage: x = PolynomialRing(RationalField(), 'x').gen()
sage: f1 = x^0
sage: f2 = 1-x
sage: f3 = 2*x
sage: f4 = 10*x-x^2
sage: f = piecewise([((0,1),f1), ((1,2),f2), ((2,3),f3), ((3,10),f4)])
sage: f.critical_points()
[5.0]
>>> from sage.all import *
>>> x = PolynomialRing(RationalField(), 'x').gen()
>>> f1 = x**Integer(0)
>>> f2 = Integer(1)-x
>>> f3 = Integer(2)*x
>>> f4 = Integer(10)*x-x**Integer(2)
>>> f = piecewise([((Integer(0),Integer(1)),f1), ((Integer(1),Integer(2)),f2), ((Integer(2),Integer(3)),f3), ((Integer(3),Integer(10)),f4)])
>>> f.critical_points()
[5.0]

幂级数

Sage 提供了几种构建和处理幂级数的方法。

为了从函数表达式中获取泰勒级数,请在表达式上使用 .taylor() 方法:

sage: var('f0 k x')
(f0, k, x)
sage: g = f0/sinh(k*x)^4
sage: g.taylor(x, 0, 3)
-62/945*f0*k^2*x^2 + 11/45*f0 - 2/3*f0/(k^2*x^2) + f0/(k^4*x^4)
>>> from sage.all import *
>>> var('f0 k x')
(f0, k, x)
>>> g = f0/sinh(k*x)**Integer(4)
>>> g.taylor(x, Integer(0), Integer(3))
-62/945*f0*k^2*x^2 + 11/45*f0 - 2/3*f0/(k^2*x^2) + f0/(k^4*x^4)

可以通过 .series() 方法获得函数的形式幂级数展开:

sage: (1/(2-cos(x))).series(x,7)
1 + (-1/2)*x^2 + 7/24*x^4 + (-121/720)*x^6 + Order(x^7)
>>> from sage.all import *
>>> (Integer(1)/(Integer(2)-cos(x))).series(x,Integer(7))
1 + (-1/2)*x^2 + 7/24*x^4 + (-121/720)*x^6 + Order(x^7)

然而,目前对此类序列的某些操作很难执行。有两种替代方案:要么使用 Sage 的 Maxima 子系统以获取完整符号功能:

sage: f = log(sin(x)/x)
sage: f.taylor(x, 0, 10)
-1/467775*x^10 - 1/37800*x^8 - 1/2835*x^6 - 1/180*x^4 - 1/6*x^2
sage: maxima(f).powerseries(x,0)._sage_()
sum(2^(2*i... - 1)*(-1)^i...*x^(2*i...)*bern(2*i...)/(i...*factorial(2*i...)), i..., 1, +Infinity)
>>> from sage.all import *
>>> f = log(sin(x)/x)
>>> f.taylor(x, Integer(0), Integer(10))
-1/467775*x^10 - 1/37800*x^8 - 1/2835*x^6 - 1/180*x^4 - 1/6*x^2
>>> maxima(f).powerseries(x,Integer(0))._sage_()
sum(2^(2*i... - 1)*(-1)^i...*x^(2*i...)*bern(2*i...)/(i...*factorial(2*i...)), i..., 1, +Infinity)

要么你可以使用形式幂级数环进行快速计算。这些环缺乏符号函数:

sage: R.<w> = QQ[[]]
sage: ps = w + 17/2*w^2 + 15/4*w^4 + O(w^6); ps
w + 17/2*w^2 + 15/4*w^4 + O(w^6)
sage: ps.exp()
1 + w + 9*w^2 + 26/3*w^3 + 265/6*w^4 + 413/10*w^5 + O(w^6)
sage: (1+ps).log()
w + 8*w^2 - 49/6*w^3 - 193/8*w^4 + 301/5*w^5 + O(w^6)
sage: (ps^1000).coefficients()
[1, 8500, 36088875, 102047312625, 1729600092867375/8]
>>> from sage.all import *
>>> R = QQ[['w']]; (w,) = R._first_ngens(1)
>>> ps = w + Integer(17)/Integer(2)*w**Integer(2) + Integer(15)/Integer(4)*w**Integer(4) + O(w**Integer(6)); ps
w + 17/2*w^2 + 15/4*w^4 + O(w^6)
>>> ps.exp()
1 + w + 9*w^2 + 26/3*w^3 + 265/6*w^4 + 413/10*w^5 + O(w^6)
>>> (Integer(1)+ps).log()
w + 8*w^2 - 49/6*w^3 - 193/8*w^4 + 301/5*w^5 + O(w^6)
>>> (ps**Integer(1000)).coefficients()
[1, 8500, 36088875, 102047312625, 1729600092867375/8]

