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Annotation of OpenXM/src/asir-contrib/packages/doc/nk_fb_gen_c/nk_fb_gen_c.oxg, Revision 1.3

1.3     ! takayama    1: $OpenXM: OpenXM/src/asir-contrib/packages/doc/nk_fb_gen_c/nk_fb_gen_c.oxg,v 1.2 2014/04/03 07:34:30 takayama Exp $
        !             2: test1.c, test1.h はこのプログラムで生成された例. data, 初期値はすでに設定済.
        !             3: /*  まだ書いてない.
1.1       takayama    4: begin: include|
                      5:
                      6: @include nk_fb_gen_c_intro.ja
                      7:
                      8: end:
                      9: */
                     10:
1.3     ! takayama   11: /* まだ書いてない.
1.1       takayama   12: begin: include|
                     13:
                     14: @include nk_fb_gen_c_intro.en
                     15:
                     16: end:
                     17: */
                     18:
                     19: /*&usage-ja
                     20: begin:  nk_fb_gen_c.gen_c(N)
1.3     ! takayama   21:   {N} 次元 Fisher-Bingham 分布についての最尤推定を HGD 法(holonomic gradient descent) でやるための C のプログラムを生成する.
1.1       takayama   22: description:
1.3     ! takayama   23:    この関数により, testN.c, testN.h なる二つの C のプログラムが生成される.
        !            24:    testN.c にデータ, 最尤推定探索用のパラメータ初期値を設定する.
        !            25:    コマンド
1.1       takayama   26:    @quotation
                     27:    @code{gcc testN.c $OpenXM_HOME/lib/libko_fb.a -lgsl -lblas }
                     28:    @end quotation
1.3     ! takayama   29:    で実行可能形式のファイルを作成する. @*
        !            30:    なお,
        !            31:    libko_fb.a は @file{OpenXM/src/hgm/fisher-bingham/src/} で @code{make install} することにより生成される.
        !            32:    またシステムには gsl がインストールされていないといけない.
        !            33:    @file{OpenXM/src/hgm/fisher-bingham/src/Testdata} にサンプルの
        !            34:   データ, 最尤推定探索用のパラメータ初期値がある. @*
        !            35:   testN.h の @code{#define MULTIMIN_FDFMINIMIZER_TYPE} で gsl のどの最適化関数を呼び出すか変更できる.
        !            36:   testN.h の @code{#define ODEIV_STEP_TYPE} で gsl のどの常微分方程式数値解析関数を呼び出すか変更できる. @*
        !            37:   アルゴリズムの詳細は,
1.1       takayama   38:   T. Koyama, H. Nakayama, K. Nishiyama, N. Takayama, Holonomic Gradient Descent for the Fisher-Bingham Distribution on the d-dimensional Sphere, Computational Statistics (2013),
                     39:   @url{http://dx.doi.org/10.1007/s00180-013-0456-z}
1.3     ! takayama   40:   を参照. @*
1.1       takayama   41:   Authors; T.Koyama, H.Nakayama, K.Nishiyama, N.Takayama.
                     42: example:
                     43: [1854] load("nk_fb_gen_c.rr");
1.3     ! takayama   44: [2186]  nk_fb_gen_c.gen_c(1);     S^1 の問題を解く program を生成.
1.1       takayama   45: generate test1.h
                     46: generate test1.c
                     47: 1
                     48: [2187] quit;
                     49: $ emacs test1.c &
                     50:
                     51:
                     52:         Write data here.
1.3     ! takayama   53: とコメントに書かれているところの後
        !            54: に $(OpenXM_HOME)/src/hgm/fisher-bingham/Testdata/s1_wind_data.h を挿入.
        !            55: 保存終了.
1.1       takayama   56:
                     57: $ gcc test1.c $OpenXM_HOME/lib/libko_fb.a -lgsl -lblas
                     58: $ ./a.out
                     59:   --- snip
                     60: points = [1.11945, 3.33044, -0.469454, 0.904504, -0.770373]
                     61: values = [3.4421, 1.13891, -0.0217944, 2.28474]
                     62: grad ; 0.005644 -0.033429 -0.005644 0.045820 0.047695
                     63: norm(grad) ; 0.074535
                     64:   --- snip
                     65:
1.3     ! takayama   66: ここで, points が parameter x11,x12,x22,y1,y2 の推定値.
        !            67: Value 3.4421 が 尤度値の逆数で, これが最小化されている.
1.1       takayama   68: end:
                     69: */
                     70:
                     71: /*&usage-en
                     72: begin:  nk_fb_gen_c.gen_c(N)
                     73:   It generates a C program to make a MLE (maximal likelihood estimate)
                     74:   by the HGD (holonomic gradient descent)
                     75:  for {N} dimensional Fisher-Bingham distribution.
                     76: description:
                     77:    This function generates two C programs testN.c and testN.h.
                     78:    After setting data and an initial point to make MLE in testN.c,
                     79:    build an executable file by the command
                     80:    @quotation
                     81:    @code{gcc testN.c $OpenXM_HOME/lib/libko_fb.a -lgsl -lblas }
                     82:    @end quotation
                     83:    The libray file libko_fb.a is generated by
                     84:    @code{make install} in the folder  @file{OpenXM/src/hgm/fisher-bingham/src/}
                     85:    The GSL (Gnu Scientific Library) should also be installed in the system.
                     86:    Sample data and initial points are in @file{OpenXM/src/hgm/fisher-bingham/src/Testdata}.
                     87:    @*
1.2       takayama   88:   The definition @code{#define MULTIMIN_FDFMINIMIZER_TYPE} in testN.h specifies
                     89:   an optimization problem solver of gsl.
                     90:   The definition @code{#define ODEIV_STEP_TYPE} in testN.h specifies a solver of the ordinary differential
                     91:   equation of gsl. @*
1.1       takayama   92:   As to the algorithm, refer to
                     93:   T. Koyama, H. Nakayama, K. Nishiyama, N. Takayama, Holonomic Gradient Descent for the Fisher-Bingham Distribution on the d-dimensional Sphere, Computational Statistics (2013),
                     94:   @url{http://dx.doi.org/10.1007/s00180-013-0456-z} @*
                     95:   Authors; T.Koyama, H.Nakayama, K.Nishiyama, N.Takayama.
                     96: example:
                     97: [1854] load("nk_fb_gen_c.rr");
                     98: [2186]  nk_fb_gen_c.gen_c(1);     Generate a program to solve MLE on S^1
                     99: generate test1.h
                    100: generate test1.c
                    101: 1
                    102: [2187] quit;
                    103: $ emacs test1.c &
                    104:
                    105: Find a line which contains
                    106:      Write data here
                    107: and insert $(OpenXM_HOME)/src/hgm/fisher-bingham/Testdata/s1_wind_data.h.
                    108: after this line.
                    109: Save and quit emacs.
                    110:
                    111: $ gcc test1.c $OpenXM_HOME/lib/libko_fb.a -lgsl -lblas
                    112: $ ./a.out
                    113:   --- snip
                    114: points = [1.11945, 3.33044, -0.469454, 0.904504, -0.770373]
                    115: values = [3.4421, 1.13891, -0.0217944, 2.28474]
                    116: grad ; 0.005644 -0.033429 -0.005644 0.045820 0.047695
                    117: norm(grad) ; 0.074535
                    118:   --- snip
                    119:
                    120: where ``points'' is the estimated value of the parameter x11,x12,x22,y1,y2.
                    121: Value 3.4421 is the inverse of the likelihood which is minimized.
                    122: end:
                    123: */
                    124:
                    125: