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colvar_UIestimator.h

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00001 // -*- Mode:c++; c-basic-offset: 4; -*-
00002 
00003 // This file is part of the Collective Variables module (Colvars).
00004 // The original version of Colvars and its updates are located at:
00005 // https://github.com/Colvars/colvars
00006 // Please update all Colvars source files before making any changes.
00007 // If you wish to distribute your changes, please submit them to the
00008 // Colvars repository at GitHub.
00009 
00010 #ifndef COLVAR_UIESTIMATOR_H
00011 #define COLVAR_UIESTIMATOR_H
00012 
00013 #include <cmath>
00014 #include <vector>
00015 #include <iostream>
00016 #include <fstream>
00017 #include <string>
00018 
00019 #include <typeinfo>
00020 
00021 // only for colvar module!
00022 // when integrated into other code, just remove this line and "...cvm::backup_file(...)"
00023 #include "colvarmodule.h"
00024 #include "colvarproxy.h"
00025 
00026 namespace UIestimator {
00027 const int Y_SIZE = 21; // defines the range of extended CV with respect to a given CV
00028 // For example, CV=10, width=1, Y_SIZE=21, then eCV=[0-20], having a size of 21
00029 const int HALF_Y_SIZE = 10;
00030 const int EXTENDED_X_SIZE = HALF_Y_SIZE;
00031 const double EPSILON = 0.000001; // for comparison of float numbers
00032 
00033 class n_matrix { // Stores the distribution matrix of n(x,y)
00034 
00035 public:
00036 n_matrix() {}
00037 n_matrix(const std::vector<double> & lowerboundary_input, // lowerboundary of x
00038 const std::vector<double> & upperboundary_input, // upperboundary of
00039 const std::vector<double> & width_input, // width of x
00040 const int y_size_input) { // size of y, for example, ysize=7, then when x=1, the distribution of y in [-2,4] is considered
00041 
00042 int i;
00043 
00044 this->lowerboundary = lowerboundary_input;
00045 this->upperboundary = upperboundary_input;
00046 this->width = width_input;
00047 this->dimension = lowerboundary_input.size();
00048 this->y_size = y_size_input; // keep in mind the internal (spare) matrix is stored in diagonal form
00049 this->y_total_size = int(cvm::pow(double(y_size_input), double(dimension)) + EPSILON);
00050 
00051 // the range of the matrix is [lowerboundary, upperboundary]
00052 x_total_size = 1;
00053 for (i = 0; i < dimension; i++) {
00054 x_size.push_back(int((upperboundary_input[i] - lowerboundary_input[i]) / width_input[i] + EPSILON));
00055 x_total_size *= x_size[i];
00056 }
00057 
00058 // initialize the internal matrix
00059 matrix.reserve(x_total_size);
00060 for (i = 0; i < x_total_size; i++) {
00061 matrix.push_back(std::vector<int>(y_total_size, 0));
00062 }
00063 
00064 temp.resize(dimension);
00065 }
00066 
00067 int get_value(const std::vector<double> & x, const std::vector<double> & y) {
00068 return matrix[convert_x(x)][convert_y(x, y)];
00069 }
00070 
00071 void set_value(const std::vector<double> & x, const std::vector<double> & y, const int value) {
00072 matrix[convert_x(x)][convert_y(x,y)] = value;
00073 }
00074 
00075 void increase_value(const std::vector<double> & x, const std::vector<double> & y, const int value) {
00076 matrix[convert_x(x)][convert_y(x,y)] += value;
00077 }
00078 
