int main()
{
srand(time(NULL));
//fillArr(a, n);
inverse_matrix();
return 0;
}
static testing::AssertionResult animated_transform_interpolate_near(
const char *animated_transform_expr,
const char *transform_expr,
const char * /*time_expr*/,
const char *abs_error_expr,
const AnimatedTransform &animated_transform,
const Transform &transform,
real_t time,
real_t abs_error)
{
auto transform_at_time = animated_transform.interpolate(time);
auto m1 = transform_at_time.matrix();
auto m1_inv = transform_at_time.inverse_matrix();
auto m2 = transform.matrix();
auto m2_inv = transform.inverse_matrix();
for (unsigned int i = 0; i < 4; i++)
{
for (unsigned int j = 0; j < 4; j++)
if (std::abs(m1(i, j) - m2(i, j)) > abs_error ||
std::abs(m1_inv(i, j) - m2_inv(i, j)) > abs_error)
return testing::AssertionFailure()
<< animated_transform_expr << " has elements that differ more "
<< "than " << abs_error_expr << " from " << transform_expr
<< " at time " << time << ".";
}
return testing::AssertionSuccess();
}
void inverse_interface(){
int size;
printf("Insert how many line/columns your matrix have: ");
scanf("%d", &size);
bool check_matrix = verify(0, size, size, 0, 0);
if(check_matrix == true){
double (**matrix) = createNewMatrix(size, size);
if(determinant(matrix, size) != 0.0){
double (**result) = inverse_matrix(matrix, size);
printf("The inverse matrix is:\n");
print_matrix(size, size, result);
}else{
printf("Your matrix do not have an inverse\n");
}
}else{
printf("There is an error with your input data.\nCheck them please.\n");
}
}
/* Aplica transformações geométrica à localização do vértice corrente e ao vetor normal associado a ele.
*
* Argumentos de entrada:
* 'vertex_oc' : Localização do vértice representada no sistema de coordenadas do objeto (object coordinates, OC).
* 'normal_oc' : Vetor normal à superfície representada no sistema de coordenadas do objeto (OC).
* 'modelview_matrix' : Matriz 4x4 composta pelas transformações de modelo e visualização (view_matrix * model_matrix).
* 'projection_matrix': Matriz 4x4 de projeção.
*
* Argumentos de saída:
* 'vertex_ec' : Localização do vértice representada no sistema de coordenadas da câmera (eye coordinates, EC).
* 'vertex_cc' : Localização do vértice representada no sistema coordenadas de recorte (clip coordinates, CC).
* 'unit_normal_ec' : Vetor normal à superfície representado no sistema de coordenadas da câmera (EC). Assume-se que
* a norma deste vetor é igual a 1.0f.
*/
void vertex_transformation(const location_struct &vertex_oc, const direction_struct &normal_oc, const matrix_struct &modelview_matrix, const matrix_struct &projection_matrix, location_struct &vertex_ec, location_struct &vertex_cc, direction_struct &unit_normal_ec) {
//Calcular 'vertex_ec'.
//Calcular 'vertex_cc'.
//Calcular 'unit_normal_ec'.
vertex_ec[0] = vertex_oc[0] * modelview_matrix(0,0) + vertex_oc[1] * modelview_matrix(0,1) +
vertex_oc[2] * modelview_matrix(0,2) + vertex_oc[3] * modelview_matrix(0,3);
vertex_ec[1] = vertex_oc[0] * modelview_matrix(1,0) + vertex_oc[1] * modelview_matrix(1,1) +
vertex_oc[2] * modelview_matrix(1,2) + vertex_oc[3] * modelview_matrix(1,3);
vertex_ec[2] = vertex_oc[0] * modelview_matrix(2,0) + vertex_oc[1] * modelview_matrix(2,1) +
vertex_oc[2] * modelview_matrix(2,2) + vertex_oc[3] * modelview_matrix(2,3);
vertex_ec[3] = vertex_oc[0] * modelview_matrix(3,0) + vertex_oc[1] * modelview_matrix(3,1) +
vertex_oc[2] * modelview_matrix(3,2) + vertex_oc[3] * modelview_matrix(3,3);
vertex_cc[0] = vertex_ec[0] * projection_matrix(0,0) + vertex_ec[1] * projection_matrix(0,1) +
vertex_ec[2] * projection_matrix(0,2) + vertex_ec[3] * projection_matrix(0,3);
vertex_cc[1] = vertex_ec[0] * projection_matrix(1,0) + vertex_ec[1] * projection_matrix(1,1) +
vertex_ec[2] * projection_matrix(1,2) + vertex_ec[3] * projection_matrix(1,3);
vertex_cc[2] = vertex_ec[0] * projection_matrix(2,0) + vertex_ec[1] * projection_matrix(2,1) +
vertex_ec[2] * projection_matrix(2,2) + vertex_ec[3] * projection_matrix(2,3);
vertex_cc[3] = vertex_ec[0] * projection_matrix(3,0) + vertex_ec[1] * projection_matrix(3,1) +
vertex_ec[2] * projection_matrix(3,2) + vertex_ec[3] * projection_matrix(3,3);
matrix_struct transposta = matrix_struct();
matrix_struct inverse = matrix_struct();
inverse_matrix(modelview_matrix, inverse);
transpose_matrix(inverse, transposta);
unit_normal_ec[0] = normal_oc[0] * transposta(0,0) + normal_oc[1] * transposta(0,1) +
normal_oc[2] * transposta(0,2);
unit_normal_ec[1] = normal_oc[0] * transposta(1,0) + normal_oc[1] * transposta(1,1) +
normal_oc[2] * transposta(1,2);
unit_normal_ec[2] = normal_oc[0] * transposta(2,0) + normal_oc[1] * transposta(2,1) +
normal_oc[2] * transposta(2,2);
normalize(unit_normal_ec);
}
void pie_Draw3DShape(iIMDShape *shape, int frame, int team, PIELIGHT colour, int pieFlag, int pieFlagData)
{
PIELIGHT teamcolour;
ASSERT_OR_RETURN(, shape, "Attempting to draw null sprite");
teamcolour = pal_GetTeamColour(team);
pieCount++;
ASSERT(frame >= 0, "Negative frame %d", frame);
ASSERT(team >= 0, "Negative team %d", team);
if (drawing_interface || !shadows)
{
pie_Draw3DShape2(shape, frame, colour, teamcolour, pieFlag, pieFlagData);
}
else
{
if (pieFlag & (pie_ADDITIVE | pie_TRANSLUCENT | pie_PREMULTIPLIED) && !(pieFlag & pie_FORCE_IMMEDIATE))
{
TranslucentShape tshape;
glGetFloatv(GL_MODELVIEW_MATRIX, tshape.matrix);
tshape.shape = shape;
tshape.frame = frame;
tshape.colour = colour;
tshape.flag = pieFlag;
tshape.flag_data = pieFlagData;
tshapes.push_back(tshape);
}
else
{
if(pieFlag & pie_SHADOW || pieFlag & pie_STATIC_SHADOW)
{
float distance;
// draw a shadow
ShadowcastingShape scshape;
glGetFloatv(GL_MODELVIEW_MATRIX, scshape.matrix);
distance = scshape.matrix[12] * scshape.matrix[12];
distance += scshape.matrix[13] * scshape.matrix[13];
distance += scshape.matrix[14] * scshape.matrix[14];
// if object is too far in the fog don't generate a shadow.
