JacobiAmplitude[u,m]
给出雅可比 (Jacobi) 椭圆函数的幅值
.
JacobiAmplitude
JacobiAmplitude[u,m]
给出雅可比 (Jacobi) 椭圆函数的幅值
.
更多信息
- 数学函数,适合符号和数值运算.
- JacobiAmplitude[u,m] 把一个椭圆函数的自变量 u 转换成幅值 ϕ.
- JacobiAmplitude 是第一类型的椭圆积分的逆运算. 如果
,则
. - 对于每对整数
和
,JacobiAmplitude[u,m] 在复平面 u 上有一个分支切割断点,从
到
. - 对于某些特定变量值,JacobiAmplitude 自动运算出精确值.
- JacobiAmplitude 可计算到任意数值精度.
- JacobiAmplitude 自动逐项作用于列表.
范例
打开所有单元 关闭所有单元基本范例 (4)
JacobiAmplitude[4., 2 / 3]Plot[JacobiAmplitude[x, 2 / 3], {x, -4, 4}]ComplexPlot3D[JacobiAmplitude[z, 1 / 3], {z, -2 - 2I, 2 + 2I}, PlotLegends -> Automatic]Series[JacobiAmplitude[z, m], {z, 0, 6}]Series[JacobiAmplitude[z, m], {m, 0, 1}]范围 (26)
数值运算 (5)
N[JacobiAmplitude[Pi / 3, 1 / 5], 50]JacobiAmplitude[Pi / 3, 0.200000000000000000000000000]JacobiAmplitude[0.2 + 0.1 I, 0.2 I]用高精度高效评估 JacobiAmplitude:
JacobiAmplitude[Pi / 3, 0.2`500]//TimingJacobiAmplitude[Pi / 3, 0.2`10000];//Timing使用 Around 计算平均值统计区间:
JacobiAmplitude[ Around[2 / 3, 0.001], 1 / 3]JacobiAmplitude[{{1 / 2, -1}, {-5 / 3, 1 / 2}}, 1]或使用 MatrixFunction 计算矩阵 JacobiAmplitude 函数:
MatrixFunction[JacobiAmplitude[#, 1]&, {{1 / 2, -1}, {-5 / 3, 1 / 2}}]//FullSimplify特殊值 (4)
{JacobiAmplitude[x, 0], JacobiAmplitude[x, 1]}{JacobiAmplitude[0, m], JacobiAmplitude[EllipticK[m], m]}JacobiAmplitude[EllipticK[m] / 2 + I EllipticK[1 - m] / 2, m]{JacobiAmplitude[Infinity, 0], JacobiAmplitude[Infinity, 1]}xzero = x /. FindRoot[JacobiAmplitude[x, -3] == 1, {x, 2}]Plot[JacobiAmplitude[x, -3], {x, -3, 6}, WorkingPrecision -> 10, Epilog -> Style[Point[{xzero, JacobiAmplitude[xzero, -3]}], PointSize[Large], Red]]JacobiAmplitude[-u, m]可视化 (3)
绘制各种参数值
的 JacobiAmplitude 函数:
Plot[{JacobiAmplitude[x, -1], JacobiAmplitude[x, 1 / 2], JacobiAmplitude[x, 1], JacobiAmplitude[x, 2]}, {x, -4, 4}, PlotLegends -> "Expressions"]按照参数
的函数绘制 JacobiAmplitude:
Plot[{JacobiAmplitude[1, m], JacobiAmplitude[2, m], JacobiAmplitude[3, m]}, {m, -10, 10}, PlotLegends -> "Expressions"]ComplexContourPlot[Re[JacobiAmplitude[z, 2]], {z, -6 - 6I, 6 + 6I}, Contours -> 20]ComplexContourPlot[Im[JacobiAmplitude[z, 2]], {z, -6 - 6I, 6 + 6I}, IconizedObject[«PlotOptions»]]函数属性 (5)
FunctionAnalytic[JacobiAmplitude[x, 2 / 3], x]FunctionSingularities[JacobiAmplitude[x, 2 / 3], x]FunctionDiscontinuities[JacobiAmplitude[x, 2 / 3], x]FunctionInjective[JacobiAmplitude[x, 2 / 3], x]Plot[{JacobiAmplitude[x, 2 / 3], 3}, {x, -5, 5}]FunctionSurjective[JacobiAmplitude[x, 2 / 3], x]Plot[{JacobiAmplitude[x, 2 / 3], -5}, {x, -10, 10}]JacobiAmplitude 不是非负也不是非正函数:
FunctionSign[JacobiAmplitude[x, 2 / 3], x]JacobiAmplitude 不是凸函数也不是凹函数:
FunctionConvexity[JacobiAmplitude[x, 1 / 3], x]微分 (3)
D[JacobiAmplitude[x, m], x]derivs = Table[D[JacobiAmplitude[x, m], {x, n}], {n, 1, 4}]//FullSimplifyPlot[Evaluate[derivs /. m -> 2 / 3], {x, -5, 5}, PlotLegends -> {"First Derivative", "Second Derivative", "Third Derivative", "Fourth Derivative"}]D[JacobiAmplitude[x, m], m]级数展开式 (3)