00079 private:
00080 std::vector<double> lowerboundary;
00081 std::vector<double> upperboundary;
00082 std::vector<double> width;
00083 int dimension;
00084 std::vector<int> x_size; // the size of x in each dimension
00085 int x_total_size; // the size of x of the internal matrix
00086 int y_size; // the size of y in each dimension
00087 int y_total_size; // the size of y of the internal matrix
00088 
00089 std::vector<std::vector<int> > matrix; // the internal matrix
00090 
00091 std::vector<int> temp; // this vector is used in convert_x and convert_y to save computational resource
00092 
00093 int convert_x(const std::vector<double> & x) { // convert real x value to its interal index
00094 
00095 int i, j;
00096 
00097 for (i = 0; i < dimension; i++) {
00098 temp[i] = int((x[i] - lowerboundary[i]) / width[i] + EPSILON);
00099 }
00100 
00101 int index = 0;
00102 for (i = 0; i < dimension; i++) {
00103 if (i + 1 < dimension) {
00104 int x_temp = 1;
00105 for (j = i + 1; j < dimension; j++)
00106 x_temp *= x_size[j];
00107 index += temp[i] * x_temp;
00108 }
00109 else
00110 index += temp[i];
00111 }
00112 return index;
00113 }
00114 
00115 int convert_y(const std::vector<double> & x, const std::vector<double> & y) { // convert real y value to its interal index
00116 
00117 int i;
00118 
00119 for (i = 0; i < dimension; i++) {
00120 temp[i] = int(round((round(y[i] / width[i] + EPSILON) - round(x[i] / width[i] + EPSILON)) + (y_size - 1) / 2 + EPSILON));
00121 }
00122 
00123 int index = 0;
00124 for (i = 0; i < dimension; i++) {
00125 if (i + 1 < dimension)
00126 index += temp[i] * int(cvm::pow(double(y_size), double(dimension - i - 1)) + EPSILON);
00127 else
00128 index += temp[i];
00129 }
00130 return index;
00131 }
00132 
00133 double round(double r) {
00134 return (r > 0.0) ? floor(r + 0.5) : ceil(r - 0.5);
00135 }
00136 };
00137 
00138 // vector, store the sum_x, sum_x_square, count_y
00139 template <typename T>
00140 class n_vector {
00141 
00142 public:
00143 n_vector() {}
00144 n_vector(const std::vector<double> & lowerboundary_input, // lowerboundary of x
00145 const std::vector<double> & upperboundary_input, // upperboundary of
00146 const std::vector<double> & width_input, // width of x
00147 const int y_size_input, // size of y, for example, ysize=7, then when x=1, the distribution of y in [-2,4] is considered
00148 const T & default_value) { // the default value of T
00149 
00150 this->width = width_input;
00151 this->dimension = lowerboundary_input.size();
00152 
00153 x_total_size = 1;
00154 for (int i = 0; i < dimension; i++) {
00155 this->lowerboundary.push_back(lowerboundary_input[i] - (y_size_input - 1) / 2 * width_input[i] - EPSILON);
00156 this->upperboundary.push_back(upperboundary_input[i] + (y_size_input - 1) / 2 * width_input[i] + EPSILON);
00157 
00158 x_size.push_back(int((this->upperboundary[i] - this->lowerboundary[i]) / this->width[i] + EPSILON));
00159 x_total_size *= x_size[i];
00160 }
00161 
00162 // initialize the internal vector
00163 vector.resize(x_total_size, default_value);
00164 
00165 temp.resize(dimension);
00166 }
00167 
00168 T & get_value(const std::vector<double> & x) {
00169 return vector[convert_x(x)];
00170 }
00171 
00172 void set_value(const std::vector<double> & x, const T value) {
00173 vector[convert_x(x)] = value;
00174 }
00175 
00176 void increase_value(const std::vector<double> & x, const T value) {
00177 vector[convert_x(x)] += value;
00178 }
00179 
00180 private:
00181 std::vector<double> lowerboundary;
00182 std::vector<double> upperboundary;
00183 std::vector<double> width;
00184 int dimension;
00185 std::vector<int> x_size; // the size of x in each dimension
00186 int x_total_size; // the size of x of the internal matrix
00187 
00188 std::vector<T> vector; // the internal vector
00189 
00190 std::vector<int> temp; // this vector is used in convert_x and convert_y to save computational resource
00191 
00192 int convert_x(const std::vector<double> & x) { // convert real x value to its interal index
00193 
00194 int i, j;
00195 
00196 for (i = 0; i < dimension; i++) {
00197 temp[i] = int((x[i] - lowerboundary[i]) / width[i] + EPSILON);
00198 }
00199 
00200 int index = 0;
00201 for (i = 0; i < dimension; i++) {
00202 if (i + 1 < dimension) {
00203 int x_temp = 1;
00204 for (j = i + 1; j < dimension; j++)
00205 x_temp *= x_size[j];
00206 index += temp[i] * x_temp;
00207 }
00208 else
00209 index += temp[i];
00210 }
00211 return index;
00212 }
00213 };
00214 
00215 class UIestimator { // the implemension of UI estimator
00216 
00217 public:
00218 UIestimator() {}
00219 
00220 //called when (re)start an eabf simulation
00221 UIestimator(const std::vector<double> & lowerboundary_input,
00222 const std::vector<double> & upperboundary_input,
00223 const std::vector<double> & width_input,
00224 const std::vector<double> & krestr_input, // force constant in eABF
00225 const std::string & output_filename_input, // the prefix of output files
00226 const int output_freq_input,
00227 const bool restart_input, // whether restart from a .count and a .grad file
00228 const std::vector<std::string> & input_filename_input, // the prefixes of input files
00229 const double temperature_input) {
00230 
00231 // initialize variables
00232 this->lowerboundary = lowerboundary_input;
00233 this->upperboundary = upperboundary_input;
00234 this->width = width_input;
00235 this->krestr = krestr_input;
00236 this->output_filename = output_filename_input;
00237 this->output_freq = output_freq_input;
00238 this->restart = restart_input;
00239 this->input_filename = input_filename_input;
00240 this->temperature = temperature_input;
00241 
00242 int i, j;
00243 
00244 dimension = lowerboundary.size();
00245 
00246 for (i = 0; i < dimension; i++) {
00247 sum_x.push_back(n_vector<double>(lowerboundary, upperboundary, width, Y_SIZE, 0.0));
00248 sum_x_square.push_back(n_vector<double>(lowerboundary, upperboundary, width, Y_SIZE, 0.0));
00249 
00250 x_av.push_back(n_vector<double>(lowerboundary, upperboundary, width, Y_SIZE, 0.0));
00251 sigma_square.push_back(n_vector<double>(lowerboundary, upperboundary, width, Y_SIZE, 0.0));
00252 }
00253 
00254 count_y = n_vector<int>(lowerboundary, upperboundary, width, Y_SIZE, 0);
00255 distribution_x_y = n_matrix(lowerboundary, upperboundary, width, Y_SIZE);
00256 
00257 grad = n_vector<std::vector<double> >(lowerboundary, upperboundary, width, 1, std::vector<double>(dimension, 0.0));
00258 count = n_vector<int>(lowerboundary, upperboundary, width, 1, 0);