if (distance < SHADOW_END_DISTANCE)
{
float invmat[9], pos_light0[4];
inverse_matrix( scshape.matrix, invmat );
// Calculate the light position relative to the object
glGetLightfv(GL_LIGHT0, GL_POSITION, pos_light0);
scshape.light.x = invmat[0] * pos_light0[0] + invmat[3] * pos_light0[1] + invmat[6] * pos_light0[2];
scshape.light.y = invmat[1] * pos_light0[0] + invmat[4] * pos_light0[1] + invmat[7] * pos_light0[2];
scshape.light.z = invmat[2] * pos_light0[0] + invmat[5] * pos_light0[1] + invmat[8] * pos_light0[2];
scshape.shape = shape;
scshape.flag = pieFlag;
scshape.flag_data = pieFlagData;
scshapes.push_back(scshape);
}
}
pie_Draw3DShape2(shape, frame, colour, teamcolour, pieFlag, pieFlagData);
}
}
}
void pie_Draw3DShape(iIMDShape *shape, int frame, int team, PIELIGHT colour, PIELIGHT specular, int pieFlag, int pieFlagData)
{
PIELIGHT teamcolour;
ASSERT_OR_RETURN(, shape, "Attempting to draw null sprite");
teamcolour = pal_GetTeamColour(team);
pieCount++;
if (frame == 0)
{
frame = team;
}
if (drawing_interface || !shadows)
{
pie_Draw3DShape2(shape, frame, colour, teamcolour, specular, pieFlag, pieFlagData);
}
else
{
if (pieFlag & (pie_ADDITIVE | pie_TRANSLUCENT))
{
if (tshapes_size <= nb_tshapes)
{
if (tshapes_size == 0)
{
tshapes_size = 64;
tshapes = (transluscent_shape_t*)malloc(tshapes_size*sizeof(transluscent_shape_t));
memset( tshapes, 0, tshapes_size*sizeof(transluscent_shape_t) );
}
else
{
const unsigned int old_size = tshapes_size;
tshapes_size <<= 1;
tshapes = (transluscent_shape_t*)realloc(tshapes, tshapes_size*sizeof(transluscent_shape_t));
memset( &tshapes[old_size], 0, (tshapes_size-old_size)*sizeof(transluscent_shape_t) );
}
}
glGetFloatv(GL_MODELVIEW_MATRIX, tshapes[nb_tshapes].matrix);
tshapes[nb_tshapes].shape = shape;
tshapes[nb_tshapes].frame = frame;
tshapes[nb_tshapes].colour = colour;
tshapes[nb_tshapes].specular = specular;
tshapes[nb_tshapes].flag = pieFlag;
tshapes[nb_tshapes].flag_data = pieFlagData;
nb_tshapes++;
}
else
{
if(pieFlag & pie_SHADOW || pieFlag & pie_STATIC_SHADOW)
{
float distance;
// draw a shadow
if (scshapes_size <= nb_scshapes)
{
if (scshapes_size == 0)
{
scshapes_size = 64;
scshapes = (shadowcasting_shape_t*)malloc(scshapes_size*sizeof(shadowcasting_shape_t));
memset( scshapes, 0, scshapes_size*sizeof(shadowcasting_shape_t) );
}
else
{
const unsigned int old_size = scshapes_size;
scshapes_size <<= 1;
scshapes = (shadowcasting_shape_t*)realloc(scshapes, scshapes_size*sizeof(shadowcasting_shape_t));
memset( &scshapes[old_size], 0, (scshapes_size-old_size)*sizeof(shadowcasting_shape_t) );
}
}
glGetFloatv(GL_MODELVIEW_MATRIX, scshapes[nb_scshapes].matrix);
distance = scshapes[nb_scshapes].matrix[12] * scshapes[nb_scshapes].matrix[12];
distance += scshapes[nb_scshapes].matrix[13] * scshapes[nb_scshapes].matrix[13];
distance += scshapes[nb_scshapes].matrix[14] * scshapes[nb_scshapes].matrix[14];
// if object is too far in the fog don't generate a shadow.
if (distance < SHADOW_END_DISTANCE)
{
float invmat[9], pos_light0[4];
inverse_matrix( scshapes[nb_scshapes].matrix, invmat );
// Calculate the light position relative to the object
glGetLightfv(GL_LIGHT0, GL_POSITION, pos_light0);
scshapes[nb_scshapes].light.x = invmat[0] * pos_light0[0] + invmat[3] * pos_light0[1] + invmat[6] * pos_light0[2];
scshapes[nb_scshapes].light.y = invmat[1] * pos_light0[0] + invmat[4] * pos_light0[1] + invmat[7] * pos_light0[2];
scshapes[nb_scshapes].light.z = invmat[2] * pos_light0[0] + invmat[5] * pos_light0[1] + invmat[8] * pos_light0[2];
scshapes[nb_scshapes].shape = shape;
scshapes[nb_scshapes].flag = pieFlag;
scshapes[nb_scshapes].flag_data = pieFlagData;
nb_scshapes++;
}
}
pie_Draw3DShape2(shape, frame, colour, teamcolour, specular, pieFlag, pieFlagData);
}
}
}
int main()
{
inverse_matrix();
return 0;
}
static int computeMatrixLMSOpt(TAsoc *cp_ass, int cnt, Tsc *estimacion) {
int i;
float LMETRICA2;
float X1[MAXLASERPOINTS], Y1[MAXLASERPOINTS];
float X2[MAXLASERPOINTS],Y2[MAXLASERPOINTS];
float X2Y2[MAXLASERPOINTS],X1X2[MAXLASERPOINTS];
float X1Y2[MAXLASERPOINTS], Y1X2[MAXLASERPOINTS];
float Y1Y2[MAXLASERPOINTS];
float K[MAXLASERPOINTS], DS[MAXLASERPOINTS];
float DsD[MAXLASERPOINTS], X2DsD[MAXLASERPOINTS], Y2DsD[MAXLASERPOINTS];
float Bs[MAXLASERPOINTS], BsD[MAXLASERPOINTS];
float A1, A2, A3, B1, B2, B3, C1, C2, C3, D1, D2, D3;
MATRIX matA,invMatA;
VECTOR vecB,vecSol;
A1=0;A2=0;A3=0;B1=0;B2=0;B3=0;
C1=0;C2=0;C3=0;D1=0;D2=0;D3=0;
LMETRICA2=params.LMET*params.LMET;
for (i=0; i<cnt; i++){
X1[i]=cp_ass[i].nx*cp_ass[i].nx;
Y1[i]=cp_ass[i].ny*cp_ass[i].ny;
X2[i]=cp_ass[i].rx*cp_ass[i].rx;
Y2[i]=cp_ass[i].ry*cp_ass[i].ry;
X2Y2[i]=cp_ass[i].rx*cp_ass[i].ry;
X1X2[i]=cp_ass[i].nx*cp_ass[i].rx;
X1Y2[i]=cp_ass[i].nx*cp_ass[i].ry;
Y1X2[i]=cp_ass[i].ny*cp_ass[i].rx;
Y1Y2[i]=cp_ass[i].ny*cp_ass[i].ry;
K[i]=X2[i]+Y2[i] + LMETRICA2;
DS[i]=Y1Y2[i] + X1X2[i];
DsD[i]=DS[i]/K[i];
X2DsD[i]=cp_ass[i].rx*DsD[i];
Y2DsD[i]=cp_ass[i].ry*DsD[i];
Bs[i]=X1Y2[i]-Y1X2[i];
BsD[i]=Bs[i]/K[i];
A1=A1 + (1-Y2[i]/K[i]);
B1=B1 + X2Y2[i]/K[i];
C1=C1 + (-cp_ass[i].ny + Y2DsD[i]);
D1=D1 + (cp_ass[i].nx - cp_ass[i].rx -cp_ass[i].ry*BsD[i]);
A2=B1;
B2=B2 + (1-X2[i]/K[i]);
C2=C2 + (cp_ass[i].nx-X2DsD[i]);
D2=D2 + (cp_ass[i].ny -cp_ass[i].ry +cp_ass[i].rx*BsD[i]);
A3=C1;
B3=C2;
C3=C3 + (X1[i] + Y1[i] - DS[i]*DS[i]/K[i]);
D3=D3 + (Bs[i]*(-1+DsD[i]));
}
initialize_matrix(&matA,3,3);
MDATA(matA,0,0)=A1; MDATA(matA,0,1)=B1; MDATA(matA,0,2)=C1;
MDATA(matA,1,0)=A2; MDATA(matA,1,1)=B2; MDATA(matA,1,2)=C2;
MDATA(matA,2,0)=A3; MDATA(matA,2,1)=B3; MDATA(matA,2,2)=C3;
if (inverse_matrix (&matA, &invMatA)==-1)
return -1;
#ifdef INTMATSM_DEB
print_matrix("inverted matrix", &invMatA);
#endif
initialize_vector(&vecB,3);
VDATA(vecB,0)=D1; VDATA(vecB,1)=D2; VDATA(vecB,2)=D3;
multiply_matrix_vector (&invMatA, &vecB, &vecSol);
estimacion->x=-VDATA(vecSol,0);
estimacion->y=-VDATA(vecSol,1);
estimacion->tita=-VDATA(vecSol,2);
return 1;
}
/*!\rst
Test that SPDMatrixInverse and CholeskyFactorLMatrixVectorSolve are working correctly
against some especially bad named matrices and some random inputs.
Outline:
1. Construct matrices, ``A``
2. Select a solution, ``x``, randomly.
3. Construct RHS by doing ``A*x``.
4. Solve ``Ax = b`` using backsolve and direct-inverse; check the size of ``\|b - Ax\|``.
\return
number of test cases where the solver error is too large
\endrst*/
OL_WARN_UNUSED_RESULT int TestSPDLinearSolvers() {
int total_errors = 0;
// simple/small case where numerical factors are not present.
// taken from: http://en.wikipedia.org/wiki/Cholesky_decomposition#Example
{
constexpr int size = 3;
std::vector<double> matrix =
{ 4.0, 12.0, -16.0,
12.0, 37.0, -43.0,
-16.0, -43.0, 98.0};
const std::vector<double> cholesky_factor_L_truth =
{ 2.0, 6.0, -8.0,
0.0, 1.0, 5.0,
0.0, 0.0, 3.0};
std::vector<double> rhs = {-20.0, -43.0, 192.0};
std::vector<double> solution_truth = {1.0, 2.0, 3.0};
int local_errors = 0;
// check factorization is correct; only check lower-triangle
if (ComputeCholeskyFactorL(size, matrix.data()) != 0) {
++total_errors;
}
for (int i = 0; i < size; ++i) {
for (int j = 0; j < size; ++j) {
if (j >= i) {
if (!CheckDoubleWithinRelative(matrix[i*size + j], cholesky_factor_L_truth[i*size + j], 0.0)) {
++local_errors;
}
}
}
}
// check the solve is correct
CholeskyFactorLMatrixVectorSolve(matrix.data(), size, rhs.data());
for (int i = 0; i < size; ++i) {
if (!CheckDoubleWithinRelative(rhs[i], solution_truth[i], 0.0)) {
++local_errors;
}
}
total_errors += local_errors;
}
const int num_tests = 10;
const int num_test_sizes = 3;
const int sizes[num_test_sizes] = {5, 11, 20};
// following tolerances are based on numerical experiments and/or computations
// of the matrix condition numbers (in MATLAB)
const double tolerance_backsolve_max_list[3][num_test_sizes] =
{ {10*std::numeric_limits<double>::epsilon(), 100*std::numeric_limits<double>::epsilon(), 100*std::numeric_limits<double>::epsilon()}, // prolate
{100*std::numeric_limits<double>::epsilon(), 1.0e4*std::numeric_limits<double>::epsilon(), 1.0e6*std::numeric_limits<double>::epsilon()}, // moler
{50*std::numeric_limits<double>::epsilon(), 1.0e3*std::numeric_limits<double>::epsilon(), 5.0e4*std::numeric_limits<double>::epsilon()} // random
};
const double tolerance_inverse_max_list[3][num_test_sizes] =
{ {1.0e-13, 1.0e-9, 1.0e-2}, // prolate
{5.0e-13, 2.0e-8, 1.0e1}, // moler
{7.0e-10, 7.0e-6, 1.0e2} // random
};
UniformRandomGenerator uniform_generator(34187);
// In each iteration, we form some an ill-conditioned SPD matrix. We are using
// prolate, moler, and random matrices.
// Then we compute L * L^T = A.
// We want to test solutions of A * x = b using two methods:
// 1) Inverse: using L, we form A^-1 explicitly (ILL-CONDITIONED!)
// 2) Backsolve: we never form A^-1, but instead backsolve L and L^T against b.
// The resulting residual norms, ||b - A*x||_2 are computed; we check that
// backsolve is accurate and inverse is affected strongly by conditioning.
for (int j = 0; j < num_tests; ++j) {
for (int i = 0; i < num_test_sizes; ++i) {
std::vector<double> matrix(sizes[i]*sizes[i]);
std::vector<double> inverse_matrix(sizes[i]*sizes[i]);
std::vector<double> cholesky_factor(sizes[i]*sizes[i]);
std::vector<double> rhs(sizes[i]);
std::vector<double> solution(2*sizes[i]);
double tolerance_backsolve_max;
double tolerance_inverse_max;
switch (j) {
case 0: {
BuildProlateMatrix(kProlateDefaultParameter, sizes[i], matrix.data());
tolerance_backsolve_max = tolerance_backsolve_max_list[0][i];
tolerance_inverse_max = tolerance_inverse_max_list[0][i];
break;
}
case 1: {
BuildMolerMatrix(-1.66666666666, sizes[i], matrix.data());
tolerance_backsolve_max = tolerance_backsolve_max_list[1][i];
tolerance_inverse_max = tolerance_inverse_max_list[1][i];
break;
}
default: {
if (j <= 1 || j > num_tests) {
OL_THROW_EXCEPTION(BoundsException<int>, "Invalid switch option.", j, 2, num_tests);
} else {
BuildRandomSPDMatrix(sizes[i], &uniform_generator, matrix.data());
tolerance_backsolve_max = tolerance_backsolve_max_list[2][i];
tolerance_inverse_max = tolerance_inverse_max_list[2][i];
break;
}
}
}
// cholesky-factor A, form A^-1
std::copy(matrix.begin(), matrix.end(), cholesky_factor.begin());
if (ComputeCholeskyFactorL(sizes[i], cholesky_factor.data()) != 0) {
++total_errors;
}
SPDMatrixInverse(cholesky_factor.data(), sizes[i], inverse_matrix.data());
// set b = A*random_vector. This way we know the solution explicitly.
// this also allows us to ignore ||A|| in our computations when we
// normalize the RHS.
