int main()
{
Graph my_graph;
my_graph = Init_Graph();
Create_Graph(my_graph , "./dij_graph.info");
Print_Graph(my_graph);
printf("********************\n");
Dijkstra(my_graph , 0);
}
/*
* === FUNCTION ======================================================================
* Name: main
* Description:
* =====================================================================================
*/
int
main ( int argc, char *argv[] )
{
Graph my_graph;
my_graph = Init_Graph();
Create_Graph(my_graph , "./dij_graph.info");
Print_Graph(my_graph);
DIJ(my_graph , 0);
return EXIT_SUCCESS;
} /* ---------- end of function main ---------- */
/*
* === FUNCTION ======================================================================
* Name: main
* Description:
* =====================================================================================
*/
int
main ( int argc, char *argv[] )
{
Graph my_graph ;
my_graph = Init_Graph();
Create_Graph(my_graph , "./path_graph.info");
Print_Graph(my_graph);
printf("\n+++++++++++++++++++++++++\n");
Critical_Path(my_graph);
return EXIT_SUCCESS;
} /* ---------- end of function main ---------- */
/*
* === FUNCTION ======================================================================
* Name: main
* Description:
* =====================================================================================
*/
int
main ( int argc, char *argv[] )
{
int k=0;
Graph my_graph;
Graph my_graph1;
my_graph = Init_Graph();
my_graph1 = Init_Graph();
Create_Graph(my_graph , "./udg_graph.info");
Create_Graph(my_graph1 , "./udg_graph.info");
Print_Graph(my_graph);
printf("*******Get vertex**********\n");
printf("the v3 name is :%s\n",Get_Vertex(my_graph , 2));
printf("*******Put vertex**********\n");
Put_Vertex(my_graph , "V3" ,"XXOO");
printf("the v3 name after changed is :%s\n",Get_Vertex(my_graph , 2));
Put_Vertex(my_graph , "XXOO" ,"V3");
printf("******First Adjacent*********\n");
printf("The V1 first adjacent is :%s\n",Get_Vertex(my_graph,First_Adjacent(my_graph , "V1")));
printf("******Next Adjacent*********\n");
printf("and next adjacent is :");
k = Next_Adjacent(my_graph , "V1",Get_Vertex(my_graph,First_Adjacent(my_graph , "V1")));
while(k!=-1)
{
printf("%s\t",Get_Vertex(my_graph,k));
k= Next_Adjacent(my_graph , "V1", Get_Vertex(my_graph , k));
}
printf("\n");
printf("****** Insert_Vertex*********\n");
Insert_Vertex(my_graph , "QQ");
Print_Graph(my_graph);
printf("****** delete_Vertex*********\n");
Delete_Vertex(my_graph , "V2");
Print_Graph(my_graph);
printf("********Insert Arcs*********\n");
Delete_Vertex(my_graph , "QQ");
Insert_Vertex(my_graph , "V2");
Insert_Arcs(my_graph , "V1","V2");
Insert_Arcs(my_graph , "V3","V2");