积分

下面的 黎曼和与梯形法积分 讨论了数值积分。

Sage 可以自行对一些简单函数进行积分:

sage: f = x^3
sage: f.integral(x)
1/4*x^4
sage: integral(x^3,x)
1/4*x^4
sage: f = x*sin(x^2)
sage: integral(f,x)
-1/2*cos(x^2)
>>> from sage.all import *
>>> f = x**Integer(3)
>>> f.integral(x)
1/4*x^4
>>> integral(x**Integer(3),x)
1/4*x^4
>>> f = x*sin(x**Integer(2))
>>> integral(f,x)
-1/2*cos(x^2)

Sage 还可以计算涉及极限的符号定积分。

sage: var('x, k, w')
(x, k, w)
sage: f = x^3 * e^(k*x) * sin(w*x)
sage: f.integrate(x)
((24*k^3*w - 24*k*w^3 - (k^6*w + 3*k^4*w^3 + 3*k^2*w^5 + w^7)*x^3 + 6*(k^5*w + 2*k^3*w^3 + k*w^5)*x^2 - 6*(3*k^4*w + 2*k^2*w^3 - w^5)*x)*cos(w*x)*e^(k*x) - (6*k^4 - 36*k^2*w^2 + 6*w^4 - (k^7 + 3*k^5*w^2 + 3*k^3*w^4 + k*w^6)*x^3 + 3*(k^6 + k^4*w^2 - k^2*w^4 - w^6)*x^2 - 6*(k^5 - 2*k^3*w^2 - 3*k*w^4)*x)*e^(k*x)*sin(w*x))/(k^8 + 4*k^6*w^2 + 6*k^4*w^4 + 4*k^2*w^6 + w^8)
sage: integrate(1/x^2, x, 1, infinity)
1
>>> from sage.all import *
>>> var('x, k, w')
(x, k, w)
>>> f = x**Integer(3) * e**(k*x) * sin(w*x)
>>> f.integrate(x)
((24*k^3*w - 24*k*w^3 - (k^6*w + 3*k^4*w^3 + 3*k^2*w^5 + w^7)*x^3 + 6*(k^5*w + 2*k^3*w^3 + k*w^5)*x^2 - 6*(3*k^4*w + 2*k^2*w^3 - w^5)*x)*cos(w*x)*e^(k*x) - (6*k^4 - 36*k^2*w^2 + 6*w^4 - (k^7 + 3*k^5*w^2 + 3*k^3*w^4 + k*w^6)*x^3 + 3*(k^6 + k^4*w^2 - k^2*w^4 - w^6)*x^2 - 6*(k^5 - 2*k^3*w^2 - 3*k*w^4)*x)*e^(k*x)*sin(w*x))/(k^8 + 4*k^6*w^2 + 6*k^4*w^4 + 4*k^2*w^6 + w^8)
>>> integrate(Integer(1)/x**Integer(2), x, Integer(1), infinity)
1

卷积

你可以计算任意分段函数与另一个函数的卷积(在定义域之外,它们被假定为零)。 以下是 \(f\), \(f*f\)\(f*f*f\) 的定义, 其中 \(f(x)=1\), \(0<x<1\):

sage: x = PolynomialRing(QQ, 'x').gen()
sage: f = piecewise([((0,1),1*x^0)])
sage: g = f.convolution(f)
sage: h = f.convolution(g)
sage: set_verbose(-1)
sage: P = f.plot(); Q = g.plot(rgbcolor=(1,1,0)); R = h.plot(rgbcolor=(0,1,1))
>>> from sage.all import *
>>> x = PolynomialRing(QQ, 'x').gen()
>>> f = piecewise([((Integer(0),Integer(1)),Integer(1)*x**Integer(0))])
>>> g = f.convolution(f)
>>> h = f.convolution(g)
>>> set_verbose(-Integer(1))
>>> P = f.plot(); Q = g.plot(rgbcolor=(Integer(1),Integer(1),Integer(0))); R = h.plot(rgbcolor=(Integer(0),Integer(1),Integer(1)))

要查看此内容,请输入 show(P+Q+R)