BuildRandomVector(sizes[i], 0.0, 1.0, &uniform_generator, solution.data());
SymmetricMatrixVectorMultiply(matrix.data(), solution.data(), sizes[i], rhs.data());
// re-scale the RHS so that its norm can be ignored in later computations
double rhs_norm = VectorNorm(rhs.data(), sizes[i]);
VectorScale(sizes[i], 1.0/rhs_norm, rhs.data());
std::copy(rhs.begin(), rhs.end(), solution.begin());
// Solve L * L^T * x1 = b (backsolve) and compute x2 = A^-1 * b
CholeskyFactorLMatrixVectorSolve(cholesky_factor.data(), sizes[i], solution.data());
SymmetricMatrixVectorMultiply(inverse_matrix.data(), rhs.data(), sizes[i], solution.data() + sizes[i]);
double norm_residual_via_backsolve = ResidualNorm(matrix.data(), solution.data(), rhs.data(), sizes[i]);
double norm_residual_via_inverse = ResidualNorm(matrix.data(), solution.data() + sizes[i], rhs.data(), sizes[i]);
if (norm_residual_via_backsolve > tolerance_backsolve_max) {
++total_errors;
OL_ERROR_PRINTF("experiment %d, size[%d] = %d, norm_backsolve = %.18E > %.18E = tol\n", j, i, sizes[i],
norm_residual_via_backsolve, tolerance_backsolve_max);
}
if (norm_residual_via_inverse > tolerance_inverse_max) {
++total_errors;
OL_ERROR_PRINTF("experiment %d, size[%d] = %d, norm_inverse = %.18E > %.18E = tol\n", j, i, sizes[i],
norm_residual_via_inverse, tolerance_inverse_max);
}
}
}
return total_errors;
}
/************************ end self doc ***********************************/
void main (int argc, char **argv)
{
/* declaration of variables */
FILE *fp, *gp; /* file pointers */
char *orientation = " "; /* orientation of recordings */
char *recFile = " "; /* receiver location file */
char *postFile = " "; /* posteriori file */
char *modelFile = " "; /* elastic model file */
char *corrDataFile = " "; /* data covariance file */
char *corrModelFile[3]; /* model covariance file */
char *frechetFile = " "; /* frechet derivative file */
int verbose; /* verbose flag */
int noFrechet; /* if 1 don't store Frechet derivatives */
int i, j, k, iU, iParam, offset, iR, shift;
/* counters */
int wL; /* taper length */
int nParam; /* number of parameters altogether */
int numberParImp; /* number of distinct parameters in */
/* impedance inversion */
float dZ; /* layer thickness within target zone */
float F1, F2, F3; /* source components */
float depth; /* current depth used in defining limits */
/* for Frechet derivatives */
float fR; /* reference frequency */
float percU; /* amount of slowness windowing */
float percW; /* amount of frequency windowing */
float limZ[2]; /* target interval (Km) */
float tMod; /* maximum modeling time */
float phi; /* azimuth angle */
float *buffer1, *buffer2; /* auxiliary buffers */
float **CmPost; /* posteriori model covariance */
float **CmPostInv; /* posteriori model covariance - inverse */
/* allocing for orientation */
orientation = malloc(1);
/* complex Zero */
zeroC = cmplx(0, 0);
/* getting input parameters */
initargs(argc, argv);
requestdoc(0);
/* seismic data and model parameters */
if (!getparstring("model", &modelFile)) modelFile = "model";
if (!getparstring("postfile", &postFile)) postFile = "posteriori";
if (!getparstring("corrData", &corrDataFile)) corrDataFile = "corrdata";
if (!getparint("impedance", &IMPEDANCE)) IMPEDANCE = 0;
if (!getparstring("frechetfile", &frechetFile)) noFrechet = 0;
else noFrechet = 1;
if (!getparint("prior", &PRIOR)) PRIOR = 1;
if (IMPEDANCE)
{
if (!getparint("p", &ipFrechet)) vpFrechet = 1;
if (!getparint("s", &isFrechet)) vsFrechet = 1;
if (!getparint("r", &rhoFrechet)) rhoFrechet = 1;
}
else
{
if (!getparint("p", &vpFrechet)) vpFrechet = 1;
if (!getparint("s", &vsFrechet)) vsFrechet = 1;
if (!getparint("rho", &rhoFrechet)) rhoFrechet = 1;
}
/* a couple of things to use later in chain rule */
if (!IMPEDANCE)
{
ipFrechet = 0; isFrechet = 0;
}
else
{
if (ipFrechet && !isFrechet)
{
vpFrechet = 1; vsFrechet = 0;
}
if (!ipFrechet && isFrechet)
{
vpFrechet = 0; vsFrechet = 1;
}
if (!ipFrechet && !isFrechet)
{
vpFrechet = 0; vsFrechet = 0;
}
if (ipFrechet && isFrechet)
{
vpFrechet = 1; vsFrechet = 1;
}
if (rhoFrechet)
{
vpFrechet = 1; vsFrechet = 1; rhoFrechet = 1;
}
}
if (!ipFrechet && ! isFrechet && !rhoFrechet && !vpFrechet && !vsFrechet)
err("No inverse unknowns to work with!\n");
numberPar = vpFrechet + vsFrechet + rhoFrechet;
numberParImp = ipFrechet + isFrechet + rhoFrechet;
if (PRIOR)
{
if (vpFrechet || ipFrechet)
{
if (!getparstring("corrP", &corrModelFile[0]))
corrModelFile[0] = "covP";
}
if (vsFrechet || isFrechet)
{
if (!getparstring("corrS", &corrModelFile[1]))
corrModelFile[1] = "covS";
}
if (rhoFrechet)
{
if (!getparstring("corrR", &corrModelFile[2]))
corrModelFile[2] = "covR";
}
}
if (!getparstring("orientation", &orientation)) orientation[0] = 'Z';
if (orientation[0] == 'z' || orientation[0] == 'Z')
{
VERTICAL = 1; RADIAL = 0;
}
else
{
VERTICAL = 0; RADIAL = 1;
}
if (!getparfloat("dz", &dZ)) dZ = .5;
if (!getparfloat("targetbeg", &limZ[0])) limZ[0] = 0.5;
if (!getparfloat("targetend", &limZ[1])) limZ[1] = 1.0;
/* geometry */
if (!getparfloat("r1", &r1)) r1 = 0.25;
if (!getparint("nr", &nR)) nR = 48;
if (!getparfloat("dr", &dR)) dR = .025;
if (!getparfloat("zs", &zs)) zs = .001;
if (!getparfloat("F1", &F1)) F1 = 0;
if (!getparfloat("F2", &F2)) F2 = 0;
if (!getparfloat("F3", &F3)) F3 = 1;
/* modeling */
if (!getparstring("receiverfile", &recFile)) recFile = " ";
if (!getparfloat("u1", &u1)) u1 = 0.0;
if (!getparfloat("u2", &u2)) u2 = 1.;
if (!getparint("directwave", &directWave)) directWave = 1;
if (!getparfloat("tau", &tau)) err("Specify tau!\n");
if (!getparint("nu", &nU)) nU = 1000;
if (!getparfloat("f1", &f1)) f1 = 2;
if (!getparfloat("f2", &f2)) f2 = 50;
if (!getparfloat("dt", &dt)) dt = 0.004;
if (!getparfloat("tmod", &tMod)) tMod = 8;
if (!getparfloat("t1", &t1)) t1 = 0;
if (!getparfloat("t2", &t2)) t2 = tMod;
if (!getparint("hanning", &hanningFlag)) hanningFlag = 1;
if (!getparfloat("wu", &percU)) percU = 10; percU /= 100;
if (!getparfloat("ww", &percW)) percW = 25; percW /= 100;
/* dialogue */
if (!getparint("verbose", &verbose)) verbose = 0;
/* checking number of receivers */
fp = fopen(recFile, "r");
if (fp != NULL)
{
nR = 0;
while (fscanf(fp, "%f\n", &auxm1) != EOF) nR++;
}
fclose(fp);
/* some hard-coded parameters */
fR = 1; wR = 2 * PI * fR; /* reference frequency */
/* how many layers */
fp = fopen(modelFile,"r");
if (fp == NULL)
err("No model file!\n");
nL = 0;
depth = 0;
while (fscanf(fp, "%f %f %f %f %f %f\n",
&aux, &aux, &aux, &aux, &aux, &aux) != EOF)
nL++;
nL--;
/* considering the unknown layers */
limRange = NINT((limZ[1] - limZ[0]) / dZ);
if (verbose)
{
fprintf(stderr,"Number of layers: %d\n", nL + 1);
fprintf(stderr,"Number of layers in target zone: %d\n", limRange);
}
if (IMPEDANCE)
{
nParam = numberParImp * limRange;
}
else
{
nParam = numberPar * limRange;
}
/* basic time-frequency stuff */
nSamples = NINT(tMod / dt) + 1;
nSamples = npfar(nSamples);
/* length of time misfit */
nDM = NINT((t2 - t1) / dt) + 1;
/* maximum time for modeling */
tMod = dt * (nSamples - 1);
dF = 1. / (tMod);
/* adjusting f1 and f2 */
aux = dF;
while (aux < f1)
aux += dF;
f1 = aux;
while (aux < f2)
aux += dF;
f2 = aux;
nF = NINT((f2 - f1) / dF);
if (nF%2 == 0)
{
f2 += dF;
nF++;
}
/* memory allocation */
alpha = alloc1float(nL + 1);
beta = alloc1float(nL + 1);
rho = alloc1float(nL + 1);
qP = alloc1float(nL + 1);
qS = alloc1float(nL + 1);
thick = alloc1float(nL + 1);
recArray = alloc1float(nR);
PSlowness = alloc2complex(2, nL + 1);
SSlowness = alloc2complex(2, nL + 1);
S2Velocity = alloc2complex(2, nL + 1);
CD = alloc1float(nDM * (nDM + 1) / 2);
if (PRIOR)
{
if(vpFrechet || ipFrechet)
CMP = alloc1float(limRange * (limRange + 1) / 2);
if(vsFrechet || isFrechet)
CMS = alloc1float(limRange * (limRange + 1) / 2);
if(rhoFrechet)
CMrho = alloc1float(limRange * (limRange + 1) / 2);
}
/* FRECHET derivative operator F */
F = alloc2float(nR * nDM, numberPar * limRange);
if (IMPEDANCE)
CmPostInv =
alloc2float(numberParImp * limRange, numberParImp * limRange);
else
CmPostInv = alloc2float(numberPar * limRange, numberPar * limRange);
v1 = alloc2complex(2, numberPar * limRange + 1);
v2 = alloc2complex(2, numberPar * limRange + 1);
DmB = alloc3complex(4, numberPar * (limRange + 2), nL);
derFactor = alloc2complex(2, nL + 1);
aux11 = alloc2complex(nR, numberPar * limRange);
aux12 = alloc2complex(nR, numberPar * limRange);
aux21 = alloc2complex(nR, numberPar * limRange);
aux22 = alloc2complex(nR, numberPar * limRange);
aux11Old = alloc2complex(nR, numberPar * limRange);
aux12Old = alloc2complex(nR, numberPar * limRange);
aux21Old = alloc2complex(nR, numberPar * limRange);
aux22Old = alloc2complex(nR, numberPar * limRange);
/* reading receiver configuration */
fp = fopen(recFile, "r");
if (fp == NULL)
{
/* standard end-on */
if (verbose) fprintf(stderr, "No receiver file available\n");
for (i = 0; i < nR; i++)
{
recArray[i] = r1 + i * dR;
}
}
else
{
if (verbose) fprintf(stderr, "Reading receiver file %s\n", recFile);
for (i = 0; i < nR; i++)
{
fscanf(fp, "%f\n", &recArray[i]);
}
}
fclose(fp);
/* reading the model file */
fp = fopen(modelFile,"r");
if (verbose)
fprintf(stderr," Thickness rho vP qP vS qS\n");
for (k = 0; k < nL + 1; k++)
{
fscanf(fp, "%f %f %f %f %f %f\n", &thick[k], &rho[k], &alpha[k],
&qP[k], &beta[k], &qS[k]);
if (verbose)
fprintf(stderr," %7.4f %4.3f %3.2f %5.1f %3.2f %5.1f\n",
thick[k], rho[k], alpha[k], qP[k], beta[k], qS[k]);
}
fclose(fp);
/* setting lim[0] and lim[1] */
for (depth = thick[0], i = 1; i <= nL; depth += thick[i], i++)
{
if (NINT(depth / dZ) <= NINT(limZ[0] / dZ)) lim[0] = i;
if (NINT(depth / dZ) < NINT(limZ[1] / dZ)) lim[1] = i;
}
lim[1]++;
/* some modeling parameters */
/* slowness increment */
dU = (u2 - u1) / (float) nU;
/* computing the window length for the slowness domain */
epslon1 = (u2 - u1) * percU;
wL = NINT(epslon1 / dU);
wL = 2 * wL + 1;
u2 += epslon1;
nU = NINT((u2 - u1) / dU); /* new nU to preserve last slowness */
/* w/o being windowed */
taper = alloc1float(nU);
/* building window for slowness integration */
for (i = (wL - 1) / 2, iU = 0; iU < nU; iU++)
{
taper[iU] = 1;
if (iU >= nU - (wL - 1) / 2)
{
i++;
taper[iU] =
.42 - .5 * cos(2 * PI * (float) i / ((float) (wL - 1))) +
.08 * cos(4 * PI * (float) i / ((float) (wL - 1)));
}
}
/* filtering in frequency domain */
filter(percW);
/* building frequency filtering */
/* I will assume that the receivers are in line (at z = 0) so phi = 0 */
phi = 0;
epslon1 = F3;
epslon2 = F1 * cos(phi) + F2 * sin(phi);
/* correction for the 1st layer */
thick[0] -= zs;
/* imaginary part of frequency for damping wrap-around */
tau = log(tau) / tMod;
if (tau > TAUMAX)
tau = TAUMAX;
/* normalization for the complex slowness */
if (f1 > 7.5)
wRef = f1 * 2 * PI;
else
wRef = 7.5 * 2 * PI;
/* reading data and model covariance matrixes */
inputCovar(corrDataFile, corrModelFile);
/* starting inverse procedure */
/* FRECHET derivative matrix */
gradient();
if (!noFrechet)
{
fp = fopen(frechetFile, "w");
for (i = 0; i < numberPar * limRange; i++)
{
fwrite(&F[i][0], sizeof(float), nR * nDM, fp);
}
fclose(fp);
}
/* building a-posteriori model covariance matrix */
/* prior information is used */
buffer1 = alloc1float(nDM);
buffer2 = alloc1float(nDM * nR);
if (verbose) fprintf(stderr, "Building posteriori covariance...\n");
for (iParam = 0; iParam < nParam; iParam++)
{
for (i = 0; i < nDM; i++)
{
for (offset = i, k = 0; k < nDM; k++)
{
buffer1[k] = CD[offset];
offset += MAX(SGN0(i - k) * (nDM - 1 - k), 1);
}
/* doing the product CD F */
for (iR = 0; iR < nR; iR++)
{
buffer2[iR * nDM + i] = 0;
for (k = 0; k < nDM; k++)
{
buffer2[iR * nDM + i] += buffer1[k] *
F[iParam][iR * nDM + k];
}
}
}
for (j = 0; j < nParam; j++)
{
CmPostInv[j][iParam] = 0;
for (k = 0; k < nDM * nR; k++)
{
CmPostInv[j][iParam] += buffer2[k] * F[j][k];
}
}
}
if (verbose)
fprintf(stderr, "Posteriori covariance built. Including prior...\n");
free1float(buffer1);
buffer1 = alloc1float(nParam);
/* including prior covariance matrix */
if (PRIOR)
{
shift = 0;
if (IMPEDANCE)
{
if (ipFrechet)
{
for (iParam = 0; iParam < limRange; iParam++)
{
for (offset = iParam, k = 0; k < limRange; k++)
{
buffer1[k] = CMP[offset];
offset += MAX(SGN0(iParam - k) * (limRange - 1 - k), 1);
}
for (k = 0; k < limRange; k++)
{
CmPostInv[iParam][k] += buffer1[k];
}
}
shift += limRange;
}
}
else
{
if (vpFrechet)
