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Review request -- Mathieu fcns #60
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| Original file line number | Diff line number | Diff line change |
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| @@ -0,0 +1,38 @@ | ||
| This is an implementation of the Mathieu fcns in C/C++. The | ||
| implementation follows the prototype algos created in Matlab and | ||
| maintained on GitHub at | ||
| https://github.com/brorson/MathieuFcnsFourier. This impl is a | ||
| header-only library for compatability with Scipy's xsf library. | ||
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| The following Mathieu fcns are implemented: | ||
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| * Angular fcn ce(n,q,v) | ||
| * Angular fcn se(n,q,v) | ||
| * Radial (modified) fcn of first kind mc1(n,q,u) | ||
| * Radial (modified) fcn of first kind ms1(n,q,u) | ||
| * Radial (modified) fcn of second kind mc2(n,q,u) | ||
| * Radial (modified) fcn of second kind ms2(n,q,u) | ||
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| Here, n = fcn order, q = frequency (geometry) parmeter, v = angular | ||
| coord (radians), u = radial coord (au). | ||
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| I also provide the following utility fcns: | ||
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| * Eigenvalue a_n(q) | ||
| * Eigenvalue b_n(q) | ||
| * Fourier coeffs A_n^k(q) for ce fcns | ||
| * Fourier coeffs B_n^k(q) for se fcns | ||
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| The goal is to provide a replacement of the Mathieu fcn suite used by | ||
| Scipy. | ||
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| These programs may be built the usual way on a Linux system using the | ||
| usual GNU build tools. The main() function runs some simple sanity | ||
| checks on the functions. In particular, it verifies some output | ||
| values against those computed by the Matlab programs. I did a lot of | ||
| verification and accuracy testing on the Matlab implementations. | ||
| Therefore, tests run here just make sure the C implementation's | ||
| outputs match those from Matlab. The code in main() also shows how to | ||
| invoke the various fcns. | ||
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| Summer 2025, SDB |
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,86 @@ | ||
| #ifndef BESSELJYD_H | ||
| #define BESSELJYD_H | ||
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| #include "../bessel.h" | ||
| #include "../config.h" | ||
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| /* | ||
| * | ||
| * This is part of the Mathieu function suite -- a reimplementation | ||
| * of the Mathieu functions for Scipy. This file holds helpers | ||
| * to the Bessel J and Y functions and also returns derivatives | ||
| * of those fcns. | ||
| * | ||
| * Stuart Brorson -- Summer and Fall 2025. | ||
| * | ||
| */ | ||
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| namespace xsf { | ||
| namespace mathieu { | ||
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| //================================================================== | ||
| double besselj(int k, double z) { | ||
| // This is just a thin wrapper around the Bessel impl in the | ||
| // xsf library. | ||
| double v = (double)k; | ||
| return xsf::cyl_bessel_j(v, z); | ||
| } | ||
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| //================================================================== | ||
| double bessely(int k, double z) { | ||
| // This is just a thin wrapper around the Bessel impl in the | ||
| // xsf library. | ||
| double v = (double)k; | ||
| return xsf::cyl_bessel_y(v, z); | ||
| } | ||
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| //================================================================== | ||
| double besseljd(int k, double z) { | ||
| // This returns the derivative of besselj. The deriv is | ||
| // computed using common identities. | ||
| double y; | ||
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| if (k == 0) { | ||
| double v = 1.0; | ||
| y = -besselj(v, z); | ||
| } else { | ||
| double kp1 = (double)(k + 1); | ||
| double km1 = (double)(k - 1); | ||
| y = (besselj(km1, z) - besselj(kp1, z)) / 2.0; | ||
| } | ||
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| // Must flip sign for negative k and odd k. | ||
| if (k < 0 && ((k % 2) != 0)) { | ||
| y = -y; | ||
| } | ||
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| return y; | ||
| } | ||