Series[JacobiAmplitude[x, 2 / 3], {x, 0, 7}]terms = Normal@Table[Series[JacobiAmplitude[x, 2 / 3], {x, 0, n}], {n, 1, 5, 2}];
Plot[{JacobiAmplitude[x, 2 / 3], terms}, {x, -2, 2}]Series[JacobiAmplitude[1, m], {m, 0, 3}]terms = Normal@Table[Series[JacobiAmplitude[1, m], {m, 0, n}], {n, 1, 3}];
Plot[{JacobiAmplitude[1, m], terms}, {m, -9, 9}]JacobiAmplitude 可应用于幂级数:
JacobiAmplitude[u, Log[1 + m] + O[m] ^ 3]JacobiAmplitude[u Cos[u] + O[u] ^ 10, m]//Simplify函数表示 (3)
JacobiAmplitude 是 EllipticF 的反函数:
Solve[u == EllipticF[ϕ, m], ϕ]//QuietIntegrate[JacobiDN[t, m], {t, 0, u}]TraditionalForm 格式:
JacobiAmplitude[u, m]//TraditionalForm应用 (4)
ϕ[t_] = With[{k = 1 + 10^-3}, 2JacobiAmplitude[k t, k^-2]];ϕ''[t] + Sin[ϕ[t]]//FullSimplifyPlot[ϕ[t], {t, 0, 36}]u[t_, x_, {v_, k_}] = Piecewise[{{π - 2JacobiAmplitude[(x - v t/kSqrt[1 - v^2]), k^2], k ≤ 1},
{2 (π - JacobiAmplitude[((1 + k) (x - v t)/2 k Sqrt[1 - v^2]), (4 k/(1 + k)^2)] + JacobiAmplitude[((1 + k) (x - v t)/2 k Sqrt[1 - v^2]) - (1 + (1/k)) EllipticK[(1/k^2)], (4 k/(1 + k)^2)]), k > 1}}];Assuming[k < 1,
Subscript[∂, {t, 2}]u[t, x, {v, k}] - Subscript[∂, {x, 2}]u[t, x, {v, k}] + Sin[u[t, x, {v, k}]]
//FullSimplify]Plot3D[u[t, x, {0.95, 0.99}], {x, -4, 4}, {t, 0, 2}]Plot3D[u[t, x, {0.8, 1.2}], {x, -4, 4}, {t, 0, 2}]Function[m, Plot[Evaluate[Table[Sum[-(-1) ^ k Sin[k JacobiAmplitude[2 EllipticK[m] / Pi v, m]] / k, {k, o}], {o, 8}]], {v, -2Pi, 2Pi}, ImageSize -> Small]] /@ {0, 0.33, 0.66, 0.99}SphericalTriangleAnglesAndSides[m_, {u1_, u2_, u3_}] /; inputQ[m, {u1, u2, u3}] := {JacobiAmplitude[2EllipticK[m]{u1, u2, u3}, m], ArcSin[Sqrt[m]JacobiSN[2EllipticK[m]{u1, u2, u3}, m]]}inputQ[m_, us_List] := 0 < m < 1 && Min[us] > 0 && Total[us] == 1{{∠A, ∠B, ∠C}, {a, b, c}} = SphericalTriangleAnglesAndSides[0.7, {0.2, 0.3, 0.5}]验证 Cagnoli 方程,它与球面三角形的所有角度和边的测量有关:
Sin[b]Sin[c] + Cos[b]Cos[c]Cos[∠A] == Sin[∠B]Sin[∠C] - Cos[∠B]Cos[∠C]Cos[a]Total[{∠A, ∠B, ∠C}] - Pi用 L'Huilier 定理 [MathWorld] 计算球面角盈:
With[{𝓈 = Total[{a, b, c}] / 2}, 4ArcTan[Sqrt[Tan[(𝓈/2)]Tan[(𝓈 - a/2)]Tan[(𝓈 - b/2)]Tan[(𝓈 - c/2)]]]]pC = {1, 0, 0};
normalBC = {0, 0, 1};
pB = RotationTransform[a, normalBC][pC];
normalAB = RotationTransform[-∠B, pB][normalBC];
pA = RotationTransform[-c, normalAB][pB];{{(pC.pB/Norm[pC] Norm[pB]), Cos[a]}, {(pA.pC/Norm[pA] Norm[pC]), Cos[b]}, {(pA.pB/Norm[pA] Norm[pB]), Cos[c]}}Show[
Graphics3D[{{Opacity[1 / 10, Gray], Sphere[{0, 0, 0}, 1]}, {Black, Sphere[{0, 0, 0}, 1 / 50],
Arrowheads[Medium], Arrow[{{0, 0, 0}, pA}], Arrow[{{0, 0, 0}, pB}], Arrow[{{0, 0, 0}, pC}]
}}],
{ParametricPlot3D[RotationTransform[a t, {pB, pC}][pB]//Evaluate, {t, 0, 1}],