{
for (iParam = 0; iParam < limRange; iParam++)
{
for (offset = iParam, k = 0; k < limRange; k++)
{
buffer1[k] = CMP[offset];
offset += MAX(SGN0(iParam - k) * (limRange - 1 - k), 1);
}
for (k = 0; k < limRange; k++)
{
CmPostInv[iParam][k] += buffer1[k];
}
}
shift += limRange;
}
}
if (IMPEDANCE)
{
if (isFrechet)
{
for (iParam = 0; iParam < limRange; iParam++)
{
for (offset = iParam, k = 0; k < limRange; k++)
{
buffer1[k] = CMS[offset];
offset += MAX(SGN0(iParam - k) * (limRange - 1 - k), 1);
}
for (k = 0; k < limRange; k++)
{
CmPostInv[iParam + shift][k + shift] += buffer1[k];
}
}
shift += limRange;
}
}
else
{
if (vsFrechet)
{
for (iParam = 0; iParam < limRange; iParam++)
{
for (offset = iParam, k = 0; k < limRange; k++)
{
buffer1[k] = CMS[offset];
offset += MAX(SGN0(iParam - k) * (limRange - 1 - k), 1);
}
for (k = 0; k < limRange; k++)
{
CmPostInv[iParam + shift][k + shift] += buffer1[k];
}
}
shift += limRange;
}
}
if (rhoFrechet)
{
for (iParam = 0; iParam < limRange; iParam++)
{
for (offset = iParam, k = 0; k < limRange; k++)
{
buffer1[k] = CMrho[offset];
offset += MAX(SGN0(iParam - k) * (limRange - 1 - k), 1);
}
for (k = 0; k < limRange; k++)
{
CmPostInv[iParam + shift][k + shift] += buffer1[k];
}
}
}
}
if (verbose) fprintf(stderr, "Prior included. Inverting matrix...\n");
/* freeing memory */
free1float(buffer1);
free1float(buffer2);
free1float(alpha);
free1float(beta);
free1float(rho);
free1float(qP);
free1float(qS);
free1float(thick);
free2complex(PSlowness);
free2complex(SSlowness);
free2complex(S2Velocity);
free1float(CD);
free1float(CMP);
free1float(CMS);
free1float(CMrho);
free2float(F);
free2complex(v1);
free2complex(v2);
free3complex(DmB);
free2complex(derFactor);
free2complex(aux11);
free2complex(aux12);
free2complex(aux21);
free2complex(aux22);
free2complex(aux11Old);
free2complex(aux12Old);
free2complex(aux21Old);
free2complex(aux22Old);
/* inverting the matrix */
CmPost = alloc2float(nParam, nParam);
for (i = 0; i < nParam; i++) for (j = 0; j < nParam; j++)
CmPostInv[i][j] = CmPost[i][j];
inverse_matrix(nParam, CmPostInv);
if (verbose) fprintf(stderr, "Done with inverse matrix routine.\n");
buffer1 = alloc1float(nParam);
gp = fopen(postFile, "w");
for (i = 0; i < nParam; i++)
{
fwrite(CmPostInv[i], sizeof(float), nParam, gp);
}
fclose(fp);
}
ENTRYPOINT void
draw_stream (ModeInfo *mi)
{
stream_configuration *es = &ess[MI_SCREEN(mi)];
Display *dpy = MI_DISPLAY(mi);
Window window = MI_WINDOW(mi);
streamtime current_time;
float cur_time;
int i;
float alpha = 1.0;
Vector vx;
Vector vy;
GLfloat m[4*4];
if (!es->glx_context)
return;
gettime (¤t_time);
cur_time = (float)(GETSECS(current_time) * 1000 + GETMSECS(current_time) - es->start_time) / 1000.0;
cur_time *= global_speed;
glXMakeCurrent (MI_DISPLAY(mi), MI_WINDOW(mi), *es->glx_context);
glClear (GL_COLOR_BUFFER_BIT | GL_DEPTH_BUFFER_BIT);
glMatrixMode (GL_PROJECTION);
glLoadIdentity ();
glFrustum (-.6f, .6f, -.45f, .45f, 1, 1000);
glMatrixMode (GL_MODELVIEW);
glLoadIdentity ();
glEnable (GL_LIGHTING);
glEnable (GL_TEXTURE_2D);
glEnable (GL_BLEND);
glBlendFunc (GL_SRC_ALPHA, GL_ONE);
glDisable (GL_CULL_FACE);
glDisable (GL_DEPTH_TEST);
glDepthMask (0);
glTexEnvi (GL_TEXTURE_ENV, GL_TEXTURE_ENV_MODE, GL_ADD);
glTranslatef (0, 0, -300);
glRotatef (cur_time * 30, 1, 0, 0);
glRotatef (30 * sin(cur_time / 3) + 10, 0, 0, 1);
{
double x, y, z;
get_position (es->rot, &x, &y, &z, !es->button_down_p);
glTranslatef((x - 0.5) * 8,
(y - 0.5) * 8,
(z - 0.5) * 15);
gltrackball_rotate (es->trackball);
get_rotation (es->rot, &x, &y, &z, !es->button_down_p);
glRotatef (x * 360, 1.0, 0.0, 0.0);
glRotatef (y * 360, 0.0, 1.0, 0.0);
glRotatef (z * 360, 0.0, 0.0, 1.0);
}
if (cur_time > change_time1)
{
if (cur_time > change_time2)
{
glRotatef (90, 0, 1, 0);
if (cur_time > change_time3)
es->start_time = GETSECS(current_time) * 1000 + GETMSECS(current_time) - 5000;
}
else
{
glRotatef (180, 0, 1, 0);
}
}
glEnable ( GL_FOG);
glFogf (GL_FOG_START, 200);
glFogf (GL_FOG_END, 500);
glFogf (GL_FOG_MODE, GL_LINEAR);
glGetFloatv (GL_MODELVIEW_MATRIX, m);
inverse_matrix (m);
vx.x = m[0] * 10;
vx.y = m[1] * 10;
vx.z = m[2] * 10;
vy.x = m[4] * 10;
vy.y = m[5] * 10;
vy.z = m[6] * 10;
mi->polygon_count = 0;
for (i = 0; i != es->num_streams; i++)
{
mi->polygon_count += es->streams[i].num_flares;
render_flare_stream (&es->streams[i], cur_time, &vx, &vy, alpha);
}
glDisable (GL_TEXTURE_2D);
glDisable (GL_LIGHTING);
glDisable (GL_FOG);
glTexEnvi (GL_TEXTURE_ENV, GL_TEXTURE_ENV_MODE, GL_MODULATE);
if (mi->fps_p) do_fps (mi);
glFinish();
glXSwapBuffers (dpy, window);
}
int main(int argc,char *argv[])
{
char *listfile,*inputfile;
char choose= ' ';
string operate=" ";
double temperature=300;
string output=" ";
string segment="all";
int segment_b=0;
int segment_e=0;
// 读取当前的时间
time_t t = time( 0 );
char TIME[64];
strftime( TIME, sizeof(TIME), "%Y/%m/%d %X ",localtime(&t) );
//
switch(argc)
{
case 1:
cout<<"Usage:CurAnalysis -f listfile.txt -i inputfile.txt"<<endl;
exit(0);
case 2:
if(string(argv[1])=="-a")
{
Printversion();
exit(0);
}
if(string(argv[1])=="-h")
{
Printhelp();
exit(0);
}
case 5:
if(string(argv[1])=="-f"&&string(argv[3])=="-i")
{
listfile=argv[2];
inputfile=argv[4];
}
break;
default:
cout<<"Usage:CurAnalysis -f listfile.txt -i inputfile.txt"<<endl;
exit(0);
}
ReadInput(inputfile,operate,choose,output,temperature,segment,segment_b,segment_e);
/*
average部分已经完成，经测试可以使用，主要的问题是读文件的异常
比如说文件残缺，文件丢失等的情况的处理的过程没有完成。
*/
if(operate=="average")
{
if(choose=='E'||choose=='F'||choose=='G'||choose=='H')
{
double ***totaldata;
struct Filelist *fl;
struct Paramater *spt;
int N=0;
ofstream outfile(output.c_str(),ios::app);
fl=Readlist(listfile);
switch(choose)
{
case 'E':
spt=E_part(fl->file);
break;
case 'F':
spt=F_part(fl->file);
break;
case 'G':
spt=G_part(fl->file);
break;
case 'H':
spt=H_part(fl->file);
break;
}
int filesize=Getfilelen(fl);
int size=GetParamaterlen(spt);
if(segment!="all")
{
size=segment_e - segment_b+1;
}
if(segment=="all")
{
segment_b=1;
segment_e=size;
}
totaldata=f3tensor(0,5,0,size-1,0,filesize-1);
outfile<<"******************************************************************"<<endl;
//output the input file!