黎曼和与梯形法积分

关于 \(\int_a^bf(x)\, dx\) 的数值近似, 其中 \(f\) 是分段函数,可以:

  • 计算(用于绘图目的)根据梯形法则定义的分段线性函数,基于将其分割为 \(N\) 个子区间进行数值积分;

  • 梯形法则给出的近似值;

  • 计算(用于绘图目的)根据黎曼和(左端点、右端点或中点)定义的分段常数函数, 基于将其分割为 \(N\) 个子区间进行数值积分;

  • 黎曼和近似值给出的近似值。

sage: f1(x) = x^2
sage: f2(x) = 5-x^2
sage: f = piecewise([[[0,1], f1], [RealSet.open_closed(1,2), f2]])
sage: t = f.trapezoid(2); t
piecewise(x|-->1/2*x on (0, 1/2), x|-->3/2*x - 1/2 on (1/2, 1), x|-->7/2*x - 5/2 on (1, 3/2), x|-->-7/2*x + 8 on (3/2, 2); x)
sage: t.integral()
piecewise(x|-->1/4*x^2 on (0, 1/2), x|-->3/4*x^2 - 1/2*x + 1/8 on (1/2, 1), x|-->7/4*x^2 - 5/2*x + 9/8 on (1, 3/2), x|-->-7/4*x^2 + 8*x - 27/4 on (3/2, 2); x)
sage: t.integral(definite=True)
9/4
>>> from sage.all import *
>>> __tmp__=var("x"); f1 = symbolic_expression(x**Integer(2)).function(x)
>>> __tmp__=var("x"); f2 = symbolic_expression(Integer(5)-x**Integer(2)).function(x)
>>> f = piecewise([[[Integer(0),Integer(1)], f1], [RealSet.open_closed(Integer(1),Integer(2)), f2]])
>>> t = f.trapezoid(Integer(2)); t
piecewise(x|-->1/2*x on (0, 1/2), x|-->3/2*x - 1/2 on (1/2, 1), x|-->7/2*x - 5/2 on (1, 3/2), x|-->-7/2*x + 8 on (3/2, 2); x)
>>> t.integral()
piecewise(x|-->1/4*x^2 on (0, 1/2), x|-->3/4*x^2 - 1/2*x + 1/8 on (1/2, 1), x|-->7/4*x^2 - 5/2*x + 9/8 on (1, 3/2), x|-->-7/4*x^2 + 8*x - 27/4 on (3/2, 2); x)
>>> t.integral(definite=True)
9/4

拉普拉斯变换

如果你有一个分段定义的多项式函数,那么有一个“原生”命令用于计算拉普拉斯变换。 这将调用 Maxima,但值得注意的是,Maxima 无法(使用最后几个示例中的直接接口)处理这种类型的计算。

sage: var('x s')
(x, s)
sage: f1(x) = 1
sage: f2(x) = 1-x
sage: f = piecewise([((0,1),f1), ((1,2),f2)])
sage: f.laplace(x, s)
-e^(-s)/s + (s + 1)*e^(-2*s)/s^2 + 1/s - e^(-s)/s^2
>>> from sage.all import *
>>> var('x s')
(x, s)
>>> __tmp__=var("x"); f1 = symbolic_expression(Integer(1)).function(x)
>>> __tmp__=var("x"); f2 = symbolic_expression(Integer(1)-x).function(x)
>>> f = piecewise([((Integer(0),Integer(1)),f1), ((Integer(1),Integer(2)),f2)])
>>> f.laplace(x, s)
-e^(-s)/s + (s + 1)*e^(-2*s)/s^2 + 1/s - e^(-s)/s^2

对于其他“合理”的函数,可以使用 Maxima 接口计算拉普拉斯变换:

sage: var('k, s, t')
(k, s, t)
sage: f = 1/exp(k*t)
sage: f.laplace(t,s)
1/(k + s)
>>> from sage.all import *
>>> var('k, s, t')
(k, s, t)
>>> f = Integer(1)/exp(k*t)
>>> f.laplace(t,s)
1/(k + s)

上面是计算拉普拉斯变换的一种方法

sage: var('s, t')
(s, t)
sage: f = t^5*exp(t)*sin(t)
sage: L = laplace(f, t, s); L
3840*(s - 1)^5/(s^2 - 2*s + 2)^6 - 3840*(s - 1)^3/(s^2 - 2*s + 2)^5 +
720*(s - 1)/(s^2 - 2*s + 2)^4
>>> from sage.all import *
>>> var('s, t')
(s, t)
>>> f = t**Integer(5)*exp(t)*sin(t)
>>> L = laplace(f, t, s); L
3840*(s - 1)^5/(s^2 - 2*s + 2)^6 - 3840*(s - 1)^3/(s^2 - 2*s + 2)^5 +
720*(s - 1)/(s^2 - 2*s + 2)^4

上面是另一种方法。

常微分方程

使用 Sage 接口与 Maxima 可以符号化地求解常微分方程。参见

sage: desolvers?
>>> from sage.all import *
>>> desolvers?