00259 
00260 written = false;
00261 written_1D = false;
00262 
00263 if (dimension == 1) {
00264 std::vector<double> upperboundary_temp = upperboundary;
00265 upperboundary_temp[0] = upperboundary[0] + width[0];
00266 oneD_pmf = n_vector<double>(lowerboundary, upperboundary_temp, width, 1, 0.0);
00267 }
00268 
00269 if (restart == true) {
00270 input_grad = n_vector<std::vector<double> >(lowerboundary, upperboundary, width, 1, std::vector<double>(dimension, 0.0));
00271 input_count = n_vector<int>(lowerboundary, upperboundary, width, 1, 0);
00272 
00273 // initialize input_Grad and input_count
00274 // the loop_flag is a n-dimensional vector, increae from lowerboundary to upperboundary when looping
00275 std::vector<double> loop_flag(dimension, 0);
00276 for (i = 0; i < dimension; i++) {
00277 loop_flag[i] = lowerboundary[i];
00278 }
00279 
00280 i = 0;
00281 while (i >= 0) {
00282 for (j = 0; j < dimension; j++) {
00283 input_grad.set_value(loop_flag, std::vector<double>(dimension,0));
00284 }
00285 input_count.set_value(loop_flag, 0);
00286 
00287 // iterate over any dimensions
00288 i = dimension - 1;
00289 while (i >= 0) {
00290 loop_flag[i] += width[i];
00291 if (loop_flag[i] > upperboundary[i] - width[i] + EPSILON) {
00292 loop_flag[i] = lowerboundary[i];
00293 i--;
00294 }
00295 else
00296 break;
00297 }
00298 }
00299 read_inputfiles(input_filename);
00300 }
00301 }
00302 
00303 ~UIestimator() {}
00304 
00305 // called from MD engine every step
00306 bool update(cvm::step_number /* step */,
00307 std::vector<double> x, std::vector<double> y) {
00308 
00309 int i;
00310 
00311 for (i = 0; i < dimension; i++) {
00312 // for dihedral RC, it is possible that x = 179 and y = -179, should correct it
00313 // may have problem, need to fix
00314 if (x[i] > 150 && y[i] < -150) {
00315 y[i] += 360;
00316 }
00317 if (x[i] < -150 && y[i] > 150) {
00318 y[i] -= 360;
00319 }
00320 
00321 if (x[i] < lowerboundary[i] - EXTENDED_X_SIZE * width[i] + EPSILON || x[i] > upperboundary[i] + EXTENDED_X_SIZE * width[i] - EPSILON \
00322 || y[i] - x[i] < -HALF_Y_SIZE * width[i] + EPSILON || y[i] - x[i] > HALF_Y_SIZE * width[i] - EPSILON \
00323 || y[i] - lowerboundary[i] < -HALF_Y_SIZE * width[i] + EPSILON || y[i] - upperboundary[i] > HALF_Y_SIZE * width[i] - EPSILON)
00324 return false;
00325 }
00326 
00327 for (i = 0; i < dimension; i++) {
00328 sum_x[i].increase_value(y, x[i]);
00329 sum_x_square[i].increase_value(y, x[i] * x[i]);
00330 }
00331 count_y.increase_value(y, 1);
00332 
00333 for (i = 0; i < dimension; i++) {
00334 // adapt colvars precision
00335 if (x[i] < lowerboundary[i] + EPSILON || x[i] > upperboundary[i] - EPSILON)
00336 return false;
00337 }
00338 distribution_x_y.increase_value(x, y, 1);
00339 
00340 return true;
00341 }
00342 
00343 // update the output_filename
00344 void update_output_filename(const std::string& filename) {
00345 output_filename = filename;
00346 }
00347 
00348 private:
00349 std::vector<n_vector<double> > sum_x; // the sum of x in each y bin
00350 std::vector<n_vector<double> > sum_x_square; // the sum of x in each y bin
00351 n_vector<int> count_y; // the distribution of y
00352 n_matrix distribution_x_y; // the distribution of <x, y> pair
00353 
00354 int dimension;
00355 
