From 4a8867c2158be841f1dc9f0a509c68c4fb31aa83 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?IOhannes=20m=20zm=C3=B6lnig?= Date: Thu, 19 May 2005 14:14:53 +0000 Subject: made all local functions static (in order to not interfere with each other) svn path=/trunk/externals/ann/; revision=3029 --- src/ann_mlp.c | 46 +++++++++++++++++++++++----------------------- src/ann_td.c | 54 +++++++++++++++++++++++++++--------------------------- 2 files changed, 50 insertions(+), 50 deletions(-) diff --git a/src/ann_mlp.c b/src/ann_mlp.c index e01b203..c8c4cb3 100755 --- a/src/ann_mlp.c +++ b/src/ann_mlp.c @@ -36,7 +36,7 @@ typedef struct _ann_mlp { t_outlet *l_out, *f_out; } t_ann_mlp; -void help(t_ann_mlp *x) +static void help(t_ann_mlp *x) { post(""); post("ann_mlp: neural nets for PD"); @@ -48,7 +48,7 @@ void help(t_ann_mlp *x) } -void createFann(t_ann_mlp *x, t_symbol *sl, int argc, t_atom *argv) +static void createFann(t_ann_mlp *x, t_symbol *sl, int argc, t_atom *argv) { unsigned int num_input = 2; unsigned int num_output = 1; @@ -108,7 +108,7 @@ void createFann(t_ann_mlp *x, t_symbol *sl, int argc, t_atom *argv) } } -void print_status(t_ann_mlp *x) +static void print_status(t_ann_mlp *x) { if (x->mode == TRAIN) post("nn:training"); @@ -116,7 +116,7 @@ void print_status(t_ann_mlp *x) post("nn:running"); } -void train(t_ann_mlp *x) +static void train(t_ann_mlp *x) { x->mode=TRAIN; if (x->ann == 0) @@ -128,13 +128,13 @@ void train(t_ann_mlp *x) print_status(x); } -void run(t_ann_mlp *x) +static void run(t_ann_mlp *x) { x->mode=RUN; print_status(x); } -void set_mode(t_ann_mlp *x, t_symbol *sl, int argc, t_atom *argv) +static void set_mode(t_ann_mlp *x, t_symbol *sl, int argc, t_atom *argv) { if (argc<1) { @@ -149,7 +149,7 @@ void set_mode(t_ann_mlp *x, t_symbol *sl, int argc, t_atom *argv) -void train_on_file(t_ann_mlp *x, t_symbol *sl, int argc, t_atom *argv) +static void train_on_file(t_ann_mlp *x, t_symbol *sl, int argc, t_atom *argv) { if (x->ann == 0) { @@ -174,7 +174,7 @@ void train_on_file(t_ann_mlp *x, t_symbol *sl, int argc, t_atom *argv) post("nn: finished training on file %s", x->filenametrain->s_name); } -void set_desired_error(t_ann_mlp *x, t_symbol *sl, int argc, t_atom *argv) +static void set_desired_error(t_ann_mlp *x, t_symbol *sl, int argc, t_atom *argv) { float desired_error = (float)0.001; if (00) @@ -202,7 +202,7 @@ void set_max_iterations(t_ann_mlp *x, t_symbol *sl, int argc, t_atom *argv) } } -void set_iterations_between_reports(t_ann_mlp *x, t_symbol *sl, int argc, t_atom *argv) +static void set_iterations_between_reports(t_ann_mlp *x, t_symbol *sl, int argc, t_atom *argv) { unsigned int iterations_between_reports = 1000; @@ -221,7 +221,7 @@ void set_iterations_between_reports(t_ann_mlp *x, t_symbol *sl, int argc, t_atom // run the ann using floats in list passed to the inlet as input values // and send result to outlet as list of float -void run_the_net(t_ann_mlp *x, t_symbol *sl, int argc, t_atom *argv) +static void run_the_net(t_ann_mlp *x, t_symbol *sl, int argc, t_atom *argv) { int i=0; fann_type input[MAXINPUT]; @@ -275,7 +275,7 @@ void run_the_net(t_ann_mlp *x, t_symbol *sl, int argc, t_atom *argv) } -void train_on_the_fly(t_ann_mlp *x, t_symbol *sl, int