获取可用命令。 可以使用 Sage 接口与 Octave(一个实验性包)或 GSL(Gnu 科学库)中的例程来数值求解常微分方程。

例如,通过 Sage 的 Maxima 接口符号化地求解常微分方程(请勿输入 ....:):

sage: y=function('y')(x); desolve(diff(y,x,2) + 3*x == y, dvar = y, ics = [1,1,1])
3*x - 2*e^(x - 1)
sage: desolve(diff(y,x,2) + 3*x == y, dvar = y)
_K2*e^(-x) + _K1*e^x + 3*x
sage: desolve(diff(y,x) + 3*x == y, dvar = y)
(3*(x + 1)*e^(-x) + _C)*e^x
sage: desolve(diff(y,x) + 3*x == y, dvar = y, ics = [1,1]).expand()
3*x - 5*e^(x - 1) + 3

sage: f=function('f')(x); desolve_laplace(diff(f,x,2) == 2*diff(f,x)-f, dvar = f, ics = [0,1,2])
x*e^x + e^x

sage: desolve_laplace(diff(f,x,2) == 2*diff(f,x)-f, dvar = f)
-x*e^x*f(0) + x*e^x*D[0](f)(0) + e^x*f(0)
>>> from sage.all import *
>>> y=function('y')(x); desolve(diff(y,x,Integer(2)) + Integer(3)*x == y, dvar = y, ics = [Integer(1),Integer(1),Integer(1)])
3*x - 2*e^(x - 1)
>>> desolve(diff(y,x,Integer(2)) + Integer(3)*x == y, dvar = y)
_K2*e^(-x) + _K1*e^x + 3*x
>>> desolve(diff(y,x) + Integer(3)*x == y, dvar = y)
(3*(x + 1)*e^(-x) + _C)*e^x
>>> desolve(diff(y,x) + Integer(3)*x == y, dvar = y, ics = [Integer(1),Integer(1)]).expand()
3*x - 5*e^(x - 1) + 3

>>> f=function('f')(x); desolve_laplace(diff(f,x,Integer(2)) == Integer(2)*diff(f,x)-f, dvar = f, ics = [Integer(0),Integer(1),Integer(2)])
x*e^x + e^x

>>> desolve_laplace(diff(f,x,Integer(2)) == Integer(2)*diff(f,x)-f, dvar = f)
-x*e^x*f(0) + x*e^x*D[0](f)(0) + e^x*f(0)

如果你已经安装了 Octavegnuplot

sage: octave.de_system_plot(['x+y','x-y'], [1,-1], [0,2]) # optional - octave
>>> from sage.all import *
>>> octave.de_system_plot(['x+y','x-y'], [Integer(1),-Integer(1)], [Integer(0),Integer(2)]) # optional - octave

将在同一个图中绘制常微分方程组的两个图像 \((t,x(t)), (t,y(t))\)\(t\)-轴为横轴)

\[x' = x+y, x(0) = 1; y' = x-y, y(0) = -1,\]

对于 \(0 \leq t \leq 2\)。使用 desolve_system_rk4 也可以获得相同的结果:

sage: x, y, t = var('x y t')
sage: P=desolve_system_rk4([x+y, x-y], [x,y], ics=[0,1,-1], ivar=t, end_points=2)
sage: p1 = list_plot([[i,j] for i,j,k in P], plotjoined=True)
sage: p2 = list_plot([[i,k] for i,j,k in P], plotjoined=True, color='red')
sage: p1+p2
Graphics object consisting of 2 graphics primitives
>>> from sage.all import *
>>> x, y, t = var('x y t')
>>> P=desolve_system_rk4([x+y, x-y], [x,y], ics=[Integer(0),Integer(1),-Integer(1)], ivar=t, end_points=Integer(2))
>>> p1 = list_plot([[i,j] for i,j,k in P], plotjoined=True)
>>> p2 = list_plot([[i,k] for i,j,k in P], plotjoined=True, color='red')
>>> p1+p2
Graphics object consisting of 2 graphics primitives