ifstream infile(inputfile);
string s;
getline(infile,s);
while(!infile.fail())
{
outfile<<"#"<<s<<endl;
getline(infile,s);
}
outfile<<TIME<<endl; //输出当前时间
infile.close();
//
while(fl!=NULL)
{
struct Paramater *sp;
switch(choose)
{
case 'E':
sp=E_part(fl->file);
break;
case 'F':
sp=F_part(fl->file);
break;
case 'G':
sp=G_part(fl->file);
break;
case 'H':
sp=H_part(fl->file);
break;
}
// int size=GetParamaterlen(sp);
double **data;
data=dmatrix(0,5,0,size-1);
struct Namelist *name;
name=(struct Namelist *)malloc(sizeof(struct Namelist));
Paramater2double(sp,data,name,segment_b,segment_e);
for(int i=0;i<6;i++)
{
for(int j=0;j<size;j++)
{
totaldata[i][j][N]=data[i][j];
}
}
free_dmatrix(data,0,5,0,size-1);
cout<<"Read file "<<fl->file<<" finished!"<<endl;//输出提示
fl=fl->next;
N++;
}
double **aveg;
aveg=dmatrix(0,5,0,size-1);
for(int i=0;i<6;i++)
{
for(int j=0;j<size;j++)
{
aveg[i][j]=0;
}
}
outfile<<endl;
outfile<<"******************************************************************"<<endl;
outfile<<"\t"<<"rise"<<"\t"<<"roll"<<"\t"<<"shift"<<"\t"<<"slide"<<"\t"<<"tilt"<<"\t"<<"twist"<<endl;
outfile<<endl;
for(int i=0;i<size;i++)
{
outfile<<i+segment_b<<"\t";
for(int j=0;j<6;j++)
{
for(int k=0;k<filesize;k++)
{
aveg[j][i]+=totaldata[j][i][k];
}
aveg[j][i]=aveg[j][i]/filesize;
outfile<<fixed<<showpoint;
outfile<<setprecision(2)<<aveg[j][i]<<"\t";
}
outfile<<endl;
}
outfile<<endl;
outfile<<"******************************************************************"<<endl;
cout<<"finished the calculation of average !"<<endl;
cout<<"the output write in the file "<<output<<" !"<<endl;
outfile.close();
free_f3tensor(totaldata,0,5,0,size-1,0,filesize-1);
}
//average for J
if(choose=='J')
{
double ***totaldata;
struct Filelist *fl;
struct Backbone *spt;
int N=0;
fl=Readlist(listfile);
spt=J_part(fl->file);
int filesize=Getfilelen(fl);
int size=GetBackbonelen(spt);
if(segment!="all")
{
size=segment_e - segment_b+1;
}
if(segment=="all")
{
segment_b=1;
segment_e=size;
}
totaldata=f3tensor(0,13,0,size-1,0,filesize-1);
ofstream outfile(output.c_str(),ios::app);
outfile<<"******************************************************************"<<endl;
//output the input file!
ifstream infile(inputfile);
string s;
getline(infile,s);
while(!infile.fail())
{
outfile<<"#"<<s<<endl;
getline(infile,s);
}
outfile<<TIME<<endl; //输出当前时间
infile.close();
//
while(fl!=NULL)
{
struct Backbone *sp;
sp=J_part(fl->file);
// int size=GetBackbonelen(sp);
double **data;
data=dmatrix(0,13,0,size-1);
struct Namelist *name;
name=(struct Namelist *)malloc(sizeof(struct Namelist));
Backbone2double(sp,data,name,segment_b,segment_e);
for(int i=0;i<14;i++)
{
for(int j=0;j<size;j++)
{
totaldata[i][j][N]=data[i][j];
}
}
free_dmatrix(data,0,13,0,size-1);
cout<<"Read file "<<fl->file<<" finished!"<<endl;//输出提示
fl=fl->next;
N++;
}
double **aveg;
aveg=dmatrix(0,13,0,size-1);
for(int i=0;i<14;i++)
{
for(int j=0;j<size;j++)
{
aveg[i][j]=0;
}
}
outfile<<endl;
outfile<<"******************************************************************"<<endl;
outfile<<"\t"<<"alpha"<<"\t"<<"ampli"<<"\t"<<"beta"<<"\t"<<"c1"<<"\t"<<"c1c2"<<"\t"<<"c2"<<"\t"<<"c2c3"<<"\t"<<"c3"<<"\t"<<"chi"<<"\t"<<"delta"<<"\t"<<"epsil"<<"\t"<<"gamma"<<"\t"<<"phase"<<"\t"<<"zeta"<<endl;
outfile<<endl;
for(int i=0;i<size;i++)
{
outfile<<i+segment_b<<"\t";
for(int j=0;j<14;j++)
{
for(int k=0;k<filesize;k++)
{
aveg[j][i]+=totaldata[j][i][k];
}
aveg[j][i]=aveg[j][i]/filesize;
outfile<<fixed<<showpoint;
outfile<<setprecision(2)<<aveg[j][i]<<"\t";
}
outfile<<endl;
}
outfile<<endl;
outfile<<"******************************************************************"<<endl;
cout<<"finished the calculation of average !"<<endl;
cout<<"the output write in the file "<<output<<" !"<<endl;
outfile.close();
free_f3tensor(totaldata,0,13,0,size-1,0,filesize-1);
}
}
//计算某一数据的分布
if(operate=="distribution")
{
//part 1: get the data
if(choose=='E'||choose=='F'||choose=='G'||choose=='H')
{
double ***totaldata;
struct Filelist *fl;
struct Paramater *spt;
int N=0;
ofstream outfile(output.c_str(),ios::app);
fl=Readlist(listfile);
switch(choose)
{
case 'E':
spt=E_part(fl->file);
break;
case 'F':
spt=F_part(fl->file);
break;
case 'G':
spt=G_part(fl->file);
break;
case 'H':
spt=H_part(fl->file);
break;
}
int filesize=Getfilelen(fl);
int size=GetParamaterlen(spt);
if(segment!="all")
{
size=segment_e - segment_b+1;
}
if(segment=="all")
{
segment_b=1;
segment_e=size;
}
totaldata=f3tensor(0,5,0,size-1,0,filesize-1);
outfile<<"******************************************************************"<<endl;
//output the input file!
ifstream infile(inputfile);
string s;
getline(infile,s);
while(!infile.fail())
{
outfile<<"#"<<s<<endl;
getline(infile,s);
}
outfile<<TIME<<endl; //输出当前时间
infile.close();
//
while(fl!=NULL)
{
struct Paramater *sp;
switch(choose)
{
case 'E':
sp=E_part(fl->file);
break;
case 'F':
sp=F_part(fl->file);
break;
case 'G':
sp=G_part(fl->file);
break;
case 'H':
sp=H_part(fl->file);
break;
}
// int size=GetParamaterlen(sp);
double **data;
data=dmatrix(0,5,0,size-1);
struct Namelist *name;
name=(struct Namelist *)malloc(sizeof(struct Namelist));
Paramater2double(sp,data,name,segment_b,segment_e);
for(int i=0;i<6;i++)
{
for(int j=0;j<size;j++)
{
totaldata[i][j][N]=data[i][j];
}
}
free_dmatrix(data,0,5,0,size-1);
cout<<"Read file "<<fl->file<<" finished!"<<endl;//输出提示
fl=fl->next;
N++;
}
// finished the input data
//calculate the distribution!
double *vect;
vect=dvector(0, size*filesize-1) ;
for(int i=0;i<6;i++)
{
outfile<<"******************************************************************"<<endl;
switch(i)
{
case 0:
outfile<<"the distribution of RISE"<<endl;
break;
case 1:
outfile<<"the distribution of ROLL"<<endl;
break;
case 2:
outfile<<"the distribution of SHIFT"<<endl;
break;
case 3:
outfile<<"the distribution of SLIDE"<<endl;
break;
case 4:
outfile<<"the distribution of TILT"<<endl;
break;
case 5:
outfile<<"the distribution of TWIST"<<endl;
break;
}
outfile<<"******************************************************************"<<endl;
//
for(int m=0;m<size;m++)
{
for(int n=0;n<filesize;n++)
{
vect[m*filesize+n]=totaldata[i][m][n];
}
}
//把二维的数据转化为一维的数据！
Distribution(vect,size*filesize,output);
outfile<<"******************************************************************"<<endl;
}
cout<<"finished the calculation of distribution !"<<endl;
cout<<"the output write in the file "<<output<<" !"<<endl;
outfile.close();
free_f3tensor(totaldata,0,5,0,size-1,0,filesize-1);
// finished the calculation !