Insert_Arcs(my_graph , "V5","V2");
Print_Graph(my_graph);
printf("********Delete Arcs*********\n");
Delete_Arcs(my_graph , "V1", "V2");
Print_Graph(my_graph);
printf("craete a new graph---------->\n");
Print_Graph(my_graph1);
system("sleep 5");
printf("************DFS_TRAVERse**********\n");
DFS_Traverse(my_graph1 , Visit);
system("sleep 5");
printf("***********BFS_TRAVERE*************\n");
BFS_Traverse(my_graph1 , Visit);
free(my_graph);
my_graph=NULL;
return EXIT_SUCCESS;
} /* ---------- end of function main ---------- */
int main()
{
#if 0
char *filepath = "../data/fly_neuron_n2/graph_d.swc";
Neuron_Structure *ns = Neuron_Structure_From_Swc_File(filepath);
Neuron_Component_Arraylist *comp_array =
Neuron_Structure_Branch_Point(ns);
filepath = "../data/fly_neuron_n2.tif";
Stack *stack = Read_Stack(filepath);
Translate_Stack(stack, COLOR, 1);
int i;
Stack_Draw_Workspace *ws = New_Stack_Draw_Workspace();
for (i = 0; i < comp_array->length; i++) {
Neuron_Component_Draw_Stack(comp_array->array + i, stack, ws);
}
Kill_Stack_Draw_Workspace(ws);
Write_Stack("../data/test.tif", stack);
#endif
#if 0
Stack *stack = NULL;
Locseg_Chain *chain1 = Read_Locseg_Chain("../data/fly_neuron_n3/chain0.tb");
Locseg_Chain *chain2 = Read_Locseg_Chain("../data/fly_neuron_n3/chain10.tb");
Connection_Test_Workspace *ws = New_Connection_Test_Workspace();
Connection_Test_Workspace_Read_Resolution(ws, "../data/fly_neuron_n1.res");
Neurocomp_Conn conn;
conn.mode = NEUROCOMP_CONN_HL;
Locseg_Chain_Connection_Test(chain1, chain2, stack, 1.0, &conn, ws);
Print_Neurocomp_Conn(&conn);
#endif
#if 0
Locseg_Chain **chain = (Locseg_Chain**) malloc(sizeof(Locseg_Chain*) * 3);
chain[0] = Read_Locseg_Chain("../data/mouse_single_org/chain4.tb");
chain[1] = Read_Locseg_Chain("../data/mouse_single_org/chain19.tb");
chain[2] = Read_Locseg_Chain("../data/mouse_single_org/chain64.tb");
Stack *signal = Read_Stack("../data/mouse_single_org.tif");
Connection_Test_Workspace *ctw = New_Connection_Test_Workspace();
FILE *fp = fopen("../data/mouse_single_org.res", "r");
darray_fscanf(fp, ctw->resolution, 3);
Neuron_Component *chain_array = Make_Neuron_Component_Array(3);
int i;
for (i = 0; i < 3; i++) {
Set_Neuron_Component(chain_array + i,
NEUROCOMP_TYPE_LOCSEG_CHAIN, chain[i]);
}
Neuron_Structure *ns = Locseg_Chain_Comp_Neurostruct(chain_array,
3, signal, 1.0, ctw);
Graph *graph = ns->graph;
Process_Neuron_Structure(ns);
Print_Neuron_Structure(ns);
Neuron_Structure_Crossover_Test(ns, 0.5375);
printf("\ncross over changed: \n");
Print_Neuron_Structure(ns);
#endif
#if 0
Neuron_Structure *ns = Make_Neuron_Structure(5);
Set_Neuron_Component(ns->comp, NEUROCOMP_TYPE_GEO3D_CIRCLE,
New_Geo3d_Circle());
Set_Neuron_Component(ns->comp + 1, NEUROCOMP_TYPE_GEO3D_CIRCLE,
New_Geo3d_Circle());
Set_Neuron_Component(ns->comp + 2, NEUROCOMP_TYPE_GEO3D_CIRCLE,
New_Geo3d_Circle());
Set_Neuron_Component(ns->comp + 3, NEUROCOMP_TYPE_GEO3D_CIRCLE,
New_Geo3d_Circle());
Set_Neuron_Component(ns->comp + 4, NEUROCOMP_TYPE_GEO3D_CIRCLE,
New_Geo3d_Circle());
NEUROCOMP_GEO3D_CIRCLE(ns->comp)->radius = 1.5;
NEUROCOMP_GEO3D_CIRCLE(ns->comp + 1)->radius = 2.5;
NEUROCOMP_GEO3D_CIRCLE(ns->comp + 2)->radius = 3.5;
NEUROCOMP_GEO3D_CIRCLE(ns->comp + 3)->radius = 4.5;
NEUROCOMP_GEO3D_CIRCLE(ns->comp + 4)->radius = 5.5;
ns->graph = Make_Graph(5, 4, 0);
//Graph_Add_Edge(ns->graph, 0, 1);
Graph_Add_Edge(ns->graph, 1, 3);
Graph_Add_Edge(ns->graph, 1, 4);
Graph_Add_Edge(ns->graph, 0, 2);
Graph_Set_Directed(ns->graph, TRUE);
Print_Graph(ns->graph);
Swc_Tree *tree = Neuron_Structure_To_Swc_Tree_Circle_Z(ns, 1.0, NULL);
Print_Swc_Tree(tree);
Swc_Tree_To_Dot_File(tree, "../data/test2.dot");
#endif
#if 0
int n;
Neuron_Component *chain_array = Dir_Locseg_Chain_Nc("../data/fly_neuron_n22",
"^chain.*\\.tb",
&n, NULL);
Neuron_Structure *ns =
Locseg_Chain_Comp_Neurostruct(chain_array, n, NULL, 1.0, NULL);
Process_Neuron_Structure(ns);
Neuron_Structure* ns2=
Neuron_Structure_Locseg_Chain_To_Circle(ns);
Neuron_Structure_To_Tree(ns2);
Graph_To_Dot_File(ns2->graph, "../data/test.dot");
Swc_Tree *tree =
Neuron_Structure_To_Swc_Tree_Circle_Z(ns2, 1.0, NULL);
Swc_Tree_Remove_Zigzag(tree);
//Swc_Tree_Tune_Fork(tree);
//Print_Swc_Tree(tree);
Write_Swc_Tree("../data/test.swc", tree);
#endif
#if 0
Graph *graph = Neuron_Structure_Import_Xml_Graph("../data/mouse_single_org/trueconn2.xml");
Graph_Normalize_Edge(graph);
Graph_Remove_Duplicated_Edge(graph);
Graph *graph2 = Neuron_Structure_Import_Xml_Graph("../data/mouse_single_org/conn.xml");
Graph_Normalize_Edge(graph2);
Graph_Remove_Duplicated_Edge(graph2);
Graph_Workspace *gw = New_Graph_Workspace();
int n = Graph_Edge_Count(graph, graph2->edges, graph2->nedge, gw);
printf("fp: %d\n", graph2->nedge - n);
printf("tp: %d\n", n);
printf("fn: %d\n", graph->nedge - n);
double p = (double) n / graph2->nedge;
double r = (double) n / graph->nedge;
printf("precision: %g\n", p);
printf("recall: %g\n", r);
printf("F-measure: %g\n", 2.0 * (p * r) / (p + r));
#endif
#if 0
Neuron_Structure *ns = Make_Neuron_Structure(2);
Local_Neuroseg *locseg = New_Local_Neuroseg();
Locseg_Chain *chain1 = New_Locseg_Chain();
Locseg_Chain_Add(chain1, locseg, NULL, DL_TAIL);
Set_Neuron_Component(ns->comp, NEUROCOMP_TYPE_LOCSEG_CHAIN, chain1);
Locseg_Chain *chain2 = New_Locseg_Chain();