00356 std::vector<double> lowerboundary;
00357 std::vector<double> upperboundary;
00358 std::vector<double> width;
00359 std::vector<double> krestr;
00360 std::string output_filename;
00361 int output_freq;
00362 bool restart;
00363 std::vector<std::string> input_filename;
00364 double temperature;
00365 
00366 n_vector<std::vector<double> > grad;
00367 n_vector<int> count;
00368 
00369 n_vector<double> oneD_pmf;
00370 
00371 n_vector<std::vector<double> > input_grad;
00372 n_vector<int> input_count;
00373 
00374 // used in double integration
00375 std::vector<n_vector<double> > x_av;
00376 std::vector<n_vector<double> > sigma_square;
00377 
00378 bool written;
00379 bool written_1D;
00380 
00381 public:
00382 // calculate gradients from the internal variables
00383 void calc_pmf() {
00384 colvarproxy *proxy = cvm::main()->proxy;
00385 
00386 int norm;
00387 int i, j, k;
00388 
00389 std::vector<double> loop_flag(dimension, 0);
00390 for (i = 0; i < dimension; i++) {
00391 loop_flag[i] = lowerboundary[i] - HALF_Y_SIZE * width[i];
00392 }
00393 
00394 i = 0;
00395 while (i >= 0) {
00396 norm = count_y.get_value(loop_flag) > 0 ? count_y.get_value(loop_flag) : 1;
00397 for (j = 0; j < dimension; j++) {
00398 x_av[j].set_value(loop_flag, sum_x[j].get_value(loop_flag) / norm);
00399 sigma_square[j].set_value(loop_flag, sum_x_square[j].get_value(loop_flag) / norm - x_av[j].get_value(loop_flag) * x_av[j].get_value(loop_flag));
00400 }
00401 
00402 // iterate over any dimensions
00403 i = dimension - 1;
00404 while (i >= 0) {
00405 loop_flag[i] += width[i];
00406 if (loop_flag[i] > upperboundary[i] + HALF_Y_SIZE * width[i] - width[i] + EPSILON) {
00407 loop_flag[i] = lowerboundary[i] - HALF_Y_SIZE * width[i];
00408 i--;
00409 }
00410 else
00411 break;
00412 }
00413 }
00414 
00415 // double integration
00416 std::vector<double> av(dimension, 0);
00417 std::vector<double> diff_av(dimension, 0);
00418 
00419 std::vector<double> loop_flag_x(dimension, 0);
00420 std::vector<double> loop_flag_y(dimension, 0);
00421 for (i = 0; i < dimension; i++) {
00422 loop_flag_x[i] = lowerboundary[i];
00423 loop_flag_y[i] = loop_flag_x[i] - HALF_Y_SIZE * width[i];
00424 }
00425 
00426 i = 0;
00427 while (i >= 0) {
00428 norm = 0;
00429 for (k = 0; k < dimension; k++) {
00430 av[k] = 0;
00431 diff_av[k] = 0;
00432 loop_flag_y[k] = loop_flag_x[k] - HALF_Y_SIZE * width[k];
00433 }
00434 
00435 j = 0;
00436 while (j >= 0) {
00437 norm += distribution_x_y.get_value(loop_flag_x, loop_flag_y);
00438 for (k = 0; k < dimension; k++) {
00439 if (sigma_square[k].get_value(loop_flag_y) > EPSILON || sigma_square[k].get_value(loop_flag_y) < -EPSILON)
00440 av[k] += distribution_x_y.get_value(loop_flag_x, loop_flag_y) * ( (loop_flag_x[k] + 0.5 * width[k]) - x_av[k].get_value(loop_flag_y)) / sigma_square[k].get_value(loop_flag_y);
00441 
00442 diff_av[k] += distribution_x_y.get_value(loop_flag_x, loop_flag_y) * (loop_flag_x[k] - loop_flag_y[k]);
00443 }
00444 
00445 // iterate over any dimensions
00446 j = dimension - 1;
00447 while (j >= 0) {
00448 loop_flag_y[j] += width[j];
00449 if (loop_flag_y[j] > loop_flag_x[j] + HALF_Y_SIZE * width[j] - width[j] + EPSILON) {
00450 loop_flag_y[j] = loop_flag_x[j] - HALF_Y_SIZE * width[j];
00451 j--;
00452 }
00453 else