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| //================================================================== | ||
| double besselyd(int k, double z) { | ||
| // This returns the derivative of besselj. The deriv is | ||
| // computed using common identities. | ||
| double y; | ||
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| if (k == 0) { | ||
| double v = 1.0; | ||
| y = -bessely(v, z); | ||
| } else { | ||
| double kp1 = (double)(k + 1); | ||
| double km1 = (double)(k - 1); | ||
| y = (bessely(km1, z) - bessely(kp1, z)) / 2.0; | ||
| } | ||
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| // Must flip sign for negative k and odd k. | ||
| if (k < 0 && ((k % 2) != 0)) { | ||
| y = -y; | ||
| } | ||
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| return y; | ||
| } | ||
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| } // namespace mathieu | ||
| } // namespace xsf | ||
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| #endif // #ifndef BESSELJYD_H |
| Original file line number | Diff line number | Diff line change |
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| @@ -0,0 +1,210 @@ | ||
| #ifndef MAKE_MATRIX_H | ||
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Member
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. could a |
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| #define MAKE_MATRIX_H | ||
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| #include "../config.h" | ||
| #include "../error.h" | ||
| #include "matrix_utils.h" | ||
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| /* | ||
| * | ||
| * This is part of the Mathieu function suite -- a reimplementation | ||
| * of the Mathieu functions for Scipy. This file holds the functions | ||
| * which make the recursion matrices. | ||
| * | ||
| * Stuart Brorson, Summer 2025. | ||
| * | ||
| */ | ||
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| #define SQRT2 1.414213562373095 | ||
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Member
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. There's a |
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| namespace xsf { | ||
| namespace mathieu { | ||
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| /*----------------------------------------------- | ||
| This creates the recurrence relation matrix for | ||
| the even-even Mathieu fcns (ce_2n). | ||
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| Inputs: | ||
| N = matrix size (related to max order desired). | ||
| q = shape parameter. | ||
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| Output: | ||
| A = recurrence matrix (must be calloc'ed in caller). | ||
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| Return: | ||
| return code = SF_ERROR_OK if OK. | ||
| -------------------------------------------------*/ | ||
| int make_matrix_ee(int N, double q, double *A) { | ||
| int j; | ||
| int i; | ||
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| // Symmetrize matrix here, then fix in caller. | ||
| i = MATRIX_IDX(N, 0, 1); | ||
| A[i] = SQRT2 * q; | ||
| i = MATRIX_IDX(N, 1, 0); | ||
| A[i] = SQRT2 * q; | ||
| i = MATRIX_IDX(N, 1, 1); | ||
| A[i] = 4.0; | ||
| i = MATRIX_IDX(N, 1, 2); | ||
| A[i] = q; | ||
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| for (j = 2; j <= N - 2; j++) { | ||
| i = MATRIX_IDX(N, j, j - 1); | ||
| A[i] = q; | ||
| i = MATRIX_IDX(N, j, j); | ||
| A[i] = (2.0 * j) * (2.0 * j); | ||
| i = MATRIX_IDX(N, j, j + 1); | ||
| A[i] = q; | ||
| } | ||
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| i = MATRIX_IDX(N, N - 1, N - 2); | ||
| A[i] = q; | ||
| i = MATRIX_IDX(N, N - 1, N - 1); | ||
| A[i] = (2.0 * (N - 1)) * (2.0 * (N - 1)); | ||
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| return SF_ERROR_OK; | ||
| } | ||
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| /*----------------------------------------------- | ||
| This creates the recurrence relation matrix for the | ||
| even-odd Mathieu fcns (ce_2n+1). | ||
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| Inputs: | ||
| N = matrix size (related to max order desired). | ||
| q = shape parameter. | ||
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| Output: | ||
| A = recurrence matrix (calloc in caller). | ||
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| Return: | ||
| return code = SF_ERROR_OK if OK. | ||
| -------------------------------------------------*/ | ||
| int make_matrix_eo(int N, double q, double *A) { | ||
| int j; | ||
| int i; | ||