该方程组也可以通过使用命令 desolve_system 来求解。

sage: t=var('t'); x=function('x',t); y=function('y',t)
sage: des = [diff(x,t) == x+y, diff(y,t) == x-y]
sage: desolve_system(des, [x,y], ics = [0, 1, -1])
[x(t) == cosh(sqrt(2)*t), y(t) == sqrt(2)*sinh(sqrt(2)*t) - cosh(sqrt(2)*t)]
>>> from sage.all import *
>>> t=var('t'); x=function('x',t); y=function('y',t)
>>> des = [diff(x,t) == x+y, diff(y,t) == x-y]
>>> desolve_system(des, [x,y], ics = [Integer(0), Integer(1), -Integer(1)])
[x(t) == cosh(sqrt(2)*t), y(t) == sqrt(2)*sinh(sqrt(2)*t) - cosh(sqrt(2)*t)]

此命令的输出 是一对函数。

最后,可以使用幂级数求解线性微分方程:

sage: R.<t> = PowerSeriesRing(QQ, default_prec=10)
sage: a = 2 - 3*t + 4*t^2 + O(t^10)
sage: b = 3 - 4*t^2 + O(t^7)
sage: f = a.solve_linear_de(prec=5, b=b, f0=3/5)
sage: f
3/5 + 21/5*t + 33/10*t^2 - 38/15*t^3 + 11/24*t^4 + O(t^5)
sage: f.derivative() - a*f - b
O(t^4)
>>> from sage.all import *
>>> R = PowerSeriesRing(QQ, default_prec=Integer(10), names=('t',)); (t,) = R._first_ngens(1)
>>> a = Integer(2) - Integer(3)*t + Integer(4)*t**Integer(2) + O(t**Integer(10))
>>> b = Integer(3) - Integer(4)*t**Integer(2) + O(t**Integer(7))
>>> f = a.solve_linear_de(prec=Integer(5), b=b, f0=Integer(3)/Integer(5))
>>> f
3/5 + 21/5*t + 33/10*t^2 - 38/15*t^3 + 11/24*t^4 + O(t^5)
>>> f.derivative() - a*f - b
O(t^4)

周期函数的傅里叶级数

\(f\) 是一个周期为 \(2L\) 的实周期函数。 \(f\) 的傅里叶级数是

\[S(x) = \frac{a_0}{2} + \sum_{n=1}^\infty \left[a_n\cos\left(\frac{n\pi x}{L}\right) + b_n\sin\left(\frac{n\pi x}{L}\right)\right]\]

其中

\[a_n = \frac{1}{L}\int_{-L}^L f(x)\cos\left(\frac{n\pi x}{L}\right) dx,\]

并且

\[b_n = \frac{1}{L}\int_{-L}^L f(x)\sin\left(\frac{n\pi x}{L}\right) dx,\]

傅里叶系数 \(a_n\)\(b_n\) 是通过声明 \(f\) 在一个周期内分段定义的函数并调用方法 fourier_series_cosine_coefficientfourier_series_sine_coefficient 来计算的, 而部分和是通过 fourier_series_partial_sum 获得的:

sage: f = piecewise([((0,pi/2), -1), ((pi/2,pi), 2)])
sage: f.fourier_series_cosine_coefficient(0)
1
sage: f.fourier_series_sine_coefficient(5)
-6/5/pi
sage: s5 = f.fourier_series_partial_sum(5); s5
-6/5*sin(10*x)/pi - 2*sin(6*x)/pi - 6*sin(2*x)/pi + 1/2
sage: plot(f, (0,pi)) + plot(s5, (x,0,pi), color='red')
Graphics object consisting of 2 graphics primitives
>>> from sage.all import *
>>> f = piecewise([((Integer(0),pi/Integer(2)), -Integer(1)), ((pi/Integer(2),pi), Integer(2))])
>>> f.fourier_series_cosine_coefficient(Integer(0))
1
>>> f.fourier_series_sine_coefficient(Integer(5))
-6/5/pi
>>> s5 = f.fourier_series_partial_sum(Integer(5)); s5
-6/5*sin(10*x)/pi - 2*sin(6*x)/pi - 6*sin(2*x)/pi + 1/2
>>> plot(f, (Integer(0),pi)) + plot(s5, (x,Integer(0),pi), color='red')
Graphics object consisting of 2 graphics primitives
_images/calculus-1.svg