ParametricPlot3D[RotationTransform[b t, {pA, pC}][pA]//Evaluate, {t, 0, 1}],
ParametricPlot3D[RotationTransform[c t, {pA, pB}][pA]//Evaluate, {t, 0, 1}]}]属性和关系 (5)
{EllipticF[JacobiAmplitude[z, m], m], JacobiAmplitude[EllipticF[z, m], m]}用 PowerExpand 略去反函数的多值性:
PowerExpand[%]将三角函数应用到 JacobiAmplitude:
{Cos[JacobiAmplitude[z, m]], Sin[JacobiAmplitude[z, m]]}Solve[JacobiAmplitude[x, m]^2 + 3JacobiAmplitude[x, m] == a, x]//QuietDSolve[Subscript[∂, z]w[z] - JacobiDN[z, m] == 0, w[z], z]对于任意整数
和
,JacobiAmplitude 有一个分支切割,从
到
:
Table[JacobiAmplitude[2s EllipticK[m] + I (4t + 1)EllipticK[1 - m], m], {s, -2, 2}, {t, -2, 2}]//Flatten//UnionTable[JacobiAmplitude[2s EllipticK[m] + I (4t + 3)EllipticK[1 - m], m], {s, -2, 2}, {t, -2, 2}]//Flatten//UnionShowJacobiAmplitudeBranchCuts[m_ ? NumericQ] := Module[{K, Kp, rK, iK, rKp, iKp},
K = EllipticK[m];Kp = EllipticK[1 - m];
{rK, iK} = ReIm[K];{rKp, iKp} = ReIm[Kp];
Graphics[{Brown, Line[Flatten[Table[{{2s rK - (4t + 1)iKp, 2s iK + (4t + 1)rKp}, {2s rK - (4t + 3)iKp, 2s iK + (4t + 3)rKp}}, {s, -3, 3}, {t, -2, 2}], 1]]}, Frame -> True, AspectRatio -> 1, ImageSize -> Small, GridLines -> Automatic, GridLinesStyle -> LightGray]
]{ShowJacobiAmplitudeBranchCuts[-3], ShowJacobiAmplitudeBranchCuts[1 / 3], ShowJacobiAmplitudeBranchCuts[3], ShowJacobiAmplitudeBranchCuts[3 + I]}可能存在的问题 (1)
With[{m = 3},
branchPoints = {PointSize[Medium], Point[Table[{2(2s + 1)EllipticK[1 / m] / Sqrt[m], 0}, {s, -2, 2}]]};
Plot[JacobiAmplitude[u, m], {u, -6, 6}, Epilog -> branchPoints]]am[u_, m_] := -(π/2) + JacobiAmplitude[(1/2) (1 + Sqrt[m]) u, (4 Sqrt[m]/(1 + Sqrt[m])^2)] - JacobiAmplitude[(1/2) (1 + Sqrt[m]) u - (1 + (1/Sqrt[m])) EllipticK[(1/m)], (4 Sqrt[m]/(1 + Sqrt[m])^2)];With[{m = 3},
Plot[{ArcSin[JacobiSN[u, m]], am[u, m]}, {u, -6, 6}, IconizedObject[«Plot options»]]]技术笔记
相关链接
历史
1988年引入 (1.0) | 在以下年份被更新:2020 (12.1)
文本
Wolfram Research (1988),JacobiAmplitude,Wolfram 语言函数,https://reference.wolfram.com/language/ref/JacobiAmplitude.html (更新于 2020 年).
CMS
Wolfram 语言. 1988. "JacobiAmplitude." Wolfram 语言与系统参考资料中心. Wolfram Research. 最新版本 2020. https://reference.wolfram.com/language/ref/JacobiAmplitude.html.
APA
Wolfram 语言. (1988). JacobiAmplitude. Wolfram 语言与系统参考资料中心. 追溯自 https://reference.wolfram.com/language/ref/JacobiAmplitude.html 年
BibTeX
@misc{reference.wolfram_2026_jacobiamplitude, author="Wolfram Research", title="{JacobiAmplitude}", year="2020", howpublished="\url{https://reference.wolfram.com/language/ref/JacobiAmplitude.html}", note=[Accessed: 31-October-2026]}
BibLaTeX
@online{reference.wolfram_2026_jacobiamplitude, organization={Wolfram Research}, title={JacobiAmplitude}, year={2020}, url={https://reference.wolfram.com/language/ref/JacobiAmplitude.html}, note=[Accessed: 31-October-2026]}