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| i = MATRIX_IDX(N, 0, 0); | ||
| A[i] = 1.0 + q; | ||
| i = MATRIX_IDX(N, 0, 1); | ||
| A[i] = q; | ||
| i = MATRIX_IDX(N, 1, 0); | ||
| A[i] = q; | ||
| i = MATRIX_IDX(N, 1, 1); | ||
| A[i] = 9.0; | ||
| i = MATRIX_IDX(N, 1, 2); | ||
| A[i] = q; | ||
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| for (j = 2; j <= N - 2; j++) { | ||
| i = MATRIX_IDX(N, j, j - 1); | ||
| A[i] = q; | ||
| i = MATRIX_IDX(N, j, j); | ||
| A[i] = (2.0 * j + 1.0) * (2.0 * j + 1.0); | ||
| i = MATRIX_IDX(N, j, j + 1); | ||
| A[i] = q; | ||
| } | ||
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| i = MATRIX_IDX(N, N - 1, N - 2); | ||
| A[i] = q; | ||
| i = MATRIX_IDX(N, N - 1, N - 1); | ||
| A[i] = (2.0 * (N - 1) + 1.0) * (2.0 * (N - 1) + 1.0); | ||
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| return SF_ERROR_OK; | ||
| } | ||
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| /*----------------------------------------------- | ||
| This creates the recurrence relation matrix for | ||
| the odd-even Mathieu fcns (se_2n) -- sometimes called | ||
| se_2n+2. | ||
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| Inputs: | ||
| N = matrix size (related to max order desired). | ||
| q = shape parameter. | ||
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| Output: | ||
| A = recurrence matrix (calloc in caller). | ||
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| Return: | ||
| return code = SF_ERROR_OK if OK. | ||
| -------------------------------------------------*/ | ||
| int make_matrix_oe(int N, double q, double *A) { | ||
| int j; | ||
| int i; | ||
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| i = MATRIX_IDX(N, 0, 0); | ||
| A[i] = 4.0; | ||
| i = MATRIX_IDX(N, 0, 1); | ||
| A[i] = q; | ||
| i = MATRIX_IDX(N, 1, 0); | ||
| A[i] = q; | ||
| i = MATRIX_IDX(N, 1, 1); | ||
| A[i] = 16.0; | ||
| i = MATRIX_IDX(N, 1, 2); | ||
| A[i] = q; | ||
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| for (j = 2; j <= N - 2; j++) { | ||
| i = MATRIX_IDX(N, j, j - 1); | ||
| A[i] = q; | ||
| i = MATRIX_IDX(N, j, j); | ||
| A[i] = (2.0 * (j + 1)) * (2.0 * (j + 1)); | ||
| i = MATRIX_IDX(N, j, j + 1); | ||
| A[i] = q; | ||
| } | ||
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| i = MATRIX_IDX(N, N - 1, N - 2); | ||
| A[i] = q; | ||
| i = MATRIX_IDX(N, N - 1, N - 1); | ||
| A[i] = (2.0 * N) * (2.0 * N); | ||
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| return SF_ERROR_OK; | ||
| } | ||
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| /*----------------------------------------------- | ||
| This creates the recurrence relation matrix for | ||
| the odd-odd Mathieu fcns (se_2n+1). | ||
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| Inputs: | ||
| N = matrix size (related to max order desired). | ||
| q = shape parameter. | ||
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| Output: | ||
| A = recurrence matrix (calloc in caller). | ||
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| Return: | ||
| return code = SF_ERROR_OK if OK. | ||
| -------------------------------------------------*/ | ||
| int make_matrix_oo(int N, double q, double *A) { | ||
| int j; | ||
| int i; | ||
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| i = MATRIX_IDX(N, 0, 0); | ||
| A[i] = 1.0 - q; | ||
| i = MATRIX_IDX(N, 0, 1); | ||
| A[i] = q; | ||
| i = MATRIX_IDX(N, 1, 0); | ||
| A[i] = q; | ||
| i = MATRIX_IDX(N, 1, 1); | ||
| A[i] = 9.0; | ||
| i = MATRIX_IDX(N, 1, 2); | ||
| A[i] = q; | ||
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| for (j = 2; j <= N - 2; j++) { | ||
| i = MATRIX_IDX(N, j, j - 1); | ||
| A[i] = q; | ||
| i = MATRIX_IDX(N, j, j); | ||
| A[i] = (2.0 * j + 1.0) * (2.0 * j + 1.0); | ||
| i = MATRIX_IDX(N, j, j + 1); | ||
| A[i] = q; | ||
| } | ||
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| i = MATRIX_IDX(N, N - 1, N - 2); | ||
| A[i] = q; | ||
| i = MATRIX_IDX(N, N - 1, N - 1); | ||
| A[i] = (2.0 * N - 1.0) * (2.0 * N - 1.0); | ||
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| return SF_ERROR_OK; | ||
| } | ||
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| } // namespace mathieu | ||
| } // namespace xsf | ||
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| #endif // #ifndef MAKE_MATRIX_H | ||
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There's a backport of
std::mdspan(from C++23) inkokkos/mdspan.hppthat sounds like a perfect fit for these functions. It's already used quite a lot in xsf, e.g. inlegendre.h.