00454 break;
00455 }
00456 }
00457 
00458 std::vector<double> grad_temp(dimension, 0);
00459 for (k = 0; k < dimension; k++) {
00460 diff_av[k] /= (norm > 0 ? norm : 1);
00461 av[k] = proxy->boltzmann() * temperature * av[k] / (norm > 0 ? norm : 1);
00462 grad_temp[k] = av[k] - krestr[k] * diff_av[k];
00463 }
00464 grad.set_value(loop_flag_x, grad_temp);
00465 count.set_value(loop_flag_x, norm);
00466 
00467 // iterate over any dimensions
00468 i = dimension - 1;
00469 while (i >= 0) {
00470 loop_flag_x[i] += width[i];
00471 if (loop_flag_x[i] > upperboundary[i] - width[i] + EPSILON) {
00472 loop_flag_x[i] = lowerboundary[i];
00473 i--;
00474 }
00475 else
00476 break;
00477 }
00478 }
00479 }
00480 
00481 
00482 // calculate 1D pmf
00483 void calc_1D_pmf()
00484 {
00485 std::vector<double> last_position(1, 0);
00486 std::vector<double> position(1, 0);
00487 
00488 double min = 0;
00489 double dG = 0;
00490 double i;
00491 
00492 oneD_pmf.set_value(lowerboundary, 0);
00493 last_position = lowerboundary;
00494 for (i = lowerboundary[0] + width[0]; i < upperboundary[0] + EPSILON; i += width[0]) {
00495 position[0] = i + EPSILON;
00496 if (restart == false || input_count.get_value(last_position) == 0) {
00497 dG = oneD_pmf.get_value(last_position) + grad.get_value(last_position)[0] * width[0];
00498 }
00499 else {
00500 dG = oneD_pmf.get_value(last_position) + ((grad.get_value(last_position)[0] * count.get_value(last_position) + input_grad.get_value(last_position)[0] * input_count.get_value(last_position)) / (count.get_value(last_position) + input_count.get_value(last_position))) * width[0];
00501 }
00502 if (dG < min)
00503 min = dG;
00504 oneD_pmf.set_value(position, dG);
00505 last_position[0] = i + EPSILON;
00506 }
00507 
00508 for (i = lowerboundary[0]; i < upperboundary[0] + EPSILON; i += width[0]) {
00509 position[0] = i + EPSILON;
00510 oneD_pmf.set_value(position, oneD_pmf.get_value(position) - min);
00511 }
00512 }
00513 
00514 // write 1D pmf
00515 void write_1D_pmf() {
00516 std::string pmf_filename = output_filename + ".UI.pmf";
00517 
00518 // only for colvars module!
00519 if (written_1D) cvm::backup_file(pmf_filename.c_str());
00520 
00521 std::ostream &ofile_pmf = cvm::proxy->output_stream(pmf_filename,
00522 "PMF file");
00523 
00524 std::vector<double> position(1, 0);
00525 for (double i = lowerboundary[0]; i < upperboundary[0] + EPSILON; i += width[0]) {
00526 ofile_pmf << i << " ";
00527 position[0] = i + EPSILON;
00528 ofile_pmf << oneD_pmf.get_value(position) << std::endl;
00529 }
00530 cvm::proxy->close_output_stream(pmf_filename);
00531 
00532 written_1D = true;
00533 }
00534 
00535 // write heads of the output files
00536 void writehead(std::ostream& os) const {
00537 os << "# " << dimension << std::endl;
00538 for (int i = 0; i < dimension; i++) {
00539 os << "# " << lowerboundary[i] << " " << width[i] << " " << int((upperboundary[i] - lowerboundary[i]) / width[i] + EPSILON) << " " << 0 << std::endl;
00540 }
00541 os << std::endl;
00542 }
00543 
00544 // write interal data, used for testing
00545 void write_interal_data() {
00546 std::string internal_filename = output_filename + ".UI.internal";
00547 
00548 std::ostream &ofile_internal = cvm::proxy->output_stream(internal_filename,