locseg = New_Local_Neuroseg();
double bottom[3] = {10, 10, 5};
double top[3] = {5, 5, 5};
Local_Neuroseg_Set_Bottom_Top(locseg, bottom, top);
Locseg_Chain_Add(chain2, locseg, NULL, DL_TAIL);
Set_Neuron_Component(ns->comp + 1, NEUROCOMP_TYPE_LOCSEG_CHAIN, chain2);
Neurocomp_Conn *conn = New_Neurocomp_Conn();
Connection_Test_Workspace *ctw = New_Connection_Test_Workspace();
Locseg_Chain_Connection_Test(chain2, chain1, NULL, 1.0, conn, ctw);
Neuron_Structure_Add_Conn(ns, 1, 0, conn);
Print_Neuron_Structure(ns);
Neuron_Structure *ns2 =
Neuron_Structure_Locseg_Chain_To_Circle_S(ns, 1.0, 1.0);
Neuron_Structure_To_Swc_File(ns2, "../data/test.swc");
#endif
#if 0
int n;
Locseg_Chain **chain_array = Dir_Locseg_Chain_Nd("../data/diadem_a1_part3",
"^chain.*\\.tb", &n, NULL);
/*
Locseg_Chain **chain_array =
Locseg_Chain_Import_List("../data/diadem_a1_part2/good_tube.txt", &n);
*/
//n = 100;
/*
Locseg_Chain **chain_array =
(Locseg_Chain**) malloc(sizeof(Locseg_Chain*) * 2);
n = 2;
chain_array[0] = Read_Locseg_Chain("../data/diadem_a1_part2/chain58.tb");
chain_array[1] = Read_Locseg_Chain("../data/diadem_a1_part2/chain154.tb");
*/
Stack *stack = Read_Stack("../data/diadem_a1_part3.tif");
Stack *mask = Make_Stack(GREY, stack->width, stack->height, stack->depth);
Zero_Stack(mask);
Sp_Grow_Workspace *sgw = New_Sp_Grow_Workspace();
sgw->size = Stack_Voxel_Number(stack);
sgw->resolution[0] = 0.0375 * 2.0;
sgw->resolution[1] = 0.0375 * 2.0;
sgw->resolution[2] = 0.33;
Sp_Grow_Workspace_Set_Mask(sgw, mask->array);
sgw->wf = Stack_Voxel_Weight_S;
Stack_Sp_Grow_Infer_Parameter(sgw, stack);
Neuron_Structure *ns =
Locseg_Chain_Sp_Grow_Reconstruct(chain_array, n, stack, 1.0, sgw);
Print_Neuron_Structure(ns);
Graph_To_Dot_File(ns->graph, "../data/test.dot");
//Neuron_Structure_To_Swc_File(ns, "../data/test.swc");
Neuron_Structure *ns2 =
Neuron_Structure_Locseg_Chain_To_Circle_S(ns, 1.0, 1.0);
//double root[3] = {31, 430, 0};
double root[3] = {1221, 449, 8.5};
Swc_Tree *tree = Neuron_Structure_To_Swc_Tree_Circle_Z(ns2, 1.0, root);
Swc_Tree_Clean_Root(tree);
Swc_Tree_Resort_Id(tree);
Write_Swc_Tree("../data/test.swc", tree);
#endif
#if 0
int n;
Locseg_Chain **chain_array = Dir_Locseg_Chain_Nd("../data/diadem_e1",
"^chain.*\\.tb", &n, NULL);
//n = 100;
/*
Locseg_Chain **chain_array =
(Locseg_Chain**) malloc(sizeof(Locseg_Chain*) * 2);
n = 2;
chain_array[0] = Read_Locseg_Chain("../data/diadem_a1_part2/chain58.tb");
chain_array[1] = Read_Locseg_Chain("../data/diadem_a1_part2/chain154.tb");
*/
Stack *stack = Read_Stack("../data/diadem_e1.tif");
Stack *mask = Make_Stack(GREY, stack->width, stack->height, stack->depth);
Zero_Stack(mask);
Sp_Grow_Workspace *sgw = New_Sp_Grow_Workspace();
sgw->size = Stack_Voxel_Number(stack);
sgw->resolution[0] = 0.3296485;
sgw->resolution[1] = 0.3296485;
sgw->resolution[2] = 1.0;
Sp_Grow_Workspace_Set_Mask(sgw, mask->array);
sgw->wf = Stack_Voxel_Weight_S;
Stack_Sp_Grow_Infer_Parameter(sgw, stack);
Neuron_Structure *ns =
Locseg_Chain_Sp_Grow_Reconstruct(chain_array, n, stack, 1.0, sgw);
Print_Neuron_Structure(ns);
//Neuron_Structure_To_Swc_File(ns, "../data/test.swc");
Neuron_Structure *ns2 =
Neuron_Structure_Locseg_Chain_To_Circle_S(ns, 1.0, 1.0);
Graph_To_Dot_File(ns2->graph, "../data/test.dot");
double root[3] = {31, 430, 0};
//double root[3] = {4882, 1797, 19};
Swc_Tree *tree = Neuron_Structure_To_Swc_Tree_Circle_Z(ns2, 1.0, root);
//Swc_Tree_Clean_Root(tree);
Swc_Tree_Resort_Id(tree);
Write_Swc_Tree("../data/test2.swc", tree);
#endif
#if 0
int n;
Locseg_Chain **chain_array =
Dir_Locseg_Chain_Nd("../data/benchmark/stack_graph/fork", "^chain.*\\.tb",
&n, NULL);
Stack *stack = Read_Stack("../data/benchmark/stack_graph/fork/fork.tif");
Stack *mask = Make_Stack(GREY, stack->width, stack->height, stack->depth);
Zero_Stack(mask);
Sp_Grow_Workspace *sgw = New_Sp_Grow_Workspace();
sgw->size = Stack_Voxel_Number(stack);
Sp_Grow_Workspace_Set_Mask(sgw, mask->array);
sgw->wf = Stack_Voxel_Weight_S;
Stack_Sp_Grow_Infer_Parameter(sgw, stack);
Neuron_Structure *ns =
Locseg_Chain_Sp_Grow_Reconstruct(chain_array, n, stack, 1.0, sgw);
Neuron_Structure *ns2 =
Neuron_Structure_Locseg_Chain_To_Circle_S(ns, 1.0, 1.0);
Swc_Tree *tree = Neuron_Structure_To_Swc_Tree_Circle_Z(ns2, 1.0, NULL);
//Swc_Tree_Clean_Root(tree);
Swc_Tree_Resort_Id(tree);
Write_Swc_Tree("../data/test.swc", tree);
#endif
#if 0
int n = 3;
Locseg_Chain **chain_array =
(Locseg_Chain**) malloc(sizeof(Locseg_Chain) * n);
chain_array[0] = Read_Locseg_Chain("/Users/zhaot/Work/neurolabi/data/benchmark/stack_graph/fork/chain0.tb");
chain_array[1] = Read_Locseg_Chain("/Users/zhaot/Work/neurolabi/data/benchmark/stack_graph/fork/chain1.tb");
chain_array[2] = New_Locseg_Chain();
printf("%d\n", Locseg_Chain_Is_Empty(chain_array[2]));
Stack *stack = Read_Stack("../data/benchmark/stack_graph/fork/fork.tif");
Stack *mask = Make_Stack(GREY, stack->width, stack->height, stack->depth);
Zero_Stack(mask);
Sp_Grow_Workspace *sgw = New_Sp_Grow_Workspace();
sgw->size = Stack_Voxel_Number(stack);
Sp_Grow_Workspace_Set_Mask(sgw, mask->array);
sgw->wf = Stack_Voxel_Weight_S;
Stack_Sp_Grow_Infer_Parameter(sgw, stack);
Neuron_Structure *ns =
Locseg_Chain_Sp_Grow_Reconstruct(chain_array, n, stack, 1.0, sgw);
Neuron_Structure *ns2 =
Neuron_Structure_Locseg_Chain_To_Circle_S(ns, 1.0, 1.0);