argc, t_atom *argv) +static void train_on_the_fly(t_ann_mlp *x, t_symbol *sl, int argc, t_atom *argv) { int i=0; fann_type input[MAXINPUT]; @@ -334,7 +334,7 @@ void train_on_the_fly(t_ann_mlp *x, t_symbol *sl, int argc, t_atom *argv) } -void manage_list(t_ann_mlp *x, t_symbol *sl, int argc, t_atom *argv) +static void manage_list(t_ann_mlp *x, t_symbol *sl, int argc, t_atom *argv) { if (x->mode) run_the_net(x, sl, argc, argv); @@ -344,7 +344,7 @@ void manage_list(t_ann_mlp *x, t_symbol *sl, int argc, t_atom *argv) } } -void set_filename(t_ann_mlp *x, t_symbol *sl, int argc, t_atom *argv) +static void set_filename(t_ann_mlp *x, t_symbol *sl, int argc, t_atom *argv) { if (argc>0) { x->filename = atom_gensym(argv); @@ -355,7 +355,7 @@ void set_filename(t_ann_mlp *x, t_symbol *sl, int argc, t_atom *argv) post("nn:filename set to %s", x->filename->s_name); } -void load_ann_from_file(t_ann_mlp *x, t_symbol *sl, int argc, t_atom *argv) +static void load_ann_from_file(t_ann_mlp *x, t_symbol *sl, int argc, t_atom *argv) { if (argc>0) { x->filename = atom_gensym(argv); @@ -367,7 +367,7 @@ void load_ann_from_file(t_ann_mlp *x, t_symbol *sl, int argc, t_atom *argv) post("nn:ann loaded fom file %s", x->filename->s_name); } -void save_ann_to_file(t_ann_mlp *x, t_symbol *sl, int argc, t_atom *argv) +static void save_ann_to_file(t_ann_mlp *x, t_symbol *sl, int argc, t_atom *argv) { if (argc>0) { x->filename = atom_gensym(argv); @@ -383,7 +383,7 @@ void save_ann_to_file(t_ann_mlp *x, t_symbol *sl, int argc, t_atom *argv) } // functions for training algo: -void set_FANN_TRAIN_INCREMENTAL(t_ann_mlp *x) +static void set_FANN_TRAIN_INCREMENTAL(t_ann_mlp *x) { if (x->ann == 0) { @@ -394,7 +394,7 @@ void set_FANN_TRAIN_INCREMENTAL(t_ann_mlp *x) post("nn:training algorithm set to FANN_TRAIN_INCREMENTAL"); } } -void set_FANN_TRAIN_BATCH(t_ann_mlp *x) +static void set_FANN_TRAIN_BATCH(t_ann_mlp *x) { if (x->ann == 0) { @@ -405,7 +405,7 @@ void set_FANN_TRAIN_BATCH(t_ann_mlp *x) post("nn:training algorithm set to FANN_TRAIN_BATCH"); } } -void set_FANN_TRAIN_RPROP(t_ann_mlp *x) +static void set_FANN_TRAIN_RPROP(t_ann_mlp *x) { if (x->ann == 0) { @@ -416,7 +416,7 @@ void set_FANN_TRAIN_RPROP(t_ann_mlp *x) post("nn:training algorithm set to FANN_TRAIN_RPROP"); } } -void set_FANN_TRAIN_QUICKPROP(t_ann_mlp *x) +static void set_FANN_TRAIN_QUICKPROP(t_ann_mlp *x) { if (x->ann == 0) { @@ -428,7 +428,7 @@ void set_FANN_TRAIN_QUICKPROP(t_ann_mlp *x) } } -void set_activation_function_output(t_ann_mlp *x, t_symbol *sl, int argc, t_atom *argv) +static void set_activation_function_output(t_ann_mlp *x, t_symbol *sl, int argc, t_atom *argv) { t_symbol *parametro = 0; int funzione = 0; @@ -464,7 +464,7 @@ void set_activation_function_output(t_ann_mlp *x, t_symbol *sl, int argc, t_atom } -void print_ann_details(t_ann_mlp *x) +static void print_ann_details(t_ann_mlp *x) { if (x->ann == 0) { @@ -490,7 +490,7 @@ void print_ann_details(t_ann_mlp *x) } -void *nn_new(t_symbol *s, int argc, t_atom *argv) +static void *nn_new(t_symbol *s, int argc, t_atom *argv) { t_ann_mlp *x = (t_ann_mlp *)pd_new(ann_mlp_class); x->l_out = outlet_new(&x->x_obj, &s_list); diff --git a/src/ann_td.c b/src/ann_td.c index 0184139..a519c2f 100755 --- a/src/ann_td.c +++ b/src/ann_td.c @@ -40,7 +40,7 @@ typedef struct _ann_td { t_outlet *l_out, *f_out; } t_ann_td; -void help(t_ann_td *x) +static void help(t_ann_td *x) { post(""); post("ann_td:time delay neural networks for PD"); @@ -52,7 +52,7 @@ void help(t_ann_td *x) } -void deallocate_inputs(t_ann_td *x) +static void deallocate_inputs(t_ann_td *x) { if (x->inputs != 0) { @@ -61,7 +61,7 @@ void deallocate_inputs(t_ann_td *x) } } -void allocate_inputs(t_ann_td *x) +static void allocate_inputs(t_ann_td *x) { unsigned int i; deallocate_inputs(x); @@ -70,7 +70,7 @@ void allocate_inputs(t_ann_td *x) for (i=0; i<(x->frames * x->num_input); i++) x->inputs[i]=0.f; } -void createFann(t_ann_td *x, t_symbol *sl, int argc, t_atom *argv) +static void createFann(t_ann_td *x, t_symbol *sl, int argc, t_atom *argv) { unsigned int num_input = 2; unsigned int num_output = 1; @@ -144,7 +144,7 @@ void createFann(t_ann_td *x, t_symbol *sl, int argc, t_atom *argv) } } -void print_status(t_ann_td *x) +static void print_status(t_ann_td *x) { if (x->mode == TRAIN) post("ann_td:training"); @@ -152,7 +152,7 @@ void print_status(t_ann_td *x) post("ann_td:running"); } -void train(t_ann_td *x) +static void train(t_ann_td *x) { x->mode=TRAIN; if (x->ann == 0) @@ -164,13 +164,13 @@ void train(t_ann_td *x) print_status(x); } -void run(t_ann_td *x) +static void run(t_ann_td *x) { x->mode=RUN; print_status(x); } -void set_mode(t_ann_td *x, t_symbol *sl, int argc, t_atom *argv) +static void set_mode(t_ann_td *x, t_symbol *sl, int argc, t_atom *argv) { if (argc<1) { @@ -185,7 +185,7 @@ void set_mode(t_ann_td *x, t_symbol *sl, int argc, t_atom *argv) -void train_on_file(t_ann_td *x, t_symbol *sl, int argc, t_atom *argv) +static void train_on_file(t_ann_td *x, t_symbol *sl, int argc, t_atom *argv) { if (x->ann == 0) { @@ -210,7 +210,7 @@ void train_on_file(t_ann_td *x, t_symbol *sl, int argc, t_atom *argv) post("ann_td: finished training on file %s", x->filenametrain->s_name); } -void set_desired_error(t_ann_td *x, t_symbol *sl, int argc, t_atom *argv) +static void set_desired_error(t_ann_td *x, t_symbol *sl, int argc, t_atom *argv) { float desired_error = (float)0.001; if (00) @@ -238,7 +238,7 @@ void set_max_iterations(t_ann_td *x, t_symbol *sl, int argc, t_atom *argv) } } -void set_iterations_between_reports(t_ann_td *x, t_symbol *sl, int argc, t_atom *argv) +static void set_iterations_between_reports(t_ann_td *x, t_symbol *sl, int argc, t_atom *argv) { unsigned int iterations_between_reports = 1000; @@ -255,7 +255,7 @@ void set_iterations_between_reports(t_ann_td *x, t_symbol *sl, int argc, t_atom } -void scale_inputs(t_ann_td *x) +static void scale_inputs(t_ann_td *x) { unsigned int j; unsigned int k; @@ -273,7 +273,7 @@ void scale_inputs(t_ann_td *x) // run the ann using floats in list passed to the inlet as input values // and send result to outlet as list of float -void run_the_net(t_ann_td *x, t_symbol *sl, int argc, t_atom *argv) +static void run_the_net(t_ann_td *x, t_symbol *sl, int argc, t_atom *argv) { int i=0; unsigned j=0; @@ -337,7 +337,7 @@ void run_the_net(t_ann_td *x, t_symbol *sl, int argc, t_atom *argv) } -void train_on_the_fly(t_ann_td *x, t_symbol *sl, int argc, t_atom *argv) +static void train_on_the_fly(t_ann_td *x, t_symbol *sl, int argc, t_atom *argv) { int i=0; unsigned int j=0; @@ -398,7 +398,7 @@ void train_on_the_fly(t_ann_td *x, t_symbol *sl, int argc, t_atom *argv) } -void manage_list(t_ann_td *x, t_symbol *sl, int argc, t_atom *argv) +static void manage_list(t_ann_td *x, t_symbol *sl, int argc, t_atom *argv) { if (x->mode) run_the_net(x, sl, argc, argv); @@ -408,7 +408,7 @@ void manage_list(t_ann_td *x, t_symbol *sl, int argc, t_atom *argv) } } -void set_filename(t_ann_td *x, t_symbol *sl, int argc, t_atom *argv) +static void set_filename(t_ann_td *x, t_symbol *sl, int argc, t_atom *argv) { if (argc>0) { x->filename = atom_gensym(argv); @@ -419,7 +419,7 @@ void set_filename(t_ann_td *x, t_symbol *sl, int argc, t_atom *argv) post("nn:filename set to %s", x->filename->s_name); } -void load_ann_from_file(t_ann_td *x, t_symbol *sl, int argc, t_atom *argv) +static void load_ann_from_file(t_ann_td *x, t_symbol *sl, int argc, t_atom *argv) { if (x->ins_frames_set==0) { @@ -439,7 +439,7 @@ void load_ann_from_file(t_ann_td *x, t_symbol *sl, int argc, t_atom *argv) allocate_inputs(x); } -void save_ann_to_file(t_ann_td *x, t_symbol *sl, int argc, t_atom *argv) +static void save_ann_to_file(t_ann_td *x, t_symbol *sl, int argc, t_atom *argv) { if (argc>0) { x->filename = atom_gensym(argv); @@ -455,7 +455,7 @@ void save_ann_to_file(t_ann_td *x, t_symbol *sl, int argc, t_atom *argv) } // functions for training algo: -void set_FANN_TRAIN_INCREMENTAL(t_ann_td *x) +static void set_FANN_TRAIN_INCREMENTAL(t_ann_td *x) { if (x->ann == 0) { @@ -466,7 +466,7 @@ void set_FANN_TRAIN_INCREMENTAL(t_ann_td *x) post("nn:training algorithm set to FANN_TRAIN_INCREMENTAL"); } } -void set_FANN_TRAIN_BATCH(t_ann_td *x) +static void set_FANN_TRAIN_BATCH(t_ann_td *x) { if (x->ann == 0) { @@ -477,7 +477,7 @@ void set_FANN_TRAIN_BATCH(t_ann_td *x) post("nn:training algorithm set to FANN_TRAIN_BATCH"); } } -void set_FANN_TRAIN_RPROP(t_ann_td *x) +static void set_FANN_TRAIN_RPROP(t_ann_td *x) { if (x->ann == 0) { @@ -488,7 +488,7 @@ void set_FANN_TRAIN_RPROP(t_ann_td *x) post("nn:training algorithm set to FANN_TRAIN_RPROP"); } } -void set_FANN_TRAIN_QUICKPROP(t_ann_td *x) +static void set_FANN_TRAIN_QUICKPROP(t_ann_td *x) { if (x->ann == 0) { @@ -500,7 +500,7 @@ void set_FANN_TRAIN_QUICKPROP(t_ann_td *x) } } -void set_activation_function_output(t_ann_td *x, t_symbol *sl, int argc, t_atom *argv) +static void set_activation_function_output(t_ann_td *x, t_symbol *sl, int argc, t_atom *argv) { t_symbol *parametro = 0; int funzione = 0; @@ -536,7 +536,7 @@ void set_activation_function_output(t_ann_td *x, t_symbol *sl, int argc, t_atom } -void print_ann_details(t_ann_td *x) +static void print_ann_details(t_ann_td *x) { if (x->ann == 0) { @@ -561,14 +561,14 @@ void print_ann_details(t_ann_td *x) } } -void set_num_input_frames(t_ann_td *x, t_floatarg ins, t_floatarg frames) +static void set_num_input_frames(t_ann_td *x, t_floatarg ins, t_floatarg frames) { x->num_input = ins; x->frames = frames; x->ins_frames_set=1; } -void *nn_new(t_symbol *s, int argc, t_atom *argv) +static void *nn_new(t_symbol *s, int argc, t_atom *argv) { t_ann_td *x = (t_ann_td *)pd_new(ann_td_class); x->l_out = outlet_new(&x->x_obj, &s_list); -- cgit v1.2.1