00549 "UI internal file");
00550 
00551 std::vector<double> loop_flag(dimension, 0);
00552 for (int i = 0; i < dimension; i++) {
00553 loop_flag[i] = lowerboundary[i];
00554 }
00555 
00556 int n = 0;
00557 while (n >= 0) {
00558 for (int j = 0; j < dimension; j++) {
00559 ofile_internal << loop_flag[j] + 0.5 * width[j] << " ";
00560 }
00561 
00562 for (int k = 0; k < dimension; k++) {
00563 ofile_internal << grad.get_value(loop_flag)[k] << " ";
00564 }
00565 
00566 std::vector<double> ii(dimension,0);
00567 for (double i = loop_flag[0] - 10; i < loop_flag[0] + 10 + EPSILON; i+= width[0]) {
00568 for (double j = loop_flag[1] - 10; j< loop_flag[1] + 10 + EPSILON; j+=width[1]) {
00569 ii[0] = i;
00570 ii[1] = j;
00571 ofile_internal << i <<" "<<j<<" "<< distribution_x_y.get_value(loop_flag,ii)<< " ";
00572 }
00573 }
00574 ofile_internal << std::endl;
00575 
00576 // iterate over any dimensions
00577 n = dimension - 1;
00578 while (n >= 0) {
00579 loop_flag[n] += width[n];
00580 if (loop_flag[n] > upperboundary[n] - width[n] + EPSILON) {
00581 loop_flag[n] = lowerboundary[n];
00582 n--;
00583 }
00584 else
00585 break;
00586 }
00587 }
00588 cvm::proxy->close_output_stream(internal_filename.c_str());
00589 }
00590 
00591 // write output files
00592 void write_files() {
00593 std::string grad_filename = output_filename + ".UI.grad";
00594 std::string hist_filename = output_filename + ".UI.hist.grad";
00595 std::string count_filename = output_filename + ".UI.count";
00596 
00597 int i, j;
00598 //
00599 // only for colvars module!
00600 if (written) cvm::backup_file(grad_filename.c_str());
00601 //if (written) cvm::backup_file(hist_filename.c_str());
00602 if (written) cvm::backup_file(count_filename.c_str());
00603 
00604 std::ostream &ofile = cvm::proxy->output_stream(grad_filename,
00605 "gradient file");
00606 std::ostream &ofile_hist = cvm::proxy->output_stream(hist_filename,
00607 "gradient history file");
00608 std::ostream &ofile_count = cvm::proxy->output_stream(count_filename,
00609 "count file");
00610 
00611 writehead(ofile);
00612 writehead(ofile_hist);
00613 writehead(ofile_count);
00614 
00615 if (dimension == 1) {
00616 calc_1D_pmf();
00617 write_1D_pmf();
00618 }
00619 
00620 std::vector<double> loop_flag(dimension, 0);
00621 for (i = 0; i < dimension; i++) {
00622 loop_flag[i] = lowerboundary[i];
00623 }
00624 
00625 i = 0;
00626 while (i >= 0) {
00627 for (j = 0; j < dimension; j++) {
00628 ofile << loop_flag[j] + 0.5 * width[j] << " ";
00629 ofile_hist << loop_flag[j] + 0.5 * width[j] << " ";
00630 ofile_count << loop_flag[j] + 0.5 * width[j] << " ";
00631 }
00632 
00633 if (restart == false) {
00634 for (j = 0; j < dimension; j++) {
00635 ofile << grad.get_value(loop_flag)[j] << " ";
00636 ofile_hist << grad.get_value(loop_flag)[j] << " ";
00637 }
00638 ofile << std::endl;
00639 ofile_hist << std::endl;
00640 ofile_count << count.get_value(loop_flag) << " " <<std::endl;
00641 }
00642 else {
00643 double final_grad = 0;
00644 for (j = 0; j < dimension; j++) {
00645 int total_count_temp = (count.get_value(loop_flag) + input_count.get_value(loop_flag));
00646 if (input_count.get_value(loop_flag) == 0)
00647 final_grad = grad.get_value(loop_flag)[j];
00648 else