Swc_Tree *tree = Neuron_Structure_To_Swc_Tree_Circle_Z(ns2, 1.0, NULL);
//Swc_Tree_Clean_Root(tree);
Swc_Tree_Remove_Zigzag(tree);
Swc_Tree_Resort_Id(tree);
Write_Swc_Tree("../data/test2.swc", tree);
#endif
#if 0
Neuron_Structure *ns = New_Neuron_Structure();
ns->graph = New_Graph();
Graph_Add_Edge(ns->graph, 0, 1);
Graph_Add_Edge(ns->graph, 0, 2);
Graph_Add_Edge(ns->graph, 2, 3);
Graph_Add_Edge(ns->graph, 2, 4);
Graph_Add_Edge(ns->graph, 4, 5);
Graph_Add_Edge(ns->graph, 5, 6);
ns->conn = (Neurocomp_Conn*) malloc(sizeof(Neurocomp_Conn) * ns->graph->nedge);
ns->conn[0].info[0] = 0;
ns->conn[0].info[1] = 0;
ns->conn[0].cost = 0.0;
ns->conn[0].mode = NEUROCOMP_CONN_LINK;
ns->conn[1].info[0] = 1;
ns->conn[1].info[1] = 1;
ns->conn[1].cost = 0.0;
ns->conn[1].mode = NEUROCOMP_CONN_LINK;
ns->conn[2].info[0] = 0;
ns->conn[2].info[1] = 0;
ns->conn[2].cost = 0.0;
ns->conn[2].mode = NEUROCOMP_CONN_LINK;
ns->conn[3].info[0] = 1;
ns->conn[3].info[1] = 0;
ns->conn[3].cost = 1.0;
ns->conn[3].mode = NEUROCOMP_CONN_HL;
ns->conn[4].info[0] = 0;
ns->conn[4].info[1] = 1;
ns->conn[4].cost = 0.0;
ns->conn[4].mode = NEUROCOMP_CONN_LINK;
ns->conn[5].info[0] = 1;
ns->conn[5].info[1] = 1;
ns->conn[5].cost = 1.0;
ns->conn[5].mode = NEUROCOMP_CONN_LINK;
Neuron_Structure_Merge_Locseg_Chain(ns);
#endif
#if 0
Neuron_Structure *ns = New_Neuron_Structure();
ns->graph = New_Graph();
ns->comp = Dir_Locseg_Chain_Nc("../data/diadem_e3", "^chain.*\\.tb",
&(ns->graph->nvertex), NULL);
Graph_Add_Edge(ns->graph, 0, 1);
Graph_Add_Edge(ns->graph, 0, 2);
Graph_Add_Edge(ns->graph, 2, 3);
Graph_Add_Edge(ns->graph, 3, 4);
Graph_Add_Edge(ns->graph, 4, 5);
ns->conn = (Neurocomp_Conn*) malloc(sizeof(Neurocomp_Conn) * ns->graph->nedge);
ns->conn[0].info[0] = 0;
ns->conn[0].info[1] = 0;
ns->conn[0].cost = 0.0;
ns->conn[0].mode = NEUROCOMP_CONN_LINK;
ns->conn[1].info[0] = 0;
ns->conn[1].info[1] = 0;
ns->conn[1].cost = 0.0;
ns->conn[1].mode = NEUROCOMP_CONN_LINK;
ns->conn[2].info[0] = 0;
ns->conn[2].info[1] = 0;
ns->conn[2].cost = 1.0;
ns->conn[2].mode = NEUROCOMP_CONN_LINK;
ns->conn[3].info[0] = 0;
ns->conn[3].info[1] = 0;
ns->conn[3].cost = 2.0;
ns->conn[3].mode = NEUROCOMP_CONN_LINK;
ns->conn[4].info[0] = 0;
ns->conn[4].info[1] = 0;
ns->conn[4].cost = 0.0;
ns->conn[4].mode = NEUROCOMP_CONN_LINK;
int i;
for (i = 0; i < ns->graph->nvertex; i++) {
printf("%d ", Locseg_Chain_Length(NEUROCOMP_LOCSEG_CHAIN(ns->comp+i)));
}
printf("\n");
Neuron_Structure_Merge_Locseg_Chain(ns);
for (i = 0; i < ns->graph->nvertex; i++) {
printf("%d ", Locseg_Chain_Length(NEUROCOMP_LOCSEG_CHAIN(ns->comp+i)));
}
printf("\n");
#endif
#if 0
int n;