}
if(choose=='J')
{
double ***totaldata;
struct Filelist *fl;
struct Backbone *spt;
int N=0;
fl=Readlist(listfile);
spt=J_part(fl->file);
int filesize=Getfilelen(fl);
int size=GetBackbonelen(spt);
if(segment!="all")
{
size=segment_e - segment_b+1;
}
if(segment=="all")
{
segment_b=1;
segment_e=size;
}
totaldata=f3tensor(0,13,0,size-1,0,filesize-1);
ofstream outfile(output.c_str(),ios::app);
outfile<<"******************************************************************"<<endl;
//output the input file!
ifstream infile(inputfile);
string s;
getline(infile,s);
while(!infile.fail())
{
outfile<<"#"<<s<<endl;
getline(infile,s);
}
outfile<<TIME<<endl; //输出当前时间
infile.close();
//
while(fl!=NULL)
{
struct Backbone *sp;
sp=J_part(fl->file);
// int size=GetBackbonelen(sp);
double **data;
data=dmatrix(0,13,0,size-1);
struct Namelist *name;
name=(struct Namelist *)malloc(sizeof(struct Namelist));
Backbone2double(sp,data,name,segment_b,segment_e);
for(int i=0;i<14;i++)
{
for(int j=0;j<size;j++)
{
totaldata[i][j][N]=data[i][j];
}
}
free_dmatrix(data,0,13,0,size-1);
cout<<"Read file "<<fl->file<<" finished!"<<endl;//输出提示
fl=fl->next;
N++;
}
double *vect;
vect=dvector(0, size*filesize-1) ;
for(int i=0;i<14;i++)
{
outfile<<"******************************************************************"<<endl;
switch(i)
{
case 0:
outfile<<"the distribution of ALPHA"<<endl;
break;
case 1:
outfile<<"the distribution of AMPLI"<<endl;
break;
case 2:
outfile<<"the distribution of BETA"<<endl;
break;
case 3:
outfile<<"the distribution of C1'"<<endl;
break;
case 4:
outfile<<"the distribution of C1'-C2'"<<endl;
break;
case 5:
outfile<<"the distribution of C2'"<<endl;
break;
case 6:
outfile<<"the distribution of C2'-C3'"<<endl;
break;
case 7:
outfile<<"the distribution of C3'"<<endl;
break;
case 8:
outfile<<"the distribution of CHI"<<endl;
break;
case 9:
outfile<<"the distribution of DELTA"<<endl;
break;
case 10:
outfile<<"the distribution of ESPIL"<<endl;
break;
case 11:
outfile<<"the distribution of GAMMA"<<endl;
break;
case 12:
outfile<<"the distribution of PHASE"<<endl;
break;
case 13:
outfile<<"the distribution of ZETA"<<endl;
break;
}
outfile<<"******************************************************************"<<endl;
//
for(int m=0;m<size;m++)
{
for(int n=0;n<filesize;n++)
{
vect[m*filesize+n]=totaldata[i][m][n];
}
}
//把二维的数据转化为一维的数据！
Distribution(vect,size*filesize,output);
outfile<<"******************************************************************"<<endl;
}
cout<<"finished the calculation of distribution !"<<endl;
cout<<"the output write in the file "<<output<<" !"<<endl;
outfile.close();
free_f3tensor(totaldata,0,13,0,size-1,0,filesize-1);
// finished the calculation !
}
}
/*计算刚性*/
if(operate=="stiffness")
{
/*get the data*/
if(choose=='E'||choose=='F'||choose=='G'||choose=='H')
{
double ***totaldata;
struct Filelist *fl;
struct Paramater *spt;
int N=0;
ofstream outfile(output.c_str(),ios::app);
fl=Readlist(listfile);
switch(choose)
{
case 'E':
spt=E_part(fl->file);
break;
case 'F':
spt=F_part(fl->file);
break;
case 'G':
spt=G_part(fl->file);
break;
case 'H':
spt=H_part(fl->file);
break;
}
int filesize=Getfilelen(fl);
int size=GetParamaterlen(spt);
if(segment!="all")
{
size=segment_e - segment_b+1;
}
if(segment=="all")
{
segment_b=1;
segment_e=size;
}
totaldata=f3tensor(0,5,0,size-1,0,filesize-1);
outfile<<"******************************************************************"<<endl;
//output the input file!
ifstream infile(inputfile);
string s;
getline(infile,s);
while(!infile.fail())
{
outfile<<"#"<<s<<endl;
getline(infile,s);
}
outfile<<TIME<<endl; //输出当前时间
infile.close();
//
while(fl!=NULL)
{
struct Paramater *sp;
switch(choose)
{
case 'E':
sp=E_part(fl->file);
break;
case 'F':
sp=F_part(fl->file);
break;
case 'G':
sp=G_part(fl->file);
break;
case 'H':
sp=H_part(fl->file);
break;
}
// int size=GetParamaterlen(sp);
double **data;
data=dmatrix(0,5,0,size-1);
struct Namelist *name;
name=(struct Namelist *)malloc(sizeof(struct Namelist));
Paramater2double(sp,data,name,segment_b,segment_e);
for(int i=0;i<6;i++)
{
for(int j=0;j<size;j++)
{
totaldata[i][j][N]=data[i][j];
}
}
free_dmatrix(data,0,5,0,size-1);
cout<<"Read file "<<fl->file<<" finished!"<<endl;//输出提示
fl=fl->next;
N++;
}
// finished the input data
/*calculate the stiffness! */
double **stiff;
double **matrix;
double **inve_matrix;
/*output the title */
outfile<<"******************************************************************"<<endl;
outfile<<"calculate the stiffness of part "<<choose<<endl;
outfile<<"******************************************************************"<<endl;
for(int x=segment_b-1;x<segment_e;x++) /* the loop for segment */
{
stiff=dmatrix(0,5,0, filesize-1) ; /* hold the space!*/
matrix=dmatrix(0,5,0,5);
inve_matrix=dmatrix(0,5,0,5);
for(int i=0;i<6;i++)
{
for(int n=0;n<filesize;n++)
{
stiff[i][n]=totaldata[i][x][n];
}
}
Getmatrix(stiff,matrix,filesize); /*cteate the helical matrix!*/
free_dmatrix(stiff,0,5,0,filesize-1);
inverse_matrix(matrix, inve_matrix,6);
free_dmatrix(matrix,0,5,0,5);
outfile<<"the stiffness of segment "<<x+1<<endl;
outfile<<"******************************************************************"<<endl;
outfile<<"\t"<<"rise"<<"\t"<<"roll"<<"\t"<<"shift"<<"\t"<<"slide"<<"\t"<<"tilt"<<"\t"<<"twist"<<endl;
outfile<<fixed<<showpoint;
for(int i=0;i<6;i++)
{
switch(i)
{
case 0:
outfile<<"rise"<<"\t";
break;
case 1:
outfile<<"roll"<<"\t";
break;
case 2:
outfile<<"shift"<<"\t";
break;
case 3:
outfile<<"slide"<<"\t";
break;
case 4:
outfile<<"tilt"<<"\t";
break;
case 5:
outfile<<"twist"<<"\t";
break;
}
for(int j=0;j<6;j++)
{
outfile<<setprecision(2)<<R*temperature*inve_matrix[i][j]<<"\t";
}
outfile<<endl;
}
outfile<<"******************************************************************"<<endl;
}
cout<<"finished the calculation of stiffness !"<<endl;
cout<<"the output write in the file "<<"\""<<output<<"\" !"<<endl;
outfile.close();
free_f3tensor(totaldata,0,5,0,size-1,0,filesize-1);
// finished the calculation !
}
else
{
cout<<"wrong input, please check!"<<endl;
exit(0);
}
}
if(operate!="stiffness"&&operate!="average"&&operate!="distribution")
{
cout<<"Input a wrong operate. the correct oprtate is 'average/distribution/stiffness'"<<endl;
exit(0);
}
return 0;
}