00649 final_grad = ((grad.get_value(loop_flag)[j] * count.get_value(loop_flag) + input_grad.get_value(loop_flag)[j] * input_count.get_value(loop_flag)) / total_count_temp);
00650 ofile << final_grad << " ";
00651 ofile_hist << final_grad << " ";
00652 }
00653 ofile << std::endl;
00654 ofile_hist << std::endl;
00655 ofile_count << (count.get_value(loop_flag) + input_count.get_value(loop_flag)) << " " <<std::endl;
00656 }
00657 
00658 // iterate over any dimensions
00659 i = dimension - 1;
00660 while (i >= 0) {
00661 loop_flag[i] += width[i];
00662 if (loop_flag[i] > upperboundary[i] - width[i] + EPSILON) {
00663 loop_flag[i] = lowerboundary[i];
00664 i--;
00665 ofile << std::endl;
00666 ofile_hist << std::endl;
00667 ofile_count << std::endl;
00668 }
00669 else
00670 break;
00671 }
00672 }
00673 cvm::proxy->close_output_stream(grad_filename.c_str());
00674 // cvm::proxy->close_output_stream(hist_filename.c_str());
00675 cvm::proxy->close_output_stream(count_filename.c_str());
00676 
00677 written = true;
00678 }
00679 
00680 // read input files
00681 void read_inputfiles(const std::vector<std::string> filename)
00682 {
00683 char sharp;
00684 double nothing;
00685 int dimension_temp;
00686 int i, j, k, l, m;
00687 
00688 colvarproxy *proxy = cvm::main()->proxy;
00689 std::vector<double> loop_bin_size(dimension, 0);
00690 std::vector<double> position_temp(dimension, 0);
00691 std::vector<double> grad_temp(dimension, 0);
00692 int count_temp = 0;
00693 for (i = 0; i < int(filename.size()); i++) {
00694 int size = 1 , size_temp = 0;
00695 
00696 std::string count_filename = filename[i] + ".UI.count";
00697 std::string grad_filename = filename[i] + ".UI.grad";
00698 
00699 std::istream &count_file =
00700 proxy->input_stream(count_filename, "count filename");
00701 std::istream &grad_file =
00702 proxy->input_stream(grad_filename, "gradient filename");
00703 
00704 if (!count_file || !grad_file) {
00705 return;
00706 }
00707 
00708 count_file >> sharp >> dimension_temp;
00709 grad_file >> sharp >> dimension_temp;
00710 
00711 for (j = 0; j < dimension; j++) {
00712 count_file >> sharp >> nothing >> nothing >> size_temp >> nothing;
00713 grad_file >> sharp >> nothing >> nothing >> nothing >> nothing;
00714 size *= size_temp;
00715 }
00716 
00717 for (j = 0; j < size; j++) {
00718 do {
00719 for (k = 0; k < dimension; k++) {
00720 count_file >> position_temp[k];
00721 grad_file >> nothing;
00722 }
00723 
00724 for (l = 0; l < dimension; l++) {
00725 grad_file >> grad_temp[l];
00726 }
00727 count_file >> count_temp;
00728 }
00729 while (position_temp[i] < lowerboundary[i] - EPSILON || position_temp[i] > upperboundary[i] + EPSILON);
00730 
00731 if (count_temp == 0) {
00732 continue;
00733 }
00734 
00735 for (m = 0; m < dimension; m++) {
00736 grad_temp[m] = (grad_temp[m] * count_temp + input_grad.get_value(position_temp)[m] * input_count.get_value(position_temp)) / (count_temp + input_count.get_value(position_temp));
00737 }
00738 input_grad.set_value(position_temp, grad_temp);
00739 input_count.increase_value(position_temp, count_temp);
00740 }
00741 
00742 proxy->close_input_stream(count_filename);
00743 proxy->close_input_stream(grad_filename);
00744 }
00745 }
00746 };
00747 }
00748 
00749 #endif

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