Locseg_Chain **chain_array = Dir_Locseg_Chain_Nd("../data/diadem_e1",
"^chain.*\\.tb", &n, NULL);
Stack *stack = Read_Stack("../data/diadem_e1.tif");
Stack *mask = Make_Stack(GREY, stack->width, stack->height, stack->depth);
Zero_Stack(mask);
Sp_Grow_Workspace *sgw = New_Sp_Grow_Workspace();
sgw->size = Stack_Voxel_Number(stack);
sgw->resolution[0] = 0.3296485;
sgw->resolution[1] = 0.3296485;
sgw->resolution[2] = 1.0;
Sp_Grow_Workspace_Set_Mask(sgw, mask->array);
sgw->wf = Stack_Voxel_Weight_S;
Stack_Sp_Grow_Infer_Parameter(sgw, stack);
Neuron_Structure *ns =
Locseg_Chain_Sp_Grow_Reconstruct(chain_array, n, stack, 1.0, sgw);
Neuron_Structure_Merge_Locseg_Chain(ns);
int i;
char filepath[100];
for (i = 0; i < ns->graph->nvertex; i++) {
Locseg_Chain_Regularize(NEUROCOMP_LOCSEG_CHAIN(ns->comp+i));
if (Locseg_Chain_Is_Empty(NEUROCOMP_LOCSEG_CHAIN(ns->comp+i)) == FALSE) {
sprintf(filepath, "../data/tmp/chain%d.tb", i);
Write_Locseg_Chain(filepath, NEUROCOMP_LOCSEG_CHAIN(ns->comp+i));
}
}
#endif
#if 0
Stack *stack = Read_Stack("../data/benchmark/fork2/fork2.tif");
Neuron_Structure *ns = New_Neuron_Structure();
ns->graph = New_Graph();
ns->comp = Dir_Locseg_Chain_Nc("../data/benchmark/fork2/tubes",
"^chain.*\\.tb", &(ns->graph->nvertex), NULL);
coordinate_3d_t roots[3];
roots[0][0] = 51;
roots[0][1] = 23;
roots[0][2] = 60;
roots[1][0] = 51;
roots[1][1] = 23;
roots[1][2] = 40;
roots[2][0] = 25;
roots[2][1] = 76;
roots[2][2] = 60;
Neuron_Structure_Break_Root(ns, roots, 3);
Neuron_Structure_Load_Root(ns, roots, 3);
Connection_Test_Workspace *ctw = New_Connection_Test_Workspace();
ctw->dist_thre = 100.0;
ctw->sp_test = FALSE;
Locseg_Chain_Comp_Neurostruct_W(ns, stack, 1.0, ctw);
Process_Neuron_Structure(ns);
Neuron_Structure_To_Tree(ns);
/*
Neuron_Structure_Remove_Conn(ns, 0, 2);
Neuron_Structure_Remove_Conn(ns, 2, 0);
*/
Neuron_Structure_Remove_Negative_Conn(ns);
Neuron_Structure* ns2= NULL;
ns2 = Neuron_Structure_Locseg_Chain_To_Circle_S(ns, 1.0, 1.0);
Neuron_Structure_To_Tree(ns2);
Swc_Tree *tree = Neuron_Structure_To_Swc_Tree_Circle_Z(ns2, 1.0, NULL);
Swc_Tree_Resort_Id(tree);
Write_Swc_Tree("../data/test3.swc", tree);
#endif
#if 1
Stack *stack = NULL;
Locseg_Chain *chain1 = Read_Locseg_Chain("../data/benchmark/diadem/diadem_e1/chain22.tb");
Locseg_Chain *chain2 = Read_Locseg_Chain("../data/benchmark/diadem/diadem_e1/chain0.tb");
Connection_Test_Workspace *ws = New_Connection_Test_Workspace();
Connection_Test_Workspace_Read_Resolution(ws, "../data/diadem_e3.res");
Neurocomp_Conn conn;
conn.mode = NEUROCOMP_CONN_HL;
Locseg_Chain_Connection_Test(chain1, chain2, stack, 1.0, &conn, ws);
Print_Neurocomp_Conn(&conn);
#endif
return 0;
}
